96199  i Remittances and the economic crisis: evidence from the Greenback 2.0 survey in Italy greenback 2.0 Working paper N.1 Laura Bartolini,§* Eleonora Castagnone* March 2015 Suggested citation: Bartolini, Laura and Castagnone, Eleonora (2015), “Remittances and the economic crisis: evidence from the Greenback 2.0 survey in Italy,” The World Bank, Greenback Working Paper n. 1. Global §  Governance Programme, European University Institute (Florence, Italy) *FIERI—International and European Forum of Research on Immigration (Turin, Italy) Laura Bartolini was in charge of the empirical analyses and wrote Sections 2, 3 and 4, Eleonora Castagnone wrote the Introduction and contributed to a critical overall revision of the paper. This paper is part of the World Bank’s Project Greenback 2.0—Remittances Champion Cities and was conceived by the authors in strict collaboration with Ferruccio Pastore (FIERI) and Marco Nicolì (Payment Systems Develop- ment Group, Finance and Markets, World Bank). Authors would like to thank Claudia Villosio (Laboratorio Revelli) for her precious com- ments and suggestions. The views expressed in this working paper are those of the authors and do not necessarily represent those of the World Bank Group.  iii ABSTRACT M onetary remittances represent the most visible transnational activity of migrants and can be considered as a function of migrant’s ability of producing savings from income and of remitting (supply side), and of the type of claims of family members, either left in the country of origin or residing abroad with the migrant (demand side). Hence, migrant’s remitting capacity is directly linked to the level of economic integration at destination. However, what happens to remittances when the labor market becomes uncertain and the earning potential decreases? Based on a recent survey, this paper explores the effect of the economic crisis on income trends and on the flow of monetary remittances sent to the families left home among three surveyed groups in Turin—Moroccans, Peruvians and Romanians. Results show a widespread worsening of the average economic conditions since the outbreak of the crisis in 2008. The protracted economic instability seems to have effects on migrants’ ability to keep remittance flows constant over time, with differentiated out- comes according to the national groups. While Moroccans show a higher propensity in receiving remittances, Peruvians are those who resist more to a remittance drop over the last five years. Beyond economic determinants, observed patterns in remittance trends can also be explained by migrant household characteristics in Italy and abroad and to unobserved variables (distance) related to the country of origin.  v Contents Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Migrant’s labour market integration in time of crisis: the case of Italy. . . . . . . . . . . . . . . 1 The impact of the crisis on migrants’ remittances. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The Italian case and objective of the paper. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Empirical data: the Greenback 2.0 survey. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Sample characteristics and main variables of interest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Modelling the impact of the economic crisis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 The model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Variables’ description. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Income trends since 2008. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Trends in the remitted amount since 2008. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Results and final conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 APPENDIX. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 List of Tables and Figures vii List of Tables and Figures Table 1: Remittances outflows from Italy, 2005–2013: first 8 provinces and total (millions of euro). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Table 2: First 3 countries of destination in 2013, first 8 Italian provinces.. . . . . . . . 5 Table 3: Demographic characteristics, by country of origin. . . . . . . . . . . . . . . . . . . . . . . 7 Table 4: Economic characteristics of the sample, by country of origin. . . . . . . . . . 8 Table 5: Chi2 test for the correlation between income and remittance trends, by sex. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Table 6: Binary variable: income decreased since 2008 (odds ratio).. . . . . . . . . . . . 11 Table 7: Binary variable: remittances decreased since 2008 (odds ratios). . . . . . 14 Table 8: Marginal effects—Change in probability of a remittances decrease when the predictor increases by 1 unit. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Table 9: Income trend since 2008—Mutinomial logit, base outcome “income unchanged”. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Figure 1: Foreign resident population and remittances in Italy, 2005–2013.. . . . . 3 Figure 2: Remittances from the Province of Turin, 2005–2013, first 3 destination countries (mln €). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Figure 3: Predictive margins calculated at fixed values of specific variables, holding the other predictors at their means, by sex.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Figure 4: Predictive margins calculated at fixed values of specific variables, holding the other predictors at their means, by sex.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1 Introduction Migrant’s labor market increased concentration of foreign labor force is observed in the low qualified positions (from integration in time of crisis: 29 percent in 2008 to 34 percent in 2012), with the case of Italy a parallel decrease in the share of migrant work- ers in qualified jobs (from 8.2 percent in 2008 The financial crisis of 2008 continues to have a to 5.9 percent in 2012) and an increase in the profound effect on both the native and the immi- proportion of “over-educated” workers: migrant grant population in Italy. Immigrant workers are workers who perform tasks below their highest often deemed to suffer more in terms of employ- level of education represent 41 percent of the ment and income reduction than Italian workers entire migrant workforce in 2012 while the same because of their relatively weaker contractual figure was around 39 percent in 2008.4 position, their lower education level, and their concentration in highly pro-cyclical economic Also underemployment, which is calculated on the sectors such as manufacturing and construction.2 volume of the total hours worked and describes Indeed, most recent figures on the labor market the level of utilization of workers, has exacerbated dynamics in Italy show a decrease in the employ- among foreign workers, growing from 7 percent in ment rate between 2008 and 2013, which strongly 2008 to 10.7 percent in 2012, 6 points higher than affects male migrants (14 percent) and to a lesser Italian workers (ibid). extent also female migrants (3.4 percent) (ISTAT 2014). While employment rates are traditionally At the same time the average