The Sensitivity of Country Ranks to Index Construction and Aggregation Choice: The Case of Immigration Policy

How sensitive are country ranks to the aggregation function used in index construction? This paper tests whether different aggregation functions come to different results in regard to the ranking of countries. Indices within the field of immigration and integration policy are analyzed, yet, the results pertain to index building across the social sciences. The paper discusses three aggregation methods: the arithmetic mean, the geometric mean, and a noncompensatory/non‐linear aggregation function based on the Condorcet method. In the empirical part, these three aggregation functions are applied to the family indicators for the year 2010 of the Immigration Policies in Comparison (IMPIC) dataset, a new dataset which measures immigration policies’ restrictiveness, as well as to the eight policy strands of the Migrant Integration Policy Index for the year 2014. Results show that the methods react differently to extreme values and thus result in different rank orders in the middle range. In the politicized field of immigration and integration policies, country ranks play a crucial role and this is shown to have profound real‐world implications. The paper thus urges researchers to be reflective of the assumptions of different aggregation functions, as these lead to different results.