Trade Liberalisation and Poverty: What do we know?

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Trade Liberalisation and Poverty: What do we know? L Alan Winters University of Sussex and CEPR 12 June 2003 GTAP Conference 1

Trade Liberalisation generally stimulates growth and through it poverty alleviation BUT it creates losers some of whom may be or become poor 12 June 2003 GTAP Conference 2

What do we know about these latter - static - effects? Conceptual framework Some empirical results from the literature A case-study of Vietnam Growth is probably more important, but Difficult to measure especially with CGE models Most critiques focus on static effects 12 June 2003 GTAP Conference 3

Conceptual Framework Figure 4.2: Trade Policy and Poverty Causal Connections World Prices and Quantities Exchange Rate Tariffs, QRs Tariff Revenue Tariff Revenue Trading Domain Pass through, competition Enterprises Border Price Wholesale Price Taxes, regulation, distributors, procurement Taxes Tradables National Profits Wages Employment Retail Price Distribution, taxes, regulation, co-ops Co-operatives, technology, random shocks Spending Regional males females Welfare Household Welfare Prices, Wages Endowments, Profits, Other Income elderly young Subsistence 12 June 2003 GTAP Conference 4 )

Households and Markets Do border price shocks get transmitted to poor households? Are markets created or destroyed? How well do households respond? Do the spillovers benefit the poor? Does trade liberalisation increase vulnerability? 12 June 2003 GTAP Conference 5

Wages and Employment Does liberalisation raise wages or employment? Is transitional unemployment concentrated on the poor? 12 June 2003 GTAP Conference 6

Government Revenue and Spending Does liberalisation actually cut government revenue? Do falling tariff revenues hurt the poor? 12 June 2003 GTAP Conference 7

Households and Markets first order approximation of the welfare effect W = ( q c ) p i i i i Barrett and Dorosh (1996) Sahn and Sarris (1991) Thomas et al (1999) 12 June 2003 GTAP Conference 8

The Transmission of Border- Price Shocks P m 1 = P r(1 + t ) w m + γ m P w r t m γ m is the world price the exchange rate the proportional tariff or tax and the transaction costs on importables P x 1 = P r(1 t ) w x γ x 12 June 2003 GTAP Conference 9

Are markets created or destroyed Romer (1994) - New technologies - Variety of productive activities and commodities Consumers also benefit from increased availability Discontinuous change de Janvry, Falchamps and Sadoulet (1991) - Non-tradabilities 12 June 2003 GTAP Conference 10

How do households respond I Affects magnitude not sign Production - Farm level data show major constraints - Absence of key productive assets - Capital inputs - Less educated - Poorer quality land - Complementary policies 12 June 2003 GTAP Conference 11

How do households respond II Consumption and Labour Supply Friedman and Levinsohn (2002) Subsistence activities, wage employment, self employment and consumption jointly determined But separability cannot be rejected 12 June 2003 GTAP Conference 12

Do the spillovers benefit the poor? Growth linkages Locally produced non-tradeables are important - Services - Bulky starch items - Perishable foods - Locally processed foods 12 June 2003 GTAP Conference 13

Does trade liberalisation increase vulnerability? Portfolio choice - From subsistence to cash crops - Risk aversion - Fully informed decisions? Variability of existing income sources or prices - Can go up or down with openness - Poor less well insured Poverty traps 12 June 2003 GTAP Conference 14

Wages and Employment Stolper-Samuelson Theorem Reserve Army Model Segmented labour markets Common feature Apparently small wage and employment effects 12 June 2003 GTAP Conference 15

Is transitional unemployment concentrated on the poor? Parallel with OECD countries not valid Little evidence for developing countries Transitional unemployment may be quite long lasting Adjustment costs greater - The more protected the sector - The greater the shock 12 June 2003 GTAP Conference 16

Trade Liberalisation and Poverty: The Empirical Evidence L. Alan Winters, Neil McCulloch and Andrew McKay Working Paper 88 Department of Economics University of Sussex 12 June 2003 GTAP Conference 17

Key External Sector Reforms Relaxation of controls on trade and introduction of Harmonised System of tariffs Regional and multilateral trading agreements Unification of multiple exchange rates into one marketbased exchange rate Relaxation of licensing procedure Phasing out of controls on retention and remittance of foreign exchange Initiation of an open door policy to promote foreign investment 12 June 2003 GTAP Conference 18

Trade indicators Trade as % of GDP Average Tariff Rate 1991 50.9.. 1992 51.9 10.7 1993 52.4 11.8 1994 60.6 12.3 1995 65.4 12.3 1996 74.7 12.9 1997 73.9 13.4 1998 70.5 13.6 1999 79.9 16.3 2000.. 16.2 Source: GSO statistics, CIEM (2001) 12 June 2003 GTAP Conference 19

Real Price Changes 1993-98 Goods / Services Change Goods / Services Change (%)* (%) Mackerel 76.9 Chicken 11.8 Sea shrimps 33.3 Petrol 10.4 Paddy 26.2 Soya beans -3.7 Spring rice 26.1 Pork -4.0 Haircut 16.5 Sugar -6.3 Cotton fabrics 13.8 Woollens -38.0 Source: Calculations based on GSO statistics. Note: * Change between 1993 and 1998. 12 June 2003 GTAP Conference 20

