Economic Development and Gender Equality a Positive or Negative Relationship

7/31/2019 Economic Development and Gender Equality a Positive or Negative Relationship

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Economic Development in Asia Tan Zhiyang, BensonResearch Paper S8308207J

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Economic Development and Gender Equality:

A Positive or Negative Relationship?

You can tell the condition of the nation by looking at the

status of its women. Jawaharlal Nehru

Introduction

It is commonly observed that the status of women in society

is related to socio-economic development. Many measures of

gender inequality support this. Looking at secondary school

education, one can see that for the poorest 25% of countries, only

5% of women has any secondary school education, whilst the

figures are 51% for the richest 25%1. Some have been more

explicit, arguing that economic development can lead to

improvement in gender equality2. Amongst many others, it has

been argued that an increase in per capita income will lead to

greater gender equality3.

However, many others have argued that economic

development has not increased gender equality. Of note is the

feminist school, which argues that economic growth increases the

vulnerability of women to gender inequality4. Which leads to the

question: which of these approaches are correct?

This question is of significant importance. Many studies have

shown that there are many positive effects on improving the


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increasing gender equality, affecting the family, society, the

economy and politics. Higher gender equality can lead to economic

growth through increased output per capita5, increase their

daughters survivals6, and reduces infant and maternal mortality7,

just to name a few.

This paper found that the relationship between economic

development and gender equality is not so clear. In some instances,

it has been found that one approach is supported, while in other

instances another approach is supported . This papers posits that a

generalizable theory between economic development and gender

equality is insufficient, and more research needs to be done to find

out what are the conditions that causes one approach to work in

one instance while causing another approach to work in another

instance.

Literature Review

Contemporary work on the impact development and growth

have on gender equality tends to fall under three schools of

thought. In the first school, called the modernisation-neoclassical

approach,believes that gender equality would improve as a country

develops8. It has been argued that gender equality tends to

improve with economic development, as gender equality in basic

rights decreases as regions of the world get poorer. Others have

suggested that increases in per capita income improve gender


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equality9. Chen postulates that economic development may affect

gender equality through wages. Wages increase with economic

development, which increases the opportunity cost of not working.

Others have stated that economic growth creates an increase in

employment opportunities and competition that would eventually

improve gender equality in education, finance and training10. As

opportunity cost increases, the formerly unemployed would be

compelled to work. In countries where gender equality is low, the

majority of the unemployed are women, thus women in this case

would be compelled to work11. Others have agreed that economic

growth together with increased access to education, health, credit,

legal rights and employment opportunities will increase womens

socio-economic role in developing countries.

A second school of thought is what is called the Boserup

approach, which believes that that economic growth and gender

equality have a relationship in the form of a U shape. Where a

country has no market economy, gender relations are more or less

equal. As growth and development takes place, equality falls initially

due to the specialisation of roles, with womens primary role as that

of childcare and mens as that of a breadwinner. As the economy

develops further, there would be an overall transformation in

society and roles, and the above can be reversed due to increased

economic opportunities and demand for female labour12.


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There is a third school, which raises objections to the above

contentions. This is know as the feminist approach, which believes

that institutions like patriarchal family structures play a major role

in reducing gender equality, and where economic growth is seen as

a factor that increases the vulnerability of women to gender

inequality. It has been argued in Morrison & Jutting that social

institutions constitute the most important single factor that

determines womens economic choices, both directly and indirectly

through their access to education and health care. They cited

evidence that in the Sub-Saharan Africa, South Asia, the Middle

East and North African regions, even as a country might experience

high per capita incomes, it might have low gender equality. In

further support, it shows that even in a same country, disparities in

gender equality exist, supporting that argument that a country can

develop even though gender inequalities persist13.

Contextualised Briefing

As this paper aims to do an Asia-wide study, and because

comparing every single Asian country is beyond the scope of this

paper, the main criteria is to select countries with the widest spread

of politics, geographical area and religious influence.

For political diversity, there are a mix of communist / socialist

and ex-communist / socialist states (China, Vietnam and Laos),

authoritarian and ex-authoritarian states (South Korea, Indonesia


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and Pakistan14), and democracies or quasi-democracies (India,

Japan and Malaysia).

For geographical diversity, there is a mix of East Asia (China,

South Korea and Japan), Southeast Asia (Vietnam, Indonesia, Laos

and Malaysia), and South Asia (India and Pakistan).

