Causality analysis between public expenditure and economic growth of Polish economy in last decade

Gurgul, Henryk and Lach, Łukasz (2011): Causality analysis between public expenditure and economic growth of Polish economy in last decade. Published in: Statistics in Transition: new series. International journal of the Polish Statistical Association , Vol. 11, (2011): pp. 329-359.

Abstract

This paper investigates the causal links between different kinds of budgetary expenditure and the economic growth of Poland. The empirical analysis was based on both the linear and nonlinear Granger causality tests and the aim was to evaluate the applicability of Wagner’s Law and contrasting theory formulated by Keynes. We based our research on aggregate and disaggregate quarterly data with the sub–division of public expenditure on human resources (HR), physical resources (PR), net interest payment (NIP) and other remaining budgetary expenditure (OTHER) for the period Q1 2000 to Q3 2008. Linear causality analysis showed that relation between total budgetary expenditure and economic growth is consistent with Keynesian theory. However, for the examined sub–categories of expenditure mixed results were reported supporting Keynesian theory (NIP), Wagner’s Law (OTHER) or none of them (HR and PR). Results of nonlinear causality analysis performed for unfiltered data also provided some support for Keynesian theory (HR and OTHER). However, after GARCH(1,1)–filtration of data nonlinear causality was not reported in any case.

• Item Type: MPRA Paper
• Language: English
• Keywords: government expenditure, linear and nonlinear causality, bootstrap technique
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets

References

1. AGIAKOGLU, C. & NEWBOLD, P., 1992, Empirical Evidence on Dickey–Fuller Type Tests, Journal of Time Series Analysis, 13, pp. 471–483.

2. ANWAR, M.S., DAVIES, S. & SAMPATH, R.K., 1996, Causality between Government Expenditures and Economic Growth: An Examination Using Cointegration Techniques, Public Finance, 51, pp. 166–184.

3. ASTERIOU, D. & ARGIOMIRGIANAKIS, G.M., 2001, Human capital and economic growth: time series evidence from Greece, Journal of Policy Modeling, 23, pp. 481–489.

4. BAEK, E. & BROCK, W., 1992, A general test for Granger causality: Bivariate model, Technical Report, Iowa State University and University of Wisconsin, Madison.

5. BENOIT, E., 1978, Growth and defence in developing countries, Economic Development and Cultural Change, 26, pp. 261–280.

6. BISWAS, B. & RAM, R., 1986, Military expenditures and economic growth in less developed countries: an augmented model and further evidence, Economic Development and Cultural Change, 34, pp.361–372.

7. BLOMQVIST, A.G. & CARTER, R.A.L., 1997, Is health care really a luxury?, Journal of Health Economics, 16, pp. 2007–2029.

8. BROCK, W., 1991, Causality, chaos, explanation and prediction in economics and finance, In: Casti J., Karlqvist A. (eds.), Beyond Belief: Randomness, Prediction and Explanation in Science, CRC Press, Boca Raton, Fla.

9. CASELLI, F., 1999, Technological revolutions, American Economic Review, 89, pp. 78–102.

10. CHANG, T., FANG, W., WEN, L.F. & LIU, C., 2001, Defense expenditure, economic growth and temporal causality: evidence from Taiwan and mainland China, 1952–1995, Applied Economics, 33, pp. 1289–1299.

11. CHEN, A.S. & LIN, J.W., 2004, Cointegration and detectable linear and nonlinear causality: analysis using the London Metal Exchange lead contract, Applied Economics, Vol. 36, pp. 1157–1167.

12. CHEN, C.H., 1993, Causality between defence spending and economic growth: the case of mainland China, Journal of Economic Studies, 26, pp. 37–43.

13. CHOU, P.H. & ZHOU, G., 2006, Using Bootstrap to Test Portfolio Efficiency, Annals of economics and finance, 2, pp. 217–249.

14. CIARRETA, A. & ZARRAGA, A., 2007, Electricity consumption and economic growth: evidence from Spain, Working Paper, Dept. of Applied Economics III (Econometrics and Statistics), University of the Basque Country.

15. CULYER, A.J., 1990, Cost containment in Europe, Health Care Systems in Transition, OECD, Paris.

16. DAVISON, A.C. & HINKLEY, D.V., 1999, Bootstrap Methods and Their Application, Cambridge University Press, Cambridge.

17. DE MEULEMEESTER, J.–L. & ROCHAT, D., 1995, A causality analysis of the link between higher education and development, Economics of Education Review, 14, pp. 351–361.

18. DEGER, S. & SEN, S., 1983, Military expenditures, spin–off and economic development, Journal of Development Economics, 13, pp. 68–83.

