COMPARATIVE ANALYSIS OF ECONOMIC STRUCTURES IN AN INPUT-OUTPUT FRAMEWORK: EXPERIMENTS WITH EAST EUROPEAN DATA.

摘要

This study explores the possibility of ranking economic structures by their degree of structural interdependence. By "economic structure" is meant, in this study, not the direct input-output coefficients matrix A which many comparative studies of economic structures have used, but the full (direct plus indirect) coefficients matrix B('-1) = (1 - A)('-1). This inverse matrix shows the full impact of the output of each sector in the economy on all the others. It is therefore thought to represent the basic technological structure of interdependence in a given economic system.;The underlying East European input-output tables are also used to determine interindustry forward and backward linkages. For this purpose, the inverse matrix B('-1), rather than the often used direct input-output coefficients matrix A, is used. High economic interdependence is characterized by high values of average backward and average forward linkages. The component economic sectors are ranked according to their forward and backward linkages. It is pointed out that the information obtained from the use of the dominant eigenvalues of B('-1) matrices not only does not contradict the information obtained from the use of the A matrices but also may give the same information as that obtained from the use of linkages as measures of economic interdependence.;The study is represented in eight chapters. The first chapter states the problem and outlines the methodological framework. The second chapter reviews briefly the different methods of structural comparisons. The eigenvalue method for comparing economic structures is suggested. Chapter 3 ranks economic structures by their degree of interdependence as implied by the use of the dominant eigenvalues. Appendix I and II augment Chapter 2 and 3. In Chapter 4, economic interdependence is measured by use of linkages. The results of linkage comparisons are compared with the results of dominant eigenvalue comparisons. And the two sets of results are found to agree to some extent.;In Chapter 5, the possibility of using the degree of structural interdependence as measured by the dominant eigenvalues, (lamda), as indicator of the phase of economic development and technological change is explored. It is argued that only technological change can cause structural change in an input-output framework. Chapter 6 presents other ratios which indicate structural change. About nine ratios ranging from Delivery Coefficients to Sector Shares in Total Imports are used for comparing the different aspects of economic structures.;The idea of a characteristic root of a non-negative indecomposable square matrix is utilized. The assumption that the inverse matrix B('-1) = (1 - A)('-1) is indecomposable allows economic structures defined by it to be compared by use of their corresponding dominant eigenvalues, (lamda). A set of defintions and theorems relating to such non-negative indecomposable matrices allow structural comparisons for certain East European input-output matrices to be ranked according to their degree of structural interdependence.;In Chapter 7, certain sectors are a priorily grouped into three complexes: Agricultural Complex; Chemical Complex; and the Machinery Complex. For each complex, the sector with the highest ratio of final demand, referred to as the key sector, is investigated in relation to the rest of the economy. In particular, the Key-Sector-Growth Quotient is used to determine whether the complexes are specialized or not. It is concluded in Chapter 8 that a single number like the dominant eigenvalues can hardly take into account all the administrative (or institutional) structural differences. Use of such measures can be interpreted only as part of the continuous effort for developing satisfactory ways of comparing complex, and in many respects, disparate economic structures.