Determination of stochastic vs. deterministic trend in quarterly GDP of Pakistan
AbstractMany 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 22091.
Date of creation: 22 Dec 2009
Date of revision: 10 Apr 2010
Bootstrapping; Stationarity; Pivotal statistic; Unit root;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-04-24 (All new papers)
- NEP-CWA-2010-04-24 (Central & Western Asia)
- NEP-ORE-2010-04-24 (Operations Research)
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- Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
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