women leading growth: an empirical analysis on the effects of women in leadership positions on gdp

UBC

ECONOMICS 490:

SEMINAR IN APPLIED ECONOMICS RESEARCH ESSAY

WOMEN LEADING GROWTH

An Empirical Analysis on the Effects of Women in Leadership Positions on GDP

Avril Espinosa-Malpica December 9, 2016

SUMMARY The likes of Angela Merkel, Hillary Clinton, Christine Lagarde, and Sheryl Sandberg demonstrate that women are more than capable to lead. Yet when it comes to positions of power, women still remain largely underrepresented. Beyond the morality of gender inequality, excluding women from top leadership positions diminishes the potential for economic growth. This paper hypothesizes that increasing the share of women in top management positions in the private sector and in elected government positions in the public sector leads to an increase in GDP per capita. The study uses panel data to estimate a generalized least squares regression. It finds that increasing women leadership by 1% in the private sector increases countries’ GDP per capita by 0.037%. The results are robust and have a 0.1% significance level. The results of women leaders in the public sector are inconclusive.

Vancouver School of Economics University of British Columbia

Vancouver, BC

UBC ECONOMICS 490 : SEMINAR IN APPLIED ECONOMICS │ RESEARCH ESSAY

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Women

Leading Growth

AN EMPIRICAL ANALYSIS ON THE EFFECTS OF

W OMEN IN LEADERSHIP POSIT IONS ON GDP

Avril Espinosa-Malpica

INTRODUCTION

The likes of Angela Merkel, Hillary Clinton, Christine Lagarde, and

Sheryl Sandberg demonstrate that women are more than capable to lead. Yet, when it

comes to positions of power, women still remain largely underrepresented. In June

2016, only 22.8 per cent of all national parliamentarians were women (UN Women

2016). Similarly, in the private sector, women made up only 24 per cent of senior

management roles in 2016 (Grant Thornton (2016); pg. 2). Beyond the morality of

gender inequality, excluding women from top leadership positions diminishes the

potential for economic growth. This paper hypothesizes that increasing the share of

women in top management positions in the private sector and in elected government

positions in the public sector leads to an increase in GDP per capita.

Over the last century, the changes in social and gender norms have led to an increase

participation of women in the labour force (Goldin 2006). This has been one of the

most significant changes in the labour market. In the developed world, female labour

has contributed more to global GDP than new technology or the new corporate giants

(The Economist 2006). While this change has allowed women to substantially

contribute to the economy, a glass ceiling remains that must be removed in order to

continue seeing substantial economic returns from female labour. Capitalizing on

AVRIL ESPINOSA-MALPICA │ DECEMBER 9, 2016

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women’s labour by reducing the gender gap could lead to a 12 per cent increase of

GDP by 2030 among OECD countries (OECD (2012); pg. 30).

Currently women are an under-utilised resource in top leadership positions. To achieve

the best results, the best people must lead – skills sets rather than gender should

determine hiring decisions. By excluding women from top level leadership positions,

governments and firms may be missing out on hiring the most qualified candidates if

they are not male. Unrestricting leadership to both genders fully expands the pool of

talent and labour force. Women’s talent is reflected by their education. In G20 nations,

25 to 34-year-old women are more likely to have completed a post-secondary degree

than men of the same age (OECD (2012); pg. 100). Opening top tier positions to

women would result in an increase in workers, which can increase productivity if they

bring specialized skills to job that were previously missing. Possible short-term

negative effects may arise when women replace current male workers in leadership

positions who are less skilled. This would negatively affect the individuals being

replaced, as they would become unemployed. According to the neo-classical labour

supply and demand model, this would lead to disequilibrium and a decrease wages as

supply of labour is increased for high-ranking positions, as would be the case when

opening top tier jobs to female workers. However, in the long run due to the flexibility of

the economy, the labour market would adjust. Those unemployed would move into

other sectors of the economy where there is a demand for labour and their skill level is

better utilized. For society as a whole, this would be beneficial as the aggregate labour

supply would be fully exploited and distributed according to skillsets, thereby

maximizing efficiency. This would generate further economic gains and contribute to

economic development.

