Emergency Assistance for Recovery and Rehabilitation from Recent Disasters (RRP INO 52324-001)
POVERTY IMPACT ASSESSMENT
A. Sector Performance, Problems, and Opportunities
1. This poverty impact assessment attempts to provide a first evaluation of the impact of the earthquake, tsunami and liquefaction that struck Central Sulawesi on 28 September 2018 as well as the earthquakes that occurred on 29 July, 5 August and 19 August on West Nusa Tenggara.1 Several data sets that are collected by Statistics Indonesia and Bank Indonesia have been used to provide key indicators and develop a baseline profile of the regional economies. Preliminary findings of the economic impact of the disasters based on simulations from IndoTERM2 are used to estimate the impact of the disasters on poverty incidence. It is estimated that the percentage of people falling below the poverty line in Central Sulawesi may increase from 14.01% pre- disaster to 16.39% post disaster, while in West Nusa Tenggara the poverty rate may increase from 14.75% pre-disaster to 16.82% post-disaster. Analysis indicates that the considerable progress made throughout Indonesia towards poverty reduction in recent years risks being setback by the impact of the recent disasters.
2. Primary commodities underpinned strong growth in Central Sulawesi. Economic growth in the province of Central Sulawesi has been outpacing national growth in recent years, as the province has been benefiting from its natural resource sectors that have contributed almost half of growth.3 Within agriculture, plantation crops and fisheries have performed well. In mining, the province is a producer of natural gas as well as raw ores and other energy products. While growth in the province has been strong, Central Sulawesi only accounts for approximately 1% of national GDP. Prior to the disaster, annual economic growth of Central Sulawesi province was expected to be in the range of 6.9% to 7.3% in 2018, with growth to be supported by an increase in export value, gains in resource intensive manufacturing, and an increase in the realization of government spending as well as other seasonal factors.4
Table 1. GRDP of Central Sulawesi, 2010 Constant Prices (Rp. billion), 2013–2017 Sector 2013 2014 2015 2016 2017 Agriculture, Forestry and Fishing 23,164 24,729 26,298 26,928 28,129 Mining and Quarrying 9,773 7,239 9,223 12,427 14,314 Manufacturing 3,957 4,274 8,120 10,971 12,209 Electricity and Gas 31 36 41 43 47 Water Supply, Sewerage, Waste 101 110 117 121 128 Construction 7,020 8,801 10,620 10,358 10,736 Wholesale and Retail Trade, Repair of Motor 6,756 7,487 7,860 8,285 8,618 Vehicles and Motorbikes Transportation and Storage 2,818 3,079 3,317 3,485 3,717 Accommodation and Food Services 363 397 437 463 501 Information and Communication 2,592 2,916 3,184 3,470 3,716 Financial and Insurance 1,598 1,659 1,760 2,070 2,217 Real Estate 1,398 1,540 1,649 1,716 1,815 Business 194 205 213 223 235
1 On 28 September 2018, Palu was hit by a 5-metre-high tsunami shortly after a magnitude 7.5 earthquake occurred 80 km north of the city. 2 A. Yusuf. 2018. Economic impact of Lombok earthquake and Sulawesi Earthquake and Tsunami. Jakarta (unpublished). 3 Statistics Indonesia. 2018. Gross Regional Domestic Product of Provinces in Indonesia by Industry, 2013-2017. Jakarta. Statistics Indonesia. 4 Bank Indonesia. 2018. Regional Economic and Financial Study of Central Sulawesi Province for August 2018. Jakarta. Bank Indonesia. 2
Public Administration, Defense, Social Security 4,125 4,509 4,892 5,193 5,532 Education 2,783 2,990 3,219 3,373 3,571 Human Health and Social Work Activities 972 1,074 1,147 1,196 1,298 Other Services 575 634 691 731 769 Total 68,220 71,679 82,788 91,053 97,552 Source: Statistic Indonesia, selected publications.
3. Weakening exports performance slowed growth in West Nusa Tenggara. Economic growth in the province of West Nusa Tenggara grew by 0.11% in 2017 as quota restrictions saw the performance of exports, especially copper and other mining exports, decline.5 Outside of mining, growth was supported by improving performance of the agricultural, trade and construction sectors. Economic growth in West Nusa Tenggara is expected to contract in the remaining half of 2018 due to the series of earthquakes that hit the islands in July and August, which is reflected in a decline in consumer confidence in August 2018 and is expected to affect household consumption and the trade sectors. Growth in the province accounts for less than 1% of national GDP.
