Summary of JOIE article (First View, 11 September 2018) by Carmine Guerriero, “Rita Levi-Montalcini” Associate Professor (RTDb),Department of Economics, University of Bologna. The full article is available on the JOIE website.
Although the idea that competition helps reach allocative efficiency to the detriment of investment-inducement has been discussed at length (Acemoglu et al., 2006; Vives, 2008), we lack a formal framework encompassing the trade-off between static and dynamic efficiency faced by a society choosing whether to deregulate an industry with inelastic demand and its link with political biases. In Guerriero (2019), I develop such a model, and I employ it to provide an empirical strategy to identify the origins and impact of deregulation, taking as case study the US power industry.
Competition Versus Regulation: Theory
Building on Laffont and Tirole (1993) and Armstrong and Sappington (2006), I compare competition and regulation in a world in which both market institutions and the regulatory contract are selected by a planner who maximizes a weighted average of the consumer surplus and the firms’ utilities, with the weight on the latter rising with society’s investment concerns. Before privately learning its marginal and average cost, which can be either high or low with the same ex ante probability, a firm can commit to an unobservable investment increasing the ex post probability of having low cost. Under competition, production is guaranteed by two firms. Each of them serves the entire market at the price proposed by the opponent when able to undercut it and half of it when the announced prices are the same. Under regulation instead, production is assured by a monopoly. Hence, the demand on which a firm makes a profit is larger under competition because the prevailing price equals the high cost, which is lower than the price necessary to assure incentive compatibility under regulation. Under competition, however, a firm realizes a profit only when its cost is low and that of the opponent is high and, thus, in default of investment, with probability 1/4, which is lower than the odds 1/2 with which a firm makes a profit absent investment under regulation. With inelastic demand, the impact on the expected profit of the larger chance of a rent that regulation entails is bigger than that of the larger demand on which the rent is obtained assured by competition. Hence, the latter entails narrower allocative inefficiencies but, also, smaller expected profits and, thus, weaker incentives to invest. Society’s preferences for competition are, thus, stronger the less socially relevant cost reduction is. If, instead, investment returns accrue more to the firm’s profits than to the consumer surplus, a tension between shareholders and ratepayers arises, and the likelihood that competition is selected rises with the political power of consumers. Finally, since regulation yields a better cost distribution but competition makes it more likely that the most efficient firms serve the market conditional on such a distribution, competition induces lower expected costs only when investment is not sufficiently effective.
Crucially, these implications survive for a generic probability of low cost, number of firms, and correlation between the costs of competing firms, under Cournot competition, for an implicitly motivated regulator, and when society can commit to reimburse investment expenses.
Competition Versus Regulation: Evidence from the US Electricity Industry
To evaluate the model predictions, I exploit data on the deregulation initiatives implemented in 43 US state electricity markets between 1981 and 1999 and on the operation of the generating plants that served these markets. This choice allows me to focus on institutions similar to those analyzed in the basic model and common to other major regulated markets (Barros and Maurer, 2011). On the one hand, electricity generation lacks the natural monopoly’s cost structure typical of the distribution and transmission segments, but it serves an inelastic demand (Joskow, 2005). On the other hand, deregulation of the US power industry turned regulated local monopolies into markets offering competitive services at auction-based prices (Joskow, 2009). To capture society’s investment concerns, I posit that a state confronted with costs and/or inefficiencies of input usage larger than those of bordering states should be more willing to stimulate cost reduction (Guerriero, 2011; 2013), since even the most pro-consumer community prefers fostering profits and investment to facing the ratepayers’ dissatisfaction. Following Fabrizio et al. (2007), I focus on fossil fuels because they are the most relevant inputs variable in the medium term. Consistent with the model, Logit estimates reveal that deregulation was implemented where the marginal fossil fuel cost and the inefficiency of fuel usage had been the lowest and politicians were the most pro-consumer. Crucially, these results are not spuriously driven by the consumers’ willingness to deregulate to deduct from prices the expenses driven by long-term wholesale contracts and investment in nuclear generation (White, 1996). To elaborate, I control for incentive regulation, share of divested plants, installed capacity, share of generation from nuclear sources, and the residential rate. Moreover, the message of the analysis is the same if I employ an Ordered Logit distinguishing between the decision to hold a hearing and that of legislating or if I study the timing of deregulation.
Building on these results and the autoregressive structure of the outcome equations, I use the marginal fossil fuel cost lagged three years and the share of bordering states that deregulated as excluded instruments for deregulation to identify its impact on input uses, the inefficiency of fuel usage, and the mark-up of the residential price over marginal costs. Consistent with the limited effectiveness of investment in the industry and conditional on plant and year fixed effects, GMM estimates suggest that deregulation lowered labor and fossil fuel expenses by pushing the most efficient firms to serve the market but it did not reduce the inefficiency of fuel usage. Crucially, the excluded instruments have no direct impact on outcomes and the analysis remains robust to the consideration of the other determinants of deregulation. Ultimately, my results help rationalize the slowdown of the deregulation wave and, in particular, the passage of legislation freezing or repealing reforms in nine out of the 24 states that had deregulated by 2000 (Joskow, 2009).
Saving Regulation from Economists
The framework I develop goes into the direction of a growing body of literature debunking many of the economists’ myths about the absolute efficiency of free markets. Such a research effort is particularly welcomed in the present-day post-crisis period given the continuous policymakers’ effort to improve exchange and investment by deregulating, re-regulating and restructuring markets.
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