Abstract
Purpose
This study aims to examine the effects of the historical prevalence of infectious diseases on contemporary gender equality. Previous studies reveal the persistence of the effects of historical diseases on innovation, through the channel of culture.
Design/methodology/approach
Drawing on the parasite stress theory, the authors propose a framework which argues that historical prevalence of infectious disease reduces contemporary gender equality. The study uses ordinary least squares and two-stage least squares in a cross-section with data from 122 countries between 2000 and 2021.
Findings
This study provide support for the underlying hypothesis. Past diseases reduce gender equality both directly and indirectly. The strongest indirect effects occur through innovation output. Gender equality analysis may take these findings into account and incorporate disease pathogens into the design of international social policy.
Originality/value
This study complements the extant literature by assessing the nexus between historical prevalence of infectious diseases and gender equality.
Keywords
Citation
Ombolo Messono, O., Asongu, S. and Tchamyou, V. (2023), "Historical prevalence of infectious diseases and gender equality in 122 countries", International Journal of Human Rights in Healthcare, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJHRH-12-2022-0137
Publisher
:Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited
1. Introduction
In recent decades, gender inequality has received particular attention from the research community. Although differences within societies in gender equality have been well documented, there is little discussion of the ecological causes of this problem. To the best of our knowledge, the study of Varnum and Grossmann (2017) is the only research which demonstrates that the reduction in gender inequality between 1951 and 2013 in the USA is a consequence of decreases in pathogen prevalence. Despite this clarification, no study to the best of our knowledge has addressed the persistence of historical infectious disease prevalence on gender inequality in a large sample by engaging the transmission channel.
In this paper, we contribute to the literature by establishing a reduced-form association between historical infectious disease prevalence and gender equality across countries. Our argument posits that populations faced with a permanent historical prevalence of diseases have developed a collectivist culture that is less open to criticism, entrepreneurship, new ideas and challenges to the status quo. This failure has retarded innovation and fostered gender inequalities.
Our measure of “historical prevalence of infectious diseases” is chosen under the inspiration of the vast cross-cultural literature developed by many authors such as Bennett and Nikolaev (2021), Bennett (2019), Bennett (2018), Nikolaev et al. (2017) and Fincher et al. (2013). The index used in this study is borrowed from Murray and Schaller (2010). This index assesses the intensity of historical disease prevalence for over 150 countries. The calculation of this index is based on the severity of nine diseases that are dangerous to human survival and reproductive health, not least, because the diseases substantially account for poor health and high death rate; these include dengue, trypanosomes, schistosomes, leprosy, typhus, malaria, filariae, leishmanias and tuberculosis. It also provides evidence for the parasitic stress theory of disease developed by Thornhill and Fincher (2014a, 2014b). The creation of the index was possible thanks to epidemiological information from the early 20th century and the archives of historical epidemiological atlases of infectious diseases. The combination of these two data sources allowed the authors to obtain a concrete measure of historical disease prevalence.
The measure of gender equality is the average value of the Sustainable Development Goal 5 (SDG5) indicator proposed by Sachs et al. (2021) between 2000 and 2021. This indicator is a combination of the following information: the demand for family planning met by modern methods, the ratio of women’s average years of education to men’s, the labor force participation rate of women compared with men and the number of seats held by women in the national parliament.
Analysis of the effect of historical prevalence of infectious diseases on gender equality yields results that support a strong negative relationship between the two variables. We establish the robustness of this result in several ways. Potential omitted variable bias is accounted for by controlling for some contemporaneous and historical confounders. Correcting for endogeneity bias does not alter our results. In addition, we use alternative measures of gender equality and control for a range of contemporaneous influences, geographic controls and continent fixed effects. The results survive these consistency checks. Given the influential findings of Bennett and Nikolaev (2021) that the path of innovation inequality is shaped by disease burden, we test whether the effect of innovation on gender equality operates through past illnesses. Analysis of this mechanism suggests that innovation is the primary mediator of the relationship between diseases of the past and gender equality. The high prevalence of epidemics reduces entrepreneurship, diversity, collaboration, research and development. It also reduces the extent to which companies and universities collaborate in research and development. In sum, an epidemic setting reduces the ability of individuals to innovate and delays the possibility of gender adjustment. While Varnum and Grossmann (2017) focus on the ecological explanation of gender inequality through the human capital component, our focus is on differences in innovation.
We explore how diseases of the past shape gender inequalities by considering several alternative mechanisms of innovation. In this article, we provide results on how an epidemiological framework affects gender equality. Innovation outcomes, entrepreneurship, capacity to innovate and business–academic collaboration in development are elements to be considered in the epidemiological analysis of gender equality. Consideration of these channels is necessary because the relationship between the incidence of historical prevalence of infectious diseases and gender is potentially subject to omitted variable bias and even measurement error. Our results, however, do not provide strong evidence that past diseases capture the variation attributable to these factors. We recognize that innovation intensity is not necessarily the only or most important determinant of gender equality. Nonetheless, we believe the results improve our understanding of the underlying causes of comparative gender differences.
We do not claim that the level of development, agriculture, political regime and diffusion of innovations and technologies do not play an important role in promoting gender equality. On the contrary, our hypothesis identifies these factors as important elements for the development of men and women. It proposes that innovation has effects or consequences of a previously unrecognized causal framework, and that it becomes important to identify it by highlighting the role of diseases of the past suffered by society.
The positioning of the study departs from the extant literature on gender equality which has largely focused on inter alia, the relevance of information and communication technology in promoting gender inclusion (Awel and Yitbarek, 2022), the linkage between gender inclusion and tax performance (Asongu et al., 2021), financial drivers of gender entrepreneurship (Ngono, 2021) and connections between mobile money, financial inclusion and gender gaps (Asongu and Odhiambo, 2018; Osabuohien and Karakara, 2018; Mndolwa and Alhassan, 2020; Kim, 2022).
This paper proceeds as follows. Section 2 presents the conceptual framework, which is discussed in more detail. Section 3 describes the empirical approach, the data and their sources. Section 4 presents the baseline estimates and several robustness checks. Section 5 provides alternative mechanisms linking the historical prevalence of past illnesses to gender equality and Section 6 concludes.
