Digitalisation and the labour force gender …...• CATO Institute Human Freedom Index ‒State control of the Internet ‒Access to foreign information Data 12 Department of the

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Department of the Prime Minister and Cabinet

Digitalisation and the labour force gender participation gap in the Indo-Pacific

Timothy WatsonDepartment of the Prime Minister and Cabinet7 February 2018

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1. Research questions

2. Background

3. Modelling approach

4. Data and estimation

5. Results

6. Policies to bridge the digital gender divide

7. Conclusions

8. Future work

Overview

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This paper seeks to address two main questions:

1. What is the relationship between female workforce participation and the digital economy in the Indo-Pacific?

2. What policies can countries in the Indo-Pacific prioritise to help women more fully share in the benefits of the digital economy?

Research Questions

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DomesticThe Australian Government is undertaking a range of actions focused on increasing women’s participation in the future of work. These include:• Towards 2025: Women’s Workforce Participation Strategy: “Jobs

of the future” package• National Innovation and Science Agenda: “Women in STEM”

package• Innovation and Science Australia (ISA) 2030 Report:

Recommendation 25- Maintain a long-term policy commitment to achieving greater gender diversity in the science, technology, engineering and mathematics workforce, including by raising awareness of gender diversity in government programs.

Background

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International • G20 2014 “25 by 2025” commitment: A legacy of Australia’s 2014

G20 Presidency was the Brisbane commitment to reduce the gap between male and female labour force participation rates by 25 per cent by 2025

• G20 Bridging the Digital Gender Divide Initiative: G20 Digital Ministers in April 2017 agreed take actions to support the equitable participation of women in the digital economy

‒ G20 Digital Economy Taskforce under Argentina’s Presidency has taken up this work in 2018, supported by the OECD

• Gender Equality and Women’s Empowerment Strategy and $55 million Gender Equality Fund

• $43 million Investing in Women initiative• International Cyber Engagement Strategy• Funding ILO and OECD research on women and the future of

work

Background

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Chart 1: Female-male participation ratio, per cent

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Chart 2: Female-male participation ratio by Indo-Pacific country, 2000 to 2015

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Chart 3: Female-male participation ratio by region and income, per cent

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Chart 4: ICT connectivity by region

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Panel dummy regression model

𝐹𝐹𝐹𝐹𝑅𝑅𝑖𝑖𝑖𝑖 = 𝛼𝛼 + 𝛽𝛽0 � 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝑅𝑅𝐼𝐼𝐼𝐼𝐼𝐼𝑖𝑖𝑖𝑖 + 𝛽𝛽1 � 𝑍𝑍𝑖𝑖𝑖𝑖 + 𝛾𝛾𝑖𝑖 + 𝛿𝛿𝑖𝑖 + 𝜀𝜀𝑖𝑖𝑖𝑖

• 𝐹𝐹𝐹𝐹𝑅𝑅𝑖𝑖𝑖𝑖 is the female labour force participation rate for country i in period t

• INTERNETit is internet use as a proportion of the population which acts as our indicator of digital activity

• 𝑍𝑍𝑖𝑖𝑖𝑖 is a vector of control variables• 𝛿𝛿𝑖𝑖 and 𝛾𝛾𝑖𝑖 are time and country dummy variables to control for time

and country specific fixed effects

Model

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• World Bank‒ Female labour force participation ‒ GDP per capita‒ Fertility‒ Female life expectancy‒ Education spending (% total government spending)‒ Trade share (% of GDP)‒ Agricultural share (% of GDP)‒ Services share (% of GDP)

• International Telecommunications Union‒ Internet usage

• CATO Institute Human Freedom Index‒ State control of the Internet‒ Access to foreign information

Data

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Data

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Data

Female part.

Internet use

GDP/capita

Trade share

Life expec.

