In collaboration with a state environmental regulator in India, we conducted a field experiment to raise the frequency of environmental inspections to the prescribed minimum for a random set of industrial plants. The treatment was successful when judged by process measures, as treatment plants, relative to the control group, were more than twice as likely to be inspected and to be cited for violating pollution standards. Yet the treatment was weaker for more consequential outcomes: the regulator was no more likely to identify extreme polluters (i.e., plants with emissions five times the regulatory standard or more) or to impose costly penalties in the treatment group. In response to the added scrutiny, treatment plants only marginally increased compliance with standards and did not significantly reduce mean pollution emissions. To explain these results and recover the full costs of environmental regulation,we model the regulatory process as a dynamic discrete game where the regulator chooses whether to penalize and plants choose whether to abate to avoid future sanctions. We estimate this model using original data on 10,000 interactions between plants and the regulator. Our estimates imply that the costs of environmental regulation are largely reserved for extremely polluting plants. Applying the cost estimates to the experimental data, we find the average treatment inspection imposes about half the cost on plants that the average control inspection does, because the randomly assigned inspections in the treatment are less likely than normal discretionary inspections to target such extreme polluters.
It is conventional wisdom that it is possible to reduce exposure to indoor air pollution, improve health outcomes, and decrease greenhouse gas emissions in the rural areas of developing countries through the adoption of improved cooking stoves. This belief is largely supported by observational field studies and engineering or laboratory experiments. However, we provide new evidence, from a randomized control trial conducted in rural Orissa, India (one of the poorest places in India), on the benefits of a commonly used improved stove that laboratory tests showed to reduce indoor air pollution and require less fuel. We track households for up to four years after they received the stove. While we find a meaningful reduction in smoke inhalation in the first year, there is no effect over longer time horizons. We find no evidence of improvements in lung functioning or health and there is no change in fuel consumption (and presumably greenhouse gas emissions). The difference between the laboratory and field findings appear to result from households’ revealed low valuation of the stoves. Households failed to use the stoves regularly or appropriately, did not make the necessary investments to maintain them properly, and usage rates ultimately declined further over time. More broadly, this study underscores the need to test environmental and health technologies in real-world settings where behavior may temper impacts, and to test them over a long enough horizon to understand how this behavioral effect evolves over time.