The Role of Infrastructure in Mitigating Poverty Dynamics

Transcription

1 Impact Aement of Infratructure Project on Poverty Reduction The Role of Infratructure in Mitigating Poverty Dynamic A Cae Study of an Irrigation Project in Sri Lanka Yauyuki Sawada Maahiro Shoji Shinya Sugawara and Naoko Shinkai No. 4 March 2010

2 Ue and diemination of thee working paper are encouraged; however the JICA Reearch Intitute requet due acknowledgement and a copy of any publication for which thee working paper have provided input. The view expreed in thee paper are thoe of the author() and do not necearily repreent the official poition of either the JICA Reearch Intitute or JICA. JICA Reearch Intitute 10-5 Ichigaya Honmura-cho Shinjuku-ku Tokyo JAPAN TEL: FA: Copyright 2010 by Japan International Cooperation Agency Reearch Intitute All right reerved.

3 The Role of Infratructure in Mitigating Poverty Dynamic: A Cae Study of an Irrigation Project in Sri Lanka Yauyuki Sawada Maahiro Shoji Shinya Sugawara Naoko Shinkai Abtract Although it i known that acce to phyical infratructure enhance houehold welfare there are very few micro-econometric tudie that analyze the role of infratructure in mitigating chronic and tranient poverty. Thi paper aim to cloe thi gap in the exiting literature by evaluating the impact of a large-cale irrigation project implemented in Sri Lanka. To thi aim we collected houehold-level monthly panel data over a period of two year. According to the point etimate with irrigation acceibility the per capita income and the per capita food and non-food conumption expenditure increae by around 17.8% 12.2% and 37.6% repectively evaluated at the average level among the treated. Alo the probability of binding credit contraint i reduced by 5.6% during the dry eaon. The latter reult implie that irrigation enhance houehold acce to credit which in turn contribute to further reduction in tranient poverty. Thee empirical reult ugget that irrigation infratructure ha a poitive impact on reducing both chronic and tranient poverty. The tructural etimation reult upport the validity of our theoretical framework. We alo perform robutne tet on thee reult. The qualitative reult are comparable even when we adopt thee alternative etimation approache. Keyword: Poverty Reduction Role of Infratructure Monthly Panel Data Correponding Author: Yauyuki Sawada JICA Reearch Intitute and Faculty of Economic Univerity of Tokyo (awada@e.u-tokyo.ac.jp) Department of EconomicSeijo Univerity Graduate School of Economic Univerity of Tokyo Graduate School of International DevelopmentNagoya Univerity Thi paper form part of a reearch project titled Impact Aement of Infratructure Project on Poverty Reduction initiated by the former Japan Bank for International Cooperation (JBIC) Intitute and wa inherited by Japan International Cooperation Agency (JICA) Reearch Intitute. We would like to thank Maahito Aoki and Taro Katurai for their collaboration in the project deign urvey implementation and data proceing. We alo acknowledge the effort of field urvey upervior Intizar Huain Fuard Marikar and Sunil Thrikawala and we thank the enumerator of the International Water Management Intitute (IWMI). We acknowledge the helpful comment and uggetion from Oumane Badiane Marcel Fafchamp Yohihia Godo Erneto Garilao Yujiro Hayami Hidehiko Ichimura Maahiro Kawai Carol A. Litwin Megumi Muto Ryuji Kaahara Takahi Kuroaki Keijiro Otuka Motoki Takahahi Ryuhei Wakaugi and the participant of a wide range of eminar and conference including the Annual Bank Conference on Development Economic (ABCDE) 2006 Tokyo the FASID Hakone Conference 2006 Aian Development Bank Intitute (ADBI) Conference on Infratructure and Poverty in 2002 the Global Development Network Rio de Janeiro Conference 2001 and the Japanee Economic Aociation. Needle to ay we are reponible for any remaining error. 1

4 Introduction Our aim in thi paper i to evaluate the role of irrigation infratructure in mitigating the negative impact of poverty dynamic uing houehold panel data from Sri Lanka. Such reearch and analyi i largely miing from the literature although development economit conider phyical infratructure to be an indipenable precondition of indutrialization and economic development (Murphy Shleifer and Vihny 1989). 1 Many empirical tudie demontrate that the development of phyical infratructure improve an economy long-term production and income level (Canning and Bennathan 2000; Efahani and Ramirez 2003; Lipton and Ravallion 1995; Jimenez 1995). For intance Hulten Bennathan and Srinivaan (2006) find that in India from 1972 to 1992 highway and electricity accounted for almot half of the growth of the Solow reidual of manufacturing indutrie. The poitive productivity effect of phyical infratructure development can be found even in rural area and agricultural ector (Jimenez 1995; Fan and hang 2004; and hang and Fan 2004). From thee finding it i evident that infratructure i likely to reduce poverty by enhancing growth becaue a trong poitive correlation between income growth and poverty reduction ha repeatedly been found in tudie uch a Beley and Burge (2003) Dollar and Kraay (2000) and Ravallion (2001). In fact an increaing amount of empirical literature ha tarted to focu on the role of infratructure in reducing poverty directly. Exiting tudie include Datt and Ravallion (1998) on tate-level poverty in India Van de Walle (1996) on the poverty reduction effect of irrigation infratructure in Vietnam Jalan and Ravallion (2003) on water upply ytem and Lokhin and Yemtov ( ) on the poverty reduction effect of community-level infratructure improvement project on water upply ytem in Georgia. In addition Brockerhoff and Deroe (1996) and Jalan and Ravallion (2003) invetigate the role of water upply and public health ytem; and Jacoby (2000) Gibon and Rozelle (2003) and Jacoby and Minten (2008) invetigate 1 Phyical infratructure in general conit of two part; namely economic infratructure uch a road irrigation and electricity; and ocial infratructure uch a water upply ewer ytem hopital and chool facilitie. 2

