WPS8021 Policy Research Working Paper 8021 Relief from Usury Impact of a Community-Based Microcredit Program in Rural India Vivian Hoffmann Vijayendra Rao Vaishnavi Surendra Upamanyu Datta Development Research Group Poverty and Inequality Team April 2017 Policy Research Working Paper 8021 Abstract The impact of micro-credit interventions on existing credit loans. Due to the program, the average rate paid on recent markets is theoretically ambiguous. Previous empirical work loans fell from 69 to 58 percent per year overall. Rates suggests the entry of a joint-liability lender may lead to a on informal loans also declined slightly. Among landless positive impact on the informal lending rate. This paper households, informal lending rates fell from 65.5 to 63.2 presents the first randomized controlled trial–based evi- percent, decreasing by 40 percent the gap in rates paid by dence on this question. Households in rural Bihar, India, landless versus landowning households. Two years after the were offered low-cost credit through a government-led initiation of the program, significant positive impacts on self-help group program, the rollout of which was ran- asset ownership among landless households were apparent. domized at the panchayat level. The intervention led to a Impacts on various indicators of women’s empowerment dramatic 14.5 percent decline in the use of informal credit, were mixed, and showed no clear direction when aggregated, as households substituted to lower-cost self-help group nor was there any impact on consumption expenditures. This paper is a product of the Poverty and Inequality Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at vrao@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Relief from Usury: Impact of a Community-Based Microcredit Program in Rural India Vivian Hoffmann, IFPRI Vijayendra Rao, World Bank Vaishnavi Surendra, UC Berkeley Upamanyu Datta, World Bank Keywords: Micro-Credit, Self-Help Groups, Rural credit markets, India JEL Codes: G21, I38, O12 We are grateful for support from 3ie, the World Bank’s Research Support budget, and by the contributions of (1) UK Aid from the UK government, (2) the Australian Departments of Foreign Affairs and Trade, (3) the European Commission (EC) through the South Asia Food and Nutrition Security Initiative (SAFANSI), which is administered by the World Bank, and (4) the International Initiative for Impact Evaluation (3ie). We thank Arvind Kumar Chaudhuri, Ajit Ranjan, Shobha Shetty and Vinay Vutukuru for their advice and support. The views expressed here do not necessarily reflect the UK, EC or Australian government's official policies or the policies of the World Bank and its Board of Executive Directors. 1. Introduction The vast majority of credit utilized by the global poor is from informal sources such as moneylenders, friends, or merchants (Banerjee and Duflo, 2007). Interest rates on these informal loans are typically high, particularly for the poorest, who borrow lower amounts and have little collateral to offer. A host of institutions, ranging from large commercial enterprises to small non- governmental organizations, have entered rural credit markets in recent years with the aim of providing lower-cost credit to the poor. While the impact of this so-called microfinance revolution on household-level outcomes has now been well documented through a number of experimental and non-experimental studies, its effect on informal credit markets, which continue to supply the lion’s share of credit in these settings, has received far less attention. We address this gap through an RCT based on the randomized roll-out of Jeevika, a government-led self-help group (SHG) program in the state of Bihar, India, which offered loans to SHG members. According to government sources, 33.2% of all loans in rural India are from traditional moneylenders (GoI, 2014). Reliance on informal credit is even more pronounced in the state of Bihar, where 47.7% of outstanding debt held by farm households is from informal sources (RBI, 2007). Traditional moneylenders charge between 12 and 150 percent annual interest, compared to typical rates of 6 to 20 percent offered by formal banks on larger loans (RBI, 2011). In this context, the public, for-profit, and non-governmental sectors have all invested heavily in rural credit markets since the early 2000s (RBI, 2007; Galab and Rao, 2003, Brishti and Chowdhury, 2013). The impact of these efforts depends, to a large extent, on how the entry of a new creditor affects interest rates charged by incumbent informal lenders. As noted by Besley (1994), rural credit markets are likely to be characterized by multiple constraints and potential market failures, making the impact of external intervention unclear. One of the motivations for public investment in micro- lending was an anticipated negative impact on informal sector rates through competitive pressure (Hoff and Stiglitz, 1990). The fact that high informal lending rates have continued to exist alongside far lower-cost institutional credit has generated an extensive theoretical literature exploring the interaction between formal and informal credit markets. Informal lenders are often modeled as engaging in monopolistic competition (Hoff and Stiglitz, 1998). This allows room for competition to bring down lending rates, but due largely to the information asymmetries that characterize credit markets, the opposite result may also obtain. An increase in lending rates could potentially arise through a number of channels. First, as noted by Hoff and Stiglitz (1998) and echoed by Jain (1999), scale economies in lending could be eroded by competition. A second possibility is that access to an outside lending option leads to moral hazard among borrowers, increasing default risk and thus lending rates (Hoff and Stiglitz, 1998; Kahn and Mookherjee, 2998; McIntosh and Wyndick, 2005). A third channel is through composition of the pool of borrowers. If the new entrant is particularly good at identifying borrowers with a low likelihood of default, one of the commonly assumed advantages of the joint liability lending model used by SHGs and many other microfinance institutions (MFIs) (Ghatak, 1999), its entry could segment the market, driving up the