For religious diversity, there is a mix of Buddhist / Taoist /

Confucian majorities (Japan and Laos), Muslim (Indonesia, Malaysia

and Pakistan), Hindu (India) and no religion (China, Vietnam and

South Korea15).

Analytical Framework

This paper chooses an empirical approach. Using this, the

paper is able to evaluate whether the different levels of economic

development corresponds with the varying levels of gender

inequality. Moreover, using this approach, this paper is able to

determine whether the strength of economic development

corresponds with an equally strong gender equality increase. An

example would be that 13% economic growth should see a higher

increase of gender equality scores, and 2% economic growth should

see a small increase in gender equality scores.

Next, the nine countries selected will be grouped together

based on the various measure of economic development to

determine which of these measures of economic development

matches corresponds closer with gender equality scores.


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Methodology

One can measure economic development in many ways. This

study would use both the static figures of per capita GDP, per capita

GNI, and proportion of population living below US$1 a day, and the

rates of change of per capita GDP, per capita GNI, and poverty

levels measured as proportion of population living under US$1 a

day, and GDP growth rates. These figures are selected because of

the ease of which they can be obtained.

Measuring gender equality is trickier. The quantitative

approach is to use indices, of which the UNDPs Gender-related

Development Index (GDI) is the most common. However, GDI alone

does not measure inequality; it is merely the Human Development

Index (HDI) adjusted for gender disparities. Gender equality is the

difference between the ratios of the two indicators16. Other ways to

measure gender equality quantitatively are by using education and

employment levels alone as proxies, as it was found that education

and earning independent income from paid employment reduces

anti-female bias and increase female voice and agency in the

home17. Education can be measured by looking at gender

differentials in enrolment rates18 or the access and achievement of

women in education19, amongst others. Employment is usually

measured by finding the female share of the labour force in a

country20. Other quantitative indicators include improvements in

health21.


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There are several criticisms for using just quantitative

measures. First, it has been shown that generally, gender equality

is improving in the world22. This creates problems as any form of

economic development will be correlated with an increase with GDI

scores. Second, the education and employment variables used in

the index are not contextualized and therefore not useful for

meaningful comparison across countries23. It has been argued that

the content of schooling matters24, and that it might require much

higher levels of education before a woman is exposed to ideas and

strategies necessary for questioning gender inequality25. Similarly,

whether gender equality increases after earning independent

income depends on whether they have control over it, and the pre-

existing power balance in the family26.

There are also qualitative measures, but its use is less

universal and limited due to difficulties in getting information and

disagreements on a standard set of measures. This is because

gender equality is a multi-faceted concept that measures many

things. These includes measuring the legal and economic parity of

women in society and marriage27, and measuring constraints like

social institutions through laws, social norms, codes of conduct and

traditions28.

For the purposes of this paper, the difference between HDI

and GDI scores (HDI-GDI) would be used as a proxy score for

gender equality. The main reason is that a comparative analysis


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requires the use of a measure that is easily obtainable. Though the

criticisms of using quantitative measures are strong, comparing

qualitative indicators is unrealistic due to the lack of data and

commonly accepted qualitative measure. Moreover, HDI-GDI scores

are truly global, and other ways of measuring gender equality have

not met universal subscription and have very specific and limited

usage, making it difficult to have any form of meaningful

comparison across countries.

In addition, due to the limitations of this paper, an analysis of

all the quantitative measure universally available is impossible.

Using HDI-GDI helps as it includes the three indicators of income,

education and life expectancy, hence encompassing a more holistic

approach to measuring gender equality.

This paper will circumvent the problem of generally increasing

GDI scores by testing if the intensity of economic development

(higher GDP growth rates, higher per capita increases in GDP and

GNI, higher poverty reduction rates) corresponds with higher

increases in HDI-GDI scores. If economic development does indeed

increase gender equality, then higher rates of economic

development should show a higher increase in gender equality.

For a static comparison, this paper would use per capita GDP,

per capita GNI and poverty levels against HDI-GDI, and grouping

countries according to their economic development indicators

against HDI-GDI. For a comparison based on the rate of change of


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economic development against the rate of change of gender

equality, this paper would use the rate of change of per capita GDP,

rate of change of per capita GNI, and rate of change of poverty

levels against the rate of change of HDI-GDI, and grouping

countries according to their economic development indicators

against the rate of change of HDI-GDI. Lastly, countries would be

grouped according to its political history, religious influence and

geographical areas to see if these factors are related to HDI-GDI.

