Khan, Zahid and Asghar, Zahid (2009): Determination of stochastic vs. deterministic trend in quarterly GDP of Pakistan.
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Many economic and financial time series show evidence of trending behavior or non stationarity in the mean. An important econometric goal is determining the most proper form of the trend in the data. The transformations of series depend on whether the series is trend stationary or difference stationary. In this paper, study is conducted to declare the nature of trend component in quarterly GDP of Pakistan whether it is trend stationary or difference stationary. It is necessary to know, because trend stationary and difference stationary models imply very different short run and long run dynamics. We have explored the type of trend in GDP series by ADF unit root test and also support our arguments by empirical distribution instead of asymptotical ones i.e., bootstrapping test. The purpose of the paper is not only to investigate the type of trend in the series by conventional methods but also to motivate small distribution theory like bootstrapping techniques that can helps ones in selection of advocate model for observed series.
|Item Type:||MPRA Paper|
|Original Title:||Determination of stochastic vs. deterministic trend in quarterly GDP of Pakistan|
|English Title:||Determination of stochastic vs. deterministic trend in quarterly GDP of Pakistan|
|Keywords:||Bootstrapping, Stationarity, Pivotal statistic, Unit root|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General
C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics
|Depositing User:||zahid khan|
|Date Deposited:||19. Apr 2010 17:51|
|Last Modified:||17. Feb 2013 02:39|
Ender, W. (1995). ‘Applied Econometric Time Series.’ New York, Wiley.
Engle, R.F., Granger, C.W.J. (1987). ‘Co integration and Error Correction:Representation,’ Estimation and Testing.’ Econometrica 55, 251-276.
Granger, C.W.J., Newbold, P. (1974). ‘Spurious Regressions in Econometrics.’ Journal of Econometrics 2, 111-120.
Kemal, A.R. and M.F, Arby (2004). ‘Quarterisation of Annual GDP of Pakistan.’ Pakistan Institute of Development Economics, Islamabad, Statistical Paper Series No.5 December.
Kim, I.M. and Maddala, G.S. (1998). ‘Unit Roots, Cointegration and Structural Change.’ Cambridge, UK. Cambridge University Press.
Nelson, C.R. and Plosser C.I. (1982). ‘Trends and Random Walks in Macroeconomic Time Series.’ Journal of Monetary Economics, 10, 139-162.
Phillips, P.C.B. and P. Perron (1988). ‘Testing for Unit Root in Time Series Regression.’ Biometrika, 75, 335-346.
Said, S.E. and D.A. Dickey (1984). ‘Testing for unit roots in autoregressive moving average models of unknown order.’ Biometrika, 71, 599-607.