The choices of female leaders could also impact GDP. Studies show that female

politicians are more likely to spend money on improving health, education,

infrastructure and poverty instead of on military (The Economist 2006). In the private

sector, women demonstrate skills such as organizational effectiveness, which can be

positive for the bottom line (UN Women 2016). By contributing different viewpoints and

characteristics to the organization, women help organizations innovate and develop in

different ways. Studies also show that a diverse team creates more creative, more

diligent and harder-working groups (Phillips 2014) (Dezsö and Ross 2014). Diversifying

gender is hence important as including women in leadership position could lead to

different and possibly better outcomes that would not necessarily be considered by a

homogenous team of men.


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These theories show plausible explanations for the positive economic contributions of

women in leadership hypothesized in this paper. This study is relevant because

understanding factors of economic development, such as female leadership, is

important to achieve global economic growth and global prosperity. This paper will use

data from fifty-four countries over a period from 1998-2014 to determine the effects of

women leaders in the public and private sector on the economy and contribute to the

economic development and gender parity literature.

LITERATURE REVIEW

Gender equality has long been a focus of research for economists. Many have

researched the effects of women in the labour force at a broad level, more recently

focused on women in top tier positions. The literature tends to differentiate between

the effects of women in the public and private sector, given the different implications of

the work, and thus this paper also analyses women in each sector as a separate

variable. The literature is generally in accordance and indicates that women leaders

have positive effects on their organization and society, which is in line with the

hypothesis. There is also literature that outlines differences in leadership styles

between men and women, which would account for the outcomes of mixed gender

teams.

At a broad level, Goldin (2006) analyses how a current revolution and past evolutions

of women’s increased involvement in the economy has affected the labour market. The

transition from evolution to revolution is linked to the change from jobs to careers, a

distinction marked between a need to earn wages and employment becoming part of

one’s identity. This in turn affects both horizon (if a woman perceives her job to be long

or short term) and human capital investment. To measure this change in labour

participation, the paper uses US Population Census from 1890 to 2004. By looking at

income elasticity, labour supply, and utilizing an economics history approach, Goldin

(2006) analyses the four stages of development in women’s involvement in the labour

market. The paper shows that over the past century female rate of participation in the

labour market has increased and that since 1990 the participation rate of married

college graduate in their thirties has stabilized at 76% (Goldin (2006); pg. 14). Given

that in the past women’s entrance into the labour market has been the main driver of

labour supply growth, the plateau would imply that the labour market supply in general

is stabilizing. This indicates that participation in the labour force has possibly peaked


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and that future advancements in the female labour force would need to occur from

within, meaning women’s career choices will need to change and improve. To continue

seeing returns due to women in the workforce, women need to pursue higher skill level

and wage positions.

In the private sector, Flabbi et al. (2014) hypothesizes that women’s under-

representation among executives has negative effects on productivity and welfare. To

test its hypothesis, the paper uses data from Italian automobile manufactories firms

with at least 50 employees between 1982 and 1997 from three sources. This comes

from the Bank of Italy’s annual survey of manufacturing firms (INVIND), the National

Social Security Institute (INPS) which provides the work histories of all workers ever

employed at an INVIND firm, and the Company Accounts Data Service (CADS) which

contains balance-sheet information on industry, location, sales, revenues, value added

at the firm-year level, and a firm identifier. Flabbi et al. (2014) uses joint two-way fixed

effects regressions and finds that placing females in top corporate jobs causes firms to

increase their sale per worker by 14.2%, which in turn increases profits, if the firm has

at least 20% of female workers employed (Flabbi et al. (2014); pg. 30). The paper

attributes this positive relation between female leadership and economic gains to

female CEO’s insight into female workers’ productivity, which creates a more efficient

workforce. Further analysis remains to be done to determine if female CEOs give

preferential treatment to female employees, which would be another explanation for

why female leaders affect the wages and productivity of female employees. Dezsö and