2. Disease pathogen and gender equality: theoretical background
The importance of historical prevalence of infectious disease, and gender equality has garnered considerable attention on the parasite stress theory of economic development (Fincher et al., 2013; Murray et al., 2011, 2013; Murray and Schaller, 2010; Schaller and Murray, 2008; Thornhill and Fincher, 2014a, 2014b; Thornhill et al., 2009; Thornhill and Fincher, 2011, 2014a, 2014b; Bennett and Nikolaev, 2021). In this theory, the link between these two variables can be drawn from many channels such as culture, innovation and political regime.
As far as the cultural channel is concerned, the intercommunity disparity of the parasitic stress allows for distinction between individualistic and collectivist societies. In collectivist societies, the border between the group of belonging and the group of nonmembership is important. One is suspicious of the members of the latter and refuses to come into contact with them. On the other hand, in individualistic societies, these constraints are not observed and the probability of contact between communities is very high (Gelfand et al., 2004; Sagiv and Schwartz, 1995; Oishi and Uhich Schimmack, 1954). As summarized by Thornhill and Fincher (2014a, 2014b), collectivist (conservative) societies favor in-group alliances while individualist (liberal) societies favor interaction with groups from other classes in society.
According to the work of Thornhill and Fincher (2014a, 2014b), individualistic societies where everyone is expected to take care of themselves and their immediate family are associated to an environment with low prevalence of infectious diseases. These societies have the distinction of valuing class equality, personal achievement, opportunity, progress, knowledge and individual freedoms. Collectivist societies, on the other hand, are formed in places where the rate of disease contamination is high. These societies integrate people from birth into strong, cohesive groups, which must ensure their safety throughout their lives in exchange for loyalty (Hofstede, 2011, p. 51). As a result, the greater value placed on harmony, cooperation and a relationship with superiors in these societies often promotes the devaluation of the lower classes and the promotion of gender inequality. It is therefore argued that the higher (lower) the incidence of infectious diseases in a community, the more that society will tend toward a collectivist (individualist) ideology that will be favorable to gender equality (gender inequality). Figure 1 above shows a negative correlation between historical prevalence of infectious disease and individualist culture.
The parasitic stress of diseases also persists on gender equality through the autocracy versus democracy divide. Indeed, according to Thornhill et al. (2009), democratization which is primarily related to individualism, significantly involves the liberalization of values under ecological conditions of low disease stress. This makes the distribution of suffrage and political participation of women, as well as their rights and freedom in general, in such a community largely favored as demonstrated, for example, by the work of Wejnert (2005).
In this environment, the relationship between women and men evolves in the direction of equity. This theoretical consideration has been supported by the empirical results of Inglehart and Norris (2003). On the other hand, the high incidence of infectious diseases encourages collectivism, which is sometimes an obstacle to gender equality. Gelfand et al. (2004) state that collectivism is negatively correlated with gender equality values. From the above, we can conclude that democracy, which is associated with the pursuit of gender equality values, is the consequence of an individualistic culture, which itself has its origins in an epidemic environment. In Figure 2, historical prevalence on infectious disease is negatively correlated with women political empowerment.
On the other hand, the autocratic ideology characterized by conservatism and gender differentiation and male superiority derives from collectivism which in reality is the consequence of an environment with high parasitic stress. Schaller and Murray (2008) following this logic show that parasitic stress positively affects cultural norms of sexual restraint, especially with regard to women. Thus, the difference in infectious disease risk observed worldwide, historically and currently, may favor democracy or autocracy which in turn determines gender equality.
Concerning the innovation channel, many studies show that innovation is positively associated with gender equality (Keisu, 2013; Saâd and Assoumou-Ella, 2019; Wrigley, 1992). Bennett and Nikolaev (2021), for example, find that, a disease environment (dengue, trypanosomes, schistosomes, leprosy, typhus, malaria, filariae, leishmanias and tuberculosis) had influential effects on the path of a culture in innovation development. The variation in associated morality rates caused society to either build an individualist or collectivist culture. According to some studies, the individualistic culture is more innovative than the collectivistic culture. Rogers (1995) demonstrates that the creation of innovation depends on people who are open to new ideas, bold and willing to put into perspective what is already established. This encourages independent thinking and self-expression which in turn promotes the adoption and creation of innovation (Alesina and Giuliano, 2010). The same scenario is not observable in collectivist societies. Innovation index in this study is measured by the indicator developed by WIPO (2021). The latter provides a more complete picture of innovation ecosystems around the world. It compiles, through weighting methods, the elements of the economy that enable and facilitate innovative activities (innovation inputs) and the outcome of innovative activities in the economy (innovation output). Its relation with historical prevalence of infectious disease in our sample is negative in Figure 3 below.
3. Methodology and data
The materials, analysis code and corresponding data are available in the following repository.https://osf.io/rxbdy/files/osfstorage
3.1 Methodology
We hypothesize that historical prevalence of infectious disease and gender equality are negatively related in a reduced-form link. To investigate the reduced-form link, the following linear specification is used:
where Gender equalityi is an indicator of the sexes ratio between men and women in country i; pathogensi the historical prevalence of infectious disease in country i; Xi is a vector of control variables and εi is an unobserved error term. β is the coefficient of interest and is expected to carry a negative sign.
3.2 Data
In this section, we discuss the key variables used. Appendix 1 provides a list of all variables used, the summary statistics and corresponding sources. Figure 4 shows a positive relationship between global innovation and gender equality for the sample countries. Their correlation coefficient is 0.79. Figures 5 and 6 give the geographical distribution of historical prevalence of infectious disease and gender equality across countries with a negative correlation. This suggests that the effect of historical prevalence of infectious disease on gender equality may potentially work through global innovation, an issue that we will explore further in Section 5.1 and 5.2.
As stated above, the measure of gender equality is the average value of the indicator of the fifth SDG proposed by Sachs et al. (2021) between 2000 and 2021. This indicator is a combination of the following information: the demand for family planning met by modern methods, the ratio of women’s average years of education to men’s average years of education, the labor force participation rate of women compared with men and the number of seats held by women in the national parliament.
The data of this variable varies between 0 and 100, where a larger value signifies greater gender equality. Figure 5 depicts how the estimates of gender equality are distributed across the world.
Historical prevalence of infectious disease is obtained from Murray and Schaller (2010). This index includes dengue, trypanosomes, schistosomes, leprosy, typhus, malaria, filariae, leishmanias and tuberculosis for 150 countries. Figure 6 above shows the distribution of this variable across the world. In this figure, African, South American and Asian countries present high scores of historical prevalence of infectious disease. It is important to emphasize that the selection of 122 countries which are apparent in Appendix 2 is motivated by data availability constraints, especially as it pertains to the gender equality and historical prevalence of infectious disease variables.