average default risk of borrowers it does not serve and thus rates in the rest of the market (Bose, 1998; Demont, 2016).1 Even if, as suggested by the empirical findings of Maitra et al. (2014), borrowers facing higher informal rates are more likely to take up a joint liability lending contract, Mookherjee and Motta (2016) show how selection according to other observable borrower characteristics could lead to even higher informal interest rates. The mechanisms described above all require that informal and formal credit are substitutes. It is also possible that due to differences in the terms of loans offered by traditional informal lenders and new entrants, credit from these two sources could in fact be complements. Jain and Mansuri (2003) develop a model in which the rigid repayment schedules imposed by MFIs lead households to use loans from informal lenders to service these debts, potentially increases demand for informal credit, and puts upward pressure on informal interest rates. On the other hand, if the loans offered through the new entrant into the credit market provide borrowers facing repayment difficulties with a way to service their informal debt, this could bring down the costs of debt collection (Aleem 1990), potentially reducing lending rates. While the potential impacts have been extensively described in the theoretical literature, empirical evidence on the impact of new lender entry on informal credit markets is comparatively thin. Three previous studies have used the approach of instrumenting for MFI entry, either using 1 While some prospective borrowers are actively screened out by MFIs and SHGs, capacity constraints may also limit the number who can be covered through such programs. This implies that while average default risk among the pool of borrowers from the informal market increases, there remain many low-risk borrowers within this pool. administrative targeting variables (Kaboski and Townsend, 2012) or the error structure of a predictive model of entry (Mallick, 2012; Berg, Emran and Shilpi, 2015). Two of these studies, both based on data from Bangladesh, find a positive impact of MFI entry on informal lending rates (Mallick; Berg, Emran and Shilpi), though in the latter the effect is only significant when MFI coverage rates are high. Kaboski and Townsend, using data from Thailand, find no statistically significant impact on lending rates, but a small positive effect on the probability of default on other loans. A fourth study uses panel data from the Indian state of Jharkhand, and finds an inverse U- shaped relationship between SHG coverage and the rates charged by moneylenders, consistent with a model in which the SHG lender has superior information on borrowers’ creditworthiness and serves those with lower risk of default (Demont, 2016). The identification of causal impacts in these studies relies on the assumption that community characteristics associated with the entry of new lenders do not affect informal credit rates directly. Given the multiple objectives of MFIs, which may include profit (or at least cost-recovery) as well as a social mission to assist the poor, it is impossible to sign the direction of potential bias in estimates from observational studies. The use of random assignment to a credit market intervention permits causal inference based on a much weaker set of assumptions. However, previous randomized evaluations of microcredit programs have not reported impacts on interest rates, presumably due to a lack of power on this outcome. The present study, which is based on the randomized roll-out of a government-led SHG program that offered microcredit and credit linkages to formal banks to the poor across 179 panchayats2 in rural Bihar, overcomes this limitation. Critical to the identification strategy, the SHG intervention had a strong direct effect on household use of informal credit. Just over two years after program initiation, households in panchayats selected for early roll-out were 51 percentage points more likely to include a member who belonged to an SHG than those in control areas. While borrowing from all sources increased overall during the study period, new borrowing from informal lenders was 18% lower in program panchayats compared to control areas, where households instead took advantage of the lower- interest loans offered by SHGs. We find that this exogenous shock to informal credit markets 2 Village government units typically consisting of between two and four villages. brought on by randomized SHG entry led to a fall of 3.8 percentage points in the average annual informal borrowing rate on a base of 68.8 percent. Program impacts are generally more pronounced for landless households than for those that own land. Members of landless households were more likely to join an SHG and to take on more debt through the program, and the decline in lending rates is driven by a reduction in the rates faced by these households. In addition to its unique contribution to understanding how the entry of a new lending institution can affect informal credit markets, this study also contributes to the substantial recent literature estimating household-level impacts of access to group-based lending (Desai and Joshi, 2014; Angelucci et al, 2015; Attanasio et al., 2015; Banerjee et al., 2015; Crépon et al., 2015; Datta, 2015; Khanna, Kocchar and Palaniswamy, 2015). In general, this literature shows that even when an expansion in access to credit results in households taking on more overall debt, impacts can be quite limited in the short to medium run (Banerjee, Karlan and Zinman, 2015). While it is common to see shifts in livelihood activities, typically away from wage labor and toward self-employment, total household income is not generally affected. Similarly, impacts on overall consumption are rare, while reallocation away from “discretionary” spending (temptation goods, entertainment, and celebrations) is more commonly observed. Finally, there is scant evidence from RCTs that these programs affect indicators of female empowerment.3 Given previous findings, it is not surprising that, in the short-run, Jeevika, which did not have a significant impact on total borrowing, also did not lead to significant impacts on consumption levels