Data

Historical data for economic development indicators are found

on the United Nations Statistics Division database online. Historical

data for HDI and GDI can be found on the United Nations Human

Development Reports online from 1996 onwards.

The independent variables used are GDP growth rates, per

capita GDP, rate of change of per capita GDP, per capita GNI, rate

of change of per Capita GNI, poverty levels, and rate of change of

poverty levels.

Table 1 shows the GDP growth estimates. As there are no

gender equality data for 1996, the GDP growth estimate for 1996

will be dropped. Hence, the GDP growth estimates for 1997 will be

revised by the formula below.

1996 GDP growth + 1997 GDP growth2

GDP growth estimate for 1997 =


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Table 2 shows the revised GDP growth estimates applying the

formula above.

Table 3 shows the per capita GDP and the rate of change of

per capita GDP in US$. The rate of change of per capita GDP in US$

is calculated as follows:

Rate of change of per capita GDP =

currentyears per capita GDP previous years per capita GDPprevious years per capita GDP

Table 4 shows the per capita GNI and the rate of change of

per capita GNI in US$. The rate of change of per capita GNI in US$

is calculated as follows:

Rate of change of per capita GNI =currentyears per capita GNI previous years per capita GNI

previous years per capita GNI

Table 5 shows the available figures of poverty levels and the

rate of change of poverty levels. The rate of change of poverty is

calculated as follows:

Rate of change of poverty levels =

previous available years poverty levels subsequent available years povertylevels

The dependent variable used is Gender Equality. Table 6

shows the gender equality score and the rate of change of gender

equality for each of the countries chosen. The gender equality

scores would get smaller as gender equality increases in the

country. If the rate of change is positive, it means gender equality

is increasing, and vice-versa. The formulas for calculations are as

follows:

Gender Equality = HDI scores GDI scores


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Rate of change of Gender Equality =

previous years Gender Equality current years Gender Equality

For comparisons of poverty reduction rates and the rate of

change of gender equality, due to the lack of poverty reduction

rates for every year, the rate of change of gender equality is

calculated as follows:

Rate of change of Gender Equality =previous corresponding years Gender Equality subsequent corresponding years

Gender Equality

Analysis of Data

GDP Growth Rates and Gender Equality Scores

Table 7 shows GDP growth rates and the corresponding

gender equality scores for each country each year. Figure 1 shows

the relationship on a scatter plot. The wide dispersal of plots

suggests that there seems to be no relationship between GDP

growth rates and gender equality scores.

Table 8 shows the countries grouped together according to

their GDP growth rates and the corresponding averaged gender

equality scores, and Figure 2 shows the relationship on a line chart.

The results show that for GDP growth rates below 0% and more

than 10%, the averaged gender equality scores are 0.0076 and

0.0060 respectively, whereas for GDP growth rates between 0%

and 10%, the averaged gender equality scores range from 0.0130


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to 0.0194, supporting the Boserup approach that economic

development and gender equality has a U relationship. The U is

inverted in this case as gender equality is measured using zero as

the perfect gender equality

GDP Growth Rates and Rates of Change of Gender Equality

Scores

Table 9 shows the GDP growth rates and the corresponding

rate of change of gender equality scores for each country each year.

Figure 3 shows the relationship on a scatter plot. The tendency of

the plots to remain near the x-axis, and the high instances of

negative rates of change of gender equality scores despite an

increase of GDP growth rates, suggests that there seems to be no

relationship between GDP growth rates and the rates of change of

gender equality scores.


their GDP growth rates and the corresponding averaged rates of

change of gender equality scores, and Figure 4 shows the

relationship on a line chart. Likewise, results suggest that there

seems to be no relationship between GDP growth groups and the

averaged rates of change of gender equality scores.


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Per capita GDP and Gender Equality Scores

Table 11 shows the per capita GDP and the corresponding


the relationship on a scatter plot. The results show that at low

levels of per capita GDP, there is a wide and uniform dispersal of

plots, suggesting that per capita GDP at the low levels does not

affect gender equality. However, at the per capita GDP increases,

the plots are uniformly near the X-axis, except for some outlying

cases, suggesting that generally, as per capita GDP increases,

gender equality would remain low, supporting the modernisation-

neoclassical approach


their per capita GDP performance and the corresponding averaged

gender equality scores, and Figure 6 shows the relationship on a

line chart. The results show that gender equality scores are lowest

when the country is in the upper middle-income bracket, supporting

the Boserup approach that economic development and gender

equality have a U shaped relationship.

