Agriculture Import Liberalization and Household Welfare in Sri Lanka

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1 Agriculture Import Liberalization and Household Welfare in Sri Lanka Ganesh Seshan 1 and Dina Umali-Deininger 2 May 2006 Keywords: import liberalization, farm-households, welfare, poverty, rice, Sri Lanka 1 Ganesh Seshan is a consultant (ETC) at the Social and Economic Development Group (MNSED), Middle East and North Africa Region, World Bank. D.C. gseshan@worldbank.org 2 Dina Umali-Deininger a is Lead Agriculture Economist at the South Asia Agriculture and Rural Development Group (SASAR), World Bank D.C. dumali@worldbank.org The findings, interpretations, and conclusions expressed in this paper are those of the authors and do not necessarily reflect the views of the Board of Executive Directors of the World Bank or the governments they represent.

2 JEL Classification: F14, F16, O24, Q12 2

3 3 1. Introduction This note sets out to forecast the distributional impact of reducing import duties on rice, chillies, onions, potatoes and wheat in Sri Lanka. Outcomes are quantified for 3 hypothetical scenarios, from a 50 percent cut in custom levies to a 75 percent reduction and finally a 100 percent cut or complete removal of custom levies. Lower domestic prices for the commodities in question are expected to benefit net consumers at the expense of net sellers. The extent to which is an empirical question which can only be resolved by looking at the data. In doing so, this work adopts a partial equilibrium approach focusing only on the markets for the commodities of interest, using the latest 2002 HIES household survey data to estimate the changes in real income and poverty status that arises from import trade liberalization in the agriculture sector. 2. Methodology The reduction of import duties on specific food crops is expected to lower domestic retail prices. The extent to which prices decline depend on the magnitude of the import duty reduction and other custom levies, including distribution cost and possible markup adjustments to retail prices. Appendix A details the components that constitute a retail price for the commodities that are examined in this study. To investigate the impact on household welfare or real income due to changes in a food crop price, the follow farm-household model based on Minot and Goletti (1998) is adopted: w Y h hi 1 1 = P HR + ( P ) HR ε P CR ( P ) CR i hi i h Si i hi i hε, (1) Di where wic is a second-order or long-term change in real income for household h due to changes in the price of crop i, Y h is household income, P i = Pi / P is the proportional i,0 change in the price of crop i, fraction of income, Y h, similarly, HR hi is the value of crop i harvest of household h as a CR hi is the value of consuming crop i by household h as

4 4 a fraction of income, Y h, ε Si is the supply-price elasticity of crop i and ε Di is the (compensated) demand-price elasticity of crop i. The model can easily be extended to cover multiple crops. If the elasticities are set to zero, this expression collapses to the welfare measure popularized by Deaton (1989, 1997) and is commonly referred to as the Net Benefit Ratio (NBR) which is a static or short-term welfare measure of price changes that assumes no quantity or dynamic responses by consumers and producers. With the exception of rice where supply and demand price elasticities are available 3, the welfare consequences for the remaining food commodities, i.e. onions, chillies, wheat flour and potatoes relies on the NBR measure. The current levies charges and rates for the commodities of interest are provided in Table 1 using 2004 data to determine import unit values from which the tariff-equivalent rate of a specific custom duty can be derived. Table 1 Sri Lanka: Levies for Selected Commodities, 2004 Commodity Name Import Unit Value (Rs/kg) Custom Duty (Rs) Tariff Equivalent Rate VAT rate PAL rate SRL rate SUR rate Rice (milled) % n/a 2.5% 0.1% n/a Flour of wheat n/a 2.5% n/a 2.5% 0.1% n/a Potatoes % 15.0% 2.5% 0.1% 10.0% Onions % 0.5% 2.5% 0.1% n/a Chillies % n/a 2.5% 0.1% n/a Note: Import unit values are constructed from value and quantity data. Source: WITS, FAOSTAT, Sri Lanka Customs. Three possible scenarios are considered which custom levies are reduced by 50 percent, 75 percent and 100 percent respectively. To further nuance the analysis, within each scenario, two possibilities are considered: (a) only a reduction in (import) custom duty and (b) a reduction in custom duty and other custom levies, including the surcharge, Social Responsibility levy (SRL) and Port and Development levy (PAL). The predicted change in retail prices are provided in Table 2. These price changes are fed into equation (1) for each food crop, produced and or consumed by a household and the resulting real incomes variations are derived at the household level. 3 elasticities for rice are obtained from Table 12 in Weerahewa (2004).

