Job Market Paper:
“Paths Out of Agriculture: Structural Change, Self-Employment, and Productivity Growth” — Link
Abstract: Poor countries concentrate labor in agriculture, while rich countries concentrate labor in non-agriculture. However, higher non-agricultural employment does not guarantee higher income, as there is still substantial variation in GDP per capita at every level of non-agricultural employment. This paper examines how the paths out of agriculture—“agricultural push” due to agricultural technological advances versus “non-agricultural pull” due to non-agricultural technological advances—shape the patterns of self-employment and income growth in the process of structural change. Using a cross-section of countries and South Korean time-series data, I find that the “push” effect is positively associated with the growth of non-agricultural self-employment, which is, in turn, associated with lower GDP per capita growth. By contrast, the “pull” effect shows the opposite pattern: it is associated with lower growth of self-employment in non-agriculture and higher GDP growth. I develop a theoretical model and calibrate it to Korean data from 1970 to 2015. Counterfactual analysis shows that agricultural and non-agricultural productivity growth produce distinct effects on employment and productivity growth—for example, labor productivity growth would have been 78% higher in the “pull-only” scenario than in the “push-only” scenario between 1970 and 2015, highlighting the need to distinguish between the different drivers of structural change.
Other Paper:
"Nominal and Real Productivity Gap: The Role of Selection"
Abstract: This paper investigates cross-country differences in sectoral productivity between rich and poor economies. Labor productivity is measured in purchasing power parity (PPP) terms to ensure comparability. The analysis begins with the construction of a new, internationally comparable dataset on sectoral value added across countries. This dataset extends the GGDC Productivity Level Database (PLD) and applies the Geary–Khamis (GK) method to maintain coherence in both within-country and cross-country productivity comparisons. Using this dataset, the paper documents the discrepancies between nominal and real sectoral productivity and explores the patterns of sectoral prices across countries. It then develops a theoretical framework with heterogeneous agents to illustrate how selection mechanisms drive the evolution of sectoral productivity. The model demonstrates that the selection mechanism can account for the observed productivity gaps across countries, in both nominal and real terms. Finally, a counterfactual analysis identifies the parameter associated with the selection mechanism that contributes most significantly to the observed results.