Adolf Buse

Evaluating the Linearized Almost Ideal Demand System

Linearizing the Almost Ideal Demand System (LAIDS) by recourse to the Stone share weighted price index is common practice. Two issues are addressed here. First, scrutiny of the errors-in-variables implications of the linearization reveals that, not only is the SUR estimator inconsistent, but a consistent IV estimator cannot be constructed. Second, some alternatives to the Green-Alston elasticities specifically designed for the LAIDS model are developed, but neither these nor the Green-Alston elasticities are found to have any advantages over the conventional elasticity formulae. Some errors in the Green-Alston (1990) paper are corrected. The inconsistency and elasticity issues are documented by a Monte Carlo investigation.

Testing Homogeneity in the Linearized Almost Ideal Demand System

The behavior of exact tests for homogeneity (F and Hotelling T-super-2) is compared with size-adjusted LR tests in the linearized AIDS model with different approximating price indexes (Stone, Paasche, Laspeyres). The Monte Carlo evidence shows that test size distortions are sensitive to the correlation structure of prices, the time-series properties of the data, and the choice of price index. None of the results explains the persistent over-rejection of homogeneity in applied work. Copyright 1998, Oxford University Press.

Renewable and non-renewable resource demand in Canadian manufacturing industries

Abstract The role of natural resource inputs in Canadian manufacturing is investigated for the 1961–1976 period with a five factor value-added translog model. Price and substitution elasticities are reported for total manufacturing, twenty two-digit manufacturing industries and three sub-aggregates of total manufacturing (based on natural resource inputs). For capital, labour and energy, the elasticities are comparable with those reported elsewhere. For natural resource inputs, the price elasticities are low and the possibilities of substitution limited,

Tests for Additive Heteroskedasticity: Goldfeld and Quandt Revisited

A number of new tests for heteroskedasticity have recently become available. Using Monte Carlo methods this paper explores the small sample properties of some of these tests in the context of additive heteroskedasticity. Lagrange multiplier and Wald tests (and variants thereof) are found to be inferior to the likelihood ratio and Goldfeld and QuandtF tests. This is a reconfirmation of the conclusions obtained byGoldfeld/Quandt [1972] in their study of additive heteroskedasticity. The paper also contains some new results onAmemiyas GLS estimator of the additive heteroskedastic structure.

Estimating the trans-log cost function with insufficient observations

Abstract If the production technology is non-homothetic, efficient estimation of the trans-log approximation requires joint estimation of the cost and share equations. In this note we adopt the method of extraneous estimation to obtain a method of efficient joint estimation when there are insufficient observations on the cost equation.

Some Evidence on the Potential of Theil's Generalized Two Stage Least Squares Estimator

This paper evaluates the small sample performance of Theils generalized two stage least squares (G2SLS) estimator for a structural equation with first order autocorrelation. We find that the bias of G2SLS and a variant thereof is always smaller than that of conventional estimators such as Sargans 2SLS and Fairs method. The Theil estimators also dominate the Fair estimator in MSE and one of them shares first place in the MSE rankings with an asymptotically efficient modified Sargan 2SLS estimator. Because G2SLS uses a much smaller instrument set than the efficient Sargan estimators it provides a useful and practical solution to the degrees of freedom problem.

The Rise And Fall Of Extraneous Estimation: Lessons From Econometric History?

It is possible to view econometric history as the retrospective assessment of intellectual resource allocations. This paper uses such a perspective to examine the history of extraneous estimation. Independently proposed by Marschak (1939, Econometrica 7, 332-335) and Wold (1940, Efterfrigan pa jordbruksprodukter och dess kdnslighet for prisoch inkomstfordndringar (The demand for agricultural products and its sensitivity to price and income changes)), extraneous estimation was widely used as a collinearity solution in demand analysis from 1950 to 1980. We give a detailed account of the origins of this procedure and the theoretical work that clarified the statistical structure that underpinned it. The subsequent literature is then assessed in terms of the optimal use of available econometric tools and the interaction between theory and applications. We find that optimal econometric procedures were rarely used and that theoretical refinements continued to be published well after extraneous estimation had ceased to be a useful tool for demand analysis.

Canadian manufacturing: The impacts of natural resource price increases on input demands and costs

Abstract The separate effects of 50% increases in the prices of energy, renewable and nonrenewable natural resource inputs on factor demands and production costs are simulated for Canadian total manufacturing and six two-digit industries. Both renewable and nonrenewable natural resource price increases have a substantially greater effect upon the demands for other factors and upon production costs than a parallel energy price increase. These results are important from a policy perspective and justify the further disaggregation of inputs in this and in other models of input demand.