5 5 Table 2 Sri Lanka: Predicted Percentage Change in Retail s Reduction in Custom Duty by: Reduction in Custom Duty & Other Custom Levies by: 50% 75% 100% 50% 75% 100% Scenarios 1(a) 2(a) 3(a) 1(b) 2(b) 3(b) Rice -20.6% -30.9% -41.1% -21.3% -31.9% -42.6% Flour of wheat -1.2% -1.8% -2.4% -2.4% -3.6% -4.8% Potatoes -12.9% -19.4% -25.8% -14.4% -21.2% -27.6% Onions -16.9% -25.3% -33.7% -17.7% -26.5% -35.4% Chillies -14.8% -22.2% -29.6% -15.7% -23.5% -31.3% Source: Author's calculation based on equation A.2 3. Data Lower domestic food prices are expected to primarily benefit lower-income households where expenditure on food constitutes a large share of total expenditure. Table A.1 in the annex provides a breakdown of household expenditure on rice, onions, chillies, potatoes and wheat. On average, Sri Lankan households allocate 11.5 percent of their consumption on rice, while the budget shares for onions, chillies, potatoes and wheat flour are approximately 1 percent respectively. The rice budget share for households in the lowest income quintile is 19 percent compared to 4 percent for the richest households in the 5 th income percentile. Agricultural households also spend relative more on food consumption relative to non-agricultural households. Figures 1 to 5 shows the budget shares for various food items across the income distribution. The vertical line is the national consumptionbased poverty line. Rice consumption clearly stands out in terms of its place in household consumption.

6 6 Figures 1-5: Food Shares across Household Wheat Flour Budget Share (%) Wheat Flour Expenditure Share: All Households Onion Budget Share (%) Onion Expenditure Share: All Households log real per-capita monthly expenditure (2002) log real per-capita monthly expenditure (2002) Chilli Budget Share (%) Chilli Expenditure Share: All Households Potato Budget Share (%) Rice Expenditure Share: All Households Rice Budget Share (%) Potato Expenditure Share: All Households log real per-capita monthly expenditure (2002) log real per-capita monthly expenditure (2002) log real per-capita monthly expenditure (2002)

7 7 The degree to which price changes effects producer and consumer welfare in the short-run depends on the production and consumption shares of the respective household. Using rice marketing for illustration, Table A.2 in the annex provides a breakdown of paddy production, consumption and net sales by various household categories. Rice production is equivalent on average to 4.1 percent of income, proxied by total expenditure, while as noted earlier, the mean budget share of rice is 11.5 percent. This results in a share of net sales to income or a net benefit ratio of -7.4 percent ( ). Thus, a 10 percent decrease in farmgate and retail rice prices would raise short-term household real income by 0.74 percent on average. Similarly, a 20 percent fall in rice prices arising from an equivalent reduction in rice import duties would raise real income in the short-run by 1.48 percent. This figure is the difference between a gross savings equivalent to 2.3 percent of income generate by lower rice prices and a loss of farmer s income amounting to 0.82 percent of initial income. The negative NBR for urban, rural and estate households indicates that on average, households, particularly in the estates will benefit from lower rice prices. The importance of rice in household incomes is highest in the North-Central province with a positive NBR. It comes as no surprise, that farmers in this province will lose in real income terms in the short-run, from a reduction in domestic rice prices. The last three columns of Table A.2 shows the percentage of households that are net sellers 4 (NBR>0), that have no net sales (NBR=0), and that are net buyers (NBR<0). Overall, close to 90 percent of Sri Lankan households are net buyers who would gain in the short-term from lower rice prices. Around 10 percent of rural households are net sellers of rice while over 88 percent are net buyers. The proportion of net sellers is the highest in the North-Central province at 44 percent followed by the North-Western province at 14.5 percent. The proportion of net sellers is higher among middle-income rural households than 4 Net sellers are farm households whose quantity of a particular crop that is sold exceeds the amount bought in the marketplace. By adding the amount set aside for home consumption out of the total harvest to both sales and quantity purchased, another equivalent way of describing a net seller is a farm household who total harvest exceeds the amount consumed (the sum of quantities bought and set aside for home consumption). In value terms, this is represented by the NBR ratio exceeding zero for the household.

