Myeong-Su Yun’s research while affiliated with Inha University and other places

We examine the patterns and correlates of the productivity gap betweenmale- and female-owned enterprises in India’s informal sector.Female-owned firms are 45 per cent less productive than male-owned firmson average, with the greatest productivity gaps observed at the lower end ofthe productivity distribution. We measure a firm’s productivity in terms ofits labour productivity. Using decomposition methods, we find thatstructural effects account for approximately 73 per cent of the productivitygap, with the remainder attributable to differences in observablecharacteristics captured by composition effects. We also find that, amongobservable characteristics, the most important set of factors explaining thegender productivity gap are the characteristics of a firm, such as its size,age, receipt of government assistance, registration with state authorities,contract-based work, and accounting records. Male-owned firms have acompetitive advantage over female-owned enterprises with respect to thesecharacteristics.

The minimum wage has been regarded as an important element of public policy for reducing poverty and inequality. Increasing the minimum wage is supposed to raise earnings for millions of low-wage workers and therefore lower earnings inequality. However, there is no consensus in the existing literature from industrialized countries regarding whether increasing the minimum wage has helped lower earnings inequality. Studying the effect of the minimum wage on the earnings distribution is more complicated in developing countries such as China than in industrialized countries owing to the presence of large informal sectors in urban areas, large pools of surplus labor in rural areas, and difficulties in ensuring compliance with minimum wage legislation. China has recently exhibited rapid economic growth and widening earnings inequality. Since China promulgated new minimum wage regulations in 2004, the magnitude and frequency of changes in the minimum wage have been substantial, both over time and across jurisdictions. The growing importance of research on the relationship between the minimum wage and earnings inequality and its controversial nature have sparked heated debate in China, highlighting the importance of rigorous research to inform evidence-based policymaking. The authors investigate the contribution of the minimum wage to the well-documented rise in earnings inequality in China over the period from 2004 to 2009 by using city-level minimum wage panel data and a representative Chinese household survey, and find that increasing the minimum wage exerts beneficial effects on the earnings distribution—by reducing the earnings gap between the median and the bottom decile—over the analysis period.

We use a new formal, practical, and easily decomposable measure to examine vulnerability to poverty in Tajikistan during the global financial crisis. Our strategy is to estimate a first-order Markov model of household expenditure with the aim of identifying the vulnerability of households to poverty. We use Bayesian methods which allow us to estimate the limiting expenditure distribution. Importantly, by introducing the index of vulnerability as the weighted probability of a household falling into poverty over a given time horizon, we can use the estimated dynamics to assess short, medium and long-run vulnerability. We find that during the “recession transition” almost all households were vulnerable to poverty while almost none were during the “recovery period”. Overall, urban households, more educated households and households receiving remittances from international labor migrants were less vulnerable to poverty. While households with a current or very recent migrant did not have a significantly lower measured vulnerability to poverty, those households receiving remittances from migrants had a lower vulnerability to poverty. Our findings stress that the international labor migration from Tajikistan may not be a reliable means of welfare security for households because external economic shocks and internal political decisions can negatively affect the Russian economy and lead to a reduction of remittance flows to Tajikistan.

The minimum wage has been regarded as an important element of public policy for reducing poverty and inequality. Increasing the minimum wage is supposed to raise earnings for millions of low-wage workers and therefore lower earnings inequality. However, there is no consensus in the existing literature from industrialized countries regarding whether increasing the minimum wage has helped lower earnings inequality. China has recently exhibited rapid economic growth and widening earnings inequality. Since China promulgated new minimum wage regulations in 2004, the magnitude and frequency of changes in the minimum wage have been substantial, both over time and across jurisdictions. The growing importance of research on the relationship between the minimum wage and earnings inequality and its controversial nature have sparked heated debate in China, highlighting the importance of rigorous research to inform evidence-based policy making. We investigate the contribution of the minimum wage to the well-documented rise in earnings inequality in China from 2004 to 2009 by using city-level minimum wage panel data and a representative Chinese household survey, and we find that increasing the minimum wage reduces inequality – by decreasing the earnings gap between the median and the bottom decile – over the analysis period.

Among the most distinctive features of Indian caste system is the close link between castes and occupations, especially in rural India, with Dalits or Scheduled Castes (SCs) clustered in the least well-paid and most socially degrading occupations. We use several rounds of quinquennial surveys from the National Sample Survey Organisation to assess whether the historic relationship between caste status and occupational segregation has been weakened. We find that the occupational structure of the SC households is converging to that of the non-scheduled households. However, we do not find a similar occupational convergence for the Scheduled Tribes households.

Using normalized regression equations, we propose an alternative estimator of industrial gender wage gaps which is identified in the sense that it is invariant to the choice of an unobserved non-discriminatory wage structure, and to the choice of the reference groups of any categorical variables. The proposed estimator measures the pure impact of industry on gender wage gaps after netting out wage differentials due to differences in characteristics and their coefficients between men and women. Furthermore, the proposed estimator is easy to implement, and hypothesis testing is straightforward. We compare the proposed estimator with existing estimators using samples from the 1998 US Current Population Survey.