Rates of Change of per Capita GDP and Rates of Change of

Gender Equality Scores

Table 13 shows the rates of change of per capita GDP and the

corresponding rates of change of gender equality scores for each

country each year. Figure 7 shows the relationship on a scatter plot.


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The results show that the plots congregate near the X-axis, except

for a few outliers, suggesting that the rates of change of per capita

GDP do not affect the rates of change of gender equality scores.


their rates of change of per capita GDP and the corresponding

averaged rates of change of gender equality scores, and Figure 8

shows the relationship on a line chart. The results show that in

times of negative rates of change of per capita GDP, the rates of

change of gender equality scores is increasing, moving towards 0%.

As the rates of change of per capita GDP increases from 0%, the

rates of change of gender equality scores decreases, to a point

where the rates of change of gender equality scores is negative at

high rates of change of per capita GDP

This suggests that economic development increases gender

equality at a faster rate only at a point when the rates of change of

per capita GDP is negative and rising towards 0%, supporting the

modernisation-neoclassical approach. As economic development

continues from where the rates of per capita GDP is positive and

increasing, gender equality scores increases at a slower rate.

Finally, the rates of change of gender equality scores turns negative

as economic development is at the high stages; when the rates of

change of per capita GDP is more than 20%. This supports the

feminist approach that economic development decreases gender

equality.


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Per capita GNI and Gender Equality Scores

Table 15 shows the per capita GNI and the corresponding


the relationship on a scatter plot. The results show that at low

levels of per capita GNI, there is a wide and uniform dispersal of

plots, suggesting that per capita GNI at the low levels does not

affect gender equality scores. However, at per capita GNI increases,

the plots are uniformly near to the X-axis, except for some outlying

cases, suggesting that generally, as economic development

increases, gender equality remains high, supporting the

modernisation-neoclassical approach.


per capita GNI and the corresponding averaged gender equality

scores, and Figure 10 shows the relationship on a line chart. The

results shows that there is no clear relationship between per capita

GNI and gender equality scores, only that gender equality scores is

highest when the country is in the upper middle-income bracket.

This supports the Boserup approach that economic development

and gender equality have a U shaped relationship.

Rates of Change of per capita GNI and Rates of Change of

Gender Equality Scores

Table 17 shows the rates of change of per capita GNI and the

corresponding rates of change of gender equality scores for each


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country each year. Figure 11 shows the relationship on a scatter

plot. The results show that the plots congregate near the X-axis,

except for a few outliers, suggesting that the rates of change of per

capita GNI do not affect the rate of change of gender equality.


their rates of change of per capita GNI and the corresponding

averaged rates of change of gender equality scores, and Figure 12

shows the relationship on a line chart. The results show that in

times of negative rates of change of per capita GNI, the rates of

change of gender equality is increasing, moving towards 0%. As the

rates of change of per capita GNI increases from 0%, the rates of

change of equality decreases, to a point where the rates of change

of gender equality is negative at high rates of change of per capita

GNI

This suggests that economic development increases gender

equality at a faster rate only at a point when rates of change of per

capita GNI is negative and rising towards 0%, supporting the

modernisation-neoclassical approach. As economic development

continues from where the rates of per capita GNI is positive and

increasing, gender equality scores increases at a slower rate.

Finally, the rates of change of gender equality scores seem to

decrease as economic development is at the high stages; when the

rates of change of per capita GNI is more than 20%. This supports


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the feminist approach that economic development decreases gender

equality.

Poverty Levels and Gender Equality

Table 19 shows the available data for poverty levels for each

country with the corresponding gender equality scores for the year.

Figure 13 shows the relationship on a scatter plot. Results show a

wide dispersal of plots regardless of instances of poverty,

suggesting that poverty levels do not affect gender equality.


their poverty levels and the corresponding averaged gender equality

scores. Figure 14 shows the relationship on a line chart. The group

for poverty levels between 10% to 20% is discarded as there is only

one data point. The results show that as poverty rates decrease,

gender equality scores increases. This supports the feminist

contention that as economic development increases, gender

equality decreases.

Poverty Reduction Rates and Rates of Change of Gender

Equality Scores

Table 19 shows the available data for the poverty reduction

rates each country with the corresponding rates of change of

gender equality scores for each available year. Figure 15 shows the

relationship on a scatter plot. Results show that the plots hover


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mostly above X-axis regardless of the poverty reduction rate,

suggesting that poverty reduction rates do not affect gender

equality.