8 8 among high income rural households, though even in the lowest quintile, surplus households make up less than 10 percent of the rural total. What the distribution of rice marketing status among Sri Lanka households show that nearly 9 out of 10 households and 6 out of seven provinces are net buyers, implying that the majority will benefit from lower rice prices in the short-run. The province that stands to gain the most is the Sabaragamuwa province followed by the Central province. It is worth pointing out that the Sabaragamuwa province has the second highest head count poverty at 28.9 percent after Uva which stood at 31.8 percent in Results The distributional impact of a reduction in custom levies under each scenario on rice, chillies, onions, wheat flour and potatoes prices is estimated using equation (1) and is shown in Annex Table A.3 to A.8 5. For illustration purpose, this discussion focuses on reductions to import duties under scenario 1(a) which is a 50 percent cut and scenario 3(a) which looks at the elimination of the duty or a 100 percent reduction. It s worth noting while that a cut in import duties as well as other custom levies yields additional real income gains, they appear to be marginal. Reading off the first column in Table A.3, the real income gain from lower prices after a 50 percent reduction in import duties is expected to be 2.2 percent on average, benefiting lower income households proportionally more. This rises to a potential real income gain of 4.8 with a removal of import duties as seen in Table A.7. Net sellers are likely to experience a decline in their real incomes, ranging from 4.3 percent after cutting import duties by half to 7.2 percent after completely removing import duties. On the other hand, households with net zero positions or net buyers would enjoy a real income gain between 2.9 and 6.1 percent. In each scenario examined in this study, households in all provinces with 5 Consumption and production responses were only computed for rice price variations due to availability of price elasticities. For all other commodities, only the first-order or static effects of price changes are considered. For potato price changes, the data did not identify potato producers hence only the consumption effect is accounted for. In addition, all wheat flour is imported which naturally leads one to considering consumption effects solely.

9 9 the exception of those in the North-Central province are also expected to benefit from lower food prices. The real income gains are also shown graphically in Figure 6 and 7 across the distribution of households, reflecting a 50 percent cut in import duties and a total removal of duties, respectively. The vertical axis measures the change in real income due to price effects of removing import duties while the horizontal axis is the (log) per-capita household expenditure in real terms. The vertical lines denote the 25 th and 75 th percentile of per-capita expenditure respectively. The right vertical axis measures the population density notice that most households are middle income homes. The lowest dashed line in blue isolates the impact of rice prices change on real income, accounting also for quantity or dynamic responses by consumers and producers The dashed red line shows the static effect of price changes for all the food items under consideration while the sold line accounts for the full impact of lower prices, incorporating the dynamic impact of rice prices changes. The downward sloping nature of each line demonstrate that lower-income households will benefit more as a proportion of their initial real income from lower prices relative to betteroff households. Figure 6: Expected Welfare Gain after 50% cut in duties Figure 7: Expected Welfare Gain after 100% cut in duties Real Income Gain due to Agri. Trade Reforms: All Households Real Income Gain due to Agri. Trade Reforms: All Households Welfare Gain (%) Density Welfare Gain (%) Density log per-capita monthly expenditure in log per-capita monthly expenditure in 2002 Total WG: Dynamic Effects Total WG: Static Effects Total WG: Dynamic Effects Total WG: Static Effects Rice WG: Dynamic Effects Population Density Rice WG: Dynamic Effects Population Density

10 10 Figures 8(a) and 8(b) divides the real income changes between agricultural 6 and nonagricultural households under a 50 percent import duty cut while Figures 9(a) and 9(b) illustrate the potential outcome under a 100 percent reduction. As opposed to nonagricultural households, real income gains to farm households are likely to be dampened by farm income losses arising from lower food prices. Figure 8(a): 50% cut in import duty Figure 8(b): 50% cut in import duty Real Income Gain from Agri. Trade Reforms: Agri. HHs Real Income Gain from Agri. Trade Reforms: Non-Agri. HHs Welfare Gain (%) Welfare Gain (%) log per-capita monthly expenditure in log per-capita monthly expenditure in 2002 Total WG: Dynamic Effects Total WG: Static Effects Total WG: Dynamic Effects Total WG: Static Effects Rice WG: Dynamic Effects Rice WG: Dynamic Effects Figure 9(a): 100% cut in import duty Figure 9(b): 100% cut in import duty Real Income Gain from Agri. Trade Reforms: Agri. HHs Real Income Gain from Agri. Trade Reforms: Non-Agri. HHs Welfare Gain (%) Welfare Gain (%) log per-capita monthly expenditure in log per-capita monthly expenditure in 2002 Total WG: Dynamic Effects Total WG: Static Effects Total WG: Dynamic Effects Total WG: Static Effects Rice WG: Dynamic Effects Rice WG: Dynamic Effects 6 Agricultural households are defines as households engaged in farm production, raising livestock or earning agricultural wages as primary occupation.

