AbstractThis paper examines the impact of climate shocks, measured as temperature and precipitation variability, on real monthly per capita consumption expenditure of Indian households over the 1988–2012 period, utilising data from the National Sample Survey Organisation's Consumer Expenditure Surveys. The regression results show an increase in consumption by 1.2 per cent on average, in response to a one standard deviation rise in temperature, with heterogeneous impacts across economic sectors.

Hotter years are associated with lower economic output in developing countries. The study shows that the effect of temperature on labor is an important part of the explanation. Using microdata from selected firms in India, the researchers estimate reduced worker productivity and increased absenteeism on hot days. Climate control significantly mitigates productivity losses. In a national panel of Indian factories, annual plant output falls by about 2% per degree Celsius. This response appears to be driven by a reduction in the output elasticity of labor.

Briefing highlights 

–    Analyzing policy attitudes is important for understanding environmental policy feasibility.

–    Pure self-interest is not sufficient to explain people’s policy positions. There are other factors that are also important for policy attitude formation.

–    Policy packaging, earmarking and revenue recycling can potentially change people’s policy positions.

Economists argue that carbon taxation (and more generally carbon pricing) is the single most powerful way to combat climate change. Since this is so controversial, we need to explain it better, and to be precise, the efficiency gains are largest when the costs of abatement are strongly heterogeneous. This is often—but not always—the case. When it is not, standards can fill much the same role.

The study analyzes factors affecting climate change coping strategies and constraints experienced by smallholder farmers under root crop (cassava and yam) farming systems in derived savannah ecological zone of Nigeria. The study used data collected from 400 farmers selected through a multistage random sampling technique from two States, Ebonyi and Enugu States, in the zone.