We evaluate the causal impacts of on-the-job soft skills training on the productivity, wages, and retention of female garment workers in India. The program increased women's extraversion and communication, and spurred technical skill upgrading. Treated workers were 20 percent more productive than controls post-program. Wages rise very modestly with treatment (by 0.5 percent), with no differential turnover, suggesting that although soft skills raise workers' marginal products, labor market frictions are large enough to create a substantial wedge between productivity and wages. Consistent with this, the net return to the firm was large: 258 percent eight months after program completion.

Although there is now an extensive literature on the economic impacts of climate change on agriculture, no study has yet addressed the endogeneity of irrigation. This paper examines how climate affects the choice to irrigate and the conditional income earned by each farmer. The paper develops a selection model of irrigation choice and conditional income. Using data from farmers across eleven African countries, the paper demonstrates that the choice of irrigation is sensitive to both temperature and precipitation. Rainfed and irrigated farm income also both respond to climate but have different climate sensitivity. Impact models that fail to account for endogenous irrigation are biased.

ABSTRACT. African societies exported more slaves in colder years. Lower temperatures reduced mortality and raised agricultural yields, lowering slave supply costs. Our results help explain African participation in the slave trade, which predicts adverse outcomes today. We use an annual panel of African temperatures and port-level slave exports to show that exports declined when local temperatures were warmer than normal. This result is strongest where African ecosystems are least resilient to climate change. Cold weather shocks at the peak of the slave trade predict lower economic activity today. We support our interpretation using the histories of Whydah, Benguela, and Mozambique.

Measurement of the full costs and benefits of energy-saving technologies is often difficult, confounding adoption decisions. We study consequences of the adoption of energy-efficient LED lighting in garment factories around Bangalore, India. We combine daily production line-level data with weather data and estimate a negative, nonlinear productivity-temperature gradient. We find that LED lighting, which emits less heat than conventional bulbs, decreases the temperature on factory floors, and thus raises productivity, particularly on hot days. Using the firm's costing data, we estimate the pay-back period for LED adoption is nearly one-sixth the length after accounting for productivity co-benefits.

The assignment of workers to tasks is an important feature of the organization of production within firms. We study how task allocation across workers changes in response to productivity shocks. Pairing hourly productivity data from a ready-made garments firm with granular data on exposure to particulate matter pollution, we show that productivity suffers as a result of pollution shocks; this effect is heterogeneous across workers and tasks. Managers respond by reassigning workers to tasks in which they perform better on average during shocks. This response is larger for managers who we identify, via survey-based measurement, as exhibiting greater managerial attention, and these same managers are also the ones who are most able to mitigate resulting productivity declines.

This study predicts the impact of climate change on African agriculture. We use a generalized linear model (GLM) framework to estimate the relationship between the proportion of various Agro-Ecological Zones (AEZs) in a district and climate. Using three climate scenarios, we project how climate change will cause AEZs to shift, causing changes in acreage and net revenue per hectare of cropland. Our results predict that Africa will suffer heavy annual welfare losses by 2070-2100, ranging between US$14 billion and US$70 billion, depending on the climate scenario and cropland measure considered.The authors would like to thank Michael Boozer and Rahul Deb for helpful suggestions, and Maarten L. Buis for helpful feedback regarding the Stata command authored by him.

We study consequences of the adoption of energy-efficient LED lighting in garment factories around Bangalore, India. Combining daily production line-level data with weather data, we estimate a negative, nonlinear productivity-temperature gradient. We find that LED lighting raises productivity on hot days. Using the firm’s costs data, we estimate that the payback period for LED adoption is less than one-third the length after accounting for productivity co-benefits. The average factory in our data gains about $2,880 in power consumption savings, and about $7,500 in productivity efficiency gains.

The version presented here is a Working Paper (or 'pre-print') that may be later published elsewhere.