In this paper, we explore the relationship between informality and earnings inequality using the data from the Russia Longitudinal Monitoring Survey (RLMS-HSE) for 2000–2010. We determine that during the entire period, earnings inequality was substantially higher in the informal sector. Informality increases earnings polarization, widening both tails of the earnings distribution. Nonetheless, inequality has declined in both formal and informal sectors. In the formal sector, changes in the distribution of monthly earnings between 2000 and 2010 were primarily generated by changes in the distribution of hourly earnings. In the informal sector, reduction of variation in monthly earnings went through two channels: declining differences in hourly rates and considerable compositional shifts within the informal sector. The results point to the importance of distributional analysis of earnings gaps and explicit accounting for the sector choice.
Informality is a defining characteristic of labour markets in developing and transition countries. This paper analyzes patterns of mobility across different forms of formal and informal employment in Russia. Using the Russian Longitudinal Monitoring Survey household panel we estimate a dynamic multinomial logit model with individual heterogeneity and correct for the initial conditions problem. Simulations show that structural state dependence is weak and that transition rates from informal to formal employment are not lower than from non-employment. These results lend support to the integrated view of the labour market.
This paper tests whether the implementation of a key market-oriented reform in post-Soviet Russia, property rights in land, proxied by the percent of privatized land by region, affected the pace of sub-national economic growth during two unprecedented expansion periods: 2001-2008 and 2010-2014. Individuals gained the Constitutional right to own land in 1993, but implementation was stalled. The pace of land privatization can be explained by arguably exogenous factors such as distance to Moscow, as well as climate and also regional political culture, proxied by concentration of votes in the 2004 presidential election. We show that this rate of land privatization in Russia’s regions was significantly associated with output growth in 2010-2014, confirming the policy importance of this measure for developing economies. Regions where private holdings expanded most rapidly with the enforcement of property rights in land, gained a competitive advantage in the growth process through increased investment in fixed assets and private consumption.
The data of the Russian Longitudinal Monitoring Survey (RLMS) – Higher School of Economics represents one of the few nationally representative sources of household and individual data for Russia. These data have been collected since 1992 and in recent years, thanks to more secure financial and logistical support, have become a resource increasingly drawn upon by scholars and students for national and cross-national studies. In this paper, we examine the extent of non-random attrition in the RLMS and discuss the circumstances under which this might give rise to biases in econometric analysis. We illustrate this with an example drawn from the health sphere.
The transition from plan to market was the largest natural experiment in economics ever. Now, 20 years from the start of transition, all former socialist countries are market economies at the middle stage of economic development, and convergence with neighbours, if not with the developed world, is largely achieved. With hindsight, it is clear that economists have spent too much time debating proper sequencing of reforms and the fine-tuning of reform packages. At the same time, the magnitude of the output and consumption fall in some countries was vastly underestimated, while the benefits of reforms have taken longer to materialize than expected. Successful practitioners of reform praise perseverance during and after the initial setbacks and willingness to make political compromises. At the conclusion of the natural experiment, transition economics has all but vanished as an academic discipline, although it played a crucial role in the formation of modern political economics.
This paper assesses the effect of sub-national institutions on the economic performance of Russia's regions (oblasts, republics, krais and okrugs) from 2001 to 2008, a period of rapid economic advancement and recentralization. Approximating sub-national institutions with the RA Expert index of investment risk, we find that a reduction in investment risk by one standard deviation increases output by 1.4 percent in the short run and 11.9 percent in the long run, suggesting a substantial regional performance gap in government practices, despite intensive political recentralization. Assuming that the main components of effective governance are running satisfactory public health programmes aimed at decreasing overall mortality among the working-age population, creating fair labour market conditions and improving the regional institutional climate to encourage investment in fixed assets, we argue that sub-national institutions remain important for growth in post-Soviet Russia after 2000. This paper contributes to the literature on institutional persistence.
This article conducts a plant-level study of the factors affecting foreign direct investment (FDI) inflow to a large openning economy endowed with specific factor advantages. We conclude that the distribution of FDI in the Russian regions depends on market access and can be most notably by the knowledge-capital framework. Factor endowments built by natural resources are more successful in explaining the location decisions of export-platform affiliates. The impact of natural resources depends on how the availability of these resources is measured. The results reject the crowding-out effects of resource FDI and prove co-location mode, when service investments are attracted to resource-rich regions. Labour cost advantages better explain the preferences of non-trading service affiliates
In this paper we use data from a large nationally representative survey in Russia to empirically estimate the distribution of the burden induced by the military draft. We focus on draft avoidance as a common response to the conscription system ridden by corruption. We develop a simple theoretical model that describes household compliance decisions with respect to enlistment as a function of its pre-draft welfare. We employ the full information maximum-likelihood instrumental variable model to estimate the effect of household characteristics on the probability of serving in the army. Our results indicate that the burden of conscription falls excessively on the poor. Poor, low-educated, rural households are much more likely to have their sons enlisted compared to urban, wealthy and better-educated families. Using the predicted probability of draft avoidance, we estimate the short-term direct economic cost of the draft as lost wages of serving conscripts. Our results suggest that losses incurred by the poor are disproportionately large and exceed the statutory rates of personal income taxes.
Employing a unique database of Ukrainian firms in 2001–2007, we use the external push for liberalization in the services sector as a source of exogenous variation to identify the effect of services liberalization on total factor productivity (TFP) of manufacturing firms. The results indicate that a standard deviation increase in services liberalization within a firm is associated with a 9.2 percent increase in TFP. The effect is stronger for firms with high productivity, bringing about a reallocation of resources within an industry. Industry-level results show that the effect of reallocation on industry productivity is almost as strong as the within-firm effect. The dynamic interaction of services liberalization and TFP through the investment channel reinforces the effect. The effect is robust to different estimation methods and to different sub-samples of the data. In particular, it is more pronounced for domestic and small firms.