82057 Paving the road to better Financial Decision-Making in Mongolia August 2013 Financial Capability and Consumer Protection Survey Report Financial Inclusion and Consumer Protection Service Line Contents Acknowledgments iv 1 Key Findings and Policy Recommendations 1 1.1 Knowledge of Financial Concepts and Products . . . . . . . . . . . . . . . . . 2 1.2 Financial Attitudes and Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Financial Inclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.4 Consumer Protection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2 Background on Mongolian Survey 9 3 Financial Capability 11 3.1 Awareness and Knowledge of Financial Concepts and Products . . . . . . . . . 11 3.1.1 Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.1.2 Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2 Financial Attitudes and Behavior . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.2.1 Dimensions of Financial Capability . . . . . . . . . . . . . . . . . . . . 20 3.2.2 Financial Capability Dimension “Controlled Budgeting” . . . . . . . . 23 3.2.3 Financial Capability Dimension “Making Provisions for the Future” . . 25 3.2.4 Financial Capability Dimension “Thinking about the Future” . . . . . 27 3.2.5 Financial Capability Dimension “Being Proactive” . . . . . . . . . . . . 28 3.3 Relationship between Financial Knowledge and Financial Attitudes and Behavior 29 4 Financial Inclusion 30 4.1 Access and use of Financial Services . . . . . . . . . . . . . . . . . . . . . . . . 30 4.1.1 Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 4.1.2 Financial Institutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.2 Relationship between Financial Inclusion and Financial Capability . . . . . . . 41 4.2.1 Relationship between Financial Inclusion and Financial Knowledge and Awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.2.2 Relationship between Financial Inclusion and Financial Attitudes and Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 5 Consumer Protection 47 Appendix 50 A Background on Mongolian Survey 50 B Financial Capability 51 B.1 Knowledge of Financial Concepts and Products . . . . . . . . . . . . . . . . . 51 B.2 Knowledge of Financial Products . . . . . . . . . . . . . . . . . . . . . . . . . 55 B.3 Financial Attitudes and Behavior . . . . . . . . . . . . . . . . . . . . . . . . . 59 B.3.1 Dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 B.3.2 Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 C Financial Inclusion: Access and Usage of Financial Services 73 C.1 Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 C.2 Financial Institutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 - ii - D Distribution Channels 80 E Spatial Overview on Financial Products 83 F Spatial Overview on Financial Institutions 84 - iii - Acknowledgments This Financial Capability and Consumer Protection (FCCP) Report was prepared by a team led by Siegfried Zottel (Economist) from the World Bank’s Financial Inclusion and Infrastructure Global Practice, with contributions from Valeria Perotti (Social Protection Specialist) and Tillmann Heidelk (Research Consultant). Peer review comments were received from Leora Klapper (Lead Economist) and Nataliya Mylenko (Senior Financial Sector Specialist). Aurora Ferrari (Service Line Manager, Micro and SME Finance), Douglas Pearce (Manager, Financial Inclusion Practice), and Giuseppe Iarossi (Senior Economist, Finance and Private Sector Development, Africa Region) provided valuable overall guidance. Special thanks also goes to Coralie Gevers (Country Manager for Mongolia) and Klaus Rohland (Country Director for China, Korea, and Mongolia) for their guidance and support. The team expresses its appreciation to the Mongolian authorities, including the Bank of Mongolia, the Ministry of Finance, the Financial Regulatory Commission, and the National Statistical Office for their cooperation and collaboration during the preparation and implementation of the survey. The team would also like to thank the firm ‘EEC Canada’ which was selected to undertake this survey work. Finally, the team owes particular appreciation to all Mongolian women and men who patiently responded to the survey. The Report was co-financed by the USAID Trust Fund on “Consumer Protection and Financial Literacy”. - iv - c 2013 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is subject to copyright. Because The World Bank encourages dissem- ination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Any queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: pubrights@worldbank.org. -v- List of Figures 1 Financial Literacy Score, by Region . . . . . . . . . . . . . . . . . . . . . . . . 11 2 Overview Financial Literacy I . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3 Overview Financial Literacy II . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 4 Financial Literacy Score, by Gender . . . . . . . . . . . . . . . . . . . . . . . . 12 5 Financial Literacy Scores, by Employment Status . . . . . . . . . . . . . . . . 12 6 Household Income vs. Financial Literacy, Age . . . . . . . . . . . . . . . . . . 12 7 Financial Literacy Scores, by Approximate Household Income . . . . . . . . . 14 8 Financial Literacy Scores, by Saving as a Child . . . . . . . . . . . . . . . . . 14 9 Financial Literacy Scores, by Media Usage . . . . . . . . . . . . . . . . . . . . 14 10 Household Debt, by Financial Literacy Score . . . . . . . . . . . . . . . . . . . 14 11 Financial Products Known in Regions . . . . . . . . . . . . . . . . . . . . . . . 15 12 Overview Awareness Financial Institutions Service Offers I . . . . . . . . . . . 15 13 Overview Awareness Financial Institutions Service Offers II . . . . . . . . . . . 15 14 Knowledge Financial Institutions Service Offers, by Income . . . . . . . . . . . 17 15 Knowledge Financial Institutions Service Offers, by Employment Status . . . . 17 16 Knowledge Financial Institutions Service Offers, by Media Usage . . . . . . . . 18 17 Knowledge Financial Institutions Service Offers, by “Erdenes Tavan Tolgoi”- Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 18 Knowledge Financial Institutions Service Offers, by Literacy . . . . . . . . . . 18 19 Knowledge Financial Institutions Service Offers, by Urbanization . . . . . . . 18 20 Overview Financial Capability Scores . . . . . . . . . . . . . . . . . . . . . . . 20 21 Average Financial Capability Scores, by Employment Status . . . . . . . . . . 21 22 Average Financial Capability Scores, by Literacy . . . . . . . . . . . . . . . . 21 23 Average Financial Capability Scores, by Saving as a Child . . . . . . . . . . . 22 24 Average Financial Capability Scores, by Income . . . . . . . . . . . . . . . . . 22 25 Average Financial Capability Scores, by Urbanization . . . . . . . . . . . . . . 22 26 Average Capability Score (Controlled Budgeting), by Region . . . . . . . . . . 23 27 Components of ‘Controlled Budgeting’ Score, by approximate Household Income 23 28 Components of ‘Controlled Budgeting’ Score, by Employment Status . . . . . 23 29 Components of ‘Controlled Budgeting’ Score, by Literacy . . . . . . . . . . . . 23 30 Components of ‘Controlled Budgeting’ Score, by Saving as a Child . . . . . . . 23 31 Average Capability Score (Making Provisions), by Region . . . . . . . . . . . . 25 32 Components of ‘Making Provisions’ Score, by Employment Status . . . . . . . 26 33 Components of ‘Making Provisions’ Score, by approximate Household Income . 26 34 Average Capability Score (Think Future), by Region . . . . . . . . . . . . . . 27 35 Components of ‘Thinking about Future’ Score, by Age . . . . . . . . . . . . . 27 36 Average Capability Score (Being Proactive), by Region . . . . . . . . . . . . . 28 37 Components of ‘Being Proactive’ Score, by Gender . . . . . . . . . . . . . . . 28 38 Components of ‘Being Proactive’ Score, by Saving as a Child . . . . . . . . . . 28 39 Components of ‘Being Proactive’ Score, by approximate Household Income . . 28 40 Components of ‘Being Proactive’ Score, by Urbanization . . . . . . . . . . . . 28 41 Overview Financial Capability Scores, by Financial Literacy Score . . . . . . . 29 42 Sum of Financial Products, by Region . . . . . . . . . . . . . . . . . . . . . . 30 43 Overview Financial Products I . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 44 Overview Financial Products II . . . . . . . . . . . . . . . . . . . . . . . . . . 30 45 Usage Financial Products, by Literacy . . . . . . . . . . . . . . . . . . . . . . 32 46 Usage Financial Products, by Age . . . . . . . . . . . . . . . . . . . . . . . . . 32 - vi - 47 Financial Inclusion, by Employment Status . . . . . . . . . . . . . . . . . . . . 32 48 Financial Inclusion, by Approximate Household Income . . . . . . . . . . . . . 32 49 Saving Behavior, by Urbanization . . . . . . . . . . . . . . . . . . . . . . . . . 33 50 Saving Behavior, by Education . . . . . . . . . . . . . . . . . . . . . . . . . . 33 51 Saving Behavior, by Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 52 Saving Behavior, by Employment Status . . . . . . . . . . . . . . . . . . . . . 34 53 Saving Behavior, by Access to Credit . . . . . . . . . . . . . . . . . . . . . . . 34 54 Saving Behavior, by Household Income . . . . . . . . . . . . . . . . . . . . . . 35 55 Access to Credit, by Urbanization . . . . . . . . . . . . . . . . . . . . . . . . . 35 56 Access to Credit, by Education . . . . . . . . . . . . . . . . . . . . . . . . . . 35 57 Access to Credit, by Employment Status . . . . . . . . . . . . . . . . . . . . . 36 58 Access to Credit, by Household Income . . . . . . . . . . . . . . . . . . . . . . 36 59 Access to Credit, by Saving Behavior . . . . . . . . . . . . . . . . . . . . . . . 36 60 Using Services offered by Financial Institutions, by Region . . . . . . . . . . . 37 61 Utilization Financial Service, Base Population . . . . . . . . . . . . . . . . . . 37 62 Utilization Financial Service, by approximate Household Income . . . . . . . . 39 63 Utilization Financial Service, by Employment Status . . . . . . . . . . . . . . 39 64 Utilization Financial Service, by Saving as a Child . . . . . . . . . . . . . . . . 40 65 Utilization Financial Service, by Urbanization . . . . . . . . . . . . . . . . . . 40 66 Utilization Financial Service, by Education . . . . . . . . . . . . . . . . . . . . 40 67 Utilization Financial Service, by “Erdenes Tavan Tolgoi”-Program . . . . . . . 40 68 Financial Inclusion vs. Financial Literacy . . . . . . . . . . . . . . . . . . . . . 41 69 Financial Inclusion vs. Financial Literacy, by Age . . . . . . . . . . . . . . . . 41 70 Financial Inclusion vs. Financial Literacy, by Education . . . . . . . . . . . . 41 71 Financial Product Usage vs. Financial Literacy . . . . . . . . . . . . . . . . . 42 72 Current Use of Financial Products, by Knowledge of Commercial Bank . . . . 42 73 Utilization Financial Service, of those who know the Services . . . . . . . . . . 42 74 Financial Inclusion, by ‘Making Provisions Score’ . . . . . . . . . . . . . . . . 44 75 Financial Inclusion, by ‘Being Proactive Score’ . . . . . . . . . . . . . . . . . . 44 76 Financial Inclusion, by ‘Controlled Budgeting Score’ . . . . . . . . . . . . . . . 44 77 Financial Inclusion, by ‘Think For Future Score’ . . . . . . . . . . . . . . . . . 44 78 Saving Behavior, by ‘Being Proactive Score’ . . . . . . . . . . . . . . . . . . . 45 79 Saving Behavior, by ‘Making Provisions Score’ . . . . . . . . . . . . . . . . . . 45 80 Usage of Credit, by ‘Think For Future Score’ . . . . . . . . . . . . . . . . . . . 45 81 Usage of Credit, by ‘Making Provisions Score’ . . . . . . . . . . . . . . . . . . 45 82 Usage Financial Services, by ‘Making Provisions Score’ . . . . . . . . . . . . . 46 83 Usage Financial Services, by ‘Being Proactive Score’ . . . . . . . . . . . . . . . 46 84 Usage Financial Services, by ‘Think For Future Score’ . . . . . . . . . . . . . . 46 85 Overview Conflicts with Financial Institutions . . . . . . . . . . . . . . . . . . 47 86 Overview of Satisfaction with Services offered by Financial Institutions . . . . 47 87 Satisfaction with Services Financial by Financial Institutions, by Urbanization 48 88 Satisfaction with Services Financial by Financial Institutions, by Age . . . . . 48 89 Satisfaction with Services Financial by Financial Institutions, by Education . . 48 90 Satisfaction with Services Financial by Financial Institutions, by Gender . . . 48 91 Map Survey Coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 92 Average Financial Capability Scores, by Age . . . . . . . . . . . . . . . . . . . 66 93 Average Financial Capability Scores, by Gender . . . . . . . . . . . . . . . . . 66 94 Average Financial Capability Scores, by Education . . . . . . . . . . . . . . . 66 95 Watching TV, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 - vii - 96 Using Internet, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 97 Reading Newspaper, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . 80 98 Using Internet, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 99 Reading National Newspaper, by Region . . . . . . . . . . . . . . . . . . . . . 80 100 Reading Local Newspaper, by Region . . . . . . . . . . . . . . . . . . . . . . . 80 101 Regular Media Consumption, by Region . . . . . . . . . . . . . . . . . . . . . 81 102 Information Distribution Channels, by Approximate Household Income . . . . 81 103 Information Distribution Channels, by Employment Status . . . . . . . . . . . 81 104 Information Distribution Channels, by Age . . . . . . . . . . . . . . . . . . . . 82 105 Information Distribution Channels, by Education . . . . . . . . . . . . . . . . 82 106 Information Distribution Channels, by Urbanization . . . . . . . . . . . . . . . 82 107 Information Distribution Channels, by Being a Herdsman . . . . . . . . . . . . 82 108 Information Distribution Channels, by Financial Literacy . . . . . . . . . . . . 82 109 Formal Credit, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 110 Informal Credit, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 111 Formal Savings, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 112 Informal Savings, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 113 Investments, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 114 Insurance Policies, by Region . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 115 Usage of Services of Commercial Banks, by Region . . . . . . . . . . . . . . . 84 116 Usage of Services of Insurance Companies, by Region . . . . . . . . . . . . . . 84 117 Usage of Services of Brokerage Houses, by Region . . . . . . . . . . . . . . . . 84 118 Usage of Services of Microfinance Organizations, by Region . . . . . . . . . . . 84 119 Usage of Services of Other Non-Banking Financial Institutions, by Region . . . 84 120 Usage of Services of Money Exchange Offices, by Region . . . . . . . . . . . . 84 121 Usage of Services of the Mongolian Stock Exchange, by Region . . . . . . . . . 85 - viii - List of Tables 1 Correlation Coefficients between Capability Scores. . . . . . . . . . . . . . . . 20 2 Formal Saving by Informal Saving . . . . . . . . . . . . . . . . . . . . . . . . . 33 3 Formal Credit by Informal Credit . . . . . . . . . . . . . . . . . . . . . . . . . 36 4 Financial Knowledge and Inclusion (Specification: Urban) . . . . . . . . . . . 51 5 Financial Knowledge and Inclusion (Specification: Regional Dummies) . . . . 52 6 Knowledge of Specific Financial Products (Specification: Urban) . . . . . . . . 56 7 Knowledge of Specific Financial Products (Specification: Regional Dummies) . 57 8 Component-weights of Financial Capability Score Dimensions . . . . . . . . . 60 9 Financial Capability Scores (Specification: Urban) . . . . . . . . . . . . . . . 61 10 Financial Capability Scores (Specification: Regional Dummies) . . . . . . . . 63 11 Elements of Financial Capability Scores (Specification: Urban 1) . . . . . . . . 67 12 Elements of Financial Capability Scores (Specification: Urban 2) . . . . . . . . 68 13 Elements of Financial Capability Scores (Specification: Regional Dummies 1) . 69 14 Elements of Financial Capability Scores (Specification: Regional Dummies 2) . 70 15 Financial Inclusion (Specification: Urban) . . . . . . . . . . . . . . . . . . . . 73 16 Financial Inclusion (Specification: Regional Dummies) . . . . . . . . . . . . . 74 17 Usage of Specific Financial Products (Specification: Urban) . . . . . . . . . . . 77 18 Usage of Specific Financial Products (Specification: Regional Dummies) . . . . 78 Glossary BoM – Bank of Mongolia ETT – Erdenes Tavan Tolgoi FCCP – Financial Capability and Consumer Protection FI – Financial Institution FRC – Financial Regulatory Commission MFO – Microfinance Organization MNT – Mongolian T¨ ogr¨og MoF – Ministry of Finance MSE – Mongolian Stock Exchange NBFI – Non-Bank Financial Institution PSU – Primary Sampling Unit - ix - 1. Key Findings and Policy Recommendations 1. Financial capability has become a priority for policy makers seeking to pro- mote beneficial financial inclusion and to ensure financial stability and func- tioning financial markets. Today people are required to take increasing responsibility for managing a variety of risks over the life cycle. People who make sound financial de- cisions and who effectively interact with financial service providers are more likely to achieve their financial goals, improve their household’s welfare, hedge against financial and economic risks, and support economic growth. Boosting financial capability has therefore emerged as a policy objective that complements governments’ financial inclu- sion and consumer protection agendas. To this end, policy makers are increasingly using surveys as diagnostic tools to identify financial capability areas that need improvement and vulnerable segments of the population which could be targeted with specific inter- ventions. 2. At the request of the Ministry of Finance (MoF) the World Bank has imple- mented a nationally representative financial capability survey in Mongolia in 2012. This survey has been tailored to measuring financial capability in low- and middle income countries. To get a better understanding of the importance of external factors on financial capability the survey instrument also measured and assessed issues in related areas of financial inclusion and financial consumer protection. 3. It is suggested that a comprehensive financial education strategy be devel- oped based on the results of the financial capability survey.1 The survey identi- fied numerous financial capability issues across various segments of the population and a number of initiatives are suggested in this report, which could be undertaken to improve the knowledge of financial concepts and products, as well as attitudes and financial be- haviors. In order to ensure that available resources are used in the most efficient way, it is important to prioritize those financial capability enhancing programs, which are considered to be most feasible and cost-effective. The process of developing a national financial education strategy could serve to identify key priorities. Such priorities could be set based on a number of criteria, including the need, costs, outreach, desired im- pacts, and replicability of programs and could also present opportunities to leverage on existing programs. Both the development of a strategy and the setting of priorities would require a wide consultation process including various stake-holders from public, private, and non-profit sectors, which would facilitate a wider consensus building about the importance of financial education. 4. Further, the survey results and recommendations outlined in this report could provide guidance on the development and implementation of financial education programs. They could not only offer useful inputs for the design and monitoring of priority programs, but they could also align priorities and coordinate them with other initiatives and reforms such as those in the area of financial consumer protection. One of the key recommendations in the strategy development process would be to ensure that all proposed measures and programs be tested initially on a small scale and only be rolled out upon evaluation of their positive impacts. For more information about the process of strategy development, see OECD/INFE High Level Principles on National Strategies for Financial Education.2 1 All results in this survey are indicative at the best and cannot be interpreted as causal. 2 Online available at: http://www.oecd.org/finance/financialeducation/OECD_INFE_High_Level_ Principles_National_Strategies_Financial_Education_APEC.pdf. -1- 1.1. Knowledge of Financial Concepts and Products Key Findings 5. Financial knowledge and awareness levels are a challenge in Mongolia, as is the case for many countries at a similar income level. Many Mongolians have a limited understanding of the basic financial concepts required to make savings and investment decisions, although the vast majority of the population masters basic cal- culus. For instance, around one third of the survey participants struggle to understand what interest rates are and more than 60 percent do not possess knowledge of how inflation affects their savings. Compared to the rest of the population, illiterate Mon- golians, low income groups, rural dwellers residing in Western regions of Mongolia, and those who did not learn savings practices as children appear to have less understanding of financial concepts, such as inflation, interest rates, and risk diversification. 6. Commercial banks are widely known as financial service providers, but awareness of broader financial services offered by insurance companies, microfinance organizations (MFOs) or other financial institutions (FIs) is limited. This finding is not surprising given the relatively new institutional model of MFOs. It is also not a striking finding with regard to brokerage houses and the Mongolian Stock Exchange (MSE). However, in light of the 2012 distribution program of shares from a large mining state-owned enterprise, “Erdenes Tavan Tolgoi” (ETT), it is critical to inform the public on how security markets operate. These findings suggests a focus area for financial knowledge and awareness efforts. 