Working Papers
Utility Rebates for ENERGY STAR Appliances: Are They Effective? (joint with Sumeet Gulati)
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Do Polluting Facilities of the Same Feather Flock Together? A Spatial Econometrics Approach to Analyzing Emission Spillovers
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Playing Dirty or Going Clean? Lobbying, Abatement and Firm Heterogeneity
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Abstract: In this paper we study the impact of cash rebates offered by utility companies on the purchase of ENERGY STAR labelled appliances in the United States. Specifically, we estimate the increase in the market share of ENERGY STAR-qualified appliances that can be attributed to these financial incentives. To estimate the impact of these incentives we use the variation in timing and size of the utility rebates across the US states. We then use these estimates along with information on the average energy saved by using an ENERGY STAR appliance relative to a non-ENERGY STAR appliance to provide a rough estimate on the cost per tonne of carbon saved by the rebate program. Results show that an increase in a dollar value of rebate leads to a 0.3% increase in the share of ENERGY STAR-qualified clothes washers while the effect of rebates is not significant for dishwashers and refrigerators. We find that the cost of saving a tonne of carbon, assuming a redemption rate of 40% for mail-in rebates, is around US$171. The cost of a megawatt hour saved, which is around US$35, is lower than the estimated cost of building and operating an additional power plant as well as the average on-peak spot prices. We conclude that the ENERGY STAR clothes washers rebate programs are a cost-effective way for utilities to reduce energy demand.
Abstract: This paper analyzes the presence of spillovers in pollution by looking at emissions and changes in emissions; that polluting facilities around other neighbouring facilities tend to have a similar environmental performance. I use information about location of each facility and exploit the variation in the emission levels and emission changes in a large sample of manufacturing facilities in Canada by using a simple and parsimonious spatial autoregressive (SAR) model and an extension of the SAR model that uses two spatial weight matrices instead of the traditional single spatial weight matrix. The “distance” between facilities is measured by the geographical distance as well as the closeness of a facility’s SIC code with that of its neighbours. Spatial dependencies may be the result of both these factors and the extension of the SAR model takes into account both these channels simultaneously. I find that, compared to OLS results, spatial dependencies exist and are significant as indicated by the statistical significance of the spatial autoregressive parameters. My results also indicate that the effect of the industry SIC distance is substantially stronger than that of geographical distance.
Abstract: In this paper I use firm-level characteristics to make predictions about the lobbying and abatement decision of firms in a model with two firms. There are three sources of firm heterogeneity, viz. the marginal cost of production, the emission intensity and the marginal cost factor of abatement. The decision to lobby or abate or do both depends on the cost-effectiveness of lobbying against that of abating. I find that a firm will abate and not lobby if its effective marginal abatement cost, which depends on the firm's output, is lower than a threshold value. An interesting outcome is that, under my assumption of perfect and complete information, the model predicts that in most cases the firm with the lower effective marginal abatement cost will not lobby but will free-ride on the lobbying effort of the other firm.