Gender Inequality and Foreign Direct Investment: Empirical Evidence from Asian Countries

In Asian countries, the relationship between gender inequality and foreign direct investment (FDI) is a sensitive topic. Due to labor market limits and the advantageous effect of women's empowerment, gender inequality is thought to have a detrimental impact on economic development and FDI. This study aims to look into the influence of gender disparity on FDI inflows to Asian countries. Our data includes 43 Asian nations and spans the years 1990 to 2018. We discover that reduced tertiary-level education and health gaps play a decisive role in FDI inflow into Asian countries using the Generalized Method of Moments (GMM). The findings are crucial to devising policies to minimize the gap in gender equality and promote FDI.


INTRODUCTION
Trade liberalization policies were expected to lessen the pay gap in developing countries while negatively affecting the wage structure in wealthier nations (Aguayo-Tellez, 2012).However, after three decades of empirical data, a sizable body of work on the impact of trade liberalization policies (TLP) and foreign direct investment (FDI) on wage disparity and employment has found something different.The wage gap has grown in developed and developing economies due to TLP and FDI.Bui et al. (2018) also explore the link between gender inequality and FDI in developing economies.Due to labor market constraints and the beneficial outcome of women's empowerment, gender inequality damages economic progress.The relationship between women's rights and a nation's ability to compete in the global economy offers an intriguing conundrum.Women's education is associated with higher economic development and progress within a nation (Klasen, 2002;Berik et al., 2009;Klasen & Lamanna, 2009;Berik, 2011;Farooq et al., 2019).Respect for women's rights implies a more skilled workforce and a secure business environment, which may appeal to foreign investors more (Coleman, 2010;Busse & Nunnenkamp, 2009).
However, preserving economic disparities between the sexes, primarily through pay inequality, may help nations compete more successfully in the global economy (Seguino, 2000(Seguino, , 2010;;Busse & Spielmann, 2006;Bezuidenhout et al., 2019).In semiindustrialized nations and export-competitive sectors, the benefits of this "low road to growth" are obvious (Seguino et al., 2009).These disparate results point to a nuanced and complicated relationship between women's rights and a state's economic objectives, as women's empowerment may have different impacts on a nation's capacity to grow and fight on the global stage.Chaudhuri & Mukhopadhyay (2014) stated that in most countries, particularly developing ones, gender inequalities in labor markets indicate a compensation gap between men and women.Jamielaa (2018) show that gender wage gap is narrower in low quantile wage distributions than in high quantile distributions.Few studies have examined FDI's influence on gender-based wage discrepancies, with mixed findings.FDI may have two adverse effects on gender pay differentials: on the one hand, the difference may widen due to women's weaker negotiating leverage in MNCs, and on the other hand, MNCs may reward the higher education levels of female workers, narrowing the gender wage gap.Foreign capital may drive economic progress, but an equal, welfare-maximizing state is only achieved if gender wage discrepancy reduces with economic growth and well-being.FDI in countries with female-intensive export sectors may enhance gender pay disparity but not economic welfare.These findings show a trade-off between wage inequality and economic health (Chen et al., 2013).Stolzenburg et al. (2021) studied globalization, notably FDI and gender disparity, using matched employer-employee data from South Africa.They analyze whether foreign-owned companies have a different gender pay gap (GWG) than domestic firms.Foreign-owned companies had a lower unconditional GWG than native ones.The Volume 22(2), 2023: 321 -332 proportion of women in international companies is lower than in domestic firms, which contradicts comparative studies and may reflect unfair opportunities for women in a developing country.Girmay (2018) claimed that foreign direct investment (FDI) inflows might raise gender gaps in gender-unequal developing nations and that transnational companies (TNCs) must augment their routine FDI operations with different policies and investments to guarantee that women are not rendered worse off.

Etikonomi
This study builds a philosophical foundation in global gender justice and then explores empirical data showing ethically problematic regions of FDI and gender equality.It then discusses why gender vulnerability to FDI must be addressed based on the global gender justice philosophy.The study utilizes cosmopolitan business ethics to establish TNCs as accountable for ensuring FDI inflows do not harm women, and it suggests policies and actions enforce this obligation.McLaren & Yoo (2017) state that measuring the effect of FDI on household welfare is more difficult rather than measuring the effect of trade policy.Blanton & Blanton (2015) said there is disagreement about how women's rights affect a country's competitiveness in the global economy.Many good things happen when women have access to education and political power, but the effects of economic rights are complicated.Most research on what causes FDI does not look at gender.Moreover, some papers that look into this FDI Gender parity nexus do not consider a broad measure of the latter.Therefore, to fill this gap, we look at the role of women's rights in attracting FDI to help us understand these issues better.Foreign capital is a crucial part of many countries' plans for growth and development, and many of the growth areas for FDI depend heavily on women's work.The novelty of this research is that it analyses an empirical model of FDI determinants that considers a variety of variables for gender inequality and focuses on many areas of gender inequality, including disparities in education (primary, secondary, and tertiary education) and health.
We analyze panel data of 43 Asian nations from 1990 to 2018 using a two-step System Generalized Method of Moments to estimate our model because of its dynamic nature and to address the endogeneity concern.Our data support the theory that gender parity promotes FDI inflows.The empirical model and estimation methods are discussed in the next section.Section 3 explains our empirical findings.Finally, we provide some closing observations in the last part.