Table 2. GRDP of West Nusa Tenggara, 2010 Constant Prices (Rp. billion), 2013–2017 Sector 2013 2014 2015 2016 2017 Agriculture, Forestry and Fishing 16,947 17,702 18,965 19,587 20,880 Mining and Quarrying 11,255 11,239 23,175 24,501 19,635 Manufacturing 3,540 3,659 3,773 3,971 4,207 Electricity and Gas 48 67 67 75 78 Water Supply, Sewerage, Waste 59 64 66 69 72 Construction 6,697 7,219 7,744 8,414 9,055 Wholesale and Retail Trade, Repair of Motor Vehicles and 9,053 9,747 10,337 11,148 12,112 Motorbikes Transportation and Storage 4,964 5,335 5,680 5,919 6,345 Accommodation and Food 1,243 1,329 1,404 1,545 1,663 Services Information and Communication 1,555 1,685 1,825 1,986 2,158 Financial and Insurance 2,106 2,269 2,480 2,796 3,075 Real Estate 2,086 2,206 2,356 2,502 2,678 Business 123 132 139 149 158 Public Administration, Defense, 4,007 4,207 4,362 4,492 4,641 Social Security Education 3,141 3,352 3,595 3,813 4,062 Human Health and Social Work 1,413 1,511 1,613 1,705 1,826 Activities Other Services 1,532 1,652 1,754 1,865 2,002 Total 69,767 73,373 89,338 94,538 94,645 Source: Statistic Indonesia, selected publications.
4. A need to broaden the economic base to foster inclusive growth. Table 3 highlights that per capita GRDP in Central Sulawesi and West Nusa Tenggara provinces is lower than national per capita GDP. In Central Sulawesi strong resources led growth in recent years has seen per capita GRDP grow rapidly and stands at 87% of national per capita GDP.6 However, GRDP per capita in West Nusa Tenggara has hovered at close to 50% of the national average in
5 Bank Indonesia. 2018. Regional Economic and Financial Study of West Nusa Tenggara Province for August 2018. Jakarta. Bank Indonesia. 6 Statistics Indonesia. 2018. Gross Regional Domestic Product of Provinces in Indonesia by Industry, 2013–2017. Jakarta. 3 recent years. In both provinces economic growth has been narrow and volatile, with performance highly influenced by commodities. Outside of primary commodities, both economies are largely informal, and a large share of the population is vulnerable to economic shocks and natural disasters. For example, manufacturing outside of large-scale resource intensive industries in both provinces is mostly associated with informal micro and small enterprises (MSEs). These enterprises rarely receive government support for business development nor do they use the internet.7 These MSEs tend to finance their business through retained earnings, and only 4% of MSE in Central Sulawesi and 6% of MSEs in West Nusa Tenggara had a bank loan in 2017, mostly from the government’s subsidized credit program, despite access to credit being identified as a primary constraint to doing business. Due to the informality of MSEs, disaster relief support will be hard to target.
Table 3. Per Capita GRDP at 2010 Constant Prices by (Rp. ‘000), 2013–2017 2013 2014 2015 2016 2017 Central Sulawesi 24,491 25,316 28,779 31,164 32,886 West Nusa Tenggara 14,810 15,370 18,475 19,309 19,099 National average 32,781 33,965 35,162 36,469 37,851 Source: Statistic Indonesia, selected publications.
5. Most rely on agriculture or services in the informal sector to support their livelihood. The largest providers of employment in Central Sulawesi include agriculture (42%) and trade (14%), followed by manufacturing (9%). 8 In West Nusa Tenggara, most employment is in agriculture (37%), followed by trade (35%) and manufacturing (14%). More than two-thirds of employment in both provinces is informal. With limited social assistance available for the jobless adult population, unemployment is low and labor force participation is high. Both Central Sulawesi’s and West Nusa Tenggara’s women’s labor force participation is higher than the national average, however many of these women work as unpaid workers. With a sizeable informal economy, growth in average wages has remain subdued and a considerable gender wage gap persists (Table 4). Education attainment is comparatively low in both provinces, with approximately 45% of the economically active population with primary school as their highest level of education attainment. Analysis highlights several risk factors for livelihood recovery from the of the impact of the disasters, including lack of income diversification, gender and income inequality, lack of access to finance and other social safety nets, and low levels of education. The implications of these risks include depletion of assets and higher vulnerability to falling into poverty.