19. DEMIRBAS, S., 1999, Cointegration Analysis–Causality Testing and Wagner’s Law: The Case of Turkey, 1950–1990, Available at: http://www.econturk.org/safaaabi.pdf.

20. DEROUEN, K.R., 1995, Arab–Israeli defence spending and economic growth, Conflict Management and Peace Science, 14, pp. 25–47.

21. DEVLIN, N. & HANSEN, P., 2001, Health care spending and economic output: Granger causality, Applied Economics Letters, 8, pp. 561–564.

22. DIKS, C.G.H. & DEGOEDE, J., 2001, A general nonparametric bootstrap test for Granger causality, In: Broer H.W., Krauskopf W., Vegter G. (eds.), Global analysis of dynamical systems, Institute of Physics Publishing, Bristol, United Kingdom.

23. DIKS, C.G.H. & PANCHENKO, V., 2005, A note on the Hiemstra–Jones test for Granger non–causality, Studies in Nonlinear Dynamics and Econometrics, 9, No. 2, Article 4.

24. DIKS, C.G.H. & PANCHENKO, V., 2006, A new statistic and practical guidelines for nonparametric Granger causality testing, Journal of Economic Dynamics & Control, 30, pp. 1647–1669.

25. DOLADO, J.J. & LÜTKEPOHL, H., 1996, Making Wald tests work for cointegrated VAR systems, Econometrics Reviews, 15, pp. 369–386.

26. DUNNE, J.P., SMITH, R.P. & WILLENBOCKEL, D., 2005, Models of military expenditure and growth: a critical review, Defence and Peace Economics, 16, No. 6, pp. 449–461.

27. EASTERLY, W., KING, R., LEVINE, R. & REBELO, S., 1994, Policy, technology adoption and growth, In: Pasinetti L., Solow R. (Eds), Economic Growth and the Structure of Long–term Development, St Martins Press, New York.

28. FREDERIKSEN, P.C. & LOONEY, R.E., 1982, Defence expenditures and economic growth in development countries: some further empirical evidence, Journal of Economic Development, 7, pp. 113–125.

29. GRANGER, C.W.J., 1969, Investigating causal relations by econometric models and cross–spectral methods, Econometrica, 37, pp. 424–438.

30. GRANGER, C.W.J. & NEWBOLD, P., 1974, Spurious regression in econometrics, Journal of Econometrics, 2, pp. 111–120.

31. GRANGER, C.W.J., HUANG, B. & YANG, C., 2000, A bivariate causality between stock prices and exchange rates: evidence from recent Asian Flu, The Quarterly Review of Economics and Finance, 40, pp. 337–354.

32. GROBAR, L. & PORTER, R., 1989, Benoit revisited: defence spending and economic growth in less developed countries, Journal of Conflict Resolution, 33, pp. 318–345.

33. GURGUL, H. & LACH, Ł., 2009, Linear versus nonlinear causality of DAX companies, Operations Research and Decisions, 3, pp. 27–46.

34. HACKER, R.S. & HATEMI–J, A., 2006, Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application, Applied Economics, pp. 1489–1500.

35. HAMILTON, J.D., 1994, Time Series Analysis, Princeton University Press, Princeton.

36. HANSEN, P. & KING, A., 1996, The determinants of health care expenditure: a cointegration approach, Journal of Health Economics, pp. 127–137.

37. HANSEN, P. & KING, A., 1998, Health care expenditure and GDP: panel data unit root test results–comment, Journal of Health Economics, 17, pp. 377–381.

38. HEO, U. & EGER, R.J., 2005, The security–prosperity dilemma in the United States, Journal of Conflict Resolution, 49, pp. 699–708.

39. HIEMSTRA, C. & JONES, J.D., 1994, Testing for linear and nonlinear Granger causality in the stock price–volume relation, Journal of Finance, 49, pp. 1639–1664.

40. HITRIS, T. & POSNETT, J., 1992, The determinants and effects of health expenditure in developed countries, Journal of Health Economics, 11, pp. 173–181.

41. HOROWITZ, J.L., 1995, Advances in Economics and Econometrics: Theory and Applications, Chapter 7: Bootstrap methods in econometrics: Theory and numerical performance, Cambridge University Press, Cambridge.

42. IN, F. & DOUCOULIAGOS, C., 1997, Human capital formation and US economic growth: a causality analysis, Applied Economics Letters, 4, pp. 329–331.

43. JACKSON, P.M., MERYEM, D.F. & SAMI, F., 1998, Conitegration, Causality, and Wagner’s Law: A test for Northern Cyprus, Available at http://www.le.ac.uk/economics/research/RePEc/lec/lpserc99–2.pdf.