income gap lower for women than men (49.3 percent against between foreign and Italian workers has 67.9 percent in 2013), the employment growth expanded. The net monthly salary is, on average, during 2013 of around 22 thousand units is only lower for foreigners: in 2012 it amounted to due to women. The differentiated impact of the €968 versus €1,304 for Italian workers (2€336). crisis by sex is mainly due to the distribution Furthermore, while the net pay of the foreign of men and women in the labor market. While labor force was only slightly higher in 2008 than males mainly employed in the manufacturing in 2012 (€973 per month), the gap between the and construction sectors which have been seri- wage of native workers was much lower, amount- ously stricken by the crisis3 female employment is ing to €266 per month (ibid). Over the past few highly concentrated in the domestic and health- years, the increase in income inequality is recog- care sectors, which have been less affected by the nized as one of the effects of the crisis, as well economic downturn (ibid). as the reason for the progressive increase in the number of the so-called “working poor.”5 Beyond the employment negative trend, further phenomena account for the impact of the cri- sis on migrant workers. In the last few years an 4 Ministero del Lavoro e delle Politiche Sociali. 2013. Terzo Rapporto Annuale—Gli Immigrati Nel Mercato Del Lavoro in Italia. http://www 2 Moressa Fondazione. Rapporto Annuale Sull’economia .italialavoro.it/wps/wcm/connect/912eae08-a9f5-45d7-a302-c1330ac4fc13/ Dell’immigrazione—Edizione 2013, Tra Percorsi Migratori E Comportamento 18+Terzo+Rapporto+Annuale++immigrati+2013.pdf?MOD=AJPERES. Economico. Bologna: Il Mulino. 5 Emanuele Galossi, L’impatto Della Crisi Sulle Condizioni Di Vita E Di 3 Pastore, Ferrucio, Ester Salis, and Claudia Villosio. 2013. “L’Italia E Lavoro Degli Immigrati: Un’indagine dell’Associazione Bruno Trentin. 2013. L’immigrazione ‘low cost’: Fine Di Un Ciclo?.” Mondi Migranti 1 (19). Associazione Bruno Trentin, IRES.  1 2 GREENBACK 2.0 survey 2015 Since the outbreak of the crisis, increasing unem- ployment and lower wages has put migrants at The impact of the crisis risk of a strong family restructuring and social on migrants’ remittances destabilization. The share of foreign dual-income Migrants’ economic contribution to origin coun- households shrunk to 24.2 percent of the total in tries takes many different forms and is associated 2013 (from 29.6 percent in 2008) and even among with the type and length of the migratory experi- migrants the single-income household model ence as well as with the level of integration into (usually with a male earner) continues to be the the labor market at destination and at different prevalent model, representing 58.7 percent of all stages of the migratory process. Remittances are households with at least one member at working perhaps the migrant’s most visible transnational age (+367 thousand families in the five years of activity as they represent an important additional the crisis). The female household member seems income source for origin households as well as to offset the loss of employment of men only in non-negligible international monetary flows at the the northern regions of the country, where the aggregate level. sharp decline in households with a single bread- winner (down from 44.7 to 36.6 percent of the Transnational monetary transfers can be under- total between 2008 and 2013) is associated with stood as the result of a bargaining process of an increase in the households where the bread- migrants and their origin households, where the winner is a woman (from 16.3 to 23.0 percent). demand from family members left behind and On the other hand, the slight rise in employment from obligations contracted before departure among women in the rest of the country is not meet the ability and willingness of the migrant enough to compensate for the employment loss to save and remit.7 In this perspective the total among men (ISTAT 2014). amount of remittances depends, among other factors, upon the occupational and economic In 2013, the number of foreign households with trajectories of migrants abroad. Indeed, several no income from pension and work has more than empirical studies provide support for the role of tripled compared to 2008, rising from 98,000 migrants’ per capita income at destination as well to 311,000, which translates to an increase from as in the origin country in explaining the total 7 percent to 14.9 percent of all households in the amount of remittances sent.8 same conditions. In the same line, the proportion of households without income from employment Historically, remittances proved to be less volatile on total foreign families with at least one working- and more resilient to idiosyncratic shocks of the age member reaches 15.5 percent, while it was economic cycle than other international financial 7.4 percent in 2008 (ISTAT 2014). flows and have shown increasing trends in times of financial crisis and natural disasters in the ori- In this context, the worsening of the economic gin countries.9 For example, remittance inflows integration is not totally addressed by a retrench- to Mexico increased following a financial crisis ing social welfare and social protection system. A in 1995, to the Philippines and Thailand after the more problematic access to the welfare system 1997 Asian crash, and to Central America after and to income support measures, the absence or Hurricane Mitch in 1998. Evidence in rural Mali the limited presence of a family network, the need showed that remittances respond positively to to send remittances to the origin countries, and the costs of bureaucracy (such as those related to residence permits’ renewals) are just some of the causes of the erosion of migrants’ incomes, 7 Hillel Rapoport and Frédéric Docquier. “The Economics of Migrants’ putting migrants at risk of falling below the Remittances,” IZA Discussion Paper Series, no. 1531 (March). 2005. 8 See Glytsos 1988 for the Greek-German migration between 1960 and poverty line.6 1982, Glytsos 2002 for European migration from Algeria, Egypt, Jordan, Morocco, Syria, Tunisia and Turkey and OECD 2006. 6 9 Devi Sacchetto and Francesca Alice Vianello. “La Diffusione Del Lavoro Dilip Ratha, Sanket Mohapatra, and Ani Silwal. Outlook for Remittance Povero. L’impatto Della Crisi Economica Sui Lavoratori Migranti.” 2012. Espa- Flows 2010–11. 