Table 4. Selected labor market indicators (No. employed people) Aug-16 Feb-17 Aug-17 Feb-18 Central Sulawesi Men Agriculture 457,214 484,771 444,092 441,867 Industry 158,677 151,461 161052 184,323 Services 287,153 294,726 280928 304,669 Total employed 903004 930958 866,072 930,859 Labour force participation rate (%) 86.81 88.44 84.1 87.28 Unemployment rate (%) 2.33 2.1 2.91 2.41 Average wage of employees Rp. 2,373,100 2,668,200 2,683,100 2,493,700 Women Agriculture 212,745 224,769 164,654 198,246 Industry 39,622 50,232 42926 67,398
7 Statistics Indonesia. 2017. Survey of micro and small manufacturing enterprises. Jakarta. 8 Statistics Indonesia. 2018. Labor force situation in Indonesia: February 2018. Jakarta. 4
Services 304,392 304,823 280562 323,801 Total employed 556 759 579 824 488,142 589,445 Labour force participation rate (%) 57.16 58.7 49.49 58.71 Unemployment rate (%) 4.81 4.35 5.39 4.39 Average wage of employees Rp. 2,160,000 1,863,900 1,976,700 2,010,000 West Nusa Tenggara Men Agriculture 514,648 583,221 484,125 566,221 Industry 284,422 248,741 325,622 243,404 Services 482,517 477,850 502,580 521,139 Total employed 1,281,587 1,309,812 1,312,327 1,330,764 Labour force participation rate (%) 82.18 83.24 82.11 82.71 Unemployment rate (%) 4.55 4.47 3.77 3.82 Average wage of employees Rp. 2,403,000 2,685,200 2,511,900 2,370,200 Women Agriculture 406,262 439,381 345,512 342,902 Industry 141,675 112,268 156,898 133,675 Services 537,786 561,989 501,983 568,470 Total employed 1,085,723 1,113,638 1,004,393 1,045,047 Labour force participation rate (%) 61.99 63.03 56.18 58.17 Unemployment rate (%) 3.2 3.12 2.71 2.82 Average wage of employees Rp. 1,555,400 1,545,000 1,628,300 1,466,400 Source: Statistics Indonesia, selected publications.
6. High rates of poverty, with the rural poor particularly vulnerable. Table 5 shows that the number of people below the poverty line in both Central Sulawesi and West Nusa Tenggara, at 14.01% and 14.75% respectively in March 2018, is high in comparison to the national average of 9.82%.9 The poverty gap (P1), which measures the extent to which an individual is below the poverty line, is substantially higher in both provinces when compared to the national average, driven in part by the large share of the population that reside in rural areas in Central Sulawesi and high urban poverty in West Nusa Tenggara.10 The implication of this large poverty gap is that not only are the poor more likely to be impoverished due to the disaster, but many of the poor may become more vulnerable and take longer to recover from the disaster. Empirical analysis shows that major disasters exacerbate the vulnerability of the poor due to limited diversification of income sources and lack of access to social protection, while recovery can take a long time.11
Table 5. Selected socio-economic variables March 2017 March 2018 Urban Rural Total Urban Rural Total Central Sulawesi Poverty line (Rp.) 416,453 383,097 408,522 434,414 405,707 413,785 Number of poor people 77.98 339.88 417.87 85.03 335.18 420.21 (‘000) Percentage of people below 10.16 15.54 14.14 10.15 15.51 14.01 the poverty line (%) Gini ratio 0.379 0.309 0.355 0.370 0.307 0.346 Poverty gap index (P1) 2.05 2.73 2.55 2.02 2.88 2.64 Poverty severity index (P2) 0.20 0.63 0.46 0.22 0.50 0.38
9 Statistics Indonesia. 2017.Executive Summary of Consumption and Expenditure of Population of Indonesia – September 2017 SUSENAS. Jakarta. 10 70% of people aged 15 and over. 11 A. Shepard et al. 2013. The Geography of Poverty, Disasters and Climate Extremes in 2030. UK Department for International Development (DFID). London. 5
