Identifying the Health, Social and Economic Impacts of COVID-19

YOUNG PEOPLE, HEALTH, AND WELLBEING PILOT PROJECT REPORT

Identifying the health, social and economic impacts of COVID-19 on young people in South Sulawesi PAIR: The Partnership for Australia-Indonesia Research (PAIR), an initiative of The Australia-Indonesia Centre, is supported by the Australian Government and run in partnership with the Indonesian Ministry of Research and Technology, the Indonesian Ministry of Transport, the South Sulawesi Provincial Government and many organisations and individuals from communities and industry.

The Australia-Indonesia Centre: The Australia-Indonesia Centre is a bilateral research consortium supported by both governments, leading Authors: universities and industry. Established in 2014, the Centre Prof. Anu Rammohan, The University of Western Australia works to advance the people-to-people and institutional Dr Sudirman Nasir, Universitas Hasanuddin links between the two nations in the fields of science, Dr Christrijogo Sumartono, Universitas Airlangga technology, education, innovation and culture. We do Dr Achmad Tohari, The University of Western Australia this through a research program that tackles shared Dr Healthy Hidayanti, Universitas Hasanuddin challenges, and through our outreach activities that Dr Moses Glorino Rumambo Pandin, Universitas Airlangga promote greater understanding of contemporary Indonesia Anis Wulandari, Universitas Airlangga and strengthen bilateral research linkages.

To discover more about the Centre and its activities, Report date: June 2021 please visit: ausindcentre.org Disclaimer: This report is the result of research funded by the Australian Government through the Australia-Indonesia To cite this report: Centre under the PAIR program. The report was edited This report is the result of research funded by the by the Australia-Indonesia Centre (AIC). The report is not Australian Government through the Australia-Indonesia intended to provide exhaustive coverage of the topic. The Centre under the PAIR program. Visit ausindcentre.org information is made available on the understanding that the AIC is not providing professional advice. While care Rammohan A., Nasir S., Sumartono C., Tohari A., has been taken to ensure the information in this report is Hidayanti H., Pandin M. G. R., Wulandari A., (2021), accurate, we do not accept any liability for any loss arising Identifying the health, social and economic impacts of from reliance on the information, or from any error or COVID-19 on young people in South Sulawesi, omission, in the report. We do not endorse any company The Australia-Indonesia Centre. or activity referred to in the report, and do not accept responsibility for any losses suffered in connection with any company or its activities. THE PARTNERSHIP FOR AUSTRALIA-INDONESIA RESEARCH (PAIR)

I am delighted to share our preliminary findings from the Partnership for Australia-Indonesia Research (PAIR).

PAIR is a development initiative that brings together researchers, policymakers, business and community groups to find solutions to real 1 problems. We do this in an integrated, Introduction ��P5 collaborative and evidence-based way. We anchor our research on a segment of Indonesia’s ambitious Trans- Sulawesi railway network – the new 145-kilometre railway line connecting two major port cities: Makassar and 2 Parepare. Methodology �� P6 The railway line will provide much- needed transport for people and goods. It also stands to stimulate the local economy, boost commodities and transform communities. Yet, 3 experience shows that investments in Analysis and results ��P7 connectivity do not necessarily benefit 3.1. COVID-19 in South Sulawesi ��P7 local communities if they are not 3.2. Disability and poverty ��P10 ‘people-centric’ - that is sustainable, affordable and accessible. Businesses 3.3 Dietary diversity and government are unable to realise the new railway policy ��P13 line’s potential without good planning 3.4 Mapping the incidence of mental and design of infrastructure. Poor health ��P17 intermodal connectivity, scheduling and intervention are unlikely to encourage use. Moreover, people are likely to remain disadvantaged if they lack the knowledge needed to take advantage of opportunities, and if they 4 lack access to resources, or the skills Conclusions and required to thrive and enterprise. recommendations ��P17 Our research explores four areas: commodities; transport, logistics and supply chain; young people, health and wellbeing; and young people and development. We investigate what the railway lines mean for local 5 communities, how they respond References ��P18 to change, and how they can take advantage of emerging opportunities.

Warm regards,

Dr Eugene Sebastian PAIR Program Director The Australia-Indonesia Centre YOUNG PEOPLE, HEALTH, AND WELLBEING PILOT PROJECT REPORT

EXECUTIVE SUMMARY

COVID-19 has brought unprecedented challenges worldwide. Our analysis focuses on four aspects of the pandemic’s impact on seaweed farming communities in Maros, Barru and Pangkep in South Sulawesi.