7. Moreover, vast parts of the population are not equipped with the required knowledge to benefit from the privatization of ETT. Mongolians eligible to receive shares under the partial privatization of ETT have the right to request cash instead of shares. When asked if they would prefer to receive shares or cash in the next round of the 2012 ETT shares distribution program, 39 percent indicated their preference to receive shares. Less than 20 percent of those opting for shares are familiar with services offered by brokerage houses and roughly one third of those know about the services provided by the MSE. Knowledge of these institutions is essential to be able to trade shares. Recommendations 8. In order to raise financial knowledge of potential users of savings and in- vestment products, innovative and interactive measures, and “edutainment” in particular, should be considered to reach adult target audience. Research has shown that innovation on delivery matters because adults often have stubborn pref- erences that are difficult to change. Conveying financial knowledge messages through innovative ways such as popular TV soap operas, films, videos or radio programs can be quite effective in improving knowledge and also in altering behavior. In order to be successful, it is pivotal that these programs be delivered in an engaging and entertaining manner through appealing stories that stick to memories. They are also presumed to be more effective if messages are repeated and reinforced over time For instance, in Kenya, a popular television drama, Makutano Junction, incorporated financial education mes- sages into some of its story lines and viewers were able to send text messages to obtain a leaflet related to these topics. These messages encouraged people to save regularly or to open bank accounts, rather than to keep money under a mattress. As with other soap -2- operas, people watch Makutano Junction because they identify with the characters and enjoy the stories; but in the course of watching the show, they benefit from the financial education messages. 9. Publications can also be a useful means of transmitting financial education since each copy can be read by several people and can be retained for future reference. A diverse range of publications can be used, including leaflets, booklets, fliers and posters. Articles in newspapers and magazines are also important tools, especially if contained within general sections of the newspaper or magazine, rather than in specialist financial ones. Comic books have been found to be particularly effective in several countries, such as Kenya, India, and South Africa, where literacy levels are low. In such cases, comic books effectively facilitate discussion within the family on topics related to financial literacy. 10. Financial education should be delivered through trusted organizations and individuals with whom the target audience interacts on a regular (day-today) basis. Many organizations have an interest in helping people to become financially knowledgeable and capable. Community organizations and trusted intermediaries, such as local community leaders, social workers, could provide these organizations with vi- tal support in terms of resources, training and funding and they could be especially important for reaching remote and marginalized communities in rural areas. 11. Particular areas of focus for financial education programs include: (i) the meaning of interest rates, (ii) the ability to understand the cost of loans, (iii) how interest earned on interest (compound interest) and inflation affect savings, and (iv) the key benefits, features, and risks of basic retail products such as savings accounts, consumer loans, remittances, and mortgage loans. 12. Financial education programs should take advantage of “teachable moments”. One of the key lessons learned from impact assessments of financial education programs is that financial education works best when delivered to adults during teachable moments. Teachable moments are times in people’s lives when they are more likely to be receptive to new information as they can relate it directly to their own life events. In terms of financial education, key teachable moments when one is most likely to re-examine his personal finances include marriage, new employment, and the launch of a new business. 13. In addition, developing and implementing a tailored investor awareness and education program dealing with the distribution of ETT shares to the popu- lation should be considered. These programs should inform about available options in the privatization and the pros and cons of each option. ETT shareholders should be informed about the services offered by the MSE and brokerage houses, about how to buy and sell shares, and about the advantages of holding shares from more than one com- pany. In order to ensure that the recipients of the shares benefit from the privatization, an extensive investor education program will be needed, including wide-reaching TV and radio programs and easy-to-understand news releases issued in national as well as local newspapers. Investor education programs should also include the development of a dedicated financial information website on ETT privatization and outreach programs delivered through workshops, road shows, exhibitions, TV, games, and mobile phones. The maps provided in appendix D (see figs. 95 throughout 100) show the extent to which different types of mass media are used in the regions covered by this survey. These may give useful insights into how best to effectively and efficiently deliver awareness and education programs. -3- 1.2. Financial Attitudes and Behaviors Key Findings 14. By applying statistical tools, four key areas of financial capability were assessed across the Mongolian population. These include (i) ‘Controlled bud- geting’, (ii) ‘Making provisions for the future’, (iii) ‘Thinking about the future’, and (iv) ‘Being Proactive’. While the first two areas relate to financial behaviors, the latter two can mainly be associated with attitudes and motivations. All financial capability areas are measured on a scale ranging from 0 (lowest score) to 100 (highest score). ‘Controlled budgeting’ comprises the ability to budget, to adhere to the budget, and to prioritize spending on essentials and affordable items. ‘Making provisions for the fu- ture’ indicates how capable respondents are with respect to living within their means, covering for unexpected or old age expenses, and choosing appropriate financial prod- ucts. ‘Thinking about the future’ measures how far-sighted and impulsive people are. Finally, the ‘Being proactive’ score measures the inclination to save whenever possible, to seek information and advice, as well as levels of achievement orientation. 15. Survey participants demonstrate high levels of financial capability in most areas, although they score higher with respect to controlled budgeting and making provisions for the future than they do in terms of thinking about the future and being proactive. The survey results suggest that on average Mongolians show strengths in areas related to controlled budgeting (68.7) and making provisions for the future (66), whereas the average scores for being proactive and thinking about the future are 62.7 and 59.7, respectively. Respondents who are out of labor force score significantly lower in the area of thinking about the future, compared to the informally employed, the self-employed, herdsmen, and retirees. Compared to herdsmen and the unemployed, they also tend to have more difficulties with controlling their budgets. 16. Rural and low income populations are mastering the management of their day-to-day finances, but struggle with being proactive and making provi- sions for the future. As compared to high income segments, Mongolians living on low incomes are significantly better at managing their day-today finances (controlled budgeting). Those with higher incomes, on the other hand, tend to be more proactive and more inclined to making provisions for the future. Consequently, daily hardship and the constant struggle with solving immediate problems can draw the attention of low income groups away from their long-term considerations and needs. While high in- come earners may be able to ‘afford’ doing worse in managing their day-to-day finances, these low scores for low income segments are more worrisome, given their implications for their ability to smooth consumption, to cope with economic shocks, to generate lump sums for productive investments, and eventually for their long-term wellbeing. Likewise, while mastering the task of controlling their budgets, rural dwellers tend to be less proactive and struggle more with making provisions for the future than urban residents. -4- Key Findings 17. Those who began savings habits as children outperform those who did not save in their childhood in almost all financial capability areas. Starting to build certain habits at an early age can have value, since those who already saved as children score on average significantly higher with respect to being proactive, thinking about the future, and making provisions for the future than their counterparts who did not save in their childhood. Recommendations 18. Provision of financial education from early age should be encouraged. Chang- ing attitudes and long term behavior of adults can be a challenging task. Early financial education in schools can therefore have huge value for teaching basic principles of finan- cial capability. Basic principles could include the following: (i) building savings cushions in order to cope with unexpected economic shocks, (ii) making provision for the future, (iii) living within means, and (iv) seeking information and advise when taking financial decisions. If people learn good habits on how to manage their money from a young age, they are more likely to stick to them throughout their lives. Although there is mixed international evidence on the effectiveness of school-based financial education programs on changing consumer behaviors, there are important lessons learned from other coun- tries that have undertaken such programs. Success has been observed when education is interactive and is directly relevant to students’ lives either currently or in the near future. Therefore, high-quality materials/textbooks developed by experts are required and teachers need to be well-trained on the content and techniques. Moreover, as exist- ing curricula are already saturated, it is practicable to integrate financial education into a variety of existing subjects, such as math, economics, and social studies, rather than adding a new course of study.3 If resources to train teachers and to develop and provide teaching and learning materials are limited, it may be best to focus, at least initially, on incorporating financial education into one or two subjects. If possible, these should be compulsory subjects so that all students benefit and they should be taught over three or four consecutive academic semesters (preferably close to the time when students tend to leave school). 19. In addition to primary target groups, financial education programs should also focus on complementary target groups. Thinking broadly about complemen- tary target groups is important. For instance, when not only students but also their parents are targeted with financial capability training, the expected outcomes are even greater. Similarly, targeting people who are out of labor force (but not retired), as well as their spouses, is expected to deliver more promising results since both desire to change behavior. The ability to apply new information is much greater if complementary groups are targeted.4 3 Bruhn, Miriam, Arianna Legovinni, and Bilal Zia ‘Financial Literacy for High School Students and their Parents: Evidence from Brazil.’ Mimeo, World Bank, Washington, D.C., 2012. 4 Yoko Doi, David McKenzie and Bilal Zia ‘Who You train Matters: Identifying Complementary Effects of Financial Education on Migrant Households’, World Bank Policy Research Working Paper no. WPS6157. -5- 1.3. Financial Inclusion Key Findings 20. The rapid expansion of the financial sector is reflected in the high usage of formal savings and credit products. A large share of the Mongolians (78 percent) saves at a formal FI, whereas two out of five Mongolians (42 percent) have a loan from a formal FI. Apart from formal savings and loans, large parts of the population have some form of insurance. However, the high insurance penetration is most likely driven by compulsory insurance policies. Informal savings instruments such as savings clubs or keeping money under the mattress are used by a third of the respondents. Around a fifth of the sample uses some form of informal credit. Investment products such as private pension products are not widely used (15 percent). Illiterate Mongolians and herdsmen, as well as the informally employed and low income groups, hold fewer financial products than their counterpart groups. Compared to rural dwellers, urban residents appear to be more likely to use formal savings. 21. Commercial banks are by far the main FI whose products and services Mongolians use (88 percent). Products and services offered by any other FIs only play a minor role. Access to/use of services from commercial banks and other FIs is limited for low income segments, herdsmen, and those who did not save as children. 22. Despite many other barriers, access and usage of financial products can be constrained by lack of financial knowledge. Respondents, who answered more of the quiz-like financial literacy questions correctly, also hold more financial products and services. Moreover, being more familiar with basic financial concepts also correlates with increased access to/use of different types of financial products and services. 23. Likewise, access and usage of financial products and services can be con- strained by financial attitudes and behavior. The survey provides strong evi- dence that specific aspects of financial attitudes and behavior relate directly with the level of participation that Mongolians have in the financial sector. Mongolians who perform better in making provisions for the future or being proactive tend to hold more financial products than those who do worse. This may be due to the fact that people who plan for unexpected events and for old age expenses are more likely to use savings and investment products. In addition, people who do better in terms of achievement orientation and getting information and advice may feel more confident about using financial products. Recommendations 24. To increase uptake of financial products, financial capability enhancing pro- grams could be combined with available financial products. The survey results may indicate that enhanced financial knowledge is key for further financial sector widen- ing and deepening. Financial education programs could be tied to those financial prod- ucts and services most people can access and use, such as bank accounts, formal loans, or compulsory insurance products (including motor third party liability insurance). Given that especially low income and rural populations struggle with saving (being proactive) or making provisions for the future, insurance companies, banks, and other FIs should consider offering education programs to their customers. In these programs, customers should be informed about the importance of saving, even if only a little, and the need -6- to plan for the future, as both of these financial behaviors have implications for their long-term well-being. Similarly, high income groups could be informed about how to budget and could potentially be provided with mobile phones or internet based per- sonal finance tools, such as Juntos Finanzas. It should be ensured, however, that all educational materials be informative, clear, impartial, and free from marketing. 25. Generic financial education programs alone may be ineffective, but when combined with other interventions, they can be valuable. The limitation of traditional financial education in changing financial behavior is well documented by research. However, coupling the financial education intervention with reminders (e.g. to save) or specific financial capability messages (e.g. to shop around or to make larger remittance transfers) is more likely to induce behavioral change. Another advantage of such interventions is that they are also quite cost-effective and could be taken rapidly to national scale.5 26. The Bank of Mongolia (BoM) may consider sharing the results of this survey with commercial banks and MFOs in particular to potentially develop sav- ings products tailored to the needs of underserved parts of the population. Consumer choice is rather limited in Mongolia. It could make good business sense for FIs to develop products which fit the needs of underserved populations and help them to reach personal savings goals. These could comprise low cost “no-frills” or basic accounts with less burdensome opening requirements. In addition, they could also create savings products with design features that affect the extent of individuals’ use of financial ser- vices, such as commitment savings or labeled accounts. The former consist of accounts where a certain amount is deposited and access to cash is relinquished for a period of time or until a goal has been reached. The latter are accounts created with explicit savings goals in mind such as a car purchase, housing, or education. Credit products could include the design feature of small, initial tester loans that provide information to lenders useful for assessing risk on subsequent larger loans. 27. Removing impediments to financial inclusion other than a lack of financial knowledge is important. The higher access to/use of formal savings in urban areas most likely reflects geographical barriers. The large size of the country and the low population density make it unprofitable to serve remote areas using traditional banking operations. To stimulate demand for formal savings and credit products, especially in rural areas, further developing and expanding alternative banking delivery channels should be considered. Mobile or agent banking can dramatically reduce the cost of providing financial services in an environment of low population density prevailing in Mongolia. In a setting like this, mobile banking technologies can have the greatest benefits because they offer a commercially viable way of reaching locations and segments of the population that were previously excluded from formal financial services due to the prohibitively high costs of providing such services. 5 Karlan, Dean, et al. ‘Getting to the top of mind: How reminders increase saving’ No. w16205. National Bureau of Economic Research, 2010. -7- 1.4. Consumer Protection Key Findings 28. Consumers do not widely report complaints or other conflicts with financial service providers. Only 5 percent of the respondents reported that they experienced conflicts with financial service providers in the past 3 years. However, only half of those who encountered a financial service provider conflict tried to solve it. The main reason reported for not trying to solve an encountered conflict was that FIs are perceived as being too powerful. This may be an indication that the lack of appropriate internal procedures for customer complaints leads to inertia and resignation. 29. Compared to the strikingly high levels of customers’ satisfaction with finan- cial services offered by commercial banks, insurance companies, and money exchange offices, other FIs satisfy their customers less. More than 90 percent of the survey participants are satisfied with the products and services used from com- mercial banks, insurance companies, and money changers. MFOs, the MSE, brokerage houses, and in particular other non-bank financial institutions (NBFIs), such as credit co-operations, seem to offer services which satisfy their customers much less. Recommendations 30. Delivering financial education is not enough, as measures to strengthen the consumer protection framework must also be taken to ensure that new and existing consumers benefit from the financial services they use. It needs to be ensured that consumers are provided with sufficient information to enable them to select financial products and services that are the most suitable and affordable. Therefore, Key Facts Statements for all basic consumer finance products should be required and regulator’s websites should provide price comparison information. For those without internet access, complimentary dissemination mechanisms should be provided. 31. FIs should also be required to provide customers with key information on internal complaints handling focal points and standards. Legal or regulatory provisions should require all FIs to provide customers with contact information of the person or division within the institution that is authorized to receive and respond to complaints. This information should be included not only in advertising or marketing materials, but also in documents provided to consumers when applications are filed and contracts are concluded. Consumers should also be provided with information on the financial institution’s complaints handling procedures.6 32. Financial regulators should analyze the statistics on consumer complaints submitted by FIs and use this information as input to their supervisory and regulatory activities. All FIs should centralize data on complaints received and share that data with the BoM and the Financial Regulatory Commission (FRC). Based on the analysis of information regarding consumer complaints and inquiries, the BoM and the FRC could propose guidelines, instructions, or awareness campaigns that address the common problems identified in such analysis. 6 Diagnostic Review of Consumer Protection and Financial Literacy in Mongolia, The World Bank (2012). -8- 2. Background on Mongolian Survey 33. This survey instrument has been extensively tested in the context of low and middle income countries. The survey instrument used is based on an instrument developed with support by the Russian Trust Fund for Financial Literacy and Educa- tion to measure financial capability in the context of low and middle income countries. Extensive qualitative research was conducted to develop this survey instrument, includ- ing about 70 focus groups and more than 200 cognitive interviews in eight countries to identify the concepts that are relevant in low- and middle-income settings, and to test and adapt the questions to ensure that they are well understood and meaningful across income and education levels. The instrument is currently used or will be used in 14 countries in Latin America, Africa, Middle East and Asia Pacific. 34. The survey instrument allows financial capability, financial inclusion and con- sumer protection issues to be assessed and measured. Financial capability is measured by knowledge of financial concepts and products, attitudes, skills and behav- ior related to day-to-day money management, planning for the future, choosing financial products and staying informed. In order to jointly analyze financial capability and inclu- sion, the survey instrument captures information on access to different kinds of financial products and service providers. The consumer protection section gathers information on incidence of conflicts with financial service providers and levels of satisfaction with financial products offered by different FIs. The survey instrument has been further cus- tomized to the policy priorities of all relevant stakeholders including the MoF, the BoM, and the FRC. This was done by adding Mongolia-specific questions, such as those related to the 2012 distribution program of shares from the large mining state-owned enterprise, ETT. The survey instrument was translated into Mongolian, the major language spoken in country and, for validation purposes, it was also back-translated into English. 