Access the full text.
Sign up today, get DeepDyve free for 14 days.
In this paper, the convergence of income per capita across U.S. metropolitan statistical areas (metros) is examined over the period between 1969 and 2011. We initiate the analysis with multivariate tests for stability, and the existence of unit roots, performed on the ratio of income per capita of a specific metro relative to the cross-sectional average. The tests used were: Multivariate homogeneous Dickey–Fuller, Levin–Lin–Chu (2002), Im–Pesaran–Shin (2003), MKPSS, Bai–Ng (2004) Panic and Hadri-LM tests. The analysis is complemented by the use of the panel stationarity test accounting for structural changes, as proposed by Carrion-i- Silvestre et al. (2005), which our other tests do not incorporate. The study of convergence is important for both economists, as a means to test growth theories and distinguish between different models, as well as policy makers who seek to maximize the utility of their constituents by making use of all information available to them. While, standard unit root tests indicates stationarity of our metric, i.e., the ratio of income per capita of a specific metro relative to the cross-sectional average, the tests of stability suggests divergence, barring the Bai–Ng test. But, given that the tests of stability are more conducive to checking for convergence, we conclude that in the 384 U.S. metros there is a divergence of per capita income. JEL codes: C12; O40 Keywords: panel data; income convergence; structural breaks; unit root test
Economics, Management, and Financial Markets – Addleton Academic Publishers
Published: Jan 1, 2016
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.