Ledeneva V.Yu., Rakhmonov A.Kh. Employment probabilities of migrants and local residents in the labor market of the Republic of Tuva. New Research of Tuva, 2026, no. 3. С. 236-253. DOI: https: ...

Текст статьи на сайте журнала URL: https://nit.tuva.asia/nit/ru/article/view/1721 (дата обращения 20.09.2026)

Abstract

This article examines differences in employment odds between migrants and local residentsin the Republic of Tuva (Russia) within a peripheral and economically constrained regional labormarket. The empirical basis is individual-level microdata from the 2010 All-Russian PopulationCensus (10% sample) harmonized in IPUMS International. The choice of these data is motivatedby their status as the most recent comparable and publicly accessible microdata source that al -lows measurement of migrant status and key socio-demographic characteristics at the individuallevel, enabling statistically valid cross-group comparisons. In order to enhance contemporaryrelevance, the findings are interpreted in light of recent scholarship on migrant incorporation intothe Russian labor market and descriptive administrative series on migration inflows to Tuva for2018–2023, which indicate persistent structural constraints on employment and a predominantlywork-oriented profile of mobility.A binary logistic regression model is applied to estimate the probability of being employed(versus unemployed) among migrants relative to local residents, controlling for age (including aquadratic term), sex, marital status and education (N = 580 economically active individuals aged15–64). Results indicate near-parity: migrants exhibit comparable or slightly higher odds of em -ployment than local residents (OR = 1.05; p < 0.001), although the substantive magnitude of thisdifference is small. At the same time, a stable gender gap is observed (women have lower employ -ment odds), and education remains one of the strongest predictors of employment. These patternsare interpreted as evidence consistent with employment-oriented and selective migration into theregion. They remain relevant for understanding integration mechanisms in a “compressed” labor market. The study isexplicitly statistical (not field-based); future research should test gender selectivity more directly, examine interactionsbetween sex and migrant status, as well as assess job quality and sectoral employment structure.

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