35. The Mongolian survey is designed to be nationally representative of the adult population aged 18 and older and it comprises a total sample of 2,500 individ- uals. The sample was designed to allow reliable estimation of main variables of interest on the national level. The most recent 2010 population census data, provided by the Na- tional Statistical Office, was used as a sampling frame. The population was divided into two strata: urban and rural. To fulfill the requirement of a scientifically sound survey, a probabilistic sample selection mode was applied. The sample was selected through a two stage cluster sampling with census enumeration areas as primary sampling units (PSUs) and households as secondary sampling units. The effective sample size was established with 2,500 interviews. However, in order to account for non-contact and non-response, a gross sample of 2,875 households was selected. In total, 125 PSUs were drawn with probability proportional to the number of households in each stratum. Within each PSU, 20 households (+3 reserve households) were selected by random walk method. Finally, within each selected household one respondent was randomly drawn by means of the Kish grid out of the pool of eligible household members. Household members eligible for being interviewed, needed to be 18 years or older and to have some role in manag- ing either personal or household finances. To appropriately balance between scope of coverage and budget, sparsely populated areas with average checking accounts/adults numbers similar to areas with higher population density (equal of higher than 1) were not covered (see appendix A, fig. 91). 36. The fieldwork took place between August and October 2012. To implement the ´ survey, the World Bank contracted the Canadian company “Etude ´ Economique Conseil” -9- (EEC Canada). After 4 days of intense training and a pilot survey, the data was collected by a team of 39 enumerators and 3 supervisors. 37. All graphs and regression analysis in this report are based on weighted data. To adjust for varying probabilities of selection and non-response proper weights were calculated for each respondent, and then applied to the data set. 38. The survey respondents are distributed as follows: 55.4 percent of the respon- dents are urban dwellers and 44.6 percent live in rural areas. More than half of the selected sample are females (57.51 percent), whereas males represent 42.5 percent of the sample. Concerning age, 29.4 percent of the respondents are younger than 35, 47.2 percent are between 35 and 55 years old, and 23.4 percent are older than 55. Regarding income, 17.3 percent of the respondents live in households with a monthly incomes below 210,000 Mongolian T¨ ugriks (MNT). Around a quarter of the respondents (25.9 percent) belong to a household which earns a monthly income of at least MNT 210,000, but less than MNT 285,000. Another quarter (26.7 percent) lives on a monthly household income which falls into the range of MNT 285,000 and less than MNT 645,000. Approximately a third of the sample (29.9 percent) lives in households with monthly incomes of MNT 645,000 or more. - 10 - 3. Financial Capability 3.1. Awareness and Knowledge of Financial Concepts and Products 3.1.1. Concepts 39. A certain level of knowledge of fundamental financial concepts and products and basic numeracy skills are needed in order to effectively participate in financial markets. To test people’s awareness of financial concepts and their basic numeracy skills all respondents were asked to answer 7 quiz-like questions (multiple choice and direct answers). These include questions where respondents were required to do simple calculations and to show their understanding of inflation, interest rates, compound interest, risk diversification, or the main purpose of insurance products. Some questions test knowledge of inflation, interest rates and compound interest which are crucial for informed savings and borrowing decisions. The last two questions, on the other hand, are vital for being able to take informed investment decisions and to protect against risks. 5.2 − 5.4 5 − 5.2 4.8 − 5 4.6 − 4.8 4.4 − 4.6 4.2 − 4.4 0 − 4.2 No data Figure 1: Average financial literacy score in regions. Lowest possible score: 0, highest possible score: 7, see fig. 3. 30 Simple Devision Compare Bargain 20 Purpose of Insurance Percent Simple Interest Risk Diversification 10 Compound Interest Inflation 0 0 20 40 60 80 100 0 1 2 3 4 5 6 7 Figure 2: Percentage of respondents who correctly answered Figure 3: Discrete frequency distribution of financial financial literacy questions. literacy scores. 40. On average, respondents were able to correctly answer 4.9 out of 7 questions on financial literacy. Around nine in ten survey participants were able to provide at least four correct answers. Slightly more than two thirds answered at least five out of seven financial literacy questions correctly, whereas at least six correct responses were given by almost two fifths of the sample. Nevertheless, giving correct responses to all 7 financial literacy questions seemed to be a challenging task, which was only solved by 7 percent of all respondents. - 11 - 41. One can conclude that whilst most have the necessary skills to do basic fi- nancial calculations, they often lack the specific knowledge required to make sensible savings and investment decisions. A closer look at the type of financial knowledge questions people were able to answer correctly reveals that almost all Mon- golians (97 percent) are able to perform simple divisions and 86 percent are comfortable with simple calculations in order to identify better bargains (see fig. 2). The same proportion of the population (86 percent) is aware of the main purpose of insurance products. By contrast, understanding of basic financial concepts appears to be more of a challenge. Around one third (30 percent) of the population fails to understand what interest rates are. Two fifths of the respondents (42 percent) struggle to understand how compound interest work or that holding stocks from a single company implies riskier re- turns than holding stocks from different companies (60 percent). Given that inflation in Mongolia has been quite high and volatile over the past decade and that it returned to double digits in summer 2012, the most concerning fact is, however, that less than 40 percent of the survey participants understand how inflation affects their savings. 5 Financial Literacy Score 4 3 2 1 4.9 5.1 0 Female, n=1425 Male, n=1075 Figure 4: Average financial literacy score, by respondents’ gender. 5 Financial Literacy Score 4 3 2 1 5.1 5.1 5.1 4.5 4.7 4.7 4.6 0 Formal (591) Informal (380) Self−empl. (591) Herdsman (93) Retired (445) Unemployed (101) Out of Laborf. (299) Figure 5: Average financial literacy score, by employment status. Number of Observations = 2066 Percentage High Household Income 80 Low income: Below 385,001 MNT High income: Over 385,000 MNT 60 40 20 34 54 71 49 50 68 69 59 71 0 0−3 4−5 6−7 0−3 4−5 6−7 0−3 4−5 6−7 Age<35, n=619 3555, n=427 Figure 6: High household income ratios, financial literacy score, and age. - 12 - 42. Illiterate survey participants, residents of western parts of Mongolia, and out of labour force populations are less familiar with financial concepts than their counterpart groups. As shown in fig. 4, hardly any differences exist between men and women with regard to their knowledge of basic financial concepts. Likewise, fi- nancial literacy scores across different age groups are indistinguishable. Higher financial literacy scores seem to correlate with higher levels of educational attainment. However, after controlling for other characteristics, by means of regression, none of the differences observed between groups with low, middle, and high educational attainment are statis- tically significant. The knowledge gap between those who are able to read and write in Mongolian and illiterate respondents is significant. As compared to residents of the cap- ital city of Ulaanbataar, rural dwellers, and in particular those living in Western parts of Mongolia (UVS, Bayan-Ulgii, Khovd), have significantly lower understanding of basic financial concepts (see fig. 1). Residents from Dornogovi and Omnogovi are significantly more familiar with financial concepts than those who live in the capital. Differences in financial knowledge across employment status reveal people who are out of labor force as being significantly less likely to answer more financial literacy questions correctly than segments of the population who are formally, informally, and self-employed (see fig. 5). 43. A better understanding of financial concepts is also strongly associated with higher income, with the regular use of different types of media, and with having learned savings practices as a child. Respondents who live on the lowest incomes are significantly more challenged with giving correct responses to these financial knowledge questions than their higher income counterpart groups(see fig. 7). As may be expected, those who tend to use different types of media regularly are also more familiar with financial concepts than those who consume fewer types of media on a regular basis, e.g. only watch TV or only read newspaper (see fig. 9). Interestingly, financial knowledge also appears to be strongly correlated with specific habits formed in the childhood. Those who learned savings practices as children score on average significantly higher with regard to the financial literacy quiz-type questions than their counterparts who did not save as children (see fig. 8). 44. Moreover, lower levels of financial knowledge do not relate with higher levels of indebtedness. Empirical evidence from the U.S. shows that low levels of financial knowledge are strongly associated with bad financial outcomes in terms of high debt loads. In particular, it was found that individuals with low levels of financial literacy are more likely to transact in high cost manners, incurring higher fees and using high debt borrowing.7 However, in Mongolia lack of understanding of financial concepts does not seem to be strongly correlated with high levels of indebtedness. For instance, of those who answered at least 6 financial literacy questions correctly, 9 percent have outstanding households debts which account for more than their annual income. This compares with a fairly similar proportion of highly indebted adults (10 percent) among those who answered less than 6 financial literacy questions correctly (see fig. 10). 45. Nevertheless, higher financial literacy levels correlate with higher levels of financial well-being. As shown in fig. 6, within each age group a clear pattern appears. Those who were able to answer the most financial literacy related questions correctly also belong to the segments of the population who enjoy a higher personal and household income. Notably, this result cannot be interpreted as causal. In other words, more 7 Annamaria Lusardi and Peter Tufano ‘Debt Literacy, Financial Experiences, and Overindebtedness’, NBER working paper no. 14808. - 13 - research would be needed to determine if higher financial literacy leads to higher financial well-being or if more affluent people are also the ones who are more financially savy. 5 5 Financial Literacy Score Financial Literacy Score 4 4 3 3 2 2 1 1 4.6 4.8 5.0 5.3 4.8 5.2 0 < MNT 210, MNT 210−385, MNT 385−645,> MNT 645K, 0 n=635 n=806 n=586 n=471 Not Save, n=1774 Did Save, n=724 Figure 7: Average financial literacy score, by approximate Figure 8: Average financial literacy score, by respondent’s Household Income. childhood saving behavior. 5 Financial Literacy Score 4 3 2 1 3.9 4.5 4.9 5.1 5.2 5.3 0 None, n=25 1, n=520 2, n=726 3, n=608 4, n=495 5, n=126 Figure 9: Average financial literacy score, by respondents’ regular media consumption. None < Two Two−Twelve < Twelve 60 Percentage 40 20 63 6 19 11 56 9 23 12 61 7 22 10 0 Low: 0−3, n=295 Medium: 4−5, n=1193 High: 6−7, n=757 Figure 10: Household debt (in month of income), by financial literacy score. - 14 - 3.1.2. Products 3.5 − 4 3 − 3.5 2.5 − 3 2 − 2.5 1.5 − 2 1 − 1.5 No data Figure 11: Average number of financial products known by respondents in different regions. Lowest possible number: 0, highest 7, see fig. 13. 30 None Commercial Bank Insurance Company 20 Percent Money Changers MNG Stock Exchange 10 Microfinance Institution Other Non−Banking Brokerage Houses 0 0 20 40 60 80 100 0 1 2 3 4 5 6 7 Figure 12: Percentage of respondents who know about the Figure 13: Discrete frequency distribution of knowledge services offered by financial institutions. about services offered by the financial institutions. 46. Commercial banks are widely known, but awareness of broader financial ser- vices offered by insurance companies, MFOs, or other FIs is much more lim- ited. More than 90 percent of the Mongolians are aware of the products and services provided by commercial banks, whereas less than half of the respondents show familiar- ity with products and services offered by insurance companies or money exchange offices. Only around a quarter of the sample (27 and 23 percent) states that they are familiar with the products and services provided by the MSE or MFOs (see fig. 12). Much less, 14 percent, know the products and services that brokerage houses provide. 47. On average, respondents are familiar with services provided by 2.6 different types of FIs. As shown in fig. 13, less than 10 percent (7.9 percent) of the respondents indicate to be familiar with the products and services offered by all seven types of FIs. Around three quarters of the survey participants (70 percent) admit that they are not familiar with the services offered by more than three different types of financial service providers. Of particular concern is that 6 percent of the respondents are not familiar with the products and services provided by commercial banks or any other FIs. 48. Knowledge of financial products and services varies noticeably with loca- tion. Significant knowledge gaps become apparent between rural and urban dwellers (see fig. 19), Interestingly, compared to urban residents, rural dwellers seem, on aver- age, to be familiar with more financial products and services. Ulaanbataar’s population, which represents around 80 percent of the urban population, appears to be less familiar - 15 - with financial products and services, compared to the residents of Southern and Eastern parts of Mongolia, such as Dornogovi, Khovsgol, Omnogovi, and Sukhbataar. These regional differences do not only exist with respect to the number of financial products, but also the type of products. As would be expected, due to a higher density of bank branches, urban residents are more knowledgeable about the services and products of- fered by banks than rural dwellers. Since MFO and NBFIs such as savings and credit cooperatives play a more important role in rural areas, rural residents are more familiar with their products than urban dwellers. 49. Being familiar with services provided by different FIs correlates with higher income and with being formally or self-employed. There does appear to be signif- icant knowledge disparities between income groups. Compared to low income segments, high income earners seem more aware of different financial service providers and their offered products (see fig. 14). Likewise, in comparison to the out of labor force pop- ulations, formally employed respondents and the self-employed show higher awareness of financial products offered by all financial service providers (see fig. 15). Herders, on the other hand, compared to people who are out of labor force, are less familiar with products and services offered by banks, MFOs, NBFIs, money exchange offices, and the MSE. 50. Another pattern which emerges is that better knowledge of financial prod- ucts and services correlates with literacy and the regular use of different types of media. Not surprisingly, those who were able to read and write in Mongolian demonstrated a higher awareness of the different financial service providers and their offered products than illiterate respondents (see fig. 18). In particular, they showed significantly greater knowledge about products and services provided by banks, NBFIs, money exchange offices, and the MSE. Likewise, people who try to stay informed by using different types of media regularly, such as TV, radio, internet, and national or local newspapers, are also more likely to show greater familiarity with products offered by different types of financial service providers, except banks (see fig. 16). 51. In addition, vast parts of the sample population are not equipped with the required knowledge to benefit from the privatization of ETT. In 2012 the Gov- ernment of Mongolia decided to privatize a tranche of shares in ETT coal mine by transferring shares to residents, who had the right to request cash instead of shares. When asked if they would prefer to receive shares or cash in the next round of the ETT shares distribution program, 39 percent of all respondents indicated their preference to receive shares. A comparison with those who indicated to choose cash instead of shares shows that the survey participants who prefer shares have indeed higher awareness levels about the MSE or brokerage houses and their offered products and services. However, the majority of those respondents who choose shares still lacks familiarity with these institutions and their products. Only one third is familiar with the MSE and its prod- ucts and a fifth with those offered by brokerage houses (see fig. 17). This knowledge is essential to be able to trade any shares and to benefit from the shares distribution program. - 16 - 100 Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers 80 Percentage 60 40 20 81 33 27 17 21 14 9 87 37 36 21 21 17 10 94 44 37 26 19 19 14 97 60 53 39 30 30 20 0 <210, n=633 210−385, n=806 385−645, n=586 >645K, n=470 Figure 14: Percentage of respondents knowing about services offered by the financial institutions, by approximate monthly household income (in 1,000 MNT). 100 Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers - 17 - 80 Percentage 60 40 20 95594933292719 94454631232415 94485337342819 6137 5 4 11 2 5 87372320 9 10 7 772729142011 1 90373012191513 0 Formal (590) Informal (380) Self−empl. (591) Herdsman (93) Retired (444) Unemployed (100) Out of Laborf. (299) Figure 15: Percentage of respondents knowing about services offered by the financial institutions, by employment status. Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers 100 80 Percentage 60 40 20 57 16 0 0 20 10 7 90 31 27 16 20 14 6 89 40 35 22 17 20 11 92 52 49 35 25 21 18 93 53 44 32 28 25 19 95 60 49 38 34 30 21 0 None, n=25 1, n=519 2, n=726 3, n=607 4, n=495 5, n=125 Figure 16: Percentage of respondents knowing about services offered by the financial institutions, by by respondents’ regular media consumption. Banks Insurance Policies Money Changers MSE Banks Insurance Policies Money Changers MSE Banks Insurance Policies Money Changers MSE 100 100 100 - 18 - MFOs Other NBFIs Brokers MFOs Other NBFIs Brokers MFOs Other NBFIs Brokers 80 80 80 Percentage Percentage Percentage 60 60 60 40 40 40 20 20 20 89 39 34 23 18 17 10 96 59 50 37 31 28 22 37 28 6 1 5 2 0 92 45 40 27 23 21 14 86 43 36 24 27 21 13 95 47 43 30 20 21 15 0 0 0 Cash, n=1460 Shares, n=821 Illiterate, n=31 Literate, n=2468 Rural, n=1497 Urban, n=1000 Figure 17: Percentage of respondents knowing about services Figure 18: Percentage of respondents knowing about services Figure 19: Percentage of respondents knowing about services offered by the financial institutions, by decision offered by the financial institutions, by literacy offered by the financial institutions, by for either cash or shares in government program (reading and writing Mongolian). urbanization. “Erdenes Tavan Tolgoi”. 3.2. Financial Attitudes and Behavior 52. Knowledge of basic financial concepts and products does not necessarily translate into sound financial behavior. To identify the role which attitudes play in individuals’ financial decisions and to see how attitudes translate into financial be- havior, the survey instrument used contains questions on different aspects (components) of financial capability that include attitudes/motivations and behaviors. 53. In the Mongolian data set, 11 main components of capability can be identi- fied, some of which refer to behaviors, and others to attitudes or motivations. Each financial capability component is measured through a combination of relevant ques- tions. These are identified by using a statistical method called factor analysis. Factor analysis is a data reduction method that finds a small number of linear combinations of those variables that explain most of the variance in the data. The method is used to aggregate the variables that measure different nuances of the same component in order to obtain a single indicator (or score) for that component. Each component score ranges between 0 (lowest score) and 100 (highest score). 54. The following seven components measure behaviors related to financial ca- pability: budgeting, not overspending, living within means, saving, planning for unexpected expenses, making provisions for old age, and choosing prod- ucts. More specifically, ‘budgeting’ measures the extent to which people plan how to use their money and whether they adhere to the plan; ‘not overspending’ assesses whether people refrain from spending their income on non-essentials or on things they cannot afford; ‘living within means’ measures the level of borrowing and whether people borrow to buy food and other essentials; ‘saving’ measures whether people see themselves as trying to save for the future, trying to save for emergencies, and trying to save even if a small amount; ‘planning for unexpected expenses’ indicates whether people could cover an unexpected expense equivalent to a month’s income and whether they worry about it; ‘making provisions for old age’ indicates whether people have strategies in place that allow them to cover for expenses in old age; and ‘choosing products’ indicates whether people search for alternatives, check terms and conditions, and search for information before getting financial products. 