Dynamic Trade Sectors Exports Increase Imports Increase (US$m) (US$m) Footwear 1071 Textiles 633 Garments 773 Electrical 522 machinery and parts Rice 517 General machinery 301 Electrical 503 Iron and steel 301 machinery and parts Coffee 490 Plastic 281 Petroleum 338 Special machinery 268 Seafood 292 Leather 214 Source: Calculations based on World Bank Mirror Statistics Note: Increase between 1993 and 1998. 12 June 2003 GTAP Conference 21

Labour demand per $1 of trade Direct labour coefficients EX93 IM93 NET93 EX98 IM98 NET98 Unskilled 0.1415 0.0859 0.0556 0.1270 0.1009 0.0261 Medium-Skilled 0.0285 0.0330-0.0045 0.0275 0.0313-0.0038 Highly-Skilled 0.0015 0.0027-0.0012 0.0015 0.0027-0.0012 Total 0.1715 0.1216 0.0499 0.1560 0.1349 0.0211 Note: calculations based on adjusted data 12 June 2003 GTAP Conference 22

Multinomial Logit Model The model analyses probability of being in one of 4 possible outcomes: 1. being poor in both periods 2. being non-poor in 1992-93 and becoming poor in 1997-9 3. being poor in 1992-93 and becoming non-poor in 1997-98 4. being non-poor in both periods; is expressed as: j e Prob( Yi = j) = 4 e k = 1 ' β x i ' k β x i, j = 1,2,3,4 Relative Risk Ratios: Ratio of the probability of each outcome relative to the probability of the base category (Y = 1): Pr ob( Y = 2) Pr ob( Y = 1) = e β ( 2 ) x 12 June 2003 GTAP Conference 23

Poverty Dynamics: Non-Trade The following variables were significant in explaining movements out of poverty: Increase probability Decrease probability White-collar occupation of household head Education of household head Spouse educated to technical level Household head being older Access to food shops, electricity, road, clinic Residing in urban area Residing in Central Highlands, South East, Mekong or Red River Deltas Longer period between the two surveys Interviewed in the last quarter of survey Unemployment of household head Having young children Belonging to a non-kinh non- Chinese ethnic group Access to a post office 12 June 2003 GTAP Conference 24

Multinomial Logit Model (RRRs) Prob. of escaping from poverty Prob. of falling into poverty Quantity of rice production ***1.75 *0.51 in Mekong River Delta **0.60 1.51 in Red River Delta **0.85 1.15 Quantity of coffee production ***2.32 1.00 Quantity of fertiliser for rice ***1.46 1.13 Quantity of fertiliser for non-rice *1.70 *0.79 Ratio of household members working in export to no. of adults (1) ***1.25 *1.19 Change in ratio **1.17 1.06 Note: *** significant at 1% level; ** significant at 5% level; * significant at 10% level. (1) The export sector includes seafood, food processing, garment, and shoes (+rubber and plastic products). 12 June 2003 GTAP Conference 25

The Benefits of Modelling Trade without trade variables with trade variables pseudo-r 2 %correct predictions predicted no. in poverty in 1998 (of 4302) (σ) 0.230 59.90 1624 0.266 61.5 1374 (σ) Predictions of number in poverty from preferred equation and from that equation with trade variables co-efficients set at half their estimated values. 12 June 2003 GTAP Conference 26

Trade Liberalisation and Poverty Dynamics in Vietnam Yoko Niimi, Puja Vasudeva-Dutta and L. Alan Winters Working Paper Poverty Research Unit, Sussex (PRUS) March 2003 12 June 2003 GTAP Conference 27

Household Consumption I Regress rice share on: Demographics, geography, ethnicity, infrastructure and seasonality w ht = α t + β t ln x ht + m= 1 γ mt Z mht + u ht 12 June 2003 GTAP Conference 28

Household Consumption II Rice share r D PL income 12 June 2003 GTAP Conference 29

Household Consumption III Rice share r r r D D D PL income 12 June 2003 GTAP Conference 30

Household Consumption IV Rice share r r h D Idiosyncratic element PL income 12 June 2003 GTAP Conference 31

Rice shares Official Basket Mean from VLSS Predicted by equation 1993 0.260 0.271 0.267 1998 0.284 0.200 0.240 12 June 2003 GTAP Conference 32

Differences to Poverty Dynamic With predicted shares: 21 households With predicted shares plus residuals 39 households (<1%) Regression results no change 12 June 2003 GTAP Conference 33

Conclusions The reform process in Vietnam has resulted in significant changes in the economy. Exports and imports have boomed during the 1990s and the prices of some tradables have increased strongly. Trade reforms may have stimulated the demand for labour and increased net labour income a little. Sectors of major export and import growth have had identifiable consequences for household poverty dynamics. Consumption differences hardly matter 12 June 2003 GTAP Conference 34