Research

with Yan Liu and Shu Yu

Abstract: This study examines the impact of Generative AI shocks on labor market demand using LightCast data in the US. By analyzing job posting trends across various occupations, we identify decline in demand driven after the emergence of ChatGPT. Our findings provide insights into how AI influences labor dynamics, highlighting the risk of displacement effect of Generative AI on labor market.

with Caglar Ozden

Abstract: How do large-scale infrastructure projects shape internal migration and labor mobility in developing countries? India’s Golden Quadrilateral (GQ) highway, with construction starting in 2001 and largely completed by 2006 to connect major economic hubs, provides a unique case to answer this question. Using 2001 and 2011 census data, this paper explores the causal link between reduced travel times and internal migration patterns. We begin by documenting how proximity to the GQ influenced migration rates using a difference-in-differences approach with instrumental variables, estimating a 17\% increase in migration for corridors with destination and origin within 50 km to the GQ. Using a modified gravity model, we, then, establish the causal effects of travel time savings on migration flows. Notably, the effect varies by travel distance, as improved infrastructure disproportionately lowers barriers for longer-distance migration. Additional analysis explores demographic heterogeneity and finds that older and lower-educated workers benefit more from the reduced travel time. Overall, we estimate that excluding population growth, 32\% of the total increase in migration flows between 2001 and 2011 is directly attributable to the GQ.

Conference presentations:

5th Annual Infra4Dev Conference, Guangzhou, China, May 2025

Asian Economic Development Conference, Beijing, China, July 2025

with Yan Liu

Abstract: This paper offers the first comprehensive, global analysis of generative AI adoption and usage, using novel data sources including website traffic and Google Trends. The paper also examines country-level factors driving the uptake and early impacts of generative artificial intelligence on online activities. As of March 2024, the top 40 generative artificial intelligence tools attract nearly 3 billion visits per month from hundreds of millions of users. ChatGPT alone commanded over 80 percent of the traffic, yet its reach remains less than two percent of Google’s. Generative artificial intelligence users skew young, highly educated, and male, particularly for video generation tools, with usage patterns strongly indicating productivity-related activities. Generative artificial intelligence has achieved unprecedentedly rapid global diffusion, reaching almost all economies worldwide within 16 months of ChatGPT’s release. Strikingly, middle-income economies account for over half of global generative AI traffic, a disproportionately high share relative to their economic size, while low-income economies contribute less than 1 percent. Country level adoption intensity is strongly correlated with the share of youth population, digital infrastructure, English fluency, foreign direct investment inflows, services’ share of GDP, and human capital. Finally, the paper also documents disruptions in online traffic patterns and emphasizes the need for targeted investments in digital infrastructure and skills development to fully realize the potential of artificial intelligence.

Conference presentation:

HKMA-Aof/HKIMR-CEPR GenAI conference, Hongkong, April 2025

with Laurent Bossavie

Abstract: Despite the importance of temporary migration from South Asia to overseas destinations, the labor market outcomes of return migrants in this region of the world have been understudied. This paper fills this gap by examining systematic differences between the labor market outcomes of return migrants and nonmigrants in Bangladesh, Nepal and Pakistan with nationally-representative survyes which include information on past migration overseas. We use regression analysis and study the following four dimensions: (i) labor force status (ii) sectoral choice (iii) employment type (iv) earnings. The paper finds that return migrants are somewhat less likely to be employed than nonmigrants, which is mainly driven by returnees close to retirement who returned at an older age. As evidenced in other contexts, return migrants are more likely to become self-employed compared to nonmigrants in Bangladesh and Pakistan, and self-employed returnees are also more likely to hire paid employees and to be engaged in non-farm activities, compared to nonmigrant entrepreneurs. Among the minority of returnees who become paid employees, the wage premium earned relative to nonmigrants is positive but small compared to estimates reported in other contexts. The returnee wage premium, however, is larger in the construction sector where the majority of return migrants were employed overseas.