55. Four financial capability components refer to attitudes and motivations, such as attitudes towards the future, (non-)impulsiveness, attitude towards infor- mation, and achievement orientation. In particular, ‘attitudes towards the future’ measure whether people agree or disagree with statements such as ‘I live for today’, ‘The future will take care of itself ’, ‘I only focus on the short term’; the measure of ‘non- impulsiveness’ is determined by whether people agree or disagree with statements about impulsivity (being impulsive, saying things without giving them too much thought, doing things without thinking them through); ‘attitudes towards information’ is a combina- tion of getting information and advice before making financial decisions, learning from others, and being disciplined; and ‘achievement orientation’ measures to what extent people agree with statements on having aspirations, working hard to be the best, always looking for opportunities to improve one’s own situation. 56. The relationship between the components indicates that there are four main areas of financial capability: (i) Controlled budgeting, (ii) Thinking about the future, (iii) Making provisions for the future, (iv) Being proactive. Through a second step of factor analysis, the components are analyzed together to see if they can - 19 - be explained by a few underlying aspects of capability. The results indicate that the budgeting and not overspending components belong to the same area, which can be de- fined as ‘Controlled budgeting’. Similarly, living within means, planning for unexpected expenses, making provisions for old age, and choosing products belong to the same area that can be named ‘Making provisions for the future’. Two additional factors emerge with respect to attitudes and motivations. The first is ‘Thinking about the future’ (a combination of attitudes toward the future and non-impulsiveness). The second is ‘Being proactive’, a combination of getting advice and information, having aspirations, being achievement oriented, and trying to save. Again, a score is calculated for each of the four areas, and it is rescaled to range between 0 (lowest score) to 100 (highest score). Table 8 in appendix B.3.1 provides the weights given to each component in the construction of the area scores. As can be seen, budgeting and not overspending are equally important for the ‘controlled budgeting’ area. By contrast, living within one’s means or planning for unexpected expenses are given much higher weights within the ‘making provisions for the future’ area than making provisions for old age or than choosing financial products. 3.2.1. Dimensions of Financial Capability Controlled Budgeting CB TF BP MP Making Provisions for Future CB 1.00 TF -0.01 1.00 Being Proactive BP 0.14∗∗∗ -0.05 1.00 Think about Future MP 0.03 0.04 0.11∗∗∗ 1.00 ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01 0 20 40 60 80 Figure 20: Average financial capability scores. Table 1: Correlation Coefficients between Capability Scores. 57. Respondents demonstrate high levels of financial capability in most areas, although they score higher with regard to controlled budgeting and making provisions for the future than they do in terms of thinking about the future and being proactive. Fig. 20 indicates the mean scores achieved by respondents in the four key areas of financial capability. The highest average scores are found in the areas of controlled budgeting (68.7) and making provisions for the future (66), whereas the scores for being proactive and thinking about the future are 62.7 and 59.7, respectively. 58. The areas of financial capability are quite distinct in Mongolia. As shown in table 1, the highest and most significant correlation is 0.14 between controlled budgeting and being proactive. These results may indicate that improvements in one financial capability area do not lead to much improvement in another area. 59. Out of labor force populations, illiterate respondents, and those who did not learn savings practices as children score particularly low in several financial capability areas. On average, survey participants who are out of labor force tend to think significantly less about the future compared to the informally employed, the self-employed, herdsmen, and retirees. Compared to herdsmen and the unemployed they also appear to struggle more in terms of controlled budgeting (see fig. 21). In comparison to their literate counterparts, illiterate respondents score lower in the area of controlled budgeting and they tend to be more challenged with making provisions for the future - 20 - (see fig. 22). Those who began savings habits as children outperform those who did not save in their childhood in almost all financial capability areas, except in the area of controlled budgeting (see fig. 23). 60. Low-income groups and high-income earners seem to have different skills. When compared to high income segments of the population, Mongolians living on low incomes are significantly better at managing their day-to-day finances (controlled bud- geting). Those with higher incomes, on the other hand, are more proactive and more inclined to make provisions for the future (see fig. 24). Consequently, daily hardship and the constant struggle with solving immediate problems can draw the attention of low income groups away from their long-term considerations and needs. 61. Moreover, living in rural areas is strongly associated with lower financial capability scores. While mastering the task of controlling their budgets, respondents who live in rural areas tend to be less proactive and more challenged with making provisions for the future than their urban counterpart groups (see fig. 25). 62. When comparing average scores for the four financial capability areas, there appear to be no major differences related with age, gender or education (see appendix B.3.1, figs. 92, 93, and 94, respectively). However, as is shown in the following subsections, which provide more detailed results for each area, significant differences emerge when looking at the scores for individual components of each area. Controlled Budgeting Making Provisions for Future Being Proactive Think about Future 80 60 Average Score 40 20 70 67 66 59 68 66 61 62 69 68 63 62 68 64 61 57 0 Formal Informal Self/Herdsm. Not Work Figure 21: Average financial capability scores, by respondents’ employment status. Controlled Budgeting Making Provisions for Future Being Proactive Think about Future 80 60 Average Score 40 20 85 66 61 59 68 66 63 60 0 Illiterate Literate Figure 22: Average financial capability scores, by respondents’ literacy (reading and writing Mongolian). - 21 - Controlled Budgeting Making Provisions for Future Being Proactive Think about Future 80 60 Average Score 40 20 68 65 61 59 69 68 65 61 0 Not Save Save Figure 23: Average financial capability scores, by respondents’ childhood saving behavior. Controlled Budgeting Making Provisions for Future Being Proactive Think about Future 80 60 Average Score 40 20 73 62 59 61 68 62 58 60 69 66 65 59 66 71 67 59 0 <210K 210K−385K 385K−645K >645K Figure 24: Average financial capability scores, by approximate monthly household income (in 1,000 MNT). Controlled Budgeting Making Provisions for Future Being Proactive Think about Future 80 60 Average Score 40 20 71 65 59 61 66 67 66 59 0 Rural Urban Figure 25: Average financial capability scores, by urbanization. - 22 - 3.2.2. Financial Capability Dimension “Controlled Budgeting” 80 − 85 75 − 80 70 − 75 65 − 70 60 − 65 55 − 60 50 − 55 0 − 50 No data Figure 26: Average Capability Score (Controlled Budgeting) in regions. 63. Controlled budgeting measures capability defined in two parts as follows: (i) making a plan for spending money and keeping to the plan (budgeting) and (ii) prioritizing expenses on essentials and affordable items (not over- spending). In Mongolia, 85 percent of the population plan how to spend money, either sometimes or always. Almost all residents who plan (95 percent) also indicate that they stick to the plan at least sometimes. Finally, even fewer people (16 percent) cannot resist temptations of spending money on non-essentials they cannot afford sometimes or regularly. 100 100 Budgeting Do not overspend Budgeting Do not overspend 80 80 60 60 40 40 20 20 65 78 63 73 64 72 67 65 70 69 65 70 68 69 59 75 0 0 <210K 210K−385K 385K−645K >645K Formal Informal Self/Herdsm. Not Work Figure 27: Average scores of individual components of the Figure 28: Average scores of individual components of the ‘Controlled Budgeting’ score, by approximate ‘Controlled Budgeting’ score, by respondents’ household income (in 1,000 MNT). employment status. 100 100 Budgeting Do not overspend Budgeting Do not overspend 80 80 60 60 40 40 20 20 71 98 65 71 62 73 70 68 0 0 Illiterate Literate Not Save Save Figure 29: Average scores of individual components of the Figure 30: Average scores of individual components of the ‘Controlled Budgeting’ score, by literacy ‘Controlled Budgeting’ score, by childhood (reading and writing Mongolian). saving behavior. - 23 - 64. Compared to higher income populations, those who live at the lowest income levels show strengths in refraining from overspending and in prioritizing their spending on their needs rather than on their wants. In terms of budgeting, the different income groups are statistically indistinguishable (see fig. 27). Similarly, herdsmen, compared to out of labor force populations, are less inclined to overspend and tend to prioritize their expenses on essentials and items they can afford. With regard to their ability to budget, herdsmen and people out of the labor force are statistically indistinguishable (see fig. 28). 65. Self-employed individuals are more likely to overspend and struggle more with prioritizing their expenses on essentials, compared to out of labor force populations. As can be seen in fig. 28, those who are out of labor force score similarly to the self employed in terms of budgeting, but perform much better in not overspending. Compared to their literate counterparts, illiterate respondents tend to struggle more with prioritizing their expenses on their needs rather than their wants. 66. Retirees caution about overspending, especially compared to others out of labor force. However, budgeting seems to be a greater challenge for them. Similarly, compared to those who learned savings practices as children, respondents who did not save in their childhood tend to be less inclined to set up a budget and to adhere to it, but show high ability in not overspending (see figs. 29 and 30, respectively). This leads to insignificant differences in the overall controlled budgeting score between these groups. - 24 - 3.2.3. Financial Capability Dimension “Making Provisions for the Future” 80 − 85 75 − 80 70 − 75 65 − 70 60 − 65 55 − 60 50 − 55 0 − 50 No data Figure 31: Average Capability Score (Making Provisions) in regions. 67. Being capable of making provisions for the future means not borrowing more than one can afford for food and other essentials (living within means), plan- ning for unexpected expenses, making old age provisions, and being capable of choosing appropriate financial products. A third of the population sometimes or regularly borrows money to buy food or other essentials, but only 2 percent borrow more than they report to be able to afford. On the contrary, 75 percent of the Mon- golians reported that they could borrow more or have not borrowed at all, which may indicate higher capability but also limited access to credit. The survey indicated that more than half of the respondents (56 percent) could not cover an unexpected expense equivalent to a month’s income and 25 percent have not done anything to make sure they can cover for such an expense. A large fraction of the sample (34 percent) does not have any strategy in place to cover for old age expenses. In terms of choosing financial products, 85 percent has at least roughly checked terms and conditions before getting a product. A much smaller percentage searches for information from alternative sources, considers many alternatives, or searches until they find the best product (57, 47 and 31 percent respectively). 68. The overall ‘making provisions for the future’ score does not reveal any major differences between age groups and groups with different educational attain- ment. However, a closer look at the individual components reveals that the ability to plan for old age expenses seems to strongly increase with age. By contrast, even after controlling for other characteristics, respondents with lower levels of education tend to be better in planning for old age expenses than their counterparts with higher educational attainments. 69. Herdsmen score better in ‘living within means’, but struggle more with ‘mak- ing provisions for old age’ and ‘choosing financial products and services’ than people out of labor force. As shown in fig. 32 herdsmen are less likely to have made provisions that cover their old age expenses than those who are out of labor force. They also score worse than those who are out of labor force with regards to choosing appropri- ate financial products and services. Out of labor force populations, on the other hand, struggle with living within means and planning for old age expenses compared to the formally employed, the informally employed, and the self-employed. 70. Starting early pays off since having saved as a child does not only strongly correlate with a higher ability to plan for unexpected and retirement age expenses, but also with a better score in choosing financial products and - 25 - services. Having saved as a child is associated with a higher score in planning for unex- pected expenses, planning for old age expenses, and in choosing financial products and services. These relationships remain significant after controlling for other characteristics. 71. Higher income groups score better in ‘planning for unexpected and old age expenses’ and in ‘choosing financial products and services’ (fig. 33) than low income segments. Despite facing small and erratic income streams, people living on low incomes are mastering the task of living within their means as well as high income populations do. However, the survey results suggest that low incomes can significantly constrain people’s ability to plan for unexpected and old age expenses and to choose financial products and services, which fit their needs best. 100 Living w/ means Plan Unexpected Prep. oldage Choosing Prod. 80 60 40 20 84 67 56 54 87 62 54 50 85 70 49 52 83 64 55 43 0 Formal Informal Self/Herdsm. Not Work Figure 32: Average scores of individual components of the ‘Making Provisions’ score, by respondents’ employment status. 100 Living w/ means Plan Unexpected Prep. oldage Choosing Prod. 80 60 40 20 84 63 40 39 83 62 49 42 84 65 54 50 86 72 66 58 0 <210K 210K−385K 385K−645K >645K Figure 33: Average scores of individual components of the ‘Making Provisions’ score, by approximate household income (in 1,000 MNT). - 26 - 3.2.4. Financial Capability Dimension “Thinking about the Future” 80 − 85 75 − 80 70 − 75 65 − 70 60 − 65 55 − 60 50 − 55 0 − 50 No data Figure 34: Average Capability Score (Think Future) in regions. 72. The overall ‘thinking about the future’ score indicates whether people have forward-looking attitudes and whether they are impulsive. Between a third and 43 percent of the respondents agree at least to some extent with the various statements that indicate a short-sighted attitude. This means that a large percentage of people seem to be focusing more on the present rather than thinking about the future. There is more variation of responses to the three questions on impulsiveness, but 45 percent of the survey participants agree at least to some extent with the statement “I am impulsive”. 73. Younger people tend to be more im- 100 Time pref Not impulsive pulsive than older cohorts. Even once other characteristics are taken into account, 80 increasing age is associated with signifi- cantly lower levels of impulsiveness. Al- 60 though the differences between age groups are small, they are statistically significant 40 (fig. 35). 20 64 59 60 60 56 59 0 Age<35 3555 Figure 35: Average scores of individual components of the ‘Thinking about Future’ score, by respondents’ age. - 27 - 3.2.5. Financial Capability Dimension “Being Proactive” 80 − 85 75 − 80 70 − 75 65 − 70 60 − 65 55 − 60 50 − 55 0 − 50 No data Figure 36: Average Capability Score (Being Proactive) in regions. 74. The ‘being proactive’ score indicates capability in ‘getting advice and infor- mation’, ‘learning from others’, ‘being disciplined’, ‘trying to save as much/as regularly as possible’, and ‘being achievement oriented’. About two thirds of the respondents agree at least to some extent that the statements “I always get information or advice when I have an important financial decision to make” and “I learn from the mistakes other people make managing their money” describe them properly. 80 percent agree at least to some extent with the statement “I am very disciplined when it comes to managing money”. Around 82 percent of the Mongolians also agree at least to some extent with the three statements about being achievement oriented. 100 100 Info Saving Achieve Info Saving Achieve 80 80 60 60 40 40 20 20 65 63 76 64 62 75 64 58 74 67 72 78 0 0 Female Male Not Save Save Figure 37: Average scores of individual components of the Figure 38: Average scores of individual components of the ‘Being Proactive’ score, by respondents’ gender. ‘Being Proactive’ score, by childhood saving behavior. 100 100 Info Saving Achieve Info Saving Achieve 80 80 60 60 40 40 20 20 62 55 74 61 58 72 66 61 79 68 72 76 61 60 75 68 64 76 0 0 <210K 210K−385K 385K−645K >645K Rural Urban Figure 39: Average scores of individual components of the Figure 40: Average scores of individual components of the ‘Being Proactive’ score, by approximate ‘Being Proactive’ score, by urbanization. household income (in 1,000 MNT). - 28 - 75. Men tend to be less proactive than women, while urban residents tend to be more proactive than rural dwellers. These differences in the overall being proactive score remain significant even after controlling for other characteristics. As shown in fig. 37, the significant difference in the proactive score between men and women is mainly due to the fact that men are less inclined to use information and to learn from others than women. On the other hand, the significant differences in the being proactive score between urban and rural dwellers can be mainly explained by the fact that urban residents, in particular those from Ulaanbataar, demonstrate higher levels of achievement orientation than people living in rural environments. 76. Starting early pays off, since having saved as a child does not only strongly correlate with an inclination to use information and learn from others, but also with the ability to save money, and with higher achievement orientation. As shown in fig. 38, starting to save at an early has value, as these respondents score on average significantly higher with regards to their savings behavior today, their willingness to use information, and their achievement orientation than their counterparts who did not save in childhood. 77. Moreover, low income groups tend to struggle more with putting money aside than high income earners (see fig. 39). As would be expected, the ability to save is constrained by available resources. Those respondents who live on the highest incomes are also the ones who are significantly more inclined to build savings cushions regularly and to save money for the future, in comparison to the lowest income group. The difference remains significant when other factors are taken into account. 78. Interestingly, urban populations, in particular residents from Ulaanbataar, seem to be more achievement-oriented than rural dwellers from most other regions (see fig. 40). 3.3. Relationship between Financial Knowledge and Financial Attitudes and Behavior 79. Lack of financial knowledge can be 80 Controlled Budgeting Making Provisions Being Proactive Thinking about Future a constraint for various aspects of fi- nancial capability. Respondents who an- 60 swered more financial literacy related ques- tions correctly tend to perform better with Percentage regard to all financial capability areas ex- 40 cept controlled budgeting. The largest gap between more and less financially literate re- spondents exists in the ‘making provisions 20 for the future’ area (see fig. 41). 68 60 62 59 68 64 61 61 69 71 65 59 80. A closer look into the individual com- 0 Low: 0−3 Medium: 4−5 High: 6−7 Figure 41: Average financial capability scores, by ponents of each financial capability financial literacy score. area reveals that financially literate people are more likely to overspend. Nevertheless, respondents who are less fi- nancially literate do less well in budgeting, living within means, planning for old age, choosing products, and getting information and advice. They are also more impulsive, short-sighted, and less achievement oriented. - 29 - 4. Financial Inclusion 81. Since the rebound from the severe financial crises in 2008 and 2009, renewed economic growth and strong capital inflows have resulted in greater finan- cial intermediation. Credit growth resumed in late 2009 and it continued to grow substantially to more than 70 percent by 2011. Likewise, deposits have grown rapidly after the crisis, by an average of 53 percent annually in both 2010 and 2011. NBFIs and savings and credit cooperatives have also steadily entered the market, although their roles remain limited and underdeveloped, as they account for only 3 percent of total fi- nancial sector lending. Today, credit and deposit penetration in Mongolia is on par with the average in the East Asia and Pacific region. At end of 2010, credit to the private sector accounted for 49 percent of GDP and deposits for 60 percent of GDP, compared to an average of 52 percent and 63 percent in the region, respectively. The FCCP survey also asked about the types of financial products/service and financial service providers, which Mongolians access or use. This provides a better understanding of the current state of financial inclusion in Mongolia and the ways Mongolians save, borrow, make transactions, and manage risks. 