or on women’s economic or decision-making roles or capabilities. In the high-indebtedness environment of rural Bihar, the primary impacts of the program were to shift a portion of households’ debt burden from high-cost loans on which monthly rates averaged over 5 percent per month, to much lower-cost SHG loans and to reduce the cost of borrowing from the informal sector. The estimated impact of Jeevika on households’ debt servicing costs is economically significant, but a longer time horizon may be required before this translates into measurable changes in the consumption or asset positions of households, or in the empowerment of women 3 Non-experimental evidence based on regression discontinuity designs or propensity score matching have also not shown any impact on income or consumption, but have shown substantial effects on women’s empowerment (Khanna, Kocchar and Palaniswamy, 2015; Datta, 2015; Desai and Joshi 2014). (Sanyal, Rao and Majumdar, 2015). 2. Setting and intervention At the time the program was initiated, Bihar was home to 32 million people living below the poverty line, and 66% of the rural population was landless (GoI, 2011). Rural Bihar had extremely low rates of participation in microcredit through Microfinance Institutions (MFIs) or Self Help Groups (SHGs) (World Bank, 2007). This prompted the Government of Bihar, with funding from the World Bank, to implement the Bihar Rural Livelihoods Project, also known as Jeevika, the Hindi word for livelihood. The primary aim of Jeevika is to provide disadvantaged groups, in particular the landless and members of Scheduled Castes, access to (relatively) low-cost credit. When Jeevika enters a new village, Community Mobilizers employed through the program target households living in particularly poor areas, and encourage the women in these households to form self-help groups (SHGs) of 10 to 15 members. These groups then meet weekly, initially with a Community Mobilizer, who leads members through a curriculum on women’s empowerment and provides basic literacy and numeracy training.4 Members are required to contribute a minimum of 2 rupees ($0.035 USD)5 each week toward a personal savings account held by the SHG. After several weeks of demonstrating consistent savings, an SHG is eligible to join the local Village Organization (VO), through which its members may access up to Rs. 50,000 (875 USD) in lending capital. SHGs can borrow these funds from the VO at a non-compounding interest rate of 1% per month, and SHG members may borrow at 2% per month. The mean credit available per SHG member is approximately Rs. 4,000, assuming the average group size is halfway between the allowable minimum and maximum number of members. VOs are further federated into Cluster Level Federations (above the panchayat level), which then establish linkages to the formal banking sector. Over the longer term, Jeevika is also meant to deliver other development interventions and livelihoods training to SHG members, however these activities were not implemented in the study area during the period spanned by data collection. 3. Methods 4 SHG members are taught to sign their names, and how to read basic sign posts, such as bus names, etc. 5 USD equivalents are calculated using the average exchange rate from initiation of the program to the end of data collection. 3.1 Experimental design In order to evaluate the impacts of Jeevika, the rollout of the project was randomized across 180 panchayats, randomly selected from within 16 blocks in seven districts where Jeevika was planning to scale up. In each of the study panchayats, one or two villages were then randomly selected for data collection. Since the intervention was targeted to poorer households, within each of the study villages, hamlets in which the majority of the population belonged to a scheduled caste or scheduled tribe were identified. Households were then randomly selected from these hamlets to be interviewed. A baseline survey was administered during July to October of 2011 to 8,988 households across 333 villages in 179 panchayats.6 Following the baseline survey, panchayats were randomly assigned to an early rollout group or a late rollout group, after stratifying the sample on administrative block and the panchayat-level mean of outstanding high cost (monthly interest rate of 4% or higher) debt held by households at baseline. The project began in the early rollout panchayats between January and April 2012, and the follow-up survey was completed between July and September 2014. Implementation in late rollout areas began after the 2014 round of data collection. Baseline and follow-up surveys included detailed questions on debt, asset holdings, consumption expenditures, livelihood activities, and women’s mobility, role in household decisions, and aspirations. In addition, in each village, a focus group discussion was conducted, through which data were collected on village-level attributes such as local sources of credit, interest rates from each source, local wage rates, and the presence of or distance to markets and other institutions and amenities. 3.2 Analysis The SHG intervention is expected to lead to a series of potential impacts, which we classify as direct, indirect and downstream. One or more direct impacts (increased SHG membership; increased utilization of credit though SHGs) is a necessary but insufficient condition for the intervention to lead to indirect effects on informal credit markets. Changes in downstream outcomes (wealth, consumption level, women’s empowerment) may follow from either direct or indirect impacts. 6 One of the selected Panchayats could not be surveyed due to political instability. Based on the registered pre-analysis plan,7 we estimate the following ANCOVA specification to test the reduced-form, intent-to-treat impact of Jeevika on each group of outcomes: !"#$%&'( = +& + +' -../012$ + +% !"#$%&'' + +3 4"#$ + +( 5$ + 6"#$ (1) where !"#$7 is the outcome of interest for household 8 in village 9 in panchayat : in year ;, -../012$ is random assignment of the panchayat to early (2012) rollout of the intervention, 4"#$ is a vector of pre-specified baseline controls used in the primary specification, 5$ represents the vector of stratification dummies, and 6"#$ is a random individual-level error (notation constant across specifications for simplicity). In addition, to test for heterogeneous treatment effects on households that were landless at baseline, we estimate specification (2):8 !"