Firstly, we studied the impact of COVID-19 on household incomes and expenditure, using secondary data. In South Sulawesi, income increased by about 2 per cent compared with other provinces in Indonesia. However, household consumption decreased by about 3 per cent.

Secondly, we mapped the incidence of people with disability (PWD) in our study sites using the Village Potential Statistics (PODES) 2018 dataset. We found on average, villages in PAIR districts have more PWD compared to South Sulawesi (Figure 7). Every village in Pangkajene and Kepulauan (Pangkep) municipality has PWD – an average of more than four per village, the highest of our three PAIR study areas. Some villages have more than three PWD and in one village there were 30 PWD.

Thirdly, we evaluated the impact of in-kind food subsidies (the Rastra program, which provides rice) versus food vouchers (BPNT) on the dietary diversity of poor households. We found the provision of food vouchers via BPNT has improved the households’ consumption of essential nutrients, except daily fat, and increased the daily consumption of calories and carbohydrates. The impact on daily calorie intake was greater on BPNT participants than those receiving rice through Rastra.

Lastly, we used nationally representative data from the Indonesian Family Health Survey (2007 and 2014) to investigate the association between individuals’ socio-economic and demographic characteristics and poor mental health. Early results show a statistically significant and positive relationship between poor health and mental health disorders. Females and unmarried individuals are more likely to report poor mental health. YOUNG PEOPLE, HEALTH, AND WELLBEING PILOT PROJECT REPORT

Source: Ariv Kurniawan

1.0. INTRODUCTION This We focus on four aspects: • the impact of COVID-19 on COVID-19 has had huge economic, interdisciplinary household incomes and health and social costs on expenditure countries worldwide. Indonesia is research project • the incidence of disability in our no exception. brings together three PAIR districts Although South Sulawesi has one • an evaluation of in-kind food of Indonesia’s highest rates of researchers subsidies versus food vouchers economic growth, recent evidence (BPNT program) and their impact points to high economic inequality, from Australia on dietary diversity high prevalence of stunting and • the association between poor maternal health (TNP2K, and Indonesia individuals’ socio-economic and 2019 based on SUSENAS 2018, to address the demographic characteristics and SUPAS 2015). There is also poor poor mental health. and uneven access to sanitation, health and This research will inform our and challenges associated with proposed Strategic Integrated poor nutrition. economic issues Project (SIP) – a key piece of work for understanding the development Against this backdrop, an affecting rural needs of Indonesia, and estimated 1.2 million workers in particularly South Sulawesi. the informal sector have lost their communities and jobs due to COVID-19 related restrictions (Ministry of Manpower, their households 2020). These challenges are more prevalent in rural areas. in South Sulawesi.

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2.0. METHODOLOGY We used secondary data from various sources (SUSENAS, PODES, IFLS and data on COVID-19 from the Badan Pusat Statistik (BPS) COVID-19 survey) to address four distinct research questions. The research methodology used graphical analysis and statistical modelling using multivariate regression analysis.

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Risk Factor High Medium Low No Classification No Data

Figure 1.1: The Risk Factor of COVID-19 at Sub-district Level - July 2020

3.0 ANALYSIS AND of COVID-19 Task Force, and local Notes: Figures 1.1 and 1.2 present the RESULTS governments. risk factors of COVID-19 at every sub- district (kecamatan) in Indonesia. This The analysis in the Pilot Project The government regularly presents map was downloaded from the BNPB addressed four research themes the number of cases, total deaths, website (www.bnpb.go.id) and the using secondary datasets. These are total recovered, and the risk factors classification was made by the National described in detail below. for every sub-district (kecamatan) in Team for COVID-19 for July 2020. Indonesia. In April 2020, for example, the government released the risk On 2 November 2020, 2,618 new factors for 2,935 sub-districts: 292 confirmed COVID-19 cases brought the 3.1 COVID-19 IN SOUTH sub-districts were classified as being total number of infections nationwide SULAWESI high-risk, 582 as medium, and 2,061 to 415,402. A further 101 people as low. died of the disease, bringing the death toll to 14,044. Figure 2 shows The status of COVID-19 in South In July 2020, updated figures for the increasing trend in the daily total Sulawesi 4,986 sub-districts (Figure 1) showed number of COVID-19 cases in both Since the first reported local COVID-19 the number of high-risk factor sub- Indonesia and South Sulawesi since case on 3 March 2020, the incidence districts had doubled to 459 nationally. the first case in March 2020. of COVID-19 and associated death The number of medium and low toll in Indonesia has increased sub-districts were 2,243 and 2,284, respectively. Among South Sulawesi’s South Sulawesi

dramatically. The country’s immediate 2000 0 Indonesia priority has been to mitigate and 235 sub-districts, 12 have been classified as high-risk, 92 as medium- contain the impact of the pandemic i s 30000 4000 0 15000 e

risk and 131 as low-risk, respectively.

