Culture, Cooperation, and the General Welfare

Berigan, Nick; Irwin, Kyle

doi:10.1177/0190272511422451

Cited by 47 publications

(35 citation statements)

References 48 publications

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“…This corresponds approximately to primary (low), secondary (middle), and tertiary (high) education. Although outliers are possible, this standard measure enhances the comparability of education systems between countries . In addition, to reduce the influence of outliers, respondents who reported a number of years that was three standard deviations from the country mean were removed from our sample .…”

Section: Methodsmentioning

confidence: 99%

“…Although outliers are possible, this standard measure enhances the comparability of education systems between countries. 32,33 In addition, to reduce the influence of outliers, respondents who reported a number of years that was three standard deviations from the country mean were removed from our sample. 34 The age of the respondent at the time of the survey is categorized into four age groups: 18 to 29 years, 30 to 44 years, 45 to 54 years, and 55 to 65 years.…”

Section: Measurementsmentioning

confidence: 99%

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Who donates? Cross‐country and periodical variation in blood donor demographics in Europe between 1994 and 2014

et al. 2017

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BACKGROUND Ageing European populations put pressure on national blood supplies, increasing the need for blood and donor base rejuvenation. Therefore, we investigate how European countries' blood donor populations differ and how they have evolved over the last 2 decades. Previous comparative research, based on 1994 Eurobarometer data, indicate that the typical donor is an educated, middle‐aged, white, married male. Other sociodemographic and socioeconomic correlates, such as employment status and type of community, are less clear. STUDY DESIGN AND METHODS Multilevel analyses are performed on repeated cross‐level data from the Eurobarometer (waves 1994, 2002, 2009, and 2014) to compare information on “ever having donated” across sociodemographic categories, countries, and periods. RESULTS There are consistent but moderate country and period differences. The donor population rose to become largest in most countries by 2009, and stabilized thereafter. Over the studied period, donors were more likely to be higher educated, married men. Nevertheless, changes across time in donor profiles within countries did occur. Women were less likely to donate blood, especially in Southern and Eastern Europe, but this gender gap has declined. Furthermore, educational attainment seems more relevant for women, although, more recently, to a lesser extent. CONCLUSION Although there is a promising trend in which women, young people, and students are increasingly likely to donate, more attention is needed to reach the unemployed and the low to medium educated. Because the unemployed may lack structural opportunities to donate, and the low to medium educated may lack relevant knowledge on blood donation necessity, we recommend providing practical opportunities and information on the necessity of blood donation.

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Section: Methodsmentioning

confidence: 99%

Section: Measurementsmentioning

confidence: 99%

Who donates? Cross‐country and periodical variation in blood donor demographics in Europe between 1994 and 2014

et al. 2017

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“…For example, Karabarbounis (2011) cite legal origins, political institutions, persistent cultural characteristics, ethnic fragmentation, prospects of upward mobility, and social beliefs about fairness. Country differences in culture (Berigan and Irwin 2011) and national identity (Shayo 2009) are also part of those specific factors that can affect the demand for redistribution. In a panel data structure with i = 1,…N individuals followed across t = 1,…,T periods, it is common to use the following specification:…”

Section: Empirical Strategymentioning

confidence: 99%

Preferences for redistribution in Europe

Olivera

2015

IZA J Labor Stud

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This paper uses pseudo panel techniques and a fixed effects estimator to analyse the determinants of preferences for redistribution in 34 European countries over the period [2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012]. The data is drawn from the six available waves of the European Social Survey. The main result is that changes in income inequality positively affect changes in preferences for redistribution over time. Though this result is predicted by standard political economy models, it has found little previous empirical support. This study shows that, at least in Europe, growing income inequality leads to more individual support for redistribution. The empirical results hold after performing a variety of robustness checks regarding the construction of pseudo panels, the use of lags and different measures of income inequality.

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“…Education is measured by years of full-time education completed, rather than highest educational level attained, as this indicator enhances the comparability of education systems between countries (Berigan & Irwin, 2011;Bracke et al, 2014). In addition, to reduce the influence of outliers, cases who score higher than the country-year specific mean plus three standard deviations are removed (Bracke et al, 2013).…”

Section: Independent Variablesmentioning

confidence: 99%