Rate of return regulation and the Le Chatelier principle

This paper examines whether rate-of return regulation alters the input quantities firms use to produce their selected output level when the corresponding input prices change, in a manner similar to the Le Chatelier principle. More specifically, would the change in a rate regulated firm’s input quantity due to a change in its input price be less price elastic than the unregulated firm’s change in the input quantity due to a change in its input price. We follow Färe and Logan (1986), Nelson and Wohar (1983) in estimating a rate regulated cost function and capital input share system of equations. Using a 1992–2000 panel of 34 US major investor-owned electric utilities, empirical results indicate that the regulated own-input price elasticities of demand for labor and fuel are less price elastic than their corresponding unregulated own-input price elasticities of demand (a Le Chatelier principle type effect). Having a fuel clause (1) reduces the firm’s willingness to substitute from fuel to either non-fuel (capital, labor) input when the price of fuel rises, and (2) enhances the firm’s willingness to substitute from non-fuel inputs to fuel when the price of non-fuel inputs rises.     

Asset Pricing with Observable Stochastic Discount Factors

The stochastic discount factor model provides a general framework for pricing assets. By specifying the discount factor suitably it encompasses most of the theories currently in use, including CAPM and consumption CAPM. The SDF model has been based on the use of single and multiple factors, and on latent and observed factors. In most situations, and especially for the term structure, single factor models are inappropriate, whilst latent variables require the somewhat arbitrary specification of generating processes and are difficult to interpret. In this paper we survey the principal different implementations of the SDF model for bonds, equity and FOREX and propose a new approach. This is based on the use of multiple factors that are observable and modelling the joint distribution of excess returns and the factors using a multi–variate GARCH–in–mean process. We argue that in general single equation and VAR models, although widely used in empirical finance, are inappropriate as they do not satisfy the no–arbitrage condition. Since risk premia arise from conditional covariation between the returns and the factors, both a multi–variate context and having conditional covariances in the conditional mean process, is essential. We explain how apparent exceptions, such as the CIR and Vasicek models, in fact meet this requirement — but at a price. We explain our new approach, discuss how it might be implemented and present some empirical evidence, mainly from our own researches. Partly, to enable comparisons to be made, the survey also includes evidence from recent empirical work using more traditional approaches.     

Compositional change,aggregation, and dynamic factor demand. Estimates on a panel of manufacturing firms

Most empirical research on investment and dynamic factor demand has used aggregated data. The large number of authors who have cited this as a source of problems strongly suggests possible benefits from analyzing individual firm data. This paper presents an analysis of a panel dataset of US manufacturing firms. Several models, based on cost minimization and a three-factor Cobb–Douglas technology, are developed. The differences concern whether the technology varies across two-digit SIC industries, the presence of fixed adjustment lags, and the determinants of adjustment costs. Identification relies on the rational expectations hypothesis, and estimation on non-linear 3SLS. The estimates indicate that versions with the adjustment lag perform better than others. Conditional elasticities reveal that factor demand responds rapidly to anticipated changes in output and factor prices, a finding consistent with other recent work. It appears that the factor demand of large firms is more price sensitive and less sensitive to output than small firms, consistent with recent work on credit market imperfections. Comparison of the results based on the pooled and the industry varying technologies indicate that the use of aggregate data is indeed a source of problems.     

COEFFICIENT CHANGE,PRICE EFFECTS,AND IMPLICIT ELASTICITIES: ESTIMATING MICROECONOMIC DETERMINANTS OVER TWO TIME PERIODS

This paper presents and estimates an input–output model in which input coefficient changes are functions of changing prices. The model produces results that mirror the characteristics of input demand functions based on the model of cost minimization subject to producing a desired level of output. It does not rely on the specification of a functional form for input coefficients, and it does not require the use of assumptions regarding the elasticity of substitution. Instead, it allows the actual price and coefficient changes that occur between periods to identify the implicit elasticities and own- and cross-price derivatives. Using this model, it is shown how accurate measures of price effects, including the full array of own and cross-elasticities of demand, can be estimated for models comprising up to 15 sectors given data for only two time periods.     

Oligopsony/oligopoly power and factor market performance

This paper is concerned with the economic performance of factor markets in an oligopsony/ oligopoly setting. Firm arid industry indexes are developed to measure factor market price distortions caused by exerted oligopsony/oligopoly power. These measures indicate that the elasticity of output demand, the elasticity of input supply, and the input and output conjectural elasticities determine the degree of non-competitive performance in factor markets. It is also shown that under special conditions the firm index equals the Lerner index and the industry index equals the Herfindahl-Hirschman index.     

