The boundaries, colors, denominations, and other information shown on any map in this volume do not imply on the part of the World Bank Group any judgment on the legal status of any territory or the endorsement or acceptance of such boundaries. The material in this publication is copyrighted. Requests for permission to reproduce portions of it should be sent to the Office of the Publisher at the address shown in the copyright notice above. The World Bank encourages dissemination of its work and will normally give permission promptly and, when the reproduction is for noncommercial purposes, without asking a fee. Permission to copy portions for classroom use is granted through the Copyright Clearance Center, Inc., Suite 910, 222 Rosewood Drive, Danvers, Massachusetts 01923, U.S.A. The complete backlist of publications from the World Bank is shown in the annual Index of Publications , which contains an alphabetical title list (with full ordering information) and indexes of subjects, authors, and countries and regions. The latest edition is available free of charge from the Distribution Unit, Office of the Publisher, The World Bank, 1818 H Street, N.W., Washington, D.C. 20433, U.S.A., or from Publications, The World Bank, 66, avenue dIéna, 75116 Paris, France.
Infrastructure and Poverty in Viet Nam Infrastructure and Poverty in Viet Nam Infrastructure and Poverty in Viet Nam The Living Standards Measurement Study The Living Standards Measurement Study (LSMS) was established by the World Bank in 1980 to explore ways of improving the type and quality of household data collected by statistical offices in developing countries Its goal is to foster increased use of household data as a basis for policy decisionmaking Specifically, the LSMS is working to develop new methods to monitor progress in raising levels of living, to identify the consequences for households of past and proposed government policies, and to improve communications between survey statisticians, analysts, and policymakers The LSMS Working Paper series was started to disseminate intermediate products from the LSMS Publications in the series include critical surveys covering different aspects of the LSMS data collection program and reports on improved methodologies for using Living Standards Survey (LSS) data More recent publications recommend specific survey, questionnaire, and data processing designs and demonstrate the breadth of policy analysis that can be carried out using LSS data LSMS Working Paper Number 121 Infrastructure and Poverty in Viet Nam Dominique van de Walle Copyright © 1996 The International Bank for Reconstruction and Development/THE WORLD BANK 1818 H Street, N.W Washington, D.C 20433, U.S.A All rights reserved Manufactured in the United States of America First printing February 1996 To present the results of the Living Standards Measurement Study with the least possible delay, the typescript of this paper has not been prepared in accordance with the procedures appropriate to formal printed texts, and the World Bank accepts no responsibility for errors Some sources cited in this paper may be informal documents that are not readily available The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) and should not be attributed in any manner to the World Bank, to its affiliated organizations, or to members of its Board of Executive Directors or the countries they represent The World Bank does not guarantee the accuracy of the data included in this publication and accepts no responsibility whatsoever for any consequence of their use Infrastructure and Poverty in Viet Nam Infrastructure and Poverty in Viet Nam The boundaries, colors, denominations, and other information shown on any map in this volume not imply on the part of the World Bank Group any judgment on the legal status of any territory or the endorsement or acceptance of such boundaries The material in this publication is copyrighted Requests for permission to reproduce portions of it should be sent to the Office of the Publisher at the address shown in the copyright notice above The World Bank encourages dissemination of its work and will normally give permission promptly and, when the reproduction is for noncommercial purposes, without asking a fee Permission to copy portions for classroom use is granted through the Copyright Clearance Center, Inc., Suite 910, 222 Rosewood Drive, Danvers, Massachusetts 01923, U.S.A The complete backlist of publications from the World Bank is shown in the annual Index of Publications , which contains an alphabetical title list (with full ordering information) and indexes of subjects, authors, and countries and regions The latest edition is available free of charge from the Distribution Unit, Office of the Publisher, The World Bank, 1818 H Street, N.W., Washington, D.C 20433, U.S.A., or from Publications, The World Bank, 66, avenue d'Iéna, 75116 Paris, France ISSN: 0253−4517 Dominique van de Walle is an economist in the World Bank's Policy Research Department Library of Congress Cataloging−in−Publication Data Van de Walle, Dominique Infrastructure and poverty in Viet Nam / Dominique van de Walle p cm — (LSMS working paper: 121) Includes bibliographical references ISBN 0−8213−3544−8 Infrastructure (Economics)—in Vietnam Poverty—Vietnam Vietnam—Economic conditions—Regional disparities Household surveys—Vietnam I World Bank II Title III Series HC444.Z9C38 1996 363'.09597—dc20 95−52159 CIP Contents Contents Infrastructure and Poverty in Viet Nam Foreword link Abstract link Acknowledgments link Introduction link Poverty and Infrastructure in Viet Nam, 1992−93 link 2.1 Availability of Physical Infrastructure in Rural Viet Nam link 2.2 Drinking Water link 2.3 Sewerage and Sanitation link 2.4 Access to Irrigation link 2.5 Sources of Energy link 2.6 Roads link 2.7 Summary and Implications link Explaining Crop Income link 3.1 Determinants of Crop Income link 3.2 The Benefits from Irrigation: Policy Simulations link 3.3 The Cost of Household Labor link 3.4 The Cost of Irrigation Expansion link Conclusions link References link Tables Table 1: Rural Infrastructure and Poverty in Viet Nam link Table 2: Rural Infrastructure in North and South Viet Nam link Table 3: Source of Drinking Water in Rural and Urban Areas of North and South Viet Nam (%) link Table 4: Source of Drinking Water by Region (%) link Table 5: Toilet Facilities in Rural and Urban Areas of North and South Viet Nam (%) link Table 6: Toilet Facilities by Region (%) link Table 7: Average per Capita Square Meters of Irrigated, Non−irrigated, Other and Total Land link Table 8: Average per Capita Square Meters of Irrigated, Non−irrigated, Other and Total Land by Region link Table 9: Lighting Source in Rural and Urban Areas of North and link South Viet Nam (%) link Tables Infrastructure and Poverty in Viet Nam Table 10: Cooking Fuel in Rural and Urban Areas of North and South Viet Nam (%) Table 11: Variable Definitions and Summary Data link Table 12: Regression Results: Crop Incomes link Table 13: Marginal Effect on Net Crop Income Allowing for Interaction Effects link Table 14: National Distribution of Impacts of Irrigation Under Different Scenarios link Table 15: Regional Distribution of Per Capita Impacts of Simulation link Table 16: Regional Distribution of Per Capita Impacts of Simulation link Table 17: Regional Distribution of Per Capita Impacts of Simulation link Table 18: Regional Distribution of Per Capita Impacts of Simulation link Table 19: Regression Results: Family Labor Costs link Table 20: Marginal Effect on Family Labor Costs Allowing for Interaction Effects link Figures Figure 1: Safe Water Sources in Rural Viet Nam link Figure 2: Sources of Safe Water in Viet Nam link Figure 3: Sanitation Facilities in Rural Viet Nam link Figure 4: Sanitation Facilities in Urban Viet Nam link Figure 5: Total and Irrigated Annual Land Distribution in Viet Nam, 1992−93 link Foreword Viet Nam is poor both in terms of household living standards and physical infrastructure How important are future infrastructural investments likely to be in promoting pro−poor economic growth in Viet Nam? This is an important question for the government and donors alike, as Viet Nam moves through its transition to a market economy This study uses the Viet Nam Living Standards Survey of 1992−93 to examine the association between household living standards and the level of access to various infrastructural services It also explores in