5 the effectivene of road and tranportation infratructure. While thee micro-econometric tudie are inightful in uncovering the role of infratructure in reducing poverty two important iue remain unaddreed. The firt iue i a proper identification of the caual impact of irrigation infratructure on poverty reduction (Duflo and Pande 2007). Thi iue may be unaddreed becaue randomized evaluation which ha been increaing rapidly (Duflo Glennerter and Kremer 2008) i difficult to implement in the context of large-cale infratructure. The econd remaining iue i that to the bet of our knowledge all the preceding micro tudie of the nexu between infratructure and poverty reduction employ a tatic concept of poverty even though mot recent poverty tudie have tarted focuing on it dynamic and tochatic nature (Dercon ed. 2005; Fafchamp 2003). 2 It ha been etablihed that policy analye baed on tatic poverty can yield ubtantial inefficiencie in policy intervention (Jalan and Ravallion 1998). Thi paper aim to cloe thee gap in the literature by evaluating the role of irrigation infratructure in mitigating the negative impact of poverty dynamic; that i in reducing chronic and tranient poverty by regulating water availability acro eaon. The data we ue on houehold acceibility to irrigation infratructure i from a unique monthly houehold panel data et which wa collected in Sri Lanka through extenive field urvey uing tandard quetionnaire modified by u pecifically for thi tudy. We firt employ propenity core matching to quantify the impact of irrigation infratructure acce on individual livelihood. We then invetigate the variou channel through which irrigation reduce chronic and tranient poverty. To do thi we extend the model of the life-cycle permanent income hypothei for a eaonal expenditure deciion imilar to Paxon (1993) by including the difference in irrigation acceibility and endogenou credit contraint. We then evaluate the impact of irrigation infratructure on poverty dynamic. We conduct a wide variety of robutne tet uch a nonnormal error term. 2 Uing ditrict-level data from India Duflo and Pande (2007) find that contructing a dam uptream reduced the advere effect of variability in rainfall poibly through improved irrigation acceibility. 3

6 The ret of the paper i organized a follow. In Section 2 we decribe our data collection procedure in the field and the baic decriptive and poverty tatitic data employed in thi paper. Section 3 ue propenity core matching to how the poverty reduction effect of irrigation. Section 4 explain our theoretical framework and in Section 5 we preent the regreion trategy and reult. Section 6 conclude the paper. 1. The Field Survey A the ample for our evaluation tudy we elected the Walawe Left Bank (hereafter WLB) irrigation ytem in the underdeveloped area of outhern Sri Lanka (Mahaweli Authority of Sri Lanka 2002). The WLB Irrigation Upgrading and Extenion Project for thi ytem wa initiated in 1997 with the help of conceional loan from the Japan Bank for International Cooperation (JBIC) formerly Overea Economic Cooperation Fund (OECF). 3 The irrigation contruction wa implemented in the north firt and then gradually extended to the outh. The government ued lotterie to ditribute land for ome one third of the farmer. Baed on the lottery reult and without regard to their own wihe thee houehold were allotted plot for certain crop (Aoyagi et al. 2010). Houehold who obtained plot in the north were able to have the earlier acce to irrigation. Thi etablihe a natural experimental ituation of exogenouly given irrigation placement which help u identify the caual impact of irrigation contruction. At the time the data ued in thi paper wa being collected the WLB ytem wa diviible into two area: the firt ha adequate acce to irrigation and the econd i a rainfed area with proviion for irrigation in the near future. The entire irrigation infratructure in the firt area already had been rehabilitated and the rainfed area wa adjacent to it. Given thi arrangement the former and latter area can be conidered treatment and control group repectively for thi irrigation contruction project. The type of farming in the tudy area i varied ranging from 3 JBIC formerly OECF provided a total of 2.57 billion (approximately US$ 25 million) for five year tarting from Thi covered about 85% of the total irrigation development cot in thi region. The government of Sri Lanka provided 0.45 billion (US$ 4.4 million). 4