#$%&'( = <& + <' -../012$ + <% =="#$ + <3 =="#$ ∗ -../012$ + <( !"#$%&'' (2) + 48% p.a., 000 Rs) 8988 7.68 7.54 0.14 (0.33) Average Interest Rate 6462 5.46 4.95 0.50*** (0.05) Interest Free Loans (No. per HH) 8988 0.11 0.27 -0.16*** (0.02) Material Well-Being: Assets and Consumption Expenditures Productive Asset Index (Filmer-Pritchett) 8988 -0.21 1.00 -1.21*** (0.08) Consumption Asset Index (Filmer-Pritchett) 8988 -0.60 0.65 -1.25*** (0.04) Housing Index (Filmer-Pritchett) 8988 -0.22 0.13 -0.34*** (0.04) Real Total Monthly Consumption PA (Rs 000) 8988 0.67 0.74 -0.08*** (0.01) Note : Standard errors of differences in means are clustered at the panchayat level to account for sampling design. Table 2. Direct Effects of Jeevika New Loans Taken, past year SHG Any Loans Outstanding Debt (000 Rs.) Interest Rates (000 Rs.) Family Membership Taken in the Index of (%) last year? SHG High Cost Monthly rate All Loans Total SHG Dependent Loans (≥ 4% / month) on new loans Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) Panel A: Main effects Jeevika 51.04*** 0.04*** -0.86* 1.97*** -1.88*** -0.95*** -0.20 1.91*** 0.80*** (1.54) (0.01) (0.44) (0.09) (0.38) (0.07) (0.32) (0.10) (0.03)‡‡‡ Additional baseline controls? yes yes yes yes yes yes yes yes yes Number of observations 8851 8987 8987 8987 8987 6805 8987 8987 8988 Number of clusters 179 179 179 179 179 179 179 179 179 R-squared 0.36 0.09 0.08 0.13 0.06 0.20 0.04 0.10 0.24 Mean of dep var, omitted cat 10.37 0.74 17.94 0.13 12.97 5.75 11.50 0.14 0.00 Hochberg-corrected p-value 0.00 Panel B: Heterogeneous effects by landholdings Jeevika 42.97*** 0.06*** -2.28* 1.69*** -1.46 -0.65*** -1.65** 1.67*** 0.69*** (2.25) (0.02) (1.36) (0.15) (0.89) (0.12) (0.81) (0.16) (0.04)‡‡‡ Landless HH -1.55 0.07*** -4.64*** -0.01 -0.51 0.56*** -1.62** 0.01 -0.01 (1.25) (0.02) (1.18) (0.06) (0.88) (0.09) (0.77) (0.07) (0.02) Jeevika X landless 11.27*** -0.02 2.05 0.39** -0.59 -0.41*** 2.06** 0.33* 0.16*** (2.19) (0.02) (1.59) (0.16) (1.07) (0.14) (0.98) (0.18) (0.04) Linear combinations Effect of Jeevika if landless 54.25*** 0.04*** -0.22 2.07*** -2.04*** -1.06*** 0.41 2.00*** 0.85*** (1.61) (0.01) (0.50) (0.10) (0.46) (0.08) (0.40) (0.11) (0.03)‡‡‡ Effect of landless if Jeevika 9.72*** 0.05*** -2.58** 0.38** -1.10 0.15 0.44 0.34** 0.15*** (1.85) (0.01) (1.16) (0.16) (0.71) (0.10) (0.70) (0.16) (0.04) Additional baseline controls? yes yes yes yes yes yes yes yes yes Number of observations 8851 8987 8987 8987 8987 6805 8987 8987 8988 Number of clusters 179 179 179 179 179 179 179 179 179 R-squared 0.36 0.09 0.09 0.13 0.06 0.21 0.04 0.10 0.24 Mean of dep var, omitted cat 8.97 0.64 24.51 0.11 13.62 5.12 13.52 0.09 -0.03 Hochberg-corrected p-values Treatment if landless 0.000 Treatment if landed 0.000 Notes: Standard errors clustered at the panchayat level shown in parentheses. Coefficients are from an ANCOVA specification - linear regressions of each outcome on its value at baseline, and an indicator of treatment status; panel B has linear regressions of each outcome on indicators of treatment status, landessness, and their interaction. Stratification dummies and baseline controls († in Table A1) are included in all specifications. Landless status is landlessness at the time of the baseline survey. Columns 9 presents coefficients in a regression of z-scores of the outcome variables in this "family" - SHG membership, any loans taken, all outstanding debt, outstanding SHG debt, outstanding High-cost debt, interest rates, total amount borrowed last year, SHG amount borrowed last year - following Kling, Liebman, and Katz (2007). p-values for these regressions are reported using Hochberg's step-down method to control the FWER across all index outcomes. * p<0.1, ** p<0.05; *** p<0.01 Table 3. Effects of Jeevika on the informal credit market (Indirect) Household Survey Data Village FGD Data Outstanding New Informal Index of Any Informal Informal Informal Money- Friends / Informal Debt Loans Taken Dependent Informal Loans Taken? Interest rate Interest rate lenders Relatives (000 Rs.) (000 Rs.) Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) Panel A: Main Effects Panel A: Mean monthly lending rate Jeevika -0.06*** -2.65*** -2.04*** -0.12* -0.16** 0.09*** -0.32* -0.32 -0.16 (0.01) (0.39) (0.30) (0.07) (0.07) (0.01)‡‡‡ (0.18) (0.23) (0.24) New borrower -0.10 (0.07) Jeevika X new borrower 0.16 (0.11) Linear combinations Effect of Jeevika if new borrower 0.00 (0.12) Additional baseline controls? yes yes yes yes yes yes yes yes yes Number of observations 8987 8987 8987 6211 6211 8988 322 292 218 Number of clusters 179 179 179 179 179 179 179 176 147 R-squared 0.09 0.07 0.05 0.22 0.22 0.06 0.42 0.41 0.55 Mean of dep var, omitted cat 0.72 16.24 11.14 5.75 5.76 -0.00 5.73 6.00 5.36 Hochberg-corrected p-value 0.00 Panel B: Heterogeneous effects by landholdings Panel B: Number of informal lenders Jeevika -0.04** -3.41*** -3.14*** 0.05 0.07** -0.27** -0.08 -0.16** (0.02) (1.09) (0.77) (0.10) (0.03)‡‡‡ (0.12) (0.07) (0.07) Landless HH 0.08*** -3.04*** -1.69** 0.48*** -0.02 (0.02) (1.05) (0.75) (0.09) (0.03) Jeevika X landless -0.03 1.12 1.56* -0.23* 0.03 (0.02) (1.32) (0.94) (0.13) (0.04) Linear combinations Effect of Jeevika if landless -0.07*** -2.30*** -1.58*** -0.19** 0.10*** (0.01) (0.49) (0.38) (0.08) (0.02)‡‡‡ Effect of landless if Jeevika 0.05*** -1.92* -0.13 0.25** 0.00 (0.02) (1.02) (0.64) (0.09) (0.03) Additional baseline controls? yes yes yes yes yes yes yes yes Number of observations 8987 8987 8987 6211 8988 333 333 333 Number of clusters 179 179 179 179 179 179 179 179 R-squared 0.09 0.07 0.05 0.22 0.06 0.32 0.25 0.42 Mean of dep var, omitted cat 0.63 20.23 13.12 5.12 0.01 2.85 1.37 1.41 Hochberg-corrected p-values Treatment if landless 0.000 Treatment if landed 0.000 Notes: Standard errors clustered at the panchayat level shown in parentheses. Coefficients are from an ANCOVA specification - linear regressions of each outcome on its value at baseline, and an indicator of treatment status; panel B has linear regressions of each