IDEAS home Printed from https://ideas.repec.org/a/ime/imemes/v16y1998i1p57-79.html
   My bibliography  Save this article

Nonstationary Time-Series Modeling versus Structural Equation Modeling: With an Application to Japanese Money Demand

Author

Listed:
  • Hsiao, Cheng

    (U Southern CA and National Taiwan U)

  • Fujiki, Hiroshi

    (Bank of Japan)

Abstract

The issues of identification, estimation, and statistical inferences of nonstationary time series and simultaneous equation models are reviewed. It is shown that prior information matters and the advantage of dichotomization of the traditional autoregressive distributed lag model into the long-run equilibrium relation and the short-run dynamic adjustment process as an empirical modeling device may be exaggerated. A Japanese money demand study is used to illustrate that a direct approach yields a more stable long-run and short-run relationship and has better predictive power than the approach of letting the data determine the long-run relationship and modeling the short-run dynamics as an adjustment of the deviation from its equilibrium position.

Suggested Citation

  • Hsiao, Cheng & Fujiki, Hiroshi, 1998. "Nonstationary Time-Series Modeling versus Structural Equation Modeling: With an Application to Japanese Money Demand," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 16(1), pages 57-79, May.
  • Handle: RePEc:ime:imemes:v:16:y:1998:i:1:p:57-79
    as

    Download full text from publisher

    File URL: http://www.imes.boj.or.jp/research/papers/english/me16-1-3.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cheng Hsiao, 1997. "Statistical Properties of the Two-Stage Least Squares Estimator Under Cointegration," Review of Economic Studies, Oxford University Press, vol. 64(3), pages 385-398.
    2. Phillips, Peter C B, 1995. "Fully Modified Least Squares and Vector Autoregression," Econometrica, Econometric Society, vol. 63(5), pages 1023-1078, September.
    3. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
    4. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    5. Goldfeld, Stephen M. & Sichel, Daniel E., 1990. "The demand for money," Handbook of Monetary Economics, in: B. M. Friedman & F. H. Hahn (ed.), Handbook of Monetary Economics, edition 1, volume 1, chapter 8, pages 299-356, Elsevier.
    6. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    7. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    8. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    9. Park, Joon Y. & Phillips, Peter C.B., 1988. "Statistical Inference in Regressions with Integrated Processes: Part 1," Econometric Theory, Cambridge University Press, vol. 4(3), pages 468-497, December.
    10. M. Hashem Pesaran & Yongcheol Shin, 2002. "Long-Run Structural Modelling," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 49-87.
    11. Phillips, P C B, 1991. "Optimal Inference in Cointegrated Systems," Econometrica, Econometric Society, vol. 59(2), pages 283-306, March.
    12. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    13. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    14. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    15. Stock, James H, 1987. "Asymptotic Properties of Least Squares Estimators of Cointegrating Vectors," Econometrica, Econometric Society, vol. 55(5), pages 1035-1056, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Daigneault, Adam J. & Sohngen, Brent & Kim, Sei Jin, 2016. "Estimating welfare effects from supply shocks with dynamic factor demand models," Forest Policy and Economics, Elsevier, vol. 73(C), pages 41-51.
    2. Borzykowski, Nicolas, 2019. "A supply-demand modeling of the Swiss roundwood market: Actors responsiveness and CO2 implications," Forest Policy and Economics, Elsevier, vol. 102(C), pages 100-113.
    3. Shiratsuka, Shigenori, 2001. "Is There a Desirable Rate of Inflation? A Theoretical and Empirical Survey," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 19(2), pages 49-83, May.
    4. Umanath Malaiarasan & R. Paramasivam & K. Thomas Felix & S. J. Balaji, 2020. "Simultaneous equation model for Indian sugar sector," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 22(1), pages 113-141, June.
    5. Tang, Tuck Cheong, 2004. "Demand for broad money and expenditure components in Japan: an empirical study," Japan and the World Economy, Elsevier, vol. 16(4), pages 487-502, December.
    6. Dekle, Robert & Hsiao, Cheng & Wang, Siyan, 2001. "Do High Interest Rates Appreciate Exchange Rates during Crisis? The Korean Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 63(3), pages 359-380, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. M. Hashem Pesaran & Yongcheol Shin, 2002. "Long-Run Structural Modelling," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 49-87.
    2. Campos, Julia & Ericsson, Neil R. & Hendry, David F., 1996. "Cointegration tests in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 70(1), pages 187-220, January.
    3. Peter Phillips & Hyungsik Moon, 2000. "Nonstationary panel data analysis: an overview of some recent developments," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 263-286.
    4. James Davidson, 2013. "Cointegration and error correction," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 7, pages 165-188, Edward Elgar Publishing.
    5. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    6. Quintos, Carmela E., 1998. "Analysis of cointegration vectors using the GMM approach," Journal of Econometrics, Elsevier, vol. 85(1), pages 155-188, July.
    7. Christopher P. P. Shafuda & Utpal Kumar De, 2020. "Government expenditure on human capital and growth in Namibia: a time series analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-14, December.
    8. Minxian, Yang, 1998. "System estimators of cointegrating matrix in absence of normalising information," Journal of Econometrics, Elsevier, vol. 85(2), pages 317-337, August.
    9. Davidson, James, 1998. "Structural relations, cointegration and identification: some simple results and their application," Journal of Econometrics, Elsevier, vol. 87(1), pages 87-113, August.
    10. Cheng, Xu & Phillips, Peter C.B., 2012. "Cointegrating rank selection in models with time-varying variance," Journal of Econometrics, Elsevier, vol. 169(2), pages 155-165.
    11. H. Peter Boswijk & Jurgen A. Doornik, 2004. "Identifying, estimating and testing restricted cointegrated systems: An overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 440-465, November.
    12. H. Youn Kim & Junsoo Lee, 2001. "Quasi-fixed inputs and long-run equilibrium in production: a cointegration analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(1), pages 41-57.
    13. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, April.
    14. Kitamura, Yuichi & Phillips, Peter C. B., 1997. "Fully modified IV, GIVE and GMM estimation with possibly non-stationary regressors and instruments," Journal of Econometrics, Elsevier, vol. 80(1), pages 85-123, September.
    15. Pierre Perron & Gabriel Rodriguez, 2012. "Residual test for cointegration with GLS detrended data," Documentos de Trabajo / Working Papers 2012-327, Departamento de Economía - Pontificia Universidad Católica del Perú.
    16. Li, Yikang & Maddala, G. S. & Rush, Mark, 1995. "New small sample estimators for cointegration regression: Low-pass spectral filter method," Economics Letters, Elsevier, vol. 47(2), pages 123-129, February.
    17. Lütkepohl, Helmut, 1999. "Vector autoregressions," SFB 373 Discussion Papers 1999,4, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    18. Gabriel Rodriguez & Pierre Perron, 2013. "Single-equation tests for Cointegration with GLS Detrended Data," Boston University - Department of Economics - Working Papers Series 2013-016, Boston University - Department of Economics.
    19. P. P. Shafuda, Christopher & De, Utpal Kumar, 2017. "Upshot of Public Health Expenditure on Economic Development," MPRA Paper 101846, University Library of Munich, Germany, revised 03 Jan 2018.
    20. Biqing Cai & Jiti Gao & Dag Tjøstheim, 2017. "A New Class of Bivariate Threshold Cointegration Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 288-305, April.

    More about this item

    JEL classification:

    • E41 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Demand for Money
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ime:imemes:v:16:y:1998:i:1:p:57-79. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/imegvjp.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kinken (email available below). General contact details of provider: https://edirc.repec.org/data/imegvjp.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.