Advertisement

Journal of Quantitative Economics

, Volume 3, Issue 1, pp 21–32 | Cite as

Reinvestigating the Nature of Persistence of Shocks in the Macroeconomic Variables Relating to the Indian Economy with Special Reference to Structural Changes and Seasonality

  • Samarjit Das
  • Balwant Singh
Article

Abstract

Over the last two decades, there is a substantial debate on the persistence of shocks, in terms of their transitory and permanent nature, caused to the macroeconomic aggregates. Macroeconomic variables with transitory shocks will revert back to the long-run deterministic path eventually, whereas variables with permanent shocks will move according to random walk having no fixed predetermined path. These two series known as Trend Stationary (TS) and Difference Stationary (DS), respectively, have their significance in the specification of the regression equation and testing competing economic theories. Consequently there are a good amount of studies to classify the macroeconomic aggregates as TS vs. DS. In this context, relatively new developments of seasonal integration and presence of structural breaks in the macro variables has aroused a need to reinvestigate these hypotheses afresh. This paper makes an attempt to examine some of these issues by making use of the Indian data.

JEL Classification

C32 E31 and E32 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, T. W. and A. Takemura (1986) Why do non-invertible estimated moving average occur? Journal of Time Series Analysis, 7, 235–254.CrossRefGoogle Scholar
  2. Banerjee, A., R. L. Lumsdaine, and J. Stock (1992) Recursive and Sequential tests of the unit root and trend break hypotheses: theory and international Evidence, Journal of Business and Economic Statistics, 10, 271–287.Google Scholar
  3. Barsky, R. B., and J. A. Miron (1989) The Seasonal Cycle and the Business Cycle, Journal of Political Economy, 97, 503–35.CrossRefGoogle Scholar
  4. Beaulieu, J. J. and J. A. Miron (1993) Seasonal unit roots in aggregate US data, Journal of Econometrics, 55, 305–328.CrossRefGoogle Scholar
  5. Beaulieu, J. J. and J. A. Miron (1991) The Seasonal Cycle in United States Manufacturing, Economics Letters, 37(2), 115–118CrossRefGoogle Scholar
  6. Canova, F. and B. E. Hansen (1995) Are seasonal pattern s constant over time?: A test for seasonal stability, Journal of Business and Economic Statistics, 13, 237–252.Google Scholar
  7. Chaterjee, S., and B. Ravikumar (1992), A stochastic Growth model with seasonal Perturbations, Journal of MonetaryEeconomics, 29, 59–86.Google Scholar
  8. Christiano, L. and M. Eichenbaum (1990) Unit roots in real GNP: Do we know and do we care? In Meltzer, A (ed.) Unit roots, Investment Measures, and other Essays, 7–61, Carnegie-Rochester Conference Series on Public Policy, 32, North Holland.Google Scholar
  9. DeJong, D. N., J. C. Nankervis, N. E. Savin, and C. H. Whiteman (1992a) The power problems of unit root tests in time series with autoregressive errors, Journal of Econometrics, 53, 323–433.CrossRefGoogle Scholar
  10. DeJong, D. N., J. C. Nankervis, N. E. Savin, and C. H. Whiteman (1992b) Integration versus trend trend stationarity in time series, Econometrica, 60, 423–433.CrossRefGoogle Scholar
  11. Dickey, D. A. and W. A. Fuller (1981) Likelihood ratio statistics for autoregressive time series with a unit root, Econometrica, 49, 1057–1072.CrossRefGoogle Scholar
  12. Dua, P. and T. Mishra (1999) Presence of Persistence in Industrial Production: The Case of India, The Indian Economic Review, 35, No.1.Google Scholar
  13. Franses, P. H. (1990) Testing for seasonal unit roots in monthly data, Econometric Institute Report No. 9032A, Erasmus University, Rotterdam.Google Scholar
  14. Franses, P. H. (1994) Testing for seasonality, Economic Letters, 38, 259–262.CrossRefGoogle Scholar
  15. Fuller, W. A. (1976) Introduction to Statistical Time series, NY, Wiley.Google Scholar
  16. Ghysels, E. (1988) A study toward a dynamic theory of seasonality for economic time series, Journal of American Statistical Association, 83, 168–72.CrossRefGoogle Scholar
  17. Ghysels, E. (1990) Unit Root tests and the statistics pitfalls of seasonal adjustment: The case of US Postwar real gross national product, Journal of Business and Economic Statistics, 8, 145–152.Google Scholar
  18. Ghysels, E. (1994) On the periodic Structure of business cycle, Journal of Business and Economic Statistics, 12, 289–298.Google Scholar