7 irrigated to rainfed and chena (lah and burn) cultivation and the project area exhibit coniderable variability in cropping pattern. The main crop grown include paddy ugarcane banana and other upland crop. Thi ituation i uitable for evaluating the role of infratructure in reducing poverty. Approximately reident are covered under the WLB including government allottee encroacher and member of nonfarm houehold i.e. landle people. In order to elect the repreentative ample houehold we adopted a multitage tratified random ampling trategy uing a complete lit of all the houehold. The actual ample conit of 858 houehold including 660 farm and 198 nonfarm houehold. In the WLB area the Yala (dry) eaon begin in February and end in September and the Maha (rainy) eaon begin in October and extend up to January. Therefore to capture eaonality houehold urvey were conducted five time in 2001 and The firt econd and third urvey took place in June Augut and October 2001 repectively. The firt wa conducted pecifically to obtain monthly data for the previou Maha eaon while the econd and third were deigned to gather data for the Yala eaon. The fourth and fifth urvey were conducted in June and October 2002 repectively to capture information on the 2002 Maha and Yala eaon. Decriptive Statitic A in JBIC and IWMI (2002) the houehold have everal baic characteritic. With regard to houehold livelihood information approximately 75% of houehold head perform agricultural work a their primary occupation. Conumption i divided into two main categorie: food conumption and nonfood conumption (Table 1). 4 Income i calculated by aggregating income from the ale of crop the imputed value of elf-production income from noncrop agriculture uch a livetock and wage from agricultural and nonagricultural ource. Our data 4 Nonfood conumption broadly defined include nondurable expenditure compriing uch item a medical care and education. 5

8 include information on monthly income only for the latter twelve month i.e. from October 2001 to September 2002 while on monthly conumption we have information for twenty-four month from October 2000 to September For the purpoe of our econometric analyi we ue the data pertaining to the congruent twelve month. 5 Irrigation coverage i meaured by the percentage of population that ue water from the irrigation canal. There i an important variation in the irrigation rate ranging from the broadet coverage of 88% in the Sooriyawewa area to merely 13% and 2% in the extenion and rainfed Sevanagala area repectively. While in Table 1 irrigation acceibility appear to be poitively and ytematically correlated with income and aet further careful invetigation i neceary to identify a caual effect of thi infratructure on chronic and tranient poverty. Table 1. Selected Houehold Characteritic by Credit and Irrigation Acceibility Credit Contrained Credit Uncontrained Variable Irrigated Rainfed Irrigated Rainfed Mean S.D. Mean S.D. Mean S.D. Mean S.D. Head Year of Schooling Head Count of Adult Male Head Count of Adult Female Head Count of Children Monthly Food Con. per Adult Male (R.) Monthly Nonfood Con. per Adult Male (R.) Monthly Income per Adult Male (R.) Age of Head Female Head Dummy Land Holding per Adult Male (Acre) Year ince Settlement Experience of Agriculture (Year) In Table 2 we provide decompoition reult of an expenditure-baed poverty index uing the framework of Ravallion (1988) and Kuroaki (2006). We can define aggregate meaure of 5 We alo utilize a et of income and expenditure variable expreed a thoe per adult male equivalent. 6

9 total poverty P chronic poverty P C and tranient poverty P T for a population of N houehold: P (1/N) N E[1-(E i /z)] α P C (1/N) N [1 - E(E i /z)] α and P T (1/N) N {E[1 - (E i /z)] α - [1 - E(E i /z)] α } where E i i the conumption level of individual i and z i a poverty line. We ue total expenditure data for the conumption level E i and calculate the expected value by computing ample average for the twelve month October 2001-September We utilize the poverty gap meaure by etting that α=2. The poverty line i et at 1.25 US dollar baed on the World Bank purchaing power parity adjuted by the local conumer price index (Chen and Ravallion 2008). The decompoition reult for the entire ample both irrigated houehold and unirrigated houehold are given in Table 2. Thi table how houehold without irrigation are more likely to uffer from both tranient and chronic poverty than houehold with irrigation. Alo the impact of irrigation infratructure on reducing chronic poverty may be more ignificant than the impact on tranient poverty. Table 2. Poverty Decompoition Whole Sample Irrigated Unirrigated Total Poverty Chronic Poverty Tranient Poverty The decompoition i baed on the poverty gap meaure. The poverty line i et at 1.25 US dollar. In thi tudy meaurement of the extent of acce to credit i important; yet regular houehold urvey do not include credit information that directly enable an identification of the prevailing credit condition (Scott 2000). To deal with thi iue we carefully deigned a pecial credit module in our quetionnaire to directly identify credit-contrained houehold. In particular we aked two related quetion. Firt we queried the amount of credit a houehold obtained in a particular period; then among thoe who had not obtained credit we aked the reaon for not We employ the age-ex weight ued by Townend (1994) in the context of Southern India. 7

10 borrowing. Houehold reponding that they did not need to borrow are labeled noncredit contrained while houehold liting uch reaon a fear of default or impoibility of borrowing are identified a credit contrained. Of the houehold that had borrowed thoe able to borrow a much a they wanted are conidered uncontrained while the other are conidered contrained. Average monthly conumption by irrigation acceibility i hown in Figure 1. Firtly it i evident that houehold in rainfed area have ytematically lower expenditure throughout the year than thoe in the irrigated area. Thi ugget that the incidence of chronic poverty may be more eriou in the rainfed area than in the irrigated area. 6 Secondly while the expenditure level vary ignificantly depending on the acceibility of irrigation infratructure the pattern of monthly expenditure fluctuation appear to be fairly imilar acro area. Expenditure level are table from October through February increaing in April immediately after the Maha harveting decreaing during May and June and increaing lightly in September after the Yala harveting. A imilar pattern i illutrated in Figure 2 which preent the pattern of monthly income fluctuation. It how a marked increae in income in April and September following the harvet. Figure 1. Monthly Conumption (per Adult Male equivalent; in R.) R. per Adult Male Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr Jun Aug Food Conumption-Irrigated Food Conumption-Rainfed Total Conumption-Irrigated Total Conumption-Rainfed 6 We alo calculate the head count ratio by uing the poverty line of $2.00 per day converted by the PPP. The overall incidence of poverty i approximately 12%. The highet head count ratio i oberved in the Extenion area with 14% and the lowet poverty rate i found in Kiriibbanwewa with 8%. Thee figure indicate that acceibility to irrigation infratructure i ytematically related to the incidence of poverty. 8

