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Modelling real GDP per capita in the USA: cointegration test

Author

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  • Ivan O. Kitov
  • Oleg I. Kitov
  • Svetlana A. Dolinskaya

Abstract

A two-component model for the evolution of real GDP per capita in the USA is presented and tested. The first component of the GDP growth rate represents an economic trend and is inversely proportional to the attained level of real GDP per capita itself, with the nominator being constant through time. The second component is responsible for fluctuations around the economic trend and is defined as a half of the growth rate of the number of 9-year-olds. This nonlinear relationship between the growth rate of real GDP per capita and the number of 9-year-olds in the USA is tested for cointegration. For linearization of the problem, a predicted population time series is calculated using the original relationship. Both single year of age population time series, the measured and predicted one, are shown to be integrated of order 1. The Engel-Granger approach is applied to the difference of the measured and predicted time series and to the residuals or corresponding linear regression. Both tests show the existence of a cointegrating relation. The Johansen test results in the cointegrating rank 1. Since a cointegrating relation between the measured and predicted number of 9-year-olds does exist, the VAR, VECM, and linear regression are used in estimation of the goodness of fit and root mean-square errors, RMSE. The highest R2=0.95 and the best RMSE is obtained in the VAR representation. Econometrically, the tests for cointegration show that the deviations of real economic growth in the USA from the economic trend, as defined by the constant annual increment of real per capita GDP, are driven by the change in the number of 9-year-olds.

Suggested Citation

  • Ivan O. Kitov & Oleg I. Kitov & Svetlana A. Dolinskaya, 2008. "Modelling real GDP per capita in the USA: cointegration test," Papers 0811.0490, arXiv.org.
    • Handle: RePEc:arx:papers:0811.0490
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    1. Franchi, Massimo & Jusélius, Katarina, 2007. "Taking a DSGE Model to the Data Meaningfully," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 1, pages 1-38.
    2. Ivan Kitov, 2005. "GDP growth rate and population," Economics Bulletin, AccessEcon, vol. 28(9), pages 1.
    3. Kitov, Ivan, 2006. "Real GDP per capita in developed countries," MPRA Paper 2738, University Library of Munich, Germany.
    4. Ivan, Kitov, 2006. "Exact prediction of inflation in the USA," MPRA Paper 2735, University Library of Munich, Germany.
    5. David F. Hendry & Katarina Juselius, 2001. "Explaining Cointegration Analysis: Part II," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 75-120.
    6. Kitov, Ivan, 2007. "Inflation, unemployment, labor force change in European countries," MPRA Paper 14557, University Library of Munich, Germany.
    7. Carl Chiarella & Shenhuai Gao, 2002. "Type I Spurious Regression in Econometrics," Working Paper Series 114, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    8. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    9. Philippe Aghion & Steven Durlauf (ed.), 2005. "Handbook of Economic Growth," Handbook of Economic Growth, Elsevier, edition 1, volume 1, number 1.
    10. Ivan O. Kitov, 2005. "Modelling the overall personal income distribution in the USA from 1994 to 2002," Working Papers 07, ECINEQ, Society for the Study of Economic Inequality.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Growth rate of the GDP per capita revisited. 3. The results from 2007, 2009, and 2012 revisited. The model
      by Ivan Kitov in Economics as Classical Mechanics on 2020-12-13 11:01:00
    2. have a happy 2017 recession
      by Ivan Kitov in Economics as Classical Mechanics on 2017-01-02 16:24:00

    Citations

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    Cited by:

    1. Kitov, Ivan, 2009. "Predicting real GDP per capita in France, Germany, New Zealand, and the UK," MPRA Paper 15503, University Library of Munich, Germany.
    2. Ivan O. KITOV, 2008. "The Driving Force of Labor Force Participation in Developed Countries," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(3(5)_Fall), pages 203-222.
    3. Kitov, Ivan & Kitov, Oleg, 2009. "Modelling and predicting labor force productivity," MPRA Paper 15152, University Library of Munich, Germany.
    4. Kitov, Ivan & Kitov, Oleg, 2010. "S&P 500 returns revisited," MPRA Paper 21733, University Library of Munich, Germany.
    5. Ivan O. KITOV, 2010. "Predicting Real Economic Growth In France, Germany, New Zealand, And The United Kingdom," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(1(11)_Spr), pages 48-54.
    6. Kitov, Ivan & Kitov, Oleg & Dolinskaya, Svetlana, 2008. "Comprehensive macro-model for the U.S. economy," MPRA Paper 9808, University Library of Munich, Germany.
    7. Guironnet Jean-Pascal, 2009. "Technological Catch-up and Scale Effect in OECD Countries: A Bipolarized Growth Convergence," Working Papers 09-05, Association Française de Cliométrie (AFC).
    8. Kitov, Ivan & Kitov, Oleg, 2007. "Exact prediction of S&P 500 returns," MPRA Paper 6056, University Library of Munich, Germany.
    9. Ivan Kitov & Oleg Kitov, 2012. "Real GDP per capita since 1870," Papers 1205.5671, arXiv.org.
    10. Dogru, Bülent, 2015. "Is Per Capıta Real GDP Stationary in High Income OECD Countrıes? Evidence from Panel Unıt Root Test With Multiple Structural Breaks," MPRA Paper 63856, University Library of Munich, Germany.

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    More about this item

    JEL classification:

    • O42 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Monetary Growth Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • O51 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - U.S.; Canada
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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