Prices and factor demand in an endogenized input–output model

This paper combines factor demand functions (for intermediate input and labour) and price equations (derived from a Generalized Leontief cost function) with the traditional input–output price model. The cost functions determine factor demands for materials and labour as well as output prices at given input prices. At the second level of aggregation, the intermediate demand as a single input is split proportional to the elements in the column of the technical coefficients matrix. The emphasis in this endogenization of technical coefficients is on two features. First, the repercussion of output on input prices, and, second, the link between the econometric model for the supply side and the input–output demand model.     

The long-run implications of the production smoothing model of inventories: An empirical test

This paper provides an empirical test of the long-run implications of the production smoothing model of inventories, the dominant framework for inventory investment research in the past. Intertemporal models of a firm holding inventories of finished goods predict a long-run relationship between inventories, shipments, factor input prices, and the real interest rate which is tested here using cointegration test procedures. These tests provide little support for the predictions of the production smoothing model. In most of the data sets used, test statistics indicate that inventories, shipments, factor input prices, the nominal interest rate, and the inflation rate maintain a long-run equilibrium relationship but parameter estimates of cointegrating vectors are often implausible, typically rejecting hypotheses implied by structural models of the production smoothing motive for holding inventories.     

Weak Axiom of Cost Dominance: A Nonparametric Test of Cost Efficiency Without Input Quantity Data

Varian's Weak Axiom of Cost Minimization provides a nonparametric test of cost minimization, which can be applied only when both input price and quantity data are available for individual firms. In this paper we propose a Weak Axiom of Cost Dominance (WACD), which serves as the basis of an alternative test of cost-minimization applicable in situations where input quantity data are missing. Unlike a previous test developed by Diewert and Parkan, the proposed test does identify individual firms that violate the assumption of cost-minimizing behavior. It also provides an upper bound of the cost-efficiency of any observed firm. The test procedure is shown to be equivalent to applying dominance analysis using normalized input prices with reference to the Cost-indirect technology. The proposed method is applied to Nerlove's electrical utility data. The nonparametric results are also compared with parametric efficiency levels computed from a stochastic frontier cost function.     

Why Are Concavity Conditions Not Satisfied in the Cost Function? The Case of Japanese Manufacturing Firms during the Bubble Period*

This paper examines empirically the reasons why Japanese manufacturing firms frequently fail to satisfy concavity of the cost function in input prices. We focus on the ‘bubble period’ in the 1980s when land was in great demand and land prices soared. By estimating the translog cost function with land as one of production inputs, we find that violation of concavity mainly resulted from weak bank–firm relationship and massive transactions of land. We also demonstrate that elasticities of substitution between land and other inputs are estimated quite differently if the firms violating concavity are not excluded from the analysis.     

THE INTERTEMPORAL DIMENSION OF NEOCLASSICAL PRODUCTION THEORY

Abstract. The aim of this survey paper is to provide a guide to the literature on optimal dynamic factor demands to the non-specialist reader interested in applied work. We start with the distinction between variable and quasi-fixed factors of production and use these to characterize the firm's temporary equilibrium. We then review the optimal intertemporal behaviour of the firm, using the notion of adjustment costs as a means to solve the firm's optimization problem. This process gives rise to a system of interrelated dynamic factor demands in a flexible accelerator format. Theoretical difficulties and empirical limitations of this model are discussed. This fact leads us to review the theory of intertemporal duality. We next analyze the issue of expectations in this class of dynamic models. A section reviewing the empirical work on dynamic factor demands follows, after which we offer some concluding remarks.     

On estimating dynamic factor demands

Many recent empirical studies on inter-related factor demands involve factor demand functions whose arguments depend on the researcher's arbitrary normalization rule. This paper shows how sensitive the estimated elasticities are to the various normalizations that are possible. Alternatives that are not dependent on a normalization are suggested.     

Empirical factor demands and flexible functional forms: a bayesian approach

In this paper we compare classical econometrics, calibration and Bayesian inference in the context of the empirical analysis of factor demands. Our application is based on a popular flexible functional form for the firm's cost function, namely Diewert's Generalized Leontief function, and uses the well-known Berndt and Wood 1947–1971 KLEM data on the US manufacturing sector. We illustrate how the Gibbs sampling methodology can be easily used to calibrate parameter values and elasticities on the basis of previous knowledge from alternative studies on the same data, but with different functional forms. We rely on a system of mixed non-informative diffuse priors for some key parameters and informative tight priors for others. Within the Gibbs sampler, we employ rejection sampling to incorporate parameter restrictions, which are suggested by economic theory but in general rejected by economic data. Our results show that values of those parameters that relate to non-informative priors are almost equal to the standard SUR estimates, whereas differences come out for those parameters to which we have assigned informative priors. Moreover, discrepancies can be appreciated in some crucial parameter estimates obtained with or without rejection sampling.     

A Bayesian approach to imposing curvature on distance functions

The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis–Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models—a fixed effects model and a random effects model—are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed.     

