Political Economy Of Regulation Research Paper

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Government regulation of firms uses the ‘coercive power’ of the state to alter firms’ pricing, entry, production, investment, or product choice decisions. An extensive empirical literature analyzes the effects of ‘economic regulation’ of price and entry as well as environmental, health, safety, and information regulation. These analyses amassed substantial evidence of high prices, excess profits, and production inefficiencies under economic regulation (see Joskow and Rose 1989, Joskow and Noll 1994; and Regulation: Empirical Analysis). Studies of environmental, health, and safety regulation revealed substantial deviations from least-cost solutions and dramatic variation in measures such as expected cost per life saved across regulatory interventions (see Viscusi 1994, Gruenspecht and Lave 1989). These outcomes, so systematic and pervasive, were difficult to reconcile with ‘public interest’ models of regulatory intervention. Examination of regulatory systems further suggested that they often deviated from cost minimization or efficiency objectives by design. This begged for an explanation beyond bureaucratic incompetence or malfeasance, common to earlier Marxian or ‘capture’ theories of government. Stigler’s (1971) Economic Theory of Regulation provided the conceptual underpinnings of what has become a vast enterprise among economists and political scientists to understand the origin, objectives, maintenance, and reversal of regulatory policy in the context of rational choice models of political behavior. These simple insights stimulated a substantial theoretical and empirical literature (Noll 1989, Peltzman 1993).

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Theories of legislative and bureaucratic behavior have become increasingly sophisticated since the 1980s. The literature has moved well beyond Stigler’s simple model to incorporate the role of competing interests, policy entrepreneurs, majoritarian political institutions, legislative oversight of regulatory agencies and commissions, and asymmetric information (see Noll 1989, Joskow and Noll 1994, Laffont 1999). The empirical literature has struggled to keep pace with these developments.

Common to virtually all empirical studies in this area is the importance, and difficulty, of defining well-specified alternatives to the political economy model under investigation. To test a given model of political behavior, or to interpret results as consistent with a given model, one must understand how predicted outcomes differ between competing hypotheses of behavior and the model being tested. For example, there is a natural tendency to identify rent conveyance with rent-seeking activity. In some cases, however, increased rents for regulated firms may be consistent with both successful rent-seeking behavior by those firms and elimination of some market inefficiency. It is important, though often quite difficult, for empirical analyses to identify and attempt to distinguish alternatives such as these. Studies vary considerably in the degree to which they meet this standard.

This research paper introduces the main empirical methodologies used to explore the political economy of economic, environmental, health and safety regulation. Examples of their applications are briefly discussed. Interested readers are urged to pursue the surveys listed in the references for more complete discussions of this literature.

1. Measuring Distributional Effects

Empirical studies of political economy generally begin with estimates of the distributional effects of a given policy. While many empirical methods may be used (see Joskow and Rose 1989), asset market ‘event studies’ have been particularly popular. These measure price movements in capital assets, such as company share prices, at the time policy changes are first announced. If the announcement is not previously anticipated, and asset markets efficiently process information, these price changes provide estimates of the policy’s effect on the capitalized value of expected rent streams. This method may be used to measure the effects of the policy change on firms within a regulated industry, corporate customers and suppliers, and possible competitors. The distributional implications for individual or small business customers, employee groups, and other noncorporate interests usually must be measured using alternative methods.

The simplest political economy studies use measured distributional effects to infer the relative influence of different interest groups in the political process. These implicitly assume that the observed changes in rent distribution are anticipated and intentional, and that larger rent gains reflect greater political power. Consider, for example, the extensive debate over the origin of the first federal economic regulatory commission in the US, the Interstate Commerce Commission created in 1887 to regulate railroads. Was this legislation intended to solve an inefficiency in an industry characterized by large sunk costs and natural monopoly conditions? If the legislation was a response to interest group politics, did it respond to agrarian interests and other shippers’ demands to constrain monopoly pricing by railroads, or was it a railroad-sponsored effort to establish a government-enforced cartel? Did legislation intend one outcome, only to be thwarted by the regulatory agency’s subsequent behavior? There have been numerous empirical studies attempting to answer these questions, many using railroad share price responses to various regulatory ‘events’ (e.g., Prager 1989, Mullin 2000). In these, railroad share price gains in response to the Interstate Commerce Act, for example, have been interpreted as evidence that the regulation was intended to benefit railroads, supporting Stiglerian models of regulatory politics. While it may be reasonable to assume that ex post gains identify ex ante intended beneficiaries, this should be made explicit and considered against alternative explanations. To move convincingly from a positive statement about the distributional consequences of a policy to an inference about its political motivation requires an understanding of distributional effects under leading alternative models.

