Appendix Chapter 2

Variable Description Example

A Region name in Gennaioli et al. (2014) exactly corresponds to WVS/EVS region.

Gennaioli et al. (2014): Tirana; WVS: AL:

Tirana

B

Region name in Gennaioli et al. (2014) is a very close approximation to WVS/EVS region.

OR: Region in one dataset contains an additional smaller (in terms of population) region that is not included in the region of the other dataset.

Gennaioli et al. (2014): Distrito Federal;

WVS: MX: Zona metropolitana

OR: Gennaioli et al. (2014): Ankara and Kirikkale; WVS: TR: Ankara (center)

C

Region in Gennaioli et al. (2014) is higher aggregated than the WVS/EVS region.

Several WVS/EVS were summarized in order to exactly match the corresponding Gennaioli et al. (2014) region.

Gennaioli et al. (2014): Prov. Brabant;

EVS: BE: Vlaams Brabant, BE: Waals-Brabant

D

See C, but summarized regions in WVS/EVS lack one or more region(s) in order to fully represent the corresponding Gennaioli et al. (2014) region.

Gennaioli et al. (2014): Jylland; EVS: DK:

Danmark - Midtjylland, DK: Danmark - Nordjylland

E

Region in WVS/EVS is higher aggregated than the Gennaioli et al. (2014) region.

WVS/EVS data for one region is (fully) allocated to several regions in Gennaioli et al. (2014) as both dataset report an an official regional division.

Gennaioli et al. (2014): Arizona, Colorado, Montana, Nevada, New Mexico, Utah, Wyoming; WVS: US: Rocky Mountain States

F

See E, but WVS/EVS report an unofficial regional division and therefore fail to fully represent one or more Gennaioli et al.

(2014) region(s).

Gennaioli et al. (2014): Berat; Elbasan;

Durres; WVS: AL: Center

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Table 9: Descriptive statistics

Variable Description Median Mean Std.

Dev. Min Max Obs Source Corr w/ Ln (GDPregion) Ln(GDPregion)

Logarithm of the gross domestic product per capita in a region (in constant 2005 PPP US$).

8.85 8.87 1.18 5.24 12.02 7,493 Gennaioli et

al. (2014) 1.00

Independence

Percentage of respondents in a region that mention “independence” as an important quality for children (Survey variable: A029).

0.46 0.47 0.20 0 1 3,002 WVS (2015);

EVS (2015) 0.24

Obedience

Percentage of respondents in a region that mention “obedience” as an important quality for children (Survey variable: A042).

0.32 0.33 0.18 0 1 3,002 WVS (2015);

EVS (2015) -0.31 Trust (control set

2)

Percentage of respondents in a region that generally trust other people (Survey variable: A165).

0.29 0.31 0.17 0 1 3,022 WVS (2015);

EVS (2015) 0.30

Christian (control set 2)

Percentage of respondents in a region that reported "Christian" as their religious denomination (answers include "Catholic: doesn't follow rules",

"Christian", "Christian Fellowship",

Percentage of respondents in a region that reported "Muslim" as their religious denomination (Survey variable: F025).

0.00 0.07 0.21 0 1 3,026 WVS (2015);

EVS (2015) -0.33 Noreligion

(control set 2)

Percentage of respondents in a region that reported "No religion" as their religious denomination (Survey variable: F025).

0.02 0.15 0.22 0 1 3,026 WVS (2015);

EVS (2015) 0.09

58

Hindu (control

set 2)

Percentage of respondents in a region that reported "Hindu" as their religious denomination (Survey variable: F025).

0.00 0.02 0.11 0 1 3,026 WVS (2015);

EVS (2015) -0.24 Buddhist

(control set 2)

Percentage of respondents in a region that reported "Buddhist" as their religious denomination (Survey

Percentage of respondents in a region that reported a religious denomination other than Christian, Muslim, Buddhist, Hindu or no religion (e.g.,

Confucianism, Zionist, Taoist, Anglican, not availabel etc.) (Survey variable: F025).

0.18 0.32 0.33 0 1 3,026 WVS (2015);

EVS (2015) -0.17

Government Effectiveness

The index captures the "perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies." The index originally ranged between -2.5 and +2.5, with higher values indicating stronger governance performance, but was normed to range from 0 to 1.