4. Results and discussion
4.1 Main results
Our hypothesis is that historical prevalence of disease pathogen, via its effect on innovation, reduces gender equality. The ordinary least squares (OLS) estimates in Table 1 support this hypothesis. The bivariate analysis in Column (1) shows that the coefficient of historical prevalence of disease pathogen is statistically significant at the 1% level and historical prevalence of disease pathogen alone can explain more than 30% of the total variation in gender equality. The historical prevalence of disease pathogen coefficients is precisely estimated, even after controlling for culture controls and continent dummy in Column (2), legal origin in Column (3), religion in Column (4) and political characteristics in Column (5). When all control variables are included in Column (6), the effect of disease pathogen remains robust.
Based on the estimates in Column (6), Canada experienced a lower prevalence of infectious disease similar to Switzerland (−1.08), the UK (−1.01), Belgium (−1), consistent with the data of Murray and Schaller (2010). The estimated gender equality score of these countries is high with, respectively, 84.89, 82.98 and 85.72 in the data collected by Sachs et al. (2021). This result is also observed in countries with a high level of infectious disease like Guinea (1.06), Burkina Faso (1.16) and Nigeria (1.16). The attendant countries present a poor performance in gender equality with 39.05, 37.55 and 38.21 scores, respectively. Our initial results suggest that efforts to improve gender equality need to assess some fundamental determinants of this objective and pay attention to disease pathogens (Varnum and Grossmann, 2017). Looking for the comparison made by the two groups of countries, it is clear that the difference between these countries can be made in innovation performance. The next section will show more.
4.2 Supplementary controls
In Table 2, we control for several other exogenous forces. Appendix 3 provides the results taking into account different components of gender equality. It is apparent that disease pathogens persist more in the ratio of education between men and women.
First, Beer (2009) highlights that gender equality is highly correlated with urbanization, agriculture, expenditure on education, income level and fragility. We control for this potential confounding effects in Columns (1), (2) and (3). Next, Bennett and Nikolaev (2021) consider geographic characteristics like landlockedness, tropical zone and distance to the Equator as the variables which are correlated with disease pathogens. These are considered in Column (4). Finally, Alesina et al. (2013) theoretically show that the gender ratio is closely linked to historical characteristics like historical technology adoption, precolonial institutions and population density. Accordingly, Columns (5), (6), (7) and (8) control for the underlying characteristics. Following the approach of Alesina et al. (2013), it is evident that the coefficients of disease pathogens remain significant in all cases.
5. Potential channels of influence and endogeneity
5.1 Innovation and women political empowerment channel
We hypothesize in this paper that a greater historical prevalence of infectious disease reduces the probability to develop innovation and this reduces the incentive to invest in gender equality. To test this hypothesis, we first control for the incidence of innovation in the regressions using innovation data provided by the World Intellectual Property Organization (WIPO, 2021). This variable is considered to be both a consequence of historical prevalence of infectious disease (Bennett and Nikolaev, 2021) and the determinant of gender equality (Keisu, 2013; Lauri, 2021; Smith-doerr and Smith-doerr, 2010). Historical prevalence of infectious disease may also be spuriously correlated with other contemporary variables such as women political empowerment that can indicate the evolution of gender equality, consistent with the parasite stress theory (Thornhill and Fincher, 2014a, 2014b). The results are reported in Table 3. The results in Column (1) show that disease pathogens continue to exert some direct effects on gender equality and the corresponding coefficient is highly significant at 1% level. In Column (2), the effect of innovation is more precisely estimated than the influence of disease pathogens, as shown by its relatively larger t-statistic. It is also relevant to note that the absolute value of the coefficient of disease pathogen and its significance falls dramatically when innovation is included. Taken together, the evidence suggests that although we cannot rule out some direct impact from disease pathogens on gender equality, a considerable amount of this influence occurs through innovation. This is not the same result with women’s political empowerment in Column (5). Building on the work of Zelekha (2016) and Bennett and Nikolaev (2021), the aggregate innovation index of the latter should be considered as the main channel of transmission of the effect of the historical prevalence of infectious diseases on gender equality. The authors also state that in this case, the historical variable (disease pathogen) is a good instrument to control the effect of innovation on gender equality.
Table 3 allows us to make several observations. We find in Columns (2) and (3) that the significance of past diseases disappears when we control for the overall innovation index and the products of innovation. In other words, the negative effect of past diseases on gender equality can be reduced by acting on innovation. In Table 4 below, to further check for a key channel of influence, we estimate the effects of disease pathogens on different measures of innovation and women political empowerment. These are the elements of the economy that enable and facilitate innovative activities (innovation inputs); the result of innovative activities within the economy (innovation output); the capacity to innovate and innovation linkage. For this purpose, each measure of innovation and women’s political empowerment is regressed on the historical prevalence of infectious disease. To reduce omitted variables bias, we maintain the used baseline controls. The results reported in Table 4 reveal that disease pathogens negatively and significantly affect the contemporary components of innovation. Otherwise this effect is not significant on women’s political empowerment.
To confirm the discussed mediation channels, we test the effectiveness of mediation using the approaches of Zhao et al. (2010) and Baron and Kenny (1986). The test results in Table 5 indicate that the null of no mediation is rejected at the 1% level of significance for innovation contrary for women political empowerment. The estimates also suggest that about 74% of the effect of disease pathogens on gender equality is channeled through innovation, suggesting that innovation is an important channel of influence.
5.2 Accounting for endogeneity
The previous results show that the main channel through which historical prevalence of infectious disease can influence gender equality is innovation. We, therefore, test whether the reduced-form effect of disease pathogens operates through innovation using an instrumental variable method in two stages. The results are reported in Table 6. We treat innovation as endogenous and instrument it using historical prevalence of infectious disease, conditional on the influence of each potential channel. If this occurs, innovation is likely to affect gender equality. The results indicate that the exogenous component of innovation exerts a strong positive effect on gender equality, and this effect is statistically significant at the 1% level. The p-value of under identification lagrange multiplier statistic is significant at the 1% level, suggesting that historical prevalence of infectious disease is a strong instrument. We run the estimation with a robust option using command “ivreg2” in Stata. The p-value of Anderson–Rubin test of endogenous regressors is significant at the 1% level. We conduct the weak instrument-robust inference using the approach of Anderson and Rubin (1949).
