Chapter 2 The Influence of the Cultural Values Independence and Obedience on Regional
2.4 The Link between Regional Culture and Regional Incomes
2.4.2 Robustness tests
Table 3 investigates the robustness of our main results along several dimensions for the cultural value Independence in panel (a) and the cultural value Obedience in panel (b)27.
26 These results support the view that Obedience is the opposite of Independence as it roughly affects income to the same extent but in different directions.
27 We outline the set of fixed effects at the top of the table which are employed in panel (a) and (b) to facilitate the overview.
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Table 3: Robustness tests for the effect of Independence (panel a) and Obedience (panel b) on regional per capita income
(1)
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Weak instruments 0.062* 0.0357*
Wu-Hausman
Test 0.003** 0.173
Note: The regressions estimate the effect of culture (Independence, Obedience) on logarithmized regional GDP p.c. for (1-2) a data subsample with respondents per regions >50 including all control variables and country, time, and country-time fixed effects, (3-4) regressions with regional and time fixed effects, (5-6) 2SLS regressions with logarithmized genetic distance to the South East of the United Kingdom (Ln(Genetic distance B*27)) as instrument including all control variables and country, time, and country-time fixed effects, (7-8) a data sample with three 10 year averages (1980-1990; 1991-2000; 2001-2010) and (9-10) a data subsample with quality mappings A, B, C including all control variables and country, time, and country-time fixed effects. Robust clustered standard error estimates (Region-level) are presented below the coefficients. Significance levels are indicated by *p<0.1; **p<0.05; ***p<0.01; Control variables set 1 includes the following covariates: Latitude, Inverse distance to coast, Malaria ecology, Ln(Oil Gas Production), Ln(Pop density), Capital in region, Temperature, Landlockedregion, Length coast, Border to other regions and the number of borders to other countries. Control variables set 2 includes the following covariates: Years education, Trust, Christian, Muslim, Hindu, Buddhist, No religion and other religion (omitted category). Endogeneity tests (Weak instrument and Wu-Hausman) are given for specifications without fixed effects and without clustered standard errors.
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Firstly, we consider a subsample that includes data for those regions where the number of respondents is above 50 in specifications (1) with all fixed effects but without controls and in specification (2) with all fixed effects and all covariates. While any threshold is to some degree arbitrary, we choose a threshold of 50 respondents as this assures a (subjectively and statistically) relevant number of interviewed individuals as well as a sufficiently large sample for our analysis. Indeed, approximately 80% of the original sample contains more than 50 respondents per region. This approach also reduces the potential risk of distortion by outliers and may help improve the representativeness of our samples.
Regarding our results, the cultural value Independence remains a positive and statistically significant predictor for regional GDP per capita, while the cultural value Obedience is negatively associated with regional GDP per capita. Quantitatively, the magnitude of the link between culture and income grows stronger compared to the results in Table 2 which raises our confidence that our results are not an artifact of issues of representativeness. Adding to this issue, we will provide further evidence (see Table 4) that our results are overall robust towards the variation of the 50-respondents-threshold and other quality checks regarding the data. We first set the threshold to regions with at least 100 (approx. 60% of the original sample remain) and then 150 (approx. 45% of the original sample remain) respondents.
Secondly, we specify a ratio of respondents to regional population exceeding 0.01% as a further test.
Moreover, Table 4 also shows that results remain valid for further variations of data matching qualities (employing data with matching quality A and data with matching quality D, E, F separately).
In specifications (3) and (4) of Table 3, we turn to a highly conservative setting by employing region fixed effects and year fixed effects instead of country-time fixed effects. The inclusion of region fixed effects takes out time-invariant across-region variation such that we only exploit changes in regional culture over time. This approach further mitigates the risk of omitted variable bias to a substantial degree. The set of control variables naturally excludes time-invariant regional variables (e.g., distance to coast) when we estimate with region fixed effects. The empirical results reveal again a comparatively robust relationship between regional Independence and regional incomes per capita. An increase in the share of people who value Independence over time by ten percentage points is linked to an increase in regional GDP by 1.3 to 2%.28 Obedience meanwhile loses its statistical significance.
We show results of our second stage instrumental variable estimations in specifications (5) and (6) using genetic distance as an instrument. Our instrument follows Gorodnichenko and Roland (2011, 2017) and measures the genetic distance in terms of the allele frequency HLA-B*27. The cross-country literature has shown allele frequency to be a relevant instrument and also suggested that culture is exogenous to income per capita. We provide a discussion of this instrumental variable strategy in Exhibit 1 in the Supplementary Material. Unfortunately, the instrument is only available for 191 regions
28 However, since aggregate psychological traits are rather slow-moving factors, the model might identify sampling variation instead of actual structural changes in such traits. Given a large number of robustness tests (including 10-year-averages, that potentially take out a lot of the variation) and that we matched economic and cultural data with a time lag of up to ten years, we minimized that risk to a certain extent.
