Publications

In this paper, we investigate how the minimum wage has shaped the earnings distribution in Lithuania between 2010 and 2019. We rely on a distribution regression framework and detailed Social Security records to characterize the earnings distribution along with the minimum wage incidence at a monthly frequency. According to our preferred estimates, our results imply that minimum wage increases can explain about 32% (40%) of the decline in total (bottom-tail) earnings inequality and up to 20% of average earnings growth.

Keywords: Minimum wage, Earnings growth, Inequality

JEL codes: D31, J31, J38

Uneven family responsibilities are at the root of gender gaps. Using a new dataset  covering all firm-level agreements signed in Spain between 2010 and 2018, we explore whether the presence of female worker representatives can facilitate the negotiation of family-friendly policies with management. We compare firms that operate under the same set of labor regulations but differ in the presence of women among employee representatives. Our findings suggest that having female representatives at the bargaining table can help transform workplaces to better meet women’s needs and ultimately close the gender gap.

Keywords: women representation, bargaining, family-friendly firms

JEL codes: J16, J32, J53

This paper characterizes the power dynamics of firms in both product and labor markets in Lithuania between 2004 and 2018. We first show that both markets are not perfectly competitive, as both price markups and wage markdowns are far from unitary and homogeneous. Interestingly, we unveil that the Dynamics of these margins followed different patterns. On the one hand, both the dispersijon and the economy-wide markup have increased, indicative of an increase in product market power. On the other hand, we document a decline in monopsony power, as both the heterogeneity and the aggregate level of markdowns have declined. Altogether, our results underline the importance of jointly analyzing product and labor markets when assessing firms’ market power.

Keywords: Firm heterogeneity, Monopoly, Markups, Monopsony, Markdowns.

JEL Classification: D4, E2, J3, L1.

Does competition in the labor market affect wage inequality? Standard textbook monopsony models predict that lower employer labor market power reduces wage dispersion. We test this hypothesis using Social Security data from Lithuania. We first fit a two-way fixed effects model to quantify the contribution of worker and firm heterogeneity to wage dispersion and document that the compression of dispersion in firm fixed effects has been the main source of the decline in inequality over the past 20 years. Using a theory-based relationship, we then leverage variation across sectors and over time to show that a 10 percentage point increase in labor market competition leads to a 0.7 percentage point reduction in the variance of firm-specific wage components. A counterfactual exercise using our preferred estimates suggests that the increase in labor market competition can explain at least 15 percent of the observed decline in overall wage inequality.

Keywords: Wage inequality, Firm heterogeneity, Monopsony, Labor supply elasticity.
JEL Classification: J31, J42, O15.

Using detailed administrative data from Spain, we investigate the impact of having an initial work experience in an employee-owned firm (EOF) versus a conventional business on subsequent earnings. We find that young workers’ exposure to EOFs at the time of labour market entry reduces earnings by about 8% during the first 15 years in the labour market. The selection of individuals with low initial ability in EOFs does not appear to be a relevant channel. Our results seem to be rather related to differences in job mobility and wage returns to experience. On the one hand, we document lower wage returns to experience acquired in EOFs, although no differences in subsequent career progression in terms of promotions. On the other hand, we find that workers who had their first job in EOFs show a strong attachment to such a business model and are less likely to voluntarily leave their employers. Taken together, our findings suggest the existence of nonpecuniary job attributes offered by EOFs that might compensate for lower lifetime earnings.

Keywords: Employee-Owned Firms, Careers, Wages, Job Mobility

JEL Classification: J31, J50, J62

This paper studies the drivers of wage growth in Lithuania over the period 2008-2020. Using administrative data as well as aggregate measures reflecting the state of the economy, we estimate an extended version of a wage Phillips curve. Our reducedform estimates indicate that nominal wage growth was tightly linked to labor market fluctuation over this period. Labor productivity, changes in the minimum wage, and the composition of employment also contributed to wage dynamics. However, we find little evidence that past inflation has been a push factor. To understand the underlying economic primitives behind our findings, we estimate a structural Bayesian autoregressive model. Our structural analysis reveals a significant contribution from aggregate supply shocks, reflecting a stronger relationship between productivity and wages than implied by our reduced-form estimates. Moreover, the historical decomposition reveals that since 2013, wages grew over and above productivity due to rising aggregate demand and labor market disturbances.