12. Migration and Development Brief. Washington, D.C: The net Conference: Risposte alla crisi. Esperienze, proposte e politiche di wel- World Bank. 2010. http://siteresources.worldbank.org/INTPROSPECTS/ fare in Italia e in Europa, 20–22 September, Roma. Resources/334934-1110315015165/MigrationAndDevelopmentBrief12.pdf. INTRODUCTION 3 shocks suffered by recipient households10 and sur- hit by income shocks. Indeed, remittances at the veys in the River Valley in Mali and in Senegal sug- global level remained remarkably stable in the gested that migration acts as an intra-household wake of the recent financial crisis, compared to risk-diversification strategy, with remittances as a other types of international financial inflows (The contingent flow that supports family consumption World Bank 2011). in case of adverse shocks.11 Unlike past emerging market crises, however, the The Italian case and objective current crisis started in the high-income countries of the paper and has subsequently spread to the developing Unlike the global trend, remittances from Italy countries, resulting in a global crisis. Migrant des- showed a sensible decline since 2011, with the tinations both in the North and the South have overall amount sent in 2013 being far below the been affected to varying degrees. level of 2008 (see Fig. 1). Official data provided Recent evidence for Italy12 suggests that migrants by the Bank of Italy,13 shows that the decrease in adopt different strategies in order to cope with the total remittance volume is due more to the the crisis, such as sending some family members decrease in the number of remitting migrants back home in order to alleviate their costs in the than to the decrease in the amount sent by each destination countries or reducing the daily expen- of them (on average €1,673 per year in 2012). The ditures in response to wage cuts by employers decrease in the number of remitting migrants (sharing accommodations, contracting the con- and in the total outflows from Italy is even more sumption costs). Nevertheless, migrants typically striking if one considers that the total migrant continue to send remittances, even when they are population residing in the country kept growing, although at a slower pace, also in the last years of the economic downturn (ISTAT 2014). 10 Flore Gubert “Do Migrants Insure Those Who Stay Behind? Evidence from the Kayes Area (Western Mali).” Oxford Development Studies 30 (3): Almost half of the entire remittances flow 267–87. 2002. “Migration and Development: Mixed Evidence from Western Mali.” Development 50 (4): 94–100. 2007. from Italy is sent from two regions, Lazio and 11 Jean-Paul Azam and Flore Gubert. 2006. “Migrants’ Remittances and Lombardy. the Household in Africa: A Review of Evidence.” Journal of African Econo- mies 15 (suppl. 2): 426–62. 12 13 Cingolani and Ricucci 2013; Galossi 2013; Fondazione Moressa 2013. Fondazione Moressa 2013: 111–112. Figure 1: Foreign resident population and remittances in Italy, 2005–2013 5.0 8,000 7,500 4.5 7,000 6,500 4.0 6,000 3.5 5,500 5,000 3.0 4,500 4,000 2.5 3,500 2.0 3,000 2005 2006 2007 2008 2009 2010 2011 2012 2013 Foreign resident population,* millions Remittance outflows, millions of € (right axis) Source: Istat and Bank of Italy. *Break in series in 2011: from 2012 data are adjusted for new Census data. 4 GREENBACK 2.0 survey 2015 Table 1 presents data for the first 8 provinces per Focusing on the supply side, hence on the abil- remittance sent: except for Naples, all of the prov- ity of migrants to send money back home, this inces are in the northern and central parts of Italy. paper investigates the labor market integration While China alone is the destination of almost of migrants residing in Turin, their income stabil- 40 percent of all remittances sent from Italy, dif- ity during the economic crisis (2008–2013) and ferences at the province level reflect the different the impact of the latter on remittances’ size. In composition of migrant population across Italy particular the paper tries to answer two intercon- (Table 2). nected questions: 1) which national groups or profiles of individuals are most affected by the Although migrant groups in Italy differ in their economic crisis and what are their characteristics? economic integration and labor market special- 2) what has been the effect of the crisis on the izations, the worsening economic conditions remittance trend? have had an impact on remittance behaviors and prospects almost everywhere (Fullin and Reyneri The rest of the paper is divided as follows: 2013). Indeed, total remittance outflows from Italy Section 2 presents the empirical data drawn decreased at about 14 percent between 2008 and from the Greenback 2.0 survey in Turin, Section 3 2013 (Table 1). presents the model adopted to describe the probability of an income drop and of a decrease Based on a recent survey conducted by the in remittances during the crisis and Section 4 World Bank in 2014, this paper explores the effect discusses the empirical results. Some concluding of the economic crisis on the flow of monetary remarks will be provided. remittances sent to the families left home in three surveyed communities in Turin—Moroccans, Peruvians and Romanians. Table 1: Remittance outflows from Italy, 2005–2013: first 8 provinces and total (millions of euro) 2008– 2005 2006 2007 2008 2009 2010 2011 2012 2013 2013 2013   a.v. a.v. a.v. a.v. a.v. a.v. a.v. a.v. a.v. % % var. Rome 1145.84 1087.09 1500.35 1697.72 1784.7 1786.27 2040.02 1938.17 965.49 17.5 243.1 Milan 675.36 614.6 824.86 862.83 890.41 941.83 1031.31 965.97 674.81 12.3 221.8 Naples 96.88 127.01 170.81 183.89 240.86 225.75 305.71 295.6 220.95 4 20.2 Prato 29.89 88.06 449.74 415.82 485.56 191.7 249.1 208.46 202.52 3.7 251.3 Florence 129.7 142.49 244.3 254.11 253.73 207.35 233.6 197.19 190.8 3.5 224.9 Turin 121.76 164.03 180.41 180.36 180.26 180.54 193.32 164.58 168.78 3.1 26.4 Brescia 72.65 106.01 127.3 132.63 131.62 132.09 152.76 134.65 140.65 2.6 6 Boulogne 69.55 103.05 126.14 138.72 130.77 130.7 131.86 108.99 117.96 2.1 215 Total 3900.79 4527.67 6039.26 6376.95 6747.82 6572.22 7394.4 6833.12 5501.76 48.7 213.7 Source: Own calculations based on Bank of Italy dataset on remittances (last update July 2014). INTRODUCTION 5 Table 2: First 3 countries of destination in 2013, first 8 Italian provinces   1° Row % 2° Row % 3° Row % Tot, % Rome China 35.76 Romania 14.03 Philippines 11.57 61.36 Milan China 24.17 Philippines 15.48 Peru 9.97 49.62 Naples China 35.57 Ukraine 9.47 Romania 7.61 52.64 Prato China 88 Pakistan 1.82 Romania 1.73 91.56 Florence China 37.84 Peru 9.68 Romania 8.96 56.48 Turin Romania 28.35 Peru 10.14 Morocco 8.12 46.6 Brescia China 15.02 Senegal 10.25 Romania 10.01 35.28 Bologna Romania 13.37 Bangladesh 11.97 China 10.61 35.95 Source: Own calculations based on Bank of Italy dataset on remittances (last update July 2014). 2 Empirical data: the greenback 2.0 survey E mpirical data on migrant transnational engagement in terms of remittances are drawn from the Greenback 2.0 survey.14 Aimed at explor- on individual and household characteristics, job integration and remittance behavior of migrants residing in Turin, a medium-sized city in the ing migrants’ financial needs and behavior, the North of Italy, between July and September survey collected quantitative in-depth data 2013. Interviewed migrants are citizens from Romania, Morocco and Peru, the first three coun- tries of origin per number of residents in the 14 The World Bank. 2014. Migrants’ Remittances from Italy—International city (representing together almost 60 percent Remittances and Access to Financial Services for Migrants in Turin, Italy. Greenback 2.0 Report. Washington, D.C. https://remittanceprices.worldbank of the total migrant population) and per total .org/sites/default/files/migrants_remittances_italy.pdf. amount of remittances from the Province of Turin, Figure 2: Remittances from the Province of Turin, 2005–2013, first 3 destination countries (min €) 55 50 45 40 35 30 25 20 15 10 5 0 2005 2006 2007 2008 2009 2010 2011 2012 2013 Romania Peru Morocco Source: Own calculations based on Bank of Italy dataset on remittances (last update July 2014). 