Author

  • Ntebogang Dinah Moroke

    • North West University, South Africa
    • South Africa

Abstract

This study applies cointegration and error correction approaches to determine the effect of macroeconomic determinants on household debt in the United States of America. Cointegration analysis provides an effective framework used for estimating and modelling relationships from time series data. Short-run and long-run cointegration models explaining the relationships between the US household debt and related macroeconomic factors are estimated. The data used covers a period of 1990 Q1 to 2013 Q1 and is sourced from the electronic data delivery system of the OECD, USA Federal Housing Finance Agency and the USA Department of the Treasury among others. SAS 9.3 version was used to obtain the results. The sample and variables were meritorious according to KMO and Cronbach’s alpha. Unit root test results provided enough evidence to conclude that the series were stationary after first differencing. Further data analysis was carried out with the first lag chosen by the AIC and SBC. Three cointegrating vectors were identified and were later standardised to correctly provide parameter estimates of the vector error correction model of household debts. The model revealed some short and long-run relationships. Revealed by the model is that 1.5 % of long-run equilibrium was corrected per quarter. The results of the current study are crucial to households and policy makers. Researchers may also refer to these results.

Keywords

References

  • Alexander, C. (2001). Market models: A guide to financial data analysis. John Wiley and Sons, Ltd.
  • Banerjee, A., Dolado, J. J., Galbraith, J. W. & Hendry, D. (2011). Co-integration, error correction and the econometric analysis of nonstationary data. OUP Catalogue.
  • Barnes, S. & Young, G. (2003). The rise in US household debt: assessing its causes and sustainability. Bank of England Working Paper No. 206.
  • Blaha, J., Merydith, S. J., Wallbrown, F. H. & Dowd, E. T. (2001). Bringing another perspective to bear on the factor structure of the MMPI-2. Measurement and Evaluation in counselling and development , 33, 234-243.
  • Brooks, C. (2008). Introductory econometrics for finance (2.ed. reprinted. Ed). Cambridge University Press, Cambridge.
  • Byrne, B. M., Shavelson, R. J. & Muthén, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin , 105(3), 456-466.
  • Churchill, G. A. (1995). Marketing Research: Methodological Foundations, Dryden Press.
  • Clark, A. E. & Daniel, T. (2006). Forecasting South African house prices. Investment Analyst Journal , 64, 27-33.
  • Cronbach, L. J. & Shavelson, R. J. (2004). My current thought on coefficient alpha and successor procedures. Educational and Psychological Measure, 64, 391-418.
  • Crook, J. (2003). The Demand and supply for household debt: a cross country comparison. Credit Research Centre Working Paper, No. 1.
  • Davidson, J. E. H., David, F., Hendry, F., Srba, L. & Yeo, S. (1978). Econometric modelling of the aggregate time series relationship between consumers’ expenditure and income in the United Kingdom. Economic Journal , 88, 661–692.
  • Davidson, R. & MacKinnon, J. G. (1993). Estimation and inference in econometrics, New York, Oxford University Press.
  • Debelle, G. (2004). Household debt and macro economy. BIS Quarterly Review, March, 51-64, http://www.bis.org/publ/qtrpdf/r_qt0403e.pdf.
  • Diamantopoulos, A. & Siguaw, J. A. (2006). Formative vs. Reflective Indicators in Measure Development: Does the Choice of Indicators Matter? British Journal of Management, 17, 263-282.
  • Dickey, D. A. & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49, 1057-1072.
  • Enders, W. (2005). Applied Econometric Time Series. USA: John Wiley and Sons Ltd.
  • Engle, R. & Granger, C. W. J. (1987). Cointegration and Error Correction Estimates: Representation, Estimation and Testing. Econometrica, LV, 251-276.
  • Fountis, N. G. & Dickey, D. A. (1989). Testing for a unit root non stationarity in multivariate autoregressive time series. Annals of Statistics, 17, 419-428.
  • Friedman, M. (1957). A Theory of the Consumption Function. New Jersey: Princeton University Press.
  • Granger, C. W. J. & Weiss, A. A. (1983). Time Series Analysis of error-correcting models: Studies in Econometrics, Time Series, and Multivariate Statistics. New York: Academic Press: 255-278.
  • Gujarati, D. N. (2010). Basic Econometrics. New York: McGraw-Hill Inc.
  • Hamilton, J. D. (1990). Analysis of time series subject to changes in regime. Journal of Econometrics , 45, 39-70.
  • Harris, R. J. D. (1995). Using Cointegration Analysis in Econometric Modelling. Harvester Wheatsheaf, Prentice Hall.
  • Hendry, D. F. & Juselius, K. (2000). Explaining cointegration analysis: Part I. Energy Journal, 21, 1-42.
  • Jacobsen, D. (2004,). What influences the growth of household debt? Economic Bulletin , 4, (3).
