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Improved Transportation Infrastructure and Rural Transformation: Insights from a Developing Country

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CGIAR Research Program on Policies, Institutions, and Markets Workshop on Rural Transformation in the 21st Century (Vancouver, BC – 28 July 2018, 30th International Conference of Agricultural Economists). Presentation by Khondoker A. Mottaleb and Dil Bahadur Rahut (CIMMYT).

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Improved Transportation Infrastructure and Rural Transformation: Insights from a Developing Country

  1. 1. Improved Transportation Infrastructure and Rural Transformation: Insights from a Developing Country Khondoker A. Mottaleb and Dil Bahadur Rahut Socioeconomics Program International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico CGIAR Research Program on Policies, Institutions and Markets (PIM) Workshop on Rural Transformation in the 21st Century. 28 July, 2018 Vancouver, British Columbia, Canada
  2. 2. Regional Disparity: East-West Divide The Padma (the Ganges), the Jamuna-> three major parts: Northwest: Rajshahi and Rangpur divisions; South West: Khulna Division and Eastern part: Dhaka and Chittagong divisions. The major industrial belts, the capital city and the major sea port are located in the eastern part. Poverty is widespread in the northwest and southwest regions. Ferry service was the major means of communication Table 1: Incidence of extreme poverty in Bangladesh by administrative Divisions (head-count-ratio, based on costs of basic needs methods) Rural poverty (%) Division 1995 2016 Southwest Barishal 44.8 14.9 Khulna 33.2 13.1 Northwest Rajshahi 44.4 15.2 Rangpur 31.3 National average 39.8 14.9
  3. 3. The Jamuna Bridge 1. Ferry service: 36 hours waiting time on average from a point in northwest side to the eastern side 2. In 1997, 20.5 % Bangladeshi were connected to electricity; however, it was only 9.1% in the case of Rajshahi and Rangpur 3. Seasonal food shortages problem “monga” was common in the northwest part in the lean season (Sep-Dec); 4. This is known as the infamous east-west divide (World Bank, 2008). In 1998, 23rd June (the day in which Bengal province of the Mughal empire (Bengal, Bihar and Odisha) lost their sovereignty to the East-India Company), the Jamuna Bridge was opened- physically connected the northwest and eastern regions by road and railway. This study examines the influence of the bridge on the transformation of the northwest region of Bangladesh
  4. 4. The Jamuna Bridge: Measuring impacts 1. 4.5km long bridge is the largest completed project 2. Actual cost: USD753.7 million 3. World Bank, JICA, ADB, Islamic Development Bank and Bangladesh govt. financed 4. Direct road and rail networks, gas telephone and electricity transmission lines The bridge reduced travel time by 8 hours (single trip) from Rajshahi to Dhaka SW region depend on ferry services still, similar to the NW region before 1998. We consider the households in SW region as the control group (n=1,223) and the households in Rajshahi (n=990) and Rangpur division (n=775) as the experiment groups. To capture the local heterogeneity we treat Rajshahi and Rangpur divisions separately. We rely Bangladesh govt. HIES 2000 (pre Jamuna bridge information) and HIES 2010 as post bridge information. We applied DID estimation procedure.
  5. 5. Major propositions 1. Physical integration NW region with economically advanced eastern region enthused labor migration from day-labor employment to other relatively high return employment 2. It enhanced daily wage rate both in the farm and nonfarm sector 3. Easy transportation to and from the economically advanced eastern region also enhanced farm revenue 4. Enhanced household welfare: higher food and nonfood consumption expenditures of the households