depth the distributional impact of an expansion in irrigation infrastructure The paper is part of a larger effort in the Policy Research Department to understand how public spending policies affect household welfare Figures Infrastructure and Poverty in Viet Nam LYN SQUIRE, DIRECTOR POLICY RESEARCH DEPARTMENT Abstract Viet Nam has poor physical infrastructure and high levels of income poverty What role might better infrastructure play in reducing poverty in Viet Nam? This paper explores the link between poverty and lack of infrastructure using the 1992−93 Viet Nam Living Standards Survey The household data indicate that although there are some regional and urban−rural imbalances, in general access to infrastructure is not very different between poor and non−poor—infrastructure tends to be bad for everyone Simulations of the potential benefits from an expansion of irrigation infrastructure and under certain assumptions about how it would be distributed, suggest that the policy would be redistributive, representing proportionately greater gains to the poor The most pro−poor impacts would occur in Viet Nam's poorest regions and under a policy which targeted irrigation expansion to small per capita landholding households The average annual economic rate of return of the irrigation investments considered would be at least 20 percent The paper also finds evidence that various constraints over and above that presented by lack of irrigation appear to diminish the benefits of irrigation to poor and non−poor alike Acknowledgments Financial assistance from the World Bank Research Committee (RPO BB67883) is gratefully acknowledged I would like to thank Shanta Devarajan, Paul Glewwe, Frannie Humplick, Nauman Ilias, Jennie Litvack, Amit Mohindra, Martin Ravallion, Hedy Sladovich, and Tom Wiens for their help and useful comments 1— Introduction Various arguments can be made as to why basic infrastructure investments in a country such as Viet Nam would reduce poverty One is that the poor have least access to infrastructure and so will benefit most from new investments If the non−poor have captured all the benefits of past infrastructure projects and are now satiated then new projects must benefit the poor Another argument is that the poor are concentrated in sectors of the economy where rates of return to infrastructure investments are high For example, the poor in Viet Nam depend heavily on agriculture, and rural infrastructure investments could have high agricultural returns This paper attempts to throw light on these arguments by asking: How large, and how pro−poor are the gains from infrastructure investments—specifically irrigation—likely to be? The Viet Nam Living Standards Survey (VNLSS) household data—collected during 199293—contains much information which is suggestive in examining this question The paper only addresses this question in any depth for irrigation The data have partly influenced this choice—the attraction of modelling irrigation is that it is household specific, and so there is ample scope for identifying interaction effects with other variables and assigning benefits at the household level The paper begins in section by linking household living standards as revealed in the VNLSS with the level of various infrastructural services Using standard descriptive techniques, an overall picture of the state of infrastructure, and how access varies by standards of living, is provided Section then attempts to explore in Abstract Infrastructure and Poverty in Viet Nam much greater depth one aspect of infrastructure—irrigation—and its association with living standards Here marginal, as opposed to average, effects of irrigation expansion are estimated and the distributional implications assessed Farm household crop incomes are modelled as functions of household characteristics, community characteristics and land, irrigated and non−irrigated The impact of irrigation on family labor inputs is also explored The final section draws some conclusions The paper defines economic infrastructure to consist of services from public utilities such as sanitation, power and water supply and public works such as road and transport networks and irrigation systems (World Bank 1994a) Such services are distinguished by the fact that ''they share technical features (such as economies of scale) and economic features (such as spillover from users to non−users)" (World Bank 1994a, p 2) For these reasons, government provision is often seen to be necessary Linkages between poverty and infrastructure are discussed in World Bank (1994a), Lipton and Ravallion (1995) and Jimenez (1995) For sector specific discussions see Howe and Richards (1984), Binswanger et al (1993) and Goldstein (1993) 2— Poverty and Infrastructure in Viet Nam, 1992−93 Except where noted, the analysis is based on the nationally representative 1992−93 Viet Nam Living Standards (VNLSS) survey The survey covers 4800 households (23,790 persons) of which 3840 (19,094 persons) are rural, and includes a separate questionnaire on the communes in which sampled rural households are found Collected information covers a wide spectrum of aspects of living standards The household survey touches upon access to and usage of infrastructure facilities in the context of its focus on household members' activities, income sources, health, education, housing and so on The community survey provides detailed information on the availability of infrastructure services in each rural household's commune of residence It does not cover urban areas For certain types of infrastructure, the community survey is the sole source of information in the VNLSS For others, details are also provided at the household level However, the latter are often conditional on the household's usage and so tend to provide a skewed view of "access" For example, for households who not report an illness or whose member's illness was not externally treated, the survey reveals nothing about the household's accessibility to health facilities The commune level data must also be treated with caution Because communes vary in size and distances differ, the figures not reveal all that we would ideally like to know about household access to infrastructure services These data were supplemented by a number of field trips to rural areas of the North, Center and South of Viet Nam during 1993 and 1994 Throughout, the paper uses household consumption expenditure per person as the welfare indicator Since prices vary spatially, each household's expenditure is deflated by the region specific poverty line relative to the national poverty line This provides a measure of household per capita expenditures at what can be termed "all Viet Nam prices" All monetary units are also converted into real values in this way The analysis is thus based on real expenditure values representing purchasing power parity throughout the country For the distributional analysis in section and the figures, individuals are ranked by the converted household per capita consumption expenditures and placed into 14 class intervals defined on per capita expenditures In the following sections, the paper first briefly looks at the general availability of physical infrastructure in the rural communes to which households belong It then turns to access to drinking water, sewerage and sanitation, irrigation, energy sources and roads for each household in both urban and rural areas Expansion factors are not needed as the survey is self−weighted The community questionnaire relies on interviews of village leaders, health care workers, teachers and local government officials 2— Poverty and Infrastructure in Viet Nam, 1992−93 Infrastructure and Poverty in Viet Nam Regional poverty lines are estimated based on the "cost of basic needs" methodology (Ravallion 1994), and detailed in World Bank, 1994c Deflating by region specific poverty lines is an alternative to using a regional price index Because the weighing diagram used in deriving poverty lines tends to be more appropriate to the poor than that typically used in spatial price indices, their use is often preferred for investigations concerning poverty 2.1— Availability of Physical Infrastructure in Rural Viet Nam Tables and combine information on household living standards from the VNLSS household level survey with information on infrastructure facilities in each household's commune of residence from the community schedule As mentioned, this is possible only