According to the World Bank Outlook Report, remittances are one of the largest sources of external finance in developing countries, into which in 2013 the total flow of remittances was more than 404 billion dollars. That level of remittance is expected to rise to 516 billion dollars by 2016.1
In 2013, officially recorded international remittances to households in Ukraine were more than 8.5 billion dollars.2 In terms of economic development, one of the main questions, aside from the key determinants of the size of remittances, is, ‘how are remittances spent in the receiving country? Is that money spent entirely on consumption, or is some of it invested, for example in securities?’
Moreover, political instability in Ukraine and uncertainty about its economic future might have a significant effect on personal investments. Major political and governmental changes, like revolutions or coups d’état might have a significantly negative impact on capital investment, whether human capital or financial.3
Researchers and policymakers tend to have diverse and rather pessimistic views of how remittances are actually used and of their impact on economic development.4A widespread belief and a major reason for the general pessimism about the effect of the use of remittances is that migrants have no strong desire to invest in productive enterprises in their home country, but would rather use their money for consumption.5 For example a report by the European Investment Bank states that remittances are used mainly for ‘daily expenses and therefore do not have large developmental impact’.6
Generally, there are a number of different views on both the expenditure channels and the economic influence of remittances in the receiving country. First, remittances are assumed to be spent at the margin; no difference exists between remittance income and other types of income. A second view is based on the idea that remittances might cause changes at the level of individual households, which would decrease their development impact. The third view holds that remittances actually have a positive effect on the level of personal investments in human and physical capital. Political instability, internal shocks, and social conflict generally create significant uncertainty about the determinants that are crucial to investment decisions. A change of Government, for example, might harm investment decisions and lead to an unstable incentive and policy framework.7
An unstable political situation leads to an economic environment that might be expected to cause a decrease in remittances, which could in turn cause the expenditure patterns of a household to change;8 and Ukraine has experienced major political changes during the last decade. Fraud uncovered during the 2004 Presidential Election led to the ‘Orange Revolution’, and the resulting major changes to political power exerted a significant influence on everyone’s expectations for the country’s future. According to a poll conducted in 2004 by the Kiev Institute of Sociology—just a week after the final round of the Presidential Elections—the majority of Ukrainians (67%) expressed either trust or hope in the newly elected president, Mr Yushchenko. The results of the elections are presented in Figure 1.
However, the greatest trust in Ukraine’s new leader was shown by Western and Central regions of Ukraine (86% and 85% respectively) with the Southern regions next (54%). The only places where the majority did not express faith in the new president’s ability were the Eastern regions, where 39% said they trusted Yushchenko while 46% said they did not.9 The economic expectations of Ukrainian emigrants who followed events in Ukraine from abroad during the 2004 elections may be expected to be similar to those results. Emigrants from the eastern regions of Ukraine were perhaps uncertain about the political and economic situation there after the Orange Revolution and might have been keener to send money to their relatives in Ukraine. On the other hand, more optimistic emigrants from Western Ukraine might have begun to send larger sums of money with the intention of its being invested in the Ukrainian economy, for example by helping finance new businesses, or investing in bonds or property.
In its exploration of the effects of the 2004 Presidential Elections and the Orange Revolution on individual decisions about expenditure on remittances this paper will examine the influence of that political instability on the final use of remittances by households throughout Ukraine. More precisely, the results of the nationally representative household survey in Ukraine are used to explore how individuals chose either to invest or to save or donate money and how those decisions depended on individual political views and future expectations.
The main question is whether individuals who supported or even were involved in the Revolution (the ‘pro-Orange’ group) and were optimistic about the future of Ukraine after the Orange Revolution, saved or donated more than those—sometimes referred to as the ‘pro-Blue-Whites’—who did not support the Revolution. We shall look too at what influence the amounts of remittances received from relatives or friends outside Ukraine had on decisions to save or donate money. In addition to that main research question we shall try to see how those amounts of remittances received in Ukraine depended in the first place on the individual political views and general characteristics of the receivers, like level of education and income, geographical region, or language spoken, for example.
