However, our estimates for ‘pronoun drop’ are unlikely to have such a problem. Endogeneity bias has three main dimensions: reverse causality bias, omitted variable bias and measurement error. As explained above, our variable of interest is most unlikely to be subject to the first. As we control for all major factors that have been found to determine education in large samples of countries, it is also unlikely to suffer from the second. And the third dimension should not be an issue either, given the high‐quality data and methodology we use to measure ‘pronoun drop’.

By contrast, most of our control variables are probably endogenous. For several reasons, we do not instrument for them either. First, instrumenting for several variables at once leads to complicated problems of identification. Second, for many of our potentially endogenous controls, there are no plausible instruments. Third, several variables that have been used as instruments in previous papers, such as geographic variables, are likely to directly affect education. Fourth, many of these potential instruments are not specific enough to the variables we would like to instrument for. Excluded instruments need to be specific to the instrumented variable (Acemoglu 2005 ). Finally, most of the potential instruments, such as geographic variables or legal origins, have been used in previous studies as instruments for various other variables. A variable can be a valid instrument in at most one such study (Bazzi and Clemens 2013 ). As, for these reasons, we do not instrument for any of our controls, our estimates of most of these variables are subject to endogeneity bias.

We do not instrument for ‘pronoun drop’ because this variable, as the variable ‘pronoun drop language’ in our individual‐level analysis, is most likely to be exogenous. Linguistic structures such as rules governing the use of personal pronouns have been formed in the distant past and evolve very slowly, over generations.

As our variable of interest, ‘pronoun drop’, is time‐invariant, we use cross‐country rather than panel data. 6 The data for the time‐variant variables has been averaged over the period 1972‐2012. As with our individual‐level analysis, the size of our sample is determined by data availability only, both with respect to countries and with respect to the time period. Using data from large samples should lead to general results.

In our country‐level analysis, our sample consists of 101 countries ( Table A4 in the online Supporting Information file). In 64 of them, the most widely spoken languages permit pronoun drop. For three reasons, we analyze country‐level in addition to individual‐level data. First, it enables us to control for contemporary culture as well as for numerous other national characteristics. Second, it also enables us to estimate the effect on national rates of schooling. Such rates are important for economic and social development. Third, related research suggests that countries are meaningful units of analysis. For example, Schwartz ( 2004 ) demonstrates that cultural values are much more similar within than between countries, differences between ethnic groups and regions within countries notwithstanding. Similarly, Inglehart and Baker ( 2000 ) report that the historically dominant religion of a country shapes all inhabitants – including those adhering to a different religion, or no religion at all – into a given national culture. Perhaps a country's dominant languages also shape all (or most) of its inhabitants’ values and norms – even if some have a different mother tongue.

In some additional regressions, we alternatively include a survey‐based measure of contemporary long‐term orientation. This is relevant here because, as indicated above, the rewards of most forms of human capital investment materialize in the long term. For example, the return to schooling accrues throughout working life. The variable ‘long‐term orientation’ measures the extent to which society fosters pragmatic virtues oriented towards future rewards.

As explained previously, pronoun drop rules may reflect ancient values and norms of collectivism. As cultural values and norms usually change slowly, including corresponding measures of contemporary culture in our regressions could attenuate or nullify any direct effect of ‘pronoun drop’. To shed light on this issue, we include in some additional regressions, one at a time, survey‐based indicators of relevant aspects of contemporary culture. We start with ‘embeddedness’, ‘autonomy’ and ‘individualism’. While ‘embeddedness’ measures the extent to which a culture views people as entities embedded in the collectivity, ‘autonomy’ measures the extent to which it encourages individuals to independently pursue their ideas and experiences. ‘Individualism’ measures the extent to which people are supposed to look after themselves and their immediate family only, as opposed to being strongly integrated and loyal to a cohesive group such as the extended family (collectivism). Higher values of this measure indicate a higher level of individualism, whereas lower values indicate a higher level of collectivism.

