We quantify the role of geography and land quality for agricultural productivity differences across countries using high-resolution micro-geography data and a spatial accounting framework. The rich spatial data provide for each cell of land covering the entire globe, the potential yield for 18 crops, which measures the maximum attainable crop output given soil quality, climate conditions, terrain topography, and a given level of cultivation inputs. While there is considerable heterogeneity in land quality across space, even within narrow geographic regions, we find that low agricultural land productivity is not due to unfavourable geographic endowments. If countries produced current crops in each cell according to potential yields, the rich-poor agricultural yield gap would virtually disappear, from 214% to 5%. We also find evidence of additional aggregate productivity gains attainable through spatial reallocation and changes in crop production.

We investigate the role of sectoral labor productivity in explaining the process of structural transformation—the secular reallocation of labor across sectors—and the time path of aggregate productivity across countries. We measure sectoral labor productivity across countries using a model of the structural transformation. Productivity differences across countries are large in agriculture and services and smaller in manufacturing. Over time, productivity gaps have been substantially reduced in agriculture and industry but not nearly as much in services. These sectoral productivity patterns generate implications in the model that are broadly consistent with the cross-country data. We find that productivity catch-up in industry explains about 50% of the gains in aggregate productivity across countries, whereas low productivity in services and the lack of catch-up explain all the experiences of slowdown, stagnation, and decline observed across countries.

We study the determinants of differences in farm size across countries and their impact on agricultural and aggregate productivity using a quantitative sectoral model featuring a distribution of farms. Measured aggregate factors (capital, land, economy-wide productivity) account for one-quarter of the observed differences in farm size and productivity. Policies and institutions that misallocate resources across farms have the potential to account for the remaining differences. Exploiting within-country variation in crop-specific price distortions and their correlation with farm size, we construct a cross-country measure of farm-size distortions which together with aggregate factors accounts for one-half of the cross-country differences in size and productivity.

We build a model of heterogeneous individuals—who make investments in schooling quantity and quality—to quantify the importance of differences in human capital vs. total factor productivity (TFP) in explaining the variation in per capita income across countries. The production of human capital requires expenditures and time inputs; the relative importance of these inputs determines the predictions of the theory for inequality both within and across countries. We discipline our quantitative assessment with a calibration firmly grounded on US micro evidence. Since in our calibrated model economy human capital production requires a significant amount of expenditures, TFP changes affect disproportionately the benefits and costs of human capital accumulation. Our main finding is that human capital accumulation strongly amplifies TFP differences across countries: to explain a 20-fold difference in the output per worker, the model requires a 5-fold difference in the TFP of the tradable sector, vs. an 18-fold difference if human capital is fixed across countries.

Recent empirical evidence from the United States indicates a high degree of persistence in earnings across generations. Designing effective public policies to increase social mobility requires identifying and measuring the major sources of persistence and inequality in earnings. We provide a quantitative model of intergenerational human capital transmission that focuses on three sources: innate ability, early education, and college education. We find that approximately one-half of the intergenerational correlation in earnings is accounted for by parental investment in education, in particular early education. We show that these results have important implications for education policy.

We use household‐level panel data from China and a quantitative framework to document the extent and consequences of factor misallocation in agriculture. We find that there are substantial within‐village frictions in both the land and capital markets linked to land institutions in rural China that disproportionately constrain the more productive farmers. These frictions reduce aggregate agricultural productivity by affecting two key margins: (1) the allocation of resources across farmers (misallocation) and (2) the allocation of workers across sectors, in particular the type of farmers who operate in agriculture (selection). Selection substantially amplifies the productivity effect of distortionary policies by affecting occupational choices that worsen average ability in agriculture.

Frictions that impede the mobility of workers across occupations and space are a prominent feature of developing countries. We disentangle the role of insecure property rights from other labor-mobility frictions for the reallocation of labor from agriculture to nonagriculture and from rural to urban areas. We combine rich household and individual-level panel data from China and an equilibrium quantitative framework featuring sorting of workers across locations and occupations. We explicitly model the farming household and the endogenous decisions of who operates the family farm and who potentially migrates, capturing an additional channel of selection in the household. We find that land insecurity has substantial negative effects on agricultural productivity and structural change, raising the share of rural households operating farms by over 40 percentage points and depressing agricultural productivity by more than 20%. Comparatively, these quantitative effects are as large as those from all residual labor-mobility frictions. We measure a sharp reduction in overall labor-mobility barriers over 2004–2018 in the Chinese economy, all accounted for by improved land security, consistent with reforms covering rural land in China during the period. JEL Codes: O11, O14, O4, E02, Q1.