How road quality investments boost economic activity and welfare: Evidence from Indonesia s Highways

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How road quality investments boost economic activity and welfare: Evidence from Indonesia s Highways Paul J. Gertler (UC Berkeley) Marco Gonzalez-Navarro (U of Toronto) Tadeja Gracner (UC Berkeley) Alexander D. Rothenberg (RAND) today

Research Question How does road quality affect economic activity and household s welfare in developing countries? 1 Firms 2 Households 3 Welfare

Preview of Results 1 Profits Total factor productivity Value added 2 Agricultural profits No change in manufacturing wages Dual labor markets? Switching from agriculture to manufacturing Switching from informal to formal sector In-migration of workers 3 Total earnings Consumption Land values

Indonesia Context Population: 250 million GDP PC PPP (2010): $4,600 51% urban Agriculture: 14% of GDP, 39% of labor force Industry: 47% of GDP, 22% of labor force Services: 38% of GDP, 47% of labor force

Background Most Indonesian roads built in colonial times: variation in road quality only. Transportation a development priority in the 1990s: Repelitas: five-year development plans Revised infrequently Funds towards road improvements instead of building new road networks Two Step Budgeting We study the effects on household s welfare due to these large changes in road quality (deterioration and upgrades) in Indonesia between 1993 and 2007.

Data: Panel of Road Quality at the Road Segment Level Road quality panel data of International Roughness Index (IRI) (1993-2007) on 10 km sections of all major inter-urban roads. Transform IRI to roughness-induced travel time: IRI rdt = R r=1 d r IRI rdt R r=1 d r d r = length of the road segment r in district d t = time

Road System: Sumatra: 1990

Road System: Sumatra 2000

International Roughness Index (IRI), 1990 and 2000 Kernel density estimates of average IRI across kabupatens.

Time variation in roughness index Substantial variation in the timing and extent of road improvements.

Data: Indonesian Family Life Survey IFLS: Panel data on individuals and households 4 waves: 1993, 1997, 2000, 2007. Follows over 30,000 individuals, living in 13 of the 27 provinces in the country

Locations of IFLS Villages

Other Datasets Industrial Survey (Survei Industri) Census of all manufacturing establishments with more than 20 employees

Identification We don t have an experiment. But we have very detailed data with repeated observations of the same individual over a long time span We use person fixed effects estimation (How do changes in family outcomes correlate to changes in road quality?) Our preferred estimates use Instrumental Variables estimation where the instrument for road quality is road budgets for each road maintenance authority

Two-step budgeting: Institutional Road Sector Arrangement Source: World Bank (2012).

