wvs: World Values Survey Aggregate Data

In psre: Presenting Statistical Results Effectively

World Values Survey Aggregate Data

Description

A subset of data from the second thorugh fifth waves of the World Values Survey.

Format

A data frame with 162 rows and 26 variables

country

Country of respondent residence.

wave

Wave of the survey.

year

Year of the survey.

pct_high_rel_imp

Religious importance is coded as Very, Rather, Not very or Not at all important in the individual data. This variable is the proportion of respondents who indicated Very or Rather.

pct_female

Proportion of observations identifying as female.

mean_lr

Left-right self-placement is coded on a 1 (Left) to 10 (Right) scale in the individual data. The mean_lr variable is the country-wave average of left-right self-placement.

pct_less_secondary, pct_secondary, pct_some_univ, pct_univ_degree

In the individual data, education is coded as Less than secondary, Secondary complete, Some university and University degree or more. In the aggregate data, we calculate the proportion of observations in each category.

pct_low_income, pct_mid_income, pct_high_income

In the individual data, income is coded in decies (i.e., a 1-10 scale). In the aggregate data, we calculate the proportion of observations in categories 1-3 (Low), 4-7 (Middle) and 8-10 (High) categories.

moral

In the individual data, we created an additive scale of variables about how justifiable the following actions are: Illegally claiming government benefits, Avoiding a fare on public transport, Cheating on taxes, Accepting a bribe, Homosexuality, Divorce, Abortion, Prostitution, Euthanasia, Suicide on a scale from 1 (Never justifiable) to 10 (Always Justifiable). In the aggregate data, we calculate the country-wave average of this scale.

sacsecval

Secular Values - opposite of traditional values wherein religion, parent-child ties, deference to authority and traditional family values are paramount. In the aggregate data, we take the country-wave average of this scale.

secpay

Imagine two secretaries, of the same age, doing practically the same job. One finds out that the other earns considerably more than she does. The better paid secretary, however, is quicker, more efficient and more reliable at her job. In your opinion, is it fair or not fair that one secretary is paid more than the other? The secpay variable is the proportion of people in each country indicating that the pay discrepancy is unfair.

resemaval

Emancipative Values - preference for gender and racial equality, liberty and personal autonomy. In the aggregate data, we take the country-wave average of this scale.

rgdpe

Expenditure-side real GDP at chained PPPs (in mil. 2017US$). Useful for making cross-country/cross-time comparisons of relative living standards. Obtained from Penn World Tables.

rel_soc

Dummy variable indicating places where at least 75 respondents identified religion as being important.

pop

Population in Millions, obtained from Penn World Tables.

gdp_cap

GDP/capita: rgdpe/pop.

gini_disp

Gini coefficient in terms of disposable income from the SWIID.

gini_mkt

Gini coefficient in terms of market prices from the SWIID.

polrt

Measure of the violation of political rights from the Freedom in the World Project. Coded on a scale from 1 (fewest violations) to 7 (most violations).

civlib

Measure of the violation of civil liberties from the Freedom in the World Project. Coded on a scale from 1 (fewest violations) to 7 (most violations).

democrat

Using the freedom status variable, we code a country as a democracy if in the past 15 years it was always at least partly free and was free for at least 50 percent of the time. This follows the work of Weakliem et. al. (2005).

civ

Categories defining the civilization in which each country belongs. Other=0, African=1, Buddhist=2, Hindu=3, Islamic=4, Japanese=5, Latin American=6, Orthodox=7, Siinic=8, Western=9.

Details

We started with waves 2 (Inglehart et. al., 2014a), 3 (Inglehart et. al., 2014b), 4 (Inglehart et. al., 2014c) and 5 (Inglehart et. al., 2014d) of the World Values Survey (WVS). The WVS is a cross-national survey effort aimed at describing the character of value systems around the globe. From each survey, we capture country and survey year, several demographic variables (Religious Importance, fairness, left-right self-placement, education, income, sex and age) along with some values scales (emancipative values and secular values). We also capture several questions about the extent to which several controversial actions are morally justifiable. We add data from several other projects to these data. To measure inequality, we use the Standardized World Income Inequality Data (Solt, 2020). From this dataset, we capture the Gini Coefficient (both in disposable income and market income, though we tend to use the former in models). We obtain GDP and population data from the Penn World Tables version 10 (Feenstra et. al., 2015). We gather data on political rights, civil liberties and freedom status from the Freedom in the World Project (Freedom House, 2020). We use the civilizations codes from Henderson and Tucker (2001), which were used to test Huntington’s (1996) argument about the “clash of civilizations”. Finally, we get the human development index (HDI) from the United Nations Development Programme (2020). The combined dataset has 237,787 individual observations nested within 84 countries. Most countries appear in only one or two waves (65), but nine appear in three waves and 10 in four waves.

We aggregate the variables in the individual dataset by country-wave to produce a more manageable data set. The aggregate dataset has 162 rows and 38 variables. The variables are as follows:

References

Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table" American Economic Review, 105(10), 3150-3182, available for download at https://www.rug.nl/ggdc/productivity/pwt/.

Freedom House. (2020). Freedom in the World 2020. New York: Freedom House.

Henderson, Errol A. and Richard Tucker. 2001. "Clear and Present Strangers: The Clash of Civilizations and International Conflict." International Studies Quarterly, 45(2):317–338.

Inglehart, R., C. Haerpfer, A. Moreno, C. Welzel, K. Kizilova, J. Diez-Medrano, M. Lagos, P. Norris, E. Ponarin & B. Puranen et al. (eds.). 2014a. World Values Survey: Round Two - Country-Pooled Datafile Version: https://www.worldvaluessurvey.org/WVSDocumentationWV2.jsp. Madrid: JD Systems Institute.

Inglehart, R., C. Haerpfer, A. Moreno, C. Welzel, K. Kizilova, J. Diez-Medrano, M. Lagos, P. Norris, E. Ponarin & B. Puranen et al. (eds.). 2014b. World Values Survey: Round Three - Country-Pooled Datafile Version: https://www.worldvaluessurvey.org/WVSDocumentationWV3.jsp. Madrid: JD Systems Institute.

Inglehart, R., C. Haerpfer, A. Moreno, C. Welzel, K. Kizilova, J. Diez-Medrano, M. Lagos, P. Norris, E. Ponarin & B. Puranen et al. (eds.). 2014c. World Values Survey: Round Four - Country-Pooled Datafile Version: https://www.worldvaluessurvey.org/WVSDocumentationWV4.jsp. Madrid: JD Systems Institute.

Inglehart, R., C. Haerpfer, A. Moreno, C. Welzel, K. Kizilova, J. Diez-Medrano, M. Lagos, P. Norris, E. Ponarin & B. Puranen et al. (eds.). 2014d. World Values Survey: Round Five - Country-Pooled Datafile Version: https://www.worldvaluessurvey.org/WVSDocumentationWV5.jsp. Madrid: JD Systems Institute.

Solt, Frederick. 2020. "Measuring Income Inequality Across Countries and Over Time: The Standardized World Income Inequality Database." Social Science Quarterly 101(3):1183-1199. SWIID Version 9.0, October 2020.

psre documentation built on Aug. 8, 2022, 5:05 p.m.