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 :^s I *-?. 
 
 FACULTY WORKING 
 PAPER NO. 875 
 
 Determinants of Regulatory Policies Toward Competition 
 in the Electric Utility Industry 
 
 Walter J. Primeaux, Jr., John E. Filer, 
 Robert S. Herren, and Daniel R. Hollas 
 
 ** 
 
 
 4fc 
 
 College of Commerce and Business Administration 
 Bureau of Economic ana Business Research 
 ersUy of Illinois. Urb?na-Champaign 
 
BEBR 
 
 FACULTY WORKING PAPER NO. 875 
 College of Commerce and Business Administration 
 University of Illinois at Urbana-Champaign 
 June 1982 
 
 Determinants of Regulatory Policies Toward Competition 
 in the Electric Utility Industry 
 
 Walter J. Primeaux, Jr., Professor 
 Department of Business Administration 
 
 John E. Filer 
 University of Mississippi 
 
 Robert S. Herren 
 University of Mississippi 
 
 Daniel R. Hollas 
 University of Mississippi 
 
Digitized by the Internet Archive 
 
 in 2011 with funding from 
 
 University of Illinois Urbana-Champaign 
 
 http://www.archive.org/details/determinantsofre875prim 
 
Abstract 
 
 Direct competition in the electric industry does actually exist in 
 some cities; its impact on firm performance has been analayzed in a 
 number of previous studies. Control of entry into a market is an important 
 method regulatory commissions use to protect the monopoly status of an 
 existing firm, yet there have been no previous attempts to investigate 
 and identify the factors which ultimately influence regulatory policy 
 toward permitting direct competition in this industry. That is one of 
 the main objectives of this study. 
 
 The model specified is a logit transformation with multiple explanatory 
 variables. The statistical results are generally consistent with the 
 Stigler-Peltzman theory of regulation. The data also tend to refute the 
 notion that regulatory policy is an exogeneous variable which results 
 from ad hoc political and administrative factors. The findings suggest, 
 instead, that regulatory policy is a direct result of economic factors. 
 
DETERMINANTS OF REGULATORY POLICIES TOWARD 
 COMPETITION IN THE ELECTRIC UTILITY INDUSTRY 
 
 INTRODUCTION 
 
 Control of entry into markets is an important method 
 regulators use to ensure monopoly in the electric utility 
 industry. Though unusual, direct competition in the 
 electric industry does actually exist in some cities 
 and its impact on performance has been analyzed in a 
 number of different studies by Primeaux (1974, 
 i975b ,' 1977 ,' 1978) . However, no previous studies have 
 attempted to invest igate and identify the factors which 
 ultimately influence regulatory policy toward permitting 
 direct competition in this industry. 
 
 George Stigler (1971) presented a revisionist theory 
 of regulation which challenges the notion that regulation 
 is designed to serve the public interest. Stigler's 
 model was formalized and extended by Sam Peltzman (1S76). 
 Peltzman concluded that special interest groups incur 
 costs and realize benefits from regulation; total realized 
 net benefits, however, are not as great as they would 
 be in the absence of regulation.- Benefits accrue in. the 
 form of transfers of wealth and arise through control 
 of entry, establishment of rate structure (price fixing), 
 control over price and production of substitutes, and 
 cash payments. 
 
 This study is concerned with the use of entry control 
 
as a manifestation of use of regulation to transfer 
 wealth. Using Peltzman's theory of regulation, an attempt 
 is made to identify factors which indicate hostility 
 toward competition on the part of regulators. The statis- 
 tical results are generally consistent with the Stigler- 
 Peltzman theory of regulation. The data also tend to 
 refute the notion that regulatory policy is an exogeneous 
 variable which results from ad hoc political and adminis- 
 trative factors. The findings suggest, instead, that 
 regulatory policy is a direct result of economic factors. 
 
 Regulatory Objectives 
 
 Following Peltzman's generalization (1976) of a 
 Stiglerian model of political wealth transfers, we assume 
 the regulator wants to maximize a majority M, of voters, 
 generated by 
 (1) M = n-f - (N-n) -h 
 
 where n = number of potential voters in the beneficiary 
 group , 
 
 f = (net) probability that a beneficiary will 
 grant support 
 
 N = total number of potential voters 
 
 h = (net) probability that he who is taxed {ewery 
 non-n) opposes. 
 