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due to data restrictions. Thus, we observe a substantial reduction in observations below 20% of the original number. While endogeneity tests suggest some explanatory power of the instrument for the variable Obedience, it is at best a weak instrument for Independence (results for the first-stage regression show a significant coefficient in the presence of all covariates). The coefficients of the second stage regressions tend to show that the effects are insignificant when employing the IV strategy for the reduced sample. Thus, although our cultural variables are lagged, we would like to mention the caveat that we cannot fully exclude a potential reverse causality in our previous findings following standard econometric procedures29. Moreover, despite the theoretic evidence for the suitability of genetic distance as an instrument for the influence of culture on income, we can hardly confirm it empirically30.
We note again that it is particularly difficult to find a suitable instrument for culture, especially when analyzing culture at the regional level. Moreover, we point to the large literature which treats culture as exogenous and provides evidence for this assumption.
As EVS/WVS survey data is reported in six time waves only and we face many missing years, we also provide results for three ten-year periods, where we average survey data for these three decades (7-8). The association between culture and regional incomes per capita remains robust and their magnitude changes to a marginal degree.
Finally, we exclude regions with a potentially less reliable data matching quality level i.e., we use a sample of mapping grades A to C only (see Table 8). Even though the number of observations decreases, we can still observe the previously found impact of Independence and Obedience in specification (9), which is still robust with control set I but becomes statistically insignificant at conventional levels once control set II is added (specification 10).
Our analysis involves an intense data effort regarding matching regions at the geographical level.
To systematically investigate the robustness of our main results, we offer a large array of further robustness tests which we describe in Table 4. With small exceptions, the results support the previously found association between regional cultural values and regional incomes per capita especially in the absence of control set II which yields few of our specifications statistically significant at conventional levels.
Table 4 briefly describes the performed tests and gives the respective number of observations (for regressions without control variables as adding controls reduces the sample to some extent). It also
29 The relationship between our cultural variables and incomes per capita remains overall robust when we investigate the subsample of 191 regions but do not employ our instrument. Thus, it is likely that the instrument employed in the cross-country literature cannot be extended to the regional level.
30 The HLA-type B*27 might not be adequate to capture the required genetic information in order to depict a comprehensive picture of genetic differences. Even though endogeneity tests suggest some relevance of our instrument we observe no correlation with our endogenous variables. Potentially, this might be due to the low number of observations, or a biased set of allele data caused by non-randomly selected individuals. In general, it remains demanding to use genetic differences as an instrument for personal traits in the regional population, given the variation in our data.
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provides two regression results (one without and the other with all covariates) for each of our two cultural variables when country-time fixed effects are employed.
We briefly describe the main results here: Firstly, we provide two tests (1-2) in order to account for the regional heterogeneity and weight our cultural variables with regional population and income to ensure that our results are not driven by very small or poor regions (and vice versa). Results confirm our baseline regressions and support the positive influence of Independence and negative influence of Obedience for our total of 1,204 regions. Secondly, we further investigate the issue of representability of our data. Consequently, we complement and confirm our previous robustness checks with data subsamples of regions with quality mapping A and D, E and F as well as for data subsamples that show a relatively high number of respondents compared to regional populations (3-7).
As stated earlier, we find that the sample’s distribution in terms of age groups, gender, and employment is broadly comparable to the actual population reported for around 140 European regions in 2000 and 2010 (see Table 1) for which we can make direct comparisons. Assuming that this holds for all available survey years, we run our baseline regressions for the entire set of European regions available in EVS and Eurostat (8), as well as for three subsets containing regions where the distribution of regional survey characteristics deviates by a maximum of 5% from the distribution in the total population (9-11). Results confirm the positive (negative) link between Independence (Obedience) and regional incomes but are sensitive to the inclusion of control variables which is most likely due to a significant drop in observations.
