Essays in Labor and Development Economics
The dissertation consists of three independent explorations of labor market dynamics in developing countries. I first investigate how minimum wages affect employment and investment decision of firms in India and how they can lead to accelerated automation and offshoring. Then, I investigate how managers of garment production lines in India's largest ready-made garment producer establish informal agreements to deal with worker absenteeism shocks. Finally, I study how Indonesian households learn about their productivity in different sectors of the economy and show that they often spend years, if not decades, in sectors where they are less productive which depresses their earning potentials, but they converge to their most productive sector over time. In the first chapter, "Effect of Minimum Wages on Automation and Offshoring Decisions of Firms: Evidence from India", I study the effect of India's local minimum wages on the production structure of firms in the formal economy. I compile data on the country's numerous minimum wages which vary at the state, year, and industry level, and show that changes to these wages have important effects on firm-level capital investment and employment of different types of employees. The effects depend on the firms' ability to automate and offshore certain tasks. Using a difference-in-difference approach, I show that firms in the average industry, that is, firms in industries neither intensive in routine nor offshorable tasks, continue to invest in machinery and computers at a rate of 8% per year following a minimum wage hike. However, they substitute payroll workers with managers and contract workers less likely to be bound by the minimum wage. Firms in industries intensive in routine tasks that are easier to automate invest 6.1% more in machinery and 4% more in computers, at the expense of payroll workers. Firms in industries intensive in tasks easier to do remotely continue to invest in machinery and computers, but the rate of investment in computers falls by 6.2% following a minimum wage hike, and payroll worker employment falls as well. This suggests that some tasks that combine workers and computers, like data analysis, may be offshored. These results support the predictions of a task-based production model, and indicate that minimum wages have a strong effect on the structure of production at the firm level, leading some towards increased rates of automation and offshoring. In the second chapter, "Absenteeism, Productivity, and Relational Contracts Inside the Firm", joint with other researchers, we study relational contracts among managers using unique data that tracks transfers of workers across teams in Indian ready-made garment factories. We focus on how relational contracts help managers cope with worker absenteeism shocks, which are frequent, often large, weakly correlated across teams, and which substantially reduce team productivity. Together these facts imply gains from sharing workers. We show that managers respond to shocks by lending and borrowing workers in a manner consistent with relational contracting, but many potentially beneficial transfers are unrealized. This is because managers' primary relationships are with a very small subset of potential partners. A borrowing event study around main trading partners' separations from the firm reinforces the importance of relationships. We show robustness to excluding worker moves least likely to reflect relational borrowing responses to idiosyncratic absenteeism shocks. Counterfactual simulations reveal large gains to reducing costs associated with forming and maintaining additional relationships among managers. In the last chapter, "Learning, Selection, and the Misallocation of Households Across Sectors", joint with other researchers, we study the role of labor misallocation (i.e., suboptimal sorting of households across sectors) in explaining low productivity in developing countries. We estimate a generalized earnings equation with dynamic correlated random coefficients, allowing households to learn about their relative productivity across the agricultural and non-agricultural sectors. Estimates show that households sort across sectors on comparative advantage, but learn and converge slowly over time, with many households spending substantial time in a suboptimal sector. Roughly 33% of households are misallocated to start, earning 64% less on average than they could have if they were properly sorted across sectors. Our approach nests several alternative models which can be ruled out, including those without dynamics and/or heterogeneity in relative productivity across sectors. We also evaluate alternative interpretations for the dynamic sorting we observe in the data such as saving out of financial constraints and skill accumulation or learning by doing.