The gradual increase in remittances sent by migrants has created increasing attention on them as a potentially important source of investment capital and foreign exchange, alongside private capital flows, foreign aid, and debt.10 For this research we looked too to the question of how far investment for economic growth depends on remittances.11 Existing literature on remittances and investments provides an analysis of how far savings, investments, financial development, and economic growth depend on the receipt of remittances.12
Patterns of spending of remittances became a lively topic for debate over the last decade. McKenzie and Sasin argued that researchers should try to determine whether remittances are spent mainly on consumption or on investment.13Chami et al. have identified three stylised facts of remittances, the first being that ‘a significant proportion, and often the majority, of remitted funds are spent on consumption.’ Their second observation was that ‘a significant, though generally smaller, part of remittances does go into uses that we can classify as saving or investment.’ Third, they say that ‘the household saving and investment that are done using remittances are not necessarily productive in terms of the overall economy.’14
Tabuga used a household survey in the Philippines to provide mixed evidence of the impact of remittance inflows.15 That research found that a large proportion of transfers from abroad is usually spent on everyday consumption, on things like consumer goods or leisure, but that in addition remittance inflows increase the money spent on education and housing. In another paper by Castaldo and Reilly the authors underline that Albanian households which receive international remittances tend to spend significant sums of money on consumer durables and utilities and proportionally rather less on food, when compared with households lacking such financial support.16In short, a larger proportion of household expenditure goes on investment-type goods, in households which benefit from remittances. The share of a household’s expenditure allocated to ‘investment is higher in households with migrants than in otherwise similar households without migrants, while the proportion of consumption expenditures is lower.’17 Those results are confirmed by Zarate-Hoyos who explored data from Mexican households and found that remittance-receiving households spent significantly on investments.18 Zarate-Hoyos went on to add that the apparent difference in consumption patterns for urban and rural areas might be explained by basic lack of rural infrastructure, rather than any great differences in individual character.
The IMF World Economic Outlook states that remittances have a positive effect on the level of personal investment in both human and physical capital.19On the other hand, Clement in his research on Tajikistan has stated that neither internal nor external remittances have any positive effect on any type of investment expenditure.17 In the case of Albania, Cattaneo found that remittances had no significant impact on human capital investment.20 However, many studies from a different research context have indeed found evidence that remittances and migration do have a significant and positive effect on how much is spent on education. For example, Kifle explored data for Eritrea and found that households receiving remittances from abroad tended to spend more on education than did households that did not receive remittances.21
Political instability, high risk, and low levels of law and order and other general risks in a remittance-receiving country seem to create an environment detrimental to investment. The irony is of course that there is much more need of remittances during any crisis, so it might be that remittances sent to the home state actually increase at such times. Moreover, investment opportunities in either receiving or sending countries might have an effect on remittances sent. A greater probability of positive returns on investments in the receiving country might increase migrants’ willingness to invest in their home country, and might influence the amounts of any remittances they do send.22
The influence of remittances on amounts of money dedicated to investment in the receiving country is a widely discussed topic. The empirical analysis presented in this paper is applied to Ukraine and is in line with previous studies. Ukraine is a country with a high level of international remittances.
Data and Methodology
For this research we used data from the Ukrainian Longitudinal Monitoring Survey (ULMS). The data were collected during three waves of the survey under the terms of a programme known as ‘Labour Markets in Emerging and Transition Economies’ by the Institute for the Study of Labour (IZA). The ULMS currently consists of data samples for three waves, from 2003, 2004, and 2007.23The first wave from 2003 consists of more than 8,600 respondents, but for this research I have used the dataset from the third wave, a decision I took because of the structure of the survey and which will be explained below.24
The main blocks in the household and individual parts of the ULMS are described in Tables 1 and 2 (the tables were taken from Lehmann et al.). Table 1 shows the main blocks in the household questionnaire according to ‘wave’. Table 2 shows the content of each individual part of the survey, again by wave. For wave 3 two subjects were added, one being the presidential elections in 2004 and including questions about the Orange Revolution; and there was one question on remittances.25 Due to the specification of the research question for this article, the household and individual questionnaires for wave 3 were merged. Moreover, in order to create a particular dummy variable, to show whether any member of a given household emigrated before 2004 (EMIGRATEDBEFORE2004), use was made of certain data from wave 2.
Source: Lehmann / Murajew/ Zimmermann, 2012, 7.
Source: Lehmann / Murajew/ Zimmermann, 2012, 8.
As outlined above, the dataset for the third wave (2007) was used for this research, because it includes two new modules in the individual survey: a module on the political attitudes of people in connection with the Orange Revolution and a module on the risk and time preference attitudes of individuals.