METHODS
In this analysis, we use Cheng and Kwan's (2000) technique, which accounts for agglomeration's economic impacts.Technology spillovers, industry-specific localization, and economic geography are three elements that are considered crucial in the spatial clustering of investment capital in agglomeration economies.To capture the influence of these three elements, Kinoshita & Campos (2003) employ the 1-year lagged value of FDI.Furthermore, using lagged FDI mitigates the effects of the missing variable (Brzozowski, 2013).
(1) On the right-hand side of the equation, we adopt the form of a dynamic panel data process with a lagged dependent variable.We employ a system generalized method of moments (GMM) estimate approach introduced by Blundell & Bond (1998) to account for the correlation between the lagged dependent variable and the country time-invariant e it , as well as the problem of the endogenous explanatory variable.The error term in the GMM approach is first order auto-correlated by design.There should be no secondorder auto-correlation, though.As a result, we use the Arellano-Bond test to evaluate the fundamental hypothesis of no second order autocorrelation.The fact that this null hypothesis was rejected implies that GMM estimations are inconclusive.The quantity of instruments is another issue with the GMM approach.The number of instruments must not exceed the number of countries, according to the rule of thumb.
Several ideas have been proposed to explain the factors that influence FDI.On the other hand, empirical evidence reveals that distinct theoretical models do not replace one another.As a result, Faeth (2009) suggested that some theories, including agglomeration economics, market size, production cost, country risks, policies, and institutional quality, should be used to investigate the determinants of FDI.The factors of market size and trade openness are found to have excellent explanatory power when it comes to FDI determinants (Busse & Nunnenkamp, 2009;Chakrabarti, 2001).According to the market size theory, market-seeking FDI is attracted to nations with high market demand and rapid growth rates.We utilize the logarithm of GDP as a proxy for market size, as in earlier research (Brzozowski, 2013;Resmini & Casi, 2010).Given the large amount of FDI flowing into tradable industries, the greater the degree of openness a country has, the more appealing it is to foreign investors (Demirhan & Masca, 2008).
We include the inflation rate in the empirical model to account for macroeconomic policy and stability.Given the importance of macroeconomic and political risks in shaping investment decisions, a background of stable pricing levels demonstrates the government's commitment to promoting a favorable investment climate.According to Kinoshita & Campos (2003), many developing and transitional countries have developed stabilization measures to reduce inflation.As a result, low inflation indicates a solid program that aids in achieving higher short-term growth.As a result, keeping prices low and consistent is an excellent approach to attracting additional FDI.
Labor costs are the most contentious aspect of FDI because their impact varies depending on the type of FDI.However, to account for efficiency-seeking FDI, this variable must be controlled in the model.Because pay data is scarce, we utilize the unemployment rate as a proxy for labor costs, as suggested by Blanton & Blanton (2015).Furthermore, transportation and communication costs should be mentioned as a reliable predictor of FDI.Poor infrastructure investment is frequently cited as a barrier to attracting FDI, particularly when foreign investors can help create infrastructure for the host country (Demirhan & Masca, 2008).As suggested by Etikonomi Volume 22(2), 2023: 321 -332 the literature, we use the number of mobile phones per 100 people as a proxy for infrastructural development.
We examine four dimensions of gender inequality in our study's primary explanatory variables, which are markers of gender disparity: inequality in education, inequality in health, and inequality in wealth.We use two indices to measure the extent of educational disparity, or the education gap, as Brzozowski (2013) suggested.We would like to know whether Asian countries' FDI inflows are more brawny or brainier.The ratio of female to male enrollment rates in primary schools is the first indication.For secondary schooling, the second indicator is constructed in the same way.For tertiary education, the third indicator is constructed in the same way.The tertiary education gap favors high-skilled labor because university education is coupled with some vocational training in some nations.As mentioned previously, we also test for the inequality in the health hypothesis.The ratio of female to male life expectancy at birth is used to calculate the health gap indicator (Brzozowski, 2013).All variables were taken from the World Bank's World Development Indicators database.Our research spans the years 1991 to 2018.There are 43 Asian nations for which we have data.Appendices 1 show the descriptive statistics for each variable.

