Agenda

• Development and Gender

• Chattopadhyay and Duflo, 2004

• Interaction Models

Gender and Representation

• Gender gap in political representation

  • Women hold only 27.0% of legislative seats (Inter-Parliamentary Union, 2023)
  • 23% of cabinet positions (UNWOMEN)

• Gender gap in political participation:

  • Disputed gender gap in turnout, large variance

Gender and Development

• Gender and poverty (feminization of poverty to a degree)

• Gender and economic participation

  • Labor force participation gap: 27% globally (ILO, 2023)
  • Gender wage gap (Pew)

• Gender and violence

  • 1/3 women have experienced GBV

• Gender and education

  • Literacy rates: 90% male vs. 83% female globally (World Bank Data, 2022)

  • School attendance gap (UNESCO, 2023)

Gender, Development, and Representation

• The two are undoubtedly related

• But could improving gender representation produce development?

From Representation to development

Why might having more women in office improve development?

Our Expectations

• Different outcomes?
  • Do women prioritize different policy domains?
• Better outcomes?
  • Potential improvements in service delivery and reduced corruption
• Conditionally different outcomes?
  • Effectiveness depends on institutional context
  • Critical mass may be necessary
  • Interactions with other social identities

Empirical Test?

• Seems like a good theory with important implications that we want to validate empirically

• Imagine we have data on share of female legislators and many development outcomes

• We compare places with female politicians to places with male politicians and see development differences

• What is the problem with this?

A (more realistic) DAG

Gender Quotas: What are they?

• Rules requiring minimum women’s representation in politics

• Goal: Improve gender parity in government

• Vary by country, region, and level of government

• Typically set minimum thresholds (20-50%)

Gender Quotas: Types

• Voluntary quotas:
  • Set by political parties themselves
  • No legal enforcement
• Mandatory quotas:
  • Required by law
    • Reserved seats:
      • Specific seats only women can hold
    • Candidate quotas:
      • Parties must nominate certain % of women

Gender Quota Adoption

• Started in 1990s, expanded rapidly

• Now used in about 130 countries

• Most common in newer democracies

• Less common in older democracies (US, Japan)

• Highest representation achieved in Rwanda (61%)

Chattopadhyay and Duflo, 2004

In a nutshell

• RQ: What are the policy consequences of “mandated representation of women”?

• Hypothesis: In reserved villages, there is more investment in goods women prioritize

• Mechanism: Heterogeneous priorities

• Treatment: Village council being randomly assigned to have female head

• Outcome: Investment Decisions

• Data: Sample of Villages

A bit more detail

  \(Y_{ij} = \beta_1 + \beta_2 * R_j + \beta_3 D_i * R_j + \sum_{l=1}^{N} \beta_l d_{li} + \epsilon_{ij}\)

Where:

• \(Y_{ij}\) is an outcome of interest

• \(R_j\) takes the value of 1 if GM is reserved

• \(D_i\) is differences in request about that good (women - men)

• \(d_{li}\) are good Fixed Effects!

Main Findings