11 Figure 2. Monthly Income (per Adult Male equivalent; in R.) R. per Adult Male Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Monthly Income-Irrigated Monthly Income-Rainfed 2. Matching Analyi A pointed out by Banerjee (2005) and Duflo and Kremer (2003) while randomization ha become a de facto tandard for program evaluation in development economic there are ome type of program that cannot be evaluated uing randomization method. Irrigation infratructure may be thi type. In WLB the area covered by our urvey the central government ditributed irrigated land to the poor baed on a et of criteria a nonrandomized ditribution of irrigated land that might bia etimation of the program effect. Land eligibility criteria were et by the Government a follow: recipient hould be married Sri Lankan citizen aged eighteen year or older landle or mallholder with holding of le than 0.8 ha and have an annual income of le than R Additional conideration included length of reidence in the project area houehold ize and recorded current or pat participation in any government organized poverty reduction program. Government official were categorically ineligible. Beneficiarie were choen by the government on the bai of thee criteria. To addre the potential problem of bia caued by thi nonrandomized ditribution we employ the propenity 7 Thi threhold i ignificantly lower than the poverty line et by government agencie (JBIC and IWMI 2002) and the PPP-converted one-dollar-per-day poverty line. 9

12 core matching of Roenbaum and Rubin (1983). In the matching analye we etimate the 1 0 average treatment effect on the treated (ATT) defined a EE E 1 where take the value of unity if a houehold own irrigated land and zero otherwie E S i a houehold expenditure during a eaon S with the irrigated land ownerhip tatu. 8 In the preent analyi the propenity core i etimated uing a probit model for each eaon; that i for the rainy eaon (Maha) and the dry eaon (Yala). While thi enable u to examine change in eaonal effect ariing from acce to irrigation our data do not include information regarding the pretreatment period uch a income and aet prior to irrigation placement. Hence we ue a et of covariate that are conidered to be almot time-invariant; uch a age education level gender of houehold head and the number of male member aged ixteen and above. Table 3 preent the reult of the propenity core etimation. 9 It indicate that houehold with older and more educated houehold head are likely to have better acce to irrigation and that houehold with more male member are more likely to own irrigated land. Thee reult reject the aumption of exogenou or random placement of irrigation facilitie. Our following regreion etimation therefore control for unoberved nonrandom factor by adding everal controlling variable. 8 0 Since 1 E i an unobervable counter-factual ituation we potulate the conditional independency 0 aumption that the log expenditure of rainfed obervation ln E i independent of acce to irrigation conditional on the et of oberved determinant of acce to irrigation. 9 We etimate the propenity core for each eaon eparately. Hence the number of obervation i 845 for each eaon. 10

13 Table 3. Propenity Score for Irrigation Acceibility Maha Yala October to April May to September Age 0.042*** 0.043*** (0.004) (0.004) Sex (0.156) (0.156) Education 0.040*** 0.041*** (0.015) (0.015) Headcount of Male over *** (0.050) 0.130*** (0.049) Contant 2.241*** 2.200*** (0.240) (0.237) N *** denote ignificance at the 1% level; ** at the 5% level; and * at the 10% level.robut tandard error are indicated in parenthee It i traightforward to verify the validity of the etimated propenity core uing the balancing core tet of Roenbaum and Rubin (1983) and Dehejia and Wahba ( ). Conditional on the propenity core the covariate are independent of acceibility to irrigation. The etimated propenity core do not reject the null hypothei; the mean of covariate are the ame between the irrigated and rainfed area for any bundle of propenity core. 10 Thi implie the validity of election on obervable aumption. Moreover there i a poitive probability of either owning or not owning irrigated land for any tratum of the propenity core. Thi indicate that the common upport condition 0 Pr 1 M 1 i atified in our pecification. We quantify the ATT for income food conumption nonfood conumption total conumption and the indicator value of credit contraint. Table 4 preent the etimated ATT of acce to irrigation on eaonal and monthly variable. 10 Thee figure are available from the correponding author upon requet. 11

