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8/10/2019 Maintain Roads When the Sun Shines: Impacts of Road Access on Subjective Well-being in Timor-Leste
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Maintain Roads When the Sun Shines:
Impacts of Road Access on Subjective
Well-being in Timor-Leste
Aekapol Chongvilaivan, PARD
Kiyoshi Taniguchi, PSOD
Rommel Rabanal, PARD8 October 2014
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Impact
Motivation from ADB operations
Outcome
Output
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Accessing Dili during rainy season was really difficult.
Due to bad roads caused by landslides and flooding,
people lack access to basic services.
Local Driver
3
Motivation from the Field
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Objectives
What matters to Timoreses well-being? Quantity vs. quality of roads
Implications for ADBs operations?
4
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Roads in Timor-Leste
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Roads after rains (1)
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Roads after rains (2)
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Roads after rains (3)
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Hypothesis
Quality matters more than quantity. Qualityaccessibility during rainy season.
Quantitywalk time to facilities.
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How to measure well-being?
Subjective, self-reported. Concerning your households over the past
one month, which of the following is true?
More than adequatethe happiest Just adequate
Less than adequatethe least happy
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Empirical strategy
Ordered PROBIT Estimations The marginal effects
Robustness check (1): OLS, OLOGIT
Robustness check (2): Redo with the 2001 TSLS
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Dataset
Timor-Leste Survey of Living Standards (TSLS)2007
Nationally representative
1,800 households
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Summary of statisticsVariable No. of Obs. Mean S.D. Min Max
Road Access Variables:
Walk time (min.) to a community center ( iWTAC ) 1,800 24.88 47.44 0 510Walk time (min.) to nearest roads (
iWTNR ) 1,800 8.62 22.34 0 210
Is road accessible during rainy season? (i
RROAD ) 1,800 0.84 0.37 0 1
Yes 1iRROAD 1,513 ---- ---- ---- ----
No 0iRROAD 287 ---- ---- ---- ----
Household Characteristics:
Rent expenditure, )ln( irent 1,800 10.29 1.49 4.71 14.51
Utility consumption, )ln( iutility 1,749 8.97 1.05 5.30 12.61
Food consumption, )ln( ifood 1,109 4.56 1.12 0.21 7.40
Non-food consumption, )ln( infood 1,704 2.41 1.27 0.01 6.62
Household size ( iHHSIZE) 1,800 5.06 2.51 1.0 19.0
Is a household poor? ( iPOOR ) 1,800 0.21 0.41 0 1
Yes 1iPOOR 384 ---- ---- ---- ----
No 0iPOOR 1,416 ---- ---- ---- ----
Does your household have children? ( iCHILD ) 1,800 0.91 0.29 0 1Yes 1iCHILD 1,629 ---- ---- ---- ----
No 0iCHILD 171 ---- ---- ---- ----
Geographical LocationsDili 378 ---- ---- ---- ----Baucau 72 ---- ---- ---- ----
Other urban areas 252 ---- ---- ---- ----Rural areas 1,098 ---- ---- ---- ----
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Correlation matrix
iWTAC
iWTNR
iRROAD
)ln( irent
)ln( iutility
)ln( ifood
)ln( infood
iHHSIZE
iPOOR
iCHILD
Dili Bacau Other urban
iWTAC 1
iWTNR 0.30 1
iRROAD -0.21 -0.36 1)ln( irent -0.10 -0.07 0.12 1
)ln( iutility -0.17 -0.12 0.23 0.31 1)ln( ifood -0.01 0.04 -0.03 0.26 0.22 1)ln(
i
nfood 0.03 -0.03 0.03 0.46 0.19 0.29 1
iHHSIZE -0.05 -0.003 0.03 -0.09 -0.24 -0.17 -0.01 1
iPOOR 0.18 0.19 -0.11 0.01 -0.12 0.13 -0.02 0.001 1
iCHILD -0.16 -0.07 0.07 -0.10 -0.07 -0.18 -0.11 0.30 -0.05 1Dili 0.04 -0.04 0.09 0.12 0.15 0.14 0.15 0.01 0.03 -0.005 1
Baucau -0.15 -0.05 0.17 0.51 0.27 0.11 0.27 0.23 0.02 0.06 -0.11 1
Other urban areas -0.03 -0.01 0.02 -0.02 -0.05 -0.07 -0.07 0.03 -0.09 0.04 -0.09 -0.18 1
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OPROBIT Results
Dependent variable: Levels of subjective well-being
Variable Food Housing Clothing Healthcare Income Child Edu.
iWTAC 0002. (.0013)***0061. (.0016) 0017. (.0015) 0004. (.0012) 0009. (.0016) ***0046. (.0017)
iWTNR 0001. (.0023)**0051. (.0025) 00001. (.0023) *0036. (.0021) 0034. (.0026) 0005. (.0026)
iRROAD ***7432. (.1351) ***5328. (.1290) ***4208. (.1342) ***7691. (.1209) ***4891. (.1457) ***4573. (.1300)
)ln( irent *0674. (.0349) ***1722. (.0362) ***1190. (.0370) 0079. (.0344) *0634. (.0375) *0341. (.0362)
)ln( iutility ***2261. (.0448) ***1675. (.0455) ***1787. (.0461) ***2762. (.0444) ***1785. (.0468) ***1570. (.0448)
)ln( ifood ***1312. (.0390) 0026. (.0383) **1014. (.0407) 0004. (.0374) ***1669. (.0455) ***1323. (.0418)
)ln( infood ***
1850. (.0322)**
0701. (.0314)***
1737. (.0333) 0307.
(.0324)***
1380. (.0340)**
0705. (.0313)
iHHSIZE***0613. (.0194) ***0512. (.0181) ***0567. (.0196) ***0538. (.0172) ***0618. (.0186) ***0842. (.0183)
iPOOR ***3317. (.1029) ***4467. (.1100) ***3677. (.1062) ***3669. (.1030) 1297. (.1107) ***3001. (.1142)
iCHILD 1176. (.1538) 2421. (.1622)***4576. (.1542) 0867. (.1539) 1269. (.1891) -----
Dili 1139. (.1842) 2850. (.1895) 0854. (.1920) 1124. (.2076) **4410. (.1984) 0607. (.1957)
Baucau 2057. (.1363) ***4275. (.1418) **3289. (.1358) **2937. (.1341) 1208. (.1363) 1329. (.1372)
Other urban areas 1905. (.1235) *2107. (.1249) **3108. (.1225) 1976. (.1321) 1278. (.1314) **3061. (.1336)
No. of Obs. 1,073 1,073 1,073 1,073 1,073 977
Wald Chi-squared ***59.232 ***71.202 ***71.211 ***18.162 ***84.140 **38.136
Pseudo R-squared .1638 .1677 .1703 .1115 .1263 .1008
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How to read Marginal Effects (ME)?
If 1 min. further away If road is accessible during rainy season
ME = Change in probability of reporting X
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If Aldeia is farther by 1 min.,
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If nearest roads farther by 1 min.,
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If roads usable during rainy season
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Implications on ADBs Operations
Road maintenance neededImpact evaluationquantity vs. quality
Area for opsrehabilitation, all-weather roads
X No need for new roads
X Other economic outcomes?
X Project prioritization
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Thank you.
Aekapol Chongvilaivan
Kiyoshi Taniguchi
Rommel Rabanal