 Although beneficiaries pay with both votes and dollars, 
 the productivity of the dollars to a regulator lies 
 in mitigation of opposition. Hence the regulator has 
 
an ob jecti ve f uncti on of the form 
 
 (2) M = M(W r W 2 , ..., W n ) 
 
 1 
 
 where W. = wealth of group i, and where M .> 
 
 This objective function is maximized subject 
 to a constraint on total wealth (V): 
 
 (3) 
 
 V = Wj + w 2 + 
 
 + w n = v(w 1 , w 2 , ... w n ) 
 
 where V->0, but where V, 2 <0 > i.e., the total wealth 
 to be distributed is limited. 
 
 Among the groups vying to achieve benefits or mitigate 
 losses from the regulatory process are consumers of the regu 
 lated good, producers (both of the regulated good, and pro- 
 ducers of substitutes), and the regulators themselves. In 
 the case of electric utility regulation by PSC's, we can 
 specialize the majority generating function, (2) as 
 
 (4) 
 
 M 
 
 = M(P, n £ , n s ) 
 
 where P = price of electricity, n E = wealth of electricity 
 
 producers, and n<- = wealth of producers of substitutes 
 
 (who may be regualted by the same commission). 
 
 We assume the regulators have powers to affect the 
 
 market which result in M > , M > 0, (i.e., greater wealth 
 
 n E n s 
 
 generates support) and M p <0 (i.e., higher electricity 
 rates generate opposition from residential customers, 
 
commercial and industrial customers, and "consumer action 
 
 2 
 
 groups ). If we introduce cost and demand conditions, 
 
 summarized by a profit function 
 
 (5) 
 
 n = f(P,c) 
 
 where c = c(Q) = production costs as function of quantity, 
 the formal problem for a successful utility regulator is to 
 maximize the Lagrangian 
 
 (6) 
 
 L = M(P,n E ,n s ) + x [ n- f(P,c)] 
 
 with respect to P, II-, n_ and A which yields 
 
 This is the Sti gl er-Pel tzman conclusion that the 
 marginal political product of a dollar of profits (Mn-» Mn<-) 
 must equal the marginal political product of a rate 
 cut (-M p ) that also costs a dollar of profits (f p is 
 the dollar profit loss per dollar of rate reduction.) 
 Or, in terms of the present study of electric utility 
 regulation, we generate a testable hypothesis that, 
 through regulation of electricity rates and entry, PSC's 
 attempt to maximize M by balancing marginal gains to 
 interested groups. 
 
 Winners and Losers from Entry Control 
 
 Regulated electric utilities tend to utilize 
 
discriminatory rate structures (Primeaux and Nelson, 
 1980; Hollas and Friedland, 1980). Entry control is a 
 necessary means of perpetuating this discrimination 
 because duopoly, or increased competition through entry, 
 would reduce the extent of the discrimination. Increased 
 competition reduces the ability of a firm to price dis- 
 criminate profitably. Residential customers are probably 
 the biggest losers in a discriminatory rate structure, 
 due to their relatively inelastic demand, consequently 
 they should benefit the most from competition. An impor- 
 tant constraint upon residential customers, in particular, 
 is that it may be costly to organize into a coalition 
 in order to exert political pressures. 
 
 However, if competition is active and the natural 
 monopoly theory does not hold, as reported in Primeaux 
 (1974), all customer groups will receive lower average 
 rates due to the competition. The discriminating utility 
 will be the only clear loser due to reduced profit poten- 
 tial from discrimination. 
 
 Of course, profit reduction may also originate 
 from other sources. Consumers of substitute fuels such 
 as natural gas benefit from competition for two reasons. 
 First, competition in the electric industry lowers electric 
 
 rates and increases competition between electric and 
 
 3 
 gas utilities; this will directly benefit gas customers. 
 
Second, since some gas users will then switch to elec- 
 tricity because of its lower price, this will tend to 
 reduce gas prices for those who continue to use natural 
 gas . 
 
 Natural gas producers would, in general, oppose 
 a policy of direct competition in electricity. Natural 
 gas and electricity are direct substitutes for many 
 residential and commercial markets (e.g. electric home 
 heating versus natural gas heating). Because all elec- 
 tricity is not produced by using natural gas as a fuel, 
 one would expect the increase in natural gas used by 
 electric producers from increased competition in the 
 electric industry to be less than the decrease in natural 
 gas used by households and commercial users from lower 
 electric rates. 
 
