In the last decade, researchers have developed many innovative ideas for the construction of indices measuring immigration policies. Methodological considerations have, however, been largely absent from the discussion. To close this gap, this paper investigates the characteristics of existing indices by critically comparing and discussing them. We start by providing a definition of immigration policy which may serve as a benchmark when assessing the indices. By means of the analytical framework developed by Munck and Verkuilen (2002), which we adapt and customize for our analysis, we then evaluate the conceptualization, measurement, and aggregation, as well as the empirical scope of thirteen immigration policy indices. We discuss methodological strengths and weaknesses of the indices, how these affect the research questions that can be answered and what the next steps in index building within the field of immigration policy should be.
Immigration is one of the most widely debated issues today. It has, therefore, also become an important issue in party competition, and radical right parties are trying to exploit the issue. This opens up many pressing questions for researchers. To answer these questions, data on the self‐ascribed and unified party positions on immigration and immigrant integration issues is needed. So far, researchers have relied on expert survey data, media analysis data and ‘proxy’ categories from the Manifesto Project Dataset. However, the former two only give the mediated party position, and the latter relies on proxies that do not specifically measure immigration. The new dataset presented in this article provides researchers with party positions and saliency estimates on two issue dimensions – immigration and immigrant integration – in 14 countries and 43 elections. Deriving the data from manifestos enables the provision of parties’ unified and unfiltered immigration positions for countries and time points not covered in expert surveys and media studies, making it possible to link immigration and immigrant integration positions and saliency scores to other issue areas covered in the Manifesto Project Dataset. Well‐established criteria are used to distinguish between statements on (1) immigration control and (2) immigrant integration. This allows for a more fine‐grained analysis along these two dimensions. Furthermore, the dataset has been generated using the new method of crowd coding, which allows a relatively fast manual coding of political texts. Some of the advantages of crowd coding are that it is easily replicated and expanded, and, as such, presents the research community with the opportunity to amend and expand upon this coding scheme.
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.
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