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Table 4: Summary of robustness tests for the effect of Independence and Obedience on regional per capita income
Test Description Regions Results for Independence Results for Obedience
Number
Confirmed with the exception that Independence turns insignificant as
soon as one adds control set II
Confirmed
Confirmed with the exception that Independence turns insignificant as
soon as one adds control set II
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.366 (0.093)*** 0.112 (0.071) -0.439
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.845 (0.144)*** 0.253 (0.110)* -0.841 (0.135)*** -0.132 (0.102)
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Confirmed with the exception that Independence turns insignificant as
soon as one adds control set II
Confirmed
Confirmed with the exception that Independence turns insignificant as
soon as one adds control set I
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.496 (0.171)*** -0.010 (0.106) -0.466 (0.159)*** -0.098 (0.097) database and that have a comparable gender distribution (i.e. +-5%)
117 (391)
Confirmed with the exception that Independence turns insignificant as
soon as one adds control set I
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set I database and that have a comparable employment ratio (i.e. +-5%)
48 (166)
Not confirmed Confirmed
0.635 (0.443) 0.390 (0.329) -0.745 (0.322)** -0.413 (0.211)*
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database and that have a comparable share of people between 15 and 24 years (i.e. +-5%)97 (314)
Confirmed with the exception that Independence turns insignificant as
soon as one adds control set I
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set I of B*27 allele to South East of United Kingdom) is available
191 (539)
Confirmed with the exception that Independence turns insignificant as
soon as one adds control set II
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.940 (0.343)** 0.066 (0.245) -1.052 (0.321)** -0.192 (0.179)
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.598 (0.103)*** 0.170 (0.062)** -0.484 (0.090)*** -0.099 (0.061)
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.576 (0.130)*** 0.120 (0.072)* -0.510 (0.103)*** -0.066 (0.064) that do not contain the national capital
1,137 (2,829)
Confirmed
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.369 (0.074)*** 0.152 (0.072)* -0.442 (0.073)*** -0.104 (0.064)
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Confirmed with the exception that Independence turns insignificant as
soon as one adds control set II
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.520 (0.177)** 0.008 (0.180) -0.698 (0.228)** -0.276 (0.180)
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.499 (0.100)*** 0.159 (0.087)* -0.559 (0.084)*** -0.073 (0.060)
(18) Results for the year 2010
Baseline regressions for
the year 2010 817 (817)
Partly confirmed; even though results stay robust with control set I only,
one yields a negative (non-significant) impact of Independence
on regional GDP
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II 0.521 (0.144)*** -0.136 (0.175) -0.924 (0.178)*** -0.110 (0.202) insignificant as soon as control set I is
added and one yields a positive (non-significant) impact of Obedience on regional GDP in specification (2) 0.655 (0.156)*** 0.294 (0.125)* -0.421 (0.149)** 0.026 (0.115)
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(20)Matched regions with a reduced timelag
Baseline regressions for a subsample of
Gennaioli et al. (2014) regions that were
matched with WVS/EVS regions with a maximum timelag of 2 years (instead of 10 years in all other regressions)
934 (2,048)
Confirmed with the exception that Independence turns insignificant as
soon as one adds control set II
Confirmed with the exception that Obedience turns insignificant as soon
as one adds control set II
0.414 (0.098)*** 0.082 (0.073) -0.565 (0.089)*** -0.106 (0.074)
Note: The regressions estimate the effect of culture (Independence, Obedience) on logarithmized regional GDP p.c. for a number of robustness checks including country, time, and country-time fixed effects and robust clustered standard error estimates (Region-level); Coefficients (Std. Errors) for specifications without controls are reported in columns (1), whereas coefficients (Std. errors) for specifications with all control variables (Set I and II) are reported in columns (2); Control variable set I includes the following covariates: Latitude, Inverse distance to coast, Malaria ecology, Ln(Oil Gas Production), Ln(Pop density), Capital in region, Temperature, Landlockedregion, Length coast, Border to other regions and the number of borders to other countries; Control variable set II includes the following covariates: Years education, Trust, Christian, Muslim, Hindu, Buddhist, No religion and other religion (omitted category).
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In specification (12) we provide evidence that regions where the instrument for genetic distance is available, confirm the previously stated association between culture and income. We are looking at various data subsamples that represent regional specifics and that might reveal a potentially interesting variation of cultural values: OECD countries; regions with a share of Christians exceeding 50%; regions not containing the national capital; Asian regions and European regions (13-17). We also account for the bias of very different time periods (previously we were looking at a time span from 1980 to 2010) and consider results for the year 2010 and 2000 separately (18-19). In addition, when matching our two datasets, we reduce our originally permitted time lag of ten years to two years only which yields us with even more accurate results although for a significantly smaller dataset (20). All these tests provide further evidence regarding the existence of a non-negligible positive link between the cultural value Independence and regional incomes per capita while the link between the cultural value Obedience and regional incomes per capita is negative.