2019
DOI: 10.1017/psrm.2019.38
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Estimating subnational preferences across the European Union

Abstract: Subnational analyses of political preferences are substantively relevant and offer advantages for causal inference. Yet, our knowledge on regional political preferences across Europe is limited, not least because there is a lack of adequate data. The rich Eurobarometer (EB) data is a promising source for European-wide regional information. Yet, it is only representative for the national level. This paper compares state-of-the-art methods for estimating regional preferences from nationally representative EB dat… Show more

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Cited by 9 publications
(6 citation statements)
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“…Our four-wave sample has a median number of 511 observations per NUTS2 region. This allows us to avoid many of the issues regarding representativeness and precision on the regional level that usually plague European comparative surveys (Lipps & Schraff 2019). The four-wave design makes our analysis a longitudinal study that can investigate change on the regional and national level.…”
Section: Methodsmentioning
confidence: 99%
“…Our four-wave sample has a median number of 511 observations per NUTS2 region. This allows us to avoid many of the issues regarding representativeness and precision on the regional level that usually plague European comparative surveys (Lipps & Schraff 2019). The four-wave design makes our analysis a longitudinal study that can investigate change on the regional and national level.…”
Section: Methodsmentioning
confidence: 99%
“…We improve the generalizability of the survey responses using MRP to reweight the responses so that they better represent the full population of previously successful noncompleters in our partner colleges. While MRP has been used extensively in political science to measure public opinion in the United States (Gao et al, 2019;Gelman et al, 2010;Gelman & Little, 1997;Howe et al, 2015;Kastellec et al, 2019;Lax & Phillips, 2009;Lei et al, 2017;Lipps & Schraff, 2019;Little, 1993;Pacheco, 2011;Park et al, 2004;Wang et al, 2015;Warshaw & Rodden, 2012), and is increasingly used by political scientists outside of the United States (Lipps & Schraff, 2019;Toshkov, 2015), sociologists (Fairbrother & Martin, 2013), and epidemiologists (Downes et al, 2018;Eke et al, 2016;Zhang et al, 2014) to generate representative estimates from nonrepresentative data, it has been seldom used in surveybased educational research. 3 Following our general description above, MRP is implemented using this two-step process:…”
Section: Methodsmentioning
confidence: 99%
“…We estimated additional models to determine how, if at all, our main results are sensitive to alternative specifications. Our first robustness check addresses possible concerns about the number and representativity of respondents surveyed at the subnational level (Lipps & Schraff, 2021a). The average number of individual respondents per region-year in our sample is 484 (and the median is 343).…”
Section: Robustness Testsmentioning
confidence: 99%
“…On the other hand, as the powers of the EU have grown, scholars have shown how economic conditions shape attitudes toward the EU (Gomez, 2015) and Eurosceptic voting behaviour (Hobolt & de Vries, 2016). To date, however, few cross‐national studies have examined the impact of subnational economic conditions on Euroscepticism (Chalmers & Dellmuth, 2015; Colantone & Stanig, 2018b; Lechler, 2019; Lipps & Schraff, 2021a; Lubbers & Scheepers, 2007; Mahler et al., 2000). Moreover, among those that do, none has directly modelled how, if at all, the relationship between EU support and subnational economic conditions has changed over the long term.…”
Section: Support For European Integrationmentioning
confidence: 99%