 Retail natural gas utilities should also be adversely 
 affected by direct electric utility competition because this 
 would reduce the price of electricity, which is a substitute 
 for the natural gas which they sell. Thus commissions in 
 states with relatively more powerful natural gas distributors 
 will be less likely to encourage ■ competi tion . 
 
 A MODEL OF REGULATORY POLICY TOWARD COMPETITION IN THE 
 ELECTRIC UTILITY INDUSTRY 
 
 The general factors which may explain the tendency 
 
of Public Service Commissions (PSC) to be hostile toward 
 competing electric utilities have been outlined in the 
 previous section. This section develops and tests a 
 model of regulatory policy toward comptition in the 
 electric utility industry. 
 
 The dependent variable in the model is unobserved. 
 It consists of an assessed probability of hostile poli- 
 cies toward competing utilities which lies between zero 
 and unity. What is actually observed is whether the 
 particular state PSC is hostile toward competition or 
 not; and the sample results in a qualitative, dichoto- 
 mous dependent variable, taking a value of zero or one. 
 
 The policy of the commisssion in each individual 
 state is classified as hostile or non-hostile toward 
 direct competition. The information used to classify 
 policies was obtained through questionnaires sent to 
 commissioners in May 1971. The policy was classified 
 as hostile if either direct competition was not permitted 
 legally or if the commission stated that it would not 
 allow competition. On the other hand, the commission 
 was classified as non-hostile either if the commission 
 does not have jurisdiction (it can not prevent competition) 
 or if it contends that direct competition would be allowed. 
 States without commissions were classified as non-hostile 
 toward competition. Table 1 presents a summary of the 
 
8 
 
 5 
 the classifications of regulatory policy. 
 
 The major hypothesis of this paper is that 
 
 economic variables explain costs and benefits (potential) 
 
 of regulation to the interest groups which support or 
 
 oppose entry control. A group derives power either 
 
 from their numbers or their (potential) wealth. We 
 
 now turn to a discussion of the explanatory variables 
 
 of the model . 
 
 Consumers of Electricity 
 
 The mean income of residential consumers should 
 be inversely related to their desire for direct competition 
 between electric utilities. For example, the price 
 elasticity of demand for electricity of a given customer 
 would be lower, the smaller the fraction his utility 
 bills are of his total budget. Lower income consumers 
 would probably be more concerned than high income consumers 
 about paying marginally higher fuel bills, because they 
 buy from a monopolist not facing direct competition. 
 
 Another factor which could indicate the strength 
 or power of consumers is whether utility regulators 
 are elected or appointed. Peltzman (1976, p. 215) argues 
 that the method of regulator selection does not make 
 any difference. Jack Hirshleifer (1976, p. 242) however, 
 maintains that it does make a difference. Whereas the 
 
governor or state legislators which appoint a commis- 
 sioner may campaign on several issues in a given plat- 
 form, an elected commissioner will campaign on a very 
 narrow platform. Thus, voters elect a governor or 
 legislator for reasons in addition to the performance 
 of their commission appointees. However, elected com- 
 missioners are selected based upon only their regula- 
 tory platform. In addition to the other questions 
 examined, this study also tests the hypothesis that 
 elected officials respond more readily to constituency 
 pressures than appointed officials. 
 
 Value added by manufacturing fimrs ia a proxy 
 for wealth of industrial customers. As this measure 
 of wealth increases, one would expect a more favorable 
 PSC policy toward competition. 
 
 Gas Producers 
 
 Because electricity and gas are substitutes, natural 
 gas producers would not benefit from increased competition 
 in the electric industry (see discussion above). Therefore, 
 as the importance of natural gas production ri ses relative 
 to that of electric utilities, we would expect PSCs 
 to become more hostile toward competing electric utilities. 
 This outcome would be expected because producers of 
 
10 
 
 substitute products for electricity prefer higher electric 
 prices to reduce competition with their products. 
 
 Electric Utilities 
 
 The more monopoly power an electric utility has, 
 the more wealth it can lose if competition takes place. 
 Therefore, in states where utilities currently exercise 
 substantial monopoly power, PSC's should be more hostile 
 toward competition; there is, however, a problem of 
 simultaneous cause and effect. Policy is certainly 
 affected by the power or influence of electric producers, 
 however, the PSC policy and attitude toward direct compe- 
 tition should also affect the power arid wealth of the electric 
 utilities. This problem is discussed in more detail 
 be! ow. 
 