for rural households Table shows availability across various household groups for all of rural Viet Nam while Table desegregates this information across North and South household groups For example, (from first row, Table 1) 70.2% of the population as a whole are estimated to live in communes which have a passable road, while this is true of 74.7% of people living in "non−poor" households and of 67.3% of those living in "poor" households (with consumption per person above and below the poverty line, respectively) Using a lower poverty line (arbitrarily set at close to two thirds of the national poverty line) 72.8 and 62.5 % of those living in non−poor and poor households respectively live in communes with a passable road Table 1: Rural Infrastructure and Poverty in Viet Nam INFRASTRUCTURE Percent of rural population living in communes with this infrastructure Total High Poverty Line Headcount Index of Poverty (% poor Low Poverty Line among those with this infrastructure) Non−Poor Poor Non−Poor Poor High Poverty Line Low Poverty Line Passable road 70.2 74.7 67.3 72.8 62.5 58.6 22.3 Passenger transport 52.3 56.2 49.8 54.0 47.3 58.2 22.7 Electricity 43.1 47.2 40.6 45.8 35.3 57.6 20.6 5.2 7.2 3.9 5.5 4.2 45.8 20.3 Post office 34.4 36.2 33.2 34.9 32.9 59.0 24.0 Lower secondary school 87.9 87.7 88.0 88.7 85.4 61.2 24.4 Upper secondary school 9.7 10.7 9.1 10.2 8.3 57.3 21.5 93.3 93.6 93.1 93.7 92.1 61.0 24.8 61.1 25.1 Pipe−borne water Clinic Total Note: The table combines data from the household and community questionnaires Poor defined by higher poverty line are those with yearly per capita expenditures deflated by regional poverty line which are less than the national poverty line of 1,209,300 Dongs Poor defined by lower line are those with per capita expenditures deflated by regional poverty line which are less than 2.1— Availability of Physical Infrastructure in Rural Viet Nam Infrastructure and Poverty in Viet Nam (0.65)*national poverty line Electricity is defined as most households in commune have it; pipe−borne water is defined as at least some households have it Source: 1993 VNLSS Table 2: Rural Infrastructure in North and South Viet Nam INFRASTRUCTURE Percent of rural population living in communes with this infrastructure Total High Poverty Line Headcount Index of Poverty (% poor Low Poverty Line among those with this infrastructure) Non−Poor Poor Non−Poor Poor High Poverty Line Low Poverty Line RURAL NORTH Passable road 76.8 89.6 70.4 82.5 62.5 61.1 23.1 Passenger transport 47.2 53.4 44.1 50.0 40.1 62.3 24.1 Electricity 55.9 68.1 49.8 61.1 42.6 59.4 21.6 3.5 6.2 2.2 4.1 2.1 41.9 17.0 Post office 27.7 29.5 26.7 28.4 25.9 64.3 26.6 Lower secondary school 90.6 93.2 89.3 92.5 85.9 65.7 26.9 Upper secondary school 9.3 9.6 9.2 9.4 9.1 66.0 27.8 93.9 97.1 92.3 95.3 90.4 65.6 27.3 66.7 28.4 Pipe−borne water Clinic Total RURAL SOUTH Passable road 58.3 56.5 60.0 57.3 62.4 52.4 20.3 Passenger transport 61.5 59.7 63.2 60.2 66.8 52.3 20.6 Electricity 20.2 21.7 18.8 21.3 15.5 47.4 14.6 8.1 8.4 7.8 7.8 9.7 49.0 22.8 Post office 46.5 44.4 48.6 45.2 52.1 53.2 21.3 Lower secondary school 83.0 81.0 84.9 82.7 84.2 52.1 19.3 Upper secondary school 10.5 12.0 9.1 11.5 6.3 44.1 11.4 Clinic 92.2 89.3 95.0 91.2 96.7 52.4 19.9 Pipe−borne water 2.1— Availability of Physical Infrastructure in Rural Viet Nam Infrastructure and Poverty in Viet Nam Total 50.9 19.0 Note: The table combines data from the household and community questionnaires Poor defined by higher poverty line are those with per capita expenditures deflated by regional poverty line which are less than national poverty line of 1,209,300 Dongs Poor defined by lower line are those with per capita expenditures deflated by regional poverty line which are less than (0.65)*national poverty line Electricity is defined as most households in commune have it; pipe− borne water is defined as at least some households have it Source: 1993 VNLSS Infrastructure for social services—schools and clinics—is much more widely accessible than other physical infrastructure such as electricity and water (Tables and 2) There are clinics in communes accounting for 93% of the total rural population, lower secondary schools in communes covering 88% and primary schools (not reported) exist in every sampled rural commune Facilities tend to be somewhat more prevalent in the North Differences between poor and non−poor are not large Thus, according to the VNLSS, communes tend to be quite well−provisioned in at least basic social services However, the data also remind us that the quality of social services may leave a lot to be desired For example, although all surveyed rural communes report having a primary school, 20% of children not attending school say this is because the school is too far; and 64 % of communes complain of poor material conditions as the number one problem facing their commune's primary school Forty−three percent of the rural population live in communes in which "most" households have electricity The variation from North (56%) to South (only 20%) is striking Pipe−borne water is even less frequently present in communes Only 5% of the rural population reside in communes where at least some households have piped water This percentage is somewhat higher in the South The availability of electricity and piped water is also related to living standards, with the poor less likely to make their home in communes where these are obtainable Particularly for water in the North, headcount indices for households in communes with this infrastructure are considerably lower than for the population at large Some of these data must be interpreted carefully For example (as noted), the survey indicates that 70% of the rural population are found in communes serviced by a road which is passable year round Two caveats should be mentioned First, in the South, coastal areas and parts of the North, canals and waterways are widely used to transport goods and passengers, so that roads may not be the relevant entity Second, the survey gives little indication of the quality of the roads or how it defines "passable" Based on casual observation during my field work in rural Viet Nam, it seems likely that being passable by a motorcycle or bicycle may have been sufficient to qualify as "passable" For these reasons, the availability of passenger transport may be a more informative indicator of accessibility Tables and thus include this variable as a proxy for the presence of a serviceable road or waterway Around half the population are in communes in which some kind of passenger transport is available Transport is more frequently found in the South probably reflecting widespread use of boats as well as road vehicles there There is also a more pronounced difference between poor and non−poor in terms of access to a passable road and transport in the North, indicating the remoteness of some of the poorest households in the North In the rest of section the household questionnaire is used to further examine access to specific infrastructure services at the household level in both urban and rural areas 2.1— Availability of Physical Infrastructure in Rural Viet Nam Infrastructure and Poverty in Viet Nam non−irrigated land Finally, simulations and target smallholders Section 2.4 showed that poor farm households tend to have less annual, as well as less irrigated land than non−poor households It is therefore of interest to examine how the distributional effects of bringing 10 percent of the country's non−irrigated annual land under irrigation would differ if those improvements were targeted to households with low total annual crop land holdings Simulation distributes the irrigation on the basis of low total household annual landholdings, while simulation targets on the basis of low per capita annual landholdings Once again, the simulations hold total annual land constant Given the existing distribution of irrigated and non−irrigated land across households, simulation results in irrigating all the non−irrigated land of households who have less than 3250 m2 total annual land and simulation 4, the non−irrigated land of all with less than 620 m2 per person The expected marginal benefit from irrigation−the change in household crop income from irrigating one unit of non−irrigated land—can be estimated by , where and are estimated at each data point, using the parameter estimates for the relevant interaction effects in Table 12 applied to the household−specific