Answers to the new questions on political attitudes in the survey show the participation of Ukraine’s residents in the Orange Revolution, and they detect information on the participation and motives of respondents. Respondents were also asked to reveal their political preferences, i.e. whether they supported the Orange Revolution or whether they sympathised with the pro-Russian Party of Regions. They were also asked their views on the future political and economic prospects of Ukraine.
The initial ULMS sample (wave 2003) includes 8,641 working age individuals in 4,055 households. The third wave survey used here includes 6,774 individuals from 3,101 households. There were no additions to the observed sample between the second and third waves, but new households might appear due to splitting of the old ones, for example by marriage, or because children had meanwhile reached adulthood or were now incorporated into the survey having reached the age of 15, and so on.
For the purpose of the current research individual and household datasets were merged using a household code for the year 2007 as a corresponding point. Finally, after several dummy variables had been created and as a consequence the data cleansed of empty variables, the size of the data sample used for this research was reduced to 3,084 observations.
Definition of Variables
The research examines household expenditure on savings, payments to higher education establishments, and any donations to public foundations, churches, or other religious organisations.
The dependent variables are Remittances received (whether a household received any money or remittances from any non-members of the household), Savings (whether a respondent saved any money in 2007), Donations (whether a respondent donated any money to public foundations/churches/religious organisations in 2007), and Education, which takes values of ‘zero’ or ‘one’ to indicate whether the respondent saved or donated money or spent anything on education during the thirty days before the interview. Education is here defined by two variables: Payment for education and Payment for training meaning whether respondents spent anything on either of those during the thirty days prior to the interview.26 Table 3 presents some descriptive statistics for the main outcome variables mentioned above with respect to each individual’s characteristics, including political views and where they lived.
The explanatory variables include the set of ‘Orange Revolution’ characteristics (political views, participation in political activities, satisfaction with the result of the election results etc.), personal characteristics (age, gender, language spoken, region, number of children in household etc.) and the financial situation of the household (financial prospects, monthly income, etc.). Remittances received are also a binary variable, showing whether a household received any money transfers from anyone not a member of that household in the twelve months prior to the interview. Explanatory variables for remittances are similar to those from the main regression. An ‘instrumental’ variable for the remittances is the Movedouthh dummy variable which is given as equal to ‘one’ if at least one member had moved out of the household (remaining within Ukraine) since the last interview (i.e. during the last 3 years). Alternatively, the second possible instrumental variable is Movedoutsidehh, which is ‘one’ if at least one member moved out of the household to live outside Ukraine in the three years since the last interview. Moreover, in addition to Moved out/outside as dummy variables, an explanatory variable was added to show whether an individual from a household emigrated before 2004 or before 2007. The ‘region’ variable was created like this: the Autonomous Republic of Crimea with Dnipropetrovsk, Donek, Kherson, Kharkiv, Luhansk, Odessa, Mykolaiv, and Zaporizhzhia oblasts27 make up the Eastern region, whereas Cherkasy, Chernihiv, Chernivtsi, Ivano-Frankivsk, Khmelnytskyi, Kiev, Kirovohrad, Lviv, Poltava, Rivne, Sumy, Ternopil, Vinnytsia, Volyn, Zakarpattia and Zhytomyr oblasts are considered to be Western Ukraine.
As Birch states, residents of the industrialised and heavily Russian east of Ukraine have been found to be politically more left-wing and pro-Russian,
According to the All-Ukrainian Population Census, the total Ukrainian population, in 2001, was 48,457,000, of whom 22,441,000, amounting to 46.3%, were men with 26,016,000 women, amounting to 53.7%. Ukrainian was considered their first language by 67.5% of the total Ukrainian population, which is 2.8 percentage points higher than given in the census of 1989. By contrast, Russian was recognised as their first language by 29.6% of the population, 3.2 percentage points lower than in the previous census. Figure 1 shows a map of language usage in Ukraine’s oblasts.
After the Orange Revolution of 2004, major changes were made to political power in Ukraine in 2005, and as a result it is possible that optimistic feelings of people who had supported the ‘Orange government’ might have stimulated support for Ukraine’s economy from some of those individuals in the expectation that they would have opportunities to make a profit, or by investing their savings. The main research question considered was whether the political orientation of individuals, whether men or women and whether in receipt or not of remittances, influenced investment decisions during the transition period in Ukraine in 2004. I checked too whether individuals who supported the Orange Revolution and the new government were optimistic about Ukraine’s economic environment and saved or donated more than people who opposed it. Consideration was also given to the influence of the general personal characteristics of individuals on the size of remittances. For that I considered things like region of origin, their education, age, language, whether they had relatives outside Ukraine, for example.
