Autoregressive Distributed Lag Approach (ARDL) to Corruption and Economic Growth Nexus in Nigeria
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This study employed annual time series data (1960-2003) and unit root tests with multiple breaks to determine the most likely times of structural breaks in major factors impacting on the trade-GDP nexus in Iran We found, inter alia, that the endogenously determined structural breaks coincided with important events in the Iranian economy, including the 1979 Islamic revolution and the outbreak of the Iraq-Iran war in 1980.By applying the Lumsdaine and Papell (1997) approach, the stationarity of the variable under investigation was examined and in the presence of structural breaks, we found that the null hypothesis of unit root could be rejected for all of the variables under analysis except one.Under such circumstances, applying the ARDL procedure was the best way of determining long run relationships.For this reason, the error correction version of the autoregressive distributed lag procedure (ARDL) was then employed to specify the short and long-term determinants of economic growth in the presence of structural breaks.The results showed that while the effects of gross capital formation and oil exports were important for the expansion of the Iranian GDP over the sample period, non-oil exports and human capital were generally less pivotal.It was also found that the speed of adjustment in the estimated models is relatively high and had the expected significant and negative sign.JEL classification numbers:
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This research focuses on tourism as a way to stimulate economic growth in Latin America and the Caribbean countries.The impact of tourism on economic growth was expected to have both short-and long-run effects.Panel autoregressive distributed lag, an econometric technique that allows for this temporal decomposition, was used.The results for the twenty-two countries revealed that, in the short-run, tourist capital investment per capita, tourist arrivals (number of persons), per capita electricity consumption, and the real exchange rate were statistically significant and had a positive impact on economic growth.In contrast, in the long-run, only tourist arrivals and per capita electricity consumption proved to be positive drivers of per capita economic growth.Policymakers should continue to develop and implement measures to attract as many tourists as possible while promoting investment in the tourism industry.However, they also need to pay attention to other economic sectors so that their countries do not become extremely dependent on tourism activity.
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Abstract We review the literature on the autoregressive distributed lag (ARDL) model, from its origins in the analysis of autocorrelated trend stationary processes to its subsequent applications in the analysis of cointegrated non‐stationary time series. We then survey several recent extensions of the ARDL model, including asymmetric and non‐linear generalisations of the ARDL model, the quantile ARDL model, the pooled mean group dynamic panel data model and the spatio‐temporal ARDL model.
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This paper contributes to the existing literature by investigating the impact of oil prices on real exchange rates in China and India. We employ the non-linear, autoregressive-distributed lag model advanced by Shin et al. (2014), which allows both short-run and long-run asymmetry pass-through to a variable of interest. Oil prices and exchange rates are frequently found to be noisy. In order to detect the accurate relationship between oil prices and exchange rates, the maximum overlap, discrete-wavelet transformation is used to remove noise from the original series. The dynamic relationship between the original and de-noised series is compared. Our empirical findings suggest only long-run asymmetric effects of oil prices on exchange rates for both countries; however, after time-series noise removal, the asymmetric long-run effect becomes symmetric for India. Policy implications also are included.
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Abstract This article studies quantile regression in an autoregressive dynamic framework with exogenous stationary covariates. We demonstrate the potential of the quantile autoregressive distributed lag model with an application to house price returns in the United Kingdom. The results show that house price returns present a heterogeneous autoregressive behaviour across the quantiles. Real GDP growth and interest rates also have an asymmetric impact on house prices variations.
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