Transcript Document

SESSION 2
Gender, Poverty Reduction, and
Economic Growth:
Why Address Gender Inequalities?
SESSION GOAL: Understand the links between
gender, poverty reduction, and economic growth
• Definitions and Concepts
• Part 1: Macroeconomic Evidence
• Part 2: Regional Evidence
DEFINITIONS AND CONCEPTS
• Factors of production: land, labor, capital and technology
• Gender equity: refers to a fair distribution of resources and
opportunities not necessarily outcomes (e.g. access to land,
education, information, finance, mobility, employment, household
decision-making)
• Capabilities: refers to what people can actually do and be, and is
not income based (Sen)
• Efficiency approach: seeks to maximize economic returns (e.g.
WB)
• Social justice perspective: measures well-being and equity
under human rights principles (e.g. HDR).
PART 1
The Macroeconomic Evidence
MACROECONOMIC EVIDENCE
Gender Equity and Growth Linkages: A Framework Model
Gender equity and shared growth: A simple model
Increased gender equality in households, markets and society
Women have better
access to markets
Women have
better
education and
health
Increased women’s labor force
participation, productivity and earnings
Differential savings rate
Income/consumption
expenditure
Current poverty reduction and
economic growth
Mother’s greater control over
decisionmaking in household
Improved children’s well- being
Better health and
educational
attainment & greater
productivity
as adults
Future poverty reduction and
economic growth
5
MACROECONOMIC EVIDENCE
Economic Models
• Cobb-Douglas—Macro
• Solow Growth Model—Macro/Industry-Sector level
• Computable General Equilibrium/Social Accounting
Model—Micro/Household level
• Sen Capabilities Approach—Micro
MACROECONOMIC EVIDENCE
Average annual GDP per capita
growth rate 1997-2004 (in percent)
MACROECONOMIC EVIDENCE
10
8
6
4
2
0
-2
-4
0.6
0.7
0.8
0.9
1
2
R = 0.1376
-6
Female-to-male ratio in HDIs, 1997
1.1
Poverty headcount ratio (in percent)
Poverty line: US$2/day
MACROECONOMIC EVIDENCE
100
90
80
70
60
50
40
30
R2 = 0.4287
20
10
0
0.6
0.7
0.8
0.9
Female-to-male ratio in HDIs, 1997
1
1.1
MACROECONOMIC EVIDENCE
Digging Deeper
• Serious issues with cross-country growth
regressions—gender equity affects growth but growth
also affects gender equity—not definitive
• Solow Model has some problems handling
augmented data
• Greater gender equity in resources (e.g. education,
access to employment) can reduce likelihood of the
household being poor
10
MACROECONOMIC EVIDENCE
Gendered Computable General Equilibrium
• “Engendered macroeconomics is the totality of paid and unpaid
activities for provisioning human being” (Cagatay et al.1995;
Grown et al. 2000, Nelson 1993, Beneria 2003 and Power 2004)
• Measure gender inequities in the parameters: consumption,
investing, savings, education labor force participation
• Arndt and Tarp and Fontana and Wood (2000) were the first to
use CGE models to differentiate labor by men and women
• Model can link back to household level expenditure and time
utilization data to account for unremunerated work
MACROECONOMIC EVIDENCE
GENDER CGE (continued)
Recent Gender CGE Models utilize Sen’s capability
approach to measure improvements in well being or
social justice to:
– Focus on distribution fairness, equity in meeting needs,
elimination of poverty and discrimination, strengthened
social cohesion, and human capacity
– Highlight the division of resources and tasks within the
household
– Raise awareness of the value of unpaid work and constraints
and costs imposed on women
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MACROECONOMIC EVIDENCE
Clearer Results, But Mixed Impacts
– Growth from privatization of public services may widen
gender gaps if prices rise because women are less able
to afford the cost (Berik et al. 2009)
– Export promotion may increase growth but cause
downward pressure on wages which will affect labor
and gender wage gap (Berik et al. 2009)
– Trade Liberalization in Sub-Saharan Africa in the 1990’s
led to greater gender literacy inequities (BaliamouneLutz 2007).
– Women’s education is important in raising labor
productivity (Knowles et al. 2002)
– Lower average education rates for women may lead to
slower growth, less investment, and greater population
growth (Klasen 2002)
PART 2
Regional Evidence of Gender and
Growth:
Kenya, Uganda, and Tanzania
REGIONAL EVIDENCE
Country Case Studies as a Tool
• Provide contextual information—the gendered
development path of a country and the links to
changes in gendered well-being
• Comparative evaluation of country studies can
identify similar outcomes and situations that can be
used to build and test formal macroeconomic models
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REGIONAL EVIDENCE
Women in the Economy
Tanzania:
• 80% participation by women in the labor force
• 43% of entrepreneurs are women
• less than 20% of women own land
Uganda:
• Women perform nearly 75% of all crop related labor
• Women are paid on average 3.5 times less than men
16
REGIONAL EVIDENCE
Education
Kenya:
•
Long-run growth rate is about 1 percentage point less than high
performing Asian economies from 1960 to 1992 due to the fact women
did not complete as much schooling on average as men (Klasen 2002)
Tanzania:
•
If female/male ratio in years of school increased toward parity, for every
tenth gain, growth would be .068 percentage points higher (Klasen and
Lamanna 2003)
Uganda:
•
Removing gender inequities in education and formal sector
employment could lead to 2 percentage points of growth a year (Klasen
1988; Blackden and Bhanu 1999)
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REGIONAL EVIDENCE
Time Poverty
• Time constraints such as nonmarket work (e.g.
processing food crops, collecting water and firewood,
and caring for sick and elderly)
• Women spend three times as much time as men on
transport activities carrying four time the volume
• Ugandan and Kenyan women work as much as 3 to 4
hours more per day than men
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REGIONAL EVIDENCE
FINDINGS
•
Gender Inequalities in Access to Inputs Reduce Yields
– Moock (1976) proposed that if female maize farm managers had the same
access to services and inputs as men, their yield would be 7 to 9% higher
– Quisumbing (1996) estimates yields for female farmers would increase 22%
if they had equal access to inputs. This would have nearly doubled the
Kenya growth rate in 2004 (pg105 GEG in Kenya 2007)
•
Gender Inequalities in Education Reduce Growth
– Conclusive evidence that gender gaps in educational attainment account for
1/6 of the slower growth in output between sub-Saran Africa and East Asia.
Much higher in some other regional comparisons.
•
Capital Mobility and Trade Liberalization Reduce Women’s Wages
– Country case studies show the effect of capital mobility and trade
liberalization have depressed wages in export industries which
disproportionally affect women’s wages.