Evaluating the employment effects of environmental regulation without abatement cost data: A nonparametric cost function approach.

Environmental policymakers are concerned that environmental regulations reduce employment. A microeconomic analysis illustrates that environmental regulations have an uncertain effect on employment, making this an empirical question. A standard cost function model, used in the literature, requires a lot of data such as pollution abatement cost data to examine effects of environmental regulations on employment, but such survey data is not always available. In this paper, we develop a nonparametric cost function which alleviates the need for pollution abatement cost data. Our cost function, therefore, allows researchers and policy analysts to estimate employment changes associated with pollution abatement as well as measure the relative importance of other factors related to changes in employment with no pollution abatement cost data. Moreover, this is the first model using a cost function that incorporates the effect of structural change among industries within the economy on employment, which allows researchers to the examine how environmental regulations change the structure of the economy via a structural decomposition component. We illustrate how to operationalize our model using a balanced panel of industry-level data for 26 industries from 17 OECD countries (1995-2006). Our findings suggest that the change in employment due to regulatory induced increases in input costs exhibits both substantial variation among countries and substantial intra-country heterogeneity among industries.

Pollution Abatement and Employment.

Morgenstern et al. (2002) is well-known for its investigation of the employment effects of environmental regulations. However, the cost function specified in that paper is handicapped by its reliance on survey data of the costs of inputs assigned to pollution abatement. In this paper, we specify an input distance function that models the joint production of good and bad outputs. This allows us to measure the relative importance of factors associated with changes in employment without pollution abatement cost data. We operationalize our model using a sample of 80 coal-fired electric power plants from 1995-2005.