RESULTS AND DISCUSSION
The impact of gender disparity characteristics in the education and health sectors on attracting FDI in Asian nations, as well as the significance of other control variables, is investigated.We used the GMM approach to estimate our empirical model since a lagged dependent variable on the right side of the equation causes OLS estimators to be inconclusive.We estimate a baseline model with only the control variables in column (1) of Table 1.We introduce our four proxies of gender inequality discussed in the preceding section, namely the primary education gap, secondary education gap, tertiary education gap, and gender health gap, in order from columns (2) to (5).The control variables have the predicted indications in general, but only a few are significant.As expected, the lagged value of FDI is a good predictor of present FDI.Furthermore, the coefficient's value is positive and smaller than 1, ensuring the stability of our models.The GDP coefficients are positive and highly significant in all models.This finding shows that foreign investors in these nations seek a vast, rapidly increasing market, verifying the market-seeking or horizontal FDI hypothesis.This result is supported by Demirhan & Masca (2008), Busse &Nunnenkamp (2009), andBrzozowski (2009).The proxy of GCF is another control variable with consistent importance across models.FDI is influenced by capital formation in a positive and significant way.Foreign investors want to invest in countries with a robust capital market, as Jordaan (2004) highlighted because a strong capital market means better production potential across models.FDI is influenced by capital formation in a positive and significant way.Foreign investors want to invest in countries with a robust capital market because a strong capital market means better production potential (Jordaan, 2004).A healthy capital market could show the government's commitment to creating a favorable investment climate.Moreover, a strong capital market can help firms reduce production costs, such as transportation and communication costs (Akalpler & Adil, 2017).
In Table 1, columns (2), (3), and (4), we present three proxies for measuring gender inequality in education: the female to male enrolment rate in primary, secondary, and postsecondary education.In terms of the findings, both the primary and secondary educational gap variables have a negative sign, which is consistent with Blanton & Blanton (2015), but with lesser explanatory power than Busse & Nunnenkamp (2009).A negative indication suggests that foreign investors are less inclined to invest in countries where male and female education levels are significantly different.Xu et al. (2021) conclude that there is a negative relationship between FDI and income inequality.The coefficients for the primary and secondary educational gaps, on the other hand, are insignificant, while the coefficient for the tertiary educational gap has a positive sign.Ben Saâd & Assoumou-Ella (2019) state that public spending on education will reduce gender inequalities at all levels of education.The composition of FDI inflows is to blame for the poor explanatory power.Both vertical and horizontal inflows characterize FDI inflows in the Asian area.Foreign investors also invest in a number of industries, ranging from low-skilled manufacturing to high-skilled factoring, as well as extractive and service industries.There are industries that desire brawny labor, while others prefer brainy labor.Vahter & Masso (2019) highlights that foreign owned firms substantially larger gender wage gap than domestic owned firms.Blanton & Blanton (2015) show that the educational gap is minor in the extractive and highly skilled manufacturing sectors but large in the services sector.Choi & Greaney (2022) find that MNEs bring their home countries' gender norms in employment with them.Anyanwu (2016) state that FDI inflows positively associated with gender equality in youth employment.Pantelopoulos (2022) conclude that female participation in the workforce will attract FDI.On contrary, Baliamoune-Lutz (2007) conclude that globalization and growth does not have an impact on gender equality in non-SSA developing countries.Besides that, Bogliaccini & Egan (2017) state that FDI in services is more likely to be associated with inequality than FDI in other sectors.
We look into the impact of health disparities on FDI inflows and publish our findings in Column 5. Large health disparities between men and women make the host country less appealing to foreign investors, resulting in lower FDI inflows.There could be a number of reasons for this: Efficiency-seeking foreign investors would be unable to benefit from a sick labor force.Previous research has demonstrated that greater disparities in health and a wider health gradient can reduce aggregate labor output (Grimm, 2011).The result of Grimm (2011) is unaffected by the direct effect of unequal mortality on labor force composition.With this research, it is clear that foreign investors would benefit from a healthy labor force in terms of productivity.Employee health would improve, reducing absenteeism and thereby increasing productivity.Another reason why foreign corporations may ask their staff to perform brawn-intensive work.Taken as a whole, it can be argued that foreign investors favor a labor force with an equal quality of health between male and female employees.

CONCLUSION
FDI plays such a vital role in fostering economic activity, most governments place a high priority on obtaining it.We used a traditional approach to develop an empirical model and use ratio of female to male enrolment rates in primary, secondary, and tertiary education, as well as the ratio of female to male life expectancy at birth, as proxies of gender inequality.We find that educational and health difference has explanatory power in attracting FDI.Foreign investors are attracted to host nations that have narrowed the gender health gap.FDI takes advantage of parities in economic and political rights between men and women and uses them as a weapon to boost their productivity.These findings have significant important for policy formulation.A higher level of education will affect the economy of a country.The authorities in Asian region should focus on formulating policies to reduce the education and health gap to attract more foreign investment and thereby foster economic development.The government needs to build education and health facilities in all regions, including rural areas