  19. Ghysels, E. and P. Perron (1993) Effects of seasonal adjustment filters on tests for a unit root, Journal of Econometrics, 55, 57–98.CrossRefGoogle Scholar
  20. Ghysels, E., H. S. Lee, and J. Noh (1994) Testing for unit roots in seasonal time series: some theoretical extensions and a Monte Carlo investigation, Journal of Econometrics, 62, 415–442.CrossRefGoogle Scholar
  21. Hall. A. (1994) Testing for a unit root in time series with pretest data based model selection, Journal of Business and Economic Statistics, 12, 461–470.Google Scholar
  22. Hansen (1993) Testing for unit roots using covariates, Manuscript, University of Rochester.Google Scholar
  23. Hylleberg, S. (1992) Modelling seasonal variation, in C. P. Hargreaves (ed.), Nonstationary Time Series Analysis and Cointegration, Oxford University Press, Oxford.Google Scholar
  24. Hylleberg, S. (1995) Tests for seasonal unit roots: General to specific or specific to general? Journal of Econometrics, 69, 5–25.CrossRefGoogle Scholar
  25. Hylleberg, S. (eds.), (1992) Modelling seasonality, Oxford University Press, Oxford.Google Scholar
  26. Hylleberg, S., C. Jorgensen and N. K. Sorensen (1993) Seasonality in macroeconomic time series, Empirical Economics, 18, 321–335.CrossRefGoogle Scholar
  27. Kang, K. M. (1975) A Comparison of Estimators of Moving average Processes, Unpublished manuscript, Australian Bureau of Census.Google Scholar
  28. Krishnan, R. and K. Sen (1995) Measuring Persistence in Industrial Output: The Indian Case, Journal of Development Economics, 48, 25–41.CrossRefGoogle Scholar
  29. Krishnan, R., K. Sen and S. Majumdar (1992) Unit roots in Indian Macroeconomic Time-Series: Tests and Implication, Journal of Quantitative Economics, 8, 67–82.Google Scholar
  30. Miron. J.A. (1990) Economics of Seasonal Cycle, NBER working paper No, 3522.CrossRefGoogle Scholar
  31. Miron. J.A. and J.J. Beaulieu (1996) What Have Macroeconomists Learned About Business Cycles from the Study of Seasonal Cycles, Review of Economics and Statistics, 78, February Miron. J.A. and S.P. Zeldes (1988) Seasonality, Cost Shocks, and the Production Smoothing Model of Inventories Econometrica, 56(4), 877–908.CrossRefGoogle Scholar
  32. Nelson, C. R. and C. I. Plosser (1982) Trends and random walk in macroeconomic time series, Journal of Monetary Economics, 10, 139–162.CrossRefGoogle Scholar
  33. Nelson, C. R. and H. Kang (1981) Spurious periodicity in inappropriately detrended time series, Journal of Monetary Economics, 10, 139–162.CrossRefGoogle Scholar
  34. Perron, P. (1989) The great crash, the oil price shock, and the unit root hypotheses, Econometrica, 57, 1361–1401.CrossRefGoogle Scholar
  35. Perron, P. and S. Ng (1996) Useful Modifications to some unit root tests with dependent errors and their local asymptotic properties, Review of Economic Studies, 63, 435–465.CrossRefGoogle Scholar
  36. Phillips, P. C. B. and P. Perron (1988) Testing for a unit root in time series regression, Biometrica, 75, 335–346.CrossRefGoogle Scholar
  37. Rudebusch, G. (1992) Trends and random walks in Macroeconomic time series: A reexamination, International Economic Review, 33, 661–680.CrossRefGoogle Scholar
  38. Said, S. E. and D. A. Dickey (1984) Testing for unit roots in autoregressive-moving average models of unknown order, Biometrika, 71, 599–607.CrossRefGoogle Scholar
  39. Schwert, G. W. (1989) Tests for Unit roots: A Monte Carlo investigation, Journal of Business and Economic Statistics, 7, 147–159.Google Scholar
  40. Stock, J. (1994) Unit roots, structural break and trend, Handbook of Econometrics, Vol.4, 2740–2841, Elsevier Science.Google Scholar
  41. Toda, H.Y. and P.C.B. Phillips (1993) Vector autoregression and causality, Econometrica, 61, 1367–1393.CrossRefGoogle Scholar
  42. Tumovsky, S. and V. D’Orey (1986) Monetary policies in interdependent economies with stochastic disturbances: A strategic Approach, Economic Journal, 96, 696–721.CrossRefGoogle Scholar
  43. Upadhyay, G. (1992) Modelling Nonstationary Macro Time-series, RBI Occasional Papers, 32, No. 1.Google Scholar
  44. West. K.D. (1988) On the interpretation of near random walk behaviour in GNP, American Economic Review, 78, 202–208.Google Scholar
  45. Zivot, E. and D. W. K. Andrews (1992) Further evidence on the Great crash, the Oil Price Shock, and the unit root hypotheses, Journal of business and Economic Statistics, 10, 251–270.Google Scholar

Copyright information

© The Indian Econometric Society 2005

Authors and Affiliations

  1. 1.Reserve Bank of IndiaIndia

Personalised recommendations