4.1. Access and use of Financial Services 4.1.1. Products 4 − 4.5 3.5 − 4 3 − 3.5 2.5 − 3 0 − 2.5 No data Figure 42: Average number of financial products used in regions, out of ‘Formal Saving’, ‘Insurance Policies’, ‘Formal Credit’, ‘Informal Credit’, ‘Formal Saving’, ‘Informal Saving’, and ‘Investments’. All Products (weighted mean=3.51) 25 Net of Insur. (weighted mean=2.48) Formal Saving 20 Insurance Policies Formal Credit 15 Percent Informal Saving 10 Informal Credit 5 Investments 0 0 20 40 60 80 100 0 1 2 3 4 5 6 7 8 Figure 43: Percentage of respondents with different forms of Figure 44: Discrete frequency distribution of financial financial products. product usage. - 30 - 82. The rapid expansion of the financial sector is also reflected in high levels of usage of formal savings and credit products. A large share of Mongolians (78 per- cent) saves at a formal institution, whereas two out of five Mongolians (42 percent) have a loan from a formal FI (see fig. 43). Formal savings include deposit accounts, checking accounts and money transfer operators (e.g. internet banking, Mobile banking, West- ern Union, debit cards). The formal credit category comprises loans from commercial banks, mortgages, credit cards, and credit from MFOs (e.g Credit Mongol LLC, Hugjil Badrakh, Erel Bank, Nomin Union, TFS, VFM). The proportion of people who save at a formal institution is considerably high as compared to the average in the East Asia and Pacific region (52 percent) or to the average in countries who belong to the same income level group (28 percent). The regional and income group averages are based on data from Global Findex, a survey conducted in 148 countries around the world, including Mongolia, that measures how adults save, borrow, make payments, and manage risks. A potential explanation for this high level of formal savings is that government payments in Mongolia are mainly made through bank accounts. Global Findex data suggests that around 50 percent of those with an account at a formal institution use the account to receive government payments, which is not only much higher than the regional average (6 percent) and the income group average (4 percent), but even higher than the average of high income countries (41 percent). 83. The proportion of people that save at a formal FI is consistent with data from Global Findex. According to Global Findex, in mid 2011, 78 percent of the adult population had an account at a formal FI and about a quarter borrowed from a formal FI. The comparability between the FCCP and the Global Findex savings and borrowing indicators is limited, especially due to the fact, that these two surveys used different reference periods. It is notable, however, that the FCCP estimate of the proportion of the population with a loan at a formal financial institution is higher than the one from Global Findex, which may reflect the strong credit growth since mid 2011. 84. Compared to formal savings and loans, informal savings and borrowing in- struments play a much less prominent role in Mongolia. Informal savings instru- ments such as savings clubs or keeping money under the mattress are used by a third of the respondents. Around a fifth uses some form of informal credit, including borrowing from savings and credit cooperatives, informal money lenders or relatives/friends. 85. Apart from formal savings and loans, significant parts of the Mongolian pop- ulation (78 percent) have access to some form of insurance. The insurance category covers two types of insurance policies: (i) health and life or income replace- ment insurances (74 percent) and (ii) general insurance policies such as car insurance or household content insurance (29 percent). However, the high insurance penetration is most likely driven by two types of compulsory insurance policies, mainly by health and to a lesser extent by motor insurances. The former is critical for mitigating risks that relate to personal health or to one’s livelihood and it has been compulsory for employees since 1991. The latter type of insurance policy, the motor third party liability insurance, is mandatory for car owners since the beginning of 2012. 86. Investment products which help to mitigate old age risks are not widely used. Only 15 percent of the survey participants are currently willing or able to manage risks related to old age through accessing this type of financial products. This category of financial products mostly comprises private pension products, but also shares and bonds. - 31 - 4 4 Number of Financial Products Number of Financial Products 3 3 2 2 1 1 1.38 3.53 3.55 3.68 3.12 0 0 Illiterate, n=32 Literate, n=2468 Age<35, n=731 3555, n=527 Figure 45: Average number of financial products used, by Figure 46: Average number of financial products used, by literacy (reading and writing Mongolian). respondents’ age. 4 Number of Financial Products 3 2 1 4.11 3.25 3.89 2.65 2.90 3.19 3.31 0 Formal (591) Informal (380) Self−empl. (591) Herdsman (93) Retired (445) Unemployed (101) Out of Laborf. (299) Figure 47: Average Number of financial Products, by employment status. 4 Number of Financial Products 3 2 1 2.93 3.11 3.50 4.19 0 < 210K, n=635 210K−385K, n=806 385K−645K, n=586 > 645K, n=471 Figure 48: Average Number of financial Products, by approximate household income (in 1,000 MNT). 87. On average Mongolians hold 3.5 financial products. Without taking insur- ance policies into account this number reduces to an average of 2.5 products (see fig. 44). Keeping in mind that insurance policies may likely be induced by manda- tory schemes, only about 30 percent of the Mongolians hold four or more financial products and services. - 32 - 88. Illiterate Mongolians, herdsmen, informally employed and low income pop- ulations hold the lowest number of financial products within the population. Regardless of whether insurance policies are taken into account or not, the same pattern emerges: illiterate Mongolians, herdsmen, informally employed and low income groups hold fewer financial products compared to their counterpart groups (see figs. 45, 46, 47, and 48, respectively). Substantial differences in the average number of financial products held can be seen across the household income groups. Respondents living on the lowest income hold on average only 2.93 products, which compares to an average of 4.19 for those in the highest income group. None Informal Formal Both None Informal Formal Both 80 80 60 60 Percentage Percentage 40 40 20 20 19 30 75 24 16 30 81 27 21 30 74 24 13 31 83 27 0 0 Rural, n=1498 Urban, n=998 Primary and Secondary, n=1470 Tertiary, n=1023 Figure 49: Percentage of respondents with access to Figure 50: Percentage of respondents with access to different forms of savings, by urbanization. different forms of savings, by respondents’ education. None Informal Formal Both 80 60 Percentage 40 Informal Saving Formal Saving No Yes Total 20 No 17 4 21 Yes 53 26 79 15 31 80 27 15 30 81 26 23 28 72 23 Total 70 30 100 0 Age<35, n=728 3555, n=526 Figure 51: Percentage of respondents with access to Table 2: Formal Saving by Informal Saving (%) different forms of savings, by respondents’ age. x 89. Large parts of the population have access to or use formal savings, in par- ticular those living in urban areas, and those with higher education (see figs. 49, 50, and 51, respectively). Regarding age, access to/use of formal savings slightly advances with age, but then decreases sharply in old age, which can most likely be explained by lifecycle needs and income drops faced in retirement. The higher access to/use of formal savings in urban areas most likely reflects geographical barriers. The large size of the country and the low population density make it unprofitable for tradi- tional banking operations to serve remote areas and consequently they increase costs to prohibitively high levels. - 33 - 90. By far the most constrained segment in terms of access to / use of formal savings are herders and low income groups. Half of all herdsmen (48 percent) do not hold formal savings, compared to 14 percent of formally employed respondents who do not save at formal institutions. Another possibly constrained segment concerning formal savings are Mongolians who live on low incomes. Whereas 89 percent of those with highest incomes reported to have formal savings, only 69 percent of the respondents with low household income hold formal savings. 60 None Informal Formal Both 40 Percentage 20 38 28 50 16 54 17 39 10 47 23 43 13 53 18 37 7 0 Formal, n=550 Informal, n=341 Self/Herdsm., n=611 Not Work, n=743 Figure 52: Percentage of respondents with access to different forms of savings, by employment status. 100 None Informal Formal Both 80 Percentage 60 40 20 23 25 71 19 8 47 86 41 14 23 83 20 6 55 92 53 0 None, n=1231 Informal, n=211 Formal, n=836 Both, n=218 Figure 53: Percentage of respondents with access to different forms of savings, by access to credit. - 34 - 60 40 None Informal Formal Both Percentage 20 57 17 33 8 54 14 38 7 48 20 42 10 37 30 50 18 0 <210, n=635 210−385, n=806 385−645, n=586 >645K, n=471 Figure 54: Percentage of respondents with access to different forms of savings, by approximated household income (in 1,000 MNT). 91. Informal savings are typically used to complement formal savings. Even 87 percent of those with informal savings also save at a formal FI (see table 2). Nevertheless, being predominantly used by the, self-employed and herders, and respon- dents who also hold informal credit perhaps indicates that there is unmet demand for formal savings products (see figs. 52 and 53). Income seems to be a key determinant for the decision and opportunity to save formally, informally, or not at all. Whereas a fifth of the respondents with low incomes neither have formal nor informal savings, of those who belong to the highest income segment, only 14 percent reportedly neither save formally nor informally (see fig. 54). 60 None Informal Formal Both None Informal Formal Both 50 40 40 Percentage Percentage 30 20 20 10 54 14 38 6 43 27 44 15 51 18 38 7 45 24 45 15 0 0 Rural, n=1500 Urban, n=1000 Primary and Secondary, n=1473 Tertiary, n=1024 Figure 55: Percentage of respondents with access to Figure 56: Percentage of respondents with access to different forms of credit, by urbanization. different forms of credit, by respondents’ education. - 35 - 60 60 None Informal Formal Both None Informal Formal Both 40 40 Percentage Percentage 20 20 38285016 54173910 47234313 531837 7 571733 8 541438 7 48204210 37305018 0 0 Formal, n=550 Informal, n=341 Self/Herdsm., n=611 Not Work, n=743 <210, n=635 210−385, n=806 385−645, n=586 >645K, n=471 Figure 57: Percentage of respondents with access to Figure 58: Percentage of respondents with access to different forms of credit, by respondents’ different forms of credit, by approximated employment status. household income (in 1,000 MNT). 92. Access to formal credit is also unevenly distributed among the Mongolian population. Since banks usually want to see a savings trend before they hand out a loan, 46 percent of those respondents who either save formally, or both formally and informally, also hold a formal credit. By contrast, of those who do not save at all or only informally, only 30 or 21 percent respectively own formal credit. The following seem to be even more important determinants for formal access to finance than a proven savings trend: living in an urban area and having a high educational attainment are equally important, being formally employed (50 percent) or earning a high income (46 percent) (see figs. 55 and 56, 57, 58, and 59, respectively). There is lower access to formal credit in rural areas and among herders and the self-employed, in particular. This might be due to lack of real estate collateral in rural areas, higher risks of agricultural loans, lack of information to assess credit-worthiness, and the large territory. 80 None Informal Formal Both Informal Credit 60 Formal Credit No Yes Total Percentage 40 No 48 10 58 Yes 31 11 42 20 Total 79 21 100 65 9 30 4 65 18 21 4 47 17 45 8 36 39 48 23 Table 3: Formal Credit by Informal Credit (%) 0 None, n=448 Informal, n=120 Formal, n=1344 Both, n=586 Figure 59: Percentage of respondents with access to x different forms of credit, by respondents’ saving x behavior. x 93. When formal sources of credit are either insufficient or simply not available, Mongolians are forced to rely on informal sources. 48 percent of the respondents with informal credit do not have formal credit. However, as shown in table 3, more than half of those with informal credit (52 percent) also tend to hold formal credit. Interestingly, better access to formal credit seems to correlate with better access to informal credit. Respondents with higher ability to borrow formally also enjoy better access to informal credit sources. Those who are overlooked by banks – residents living in rural areas, those with low income and low educational attainment, and those who are not working at all – also seem to be less successful in tapping into informal credit sources. Another segment of the population with lower access to finance, both formal or informal, are seniors. Their lower access to finance might be due to lower life cycle needs. - 36 - 4.1.2. Financial Institutions 3.5 − 4 3 − 3.5 2.5 − 3 2 − 2.5 1.5 − 2 1 − 1.5 No data Figure 60: Average number of financial services used in regions, out of ‘Commercial Bank’, ‘Insurance Companies’, ‘Brokerage Houses’, ‘Microfinance Organizations’, ‘Other Non-Banking Financial Institutions’, ‘Money Exchange Offices’, and the ‘Mongolian Stock Exchange’. 94. Commercial banks are by far the 100 Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers main FI whose products and ser- vices Mongolians use (88 percent). 80 Products and services offered by other FIs only play a minor role (see fig. 61). In 60 contrast to the widespread usage of insur- ance policies, only a third of Mongolians 40 reported to use the services offered by in- surance companies. This number might be a better estimate of non-compulsory, 20 actively chosen insurance products held 88 34 30 10 11 7 5 by Mongolians.8 Services offered by 0 Figure 61: Percentage of respondents using financial money exchange offices are used by 30 services. percent of the population, whereas MFOs only reach about a tenth of the population. Thus far, hardly any respondents (5 percent) report using services of brokerage houses. 95. Access and use of services from commercial banks and other FIs is limited for low income segments, herdsmen, and those who did not save as children. Compared to high income groups, individuals living on low incomes are significantly less likely to report having used any basic services provided by commercial banks or money exchange offices or the more complex services provided by insurance companies, brokerage houses, and the MSE (see fig. 62). Likewise, herdsmen are less likely to have used services provided by commercial banks, money exchange offices, and brokerage houses, compared to the out of labor force populations (excluding retirees), see fig. 63. Those who already learned savings practices as children are more likely to have used services provided by all types of financial institutions, except brokerage houses (see fig. 64). 96. MFOs and their products are, as would be expected, more likely to be used by urban residents than by rural dwellers. Moreover, compared to those who have at most completed primary education, respondents with higher educational attainment 8 This number would match with an FRC estimate that around a fourth of the total population has insurance policies (FRC Annual report 2010). - 37 - seem to be more likely to have been served by MFOs (see figs. 65 and 66). Services offered by the MSE and by brokerage houses are most likely used by respondents who reported that they would prefer to receive shares in the next round of the 2012 ETT shares distribution program. Nevertheless, even among this segment of the population, 17 percent and 9 percent respectively, report having used the services of these institutions (see fig. 67). - 38 - 100 Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers 80 Percentage 60 40 20 78 24 20 4 12 4 3 82 23 27 6 10 6 2 92 35 26 9 8 6 4 95 48 41 20 12 9 9 0 <210, n=635 210−385, n=806 385−645, n=586 >645K, n=471 Figure 62: Percentage of respondents using financial service, by approximate household income (in 1,000 MNT). - 39 - 100 Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers 80 Percentage 60 40 20 92453413138 6 92323412118 5 9135431514116 59321 1101 1 8427158 4 1 3 7521205186 0 8727233 9 5 8 0 Formal (591) Informal (380) Self−empl. (591) Herdsman (93) Retired (445) Unemployed (101) Out of Laborf. (299) Figure 63: Percentage of respondents using financial service, by employment status. Banks Insurance Policies Money Changers MSE Banks Insurance Policies Money Changers MSE 100 100 MFOs Other NBFIs Brokers MFOs Other NBFIs Brokers 80 80 Percentage Percentage 60 60 40 40 20 20 86 29 25 9 8 6 4 92 44 40 14 16 9 6 82 29 26 7 14 7 3 93 37 33 13 8 6 7 0 0 Not Save, n=1774 Save, n=724 Rural, n=1500 Urban, n=1000 Figure 64: Percentage of respondents using financial service, by childhood saving Figure 65: Percentage of respondents using financial service, by urbanization. behavior. - 40 - Banks Insurance Policies Money Changers MSE Banks Insurance Policies Money Changers MSE 100 100 MFOs Other NBFIs Brokers MFOs Other NBFIs Brokers 80 80 Percentage Percentage 60 60 40 40 20 20 84 29 24 6 9 6 3 92 39 36 15 12 7 7 86 27 23 7 8 6 3 94 47 40 17 14 8 9 0 0 Primary and Secondary, n=1473 Tertiary, n=1024 Cash, n=1462 Shares, n=821 Figure 66: Percentage of respondents using financial service, by respondents’ Figure 67: Percentage of respondents using financial service, by decision for either educational attainment. cash or shares in government program “Erdenes Tavan Tolgoi”. 4.2. Relationship between Financial Inclusion and Financial Capability 4.2.1. Relationship between Financial Inclusion and Financial Knowledge and Awareness 10 Jittered Scatter, Jitter=15 Number of Financial Products Unjittered Scatter 8 Fit (All Participants): b=.3*** Fit (At least 1 Prod.): b=.27*** 0 2 4 6 0 1 2 3 4 5 6 7 Financial Literacy Score Linear fit without further controls. Significance levels: p < .01***; p < .05**; p < .1*. Figure 68: Relationship between financial inclusion vs. financial literacy. 97. Access and use of financial products can be constrained by lack of awareness about financial concepts. As shown in fig. 68, a positive relationship between better understanding of financial concepts and the number of financial products used exists (i.e. respondents who answered more of the quiz-like financial literacy questions correctly also hold more financial products). However, one has to keep in mind at hat the direction of causality is not clear. It is also plausible that those who are more exposed to financial products are also more likely to become more familiar with financial concepts. This positive relationship can also be seen within different age or education groups. Regardless of educational attainment or age, individuals with higher financial literacy scores also tend to hold more financial products (see figs. 69 and 70). 4 Number of Financial Products 1 2 3 2.7 3.6 3.8 3.0 3.5 4.1 2.3 3.1 3.6 0 0−3 4−5 6−7 0−3 4−5 6−7 0−3 4−5 6−7 Age<35, n=731 3555, n=527 Figure 69: Relationship between financial inclusion vs. financial literacy, by age. 4 Number of Financial Products 1 2 3 2.1 2.8 3.2 2.7 3.3 3.8 2.9 3.7 4.1 0 0−3 4−5 6−7 0−3 4−5 6−7 0−3 4−5 6−7 Primary, n=247 Secondary, n=1226 Tertiary, n=1024 Figure 70: Relationship between financial inclusion vs. financial literacy, by respondents’ education. - 41 - Formal Savings Insurance Policies Formal Credit Informal Savings Informal Credit Investments 80 60 Percentage 40 20 64 69 31 21 13 12 79 77 42 28 21 16 83 83 46 36 25 14 0 0−3, n=337 4−5, n=1326 6−7, n=837 Figure 71: Percentages of respondents currently using the financial product, given their financial literacy score. Insurance Formal Saving Checking Acc. Formal Credit Informal Saving Gen. Insurance Invest./Pr. Pens. Informal Credit Credit MFO Mortage Semi−form. Sav. 80 60 Percentage 40 20 67 39 30 26 21 16 13 9 5 2 1 75 77 61 38 31 30 15 22 8 3 2 0 Not Know Commercial Bank Know Commercial Bank Figure 72: Percentages (numbers) of individuals currently using different financial products, by knowing about the services offered by the commercial banks. 100 Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers 80 60 40 20 97 74 75 38 47 32 35 0 Figure 73: Percentage of respondents using financial service, of those who know the services offered by the financial institution. 98. In addition, being more financially literate correlates with increased access and use of different types of financial products. Relative to respondents who answered less than four financially literacy questions correctly, those with better under- standing of financial concepts are more likely to use formal savings, insurance policies, and formal and informal credit (see fig. 71). The largest gap – in absolute numbers – exists with regard to formal savings: 83 percent of those who correctly answered most - 42 - of the financial literacy questions have formal savings, whereas only 64 percent of the respondents with lowest financial literacy scores have access to/use formal savings. 99. Access and use of financial products can be further constrained by a lack of knowledge with financial products. Those who reported that they are not familiar with any products offered by commercial banks use all types of financial products, basic and more sophisticated ones, much less (see fig. 72). For instance, whereas 77 percent of those with knowledge about bank products hold formal savings, only 39 percent of those with no knowledge have these savings. 100. Simple knowledge about the services provided by specific FIs does not nec- essarily mean that they are used. Whereas 97 percent of those who know about the products of commercial banks also used them, products of MFOs are only used by 47 percent of those who claim to know about them (see fig. 73). The services provided by the MSE, savings- and credit-cooperatives and brokers are used by about a third of those with knowledge about them. - 43 - 4.2.2. Relationship between Financial Inclusion and Financial Attitudes and Behavior 4 4 Number of Financial Products Number of Financial Products 3 3 2 2 1 1 3.33 3.52 4.03 3.02 3.41 4.03 0 0 Lower, n=712 Middle, n=721 High, n=740 Lower, n=730 Middle, n=730 High, n=755 Figure 74: Average Number of financial Products, by Figure 75: Average Number of financial Products, by ‘being ‘making provisions score’. proactive score’. 4 4 Number of Financial Products Number of Financial Products 3 3 2 2 1 1 3.54 3.53 3.46 3.65 3.47 3.41 0 0 Lower, n=723 Middle, n=771 High, n=997 Lower, n=815 Middle, n=706 High, n=948 Figure 76: Average Number of financial Products, by Figure 77: Average Number of financial Products, by ‘think ‘controlled budgeting score’. for future score’. 101. Access and use of financial products and services can be further constrained by lower levels of financial capability. However, in Mongolia only specific aspects of financial capability seem to be directly related with the level of participation that Mongolians have in the financial sector. Respondents who perform better in making provisions for the future or being proactive tend to hold more financial products on average than those who do worse (see figs. 74 and 75). The average number of financial products held does not vary between those who score better in controlling their budget and thinking about the future (see figs. 76 and 77). 