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What is Augmented Dickey–Fuller Test (ADF)

Chapter 20
Handbook of Research on Strategic Developments and Regulatory Practice in Global Finance
In statistics and econometrics, an augmented Dickey–Fuller test (ADF) is a test for a unit root in a time series sample. It is an augmented version of the Dickey–Fuller test for a larger and more complicated set of time series models. The augmented Dickey–Fuller (ADF) statistic, used in the test, is a negative number. The more negative it is, the stronger the rejection of the hypothesis that there is a unit root at some level of confidence.
Published in Chapter:
Causal Relationship between Foreign Direct Investment and Economic Growth: Evidence from Turkey
Hasan Bakır (Uludağ University, Turkey) and Filiz Eryılmaz (Uludağ University, Turkey)
Copyright: © 2015 |Pages: 12
DOI: 10.4018/978-1-4666-7288-8.ch020
Abstract
In this chapter, the authors investigate the causality relationship between the inflows of foreign direct investment (FDI) and economic growth as measured by Real Gross Domestic Product (GDP) per capita in Turkey during the period 1974-2012 by using the Granger causality tests. The causality test indicates that economic growth Granger-causes FDI. This means that there is bidirectional causality from Reel GDP to FDI in Turkey. So the author results support “the growth – driven FDI hypothesis”. This demonstrates that in the related time in Turkey, more direct foreign investment entered the economy together with an increase in economic growth.
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