11 11 Assuming that households do not reallocate expenditure with lower prices, the expected gross savings 7 from lower prices under a 50 percent duty cut is equivalent to 2.9 percent of initial income, with households in the first income quintile saving 4.6 percent relative to 1.1 percent savings by the highest earning households in the fifth quintile. Removing all custom duties can potentially generate an average household savings of 5.6 percent, ranging from 9.1 percent savings for the poorest households to 2.2 percent savings for the richest group. The remaining columns in Table A.3 and A.7 provide the impact of the agriculture trade reform on headcount poverty (columns 2 and 3), poverty gap (columns 4 and 5) and the severity index (columns 6 and 7). Each poverty measures provide the value before and after the proposed trade reforms with 2002 as the base year. For example, the difference between the headcount poverty rate due to the price effect of trade liberalization (column 3) and the observed rate in 2002 (column 2) isolates the impact of agriculture trade reforms working through predicted changes in the price of rice, chillies, onions and potatoes. For Sri Lanka, the price effects of reducing import duties can potentially reduce headcount poverty by an average of 1.6 percentage points with a 50 percent cut in import duties to 3.2 percentage points under a complete duty removal. Though net sellers experience an increase in poverty, ranging between 2.8 and 6.4 percentage points, other households holding a net-zero or more disproportionately, a net buyer 8 position can anticipate a decline in poverty from anywhere between 2.0 to 4.3 percentage points. Among net sellers, it is paddy farmers that form the bulk (almost 92 percent) that likely to be adversely affected by price declines, with increases in headcount poverty expected to range from 3.1 percentage points (a 50 percent cut) to 7 percentage points (under a total duty removal). Non-paddy farmers who are net sellers in their respective crops may face falling prices for these crops but end up benefiting as a whole from lower prices of rice which they consume. 7 Recall that the share of gross savings is simply the consumption ratio multiplied by the change in crop prices it assumes that quantities consumed are unchanged after the prices fall. 8 Among net buyers, paddy farmers only constitute 9 percent of the total share.

12 12 Although net sellers may experience losses but they represent less than 10 percent of the total population as of In addition net sellers constitute less than 18 percent of agricultural households in Sri Lanka, where income from non-agricultural activities are larger relative to those earned from agriculture. The gains are most evident in the lowest-income households in the first quintile which on average, can expect a decline of poverty incidence ranging from 6.9 percentage points with a 50 percent cut to 16.5 percentage points when import duties are completely lifted. Among the households in the first quintile, those in the estate sector are likely to experience the highest drop in headcount poverty, between 12.7 and 26.3 percentage points, followed by a range of 6.5 to 15.9 percentage points by those residing in the rural sector, depending on the size of the duty cut. Aside from the incidence of poverty, additional poverty measures capturing its depth and severity are shown in Table A.3 and A.7 which includes the poverty gap ratio and poverty severity ratio The poverty gap which reflects how far below poor households are from the specified poverty line as a ratio of that line, is expected to decline for the lowest income group from 20.6 percent to 18.1 percent, i.e., by 2.5 percentage points under a 50 percent cut and by 5.1 percentage points with a total removal of import duties. The severity index which is the square of the poverty gap is sensitive to the income distribution among the poor the more unequal this distribution is, the higher the index. Rising real incomes among the poorest (those in the first income quintile) due to the trade reforms is anticipated to contribute to reducing the severity index by 0.9 percentage points with a 50 percent cut and doubling to 1.8 percentage points under a 100 percent cut in duties. 5. Conclusion The lowering of import duties in Sri Lanka on staple food items will benefit the vast majority of its population who are net consumers of these commodities. A reduction of custom duties by 50 percent can be expected to raise real incomes by 2.2 percent and lower headcount poverty among the poorest households by nearly 7 percent. Further gains can be expected from larger duty cuts in fact a total removal of import duties and levies on rice,

13 13 wheat, onions, potatoes and chillies can potentially raise household real incomes on average by 5.1 percent and more significantly, lift 17.8 percent of the poorest households in the first quintile, who reside primarily in the estate and rural sector, out of poverty.