102. The average number of financial products held does not vary with capability scores in the area of controlled budgeting. However, when looking at the individual components, this result appears to be driven by the fact that the average number of products is higher for people who are mastering the management of their day-to-day finances, but it is lower for people who are less likely to overspend. 103. Individuals who are more inclined to make provisions for the future and to be proactive tend to hold more financial products than those with low scores in these areas. In particular, when looking at specific components, people who are inclined to plan for unexpected expenses, make provisions for old age, choose appropriate products, as well as who are trying to save whenever possible and who are more achievement oriented, tend to hold a higher number of financial products. - 44 - 100 80 No Saving Informal Formal Both No Saving Informal Formal Both 80 60 Percentage Percentage 60 40 40 20 20 23 26 71 20 20 28 76 24 11 33 86 30 20 23 75 19 15 30 80 25 6 39 90 35 0 0 Lower 1/3, n=730 Middle 1/3, n=730 High 1/3, n=755 Lower 1/3, n=712 Middle 1/3, n=721 High 1/3, n=740 Figure 78: Percentage of respondents with access to Figure 79: Percentage of respondents with access to different forms of savings, by ‘being proactive different forms of savings, by ‘making provisions score’. score’. No Credit Informal Formal Both No Credit Informal Formal Both 50 50 40 40 Percentage Percentage 30 30 20 20 10 10 44 25 44 13 48 22 41 11 53 17 40 10 37 19 52 9 50 21 39 10 50 26 38 14 0 0 Lower 1/3, n=815 Middle 1/3, n=706 High 1/3, n=948 Lower 1/3, n=712 Middle 1/3, n=721 High 1/3, n=740 Figure 80: Percentage of respondents with access to Figure 81: Percentage of respondents with access to different forms of credit, by ‘think for future different forms of credit, by ‘making provisions score’. score’. 104. Some aspects of capability also seem to matter for the type of financial prod- ucts that people hold. Compared to those who tend to be less proactive, more proactive respondents are more likely to have a saving product and, in particular, to have a formal rather than an informal saving product (see fig. 78). Residents who are inclined to make provisions for the future are instead more likely to have both types of saving products (see fig. 79). The proportion of people without any credit products is much higher among those who are inclined to think about or to make provisions for the future as compared to those who score low in these areas (see figs. 80 and 81). 105. At the same time, some aspects of capability also matter for the kind of FIs individuals can access. Those who are inclined to make provisions for the future and who tend to be proactive enjoy better access to all types of financial service providers than those with low scores in these areas (see figs. 82 and 83). On the other hand, compared to respondents with forward looking attitudes, those who are rather short- sighted are less likely to use the services provided by insurance companies (see fig. 84). - 45 - 100 100 Banks Insurance Policies Money Changers MSE Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers MFOs Other NBFIs Brokers 80 80 60 60 40 40 20 20 852518 5 7 4 3 903526 8 8 5 4 954543181511 8 872334 9 9 6 4 8735291211 7 5 9043321313 8 7 0 0 Lower 1/3, n=712 Middle 1/3, n=721 High 1/3, n=740 Lower 1/3, n=730 Middle 1/3, n=730 High 1/3, n=755 Figure 82: Percentage of usage of services offered by financial institutions relative to entire Figure 83: Percentage of usage of services offered by financial institutions relative to entire population, by ‘making provisions score’. population, by ‘being proactive score’. 100 Banks Insurance Policies Money Changers MSE - 46 - MFOs Other NBFIs Brokers 80 60 40 20 8735221011 8 6 9132341010 5 3 8733341112 7 6 0 Lower 1/3, n=815 Middle 1/3, n=706 High 1/3, n=948 Figure 84: Percentage of usage of services offered by financial institutions relative to entire population, by ‘think for future score’. 5. Consumer Protection Any Conflict Try Solve if Conflict Comp. Grievance Opt Out GOV Claim Legal Court Friends & Fam. Comm. Elders Commercial Bank (N=2140) 60 Insurance Company (N=742) Money Changers (N=685) Percentage 40 MNG Stock Exchange (N=192) Microfinance Institution (N=270) Other Non−Banking (N=146) 20 Brokerage Houses (N=86) 5 52 54 20 22 8 2 2 0 20 40 60 80 100 0 Figure 85: Overview whether respondents had a conflict Figure 86: Percentage of respondents being satisfied with with a financial institution in last three years, if services offered by financial institutions given the agent tried to solve it, and if so how. respondents use it; number of cases in parentheses. 106. Consumer protection is critical for ensuring confidence in the financial system and for increasing financial inclusion. A high incidence of conflicts with financial service providers or low levels of satisfaction with financial products offered by FIs could undermine the trust in the financial system and impede financial inclusion. Also, weak consumer protection can result in consumers being harmed by financial products rather than benefitting from them. 107. Consumers do not widely report complaints or other conflicts with financial service providers. Only 5 percent of the respondents reported that they experienced conflicts with FIs in the past 3 years. Around half of those who encountered a conflict also tried to solve it. The most common approach followed in trying to resolve the conflict was to submit a grievance to the company which sold the product (see fig. 85). Slightly more than a fifth of those who experienced a financial service provider conflict stopped using the service before the contract expired or alternatively submitted a claim to the appropriate government authority. Legal courts were approached in less than 10 percent of all conflict cases. 108. Wide differences exist between the self-reported behavior of those who en- countered a conflict and the hypothetical behavior of those who did not face a financial service provider conflict. Whereas half of those who encountered a fi- nancial service provider conflict did not try to solve it, only 10 percent of those who did not experience a conflict stated, that if they faced a conflict they would not do anything at all. The main reason reported for not trying to solve an encountered conflict was that FIs are perceived as being too powerful. This may be an indication that the lack of appropriate internal procedures for customer complaints leads to inertia and resignation. 109. Compared to the strikingly high levels of customers’ satisfaction with finan- cial services offered by commercial banks, insurance companies, and money exchange offices, other FIs satisfy their customers less (see fig. 86). More than 90 percent of the respondents are satisfied with the products and services used from commercial banks, insurance companies and money changers. The MSE, MFOs, brokerage houses and in particular other NBFIs, such as credit co-operations, seem to offer services which satisfy their customers much less. - 47 - 100 80 Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers Percentage 60 40 20 94 88 84 65 74 57 71 95 87 88 81 76 72 80 0 Rural Urban Figure 87: Percentage of individuals being satisfied with services offered by financial institution, by urbanization. Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers 100 80 Percentage 60 40 20 95 85 87 74 73 62 86 94 88 86 79 76 66 72 95 91 84 75 75 68 85 0 Age<35 3555 Figure 88: Percentage of individuals being satisfied with services offered by financial institution, by respondents’ age. Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers 100 80 Percentage 60 40 20 95 90 86 74 66 61 73 94 86 86 78 82 68 80 0 Primary and Secondary Tertiary Figure 89: Percentage of individuals being satisfied with services offered by financial institution, by respondents’ education. Banks Insurance Policies Money Changers MSE MFOs Other NBFIs Brokers 100 80 Percentage 60 40 20 95 88 85 74 71 68 80 94 88 88 79 80 61 75 0 Female Male Figure 90: Percentage of individuals being satisfied with services offered by financial institution, by respondents’ gender. 110. Some clients of MFOs are less satisfied with the services they receive than others. Although MFOs play a greater role in rural than in urban areas, urban dwellers are more likely to be satisfied with their services than rural residents. Rural residents are less likely to be satisfied with services offered by most FIs, except the ones provided - 48 - by insurance companies (see fig. 87). Interestingly, younger adults are less likely to be satisfied with products offered by MFOs compared to those aged 35 or more, whereas the latter are less likely to be satisfied with brokerage houses (see fig. 88). Figs. 89 and 90 reveal that women and those with lower education are also less likely to be satisfied with the services provided by MFOs than males and those with higher educational attainment respectively. Compared to respondents with any other employment status, the informally employed are less likely to be satisfied with MFOs and their services. The lower satisfaction with the products offered by MFOs perhaps explains why only half of those respondents who know about their products also use them (see fig. 73). - 49 - Appendix A. Background on Mongolian Survey Included No data Figure 91: Map showing regions, which became covered by survey. - 50 - B. Financial Capability B.1. Knowledge of Financial Concepts and Products Background Information: Methods and Dependent Variables in Tables 4 and 5 Literacy Score based on questions from sec. 3.1.1. The score sums all correct answers per respondent. Each question receives the same weight, i.e. knowing more difficult questions is not “rewarded”. The analysis applies a basic linear probability model, extended for the correction of the survey design. Financial Products Knowledge Score The respondent is confronted with a list of financial institutions: Commercial banks, Insurance companies, Broker (Intermediary organizations), Microfinance orga- nizations, Other non-banking financial institutions, Exchange office, and money transfer. For each institution the respondent answers ‘Yes’ or ‘No’ to the following question: ‘Do you know about the services offered by the following institutions? ’. The variable counts how any institutions are know by the respondent. For the analysis a poisson model is fitted, extended for the correction of the survey design. Table 4: Financial Knowledge and Inclusion (Specification: Urban) Financial Literacy Financial Products Score Knowledge Score Age −0.02 −0.00 [−0.14, 0.09] [−0.07, 0.07] Age Square 0.00 0.00 [−0.00, 0.00] [−0.00, 0.00] Age Cube −0.00 −0.00 [−0.00, 0.00] [−0.00, 0.00] Male 0.08 0.05 [−0.11, 0.27] [−0.06, 0.16] Household Head 0.10 −0.06 [−0.09, 0.30] [−0.19, 0.06] Secondary Educ. −0.11 0.05 [−0.30, 0.07] [−0.10, 0.19] Tertiary Educ. −0.13 0.10 [−0.36, 0.09] [−0.06, 0.25] Literate (Mongolian) 0.48∗∗∗ 0.69∗∗∗ [0.12, 0.83] [0.42, 0.95] Household Size −0.02 −0.04∗∗ [−0.08, 0.04] [−0.07, −0.01] Econ. Dep. Kids 0.01 −0.01 [−0.05, 0.08] [−0.05, 0.02] Married/Cohabit 0.04 −0.07∗ [−0.13, 0.21] [−0.15, 0.01] Formal Sector 0.33∗∗∗ 0.24∗∗∗ [0.11, 0.55] [0.13, 0.36] Informal Sector 0.41∗∗∗ 0.17∗∗∗ [0.13, 0.69] [0.04, 0.30] Self Employed 0.37∗∗∗ 0.30∗∗∗ [0.16, 0.57] [0.19, 0.42] - 51 - Herdsman 0.04 −0.40∗∗∗ [−0.30, 0.38] [−0.64, −0.16] Retired 0.19 −0.05 [−0.10, 0.49] [−0.18, 0.09] Unemployed 0.19 −0.11 [−0.15, 0.52] [−0.28, 0.06] 210k to 385k 0.22∗∗∗ 0.10∗ [0.06, 0.37] [−0.01, 0.21] 385k to 645k 0.30∗∗∗ 0.17∗∗∗ [0.12, 0.48] [0.05, 0.29] Higher 645k 0.48∗∗∗ 0.40∗∗∗ [0.26, 0.70] [0.28, 0.52] Media Consumption 0.16∗∗∗ 0.08∗∗∗ [0.10, 0.22] [0.04, 0.12] Save as Child 0.22∗∗∗ 0.23∗∗∗ [0.09, 0.35] [0.15, 0.30] Urban Environment 0.09 −0.13∗∗ [−0.11, 0.28] [−0.24, −0.02] Observations 2493 2493 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, rural environment, income lower MNT 210k, not saved as a child Table 5: Financial Knowledge and Inclusion (Specification: Regional Dummies) Financial Literacy Financial Products Score Knowledge Score Age −0.03 0.00 [−0.15, 0.09] [−0.06, 0.07] Age Square 0.00 −0.00 [−0.00, 0.00] [−0.00, 0.00] Age Cube −0.00 −0.00 [−0.00, 0.00] [−0.00, 0.00] Male 0.07 0.04 [−0.11, 0.25] [−0.07, 0.14] Household Head 0.13 −0.05 [−0.06, 0.32] [−0.17, 0.08] Secondary Educ. −0.13 0.03 [−0.31, 0.06] [−0.11, 0.16] Tertiary Educ. −0.11 0.08 [−0.33, 0.11] [−0.07, 0.23] Literate (Mongolian) −0.19 0.70∗∗∗ [−0.74, 0.36] [0.43, 0.96] Household Size −0.01 −0.04∗∗ [−0.07, 0.04] [−0.07, −0.00] Econ. Dep. Kids 0.04 −0.00 [−0.03, 0.10] [−0.04, 0.03] - 52 - Married/Cohabit 0.05 −0.04 [−0.12, 0.23] [−0.12, 0.04] Formal Sector 0.36∗∗∗ 0.27∗∗∗ [0.15, 0.56] [0.16, 0.39] Informal Sector 0.44∗∗∗ 0.15∗∗ [0.17, 0.72] [0.02, 0.28] Self Employed 0.36∗∗∗ 0.30∗∗∗ [0.16, 0.56] [0.18, 0.41] Herdsman 0.31∗ −0.13 [−0.03, 0.64] [−0.34, 0.07] Retired 0.22 −0.01 [−0.08, 0.51] [−0.15, 0.12] Unemployed 0.25 −0.04 [−0.07, 0.58] [−0.19, 0.12] 210k to 385k 0.15∗ 0.10∗∗ [−0.00, 0.31] [0.00, 0.20] 385k to 645k 0.29∗∗∗ 0.20∗∗∗ [0.11, 0.47] [0.09, 0.32] Higher 645k 0.46∗∗∗ 0.45∗∗∗ [0.22, 0.69] [0.33, 0.57] Media Consumption 0.20∗∗∗ 0.10∗∗∗ [0.14, 0.26] [0.06, 0.13] Save as Child 0.20∗∗∗ 0.19∗∗∗ [0.07, 0.33] [0.11, 0.26] statecode==Arkhangai 0.10 0.41∗∗∗ [−0.19, 0.38] [0.25, 0.58] Bayan-Ulgii −0.99∗∗∗ 0.05 [−1.39, −0.59] [−0.09, 0.20] Bulgan 0.06 −0.19∗∗ [−0.18, 0.31] [−0.35, −0.03] Darkhan-Uul 0.10 −0.30∗∗ [−0.19, 0.39] [−0.59, −0.02] Dornogovi 0.29∗∗ 0.53∗∗∗ [0.04, 0.53] [0.30, 0.76] Govisumber −0.33 −0.38∗∗∗ [−0.92, 0.25] [−0.60, −0.16] Khovd −0.36∗∗ −0.31∗∗ [−0.64, −0.08] [−0.59, −0.04] Khovsgol −0.10 0.34∗∗∗ [−0.37, 0.18] [0.18, 0.50] Omnogovi 0.48∗∗∗ 0.44∗∗∗ [0.25, 0.72] [0.27, 0.62] Orkhon −0.18 −0.01 [−0.44, 0.08] [−0.17, 0.15] Ovorkhangai 0.12 −0.04 [−0.16, 0.40] [−0.29, 0.21] Selenge −0.15 0.23∗ [−0.38, 0.08] [−0.04, 0.49] - 53 - Sukhbaatar −0.05 0.51∗∗∗ [−0.42, 0.32] [0.21, 0.80] Tov 0.20 −0.32∗∗∗ [−0.20, 0.61] [−0.50, −0.13] Uvs −0.45∗∗ −0.15∗ [−0.80, −0.10] [−0.29, 0.00] Observations 2493 2493 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, region Ulaanbaatar, income lower MNT 210k, not saved as a child - 54 - B.2. Knowledge of Financial Products Background Information: Methods and Dependent Variables in Tables 17 and 18 Tables 17 and 18 considers the same list of institutions as analyzed for tables 4 and 5. The analyses in tables 17 and 18 explore the results from the ‘Knowledge’-columns in greater detail. Each institution is considered separately. For each institution a zero-one dummy is created, equal to one if the respondent answers ‘Yes ’ and zero if the reply is ‘No ’. The results are obtained by fitting probit models, extended for the correction of the survey setup. The following abbreviations are applied: • Banks Commercial banks • Insur Insurance Companies • Broker Intermediary organizations • MFO Microfinance Organizations • NBFI Other Non-Banking Financial Institutions • Exch. Exchange Office • MSE Mongolian Stock Exchange - 55 - Table 6: Knowledge of Specific Financial Products (Specification: Urban) Banks Insur Broker MFO NBFI Exch. MSE Age 0.07 −0.12 −0.04 0.06 0.04 0.01 0.03 [−0.08, 0.22] [−0.27, 0.03] [−0.18, 0.11] [−0.08, 0.20] [−0.08, 0.17] [−0.14, 0.16] [−0.11, 0.18] Age Square −0.00 0.00∗ 0.00 −0.00 −0.00 −0.00 −0.00 [−0.00, 0.00] [−0.00, 0.01] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Age Cube 0.00 −0.00∗∗ −0.00 0.00 0.00 0.00 0.00 [−0.00, 0.00] [−0.00, −0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Male −0.02 −0.00 0.13 −0.03 −0.04 0.22∗∗ 0.16 [−0.26, 0.22] [−0.20, 0.20] [−0.13, 0.38] [−0.27, 0.21] [−0.27, 0.18] [0.05, 0.40] [−0.06, 0.38] Household Head −0.12 −0.06 −0.21 −0.04 −0.05 −0.14 −0.08 [−0.43, 0.19] [−0.29, 0.18] [−0.49, 0.07] [−0.28, 0.21] [−0.31, 0.22] [−0.33, 0.04] [−0.30, 0.14] Secondary Educ. 0.01 0.19∗ 0.13 −0.06 0.04 −0.06 0.11 [−0.30, 0.32] [−0.04, 0.42] [−0.19, 0.44] [−0.34, 0.22] [−0.27, 0.34] [−0.33, 0.21] [−0.17, 0.40] Tertiary Educ. 0.12 0.25∗ 0.26 0.05 −0.00 0.00 0.20 [−0.22, 0.47] [−0.02, 0.52] [−0.06, 0.58] [−0.26, 0.36] [−0.33, 0.33] [−0.28, 0.29] [−0.12, 0.51] Literate (Mongolian) 1.05∗∗∗ −0.14 0.54 0.69∗∗∗ 0.72∗ 1.06∗∗∗ [0.65, 1.46] [−0.52, 0.23] [−0.82, 1.91] [0.21, 1.18] [−0.04, 1.49] [0.61, 1.52] Household Size −0.04 −0.04 −0.06∗ −0.01 −0.08∗∗ −0.11∗∗∗ −0.05 [−0.12, 0.04] [−0.11, 0.03] [−0.12, 0.00] [−0.06, 0.04] [−0.14, −0.02] [−0.16, −0.06] [−0.12, 0.02] Econ. Dep. Kids −0.02 −0.04 −0.03 −0.02 −0.00 0.02 −0.03 [−0.11, 0.08] [−0.11, 0.03] [−0.12, 0.07] [−0.10, 0.05] [−0.08, 0.07] [−0.05, 0.09] [−0.11, 0.05] Married/Cohabit 0.13 0.07 −0.29∗∗∗ −0.12 −0.14 −0.12 −0.21∗∗ [−0.12, 0.38] [−0.09, 0.23] [−0.48, −0.11] [−0.28, 0.03] [−0.33, 0.05] [−0.28, 0.05] [−0.39, −0.04] Formal Sector 0.23 0.42∗∗∗ 0.08 0.24∗ 0.31∗∗∗ 0.38∗∗∗ 0.57∗∗∗ [−0.14, 0.60] [0.13, 0.70] [−0.23, 0.39] [−0.01, 0.49] [0.10, 0.53] [0.16, 0.59] [0.35, 0.80] Informal Sector 0.33 0.13 −0.01 0.09 0.26∗ 0.35∗∗∗ 0.55∗∗∗ [−0.08, 0.75] [−0.15, 0.40] [−0.34, 0.31] [−0.14, 0.31] [−0.02, 0.53] [0.12, 0.57] [0.27, 0.84] Self Employed 0.28 0.20 0.19 0.43∗∗∗ 0.40∗∗∗ 0.58∗∗∗ 0.77∗∗∗ [−0.11, 0.67] [−0.07, 0.46] [−0.09, 0.48] [0.20, 0.66] [0.16, 0.65] [0.35, 0.82] [0.51, 1.02] Herdsman −0.50∗∗ 0.18 −0.37 −0.43∗ −0.87∗ −1.00∗∗∗ −0.46∗ [−0.95, −0.05] [−0.27, 0.62] [−0.89, 0.16] [−0.92, 0.06] [−1.74, 0.01] [−1.68, −0.32] [−0.96, 0.05] - 56 - Retired 0.12 −0.01 −0.59∗∗ −0.22 −0.12 −0.04 0.37∗∗∗ [−0.42, 0.66] [−0.35, 0.33] [−1.15, −0.03] [−0.57, 0.13] [−0.48, 0.24] [−0.35, 0.27] [0.10, 0.64] Unemployed −0.28 −0.18 −1.15∗∗∗ 0.07 −0.07 0.11 0.21 [−0.67, 0.11] [−0.52, 0.17] [−1.44, −0.86] [−0.31, 0.44] [−0.47, 0.33] [−0.32, 0.53] [−0.23, 0.64] 210k to 385k 0.19∗∗ 0.09 0.05 −0.01 0.17∗ 0.27∗∗∗ 0.12 [0.01, 0.37] [−0.09, 0.27] [−0.22, 0.33] [−0.22, 0.19] [−0.01, 0.36] [0.08, 0.45] [−0.09, 0.34] 385k to 645k 0.46∗∗∗ 0.24∗∗ 0.19 −0.01 0.28∗∗ 0.25∗∗ 0.22∗ [0.26, 0.67] [0.03, 0.45] [−0.13, 0.51] [−0.22, 0.20] [0.06, 0.51] [0.03, 0.46] [−0.01, 0.45] Higher 645k 0.73∗∗∗ 0.63∗∗∗ 0.39∗∗∗ 0.43∗∗∗ 0.67∗∗∗ 0.60∗∗∗ 0.56∗∗∗ [0.38, 1.08] [0.37, 0.89] [0.10, 0.67] [0.18, 0.67] [0.42, 0.93] [0.35, 0.85] [0.34, 0.78] Media Consumption 0.01 0.13∗∗∗ 0.17∗∗∗ 0.09∗∗ 0.08∗ 0.11∗∗∗ 0.13∗∗∗ [−0.07, 0.10] [0.07, 0.19] [0.09, 0.24] [0.02, 0.17] [−0.00, 0.16] [0.04, 0.18] [0.06, 0.20] Save as Child 0.22∗∗ 0.34∗∗∗ 0.29∗∗∗ 0.38∗∗∗ 0.25∗∗ 0.33∗∗∗ 0.38∗∗∗ [0.04, 0.40] [0.21, 0.48] [0.15, 0.42] [0.24, 0.53] [0.06, 0.45] [0.15, 0.52] [0.20, 0.56] Urban Environment 0.29∗ −0.19 −0.16 −0.52∗∗∗ −0.30∗∗∗ −0.04 −0.15 [−0.01, 0.59] [−0.43, 0.04] [−0.39, 0.08] [−0.73, −0.31] [−0.50, −0.11] [−0.25, 0.17] [−0.38, 0.08] Observations 2493 2492 2461 2493 2493 2492 2490 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, rural environment, income lower MNT 210k, not saved as a child Table 7: Knowledge of Specific Financial Products (Specification: Regional Dummies) Banks Insur Broker MFO NBFI Exch. MSE Age 0.07 −0.11 −0.05 0.09 0.04 0.02 0.03 [−0.10, 0.23] [−0.26, 0.04] [−0.21, 0.11] [−0.06, 0.24] [−0.09, 0.17] [−0.15, 0.19] [−0.12, 0.18] Age Square −0.00 0.00∗ 0.00 −0.00 −0.00 −0.00 −0.00 [−0.00, 0.00] [−0.00, 0.01] [−0.00, 0.00] [−0.01, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Age Cube 0.00 −0.00∗ −0.00 0.00 0.00 0.00 0.00 [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Male −0.05 −0.02 0.11 −0.03 −0.05 0.21∗∗ 0.16 [−0.29, 0.20] [−0.22, 0.18] [−0.14, 0.37] [−0.28, 0.21] [−0.28, 0.18] [0.03, 0.39] [−0.07, 0.38] Household Head −0.03 −0.02 −0.21 −0.04 −0.04 −0.10 −0.08 [−0.36, 0.29] [−0.26, 0.21] [−0.49, 0.08] [−0.29, 0.21] [−0.30, 0.23] [−0.29, 0.09] [−0.30, 0.15] Secondary Educ. −0.03 0.20 0.10 −0.12 0.00 −0.12 0.07 [−0.36, 0.30] [−0.04, 0.44] [−0.24, 0.44] [−0.44, 0.19] [−0.32, 0.32] [−0.40, 0.16] [−0.23, 0.37] Tertiary Educ. 0.14 0.26∗ 0.23 0.01 −0.03 −0.04 0.13 [−0.23, 0.52] [−0.02, 0.54] [−0.11, 0.58] [−0.34, 0.35] [−0.38, 0.33] [−0.34, 0.26] [−0.21, 0.48] Literate (Mongolian) 0.44 −0.18 0.80 0.72∗∗∗ 0.81∗∗ 1.32∗∗∗ [−0.18, 1.06] [−0.68, 0.33] [−0.58, 2.17] [0.28, 1.17] [0.09, 1.52] [0.90, 1.74] Household Size −0.01 −0.04 −0.05 −0.00 −0.08∗∗ −0.10∗∗∗ −0.06 [−0.10, 0.08] [−0.11, 0.03] [−0.12, 0.01] [−0.05, 0.05] [−0.15, −0.02] [−0.16, −0.05] [−0.13, 0.01] Econ. Dep. Kids 0.04 −0.04 −0.00 −0.04 0.02 0.04 −0.02 [−0.07, 0.14] [−0.11, 0.03] [−0.11, 0.10] [−0.12, 0.04] [−0.06, 0.10] [−0.03, 0.12] [−0.10, 0.07] Married/Cohabit 0.20 0.09 −0.25∗∗ −0.09 −0.10 −0.06 −0.15 [−0.08, 0.48] [−0.08, 0.25] [−0.43, −0.06] [−0.25, 0.07] [−0.29, 0.10] [−0.23, 0.11] [−0.34, 0.03] Formal Sector 0.26 0.44∗∗∗ 0.13 0.29∗∗ 0.36∗∗∗ 0.43∗∗∗ 0.66∗∗∗ [−0.15, 0.66] [0.15, 0.73] [−0.18, 0.45] [0.03, 0.55] [0.13, 0.59] [0.20, 0.66] [0.43, 0.89] Informal Sector 0.42∗ 0.11 −0.03 0.03 0.24 0.29∗∗ 0.53∗∗∗ [−0.03, 0.87] [−0.17, 0.39] [−0.37, 0.31] [−0.20, 0.27] [−0.05, 0.53] [0.06, 0.53] [0.23, 0.82] Self Employed 0.24 0.18 0.19 0.47∗∗∗ 0.40∗∗∗ 0.57∗∗∗ 0.79∗∗∗ [−0.17, 0.65] [−0.09, 0.45] [−0.11, 0.48] [0.23, 0.71] [0.15, 0.66] [0.33, 0.81] [0.53, 1.05] Herdsman −0.05 0.29 −0.00 −0.44 −0.46 −0.54∗ −0.06 [−0.49, 0.39] [−0.24, 0.81] [−0.61, 0.61] [−1.15, 0.27] [−1.38, 0.47] [−1.15, 0.07] [−0.61, 0.50] - 57 - Retired 0.18 0.02 −0.59∗ −0.17 −0.08 0.01 0.40∗∗∗ [−0.39, 0.76] [−0.32, 0.37] [−1.18, 0.00] [−0.52, 0.19] [−0.45, 0.29] [−0.31, 0.33] [0.12, 0.69] Unemployed −0.17 −0.20 −1.17∗∗∗ 0.15 0.02 0.24 0.36 [−0.59, 0.24] [−0.56, 0.16] [−1.47, −0.87] [−0.28, 0.58] [−0.41, 0.45] [−0.17, 0.65] [−0.11, 0.83] 210k to 385k 0.06 0.10 0.04 0.07 0.15 0.29∗∗∗ 0.15 [−0.14, 0.26] [−0.08, 0.29] [−0.26, 0.34] [−0.15, 0.29] [−0.03, 0.34] [0.10, 0.48] [−0.07, 0.37] 385k to 645k 0.45∗∗∗ 0.31∗∗∗ 0.24 0.03 0.31∗∗ 0.34∗∗∗ 0.24∗∗ [0.23, 0.67] [0.10, 0.52] [−0.11, 0.58] [−0.19, 0.25] [0.07, 0.54] [0.11, 0.56] [0.00, 0.48] Higher 645k 0.72∗∗∗ 0.71∗∗∗ 0.44∗∗∗ 0.50∗∗∗ 0.70∗∗∗ 0.73∗∗∗ 0.58∗∗∗ [0.34, 1.10] [0.45, 0.98] [0.11, 0.76] [0.23, 0.76] [0.43, 0.98] [0.48, 0.98] [0.35, 0.81] Media Consumption 0.10∗∗ 0.14∗∗∗ 0.20∗∗∗ 0.09∗∗ 0.11∗∗ 0.15∗∗∗ 0.14∗∗∗ [0.00, 0.20] [0.07, 0.20] [0.11, 0.28] [0.02, 0.17] [0.02, 0.20] [0.08, 0.22] [0.06, 0.22] Save as Child 0.17∗ 0.32∗∗∗ 0.23∗∗∗ 0.33∗∗∗ 0.19∗ 0.26∗∗∗ 0.29∗∗∗ [−0.01, 0.36] [0.19, 0.46] [0.08, 0.37] [0.19, 0.48] [−0.01, 0.39] [0.07, 0.46] [0.10, 0.48] statecode==Arkhangai 0.36 0.45∗∗ 0.42∗ 1.00∗∗∗ 0.47∗∗∗ 0.67∗∗∗ 0.38∗∗ [−0.15, 0.87] [0.09, 0.82] [−0.03, 0.87] [0.66, 1.35] [0.19, 0.76] [0.33, 1.01] [0.07, 0.68] Bayan-Ulgii −1.25∗∗∗ 0.18 −0.40∗ 0.85∗∗∗ 0.21 0.10 0.35∗∗ [−1.77, −0.73] [−0.24, 0.60] [−0.81, 0.02] [0.58, 1.12] [−0.06, 0.48] [−0.28, 0.47] [0.05, 0.65] Bulgan −0.12 0.18 −0.52∗ −0.45 −0.01 −0.46∗ −0.75∗∗ [−0.70, 0.47] [−0.16, 0.52] [−1.06, 0.02] [−1.19, 0.30] [−0.44, 0.42] [−0.97, 0.06] [−1.33, −0.17] Darkhan-Uul −0.20 −0.15 −0.36 −0.27 −0.48∗ −0.55∗∗ −0.88∗∗ [−0.78, 0.38] [−0.59, 0.30] [−0.85, 0.13] [−1.13, 0.59] [−1.03, 0.06] [−1.01, −0.09] [−1.58, −0.18] Dornogovi 0.16 0.61∗∗∗ 0.62 1.01∗∗∗ 0.87∗∗ 0.84∗∗ 0.64∗∗∗ [−0.22, 0.54] [0.30, 0.92] [−0.34, 