14 Table 4. Etimated Seaonal ATT Method: Propenity Score Matching with a Matching Radiu of Monthly Income Food Con. Nonfood Con. Total Con. Credit Contraint N ATT N ATT N ATT N ATT N ATT Seaonal/Annual Maha 310.9* 134.9*** 174.0*** 296.8*** (Rainy) (173.1) (42.3) (38.8) (66.2) (0.03) Yala 381.8** 153.1*** 197.6*** 342.4*** 0.056* (Dry) (159.2) (43.0) (59.7) (80.7) (0.029) Annual *** 137.2*** 180.2*** 305.1*** (115.7) (38.2) (35.9) (60.5) Monthly Oct ** 136.3*** 525 (222.60) (41.7) 512 Nov *** 527 (355.4) (41.7) 511 Dec *** 527 (233.2) (43.9) 513 Jan ** 526 (255.4) (42.5) 519 Feb ** 526 (210.1) (45.0) 512 Mar ** 207.0*** 526 (387.9) (46.9) 517 Apr * 133.5** 525 (861.1) (60.0) 526 May *** 531 (312.1) (48.0) 524 Jun *** 530 (256.7) (45.3) 528 Jul *** 531 (284.6) (43.5) 525 Aug *** 532 (272.9) (44.9) 522 Sep *** 149.4*** 532 (434.2) (47.5) 528 Outcome variable are monthly averaged value *** (41.3) 160.7*** (39.7) 208.2*** (72.1) 151.3* (82.3) (83.8) (97.9) 283.3*** (102.6) 232.8* (120.1) (133.1) (87.1) 235.5** (109.3) 249.7** (112.1) *** (63.9) 281.3*** (62.4) 329.8*** (90.5) 197.3** (81.9) 190.1* (99.7) 346.1*** (119.2) 425.8*** (140.1) 386.5*** (139.7) 262.4* (144.5) 279.3*** (103.2) 386.2*** (121.4) 391.7*** (128.1) *** denote ignificance at the 1% level; ** at the 5% level; and * at the 10% level. 12

15 The radiu matching method with a radiu of i ued to contruct the matching group. 11 A erie of matching etimation indicate that the effect of irrigation on income and conumption are poitive and tatitically ignificant for all eaon; thi implie that acceibility to irrigated land ignificantly reduce poverty. Not urpriingly the etimated impact are greater in the dry eaon. While in the late- and pot-harvet month of March April September and October we oberve poitive and ignificant effect of irrigation on income; in the non-harvet month the ATT etimate are tatitically inignificant. According to the point etimate with irrigation acceibility per capita income per capita food and per capita non-food conumption expenditure increae by around 17.8% 12.2% and 37.6% repectively evaluated at the average level among the treated. The etimated effect on credit contraint during the rainy and dry eaon are and repectively. The effect i tatitically ignificant in the dry eaon at the 10% ignificance level uggeting that acceibility to irrigation decreae the probability of binding credit contraint by 5.6% during the dry eaon. 3. Modeling the role of infratructure in poverty reduction dynamic Given the overall poverty reduction effect hown in the previou ection we aim in thi ection to capture the channel through which irrigation reduce poverty. To do thi we extend Paxon (1993) eaonal conumption model by introducing endogenou credit contraint. Each houehold determine eaonal conumption by maximizing it lifetime utility ubject to it intertemporal budget contraint. Here we aume that all the houehold have perfect credit market acceibility. A houehold ha a time-eparable contant relative rik averion (CRRA) utility function U(C t ) = (C t ) 1-a (1 a) -1 of the houehold conumption C t in eaon in year t. For purpoe of expoition we exclude the year ubcript in the following preentation. 11 We alo attempt variou alternative pecification of matching etimation a follow: the radiu matching with a wider radiu (r = 0.05) the nearet neighbor matching with replacement conumption level rather than logarithm and the firt tage covariate conitent with the previou tructural etimation. Thee etimation generate comparable qualitative reult to the benchmark matching etimation reult. 13

16 repreent a tate parameter and a i the coefficient of relative rik averion. The houehold deciion problem i to chooe C t that maximize the dicounted lifetime utility with a eaonal dicount factor ubject to an intertemporal budget contraint with eaonal income Y t houehold aet at the beginning of the period W and exogenou eaonal interet rate r R 1. Auming no conumption tilting i.e. R = 1 we have the following optimal expenditure for eaon : (1) E * R where E * = P C with P j repreenting the price of conumption in eaon ; and are utility weight aigned to conumption in eaon and total houehold aet repectively; i.e. they correpond to the um of human and initial phyical aet. verion of the life-cycle permanent income hypothei. Note that Equation (1) i an extended The utility weight involve the tate parameter in the utility function and the relative conumption price in the two period. Defining Y a the um of expenditure in different period we have Y = R becaue = 1. Note that Y meaure the total annual income incluive of net annual interet earning for the year. Thu far we have aumed perfect credit market acceibility. In order to introduce the poibility of binding credit contraint captured by income volatility we follow Flavin (1981) and Paxon (1993) and aume that the expenditure at i a weighted average of the optimal expenditure at and income in that eaon: (2) E ( 1) E * Y where repreent the degree of credit contraint. If = 0 then the credit contraint i not binding and if = 1 it i perfectly binding. Recalling that Y = R Equation (2) can be rewritten a E Y (1 ) A ] where A Y /Y; i.e. the fraction of annual income earned in eaon. [ By log-linearizing thi equation we obtain the tructural form of the eaonal expenditure model: (3) ln E lny (1 ) A 1 Irrigation increae conumption and reduce chronic and tranient poverty through multiple path. Conceptually we conider four channel for evaluating the role of irrigation 14

