We document strong skill matching in Turkish firms’ production networks. Additionally, in the data, export demand shocks from rich countries increase firms’ skill intensity and their trade with skill-intensive domestic partners. We explain these patterns using a quantitative model with heterogeneous firms, quality choices, and endogenous networks. A counterfactual economy-wide export demand shock of 5% leads both exporters and nonexporters to upgrade quality, raising the average wage by 1.2%. This effect is nine times the effect in a scenario without interconnected quality choices. We use the model to study the conditions for the success of export promotion policies.
What is the pathway to development in a world marked by rising economic nationalism and less international integration? This paper answers this question within a framework that emphasizes the role of demand-side constraints on national development, which is identified with sustained poverty reduction. In this framework, development is linked to the adoption of an increasing returns to scale technology by imperfectly competitive firms that need to pay the fixed setup cost of switching to that technology. Sustained poverty reduction is measured as a continuous decline in the share of the population living below $1.90/day purchasing power parity in 2011 U.S. dollars over a five-year period. This outcome is affected in a statistically significant and economically meaningful way by domestic market size, which is measured as a function of the income distribution, and international market size, which is measured as a function of legally-binding provisions to international trade agreements, including the General Agreement on Tariffs and Trade, the World Trade Organization, and 279 preferential trade agreements. Counterfactual estimates suggest that, in the absence of international integration, the average resident of a low- or lower-middle-income country does not live in a market large enough to experience sustained poverty reduction. Domestic redistribution targeted towards generating a larger middle class can partially compensate for the lack of an international market.
We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2 km and 2.4 km (where the average US county has dimension of 51.9 km), our model predictions achieve R2 values of 0.85 to 0.91 in levels, which far exceed the accuracy of existing models, and 0.32 to 0.46 in decadal changes, which have no counterpart in the literature and are 3–4 times larger than for commonly used nighttime lights. Our network has wide application for analyzing localized shocks.
This paper studies the role of private sector companies in the development of local amenities. We use evidence from one of the largest multinationals of the 20th century: the United Fruit Company (UFCo). The firm was given a large land concession in Costa Rica—one of the so‐called “Banana Republics”—from 1899 to 1984. Using administrative census data with census‐block geo‐references from 1973 to 2011, we implement a geographic regression discontinuity design that exploits a land assignment that is orthogonal to our outcomes of interest. We find that the firm had a positive and persistent effect on living standards. Company documents explain that a key concern at the time was to attract and maintain a sizable workforce, which induced the firm to invest heavily in local amenities—like the development of education and health infrastructure—that can account for our result. Consistent with this mechanism, we show, empirically and through a proposed model, that the firm's investment efforts increase with worker mobility.
We examine the employment effects of 3G mobile internet expansion in developing countries. We find that 3G significantly increases the labor force participation rate of women and the employment rates of both men and women. Our results suggest that 3G affects the type of jobs and there is a distinct gender dimension to these effects. Men transition away from unpaid agricultural work into operating small agricultural enterprises, while women take more unpaid jobs, especially in agriculture, and operate more small businesses in all sectors. Both men and women are more likely to work in wage jobs in the service sector.
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 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.
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.
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.
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.