Research

We construct an endogenous growth model with random interactions where firms are subject to distortions. The TFP distribution evolves endogenously as firms seek to upgrade their technology over time either by innovating or by imitating other firms. We use the model to quantify the effects of misallocation on TFP growth in emerging economies. We structurally estimate the stationary state of the dynamic model targeting moments of the empirical distribution of R&D and TFP growth in China during the period 2007–2012. The estimated model fits the Chinese data well. We compare the estimates with those obtained using data for Taiwan and perform counterfactuals to study the effect of alternative policies. R&D misallocation has a large effect on TFP growth.

We show that labor market transaction costs explain why the smallest farms are more efficient than slightly larger farms in most low-income countries and that increases in machine capacity with operational scale result in the globally observed rising upper tail of productivity. We find evidence consistent with these mechanisms using Indian data, and we show that if all Indian farms were at the minimum scale required to maximize the return on land, the number of farms would be reduced by 82% and income per farm worker would rise by 68%.

This chapter reviews a recent body of theoretical and empirical work that studies the normative and positive aspects of trade policy. We start by presenting reduced-form evidence of the effects of trade policy in the presence of supply-chain linkages, on the short-run and persistent effects of trade policy across local labor markets, and on the effects of trade policy uncertainty on employment and firms. We describe the shift-share method for trade policy analysis, discuss the interpretation of the estimated effects, and provide a theoretical foundation. We then describe new quantitative frameworks, methods, and data used to study the aggregate and distributional effects of trade policy in general equilibrium. We discuss how to take into account supply-chain linkages, local labor markets, and different sources of dynamics. As an illustration, we quantify the aggregate and distributional effects of the 2018 trade war between the United States and its trading partners. Finally, we present recent theoretical insights on optimal unilateral trade policy with firm and product heterogeneity in the context of large and small open economies with perfectly and imperfectly competitive product markets. We also discuss how optimal trade policy is shaped by the presence of multiple sectors, intermediate goods, and supply-chain linkages. We close the chapter by discussing the scope of future research.

We document that an experimental intervention offering transport subsidies for poor rural households to migrate seasonally in Bangladesh improved risk sharing. A theoretical model of endogenous migration and risk sharing shows that the effect of subsidizing migration depends on the underlying economic environment. If migration is risky, a temporary subsidy can induce an improvement in risk sharing and enable profitable migration. We estimate the model and find that the migration experiment increased welfare by 12.9%. Counterfactual analysis suggests that a permanent, rather than temporary, decline in migration costs in the same environment would result in a reduction in risk sharing.

We build a multicountry dynamic general equilibrium model to study the economic effects of the 2004 enlargement of the European Union. In our model, trade is costly and households of different skills and nationalities face costly forward-looking migration decisions. We exploit the timing of migration policy changes to identify the changes in migration costs. We find that the changes in migration and trade policy resulted in aggregate welfare gains but with heterogeneous effects across skill groups. We study the interaction between trade and migration policies and highlight the importance of trade for quantifying the welfare and migration effects of labor market integration.

We develop a framework for quantifying barriers to labor force participation (LFP) and entrepreneurship faced by women in developing countries, and apply it to the Indian economy. We find that women face substantial barriers to LFP. The costs for expanding businesses through the hiring of workers are also substantially higher for women entrepreneurs. However, there is one area in which female entrepreneurs have an advantage: the hiring of female workers. We show that this is not driven by the sectoral composition of female employment. Consistent with this pattern, we find even without promoting female LFP, policies that boost female entrepreneurship can significantly increase female LFP. Counterfactual simulations indicate that removing all excess barriers faced by women entrepreneurs would substantially increase the fraction of female-owned firms, female LFP, earnings, and generate substantial gains in aggregate productivity and welfare. These gains are due to higher LFP, higher real wages and profits, and reallocation: low productivity male-owned firms previously sheltered from female competition are replaced by higher productivity female-owned firms previously excluded from the economy.

To quantify trade frictions, we examine multiproduct exporters. We build a flexible general-equilibrium model and estimate market entry costs using Brazilian firm-product-destination data under rich demand and market access cost shocks. Our estimates show that additional products farther from a firm's core competency come at higher production costs, but there are substantive economies of scope in market access costs. Market access costs differ across destinations, falling more rapidly in scope at nearby regions and at destinations with fewer nontariff barriers. We evaluate a counterfactual scenario that harmonizes market access costs across destinations and find global welfare gains similar to eliminating all current tariffs.