According to Ang et al. (2018), this method which is robust to the presence of weak instruments, tests the significance of the endogenous regressor in the structural equation. The test rejects the null hypothesis that the coefficient of the endogenous regressor is equal to zero at the 5% level of significance, thus providing evidence that our endogenous regressor is relevant even in the presence of a weak instrument.
6. Concluding implication and future research directions
The literature on comparative development has attributed the determinants of gender equality to factors such as agriculture, urbanization, democracy, education and culture. This paper departs from the literature by showing that historical prevalence of infectious disease plays a part in long-run gender equality. Disease pathogens according to parasite stress theory determine innovation, culture and political regime, which lead to the liberalization of values and promote equality between men and women. This reduced-form argument suggests that historical prevalence of infectious disease and gender equality are related. Our results provide considerable support for this notion. In fact, innovation is the main channel through which disease pathogens persist on gender ratio.
The main implication of this study is that innovation should be promoted as a means of fighting disease pathogens and by extension, promoting gender equality. It follows that countries that substantially invest in favoring an economic development culture that is supportive of innovation are also likely to benefit from comparatively less disease burden and gender equality.
Future studies can extend the findings in this study by assessing how other historical factors influence contemporary gender equality. Moreover, to provide findings with complementary implications, understanding how contemporary factors influence contemporary gender equality dynamics is also worthwhile for the achievement of SDG5 focusing on gender equality and women empowerment.
Figures
Figure 1
Historical prevalence of infectious disease and individualist culture
Figure 2
Historical prevalence of infectious disease and women’s political empowerment
Figure 3
Historical prevalence of infectious disease and global innovation
Figure 4
Global innovation and gender equality
Figure 5
Geographical distribution of gender equality across the world
Figure 6
Geographical distribution of historical prevalence of pathogens across the world
Reduced-form effect of disease pathogens and gender equality
| Variables and information criteria | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| Basic specification | Add culture controls and continent dummy | Add legal origin | Add religion control | Add political regime | Full specification | |
| Dependent variable: gender equality | OLS | OLS | OLS | OLS | OLS | OLS |
| Disease pathogen | −13.592*** (1.504) | −7.489*** (2.746) | −7.828*** (2.348) | −7.637*** (2.063) | −7.612*** (2.048) | −6.442*** (1.991) |
| Individualist/collectivist | 10.876*** (3.327) | 9.921*** (3.056) | 2.337 (2.865) | 2.499 (2.966) | 3.995 (3.211) | |
| German legal origin | 2.564 (1.862) | −0.655 (1.846) | 0.389 (2.293) | −0.387 (2.644) | ||
| French legal origin | −1.394 (2.627) | −0.695 (2.327) | −0.530 (2.340) | −0.013 (2.311) | ||
| Scandinavian legal origin | 10.620*** (2.405) | 3.962 (4.887) | 5.389 (5.241) | 4.006 (5.355) | ||
| Catholic trust | 0.067** (0.032) | 0.052 (0.035) | 0.056 (0.038) | |||
| Muslim trust | −0.199*** (0.040) | −0.209*** (0.042) | −0.207*** (0.043) | |||
| Protestant trust | 0.109 (0.067) | 0.081 (0.073) | 0.119 (0.072) | |||
| Democracy | 0.119* (0.071) | 0.119* (0.067) | ||||
| America dummy | 10.640*** (2.930) | 2.838 (2.916) | ||||
| Asia dummy | −1.640 (3.543) | 4.489* (2.696) | ||||
| Other continent dummy | −3.081 (3.922) | −1.340 (2.870) | ||||
| Constant | 65.533*** (1.131) | 63.495*** (2.792) | 62.814*** (2.305) | 65.900*** (2.463) | 66.577*** (2.656) | 64.650*** (2.700) |
| Observations | 122 | 122 | 119 | 112 | 107 | 107 |
| R2 | 0.32 | 0.43 | 0.38 | 0.65 | 0.67 | 0.68 |
| Fisher | 81.65 | 22.12 | 53.51 | 41.64 | 38.71 | 30.29 |
This table shows the correlation between disease pathogen in the past and gender equality. Consistent with our prediction, the results suggest that a higher level of historical prevalence of infectious disease is associated with lower score in gender equality. The results are robust to the inclusion of culture, legal origin, political controls and continental fixed effects. Robust standard errors are used and t-statistics are reported in the parentheses. *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively
Source: Authors’ construction
Supplementary controls
| Variables and information criteria | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) |
|---|---|---|---|---|---|---|---|---|
| Disease pathogen | −6.702** (2.675) | −4.350** (2.023) | −4.636** (2.246) | −6.783* (3.846) | −4.833** (2.044) | −4.619** (2.146) | −6.900** (3.440) | −8.073** (3.541) |
| Urbanization | 0.335 (0.718) | |||||||
| Agriculture | −0.097 (0.106) | |||||||
| Education | 0.524** (0.262) | |||||||
| High income | 10.127*** (3.212) | |||||||
| Country size | −1.915 (4.382) | |||||||
| Fragility | −8.776*** (3.182) | |||||||
| Island | 3.230 (4.127) | |||||||
| Landlocked | −3.116 (4.195) | |||||||
| Tropical dummy | 4.288 (5.359) | |||||||
| Distance to equator | 18.765 (19.434) | |||||||
| Precolonial institution | 17.946*** (6.692) | |||||||
| State antiquity | 1.329 (7.204) | |||||||
| Technology 1500 BC | 23.556*** (6.885) | |||||||
| Population density in 1000 BC | −4.548 (3.044) | |||||||
| Base line control | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Cultural controls | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Continent dummy | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Constant | 60.737*** (7.266) | 63.455*** (2.696) | 64.840*** (2.810) | 61.773*** (11.172) | 45.310*** (7.805) | 65.782*** (4.165) | 47.567*** (6.622) | 75.826*** (7.639) |
