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The Role of Infrastructure in Reducing Chronic and Transient Poverty The Case of JBIC Supported Irrigation Project in Sri Lanka Yasuyuki Sawada, Masahiro.

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Presentation on theme: "The Role of Infrastructure in Reducing Chronic and Transient Poverty The Case of JBIC Supported Irrigation Project in Sri Lanka Yasuyuki Sawada, Masahiro."— Presentation transcript:

1 The Role of Infrastructure in Reducing Chronic and Transient Poverty The Case of JBIC Supported Irrigation Project in Sri Lanka Yasuyuki Sawada, Masahiro Shoji, and Shinya Sugawara University of Tokyo

2 2 Research Objective and Strategy Is infrastructure an effective and efficient device to reduce poverty? Does irrigation infrastructure play an important role in reducing chronic and transient poverty? Research strategy: evaluation of a large irrigation infrastructure project in Southern Sri Lanka funded by the Japanese government through JBIC

3 3 Presentation Outline Overview of the project Data description Econometric analysis Results

4 4 JBICs WLB project in Sri Lanka to be examined The Walawe Left Bank Upgrading and Extension Project –Initiated in 1997 –Funded by the Japanese gov t through JBIC –Improvements of irrigation systems completed in 2001 (Phase I) –On-going extensions (Phase II-)

5 5 JBIC Institutes Evaluation Project in Sri Lanka Impact assessment of irrigation infrastructure development on poverty reduction –Collaboration with IWMI –858 households were randomly sampled from six strata of the whole left bank area –Unique household panel data exclusively for the study Rare seasonal panel for two years: Maha (Rainy) Yala (Dry) Maha (Rainy) Yala (Dry) Oct nd Jul. 3rd Oct. 4th May th Sep. 1st May 2001

6 6 Descriptive statistics Fig 1. Average monthly expenditure per adult male Rainy season: Oct~March (Maha); Dry season: April~Sep (Yala)

7 7 Descriptive statistics Fig 2. Average monthly Ag. Income per adult male Rainy season: Oct~March (Maha); Dry season: April~Sep (Yala) Average income: 799Rs. in irrigated, 610Rs. in rainfed.

8 8 Empirical model A Estimation equation a la Paxson (1993) We regress monthly household expenditure (E) on –constant –log income (lnY) –monthly dummies (M) –interactions of M with irrigation dummies (z).

9 9 Table 5. Estimation result of model A FoodNon Food Log of average monthly income (measure of permanent income) (28.55) (13.55) N t-values in parentheses.

10 10 Estimation Result of Empirical Model A: Fig 3. Month effects of expenditure by irrigation availability Rainy season: Oct~March (Maha); Dry season: April~Sep (Yala)

11 11 Summary of empirical model A There are significant differences in the month effects b/w irrigated and rainfed areas: –Chronic poverty is more serious in the rainfed area –Decreasing month effects of non-food consumption in planting season, suggesting transient poverty in both areas

12 12 Empirical model B Consider poverty dynamics, particularly the role of credit explicitly Estimation equations (Type 5 Tobit model): if Hj < 0, If credit constraint is binding if Hj 0. If credit constraint is not binding

13 13 Estimation result of empirical model B: Probit estimation of credit constraint eq. (reduced form version of Table 7) Credit Constraint Coef.Std. Err. Access to Irrigation Dummy-0.188***0.041 Active Organization Membership-0.165***0.042 Land Holding0.120*0.070 (Land Holding) *0.022 Monthly Income1.94E E-06 (Monthly Income) E E-10 Age of Head0.004**0.002 Female Head0.115**0.055 Head Count of Adult Male-0.051***0.019 Head Count of Adult Female Head Count of Children Constant-1.250***0.093 N9060

14 14 Table 8 and 9. Estimation result of model B: ConstrainedUnconstrained FoodNon FoodFoodNon Food Log of average monthly income (measure of permanent income) (9.65) (3.53) (25.90) (11.95) t-values in parentheses.

15 15 Estimation result of empirical model B: unconstrained group (Table 5) Rainy season: Oct~March (Maha); Dry season: April~Sep (Yala)

16 16 Estimation result of empirical model B: Credit constrained group (Table 4) Rainy season: Oct~March (Maha); Dry season: April~Sep (Yala)

17 17 Summary of empirical model B Access to irrigation mitigates : –probability of binding credit constraint –negative welfare effects of credit constraints The monthly effects for the irrigated group seems consistently larger than those for the rainfed group. –Statistically, the difference is significant for un-constrained group –As to the constrained group, the gap of non-food consumption during Yala season is significant –However, credit constraints cannot fully explain the remaining differences in the month effects between the irrigated and rainfed groups, suggesting that irrigation accessibility reduce poverty through multiple paths other than improvements in credit accessibilities.

18 18 A test of the model structure We test the validity of Paxson (1993) structure by using the following framework: –Examine whether household expenditure is sensitive to income changes, treating the change as an endogenous variable –Investigate the coefficients on income variability π where the lack of credit accessibility will enhance vulnerability even with irrigation. if Hj < 0, If credit constraint is binding if Hj 0. If credit constraint is not binding

19 19 Table 11 and 12 A test of the model structure t-values in parentheses. Constrained Group Unconstrained Group Food Non Food Food Non Food The smoother parameter π Ratio of income earned in month to average monthly income (-0.75) 0.21 (2.12) (0.41) (0.21) Permanent income Average monthly income 0.14 (3.43) 0.62 (3.69) 0.17 (10.82) 0.25 (7.91)

20 20 Concluding remarks Irrigation reduces chronic poverty by enhancing permanent income possibly through improving productivity of agriculture. Access to Irrigation enhances credit availability of households –Theoretically, this will mitigate the negative welfare effects arising from seasonality, i. e., transient poverty However, credit constraints cannot fully explain the remaining differences in the month effects between the irrigated and rainfed groups. –This suggest that irrigation accessibility reduce poverty through multiple paths other than improvements in credit accessibilities.

21 21 Thank you very much!


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