Ross (2012) also analyse economic gains in private firms, it hypothesizes that female

representation in top management positions brings informational and social diversity to

the top management team, enriches behaviour of managers throughout the firm, and

motivates women in middle management. The paper uses 15 years of panel data on

the top management teams of the S&P 1,500 firms, from the S&P’s ExecuComp

database, to run a fixed effects time series regression. The results are that a

company’s value is 1.19% higher with female representation in top management than

without it (Dezsö and Ross (2012); pg. 1080). This is particularly true in firms with a

strategy focused on innovation, as the paper finds also finds a correlation of 0.32

between female representation and innovation intensity (Dezsö and Ross (2012); pg

1079). The study indicates that further work needs to be done in examining the type of

women that make it to the top management team. Since it is significantly more difficult

for women than for men to reach the top of the corporate ladder, questions remain

about whether the results obtained are due to the possibility that the women that do

make it are exceptionally hard and thus must be even better than their male counter


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parts. Introducing gender quotas, despite evidence that women are beneficial, could

deter companies from hiring women as they may wary of losses. Niederle, Carmit and

Vesterlund (2013) analyses whether or not introducing gender quotas affects team

performance and how costly these quotas are. To test if affirmative action has an

effect, this study ran an experiment and collected data using 42 male and 42 female

subjects from the Harvard Business School’s Computer Lab for Experimental

Research pool. To test the hypothesis, the research conducted a tournament entry

model with team variations on gender, gender winning quotas, and knowledge of the

quotas. Niederle, Carmit and Vesterlund (2013) finds that by introducing a gender

quota there are no significant losses, as reflected by the winning earnings of female

participants. The standard tournament yields an average score by winners of 19.2,

while the gender quota tournament yields 18.7 (Niederle, Carmit and Vesterlund

(2013); pg. 7). This is not a significant difference suggesting that including a gender

quota does not reduce the earnings of winners. This implies that introducing gender

quotas does not lower the skill level of applicants and thus the costs to firms. The

paper recommends further research into the long-term effects of increased gender

parity. In particular, research needs to be conducted to test if gender parity increases

mentorship opportunities for women and changes the perception of women’s ability to

hold high-ranking positions.

In the public sector, Clots-Figueras (2012) analyses Indian state governments and the

impact that female politicians have on the education levels of the people from their

constituency. To test its hypothesis, Clots-Figueras (2012) uses data from the Election

Commission of India state legislatures from 1967-2001, which provides observations

for 29,686 politicians in 16 states. The observations indicate candidates’

characteristics and election results. Data from the National Sample Survey data (NSS)

is also collected to determine the level of education of individuals in each constituency

from 1999-2000. Clots-Figueras (2012) estimates an OLS regression and finds that

increasing female representation in politicians by 10% increases the probability that an

individual will get an elementary school education in urban areas by 7.3% (Clots-

Figueras (2012); pg. 229). This shows an improvement of human capital through

education, as a result of increasing female leadership in the public sector, which leads

to economic gains. Clots-Figueras (2012) cites that in urban areas, an educated

woman earns 3.5 times as much as an uneducated one, while men earn 1.9 times as

much if they are educated. The paper indicates that further studies remain to be done

to analyse the reasons behind this effect. Possible causes could be that female

politicians’ care more about education spending than male politicians or that female


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politicians act as role models which incentivise young women to further their education.

Holman (2014) also analyzes the role of women leaders in the public sector. It

hypothesizes that increasing the percentage of women on the city council has a

positive effect on the city’s participation and funding of social welfare programs. Data

from 300 US cities with a population of 5,000 or more is drawn from the US Census

Bureau. As well, the Center for American Women in politics provides data about the

sex of city leaders to determine the level of female representation in 2007.

Furthermore, by obtaining and coding each of the 2008 budgets of cities studied, the

paper measures the city’s level of welfare funding. By using a logistical regression, the

study finds that when city councils U.S. municipalities are made up of at least 30%

female councillors, significant effects on social welfare programs funding takes place –

at this level, $10 per capita is budgeted towards social welfare programs (Holman

(2014); pg. 710). The findings of Holman (2014) could further explain the effects

female politicians have on development as a result of the policies they enact. Since the

effect of female city councillors on social welfare, funding is truly noticeable only when

the council is made up of at least 30% female councillors, studies remain to be done

on how critical mass works. Questions remain as to why a substantial amount of

female representatives is necessary for substantial effects on social welfare funding,

and why a linear growth proportionate to the growth of female leaders elected is not

seen.

