Data and Code for: Temperature, Worker Productivity, and Adaptation: Evidence from Survey Data Production

Name	File Type	Size	Last Modified
AEJ Replication Files			02/24/2022 03:21:PM

Project Citation:

LoPalo, Melissa. Data and Code for: Temperature, Worker Productivity, and Adaptation: Evidence from Survey Data Production. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-12-08. https://doi.org/10.3886/E141721V1

Project Description

Summary:

This paper estimates the impact of daily weather on worker productivity by using household survey data to study interviewers. Using data from over 9,000 Demographic and Health Survey interviewers in 46 countries, I find that interviewers complete 13.6 percent fewer interviews per hour on the hottest and most humid days. Workers maintain the same total output by starting earlier in the day and spending more time on each interview at the expense of spending more hours in the field with the same total pay. In addition, interviewers become differentially less productive on tasks that are less easily monitored. These findings are important not only because temperatures are predicted to rise significantly over the next century, but also because they shed light on how adaptation by workers to adverse conditions can be costly in ways not captured by aggregate productivity measures such as GDP.

Scope of Project

Subject Terms: climate change; labor productivity; adaptation; development

JEL Classification:
      H23 Taxation and Subsidies: Externalities; Redistributive Effects; Environmental Taxes and Subsidies
      J22 Time Allocation and Labor Supply
      J24 Human Capital; Skills; Occupational Choice; Labor Productivity
      O10 Economic Development: General
      Q51 Valuation of Environmental Effects
      Q54 Climate; Natural Disasters and Their Management; Global Warming
      Q56 Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

Geographic Coverage: Global

Time Period(s): 1/1990 – 12/2010

Collection Date(s): 1/1990 – 12/2010

Universe: Household survey interviewers 1990-2010.

Data Type(s): geographic information system (GIS) data; survey data

Methodology

Data Source: Demographic and Health Surveys (DHS)
Princeton Meteorological Forcing Dataset

Unit(s) of Observation: interview; interviewer-day

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Published Versions

V1 [2022-12-08]

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