| Observations | 93 | 108 | 108 | 89 | 108 | 94 | 84 | 78 |
| R2 | 0.72 | 0.70 | 0.70 | 0.68 | 0.70 | 0.69 | 0.75 | 0.70 |
| Fisher | 24.00 | 25.11 | 28.50 | 23.53 | 26.03 | 23.18 | 22.72 | 19.41 |
This table shows supplementary controls of the effect of disease pathogen in the past on gender equality. Consistent with our prediction, the results suggest that the coefficients of disease pathogens remain significant in all cases. The results are robust to the inclusion of culture, legal origin, political controls and continental fixed effects. Robust standard errors are used and t-statistics are reported in the parentheses. *, ** and *** indicate significance at the 10, 5 and 1% levels, respectively
Source: Authors’ construction
Potential channels linking historical prevalence of disease to gender equality
| Variables and information criteria | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| Dependent variable: gender equality | OLS | OLS | OLS | OLS | OLS | OLS |
| Disease pathogen | −6.480*** (1.994) | −2.685 (2.044) | −2.163 (1.908) | −6.058*** (2.048) | −6.430*** (2.045) | −2.892 (2.021) |
| Global innovation | 0.532*** (0.131) | 0.501*** (0.136) | ||||
| Innovation output | 0.525*** (0.107) | |||||
| Innovation input | 0.137 (0.147) | |||||
| Women political empowerment | 17.053* (9.017) | 6.135 (9.314) | ||||
| Constant | 64.631*** (2.714) | 45.388*** (5.473) | 42.959*** (5.182) | 63.807*** (2.753) | 50.303*** (7.852) | 41.375*** (8.633) |
| Observations | 108 | 108 | 108 | 108 | 108 | 108 |
| R2 | 0.68 | 0.73 | 0.75 | 0.68 | 0.69 | 0.73 |
| Fisher | 30.38 | 28.17 | 31.31 | 29.39 | 27.67 | 26.40 |
This table shows the potential channels linking historical prevalence of disease to gender equality. Consistent with our prediction, the results suggest that the aggregate innovation index rather than women political empowerment should be considered as the main channel of transmission of the effect of the historical prevalence of infectious diseases on gender equality. The results are robust to the inclusion of culture, legal origin, political controls and continental fixed effects. Robust standard errors are used and t-statistics are reported in the parentheses. *, ** and *** indicate significance at the 10, 5 and 1% levels, respectively
Source: Authors’ construction
Effect of disease pathogens on innovation and women’s political empowerment
| Variables and information criteria | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| OLS | OLS | OLS | OLS | OLS | |
| Method | Global innovation | Innovation output | Innovation linkages | Capacity for innovation | Women political empowerment |
| Disease pathogen | −6.550** (2.690) | −8.065** (3.398) | −6.248** (2.936) | −0.402*** (0.152) | 0.043 (0.036) |
| Base line control | Yes | Yes | Yes | Yes | Yes |
| Geographic controls | Yes | Yes | Yes | Yes | Yes |
| Continent dummy | Yes | Yes | Yes | Yes | Yes |
| Constant | 46.875*** (3.323) | 50.518*** (3.711) | 47.170*** (5.156) | 4.256*** (0.222) | 0.933*** (0.050) |
| Observations | 95 | 95 | 94 | 95 | 95 |
| R2 | 0.70 | 0.66 | 0.59 | 0.57 | 0.64 |
| Fisher | 51.27 | 40.60 | 28.95 | 47.41 | 10.89 |
This table shows the effects of disease pathogens on different measures of innovation and women political empowerment. The results that disease pathogens negatively and significantly affect the contemporary components of innovation. Robust standard errors are used and t-statistics are reported in the parentheses. *, ** and *** indicate significance at the 10, 5 and 1% levels, respectively
Source: Authors’ construction
Mediation analysis using structural equations modeling
| Mediation variables | (1) | (2) |
|---|---|---|
| Dependent variable: gender equality | ||
| Mediator: | Global innovation index | Women political empowerment |
| Step 1 (X → M) | −0.724 *** (0.000) | −0.426 *** (0.000) |
| Step 2 (M → Y) | 0.434*** (0.000) | 0.161* (0.071) |
| Step 3 (X → Y) | −0.112 (0.049) | −0.210 (0.268) |
| Sobel test (of indirect effect) | −0.314 *** (0.000) | −0.069* (0.085) |
| RIT | 0.737 | 0.247 |
| RID | 2.796 | 0.327 |
| Conclusion ZLC | full mediation | No mediation |
| Conclusion BK | mediation is complete | No mediation |
This table reports the partial results of structural equation modeling and distinguishes direct and indirect effects. p-Values are in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. RIT = (indirect effect/total effect). RID = (indirect effect/direct effect) ZLC: Zhao et al. (2010); BK: Baron and Kenny (1986)
Source: Authors’ construction
Dealing with endogeneity
| Panel A: 2nd-stage regressions | (1) |
|---|---|
| Dependent variable: gender equality | |
| Innovation | 0.945*** (0.093) |
| Constant | 29.895*** (3.888) |
| Panel B: 1st-stage regressions | |
| Dependent variable: innovation | |
| Disease pathogen | −14.241*** (1.118) |
| Constant | 37.450*** (0.856) |
| Observations | 123 |
| R2 | 0.41 |
| Fisher | 101.78*** |
| Under identification LM statistic (p-value) | 0.000 |
| Anderson–Rubin chi-sq test of endogenous regressors (p-value) | 0.048 |
Source: Authors’ construction
Descriptive statistics
| Variables | Obs | Mean | Std. Dev. | Min | Max | source |
|---|---|---|---|---|---|---|
| Gender equality | 123 | 63.707 | 15.708 | 26.822 | 91.371 | Sachs et al. (2021) |
| Diseases pathogens(historically) | 123 | 0.133 | 0.656 | −1.31 | 1.17 | Murray and Schaller (2010) |
| German legal origin | 121 | 0.05 | 0.218 | 0 | 1 | Acemoglu et al. (2001) |
| culture | 123 | 0.211 | 0.41 | 0 | 1 | |
| French legal origin | 120 | 0.525 | 0.501 | 0 | 1 | Acemoglu et al. (2001) |
| Scandinavian legal origin | 121 | 0.041 | 0.2 | 0 | 1 | Acemoglu et al. (2001) |
| catholic trust | 114 | 31.842 | 35.986 | 0 | 96.9 | Acemoglu et al. (2001) |