Post (2015) and Beaman et al. (2009) analyze the capabilities of women leaders. Post

(2015) studies whether teams with female leaders are more cohesive and cooperative

than those with male leaders. Data is collected through surveys by the Industrial

Research Institute, which compiled information about teams and their performance.

Through a hierarchical linear modeling OLS regression, Post (2015) finds that female

leadership is linked with cohesion on larger and more functionally diverse teams and

with cooperative learning and participative communication on larger and

geographically dispersed teams. This demonstrates that there are certain female

leadership characteristics that have a greater effect than men in team relations and

thus productivity. Beaman et al. (2009) analyses how exposure to female leaders

improves the perception of their abilities, which weakens the stereotype of females

being unable to be proper leaders due to gender. For the paper, data is collected from

the Indian state of West Bengal, where village councils consist of elected councillors of

which one third of the seats are for females due to a gender quota. To evaluate

changing attitudes towards women in leadership, the authors conduct a survey. A

regression framework is used to analyse the data. Their findings indicate that exposure


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to at least one female Pradhan (high level official) as result of gender quotas strongly

reduce male villagers’ bias in the perception of female leadership abilities after two

election cycles (Beaman et al. (2009); pg. 1499). This demonstrates that the glass

ceiling women face is not a result of their abilities but of the perception of their abilities.

The implications are that introducing gender quotas has an impact on mitigating voter

discrimination.

This paper contributes to the existing literature by analysing the effects of women

leaders at a global level, which is a sample not previously analysed in recent years as

far as it is known. While this might pose limitations, as the results will not clearly show

how women work in and react to the different environments each country and industry

might present, it should demonstrate general trends of women leaders in the world.

The hypothesis in this paper is in line with previous studies and expects that women

leaders will have a positive correlation with output.

DATA

To test this paper’s hypothesis, the following panel data is used to estimate the

long run growth accounting regression. The data is transformed using the natural log

due to the non-linear relationship between the variables used. Annual data covering

182 countries between 1950 and 2014 is gathered from the Penn World Tables 9.0

database (Feenstra, Inklaar and Timmer 2015). This data provides the dependent

variable gdppc, which is a measure of countries’ real GDP at constant national prices

per capita, transformed using the natural log. This is measured in millions of dollars at

the 2011 United States’ dollar price. The following explanatory variables are acquired

using the Penn World 9.0 database (Feenstra, Inklaar and Timmer 2015). The growth

rate of population year-on-year is measured using the variable growthpop. This

measures the growth rate of the labour force. The index of human capital, ihc, reflects

the increased efficiency of labor based on the years of schooling and returns to

education. The share of merchandise exports current purchasing power parity, sme,

measures the country’s openness to the international market. The variable gcf is gross

capital formation. This measures the net additions to the capital stock of a country, at

current purchasing power parity.

To measure the effects on GDP by women in leadership positions, two explanatory

variables from other sources are retrieved. The data on the share of women leaders in

the public sector, gfs, is gathered from the Inter-Parliamentary Union (IPU) (1990-


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2016). This data covers a period of 27 years from the years 1990 to 2016, inclusive, for

189 countries. It reflects the percentage of parliamentary seats in a single or lower

chamber held by women, which indicates women who are in the highest leadership

positions in the public sector. Members usually win the seats measured in these data

in general parliamentary elections. Seats may also be filled by nomination,

appointment, indirect election, rotation of members and by-election. The data on the

share of women leaders in the private sector, pfs, is gathered from the International

Labour Organization Statistics (ILOSTAT) (1998-2014). This data covers a period of 17

years from the years 1998 to 2014, inclusive, for 68 countries. It shows the percentage

of women in total employment in senior and middle management roles in large

enterprises and institutions. This measurement reflects women who have decision-

making and management responsibilities in the private sector. To visualize the

relationships between the dependent variable gdppc and the explanatory variables of

interest to the hypothesis, pfs and gfs, scatter plot graphs can be seen in Graph 1 and

Graph 2. These graphs represent data from the years 1998 to 2014 and include a fitted

values line.

