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A dynamic macroeconometric model for short-run stabilization in India

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  • Sushanta Mallick

Abstract

A small macroeconometric model examining the determinants of India's trade and inflation is developed to address the effects of a reform policy package similar to those implemented in 1991. This is different from the previous studies in two important respects. First, inflation has been modelled in an open economy context, and second, the non-stationarity of the data into the model and estimation procedures has been explicitly incorporated, suggesting that the stationarity assumption in earlier studies may be a source of misspecification. The model in this paper has been estimated using data from 1950 to 1995 employing fully modified Phillips-Hansen method of estimation to obtain the cointegrating relations and the short-run dynamic model. Policy simulations using dynamic simulation method compare the responses to devaluation with the responses to tight credit policy. It is shown that the trade balance effects of tight credit policy are more enduring than that of devaluation. The simulations demonstrate that the devaluation actually worsens trade balance and hence devaluation cannot be an option in response to a negative trade shock, whereas the reduction in domestic credit reflecting demand contraction produces a desirable improvement in the trade balance.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 36 (2004)
Issue (Month): 3 ()
Pages: 261-276

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Handle: RePEc:taf:applec:v:36:y:2004:i:3:p:261-276

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  1. James G. MacKinnon, 1990. "Critical Values for Cointegration Tests," Working Papers 1227, Queen's University, Department of Economics.
  2. Peter C.B. Phillips & Bruce E. Hansen, 1988. "Statistical Inference in Instrumental Variables," Cowles Foundation Discussion Papers 869R, Cowles Foundation for Research in Economics, Yale University, revised Apr 1989.
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  4. Kamal Upadhyaya & Dharmendra Dhakal, 1997. "Devaluation and the trade balance: estimating the long run effect," Applied Economics Letters, Taylor & Francis Journals, vol. 4(6), pages 343-345.
  5. Banerjee, Anindya & Dolado, Juan J. & Galbraith, John W. & Hendry, David, 1993. "Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data," OUP Catalogue, Oxford University Press, number 9780198288107.
  6. Lucas, Robert E. B., 1988. "Demand for India's manufactured exports," Journal of Development Economics, Elsevier, vol. 29(1), pages 63-75, July.
  7. Phillips, Peter C B & Hansen, Bruce E, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," Review of Economic Studies, Wiley Blackwell, vol. 57(1), pages 99-125, January.
  8. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
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  10. Sedgley, Nigel & Smith, Jeremy, 1994. "An Analysis of UK Imports Using Multivariate Cointegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 56(2), pages 135-50, May.
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Cited by:
  1. Valadkhani, A., 2005. "Macroeconomic Modelling: Approaches and Experiences in Development Countries," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 5(1).
  2. Valadkhani, Abbas, 2005. "Macroeconometric Modelling: Approaches and Experiences in Developing Countries," Economics Working Papers wp05-10, School of Economics, University of Wollongong, NSW, Australia.

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