values of the relevant variables To simulate policy impacts one can then multiply the marginal benefit by the household specific increment However, the marginal benefit function, is only a first−order approximation and strictly valid for small changes only For estimating the gains from discrete changes, a more accurate methodology is to recalculate the value of the function after substituting constrained land changes into the profit function as follows: where, for example in the case of simulation (and as appropriate for the others) so that the exact amount of land shifted into irrigation is appropriate to each household's circumstances—zero for those who have no unirrigated land and up to 500 m2 for households who The results are termed the ''simulated total impacts." The distribution of the impact in per capita Dongs and as a percent of per capita household expenditures across all farm households classified into expenditure groups, is shown in Table 14 for the four simulations Tables 15 to 18 show the results disaggregated across regions (with the exception of the Central Highlands where there are too few observations for the breakdown) Table 14: National Distribution of Impacts of Irrigation Under Different Scenarios Simulated total impacts (per capita) Expenditure % cf farm group population ('000 Dongs/person/yr) 0−500 4.1 9099.3 Total impact as % of household expenditure 6700.7 11878.1 19310.3 2.13 1.57 2.78 3.2— The Benefits from Irrigation: Policy Simulations 4.52 32 Infrastructure and Poverty in Viet Nam 501−600 4.1 12645.6 15513.5 13267.7 15314.7 2.29 2.81 2.40 2.77 601−700 6.9 16059.4 13118.9 14217.7 14604.0 2.47 2.02 2.18 2.24 701−800 9.6 14132.9 12312.0 15185.0 16657.2 1.88 1.64 2.02 2.22 801−900 9.2 13750.1 11443.8 15974.4 10287.4 1.62 1.35 1.88 1.21 901−1000 9.2 14775.1 10704.2 14482.1 9108.2 1.56 1.13 1.53 0.96 1001−1100 9.1 12924.6 9183.1 11281.8 11328.6 1.23 0.88 1.08 1.08 1101−1250 11.5 11396.7 10261.8 11310.6 7977.2 0.97 0.87 0.96 0.68 1251−1400 8.0 15035.7 12469.1 14279.8 14383.4 1.14 0.94 1.08 1.09 10 1401−1550 7.3 14185.6 13287.7 13194.1 9476.3 0.96 0.90 0.90 0.64 11 1551−1800 7.2 10240.5 10226.4 6653.9 2836.9 0.62 0.62 0.40 0.17 12 1801−2200 6.9 9328.1 10000.7 3602.2 0.50 0.47 0.51 0.18 13 2201−3000 5.0 10142.9 11421.5 5143.5 3433.6 0.41 0.46 0.21 0.14 14 3001−4500 2.1 10935.7 13185.7 5215.5 3900.1 0.28 0.34 0.13 0.10 Total 100 12844.6 11226.5 12221.3 10293.6 1.05 0.92 1.00 0.84 9947.0 Note: Results are based on the unrestricted model A conversion of 10% of non−irrigated annual land to irrigation is common to all simulations Under simulation (1): irrigation is distributed to all households subject to feasibility; (2) irrigation is distributed only to households without irrigated land; (3) irrigation is targeted to households with low total annual landholdings; and (4) irrigation is distributed to households with low per capita annual landholdings Table 15: Regional Distribution of Per Capita Impacts of Simulation Northern Uplands Red River Delta North Coast Central Coast South East M Simulated Total total impact impact % of hh exp Simulated Total total impact impact % of hh exp Simulated Total total impact impact % of hh exp Simulated Total total impact impact % of hh exp S to im Exp Simulated group total impact Total impact % of hh exp 27985.5 6.53 8335.3 1.88 14788.3 3.35 1855.0 0.47 1216.7 0.30 31584.0 5.80 5188.6 0.93 18062.1 3.28 2989.3 0.54 12305.0 2.25 35212.4 5.37 9028.8 1.39 15553.4 2.40 2645.0 0.41 13792.3 2.08 34651.3 4.62 5162.9 0.68 16729.4 2.23 2704.7 0.36 10336.9 1.38 35820.9 4.22 6623.6 0.78 18529.7 2.19 5195.5 0.61 14442.1 1.69 35807.7 3.81 10776.5 1.14 20855.1 2.19 5480.6 0.57 6382.4 0.67 30698.2 2.93 5547.2 0.53 19847.3 1.89 6768.6 0.64 14822.4 1.41 33514.2 2.83 11012.6 0.93 18230.6 1.54 5822.9 0.50 4831.1 0.41 33915.7 2.58 12650.2 0.95 22188.9 1.68 7073.4 0.54 14254.1 1.06 3.2— The Benefits from Irrigation: Policy Simulations 33 Infrastructure and Poverty in Viet Nam 10 30031.7 2.05 9656.7 0.67 25121.2 1.70 4587.0 0.31 14492.9 0.96 11 29949.4 1.82 8392.4 0.50 22120.2 1.35 3201.8 0.20 18261.2 1.10 12 36663.7 1.86 10786.7 0.55 26043.7 1.32 6518.4 0.33 16186.4 0.83 13 29741.7 1.23 11884.4 0.47 22954.4 0.93 9928.3 0.41 21402.4 0.86 14 28907.6 0.84 8488.1 0.22 2900.7 0.08 10387.3 0.31 9820.4 0.20 33211.4 3.00 8798.9 0.72 18767.2 1.96 5151.6 0.42 12805.3 0.86 Note: Results are based on the unrestricted model Under simulation the conversion of 10% of non−irrigated annual land distributed to all households subject to feasibility Table 16: Regional Distribution of Per Capita Impacts of Simulation Northern Uplands Red River Delta North Coast Central Coast South East M Simulated Total total impact impact % of hh exp Simulated Total total impact impact % of hh exp S to im Exp Simulated group total impact Total impact % of hh exp Simulated Total total impact impact % of hh exp Simulated Total total impact impact % of hh exp 26082.1 6.08 14515.3 3.28 14568.9 3.30 521.3 0.13 1302.0 0.33 41024.3 7.53 8358.8 1.49 18248.0 3.31 3641.7 0.66 15214.6 2.78 32702.6 4.99 8242.8 1.27 8442.5 1.30 −1617.5 −0.25 23844.4 3.60 32412.3 4.32 3453.1 0.46 12476.5 1.67 2698.4 0.36 11907.8 1.59 34634.2 4.08 2869.5 0.34 14847.7 1.75 5327.0 0.63 13564.9 1.59 27266.9 2.90 4734.2 0.50 16719.4 1.75 6941.2 0.73 7792.4 0.82 18956.6 1.81 4392.2 0.42 14756.4 1.41 3512.5 0.33 25629.1 2.43 34830.1 2.94 6677.5 0.57 18470.4 1.56 4240.4 0.36 7473.9 0.63 28508.3 2.17 5480.9 0.41 22731.8 1.73 3667.2 0.28 16530.1 1.23 10 33139.2 2.26 1548.1 0.11 24518.8 1.66 1473.0 0.10 21100.6 1.40 11 36228.6 2.20 0.00 0.00 20050.8 1.22 1858.6 0.11 28771.1 1.74 12 28678.7 1.46 1006.7 0.05 27010.3 1.37 4097.1 0.21 24500.3 1.26 13 24897.8 1.03 4849.1 0.19 16223.0 0.66 13118.5 0.54 29843.5 1.20 14 36872.1 1.07 4315.9 0.11 0.00 0.00 17885.7 0.53 7788.0 0.16 Total 30499.2 2.76 4323.2 0.35 15755.8 1.65 4153.3 0.34 17769.4 1.19 Note: Results are based on the unrestricted model Under simulation the conversion of 10% of non−irrigated annual land distributed only to households without irrigated land 3.2— The Benefits from Irrigation: Policy Simulations 34 Infrastructure and Poverty in Viet Nam Table 17: Regional Distribution of Per Capita Impacts of Simulation Northern Uplands North Coast Central Coast South East M Exp Simulated Total Simulated Total group total impact total impact impact % impact % of hh exp of hh exp Simulated Total total impact impact % of hh exp Simulated Total total impact impact % of hh exp Simulated Total total impact impact % of hh exp Si to im 40040.0 9.34 0.00 0.00 16744.0 3.79 201.9 0.05 1287.6 0.32 16 28688.4 5.26 8789.7 1.57 18282.8 3.32 1763.3 0.32 13122.9 2.40 15 41771.8 6.37 2980.7 0.46 16166.5 2.49 −4232.3 −0.66 0.00 0.00 60 32566.1 4.34 3814.9 0.50 22552.6 3.01 3308.1 0.44 23583.0 3.15 18 48170.9 5.68 2630.6 0.31 30108.0 3.56 9489.9 1.12 15552.6 1.83 20 30457.6 3.24 10523.6 1.12 18341.9 1.92 6740.2 0.71 2634.5 0.28 40 22029.0 2.10 3662.2 0.35 21273.1 2.03 7292.6 0.69 16304.3 1.55 29176.5 2.46 9711.9 0.82 23350.0 1.97 7016.3 0.60 9025.0 0.76 −4 31302.4 2.38 11247.7 0.85 17343.6 1.32 3902.9 0.30 27273.7 2.03 13 10 36372.9 2.48 8862.0 0.60 31239.5 2.11 4978.5 0.33 4394.7 0.29 35 11 21393.9 1.30 6116.1 0.37 24493.6 1.50 4465.9 0.27 10752.1 0.65 15 12 30343.8 1.54 9582.8 0.49 41661.6 2.11 6564.8 0.33 11809.2 0.61 46 13 44089.7 1.82 14057.4 0.56 22001.1 0.89 23895.0 0.98 7336.1 0.29 14 522.3 0.02 6134.8 0.16 0.00 0.00 9968.8 0.29 5342.3 0.11 52 32870.9 2.97 7061.2 0.58 21878.8 2.29 6166.9 0.98 12051.9 0.81 21 Total Red River Delta Note: Results are based on the unrestricted model Under simulation the conversion of 10% of non−irrigated annual land targeted to households with low total annual landholdings Table 18: Regional Distribution of Per Capita Impacts of Simulation Northern Uplands Red River Delta North Coast Central Coast South East Simulated Total total impact % impact of hh exp Simulated total impact Exp Simulated group total impact Total Simulated Total impact total impact impact % % of hh exp of hh exp Simulated Total total impact impact % of hh exp 66093.4 15.42 0.00 0.00 23270.5 5.27 51335.4 9.42 385.7 0.07 15460.6 2.81 12444.7 2.26 31943.0 4.87 2162.0 0.33 25377.8 3.92 −2818.3 −0.44 43557.8 5.80 4634.6 0.61 21889.9 2.92 572.5 35629.3 4.20 2384.4 0.28 13680.9 1.62 26856.1 2.86 2441.6 0.26 21172.2 2.22 3.2— The Benefits from Irrigation: Policy Simulations −12.8 −0.003 M Total impact % of hh exp S t i 1287.6 0.32 