0.38 0.45 0.26 0 1 4,056 World Bank

(2017) 0.77

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Rule of Law

The index captures the “perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence”. The index originally ranged between -2.5 and +2.5, with higher values indicating stronger governance performance, but

The index captures the "perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of

corruption, as well as "capture" of the state by elites and private interests."

The index originally ranged between -2.5 and +-2.5, with higher values indicating stronger governance performance, but was normed to range from 0 to 1.

(logarithmized) genetic distance to the South West of the United Kingdom in terms of the regional allele frequency B*27. The variable is calculated by substracting the allele frequency of B*27 in the South West of the UK from the allele frequency B*27 in any given region. The distance is given as non-negative values (modulus |x|).

Latitude of the centroid of each region

calculated in ArcGIS. 37.53 33.53 16.70 0.02 69.95 7,493 Gennaioli et

al. (2014) 0.57

60

Inverse distance

to coast (control set 1)

The ratio of 1 over 1 plus the region's average distance to the nearest coastline in thousands of kilometres. Higher values for this variable indicate that a region is closer to the coast, smaller values indicate larger average distances to the coast. Gennaioli et al. (2014) create an equal distance projection of the Collins-Bartholomew World Digital Map and a map of the coastlines. With these two maps Gennaioli et al. (2014a) create a raster with the distance to the nearest coastline of each cell in a given region. In order to obtain the average distance to the nearest coastline, the authors sum the distance to the nearest coastline of all cells within each region and divide that sum by the number of cells in the region.

0.01 0.03 0.05 0.00 0.65 7,493 Gennaioli et

al. (2014) 0.10

Malaria ecology (control set 1)

The “malaria ecology” index of Kiszewski et al. (2004) measures the risk of being infected by Malaria. The index variable ranges from 0 to 39 with higher values indicating a higher risk and thus less Malaria stability. The index takes into account both climatic factors and the dominant vector species to give an overall measure of the component of malaria variation that is exogenous to human intervention. The index is calculated for grid squares of one half degree longitude by one half degree latitude. Regional averages are calculated via ArcGIS.

0.01 1.23 2.96 0.00 28.68 7,493 Gennaioli et

al. (2014) -0.44

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Ln(Oil Gas

Production) (control set 1)

(Logarithmized) cumulative oil, gas and liquid natural gas production from the time production began to 2000. Oil and liquid natural gas were collected in millions of barrels. Gas was collected in billions of cubic feet and divided by 6 to convert to millions of barrels of oil equivalents.

0.00 0.00 0.01 0.00 0.12 7,493 Gennaioli et

al. (2014) 0.11

Ln(Pop density) (control set 1)

Logarithm of the population density which is measured as people per square kilometres in a region.

4.20 4.14 1.69 -4.06 10.06 7,493 Gennaioli et

al. (2014) 0.06 Capital in region

(control set 1)

Dummy variable that is equal to 1 if the region contains a national capital city, 0 otherwise.

0.00 0.05 0.22 0 1 7,493 Gennaioli et

al. (2014) 0.11 Years education

(control set 2)

Average years of schooling from primary school onwards for the population aged 15 years or older in a region.

7.74 7.55 3.14 0.67 13.76 5,198 Gennaioli et

al. (2014) 0.76

Temperature (control set 1)

Monthly average of daily mean temperature (Celsius) averaged across all data points within the subnational region.

12.66 14.32 8.26 -14.49 28.19 1,016 Gennaioli et

al. (2014) -0.48 1/Ln_regpop Inverse of the logarithm of the

population in a region. 0.07 0.07 0.00 0.05 0.11 7,493 Gennaioli et

al. (2014) 0.04 1/Ln_natpop Inverse of the logarithm of the

population in a country. 0.06 0.06 0.00 0.05 0.07 7,493 Gennaioli et

al. (2014) 0.05

Landlocked-region

(control set 1)

Dummy variable that is equal to 1 if the

region is landlocked, 0 otherwise. 1 0.57 0.50 0 1 7,493 ArcGIS -0.18

Dummy variable that is equal to 1 if the region has a border to another region in a neighboring country, 0 otherwise.

0 0.45 0.50 0 1 7,490 ArcGIS -0.12

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No

countryborders (control set 1)

Number of borders to other countries

incl. a region's own country border. 1 1.60 0.86 0 8.00 7,490 ArcGIS -0.13

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CHAPTER 3

EVALUATING WATER- AND HEALTH-RELATED DEVELOPMENT

Im Dokument The influence of culture, development aid and temperature on regional incomes (Seite 68-75)