We use a large number of variables to control for the impact of other potential determinants of education. 5 The control variables we employ have been selected on the basis of the relevant theoretical and empirical literature. For brevity, instead of surveying this literature in detail let us just list the variables and cite some of the papers that have found the respective variable to be potentially important. To start with, we control for public spending on education (e.g., Trostel 2002 ). Moreover, we control for political rights and civil liberties (e.g., Lake and Baum 2001 ). We employ several demographic variables: life expectancy (e.g., Soares 2005 ), urbanization rate (e.g., Bertinelli and Zou 2008 ) and, in some robustness checks, population growth rate (e.g., Becker and Lewis, 1973 ), death rate (e.g., Forston 2011 ) and the shares of children and elderly in the population (e.g., Poterba 1997 ). Throughout, we control for major religions (e.g., Feldmann 2016a ). We also control for relevant economic characteristics. Specifically, we use GDP per capita (e.g., Mincer 1996 ), GDP growth rate as a proxy for business cycle fluctuations (e.g., Méndez and Sepúlveda 2012 ), private credit as a proxy for credit constraints (e.g., De Gregorio 1996 ), openness (e.g., Baskaran and Hessami 2012 ) and, in one robustness check, economic freedom (e.g., Feldmann 2017 ). Furthermore, we control for geographic conditions (e.g., Gallup et al. 1999 ) and, in one robustness check, regional characteristics. As educational investments are future‐oriented, we control for languages with strong future‐time reference in a further robustness check (e.g., Chen 2013 ). While in one robustness check we add controls for linguistic, ethnic and religious fractionalization (e.g., Alesina et al. 2003 ), in another one we additionally control for colonial history (e.g., Feldmann 2016b ).

As in our individual‐level analysis, we estimate regressions separately for females and males. As explained in section II , countries dominated by pronoun drop languages are likely to restrict the schooling of girls in particular. Our separate regressions are intended to test this part of our hypothesis.

Our educational investment variables refer to secondary schooling. Specifically, we use secondary enrollment rates, which are defined as children enrolled in secondary education, regardless of age, as a percentage of children in the age group that officially corresponds to this level of education. We do not use tertiary enrollment rates because in almost all developing countries these rates have been very low over our sample period. Also, data availability for tertiary enrollment rates is much more limited.

Here, our variable of interest is ‘pronoun drop’, measuring the decimal fraction of a country's population speaking a language that permits to drop a personal pronoun when it is used as the subject of a sentence (for definitions, descriptive statistics and sources of all country‐level variables, see Table A3 in the online Supporting Information file). For this variable, our data is mainly from Davis and Abdurazokzoda's ( 2016 ) recently constructed linguistic dataset, which overcomes weaknesses of Kashima and Kashima's ( 1998 ) original data (for a discussion of these weaknesses, see Davis and Abdurazokzoda 2016 ). Using the same sources and methodology as Davis and Abdurazokzoda ( 2016 ), we coded the ‘pronoun drop’ variable for several more countries. The country‐level measure of pronoun drop has been constructed by taking into account, for each country, up to three popularly spoken languages.

IV.2 Results and discussion

Tables 2-5 present the regression results using country‐level data. While Table 2 reports the results from our baseline specification, Tables 3 and 4 report the results from our robustness checks – Table 3 for girls and Table 4 for boys. Table 5 presents the results from regressions in which we add contemporary culture variables – columns 1‐5 for girls and columns 6‐10 for boys. For brevity, the estimates for the main control variables are omitted in Tables 3-5. Each of the regressions in these tables additionally uses the same controls as the baseline regressions of Table 2. Note that our country‐level regressions explain about 80% of the variability in the data. Thus, the overall fit of the equations is very good.

Table 2. Country‐level main estimates (1) (2) Female secondary enrollment rate Male secondary enrollment rate Pronoun drop ‐11.50*** (3.35) ‐10.53*** (3.03) Public spending on education ‐40.02 (68.78) ‐35.03 (65.87) Political rights & civil liberties 5.49 (9.97) ‐0.82 (9.57) Life expectancy 1.78*** (0.37) 1.51*** (0.36) Urbanization rate 20.39** (8.94) 8.29 (8.72) Christian population share ‐9.82 (9.59) ‐8.91 (8.99) Muslim population share ‐18.44*** (6.81) ‐10.63 (6.95) Eastern religions population share ‐9.59 (10.32) ‐1.98 (10.45) GDP per capita ‐3.05 (3.77) 1.47 (3.59) GDP growth rate ‐3.93*** (1.24) ‐3.63*** (1.09) Private credit 0.81 (6.12) ‐2.19 (5.31) Openness 12.80** (5.98) 7.56 (5.80) Tropical area ‐11.59** (4.80) ‐14.78*** (4.62) Navigable waters ‐4.63 (6.71) ‐4.30 (6.19) Number of observations 101 101 R2 0.82 0.79 F statistic 61.04*** 36.46*** Root mean squared error 12.83 12.60