This paper evaluates the worker-level effects of a historically large and permanent increase in the minimum wage in Lithuania. Our identification strategy leverages variation in workers’ exposure to the new minimum wage, and exploits the fact that there has been no increase in the minimum wage in previous years, to account for heterogeneous labor market prospects of low-wage workers relative to high-wage workers. Using detailed administrative records to track workers before and after the policy change, we show that the minimum wage hike significantly increased the earnings of low-wage workers. This direct effect was amplified by wage spillovers reaching the median of the income distribution. Overall, we find no negative effects on the employment prospects of low-wage workers. However, we provide suggestive evidence that young workers, highly exposed municipalities, and tradable sectors may be more negatively affected. Taken together, our findings imply an employment elasticity with respect to the minimum wage of -0.021, and an own-wage elasticity of -0.033, suggesting that wage gains dominated employment losses.

Keywords: Minimum Wage, Employment, Wages.

JEL codes: J23, J38, J48.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

In this paper we study how labor market duality affects human capital accumulation and wage trajectories of young workers. Using rich administrative data for Spain, we follow workers since their entry into the labor market to measure experience accumulated under different contractual arrangements and we estimate their wage returns. We document lower returns to experience accumulated in fixed-term contracts compared to permanent contracts and show that this difference is not due to unobserved firm heterogeneity or match quality. Instead, we provide evidence that the gap in returns is due to lower human capital accumulation while working under fixed-term contracts. This difference widens with worker ability, in line with skill-learning complementarity. Our results suggest that the widespread use of fixed-term work arrangements reduces skill acquisition of high-skilled workers, holding back life-cycle wage growth by up to 16 percentage points after 15 years since labor market entry.

Keywords: labor market duality, human capital, earnings dynamics.

JEL codes: J30, J41, J63.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

The use of social contacts in the labor market is widespread. This paper investigates the impact of personal connections on hiring probabilities and re-employment outcomes of displaced workers in Portugal. We rely on rich matched employer-employee data to define personal connections that arise from interactions at the workplace. Our empirical strategy exploits firm closures to select workers who are exogenously forced to search for a new job and leverages variation across displaced workers with direct connections to prospective employers. The hiring analysis indicates that displaced workers with a direct link to a firm through a former coworker are roughly three times more likely to be hired compared to workers displaced from the same closing event who lack such a tie. However, we find that the effect varies according to the type of connection as well as firms’ similarity. Finally, we show that successful displaced workers with a connection in the hiring firm have higher entry-level wages and enjoy greater job security although these advantages disappear over time.

Keywords: Job Displacement, Coworker Networks, Re-Employment.

JEL codes: J23, J63, L14.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper provides empirical evidence on the impact of Covid-19 on unemployment and underemployment in Lithuania. Based on the Labor Force Survey, we document the evolution of the unemployment rate using broader definitions that incorporate the underemployed and marginally attached workers. Our results show that, compared to previous recessions, Covid-19 had a milder impact on the Lithuanian labor market. Moreover, Lithuania fared reasonably well relative to other Eurozone countries. However, the data reveal a substantial increase in marginal workers and underemployment during 2020, with women, young workers and individuals in rural areas being most affected by the pandemic-induced recession.

Keywords: labor market statistics, labor force, unemployment.

JEL codes: E24, J21, J64

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This paper studies the impact of the Great Recession on the relationship between reallocation and productivity dynamics in Lithuania. Using detailed microlevel data, we first document the aggregate contribution of firm exit and employment reallocation to productivity growth. Next, we estimate firm-level regressions to confirm the findings and to perform a heterogeneity analysis. This analysis shows that productivity shielded firms from exit, and that this relationship became stronger during the Great Recession. Moreover, we demonstrate that more productive firms experienced on average lower employment losses, and that this effect was even stronger during the economic slump. Taken together, our results suggest that reallocation was productivity-enhancing during the Great Recession. However, the analysis also indicates that reallocation intensity varied with sector's dependence on external financing or international trade as well as market concentration.

Keywords: firm dynamics, job reallocation, productivity, Great Recession

JEL Codes E24, E32, L11, J23

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.

This document explores the incidence of the minimum wage in Lithuania. The descriptive analysis exploits high-frequency data on monthly labor income coming from Social Security records between July 2013 and July 2020 to characterize (i) the evolution of the monthly minimum wage, (ii) the percentage of workers who earn the minimum wage, (iii) the bite of the minimum wage in the wage distribution, and (iv) the heterogeneity of the findings with respect to gender and age. The evidence shows that the minimum wage was raised 7 times with an average (real) increase of 7.3% and, on average, less than 10% of the workers earn at most the minimum wage but low-pay incidence is around 20%. In terms of the impact of the wage distribution, the minimum wage relative to the average wage in the economy fluctuates between 45 and 50 percent. Females and young workers exhibit a larger low-pay incidence and minimum wage bite.

JEL Codes: J38, J48

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.