Gender and the Dynamic Gains from Trade John Cockburn

Bernard DecaluwéIsmaël Fofana

Véronique Robichaud

Poverty and Economic Policy (PEP) Research Network and CIRPÉE (Université Laval)

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.

Manila, 9 December 2008

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?

Today’s presentation Overview Literature Model:

Salient characteristics Labour disaggregation Growth channels

Simulation Results

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.

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.

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.).

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:

User’s price of capital:

Equilibrium:

Household capital accumulation:

i,t+1 i,t i,tKD =KD 1-δ +INDKiσ

i,t i,ti

i,t t

IND r=φ

KD U

t t tU =PK × ir +δ

i t i,tI

IT =PK × IND ,

, 1 , 1h t

h t h tt

SHKH KH

PK

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).

Labour Disaggregation

Output

Value added

Material inputs

(Leontief)

Composite factor

Unskilled workers

(CES)

Rural

Urban

Female

Male

Male

Female

Skilled workers

Capital

Rural

Urban

Female

Male

Male

Female

(CES)

(CES)

(CES)

(CES)

(CES)

(CES)

(CES)

Growth channels Openness and TFP (competition, diffusion):

VAi

VAi

VAi

1

tiVAiti

VAiti

VAiti KLQ1LNQAVA

,,,,

Foreign savings and openness/returns to capital:

0

0 0 0 0 0 0

/

/

FSOFSR

t t tt tt t

IM EX GDPrmoy PINDEXCABCAB GDP

GDP rmoy PINDEX IM EX GDP

Growth channels (cont)

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

Household savings and returns to capital:

th00tt

hth YDHPINDEXrmoy

PINDEXrmoySH

HSh

,,

Simulation Complete and unilateral trade liberalization;

Public deficit held constant as a share of GDP through an endogenous compensatory sales tax;

Initial tariffs:

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

Ghana Honduras Senegal 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 -0.5All 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

Gender impacts Variation in Gender Wage Gap:

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)

Gender impacts (cont.)

Ghana Honduras Senegal UgandaYear 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 0.6Skilled 0.1 0.1 0.1 0.0 -0.3 -0.4 -0.3 -0.5All 0.2 0.4 -0.1 -0.2 1.1 1.4 0.8 0

No TFPUnskilled 0.6 0.6 -0.4 0.1 1.5 1.3 -0.1 -0.1Skilled 0.2 0.3 0.0 -0.1 -0.1 0 0 -0.2All 0.3 0.5 -0.2 -0.2 0.9 1.1 0 -0.3

Variation in Gender Wage Gap:

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)

Gender impacts (cont.) Variation in Gender Wage Gap:

Ghana Honduras Senegal UgandaYear 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 0.6Skilled 0.1 0.1 0.1 0.0 -0.3 -0.4 -0.3 -0.5All 0.2 0.4 -0.1 -0.2 1.1 1.4 0.8 0

No TFPUnskilled 0.6 0.6 -0.4 0.1 1.5 1.3 -0.1 -0.1Skilled 0.2 0.3 0.0 -0.1 -0.1 0 0 -0.2All 0.3 0.5 -0.2 -0.2 0.9 1.1 0 -0.3

Growth channels

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

Variation in GDP relative to BAU (final period):

The openness-TFP channel dominates

The investment price channel is also important

The foreign and household savings channels are much smaller

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

Other results

Impact on wages (%)Ghana Honduras Senegal Uganda

First Last First Last First Last First LastRural – 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 0.7Urban – 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 2.9Total Male -1.7 0.8 -1.2 0.7 -3.1 0.5 Total Male 0.0 1.7Rural – 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 -0.5Urban - 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 3.3Total Female -1.9 0.4 -1.1 0.9 -4.2 -0.9 Total Female -0.8 1.7

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

Other results

Impact on wages (%)Ghana Honduras Senegal Uganda

First Last First Last First Last First LastRural – 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 0.7Urban – 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 2.9Total Male -1.7 0.8 -1.2 0.7 -3.1 0.5 Total Male 0.0 1.7Rural – 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 -0.5Urban - 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 3.3Total Female -1.9 0.4 -1.1 0.9 -4.2 -0.9 Total Female -0.8 1.7

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: MS≤0.1; XS≤0.31)

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)