Graph 1


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Graph 2

Once the data from the three sources is compiled, 509 observations from 54 countries

remain to be used in this study as panel data. The data covers a period of 17 years

from the years 1998 to 2014, inclusive. The following tables show a summary of the

data used in the panel regression (Table 1) as well as the means of each country’s real

GDP and share of women leaders in the public and private sectors (Table 2).

Table 1

Summary of Data Number of observations 509

Variable Mean Std. Dev. Min Max

gdppc - Real GDP per Capita (in mil. 2011US$)

21562.22 13347.82 741.838 51218

pfs - Share of Women Leaders in the Private Sector

0.1822279

0.1043843 0.018 0.473

gfs - Share of Women Leaders in the Public Sector

0.2829444

0.105459 0.02095 0.589625

growthpop - Logged Population Growth Year on Year

0.6441342

0.9454918 -3.36685 2.11953

gcf - Gross Capital Formation at Current PPs

0.2293829

0.0606038 0.087084 0.504507

ihc - Index of Human Capital Per Person

2.840015 0.5727749 1.23469 3.71755

sme - Share of Merchandise Exports

0.3229921

0.242167 0.022493 1.394


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Table 2

Summary of Observations by Country

Country Name

Mean Real

GDP (in

millions of

dollars at 2011

USD price)

Mean Share

of Women

Leaders in

Public Sector

Mean Share

of Women

Leaders in

Private

Sector

Number of

Observations

Algeria $404,155.00 0.0660153 0.1185 4

Argentina $537,290.29 0.28330401 0.31485714 7

Australia $818,002.55 0.33534482 0.23136363 11

Bangladesh $344,786.00 0.14387795 0.1085 2

Belgium $375,120.87 0.31800867 0.29593333 15

Bolivia $39,746.78 0.28698433 0.16133333 9

Botswana $19,997.50 0.324785 0.13083334 6

Brazil $2,457,142.90 0.35259428 0.08714286 7

Cambodia $16,400.00 0.1319125 0.074 2

Canada $1,281,365.10 0.36044435 0.2127647 17

Colombia $503,401.50 0.53280202 0.1055 2

Costa Rica $42,228.36 0.28936929 0.30200001 14

Cyprus $20,359.23 0.15601961 0.11953846 13

Czech Republic $236,051.60 0.26937054 0.166 15

Denmark $232,346.00 0.24186557 0.37435714 14

Dominican Republic

$88,877.29 0.33464985 0.17907143 14

Egypt $671,104.23 0.10448615 0.02969231 13

El Salvador $40,622.87 0.307507 0.1492 15

Ethiopia $78,972.33 0.192908 0.237 3

France $2,193,333.30 0.36577594 0.139 15

Germany $3,180,000.00 0.28059007 0.31213333 15

Greece $284,127.50 0.26266993 0.11264285 14

Hungary $190,154.27 0.354039 0.09553333 15

India $3,200,000.00 0.14585751 0.0865 2

Indonesia $1,960,000.00 0.21111 0.1554 5

Iran (Islamic Rep of)

$1,125,000.00 0.1434265 0.03775 4

Israel $160,953.67 0.27490208 0.12858334 12

Italy $2,071,428.60 0.25645157 0.14071429 14

Latvia $31,359.08 0.40747 0.1875 12

Lithuania $51,194.31 0.41292976 0.17292308 13

Madagascar $27,595.50 0.2359375 0.122 2


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Malaysia $433,043.00 0.2369302 0.0992 10

