Gender and the Dynamic Gains from Trade John Cockburn Bernard Decaluw

1
Gender and the Dynamic Gains from Trade John
CockburnBernard DecaluwéIsmaël FofanaVéronique
RobichaudPoverty and Economic Policy (PEP)
Research Network and CIRPÉE (Université Laval)
Manila, 9 December 2008
Our thanks to Maurizio Bussolo, André Martens and
Rafael de Hoyos for comments and suggestions. We
also thank Erwin Corong for excellent research
assistance. Funding for this study was provided
by the World Bank-Netherlands Partnership Program
(BNPP) and the Poverty and Economic Policy (PEP)
research network, which is financed by the
Australian Aid Agency, the Canadian International
Development Agency and the International
Development Research Centre.
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Motivation

• Continuing trade liberalization in developing
  countries (unilateral, regional and global trade
  reform)
• Dynamic gains from trade thought to be much
  larger than the comparative static resource
  re-allocation effects generally examined in CGE
  models
• Static effects are known to differ, often
  substantially, by gender.
• What are the gender (as well as the sectoral and
  distributive) impacts of trade liberalization in
  the presence of dynamic gains?

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Todays presentation

• Overview
• Literature
• Model
• Salient characteristics
• Labour disaggregation
• Growth channels
• Simulation
• Results

4
Overview

• Ghana, Senegal, Uganda and Honduras
• Sequential dynamic CGE model
• Gender-disaggregated labour market
• Unilateral trade liberalization (revenue-neutral)
• Growth mechanisms
• Increased openness raises TFP
• Increased openness and returns to capital raise
  foreign investment
• Increased returns to capital raises household
  savings.

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Literature Trade and Gender

• Women benefit more in (semi-)industrial economies
  (female intensity of export-oriented sectors)
• Elson and Pearson (1981) Standing (1989) Wood
  (1991) Cagatay and Ozler (1995) Joekes (1995
  and 1999) Ozler (2000 and 2001)
• Men may benefit more in agricultural sectors and
  economies (female intensity of subsistence
  agriculture)
• Gladwin 1991 Fontana et al 1998
• Female labour market participation may come at
  the expense of their leisure time
• Labour market participation increase female
  income share and, possibly, intra-household
  bargaining power This may favour children, but
  may also deprive them of home care.

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Literature Trade and Growth

• Cross-country analysis some debate
• Positive Dollar (1992), Ben-David (1993),
  Sachs-Warner (1995), Edwards (1998), Baldwin
  (2003), Warner (2003), Cline (2004),
  Aksoy-Salinas (2006)
• No relationship Rodrik and Rodriguez (1999)
• Openness increases TFP
• Competition, technology diffusion, import
  availability, rationalization, etc.
• Melitz (2003), Bernard et al. (2003), Helpman et
  al. (2004), Baldwin and Robert-Nicoud (2006), and
  Gustafsson and Segerstrom (2007)
• Openness and FDI
• Trade and factor flows are, in theory,
  substitutes (factor-price equalization)
• Less clear in the absence of identical production
  functions and in the presence of economies of
  scale, market imperfections, factor distortions,
  impediments to trade and factor intensity
  reversals (Markusen and Svensson, 1985 de Melo
  and Grether, 1997, etc.).

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Model Salient Characteristics

• CGE model TL (and growth) is a big and complex
  shock with GE effects
• Sequential dynamic to capture growth effects.
• Capital accumulation
• Investment by sector
• Users price of capital
• Equilibrium
• Household capital accumulation

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Model Salient Characteristics (cont.)

• Labour market
• Categories (8) male/female, rural/urban,
  skilled/unskilled (next slide)
• No mobility between categories no
  migration/training (or sex changes!)
• Full intersectoral mobility (conditioned by
  initial shares)
• Exogenous labour supply and fixed unemployment
  (future research)
• Senegal No skill decomposition in rural areas
  (treated as unskilled workers)
• Uganda No rural/urban decomposition, but
  elementary workers distinguished from unskilled
  workers (in low-skilled composite labor).