Table 3. Country‐level robustness checks females (1) (2) (3) (4) (5) (6) (7) (8) Strong future‐time reference added Fractionalization variables added Colonial variables added Population growth rate added Child and elderly population shares added Death rate added Economic freedom added Regional dummies added Pronoun drop ‐12.58*** (3.62) ‐8.03** (3.47) ‐7.61** (3.60) ‐10.33*** (3.61) ‐9.99*** (3.46) ‐11.49*** (3.40) ‐9.14*** (2.83) ‐9.71*** (3.34) Strong future‐time reference 4.21 (3.87) Linguistic fractionalization ‐2.02 (11.84) Ethnic fractionalization ‐10.97 (13.42) Religious fractionalization 13.26 (8.95) Former British colony 0.80 (4.12) Former Spanish colony ‐14.45* (7.94) Former French colony ‐12.60*** (3.91) Population growth rate ‐3.07 (2.41) Child population share ‐1.34** (0.59) Elderly population share ‐1.59* (0.94) Death rate 1.87 (8.41) Economic freedom 58.87* (30.40) America ‐25.58 (18.98) Africa & the Middle East ‐18.81 (19.64) Europe ‐21.71 (19.15) Asia ‐15.32 (20.45) Main control variables Yes Yes Yes Yes Yes Yes Yes Yes Number of observations 93 96 101 101 99 101 86 101 R2 0.80 0.84 0.84 0.82 0.84 0.82 0.84 0.84 F statistic 38.27*** 53.81*** 62.82*** 60.46*** 57.01*** 57.30*** 43.74*** 46.71*** Root mean squared error 12.56 12.45 12.14 12.78 12.45 12.90 12.31 12.52

Table 4. Country‐level robustness checks males (1) (2) (3) (4) (5) (6) (7) (8) Strong future‐time reference added Fractionalization variables added Colonial variables added Population growth rate added Child and elderly population shares added Death rate added Economic freedom added Regional dummies added Pronoun drop ‐11.23*** (3.50) ‐7.43** (3.17) ‐7.03** (3.19) ‐9.40*** (3.20) ‐9.34*** (3.18) ‐10.52*** (3.07) ‐8.38*** (2.54) ‐8.90*** (2.93) Strong future‐time reference 3.32 (3.78) Linguistic fractionalization 0.46 (11.02) Ethnic fractionalization ‐11.76 (13.15) Religious fractionalization 14.70 (9.33) Former British colony 0.25 (3.93) Former Spanish colony ‐13.38* (7.66) Former French colony ‐13.30*** (3.54) Population growth rate ‐2.98 (2.16) Child population share ‐1.41** (0.57) Elderly population share ‐1.56* (0.85) Death rate 2.03 (6.95) Economic freedom 55.06* (29.83) America ‐28.34 (20.00) Africa & the Middle East ‐21.28 (20.45) Europe ‐22.73 (20.07) Asia ‐18.85 (21.16) Main control variables Yes Yes Yes Yes Yes Yes Yes Yes Number of observations 93 96 101 101 99 101 86 101 R2 0.76 0.81 0.82 0.79 0.81 0.79 0.81 0.81 F statistic 23.59*** 30.21*** 49.74*** 33.70*** 32.87*** 33.42*** 28.61*** 27.76*** Root mean squared error 12.59 12.36 11.96 12.55 12.18 12.67 12.03 12.17

Table 5. Culture variables added in country‐level regressions (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Female secondary enrollment rate Male secondary enrollment rate Embeddedness added Autonomy added Individualism added Long‐term orientation added Long‐term orientation and interaction added Embeddedness added Autonomy added Individualism added Long‐term orientation added Long‐term orientation and interaction added Pronoun drop ‐11.26*** (3.36) ‐11.11*** (3.68) ‐11.75** (4.96) ‐11.78*** (3.97) ‐31.85** (12.76) ‐9.78*** (2.92) ‐10.16*** (3.40) ‐9.09* (4.52) ‐10.97*** (3.25) ‐30.09*** (9.80) Embeddedness 11.35 (12.30) 9.78 (12.82) Autonomy ‐1.96 (10.07) ‐6.19 (10.01) Individualism 20.69 (19.21) 26.37 (19.81) Long‐term orientation ‐4.40 (9.64) ‐25.98* (15.14) 0.42 (9.39) ‐20.14 (12.47) Pronoun drop x 41.80* 39.82** Long‐term orientation (20.94) (17.37) Main control variables Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Number of observations 62 62 61 73 73 62 62 61 73 73 R2 0.87 0.87 0.83 0.82 0.84 0.83 0.83 0.80 0.79 0.82 F statistic 47.52*** 45.06*** 26.47*** 35.09*** 41.07*** 25.81*** 25.49*** 16.87*** 21.88*** 23.88*** Root mean squared error 11.43 11.60 12.29 13.35 12.71 11.66 11.73 12.18 12.91 12.31

