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Abstract

The paper investigates the informalisation of employment among male workers in Kyrgyzstan and explores how migration experience shapes labour market trajectories. Drawing on six waves of nationally representative panel data from the KGZ LiK-Study covering the period 2010-2019, the analysis applies an empirical strategy based on panel-probit models. The dependent variable indicates whether an individual transitions from formal to informal employment between survey waves. Endogeneity of migration choice is controlled by adding Mundlak (1978) corrections. Potential selection bias is accounted for through the inclusion of inverse Mills ratios, derived from a first-stage selection models (survey attrition and emploment participation) identified using an exogenous instrument. The results indicate that sectoral mobility is the strongest determinant of transitions into informal employment. However, return migrants are significantly less likely than non-migrants to become informal following a sector change. This finding suggests that migration experience may disrupt the typical informalisation trajectory. A plausible explanation is that return migrants accumulate financial resources and human capital while abroad, which may help them remain in formal employment even when changing sectors. The results are further supported by robustness checks employing propensity score matching and covariate matching methods.

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Abstract

Large-scale migration of Russian citizens to Kazakhstan in 2022–2023 represents one of the most significant recent cases of a sudden, politically driven mobility in the post-Soviet space. Almaty, as the country’s largest city, became a primary immigration destination, even though a large fraction of it has been transitory.

This paper examines the impact of immigration flows from Russia to regional economy of Almaty city using a simple structural econometric model. We explore the effect of district-level inflows of Russian migrants on various sectors of the city economy at a level of 8 districts of Almaty in 2010-2024, split up to two period: pre-war (2010-2021) and wartime (2022-2024). Sectors of economic activities include professional, scientific, and technical services; management and consulting, information and IT, architectural and engineering, building and office maintenance, creative and cultural industries, advertising, rental, repair, sports and recreation, legal and accounting, real estate, and employment services, all in terms of their monetary values in the respective years. Altogether, our empirical analysis covers a panel of 14 years over 8 districts of Almaty, conducted for twenty urban service sectors. To identify causal effects, we employ a difference-in-differences model, controlling for fixed effects, capital and human resources, and exploit variation in migration flows from Russia before and after the 2022 migration shock. This approach allows us to capture how migration-driven spatial concentration translates into differentiated trajectories of sectoral development across the city districts.

The estimated effects are overall statistically significant, declining effect of migrants for most sectors of the city economy. Specifically, while the overall effect of migrants is positive, returns to scale of Russian migration in pre-war period is mostly negative. This tendency, however, reverses for the war migrants: the difference-in-differences estimator is highly significant and positive for most of the sectors, especially for services. This effect can be attributed to higher average human capital of this wave of migrants, agglomeration effects, and institutional adaptation, especially in such industries as informatics and IT, science and technologies, real estate services and cultural products.

The paper contributes to migration scholarship by offering one of the first quantitative, district-level assessments of post-2022 migration impacts in the CIS context, highlighting how migration reshapes cities through intertwined demographic, economic, and social processes.

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Abstract

This study re-examines a stylised fact: that money sent home by migrants (remittances) helps families start businesses. Using seven years of data from the World Bank’s Listening to the Citizens of Uzbekistan survey—covering more than half a million person–round observations—we examine whether receiving remittances actually increases the likelihood of owning a business or being self-employed.

Our preferred propensity score matching (PSM) estimates suggest a significant negative relationship between remittances and entrepreneurship in the short term. This negative effect is immediate and persists, albeit more weakly, at one- and two-year lags. We test this finding in many different ways, using various definitions of remittances and different groups of households (both with and without migrants), as well as considering return migration. The overall conclusion does not change significantly. However, our econometric models suggest that the likelihood of engaging in entrepreneurship depends on the legality of migration and the destination country.

These results are important for countries such as Uzbekistan, where many families depend on money earned abroad. Remittances seem to be used mainly to cover daily expenses rather than to start new businesses. In order to stimulate local economic growth, policymakers may need to introduce special programmes, such as grants for business plans, improved access to finance, diversification of migration corridors with a focus on more developed countries, and more secure legal pathways for migrants working overseas.

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Abstract

This paper investigates a central puzzle in development economics: why sustained GDP growth does not always coincide with productivity-enhancing structural change. Focusing on two major Central Asian economies—Kazakhstan and Uzbekistan—over 2000–2024, we document that both countries experienced steady increases in output per worker, yet followed markedly different structural transformation paths.

To explain this divergence, we combine aggregate growth accounting, sectoral productivity decomposition, and a shift-share structural change framework across agriculture, industry, and services. Using World Bank World Development Indicators, we decompose output growth into contributions from capital, labor, and total factor productivity (TFP), and then isolate the roles of within-sector productivity growth and labor reallocation (static and dynamic effects).

Our empirical strategy allows us to test whether aggregate growth is driven by productivity improvements within sectors or by the movement of labor toward more productive activities. We show that Kazakhstan’s growth was largely TFP-driven—particularly in the early 2000s—consistent with a commodity-led expansion, but accompanied by weak or negative dynamic reallocation. In contrast, Uzbekistan’s growth was more accumulation-led, with stronger contributions from capital deepening and employment growth, and only post-2012 evidence of positive dynamic structural change.

The results demonstrate that high growth alone is neither sufficient nor necessary for productivity-enhancing structural transformation. We contribute to the literature by showing that the composition of growth—rather than its rate—determines whether structural change supports or undermines long-run productivity gains. These findings have important implications for resource-rich and transition economies seeking to translate growth into sustainable development.