2009
DOI: 10.2139/ssrn.1480682
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Stationarity of Time Series and the Problem of Spurious Regression

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Cited by 20 publications
(20 citation statements)
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References 17 publications
(11 reference statements)
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“…When it comes to quantifying transport infrastructure implications on the economic growth, the studies highlighted the specific inputs and outputs, being simpler to choose the variables involved. As can be seen in Appendix A, Table A1 follow the literature [98,99], we use GDP per capita based on purchasing power parity (PPP) as a dependent variable. Even if most studies use GDP at market prices (euro per capita), given the distribution of these variables and the implication on the viability of model, the chosen variable is better for provide an adequate measure of economic growth.…”
Section: Sample and Variablesmentioning
confidence: 99%
See 1 more Smart Citation
“…When it comes to quantifying transport infrastructure implications on the economic growth, the studies highlighted the specific inputs and outputs, being simpler to choose the variables involved. As can be seen in Appendix A, Table A1 follow the literature [98,99], we use GDP per capita based on purchasing power parity (PPP) as a dependent variable. Even if most studies use GDP at market prices (euro per capita), given the distribution of these variables and the implication on the viability of model, the chosen variable is better for provide an adequate measure of economic growth.…”
Section: Sample and Variablesmentioning
confidence: 99%
“…To test the validity of a regression, the literature indicates the need to check if it is stationary or not by the Augmented Dicky Fuller (henceforth "ADF"). If it is stationary, it is indicated to work with the differences or logarithms of the series and if it is seasonal it is necessary to use moving averages or to log of the series [4,16,98,99]. In order to eliminate the problem of spurious regression or the existing non-linear relationship between the independent and dependent variables and to achieve a normal distribution of variables, some of the variables (except Index_Transport for example), were logarithmically transformed (see Table A2).…”
Section: Sample and Variablesmentioning
confidence: 99%
“…In conducting a unit root test, Baumöhl and Lyócsa (2009) argued that providing results of at least two tests is a convention in economic literature. Most frequently ADF, Phillips-Perron (PP) test, and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test are used, and are also incorporated into the majority of statistical or econometric software.…”
Section: Unit Root Testmentioning
confidence: 99%
“…Most frequently ADF, Phillips-Perron (PP) test, and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test are used, and are also incorporated into the majority of statistical or econometric software. However, since KPSS includes a transposed null hypothesis, which identifies a dataset as stationarity against alternative of a unit root, the results of this test could be mixed (Baumöhl and Lyócsa 2009). Thus, the KPSS test was not included in this study; rather, a modified Dickey-Fuller (DF) unit root test transformed via a generalized least squares (GLS) regression that was proposed by Elliott et al (1996) was used: the DF-GLS test.…”
Section: Unit Root Testmentioning
confidence: 99%
“…However, the unusually high R 2 coefficient might be an indicator of a spurious regression, moreover when most of the variables are non-stationary at levels. Theory suggests that in case of spurious regression R 2 is greater than Durbin-Watson (DW) statistics ("rule of thumb"), and there is high risk of type I error, or false rejection of the null hypothesis βi=0 (Baumohl, Lyocsa, 2009). In this case DW statistics is around 2 (R 2 <DW), all CLRM assumptions are met, and the null hypothesis for the main parameter of interest (budget deficit) is not rejected anyway, so the selection of the OLS method as most appropriate can be considered as justified.…”
Section: Econometric Modelmentioning
confidence: 99%