Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

The role of spatial scale in regional convergence: the effect of MAUP in the estimation of $$\beta $$ β -convergence equations

The role of spatial scale in regional convergence: the effect of MAUP in the estimation of... Empirical analysis of regional convergence is normally based on data collected at a geographical scale corresponding to states or large regions (NUTS-2 or NUTS-3 for the case of Europe). However, it could be more realistic to consider that the dynamics generating economic growth take place at a smaller spatial scale. Potential heterogeneity across local areas might be not correctly quantified if the analysis is made at an aggregated geographical scale, which produces the so-called modifiable areal unit problem (MAUP). The objective of this paper is to explore to which extent MAUP has an effect on convergence analysis, in particular in the empirical estimation of $$\beta $$ β -convergence equations. First, we show how aggregation of spatial data can generate a problem of bias in the OLS estimator of $$\beta $$ β -convergence equations from cross-sectional data, as well as inflating its variance. Second, by means of a numerical simulation, we quantify the effect of geographical aggregation on the estimates of $$\beta $$ β -convergence. Our experiment is based on real spatial structures of aggregated and disaggregated data for different countries, and it numerically illustrates how a modification in the spatial scale has a significant effect on this type of studies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Annals of Regional Science Springer Journals

The role of spatial scale in regional convergence: the effect of MAUP in the estimation of $$\beta $$ β -convergence equations

Loading next page...
 
/lp/springer-journals/the-role-of-spatial-scale-in-regional-convergence-the-effect-of-maup-lAHfFOIVWt

References (47)

Publisher
Springer Journals
Copyright
Copyright © 2016 by Springer-Verlag Berlin Heidelberg
Subject
Economics; Regional/Spatial Science; Landscape/Regional and Urban Planning; Microeconomics; Environmental Economics; Geography, general
ISSN
0570-1864
eISSN
1432-0592
DOI
10.1007/s00168-016-0750-0
Publisher site
See Article on Publisher Site

Abstract

Empirical analysis of regional convergence is normally based on data collected at a geographical scale corresponding to states or large regions (NUTS-2 or NUTS-3 for the case of Europe). However, it could be more realistic to consider that the dynamics generating economic growth take place at a smaller spatial scale. Potential heterogeneity across local areas might be not correctly quantified if the analysis is made at an aggregated geographical scale, which produces the so-called modifiable areal unit problem (MAUP). The objective of this paper is to explore to which extent MAUP has an effect on convergence analysis, in particular in the empirical estimation of $$\beta $$ β -convergence equations. First, we show how aggregation of spatial data can generate a problem of bias in the OLS estimator of $$\beta $$ β -convergence equations from cross-sectional data, as well as inflating its variance. Second, by means of a numerical simulation, we quantify the effect of geographical aggregation on the estimates of $$\beta $$ β -convergence. Our experiment is based on real spatial structures of aggregated and disaggregated data for different countries, and it numerically illustrates how a modification in the spatial scale has a significant effect on this type of studies.

Journal

The Annals of Regional ScienceSpringer Journals

Published: Feb 18, 2016

There are no references for this article.