  6. 6. Employment Status1: Pre-bridge scenario Year 2000 Control group (a) Experiment groups Rajshahi (b) Diff (a-b) Rangpur (c) Diff (a-c) Self-employed, farm (%) 39.6 (0.01) 53.2 (0.02) -13.7*** (-6.47) 64.5 (0.02) -25.1*** (-11.26) Day-labor, farm 28.01 (0.01) 33.8 (0.02) -5.79** (-2.94) 51.2 (0.02) -23.2*** (-10.75) Self-employed, nonfarm (%) 29.2 (0.01) 30.2 (0.02) -1.01 (-0.52) 25.3 (0.01) 3.9* (1.90) Day-labor, nonfarm 25.5 (0.01) 29.9 (0.01) -4.39** (2.30) 32.1 (0.02) -6.62*** (-3.21) Salaried worker 26.5 (0.01) 19.4 (0.01) 7.09*** (3.94) 13.8 (0.01) 12.7*** (6.79) % Work place is not the home district 6.89 (0.01) 20.4 (0.01) -13.62*** (-9.71) 6.06 (0.01) 0.70 (0.64) Households in NW region relied more on farm and day labor (farm and non farm) wage income
  7. 7. Employment Status2: Post-bridge scenario Drastic change: agriculture (self employed) and day labor job lost significance in NW. Opposite trend or at least similar in 2010. Year 2010 Control group (a) Experiment groups Rajshahi (b) Diff (a-b) Rangpur (c) Diff (a-c) Self-employed, farm (%) 34.4 (0.01) 29.7 (0.01) -4.77*** (-3.07) 32.8 (0.01) 1.65 (0.98) Day-labor, farm 22.6 (0.01) 26.9 (0.01) -4.3** (-3.03) 25.9 (0.01) -3.41** (-2.26) Self-employed, nonfarm (%) 28.2 (0.01) 30.5 (0.01) -2.28 (-1.51) 27.5 (0.01) 0.7 (0.44) Day-labor, nonfarm 23.8 (0.01) 22.9 (0.01) 0.01 (0.59) 26.1 (0.01) -2.37* (-1.55) Salaried worker, farm and nonfarm 27.2 (0.01) 19.5 (0.01) 7.70*** (5.45) 20.9 (0.01) 6.18*** (4.03) % Work place is not the home district 7.81 (0.01) 21.88 (0.01) -14.07*** (-12.75) 10.37 (0.01) -2.56*** (-2.57)
  8. 8. Daily wage rate and crop income: pre and post bridge Control group (a) Experiment groups Year 2000 Rajshahi (b) Diff (a-b) Rangpur (c) Diff (a-c) Daily wage rate (BDT) day- labor in agriculture 37.9 (29.7) 34.6 (32.3) 3.32* (1.39) 32.6 (26.9) 5.31*** (2.55) Daily wage rate (BDT) day- labor in nonag sectors 55.6 (48.7) 50.7 (42.8) 4.96* (1.33) 37.4 (33.2) 18.2*** (5.05) Yearly crop revenue (BDT) 28.3 (40.9) 28.8 (42.8) -0.44 (-0.17) 25.4 (38.8) 5.7** (2.30) Year 2010 Daily wage rate (BDT) day- labor in agriculture 96.1 (62.6) 110.9 (57.1) -14.8*** (-3.71) 103.3 (47.5) -7.19** (-1.75) Daily wage rate (BDT) day- labor in nonag sectors 128.6 (98.1) 133.2 (99.3) -4.56 (-0.67) 127.9 (95.1) 1.66 (0.25) Yearly crop revenue (000, BDT) 71.3 (78.13) 89.8 (155.6) -18.6*** (-2.80) 77.04 (83.5) -5.79 (-1.18) NW Lower wage rates and crop revenue in 2000 but opposite or equal in 2010
  9. 9. Household welfare1: nonfood expenditure Year 2000 Control group (a) Rajshahi (b) Diff (a-b) Rangpur (c) Diff (a-c) Total household expenditure 38837.4 (1013.9) 34103.1 (929.8) 4734.3*** (3.37) 28573.8 (906.4) 10263.6*** (7.01) -Health expenditure 1223.3 (90.9) 1096.9 (124.9) 126.4 (0.84) 784.2 (73.3) 439.1*** (3.42) -Education expenditure 1864.1 (131.4) 1132.7 (108.6) 731.4*** (4.16) 1070.7 (103.4) 793.4*** (4.30) Year 2010 Total household expenditure 77899.4 (1083.9) 74819.7 (1303.7) 3079.7 (1.80) 73454.5 (1484.8) 4444.9** (2.41) -Health expenditure 2216.6 (95.2) 1876.7 (106.2) 339.9** (2.33) 1835.9 (254.4) 380.7* (1.68) -Education expenditure 3114.2 (150.6) 2727.3 (162.1) 386.9* (1.69) 2331.1 (161.5) 783.1*** (3.27) Significant changes in household expenditure between 2000 and 2010 and between control and experiment groups: no difference in total exp in the case of Rajshahi, the difference reduced in the case of Rangpur division-still significant
  10. 10. Household welfare2: food expenditure Year 2000 Control group (a) Rajshahi (b) Diff (a-b) Rangpur (c) Diff (a-c) Total food expenditure 20173 (394.8) 18576.3 (358.1) 1596.7*** (2.93) 15939.9 (408.3) 4233.1*** (7.14) Cereal expenditure 8441.0 (130.3) 8385.9 (137.5) 55.2 (0.29) 8010.7 (170.4) 430.4** (2.02) Noncereal expenditure 11731.9 (312.2) 10190.4 (264.7) 1541.6*** (3.66) 7929.3 (274.4) 3802.7*** (8.47) Year 2010 Total food expenditure 51608.2 (557.9) 49675.9 (709.1) 1932.2** (2.15) 51250.7 (838.8) 357.5 (0.36) Cereal expenditure 22396.3 (211.5) 22243.6 (279.8) 152.7 (0.44) 23218.1 (312.2) -821.8** (-2.22) Noncereal expenditure 29211.9 (419.9) 27432.4 (519.9) 1779.5*** (2.66) 28032.6 (654.7) 1179.3 (1.) 180 Degree change in the case of Rangpur division in 2010