 Empirical Results 
 
 The model specified is a logit transformation with 
 multiple explanatory variables of the type introduced 
 by M. Nerlove and S. J. Press (1973) and take'the form: 
 
 (3) 
 
 P = 
 
 e 3 i X i+ u i 
 
 1+e 
 
 6 i X i+ u i 
 
 which when transformed, gives 
 
 (9) 
 
 In (yip) = s i X. + u i 
 
11 
 
 where P is the probability that the relevant PSC is 
 
 p 
 "hostile" toward competition, (In(-rrp) is the "log 
 
 of the odds" of a PSC being hostile), the X. are vectors of 
 
 explanatory variable values, and u. is an error ter 
 
 m 
 
 As u. is either (1-6. X.) or (-e,X.)» u- is heterosce- 
 dastic, and maximum likelihood estimation of the g. 
 must be used. 
 
 Specifically, the model to be tested is: 
 
 (10) In(yTp-) = 6 1 (ELECTRICITY) + ^(ELECTED) + 
 
 6 3 (INCOME) + e 4 (VALUE ADDED) + 5 (NATGAS) + u 
 
 where ELECTRICITY measures the influence of electric utilities, 
 ELECTED, INCOME, and VALUE ADDED represent consumer 
 interest variables, and NATGAS represents a substitute 
 producer's interest variable. The nature of the variables 
 and data is presented in Table 2, however,- a few additional 
 comments on the ELECTRICITY variable may be in order. 
 If the ratio equals unity, then the utility is charging 
 the monopoly price. Consequently, a larger ratio indicates 
 less realized monopoly power. 
 
 Two complications arise with measurement of the 
 ELECTRICITY variable. First, the 1969 estimates of 
 this variable for residential consumers presented in 
 a recent article by Robert Meyer, and Leland Hayne (1980) 
 
12 
 
 were used in the analysis. Second, simultaneous 
 equation bias exists because the power and strength 
 of the utility affects policy but the effect is not 
 one way only; policy also affects the power and strength 
 of the utility. Since data processed by equation (3) 
 showed a (expected) high correlation between ELECTRICITY 
 and the error term, an instrumental variable (IV) tech- 
 nique was utilized in which estimates of ELECTRICITY 
 were obtained by regressing ELECTRICITY on a subset 
 of exogenous variables. 
 
 The following analysis should clarify the technique: 
 
 (11) 
 
 and 
 (12) 
 
 Y l = 6 1 Y 2 + e 2 Z l + 3 3 Z 2 + 6 4 Z 3 + U l 
 
 a l Y l + a 2 Z 4 + a 3 Z 5 + V 2 
 
 whe 
 
 re Y, = policy (1,0) 
 
 Y ? = influence (power) of electric producers 
 
 Z, = influence of natural gas producers 
 
 Zp = influence of residential consumer interest 
 
 - Z 3 = influence of industrial consumer interest 
 
 etc . 
 
 and u, and v~ are error terms. 
 
 A small increase in lt. would result in a small 
 increase in Y,. However, equation (12) shows that a change 
 in Y. results in a change in Y~- Therefore, a change 
 
13 
 
 in u, results in a change in Y^; that is, one of the 
 explanatory variables and the error term are correlated 
 (highly correlated in this specific case). An instru- 
 mental variable was created to remove correlation by 
 regressing Y- on a subset of the exogenous, variables. 
 
 Specifically, the power of an electric utility Y ? measured 
 by the ratio of residential monopoly price to actual 
 price, was regressed on the following exogenous variables: 
 number of retail establishments in 1972, 1971 state 
 per capita income, number of municipal electric utilities 
 in 1971, 1971 total revenue of municipal utilities, 
 1971 percent of population in SMSA areas, 1971 state 
 bituminous coal production per capita, and retail sales 
 per establishment. From this equation a predicted 
 value of the ratio of the residential monopoly price 
 to actual price, Y,,, was obtained. These estimates 
 of Y 2 were then substituted into equation (11) for the 
 log it estimation procedure. 
 
 Table 3 presents the results of the logit analysis. 
 
 The coefficients are defined as the marginal impact 
 
 on the dependent variable of a one unit change in the 
 
 explanatory variable, holding other variables constant 
 
 at mean values. Care must be taken in interpreting 
 
 the coefficients; in this case the depedent variable 
 
 p 
 is 1n (7Tp)- To assess the effect on the probabil i ty 
 
14 
 
 of hostile policy, P, the effect on ln(y^p) must be 
 solved for P. (The relationship between a unit 
 change in an independent variable and the value of P 
 is, hence nonlinear, and depends on the level of P . 
 (See Footnote 9.) Column 1 presents the estimated co- 
 efficients and column 2 reports the t-ratios. 
 