13122.9 2.40 0.00 0.00 0.08 22153.2 2.96 − 3166.1 0.37 15552.6 1.83 10350.7 1.08 2634.5 0.28 35 Infrastructure and Poverty in Viet Nam 27165.8 2.59 2837.3 0.27 21864.7 2.08 2006.5 0.19 16304.3 1.55 26032.9 2.20 8312.0 0.71 21085.6 1.78 4904.6 0.42 10021.0 0.84 37681.2 2.87 11383.2 0.86 8878.4 0.67 5234.4 0.40 16070.5 1.20 10 25623.7 1.75 3072.4 0.21 18073.4 1.22 6787.5 0.46 4394.7 0.29 11 1761.8 0.11 4892.5 0.29 4787.3 0.29 4066.6 0.25 1635.3 0.10 12 8570.6 0.43 5237.3 0.27 14804.9 0.75 6902.3 0.35 7262.8 0.37 13 29762.1 1.23 2424.2 0.10 10597.2 0.43 25819.3 1.06 7336.1 0.29 14 522.3 0.02 6134.8 0.16 0.00 0.00 0.00 0.00 0.00 0.00 31234.6 2.83 4660.9 0.38 19199.2 2.01 5785.7 0.47 9284.6 0.62 Total − Note: Results are based on the unrestricted model Under simulation the conversion of 10% of non−irrigated annual land distributed to households with low per capita annual landholdings Converting 10 percent of non−irrigated land to irrigation produces an increase in crop incomes equal on average to around percent of mean household expenditures This implies an elasticity of 0.1 The elasticities vary only slightly across the simulations However, the level and distribution of per capita impacts differs across national expenditure groups according to how the irrigation is distributed (Table 14) This reflects the method of allocating the irrigation expansion combined with the existing household distribution of irrigated and nonirrigated annual crop land and the influence of other household and community specific factors entering the marginal benefit of irrigation function such as education, household size and region Under equal distribution to all households subject only to land constraints (simulation 1), impacts are smaller at the lower and upper ends of the distribution but otherwise relatively steady across expenditure groups Simulation tends to be more generous towards the upper end of the distribution and less so at the bottom end though it is not altogether that different from impacts under simulation Targeting the irrigation expansion to smallholders results in larger absolute impacts at the lower end of the distribution which fall much more sharply when targeting is done on the basis of per capita than household annual landholdings Impacts under all simulations are certainly progressive—declining as a proportion of household expenditures as living standards rise—and so inequality reducing Progressivity is most pronounced for simulation which confers large benefits to the poorest groups (worth 4.5 percent of household expenditures for the poorest group and only 0.1 percent for the wealthiest expenditure group) Gains are very concentrated regionally (Tables 15 to 18) The potential benefits of irrigation appear to be strongest in the Northern Uplands where simulated total impacts are largest for all simulations (mean impacts of up to percent of mean household expenditures) Irrigation expansion is inequality reducing there, exceptionally so when irrigation expansion is targeted to low per capita landholding farm households However, the net absolute gains tend to be relatively steady across the distribution of per capita expenditures in all except simulation The next most substantial impacts are found in the North Coast and South East regions In the North Coast, impacts are generally inequality reducing on the whole, though the gradient is much lower than for the Northern Uplands Absolute benefit levels tend to increase with expenditure class except under simulation which, here too, is found to result in the most progressive distribution of benefits In the South East, total impacts tend to be larger for the better off (with the exception of simulation 4) and flat or only somewhat progressive when expressed as a proportion of household expenditures The smallest total impacts are evidenced for the Central Coast and the Mekong River Delta In both regions the benefits are also far from progressive Indeed, the simulated per capita total impacts, though small, tend to increase for higher expenditure groups One interesting finding from the above is that concentration of benefits and progressivity appear to go hand in hand Benefits tend to be higher where their distribution is also more pro−poor The results hint towards targeting irrigation expansion to the Northern Uplands and North Coast regions, where absolute benefits are not only higher but also well distributed These are also Viet Nam's poorest regions (World Bank 1994c; Dollar and Glewwe 1995) 3.2— The Benefits from Irrigation: Policy Simulations 36 Infrastructure and Poverty in Viet Nam The overall regional picture is quite robust across simulations Nationally, there is not much of an obvious tradeoff between the ways of distributing the irrigation across regions Interestingly, however, there is a distinct regional pattern to which simulation has the greatest impact on regional absolute benefit levels This no doubt reflects characteristics of how annual land is distributed regionally Simulation produces the highest absolute gains for both the Northern Uplands and the Red River; simulation for the North and Central Coasts; and simulation for the South East and Mekong In each case these are contiguous regions Simulation is distinguished not by producing the largest benefits in any region but by tending to favor the poor with larger absolute impacts and by producing the most progressive distribution of benefits almost universally across regions At first sight, the simulation outcomes appear surprising for the Mekong River Delta They also appear robust This is the country's primary producer of rice with, as yet, only half its total cultivated area under irrigation It is sometimes said that extending irrigation will enable double and triple cropping and boost production and incomes formidably in this ideal setting for paddy cultivation However, the Mekong delta situation is complex Various characteristics of the region's ecosystem and economy appear to provide credible explanations for the simulation results Irrigation systems in the Mekong Delta have been plagued by problems of sea water intrusion and acid−sulphate soils In recent years, as supplementary areas are brought under irrigation in upstream areas, the level and flow of the Mekong river has dwindled, resulting in salt water intrusion in previously productive irrigated fields downstream (NEDECO 1991) 19 This has meant that only one crop can be grown annually or, under the worse case, that continued rice cultivation is rendered impossible In the latter case, the areas are often transferred to aquaculture activities such as the farming of brackish shrimp which can be very profitable but would be reflected in lower crop incomes Furthermore, fully irrigated areas may also suffer from extensive flooding and water logging for long periods of the year In such areas of the Mekong, what is needed is better water management and drainage control rather than irrigation as such The issue seems to be that, because of the heterogeneity of irrigated land in the Mekong Delta, it is hard to generalize about the impact of irrigation infrastructure there If the data allowed a separation between irrigated areas which suffer from salinity and acidity problems and other irrigated land, we would probably get strong impacts of additional irrigation investments in the Mekong River Delta Irrigation can be very positive depending on whether it is upstream or not The results indicate low marginal benefits on average , where they are being averaged over a considerable amount of heterogeneity The profits from irrigation vary by region but there is also variation within region 19 NEDECO 1991 quotes farmers in the center of the delta complaining about this 3.3— The Cost of Household Labor The costs of household labor inputs on the family farm were ignored in defining net crop incomes 20 This is entirely defensible if one is concerned solely with the impact of irrigation on family consumption (since the implicit payment for own−labor inputs is exactly matched by the receipts leaving consumption unchanged) However, to assess the gains to farm profits the family labor cost should be debited And, like other costs of production, family labor inputs may well be related to whether land is irrigated or non−irrigated It is not obvious that irrigation would save on family labor However, one then faces the long−standing issue of what wage rate one should use for valuing family