with Maggie Liu, and Caglar Ozden

Abstract: How local labor markets are linked and how wage spillovers are transmitted across markets via labor flows  have important implications for economic development and poverty reduction. We explore these issues in the context of India with its low internal migration rates and wide income disparities. To guide our analysis, we construct a spatial equilibrium model of endogenous labor mobility where the migration decisions are based on the standard random utility model. We show that the resulting equilibrium distribution of wages across markets can be estimated by a spatial autoregressive (SAR) specification where the elements of the weight matrix are functions of the bilateral migration flows. We use internal migration and wage data from India to estimate the extent of the spatial interdependence of wages while accounting for the endogeneity of migration patterns. Using the estimated parameters, we simulate counterfactual scenarios with exogenous productivity shocks and lower migration barriers. We show that productivity shocks spillover to other markets with stronger migration linkages with the initial market as well as with the rest of the country. In the case of the lower transportation costs, larger benefits accrue to those areas that already have nationally integrated labor markets. In the case of the removal of the linguistic barriers, wage gains are concentrated  in districts where the native language is not Hindi.

Conference Presentation:

10th South Asia Economic Policy Network Conference on Migration, Nepal, November 2022

with Laurent Bossavie, Joseph-Simon Georlach, and Caglar Ozden

Abstract: New survey data from Bangladesh provide direct evidence that temporary migration is an effective strategy for workers to accumulate capital and finance self-employment activities back home. We estimate a dynamic model of temporary migration and entrepreneurial investment under constraints, which we use for policy analysis. Lowering of migration costs increases emigration, reduces the age at which workers depart and the duration of their time abroad, which together lead to higher savings and domestic self-employment. Cutting the cost of migration by one half boosts business creation by 8%. Reducing the interest rate for entrepreneurial loans lowers migration and savings repatriation, undercutting the positive effects on business creation at home. This highlights the need to investigate migration and investment jointly, since policies targeting either choice may be enhanced or undercut by endogenous responses in the other.

with Laurent Bossavie, Joseph-Simon Georlach, and Caglar Ozden

Abstract: This paper examines international temporary migration as an intermediary step among aspiring entrepreneurs to accumulate the needed capital when they face credit constraints at home. The analysis is based on a representative dataset of lifetime employment histories of return migrants from Bangladesh. After establishing the credit constraints that potential entrepreneurs face, the paper shows that non-agricultural self-employment rates are significantly higher among returning migrants — over half versus around 20% of non-migrants. Most migrants transition into self-employment by using their savings from abroad as the main source of financing. The paper then offers, for the first time, a detailed account of the financial costs and benefits of international migration. Our findings suggest that temporary migration can contribute to structural transformation of lower-income countries by enabling credit-constrained workers to enter into non-agricultural entrepreneurship.

with Yang Yao and Yue Zhou

Abstract: We study China’s municipal bond markets to find whether mayors’ political human capital —measured by their abilities to grow their cities’ economy—is recognized and priced by market investors. We find an increase of one standard deviation in a mayor’s ability reduces municipal bond yields (investors’ bid yields) by 11.4 basis points, equivalent to saving 38 million yuan during an average mayor’s tenure. Ability has stronger impacts in the first year of a mayor’s tenure, on bonds issued by issuers with lower ratings, and by economically or financially less developed cities.

with Christine Zhenwei Qiang, and L. Colin Xu

Abstract: We investigate how the effects of the business environment depend on whether the measure is de jure or de facto, and how the business environment effects differ by ownership. Four aspects of the business environment are found to be relatively robust by multiple data sources: access to finance, electricity, internet, and human capital. The effects of de jure business environment indicators on firm performances depend on measures of contract enforcement. Foreign-owned firms benefit more from the maintenance of physical safety and ease in obtaining construction permits, and gain competitive advantage in productivity when domestic infrastructure or access to finance is worse.