  • Johansen, S. (1991). Estimation and hypothesis testing of cointegrating vectors in Gaussian Vector Autoregressive Models. Econometrica , 59, 1551-1580.
  • Johansen, S. & Juselius, K. (1990). Maximum Likelihood estimation and inference on cointegration with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52, 169-210.
  • Kaiser, H. F. (1974). An index of Factorial Simplicity. Psychometrika, 39, 34-36.
  • Kearns, A. & Woods, M. (2006). The Concentration in property-related lending: a financial stability perspective. Financial Stability Report CBFSAI, 133-144.
  • Kennedy, P. (1996). A Guide to Econometrics. 3rd Edition. Massachusetts, Blackwell Publishers Inc.
  • Keynes, J. M. (1936). The general theory of employment, interest and money. Macmillan Cambridge University Press, London.
  • Kim, Y. K. (2011). The macroeconomic implications of households’ debt: An empirical analysis. Trinity College Department of Economics, Working Paper No. 11-03.
  • Kline, P. (1999). The Handbook of Psychological Testing (2nd Ed.). London: Routledge.
  • Kwiatkowski, D., Phillips, P. C. B., Schmidt, P. & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that time series have a unit root? Journal of Econometrics, 54, 159-178.
  • Laina, P. (2011). Dynamic Effects of total debt and GDP, A Time-Series Analysis of the United States. Masters’ Dissertation, Department of Economics, Alto University.
  • Lauridsen, J. (1998). Spatial Cointegration Analysis in Econometric Modelling. Department of Statistics and Demography, Odense University. Campus survey 55 DK-5230 Odense M Available online at www.ou.dk/rrvf/statdem/lauriden.html (Accessed 14/7/2010).
  • Mason, J. W. & Jayadev, A. (2012). Fisher dynamics in household debt: the case of the United States. 19292011.
  • Maysami, R. C. & Koh, T. S. (2000). A vector error correction model of the Singapore stock market. International Review of Economics and Finance , 9, 79–96
  • Meng, S., Hoang, T. N. & Siriwardana, M. (2011). The determinants of Australia household debt: a macro Level study. Business, economics and public policy working papers, 2011-2014.
  • Modigliani, F. (1986). Life cycle hypothesis, individual thrift and the wealth of nations. The American Economic Review , 76(3), 297-313.
  • Moroke, N.D. & Mavetera, N. (2014). Exploratory Factor Analysis to investigate inter-relationships amongst serious crime in South Africa. European Journal of Social Sciences, 41(8).
  • Nelson, C. R. & Plosser, C. I. (1982). Trends and random walks in macroeconomic time series: some evidence and implications. Journal of Monetary Economics, 10, 139-62.
  • Nwachukwu, T. E. & Egwaikhide, F. O. (2007). An Error-Correction Model of the determinants of private saving in Nigeria. A Paper presented at the African Economic Society (AES) Conference, Cape Town, South Africa.
  • Obayelu A. E. & Salau, A. S. (2010). Agricultural response to prices and exchange rate in Nigeria: Application of cointegration and vector error correction model. Journal of Agricultural Science , 1(2), 73-81
  • Osterwald-Lenum, M. (1992). A Note with Quantiles of the asymptotic distribution of the maximum likelihood cointegration rank test statistic. Oxford Bulletin of Economics and Statistics , 54, 461472.
  • Phillips, A. W. H. (1954). Stabilization policy in a closed economy. Economic Journal, 64, 290–333.
  • Prinsloo, J. W. (2002). Household debt, wealth and saving. South African Reserve Bank Quarterly Bulletin , 226, 63-78.
  • Sargan J. D. (1964). Wages and Prices in the United Kingdom: A study in econometric methodology. PE Hart.
  • Sjö, B. (2008). Test ing for unit roots and cointegration. Available at: http://ww w.iei.liu.se/nek/ekonometrisk-teori-7-5-hp-730a07/labbar/1.233753/dfdistab7b.pdf
  • Subhanij, T. (2007). Some lessons from Securitisation Crisis. Bangkok Post Business New, (13 July, 2007). Thaicharoen, Y., Ariyapruchya, K. & Chucherd, T. (2004). Rising Thai Household debt: assessing risk and policy implications. Bank of Thailand discussion paper, http://www.bot.or.th/BOTHomepage/DataBank/Econcond/seminar/yearly/9-14-2004-Eng-i12/paper1.pdf.
  • Toda, H. Y. & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics , 66, 225-250.
  • Tudela, M. & Young, G. (2005). The determinants of household debt and balance sheets in the United Kingdom. Bank of England Working Paper 266.
  • Verbeek, M. (2004). A Guide to Modern Econometrics . (2nd Ed). New York: John Wiley and Sons.

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How to Cite

Moroke, N. D. (2014). Household Debts-and Macroeconomic factors Nexus in the United States: A Cointegration and Vector Error Correction Approach. Journal of Economics and Behavioral Studies, 6(6), 452-465. https://doi.org/10.22610/jebs.v6i6.507

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Research Paper

Published in

Vol. 6 No. 6 (2014) Business Tourism, Household Finance & Workplace Dynamics View issue contents

Published

2014-06-30

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