IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/2734.html
   My bibliography  Save this paper

Inflation as a function of labor force change rate: cointegration test for the USA

Author

Listed:
  • Kitov, Ivan
  • Kitov, Oleg
  • Dolinskaya, Svetlana

Abstract

Previously, a linear and lagged relationship between inflation and labor force change rate, π(t)= A1dLF(t-t1)/LF(t-t1)+A2 (where A1 and A2 are empirical country-specific coefficients), was found for developed economies. The relationship obtained for the USA is characterized by A1=4.0, A2=-0.03075, and t1=2 years. It provides a root mean square forecasting error (RMFSE) of 0.8% at a two-year horizon for the period between 1965 and 2002 (the best among other inflation forecasting models) and has a perfect parsimony - only one predictor. The relationship is tested for cointegration. Both variables are integrated of order one according to the presence of a unit root in the series and its absence in their first differences. Two methods of cointegration testing are applied - the Engle-Granger one based on the unit root test of the residuals including a variety of specification tests and the Johansen cointegration rank test based on the VAR representation. Both approaches demonstrate that the variables are cointegrated and the long-run equilibrium relation revealed in previous study holds. According to the Granger causality test, the labor force change is proved to be a weakly exogenous variable - a natural result considering the time lead and the existence of a cointegrating relation. VAR and VECM representations do not provide any significant improvement in RMSFE. There are numerous applications of the equation: from purely theoretical - a robust fundamental relation between macroeconomic and population variables, to a practical one - an accurate out-of-sample inflation forecasting at a two-year horizon and a long-term prediction based on labor force projections. The predictive power of the relationship is inversely proportional to the uncertainty of labor force estimates. Therefore, future inflation research programs should start from a significant improvement in the accuracy of labor force estimations

Suggested Citation

  • Kitov, Ivan & Kitov, Oleg & Dolinskaya, Svetlana, 2007. "Inflation as a function of labor force change rate: cointegration test for the USA," MPRA Paper 2734, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:2734
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/2734/1/MPRA_paper_2734.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kitov, Ivan, 2007. "Inflation, unemployment, labor force change in European countries," MPRA Paper 14557, University Library of Munich, Germany.
    2. 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.
    3. 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.
    4. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    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. Oleg KITOV & Ivan KITOV, 2012. "Inflation And Unemployment In Switzerland: From 1970 To 2050," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 7(2(20)/ Su), pages 141-156.
    2. Kitov, Ivan, 2009. "The anti-Phillips curve," MPRA Paper 13641, University Library of Munich, Germany.
    3. Kitov, Ivan & Kitov, Oleg & Dolinskaya, Svetlana, 2007. "Relationship between inflation, unemployment and labor force change rate in France: cointegration test," MPRA Paper 2736, University Library of Munich, Germany.
    4. Kitov, Ivan, 2007. "Exact prediction of inflation and unemployment in Canada," MPRA Paper 5015, University Library of Munich, Germany.
    5. Ivan O. Kitov & Oleg I. Kitov, 2008. "Long-Term Linear Trends In Consumer Price Indices," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(2(4)_Summ).
    6. Ivan O. KITOV & Oleg I. KITOV, 2010. "Dynamics Of Unemployment And Inflation In Western Europe: Solution By The 1- D Boundary Elements Method," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(2(12)/Sum), pages 94-113.
    7. Ivan Kitov & Oleg Kitov & Svetlana Dolinskaya, 2007. "Linear Lagged Relationship Between Inflation, Unemployment and Labor Force Change Rate in France: Cointegration Test," Mechonomics mechonomics2, Socionet.
    8. Ivan Kitov & Oleg Kitov, 2009. "Unemployment and inflation in Western Europe: solution by the boundary element method," Papers 0903.5064, arXiv.org.
    9. Kitov, Ivan, 2009. "Predicting the price index for jewelry and jewelry products: 2009 to 2016," MPRA Paper 15875, University Library of Munich, Germany.
    10. Ivan O. KITOV & Oleg I. KITOV & Svetlana A. DOLINSKAYA, 2008. "Comprehensive Macro Ï¿½ Model For The Us Economy," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(4(6)_Wint).
    11. Kitov, Ivan, 2007. "Exact prediction of inflation and unemployment in Japan," MPRA Paper 5464, University Library of Munich, Germany.
    12. Oleg KITOV & Ivan KITOV, 2012. "A Win-Win Monetary Policy In Canada," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 6(6(18)/ Su), pages 160-176.
    13. Kitov, Ivan & Kitov, Oleg, 2009. "PPI of durable and nondurable goods: 1985-2016," MPRA Paper 15874, University Library of Munich, Germany.
    14. Kitov, Ivan, 2007. "Exact prediction of inflation and unemployment in Germany," MPRA Paper 5088, University Library of Munich, Germany.
    15. Mosso-Martínez, Margarita M. & López-Herrera, Francisco, 2020. "Variables económicas y deterioro de la calidad de la cartera de hipotecas bursatilizadas en México," eseconomía, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 15(52), pages 47-68, Primer se.
    16. Ivan Kitov & Oleg Kitov, 2011. "The Australian Phillips curve and more," Papers 1102.1851, arXiv.org.
    17. Kitov, Ivan, 2009. "Predicting gold ores price," MPRA Paper 15873, University Library of Munich, Germany.
    18. Kitov, Ivan & Kitov, Oleg, 2009. "A fair price for motor fuel in the United States," MPRA Paper 15039, University Library of Munich, Germany.
    19. Kitov, Ivan & Kitov, Oleg & Dolinskaya, Svetlana, 2008. "Comprehensive macro-model for the U.S. economy," MPRA Paper 9808, University Library of Munich, Germany.