West Nusa Tenggara Poverty line (Rp.) 355,250 337,333 345,341 377,145 356,361 365,901 Number of poor people 387.04 406.73 793.78 370.38 367.08 737.46 (‘000) Percentage of people below 17.53 14.89 16.07 15.94 13.72 14.75 the poverty line (%) Gini ratio 0.413 0.314 0.371 0.398 0.333 0.372 Poverty gap index (P1) 3.59 2.76 3.13 3.24 2.45 2.82 Poverty severity index (P2) 1.06 0.68 0.85 0.91 0.6 0.74 National average Poverty line (Rp.) 385,621 361,496 387,160 415,614 383,908 401,220 Number of poor people 10,673.83 17,097.39 27,771.22 10,144.37 15,805.43 25,999.80 (‘000) Percentage of people below 7.72 13.93 10.64 7.02 13.20 9.82 the poverty line (%) Gini ratio 0.407 0.320 0.393 0.401 0.324 0.389 Poverty gap index (P1) 1.24 2.49 1.83 1.17 2.37 1.71 Poverty severity index (P2) 0.31 0.67 0.48 0.29 0.63 0.44 Source: Statistics Indonesia, selected publications.
7. Price stability important, with food accounting for a high share of expenditure. Table 6 provides data on average monthly expenditure per capita in both provinces and shows that it is lower than the national average and food expenditure accounts for more than 50% of average expenditure.12 Calorie and protein consumption in both provinces is higher than the national average, with access to agriculture lands and fishing supporting consumption. Relatively controlled inflation and improvements in the farmers' terms of trade have seen poverty decline recently. However, farmers’ incomes remain low and more efforts are needed to improve the empowerment of farmers, both through intensification programs and improving access to markets. Prior to the disaster, annual inflation in Central Sulawesi and West Nusa Tenggara was expected to be controlled in the specified range of 3.5 +/- 1% for 2018.13 In October 2018, national average inflation remained controlled at 3.2% year-on-year, while inflation in Central Sulawesi picked up to 6.2% from 4.5% a month earlier. The pick-up in inflation is likely to erode purchasing power for the poor and without appropriate social protection interventions, they may be driven further into poverty.
Table 6. Selected socio-economic variables, September 2017 Urban Rural Total Central Sulawesi Average monthly expenditure per capita Rp. 1,245,285 825,437 936,103 Percentage of expenditure on food (%) 42.59 56.43 51.58 Average daily per capita consumption of calories N/A N/A 2191.75 Average daily per capita consumption of protein N/A N/A 64.26 West Nusa Tenggara Average monthly expenditure per capita Rp. 950,677 716,288 821,052 Percentage of expenditure on food (%) 51.61 60.16 55.74 Average daily per capita consumption of calories N/A N/A 2187.31 Average daily per capita consumption of protein N/A N/A 62.85 National average
12 Statistics Indonesia. 2017.Executive Summary of Consumption and Expenditure of Population of Indonesia – September 2017 SUSENAS. Jakarta. 13 Bank Indonesia. 2018. Regional Economic and Financial Study of Central Sulawesi Province for August 2018. Jakarta; Bank Indonesia. 2018. Regional Economic and Financial Study of West Nusa Tenggara Province for August 2018. Jakarta. 6
Average monthly expenditure per capita Rp. 1,548,533 910,472 1,085,923 Percentage of expenditure on food (%) 46.72 57.97 50.62 Average daily per capita consumption of calories N/A N/A 2119.61 Average daily per capita consumption of protein N/A N/A 62.11 Source: Statistic Indonesia, selected publications.
8. Other socio-economic indicators highlight challenges for inclusive growth for Central Sulawesi and West Nusa Tenggara. Life expectancy is lower than the national average, at 67.31 in Central Sulawesi and 65.48 in West Nusa Tenggara, while infant mortality rates and rates of stunting are higher than the national average.14 Access to health care services is a challenge, with only 16 doctors per 100,000 people in Central Sulawesi and 14 doctors per 100,000 in West Nusa Tenggara, and these services now even more stretched by the current disaster. Only 63.69% of the population in Central Sulawesi and 73.62% of the population in West Nusa Tenggara have access to clean drinking water, while only 57.15% and 59.67% of households respectively have a septic tank.