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Labour Disaggregation
Male
(CES)
Rural
Unskilled workers
Female
(CES)
Male
Urban
(CES)
Value added
(CES)
Female
Composite factor
Capital
Male
(CES)
(Leontief)
Output
(CES)
Rural
Skilled workers
Female
(CES)
Material inputs
Urban
Male
(CES)
Female
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Growth channels

• Openness and TFP (competition, diffusion)

• Foreign savings and openness/returns to capital

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Growth channels (cont)

• Household savings and returns to capital

• Fall in the cost of investment (importable
  capital goods).

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Simulation

• Complete and unilateral trade liberalization
• Public deficit held constant as a share of GDP
  through an endogenous compensatory sales tax
• Initial tariffs

Ghana Ghana Honduras Senegal Uganda
Primary 8.2 6.7 7.1 5.2
Industrial 7.3 5.7 16.7 25.2
Services 0.0 0.0 0.0 0.0
TOTAL 6.2 4.6 13.6 18.8
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Gender impacts

• Variation in Gender Wage Gap

Ghana Ghana Honduras Honduras Senegal Senegal Uganda Uganda
Year 1 Year 15 Year 1 Year 15 Year 1 Year 15 Year 1 Year 15
Unskilled 0.3 0.3 -0.3 0.0 1.7 1.4 1.6 0.6
Skilled 0.1 0.1 0.1 0.0 -0.3 -0.4 -0.3 -0.5
All 0.2 0.4 -0.1 -0.2 1.1 1.4 0.8 0

• Overall, trade liberalisation increases gender
  gap in African countries
• Greater increase among unskilled workers
• No clear rural/urban pattern
• Male workers are employed more intensively in the
  expanding export-oriented sectors export crops,
  mining
• Whereas female workers are employed more
  intensively in import-competing sectors
  subsistence agriculture and livestock.
• Opposite in Honduras

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Gender impacts (cont.)

• Variation in Gender Wage Gap

Ghana Ghana Honduras Honduras Senegal Senegal Uganda Uganda
Year 1 Year 15 Year 1 Year 15 Year 1 Year 15 Year 1 Year 15
Unskilled 0.3 0.3 -0.3 0.0 1.7 1.4 1.6 0.6
Skilled 0.1 0.1 0.1 0.0 -0.3 -0.4 -0.3 -0.5
All 0.2 0.4 -0.1 -0.2 1.1 1.4 0.8 0
No TFP No TFP No TFP No TFP No TFP No TFP No TFP No TFP No TFP
Unskilled 0.6 0.6 -0.4 0.1 1.5 1.3 -0.1 -0.1
Skilled 0.2 0.3 0.0 -0.1 -0.1 0 0 -0.2
All 0.3 0.5 -0.2 -0.2 0.9 1.1 0 -0.3

• The openness-TFP effect contributes to the rise
  in the gender gap (except in Ghana)
• In its absence, the gender gap evolves more
  favourably
• Women are relatively more intensively employed in
  the sectors that experience the greatest increase
  in openness (import-competing sectors)

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Gender impacts (cont.)

• Variation in Gender Wage Gap

Ghana Ghana Honduras Honduras Senegal Senegal Uganda Uganda
Year 1 Year 15 Year 1 Year 15 Year 1 Year 15 Year 1 Year 15
Unskilled 0.3 0.3 -0.3 0.0 1.7 1.4 1.6 0.6
Skilled 0.1 0.1 0.1 0.0 -0.3 -0.4 -0.3 -0.5
All 0.2 0.4 -0.1 -0.2 1.1 1.4 0.8 0
No TFP No TFP No TFP No TFP No TFP No TFP No TFP No TFP No TFP
Unskilled 0.6 0.6 -0.4 0.1 1.5 1.3 -0.1 -0.1
Skilled 0.2 0.3 0.0 -0.1 -0.1 0 0 -0.2
All 0.3 0.5 -0.2 -0.2 0.9 1.1 0 -0.3

• The openness-TFP effect lessens the rise in the
  gender gap in Ghana
• In its absence, the gender gap increases even
  more
• Women are relatively more intensively employed in
  the sectors that experience the smallest increase
  in openness (services)

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Growth channels

• Variation in GDP relative to BAU (final period)

Full NoTFP NoPK NoHS NoFS
Ghana 2.2 0.3 1.7 1.9 2.2
Honduras 1.5 0.2 1.5 1.5 1.2
Senegal 4.0 0.8 2.5 3.6 3.8
Uganda 3.8 1.4 2.3 3.2 3.8