17 infratructure: firt impact on permanent income Y; econd demand for credit by changing income fluctuation pattern A ; third upply of credit through change in creditworthine; and finally other channel uch a preference and time allocation. To quantify the relative importance of the different channel we conider the following etimation equation: Y 0 (4) ln E γ lny γ γ γ γk H k u where include demographic houehold head characteritic and geographic characteritic; i the ize of irrigated land and it coefficient; γ repreent time-invariant impact of irrigation 0 through non-income channel uch a change in preference; and following Paxon (1993) denote common month-pecific effect reflecting month-pecific preference and price. The 0 three term γ γ and γ on the right-hand ide of Equation (4) correpond to the econd term on the right-hand ide of Equation (3). The fifth term on the right-hand ide of Equation (4) γ k H k capture the income fluctuation term in Equation (3) i.e. πa S where H k (k = 1 2 3) are the binary variable repreenting the harvet period of the rainy eaon (March and April) planting period of the dry eaon (May and June) and harvet period of the dry eaon (July to September) repectively. The remaining eaon (October to February) i the planting period of the rainy eaon which i ued a the reference eaon. Hence the coefficient γ k on the interaction term of the binary variable H k and irrigated land ize S capture the remaining time-dependent impact of irrigation which mainly include change in income fluctuation pattern. In other word a can be een in the fifth term on the right-hand ide of Equation (4) we take the interaction term H k S a the intrument for the endogenou variable A. Following the theoretical implication if the credit contraint i not binding i.e. = 0 then the parameter k hould jointly be zero. Thi i a joint tet for credit acceibility and effectivene of irrigation on increaing income. A to the identifying intrumental variable to handle the endogeneity problem of permanent income after careful invetigation of ixteen type of agricultural aet and eighteen type of nonagricultural 15

18 aet we decide to employ the holding of ewing machine and mall tractor. 12 Endogenou Credit Contraint In the development literature it i commonly accepted that poor houehold in developing countrie which typically are compried of landle farmer have only limited acce to credit. While irrigation acceibility potentially affect the demand for credit by affecting income fluctuation pattern it could alo affect the upply of credit a determined by creditworthine. Thi tudy examine the overall impact of irrigation on the credit contraint. A conventional empirical approach for incorporating credit contraint into etimation model ignore the endogeneity of the contraint and exogenouly plit the ample into thoe contituent likely to be credit contrained and thoe not likely to be o (Foter 1995). In contrat following Jappelli (1990) we introduce an empirical model of endogenou credit contraint. Recall that E* repreent the optimal LC-PIH conumption in the abence of current credit contraint. Then E* = E hold if the credit contraint i not binding while E* > E hold if the credit contraint i binding. A dicrete model of credit contraint i obtained a follow: (5) cc [ S 0] where 1[ ] denote an indicator function for a dicrete variable of credit contraint cc; S include binary variable to repreent unanticipated negative hock uch a damage to plot from wild animal or water hortage; and denote an error term that capture unoberved element and a meaurement error. Program Placement Note that Equation (4) can be viewed a a linear program evaluation equation (Lee 2005). 12 The criteria for chooing thee two variable are high adoption rate and low poibility of violating the excluion retriction. Compared to other aet uch a motor-cycle and electric cooker ewing machine and mall tractor are productive aet and are le likely to affect conumption dynamic through channel other than income. Alo the adoption rate of ewing machine and mall tractor are 39.4% and 12.5% repectively while only 2.0% of houehold for intance own hand threher. 16

19 The parameter k capture the extra amount of expenditure that farmer can achieve with irrigation acce; thee are expenditure that are enabled by the irrigation infratructure or imply by the eaon-pecific treatment effect of irrigation infratructure. However an endogeneity iue remain to be addreed. Since our data are taken from a newly developed farming area irrigation acceibility ha been determined by the government land allocation rule. Specifically the government provided irrigated land mainly to the poor a decribed above in Section 2. The correlation between conumption and unoberved determinant of irrigation acceibility ha the potential to generate bia in the etimated coefficient. Yet the correlation i likely to be negative and therefore from the viewpoint of thi tudy the irrigation acceibility variable may underetimate rather than overetimate irrigation impact. In order to mitigate thi endogeneity problem we conduct robutne tet uing among other the fixed effect model in addition to the propenity core matching method. 4. Regreion Analyi One of the mot important effect of acce to irrigation i likely to be an increae in annual income overall. Not only will irrigation allow farmer to grow more valuable crop in the dry eaon but it may alo allow more intenive cultivation in the rainy eaon. To addre thi income effect of irrigation we etimate a linear regreion model of permanent income in which we regre average houehold income over twelve month on a et of houehold human and phyical aet variable. Table 5 report the etimation reult of the permanent income model. Irrigated land ize ha poitive and tatitically ignificant coefficient on permanent income. While the eaonal effect of irrigated land ize on permanent income are negative during dry eaon planting and harveting tage our joint tet reult how that the total effect of irrigated land ize are poitive and tatitically ignificant. Human and phyical aet variable uch a level of education of the head of houehold number of adult male member and ownerhip of ewing machine and tractor alo are poitively related to the level of permanent income. 17