The estimates for our variable of interest, ‘pronoun drop’, are consistent with our individual‐level estimates. In all country‐level regressions, the coefficient on ‘pronoun drop’ is statistically significant, mostly at the 1% level. Its algebraic sign is negative, suggesting that during the sample period, pronoun drop languages had a detrimental impact on secondary school enrollment. Also in line with our individual‐level estimates, we find the magnitude of the effect to be substantial, particularly among girls. Specifically, countries in which the popularly spoken languages permit personal pronoun drop had a secondary enrollment rate that was approximately 10‐11 percentage points lower among girls and about 9‐10 percentage points lower among boys, compared with countries in which the popularly spoken languages require the use of personal pronouns (Tables 2-5). Thus, the estimates corroborate our hypothesis, including that the magnitude of the negative effect is likely to be larger among girls (section II). However, as in the case of our individual‐level regressions the difference in the estimated effects between girls and boys is small.

As indicated above, we also explore the effect of pronoun drop languages in the context of contemporary culture. With respect to the latter, we focus on those measures that are most likely to be relevant here: ‘embeddedness’, ‘autonomy’, ‘individualism’ and ‘long‐term orientation’. 3 In a first exercise, we add these variables to our baseline specification, one at a time. As reported in Table 5, columns 1‐4 and 6‐9, each of them is statistically insignificant. By contrast, ‘pronoun drop’ remains statistically significant, in most cases at the 1% level. However, when adding ‘individualism’ the significance of ‘pronoun drop’ falls to 5% in the female regression and to just 10% in the male regression. Also, in the latter regression the absolute size of the coefficient on ‘pronoun drop’ falls substantially. In this context, it is also noteworthy that the absolute size of the correlation coefficient between ‘pronoun drop’, on the one hand, and measures of contemporary culture, on the other, is the highest for ‘individualism’ (Table A5 in the online Supporting Information file).

In a second exercise with the contemporary culture variables, we additionally interact them with ‘pronoun drop’. The intention here is to check whether the magnitude of the negative effect of the latter varies with the degree of one or more of the four dimensions of contemporary culture. With respect to ‘embeddedness’, ‘autonomy’ and ‘individualism’, we find no such interaction effect (results not reported here). However, we find that the negative effect of ‘pronoun drop’ is weaker in countries with more long‐term orientation (columns 5 and 10 of Table 5). In the case of girls, this interaction effect is only marginally significant though.

To explore the possibility that ‘pronoun drop’ may mask any effect of contemporary culture, we exclude the former from regressions 1‐4 and 6‐9 of Table 5 in a third exercise, finding that each of the contemporary measures remains statistically insignificant. Since these regressions obviously suffer from omitted variable bias, we do not report them here.

In a fourth exercise, we explore whether pronoun drop languages affect secondary schooling through contemporary culture. Specifically, we now use ‘pronoun drop’ as an instrument for each of the four contemporary measures, one at a time. This exercise closely resembles several recent papers that use Kashima and Kashima's (1998) pronoun drop data to instrument for a variety of dimensions of contemporary culture: ‘embeddedness’ and ‘autonomy’ (Licht et al. 2007), ‘trust and respect’ (Tabellini 2008), ‘individualism’ (Klasing 2013, Gorodnichenko and Roland 2017) and ‘power distance’ (Klasing 2013). Unfortunately, apart from the downside that these papers use Kashima and Kashima's (1998) problematic data (Davis and Abdurazokzoda 2016), they have several econometric issues. First, pronoun drop can be a valid instrument for at most one of these measures (Bazzi and Clemens 2013). Second, in several of these papers the first‐stage F statistic is below ten, indicating that pronoun drop is a weak instrument (Staiger and Stock 1997). Third, except for Gorodnichenko and Roland (2017), none of the papers provides statistical evidence that pronoun drop is exogenous.