Results: Exclusion Restriction DV: log Budget t Province Panel District Panel Nat. roads Nat. roads Prov. roads Prov. roads District roads District roads (1) (2) (3) (4) (5) (6) log GDP t 2-0.080-0.584-0.087 (0.185) (0.506) (0.118) log #Firms t 2-0.080-0.291-0.086 (0.124) (0.284) (0.065) N 241 256 249 265 545 568 Adjusted R 2 0.319 0.310 0.389 0.363 0.091 0.097 Road FE No No No No No No Year FE Yes Yes Yes Yes Yes Yes Robust standard errors in parentheses, clustered at the road segment level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Firms and Value Added DV: Log Value Added (1) (2) Log Avg IRI -0.138-0.074 (0.036)*** (0.031)** N 234134 230096 N Firms 29362 29362 Adjusted R 2 0.467 0.859 Regression F Statistic 15.048 5.624 Kleibergen-Paap F -Stat 2032.975 1821.119 Year FE Yes Yes Industry FE Yes Yes Kabupaten / Kota FE Yes Yes Firm FE. Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the firm level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Firms and TFP DV: Log TFP (1) (2) Log Avg IRI -0.099-0.134 (0.040)** (0.037)*** N 126629 122859 N Firms 19073 19073 Adjusted R 2 0.480 0.725 Regression F Statistic 6.255 13.041 Kleibergen-Paap F -Stat 1190.051 1010.144 Year FE Yes Yes Industry FE Yes Yes Kabupaten / Kota FE Yes Yes Firm FE. Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the firm level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Firms and Hiring (1) Firm Outcomes DV: Log # DV: Log # of Firms of Workers (1) (2) Log Avg IRI -1.194-1.294 (0.182)*** (0.286)*** N 3121 3121 N Kabupaten / Kota 204 204 Adj. R 2 0.910 0.914 Regression F -Stat 110.553 241.978 Kleibergen-Paap F -Stat 47.239 47.239 DV Mean 2.890 6.660 Kabupaten / Kota FE Yes Yes Year FE Yes Yes All regressions include a constant. Robust standard errors are reported in parentheses. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Firms and Hiring (2) DV: Log Number of Workers (1) (2) Log Avg IRI -0.057 0.003 (0.017)*** (0.012) N 234272 230224 N Firms 29366 29366 Adjusted R 2 0.266 0.924 Regression F Statistic 11.563 0.069 Kleibergen-Paap F -Stat 2034.234 1821.897 Year FE Yes Yes Industry FE Yes Yes Kabupaten / Kota FE Yes Yes Firm FE. Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the firm level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Total Earnings by Sector DV: Earnings by Sector Manu- Agri- Sales and facturing culture Services Other (1) (2) (3) (4) Log Avg IRI -0.533-3.474-0.160-0.132 (0.363) (1.224)*** (0.404) (0.201) Adj. R 2 0.282 0.125 0.197 0.066 Regression F -Stat 1.818 2.181 2.182 1.940 Kleibergen-Paap F -Stat 23.238 19.200 24.000 32.073 DV Mean 11.177 7.806 11.024 0.135 N 4160 5464 3692 10763 N Individuals 1722 2130 1540 4235 N Desa / Kelurahan 227 189 231 260 Individual FE Yes Yes Yes Yes Year FE Yes Yes Yes Yes Controls Yes Yes Yes Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the (initial) village level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Labor Supply (1) DV: Working? (0 1) (1) Log Avg IRI -0.037 (0.034) Adj. R 2 0.427 Regression F -Stat 34.111 Kleibergen-Paap Wald rk F -Stat 33.594 DV Mean 0.704 N 35193 N Individuals 12459 N Desa / Kelurahan 377 Individual FE Year FE Controls Yes Yes Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the (initial) village level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Labor Supply (2) DV: Log Hours Worked (Cond. on working) (1) Log Avg IRI -0.011 (0.060) Adj. R 2 0.237 Regression F -Stat 3.461 Kleibergen-Paap Wald rk F -Stat 32.698 DV Mean 5.148 N 22255 N Individuals 8168 N Desa / Kelurahan 321 Individual FE Year FE Controls Yes Yes Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the (initial) village level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Sector Swtiching (1) DV: Any Primary Sector Log Hours Employment? Employment? Worked By Industry (1) (2) (3) Manufacturing -0.114-0.129-6.240 (0.036)*** (0.033)*** (1.802)*** Adj. R 2 0.462 0.493 0.395 Regression F -Stat 8.807 10.079 8.151 Kleibergen-Paap F -Stat 32.711 32.711 32.910 DV Mean 0.285 0.253 12.219 Agriculture 0.055 0.055 2.889 (0.033)* (0.034) (2.494) Adj. R 2 0.648 0.653 0.399 Regression F -Stat 6.559 4.923 2.887 Kleibergen-Paap F -Stat 32.711 32.711 32.695 DV Mean 0.419 0.367 13.013 Individual FE Yes Yes Yes Year FE Yes Yes Yes Controls Yes Yes Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the (initial) village level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Sector Swtiching (2) DV: Any Primary Sector Log Hours Employment? Employment? Worked Formal vs. Informal (1) (2) (3) Informal 0.079 0.091 6.074 (0.033)** (0.032)*** (2.592)** Adj. R 2 0.560 0.598 0.366 Regression F -Stat 11.468 6.857 7.955 Kleibergen-Paap F -Stat 32.698 32.707 33.050 DV Mean 0.636 0.576 23.298 Individual FE Yes Yes Yes Year FE Yes Yes Yes Controls Yes Yes Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the (initial) village level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: In-migration of workers DV: Log Share of Recent Migrants (2000 Census) (1) (2) Log IRI (2000-1995) -1.257-0.690 (0.153)*** (0.225)*** N 201 201 Adjusted R 2 0.366 0.474 F Statistic 38.992 8.436 Kleibergen-Paap F -Stat 14.779 11.570 DV Mean -3.156-3.156 Province FE. Yes Kabupaten / Kota FE Yes Yes Year FE Yes Yes All regressions include a constant. Robust standard errors are reported in parentheses. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: HH Consumption DV: Log Consumption (Per Capita) (1) Log Avg IRI -0.261 (0.061)*** Adj. R 2 0.594 Regression F -Stat 191.771 Kleibergen-Paap F -Stat 35.450 DV Mean 11.046 N 22541 N Households 6928 N Desa / Kelurahan 852 Household FE Year FE Controls Yes Yes Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the (initial) village level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: HH Total Earnings DV: Log Total Earnings (1) Log Avg IRI -0.894 (0.328)*** Adj. R 2 0.265 Regression F -Stat 10.118 Kleibergen-Paap F -Stat 33.684 DV Mean 10.633 N 16935 N Individuals 6460 N Desa / Kelurahan 298 Household FE Year FE Controls Yes Yes Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the (initial) village level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Results: Land Prices DV: Log Rent DV: Log Land per Room Value (1) (2) Log Avg IRI -0.244-0.658 (0.116)** (0.217)*** Adj. R 2 0.360 0.488 Regression F -Stat 25.589 12.117 Kleibergen-Paap F -Stat 36.627 19.970 DV Mean 8.276 14.819 N 19115 7441 N Households 6475 2498 N Desa / Kelurahan 793 321 Household FE Yes Yes Year FE Yes Yes Controls Yes Yes All regressions include a constant. Robust standard errors in parentheses, clustered at the (initial) village level. */**/*** denotes significant at the 10% / 5% / 1% levels.

Decomposition - preliminary Amenity = A Total Hours Worked = H Wage = w Sector = s Total earnings = Y = S Y A = S s=1 w s ( Hs A E Y,A = S s=1 s=1 w sh s ) ( + ws ) Hs A ( ws H s Y ) EHs,A + ( w s H s Y ) Ews,A

Conclusions Improved road quality increases firm s value added, total factor productivity and labor demand through firms entry. Agricultural profits are very sensitive to road quality; manufacturing wages are not Earning gap persists: dual labor markets In-migration of workes to where road quality improves Switching from agriculture/informal to manufacturing/formal sector where road quality improves Improved road quality increases households welfare (consumption, income, land value ) Next: decomposition