20 Table 5. Permanent Income Regreion Dependent Variable: Permanent Income Coef. Std. Err. Irrigated Land *** Unirrigated Land *** Age of Head *** Female Head Age of Head x Female Head Education of Head *** Head Count of Adult Male *** Head Count of Adult Female *** Head Count of Children *** Ditance to Local Bu Terminal ** Ditance to Daily Market ** Seaonal Effect of Irrigated Land Size Harvet in Rainy Seaon Planting in Dry Seaon * Harvet in Dry Seaon * Value of Sewing Machine *** Value of Small Tractor * F-tatitic for zero Total Seaonal Irrigation Harvet in Rainy Seaon *** Planting in Dry Seaon *** Harvet in Dry Seaon *** Joint Tet *** N 8168 *** denote ignificance at the 1% level; ** at the 5% level; and * at the 10% level. Month effect which are not reported in the table are alo included in the etimation. Our main econometric analyi i compried of the following three model: firt we conduct reduced form etimation for the eaonal expenditure baed on Equation (4); econd to tet the validity of our model framework we etimate the tructural model of Equation (3); and finally we conduct a wide range of tet for robutne. Etimation Reult 1: Reduced Form Etimation We firt attempt to etimate Equation (4) by addreing two endogeneity problem: firtly 18

21 19 we mitigate the endogeneity of the permanent income variable uing the intrumental variable method. Secondly in order to cope with the ample election bia ariing from endogenou credit contraint we combine the dummy endogenou variable pecification for credit contraint in Equation (5) with the eaonal expenditure model in Equation (4). Accordingly we have the following econometric model of expenditure with and without endogenou credit contraint in which ample election correction term are included under joint normality of error term (Lee 1978; Amemiya 1985): (6) C C k C k C C C C Y u S S φ γ H γ γ γ γ Y γ E ) ( ) ( ln ln if cc = 1 (7) N N k N k N N N N Y u S S φ γ H γ γ γ γ Y γ E ) ( 1 ) ( ln ln if cc = 0 where upercript C and N denote the credit contrained and uncontrained group and φ ( ) and Φ( ) repreent the probability denity and cumulative denity function of tandard normal ditribution. In Equation (6) and (7) the time-dependent irrigation enitivity parameter C and N capture the indirect impact of irrigation on expenditure through changing income fluctuation. The time-invariant irrigation enitivity parameter C and N capture the direct role of irrigation infratructure on expenditure. According to the etimation reult of the credit contraint equation reported in Table 6 the probability of binding credit contraint i negatively related to irrigated land ize. Thi reult implie that loan proviion are poitively affected by acce to irrigation facilitie poibly through enhanced land value a collateral. After controlling the endogenou permanent income and credit contraint Panel A of Table 7 report the reduced form etimation reult for the houehold expenditure model. While the eaon-pecific effect of irrigated land ize through income on

22 expenditure and C N are not alway poitive and ignificant the joint F tet for thee effect how that irrigation ha an overall poitive and ignificant effect on houehold expenditure for the contrained group. By contrat for the uncontrained group the overall eaon-pecific irrigation effect are not different from zero. Thee reult are conitent with the theoretical implication of the intertemporal model of expenditure with and without binding credit contraint. Intriguingly the time-invariant irrigation effect are poitive and tatitically ignificant only for the C contrained group i.e. γ 0 uggeting that irrigation acceibility could reduce poverty via path other than improvement in credit acceibility. Table 6. Etimated Marginal Effect of the Credit Contraint Equation Method: Probit model Dependent Variable: Credit Contraint Marginal Effect Std. Err. Irrigated Land *** Unirrigated Land Age of Head Female Head * Age of Head x Female Head * Education of Head *** Head Count of Adult Male *** Head Count of Adult Female * Head Count of Children Ditance to Local Bu Terminal *** Ditance to Daily Market *** Seaonal Fraction of Farming Land with Water Shortage Rainy Seaon Dry Seaon Attacked by Wild Animal N 8168 *** denote ignificance at the 1% level; ** at the 5% level; and * at the 10% level. For female head and attacked by wild animal dummy variable dicrete marginal effect when the variable hift from zero to one i reported. 20

23 Table 7. Etimated Reult of the Reduced Form and Structural Form Expenditure Equation Panel A: Reduced Form Panel B: Structural Form Credit Contrained Credit Uncontrained Credit Contrained Credit Uncontrained Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Permanent Income # ** # *** ## *** ## *** Income Ratio () ## ** ## Irrigated Land *** *** * ** Unirrigated Land ** *** *** Age of Head ** Female Head * *** *** Age of Head x Female Head *** *** Education of Head *** *** ** *** Head Count of Adult Male * *** *** Head Count of Adult Female *** *** Head Count of Children ** * Ditance to Local Bu Terminal *** *** ** *** Ditance to Daily Market *** *** ** *** Seaonal Effect of Irrigated Land Size Harvet in Rainy Seaon Planting in Dry Seaon * Harvet in Dry Seaon ** Sample Selection Correction Term ** *** * *** Monthly Effect Ye Ye Ye Ye F Statitic for no Seaonal Irrigation Effect 9.81 ** 4.15 F Stat. for 1t Stage Intrument (Permanent Income) 7.48 *** *** 3.45 *** *** F Stat. for 1t Stage Intrument (Income Ratio) 2.61 ** 2.44 ** Sargan Statitic for Over-identification N *** denote ignificance at the 1% level; ** at the 5% level; and * at the 10% level. # denote an endogenou variable where the identifying intrumental variable include value of ewing machine and value of mall tractor. ## denote endogenou variable where the identifying intrumental variable include three eaonal effect of irrigated land ize (i.e. harvet in rainy eaon planting in dry eaon and harvet in dry eaon) value of ewing machine and value of mall tractor. 21

