Journal Article Liquidity Preference and Risk Aversion with an Exponential Utility Function: Comment Get access G. O. Bierwag G. O. Bierwag University of Oregon Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 41, Issue 2, April 1974, Pages 301–302, https://doi.org/10.2307/2296720 Published: 01 April 1974
Journal Article Derived Demand, Returns to Scale and Stability Get access Michel Andrieu Michel Andrieu Department of Consumer and Corporate Affairs Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 41, Issue 3, July 1974, Pages 405–417, https://doi.org/10.2307/2296758 Published: 01 July 1974
Journal Article Non-linearity and Non-stationarity in Dynamic Econometric Models Get access Roger J. Bowden Roger J. Bowden University of Auckland Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 41, Issue 2, April 1974, Pages 173–179, https://doi.org/10.2307/2296711 Published: 01 April 1974
J. M. Grandmont, A. P. Kirman, W. Neuefeind; A New Approach to the Uniqueness of Equilibrium12, The Review of Economic Studies, Volume 41, Issue 2, 1 April 1974
Many studies of k-class estimators have investigated their distributional properties (see Kadane [4], pp. 723-724 for a useful summary). Here we are concerned with the mathematical analysis of the k-class formulae rather than with their statistical analysis. Other work in this field includes Theil [10], pp. 233-237, Maeshiro [7], Oi [8] and Kadiyala [5]. In this paper we examine how the k-class estimator varies with k. We derive an expression from which the main features of the graph of a k-class estimator may be obtained and show that, except in a subspace of measure zero, the parameter estimates and their asymptotic standard errors become infinite for some value k1 that is common to the parameters of an equation whilst their ratios (the t-ratios) tend to zero.
Journal Article Correct Fixed-capital Replacement in Input-output Growth Models Get access W. F. Gossling W. F. Gossling University of East Anglia and West Virginia University Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 41, Issue 4, October 1974, Pages 525–531, https://doi.org/10.2307/2296702 Published: 01 October 1974
Journal Article Generalized Errors in Variables Regression Get access M. C. Casson M. C. Casson University of Reading Search for other works by this author on: Oxford Academic Google Scholar The Review of Economic Studies, Volume 41, Issue 3, July 1974, Pages 347–352, https://doi.org/10.2307/2296754 Published: 01 July 1974
The purpose of a recent paper by Herbert Grubel and Peter Lloyd [5] was to examine the nature and magnitude of the bias introduced by the neglect of factor substitution between produced and primary inputs when calculating effective rates of protection (ERP). They concluded that the bias from neglecting substitution possibilities between produced and primary inputs is usually small. The purpose of this paper is to make three comments on their conclusions. Firstly, there is an error, or possibly a misprint, which can be misleading. Secondly, because Grubel and Lloyd restrict their calculations to a narrower range of parameter values than is empirically reasonable their results understate the magnitude of the bias which one might reasonably expect to encounter in empirically grounded calculations. Thirdly, Grubel and Lloyd conclude that the bias from neglecting substitution possibilities is usually small 3 without discussing criteria for determining when a bias becomes significant. It is shown here that the magnitude of the bias encountered when using empirically relevant data is very significant because the ranking of production processes by their calculated ERP can vary greatly with biased estimates. These comments have significant implications for the notion that the elasticity of substitution is not an important parameter in calculating the ERP.
Most studies of the demand for cars are designed to explain new purchases and assume that purchases are divided into net investment and replacement. Replacement is invariably identified with stock depletion, defined either as scrapping (determined by the length of life of a car) or as depreciation (determined by the decline in the price of a used car with age). Implicit in these theories is the assumption that the elasticity of substitution between the new and used car markets is rather high. This assumption is necessary to ensure that the price mechanism will induce consumers to buy new cars to make good the stock depleted by the scrapping or depreciation of used cars. Most empirical evidence indicates that this assumption is not justified and that new and used cars are poor substitutes, e.g. [1], [8] and [6]. Since the low degree of substitution between the two markets insulates new car purchases from the factors that influence the stock of used cars, stock depletion cannot explain replacement purchases of new cars. In this note an alternative approach will be suggested and its use illustrated by the case of new car sales in the US. The advantages of this approach are: (1) replacement is directly observable; (2) the assumption of perfect substitution between new and used car services is not necessary; and (3) it may help account for a series of implausible estimates of the depreciation rate that have been obtained from more orthodox models. It is generally accepted in the US automobile industry that new and used cars are bought by distinct groups. For instance, White in a recent study of the industry [6] says: New cars are not bought by a random selection of car owners but, instead, tend to be bought by a small group who buy new cars comparatively frequently and sell their used cars to the general public to hold. As an approximation, therefore, we can split buyers into two groups, those who buy their car new and those who buy it used, treating these groups as distinct. The demand of the new car buying group is primarily for replacement, since between 80 and 90 per cent of them trade-in or sell an old car when buying a new one; the average time from purchase to resale is between two and three years. This leads us to a definition of replacement as the process by which a consumer disposes of a car bought i years ago and purchases a new one. The existence of a well-developed second-hand market confirms that the replacement interval, i, is considerably shorter than the lifetime of a car, so that replacement does not equal scrapping. This replacement interval will vary between household and we shall observe a distribution of intervals, say c(i), which will determine the lag distribution generating replacement, U, from past purchases, Q; i.e.