Mauritius $16,240.50 0.20953833 0.133 6

Mexico $1,533,333.30 0.25195633 0.19683333 12

Mongolia $18,687.00 0.48551574 0.06025 4

Morocco $187,603.00 0.1198718 0.1068 5

Nepal $43,391.67 0.13492977 0.15 3

Netherlands $675,973.40 0.2608856 0.37340001 15

Pakistan $631,147.57 0.0267191 0.21457143 7

Philippines $412,238.13 0.57405674 0.175375 8

Republic of Korea

$1,124,835.80 0.0653166 0.08491667 12

Romania $289,522.57 0.30064379 0.10185714 14

Russian Federation

$2,811,111.10 0.38307489 0.11133333 9

Slovakia $93,083.27 0.3139068 0.16533333 15

South Africa $610,023.75 0.30507775 0.40525001 4

Sweden $344,545.87 0.30864433 0.4448 15

Syrian Arab Republic

$123,862.33 0.09233167 0.12266666 3

Thailand $756,208.00 0.26466563 0.11045455 11

Turkey $1,045,491.20 0.0827629 0.06466667 9

U.R. of Tanzania

$63,361.00 0.3280125 0.2635 2

Ukraine $440,717.14 0.39764685 0.07 7

United Kingdom $2,006,666.70 0.33919973 0.19146667 15

United States $15,090,909.00 0.42706737 0.16436364 11

Viet Nam $232,825.00 0.19292667 0.2665 6

Mean $1,045,787.3 0.28294438 0.1822279 Total 509

Potential weaknesses of this data are that a leadership position may not necessarily

reflect a woman’s ability to contribute to the decision making process. These share

indicators may not be sufficient because some women may face obstacles in being

able to fully and efficiently carrying out their roles. This may occur due to cultural or

social barriers, both of the institution and of the county. In this case, the presence of

women in leadership may not have an effect on GDP as their role would be more

symbolical than active. Additionally, within the public and private sector there are sub-

categories, such as different industries and governmental systems, which may respond

differently to women in leadership. Further studies would need to be conducted to

determine if women in leadership are better suited to more specific roles beyond the

general public and private sector areas analyzed here.


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EMPIRICAL ANALYSIS

In its augmented Solow model, Mankiw, Romer, and Weil (1992) finds that the

steady-state level of income increases when savings rate and investment in human

capital are increased and it decreases when population growth rate is increased.

While it is able to account for a large portion of factors influencing GDP, the analysis

does not account for all the growth in GDP per capita. To explain unaccounted sources

of GDP growth, this paper expands on the augmented Solow model done by MRW

(1992) by analysing the effects of additional variables, women in leadership roles. This

paper uses the following time series regression to estimate the effects of the variables

on GDP. It is estimated by using the following generalized least squares regression.

𝑌𝑖,𝑡 = 𝛽0 + 𝛽1 ln(𝑔𝑓𝑠𝑖.𝑡) + 𝛽2 ln(𝑝𝑓𝑠𝑖,𝑡) + 𝛽3 ln(𝑔𝑟𝑜𝑤𝑡ℎ𝑝𝑜𝑝𝑖,𝑡)

+ 𝛽4 ln (𝑔𝑐𝑓𝑖,𝑡

) + 𝛽5 ln(𝑠𝑚𝑒𝑖,𝑡) + 𝛽6 ln(𝑖ℎ𝑐𝑖,𝑡)

+ ∑ ∝𝑠

𝑁

𝑆=2𝐶𝐶𝑆1 + ∑ ∝𝐽

𝑁

𝐽=2𝑇𝐹𝐽2 + 𝜖𝑖,𝑡

Where, for country i and year t: Y is real gdp per capita, gfs is

female’s share of women leaders in the public sector, pfs is

female’s share of women leaders in the private sector,

growthpop is the growth rate of population, gcf is gross capital

formation, sme is the share of merchandise exports, ihc is the

index of human capital, ∑ ∝𝑠𝑁𝑆=2 𝐶𝐶𝑆1 is the country code

dummy to control for serial correlation and country fixed effects,

∑ ∝𝐽𝑁𝐽=2 𝑇𝐹𝐽2 is time fixed effects, ∈ is the residuals, and 𝛽0 is

the constant. All variables are calculated using the natural log

due to the non-linear relationship between them.

The following pre-regression tests were conducted to test the appropriateness of the

model and correct for any issues. Using a Hausman test it was determined that the

fixed effects regress is appropriate. The appropriate test found that multicollinearity is

not present. To test for serial correlation between the independent variables, the

Wooldridge test was used. The test indicated the presence of serial correlation. To

correct for this, a country dummy variable was introduced to the model. A modified

Wald test concluded that there was heteroskedasticity in the model. Robustness was


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included in the model to correct for heteroscedasticity. Data was also checked for

residuals. This found that 34 observations had residuals larger than the absolute value

of two. These outliers were dropped. Finally, a kernel density estimation determined

that the probability density function of residuals was normal. After choosing the

appropriate model and correcting for residuals, the following results in Table 3 are

obtained to estimate for the dependent variable, gdppc.