Fertility rate

Education Ag. share

Services share

Female participation 1.00

Internet use 0.07 1.00

GDP/capita 0.14 0.77 1.00

Trade share 0.07 0.19 0.15 1.00

Life expectancy 0.02 0.80 0.64 0.16 1.00

Fertility rate -0.20 -0.60 -0.45 -0.28 -0.70 1.00

Education 0.11 -0.11 -0.05 0.14 0.08 0.05 1.00

Ag. Share 0.23 -0.72 -0.59 -0.17 -0.77 0.55 -0.01 1.00

Services share -0.17 0.37 0.22 0.07 0.62 -0.35 0.14 -0.40 1.00

Table 2: Correlation matrix

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• The model was estimated using the Prais-Winsten technique with panel corrected standard errors (PCSEs)

‒ PCSEs are robust to contemporaneous correlation and heteroscedasticity between panels, and first order serial autocorrelation within panels

Estimation

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Results – female participation

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• There is a statistically significant and positive relationship between Internet use and female participation that is relatively stable between model specifications

• The increase in Internet use between 2000 and 2015 is associated with between a 1.2 and 2.4 percentage point increase in the female participation. ‒ Equivalent to between around two-thirds and one and

one-third of the increase in the female participation rate. • Larger positive impact than GDP/capita, education and

fertility. • However, offsetting effects- For example, increase in life

expectancy associated with a 2.6 to 3.4 percentage point decline in participation over the period.

Results

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• Why is Internet use good for female participation?‒ Access to information that challenges traditional ideas about role

of women in society. ‒ Supports higher levels of services, part-time, flexible and home-

based employment.‒ Speeds up tech/knowledge transfer ‒ More efficient search and matching in the labour market.‒ Related productivity increases combined with changing attitudes

to women in the workforce mean higher demand for female workers.

» World Bank (2009): 10 percentage point increase in internet use is associated with a 0.77 (1.12) percentage point increase in GDP growth in high (low and middle-income countries).

» Digital Mismeasurement?

Results

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Results – female/male ratio

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• Increases in internet usage are related to between 40 and 75 per cent of the increase in the female-male participation ratio.

‒ Lower than for female participation models as expected. » Digitalisation also good for male participation.

• Trade positive in half models, but economically insignificant.• Fertility rates appear to have a stronger impact on closing the gap

between female and male participation. • Education spending has no impact, potentially because unequal

representation no longer a driver of differences in education spending.

• Ag. share no longer significant. Agriculture’s share is a predictor of higher levels of female participation, but women are not disproportionately represented in the agricultural sector (on average) relative to men.

Results

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• To formally assess causation, we need to find instruments that are strongly related to increases in internet use, and unlikely to directly affect female participation rates.

‒ Variables representing Internet freedom should be strongly positively correlated with Internet use, and not correlated with female participation.

‒ Further, variables reflecting state control over traditional media sources, such as access to foreign newspapers and television channels, should be negatively correlated with internet use, and not correlated with female participation.

Causation

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• CATO Human Freedom Index includes subindexes representing “state control over Internet access”, and “access to foreign information” in the form of foreign newspapers and television channels.

‒ A score of 10 under each sub-index represents the highest degree of Internet or media freedom, and zero the absence of freedom.

‒ Unfortunately this information is only available for 2008 and the 2010-2014 period, with small sample sizes exacerbating the loss of estimation efficiency of two-stage least squares estimation.

Causation

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• Results suggest a positive and significant causal relationship between internet use and female labour force participation in the Indo-Pacific region, at least since 2008

• Instruments jointly significant in first stage regression, and satisfy overidentification test of instrument validity in second stage regression

• Parameter estimates for internet use are actually higher under 2SLS estimation‒ However different sample. Could be that Internet use has

become more important relatively recently.