In order to assess the probability of receipt of remittances from abroad, I used a model similar to Merkle / Zimmermann.29 The research question explored by analysing that hypothesis is whether those respondents who felt optimistic about Ukraine’s future after the Orange Revolution and the final stage of the presidential elections saved or donated more money in physical capital. The second research question examined was whether the attitudes of respondents to the winning ‘Orange’ side—meaning whether they were supporters or opponents of it—has a significant effect on their decisions either to save or donate.
The results of estimated benchmark models (marginal effects) for remittances are shown in the Annex.30 Both instrumental variables–Moved out from the household and Moved outside Ukraine– were found to be significant on a 10% significance level and positive (one unit increases in these variables lead to an increase by almost 3.7 percentage points in the probability of receiving remittances). That shows that respondents were more likely to receive financial help from outside their households if there was at least one member who had moved either to another country or even to another city in Ukraine. However, the variable that shows whether there was at least one member who had emigrated before 2004 was found not to be significant. On the other hand, the variable showing whether at least one member had emigrated after 2004 but before the Orange Revolution in 2007 was found to be both highly significant and positive. Clearly then, it seems that people who had emigrated even just a couple of years before the Orange Revolution had been sending remittances to their families. Our results show too that individuals were investing those remittances in human capital, for both Personal political views and Paying for education were found significant in all models. Even though Paying for education was found to be negative (approximately - 1.2 percentage points), Payment for training classes proved positive (approximately 1.5 percentage points). None of that provides concrete results to allow any estimate of how far investment in human capital depends on the likelihood of receiving remittances. However, it can be stated firmly enough is that remittances do indeed have a significant effect on human capital, which tends to corroborate the results of previous research.31
The probability of receiving remittances showed a negative and significant correlation with Personal political views, namely a decrease of approximately seven percentage points. Those results show that individuals were less likely to have received remittances if they supported Yanukovych the ‘Blue-and-Whites’, which might show that Yushchenko was more popular with emigrants than was Yanukovych.
Another interesting result concerns the language variable, which proved to be significant and negative, at around - 5 percentage points. That was a rather controversial finding, showing that Ukrainian speakers were less likely than Russian-speakers to have received remittances. Ukrainian statistics show that proportionally more emigrants had left from the east of Ukraine, so the results for the language variable set us thinking about exactly who sends remittances to relatives in Ukraine, since it was impossible to track the countries from where remittances were sent.
Tables 2.a and 2.b present the results of estimates of remittances separately for the Ukrainian - and Russian-speaking populations.32According to the results for marginal effects, the Ukrainian-speaking population were less likely to have been sent remittances if they supported the ‘Blue-and-Whites’. Moreover, the likelihood of a household’s receiving remittances depended positively on the emigration of at least one member of it (17 percentage points increase in probability). For Russian-speaking respondents the only significant variable was the dummy showing a 0.19% increase in the likelihood of receipt of remittances if a member of that household had emigrated.
Estimations of the four other benchmark models for Savings, Donations, and Investment in Human Capital are presented in Tables 3.a-4b.33 Results suggest that the probability of receipt of remittances does have a significantly positive effect on all dependent variables. In the cases of savings and paying for education, remittances have a negative effect (9.7 and 7.6 percentage points respectively). On the other hand donations and paying for training classes are positively correlated with remittances (5.6 and 1.67 percentage points respectively). Together, those figures show that individuals are able, out of altruism, to devote funds to both human and personal capital investments and to help others make a future for themselves.
Regional and language variables were found to be significant for different models. For example, Ukrainian speakers are more likely than Russian speakers to make donations to pay for training, but on the other hand, respondents from western regions of Ukraine proved less likely to save, or to invest in human capital. In general, estimated results show that those who voted for Yanukovych were less likely to receive remittances from outside the household. Then again, Ukrainian speakers from eastern regions were more likely to receive money.
I was unable to confirm one of the main hypotheses about the Optimistic views of respondents. For almost all dependent variables, except spending on education, Optimistic views were in fact found to be both negative and significant. Our results were therefore the opposite of our model’s expectations, which might be explained by the fact that with a change in the political orientation of Ukraine after the Orange Revolution, ‘pro-Orange’ individuals perhaps felt less optimistic about the future of Ukraine and so decided not to save money. On the other hand, those individuals who were pessimistic about Ukraine’s future after the political change in 2004 might have invested more in their own or their children’s human capital by helping to fund things like a university education, or some specific training course or a variety of training courses in the hope of improving prospects.