outcome on indicators of treatment status, landessness, and their interaction. Stratification dummies and baseline controls († in Table A1) are included in all specifications. Landless status is landlessness at the time of the baseline survey. Village level regressions are from a separate village focus group discussion dataset. Column 6 presents coefficients in a regression of z-scores of the outcome variables in this "family" - any loans taken, outstanding debt, new loans, interest rates - following Kling, Liebman, and Katz (2007). p-values for these regressions are reported using Hochberg's step-down method to control the FWER across all index outcomes. * p<0.1, ** p<0.05; *** p<0.01 ‡ p-adjusted < 0.1, ‡‡ p-adjusted < 0.05, ‡‡‡ p-adjusted < 0.01 Table 4. Effects of Jeevika on Household Assset position, Entitlements, and Welfare Real Access to Index of Consumption Productive Asset Housing quality Consumption entitlements Dependent Asset Index Index Index per AE (% any) Variables (000 Rs) (1) (2) (3) (4) (5) (6) Panel A: Main Effects Jeevika 0.10** -0.01 0.01 -0.18 0.00 0.02 (0.04) (0.02) (0.03) (0.43) (0.02) (0.01) Additional baseline controls? yes yes yes yes yes yes Number of observations 8987 8987 8987 8987 8987 8988 Number of clusters 179 179 179 179 179 179 R-squared 0.36 0.23 0.33 0.09 0.06 0.34 Mean of dep var, omitted cat 0.18 -0.11 0.11 94.42 0.95 0.00 Hochberg corrected p-value 0.47 Panel B: Heterogeneous effects by landholdings Jeevika -0.07 -0.13 -0.09* -0.44 -0.01 -0.06* (0.07) (0.08) (0.06) (1.02) (0.04) (0.03) Landless HH -0.31*** -0.33*** -0.21*** 1.28 -0.07* -0.17*** (0.06) (0.06) (0.05) (0.90) (0.04) (0.03) Jeevika X landless 0.25*** 0.17* 0.15** 0.35 0.03 0.11*** (0.08) (0.09) (0.06) (1.24) (0.05) (0.04) Linear combinations Effect of Jeevika if landless 0.18*** 0.04* 0.06* -0.09 0.01 0.05*** (0.05) (0.02) (0.03) (0.52) (0.02) (0.01)‡‡‡ Effect of landless if Jeevika -0.07 -0.16*** -0.06 1.63* -0.04 -0.06*** (0.05) (0.05) (0.04) (0.90) (0.04) (0.02) Additional baseline controls? yes yes yes yes yes yes Number of observations 8987 8987 8987 8987 8987 8988 Number of clusters 179 179 179 179 179 179 R-squared 0.37 0.24 0.33 0.09 0.06 0.35 Mean of dep var, omitted cat 0.95 0.45 0.48 91.26 1.09 0.34 Hochberg-corrected p-values Treatment if landless 0.000 Treatment if landed 0.172 Notes: Standard errors clustered at the panchayat level are shown in parentheses. Coefficients are from an ANCOVA specification - linear regressions of each outcome on its value at baseline, and an indicator of treatment status (plus an indicator of landessness at baseline and its interaction with treatment status in Panel B). Stratification dummies and baseline controls († in Table A1) are included in all specifications. Columns 6 presents coefficients in a regression of z-scores of the outcome variables in this "family" - consumption assets, productive assets, housing quality, access to entitlements, real consumption per adult equivalent - following Kling, Liebman, and Katz (2007). p-values for these regressions are reported using Hochberg's step-down method to control the FWER across all index outcomes. * p<0.1, ** p<0.05; *** p<0.01 ‡ p-adjusted < 0.1, ‡‡ p-adjusted < 0.05, ‡‡‡ p-adjusted < 0.01 Table 5. Effects of Jeevika on Women's Economic Roles, Empowerment, and Aspirations Women's Proportion HH Women's Index of decision- Women's Aspirations for women work for collective Dependent making in HH Mobility girls income (%) action index Variables index (1) (2) (3) (4) (5) (6) Panel A: Main Effects Jeevika -0.52 -0.08* 1.96* -0.01 0.28 -0.00 (0.83) (0.05) (1.05) (0.02) (1.41) (0.01) Additional baseline controls? yes yes yes yes yes yes Number of observations 8830 8841 8841 8029 3910 8988 Number of clusters 179 179 179 179 179 179 R-squared 0.17 0.07 0.05 0.06 0.16 0.08 Mean of dep var, omitted cat 72.58 6.27 87.44 5.79 29.08 -0.00 Hochberg corrected p-value 0.82 Panel B: Heterogeneous effects by landholdings Jeevika 1.10 -0.11 2.09 -0.00 2.94 0.01 (1.93) (0.06) (1.56) (0.03) (2.98) (0.02) Landless HH 7.10*** -0.02 -0.14 0.04** -10.53*** 0.03* (1.82) (0.04) (1.12) (0.02) (2.47) (0.02) Jeevika X landless -2.40 0.04 -0.19 -0.01 -3.33 -0.02 (2.33) (0.06) (1.49) (0.03) (3.35) (0.02) Linear combinations Effect of Jeevika if landless -1.30 -0.07 1.90* -0.01 -0.39 -0.01 (1.02) (0.05) (1.10) (0.02) (1.61) (0.01) Effect of landless if Jeevika 4.70** 0.01 -0.33 0.03 -13.86*** 0.01 (1.70) (0.05) (1.18) (0.02) (2.94) (0.02) Additional baseline controls? yes yes yes yes yes yes Number of observations 8830 8841 8841 8029 3910 8988 Number of clusters 179 179 179 179 179 179 R-squared 0.18 0.07 0.05 0.06 0.17 0.08 Mean of dep var, omitted cat 61.26 6.29 87.77 5.14 45.87 -0.04 Hochberg-corrected p-values Treatment if landless 0.57 Treatment if landed 0.70 Notes: Standard errors clustered at the panchayat level shown in parentheses. Coefficients are from an ANCOVA specification - linear regressions of each outcome on its value at baseline, and an indicator of treatment status; panel B has linear regressions of each outcome on indicators of treatment status, landessness, and their interaction. All specifications control for block dummies and mean high cost debt at the panchayat level at baseline. Additional controls († in Table 1) are included in even-numbered columns. Landless status is landlessness at the time of the baseline survey. Column 6 presents coefficients in a regression of z-scores of the outcome variables in this "family" - working women, decision making, collective action, mobility, aspirations - following Kling, Liebman, and Katz (2007). p-values for these regressions are reported using Hochberg's step-down method to control the FWER across all index outcomes. * p<0.1, ** p<0.05; *** p<0.01 ‡ p-adjusted < 0.1, ‡‡ p-adjusted < 0.05, ‡‡‡ p-adjusted < 0.01 Table A1. Summary Statistics and Randomization Balance across Treatment Groups at Baseline Means Difference in means, T-C (SE), Adjusted for stratification controls Full sample Landless Landed Obs Overall Control Treatment (1) (2) (3) Household Characteristics Caste Group 8988 71.91 71.77 % 72.05 % 0.30 -0.28 -0.93 (1.38) (1.40) (2.80) Land Ownership 8988 28.73 29.63 % 27.82 % -1.94* NA NA (1.12) Household Size 8988 5.95 5.96 5.93 -0.04 -0.00 -0.10 (0.05) (0.06) (0.10) Female HH Head 8988 16.31 16.56 % 16.06 % -0.34 -0.48 -0.57 (0.90) (1.18) (1.31) Self Help Groups, Savings and Debt SHG membership (†) 8988 6.19 5.14 % 7.25 % 2.48*** 2.92*** 1.34 (0.81) (0.99) (1.07) Any Savings? (†) 8988 37.07 35.63 % 38.53 % 3.28* 3.42 3.60 (1.93) (2.16) (2.48) High cost debt (000 Rs) (Real) (†) 8988 7.64 7.67 7.61 -0.03 0.19 -0.59 (0.08) (0.19) (0.44) Total Debt (000 Rs.) (Real) 8988 10.09 10.24 9.93 -0.31 0.01 -0.83 (0.20) (0.28) (0.76) Outstanding Informal Debt (000 Rs.) (Real) 8988 9.05 9.07 9.02 -0.02 0.00 0.05 (0.16) (0.25) (0.56) Outstanding SHG Debt (000 Rs.) (Real) 8988 0.07 0.05 0.10 0.06*** 0.03 0.13*** (0.02) (0.02) (0.05) Credit Markets: Interest Rates and Number of Informal Lenders per Village Mean monthly interest rate paid (†) 6462 5.33 5.27 5.39 0.13** 0.15** 0.04 (0.05) (0.06) (0.08) Mean monthly rate, informal loans 6391 5.34 5.28 5.41 0.13** 0.15** 0.03 (0.05) (0.06) (0.08) Mean rate, informal loans (Village FGD data) 311 5.25 5.22 5.28 0.02 NA NA (0.15) Number of informal lenders (FGD) 180 2.04 2.08 1.99 -0.03 NA NA (0.09) Mean rate, moneylender loans (FGD) 311 5.25 5.22 5.28 0.09 NA NA (0.18) Number of moneylenders (FGD) 180 2.04 2.08 1.99 -0.06 NA NA (0.05) Mean rate, friend/relative loans (FGD) 311 5.25 5.22 5.28 0.07 NA NA (0.24) Number of friends/relatives offering loans (FGD) 180 2.04 2.08 1.99 0.02 NA NA (0.07) Notes: Adjusted differences in means across treatment groups and their standard errors (clustered at the panchayat level) are from separate linear regressions of each baseline variable on an indicator of treatment status, with controls for stratification variables (block dummies and panchayat mean high cost debt). The result for outstanding high cost debt is from a regression with the same specification as described previously, excluding the control for baseline panchayat high cost debt in order to avoid over-fitting. Outcomes marked with † are primary outcomes of interest according to the pre-analysis plan, and are used as controls in later regressions as specified in the plan. * p<0.1, ** p<0.05; *** p<0.01 Table A1. Summary Statistics and Randomization Balance across Treatment Groups at Baseline (continued) Difference in means, T-C (SE), Means Adjusted for stratification controls Full sample Landless Landed Obs Overall Control Treatment (1) (2) (3) Productive asset index (†) 8988 0.14 0.18 0.09 -0.10*** -0.03 -0.19 (0.04) (0.04) (0.12) Consumption asset index (†) 8988 -0.24 -0.27 -0.21 0.06 0.13** -0.01 (0.05) (0.05) (0.08) Housing quality index (†) 8988 -0.12 -0.12 -0.12 0.02 0.02 0.02 (0.03) (0.04) (0.07) Consumption value per AE (†) 8988 0.69 0.68 0.69 0.01 0.01 0.00 (0.01) (0.01) (0.01) Entitlements accessed by HH (†) 8988 66.59 66.05 % 67.13 % 1.40 0.88 1.13 (1.33) (1.37) (2.28) Women's Roles and Capabilities Prop. HH women work for income (†) 8985 77.08 77.68 % 76.47 % -1.31 -1.75 -1.01 (1.12) (1.16) (2.00) Women's HH decision-making index (†) 8988 5.97 5.98 5.97 -0.00 0.06 -0.16** (0.05) (0.06) (0.08) Women's collective action index (†) 8988 81.70 81.93 % 81.46 % -0.11 0.47 -1.48 (0.97) (1.20) (1.74) Women's mobility (†) 8303 0.31 0.30 0.31 0.01 0.00 0.02 (0.01) (0.02) (0.02) Aspirations for girls (†) 5235 28.75 28.00 % 29.48 % 1.38 2.67 -1.13 (1.41) (1.63) (2.75) Attrition Attrition 8988 2.89 2.83 % 2.95 % 0.15 0.18 0.05 (0.28) (0.39) (0.57) Notes: Adjusted differences in means across treatment groups and their standard errors (clustered at the panchayat level) are from separate linear regressions of each baseline variable on an indicator of treatment status, with controls for stratification variables (block dummies and panchayat mean high cost debt). The result for outstanding high cost debt is from a regression with the same specification as described previously, excluding the control for baseline panchayat high cost debt in order to avoid over-fitting. Outcomes marked with † are primary outcomes of interest according to the pre-analysis plan, and are used as controls in later regressions as specified in the plan. * p<0.1, ** p<0.05; *** p<0.01 Table A2. Direct Effects, alternative estimators Monthly rate on Loans taken past year (000 SHG Any loans taken Outstanding debt (000 Rs) loans taken last 12 Rs) membership months (%) All loans All loans SHG loans Total SHG > 4% /mo All loans (1) (2) (3) (4) (5) (6) (7) (8) Panel A: Simple Difference Estimator, no Baseline Controls Overall Jeevika impact 51.36*** 0.04*** -0.12 1.93*** -0.88* 1.99*** -1.80*** -0.98*** (1.55) (0.01) (0.33) (0.10) (0.45) (0.09) (0.39) (0.07) Impact on landholding HHs 43.03*** 0.06*** -1.80** 1.68*** -2.71* 1.69*** -1.61* -0.69*** (2.31) (0.02) (0.83) (0.16) (1.40) (0.14) (0.91) (0.12) Impact on landless HHs 54.52*** 0.04** 0.61 2.03*** 0.09 2.10*** -1.84*** -1.08*** (1.61) (0.01) (0.40) (0.11) (0.51) (0.10) (0.46) (0.08) Panel B: Simple Difference Estimator with Baseline Controls Overall Jeevika impact 51.36*** 0.04*** -0.21 1.91*** -0.93** 1.97*** -1.88*** -1.00*** (1.55) (0.01) (0.32) (0.10) (0.43) (0.09) (0.38) (0.07) Impact on landholding HHs 42.97*** 0.06*** -1.65** 1.68*** -2.32* 1.70*** -1.46 -0.72*** (2.25) (0.02) (0.81) (0.16) (1.35) (0.15) (0.89) (0.12) Impact on landless HHs 54.25*** 0.04** 0.39 2.00*** -0.28 2.07*** -2.04*** -1.09*** (1.61) (0.01) (0.40) (0.12) (0.50) (0.10) (0.46) (0.08) Panel C: Difference in Differences Estimator Overall Jeevika impact 49.09*** 2.26 -0.04 1.88*** -0.63 1.93*** -1.79*** -1.04*** (2.54) (1.73) (0.51) (0.14) (0.69) (0.12) (0.56) (0.12) Impact on landholding HHs 40.89*** 4.61* -1.65 1.57*** -1.93 1.54*** -1.10 -0.56*** (2.96) (2.72) (1.10) (0.18) (1.62) (0.17) (1.10) (0.16) Impact on landless HHs 52.19*** 1.35 0.63 2.00*** -0.00 2.08*** -2.04*** -1.19*** (2.78) (1.91) (0.50) (0.15) (0.65) (0.14) 0.60 (0.14) Notes: All specifications control for stratification dummies. Results shown in Panel B are from specifications in which baseline controls (Table A1) are included. Table A3. Effects on Informal Credit Market, alternative estimators Monthly rate, Informal loans Outstanding Any informal informal loans taken past year informal debt loans taken taken last 12 (000 Rs) (000 Rs) months (1) (2) (3) (4) Panel A: Simple Difference Estimator, no Baseline