Results

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• So Internet use appears to have had a positive impact on female workforce participation in the Indo-Pacific

• However, still serious issues about unequal representation of women in the digital economy globally:

• 250 million fewer women online than men in 2016 (ITU, 2016)• 1.7 billion women in low and middle income countries do not

own a mobile phone (GSMA, 2015)• women make up fewer than 20 per cent of the ICT workforce;

9 per cent of ICT sector CEOs; and only 6 per cent of app developers (ITU 2016)

• Despite this, less than 50 per cent of countries include relevant references, actions and goals to address gender equality in national digital strategies (Australian Government, 2017).

Policies to bridge the digital gender divide

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Conceptual Framework• Overarching issues• Access• Skills and entrepreneurship• Norms• Evidence

Policies to bridge the digital gender divide

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• National digital strategies and policies should:‒ Incorporate a gender perspective that addresses women’s

needs, circumstances, capabilities and preferences‒ Where necessary, include gender equality targets for

Internet and broadband access and use (Connect 2020 Agenda Target 2.5.A)

‒ Mainstream the application of formal gender impact analysis to all new digital policy proposals

‒ Leverage existing private sector and civil society initiatives to promote access to infrastructure and skills where these have proven to be effective.

Overarching issues

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Data• The free flow of data online is a critical enabler of participation in global value

chains, and opportunities for trade and employment in the future of work• The same rights that apply online should apply offline

‒ Freedom of expression and privacy rights are critical enablers of digital participation.

Infrastructure• Open and competitive markets for digital infrastructure• Direct funding or provision where there is market failure• Universal service obligations

‒ However, careful design crucial to avoid being counterproductiveAffordability • Most efficiently addressed through the tax and transfer system• Digital connectivity should be viewed as an essential service when considering

welfare adequacy and consumer protections such as financial hardship provisions

Access

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• Include coding and other digital skills in school curricula while fostering creativity, and the development of interpersonal and uniquely human skills

• Increase female Computer Science graduates‒ See Building, Recruiting and Inclusion for Diversity (BRAID)

Initiative commitments ‒ Voluntary single sex introductory classes (Booth, Cardona

Sosa and Nolen, 2013) • Promote initiatives such as the Athena SWAN (Scientific Women’s

Academic Network) Charter that promote gender equality and diversity in STEM fields

• Support lifelong learning (SkillsFuture)• Encourage female digital entrepreneurship (NEIS, We-Fi)

Skills and entrepreneurship

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• Promote positive female role models • Ensure human rights and the rule of law apply online as offline. • Review and reform of national legislation on violence against women to

include technology-related forms of violence• Enact and enforce laws that make it illegal to use the Internet to

threaten, harass or offend, and cooperate in international enforcement• Support risk-based policy interventions that aim to lower the probability

of cybercrime against women taking place, and reduce impact of these crimes on victims

• Ensure IR laws support non-discrimination principles and flexible work practices

• Ensure tax, transfer and childcare systems encourage participation of low income and secondary income earners

• Support higher levels of female representation in leadership

Norms

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• Sex-disaggregated ICT statistics• More regular time-use surveys for more developed economies• Make the digital economy visible in macroeconomic statistics • Address mismeasurement concerns• Collect labour market data for contingent work arrangements and

‘gig’ employment

Evidence

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• Labour force participation gap in the Indo-Pacific has been narrowing at a time of rapid growth in Internet usage and digital connectivity

• Statistically significant correlation between internet usage and female participation between 2000-15 robust to a number of controls‒ Evidence of a statistically significant causal relationship

between 2008-2014• Despite this, a number of barriers remain which are preventing

women from fully participating in the digital economy• The G20 Taskforce on Digitalisation is focused on addressing the

access, skills, normative and evidentiary barriers to higher levels of female participation in the digital economy, and better job quality for women in the future of work

Conclusions

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• We have results for all countries (including high, middle, and low income splits), G20 and OECD countries‒ So plenty of scope for further analysis

• Modelling improvements?• What additional policy actions should we be

advocating to help bridge the digital gender divide?

Future work/ questions

Documents

Digitalisation and the labour force gender …...• CATO Institute Human Freedom Index ‒State control of the Internet ‒Access to foreign information Data 12 Department of the