labor inputs; with surplus labor in rural areas and supervision costs, the opportunity cost of family labor may be well below the market wage rates for similar work 3.3— The Cost of Household Labor 37 Infrastructure and Poverty in Viet Nam Here I try to assess the possible bias in the above results due to the omission of family labor input costs The results may either over− or under−estimate the net returns to irrigation, depending on family labor requirements on irrigated versus non−irrigated annual land The shadow wage of family labor is somewhere between zero and the agricultural wage rate I assume that the shadow wage is a constant proportion of the prevailing market wage The cost of family inputs to own−farm production by household j is then given by where w k is the wage rate for the k'th demographic−group (adult men and women, and children), and F jk is the labor time devoted to farm work by demographic group for household j Information on wage rates are available in the community survey separately for men, women and children for a series of tasks (preparation, planting/transplanting, weeding, and harvesting) 21 However, the household survey does not include the time allocation for each member by those tasks Furthermore, in practice the wage data are very incomplete reflecting the lack of labor markets in many of the communes Thus demographic−specific commune mean agricultural wages are formed over all tasks for which wage rates are recorded and these are used to value the time on all farm tasks by each household member Missing data at the commune level are then replaced by the regional means for males, females or children as appropriate 22 20 Recall that non−family labor costs are included 21 Note that since the wage rates can only be obtained from the community schedule, they are not household specific 22 Data are missing for 398, 430, and 2406 households on wage rates for men, women, and children respectively The parameter is unknown To get an upper bound estimate, family labor input costs are evaluated at agricultural market wage rates , and the family labor cost is regressed against the same right−hand−side variables used to explain crop incomes The net marginal impact of irrigation over non−irrigation on the cost of the family labor input can then be compared to the previously calculated net marginal effect of irrigated over non−irrigated land on crop incomes If there is no significant difference between irrigated and non−irrigated land, then we need not worry; for any value of my results for crop income carry over to profits net of family labor If there is a difference then we can ask if there is an admissible value of which reverses the earlier conclusions The regression results (given in Table 19) indicate that irrigation tends to increase work on the family farm It is also notable that, other things being equal, bigger households and ones with a larger proportion of adults and teenagers tend to use more family labor Table 20 presents the total marginal effects of the main variables on labor costs allowing for all interaction effects The effect on the market value of family labor time of irrigation over non−irrigated land is estimated to be 7,279 Dongs per 100 m2 Subtracting this full amount from the average net impact on crop incomes of converting 100 m2 of non−irrigated land to irrigation reduces the latter to 21,299 Dongs, a 25 percent decline Of course this is an upper bound estimate which may considerably overestimate the costs If the opportunity cost of family labor is half of the market wage , then the gain in farm profit from irrigating 100 m2 of nonirrigated land is 24,939 Dongs, a 13 percent decline In conclusion, the earlier results overestimated the marginal effect of irrigation on farm profits, though the difference is not prohibitively large, representing a maximum of 25 % of the previous estimates of net income gains 3.3— The Cost of Household Labor 38 Infrastructure and Poverty in Viet Nam 3.4— The Cost of Irrigation Expansion Information on the costs of irrigation expansion is hard to come by, and generalizations across regions and types of irrigation investments are risky Nonetheless, even a rough sense of the cost−benefit appraisal can be useful Irrigation project costs have been estimated by a number of agencies for various regions Estimated average costs—including for a World Bank irrigation rehabilitation project in the Central Coast and for a large number of water resource development projects in the Mekong River Delta drawn up as part of the Mekong Delta Master Plan—fluctuate around 85,000 Dongs per 100 m2 ; these are averages over appraisals for multiple Table 19: Regression Results: Family Labor Costs laborcost sexhh Unrestricted Model Restricted Model Coefficient Coefficient 158669.5 hhsvgs t−ratio 1.45 t−ratio 160862.6 3.58 1.52 −0.0239 3.78 −0.0231 hhsize 246193.1 5.31 prop716 1471817.0 2.29 1185507 4.24 pfadlt 1507441.0 2.20 1435968 4.09 pmadlt 1754666.0 2.50 1711478 5.2 oedl*oed1 oed2 oed2*oed2 irrigated 2.42 3135.26 5.03 −24043.93 1.17 −19321.13 1.19 −1079.62 1.53 −1059.71 1.68 322.208 3.24 6.16 4.66 −0.00258 −126.674 nonirrig*nonirrig 1.68 −58.595 5.65 −0.00252 −197.220 perennial*perennial 7.23 1.02 −283.297 4.72 12564.61 1.20 −0.00290 −0.00858 waterland 306.387 2.52 −0.0021 perennial 6.93 2276.06 irrigated*irrigated nonirrigated 269214.9 1.88 6.51 −0.00887 2.82 13290.42 3.07 propauct 842682.1 1.60 939847.9 1.95 propall 488905.0 1.81 509353.9 2.80 hedl*pernnial 46.6154 2.17 34.251 2.30 hed2*irrigated −8.9632 1.77 −12.528 3.30 hed2*nonirrigated −8.4584 1.97 −8.368 2.61 3.4— The Cost of Irrigation Expansion 39 Infrastructure and Poverty in Viet Nam hed2*waterland 119.046 2.15 57.577 1.67 oed1*irrigated 9.620 3.09 9.627 3.96 oed1*nonirigated −5.151 1.99 −2.592 1.38 oed1*forest 25.395 1.70 12.208 2.06 oed2*irrigated −2.499 1.08 −2.863 1.32 oed2*perennial −7.088 1.43 −7.862 1.90 oed2*otherland 15.0682 1.48 6.371 1.91 hhsize*irrigated 13.962 2.24 13.641 2.70 hhsize*nonirrigated 17.257 3.48 15.766 3.55 1.60 27.969 3.14 hhsize*perennial 22.0446 pfadlt*irrigated −179.628 1.82 −178.334 2.60 pfadlt*nonirrigated 182.699 2.29 131.447 2.00 pfadlt*perennial 273.755 1.23 327.912 1.90 pmadlt*nonirrigated 268.217 3.54 193.512 3.15 pmadlt*perennial 373.679 2.06 458.372 3.33 pmadlt*forest −684.857 1.77 −399.353 2.17 prop716*irrigated −318.899 3.45 −326.617 4.48 prop716*perennial 203.644 1.14 300.683 1.91 99.855 1.34 rr*irrgated 85.881 1.065 rr*waterland −13158.55 2.99 mk*irrigated −125.50 2.99 −13419.56 −115.506 3.10 3.25 Table 19 (continued) Unrestricted Model laborcost mk*nonirrigated mk*waterland nw*irrigated nw*nonirrigated nw*waterland nc*irrigated nc*nonirrigated nc*perennial Coefficient 51.107 −12923.81 Restricted Model t−ratio 1.25 2.93 Coefficient 66.613 −13184.76 t−ratio 2.39 3.05 −144.161 1.63 −133.200 1.60 48.626 1.03 65.681 1.87 −13165.85 2.99 −13408.45 3.10 −123.831 1.36 −118.265 1.37 88.077 1.58 106.054 2.35 −129.440 1.49 −104.656 1.36 nc*waterland −12856.66 2.91 cc*perennial −284.91 1.30 3.4— The Cost of Irrigation Expansion −13153.33 −266.521 3.03 1.27 40 Infrastructure and Poverty in Viet Nam cc*waterland −106753.7 1.42 −106546.7 1.42 ch*irrigated −798.508 1.13 −877.190 1.27 ch*perennial −260.649 3.05 −245.386 3.20 ch*otherland 789.428 1.58 782.188 3.02 ch*waterland −13286.87 2.79 −13973.44 2.98 Number of obs = 3025 Number of obs = 3025 F(232, 2792) = 16.32 F(232, 2792) = 16.32 Prob > F = 0.0000 Prob > F = 0.0000 R−square = 0.5756 R−square = 0.5756 Adj R−square = 0.5404 Adj R−square = 0.5404 Root MSE = 1.9e+06 Root MSE = 1.9e+06 Note: The restricted model results from the pruning of all variables with t−ratios less than in the unrestricted model The unrestricted model contained exactly the same variables as the crop income regression reported in table 12 projects, though the variance is low 23 For these costs, the estimated model indicates an annual gain in net crop income of around 28,600 Dongs per 100 m2 , falling to a gain of 21,300 Dongs in farm profit at the maximum shadow wage for family labor This represents a rate of return of at least 25 to 35 % per year, assuming the project delivers such benefits indefinitely But even under conservative assumptions of a project life of only 10 years and with the maximum shadow wage for family labor, the rate of return is about 20% 24 23 The World Bank project average costs are estimated at about 83,150 Dongs per square meter when