“Book Descriptions: The Autoregressive Distributed Lag (ARDL) approach to cointegration was proposed by Pesaran and Shin (1999) and further extended by Pesaran et al. (2001). This method is also known as the bounds testing procedure for cointegration. It is used to estimate the short and long-run effects of one or more variables. It is also used to investigate the causal short- and long-run relationships between two or more variables.The ARDL bounds testing approach to cointegration has been extensively applied in different fields such as economics, finance, tourism, agriculture, and energy. Therefore, this method has become increasingly popular over the last ten years among post-graduate students and researchers. The ARDL bounds testing approach has some advantages in comparison with other traditional cointegration techniques such as the Engle-Granger procedure (Engle and Granger, 1987) and the Johansen test (Johansen, 1988). The ARDL approach to cointegration is a more suitable test for cointegration in the case of small sample data sizes, while the other conventional cointegration procedures require large sample data sets to obtain better results. Unlike the other traditional cointegration techniques, the ARDL approach does not require that all variables under study must be integrated in the same order. Also, the ARDL method gives unbiased estimates of long-run model coefficients.The objectives of this series are outlined as follows:To show the steps using EViews 12 with empirical data for applying the ARDL approach to carry out the following: - Measuring the short and long-run effects of one variable or more - Investigating the short- and long-run relationship between two or more variables;To interpret the EViews output of applying the ARDL approach to cointegration (long-run estimates) and error correction models (short-run estimates and error correction estimates and short and long-run causality relationships); andTo show the ways of writing, presenting, organizing, interpreting, or explaining the EViews results of applying the ARDL approach in your research paper or thesis or dissertation, Hence, this series is very helpful for post-graduate students, academicians, and researchers in economics and related fields.To achieve these objectives, the series has been divided into four books: In the first book, the time series ARDL model is discussed. The second book details the steps for applying the ARDL approach to measure the impact of trade openness on economic growth in Egypt during the period 1974–2015 as an example for the case of measuring the short and long-run effects of one variable. The third book shows the steps for applying the ARDL approach to examine the relationship between domestic investment and economic growth in Egypt during the period 1967–2016 as an example for the case of examining the short and long-run relationship between two variables. The Non-ARDL (NARDL) Approach is applied in the fourth book to estimate the asymmetric impact of trade openness on economic development in Egypt from 1974 to 2015.The objective of this book is to discuss the Autoregressive Distributed Lag (ARDL) model. To achieve this goal, this book is divided into six sections: The first section defines the ARDL model. The second section deals with the first order ARDL model. The third section presents the more general ARDL model. The fourth section shows the advantages of the ARDL model. The fifth section shows the selection criteria of the ARDL Model. The estimated ARDL model's evaluation tests and methods are included in the sixth section. Read more” DRIVE
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