Table 3

Independent Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

b/se b/se b/se b/se b/se b/se

gfs 0.172*** 0.079* 0.072* 0.069* 0.036 -0.026

(-0.04) (-0.03) (-0.03) (-0.03) (-0.03) (-0.02)

pfs

0.199*** 0.182*** 0.143*** 0.129*** 0.037***

(-0.02) (-0.02) (-0.02) (-0.01) (-0.01)

growthpop

-0.162*** -0.136*** -0.133*** -0.023

(-0.03) (-0.03) (-0.02) (-0.02)

gcf

0.363*** 0.299*** 0.265***

(-0.03) (-0.02) (-0.02)

sme

0.183*** 0.096***

(-0.02) (-0.01)

ihc

2.313***

(-0.11)

constant 9.745*** 9.861*** 9.972*** 10.551*** 10.775*** 7.921***

(-0.05) (-0.05) (-0.05) (-0.06) (-0.06) (-0.15

Year fixed effects Yes Yes Yes Yes Yes Yes

Number of obs 509 509 509 509 509 509

* p<0.05, ** p<0.01, *** p<0.001 Standard errors are notated in parentheses

The results from Table 3 are used to estimate the following regression.

ŷ𝑖,𝑡 = 7.921 − 0.026 ln(𝑔𝑓𝑠𝑖.𝑡) + 0.037 ln (𝑝𝑓𝑠

𝑖,𝑡) − 0.023 ln (𝑔𝑟𝑜𝑤𝑡ℎ𝑝𝑜𝑝𝑖,𝑡)

+ 0.265 ln (𝑔𝑐𝑓𝑖,𝑡) + 0.096 ln(𝑠𝑚𝑒𝑖,𝑡) + 2.313 ln(𝑖ℎ𝑐𝑖,𝑡)

The results indicate a 0.1 percent significance level for female leadership in the private

sector and no significance for female leadership in the private sector. This indicates

that countries that increase women leaders by 1% in the private sector grow their GDP

by 0.037%. In Canada, increasing female leadership in the private sector by 1% would

lead to a GDP growth of fifty-seven billion three hundred sixty-nine million USD (at


[15]

current US$).1 This is close to the total GDP earned in Canada by the Educational

Services industry, the eleventh largest industry out of the twenty main sectors in the

Canadian economy.2 This reflects potentially significant gains for the country if it

enacts policies that encourage an increase in the share of women in leadership

positions in the private sector. These results show evidence that maximizing the labour

pool of talent by allowing women to serve in top leadership positions in the private

sector has positive benefits, which the companies stand to profit from. This is in line

with the results of Flabbi et al. (2014), Dezsö and Ross (2012), and Niederle, Carmit

and Vesterlund (2013). As well, these results might indicate that women do have

different beneficial attributes that contribute to productivity, as found in UN Women

(2016), Phillips (2014) and Dezsö and Ross (2014).

The effects of female leadership in government are not significant in this regression

and therefore no conclusions can be drawn on how it affects GDP. However further

studies could be done to explain the potential negative effects women leaders in

government may have on GDP, indicated by the negative coefficient. In particular

research should be conducted to determine how democracies affect the role of women

in government, given that the countries with the highest female representation in

parliament are Rwanda with 64% of women, followed by Bolivia at 50% and Cuba at

49% (Inter- Parliamentary Union 2016). All of these three countries score low on the

2015 Democracy Index (The Economist Intelligence Unit 2015), so there appears to be

a correlation between high share of female leaders in government and low levels of

democracy. This correlation should be further analysed as it could be distorting the

results of this study, in regards to the effects of women in government on GDP, which

may be positive in democratic countries.