| Muslim | 114 | 23.034 | 35.265 | 0 | 99.4 | Acemoglu et al. (2001) |
| Protestant trust | 120 | 12.342 | 21.691 | 0 | 97.8 | Acemoglu et al. (2001) |
| Democracy | 116 | −0.051 | 14.42 | −66 | 10 | V-DEM (2021) |
| Innovation | 123 | 35.789 | 12.966 | 10.6 | 66.6 | WIPO (2021) |
| Innovation outputs | 123 | 38.417 | 13.926 | 4.4 | 66.833 | WIPO (2021) |
| Innovation inputs | 123 | 10.701 | 8.68 | 0.5 | 65.2 | WIPO (2021) |
| Women political empowerment | 120 | 0.761 | 0.168 | 0.184 | 0.962 | V-DEM (2021) |
| urbanization | 113 | 8.068 | 1.624 | 4.357 | 12.009 | V-DEM (2021) |
| Agriculture | 119 | 15.195 | 14.559 | 0.116 | 75.362 | WDI (2021) |
| Expenditure on education | 113 | 14.314 | 4.332 | 6.293 | 24.938 | WDI (2021) |
| high income | 121 | 0.296 | 0.417 | 0 | 1 | World Bank classification (2021) |
| Small country | 120 | 0.092 | 0.29 | 0 | 1 | World Bank classification (2021) |
| Fragile country | 120 | 0.108 | 0.312 | 0 | 1 | World Bank classification (2021) |
| Island | 120 | 0.033 | 0.18 | 0 | 1 | World Bank classification (2021) |
| Landlocked | 105 | 0.171 | 0.379 | 0 | 1 | Comin et al. (2010) |
| tropical | 105 | 0.476 | 0.502 | 0 | 1 | Comin et al. (2010) |
| Distance to equator | 99 | 0.294 | 0.195 | 0.003 | 0.669 | Comin et al. (2010) |
| Precolonial institution | 122 | 0.934 | 0.17 | 0 | 1 | Giuliano andNunn (2018) |
| State antiquity | 105 | 0.492 | 0.236 | 0.028 | 0.964 | Ang and Fredriksson (2018) |
| Technology adoption in 1500 BC | 92 | 0.647 | 0.253 | 0.157 | 0.995 | Comin et al. (2010) |
| Population density in 1000 BC | 87 | 1.793 | 0.701 | 1 | 3 | Comin et al. (2010) |
| American dummy | 123 | 0.146 | 0.355 | 0 | 1 | Authors |
| Asian dummy | 123 | 0.252 | 0.436 | 0 | 1 | Authors |
| other continent dummy | 123 | 0.74 | 0.441 | 0 | 1 | Authors |
Source: Authors’ construction
List of countries
| List of Countries | ||||
|---|---|---|---|---|
| Albania | Costa Rica | Israel | Netherlands | Syria |
| Algeria | Ivorycost | Italy | Nigeria | Tanzania |
| Angola | Croatia | Jamaica | Norway | Thailand |
| Argentina | Cyprus | Japan | Oman | Trinidad and tobago |
| Armenia | CzechRep. | Jordan | Pakistan | Tunisia |
| Australia | Denmark | Kenya | Panama | Turkey |
| Austria | Ecuador | Korea | Peru | Uganda |
| Azerbaijan | Egypt | Koreasouth | Philippines | Ukraine |
| Bahrain | El Salvador | Kuwait | Poland | United Arabe emirate |
| Bangladesh | Estonia | Laos | Portugal | United Kindom |
| Belgium | Ethiopia | Latvia | Romania | Uruguay |
| Benin | Finland | Lebanon | Russia | USA |
| Bolivia | France | Liberia | Rwanda | Venezuela |
| Bosnia | Gabon | Lithuania | Saudiarabia | Vietnam |
| Botswana | Gambia | Luxembourg | Senegal | Zambia |
| Brazil | Georgia | Macedonia | SerbiaMontengro | |
| Brunei | Germany | Madagascar | Sierra leone | |
| Bulgaria | Ghana | Malawi | Singapore | |
| Burkina faso | Greece | Malaysia | Slovakia | |
| Burundi | Guatemala | Mali | Slovenia | |
| Cambodia | Guinea | Mauritania | South Africa | |
| Cameroon | Hungary | Mayanmar | Spain | |
| Canada | Iceland | Mexico | Sri Lanka | |
| Chad | India | Moldova | Suriname | |
| Chile | Indonesia | Morocco | Swaziland | |
| China | Iran | Mozambique | Sweden | |
| Colombia | Ireland | Namibia | Switzerland | |
Source: Authors’ construction
Controlling for other measures of gender equality
| Variables and information criteria | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| OLS | OLS | OLS | OLS | OLS | OLS | |
| Gender equality | Ratio on family planning | Ratio on education | Ratio on labor force | Ratio on national parliament | Gender wage gap | |
| Disease pathogen | −6.480*** (1.994) | −5.286 (3.673) | −14.905*** (3.121) | 5.690* (3.182) | −0.350 (1.683) | 3.792 (2.454) |
| Culture | 3.953 (3.218) | 13.239** (6.031) | −5.325 (4.702) | 7.394* (4.019) | 2.215 (2.429) | 1.366 (2.935) |
| German legal origin | 0.063 (2.778) | 7.202 (5.176) | −4.441 (3.858) | −1.546 (3.744) | 1.818 (2.702) | 6.879 (4.184) |
| French legal origin | −0.002 (2.307) | 1.113 (3.113) | 1.081 (3.141) | −2.543 (3.181) | 2.119 (1.903) | −4.208 (2.637) |
| Scandinavian legal origin | 3.995 (5.347) | −1.446 (6.846) | −7.429 (5.958) | 3.235 (5.152) | 13.877*** (5.069) | −12.980** (5.353) |
| Catholic trust | 0.056 (0.037) | −0.007 (0.070) | 0.025 (0.055) | −0.048 (0.052) | 0.080*** (0.030) | −0.058 (0.046) |
| Muslim trust | −0.207*** (0.043) | −0.176*** (0.061) | −0.136** (0.055) | −0.328*** (0.066) | −0.007 (0.031) | −0.114** (0.046) |
| Protestant trust | 0.120* (0.072) | 0.119 (0.105) | 0.105 (0.087) | 0.058 (0.083) | 0.097* (0.058) | 0.102 (0.076) |
| Democracy | 0.113* (0.061) | 0.159* (0.088) | 0.225*** (0.076) | −0.048 (0.083) | −0.020 (0.039) | −0.110** (0.052) |
| America dummy | 2.838 (2.918) | 19.517*** (6.143) | 12.248*** (4.266) | −16.022*** (4.651) | −1.701 (2.676) | 2.021 (3.507) |
| Asia dummy | 4.509* (2.687) | 17.875*** (4.576) | 16.300*** (3.800) | −16.723*** (4.492) | −2.200 (2.005) | 2.375 (5.952) |
| Other dummy | −1.288 (2.889) | −3.881 (6.912) | −4.802 (4.455) | 8.833** (4.448) | −1.530 (2.125) | −0.923 (2.707) |
| Constant | 64.631*** (2.714) | 58.628*** (6.824) | 89.661*** (4.088) | 77.278*** (3.770) | 15.552*** (2.538) | 18.925*** (4.254) |
| Observations | 108 | 107 | 109 | 109 | 109 | 35 |
| R2 | 0.68 | 0.58 | 0.57 | 0.56 | 0.43 | 0.74 |
| Fisher | 30.38 | 24.35 | 12.75 | 29.16 | 16.49 | 31.14 |
Source: Authors’ construction
Appendix 1
Appendix 2
Appendix 3
References
Acemoglu, D., Johnson, S. and Robinson, J.A. (2001), “The colonial origins of comparative development: an empirical investigation”, American Economic Review, Vol. 91 No. 5, pp. 1369-1401, available at: www.jstor.org/stable/2677930
Alesina, A. and Giuliano, P. (2010), “The power of the family”, Journal of Economic Growth, Vol. 15, No. 2, pp. 93-125, doi: 10.1007/s10887-010-9052-z.
