Page 95 - Azerbaijan State University of Economics

Fadai Mardanli Mehman, Vildan Zahidkizi Rizayeva: Do Remittances Compensate for the
Labor Market Gaps Created by Emigration?

rate of around 4.3%. However‚ this plateaus at around this level. An R² of 0.750 means
that the variation in the level of remittances over time could explain 75% of the
variation in Kyrgyzstan's unemployment rate over the same period. These results
confirm the inverse relationship between unemployment and remittances: emigration
eased excess supply‚ while consumption supported the domestic economy through
remittances. Nevertheless‚ this outcome should not be seen as a sustainable development
model as it relies on a constant emigration of the working-age population.

The estimated coefficient for the case of Moldova is positive and statistically
meaningful (β = +0.1548). A 1 percent increase in remittance GDP is associated with
an increase of 0.155 percentage points in the unemployment rate. The R² value of
0.569 means approximately 57 percent of the variation in unemployment can be
explained by remittance dynamics. The finding is consistent with the correlation
results above that times of higher remittance inflows did not lead to a proportional
increase in employment. The data show that in a period where remittances were
approximately 30% of GDP‚ unemployment was around 7%‚ but as remittances
dropped to perhaps 15% of GDP‚ unemployment fell to 3-4%. Such patterns could be
explained by long-term labor market dislocations‚ high reservation wages or labor market
detachment of some households. However‚ analysis of remittances in Moldova found
that‚ while remitting was associated with positive household outcomes‚ it was also
associated with lesser attachment to the labor market‚ especially in rural areas (Meyer &
Shera‚ 2017). Though the low intercept of 1.753 should be taken with caution‚ the positive
coefficient suggests that remittances did not incentivize employment within Moldova‚ but
instead reinforced Moldova's reliance on remittance income.

Thus‚ even if we include remittances in Nepal‚ the estimated coefficient is still very
small and statistically indistinguishable from zero (β = +0.0069). In other words‚
remittances‚ if present‚ had no statistically meaningful effect on the unemployment
rate during this period in this country. The R²‚ again almost zero‚ shows that
remittances had virtually no effect on the unemployment rate in Nepal. The intercept
of 10.488 is also very close to the mean unemployment of Nepal. This implies that the
regression line almost has a zero slope concerning remittances. Indeed‚ even though
remittance as a percentage of GDP increased from around 11% in 2002 to 27% in 2016
and even higher in 2024‚ the unemployment rate remained almost unchanged.
Remittances in Nepal seem to have compensated for the shock to household income but
not employment from workers' emigration‚ even though important external resources
have been injected into Nepal. Underemployment‚ a low female labor force participation
rate‚ and lack of job creation in the domestic labor market remain structural issues
(Shrestha‚ 2017). The findings support the view that remittances alone are not sufficient

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