    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. Ivan O. KITOV & Oleg I. KITOV & Svetlana A. DOLINSKAYA, 2009. "Modelling Real Gdp Per Capita In The Usa:Cointegration Tests," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 4(1(7)_ Spr).
    2. Ivan Kitov & Oleg Kitov & Svetlana Dolinskaya, 2007. "Linear Lagged Relationship Between Inflation, Unemployment and Labor Force Change Rate in France: Cointegration Test," Mechonomics mechonomics2, Socionet.
    3. Ivan Kitov & Oleg Kitov, 2013. "Does Banque de France control inflation and unemployment?," Papers 1311.1097, arXiv.org.
    4. Kitov, Ivan & Kitov, Oleg & Dolinskaya, Svetlana, 2007. "Relationship between inflation, unemployment and labor force change rate in France: cointegration test," MPRA Paper 2736, University Library of Munich, Germany.
    5. Paul Plummer & Daisaku Yamamoto, 2019. "Economic resilience of Japanese nuclear host communities: A quasi-experimental modeling approach," Environment and Planning A, , vol. 51(7), pages 1586-1608, October.
    6. Asche, Frank & Gjolberg, Ole & Volker, Teresa, 2003. "Price relationships in the petroleum market: an analysis of crude oil and refined product prices," Energy Economics, Elsevier, vol. 25(3), pages 289-301, May.
    7. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
    8. Reza Anglingkusumo, 2005. "Money - Inflation Nexus in Indonesia: Evidence from a P-Star Analysis," Tinbergen Institute Discussion Papers 05-054/4, Tinbergen Institute.
    9. Dipesh Karki & Hari Gopal Risal, 2019. "Asymmetric Impact of Oil Price on Inflation: Evidence from Nepal," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 31(1), pages 21-46, April.
    10. Robert Socha & Piotr Wdowiński, 2018. "Tendencje zmian cen na światowym rynku ropy naftowej po 2000 roku," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 1, pages 103-135.
    11. Zaklan, Aleksandar & Cullmann, Astrid & Neumann, Anne & von Hirschhausen, Christian, 2012. "The globalization of steam coal markets and the role of logistics: An empirical analysis," Energy Economics, Elsevier, vol. 34(1), pages 105-116.
    12. Gaolu Zou & K. W. Chau, 2019. "Long- and Short-Run Effects of Fuel Prices on Freight Transportation Volumes in Shanghai," Sustainability, MDPI, vol. 11(18), pages 1-12, September.
    13. Sukati, Mphumuzi, 2013. "Cointegration Analysis of Oil Prices and Consumer Price Index in South Africa using STATA Software," MPRA Paper 49797, University Library of Munich, Germany.
    14. Gao Lu Zou & Kwong Wing Chau, 2015. "Determinants and Sustainability of House Prices: The Case of Shanghai, China," Sustainability, MDPI, vol. 7(4), pages 1-25, April.
    15. Ljungwall, Christer, 2005. "State fixed investment and non-state sector growth in China," Journal of Policy Modeling, Elsevier, vol. 27(2), pages 211-229, March.
    16. Theodore Panagiotidis & Emilie Rutledge, 2004. "Oil and gas market in the UK: evidence from a cointegration approach," Discussion Paper Series 2004_18, Department of Economics, Loughborough University, revised Nov 2004.
    17. Mustafa Ismihan & Kivilcim Metin-Ozcan & Aysit Tansel, 2002. "Macroeconomic Instability, Capital Accumulation and Growth: The Case of Turkey 1963-1999," Working Papers 0209, Economic Research Forum, revised 21 Mar 2002.
    18. Hillen, J., 2018. "Protecting the Swiss milk market from foreign price shocks: Public border protection vs. quality differentiation," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 276015, International Association of Agricultural Economists.
    19. Christopher Spencer & Paul Temple, 2012. "Alternative Paths of Learning: Standardisation and Growth in Britain, 1901-2009," Discussion Paper Series 2012_10, Department of Economics, Loughborough University, revised Oct 2012.
    20. Julia Campos & Neil R. Ericsson & David F. Hendry, 2005. "General-to-specific modeling: an overview and selected bibliography," International Finance Discussion Papers 838, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    Keywords

    cointegration; inflation; labor force; forecasting; USA; VAR; VECM;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:2734. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.