Alesina, A., Giuliano, P. and Nunn, N. (2013), “On the origins of gender roles: women and the plough”, The Quarterly Journal of Economics, Vol. 128 No. 2, pp. 469-530, doi: 10.1093/qje/qjt005.Advance.
Anderson, T.W. and Rubin, H. (1949), “Estimation of the parameters of a single equation in a complete system of stochastic equations”, The Annals of Mathematical Statistics, Vol. 20, No. 1, pp. 46-63, doi: 10.1214/aoms/1177730090.
Ang, J.B. and Fredriksson, P.G. (2018), “State history, legal adaptability and financial development”, Journal of Banking and Finance, Accepted M, Vol. 89, doi: 10.1016/j.jbankfin.2018.02.009.
Ang, J.B., Fredriksson, P.G., Luqman, A. and Tay, E.H. (2018), “Sunlight, disease, and institutions”, Kyklos, Vol. 71 No. 3, pp. 374-401, doi: 10.1111/kykl.12174.
Asongu, S.A., Adegboye, A. and Nnanna, J. (2021), “Promoting female economic inclusionfor tax performance in Sub-Saharan Africa”, Economic Analysis and Policy, Vol. 69 No. March, pp. 159-170, doi: 10.1016/j.eap.2020.11.010.
Asongu, S.A. and Odhiambo, N.M. (2018), “ICT, financial access and gender inclusion inthe formal economic sector: evidence from Africa”, African Finance Journal, Vol. 20 No. 2, pp. 46-66, available at: https://hdl.handle.net/10520/EJC-139fe7e407
Awel, Y. and Yitbarek, E. (2022), “Mobile money demand in utility bill payments: a WTP estimate from Ethiopia”, Journal of Development Effectiveness, Vol. 14 No. 1, pp. 56-75, doi: 10.1080/19439342.2021.1964576.
Baron, R.M. and Kenny, D.A. (1986), “The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations”, Journal of Personality and Social Psychology, Vol. 51 No. 6, pp. 1173-1182.
Beer, C. (2009), “Democracy and gender equality”, Studies in Comparative International Development, Vol. 44 No. 3, pp. 212-227, doi: 10.1007/s12116-009-9043-2.
Bennett, D.L. (2018), “Infrastructure investments and entrepreneurial dynamism in the”, Journal of Business Venturing, Vol. 34 No. 5, pp. 1-28, doi: 10.1016/j.jbusvent.2018.10.005.
Bennett, D.L. (2019), “Infrastructure investments and entrepreneurial dynamism in the”, Journal of Business Venturing, Vol. 34 No. 5, p. 105907, doi: 10.1016/j.jbusvent.2018.10.005.
Bennett, D.L. and Nikolaev, B. (2021), “Historical disease prevalence, cultural values, and global innovation”, Entrepreneurship Theory and Practice, Vol. 45 No. 1, pp. 145-174, doi: 10.1177/1042258720914506.
Comin, D., Easterly, W. and Gong, E. (2010), “Was the wealth of nations determined in 1000 bc?”, American Economic Journal: Macroeconomics, Vol. 2 No. 3, pp. 65-97.
Fincher, C.L., Thornhill, R., Murray, D.R., Schaller, M. and Fincher, L. (2013), “Predicts human pathogen prevalence variability in individualism/collectivism”, Proceedings of the Royal Society B: Biological Sciences, Vol. 275 No. 1640, pp. 1279-1285, doi: 10.1098/rspb.2008.0094.
Gelfand, M.J., Bhawuk, D.P.S., Nishii, L.H. and Bechtold, D.J. (2004), “Individualism and collectivism”, in House, R.J. (Ed.), Culture, Leadership, and Organizations: The GLOBE Study of 62 Societies, Sage Publications, London.
Hofstede, G. (2011), “Dimensionalizing cultures: the hofstede model in context dimensionalizing cultures: the hofstede model in context”, Vol. 2, pp. 1-26.
Inglehart, R. and Norris, P. (2003), “Rising tide: gender equality and cultural change around the world. rising tide: gender equality and cultural change around the world”, pp. 1-226, doi: 10.1017/CBO9780511550362.
Keisu, M.R.B.-I. (2013), “Constructions of innovation and gender (equality) in Swedish universities”, International Journal of Gender and Entrepreneurship, Vol. 5 No. 3, pp. 342-356, doi: 10.1108/IJGE-09-2012-0047.
Kim, K. (2022), “Assessing the impact of mobile money on improving the financial inclusion of Nairobi women”, Journal of Gender Studies, Vol. 31 No. 3, pp. 306-322, doi: 10.1080/09589236.2021.1884536.
Lauri, J. (2021), “The discourse of social innovation and gender equality the discourse of social innovation and gender equality”, Prometheus, Vol. 37 No. 1, pp. 27-43.
Mndolwa, F.D. and Alhassan, A.L. (2020), “Gender disparities in financial inclusion: insights from tanzania”, African Development Review, Vol. 32 No. 4, pp. 578-590, doi: 10.1111/1467-8268.12462.
Murray, D.R. and Schaller, M. (2010), “Historical prevalence of infectious diseases within 230 geopolitical regions: a tool for investigating origins of culture”, Journal of Cross-Cultural Psychology, Vol. 41 No. 1, pp. 99-108, doi: 10.1177/0022022109349510.