14 14 References Deaton, A. (1997), The Analysis of Household Surveys, World Bank. Minot, N. and Goletti, F. (1998), Export Liberalization and Household Welfare: The Case of Vietnam, American Journal of Agricultural Economics, vol, pp Weerahewa, J. (2004), Impacts of Trade Liberalization and Market Reforms on the Paddy/Rice Sector in Sri Lanka IFPRI, MTID Discussion Paper No. 70.

15 15 Annex 1 Computation of Commodity Change To determine how prices are potentially affected by changed to custom duties and levies 9, it can first be assumed that retail price for a particular commodity can be constructed as follows: P = (1 + α )( D + S + L +Θ + VAT + P ), (A.1) i i i i i i i M, i where, P i : retail price of commodity i P : C.I.F. price of commodity i α i Mi, : distribution and markup rate D i : custom duty, where Di = dp i Mi,, and d is the ad-valorem duty rate S i : surcharge, where Si = sd i i, where s is the surcharge rate. L i : Social responsibility levy (SRL), L= ( Di + Si) li, where l i is the SRL rate. Θ i : Port and Airport Development (PAL) levy, Θ i= θipmi,, where θ i is the PAL rate VAT :Value added tax, VATi = (1.07 PMi, + Di + Si +Θ i) ν i, where ν i is the VAT rate. Taking P i to be the retail price, the expected percentage change in retail price after changes to various trade levies can be computed as: P P Pi i i i =, where the post retail price after the levy change, (A.2) P P = (1 + α )( D + S + L +Θ + VAT + P ) (A.3) i i i i i i i M, i The change in retail price, P i assumes that retail and markups will not be affected by variations made to its custom duty and levies. 9 Further information on custom duty and levies can be obtained from the Sri Lankan Custom s website at

16 16 Annex 2 Table A.1 Sri Lanka: Budget Shares of Selected Food Items (in percent) Rice Expenditure Onion Expenditure Chilli Expenditure Potato Expenditure Wheat Flour Expenditure All Sector Urban Rural Estate Province Western Central Southern North-Western North-Central Uva Sabaragamuwa Household Type Non-agriculture Agriculture Income Group 1st quintile nd quintile rd quintile th quintile th quintile Urban 1st quintile nd quintile rd quintile th quintile th quintile Rural 1st quintile nd quintile rd quintile th quintile th quintile Estate 1st quintile nd quintile rd quintile th quintile th quintile Source: Author s calculation using HIES 2002.

17 17 Table A.2 Rice Production, Consumption and Net Sales by Household Group Rice Production (% of income) Rice Consumption (% of income) Net Sales of Rice (% of income) Net Sellers of Rice Zero Net Position Net Buyers of Rice (Average Percentage) (Percentage of Households) Sri Lanka Sector Urban Rural Estate Province Western Central Southern North-Western North-Central Uva Sabaragamuwa Household Type Non-agriculture Agriculture Income Group 1st quintile nd quintile rd quintile th quintile th quintile Urban 1st quintile nd quintile rd quintile th quintile th quintile Rural 1st quintile nd quintile rd quintile th quintile th quintile Estate 1st quintile nd quintile rd quintile th quintile th quintile Note: Income is proxied using total household expenditure. Source: Author s calculation using HIES 2002.

18 18 Table A.3 Sri Lanka: Impact of Agriculture Trade Reforms (50% cut in custom duties) Headcount (%) Poverty Gap (%) Severity Gap (%) Real Income Houshold Category Change (%) 2002 Effect 2002 Effect 2002 Effect (1) (2) (3) (4) (5) (6) (7) All Sector Urban Rural Estate Province Western Central Southern North-Western North-Central Uva Sabaragamuwa Household Type Non-agriculture Agriculture Farm-household Type Net Seller Paddy farmer Non-paddy farmer Net Zero/Buyer Paddy farmer Otherwise Income Group 1st quintile nd quintile rd quintile th quintile th quintile Urban 1st quintile nd quintile rd quintile th quintile th quintile Rural 1st quintile nd quintile rd quintile th quintile th quintile Estate 1st quintile nd quintile rd quintile th quintile th quintile Note: Income is proxied using total household expenditure. Source: Author s calculation using HIES 2002.