 All coefficients have the correct sign and all 
 coefficients are statistically significant at the .05 
 level or better except for the NATGAS variable, which 
 is significant at about the .07 level. The Stigler- 
 Peltzman hypothesis that numerous groups will benefit 
 from regulation is generally supported, however, it 
 appears that elected commissioners are more likely 
 to favor a competitive policy. This result is at odds 
 with Peltzman's argument that the method of regulator 
 selection should be unimportant. 
 
 The estimates of the coefficients of the logit model 
 can be used to assess the relative influence of the in- 
 terested groups vying for political favor from the 
 commissions. Table 4 below gives the effect on the 
 assessed probability of a given PSC being "hostile" 
 toward competition, given a change in the circumstances 
 of interested groups. The probability is calculated 
 for both elected and appointed commissions. The mean 
 
15 
 
 value of each explanatory variable, X., was inserted 
 in the regression equation and a predicted value of 
 ln(-T^T5") , and hence P, was obtained. We then changed 
 each expl ana tcry variable from X. to (X. + s.) where 
 s. is the sample standard deviation of the explanatory 
 variable, X., and solved for P, holding the remaining 
 
 g 
 
 explanatory variables constant at their means. The 
 third and fourth columns give the percentage change 
 in the probability of observing an anti -competi ti ve 
 commission, given a one- standard-deviation change in 
 the value of the explanatory variable. From this we 
 note a number of conclusions, most of which reinforce 
 the Stigler-Peltzman theory. The regulated industry 
 itself has the greatest influence on commission policies, 
 regardless of whether the commission is elected or appointed. 
 If the variable measuring the relative strength of natural 
 gas interests is increased, there is a significant impact 
 on policy in the predicted direction, and elected commissions 
 
 are significantly more sensitive than appointed 
 
 10 
 
 
 Large industrial users of electricity have the 
 third highest level of influence on commission policies 
 after the utilites themselves and producers of substitutes, 
 while the more diffuse residential consumer interest 
 has the least impact. The only result inconsistent 
 with Peltzman's predictions is the different impact 
 
16 
 
 on elected versus appointed commission, as noted above 
 
 Summary 
 
 Statistical results from this study generally 
 support the Sti gl er-Pel tzman theory of regulation. 
 The only finding not consistent with Peltzman's formu- 
 lation of the theory is that elected officials are more 
 likely to favor pro-competitive policies than appointed 
 officials. Pel tzman has argued this should be an unim- 
 portant factor. For public policy purposes, however, 
 it seems that any movement toward elected regulatory 
 commissions would tend to foster pro-competitive policies, 
 at least in the short run. 
 
 Data reveal that an increase in realized monopoly 
 power of the utility increases the probability of hostile 
 PSC policies toward competition. An increase in average 
 value added in manufacturing and a decrease in the state's 
 per capita income increased the probability of favorable 
 PSC policies toward competition. Also, the more power- 
 ful are natural gas interests, the more hostile are 
 commission policies toward competition. 
 
 These empirical findings refute the hypothesis 
 that regulatory policy is somehow an exogenous variable 
 which results from ad hoc political and administrative 
 factors. Instead, it appears that regulatory policy 
 is a direct result of economic factors. 
 
Table 1 
 
 Public Service Commission Policies 
 Toward Competition in 1971 
 
 State 
 
 Al abama 
 
 Alaska 
 
 Ari zona 
 
 Arkansas 
 
 California 
 
 Col orado 
 
 Connecticut 
 
 Del aware 
 
 Florida 
 
 Georgia 
 
 Idaho 
 
 Illinois 
 
 Indiana 
 
 Iowa 
 
 Kansas 
 
 Kentucky 
 
 Louisiana 
 
 Maine 
 
 Maryl and 
 
 Massachusetts 
 
 Michigan 
 
 Missouri 
 
 Montana 
 Nevada 
 New Mexico 
 New York 
 
 North Carol ina 
 
 North Dakota 
 Ohio 
 Oregon 
 
 Pennsyl vania 
 Rhode Island 
 South Carolina 
 
 South Dakota 
 
 Tenenssee 
 
 Texas 
 
 Utah 
 
 Vermont 
 
 Virginia 
 
 West Virginia 
 
 Wisconsin 
 
 Commi ss i on Pol i 
 Direct Compe 
 
 cy Toward 
 t i t i o n 
 
 Ca teg 
 of 
 
 onzation 
 
 Pol icy 
 
 Wyomi ng 
 
 no pel icy 
 seeks to elimin 
 not permitted 
 not permitted 
 probably not pe 
 no policy 
 actively di scou 
 no jurisdiction 
 not permitted 
 no pol i cy 
 not permitted 
 not permitted 
 not permitted 
 no jurisdiction 
 not permitted 
 a 1 1 owed i n some 
 not permitted 
 