1.57] [0.67, 1.35] [0.21, 1.54] [0.02, 1.66] [0.17, 1.12] Govisumber −0.58 −0.48∗∗ −0.40∗ 0.10 −0.26 −0.79∗∗∗ −0.81∗∗∗ [−1.29, 0.13] [−0.88, −0.09] [−0.86, 0.06] [−0.33, 0.52] [−0.67, 0.15] [−1.29, −0.29] [−1.25, −0.36] Khovd −1.00∗∗∗ 0.35 −0.28 0.13 −0.44∗ −1.00∗∗∗ −0.73∗∗∗ [−1.54, −0.46] [−0.23, 0.92] [−0.70, 0.14] [−0.45, 0.71] [−0.93, 0.04] [−1.36, −0.64] [−1.14, −0.32] Khovsgol 0.34 0.30∗ 0.58∗∗∗ 0.45∗∗∗ 0.51∗∗∗ 0.62∗∗∗ 0.43∗∗ [−0.28, 0.96] [−0.02, 0.62] [0.25, 0.90] [0.16, 0.73] [0.19, 0.84] [0.26, 0.97] [0.08, 0.77] Omnogovi 0.30 0.29∗ 0.59∗∗∗ 0.92∗∗∗ 0.71∗∗∗ 0.64∗∗∗ 0.67∗∗ [−0.18, 0.79] [−0.01, 0.59] [0.22, 0.96] [0.41, 1.43] [0.31, 1.12] [0.17, 1.11] [0.06, 1.27] Orkhon 0.35 0.33 −0.73∗∗ 0.01 −0.23 0.27 −0.75∗∗∗ [−0.25, 0.96] [−0.19, 0.85] [−1.40, −0.07] [−0.33, 0.35] [−0.74, 0.29] [−0.11, 0.65] [−1.24, −0.27] Ovorkhangai −0.24 0.28 −0.03 0.16 0.10 −0.35 −0.32 [−0.67, 0.20] [−0.07, 0.64] [−0.53, 0.46] [−0.21, 0.52] [−0.22, 0.42] [−0.77, 0.08] [−0.90, 0.26] Selenge −0.04 0.33∗ 0.22 0.39 0.43∗∗∗ 0.44∗∗ 0.19 [−1.26, 1.19] [−0.02, 0.68] [−0.23, 0.67] [−0.31, 1.10] [0.14, 0.72] [0.00, 0.88] [−0.36, 0.74] Sukhbaatar 0.46∗∗ 0.43∗ 0.46 1.20∗∗∗ 0.83∗∗∗ 0.75∗∗∗ 0.57∗ [0.07, 0.84] [−0.07, 0.93] [−0.67, 1.58] [0.82, 1.57] [0.44, 1.23] [0.27, 1.22] [−0.11, 1.25] Tov 0.25 −0.11 −0.58 −0.93∗∗∗ −0.19 −0.92∗∗ −0.93∗∗ [−0.38, 0.89] [−0.48, 0.26] [−1.32, 0.16] [−1.41, −0.46] [−0.65, 0.26] [−1.63, −0.20] [−1.75, −0.12] Uvs −0.86∗∗∗ 0.06 −0.24 0.83∗∗∗ −0.41∗ −0.63∗∗∗ −0.41 [−1.30, −0.41] [−0.42, 0.54] [−0.74, 0.27] [0.51, 1.14] [−0.83, 0.01] [−0.96, −0.30] [−0.96, 0.13] Observations 2493 2492 2461 2493 2493 2492 2490 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, region Ulaanbaatar, income lower MNT 210k, not saved as a child - 58 - B.3. Financial Attitudes and Behavior Background Information: Methods and Dependent Variables in Tabs. 9 throughout 14 Based on factor analysis four financial capability dimensions are derived. The scores are ranging from 0 (lowest capability) to 100 (highest capability). Each dimension entails several components, equally ranging from 0 to 100. All analyses in tabs. 9 throughout 14 apply the same linear probability model, correcting for the survey design. The following financial capability scores and abbreviations are applied: Controlled Budgeting Budgeting measures the extent to which people plan how to use their money and whether they adhere to the plan. Not Overspend assesses whether people refrain from spending their income on unnecessary things or on things they cannot afford. Making provisions for the future Living w/ means The outcome living within means measures the level of borrowing, whether people borrow to buy food and other essentials, and whether people who have money left over after buying essentials save it (instead of only spending it on non-essentials). Plan unexpected indicates whether people could cover an unexpected expense equivalent to a month’s income and whether they worry about it. Oldage Prep indicates whether people have strategies in place that allow them to cover for expenses in old age. Choosing product indicates whether people search for alternatives, check terms and conditions, and search for information before getting financial products. Thinking about the future Time preference measure whether people agree or disagree with statements such as ‘I live for today’, ‘The future will take care of itself’, ‘I only focus on the short term’. Not impulsive measures whether people agree or disagree with statements about impulsivity (being impulsive, saying things without giving them too much thought, doing things without thinking them through). Being Proactive Info/Learn The measure for attitudes towards information is a combination of getting information and advice before making financial decisions, learning from others, and being disciplined. Saving measures whether people see themselves as trying to save for the future, trying to save for emergencies, and trying to save even if a small amount. Achievement designates achievement orientation and assesses to what extent people agree with state- ments on having aspirations, working hard to be the best, always looking for opportunities to improve one’s own situation. - 59 - Table 8 presents the weights attached to specific components for the financial capability scores. An empty cell means that this component does not feed into the score of that column. Table 8: Component-weights of Financial Capability Score Dimensions Domain Compo- Controlled Making pro- Thinking Being proac- nents budgeting visions for about the tive the future future Budgeting 0.500 Not overspend 0.500 Living within means 0.550 Plan unexpected 0.516 Oldage Prep 0.303 Choosing product 0.391 Time preference 0.500 Not impulsive 0.500 Info 0.566 Saving 0.560 Achieve 0.370 - 60 - B.3.1. Dimensions Table 9: Financial Capability Scores (Specification: Urban) Controlled Budgeting Think Future Being Proactive Make Provisions Age 0.85 1.54∗ 0.24 1.15∗ [−1.39, 3.10] [−0.22, 3.29] [−1.00, 1.49] [−0.15, 2.45] Age Square −0.02 −0.03∗ −0.01 −0.03∗ [−0.06, 0.03] [−0.07, 0.00] [−0.03, 0.02] [−0.05, 0.00] Age Cube 0.00 0.00∗ 0.00 0.00∗∗ [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [0.00, 0.00] Male −2.06 2.12 −3.15∗∗∗ 2.71∗∗ [−5.21, 1.09] [−0.94, 5.19] [−5.27, −1.03] [0.20, 5.22] Household Head 1.49 −1.97 3.28∗∗∗ −1.67 [−1.10, 4.08] [−4.80, 0.85] [0.91, 5.64] [−4.18, 0.84] Secondary Educ. −0.59 0.13 −0.95 −0.74 [−4.47, 3.28] [−2.89, 3.14] [−3.96, 2.06] [−3.32, 1.84] - 61 - Tertiary Educ. −0.84 2.09 −0.87 −0.63 [−5.09, 3.42] [−1.60, 5.77] [−4.00, 2.26] [−3.73, 2.46] Literate (Mongolian) −11.24∗∗∗ 2.30 −0.72 −4.96∗ [−15.98, −6.50] [−9.81, 14.42] [−6.09, 4.65] [−10.27, 0.34] Household Size −0.35 −0.61 0.21 −1.37∗∗∗ [−1.72, 1.01] [−1.80, 0.57] [−0.41, 0.84] [−2.12, −0.62] Econ. Dep. Kids 1.53∗∗ 0.02 0.01 −0.79∗ [0.18, 2.87] [−0.84, 0.88] [−0.81, 0.83] [−1.66, 0.08] Married/Cohabit 0.71 −0.68 2.08∗ −0.04 [−2.00, 3.43] [−3.27, 1.91] [−0.04, 4.19] [−1.87, 1.79] Formal Sector 0.85 2.73 2.03 2.48 [−2.06, 3.75] [−1.14, 6.60] [−1.72, 5.79] [−0.81, 5.77] Informal Sector −0.20 5.27∗∗∗ −1.82 2.69 [−3.99, 3.59] [2.35, 8.19] [−5.90, 2.26] [−0.74, 6.11] Self Employed −1.30 5.09∗∗∗ 0.28 4.44∗∗ [−4.66, 2.06] [1.98, 8.20] [−3.45, 4.02] [0.72, 8.15] Herdsman 6.30∗∗ 8.80∗∗ 6.04∗∗ −0.66 [1.35, 11.24] [1.00, 16.60] [0.20, 11.88] [−5.13, 3.81] Retired −2.20 4.39∗∗ −2.70 0.85 [−6.60, 2.20] [0.09, 8.68] [−7.62, 2.23] [−2.30, 4.00] Unemployed 3.96∗ −0.30 1.52 −1.05 [−0.17, 8.09] [−4.20, 3.61] [−4.53, 7.57] [−5.64, 3.55] 210k to 385k −2.86∗∗ 0.23 −0.91 0.68 [−5.43, −0.29] [−2.34, 2.79] [−2.96, 1.13] [−1.50, 2.85] 385k to 645k −1.69 −0.48 4.19∗∗ 4.38∗∗∗ [−4.14, 0.75] [−3.21, 2.25] [0.93, 7.45] [2.16, 6.60] Higher 645k −4.16∗∗ −0.95 3.26∗ 9.85∗∗∗ [−7.56, −0.77] [−4.01, 2.12] [−0.28, 6.80] [7.10, 12.60] Media Consumption 2.92∗∗∗ −1.25∗∗ 0.96∗∗ 0.75 [1.82, 4.01] [−2.37, −0.13] [0.15, 1.77] [−0.17, 1.68] Save as Child 0.38 2.27∗∗ 2.97∗∗∗ 1.76∗∗ [−2.29, 3.05] [0.19, 4.35] [0.83, 5.11] [0.11, 3.42] - 62 - Urban Environment −4.00∗∗ −1.44 5.89∗∗∗ −1.90 [−7.52, −0.48] [−4.60, 1.72] [2.80, 8.98] [−4.71, 0.91] Observations 2484 2462 2210 2168 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, rural environment, income lower MNT 210k, not saved as a child Table 10: Financial Capability Scores (Specification: Regional Dummies) Controlled Budgeting Think Future Being Proactive Make Provisions Age 1.19 1.52∗ 0.02 1.09 [−1.09, 3.47] [−0.26, 3.31] [−1.27, 1.31] [−0.24, 2.42] Age Square −0.02 −0.03∗ −0.00 −0.03∗ [−0.07, 0.02] [−0.07, 0.00] [−0.03, 0.03] [−0.05, 0.00] Age Cube 0.00 0.00∗ −0.00 0.00∗∗ [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [0.00, 0.00] Male −2.23 2.13 −2.66∗∗ 2.26∗ [−5.37, 0.91] [−0.95, 5.22] [−4.72, −0.61] [−0.24, 4.77] Household Head 1.28 −1.87 2.25∗ −1.22 [−1.30, 3.86] [−4.77, 1.02] [−0.08, 4.59] [−3.69, 1.26] Secondary Educ. 0.36 0.34 −0.32 −1.09 [−3.28, 4.01] [−2.54, 3.22] [−3.31, 2.68] [−3.54, 1.36] Tertiary Educ. 0.07 2.31 −1.11 −0.80 [−4.06, 4.20] [−1.31, 5.93] [−4.18, 1.96] [−3.67, 2.08] - 63 - Literate (Mongolian) −8.47∗∗∗ 1.14 2.95 −6.25∗ [−13.55, −3.39] [−8.38, 10.66] [−2.28, 8.19] [−13.14, 0.64] Household Size −0.63 −0.56 −0.00 −1.33∗∗∗ [−1.99, 0.74] [−1.76, 0.64] [−0.60, 0.59] [−2.06, −0.60] Econ. Dep. Kids 1.07 0.00 −0.34 −0.49 [−0.26, 2.40] [−0.87, 0.88] [−1.18, 0.50] [−1.37, 0.38] Married/Cohabit −0.03 −0.76 1.62 0.40 [−2.74, 2.68] [−3.33, 1.80] [−0.47, 3.72] [−1.46, 2.27] Formal Sector 0.81 2.77 1.54 3.15∗ [−2.03, 3.65] [−1.18, 6.73] [−2.08, 5.15] [−0.06, 6.35] Informal Sector 0.07 5.00∗∗∗ −1.78 2.88 [−3.59, 3.73] [2.06, 7.94] [−5.69, 2.12] [−0.57, 6.33] Self Employed −0.99 4.91∗∗∗ 1.05 4.32∗∗ [−4.25, 2.26] [1.77, 8.05] [−2.46, 4.56] [0.64, 7.99] Herdsman 0.89 7.14∗∗ −1.97 5.85∗∗ [−3.16, 4.94] [0.35, 13.93] [−6.67, 2.74] [1.19, 10.51] Retired −1.45 4.37∗∗ −3.98 1.61 [−5.73, 2.83] [0.07, 8.67] [−8.81, 0.86] [−1.47, 4.68] Unemployed 1.49 −0.45 −0.40 −0.33 [−2.29, 5.26] [−4.36, 3.46] [−4.81, 4.01] [−4.62, 3.95] 210k to 385k −1.69 0.51 −0.40 0.35 [−4.16, 0.77] [−2.11, 3.14] [−2.45, 1.66] [−1.78, 2.48] 385k to 645k −0.45 0.11 2.79∗ 4.99∗∗∗ [−2.85, 1.95] [−2.65, 2.87] [−0.36, 5.95] [2.81, 7.16] Higher 645k −3.09∗ −0.16 1.42 10.24∗∗∗ [−6.54, 0.36] [−3.25, 2.92] [−2.07, 4.91] [7.43, 13.05] Media Consumption 2.22∗∗∗ −1.30∗∗ 0.37 1.03∗∗ [1.06, 3.38] [−2.51, −0.09] [−0.39, 1.14] [0.12, 1.93] Save as Child 1.00 2.08∗ 3.68∗∗∗ 1.10 [−1.65, 3.64] [−0.02, 4.17] [1.58, 5.79] [−0.54, 2.74] statecode==Arkhangai 1.10 1.11 −16.56∗∗∗ 7.47∗∗∗ - 64 - [−3.40, 5.60] [−3.02, 5.25] [−20.49, −12.63] [4.31, 10.63] Bayan-Ulgii 11.50∗∗∗ 1.62 1.04 −2.74 [6.78, 16.23] [−5.08, 8.32] [−2.57, 4.66] [−8.77, 3.30] Bulgan 15.16∗∗∗ −0.63 −6.14∗∗∗ 2.08 [10.33, 19.98] [−5.19, 3.94] [−9.47, −2.80] [−3.06, 7.22] Darkhan-Uul 4.81 2.28 −0.33 0.13 [−2.75, 12.37] [−2.97, 7.53] [−3.99, 3.32] [−4.76, 5.01] Dornogovi 0.04 0.73 −15.92∗∗∗ 8.76∗∗∗ [−5.22, 5.30] [−6.68, 8.14] [−19.97, −11.86] [4.91, 12.60] Govisumber −0.24 −3.72 2.92∗ −6.50∗∗ [−6.33, 5.85] [−8.62, 1.19] [−0.25, 6.10] [−12.03, −0.96] Khovd 16.73∗∗∗ 0.79 9.17∗∗∗ −4.60 [12.43, 21.03] [−4.69, 6.26] [3.73, 14.61] [−10.23, 1.03] Khovsgol −4.22∗ 3.09 −12.74∗∗∗ 5.70∗∗∗ [−8.88, 0.44] [−1.23, 7.40] [−16.13, −9.35] [2.20, 9.19] Omnogovi −2.33 4.74∗ −16.57∗∗∗ 5.30∗∗ [−6.33, 1.67] [−0.80, 10.29] [−19.51, −13.64] [1.14, 9.45] Orkhon 1.26 4.99∗ −8.11∗∗∗ −3.47 [−4.37, 6.88] [−0.09, 10.07] [−13.92, −2.30] [−8.06, 1.12] Ovorkhangai 10.82∗∗∗ 0.88 −7.72∗∗∗ 3.55 [5.60, 16.03] [−3.39, 5.15] [−11.37, −4.06] [−1.04, 8.14] Selenge 1.97 6.22∗∗ −8.20∗∗∗ 3.81∗ [−6.20, 10.14] [0.93, 11.52] [−12.91, −3.50] [−0.01, 7.62] Sukhbaatar −1.88 3.07 −15.21∗∗∗ 7.54∗∗∗ [−7.47, 3.72] [−4.17, 10.31] [−18.55, −11.88] [4.34, 10.74] Tov −6.16∗ 2.27 0.66 −6.57∗∗ [−13.25, 0.93] [−1.92, 6.47] [−4.97, 6.29] [−11.91, −1.23] Uvs 13.88∗∗∗ 8.13∗∗ 1.25 −8.28∗∗∗ [8.79, 18.96] [1.69, 14.57] [−4.75, 7.24] [−12.39, −4.17] Observations 2484 2462 2210 2168 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. - 65 - Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, region Ulaanbaatar, income lower MNT 210k, not saved as a child Controlled Budgeting Making Provisions for Future Being Proactive Think about Future 80 60 Average Score 40 20 67 66 64 61 69 66 62 59 0 Young Old Figure 92: Average financial capability scores, by respondents’ age. Controlled Budgeting Making Provisions for Future Being Proactive Think about Future 80 60 Average Score 40 20 68 65 63 59 68 67 62 60 0 Female Male Figure 93: Average financial capability scores, by respondents’ gender. Controlled Budgeting Making Provisions for Future Being Proactive Think about Future 80 60 Average Score 40 20 69 65 61 59 67 67 64 60 0 Primary / Seconday Tertiary Figure 94: Average financial capability scores, by respondents’ education. - 66 - B.3.2. Components Table 11: Elements of Financial Capability Scores (Specification: Urban 1) Budget Overspend Liv w Means Plan unexp. Oldage Prep Choose Prod Age 1.75 0.16 −0.18 2.38 5.32∗∗ −0.31 [−1.67, 5.17] [−2.01, 2.33] [−1.69, 1.33] [−0.74, 5.49] [0.96, 9.68] [−3.57, 2.95] Age Square −0.03 −0.01 −0.00 −0.06∗ −0.08∗ 0.01 [−0.10, 0.04] [−0.05, 0.04] [−0.04, 0.03] [−0.12, 0.01] [−0.17, 0.01] [−0.06, 0.08] Age Cube 0.00 0.00 0.00 0.00∗ 0.00 −0.00 [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Male −4.70∗ 0.03 4.49∗∗∗ −0.79 3.85 1.78 [−9.55, 0.15] [−3.48, 3.53] [2.12, 6.87] [−5.94, 4.36] [−3.39, 11.10] [−3.12, 6.68] Household Head 0.75 2.13 −3.65∗∗∗ 0.65 −2.08 1.02 [−3.41, 4.91] [−1.21, 5.47] [−6.16, −1.13] [−5.01, 6.31] [−8.29, 4.13] [−4.37, 6.41] Secondary Educ. −0.33 −0.82 0.32 4.25 −1.60 −8.20∗∗∗ [−6.38, 5.71] [−4.53, 2.90] [−3.23, 3.88] [−1.20, 9.70] [−8.54, 5.35] [−13.91, −2.48] Tertiary Educ. 0.65 −2.11 −1.27 6.01∗ −7.95∗∗ −3.48 [−6.19, 7.48] [−6.20, 1.98] [−5.09, 2.54] [−0.15, 12.16] [−15.14, −0.77] [−10.76, 3.81] Literate (Mongolian) −8.20 −13.77∗∗∗ −12.31∗∗∗ −13.53∗∗∗ 4.32 15.28∗∗∗ [−18.48, 2.08] [−17.24, −10.31] [−18.23, −6.39] [−21.67, −5.40] [−3.28, 11.93] [7.04, 23.52] Household Size −1.12 0.29 −0.70∗ −2.13∗∗∗ −1.23 −2.31∗∗∗ [−2.80, 0.56] [−1.24, 1.81] [−1.42, 0.02] [−3.49, −0.77] [−3.70, 1.23] [−3.68, −0.94] Econ. Dep. Kids 1.71∗ 1.38∗ −1.29∗∗ −0.67 −2.23∗ 0.81 [−0.09, 3.50] [−0.12, 2.89] [−2.30, −0.28] [−2.27, 0.93] [−4.47, 0.01] [−1.12, 2.74] Married/Cohabit 1.27 0.27 −1.78∗ 3.77∗∗ 1.14 0.37 [−2.82, 5.35] [−2.70, 3.23] [−3.82, 0.25] [0.29, 7.25] [−5.59, 7.86] [−3.63, 4.37] Formal Sector 3.05 −0.76 3.73∗ −2.29 11.76∗∗∗ 0.13 [−2.25, 8.36] [−3.87, 2.35] [−0.40, 7.85] [−7.59, 3.01] [3.03, 20.48] [−6.85, 7.10] Informal Sector −0.08 −0.10 6.21∗∗∗ −5.88∗ 14.35∗∗∗ −1.51 - 67 - [−6.58, 6.41] [−3.74, 3.54] [2.37, 10.05] [−12.24, 0.48] [4.16, 24.53] [−9.25, 6.23] Self Employed 2.16 −3.96∗∗ 5.59∗∗∗ 1.35 9.16∗ 3.35 [−3.95, 8.26] [−7.16, −0.76] [1.60, 9.59] [−4.62, 7.31] [−0.64, 18.96] [−3.53, 10.22] Herdsman 2.17 9.96∗∗∗ 6.89∗∗ 3.95 −11.78∗∗ −23.32∗∗∗ [−6.83, 11.16] [4.76, 15.16] [1.26, 12.52] [−3.35, 11.26] [−23.42, −0.15] [−31.64, −15.01] Retired −9.68∗∗ 4.35∗∗ 4.07 −5.16 13.37∗∗∗ −8.36∗∗ [−17.61, −1.75] [0.31, 8.39] [−1.21, 9.36] [−13.66, 3.33] [3.90, 22.84] [−15.75, −0.97] Unemployed 4.53 3.69 1.39 −0.92 −7.11 −2.57 [−3.12, 12.18] [−1.02, 8.41] [−4.40, 7.17] [−8.81, 6.97] [−17.43, 3.20] [−11.35, 6.21] 210k to 385k −1.24 −4.13∗∗∗ −0.62 0.83 6.00∗∗ 3.59∗ [−5.11, 2.63] [−6.73, −1.52] [−3.41, 2.16] [−3.23, 4.90] [1.10, 10.89] [−0.16, 7.34] 385k to 645k 0.02 −3.09∗∗ −0.15 6.41∗∗∗ 8.66∗∗∗ 9.70∗∗∗ [−4.03, 4.07] [−5.82, −0.36] [−2.56, 2.25] [1.60, 11.21] [2.98, 14.35] [4.41, 14.99] Higher 645k 1.16 −8.59∗∗∗ 2.35 15.59∗∗∗ 19.25∗∗∗ 15.73∗∗∗ [−4.05, 6.37] [−12.20, −4.99] [−1.21, 5.91] [9.66, 21.52] [11.36, 27.13] [9.58, 21.88] Media Consumption 4.87∗∗∗ 1.31∗∗ 0.74 0.14 2.20∗∗ 1.22 [3.07, 6.67] [0.13, 2.48] [−0.37, 1.84] [−1.38, 1.66] [0.06, 4.34] [−0.82, 3.27] Save as Child 4.89∗∗ −3.33∗∗ −1.40 3.48∗ 5.77∗∗ 5.26∗∗∗ [0.86, 8.92] [−5.93, −0.72] [−3.40, 0.60] [−0.31, 7.26] [1.37, 10.18] [1.78, 8.74] Urban Environment −2.97 −4.85∗∗∗ 1.05 −9.15∗∗∗ 4.19 1.32 [−9.17, 3.24] [−8.28, −1.41] [−2.05, 4.15] [−13.86, −4.44] [−3.95, 12.34] [−4.24, 6.87] Observations 2492 2485 2470 2472 2389 2297 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, rural environment, income lower MNT 210k, not saved as a child Table 12: Elements of Financial Capability Scores (Specification: Urban 2) Timepref Not Impuls Info Save Achieve Age 0.37 2.62∗∗ −0.49 1.16 −1.31 [−2.10, 2.83] [0.25, 5.00] [−2.01, 1.02] [−1.77, 4.09] [−3.72, 1.10] Age Square −0.02 −0.05∗∗ 0.01 −0.02 0.02 [−0.07, 0.04] [−0.10, −0.00] [−0.02, 0.04] [−0.09, 0.04] [−0.03, 0.07] Age Cube 0.00 0.00∗ −0.00 0.00 −0.00 [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Male 0.40 3.58∗ −2.92∗∗ −3.23 −2.38 [−3.25, 4.05] [−0.51, 7.67] [−5.59, −0.25] [−8.87, 2.41] [−6.19, 1.42] Household Head −2.05 −1.91 2.75∗ 3.51 3.71∗∗ [−5.78, 1.68] [−5.23, 1.42] [−0.01, 5.52] [−1.40, 8.43] [0.15, 7.27] Secondary Educ. −2.12 2.19 −0.47 1.91 −2.09 [−6.79, 2.55] [−2.28, 6.65] [−4.52, 3.59] [−4.41, 8.23] [−5.73, 1.55] Tertiary Educ. 1.66 2.52 −0.75 2.91 0.48 [−3.90, 7.23] [−1.93, 6.96] [−5.16, 3.66] [−3.97, 9.79] [−3.41, 4.37] Literate (Mongolian) 10.26∗ −4.62 −2.64 30.17∗∗∗ −1.20 [−1.53, 22.04] [−19.25, 10.01] [−7.96, 2.69] [15.30, 45.05] [−9.02, 6.62] Household Size −0.68 −0.57 −0.16 −1.32 1.05∗∗ - 68 - [−1.96, 0.60] [−1.84, 0.69] [−1.04, 0.73] [−3.06, 0.41] [0.17, 1.93] Econ. Dep. Kids 0.76 −0.61 0.49 0.07 −0.05 [−0.36, 1.88] [−1.62, 0.40] [−0.65, 1.63] [−1.81, 1.95] [−1.14, 1.04] Married/Cohabit −0.83 −0.74 2.37∗ 1.34 0.43 [−3.76, 2.10] [−3.91, 2.42] [−0.04, 4.77] [−2.66, 5.34] [−2.93, 3.80] Formal Sector 1.97 3.39 3.32 0.83 −3.01 [−2.70, 6.65] [−0.72, 7.50] [−0.82, 7.46] [−4.95, 6.62] [−7.32, 1.29] Informal Sector 5.28∗∗∗ 5.26∗∗∗ −0.27 −7.41∗∗ −2.52 [1.35, 9.22] [1.57, 8.95] [−4.59, 4.05] [−13.50, −1.32] [−7.12, 2.08] Self Employed 6.47∗∗∗ 3.85∗∗ 2.77 2.90 −7.04∗∗∗ [2.39, 10.55] [0.05, 7.64] [−1.11, 6.65] [−2.81, 8.61] [−11.73, −2.35] Herdsman 8.69∗∗ 8.82∗∗ 6.30∗ −11.81∗∗ −0.14 [0.19, 17.20] [0.69, 16.96] [−0.13, 12.73] [−20.93, −2.68] [−6.13, 5.85] Retired 1.90 6.20∗∗ −3.08 −7.59∗∗ −6.76∗∗∗ [−4.24, 8.04] [0.91, 11.48] [−7.80, 1.64] [−14.18, −1.00] [−11.62, −1.91] Unemployed −2.17 1.28 3.23 −4.91 2.67 [−8.13, 3.79] [−3.21, 5.76] [−2.68, 9.14] [−12.79, 2.97] [−3.61, 8.94] 210k to 385k −0.05 0.43 −0.31 2.79 −1.97 [−3.52, 3.42] [−2.47, 3.32] [−2.87, 2.24] [−1.16, 6.74] [−5.08, 1.14] 385k to 645k −1.12 0.11 2.85∗ 6.11∗∗∗ 5.51∗∗∗ [−4.95, 2.72] [−3.28, 3.51] [−0.39, 6.10] [1.94, 10.27] [1.81, 9.21] Higher 645k 0.69 −2.23 1.73 16.93∗∗∗ 2.23 [−3.51, 4.88] [−6.14, 1.69] [−1.85, 5.30] [11.65, 22.21] [−2.39, 6.86] Media Consumption −1.93∗∗ −0.64 1.57∗∗∗ 0.42 −0.00 [−3.43, −0.44] [−1.88, 0.59] [0.45, 2.68] [−1.79, 2.63] [−1.25, 1.24] Save as Child 1.87 2.70∗ 1.72 11.21∗∗∗ 3.62∗∗∗ [−0.72, 4.47] [−0.01, 5.41] [−0.63, 4.06] [7.95, 14.48] [0.99, 6.26] Urban Environment −2.48 −0.68 6.42∗∗∗ −3.70 −1.17 [−7.06, 2.11] [−4.10, 2.75] [3.85, 8.99] [−8.91, 1.51] [−5.90, 3.55] Observations 2470 2466 2279 2489 2444 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, rural environment, income lower MNT 210k, not saved as a child Table 13: Elements of Financial Capability Scores (Specification: Regional Dummies 1) - 69 - Budget Overspend Liv w Means Plan unexp. Oldage Prep Choose Prod Age 2.10 0.48 −0.42 2.88∗ 5.34∗∗ −0.54 [−1.37, 5.57] [−1.74, 2.69] [−1.98, 1.14] [−0.18, 5.95] [0.96, 9.72] [−3.84, 2.75] Age Square −0.04 −0.01 0.00 −0.07∗∗ −0.08∗ 0.01 [−0.11, 0.04] [−0.06, 0.03] [−0.03, 0.03] [−0.13, −0.00] [−0.17, 0.01] [−0.06, 0.08] Age Cube 0.00 0.00 0.00 0.00∗∗ 0.00∗ −0.00 [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Male −5.26∗∗ 0.20 4.02∗∗∗ −1.32 4.21 0.88 [−9.89, −0.63] [−3.42, 3.82] [1.64, 6.39] [−6.48, 3.84] [−3.14, 11.57] [−3.90, 5.66] Household Head 0.85 1.65 −3.25∗∗ 1.10 −2.12 2.33 [−3.16, 4.86] [−1.82, 5.12] [−5.71, −0.79] [−4.67, 6.87] [−8.33, 4.10] [−2.86, 7.52] Secondary Educ. 0.92 −0.11 0.30 4.24 −3.46 −8.62∗∗∗ [−5.06, 6.91] [−3.66, 3.44] [−3.18, 3.79] [−1.14, 9.63] [−10.13, 3.21] [−13.66, −3.58] Tertiary Educ. 2.24 −1.76 −1.43 5.95∗ −8.47∗∗ −3.29 [−4.68, 9.15] [−5.67, 2.14] [−5.08, 2.22] [−0.05, 11.96] [−15.39, −1.56] [−9.94, 3.35] Literate (Mongolian) −7.30 −9.47∗∗∗ −13.52∗∗∗ −8.73∗ −1.75 10.92∗∗ [−16.31, 1.70] [−13.86, −5.07] [−21.59, −5.45] [−18.80, 1.35] [−11.18, 7.67] [1.66, 20.18] Household Size −1.51∗ 0.11 −0.71∗ −2.19∗∗∗ −1.17 −2.13∗∗∗ [−3.16, 0.14] [−1.45, 1.66] [−1.42, 0.00] [−3.52, −0.85] [−3.67, 1.33] [−3.43, −0.83] Econ. Dep. Kids 1.40 0.81 −0.88∗ −0.98 −1.86 1.51 [−0.32, 3.12] [−0.74, 2.35] [−1.89, 0.14] [−2.60, 0.65] [−4.16, 0.45] [−0.32, 3.35] Married/Cohabit 0.39 −0.36 −1.01 3.99∗∗ 1.27 1.11 [−3.67, 4.45] [−3.35, 2.62] [−3.08, 1.06] [0.49, 7.50] [−5.59, 8.13] [−2.87, 5.08] Formal Sector 3.35 −1.08 4.51∗∗ −1.82 12.05∗∗∗ 1.03 [−1.87, 8.56] [−4.12, 1.97] [0.43, 8.58] [−7.07, 3.43] [3.51, 20.59] [−5.84, 7.90] Informal Sector 1.26 −0.73 6.48∗∗∗ −7.03∗∗ 16.44∗∗∗ −1.12 [−5.00, 7.51] [−4.40, 2.93] [2.62, 10.34] [−13.34, −0.72] [6.33, 26.55] [−8.75, 6.52] Self Employed 2.74 −3.89∗∗ 5.30∗∗∗ 0.85 10.48∗∗ 2.75 [−3.08, 8.56] [−7.10, −0.69] [1.34, 9.26] [−5.15, 6.86] [0.89, 20.07] [−3.89, 9.39] Herdsman 2.76 −0.53 13.48∗∗∗ 1.28 3.47 −7.94∗ [−5.95, 11.47] [−4.03, 2.96] [7.95, 19.01] [−5.26, 7.81] [−7.28, 14.23] [−17.29, 1.41] Retired −7.76∗ 4.09∗∗ 4.37 −4.62 14.70∗∗∗ −6.77∗ [−15.62, 0.11] [0.09, 8.09] [−0.96, 9.69] [−13.08, 3.85] [5.29, 24.11] [−14.16, 0.63] Unemployed 2.40 0.91 2.61 −2.59 −3.77 −0.21 [−4.32, 9.11] [−4.04, 5.86] [−2.43, 7.66] [−10.52, 5.34] [−13.78, 6.24] [−8.80, 8.39] 210k to 385k −0.90 −2.28∗ −1.61 2.46 3.77 2.08 [−4.55, 2.74] [−4.83, 0.27] [−4.38, 1.16] [−1.80, 6.71] [−0.92, 8.46] [−1.48, 5.64] 385k to 645k 1.66 −2.18 −0.12 8.68∗∗∗ 6.40∗∗ 10.82∗∗∗ [−2.25, 5.56] [−4.92, 0.57] [−2.53, 2.30] [3.88, 13.48] [1.07, 11.72] [5.68, 15.96] Higher 645k 2.44 −7.71∗∗∗ 1.99 18.15∗∗∗ 16.70∗∗∗ 16.85∗∗∗ [−2.89, 7.78] [−11.40, −4.01] [−1.72, 5.71] [12.26, 24.04] [8.94, 24.45] [10.69, 23.01] Media Consumption 4.19∗∗∗ 0.58 0.86 −0.28 3.16∗∗∗ 2.18∗∗ [2.30, 6.09] [−0.63, 1.79] [−0.26, 1.98] [−1.81, 1.26] [0.94, 5.38] [0.02, 4.34] Save as Child 5.78∗∗∗ −2.94∗∗ −1.96∗ 2.87 6.00∗∗∗ 3.88∗∗ [1.81, 9.75] [−5.56, −0.33] [−3.97, 0.06] [−0.85, 6.60] [1.72, 10.27] [0.40, 7.36] statecode==Arkhangai 1.00 0.98 −0.09 12.79∗∗∗ −1.26 13.33∗∗∗ [−7.06, 9.05] [−4.10, 6.06] [−4.13, 3.95] [5.82, 19.75] [−13.65, 11.13] [4.24, 22.41] Bayan-Ulgii 6.37∗ 15.74∗∗∗ −6.64∗ 17.72∗∗∗ −20.50∗∗∗ −11.26∗∗∗ [−1.03, 13.78] [10.31, 21.17] [−13.65, 0.37] [8.34, 27.10] [−33.26, −7.73] [−17.53, −4.99] Bulgan 27.17∗∗∗ 5.14∗ 1.05 6.07∗ −2.40 0.68 [19.75, 34.60] [−0.62, 10.90] [−4.75, 6.84] [−0.87, 13.01] [−15.28, 10.49] [−8.68, 10.05] Darkhan-Uul 8.96 1.36 −1.29 −1.13 0.67 1.93 [−3.99, 21.90] [−5.42, 8.13] [−5.13, 2.55] [−6.01, 3.74] [−11.97, 13.31] [−14.18, 18.04] Dornogovi 0.30 −0.18 4.81∗∗ 14.83∗∗∗ 3.13 11.29∗∗ [−11.71, 12.30] [−5.14, 4.79] [0.19, 9.43] [3.93, 25.73] [−8.13, 14.38] [2.29, 20.29] Govisumber 1.45 −1.70 −8.93∗∗∗ −12.36∗∗∗ 20.27∗∗ −17.36∗∗∗ [−7.61, 10.51] [−7.49, 4.09] [−14.19, −3.68] [−20.86, −3.85] [3.12, 37.41] [−27.35, −7.38] Khovd 9.58∗∗ 22.68∗∗∗ −10.44∗∗∗ 22.87∗∗∗ −14.89∗∗∗ −27.91∗∗∗ [1.05, 18.11] [18.20, 27.16] [−17.71, −3.18] [17.91, 27.83] [−25.72, −4.07] [−38.10, −17.71] Khovsgol −8.08∗∗ −1.04 7.42∗∗∗ 12.25∗∗∗ −18.72∗∗∗ 7.93∗∗ [−16.12, −0.05] [−5.79, 3.71] [4.18, 10.66] [5.48, 19.01] [−30.04, −7.41] [1.90, 13.95] Omnogovi −6.08 0.78 −3.92 12.10∗∗ 9.13∗ 14.85∗∗∗ [−16.04, 3.89] [−4.34, 5.91] [−9.27, 1.44] [1.52, 22.69] [−1.12, 19.37] [5.54, 24.16] Orkhon 2.83 −0.06 −7.24∗∗∗ 4.08 −11.04 2.66 [−6.31, 11.96] [−5.13, 5.00] [−12.28, −2.20] [−6.68, 14.84] [−24.48, 2.41] [−5.39, 10.72] Ovorkhangai 18.66∗∗∗ 4.28∗ −0.47 7.08∗∗ 6.00 2.84 [10.12, 27.21] [−0.47, 9.03] [−5.21, 4.27] [0.33, 13.83] [−6.20, 18.19] [−6.19, 11.86] - 70 - Selenge 4.02 0.22 1.69 12.54∗∗∗ −10.42 6.29∗ [−8.12, 16.16] [−5.98, 6.42] [−3.80, 7.19] [4.03, 21.05] [−23.81, 2.98] [−0.80, 13.38] Sukhbaatar −3.57 −0.44 1.63 18.87∗∗∗ −0.86 9.15∗∗∗ [−13.69, 6.55] [−5.75, 4.86] [−3.77, 7.03] [12.90, 24.84] [−11.44, 9.72] [2.61, 15.69] Tov −21.88∗∗∗ 6.93∗∗ −8.27∗∗∗ −1.28 −13.74∗∗∗ −9.49∗∗ [−34.32, −9.43] [1.11, 12.74] [−12.06, −4.47] [−15.00, 12.44] [−22.28, −5.20] [−18.47, −0.50] Uvs 4.97 21.43∗∗∗ −12.08∗∗∗ 13.26∗∗∗ −35.08∗∗∗ −19.61∗∗∗ [−4.72, 14.66] [17.90, 24.97] [−17.22, −6.94] [6.99, 19.52] [−44.25, −25.92] [−27.72, −11.50] Observations 2492 2485 2470 2472 2389 2297 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, region Ulaanbaatar, income lower MNT 210k, not saved as a child Table 14: Elements of Financial Capability Scores (Specification: Regional Dummies 2) Timepref Not Impuls Info Save Achieve Age 0.10 2.83∗∗ −0.34 1.62 −1.71 [−2.43, 2.63] [0.45, 5.20] [−1.88, 1.19] [−1.28, 4.51] [−4.27, 0.86] Age Square −0.01 −0.06∗∗ 0.01 −0.03 0.03 [−0.06, 0.04] [−0.11, −0.01] [−0.02, 0.04] [−0.09, 0.03] [−0.02, 0.09] Age Cube 0.00 0.00∗∗ −0.00 0.00 −0.00 [−0.00, 0.00] [0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Male 0.51 3.48∗ −2.82∗∗ −2.99 −1.50 [−3.14, 4.16] [−0.61, 7.57] [−5.35, −0.28] [−8.64, 2.66] [−5.33, 2.33] Household Head −1.98 −1.77 2.34∗ 3.32 2.08 [−5.73, 1.78] [−5.19, 1.65] [−0.35, 5.04] [−1.68, 8.31] [−1.53, 5.70] Secondary Educ. −2.21 2.65 0.25 1.58 −1.63 [−6.78, 2.37] [−1.76, 7.06] [−3.75, 4.24] [−4.55, 7.71] [−5.15, 1.90] Tertiary Educ. 1.75 2.81 −0.41 3.61 0.08 [−3.82, 7.33] [−1.63, 7.26] [−4.75, 3.94] [−3.20, 10.42] [−3.74, 3.89] Literate (Mongolian) 4.02 −1.36 −1.20 29.67∗∗∗ 4.63 [−7.87, 15.91] [−13.33, 10.61] [−7.40, 5.00] [12.02, 47.32] [−5.36, 14.62] Household Size −0.51 −0.63 −0.40 −1.26 0.85∗ [−1.81, 0.79] [−1.90, 0.63] [−1.31, 0.51] [−3.02, 0.50] [−0.04, 1.75] Econ. Dep. Kids 1.02∗ −0.85 0.15 0.10 −0.36 [−0.09, 2.12] [−1.88, 0.19] [−1.01, 1.31] [−1.77, 1.98] [−1.49, 0.76] Married/Cohabit −0.72 −0.99 1.68 1.28 0.13 [−3.64, 2.20] [−4.15, 2.16] [−0.68, 4.04] [−2.73, 5.30] [−3.23, 3.48] Formal Sector 2.03 3.42 2.96 1.22 −3.32 [−2.78, 6.84] [−0.75, 7.60] [−1.13, 7.05] [−4.67, 7.10] [−7.44, 0.80] Informal Sector 5.02∗∗ 4.95∗∗∗ −0.01 −6.54∗∗ −2.48 - 71 - [1.10, 8.93] [1.29, 8.61] [−4.33, 4.31] [−12.63, −0.46] [−6.84, 1.87] Self Employed 6.36∗∗∗ 3.60∗ 3.12 4.04 −6.29∗∗∗ [2.29, 10.43] [−0.22, 7.41] [−0.75, 6.98] [−1.62, 9.70] [−10.89, −1.68] Herdsman 8.71∗∗ 5.74 0.18 −6.03 −9.34∗∗∗ [0.84, 16.58] [−1.39, 12.86] [−6.25, 6.61] [−14.42, 2.37] [−15.15, −3.53] Retired 1.56 6.48∗∗ −3.08 −5.88∗ −8.72∗∗∗ [−4.55, 7.67] [1.21, 11.75] [−7.81, 1.64] [−12.42, 0.66] [−13.47, −3.97] Unemployed −1.62 0.50 0.95 −2.84 1.41 [−7.59, 4.34] [−3.99, 4.99] [−4.24, 6.15] [−10.76, 5.09] [−3.97, 6.78] 210k to 385k −0.18 1.09 0.19 2.22 −1.36 [−3.65, 3.29] [−1.89, 4.07] [−2.42, 2.81] [−1.76, 6.20] [−4.39, 1.66] 385k to 645k −1.19 1.26 2.55 5.58∗∗∗ 3.38∗ [−5.17, 2.79] [−2.06, 4.59] [−0.75, 5.85] [1.37, 9.80] [−0.18, 6.95] Higher 645k 0.97 −1.02 1.08 16.14∗∗∗ −0.70 [−3.42, 5.35] [−4.90, 2.85] [−2.66, 4.83] [10.75, 21.54] [−5.04, 3.64] Media Consumption −1.64∗∗ −0.98 1.22∗∗ 0.83 −0.82 [−3.24, −0.04] [−2.32, 0.36] [0.05, 2.39] [−1.59, 3.24] [−2.03, 0.39] Save as Child 1.40 2.75∗∗ 2.46∗∗ 11.47∗∗∗ 4.25∗∗∗ [−1.18, 3.98] [0.01, 5.48] [0.16, 4.75] [8.18, 14.75] [1.65, 6.85] statecode==Arkhangai 1.73 0.77 −12.76∗∗∗ 6.17 −13.44∗∗∗ [−3.86, 7.32] [−3.79, 5.33] [−17.19, −8.33] [−2.75, 15.08] [−19.31, −7.58] Bayan-Ulgii −5.31 7.64∗∗ −1.58 1.23 9.08∗∗∗ [−13.59, 2.98] [0.31, 14.97] [−5.29, 2.13] [−9.18, 11.64] [2.90, 15.26] Bulgan −2.37 0.91 0.43 11.47∗∗∗ −2.21 [−8.98, 4.24] [−3.79, 5.62] [−3.00, 3.86] [3.74, 19.21] [−7.46, 3.04] Darkhan-Uul −2.42 5.13∗ 0.56 8.09∗∗ 3.47 [−11.11, 6.27] [−0.11, 10.36] [−6.32, 7.45] [0.39, 15.79] [−2.28, 9.21] Dornogovi 2.72 −1.00 −15.27∗∗∗ 12.18∗∗ −6.17∗ [−8.00, 13.45] [−7.51, 5.51] [−20.89, −9.66] [1.68, 22.68] [−13.06, 0.72] Govisumber 4.57 −10.86∗∗∗ −5.94∗∗∗ 16.21∗∗∗ 12.13∗∗∗ [−4.37, 13.50] [−14.95, −6.76] [−9.60, −2.27] [9.03, 23.39] [6.72, 17.53] Khovd −0.51 1.93 5.95∗∗ −11.08∗ 11.36∗∗∗ [−9.11, 8.08] [−3.10, 6.97] [0.76, 11.13] [−22.36, 0.21] [5.99, 16.73] Khovsgol 6.19∗∗ 0.41 −16.78∗∗∗ −6.78 −3.27 [0.50, 11.89] [−4.21, 5.02] [−19.93, −13.62] [−16.34, 2.77] [−9.25, 2.71] Omnogovi 9.08∗∗ 1.01 −12.48∗∗∗ 3.05 −11.12∗∗∗ [1.39, 16.77] [−4.11, 6.13] [−15.43, −9.53] [−4.10, 10.20] [−19.36, −2.87] Orkhon 3.53 6.27∗∗ −2.31 −0.44 −16.32∗∗∗ [−3.93, 10.98] [1.19, 11.35] [−6.05, 1.43] [−9.43, 8.55] [−26.66, −5.97] - 72 - Ovorkhangai −1.31 2.78 −2.24 8.45∗∗∗ −5.84∗∗ [−7.55, 4.93] [−2.58, 8.14] [−5.57, 1.09] [2.35, 14.56] [−10.90, −0.77] Selenge 10.80∗∗∗ 2.30 −9.42∗∗∗ 1.10 −8.00∗∗ [5.45, 16.15] [−4.91, 9.50] [−15.55, −3.29] [−7.73, 9.93] [−15.73, −0.26] Sukhbaatar 5.18 1.23 −12.16∗∗∗ 19.84∗∗∗ −11.01∗∗∗ [−4.91, 15.28] [−6.28, 8.74] [−14.90, −9.42] [12.32, 27.37] [−17.31, −4.70] Tov 4.75 0.22 −1.62 −7.68 10.91∗∗ [−2.95, 12.45] [−4.29, 4.74] [−5.17, 1.92] [−19.49, 4.14] [0.65, 21.17] Uvs 6.52 9.50∗∗∗ 0.20 0.49 9.61∗∗∗ [−1.62, 14.65] [3.40, 15.60] [−5.93, 6.33] [−7.17, 8.15] [3.80, 15.42] Observations 2470 2466 2279 2489 2444 ∗ ∗∗ ∗∗∗ Significance: (p < 0.10), (p < 0.05), (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, region Ulaanbaatar, income lower MNT 210k, not saved as a child C. Financial Inclusion: Access and Usage of Financial Services C.1. Products Background Information: Methods and Dependent Variables in Tables 15 and 16 Products Similar to Knowledge, but asking; ‘Regarding some financial products and services that some people use, do you currently have any of the following? ’. The products and services are: Insurance (health, life or income replacement insurance), Mortgage, Formal credit (loan from a commercial bank, credit card), General insurance (car insurance, household contents insurance, building insurance), Formal savings / deposit account in a commercial bank, Checking account / money transfer services (internet banking, Mobile banking, Western Union, debit card), Credit from micro finance institution (e.g Imon, Humo etc), Saving at micro deposit institution (e.g Bovari va Hamkori etc), Informal credit (loan from informal money lenders, loan from family or friends that need to be repaid), Informal savings (at home: keeping money under the mattress), and Other. The same model is fitted. Table 15: Financial Inclusion (Specification: Urban) Products Age 0.02 [−0.02, 0.06] Age Square −0.00 [−0.00, 0.00] Age Cube 0.00 [−0.00, 0.00] Male −0.05 [−0.13, 0.03] Household Head 0.05 [−0.04, 0.13] Secondary Educ. 0.05 [−0.04, 0.13] Tertiary Educ. 0.08 [−0.02, 0.17] Literate (Mongolian) 0.66∗ [−0.04, 1.35] Household Size −0.03∗ [−0.05, 0.00] Econ. Dep. Kids 0.01 [−0.01, 0.04] Married/Cohabit 0.06∗∗ [0.00, 0.12] Formal Sector 0.10∗∗∗ [0.03, 0.17] Informal Sector −0.07∗ [−0.16, 0.01] Self Employed 0.09∗∗ [0.01, 0.17] Herdsman −0.14∗∗ - 73 - [−0.25, −0.03] Retired −0.09 [−0.20, 0.02] Unemployed 0.01 [−0.12, 0.15] 210k to 385k 0.06∗ [−0.01, 0.12] 385k to 645k 0.18∗∗∗ [0.11, 0.25] Higher 645k 0.34∗∗∗ [0.26, 0.42] Media Consumption 0.03∗ [−0.00, 0.06] Save as Child 0.17∗∗∗ [0.12, 0.22] Urban Environment −0.09∗∗ [−0.18, −0.01] Observations 2493 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, rural environment, income lower MNT 210k, not saved as a child Table 16: Financial Inclusion (Specification: Regional Dummies) Products Age 0.03 [−0.02, 0.07] Age Square −0.00 [−0.00, 0.00] Age Cube 0.00 [−0.00, 0.00] Male −0.04 [−0.12, 0.04] Household Head 0.04 [−0.04, 0.13] Secondary Educ. 0.04 [−0.05, 0.12] Tertiary Educ. 0.08∗ [−0.01, 0.18] Literate (Mongolian) 0.68∗ [−0.04, 1.40] Household Size −0.03∗ [−0.05, 0.00] Econ. Dep. Kids 0.01 [−0.02, 0.04] Married/Cohabit 0.05∗ [−0.01, 0.11] - 74 - Formal Sector 0.10∗∗∗ [0.03, 0.17] Informal Sector −0.06 [−0.15, 0.02] Self Employed 0.10∗∗ [0.02, 0.18] Herdsman −0.13∗ [−0.27, 0.01] Retired −0.07 [−0.19, 0.04] Unemployed 0.03 [−0.11, 0.17] 210k to 385k 0.05 [−0.01, 0.12] 385k to 645k 0.16∗∗∗ [0.09, 0.23] Higher 645k 0.32∗∗∗ [0.24, 0.40] Media Consumption 0.03∗∗ [0.00, 0.07] Save as Child 0.18∗∗∗ [0.13, 0.24] statecode==Arkhangai 0.06 [−0.10, 0.23] Bayan-Ulgii 0.12 [−0.04, 0.28] Bulgan 0.17∗∗∗ [0.05, 0.28] Darkhan-Uul 0.03 [−0.09, 0.15] Dornogovi 0.22∗∗ [0.05, 0.39] Govisumber 0.30∗∗∗ [0.18, 0.42] Khovd −0.02 [−0.25, 0.21] Khovsgol −0.22∗∗∗ [−0.37, −0.07] Omnogovi 0.11 [−0.08, 0.31] Orkhon 0.05 [−0.07, 0.17] Ovorkhangai 0.13∗∗ [0.02, 0.25] Selenge −0.06 [−0.19, 0.07] Sukhbaatar 0.24∗∗∗ [0.11, 0.36] - 75 - Tov 0.17∗∗ [0.03, 0.30] Uvs 0.10 [−0.02, 0.22] Observations 2493 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, region Ulaanbaatar, income lower MNT 210k, not saved as a child C.2. Financial Institutions Background Information: Methods and Dependent Variables in Tables 17 and 18 Tables 17 and 18 extend the analyses of tables 15 and 16. Following the same list and given that an individual knows the services offered by the institution (see tabs. 4 and 5) he or she is asked: ‘If Yes, have you ever used it? ’. Again zero-one dummies are generated. Agents who did not know the services offered by the institution where assessed as never having used these services. Thereby the results include the entire sample and the analyses become more meaningful. Like above probit models are estimated, extended for the correction of the survey setup. Again, the following abbreviations are applied: Banks Commercial banks Insur Insurance companies Broker Brokerage Houses MFO Microfinance organizations Exch. Exchange office MSE Mongolian Stock Exchange Analyses for other NBFIs are excluded since too few people use these products, which makes a more thorough statistical investigation not applicable. - 76 - Table 17: Usage of Specific Financial Products (Specification: Urban) Banks Insur Broker MFO Exch. MSE Age 0.13∗ −0.14∗∗ −0.21 −0.02 0.06 0.01 [−0.01, 0.27] [−0.27, −0.02] [−0.54, 0.12] [−0.14, 0.11] [−0.11, 0.23] [−0.23, 0.25] Age Square −0.00∗ 0.00∗∗ 0.01 0.00 −0.00 −0.00 [−0.01, 0.00] [0.00, 0.01] [−0.00, 0.01] [−0.00, 0.00] [−0.01, 0.00] [−0.01, 0.01] Age Cube 0.00∗ −0.00∗∗ −0.00 −0.00 0.00 0.00 [−0.00, 0.00] [−0.00, −0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Male −0.03 0.05 −0.16 −0.00 0.12 0.25∗ [−0.26, 0.20] [−0.17, 0.27] [−0.56, 0.24] [−0.25, 0.25] [−0.06, 0.30] [−0.04, 0.53] Household Head −0.13 −0.11 0.16 −0.07 −0.14 −0.17 [−0.40, 0.14] [−0.37, 0.14] [−0.29, 0.60] [−0.36, 0.21] [−0.35, 0.08] [−0.46, 0.13] Secondary Educ. −0.05 0.14 0.06 0.29∗∗ −0.00 −0.00 [−0.34, 0.24] [−0.12, 0.40] [−0.55, 0.66] [0.07, 0.51] [−0.33, 0.32] [−0.61, 0.60] Tertiary Educ. 0.11 0.22 0.34 0.47∗∗∗ 0.14 0.34 [−0.23, 0.44] [−0.08, 0.51] [−0.25, 0.93] [0.20, 0.73] [−0.18, 0.47] [−0.25, 0.93] Literate (Mongolian) 1.29∗∗∗ −0.22 0.32 [0.78, 1.79] [−0.57, 0.13] [−0.14, 0.77] Household Size −0.04 −0.02 0.01 −0.00 −0.10∗∗∗ −0.05 [−0.11, 0.03] [−0.10, 0.06] [−0.12, 0.15] [−0.08, 0.07] [−0.15, −0.04] [−0.14, 0.05] Econ. Dep. Kids 0.00 −0.00 −0.06 0.07 0.02 0.02 [−0.08, 0.09] [−0.08, 0.07] [−0.22, 0.09] [−0.02, 0.16] [−0.06, 0.09] [−0.08, 0.11] Married/Cohabit 0.10 0.19∗∗ −0.00 −0.02 −0.11 −0.21∗ [−0.13, 0.32] [0.00, 0.37] [−0.33, 0.32] [−0.20, 0.16] [−0.29, 0.06] [−0.42, 0.01] Formal Sector 0.15 0.34∗∗ −0.34 0.12 0.21∗ 0.45∗∗ [−0.22, 0.52] [0.06, 0.62] [−0.80, 0.11] [−0.16, 0.41] [−0.00, 0.43] [0.07, 0.82] Informal Sector 0.28 0.07 −0.37 0.05 0.26∗∗ 0.53∗∗ [−0.10, 0.67] [−0.24, 0.37] [−0.86, 0.13] [−0.24, 0.34] [0.02, 0.50] [0.09, 0.97] Self Employed 0.21 0.13 −0.23 0.24 0.53∗∗∗ 0.66∗∗∗ [−0.15, 0.57] [−0.12, 0.39] [−0.78, 0.31] [−0.06, 0.54] [0.29, 0.78] [0.29, 1.02] Herdsman −0.42∗ 0.27 −0.60∗∗ −0.13 −1.36∗∗∗ −0.13 [−0.87, 0.03] [−0.14, 0.67] [−1.17, −0.04] [−0.68, 0.42] [−1.75, −0.98] [−0.65, 0.40] - 77 - Retired 0.04 0.00 −0.84∗ −0.36∗ −0.14 0.08 [−0.43, 0.52] [−0.34, 0.35] [−1.70, 0.02] [−0.79, 0.06] [−0.50, 0.22] [−0.36, 0.52] Unemployed −0.18 −0.06 0.36∗ 0.02 0.41 [−0.56, 0.20] [−0.43, 0.32] [−0.05, 0.78] [−0.43, 0.47] [−0.22, 1.04] 210k to 385k 0.10 −0.06 −0.27 −0.09 0.26∗∗ 0.18 [−0.07, 0.27] [−0.24, 0.12] [−0.64, 0.11] [−0.32, 0.13] [0.06, 0.46] [−0.16, 0.51] 385k to 645k 0.45∗∗∗ 0.24∗∗ 0.02 −0.20 0.14 0.26 [0.23, 0.67] [0.03, 0.45] [−0.43, 0.47] [−0.45, 0.05] [−0.08, 0.37] [−0.08, 0.60] Higher 645k 0.52∗∗∗ 0.51∗∗∗ 0.27 0.09 0.50∗∗∗ 0.64∗∗∗ [0.22, 0.82] [0.25, 0.78] [−0.12, 0.65] [−0.24, 0.41] [0.22, 0.78] [0.31, 0.97] Media Consumption −0.01 0.11∗∗∗ 0.19∗∗∗ 0.11∗∗∗ 0.09∗∗∗ 0.22∗∗∗ [−0.10, 0.07] [0.04, 0.18] [0.05, 0.32] [0.03, 0.20] [0.03, 0.16] [0.13, 0.31] Save as Child 0.20∗∗ 0.32∗∗∗ 0.08 0.32∗∗∗ 0.30∗∗∗ 0.24∗∗ [0.02, 0.38] [0.17, 0.48] [−0.15, 0.31] [0.14, 0.51] [0.12, 0.48] [0.00, 0.48] Urban Environment 0.35∗∗ −0.07 0.06 −0.42∗∗∗ −0.01 −0.02 [0.07, 0.63] [−0.32, 0.19] [−0.24, 0.35] [−0.66, −0.18] [−0.24, 0.22] [−0.25, 0.21] Observations 2493 2493 2365 2493 2461 2461 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, rural environment, income lower MNT 210k, not saved as a child Table 18: Usage of Specific Financial Products (Specification: Regional Dummies) Banks Insur Broker MFO Exch. MSE Age 0.11 −0.13∗∗ −0.23 0.02 0.06 0.00 [−0.04, 0.26] [−0.26, −0.00] [−0.57, 0.11] [−0.11, 0.16] [−0.12, 0.25] [−0.25, 0.25] Age Square −0.00 0.00∗∗ 0.01 −0.00 −0.00 0.00 [−0.01, 0.00] [0.00, 0.01] [−0.00, 0.01] [−0.00, 0.00] [−0.01, 0.00] [−0.01, 0.01] Age Cube 0.00 −0.00∗∗ −0.00 0.00 0.00 −0.00 [−0.00, 0.00] [−0.00, −0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] [−0.00, 0.00] Male −0.05 0.03 −0.18 −0.00 0.11 0.25∗ [−0.28, 0.19] [−0.19, 0.26] [−0.59, 0.24] [−0.26, 0.26] [−0.07, 0.29] [−0.04, 0.54] Household Head −0.06 −0.09 0.16 −0.08 −0.11 −0.18 [−0.34, 0.21] [−0.35, 0.17] [−0.30, 0.62] [−0.37, 0.22] [−0.33, 0.12] [−0.49, 0.13] Secondary Educ. −0.07 0.14 0.01 0.27∗ −0.02 −0.02 [−0.37, 0.23] [−0.12, 0.41] [−0.67, 0.70] [−0.00, 0.55] [−0.36, 0.32] [−0.61, 0.58] Tertiary Educ. 0.13 0.22 0.31 0.46∗∗∗ 0.15 0.32 [−0.23, 0.49] [−0.08, 0.52] [−0.36, 0.98] [0.14, 0.77] [−0.19, 0.49] [−0.26, 0.90] Literate (Mongolian) 0.70∗∗ −0.26 0.67∗∗ [0.02, 1.38] [−0.71, 0.19] [0.11, 1.23] Household Size −0.02 −0.02 0.02 0.00 −0.08∗∗∗ −0.05 [−0.09, 0.06] [−0.10, 0.06] [−0.12, 0.16] [−0.07, 0.08] [−0.14, −0.03] [−0.15, 0.05] Econ. Dep. Kids 0.05 −0.01 −0.05 0.04 0.05 0.04 [−0.04, 0.14] [−0.08, 0.07] [−0.21, 0.12] [−0.05, 0.13] [−0.03, 0.13] [−0.07, 0.15] Married/Cohabit 0.14 0.19∗∗ 0.04 0.00 −0.05 −0.17 [−0.10, 0.38] [0.00, 0.37] [−0.30, 0.38] [−0.19, 0.19] [−0.24, 0.13] [−0.39, 0.05] Formal Sector 0.16 0.36∗∗ −0.32 0.16 0.26∗∗ 0.48∗∗ [−0.23, 0.55] [0.07, 0.64] [−0.79, 0.15] [−0.12, 0.45] [0.02, 0.50] [0.08, 0.87] Informal Sector 0.35∗ 0.06 −0.39 −0.01 0.20 0.48∗∗ [−0.06, 0.77] [−0.25, 0.37] [−0.90, 0.12] [−0.31, 0.29] [−0.05, 0.46] [0.03, 0.94] Self Employed 0.17 0.13 −0.27 0.29∗ 0.53∗∗∗ 0.64∗∗∗ [−0.20, 0.55] [−0.13, 0.39] [−0.84, 0.31] [−0.02, 0.60] [0.27, 0.79] [0.25, 1.02] Herdsman −0.01 0.22 −0.15 −0.31 −0.77∗∗∗ 0.33 [−0.47, 0.46] [−0.28, 0.72] [−0.81, 0.52] [−1.05, 0.42] [−1.12, −0.41] [−0.27, 0.93] - 78 - Retired 0.08 0.03 −0.85∗ −0.32 −0.11 0.06 [−0.41, 0.56] [−0.31, 0.38] [−1.77, 0.06] [−0.75, 0.11] [−0.49, 0.28] [−0.40, 0.52] Unemployed −0.09 −0.11 0.43∗ 0.19 0.52 [−0.50, 0.33] [−0.50, 0.29] [−0.04, 0.90] [−0.29, 0.66] [−0.20, 1.24] 210k to 385k −0.02 −0.04 −0.28 0.02 0.26∗∗ 0.20 [−0.20, 0.15] [−0.22, 0.14] [−0.69, 0.12] [−0.23, 0.27] [0.05, 0.47] [−0.15, 0.56] 385k to 645k 0.44∗∗∗ 0.30∗∗∗ 0.06 −0.20 0.21∗ 0.27 [0.20, 0.67] [0.08, 0.52] [−0.42, 0.55] [−0.48, 0.08] [−0.03, 0.45] [−0.08, 0.63] Higher 645k 0.51∗∗∗ 0.58∗∗∗ 0.29 0.13 0.61∗∗∗ 0.65∗∗∗ [0.19, 0.84] [0.30, 0.86] [−0.14, 0.72] [−0.24, 0.50] [0.33, 0.89] [0.30, 1.01] Media Consumption 0.06 0.11∗∗∗ 0.22∗∗∗ 0.10∗∗ 0.15∗∗∗ 0.24∗∗∗ [−0.04, 0.16] [0.03, 0.19] [0.06, 0.37] [0.02, 0.19] [0.08, 0.22] [0.13, 0.35] Save as Child 0.16∗ 0.33∗∗∗ 0.06 0.30∗∗∗ 0.23∗∗ 0.18 [−0.02, 0.35] [0.17, 0.48] [−0.17, 0.29] [0.11, 0.49] [0.03, 0.42] [−0.07, 0.43] statecode==Arkhangai −0.04 0.11 0.22 0.85∗∗∗ 0.68∗∗∗ 0.12 [−0.47, 0.39] [−0.27, 0.49] [−0.72, 1.16] [0.55, 1.15] [0.29, 1.07] [−0.34, 0.59] Bayan-Ulgii −1.28∗∗∗ 0.12 −0.50 0.90∗∗∗ −0.29 0.01 [−1.79, −0.77] [−0.30, 0.55] [−1.23, 0.24] [0.54, 1.26] [−0.98, 0.40] [−0.62, 0.65] Bulgan −0.10 0.07 −0.51 −0.93∗∗ −0.48 [−0.68, 0.47] [−0.43, 0.58] [−1.46, 0.43] [−1.65, −0.21] [−1.19, 0.23] Darkhan-Uul −0.07 −0.17 −0.17 −0.25 −0.48∗ −0.92∗∗∗ [−0.58, 0.44] [−0.60, 0.26] [−0.86, 0.52] [−1.12, 0.62] [−0.98, 0.03] [−1.59, −0.24] Dornogovi −0.08 0.24 0.26 0.82∗∗∗ 0.96∗∗∗ 0.19 [−0.91, 0.75] [−0.09, 0.56] [−1.28, 1.80] [0.23, 1.40] [0.26, 1.66] [−0.53, 0.90] Govisumber −0.40 −0.58∗∗∗ −0.07 −0.83∗∗∗ [−1.09, 0.29] [−0.96, −0.19] [−0.54, 0.39] [−1.13, −0.53] Khovd −0.97∗∗∗ 0.43 0.17 −1.29∗∗∗ [−1.50, −0.44] [−0.19, 1.04] [−0.46, 0.80] [−1.81, −0.77] Khovsgol 0.25 −0.01 0.34 0.18 0.61∗∗∗ 0.31 [−0.32, 0.81] [−0.41, 0.39] [−0.12, 0.81] [−0.20, 0.57] [0.24, 0.99] [−0.08, 0.70] Omnogovi 0.20 0.06 −0.19 0.61∗ 0.54∗∗∗ 0.38∗ [−0.46, 0.85] [−0.32, 0.45] [−0.74, 0.36] [−0.00, 1.22] [0.32, 0.75] [−0.03, 0.80] Orkhon 0.40 0.22 −0.56 0.05 0.22 [−0.16, 0.95] [−0.27, 0.71] [−1.53, 0.42] [−0.39, 0.49] [−0.26, 0.71] Ovorkhangai −0.29∗ 0.26 −0.12 −0.04 −0.48∗∗ −0.62∗∗ [−0.64, 0.05] [−0.10, 0.62] [−0.81, 0.56] [−0.58, 0.49] [−0.93, −0.04] [−1.20, −0.05] Selenge 0.01 −0.01 −0.02 −0.22 0.57∗∗∗ 0.28 [−1.21, 1.23] [−0.32, 0.30] [−0.89, 0.85] [−0.70, 0.26] [0.18, 0.95] [−0.28, 0.84] Sukhbaatar 0.05 0.18 0.32 0.95∗∗∗ 0.71∗ 0.37 [−0.43, 0.53] [−0.20, 0.55] [−0.68, 1.32] [0.66, 1.23] [−0.01, 1.44] [−0.10, 0.84] Tov 0.09 −0.00 −0.10 −0.71 −0.15 [−0.49, 0.66] [−0.43, 0.43] [−0.55, 0.36] [−1.77, 0.35] [−0.96, 0.66] Uvs −0.84∗∗∗ 0.10 −0.49 1.00∗∗∗ −0.93∗∗∗ −0.58∗ [−1.25, −0.42] [−0.32, 0.51] [−1.23, 0.24] [0.64, 1.36] [−1.50, −0.36] [−1.26, 0.11] Observations 2493 2493 2111 2394 2361 2181 Significance: ∗ (p < 0.10), ∗∗ (p < 0.05), ∗∗∗ (p < 0.01); 95% Confidence Intervals in brackets. Reference Categories: female, cannot read or write Tajik, neither married nor living with partner, maximum primary education, not head of household, out of labor force, region Ulaanbaatar, income lower MNT 210k, not saved as a child - 79 - D. Distribution Channels 95 − 100 95 − 100 70 − 95 70 − 95 50 − 70 50 − 70 40 − 50 40 − 50 30 − 40 30 − 40 20 − 30 20 − 30 10 − 20 10 − 20 0 − 10 0 − 10 No data No data Figure 95: Percentage of respondents watching regularly TV in regions. Figure 96: Percentage of respondents listening regularly radio in regions. 95 − 100 95 − 100 70 − 95 70 − 95 50 − 70 50 − 70 - 80 - 40 − 50 40 − 50 30 − 40 30 − 40 20 − 30 20 − 30 10 − 20 10 − 20 0 − 10 0 − 10 No data No data Figure 97: Percentage of respondents reading regularly local or national newspapers in regions. Figure 98: Percentage of respondents using regularly the internet in regions. 95 − 100 95 − 100 70 − 95 70 − 95 50 − 70 50 − 70 40 − 50 40 − 50 30 − 40 30 − 40 20 − 30 20 − 30 10 − 20 10 − 20 0 − 10 0 − 10 No data No data Figure 99: Percentage of respondents reading regularly national newspapers in regions. Figure 100: Percentage of respondents reading regularly local newspapers in regions. (4,5] (3,4] (2,3] (1,2] [0,1] No data Figure 101: Average number of different media consumed regularly in regions. TV Radio Nat. Newspaper Loc. Newpaper Internet 100 80 Percentage 60 40 20 92 57 31 39 20 96 47 27 39 24 98 47 34 56 35 98 42 36 72 56 0 <210, n=635 210−385, n=806 385−645, n=586 >645K, n=471 Figure 102: Percentage of respondents who regularly use different forms of media, by approximate household income (in 1,000 MNT). TV Radio Nat. Newspaper Loc. Newpaper Internet 100 80 Percentage 60 40 20 98 43 39 60 49 97 53 31 53 49 97 44 33 50 34 95 49 28 53 23 0 Formal, n=591 Informal, n=380 Self/Herdsm., n=684 Not Work, n=845 Figure 103: Percentage of respondents who regularly use different forms of media, by employment status. - 81 - TV Radio Nat. Newspaper TV Radio Nat. Newspaper Loc. Newpaper Internet Loc. Newpaper Internet 100 100 80 80 Percentage Percentage 60 60 40 40 20 20 97 41 26 40 61 98 49 35 57 30 94 51 35 65 15 96 47 31 46 26 97 47 33 62 46 0 0 Age<35, n=731 3555, n=527 Primary and Secondary, n=1473 Tertiary, n=1024 Figure 104: Percentage of respondents who regularly use different forms of media, by Figure 105: Percentage of respondents who regularly use different forms of media, by respondents’ age. education. - 82 - TV Radio Nat. Newspaper TV Radio Nat. Newspaper TV Radio Nat. Newspaper Loc. Newpaper Internet Loc. Newpaper Internet Loc. Newpaper Internet 100 100 100 80 80 80 Percentage Percentage Percentage 60 60 60 40 40 40 20 20 20 95 51 34 39 28 98 44 31 65 41 97 46 32 54 36 83 76 47 39 3 94 50 21 44 21 97 47 34 55 38 0 0 0 Rural, n=1500 Urban, n=1000 Other, n=2407 Herdsman, n=93 Low: 0−4, n=337 High: 5−7, n=2163 Figure 106: Percentage of respondents who regularly use Figure 107: Percentage of respondents who regularly use Figure 108: Percentage of respondents who regularly use different forms of media, by urbanization. different forms of media, by being a herdsman. different forms of media, by financial literacy score. E. Spatial Overview on Financial Products 90 − 100 90 − 100 75 − 90 75 − 90 50 − 75 50 − 75 25 − 50 25 − 50 10 − 25 10 − 25 0 − 10 0 − 10 No data No data Figure 109: Percentage of respondents with access to formal credit in regions. Figure 110: Percentage of respondents with access to informal credit in regions. 90 − 100 90 − 100 - 83 - 75 − 90 75 − 90 50 − 75 50 − 75 25 − 50 25 − 50 10 − 25 10 − 25 0 − 10 0 − 10 No data No data Figure 111: Percentage of respondents with access to formal savings in regions. Figure 112: Percentage of respondents with access to informal savings in regions. 40 − 65 85 − 95 25 − 40 75 − 85 10 − 25 65 − 75 5 − 10 55 − 65 0−5 0 − 55 No data No data Figure 113: Usage of investments in regions. Figure 114: Usage of insurance policies in regions. F. Spatial Overview on Financial Institutions 91.34622 − 94.49827 33.20797 − 40.40088 87.63315 − 91.34622 28.30097 − 33.20797 83.29865 − 87.63315 26.36332 − 28.30097 53.87431 − 83.29865 14.69923 − 26.36332 No data No data Figure 115: Usage of services of commercial banks in regions (relative to entire population). Figure 116: Usage of services of insurance companies in regions (relative to entire population). - 84 - 4.201903 − 7.342885 23.34965 − 30.07047 2.449192 − 4.201903 9.227415 − 23.34965 1.332525 − 2.449192 4.943923 − 9.227415 0 − 1.332525 0 − 4.943923 No data No data Figure 117: Usage of services of brokerage houses in regions (relative to entire population). Figure 118: Usage of services of microfinance organizations in regions (relative to entire population). 9.555539 − 15.08386 46.56966 − 59.43485 6.514399 − 9.555539 25.07544 − 46.56966 3.238964 − 6.514399 7.433427 − 25.07544 0 − 3.238964 0 − 7.433427 No data No data Figure 119: Usage of services of other non-banking financial institutions in regions (relative to Figure 120: Usage of services of money exchange offices in regions (relative to entire entire population). population). 11.5291 − 15.07744 5.848656 − 11.5291 2.337418 − 5.848656 0 − 2.337418 No data Figure 121: Usage of services of the Mongolian Stock Exchange in regions (relative to entire population). - 85 -