The economic development and growth literature contains extensive discussions on relationships between exports and economic growth. One debate centres on whether countries should promote the export sector to obtain economic growth. An abundant empirical literature on this export-led growth (ELG) hypothesis has followed. We aim to contribute to this literature in two ways. In this paper, part 1, we provide a comprehensive survey of more than 150 export-growth applied papers. We describe the changes that have occurred, over the last two decades, in the methodologies used empirically to examine for relationships between exports and economic growth, and we provide information on the current findings.The last decade has seen an abundance of time series studies that focus on examining for causality via exclusions restrictions tests, impulse response function analysis and forecast error variance decompositions. Our second contribution is to examine some of these time series methods. We show, in part 2, that ELG results based on standard causality techniques are not typically robust to specification or method. We do this by reconsidering two export-led growth applications - Oxley's (1993) study for Portugal, and Henriques and Sadorsky's (1996) analysis for Canada. Our results suggest that extreme care should be exercised when interpreting much of the applied research on the ELG hypothesis.Economic Growth, Export Promotion, Causality, Time Series Models, Cointegration, Innovation Accounting,

This paper continues the investigation of Giles and Williams (2000) on export-led growth (ELG). In the first part, we surveyed the empirical export-led growth literature; it was evident that Granger non-causality tests are commonly applied as a test for ELG. In this paper, we explore the sensitivity of the test for exclusions restrictions often used as the Granger non-causality test for ELG by reconsidering two applications: Oxley's (1993) study for Portugal and Henriques and Sadorsky's (1996) analysis for Canada. We focus on the robustness of the method adopted to deal with non-stationarity, including the choice of deterministic trend degree. We show that different noncausality outcomes are easy to obtain, and consequently we recommend that readers interpret the empirical ELG literature with care. Our analysis also highlights the importance of examining the robustness of Granger non-causality test results to avoid spurious outcomes in applications.Economic Growth, Causality, Time Series Models, Robustness, Misspecification, Model Dimension, Cointegration,

The economic development and growth literature contains extensive discussions on relationships between exports and economic growth. One debate centers on whether countries should promote the export sector to obtain economic growth. An abundant empirical literature on this export-led growth (ELG) hypothesis has followed. We contribute to this literature in two ways. First, we provide a comprehensive survey of more than one hundred and fifty export-growth applied papers. We describe the changes that have occurred, over the last two decades, in the methodologies used to empirically examine for relationships between exports and economic growth, and we provide information on the current findings. The last decade has seen an abundance of time series studies which focus on examining for causality via exclusions restrictions tests, impulse response function analysis and forecast error variance decompositions. Our second contribution is to examine some of these time series methods. We show that ELG results based on standard causality techniques are not typically robust to specification or method. We do this by reconsidering two export-led growth applications -Oxley=s 1993 study for Portugal and Henriques and Sadorsky=s 1996 analysis for Canada. Our results suggest that extreme care should be exercised when interpreting much of the applied research on the ELG hypothesis.

This paper surveys a range of important developments in the area of preliminary-test inference in the context of econometric modelling. Both pre-test estimation and pre-test testing are discussed. Special attention is given to recent contributions and results. These include analyses of pre-test strategies under model mis-specification and generalised regression errors; exact sampling distribution results; and pre-testing inequality constraints on the model's parameters. In many cases, practical advice is given to assist applied econometricians in appraising the relative merits of pre-testing. It is shown that there are situations where pre-testing can be advantageous in practice

No abstract