Table 21 shows the countries grouped together based on

poverty reduction rates and the corresponding averaged rates of

change of gender equality scores. Figure 16 shows the relationship

on a line chart. The results show that the averaged rates of change

for gender equality are negative for both periods of increasing

poverty rates and poverty reduction rates above 20%. This

suggests that economic development increases gender equality

when the rate of change of poverty is moving from negative to a

positive 10% rate, supporting the modernisation-neoclassical

approach. However, when the rate of change of poverty more than

positive 10%, the rates of change of averaged gender equality

scores is negative, supporting the feminist approach.

Summary of Key Results & Conclusion

Table 22 shows the summary of the findings. This paper

shows that all the approaches are supported at one point or

another, and therefore, the verdict of the relationship between

economic development and gender equality is still out. In addition,

whether the relationship supports one of the approaches or none at

all depends on the economic indicators one uses, and on which

stage of economic development one looks at.


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This paper suggests that a generalizable economic theory

explaining the relationship between economic development and

gender equality should not be the end and focus of research in this

area. More research needs to be done to discover why one approach

is supported in one instance but another approach supported in

another.

This paper readily agrees that there are limitations inherent in

this paper. Amongst some of this is the small sample size of nine

countries spread over the breadth of Asia. Future research can

embark on, if the information is available, a sampling all the Asian

countries, or a sampling of Asian countries based on regions,

religions, type of government, or other types of classifications, to

come up with a more generalizable and better supported validation

of the approaches mentioned.

Another possible future research strategy would be to look at

a few individual countries to see why one approach works in one

country but another approach works in another. These strategies

can focus on the institutions of the individual countries and the

effect on gender equality, grouped according to similar experiences

of economic conditions. Examples of research could include legal

institutions and the instances of discriminatory laws against women,

and social institutions affecting economic activities favouring men

over women.


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Notes

1 Dollar, D. & Gatti, R. (1999). Gender Inequality, Income and Growth: Are GoodTimes Good for Women?2 Chen, D. H.C. (2004). Gender Equality and Economic Development: The Role forInformation and Communication Technologies.3 Supra, note (1), at pp. 17.4 Morrison, C. & Jutting, J. (2004). The Impact of Social Institutions on theEconomic role of Women in Developing Countries, at pp. 6 & 8.5 Esteve-Volart, B. (2004), Gender Discrimination and Growth: Theory andEvidence from India.6 Bourne, K. L. & Walker, G. M. Jr (1991), The Differential Effect of MothersEducation on Mortality of Boys and Girls in India.7 UNICEF (undated), Factsheet: Early Marriage, at pp. 1.8 Supra, note (4), at pp. 8. Retrieved on 1st February 2009 from

http://www.oecd.org/dataoecd/23/43/31652310.pdf.9

Supra, note (2), at pp. 11.10 Supra, note (4), at pp. 811 Supra, note (2), at pp. 13.12 Supra, note (4), at pp. 8-9.13 Ibid, at pp. 6 & 8.14 Even though Pakistan is formally a federal republic since its independence in

1947, it has seen military rule three times lasting a total of thirty-three years. Formore information, see Story of Pakistan found onhttp://www.storyofpakistan.com.15 China and Vietnam are officially communist, and hence there is no statereligion. South Koreas official census in 1995 shows 49% of the population

choosing no religion as the answer. However, it is arguable that these countries

experience a strong influence from Buddhism, Taoism and Confucianism throughhistory.16 UNDP. (undated). Measuring Inequality: Gender-related Development Index(GDI) and Gender Empowerment Measure (GEM).17 Mukhopadhyay, S. & Sudarshan, R. M. (1997).Gender Discrimination and its

Indicators: A Research Agenda at pp. 3.18 Supra, note (2), at pp. 5.19 Ibid, at pp. 11.20 Ibid, at pp. 5.21 Ibid, at pp. 11.22 Ibid, at pp. 4.23 Supra, note (17), at pp. 13.24 Ibid, at pp. 3.25 Ibid, at pp. 4.26 Ibid.27 Supra, note (2), at pp. 11.28 Supra, note (4), at pp. 8.
http://www.oecd.org/dataoecd/23/43/31652310.pdfhttp://www.oecd.org/dataoecd/23/43/31652310.pdfhttp://www.storyofpakistan.com/http://www.storyofpakistan.com/http://www.storyofpakistan.com/http://www.oecd.org/dataoecd/23/43/31652310.pdf

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