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Another Look at what to do with Time-series Cross-section Data

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Abstract

Our study revisits Beck and Katz' (1995) comparison of the Parks and PCSE estimators using time-series, cross-sectional data (TSCS). Our innovation is that we construct simulated statistical environments that are designed to approximate actual TSCS data. We pattern our statistical environments after income and tax data on U.S. states from 1960-1999. While PCSE generally does a better job than Parks in estimating standard errors/confidence intervals, it too can be unreliable, sometimes producing standard errors/confidence intervals that are substantially off the mark. Further, we find that the benefits of PCSE can come at a large cost in estimator efficiency.

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File URL: http://www.econ.canterbury.ac.nz/RePEc/cbt/econwp/0604.pdf
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Bibliographic Info

Paper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 06/04.

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Length: 32 pages
Date of creation: 31 Mar 2006
Date of revision:
Handle: RePEc:cbt:econwp:06/04

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Keywords: Panel data; Parks model; PCSE estimator; Monte Carlo methods;

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  1. Helms, L Jay, 1985. "The Effect of State and Local Taxes on Economic Growth: A Time Series-Cross Section Approach," The Review of Economics and Statistics, MIT Press, vol. 67(4), pages 574-82, November.
  2. Kwok Tong Soo, 2004. "Zipf's law for cities: a cross country investigation," LSE Research Online Documents on Economics 19947, London School of Economics and Political Science, LSE Library.
  3. Luca Nunziata, 2005. "Institutions and Wage Determination: a Multi-country Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(4), pages 435-466, 08.
  4. Brulhart, Marius & Trionfetti, Federico, 2004. "Public expenditure, international specialisation and agglomeration," European Economic Review, Elsevier, vol. 48(4), pages 851-881, August.
  5. Kristian Jönsson, 2005. "Cross-sectional Dependency and Size Distortion in a Small-sample Homogeneous Panel Data Unit Root Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(3), pages 369-392, 06.
  6. Joseph DeJuan & Maria J. Luengo-Prado, 2005. "Consumption and Aggregate Constraints: International Evidence," Macroeconomics 0501018, EconWPA.
  7. Reed, W. Robert, 2006. "Democrats, republicans, and taxes: Evidence that political parties matter," Journal of Public Economics, Elsevier, vol. 90(4-5), pages 725-750, May.
  8. Woojin Lee & John E. Roemer, 2005. "The Rise and Fall of Unionised Labour Markets: A Political Economy Approach," Economic Journal, Royal Economic Society, vol. 115(500), pages 28-67, 01.
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Cited by:
  1. Aleksander Aristovnik, 2006. "The Determinants & Excessiveness of Current Account Deficits in Eastern Europe & the Former Soviet Union," William Davidson Institute Working Papers Series wp827, William Davidson Institute at the University of Michigan.
  2. Pitelis, Christos & Vasilaros, Vassilis, 2009. "The Determinants of Value Creation at the Firm, Industry and National Levels: A Framework and Evidence," Papers DYNREG37, Economic and Social Research Institute (ESRI).
  3. Mellati, Ali, 2008. "Uncertainty and investment in private sector: An analytical argument and a review of the economy of Iran," MPRA Paper 26655, University Library of Munich, Germany.
  4. Roberto Fernández Llera & María A. García Valiñas, 2010. "Efficiency and elusion: both sides of public enterprises in Spain," Working Papers 2010/5, Institut d'Economia de Barcelona (IEB).
  5. Etienne Bordeleau & Allan Crawford & Christopher Graham, 2009. "Regulatory Constraints on Bank Leverage: Issues and Lessons from the Canadian Experience," Discussion Papers 09-15, Bank of Canada.
  6. Aleksander Aristovnik, 2005. "Current Account Reversals In Selected Transition Countries," International Finance 0510021, EconWPA.

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