9. Low revenues from local government. There is a well-developed body of international literature linking natural disasters with poverty in developing economies. The relationship between disasters and poverty is complex with vulnerability to extreme poverty a function of the country’s level of exposure to multi-hazards and disasters (earthquakes, tsunamis, volcanic eruptions), and available government revenues and capacity to support emergency relief and recovery programs, among others. In Indonesia, revenue from local governments remains limited. Table shows that revenue from village government in both Central Sulawesi and West Nusa Tenggara is low and is primarily sourced from transfers from the central government, with most of these funds spent on village government administration and village development projects.15 Revenue from district governments in both provinces is also primarily derived from central government transfers, including the general allocation fund and special allocation fund, and only a small share comes from taxes.16 District expenditure is largely for personal expenditures, goods and services, and capital expenditures. With a high level of dependence on central government transfers for local government development projects, the impact of local tax revenue losses from the disasters on local government spending is likely to be low. However, countries with limited fiscal space, may not be able to respond effectively in restoring public infrastructure and livelihoods of families affected.
Table 7. Actual revenue and expenditure of district and village governments (Rp ‘000) 2016 2017 Revenue Expenditure Revenue Expenditure Central Sulawesi Village government 1,849,107,764 1,836,844,312 2,221,223,617 2,204,851,743 District government 15,044,081,370 15,044,081,370 15,151,557,231 15,151,557,231 West Nusa Tenggara Village government 1,404,630,573 1,387,127,023 1,610,813,030 1,561,660,828 District government 15,008,046,368 15,008,046,368 14,520,538 14,520,538 National Village government 82,311,844,142 80,800,750,832 97,490,586,778 95,363,276,556 District government 782,093,528,668 782,093,528,668 808,255,481,959 808,255,481,959 Source: Statistic Indonesia, selected publications.
14 Statistics Indonesia. 2017. Welfare indicators: Equity in Access to Health Services Towards Healthy Indonesia. Jakarta. 15 Statistics Indonesia. 2017. Financial Statistics of Village Governments. Jakarta. 16 Statistics Indonesia. 2017. Financial Statistics of Regency / Municipality Government. Jakarta. 7
10. Disasters can affect people through five channels: death and disability, sudden loss of income, depletion of assets, loss of public infrastructure, and macroeconomic shocks, all of which may impact on poverty. Major disasters not only hurt the poor directly through depletion of assets, but also through stress on public and private resources. A preliminary evaluation of the impact on poverty from the recent earthquake and tsunami in Central Sulawesi and the earthquake in West Nusa Tenggara was undertaken using the National Social and Economic Survey (SUSNEAS) from March 2017 as the baseline poverty profile for each province. Analysis generated from a simulation using IndoTERM was used to estimate the economic impact of the disasters, with the simulation estimating an immediate decrease of GRDP in Central Sulawesi by 3.61% and a decrease of GRDP in West Nusa Tenggara Province by 1.55%. Based on this number, the following assumptions are used to generate estimates for the poverty impact of the disasters:
a. The decrease in total consumption in the province is assumed to be same as the decrease in GRDP; b. Due to limited information of the severity level of the damage for each area caused by the disaster, it is assumed that the fall in total consumption within the Central Sulawesi is absorbed only by the most affected regions (Palu, Donggala and Sigi), while in the West Nusa Tenggara the districts include West Lombok, Central Lombok, East Lombok, North Lombok and Mataram City; c. All households in the three districts in Central Sulawesi are assumed to be affected at the same rate. Therefore, the decrease in provincial consumption by 3.61% translates into a 10.16% decrease in household consumption for every households in those three districts. Similarly, all households in the affected districts in West Nusa Tenggara are assumed to be affected at the same rate. Therefore, the decrease in provincial consumption by 1.55% translates into 2.23% decrease in household consumption for all households in the affected districts; d. The estimated district poverty line is derived from the district poverty rate as per SUSENAS March 2017; and e. Due to limited information on population movements, it is assumed that there is no change in the provincial population.
