IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v48y2016i37p3558-3568.html
   My bibliography  Save this article

Detecting multiple factors in panel data: an application on the growth of local regions in China

Author

Listed:
  • W.D. Chen

Abstract

Due to unbalanced growth in China’s local regions, we construct a panel data model with multiple common factors to examine the differences among the growth factors in these areas. This article shows the various impacts from the supply and demand sides on economic growth. Different from the demand side, the supply-side impacts have permanent influences. This article focuses on these deep and profound impacts to explain the reasons behind China’s fast economic growing. By using data on 27 regions from 1958 to 2013, we summarize the main permanent influences along three lines. The first comes from the coastal regions, which have learned modern technology and systems from foreign companies, such as in Guangdong, Zhejiang, Fujian and Liaoning. The second comes from big cities, such as Beijing and Shanghai, in which a huge migration has given the companies opportunities to recruit excellent workers, making the resource allocation specialized and more efficient. The third is from the government’s major public works, which have improved areas’ infrastructure and assisted long-run economic growth, such as for Sichuan, Guangxi and Yunnan.

Suggested Citation

  • W.D. Chen, 2016. "Detecting multiple factors in panel data: an application on the growth of local regions in China," Applied Economics, Taylor & Francis Journals, vol. 48(37), pages 3558-3568, August.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:37:p:3558-3568
    DOI: 10.1080/00036846.2016.1142654
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2016.1142654
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2016.1142654?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
    2. John Y. Campbell & N. Gregory Mankiw, 1987. "Are Output Fluctuations Transitory?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 857-880.
    3. 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.
    4. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    5. Fischer, Stanley, 1977. "Long-Term Contracts, Rational Expectations, and the Optimal Money Supply Rule," Journal of Political Economy, University of Chicago Press, vol. 85(1), pages 191-205, February.
    6. Long, John B, Jr & Plosser, Charles I, 1983. "Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 91(1), pages 39-69, February.
    7. Aviral Tiwari & Amrit Chaudhari & K. Suresh, 2012. "Are Asian Per Capita GDP Stationary? Evidence from First and Second Generation Panel Unit Root Tests," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 19(1), pages 3-11, September.
    8. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
    9. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    10. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    11. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    12. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    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. Chen, W.D., 2018. "Upward wage rigidity and Japan's dispatched worker system," Economic Modelling, Elsevier, vol. 73(C), pages 152-162.
    2. Hongbo Wang & Dan Rickman, 2018. "Regional growth differences in China for 1995–2013: an empirical integrative analysis of their sources," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 99-117, January.

    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. Pami Dua, 2023. "Macroeconomic Modelling and Bayesian Methods," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 19-37, Springer.
    2. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    3. Kahn, James A. & Rich, Robert W., 2007. "Tracking the new economy: Using growth theory to detect changes in trend productivity," Journal of Monetary Economics, Elsevier, vol. 54(6), pages 1670-1701, September.
    4. Francisco Corona & Pilar Poncela & Esther Ruiz, 2020. "Estimating Non-stationary Common Factors: Implications for Risk Sharing," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
    5. Philippe Aghion & Gilles Saint‐Paul, 1998. "Uncovering Some Causal Relationships Between Productivity Growth and the Structure of Economic Fluctuations: A Tentative Survey," LABOUR, CEIS, vol. 12(2), pages 279-303, July.
    6. Caporale, Guglielmo Maria & Hassapis, Christis & Pittis, Nikitas, 1998. "Unit roots and long-run causality: investigating the relationship between output, money and interest rates," Economic Modelling, Elsevier, vol. 15(1), pages 91-112, January.
    7. In Choi, 2011. "Efficient Estimation of Nonstationary Factor Models," Working Papers 1101, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised Jun 2011.
    8. J.P.G. Reijnders, 2007. "Impulse or propagation? How the tides turned in Business Cycle Theory," Working Papers 07-07, Utrecht School of Economics.
    9. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, April.
    10. Leo Butler, 1996. "The Bank of Canada's New Quarterly Porjection Model Part 4 : A Semi- Structural Method to Estimate Potential Output : Combining Economic Theory with a Time-Series Filter," Technical Reports 77, Bank of Canada.
    11. Matteo Barigozzi & Matteo Luciani, 2017. "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series 2017-111, Board of Governors of the Federal Reserve System (U.S.).
    12. Peijie Wang, 2008. "A Spectral Analysis of Business Cycle Patterns in UK Sectoral Output," Working Papers 2008-FIN-02, IESEG School of Management.
    13. Froyen, Richard T & Waud, Roger N, 1988. "Real Business Cycles and the Lucas Paradigm," Economic Inquiry, Western Economic Association International, vol. 26(2), pages 183-201, April.
    14. Carlo A. Favero, 2007. "Model Evaluation in Macroeconometrics: from early empirical macroeconomic models to DSGE models," Working Papers 327, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    15. Yi‐Chiuan Wang & Jyh‐Lin Wu, 2015. "Fundamentals and Exchange Rate Prediction Revisited," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(8), pages 1651-1671, December.
    16. Bergman, Michael, 1996. "International evidence on the sources of macroeconomic fluctuations," European Economic Review, Elsevier, vol. 40(6), pages 1237-1258, June.
    17. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    18. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    19. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers halshs-02262202, HAL.
    20. Kugler, Maurice, 2006. "Spillovers from foreign direct investment: Within or between industries?," Journal of Development Economics, Elsevier, vol. 80(2), pages 444-477, August.

    More about this item

    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:taf:applec:v:48:y:2016:i:37:p:3558-3568. See general information about how to correct material in RePEc.

    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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.