24 22 Etimation Reult 2: Structural Etimation The reduced form model reult cannot directly quantify the degree of credit contraint. Hence we invetigate the eaonal effect by etimating the tructural model of Equation (3) with the endogenou credit contraint of Equation (5). By including the ample election correction term under joint normality of error term the etimation verion of Equation (3) and (5) become: (8) C C C C S C C S C Y ν S S φ δ A π δ δ δ Y δ E ) ( ) ( ln ln if cc j = 1 (9) N N N N S N N S N Y ν S S φ δ A π δ δ δ Y δ E ) ( 1 ) ( ln ln if cc j = 0 where are captured by monthly dummy variable. The income hare variable A i treated a an endogenou variable which i intrumented by the interaction variable of eaon dummie and irrigated land ize H k S a well a productive aet variable a before. The tet on the theoretical hypothee 0 < C <1 and N = 0 will provide further direct evidence of the extent to which conumption i moothed againt income fluctuation. Panel B of Table 7 report the etimation reult of the tructural model. For conumption of the credit contrained group the coefficient of monthly income fluctuation π C are poitive and ignificant. Further their 95% confidence interval are [ ] and located within the range of [01]. On the other hand the monthly income coefficient for the uncontrained houehold π N i not tatitically different from zero. Conumption by the contrained group track the fluctuated income path uggeting that people under credit contraint cope with negative economic hock by reducing conumption. By contrat the uncontrained group are able to mooth their conumption path under income fluctuation. The reult ummarized here provide upportive evidence for our theoretical framework.

25 Etimation Reult 3: Robutne Tet 13 Here we perform three robutne tet on our reult: an alternative pecification non-normality of error term and nonrandom irrigation placement. For the firt robutne tet we employ an alternative model pecification in which we do not control for the time-invariant direct effect of the irrigated land ize i.e. γ. While thi alternative model i comparable to the one developed by Paxon (1993) the model i retricted in the ene that it conider only the indirect effect of irrigation infratructure on expenditure through increaed permanent income eaed credit contraint and moothed monthly conumption. Baically the qualitative reult are comparable to the reult of the previou model preented in thi paper with the notable exception of the over-identification tet reult in the tructural etimation. Without the time-invariable direct effect we reject the orthogonality condition of the Sargan over-identification tet. Thi reult may upport the incluion of the direct effect variable in our regreion analye. Thu far the eaonal expenditure model with the endogenou credit contraint ha been etimated under the aumption that the error term in the reduced and tructural form model follow trivariate joint normal ditribution. However if thi aumption doe not hold it i likely that the econd tep etimator are eriouly biaed. Hence for the econd robutne tet we relax the normality aumption by adopting the approach propoed by Lee (1982) and Newey Powell and Walker (1990). The qualitative reult are comparable even under a relaxed normality aumption. For the third robutne tet to correct bia ariing from the nonrandomized ditribution of irrigated land we mitigate the correlation between unoberved heterogeneity and program placement by including houehold fixed effect. We reerve the endogeneity iue of the credit contraint and imply etimate the reduced form model of Equation (6) and (7) by 13 The reult of thee robutne tet are not preented in thi paper but are available in the electronic Appendix. 23

26 incorporating houehold fixed effect. 14 The etimation reult are the ame qualitatively a without houehold fixed effect. Concluion In thi paper we identify a relationhip between infratructure development and poverty reduction with regard to eaonal fluctuation in conumption expenditure. We find that irrigation reduce chronic poverty by enhancing permanent income and that it alo eliminate the negative impact of tranient poverty by reducing the downide expenditure rik. The point etimate derived by the propenity core matching method how that with irrigation acceibility per capita income and per capita food and non-food conumption expenditure increae by around 17.8% 12.2% and 37.6% repectively when evaluated at the average level among the treated and that the probability of binding credit contraint i reduced by 5.6% during the dry eaon. Our reult provide evidence in upport of the role of infratructure in reducing both chronic and tranient poverty. Since very few micro-econometric tudie have analyzed the role of infratructure in mitigating chronic and tranient poverty we believe that thi paper will cloe an important gap in the exiting literature. Intriguingly we find that there i a poitive and ignificant time-invariant irrigation effect on expenditure only for the credit contrained group. Thi finding ugget that irrigation acce can reduce poverty via multiple path apart from improvement in credit acceibility. Uually when irrigation infratructure i contructed other type of infratructure uch a road and electricity facilitie are developed alongide. The unexplained poitive irrigation effect on the credit contrained group may be attributable to thi apect of infratructure development. Further exploration of thee broader external effect of irrigation infratructure hould be purued in future tudie. 14 Since incluion of houehold fixed effect render the permanent income coefficient unidentifiable we include the two aet variable ued a the excluion retriction in the expenditure equation. 24

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