11. Poverty incidence in both Central Sulawesi and West Nusa Tenggara is expected to increase post disaster, particularly for urban areas and among female-headed households. Based on the assumptions outlined above and preliminary analysis of the impact of the disaster on GRDP, it is estimated that the province poverty rate would increase to 16.39% in Central Sulawesi and 16.82% in West Nusa Tenggara post disaster (Table 8). While the incidence of poverty in rural areas is higher in both provinces, it is expected that urban poverty would deteriorate substantially from baseline levels in the post disaster context. In addition, female headed households in rural areas within Central Sulawesi are expected to be harder hit than male headed households in rural areas in the province. In West Nusa Tenggara, female headed households in urban areas are expected to be harder hit than male headed households.
Table 8. Baseline and Post Disaster Simulation of Poverty Incidence (%)17 Area Poverty incidence Baseline Simulated Male Female Male Female head Head head Head All HHs HHs HHs All HHs HHs HHs
17 The results presented in the table are simulations and the impact on poverty may be higher depending on the effectiveness of the emergency response and recovery programs implementation. More detailed analysis will be available when SUSENAS March 2019 becomes available. 8
Central Sulawesi 14.68 14.91 12.33 16.39 16.66 13.69 - Urban 11.04 11.27 9.55 13.58 14.11 10.22 - Rural 15.96 16.11 14.11 17.38 17.50 15.90 Affected districts - Donggala 18.17 18.55 14.06 24.18 24.45 21.26 - Sigi 12.81 12.51 15.73 18.2 17.96 20.49 - Palu 7.42 7.03 9.76 12.69 12.97 11.04 West Nusa Tenggara 15.88 15.14 19.55 16.82 16.05 20.62 - Urban 15.47 14.67 19.14 17.03 16.18 20.95 - Rural 16.21 15.51 19.93 16.64 15.94 20.33 Affected districts - Lombok Barat 16.42 15.75 20.61 17.12 16.56 20.61 - Lombok Tengah 15.09 13.99 18.92 16.61 15.28 21.25 - Lombok Timur 18.06 16.64 22.66 19.63 18.5 23.28 - Lombok Utara 31.62 31.19 34.47 34.23 34.19 34.47 - Kota Makasar 9.21 9.08 9.86 9.89 9.29 12.87 Source: Estimates based on SUSENAS March 2017 using estimated 2017 district poverty lines. HH= Household.
12. Within the affected districts in both provinces, poverty incidence is expected to soar, with Donggala district in Central Sulawesi and North Lombok district in West Nusa Tenggara the worst affected areas. Figure 1 provides poverty estimates for 2017 and 2018 from SUSENAS and simulations of poverty incidence post-disaster for 2018 until 2020. Analysis shows that the poverty impact of the disasters is expected to reach its peak in the remaining months of 2018, before beginning to gradually recover in 2019 and 2020.
Figure 1. Estimated Poverty Incidence (%), 2017–2020 20%
18% 16.8% 16.4% 16.5% 16.1% 16% 15.4% 15.3% 14.8% 14.8% 14.1% 14.0% 14%
12%
10% 2017 Pre disaster 2018 Post disaster 2018* 2019* 2020* Central Sulawesi West Nusa Tenggara Source: Statistics Indonesia; ADB estimates based on IndoTERM. * denotes simulation
B. Government’s Recovery and Rehabilitation Plan
13. An initial Damage and Loss Assessment for Central Sulawesi conducted by the National Disaster Management Agency (BNPB) suggests damages and losses of Rp13.8 trillion ($908 million equivalent) of which approximately Rp11.8 trillion is damages and Rp2.0 trillion is losses. The government faces the dual burden of responding to these events following the similarly destructive West Nusa Tenggara earthquake and related emergency in August 2018. A damage and loss assessment for the West Nusa Tenggara emergency conducted by BNPB suggests total costs of Rp18.2 trillion ($1.18 billion equivalent), comprising Rp12.4 trillion of damages and Rp5.8 trillion of losses). In total, disaster-related damage and losses are estimated to exceed Rp32.0 9 trillion ($2.10 billion equivalent).