CONCLUSION

The recent 2016 presidential election in the United States has reignited the

debate over women’s leadership abilities. Historically women have faced greater

barriers than men when it comes to fully participating in the economy, particularly in top

1 Based on Canada’s 2015 GDP of 1.55 trillion USD (measured in current US$) (World Bank

1966-2015). 2 Based on a 1.33USD conversion rate, 0.037% of the Canadian GDP obtained from the World

Bank 1996-2015 equals to approximately $76 billion CAD. Statistics Canada (2010-2014) indicates that the GDP of the Educational Services Industry in 2014 was $ 84.639 billion CAD. Given that from 2013-2014 the GDP of the Educational Services Industry was decreasing it is estimated that two years later it has continued to decrease and thus is approximately the closest industry in GDP to the estimated change in GDP if the share of women in the private sector increased by 1%.


[16]

leadership positions. While numbers of female leaders in the public and private sector

are slightly growing, the full benefits of the female labour force have yet to be obtained.

To analyse the potential impact that women could have, it was theorized in this paper

that increasing the share of women in top public and private sector positions leads to

an increase in GDP per capita. The results are partially consistent with the hypothesis.

This paper finds that increasing women leadership by 1% in the private sector

increases countries’ GDP per capita by 0.037%. The panel data regression results are

robust and have a 0.1% significance level. The results of women leaders in the public

sector were inconclusive.

This evidence is consistent with research done on women leaders in the private sector.

However, there remains varying degrees of expected growth in the private sector

within the literature which may be a result of the different types of industries analysed

and the role of women leaders within these subcategories. Flabbi et al. (2014) finds

that in Italian automobile manufactories, having women in top corporate jobs causes

firms to increase their sale per worker by 14.2% for firms that have at least a 20%

female workforce (Flabbi et al. (2014); pg. 30). This is attributed to women CEO’s

increased awareness of female workers’ productivity which in turn creates a more

efficient workforce. Dezsö and Ross (2012) also finds a positive correlation between

economic gains and female representation in top management positions. The paper

argues that female leadership brings informational and social diversity to the top

management team, enriches behaviour of managers throughout the firm, and

motivates women in middle management. This leads to a 1.19% increase in the

company’s value, particularly in firms with a strategy focused on innovation (Dezsö and

Ross (2012); pg. 1080). The implications of the results from the literature and this

study are that firms should promote female leadership to increase their own growth.

The effects of female leadership in the public sector are not statistically significant in

this study and therefore no conclusions can be drawn. The difference in the public and

private sector may be explained by institutional constraints women face in the non-

democratic governments, where the share of women leaders in the public sector is the

highest. This may misrepresent the data as there are other factors at play in institutions

that contribute to economic decline and share of women in power. The three countries

with highest female representation are Rwanda with 64% of women, followed by

Bolivia at 50% and Cuba at 49% which also have low levels of democracy (Inter-

Parliamentary Union 2016) (The Economist Intelligence Unit 2015). The negative and

insignificant results differ from the literature. The studies conducted in Clots-Figueras


[17]

(2012) and Holman (2014) took place in India and the United States respectively,

which rank well in terms of democracy according to The Economist Intelligence Unit

(2015). These studies would thus be reflective of the positive attributions female

leaders in the public sector have in GDP in democratic countries. Additional work

remains to be done in this subject to explain how different governmental institutions

affect the role of female leadership in the public sector.

The case for gender equality has long been argued, the suffragette movement

asserted women’s roles to be beyond those of child-rearing and taking care of the

home. ‘Because it is 2016’3, many would argue we are now beyond such debates and

gender parity should be mainstreamed and universally accepted. Yet the fact remains

that the gap persists in top leadership positions. This paper analyses empirically that

the case for morality is supplemented by the economic gains. In a time where

resources are scarce and economic development an international topic, reflected by

the UN’s Sustainable Development Goals for example, exploiting this readily available

human capital resource is an empirically sound choice. Half the population is set to

contribute; women can lead growth.

3 On November 4, 2015, Canadian Prime Justin Trudeau stated “Because it’s 2015” as an

explanation for his newly formed gender equal cabinet. This highlighted the importance of gender parity in the modern era.


[18]

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women leading growth: an empirical analysis on the effects of women in leadership positions on gdp

Economy & Finance