Pollution abatement expenditures and plant-level productivity: A production function approach

Abstract

In this paper we investigate the impact of environmental regulation on productivity using a Cobb-Douglas production function framework. Estimating the effects of regulation on productivity can be done with a top-down approach using data for broad sectors of the economy, or a more disaggregated bottom-up approach. Our study follows a bottom-up approach using data from the U.S. paper, steel, and oil industries. We measure environmental regulation using plant-level information on pollution abatement expenditures, which allows us to distinguish between productive and abatement expenditures on each input. We use annual Census Bureau information (1979-1990) on output, labor, capital, and material inputs, and pollution abatement operating costs and capital expenditures for 68 pulp and paper mills, 55 oil refineries, and 27 steel mills. We find that pollution abatement inputs generally contribute little or nothing to output, especially when compared to their 'productive' equivalents. Adding an aggregate pollution abatement cost measure to a Cobb-Douglas production function, we find that a $1 increase in pollution abatement costs leads to an estimated productivity decline of $3.11, $1.80, and $5.98 in the paper, oil, and steel industries respectively. These findings imply substantial differences across industries in their sensitivity to pollution abatement costs, arguing for a bottom-up approach that can capture these differences. Further differentiating plants by their production technology, we find substantial differences in the impact of pollution abatement costs even within industries, with higher marginal costs at plants with more polluting technologies. Finally, in all three industries, plants concentrating on change-in-production-process abatement techniques have higher productivity than plants doing predominantly end-of-line abatement, but also seem to be more affected by pollution abatement operating costs. Overall, our results point to the importance using detailed, disaggregated analyses, even below the industry level, when trying to model the costs of forcing plants to reduce their emissions.

Clean and Productive? Evidence from the German Manufacturing Industry

“…Our result that environmental expenditures do not affect production (growth) of the respective sector of the German manufacturing industry is largely in line with the existing literature, e.g. with Shadbegian and Gray (2005). If we abstain from the possible explanation of misreporting, our results suggest that environmental expenditures are, economically speaking, not productive at all.…”

“…If part of the expenditures are a direct consequence of environmental regulation, they may in principle be considered as non-productive (pollution abatement) input as opposed to, e.g. capital and labor used for production (Shadbegian and Gray, 2005). (In other words, pollution abatement expenditures could be considered to implicitly produce a second good, namely pollution abatement to comply with some regulation.…”

“…In contrast, a recent study undertaken by Hamamoto (2006) suggests that pollution control expenditures measured at the industry level for Japan positively affect TFP growth via a stimulation of R&D investment. Our study is most closely related to Shadbegian and Gray (2005) that introduce PACE data into a production function approach at the U.S. plant level for pulp and paper mills, oil refineries, and steel mills. The authors find that pollution abatement expenditures contribute very little to production and negatively affect non-abatement inputs.…”

Effect of Environmental Regulation Stringency on the Pulp and Paper Industry

“…A negative effect is also found in some of the more contemporary studies [8,16,22,23,37,38]. However, regarding the studies conducted during the last 20 years, the results are somewhat ambiguous.…”

The dynamic lot-sizing problem with convex economic production costs and setups

“…One of the most common production functions is the Cobb-Douglas production function, which was introduced at a macroeconomic level for the US manufacturing industries for the period 1899-1922 but has been widely applied to individual production processes at the microeconomic level, as well. For example, Shadbegian and Gray (2005) use the Cobb-Douglas production function to model production processes in the paper, steel and oil industries, Hatirli et al (2006) to model agricultural production, and Kogan and Tapiero (2009) to model logistics/supply chain operations. The Cobb-Douglas production function assumes that multiple (m) resources are needed for output, Q and they may be substituted to exploit the marginal cost advantages.…”