  11. 11. Regression results: Livelihood source Estimation method Multinomial logit model (base: self-employed in nonfarm) Sector Agriculture Nonfarm Farm and nonfarm Employment status Self- employed (yes=1) Day-labor (yes=1) Day-labor (yes=1) Salaried worker (yes=1) Year 2010 dummy (Y10) (base=2000) 0.19 (0.14) 0.53*** (0.14) 0.16 (0.13) -0.16 (0.13) Rajshahi Division dummy (RD) (yes=1) 0.56*** (0.19) 0.12 (0.18) 0.30* (0.16) 0.065 (0.17) RD X Y10 -0.80*** (0.22) -0.29 (0.20) -0.67*** (0.19) -0.62*** (0.19) Rangpur Division dummy (RNGD) (yes=1) 0.39 (0.28) 0.024 (0.26) 0.30 (0.26) 0.10 (0.26) RNGD X Y10 -0.93*** (0.26) -1.27*** (0.24) -1.15*** (0.23) -0.60** (0.24) Constant 0.17 (0.31) -0.20 (0.31) 0.31 (0.29) -0.38 (0.29) Number of observations 8,015
  12. 12. Regression results: Wage rate and crop revenue Estimation method Generalized linear model (GLM) estimation process Sector Mobility (1= if work place is not in home district, 0 otherwise) Agriculture Non agriculture Agriculture Employment status Wage/BDT/ day Wage/BDT/ day ln(annual crop income) Year 2010 dummy (Y10) (base=2000) 0.08 (0.14) 57.4*** (3.21) 73.2*** (5.10) 0.79*** (0.13) Rajshahi Division dummy (RD) (yes=1) 1.72*** (0.15) -3.29 (2.43) -2.36 (3.86) 0.32** (0.13) RD X Y10 (𝛽4) -0.0021 (0.17) 16.8*** (4.61) 5.67 (7.66) 0.10 (0.17) Rangpur Division dummy (RNGD) (yes=1) 1.19*** (0.22) -5.24** (2.17) -12.5*** (3.79) -0.12 (0.14) RNGD X Y10 (𝛽5) 0.56** (0.23) 12.5*** (4.35) 12.3* (7.25) 0.57*** (0.18) Constant -2.49*** (0.27) 58.1*** (4.71) 97.6*** (7.02) 10.8*** (0.22) Number of observations 8,015 2,315 2,068 2,649
  13. 13. Regression results: nonfood expenditure Dependent variables: yearly expenditure at the household level in 000, BDT (real) Total expenditure Nonfood expenditure Health expenditure Education expenditure Year 2010 dummy (Y10) (base=2000) -0.49 (2.24) -12.1*** (1.53) 0.15 (0.26) -1.29*** (0.31) Rajshahi Division dummy (RD) (yes=1) -1.54 (1.49) -2.20** (0.98) -0.34* (0.19) -0.33* (0.18) RD X Y10 -0.16 (1.90) 1.11 (1.29) -0.25 (0.21) 0.23 (0.27) Rangpur Division dummy (RNGD) (yes=1) -9.29*** (2.16) -6.35*** (1.35) -1.30*** (0.27) -0.13 (0.26) RNGD X Y10 5.22*** (2.00) 1.08 (1.30) -0.059 (0.28) -0.098 (0.27) Constant -88.1*** (5.17) -40.2*** (3.41) -3.54*** (0.84) -6.29*** (0.72) No. of observations 8015 8015 8015 8015
  14. 14. Regression results: food expenditure Dependent variables: yearly expenditure at the household level in 000, BDT (real) Food expenditure Cereal food expenditure Non cereal food expenditure Year 2010 dummy (Y10) (base=2000) 11.6*** (1.05) 10.0*** (0.35) 1.64* (0.85) Rajshahi Division dummy (RD) (yes=1) 0.65 (0.71) 0.54* (0.29) 0.11 (0.50) RD X Y10 (𝛽4) -1.26 (0.93) -0.34 (0.37) -0.92 (0.69) Rangpur Division dummy (RNGD) (yes=1) -2.94** (1.15) -1.35*** (0.45) -1.59* (0.84) RNGD X Y10 (𝛽5) 4.14*** (1.03) 1.76*** (0.41) 2.38*** (0.77) Constant -47.9*** (2.62) -14.2*** (0.92) -33.7*** (2.05) No. of observations 8015 8015 8015
  15. 15. Take home messages 1. Currently 11% (767 million) of 7.18 billion global population still under absolute poverty 2. Most of them concentrated in the rural areas of Southern Asia and Sub-Saharan Africa 3. Nearly 80% of the rural poor rely on agriculture for their livelihoods 4. How to attain SDG of zero hunger and transform rural area into economically vibrant area? 1. Enabling environment in which poor can employ their labor in high-return sector- instrumental to poverty alleviation 2. The environment can be enabled by investing on appropriate infrastructure 3. The Jamuna bridge of Bangladesh lends supports to the proposition. -poverty was widespread in the NW region of Bangladesh -Households mostly relied on agriculture and day labor income -Jamuna bridge enabled hh to out migrate and reallocate labor to other high return sector -It enhanced the daily wages both in farm and nonfarm and crop revenue -Enhanced the overall welfare of the households in the NW region
  16. 16. Thank you for your interest!

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