A POST-KEYNESIAN AGE MODEL TO FORECAST ENERGY DEMAND IN SPAIN

This paper develops an extended input–output model for the estimation of energy demand and related issues. It is built on the last Spanish Symmetric Input–Output Table (IOT, 2005). It has been tested for the period 2005–2008 and used for forecasting energy demand for the years 2009–2012 under different economic scenarios. The model shares some traits of the computable and applied general equilibrium models where quantity and price systems are interwoven. The differences lie in the theories explaining output and prices. Our quantity system is based on Keynes’ principle of effective demand (broad energy multipliers are derived). The price system is based on the classical (Sraffian) theory of prices of production, akin to post-Keynesian full-cost prices. The general price system can be manipulated to account for the specificities of energy prices. Historical trends of energy coefficients are computed by extrapolation of past IOTs and calibration.     

Productivity,price recovery,capacity constraints and their financial consequences

Mining and fishing are both extractive industries, although one resource is renewable and the other is not. Miners and fishers pursue financial objectives, although their objectives may differ. In both industries financial performance is influenced by productivity and prices. Finally, in both industries capacity constraints influence financial performance, perhaps but not necessarily through their impact on productivity, and both industries encounter external as well as internal capacity constraints. In this study we develop an analytical framework that links all four phenomena. We use return on assets to measure financial performance, and our analytical framework is provided by the duPont triangle. We measure productivity change in two ways, with a theoretical technology-based index and with empirical price-based indexes. We measure price change with empirical quantity-based indexes. We measure internal capacity utilization by relating a pair of output quantity vectors representing actual output and full capacity output, and we develop physical and economic measures of internal capacity utilization. We also show how external capacity constraints can restrict the ability to reach full capacity output. The analytical framework has productivity change, price change and change in capacity utilization influencing change in return on assets.     

Interrelated Factor Demands and Technological Change: An Empirical Assessment of Adjustment for Sectors of the Dutch Economy

Using a translog cost functional form, a formal operational model with an adjustment process according to a first-order autoregressive scheme is presented, that allows the simultaneous determination of factor demands and of technological change in an input–output system. The analysis is carried out for sectors of the Dutch economy over the period 1954–83 and it reveals evidence of the dependence of factor demands on relative prices and on technological change.     

Forecasting with factor-augmented error correction models

As a generalization of the factor-augmented VAR (FAVAR) and of the Error Correction Model (ECM), Banerjee and Marcellino (2009) introduced the Factor-augmented Error Correction Model (FECM). The FECM combines error-correction, cointegration and dynamic factor models, and has several conceptual advantages over the standard ECM and FAVAR models. In particular, it uses a larger dataset than the ECM and incorporates the long-run information which the FAVAR is missing because of its specification in differences. In this paper, we examine the forecasting performance of the FECM by means of an analytical example, Monte Carlo simulations and several empirical applications. We show that FECM generally offers a higher forecasting precision relative to the FAVAR, and marks a useful step forward for forecasting with large datasets.     

Returns to scale in the United States intercity bus industry

This paper has taken into account the a priori restrictions available from neoclassical cost theory in evaluating the relationship between cost and the level of output and input prices for U.S. intercity bus service. A general translog cost function is used which allows tests of the degree of returns to scale, homotheticity and non-constant elasticities of substitution among input pairs. Major empirical findings are: (i) the intercity bus service can be modeled by a homothetic production function, (ii) operators can substitute labor for capital by using vehicles more extensively, (iii) there are potential economies of scale in the provision of intercity bus service, and (iv) the Cobb-Douglas functional form used in earlier studies of the industry is inappropriate.     

Permanent-transitory Decomposition in Var Models With Cointegration and Common Cycles

In this paper we derive permanent-transitory decompositions of non-stationary multiple times series generated by (r)nite order Gaussian VAR(p) models with both cointegration and serial correlation common features. We extend existing analyses to the two classes of reduced rank structures discussed in Hecq, Palm and Urbain (1998). Using the corresponding state space representation of cointegrated VAR models in vector error correction form we show how decomposition can be obtained even in the case where the number of common feature and cointegration vectors are not equal to the number of variables. As empirical analysis of US business fluctuations shows the practical relevance of the approach we propose.     

Hypothesis of Price Formation in Input–Output Tables

The goal of this paper is to check if different theoretical approaches to price formation can be verified in the structure of empirical input–output tables. From a propositive point of view, the hypothesis is made of two different markets (the ‘industrial’ market of intermediate and investment goods; and the ‘commercial’ market of final consumption goods), with two different mechanisms of price formation. The consequences of this hypothesis are outlined as regards deflation procedures. An empirical test of the theories about price formation and of the method of deflation suggested by the two-market hypothesis is made using 1985 Italian input–output tables at 1980 prices.