6 EMPIRICAL DATA:THE GREENBACK 2.0 SURVEY 7 representing respectively 28.2 percent, 10.8 per- included in the sample the interviewed migrants cent, and 8.2 percent of the overall outflows.15 had to meet four criteria: 1) to have resided in Italy for at least one year (with or without a regular At the same time, these three countries differ in residence status); 2) to live in the city of Turin their geographical position, patterns of socio- and its metropolitan area; 3) to have an income economic integration in Italy (in terms of partici- (obtained from any type of job or occupation, pation to the labor market by sex and distribution including activities in the informal sector); and in different economic sectors) and migratory sys- 4) to have sent remittances to his/her country of tems (in relation to the organization of the migra- origin at least once since the beginning of 2013. A tory chain within families). The overall sample ‘center sampling technique’ was adopted to cap- is composed of three equally large subsamples ture also migrants not legally residing in the coun- according to the citizenship at birth of the inter- try and to create a balanced sample.16 viewees: short-range EU migration (Romania), short-range non–EU migration (Morocco) and long-range migration (Peru). Sample characteristics and main variables of interest The sample is composed of foreign-born indi- viduals residing in the city of Turin at the time of The average profile of the final sample is reported the interview, including naturalized immigrants, in Table 3 and Table 4. The first table includes between the ages of 18 and 64 years. To be 16 Baio, Gianluca, Gian Carlo Blangiardo, and Marta Blangiardo. 2011. “Center Sampling Technique in Foreign Migration Surveys: A Methodological 15 Fondazione Moressa 2013; Banca d’Italia 2014. Note.” Journal of Official Statistics 27 (3): 451–65. Table 3: Demographic characteristics, by country of origin Morocco Peru Romania Total Freq. Col % Freq. Col % Freq. Col % Freq. Col % Sex Male 136 85.53 74 45.96 62 38.75 272 56.67 Female 23 14.47 87 54.04 98 61.25 208 43.33 Arrival in Before 2008 128 80.5 117 72.67 121 75.63 366 76.25 Italy After 2008 31 19.5 44 27.33 39 24.38 114 23.75 Education None 6 3.77 0 0 0 0 6 1.25 Elementary 7 4.4 0 0 2 1.25 9 1.88 Lower second 63 39.62 26 16.15 21 13.13 110 22.92 Upper second 58 36.48 95 59.01 94 58.75 247 51.46 Post-sec, non ter.* 0 0 1 0.62 27 16.88 28 5.83 Bachelor 12 7.55 11 6.83 9 5.63 32 6.67 Master 13 8.18 28 17.39 7 4.38 48 10 Marital Married 83 52.2 78 48.45 74 46.25 235 48.96 status Separated 8 5.03 14 8.7 6 3.75 28 5.83 Divorced 7 4.4 13 8.07 19 11.88 39 8.13 Widow 0 0 1 0.62 2 1.25 3 0.63 Single 56 35.22 34 21.12 32 20.0 122 25.42 Cohabiting 5 3.14 21 13.04 27 16.88 53 11.04 Italian 15 9.43 10 6.21 3 1.88 28 5.83 citizenship Total 159 100 161 100 160 100 480 100 * ISCED education levels: the post-secondary non tertiary class includes all vocational or university courses after the high school diploma and which last no more than 1 year. 8 GREENBACK 2.0 survey 2015 Table 4: Economic characteristics of the sample, by country of origin Morocco Peru Romania Total Mean values M F M F M F M F Age 36.6 37.1 42.1 41.1 35.9 38.1 37.9 39.3 Length of stay in Italy 10.9 10.6 8.8 10.7 9.4 8.6 10 9.7 Annual income (€) 11181.5 9780 12240 10221.4 15541 10781.6 12451.8 10439.7 Annual remittances (€) 1590.5 1715.2 2240.8 2004.3 1875 1677.3 1832.3 1818.2 Remittance to income ratio 0.166 0.187 0.209 0.215 0.127 0.159 0.169 0.186 general statistics on sex, arrival in Italy, education worth noticing that 7 percent of migrants have level and marital status of the 480 interviewed achieved their highest education level in Italy and individuals, while Table 4 reports statistics on age, that 35.6 percent of them have attended some length of stay in Italy, income and remittances. sort of professional and/or vocational training courses in Italy, with high variations in terms of While the overall sample is relatively gender- length (from 1 months to 2 years) and subject of balanced (43 percent of those interviewed are the course (from carpentry to health care, from women), gender differences are more evident computer science to cooking). Almost half of within each subsample: women represent 61 per- the interviewed migrants are married. Moroccans cent of Romanians, 54 percent of Peruvians, have the highest number of single individuals and only 14 percent of Moroccans, the latter less (35 percent), while among Romanians and Peru- frequently complying with the survey criteria vians there is a higher incidence of separated or because of their low activity rate. Each subsample divorced individuals (respectively 18 percent and is stratified according to the length of stay in Italy, 16 percent). with around 24 percent of interviewed migrants with a ‘short’ migratory experience and arriving Table 4 provides summary statistics on some key after 2008. demographic and economic variables by country of origin. Although Peruvians had the oldest age, With regard to formal qualifications and compe- Moroccans had the longest length of stay, with tences, Peruvians show the highest level of edu- more than 10 years on average. At the same time, cation attained (59 percent with a high school Moroccans earn and remit less annually than both diploma and 17 percent with a master degree), Romanians and Peruvians. Differences in the total closely followed by Romanians (59 percent with amount of remittances sent per year are sensible a high school diploma, 17 percent with a non- both in absolute terms and in relative terms with university qualification after the high school the declared annual income: the remittance to diploma). Almost 40 percent of Moroccans income ratio ranges from 12.7 percent of male attained a lower secondary school diploma, while Romanian migrants to 21.5 percent of female 36 percent an upper secondary diploma. It is Peruvian migrants. 