excluding consultant costs as well as physical and price contingencies The Mekong Master Plan projects average 85,830 Dongs per m2 (table 8.2), 87,650 Dongs (table 8.3), and 87,120 Dongs (table A2.1) all in NEDECO 1993 24 These are internal rates of return which equate the present value of the stream of benefits over the chosen time period with initial costs Table 20: Marginal Effect on Family Labor Costs Allowing for Interaction Effects Variable Unrestricted model Restricted Model Marginal effect on Marginal effect on t−ratio family labor cost t−ratio family labor cost irrigated annual land Dongs/100m2 19,249.7 5.3 20,032.5 5.7 non−irrigated annual land Dongs/100m2 11,970.8 4.0 10,864.3 6.3 perennial land Dongs/100m2 23,231.6 3.7 21,530.7 5.3 3.4— The Cost of Irrigation Expansion 41 Infrastructure and Poverty in Viet Nam forest land Dongs/100m2 −3,777.0 0.7 −2,795.3 1.4 water surface land Dongs/100m2 −764,911.9 1.1 −755,668.6 1.1 other land Dongs/100m2 12,901.6 1.2 2,612.2 1.9 household size Dongs/person 9.5 360,211.8 11.2 prop female adults Dongs/% point 17,197.3 2.7 1596511 5.3 prop male adults Dongs/% point 25,086.1 3.9 2415231 7.9 prop aged 7−16 Dongs/% point 9,143.5 1.5 648723.4 2.8 primary ed (head) Dongs/year −31,351.0 0.4 23,235.7 2.3 ed > primary (head) Dongs/year −49,473.3 2.2 −43,136.9 3.6 primary ed (other adults) Dongs/year 78,568.7 4.7 61,565.8 7.9 ed > primary (other adults) Dongs/year −41,642.1 2.8 −38,451.3 3.1 mean family labor costs 342,305 3,034,006 3,034,006 Note: Marginal effects are evaluated at mean points 4— Conclusions Viet Nam has poor infrastructure and high poverty These two facts are intimately connected However, the nature of those connections and their implications for the role of infrastructure investments in fighting poverty are complex to disentangle This paper has focused on some aspects of the link between poverty and lack of infrastructure using the VNLSS Access to infrastructure services tends to be poor for the majority of Vietnamese Urban areas are better provisioned and some regions certainly fare worse than others In particular, there are some distinct differences between the North and South of the country Imbalances are also evidenced among infrastructure services For example, the provision of social service facilities is generally superior than that of other physical infrastructure Piped water provision and electricity reveal considerable disparities between poor and non−poor groups But, by and large, the data indicate that basic infrastructure services are generally inadequate for all groups, though generally worst for the poor As a result, it cannot be surmised that an expansion in investment in basic infrastructure will be well−targeted to the poor Indeed, there is ample scope for the non−poor to capture the lion's share of the direct gains from infrastructure investment in Viet Nam To assess the impacts on poverty it is necessary to examine the distribution of the marginal benefits of specific infrastructure investments The paper focuses on irrigation investments to explore this issue in more depth The cross−sectional variation is used to estimate the marginal impacts of converting non−irrigated annual crop land over to irrigation In particular, a policy of irrigating 10 percent of currently non−irrigated annual land is simulated based on a regression model for crop income which includes irrigated and non−irrigated land as explanatory variables The simulations allow for four different ways of distributing the irrigation expansion across households: in simulation (1): irrigation is distributed to all households subject to feasibility; in (2) it goes only to households currently without irrigated land; in (3) it is targeted to households with low total annual landholdings and in simulation (4) it is targeted to households with low per capita annual landholdings In general, at the 4— Conclusions 42 Infrastructure and Poverty in Viet Nam national level the absolute income gains across expenditure groups imply that an undifferentiated expansion of irrigation would be redistributive—having higher proportionate gains to poorer households Targeting the irrigation expansion to households with small per capita landholdings produces the most progressive incidence of gains as well as the largest absolute benefits to the poor The results under all simulations show the highest total impacts on net crop incomes would occur for Viet Nam's two poorest regions—the Northern Uplands and the North Coast, where the impacts also show the most pro−poor distribution These substantial potential gains from irrigation from an equity point of view are likely to be accompanied by sizable average rates of return Even under quite conservative assumptions—namely a project life of only 10 years and valuing family labor inputs at the market wage for similar work—the average annual rate of return implied by my estimates of the gains to farm profits, and recent estimates of the investment cost of irrigation, is about 20% An even larger impact may be possible with a more differentiated expansion of irrigation—emphasizing key regions such as the Northern Uplands and addressing the need for rehabilitation of existing irrigation infrastructure, to realize its full potential Conversely, the rate of return will undoubtedly be lower in some areas where irrigation expansion is particularly costly Lack of irrigation infrastructure is clearly not the only constraint to reducing rural poverty in Viet Nam The quantity (in particular household size) and quality (education) of the family's human resources also matter greatly And not only other important constraints exist, but these are inextricably bound to the benefits which can ultimately be derived from irrigation infrastructure The analysis uncovers important complementarities between education, particularly primary education, and the gains from irrigation Demographics are also found to be key Finally, one can conjecture that the current lack of other infrastructure such as roads, electricity, communications and so forth, must also conspire to reduce the impacts which can be garnered from irrigation alone References Binswanger, Hans P., Shahidur R Khandker and Mark R Rosenzweig 1993 ''How Infrastructure and Financial Institutions Affect Agricultural Output and Investment in India." Journal of Development Economics , 41(2): 337−366 Dollar, David and Paul Glewwe 1995 "Poverty and Inequality in Viet Nam: The Current Situation." Mimeo, EA1CO and PRDPH, World Bank Goldstein, Ellen 1993 "The Impact of Rural Infrastructure on Rural Poverty." Mimeo, South Asia Region, World Bank Howe, J and P Richards 1984 Rural Roads and Poverty Alleviation ILO, Intermediate Technology Publications Ltd., London, U.K Jimenez, Emmanuel 1995 "Human and Physical Infrastructure: Public Investment and Pricing Policies in Developing Countries." In Jere Behrman and T.N Srinivasan, eds., Handbook of Development Economics , Volume , Amsterdam: North−Holland Lipton, Michael and Martin Ravallion 1995 "Poverty and Policy." In Jere Behrman and T.N Srinivasan, eds., Handbook of Development Economics , Volume , Amsterdam: North−Holland NEDECO 1991 "Mekong Delta Master Plan: Inception Report." May 13, The Netherlands References 43 Infrastructure and Poverty in Viet Nam ——— 1993 "Draft Master Plan for the Mekong Delta in Viet Nam: A perspective for Sustainable Development of Land and Water Resources." June, The Netherlands Ravallion, Martin 1994 Poverty Comparisons Chur, Switzerland: Harwood Academic Press, Fundamentals in Pure and Applied Economics, Volume 56 Salinger, Lynn B 1993 "Viet Nam's Agricultural Comparative Advantage and Export Potential." Associates for International Resources and Development, Cambridge, Mass State Planning Committee, UNDP, FAO and World Bank 1989 "Viet Nam Agricultural and Food Production Sector Review." Mission report UNICEF 1994 Situation Analysis of Women and Children in Viet Nam Hanoi van de Walle, Dominique 1995a "Targeting and Incidence: An Overview of Implications for Research and Policy." In D van de Walle and K Nead Public Spending and the Poor: Theory and Evidence London and Baltimore: The Johns Hopkins University Press ——— 1995b "Rural Poverty in an Emerging Market Economy: Is Diversification into Non Farm Activities in Rural Viet Nam the Solution?" Mimeo, PRDPE, World Bank Vu, Tu Lap and Christian Taillard 1993 Atlas du Viet Nam Montpellier et Paris: Reclus, La Documentation