 no established pol 
 no response 
 not permitted 
 opposed to exte 
 no jurisdiction 
 
 competition be 
 
 municipal util 
 no jurisdiction 
 not permitted 
 not permitted 
 would allow com 
 
 considered use 
 North Carol ina 
 
 that municipal 
 
 systems are fr 
 not a 1 1 owed 
 not sanctioned 
 no response 
 not encouraged 
 legislature wou 
 not permitted b 
 
 util i t i e s 
 no regulation 
 not permitted 
 no regulation 
 not permitted 
 not permitted 
 not permitted 
 permitted if ex 
 
 is inadequate 
 permitted if ex 
 
 is inadequate 
 not permitted 
 
 ate 
 
 rmi t 
 rages 
 
 cases 
 
 icy 
 
 nsion of competition 
 
 over existing 
 
 tween private and 
 i t i e s 
 
 petition if 
 ful 
 
 courts have held 
 ly owned electric 
 ee to compete 
 
 or advocated 
 Id not permit 
 e tween private 
 
 non 
 hos 
 hos 
 hos 
 hos 
 non 
 hos 
 non 
 hos 
 non 
 hos 
 hos 
 hos 
 non 
 hos 
 non 
 hos 
 non- 
 hos 
 hos 
 non 
 non 
 
 -hostile 
 
 tile 
 
 tile 
 
 tile 
 
 tile 
 
 -hostile 
 
 tile 
 
 -hostile 
 
 tile 
 
 -hostile 
 
 tile 
 
 tile 
 
 tile 
 
 -hosti 1 e 
 
 tile 
 
 -host i 1 e 
 
 tile 
 
 ■hostile 
 
 tile d 
 
 tile 
 
 -hostile 
 
 -hos tile 
 
 lsting service 
 i s t i n g service 
 
 non -hostile 
 hostile 
 hostile 
 non-hostile 
 
 non-hostile 
 
 hostile 
 
 non-hosti 1 e 
 
 hostile 13 
 
 non-hostile 
 
 hostile 
 
 non-hostile 
 
 non-hosti le c 
 
 hostile 
 
 non-host ile c 
 
 hostile 
 
 hostile 
 
 hostile 
 
 non-hostile 
 
 non-hostile 
 
 hostile 
 
a This commission was categorized as hostile due to corr- 
 spondence with utility official in Hagerstown, Maryland. 
 
 This commission was categorized as hostile due to studies 
 by Primeaux (1975a) and Galat (1971). 
 
 c These states were categorized as non-hostile toward compe- 
 tition as 1) they had no state regulatory commission in 
 1971 and 2) we observed the existence of cities with 
 competing electric utilities. 
 
Table 2 
 Variables Included in the Analysis 
 
 Yj - 1971 PSC policy toward competition in . the state; 
 
 1 = hostile toward competition, = favors competition. 
 
 ELECTRICITY = 1969 ratio of the monopoly price to actul 
 price for residential customers. 
 
 ELECTED = method of selecting commissioners; 
 1 = elected, = appointed. 
 
 INCOME 
 
 natural log of 1971 state per capita inc 
 
 ome 
 
 VALUE ADDED = 1972 state value-added per firm in manufacturing 
 (in millions) 
 
 NATGAS = 1971 ratio of cubic feet of natural gas produced 
 (in millions) to KWH (in millions) of electricity 
 sold in the state. 
 