14. The government is leading the rehabilitation and reconstruction process by developing the Action Plan for Rehabilitation and Reconstruction which will inform the Action Plan for Redevelopment of Post-Disaster Central Sulawesi (Action Plan). Four ministries have been tasked for preparing the Action Plan: BAPPENAS, Ministry of Public Works, Ministry of Agrarian Affairs and Spatial Panning (ATR), and Ministry of Energy and Mineral Resources. The Action Plan to be finalized by the end of the year, will be developed based on robust understanding of damage assessment and disaster risk and include sections on: (i) urban development; (ii) infrastructure reconstruction; (iii) social and economic recovery; (iv) financing and partnership; and (v) regulatory and institutional development. BAPPENAS is coordinating the development of the Action Plan, and has identified partners, including the World Bank, United Nations Development Programme, Japan International Cooperation Agency and ADB to provide technical support.
15. Development partners have been coordinating their efforts in support of response and recovery. The Humanitarian Country Team has been activated to coordinate the response operations being carried out by various agencies. The coordination structure includes eight clusters, namely, logistics, health, displacement and protection, early recovery, economy, education, infrastructure, and search and rescue. The ASEAN Coordinating Centre for Humanitarian Assistance on disaster management (AHA Centre), an intergovernmental organization established by 10 ASEAN Member States, has been actively supporting the BNPB to facilitate the cooperation and coordination among ASEAN Member States and with the United Nations and international organizations on emergency response. Bi-lateral donors have been actively supporting the emergency response process by providing finances, goods, and in-kind services. USAID, IOM and the Ministry of Social Affairs have also developed displacement tracking matrices for each of the disaster locations.18 These combined efforts will help to ensure that government’s recovery and rehabilitation plan has identified appropriate actions needed to restore livelihoods and address the increase in poverty incidence. Crucially important for lifting the poor out of poverty will be ensuring sufficient resources are available to fund the recovery and reconstruction, including disbursement of budgetary funds and timely implementation of projects that are targeted to affected persons and areas.
C. ADB Experience and Assistance Program
16. ADB has committed to supporting the government’s rehabilitation and reconstruction efforts for the 2018 disaster events. Support includes a $3 million grant from ADB’s Asia Pacific Disaster Response Fund, approved on 8 October 2018 and an emergency assistance loan. This support will be followed by an investment project to support more specific reconstruction investment needs. ADB will also provide inputs on disaster risk management through upscaling knowledge work in this area.
17. Several lessons from previous emergency assistance are relevant for current efforts: (i) providing immediate financing is critical to ensure timely rehabilitation and reconstruction, thereby reducing the overall social and economic impacts of the disaster event; (ii) coursing the financial assistance through the government’s budget ensures ownership of the rehabilitation and reconstruction process; (iii) support for monitoring and evaluation of implementation of recovery activities will help to ensure social impacts of the disaster are adequately mitigated; (iv) processing the emergency loan while the government is finalizing its Action Plan for
18 See: https://displacement.iom.int/ 10 rehabilitation and reconstruction provides the government with the certainty of funding and ensures implementation of the Action Plan; (v) parallel to processing the emergency loan, providing technical assistance to the government in developing the Action Plan ensures that potential implementation challenges are thought through, thereby minimizing the risk of any implementation delays for the EAL; and (vi) providing the technical assistance to develop the Action Plan that integrates building back better and resilience principles, ensures that the emergency assistance loan contributes to the objectives and priorities of ADB’s country partnership strategy.
18. In addition, various evaluations of post-disaster recovery and reconstruction programs provide several key lessons for achieving their poverty reduction objectives. In particular, there are several good lessons from the post-tsunami assistance to Aceh from 2004 to 2008. Evaluations of the Aceh recovery program found that it avoided many typical problems associated with post disaster recovery programs including high volatility of output due to unstable or uncertain funding, poor coordination of development partner and activities, and lack of information and data on fund pledges, disbursement, and program implementation. Key success factors in the Aceh case include the Indonesian government establishing a central board to coordinate government agencies development partners; setting up information portals to track donor funds and programs; establishing a multi-donor trust fund to coordinate donor programs; and ensuring sufficient funding for the recovery program coursed through government in a flexible and manner.