Estimating the models separately for Ukrainian - and Russian-speakers did not change the results significantly. Ukrainian-speaking respondents were more likely to receive remittances from family abroad if those respondents were intending to save the money rather than use it for donations (9 vs. -7.13 percentage points). The ‘Region’ variable was found to be negative and significant for all estimated models. For Russian-speaking respondents, the results show that few factors influence respondents’ decisions to save/donate or invest in human capital. Remittances seem to have significant influence only on the likelihood of saving, similarly to the ‘Region’ variable.
This article has explored individual expenditure and the likelihood of receiving remittances from abroad against the political backdrop of the Orange Revolution and the Presidential Elections in Ukraine in 2004. The results of the nationally-representative household survey in Ukraine were used to compare individual decisions to invest in relation to their political views and expectations for the future. The main question under consideration was whether ‘pro-Orange’ respondents who were optimistic about the future of Ukraine after the Orange Revolution invested more money in long-term assets than did opponents of the Revolution. We found that the political views of respondents have no significant effect on their decisions to save or donate money, but that their political orientations did have a significant effect on the likelihood that they would receive remittances. A respondent’s vote for Yushchenko meant that that individual was less likely to have been in receipt of remittances from outside the household.
A respondent’s likelihood of obtaining financial help from outside the household seemed to have a highly significant but negative effect on that individual’s decision to donate money in future. In general, it can be stated that political instability had no significant effect on individual decisions to save or donate money, although for some respondents their own political views had a significant effect on how likely they were to receive remittances, and there are two theories which might explain that. First, family ties do matter to anyone thinking of sending money to family members living in a foreign country. Secondly, in our survey people proved least likely to send money to individuals who had supported the winning political party. It should be added that the probability of future spending on human capital had an ambiguous effect on the probability of a respondent’s receiving additional financial remittances. Paying for education was found to have a negative effect on remittances, while by contrast payment for professional training had a positive effect.
Migrant remittances in general have a significant influence on savings and donations in the receiving country and might stimulate an accumulation of capital in labour-exporting countries. My findings from the research laid out here suggest that remittances are likely to contribute to economic development because they encourage recipients to save money or invest it in capital accumulation in the country of origin of the senders of the remittances. Overall, the results of this paper are in line with previous research suggesting that the impact of remittances in a country receiving them will depend on the final use to which recipients put them, as well as on the size of the emigrant population.
The problem of the collection and control of international remittances should receive closer attention from international institutions. There is too little interest in the private and unofficial channels of remittance transactions that still prevail especially among senders from developing countries. The full effect of remittances on investments, development and a country’s economic situation must all be more thoroughly investigated, so that the significant levels of remittances sent through unofficial channels can be properly taken into account.
Policymakers and international institutions worldwide, such as the IMF and the World Bank, are indeed beginning to show more interest in the matter of the dependency of international migration and remittances on savings in the country of an emigrant’s origin. These are considered to be second or third-level effects of remittances, but the question of their overall effect on a country’s economy and whether remittances can have an influence on the economic development of ‘countries of origin’ has not been especially popular in the recent literature. However, I might well decide to review it myself in some future research.
Dilip Ratha et al., Migration and Remittances. Recent Developments and Outlook, World Bank Migration and Development Brief 22 (April 2014), https://siteresources.worldbank.org/INTPROSPECTS/Resources/334934-1288990760745/MigrationandDevelopmentBrief22.pdf. All internet references were accessed on 29 January 2016.
National Bank of Ukraine, External Sector Statistics, http://www.bank.gov.ua/doccatalog/document?id=20008703.
Dilip Ratha, The Impact of Remittances on Economic Growth and Poverty Reduction, Migration Policy Institute (MPI) Policy Brief 8 (2013), 1-13; Richard H. Adams, Jr./ Alfredo Coecuecha / John Page, Remittances, Consumption and Investment in Ghana, World Bank Policy Research Working Paper Series, February 2008, http://siteresources.worldbank.org/INTINTERNATIONAL/Resources/1572846-1253029981787/6437326-1253030181441/Adams_ Cuecuecha_Page.pdf.