 Sources: Y. was obtained through questionnaires mailed 
 
 by Primeaux to utility commissions; ELECTRICITY 
 was taken from Table 2 of Meyer and Hayne 
 (1980, p. 560); INCOME and VALUE ADDED are from 
 Statistical Abstract ; NATGAS is from Gas Facts 
 and Stati stical Yearbook. "~~ 
 
.Table 3 
 Results of Logit Analysis 
 
 ELECTED 
 VALUE ADDED 
 NATGAS 
 ELECTRICITY 
 
 INCOME 
 
 Coefficient 
 
 -0.933 
 (0.533) 
 
 -2.721 
 (1.213) 
 
 0.022 
 (0.014) 
 
 -0.112 
 (0.042) 
 
 1.431 
 (0.520) 
 
 t- ratio 
 
 ■1.75 
 
 ■2.24 
 
 1.52 
 
 2.64 
 
 2.7 5 
 
 Standard errors in parentheses 
 
 b Signif i cant at the .01 level 
 
 Significant at the .05 level 
 
 Significant at the .10 level 
 
-Table 4 
 
 Relative Influence of Interested 
 Groups on Commission Policies 3 
 
 (Elected 
 
 (Appointed 
 
 Mean Predicted 
 Probability 13 .25 9 
 
 Commercial /Industrial .094 
 Electricity Consumers 
 (VALUE ADDED) 
 
 Natural Gas Interests .540 
 (NATGAS) 
 
 Residential Consumers/ . 300 
 Consumer Action Groups 
 (INCOME) 
 
 Electric Utility Interests .062 
 (ELECTRICITY) 
 
 Commission) %a P Commission) %aP 
 
 .471 
 -64% .209 
 
 103% .749 
 16% .521 
 
 -76% 
 
 143 
 
 -56% 
 
 5 9% 
 11% 
 
 -70% 
 
 Effect of a one-standard deviation increase in explanatory 
 variable value on P, holding other variables constant at their 
 means . 
 
 Mean values of continuous explanatory variables inserted in 
 estimated equation. 
 
 'Value of 1 inserted (if commission elected), and inserted 
 (if commission appointed) in estimated equation. 
 
Footnotes 
 
 differs from Peltzman's in 
 
 two 
 i 
 
 respects 
 
 explicitly incorporate Hi rshl ei f er ' s suggestion 
 
 Our function 
 1 ) we 
 
 (1976) that "the regulators themselves constitute an 
 interest group"; and 2) we implicitly relax Peltzman's 
 assumption that M..=0, if j, or, "there are no inter- 
 group dependencies:" An example of such an interde- 
 pendency would be the PSC regulation of both natural 
 gas prices and electricity rates, when natural gas 
 and electricity are substitutes (in residential usage, 
 say) and natural gas is used as fuel for electricity 
 generation . 
 
 The interests of consumers and "consumer action 1 
 will not be, in general, identical. 
 
 groups 
 
 3. This analysis assumes that the electric and gas com- 
 panies are competing firms and not combination utili- 
 ties providing both energy services. 
 
 4. There may also be a second order effect: producers of 
 fuels used by the utilities may gain or lose depending 
 upon output effects. That is, second degree price 
 discrimination probably increases output, creating 
 additional demand for fuels such as coal, oil, and 
 natural gas. Output effects of third degree price 
 discrimination are not as clear and depend upon the 
 shape of the demand curve (Robinson, 1933). On the 
 other hand, increase competition will also increase 
 output due to lower prices of electricity. This also 
 creates increased consumption by utilities for fuels 
 to generate electricity. 
 
 This information was obtained through questionnaires 
 sent to commissioners in May 1971 (Primeaux, book 
 manuscript in progress). The states not included 
 were those which Primeaux had no responses, or all 
 utilities were publicly owned, or which did not have 
 commissions and competing utilities. 
 
 It is our intuitive feeling that Peltzman is correct 
 in long-run equilibrium. The observed difference in 
 the policies of elected versus appointed regulators 
 reported later in this paper may be analagous to the 
 (seemingly) contradictory theories of the consumption 
 function reconciled by Friedman's "permanent income 
 hypothesi s . " 
 
8 
 9 
 
 10 
 
 As i 
 
 for 
 
 corr 
 
 dard 
 
 For 
 
 Econ 
 
 s st 
 
 this 
 
 elat 
 
 err 
 
 a di 
 omet 
 
 anda 
 
 equ 
 
 ed w 
 
 cr o 
 sens 
 r i cs 
 
 vi ae 
 the 
 (in 
 Year 
 
 d th 
 numb 
 mill 
 book 
 
 el ec 
 util 
 
 of s 
 
 trie 
 i t i e 
 hort 
 
 r d with 
 ati on a 
 f th Y~, 
 
 f the^e 
 s i o n of 
 , pp. 4 
 ta. St 
 f retai 
 
 of do! 
 
 the so 
 1 i t i e s 
 Mi neral 
 
 an IV technique, the regressors 
 re uncor related with u. and highly 
 
 and chosen to minimize the stan- 
 stimate and the covariance matrix. 
 