3 Modelling the impact of the economic crisis The model categorical dependent variables, taking into account the pros and cons of each of them in The purpose of the empirical analysis is to test terms of assumptions, goodness of fit and ease what are the main factors that contribute to of results’ interpretation. Using an ordered logit determine the income and remittances trends model implies the acceptance of the propor- since the beginning of the economic crisis in Italy tional odds assumption, for which the relation- among the surveyed population. The Greenback ship between all pairs of groups is the same and 2.0 survey provides two variables that account therefore only one set of coefficient is estimated. for the income trend and the remittance trend Since this assumption was not confirmed by the between 2008 and 2013: these two variables two different tests (the Likelihood-ratio test and have three outcomes (decreased, unchanged, and the Brant test in Stata), we discarded this option increased) for which we can assume that ordering in favor of a non-ordinal multinomial method. is relatively straightforward and self-perception of After some further consistency checks,17 we chose respondents should not introduce an important to dichotomize the two outcome variables, distin- bias. A Chi-squared test to measure the associa- guishing between ‘decreased’ and ‘non decreased’ tion between the two by sex confirms that there is a strong, although not perfect, correlation 17 We tried with a multinomial logistic regression model, taking as the between them (Table 5). base outcome the case of unchanged income and estimating two sets of coefficients for the ‘decreased’ and ‘increased’ outcome. While the inter- pretation of results with this model is not straightforward, the estimates Since the income trend is not enough to explain are biased if the independence of irrelevant alternatives (IIA) assumption the variation in remittances, we proceeded by does not hold. In our case, although there is virtually no other alternative that can be added to the three considered ones in the outcome variable, the splitting the empirical test in two parts. Model- IIA is not confirmed. Hence, we finally opt for dichotomizing the two out- ling the two trends in income and remittances come variables and test binary logistic models. We provide the multinomial logit regression results for the income trend in the Appendix for a compari- required choosing between different non-linear son. For a discussion on alternative models see (Long and Freese 2006; regression models for ordered and non-ordered Williams 2012). Table 5: Chi2 test for the correlation between income and remittance trends, by sex Male Remittances Female Remittances Income Decreased Unchanged Increased Total Income Decreased Unchanged Increased Total Decreased 105 32 5 142 Decreased 64 23 2 89 38.75 11.81 1.85 52.4 31.07 11.17 0.97 43.2 Unchanged 16 58 3 77 Unchanged 24 40 5 69 5.9 21.4 1.11 28.41 11.65 19.42 2.43 33.5 Increased 17 21 14 52 Increased 13 23 12 48 6.27 7.75 5.17 19.19 6.31 11.17 5.83 23.3 Total 138 111 22 271 Total 101 86 19 206 50.92 40.96 8.12 100 49.03 41.75 9.22 100 Pearson chi2(4) 5 93.9237 Pr 5 0.000 Pearson chi2(4) 5 45.1975 Pr 5 0.000  9 10 GREENBACK 2.0 survey 2015 and we run two binary logistic regressions for sector of occupation, dependent or autonomous modelling the probability of experiencing an status, the presence of one or more secondary income drop and for the probability of a decrease jobs to top-up the main occupation (either in in remittance between 2008 and 2013. terms of hours and income). The logit model is a non-linear regression model Remittance variables refer to the estimated total that forces the output to be either 0 or 1. Our amount of money sent annually, obtained by model has the following form: combining data on frequency and amount of each registered flow. The remittance/income ratio P(y 5 1|x) 5 F(b0 1 b 1x 1 1    1 b kxk) 5 F(b0 + b x) provides an estimate of the proportion of total income that is devoted to remittances. Moreover, where the response probability is defined as a dummy for migrants who declare to receive P(y 5 1|x 1, x 2, . . . , xk ), x denotes the vector of money transfers from abroad, either their origin explanatory variables and F(.) is the cumulative country or third countries where relatives reside, standard logistic distribution, with 0 , F(.) , 1 for is also considered. all values of the parameters and of x. The depen- dent variable is equal to 1 if the migrant individual Birth country dummies are included to control for income (or remittances) decreased over the the impact of unobserved variables connected 5 year period since 2008, or 0 otherwise. with the origin country, for example distance and possibility of personal visits to the home country Variables’ description throughout a year. While many variables are used in both models to control individual characteristics and history Income trends since 2008 of migration, the main explanatory variables for Table 6 shows the odds ratios of the logistic the probability of a decrease in income and for a regression. Odds ratios are the exponentiated drop in remittances do not completely overlap. logit coefficients, which represent the odds of Income trends are likely to be related to job char- y 5 1 when one independent variable increases by acteristics and the overall level of labor market one unit: integration. Remittances instead may respond to changes in economic circumstances as well as to P(y 5 1|x 1 1)/(1 2 P(y 5 1|x 1 1) 0R 5 changes in family structure both in Italy and in the P(y 5 1|x)/(1 2 P(y 5 1|x) country of origin. Demographic variables consider migrant’s sex, age, age at migration and conse- Hence if the reported odds ratio is higher than 1, quent length of stay, formal level of education, then the odds of y 5 1 increases, while if 0R , 1, additional training/vocational courses attended the odds of y 5 1 decreases for a unit increase in Italy and migrant’s legal status at the time of of x. arrival. Variables that describe the migrant family structure between Italy and the country of origin, Size and statistical significance of estimated defined as first-grade family members (parents, odds ratios are interesting. Variables that account siblings, partner and children), add important for the overall integration into the labor market insights on the migratory history of the inter- seem to explain a big part of the variation in the viewed migrants. Together with the household expected outcome. Having a full-time occupation, structure in Italy (one or more working individuals being in a dependent, non-autonomous position in the household), these can be used as a proxy and having a regular contract, lower the prob- for the availability of connections here and there ability of an income decrease. Consistently, having and on the level of integration into the country of a secondary occupation to top-up earnings from destination. the principal earner is positively related to an income drop since 2008. Monthly income levels Income and job characteristics are widely inves- show a non-linear tendency, with the mid- tigated with variables accounting for the type category of €1000–1500 per month the most of job in terms of hours, contract arrangement, likely to experience an income drop other things MODELLING THE IMPACT OF THE ECONOMIC CRISIS 11 being equal. Specifications (2) and (3) add beginning of their presence in Italy. Education- estimated odds ratios for different sectors of related coefficients are not significant, which employment and job categories: while size and might be partly due to their correlation with significance are not straightforward, this could job characteristics, while being the only income be partially explained by the sample selection earner in the household is associated with higher which excluded those who lost their job and had probability of a negative income trend, as well no income at all at the time of the survey. Indeed, as the dummy variable for being documented