I consider the aggregate impact of low intermediate input intensity in the agricultural sector of developing countries. In a dynamic general equilibrium model with idiosyncratic shocks, incomplete markets, and subsistence requirements, farmers in developing countries use fewer intermediate inputs because it limits their exposure to uninsurable shocks. The calibrated model implies that Indian agricultural productivity would increase by 16% if markets were complete, driven by quantitatively important increases in both the average real intermediate share and measured TFP through lower misallocation. I then extend the results to consider the importance of risk in other contexts. First, the introduction of insurance decreases cross-country differences in agricultural labour productivity by 14%. Second, scaling the introduction of improved seeds to decrease downside risk reduces inequality by reallocating resources from rich to poor farmers via equilibrium effects. This reallocation substantially increases aggregate productivity relative to what would be expected from extrapolating the partial equilibrium impact.

We propose a methodology for defining urban markets based on builtup landcover classified from daytime satellite imagery. Compared to markets defined using minimum thresholds for nighttime light intensity, daytime imagery identify an order of magnitude more markets, capture more of India’s urban population, are more realistically jagged in shape, and reveal more variation in the spatial distribution of economic activity. We conclude that daytime satellite data are a promising source for the study of urban forms.

We review the literature that studies the dynamics of firms in foreign markets, at both the intensive and extensive margins, and their aggregate implications. We first summarize a set of micro facts on exporter entry, expansion, contraction, and exit and several macro facts about the response of aggregate trade flows to trade-policy and business-cycle shocks. We then present the canonical model developed to account for these facts and discuss its connection to the empirical evidence. We show how three model features—future uncertain profits, an investment in market access, and high depreciation of that access upon exit—generate transition dynamics and long-run aggregate outcomes from a cut in tariffs. The model and its extensions contribute to our understanding of trade integration and the evolution of future trade barriers. We discuss the key challenges faced by the canonical model, its possible extensions, and applications of the framework to recent global events.

Occasional widely publicized controversies have led to the perception that growth statistics from developing countries are not to be trusted. Based on the comparison of several data sources and analysis of novel IMF audit data, we find no support for the view that growth is on average measured less accurately or manipulated more in developing than in developed countries. While developing countries face many challenges in measuring growth, so do higher-income countries, especially those with complex and sometimes rapidly changing economic structures. However, we find consistently higher dispersion of growth estimates from developing countries, lending support to the view that classical measurement error is more problematic in poorer countries and that a few outliers may have had a disproportionate effect on (mis)measurement perceptions. We identify several measurement challenges that are specific to poorer countries, namely limited statistical capacity, the use of outdated data and methods, the large share of the agricultural sector, the informal economy, and limited price data. We show that growth measurement based on the System of National Accounts (SNA) can be improved if supplemented with information from other data sources (for example, satellite-based data on vegetation yields) that address some of the limitations of SNA.

The last decades have seen a significant increase in the concentration of economic activity. Firms are getting bigger and the top firms account for a larger and larger share of employment and sales. The paper The ‘Matthew effect’ and market concentration: Search complementarities and monopsony Power provides a novel and intriguing take on these patterns. It starts from the premise that production is subject to search frictions. Producing firms need to find retailers to sell their goods to consumers. Similarly, retailers need to find producers to actually have something to sell. Crucially, both producers and retailers can decide on their search effort and search more intensely if the return of doing so is large.

Can targeting information to network-central farmers induce more adoption of a new agricultural technology? By combining social network data and a field experiment in 200 villages in Malawi, we find that targeting central farmers is important to spur the diffusion process. We also provide evidence of one explanation for why centrality matters: a diffusion process governed by complex contagion. Our results are consistent with a model in which many farmers need to learn from multiple people before they adopt themselves. This means that without proper targeting of information, the diffusion process can stall and technology adoption remains perpetually low.

While intergenerational transmission of entrepreneurship is a well-known regularity, we hypothesize that in a transition economy where the state retains an important role, those whose parents are government workers may also be more likely to become business owners. We test the hypothesis in China and show that (1) on average, both entrepreneurs and government workers have a higher likelihood of having children who own incorporated businesses and (2) In provinces where government involvement is higher, the likelihood that children of government workers (entrepreneurs) own incorporated businesses is significantly higher (lower). Our study demonstrates that the local economic business environment shapes the influence of parental background on business ownership.

This paper employs a benchmark heterogeneous-agent macroeconomic model to examine a number of plausible drivers of the rise in wealth inequality in the US over the last forty years. We find that the significant drop in tax progressivity starting in the late 1970s is the most important driver of the increase in wealth inequality since then. The sharp observed increases in earnings inequality and the falling labor share over the recent decades fall far short of accounting for the data. The model can also account for the dynamics of wealth inequality over the period—in particular the observed U-shape—and here the observed variations in asset returns are key. Returns on assets matter because portfolios of households differ systematically both across and within wealth groups, a feature in our model that also helps us to match, quantitatively, a key long-run feature of wealth and earnings distributions: the former is much more highly concentrated than the latter.