James M. Griffin

A General Index of Technical Change

This paper outlines a procedure for estimating a general index of technical change within the context of a quite general production technology. Specifically, when panel data are available for firms in an industry, time-specific dummies can be combined in a nonlinear estimation procedure to yield a general index of technical change that may be both nonneutral and scale augmenting. This approach offers numerous advantages over the traditional time trend representation of technical change. For example, the general index can serve as the basis for analysis of the determinants of technical change. Results for a sample of 30 electric utilities over the period 1951-78 show that the productivity decline of the 1970s can be attributed primarily to sulphur oxide restrictions and secularly declining capacity utilization due to rapidly increasing peak-load demands.

NEW EVIDENCE ON ASYMMETRIC GASOLINE PRICE RESPONSES

In a 1997 paper, Borenstein, Cameron, and Gilbert (BCG) claim that gasoline prices rise quickly following an increase in the price of crude oil, but fall slowly following a decrease. This note estimates an error-correction model with daily spot gasoline and crude-oil price data over the period 19851998 and finds no evidence of asymmetry in wholesale gasoline prices. The sources of the difference in results are twofold. First, we use the standard Engle-Granger two-step estimation procedure, whereas BCG used a nonstandard estimation methodology. Second, even using BCGs nonstandard specification, the use of daily rather than weekly data yields little evidence of price asymmetry.

Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline

Abstract This paper utilizes an international panel data set and a dynamic demand specification for gasoline to compare the performance of homogeneous and heterogeneous parameter estimators. In addition to comparing the plausibility of the various estimates, a forecast performance comparison is performed to examine differences in predictions over one-, five-, and ten-year horizons.

TO POOL OR NOT TO POOL: HOMOGENEOUS VERSUS HETEROGENEOUS ESTIMATORS APPLIED TO CIGARETTE DEMAND

This paper reexamines the benefits of pooling and, in addition, contrasts the performance of newly proposed heterogeneous estimators. The analysis utilizes a panel data set from 46 American states over the period 1963 to 1992 and a dynamic demand specification for cigarettes. Also, the forecast performance of the various estimators is compared.

Uncertainty and the choice of pollution control instruments

Abstract This paper compares the relative efficiencies of pollution taxes, pollution standards, and the auctioning of pollution rights when the marginal damage function or marginal control cost are subject to uncertainty. In the first case, we find that all instruments yield the same expected social surplus. In the latter case, the choice of the optimal instrument depends, in general, on the relative elasticities of the marginal damage and marginal expected cost functions, on the way in which uncertainty enters the model, and on the distribution of the error term. Policy conclusions are derived.

Gasoline demand in the OECD: An application of pooling and testing procedures

Abstract This study utilizes a pooled inter-country data set, finding the long-run price-elasticity falls in the range −0.55 to −0.9, depending on the choice of pooled estimators. The estimators included the OLS, within-, and between-country estimators, plus five feasible GLS estimators. Even allowing for a ten-year distributed lag on price to reflect changes in auto-efficiency characteristics, the within-country estimator yields appreciably more inelastic estimates than did the O:S estimator, which was heavily influenced by the between- or inter-country variation. This difference raises intriguing questions for future research.

Short and Long Run Effects in Pooled Models

ACADEMIC POSITIONS Distinguished Professor of Economics, Syracuse University, 2005-present. Part-time Chair in Economics, University of Leicester, 2004-present. George Summey, Jr. Professor of Liberal Arts, Texas A&M University, 1993-2005. Visiting Professor, University of California-San Diego, 2002. Visiting Professor, University of Arizona, 1996. Visiting Professor, Université Pantheon-Assas, Paris II, 2003-present. Professor of Economics, Texas A&M University, 1988-2005. Associate Professor of Economics, University of Houston, 1984-1988. Assistant Professor of Economics, University of Houston, 1979-1984.

Airline Deregulation: The Cost Pieces of the Puzzle

This paper analyzes cost changes in the U.S. airline industry in the pre- and postderegulation era using a panel data set of airlines. Specifically, it seeks to disentangle cost changes attributable to technical change, economies of scale and density, and input prices. The authors estimate a purely general index of industry technical change and in turn analyze its determinants. Despite the slowing of productivity growth in the 1980s, deregulation does appear to have stimulated technical change due to more efficient route structures. Copyright 1995 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

The econometrics of rational addiction: The case of cigarettes

This article reexamines the econometric estimation of rational-addiction models considered by Becker, Grossman, and Murphy (BGM) for cigarette consumption. The rational-addiction model poses a number of additional econometric difficulties including endogeneity due to the presence of leads and lags of the dependent variable and serial correlation in the disturbances. BGM considered a fixed-effects two-stage least squares (2SLS) estimator. It is well known that this estimator is biased for fixed T. This article suggests a forward-filter first-difference 2SLS estimator and a generalized method of moments type of estimator that are consistent. Using a panel dataset of 46 states over the period 1963–1992, this article estimates the rational-addiction model for cigarettes. Our empirical results are both supportive of the rational-addiction hypothesis and more plausible than BGMs original results.

Inter-fuel Substitution Possibilities: A Translog Application to Intercountry Data

One of the pressing issues in current energy policy debates in both the U. S. and other consuming countries is the feasibility of substantially reducing the use of crude oil. In some energy consuming sectors suchl as transportation, the shortrun mechanism to reduce consumption is through lower utilization of energyconsuming equipment while in the long-run, the equipment can be redesigned to achieve greater fuel efficiencies. In electricity generation and heatilng uses the primary mechanism to reduce consumption is inter-fuel substitution rather than capital/energy substitution. This paper is concernied with estimating the interfuel substitution relationships between fossil fuels (coal, gas, and residual fuel oil) in the generation of electricity. It is important to consider fossil fuel substitution possibilities in electricity generation both because considerable technical flexibility exists2 and because electric utilities are large consumers of fossil fuels. For example, electric utilities consumed 25% of primary energy inputs in the U. S. in 1970. Although not as high as the U. S., the other developed countries exhibit a similar pattern. In the 20 0. E. C. D. coun-tries, electric utilities consumed 50% of the coal, 17% of the gas, and 11% of petroleum products.3 High substitution elasticities among fuels in electricity generation indirectly increase subsequenit substitution of electricity for petroleum as a fuel source in residential, commercial, and industrial sectors. Thus the nature and extent of inter-fuel substitution possibilities in electricity generation are fundamental to the question of reducing dependency on crude oil. There have been several econometric studies of inter-fuel substitution in electricity generation using a variety of estimation procedures and samples. MacAvoy [15] used cross sectional data for U. S. power regions to examine substitution between nuclear fuel and fossil fuel. Griffin [10] estimated dynamic price and cross price elasticities among fuels utilizing annual time series data. More recently, Joskow and Mishkin [13] used individual plant data to analyze fuel choice in a logit model framework. But probably the approach capturing the most attention is the application of