Jacqueline Barendse et al., Study on Improving the Efficiency of Worker’s Remittances in Mediterranean Countries. European Investment Bank, 2006, 136, http://www.eib.org/attachments/country/femip_workers_remittances_en.pdf.
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Democratic Initiatives / Kyiv International Institute of Sociology (DI/KIIS), The Opinions and Views of the Population of Ukraine, February 2005, http://dif.org.ua/ua/polls/2005_polls/erjjwepgjkwepgeg.htm.
World Bank, Global Economic Prospects 2006. Economic Implications of Remittances and Migration. The World Bank, 2005, http://documents.worldbank.org/curated/en/2005/11/6413332/global-economic-prospects-2006-economic-implications-remittances-migration; Dilip Ratha / Sanket Mohapatra, Increasing the Macroeconomic Impact of Remittances on Development, World Bank 2007, 1-11; Dilip Ratha, Leveraging Remittances for Development, Migration Policy Institute (MPI) Policy Brief June 2007, http://www.migrationpolicy.org/research/leveraging-remittances-development.
Slobodan Djajić, International Migration, Remittances and Welfare in a Dependent Economy, Journal of Development Economics 21, No. 2 (1986), 229-234; Slobodan Djajić, Emigration and Welfare in an Economy with Foreign Capital, Journal of Development Economics 56, No.2 (1998), 433-445; Christos Nikas/Russell King, Economic Growth through Remittances. Lessons from the Greek Experience of the 1960s Applicable to the Albanian Case, Journal of Southern Europe and the Balkans 7, No.2 (2005), 235-257; Alexei Kireyev, The Macroeconomics of Remittances. The Case of Tajikistan, IMF Working Paper (January 2006), 1-26, https://www.imf.org/external/pubs/ft/wp/2006/wp0602.pdf; Carlos Vargas-Silva/Peng Huang, Macroeconomic Determinants of Workers’ Remittances. Host Versus Home Country’s Economic Conditions, Journal of International Trade & Economic Development 15, No. 1 (2006), 81-99.
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Ralph Chami / Connel Fullenkamp / Samir Jahjah, Are Immigrant Remittance Flows a Source of Capital for Development?, IMF Working Paper WP/03/189 (2003), 1-48, https://www.imf.org/external/pubs/ft/wp/2003/wp03189.pdf.
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Temesgen Kifle, Do Remittances Encourage Investment in Education? Evidence from Eritrea, GEFAME Journal of African Studies 4, No. 7 (2007), http://quod.lib.umich.edu/cgi/t/text/text-idx?c=gefame;view=text;rgn=main;idno=4761563.0004.101.
Hartmut Lehmann / Alexander Muravyev / Klaus F. Zimmermann, The Ukrainian Longitudinal Monitoring Survey. Towards a Better Understanding of Labor Markets in Transition, IZA Journal of Labor & Development 1¸ No. 1 (2012), 1-15; Institute for the Study of Labor (IZA), The Ukrainian Longitudinal Monitoring Survey (2003-2007), International Data Service Center, DOI: http://dx.doi.org/10.15185/izadp.7090.1.
Also, the respondents’ decision to buy bonds/securities in the year 2007 was supposed to be one of outcome variables in the research, but after the data was obtained it was dropped out due to lack of observations.
Oblast is a type of administrative division of Ukraine. The term is analogous to region. whereas those of the more agricultural and ethnic Ukrainian west tend to favour market reforms and closer ties with Western Europe.28 The difference in the political orientations of eastern and western Ukraine was what led to Ukraine’s division during the Orange Revolution, and Ukrainian emigrants from the different regions had different expectations both before and after the revolution. Those differences might have been what led to the differences in remittance patters.
Full model specification can be found in the Annex, available at DOI: http://doi. org/10.15457/soe_2016-1-1_v2.
Cynthia Bansak / Brian Chezum, How do Remittances Affect Human Capital Formation of School-Age Boys and Girls?, The American Economic Review 99, No. 2 (2009), 145-148; Pablo A. Acosta / Pablo Fajnzylber / Humberto Lopez, The Impact of Remittances on Poverty and Human Capital. Evidence from Latin American Household Surveys, World Bank Policy Research Working Paper 4247, 2007; Carla Calero / Arjun S. Bedi / Robert Sparrow, Remittances, Liquidity Constraints and Human Capital Investments in Ecuador, World Development 37, No. 6 (2009), 1143-1154.