Francaise World Bank 1990 "Viet Nam: Water Supply and Sanitation Sector Study." April ——— 1994a World Development Report 1994: Infrastructure for Development New York: Oxford University Press ——— 1994b "Viet Nam Transport Sector: Serving an Economy in Transition." Report No 12778−VN, August ——— 1994c "Viet Nam: Poverty Assessment and Strategy." Report No 13442 VN,September LSMS Working Papers (continued) Decomposition with Applications to Brazil and India in the 1980s No 84 Vijverberg, Measuring Income from Family Enterprises with Household Surveys No 85 Deaton and Grimard, Demand Analysis and Tax Reform in Pakistan No 86 Glewwe and Hall, Poverty and Inequality during Unorthodox Adjustment: The Case of Peru, 198590 No 87 Newman and Gertler, Family Productivity, Labor Supply, and Welfare in a Low−Income Country No 88 Ravallion, Poverty Comparisons: A Guide to Concepts and Methods No 89 Thomas, Lavy, and Strauss, Public Policy and Anthropometric Outcomes in Côte d'Ivoire References 44 Infrastructure and Poverty in Viet Nam No 90 Ainsworth and others, Measuring the Impact of Fatal Adult Illness in Sub−Saharan Africa: An Annotated Household Questionnaire No 91 Glewwe and Jacoby, Estimating the Determinants of Cognitive Achievement in Low−Income Countries: The Case of Ghana No 92 Ainsworth, Economic Aspects of Child Fostering in Côte d'Ivoire No 93 Lavy, Investment in Human Capital: Schooling Supply Constraints in Rural Ghana No 94 Lavy and Quigley, Willingness to Pay for the Quality and Intensity of Medical Care: Low−Income Households in Ghana No 95 Schultz and Tansel, Measurement of Returns to Adult Health: Morbidity Effects on Wage Rates in Côte d'Ivoire and Ghana No 96 Louat, Grosh, and van der Gaag, Welfare Implications of Female Headship in Jamaican Households No 97 Coulombe and Demery, Household Size in Côte d'Ivoire: Sampling Bias in the CILSS No 98 Glewwe and Jacoby, Delayed Primary School Enrollment and Childhood Malnutrition in Ghana: An Economic Analysis No 99 Baker and Grosh, Poverty Reduction through Geographic Targeting: How Well Does It Work? No 100 Datt and Ravallion, Income Gains for the Poor from Public Works Employment: Evidence from Two Indian Villages No 101 Kostermans, Assessing the Quality of Anthropometric Data: Background and Illustrated Guidelines for Survey Managers No 102 van de Walle, Ravallion, and Gautam, How Well Does the Social Safety Net Work? The Incidence of Cash Benefits in Hungary, 198789 No 103 Benefo and Schultz, Determinants of Fertility and Child Mortality in Côte d'Ivoire and Ghana No 104 Behrman and Lavy, Children's Health and Achievement in School No 105 Lavy and Germain, Quality and Cost in Health Care Choice in Developing Countries No 106 Lavy, Strauss, Thomas, and De Vreyer, The Impact of the Quality of Health Care on Children's Nutrition and Survival in Ghana No 107 Hanushek and Lavy, School Quality, Achievement Bias, and Dropout Behavior in Egypt No 108 Feyistan and Ainsworth, Contraceptive Use and the Quality, Price, and Availability of Family Planning No 109 Thomas and Maluccio, Contraceptive Choice, Fertility, and Public Policy in Zimbabwe No 110 Ainsworth, Beegle, and Nyamete, The Impact of Female Schooling on Fertility and Contraceptive Use: A Study of Fourteen Sub−Saharan Countries References 45 Infrastructure and Poverty in Viet Nam No 111 Oliver, Contraceptive Use in Ghana: The Role of Service Availability, Quality, and Price No 112 Montgomery, Kouamé, and Oliver, The Tradeoff between Number of Children and Child Schooling: Evidence from Côte d'Ivoire and Ghana No 113 Pradhan, Sector Participation Decisions in Labor Supply Models No 114 Beegle, The Quality and Availability of Family Planning Services and Contraceptive Use in Tanzania No 115 Lavy, Spratt, and Leboucher, Changing Patterns of Illiteracy in Morocco: Assessment Methods Compared No 116 Lavy, Palumbo, and Stern, Health Care in Jamaica: Quality, Outcomes, and Labor Supply No 117 Glewwe and Hall, Who Is Most Vulnerable to Macroeconomic Shocks? Hypotheses Tests Using Panel Data from Peru No 118 Grosh and Baker, Proxy Means Tests for Targeting Social Programs: Simulations and Speculation No 119 Pitt, Women's Schooling, the Selectivity of Fertility, and Child Mortality in Sub−Saharan Africa No 120 Grosh and Glewwe, A Guide to Living Standards Measurement Study Surveys and their Data Sets References 46 [...]... the infrastructure stock in Viet Nam, the road network—dating largely from before the 1970s in the South and pre−1954 in the North—is old and in severe disrepair This is also true of other transport infrastructure including inland waterways (a 40,000 km network), ports, and the railway system (World Bank 1994b) 2.7— Summary and Implications The current state of physical infrastructure in Viet Nam is... Roads 20 Infrastructure and Poverty in Viet Nam 1994b) In 1992, around 12 percent of Viet Nam' s existing road network was paved compared to 30% of India's in 1985 and 48% of Indonesia's in 1990 (World Bank 1994b) Average road density is quite low at 0.32 km per sq km of land area and 1.6 km per 1000 inhabitants Not unexpectedly, densities are highest in the two deltas and lowest in the more mountainous... of Energy 19 Infrastructure and Poverty in Viet Nam Note: The table gives % of persons in each subgroup according to their household's cooking fuel Totals may not add up to 100 The remainder is attributable to "other" and kerosene and electricity in rural areas, and to other and bottled gas in urban areas Source: 1993 VNLSS Figure 5: Total and Irrigated Annual Land Distribution in Viet Nam, 1992−93... 100.1 125.5 17 Infrastructure and Poverty in Viet Nam Total land 932.4 888.6 902.9 2505.7 1249.4 1872.8 1604.3 985.8 1222.9 Note: Per capita m2 of land are calculated over the rural farm population Other land includes forest, water surface, and "other" as defined in footnote 10 Source: 1993 VNLSS 8 According to the interviewer's instruction manual, irrigated land in the VNLSS includes all land which is... favorably to that in both Ghana (69% of urban and 9% rural households) and Tanzania (35% and 1%) but less well to Peru (95% of the total population) 2.5— Sources of Energy 18 Infrastructure and Poverty in Viet Nam Electricity is rarely used for cooking Table 10 indicates that wood and leaves predominate in the rural areas of the North and wood dominates in the South's rural sector, while coal and kerosene... household and from region to region Education is found to be of considerable importance to agricultural productivity The primary schooling of the household head is important on its own and is found to be convex in its impact on crop incomes, implying 3.1— Determinants of Crop Income 30 Infrastructure and Poverty in Viet Nam increasing returns to schooling Interaction effects between education variables and. .. and Peru: 91 % of the rural Sierra population (1991 Living Standard Measurement Survey) 2.2— Drinking Water 10 Infrastructure and Poverty in Viet Nam Table 3: Source of Drinking Water in Rural and Urban Areas of North and South Viet Nam (%) Rural North Non−poor Rural South Poor Total Non−poor Poor Total Private Tap 2.2 0.1 0.8 0.4 0.0 0.2 Public Standpipe 1.3 0.1 0.5 0.1 0.5 0.3 Well w/ pump 2.0 1.4... constrained and simultaneously challenged by a plethora of real investment and consumption needs 3.1— Determinants of Crop Income In attempting to throw some light on these questions the paper looks at the determinants of net farm crop income and the role played by irrigation The size of the difference in marginal returns between irrigated and non−irrigated land determines the income gains from irrigating... function is assumed to be linearized as follows: where the marginal returns to non−irrigated and irrigated land are given by and 3.1— Determinants of Crop Income 22 Infrastructure and Poverty in Viet Nam respectively, and where d is a vector of regional dummy variables The error term in (1) is assumed to be independently and identically normally distributed The regression includes a full set of commune... persons in each subgroup according to their household's primary source of drinking water Totals may not add up to 100—remainder is attributable to "other" Private inside and outside taps are aggregated for rural areas Bottled water is one of the options though it is rare Source: 1993 VNLSS 2.2— Drinking Water 11 Infrastructure and Poverty in Viet Nam Figure 1: Safe Water Sources in Rural Viet Nam Figure