19 19 Table A.4 Sri Lanka: Impact of Agri. Trade Reforms (50% cut in custom duties & levies) Headcount (%) Poverty Gap (%) Severity Gap (%) Real Income Houshold Category Change (%) 2002 Effect 2002 Effect 2002 Effect (1) (2) (3) (4) (5) (6) (7) All Sector Urban Rural Estate Province Western Central Southern North-Western North-Central Uva Sabaragamuwa Household Type Non-agriculture Agriculture Farm-household Type Net Seller Paddy farmer Non-paddy farmer Net Zero/Buyer Paddy farmer Otherwise Income Group 1st quintile nd quintile rd quintile th quintile th quintile Urban 1st quintile nd quintile rd quintile th quintile th quintile Rural 1st quintile nd quintile rd quintile th quintile th quintile Estate 1st quintile nd quintile rd quintile th quintile th quintile Note: Income is proxied using total household expenditure. Source: Author s calculation using HIES 2002.

20 20 Table A.5 Sri Lanka: Impact of Agriculture Trade Reforms (75% cut in custom duties) Headcount (%) Poverty Gap (%) Severity Gap (%) Real Income Houshold Category Change (%) 2002 Effect 2002 Effect 2002 Effect (1) (2) (3) (4) (5) (6) (7) All Sector Urban Rural Estate Province Western Central Southern North-Western North-Central Uva Sabaragamuwa Household Type Non-agriculture Agriculture Farm-household Type Net Seller Paddy farmer Non-paddy farmer Net Zero/Buyer Paddy farmer Otherwise Income Group 1st quintile nd quintile rd quintile th quintile th quintile Urban 1st quintile nd quintile rd quintile th quintile th quintile Rural 1st quintile nd quintile rd quintile th quintile th quintile Estate 1st quintile nd quintile rd quintile th quintile th quintile Note: Income is proxied using total household expenditure. Source: Author s calculation using HIES 2002.

21 21 Table A.6 Sri Lanka: Impact of Agri. Trade Reforms (75% cut in custom duties & levies) Headcount (%) Poverty Gap (%) Severity Gap (%) Real Income Houshold Category Change (%) 2002 Effect 2002 Effect 2002 Effect (1) (2) (3) (4) (5) (6) (7) All Sector Urban Rural Estate Province Western Central Southern North-Western North-Central Uva Sabaragamuwa Household Type Non-agriculture Agriculture Farm-household Type Net Seller Paddy farmer Non-paddy farmer Net Zero/Buyer Paddy farmer Otherwise Income Group 1st quintile nd quintile rd quintile th quintile th quintile Urban 1st quintile nd quintile rd quintile th quintile th quintile Rural 1st quintile nd quintile rd quintile th quintile th quintile Estate 1st quintile nd quintile rd quintile th quintile th quintile Note: Income is proxied using total household expenditure. Source: Author s calculation using HIES 2002.

22 22 Table A.7 Sri Lanka: Impact of Agri. Trade Reforms (100% cut in custom duties) Headcount (%) Poverty Gap (%) Severity Gap (%) Real Income Houshold Category Change (%) 2002 Effect 2002 Effect 2002 Effect (1) (2) (3) (4) (5) (6) (7) All Sector Urban Rural Estate Province Western Central Southern North-Western North-Central Uva Sabaragamuwa Household Type Non-agriculture Agriculture Farm-household Type Net Seller Paddy farmer Non-paddy farmer Net Zero/Buyer Paddy farmer Otherwise Income Group 1st quintile nd quintile rd quintile th quintile th quintile Urban 1st quintile nd quintile rd quintile th quintile th quintile Rural 1st quintile nd quintile rd quintile th quintile th quintile Estate 1st quintile nd quintile rd quintile th quintile th quintile Note: Income is proxied using total household expenditure. Source: Author s calculation using HIES 2002.

23 23 Table A.8 Sri Lanka: Impact of Agri. Trade Reforms (100% cut in custom duties & levies) Headcount (%) Poverty Gap (%) Severity Gap (%) Real Income Houshold Category Change (%) 2002 Effect 2002 Effect 2002 Effect (1) (2) (3) (4) (5) (6) (7) All Sector Urban Rural Estate Province Western Central Southern North-Western North-Central Uva Sabaragamuwa Household Type Non-agriculture Agriculture Farm-household Type Net Seller Paddy farmer Non-paddy farmer Net Zero/Buyer Paddy farmer Otherwise Income Group 1st quintile nd quintile rd quintile th quintile th quintile Urban 1st quintile nd quintile rd quintile th quintile th quintile Rural 1st quintile nd quintile rd quintile th quintile th quintile Estate 1st quintile nd quintile rd quintile th quintile th quintile Note: Income is proxied using total household expenditure. Source: Author s calculation using HIES 2002.

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