44. JOERDING, W., 1986, Economic growth and defense spending, Economics, 21, pp. 35–40.

45. KALYONCU, H. & YUCEL, F., 2006, An analytical approach on defense and expenditure and economic growth. The case of Turkey and Greece, Journal of Economic Studies, 33, pp. 336–343.

46. KHAN, A.H., 1990, Wagner’s Law and the Developing Economy: A Time Series Evidence from Pakistan, Indian Economic Journal, 38, pp. 115–123.

47. KOLLIAS, C., 1994, The economic effects of defense spending in Greece 1963–90: some preliminary econometric findings, Spoudai, 44, pp. 114–130.

48. LACH, Ł., 2010, Application of bootstrap methods in investigation of size of the Granger causality test for integrated VAR systems, to appear in Managing Global Transition.

49. LAI, C–N., HUANG, B–N. & YANG, C–W., 2005, Defense spending and economic growth the Taiwan straits: a threshold regression model, Defence and Peace Economics, 16, pp. 45–57.

50. LANDAU, D., 1996, Is one of the “peace dividends” negative? Military expenditure and economic growth in the wealthy OECD countries, The Quarterly Review of Economic and Finance, 36, pp. 183–195.

51. LIM, D., 1983, Another look at growth and defense in developed countries, Economic Development and Cultural Change, 31, pp. 377–384.

52. LIU, L.C., HSU, C.E. & YOUNIS, M.Z., 2008, The association between government expenditure and economic growth: Granger causality test of US data, 1947–2002, Journal of Public Budgeting & Financial Management, 20, pp. 537–553.

53. LÜTKEPOHL, H., 1993, Introduction to Multiple Time Series Analysis, 2nd ed., Springer–Verlag, New York.

54. MANTALOS, P., 2000, A Graphical Investigation of the Size and Power of the Granger–Causality Tests in Integrated–Cointegrated VAR Systems, Studies in Nonlinear Dynamics & Econometrics, 4, Issue 1, Article no. 2

55. MCCOSKEY, S.K. & SELDON, T.M., 1998, Health care expenditures and GDP: panel data unit root test results, Journal of Political Economy, 70, pp. 129–157.

56. NAGARAJAN, P. & SPEARS, A., 1990, An Econometric Test of Wagner's Law for Mexico: A Re–Examination, Public Finance, 45, pp. 165–168.

57. NARAYAN, P.K. & SINGH, B., 2007, Modelling the relationship between defence spending and economic growth for the Fiji islands, Defence and Peace Economics, 18, pp. 391–401.

58. NARAYAN, P.K. & SMYTH, R., 2006, Higher Education, Real Income and Real Investment in China: Evidence from Granger Causality, Education Economics, 14, pp. 107–125.

59. PARK, W.K., 1996, Wagner's Law vs. Keynesian Paradigm: The Korean Experience, Public Finance, 51, pp.71–91.

60. PAULSEN, J., 1984, Order determination of multivariate autoregressive time series with unit roots, Journal of time series analysis, 5, pp. 115–127.

61. PHILLIPS, P.C.B., 1986, Understanding the spurious regression in econometrics, Journal of Econometrics, 33, pp. 311–340.

62. PHILLIPS, P.C.B. & PERRON, P., 1988, Testing for a Unit Root in Time Series Regressions, Biometrika, 75, pp. 335–346.

63. PLUTA, J.E., 1979, Wagner's Law, Public Sector Patterns, and Growth of Public Enterprises in Taiwan, Public Finance Quarterly, 7, pp. 25–46.

64. REITSCHULER, G. & LOENING, J.L., 2005, Modeling the defense–growth nexus, World Development, 33, pp. 513–526.

65. ROBERTS, J., 1999, Sensitivity of elasticity estimates for OECD health care spending analysis of a dynamic heterogenous data field, Health Economics, 8, pp. 459–472.

66. SAUNDERS, P., 1985, Public Expenditure and Economic Performance in OECD Countries, Journal of Public Policy, 5, pp. 1–21.

67. SINHA, D., 1998, Government Expenditure and Economic Growth in Malaysia, Journal of Economic Development, 23, pp. 265–283.

68. SKAUG, H.J. & TJØSTHEIM, D., 1993, Nonparametric tests of serial independence, In: Subba Rao T. (ed.), Developments in time series analysis, Chapman and Hall, London.

69. SMITH, R., 1980, ME and investment in OECD countries, 1954–1973, Journal of Comparative Economics, 4, pp. 19–32.

70. TODA, H.Y. & YAMAMOTO, T., 1995, Statistical inference in vector autoregressions with possibly integrated processes, Journal of Econometrics, 66, pp. 225–250.

71. WOLDE–RUFAEL, Y., 2006, Electricity consumption and economic growth: a time series experience for 17 African countries, Energy Policy, 34, pp. 1106–1114.