Murray, D.R., Schaller, M. and Suedfeld, P. (2013), “Pathogens and politics: further evidence that parasite prevalence predicts authoritarianism”, PLoS One, Vol. 8 No. 5, doi: 10.1371/journal.pone.0062275.
Murray, D.R., Trudeau, R. and Schaller, M. (2011), “On the origins of cultural differences in conformity: four tests of the pathogen prevalence hypothesis”, Personality and Social Psychology Bulletin, Vol. 37 No. 3, pp. 318-329, doi: 10.1177/0146167210394451.
Ngono, J.F.L. (2021), “Financing women’s entrepreneurship in Sub-Saharan Africa: bank, microfinance and mobile money”, Labor History, Vol. 62 No. 1, pp. 59-73, doi: 10.1080/0023656X.2020.1851666.
Nikolaev, B., Boudreaux, C. and Salahodjaev, R. (2017), “Journal of economic behavior & organization are individualistic societies less equal? Evidence from the parasite stress theory of values”, Journal of Economic Behavior & Organization, Vol. 138, pp. 30-49, doi: 10.1016/j.jebo.2017.04.001.
Oishi, S. and Uhich Schimmack, E.D. (1954), “The measurement of values and Individualism-Collectivism”, Psychological Review, Vol. 61 No. 1, pp. 47-58, doi: 10.1037/h0060035.
Osabuohien, E. and Karakara, A.A. (2018), “ICT usage, mobile money and financial access of women in Ghana”, Africagrowth Agenda Journal, Vol. 15 No. 1, pp. 14-18, available at: https://hdl.handle.net/10520/EJC-dc947bee3
Rogers, E. (1995), Diffusion of Innovations, 4th edn., The Free Press, New York.
Saâd, M.B. and Assoumou-Ella, G. (2019), “Complexity and gender inequality in education: an empirical study”, Economics Bulletin, Vol. 39 No. 1, pp. 321-334.
Sachs, J., Kroll, C., Lafortune, G. and Fuller, G.W.F. (2021), “The decade of action for the sustainable development goals: sustainable development report 2021”, C.U. Press (Ed.), ISBN 978-1, Cambridge University Press, Cambridge, doi: 10.1017/9781009106559
Sagiv, L. and Schwartz, S.H. (1995), “Value priorities and readiness for out-group social contact”, Journal of Personality and Social Psychology, Vol. 69 No. 3, pp. 437-448, doi: 10.1037/0022-3514.69.3.437.
Schaller, M. and Murray, D.R. (2008), “Pathogens, personality, and culture: disease prevalence predicts worldwide variability in sociosexuality, extraversion, and openness to experience”, Journal of Personality and Social Psychology, Vol. 95 No. 1, pp. 212-221, doi: 10.1037/0022-3514.95.1.212.
Smith-Doerr, L. and Smith-Doerr, L. (2010), “Flexible organizations, innovation and gender equality: Writing for the US film industry, 1907-27”, Industry & Innovation, Vol. 17 No. 1, pp. 5-22, doi: 10.1080/13662710903573810.
Thornhill, R. and Fincher, C.L. (2014a), Stress Theory of Values and Sociality, Springer, Berlin, available at: https://link.springer.com/content/pdf/10.1007/978-3-319-08040-6.pdf
Thornhill, R. and Fincher, C.L. (2011), “Parasite stress promotes homicide and child maltreatment”, Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 366 No. 1583, pp. 3466-3477, doi: 10.1098/rstb.2011.0052.
Thornhill, R. and Fincher, C.L. (2014b), “The parasite-stress theory of sociality, the behavioral immune system, and human social and cognitive uniqueness”, Evolutionary Behavioral Sciences, Vol. 8 No. 4, pp. 257-264, doi: 10.1037/ebs0000020.
Thornhill, R., Fincher, C.L. and Aran, D. (2009), “Parasites, democratization, and the liberalization of values across contemporary countries”, Biological Reviews, Vol. 84 No. 1, pp. 113-131, doi: 10.1111/j.1469-185X.2008.00062.x.
Varnum, M.W. and Grossmann, I. (2017), “Pathogen prevalence is associated with cultural changes in gender equality”, Nature Human Behaviour, Vol. 1 No. 1, pp. 14-17, doi: 10.1038/s41562-016-0003.
Wejnert, B. (2005), “Diffusion, development, and democracy, 1800-1999”, American Sociological Review, Vol. 70 No. 1.
WIPO (2021), “Global innovation index 2021: tracking innovation through the COVID-19 Crisis”, in Soumitra Dutta, B.L. and Wunsch-Vincent, L.R.L.S. (Eds), World Intellectual Property Organization, Geneva.
Wrigley, J. (1992), Education and Gender Equality, W. 2ET UK The Falmer Press, London.
Zhao, X., Lynch, J.G.J. and Chen, Q. (2010), “Reconsidering baron and Kenny: myths and truths about mediation anaiysis”, Journal of Consumer Research, Vol. 37 No. 2, pp. 197-206, doi: 10.1086/651257.
Zelekha, B.Y. (2016), Do Colonialism and Slave Trade Still Affect Modern Economic Performance? Applied Economics Quarterly, Vol. 62 No. 2, pp. 147-168.
Further reading
Giuliano, P. and Nunn, N. (2018), “Ancestral characteristics of modern populations”, Economic History of Developing Regions, Vol. 33 No. 1, pp. 1-17, doi: 10.1080/20780389.2018.1435267.
Murry, B.A., Fish, U.S., Service, W., Applications, S., Juan, S., States, U., Naturaleza, P., Juan, S. and States, U. (2023), “An overview of the socio-ecological system of cays and islets in the us Caribbean and their vulnerability to climate change”, doi: 10.1016/B978-0-12-409548-9.12010-X.
Acknowledgements
The authors are indebted to the editors and reviewers for constructive comments.
Compliance with Ethical Standards.
Conflict of Interest: The authors declare that they have no conflict of interest.
Ethical approval: This article does not contain any studies with human participants or animals performed by the authors.
Data availability: the data for this research are available upon request.
Corresponding author
About the authors
Omang Ombolo Messono is based at the Faculty of Economics and Applied Management, University of Douala, Douala, Cameroon.
Simplice Asongu is based at the School of Economics, University of Johannesburg, Johannesburg, South Africa and Department of Economic and Data Science, New Uzbekistan University, Tashkent, Uzbekistan.
Vanessa Tchamyou is based at the Department of Research, Association for Promoting Women in Research and Development in Africa (ASPROWORDA), Yaoundé, Cameroon.