 this technique, see Maddala, 
 76-477. The following works pro- 
 i c a 1 Abstract, 1976 provided 
 shments and retail sales 
 dison Electric's Statistical 
 
 e da 
 
 er of retai 1 es tab 1 i 
 
 ions of dollars). E 
 
 was the source for 
 
 utilities and total 
 s . Mineral Yearbook 
 
 tons of bituminous coal and lignite 
 
 the number of municipal 
 revenue of municipal 
 1971 supplied number 
 
 We are indebted to Sam Peltzman for this method of 
 assessing "relative contribution." 
 
 p 
 Due to the nature of the In(y^-p-) function, 
 
 ( p [1n( ^ )] = P ( 1 - P ) and is not independent of 
 
 the level of P), one cannot take any single mean 
 
 p 
 effect of a varaible on W^rpO by itself and solve 
 
 for the mean effect of the explanatory variable on 
 P, the probability of a commission being hostile 
 toward competition. Values for allother explana- 
 tory variables must be included before 
 p 
 
 Aln(j T Q) can be solved for aP 
 
References 
 
 American Gas Association, Gas Facts 1971, 1976 (Arling- 
 ton , Va . ) . 
 
 Edison Electric Institute, Statistical Year Book of 
 The Electric Utility Industry 1971 (New York). 
 
 John R. Galat, "Direct Competition Between Regulated 
 Public Utilities: A Case Study," in Joseph E. Haring 
 and Joseph F. Humphrey (eds) Utility Regulation During 
 Inflation (Occidential College: 1971) . 
 
 Jack Hirshleifer, "Toward a More General Theory of Regu- 
 lation, Comment," Journal of Law and Economics , 19:241- 
 244 (August 1976). 
 
 Daniel R. Hollas and Thomas S. Friedland, "Price Dis- 
 crimination in the Municipal Electric Industry," Research 
 in Law and Economics , 2:181-198 (1980). 
 
 G. S. Maddala. Econometrics (McGraw-Hill, 1977). 
 
 Robert A. Meyer and Leland Hayne , "The Effectiveness 
 
 of Price Regulation," Review of Economics and Statistics , 
 
 62:555-66 (Nov. 1980). 
 
 Mark Nerlove and S. J. Press, "Univariate and Multivariate 
 Log-Linear and Logistic Models," Rand Corporation , 
 R-1305-EDA/NIH (December 1973). 
 
 Sam Peltzman, "Twoard a More General Theory of Regulation," 
 Journal of Law and Economics , 19:211-240 (August 1976). 
 
 Walter J. Primeaux, Jr., "A Duopoly in Electricity: 
 Competition in a 'Natural Monopoly 1 " Quarterly Review 
 of Economics and Business , 14:65-73 (Summer 1974). 
 
 Walter J. Primeaux, Jr. "The Decline in Electric Utility 
 Competition." Land Economics , 51:144-148 (May 1975a). 
 
 Walter J. Primeaux, Jr., "A Reexamination of the Mono- 
 poly Market Structure for Electric Utilities" in Pro - 
 moting Competition in Regulated Industries (Washington, 
 D.C.: The Brookings Institutions, 1975b). 
 
 Walter J. Primeaux, Jr., "An Assessment of X-Efficiency 
 Gained Through Competition," Review of Economics and 
 Statistics , 59: 105-103 (February 1977) . 
 
Walter J. Primeaux Jr. An Examination of Direct Electric 
 Utility Competition: Some Persepecti ves on the Natural 
 Monopoly Myth (Book manuscript in progress). 
 
 Walter J. Primeaux, Jr. "The Effect of Competition 
 on Capacity Uti 1 i ti za t i on in the Electric Industry," 
 Economic Inquiry , 26:237-68 (April 1978). 
 
 Walter J. Primeaux, Jr. and Randy A. Nelson, "An Exa- 
 mination of Price Discrimination and Internal Subsidi- 
 zation by Electric Utilities," Southern Economic Journal 
 47:84-99 (July 1980). 
 
 Joan Robinson, The Economics of Imperfect Competition 
 (London: Macmi 1 1 an , 1933 ) . 
 
 Statistical Abstract of the U.S. 1976 (U.S. Dept. of 
 Commerce , 1976 ) . 
 
 U.S. Bureau of Mines. 
 
 1 (U.S. Government Printing Office, 
 
 Minerals Yearbook, 1971 vol . 
 
 Washington : 1973) 
 

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