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Identification of temporal fundamental economic structure (FES) of India: An input-output and cross-entropy analysis

Listed author(s):
  • Thakur, Sudhir K.
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    This study provides an understanding of the economic structure and structural changes in the Indian economy utilizing the fundamental economic structure (FES) approach. The FES construct states that certain selected characteristics of an economy will vary predictably with economic size, as measured by gross national product, population and total gross output. The main problem addressed in this study concerns the question whether identifiable patterns of relations between various macro-aggregates and economic transactions can be revealed via input-output tables. Jensen, West and Hewings have discussed the tiered, partitioned, and temporal approaches to the identification of FES using input-output tables. This study addresses the following four research questions: Does a temporal FES exist for the Indian economy? What proportions of the cells are predictable? Can the 1968-1990 temporal FES predict 1993-1994 table? Does a temporal FES manifest an enhanced understanding of the Indian economic structure? Regression analyses are used to identify the FES and non-FES cells for the Indian economy. Small sample estimation issues are addressed applying the cross-entropy approach. The input-output tables for 1968-1969, 1973-1974, 1978-1979, 1983-1984, 1989-1990 and 1993-1994 provide data for the analysis. Analysis reveals that temporal FES includes primary, secondary and tertiary sectors as components. This research has extended the notion of FES to include weak, moderate and strong FES cells.

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    Article provided by Elsevier in its journal Structural Change and Economic Dynamics.

    Volume (Year): 19 (2008)
    Issue (Month): 2 (June)
    Pages: 132-151

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    Handle: RePEc:eee:streco:v:19:y:2008:i:2:p:132-151
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    1. K Pandit, 1990. "Tertiary Sector Hypertrophy during Development: An Examination of Regional Variation," Environment and Planning A, , vol. 22(10), pages 1389-1406, October.
    2. K Pandit, 1990. "Tertiary sector hypertrophy during development: an examination of regional variation," Environment and Planning A, Pion Ltd, London, vol. 22(10), pages 1389-1405, October.
    3. Golan, Amos & Judge, George & Robinson, Sherman, 1994. "Recovering Information from Incomplete or Partial Multisectoral Economic Data," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 541-549, August.
    4. Pandit, Kavita, 1990. "Service Labor Allocation during Development: Longitudinal Perspectives on Cross-sectional Patterns," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 24(1), pages 29-41.
    5. Syrquin, Moshe, 1988. "Patterns of structural change," Handbook of Development Economics,in: Hollis Chenery & T.N. Srinivasan (ed.), Handbook of Development Economics, edition 1, volume 1, chapter 7, pages 203-273 Elsevier.
    6. Sherman Robinson & Andrea Cattaneo & Moataz El-Said, 2001. "Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods," Economic Systems Research, Taylor & Francis Journals, vol. 13(1), pages 47-64.
    7. Balaji Parthasarathy, 2004. "India's Silicon Valley or Silicon Valley's India? Socially Embedding the Computer Software Industry in Bangalore," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 28(3), pages 664-685, 09.
    8. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    9. Hewings, Geoffry J. D. & Jensen, Rodney C. & West, Guy R. & Sonis, Michael & Jackson, Randall W., 1989. "The spatial organization of production: An input-output perspective," Socio-Economic Planning Sciences, Elsevier, vol. 23(1-2), pages 67-86.
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