workers in the manufacturing and construction at the time of arrival. Other things being equal, sector could either experience a drop of income control variables for the country of origin are not due to short-time work schemes (included in the significant. sample) or a total loss of income due to a layoff (excluded from the sample). On the other hand, Since most predictors are specified as factor vari- domestic and health workers and workers in res- ables and the magnitude of each effect is difficult taurants and other services are more likely to have to understand with odds ratios, a more tangible more flexible contract arrangements which allow way of presenting results and of accounting for for salary adjustments in time of crisis. the single effect of each predictor on the prob- ability of experiencing an income drop is to cal- Control variables for individual characteristics also culate the adjusted predictions at representative show interesting patterns. The non-linear effect of values or for specific groups. age, with younger migrants less likely to experi- ence an income drop, has to be combined with Graphs in Figure 3 present the predicted prob- migrant length of stay: more recent migrants are ability of an income drop setting some meaningful less likely to experience income mobility since the variables at specific values, by sex. This means Table 6: Binary variable: income decreased since 2008 (odds ratio) Variables (1) (2) (3) Female 0.598** 0.721 0.691 (0.153) (0.225) (0.22) Age (years) 1.209** 1.209** 1.184** (0.0957) (0.0964) (0.0948) Age^2 0.998** 0.998** 0.998** (0.000965) (0.000971) (0.000971) Length of stay: 6–10 4.091*** 4.011*** 4.125*** (1.285) (1.275) (1.327) Length of stay: 11–15 4.615*** 4.491*** 4.693*** (1.611) (1.583) (1.676) Length of stay: 15–1 3.040*** 2.929** 3.334*** (1.285) (1.25) (1.458) Education level—medium 0.905 0.891 0.917 (0.25) (0.25) (0.258) Education level—high 0.633 0.65 0.793 (0.226) (0.234) (0.298) Training in Italy 1.198 1.21 1.286 (0.278) (0.283) (0.322) Documented at arrival 1.662** 1.667** 1.618** (0.396) (0.401) (0.394) (continues) 12 GREENBACK 2.0 survey 2015 Table 6: (continued) Variables (1) (2) (3) Peru 1.062 1.116 1.024 (0.319) (0.352) (0.326) Romania 0.999 1.005 1.008 (0.323) (0.328) (0.335) Income class: 501–1000 0.769 0.77 0.782 (0.281) (0.284) (0.291) Income class: 1001–1500 0.391** 0.364** 0.389** (0.171) (0.163) (0.179) Income class: 1501–1 0.412 0.403 0.466 (0.235) (0.233) (0.275) Mono income HH 1.719** 1.838** 1.726** (0.414) (0.453) (0.423) Full-time 0.574** 0.578** 0.609* (0.151) (0.154) (0.163) Contract 0.461** 0.464** 0.470** (0.14) (0.142) (0.145) Dependent job 0.387*** 0.409*** 0.340*** (0.119) (0.129) (0.118) Second job 2.378*** 2.365*** 2.420*** (0.686) (0.687) (0.717) Job type: cook & barman 1.11 (0.669) Job type: domestic worker 2.037 (0.971) Job type: nurse/OSS 1.273 (0.725) Job type: seller & retailer 2.366 (1.384) Job type: shop owner 0.84 (0.679) Job type: worker 2.247* (1.036) Sector: primary & secondary 1.446 (0.527) Sector: transport & trade 1.673 (0.642) Sector: domestic & health 1.059 (0.385) Constant 0.0448* 0.0324** 0.0363** 20.0725 (0.0534) (0.0608) Observations 474 473 474 Standard errors in parentheses ***p , 0.01, **p , 0.05, *p , 0.1 MODELLING THE IMPACT OF THE ECONOMIC CRISIS 13 Figure 3: Predictive margins calculated at fixed values of specific variables, holding the other predictors at their means, by sex       that in each group we compare three artificial the economic situation of the migrant play a big groups, which take specific values for age, length role in explaining a drop in remittances: negative of stay, income, sector of employment and educa- trends in income size and income security show a tion level, while all other variables are considered significant impact on the probability of decreasing at their mean values. Female migrants always remittances, irrespective from the income level. show a lower probability of an income drop. Moreover, being the sole income earner in the Lower income classes as well as manufacturing, household also negatively affects the remittance transport and trade sectors present the higher trend while receiving money from abroad (either probability of an income drop. Such results are from the household at origin or from relatives consistent with the overall Italian labor market migrated in third countries) shows a positive but performance during the crisis and with the gen- non-significant effect on the outcome variable. dered specialization of migrant women in the domestic and health sectors. Alongside economic conditions, other individual and household characteristics present interesting patterns. Length of stay in Italy, often used as a Trends in the remitted amount proxy for the level of integration, does not have since 2008 a straightforward interpretation as the impact on the probability of a decrease in remittances The second step of our empirical exercise mirrors changes for different length groups. On the con- the one presented above. A logit model was used trary, attending vocational or training courses in to determine the factors that affect the probability Italy, in addition to a formal education (almost of a decrease in the annual amount of remittances always acquired in the country of origin) increases since 2008. Table 7 reports the estimated odds the odds of a decrease in remittances. ratios. As expected, variables that account for 14 GREENBACK 2.0 survey 2015 Table 7: Binary variable: remittances decreased since 2008 (odds ratios) Variables (1) (2) (3) Female 1.556 1.14 1.14 (0.429) (0.408) (0.409) Age (years) 1.075 1.07 1.069 (0.0898) (0.0956) (0.0968) Age^2 0.999 0.999 0.999 (0.00101) (0.00109) (0.0011) Length of stay: 6–10 0.421*** 0.398*** 0.397*** (0.136) (0.138) (0.138) Length of stay: 11–15 0.599 0.555 0.553 (0.217) (0.213) (0.216) Length of stay: 15–1 0.329** 0.285** 0.283** (0.15) (0.142) (0.144) Education level—medium 1.592 1.335 1.337 (0.467) (0.418) (0.418) Education level—high 1.217 1.023 1.024 (0.463) (0.417) (0.417) Training in Italy 2.059*** 1.982** 1.983** (0.524) (0.55) (0.55) Documented at arrival 0.934 0.919 0.919 (20.236) (0.251) (0.251) Peru 0.566* 0.526* 0.525* (0.188) (0.195) (0.196) Romania 1.065 1.368 1.363 (0.375) (0.515) (0.518) Income class: 501–1000 0.756 0.811 0.811 (0.281) (0.324) (0.324) Income class: 1001–1500 1.547 2.038 2.033 (0.678) (0.967) (0.967) Income class: 1501–1 2.169 2.026 2.018 (1.387) (1.416) (1.413) Income decreased since 2008 7.540*** 8.525*** 8.519*** (1.987) (2.468) (2.467) Income security decreased 1.654** 1.636* 1.635* (0.418) (0.444) (0.443) Remittance to income ratio 0.505 0.344 0.349 (0.331) (0.258) (0.269) Mono income HH 1.868** 1.789** 1.794** (0.493) (0.507) (0.512) Receiving remittances 1.507 1.482 1.481 (0.56) (0.584) (0.584) MODELLING THE IMPACT OF THE ECONOMIC CRISIS 15 Variables (1) (2) (3) At least 1 child in Italy 1.795** 1.023 (0.469) (0.325) N. of recipients decreased 11.98*** 11.95*** since 2008 (5.326) (5.331) At least 1 relative arrived in 1.767** 1.751* Italy since 2008 (0.465) (0.512) Sector: primary & secondary 1.17 1.17 (0.487) (0.487) Sector: transport & trade 1.455 1.454 (0.6) (0.599) Sector: domestic & health 2.240** 2.235* (0.921) (0.922) Constant 0.0277** 0.0204** 0.0209** 20.0479 (0.0377) (0.0392) Observations 470 469 469 Standard errors in parentheses ***p , 0.01, **p , 0.05, *p , 0.1 Finally, the family structure in Italy and abroad for some meaningful predictor while holding all has a significant impact on the remittance trend: other variables at their means provide a good having at least one child residing in the same approximation of the change in the probability household in Italy and having undergone at least of experiencing a remittance drop produced by one process of family reunification since 2008 (at a one-unit change in the listed variables. Hence, least one first-grade relative in Italy) have a strong having two otherwise average migrants, one impact on the odds of a remittance decrease. experiencing an income drop since 2008 and the Moreover, a decrease in the number of remittance other not, the probability of the first of having recipients abroad explains the big variation in decreased remittances is 48 percent higher. Also, remittances. This might be a confirmation of the the probability of a remittance drop decreases at effect of family reunification: the number of recip- around 25 percent for two intermediate length-of- ients decreases when they join migrants in Italy, or stay groups while it grows at about 14 percent for changes in the demographic dynamics of relatives the sole income earners in the household (mono- in origin countries (growing up until the working income household). As for family characteristics age or marriage, further migrating in a third coun- in Italy and abroad, a decrease in the number of try, dying, etc.). recipients at origin results in an increase in prob- ability of 47 percent of a decrease in remittances, Again, since understanding what an increase/ while family reunification processes over the decrease in odds means is not easy, predicted last five years increase the probability at around probabilities and marginal effects help disentan- 14 percent. Also, Peruvians show a 216 percent gle the effect of single predictor variables on the probability of decreasing remittances. This might outcome variable. Figure 4 shows adjusted pre- be due, among other things, to the distance dictions for each length of stay, income class and from their origin country. Peruvians are less likely sector of employment, while marginal effects are than Moroccans and Romanians to visit their presented in Table 8. Marginal effects calculated origin household and monetary remittances 16 GREENBACK 2.0 survey 2015 Figure 4: Predictive margins calculated at fixed values of specific variables, holding the other predictors at their means, by sex    Predictive margins at each length of stay, recipients decreased/not decreased    Table 8: Marginal effects—Change in probability of a remittances decrease when the predictor increases by 1 unit Variables Marginal effects (dydx) Income decreased since 2008 0.486*** (0.0552) Income security decreased 0.122* (0.0668) Mono-income HH 0.143** (0.0682) Length of stay: 6–10 20.220*** (0.0787) Length of stay: 11–15 20.138 (0.0886) Length of stay: 15–1 20.303*** (0.116) N. of recipients decreased since 2008 0.468*** (0.0519) At least 1 relative arrived in Italy since 2008 0.137** (0.0698) Peru 20.160* (0.0908) Observations 469 Standard errors in parentheses ***p , 0.01, **p , 0.05, *p , 0.1 MODELLING THE IMPACT OF THE ECONOMIC CRISIS 17 may represent a substitute for money, presents of remittance trends over the same period. Fam- and personal attachment brought directly dur- ily reunification processes and changing family ing a visit. This is also coherent with the fact structures in Italy and in the country of origin that Peruvians register the highest remittance increase the economic needs and expenditures in to income ratio, devoting a high share of their Italy, while migrants receive less and less pressure income to remittances. Summing up, the trend in (demand) from the origin household. income since 2008 is not the only determinant 4 Results and final conclusions I n this paper, we sought to investigate how the economic crisis has shaped the economic condi- tions and transnational behaviors of migrants in while older migrants suffer more than younger generations. The strong sample selection can help explain why sectors of employment and types of Italy over the last five years. Based on a recent occupation are not significantly associated with survey (The World Bank 2014), this paper has income outcomes. Excluding from the sample explored the effect of the economic crisis on those who lost their job and had no income at the income trends and on the flow of monetary time of the survey might have hindered the rela- remittances sent to the families left home among tively worse conditions of typically male sectors three surveyed groups in Turin—Moroccans, such as manufacturing, constructions and trans- Peruvians and Romanians—who represent the ports, in comparison to the domestic and health- largest migrant nationalities in the city and offer care sectors where women are concentrated. a comprehensive picture of the differentiated Moreover sectors and types of occupation differ integration paths in terms of gender, length of the for the prevailing contractual arrangements and migratory experience, labor market specializations average level of job and income security, which and the related economic stability. Consistent we are not able to fully grasp due to the limita- with national and local official data (ISTAT 2014; tions of our data. Fullin and Reyneri 2013), our empirical analysis confirms the negative trends in income and eco- The observed economic instability seems to have nomic stability for the surveyed migrants, which is produced effects on migrants’ capacity to keep also mirrored by decreasing remittances. remittance flows constant over time. Considering monetary transfer to the origin household as one Results show a widespread worsening of the of the most important transnational activities of economic conditions since the outbreak of the migrants, we modelled the individual remittance crisis in 2008, with slightly less than half of the trend since 2008 as a function of migrant’s abil- total sample experiencing a decrease in income. ity to earn and save a share of available income As expected, logistic regression results confirm for remittance purposes and of the type of needs the importance of labor market integration vari- and claims of migrant family members, either left ables in determining income outcomes. Having a in the country of origin or residing abroad with full-time, dependent job with a regular contract the migrant. Hence, we assumed that migrant’s protects migrants from income losses more than remitting capacity is directly linked to the level being part-time employed, self-employed or of economic integration at destination.18 Our with secondary jobs. Also, lower income levels empirical results confirm that economic trends in (below €1,000 per month) are associated with a terms of income size and stability strongly affect higher probability of income drop. Furthermore, remittance trends, irrespective of the income the income trend varies systematically by sex, level. Moreover, migrants in single-income house- age and migration history: women tend to resist holds are more likely to reduce their remittances. more than men to an income drop, while age and Finally, the presence of reverse remittances, which length of stay act in a non-linear, combined way on income trends. A shorter migratory experience 18 Eralba Cela, Tineke Fokkema, and Elena Ambrosetti. 