In line with most of these papers, we also find ‘pronoun drop’ to be a weak instrument, for all four contemporary culture variables used here. This is evident not just from the first‐stage F statistic but also from Shea's (1997) partial R2 and Kleibergen and Paap's (2006) rk LM statistic. As an example, Table A6 (in the online Supporting Information file) reports the results from IV regressions in which we use ‘pronoun drop’ as an instrument for ‘individualism’, the measure which is most likely to be relevant here. Furthermore, as in Table 5, ‘individualism’ is statistically insignificant in the IV regressions too – as are the other three contemporary variables in their IV regressions (the latter results are not reported here).

What is the upshot of all of these exercises involving contemporary culture variables? Most importantly, we find no evidence that any of them affect secondary schooling. Nor do we find evidence that ‘pronoun drop’ affects schooling indirectly, through contemporary culture. Rather, the results from these exercises reinforce our previous result that ‘pronoun drop’ appears to have a direct effect. The effect may be slightly smaller in countries with more long‐term orientation. More intriguingly, the fact that the effect of ‘pronoun drop’ is smaller and less statistically significant when adding ‘individualism’ lends tentative support to our conjecture that pronoun drop languages may be an indicator of, and may perpetuate, ancient collectivism. Specifically, pronoun drop languages may pass on to their speakers the ancestral cultural norm that the individual has to subordinate to the collective and, more specifically, that education should be limited in order to avoid that young individuals reduce their commitment to the extended family and the state. As a result of such beliefs, which appear to be maintained by a language structure that accentuates the social embeddedness of the individual, educational investments in young people may remain limited. They may remain especially limited in girls because, as explained in section II, females’ contributions to maintaining the extended family are particularly important in collectivist societies.

How can an indicator of ancient collectivism affect contemporary school enrollment rates while related indicators of contemporary culture do not? Apart from the fact that both types of indicators have measurement issues 4 , there may be a fundamental reason for the answer to be in the affirmative. As explained previously, we think that rules allowing pronoun drop reflect and perpetuate deep‐routed cultural values of collectivism that put comparatively little emphasis on the educational advancement of the young, especially girls. By contrast, contemporary values have become much more individualistic in recent decades, including in many traditionally collectivist societies. These more individualistic values foster and call for the education of the young. In all societies, traditional and modern values co‐exist alongside each other. For example, in a seminal paper that uses World Values Survey data from the 1980s and 1990s on 65 societies and 75% of the world population, Inglehart and Baker (2000) provide evidence of both massive cultural change and the persistence of traditional values. They find economic development to be associated with shifts towards values that are increasingly rational, tolerant, trusting and participatory – values that support and call for education. But they also find that the cultural heritage of a society leaves an imprint on values that endures despite modernization. Thus, Inglehart and Baker's (2000) findings support our interpretation of our results.

Finally, a brief comment on the estimates for the controls (Tables 2-4). Many of them accord with the previous literature. For example, we find longer life expectancy to have a positive effect and larger shares of both children and elderly to have negative effects on schooling. Additionally, girls’ education is negatively affected by Islam and positively by both urbanization and openness. Also in line with the previous literature, we find that economic freedom has a positive effect on boys as well as girls and that the legacies of both Spanish and French colonial education still adversely affected schooling in the respective former colonies in recent decades. Furthermore, we find evidence that schooling is countercyclical and that tropical climates affect schooling negatively. Both of these results are in line with the previous literature too. In contrast to Chen (2013) and Galor et al. (2017) though, we find no effect of future‐time rules.

Previously, we have indicated that pronoun drop languages may affect schooling through public spending on education. However, in some unreported regressions we find no evidence for such an indirect effect, nor for a corresponding interaction effect. Therefore, we stick to the commonly used specification of including ‘public spending on education’ as a regular control variable. The fact that it turns out to be insignificant in this specification, too, is little surprising. Several other papers do not find a statistically significant effect of public education spending on secondary school enrollment either (e.g., Flug et al. 1998, Papagapitos and Riley 2009).

In some more supplementary regressions, we interact ‘pronoun drop’ with ‘political rights & civil liberties’ and, alternatively, with ‘economic freedom’. The intention here is to check whether the negative effect of pronoun drop is smaller in countries with more political or economic freedom. However, we find the respective interaction terms to be statistically insignificant (results not reported here).

Lastly, it should be noted that the large number of control variables we use ensures that ‘pronoun drop’ does not proxy for factors such as GDP per capita, public education spending, political or economic freedom, religion, or demographic or geographic conditions. As we have seen, it does not proxy for contemporary culture either.