Table 2 shows a summary of basic demographic and labor market characteristics of Russians and migrant (defined as non-Russians) workers. On average, migrants are not very different from Russian workers in age and gender composition. However, they are significantly less schooled, less likely to reside in urban areas, more likely to work in market services, and work longer hours. While 15.7 percent of Russians report to be informally employed, for migrant workers that share is significantly higher at 26.2 percent. They also get paid less per hour and have a 29 percent likelihood of receiving part or all of their wages unofficially, compared to 19 percent among Russian workers. These characteristics indicate that migrant workers are most likely clustered at the lower end of the income distribution.

We find that being a migrant (defined as non-Russian) worker is associated with being an informal worker, but not any type of informal worker. The results in Table 3 indicate that migrant workers are more likely to be working informally (column 1), and this association remains significant even after controlling for occupation characteristics (column 2). However, if dropping from the sample self-employed informal workers, being informal loses statistical significance (column 3). In other words, the Russian / non-Russian status does not involve a higher likelihood of being salaried informal (i.e., salaried but without a contract in their primary job).

Again, the important limitation of this analysis is that traditional surveys do not capture either across regions or illegal migrants. Hence, our results do not definitively conclude that migrant workers do not impact informality in Russia. We find evidence with the data at hand that nonRussians are more likely to work as self-employed informals, but not salaried informals. The analysis involving non-Russians, because of not capturing other forms of migration, should be viewed with the caveat that the share of migrants is likely underestimated in the survey and that a more fine-tuned definition of migrants through better surveys may render rather different results.

# **III. Methodology**

The study of well-being using subjective indicators has grown significantly in recent years. Subjective measures of well-being go from life satisfaction (sometimes called happiness) to job satisfaction, self-assessed health and other indicators of access to basic needs. These measures complement, or contrast, the more conventional estimates of well-being that use objective measures such as GDP per capita, labor incomes or consumption-based poverty measures. The quality of these indicators of subjective well-being can help to discern important aspects of economic behavior and policy (Kahneman & Krueger, 2006). Moreover, many of these studies explore the connection between subjective indicators of well-being (i.e., job satisfaction, life satisfaction, self-reported health) and specific labor market status such as unemployment, selfemployment, commuting to work, volunteer work or informality.<sup>20</sup> Most of these studies test the 20 For a review of the literature <u>on the Economics of Happiness see (MacKerron, 2012).</u> Informal Employment and Worker’s Wellbeing in Russia 16/67