2. Estimating Political Support For Regulation

A second empirical methodology estimates the determinants of regulatory incidence or political support as a function of underlying economic interests. These studies generally involve three steps. First, ex ante winners and losers of a regulatory policy are identified, using either prior estimates or a model of the regulation’s effect. For example, Stigler’s (1971) analysis of truck weight laws modeled state truck weight and size limits as raising the cost of trucking service, particularly over longer hauls. Truckers therefore lose from lower limits, as do their current customers, businesses using their own trucks, and potential customers for whom trucking rates constrain alternative transportation rates. Competitors to trucks, such as railroads, gain from tighter restrictions. There may be diffuse ‘public interests’ as well, for example, in limiting damage to roadbeds and reducing congestion, though these may well be endogenous.

Second, the importance of the identified economic interests within a given jurisdiction or at a particular point in time is measured. There is considerable variation in how this is done. For example, the number of trucks, scaled or unscaled, the dollar volume of activity in trucking, and the fraction of freight hauls susceptible to potential truck competition are all possible measures of the importance of trucking interests in a jurisdiction.

Finally, the incidence or intensity of regulation, or the political support for regulation, is estimated to be a function of the measured economic interests and any other relevant factors. Stigler used this method to explain differences in the intensity of truck weight limitations across states, for example. Other studies apply this technique to model variation in political support, such as voting records, as a function of constituent economic interests in the policy, inter alia.

Most studies in this area find that constituent interests are significant determinants of regulatory policy, though interests must be defined broadly to include constituent preferences (such as conservation or environmental preferences) as well as direct economic interests. Detailed studies of voting behavior suggest that the underlying models may be quite complex, however; see, for example, Joskow and Schmalensee (1998) on the US acid rain program. The significant impact of legislators’ ideology on their voting behavior (e.g., Kalt and Zupan 1984) suggests possible slack in the agency relationship between constituents and their legislators, as well support for more sophisticated models of voting in majoritarian systems across issues and over time.

3. Modeling Regulatory Agency Behavior

A final strand of empirical work in political economy begins with the recognition that most regulatory legislation leaves considerable discretion over its implementation to regulatory agencies or commissions. Early work on regulatory ‘capture’ assumed that industry groups could influence regulators to use this discretion to benefit the industry in direct contravention to legislative intent. As economists and political scientists began to explore the extent to which apparent regulatory capture was instead a reflection of legislative intent, they confronted the questions of how much discretion regulators retain and how regulators use that discretion to form policy (e.g., McCubbins et al. 1987). This led to an extensive literature on the operation and oversight of the administrative process, most of it within political science. This area remains one of the least-developed empirical literatures in regulatory economics.

While some early analyses explored the responsiveness of regulatory agency decision-making to congressional preferences, most economics research in this area analyzes the responsiveness of agency decision-making to interest groups and various measures of efficiency or social welfare. This is methodologically quite similar to the legislative studies described in Sect. 2, with individual regulatory decisions as the unit of observation. As in those studies, the results suggest a role for concentrated economic interests to influence regulatory outcomes. This does not itself demonstrate that regulators respond to interest groups in contravention with broader social objectives, however. For example, studies have found that despite significant overall delays in the process by which the Food and Drug Administration (FDA) controls entry of new pharmaceutical products, the FDA responds more quickly to drugs with greater market potential (Dranove and Meltzer 1994). In this case, both producer and social interests are aligned with reducing delay of an innovation.

4. Conclusion

While research on the political economy of regulation has made significant progress since the 1970s, fundamental questions remain unanswered by either theoretical or empirical work (Peltzman 1993, Joskow and Noll 1994). One of the most basic is why some industries are regulated (or deregulated) and others are not. Another is why regulatory policy seems characterized by ‘waves’ or cycles: changes tend to occur across broad ranges of industries and sectors within fairly short periods, separated by longer periods of relative inactivity. Considerable scope remains for additional work in this area.


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