• The openness-TFP channel dominates
• The investment price channel is also important
• The foreign and household savings channels are
  much smaller

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Other results

• Trade liberalization tends to increase
  rural-urban wage gap (pro-urban)

Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages ()
Ghana Ghana Honduras Honduras Senegal Senegal Uganda Uganda Uganda
First Last First Last First Last First Last
Rural Male -1.8 0.6 -1.9 0.1 -5.5 -3.8
- Unskilled -1.7 0.1 -2.0 -0.1 Elementary 0.3 1.1
- Skilled -1.8 1.2 -1.2 0.9 Unskilled 0.1 0.7
Urban Male -1.6 1.1 -1.0 1.0 -2.4 1.8 Skilled -0.2 3.2
- Unskilled -1.6 0.1 -1.1 0.4 -2.8 -1.4
- Skilled -1.6 1.4 -0.9 1.4 -2.2 2.9
Total Male -1.7 0.8 -1.2 0.7 -3.1 0.5 Total Male 0.0 1.7
Rural Female -2.0 0.1 -0.8 0.8 -7.7 -5.5
- Unskilled -2.0 -0.2 -0.7 0.5
- Skilled -1.8 1.0 -1.0 1.4 Elementary -2.0 -0.5
Urban - Female -1.9 0.6 -1.2 0.9 -2.3 1.6 Unskilled -1.3 0.4
- Unskilled -1.9 -0.1 -1.4 0.1 -3.2 -1.6 Skilled 0.1 3.7
- Skilled -1.8 1.2 -1.1 1.3 -1.9 3.3
Total Female -1.9 0.4 -1.1 0.9 -4.2 -0.9 Total Female -0.8 1.7
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Other results

• Trade liberalization tends to increase skill wage
  gap (favours skilled workers especially in the
  long run)

Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages () Impact on wages ()
Ghana Ghana Honduras Honduras Senegal Senegal Uganda Uganda Uganda
First Last First Last First Last First Last
Rural Male -1.8 0.6 -1.9 0.1 -5.5 -3.8
- Unskilled -1.7 0.1 -2.0 -0.1 Elementary 0.3 1.1
- Skilled -1.8 1.2 -1.2 0.9 Unskilled 0.1 0.7
Urban Male -1.6 1.1 -1.0 1.0 -2.4 1.8 Skilled -0.2 3.2
- Unskilled -1.6 0.1 -1.1 0.4 -2.8 -1.4
- Skilled -1.6 1.4 -0.9 1.4 -2.2 2.9
Total Male -1.7 0.8 -1.2 0.7 -3.1 0.5 Total Male 0.0 1.7
Rural Female -2.0 0.1 -0.8 0.8 -7.7 -5.5
- Unskilled -2.0 -0.2 -0.7 0.5
- Skilled -1.8 1.0 -1.0 1.4 Elementary -2.0 -0.5
Urban - Female -1.9 0.6 -1.2 0.9 -2.3 1.6 Unskilled -1.3 0.4
- Unskilled -1.9 -0.1 -1.4 0.1 -3.2 -1.6 Skilled 0.1 3.7
- Skilled -1.8 1.2 -1.1 1.3 -1.9 3.3
Total Female -1.9 0.4 -1.1 0.9 -4.2 -0.9 Total Female -0.8 1.7
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Elasticities

• TFP-openness (Martens, 2008)
• Most focus on (capital) import share (MS) or
  export share (XS)
• Two studies on growth openness, as we define it,
  in South Africa
• Jonsson and Subramanian (IMF Staff Papers, 2001)
  0.34
• Arora and Bhundia (IMF, 2003) 0.74
• We adopt 0.5 (may be too high MS0.1 XS0.31)
• FDI-openness (Martens, 2008)
• Some evidence in favor of complementarity.
  Elasticities
• 0.02-0.06 for African countries
• 0.04-0.065 for Latin American countries
• 0.6-1.7 for Asian countries.
• We adopt 0.04
• FDI-returns to capital (Martens, 2008)
• Weak evidence
• We experiment with 0.5 (no significant impacts)