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Economic Systems Research | 1990

Aggregation in Input–Output Models: a Comprehensive Review, 1946–71

Kern O. Kymn

This paper consists of two parts. The first surveys the theory of aggregation that had been developed in Input–Output analysis up to 1971. This review provides a comprehensive portraft of the development of aggregation theory in relation to the concepts of aggregation bias and consistency. The second part surveys the theory of aggregation that has evolved through the extension of the concept of entropy and information theory. It reviews the theory of correlational measures of aggregation and the linear aggregation coeficient. The objective of the paper is to summarize studies of various authors who have demonstrated how the trade-offs between the smaller order of aggregation and the infusion of aggregation bias may be minimized with a view toward developing an optimal aggregation system in Input–Output models.


Energy Economics | 1999

Modeling economies of scale : the case of US electric power companies

John J. Hisnanick; Kern O. Kymn

Modeling and validating the existence of technical progress within the neoclassical production function specification has been facilitated through the translog functional form. However, attempts to separate out the effects of technical progress and returns to scale has been limited. This study develops and presents a model for testing the existence of these two separate effects using data from a sample of US electric power companies. The analysis found that for these electric utilities there existed increasing returns to scale and technical progress that was energy using but capital-neutral. However, scale effects were found to be a dominant factor in lessening the impact of declining average productivity.


Energy Economics | 1992

The impact of disaggregated energy on productivity: A study of the US manufacturing sector, 1958–1985

John J. Hisnanick; Kern O. Kymn

Abstract The issue of the productivity slowdown of the 1970s and 1980s has received considerable analysis in the literature. However, the issue of the impact of energy on productivity is still debated. This study contributes to the debate, with the hope that some sight could be provided through disaggregating the factor input energy into two components; a petroleum component and a non-petroleum component. By analysing labour productivity growth, total factor productivity growth and labour intensity ratios, the disaggregated energy component can be viewed as a major influence in explaining the productivity decline.


The American economist | 1976

A Review of Industry Aggregation in Input-Output Models

Kern O. Kymn; John Norsworthy

Aggregation in input-output analysis is the operation of combining of sectors to groups of sectors for the purpose of reducing the size of the input-output tables to a smaller order. Although this definition is not rigorous, it is adequate for all practical purposes. Examples of a more rigorous definition of aggregation can be found in Fisher [15] or Ijiri [23, 24] or Rosenblatt [43,44], Investigators often found that handling and comprehending a large and a detailed table were costly and cumber some. Such a difficulty of managing a detailed table is indeed reduced by aggregation and aggrega tion works as an advantage to the investigator by saving the cost of working with a large table. How ever, valuable information concerning the detailed subsets of the original table is lost by aggregation. Thus the trade-off an investigator is confronted with is the loss of information that in turn results in the infusion of the aggregation bias into the merged input-output models. Because of such trade-offs, economists have long searched for the extraction of an optimal technique of aggregation in input-output analysis with vigor. This paper reviews the theory of aggregation in input-output analysis in relation to consistency, aggregation bias, aggregation coefficient, and in formation theory that has been developed in the past decades. We begin our survey by defining basic notations. Let Xtj represent the flow of goods and services from industry i to industry j. There are m industries. Let Xt and F? be total output of industry i. In matrix notation X = (I-A)-1F (1)


Atlantic Economic Journal | 1985

Energy-Capital and energy-labor: Complementarity and substitutability

Mahmood Moghimzadeh; Kern O. Kymn

I. Introduct ion The objective of this paper is to determine the aggregate long-run relationship between capital and energy and between labor and energy in the production of manufacturing output, disaggregating energy into electric and non-electric energy for the years 1954 to 1977. A brief review of the literature will outline the background for this effort. A translog study performed by Berndt and Wood [1975] showed that energy (E) and capital (K) are complements in the U.S. manufacturing sector for the years 1947 to 1971. Their model consisted of four factors: capital, energy, labor, and materials. Hudson and Jorgenson [1974] performed an empirical study of factor substitution that applied a translog cost function at the industry level. Their model also incorporated capital services, labor services, energy input, and nonenergy inputs. They found that energy is a substitute for labor and a complement to capital. Griffin and Gregory [1976] applied a translog production function similar to the one used by Berndt and Wood, but they found capital and energy to be substitutes in the long run, and rejected Berndt and Woods conclusions about capital-energy complementarity. In another study, Pindyck [1979(a)] examined time-series cross-sectional data for 10 industrial countries during the period 1959 to 1974. He concluded that in the long run, energy and capital are substitutes, and the elasticity of substitution between energy and capital is 0.8 in the United States. Halvorsen and Ford [1979] also estimated the long-run relationship between energy and capital using cross-sectional data for two-


Economics Letters | 1979

Alternative computing formulas for the generalized inverse and the evaluation of their performances

Kern O. Kymn; John Norsworthy; Tatsuo Okamoto

Abstract Computational methods for evaluating the generalized inverse are described. Alternative approaches are evaluated in terms of accuracy and speed of computation on a UNIVAC 1108 computer.


Economics Letters | 1983

Rational choice and gain functions derived from a fuzzy relation

Jin Bai Kim; Kern O. Kymn

Abstract No theory of choice and gain based on a set-theoretic approach developed from new relational concepts termed ‘fuzzy relations’ in mathematics [Kim (1979,1980)] has been advanced. As evidenced in the literature [Kim (1979, 1980)], advances have occurred in set theory involving the concept of fuzzy relations that appear to be suitable for application in constructing a new and rigorous theory of choice and gain. The purpose of this paper is to derive rational choice and gain functions using the concept of fuzzy relations.


Bulletin of Economic Research | 2001

The CES‐‐Translog Production Function, Returns to Scale and AES

Kern O. Kymn; John J. Hisnanick

The translog functional form imposes no a priori restrictions on the substitution possibilities between the factor inputs, by relaxing the assumption of strong separability, and the CES-translog cost function specification allows for testing homothetic technology with Hicks-neutral technical change. In this paper an n-factor CES-translog production function is presented which develops the parameters to directly assess scale effects from those due to technology in the production structure. In addition, by applying Shephards lemma it was possible to derive the input demand functions, as well as the partial elasticities of substitution and the cross-partial price elasticities of demand for a generalized CES-translog production structure. Copyright 2001 by Blackwell Publishing Ltd and the Board of Trustees of the Bulletin of Economic Research


Energy | 1979

U.S. interindustry cost structure of the energy sectors, 1958, 1967, and 1968

Kern O. Kymn; Walter P. Page

The purpose of this research has been 1.(1) to examine the similarity in the cost structure of energy sectors in the 86-order input-output tables (1967)2.(2) to examine changes for the periods 1958–1967 and 1967–1968, in energy sector cost structures. This analysis provides information on which non-energy sectors have been most influenced by both technological and price changes in the energy sectors.


Energy | 1978

Some interindustry empirical evidence on the question of stockpiling crude oil

Kern O. Kymn; Walter P. Page

86-order interindustry transactions tables for selected years are used to assess the forward and backward linkage effects of energy sectors, 1958–1970, in the U.S. economy. The magnitude of the linkage effects were obtained by calculating intermediate input and demand coefficients. The crude oil sector is found to have the second largest forward linkages of all sectors in the 86-order table and the largest of all energy sectors. As a consequence, there is strong empirical evidence supporting the argument for stockpiling crude oil supplies.

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Eugene Kouassi

West Virginia University

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John J. Hisnanick

United States Census Bureau

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Joel Sango

École Normale Supérieure

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John Norsworthy

Bureau of Labor Statistics

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Walter P. Page

West Virginia University

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