Relative productivity and factor-intensity in the manufacturing sectors of the U.S. and the U.K. during the nineteenth century

Summary The main objective of the paper is to examine the relationship between relative factor-costs and relative factor-intensity in the American and British textile sectors during the nineteenth century. The empirical attempt is made within an explicit theoretical framework (a model). This framework is based primarily onimplicit analytical arguments made by E. Rothbarth and H. J. Habakkuk while explaining the causes for the superiority of American industrial efficiency as compared with the British. It is shown that various indicators for the textile sectors during most of the second half of the nineteenth century favor a higher capitalintensity in the U.S.This work is part of a Ph.D. thesis written for the University of Rochester Department of Economics. The author is deeply indebted to S. Engerman for his valuable help and comments. He has also benefited from comments by E. Drandakis, G. S. Maddala, F. J. de Jong and T. K. Kumar. Needless to say, the author takes full responsibility for the content of this paper. Currently the author is an Assistant Professor at Florida State University, Tallahassee, Florida, U.S.A.     

The demand for cars and gasoline: A simultaneous approach

This paper develops and estimates a simple model of the demand and supply of cars and gasoline in Israel, focusing on an individual maximizing his life-time utility function under various constraints. Particular emphasis is placed on the transaction cost in a car purchase, and the fact that cars can be characterized by size and age factors which, in turn, affect running costs and maintenance costs. The empirical results show that a change in the price of gasoline (and/or the price of new cars) changes the structure of the stock of cars with respect to engine size.     

Alternative estimation methods for two-regime models: A mathematical programming approach

This paper suggests mathematical programming methods for estimating the parameters of piecewise regression models. Maximum likelihood estimation results in a non-convex optimization problem which is not continuously differentiable, and might even become discontinuous. To solve these difficulties we suggest two classes of methods. The first one consists of ‘scanning methods’, which are combinatorial in nature and therefore adequate for problems limited in size. The second class consists of ‘smoothing (or approximation) methods’, which can be used for larger problems. While scanning methods always find the global solution in a finite number of steps, smoothing methods are only guaranteed to find a local optimum. The paper ends with an application of the methods to the determination of export prices.