Andrea Vaccaro on comparing cross-national measures of state capacity

WIDER Seminar Series

Andrea Vaccaro on comparing cross-national measures of state capacity

Andrea Vaccaro gave a presentation for the UNU-WIDER staff on 29 April 2020. The presentation was held as a webinar.

Summary: Comparing cross-national measures of state capacity

In the last few decades research on state capacity, its causes, and its consequences has attracted a large number of scholars from a variety of social science fields. Despite proliferating quantitative cross-national work on the topic, the statistical analysis of cross-national measures of state capacity remains limited. A deeper understanding of the similarities, divergencies, and shortcomings of these measures is critical, if we are to get a better picture on extant cross-national literature on state capacity and conduct more meaningful research on the topic in the future.

This study provides a systematic comparative analysis of seven frequently used cross-national measures of state capacity by focusing mainly on three measurement issues: validity, interchangeability, and rating discrepancy. The findings show that the measures are strongly associated among each other and have high convergent validity but are only weakly interchangeable. The cause of these somewhat counterpoising findings seems to lie in strikingly high rating discrepancies in individual countries.

No measure of state capacity seems to be clearly superior to others, so future cross-national studies on the topic should ensure that a given definition of state capacity matches with the chosen measure and make explicit whether the findings are generalizable or not.

About the speaker

Andrea Vaccaro is a PhD Fellow at UNU-WIDER and a PhD Candidate at the Department of Social Sciences and Economics, Sapienza University of Rome. His doctoral research focuses on cross-national measures of state capacity. More broadly, his research interests include state capacity, political institutions, socio-economic development, measurement issues, and quantitative methods.