2013. “Variation is, on average, associated with less income mobil- in Transnationalism among Eastern European Migrants in Italy: The Role of Duration of Residence and Integration.” Southeast European and Black Sea ity, hence less probability of a decrease in income, Studies 13 (2): 195–209. 18 RESULTS AND FINAL CONCLUSIONS 19 is particularly relevant in the case of Moroccan complement or substitute remittances in specific migrants, is not significantly associated with a circumstances. Data on personal visits to the ori- reduction in remittances, confirming that trans- gin countries, which are likely to bring additional national flows in both directions can coexist as money and presents, and to reinforce the personal part of reciprocal and bi- or even multi-directional sense of belonging and attachment between the social relations.19 migrant and the origin household (Levitt 2003), would certainly help explain the degree of stabil- Interestingly, the economic conditions of migrants ity of Peruvian remittances, since migrants from are not enough to fully explain remittance trends overseas countries are less likely to visit their and other individual and household characteris- country on a regular basis than migrants from tics help complete the picture. In particular, the European and Northern African countries. structure of the migrant family at origin and at destination is strongly associated with a variation Several limitations to our study must be noted. in remittance flows. Irrespective of income trends, First, our sample is taken from a single Italian city variables which account for migrant integra- and it hardly provides evidence applicable to the tion at destination both in the sense of pursuing whole country. Moreover, the sampling method- additional training and vocational courses and ology and criteria applied produced a selected of undergoing reunification processes explain a sample, which includes only migrants which “sur- big part of the diminishing trend of remittances. vived” in terms of income and remittances since Migrants who have at least one child living in Italy 2008 and do not observe behaviors and charac- as well as those who welcomed the arrival of a teristics of migrants who either lost their job or new family member in Italy through family reunifi- did not send remittances at the time of the survey cation processes over the last five years are more as a control (see The World Bank 2014, 42–43 for likely to decrease remittances. The same signifi- a discussion on sample’s drop-outs). cant relation is proved for migrants who declare a decreasing number of recipients, either due to Nevertheless, our empirical results are consistent new outmigration, to the labor market entry of with the most recent official data on the impact of previous dependent young members or to the the economic crisis on native and migrant workers death of older relatives in the country of origin. in terms of income losses and increasing insecu- rity, especially in the manufacturing, construction Finally, dummy variables for the countries of and transport sectors. Our results in terms of sex origin show differentiated trends in income and are coherent with the prevalence of a gendered remittances among the three subsamples. After division of labor, with women mainly concentrated considering demographic characteristics and type in the domestic, homecare and healthcare sectors. of economic integration into the labor market, income trends of Moroccan are no more worse-off Also, we found evidence that economic conditions than those of Peruvians and Romanians. On the during the crisis hampered the ability of migrants remittance side, instead, Peruvians resist more to keep remittances stable over time. Although than Moroccans and Romanians to a decrease remittance trends are also dependent upon other in transnational monetary flows. 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Journal 12 (2): 308–31. 22 ap p end i x Table 9: Income trend since 2008—Mutinomial logit, base outcome “income unchanged” (1) (2) (3) Variables Decreased Increased Decreased Increased Decreased Increased Income class: 501–1000 20.579 0.891 20.0174 0.929 20.00300 0.964 (0.353) (0.597) (0.413) (0.655) (0.417) (0.658) Income class: 1001–1500 21.378*** 1.261** 20.646 1.167 20.730 1.208* (0.406) (0.624) (0.505) (0.715) (0.520) (0.724) Income class: 1501–1 20.702 1.786** 20.209 1.890** 20.200 1.930** (0.612) (0.805) (0.713) (0.908) (0.721) (0.921) Age class: 30–49 20.107 20.766** 20.134 20.507 20.0915 20.443 (0.330) (0.347) (0.401) (0.407) (0.409) (0.414) Age class: 50–1 20.621 21.488*** 20.661 21.219** 20.641 21.141* (0.413) (0.508) (0.511) (0.582) (0.519) (0.595) Female 20.670*** 0.257 20.231 0.122 20.00675 0.0593 (0.239) (0.282) (0.309) (0.338) (0.379) (0.410) Length of stay: 6–10 1.483*** 0.272 1.396*** 0.218 1.389*** 0.245 (0.311) (0.336) (0.353) (0.362) (0.358) (0.365) Length of stay: 11–15 1.396*** 20.0772 1.408*** 0.0174 1.389*** 0.0424 (0.329) (0.381) (0.386) (0.418) (0.390) (0.421) Length of stay: 15–1 1.378*** 20.0809 1.195** 20.0463 1.141** 20.0387 (0.393) (0.477) (0.471) (0.536) (0.476) (0.540) Income security decreased 1.789*** 20.165 1.802*** 20.154 since arrival (0.268) (0.296) (0.270) (0.296) Mono income HH 0.373 20.492 0.442 20.494 (0.284) (0.353) (0.290) (0.358) Full-time 20.566* 0.0862 20.568* 0.0632 (0.312) (0.378) (0.316) (0.383) Contract 20.482 0.286 20.486 0.279 (0.354) (0.454) (0.358) (0.456) Dependent job 20.774** 0.539 20.642* 0.628 (0.370) (0.499) (0.381) (0.507) Education level—medium 20.0580 0.0771 20.0698 0.0822 (0.315) (0.375) (0.318) (0.376) Education level—high 0.302 1.100** 0.319 1.078** (0.425) (0.468) (0.428) (0.470) Training in Italy 20.0158 20.200 0.00515 20.187 (0.280) (0.321) (0.282) (0.324) Marital status: single 20.00109 20.102 0.00892 20.110 (0.320) (0.357) (0.322) (0.359) Marital status: divorced/ 0.647* 0.158 0.629 0.128 separated (0.382) (0.457) (0.383) (0.459) (continues) Appendix 23 Table 9: (continued) (1) (2) (3) Variables Decreased Increased Decreased Increased Decreased Increased Morocco 0.233 20.154 0.184 20.222 (0.393) (0.425) (0.398) (0.430) Peru 20.584* 21.389*** 20.514 21.382*** (0.323) (0.371) (0.338) (0.387) Sector: primary & secondary 0.172 20.398 (0.437) (0.474) Sector: transport & trade 0.541 20.0551 (0.469) (0.506) Sector: domestic & health 20.159 20.236 (0.429) (0.446) Constant 0.524 –0.851 0.0643 21.269 20.249 21.182 (0.442) (0.643) (0.705) (0.917) (0.763) (0.967) Observations 477 477 477 477 476 476 Prob.  chi2 0.0000 0.0000 0.0000 Pseudo R2 0.0810 0.2149 0.2176 Standard errors in parentheses ***p , 0.01, **p , 0.05, *p , 0.1