Controls Overall Jeevika impact -0.06*** -2.00*** -2.58*** -0.11 (0.01) (0.32) (0.40) (0.07) Impact on landholding HHs -0.04* -3.27*** -3.54*** 0.07 (0.02) (0.79) (1.11) (0.11) Impact on landless HHs -0.07*** -1.43*** -2.06*** -0.19** (0.01) (0.39) (0.50) (0.09) Panel B: Simple Difference Estimator with Baseline Controls Overall Jeevika impact -0.06*** -2.06*** -2.65*** -0.12* (0.01) (0.30) (0.38) (0.07) Impact on landholding HHs -0.04** -3.12*** -3.29*** 0.05 (0.02) (0.77) (1.08) (0.10) Impact on landless HHs -0.07*** -1.61*** -2.34*** -0.19** (0.01) (0.38) (0.48) (0.08) Panel C: Difference in Differences Estimator Overall Jeevika impact -7.92*** -1.96*** -2.58*** -0.22* (1.70) (0.50) (0.63) (0.12) Impact on landholding HHs -5.00* -3.42*** -3.64*** 0.13 (2.76) (1.03) (1.30) (0.16) Impact on landless HHs -9.05*** -1.33** -2.07*** -0.34** (1.87) (0.49) (0.65) (0.14) Notes: All specifications control for stratification dummies. Results shown in Panel B are from specifications in which baseline controls (Table A1) are included. Table A4. Effects on Informal Credit Market, Village Level Outcomes Monthly Interest Rate Number of Lenders Friends and Money- Friends and Informal Money-lenders Informal Relatives lenders Relatives (1) (2) (3) (4) (5) (6) Panel A: Simple Difference Estimator, no Baseline Controls Overall Jeevika impact EL_informal_rate_s1 0 176 EL_number_informal_s1 0 179 0 0 0.36 0 0 0.21 Panel B: Simple Difference Estimator with Baseline Controls Overall Jeevika impact EL_informal_rate_s2 0 176 EL_number_informal_s2 0 179 0 0 0.41 0 0 0.25 Panel C: Difference in Differences Estimator Overall Jeevika impact -0.32 -0.37 -0.23 -0.20 0.02 -0.17 (0.26) (0.30) (0.37) (0.17) (0.10) (0.13) Notes: All specifications control for stratification dummies. Results shown in Panel B are from specifications in which baseline controls (Table A1) are included. Table A5. Effects on Household Assset position, Entitlements, and Welfare Real Access to Consumption Productive Housing Quality Consumption Entitlements (% Asset Index Asset Index Index per AE (000 any) Rs.) (1) (2) (3) (4) (5) Panel A: Simple Difference Estimator, no Baseline Controls Overall Jeevika impact 0.13** -0.05 0.02 -0.14 0.01 (0.06) (0.03) (0.04) (0.48) (0.02) Impact on landholding HHs -0.07 -0.20* -0.08 -0.43 -0.02 (0.09) (0.10) (0.07) (1.11) (0.04) Impact on landless HHs 0.24*** 0.03 0.08** -0.15 0.02 (0.06) (0.03) (0.04) (0.55) (0.02) Panel B: Simple Difference Estimator with Baseline Controls Overall Jeevika impact 0.10** -0.01 0.01 -0.18 0.00 (0.04) (0.02) (0.03) (0.43) (0.02) Impact on landholding HHs -0.07 -0.13 -0.09* -0.44 -0.01 (0.07) (0.08) (0.06) (1.02) (0.04) Impact on landless HHs 0.18*** 0.04* 0.06* -0.09 0.01 (0.05) (0.02) (0.03) (0.52) (0.02) Panel C: Difference in Differences Estimator Overall Jeevika impact 0.07 0.04 0.02 -1.21 -0.01 (0.07) (0.04) (0.04) (1.67) (0.03) Impact on landholding HHs -0.03 0.01 -0.10 -0.86 -0.03 (0.10) (0.12) (0.07) (2.48) (0.04) Impact on landless HHs 0.10 0.04 0.07 -0.87 0.01 (0.07) (0.03) (0.04) (1.65) (0.03) Notes: All specifications control for stratification dummies. Results shown in Panel B are from specifications in which baseline controls (Table A1) are included. Figure 1. Interest rates on loans from informal lenders, FGD data. Table B1. Direct Effects of Jeevika New loans taken, past SHG Any Loans Outstanding debt (000 Rs) Interest Rates year (000 Rs.) Family membership Taken in the High cost Monthly Index of (%) last year? SHG All Loans (≥ 4% / rate on Total SHG Dependent Loans month) new loans Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) Panel A: Overall Program Effects Jeevika 51.19*** 0.04*** -0.78* 1.98*** -1.79*** -0.96*** -0.10 1.92*** 0.81*** (1.57) (0.01) (0.46) (0.09) (0.39) (0.07) (0.32) (0.10) (0.03)‡‡‡ Additional baseline controls? no no no no no no no no no Hochberg-corrected p-value 0.00 Panel B: Heterogeneous effects by household landholding status Jeevika 42.93*** 0.05*** -2.48* 1.68*** -1.52* -0.63*** -1.76** 1.66*** 0.69*** (2.31) (0.02) (1.40) (0.15) (0.91) (0.12) (0.83) (0.16) (0.04)‡‡‡ Landless HH 2.35* 0.12*** -8.16*** 0.02 -1.01 0.85*** -2.77*** 0.04 0.04* (1.21) (0.01) (1.21) (0.04) (0.86) (0.10) (0.77) (0.06) (0.02) Jeevika X landless 11.41*** -0.02 2.57 0.42** -0.35 -0.45*** 2.38** 0.36** 0.16*** (2.23) (0.02) (1.61) (0.17) (1.08) (0.14) (0.99) (0.18) (0.04) Linear combinations Effect of Jeevika if landless 54.34*** 0.03** 0.08 2.10*** -1.87*** -1.08*** 0.62 2.02*** 0.85*** (1.63) (0.01) (0.50) (0.10) (0.46) (0.08) (0.39) (0.11) (0.03)‡‡‡ Effect of landless if Jeevika 13.75*** 0.10*** -5.59*** 0.44** -1.36* 0.40*** -0.39 0.40** 0.20*** (1.92) (0.01) (1.06) (0.16) (0.67) (0.09) (0.64) (0.17) (0.04) Additional baseline controls? no no no no no no no no no Hochberg-corrected p-value Treatment if landless 0.00 Treatment if landed 0.00 Notes: Standard errors clustered at the panchayat level are shown in parentheses. Coefficients are from an ANCOVA specification - linear regressions of each outcome on its value at baseline, and an indicator of treatment status (plus an indicator of landessness at baseline and its interaction with treatment status in Panel B). Stratification dummies are included in all specifications. Columns 9 presents coefficients in a regression of z-scores of the outcome variables in this "family" - SHG membership, any loans taken, all outstanding debt, outstanding SHG debt, outstanding High-cost debt, interest rates, total amount borrowed last year, SHG amount borrowed last year - following Kling, Liebman, and Katz (2007). p-values for these regressions are reported using Hochberg's step-down method to control the FWER across all index outcomes. * p<0.1, ** p<0.05; *** p<0.01 ‡ p-adjusted < 0.1, ‡‡ p-adjusted < 0.05, ‡‡‡ p-adjusted < 0.01 Table B2. Effects of Jeevika on the informal credit market (Indirect) Household Survey Data Village FGD Data Any Informal Outstanding New Informal Index of Informal Money-lenders / Loans Informal Debt Loans Taken Dependent Informal Friends / Relatives interest rate Shopkeepers Taken? (000 Rs.) (000 Rs.) Variables (1) (2) (3) (4) (5) (6) (7) (8) Panel A: Main Effects Panel A: Mean monthly lending rate EL_informal_rate Jeevika -0.06*** -2.58*** -1.98*** -0.13* 0.09*** _m1 0 176 (0.01) (0.41) (0.31) (0.07) (0.01)‡‡‡ 0 0 0.36 Additional baseline controls? no no no no no no no no Hochberg-corrected p-value 0.00 Panel B: Heterogeneous effects by landholdings Panel B: Number of informal lenders Jeevika -0.04** -3.55*** -3.27*** 0.07 0.07** EL_number_informal_nc 0 179 (0.02) (1.11) (0.78) (0.11) (0.03)‡‡‡ 0 0 0.21 Landless HH 0.12*** -5.38*** -2.79*** 0.82*** -0.03 (0.02) (1.02) (0.75) (0.09) (0.03) Jeevika X landless -0.03 1.49 1.86** -0.29** 0.02 (0.02) (1.32) (0.94) (0.13) (0.04) Linear combinations Effect of Jeevika if landless -0.07*** -2.06*** -1.41*** -0.22** 0.09*** (0.01) (0.49) (0.38) (0.08) (0.02)‡‡‡ Effect of landless if Jeevika 0.09*** -3.89*** -0.93 0.54*** -0.00 (0.02) (0.85) (0.58) (0.09) (0.02) Additional baseline controls? no no no no no no no no Hochberg-corrected p-values Treatment if landless 0.00 Treatment if landed 0.00 Notes: Standard errors clustered at the panchayat level are shown in parentheses. Coefficients are from an ANCOVA specification - linear regressions of each outcome on its value at baseline, and an indicator of treatment status (plus an indicator of landessness at baseline and its interaction with treatment status in Panel B). Stratification dummies are included in all specifications. Village level regressions are from a separate village focus group discussion dataset. Columns 5 presents coefficients in a regression of z-scores of the outcome variables in this "family" - any loans taken, outstanding debt, new loans, interest rates - following Kling, Liebman, and Katz (2007). p-values for these regressions are reported using Hochberg's step-down method to control the FWER across all index outcomes. * p<0.1, ** p<0.05; *** p<0.01 ‡ p-adjusted < 0.1, ‡‡ p-adjusted < 0.05, ‡‡‡ p-adjusted < 0.01 Table B3. Effects of Jeevika on Household Assset position, Entitlements, and Welfare Real Access to Index of Consumption Productive Asset Housing quality Consumption entitlements Dependent Asset Index Index Index per AE (% any) Variables (000 Rs) (1) (2) (3) (4) (5) (6) Panel A: Main Program Effects Jeevika 0.10** -0.01 0.02 -0.26 0.00 0.02 (0.05) (0.02) (0.03) (0.45) (0.02) (0.02) Additional baseline controls? no no no no no no Hochberg corrected p-value 0.99 Panel B: Heterogeneous effects by household landholding status Jeevika -0.07 -0.13 -0.09 -0.52 -0.02 -0.06 (0.08) (0.08) (0.06) (1.06) (0.04) (0.03) Landless HH -0.43*** -0.37*** -0.40*** 2.62*** -0.16*** -0.22*** (0.06) (0.06) (0.05) (0.88) (0.04) (0.03) Jeevika X landless 0.25*** 0.17* 0.16** 0.30 0.03 0.10*** (0.08) (0.09) (0.07) (1.26) (0.05) (0.04) Linear combinations Effect of Jeevika if landless 0.18** 0.04 0.07* -0.22 0.01 0.05** (0.05) (0.02) (0.03) (0.53) (0.02) (0.02)‡‡‡ Effect of landless if Jeevika -0.19** -0.20*** -0.24*** 2.92*** -0.13** -0.11*** (0.06) (0.05) (0.04) (0.93) (0.03) (0.02) Additional baseline controls? no no no no no no Hochberg-corrected p-values Treatment if landless 0.00 Treatment if landed 0.21 Notes: Standard errors clustered at the panchayat level are shown in parentheses. Coefficients are from an ANCOVA specification - linear regressions of each outcome on its value at baseline, and an indicator of treatment status (plus an indicator of landessness at baseline and its interaction with treatment status in Panel B). Stratification dummies are included in all specifications. Columns 6 presents coefficients in a regression of z-scores of the outcome variables in this "family" - consumption assets, productive assets, housing quality, access to entitlements, real consumption per adult equivalent - following Kling, Liebman, and Katz (2007). p-values for these regressions are reported using Hochberg's step-down method to control the FWER across all index outcomes. * p<0.1, ** p<0.05; *** p<0.01 ‡ p-adjusted < 0.1, ‡‡ p-adjusted < 0.05, ‡‡‡ p-adjusted < 0.01 Table B4. Effects of Jeevika on Women's Economic Roles, Empowerment, and Aspirations Proportion HH Women's Women's Index of women work decision- collective Women's Aspirations for Dependent for income making in action index Mobility girls (%) Variables (%) HH index (%) (1) (2) (3) (4) (5) (6) Panel A: Main Program Effects Jeevika -0.49 -0.08 2.12** -0.01 0.69 -0.00 (0.88) (0.05) (1.05) (0.02) (1.46) (0.01) Additional baseline controls? no no no no no no Number of observations 8830 8841 8841 8029 3910 8988 Number of clusters 179 179 179 179 179 179 R-squared 0.12 0.06 0.05 0.05 0.11 0.06 Mean of dep var, omitted cat 72.58 6.27 87.44 5.79 29.08 -0.00 Hochberg corrected p-value 0.81 Panel B: Heterogeneous effects by household landholding status Jeevika 1.09 -0.10 2.21 -0.00 3.09 0.01 (2.05) (0.06) (1.57) (0.03) (3.06) (0.02) Landless HH 13.79*** 0.00 -0.45 0.08*** -17.75*** 0.07*** (1.73) (0.04) (1.05) (0.02) (2.31) (0.02) Jeevika X landless -2.62 0.03 -0.11 -0.01 -2.84 -0.02 (2.44) (0.06) (1.49) (0.03) (3.44) (0.02) Linear combinations Effect of Jeevika if landless -1.53 -0.07 2.10 -0.01 0.25 -0.01 (1.06) (0.05) (1.09) (0.02) (1.66) (0.01) Effect of landless if Jeevika 11.17*** 0.04 -0.56 0.07*** -20.60*** 0.05*** (1.73) (0.05) (1.04) (0.02) (2.80) (0.02) Additional baseline controls? no no no no no no Number of observations 8830 8841 8841 8029 3910 8988 Number of clusters 179 179 179 179 179 179 R-squared 0.14 0.06 0.05 0.05 0.14 0.07 Mean of dep var, omitted cat 61.26 6.29 87.77 5.14 45.87 -0.04 Hochberg-corrected p-values Treatment if landless 0.48 Treatment if landed 0.64 Notes: Standard errors clustered at the panchayat level are shown in parentheses. Coefficients are from an ANCOVA specification - linear regressions of each outcome on its value at baseline, and an indicator of treatment status (plus an indicator of landessness at baseline and its interaction with treatment status in Panel B). Stratification dummies are included in all specifications. Column 6 presents coefficients in a regression of z-scores of the outcome variables in this "family" - working women, decision making, collective action, mobility, aspirations - following Kling, Liebman, and Katz (2007). p-values for these regressions are reported using Hochberg's step-down method to control the FWER across all index outcomes. * p<0.1, ** p<0.05; *** p<0.01 ‡ p-adjusted < 0.1, ‡‡ p-adjusted < 0.05, ‡‡‡ p-adjusted < 0.01