– for example, by encouraging safe w si a

COVID-19 clearly remains a challenge e n behaviours, intervening to mitigate Sul a

for the government. t u healthcare-capacity constraints, and Ind o o 20000 pushing hard on COVID-19 testing. S Risk Factor High 5000 10000 10000

From 15 March 2020, the Indonesian Medium

Low

Government imposed social restrictions No Data 0 0 (the Large-scale Social Distancing 1 Mar 1 May 1 Jul 1 Sep 1 Nov Policy or PSBB) in some areas, Date closing schools and workplaces and Figure 2: Total Cases of COVID-19 in limiting public and religious activities. South Sulawesi and Indonesia Several regional administrations had Notes: This figure presents the total already introduced similar (less strict) case number of COVID-19 in South measures. Sulawesi and Indonesia. Source: Gugus We evaluated the effect of these Tugas Nasional Percepatan Penanganan measures on household income COVID-19 and well-being using secondary data collected from the websites of Figure 1.2: The Risk Factor of COVID-19 government agencies including the at Sub-district Level - July 2020, South Ministry of Health, National Team Sulawesi

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The situation in South Sulawesi reflects Kabupaten/Kota Confirmed national figures. As of 2 November Treatment Recovered Death Total 2020, there have been 18,372 cases of Kota Makassar 476 8438 291 9205 COVID-19. Of these, 16,617 people (90.4 Kabupaten Gowa 80 1346 29 1455 per cent) have recovered, and 468 (2.5 per cent) have died. Kabupaten Luwu Timur 123 1409 4 1536 Kabupaten Jeneponto 76 430 3 509 COVID-19 has spread to all municipalities Kabupaten Maros 24 557 8 589 in South Sulawesi (Table 1). Makassar city Kabupaten Pinrang 9 165 4 178 has the most confirmed cases (9,205) Kabupaten Bulukumba 40 277 6 323 and deaths (291). Of our three PAIR Kabupaten Sinjai 20 392 0 412 municipalities, Maros records the highest prevalence of COVID-19, with 589 total Kabupaten Luwu Utara 43 276 13 332 cases, 557 people recovered, and eight Kota Parepare 54 259 8 321 deaths. Rekreasi Duta Covid19 SulSel 0 576 0 576 Kabupaten Bone 46 147 2 195 The impact of COVID-19 on Kota Palopo 116 206 8 330 economic and social conditions Kabupaten Enrekang 16 133 10 159 While it is hard to predict the long-term Kabupaten Takalar 17 296 1 314 economic impact of COVID-19, a 2020 RS Lain-lain 25 174 7 206 World Bank report estimated that 11 Kabupaten Pangkep 2 396 49 447 million people could fall into poverty Kabupaten Bantaeng 12 208 4 224 across East Asia and the Pacific. Kabupaten Tana Toraja 23 90 2 115 Our evaluation of available secondary data Kabupaten Luwu 41 73 4 118 suggests COVID-19 could slow Indonesia’s Kabupaten Sidenreng Rappang 10 156 3 169 sustained economic growth and reduction Kabupaten Soppeng 7 194 6 207 in poverty. As elsewhere, one of the Kabupaten Kepulauan Selayar 1 165 0 166 greatest costs comes from social (or Kabupaten Wajo 14 129 4 147 physical) distancing – a proven public Kabupaten Toraja Utara 6 29 2 37 health measure to reduce the spread of Kabupaten Barru 6 96 0 102 the virus by limiting people’s movements Kabupaten/Kota lain 0 0 0 0 and interactions. Table 1: COVID-19 in South Sulawesi, 2 November 2020 An early indicator of the pandemic’s Notes: This table reports COVID-19 statistics for South Sulawesi. The data was impact on poverty is the 1.63 million downloaded from the COVID-19 South Sulawesi Task Force website (https://covid19. increase in the number of poor people in sulselprov.go.id/data) up to 2 November 2020. Indonesia between 2019 and 2020, to 26.42 million (BPS 2020). There was an 30 increase of about 0.56 per cent in people living below the poverty line, compared 25 to September 2019 (BPS 2020). The 20 number of poor people in South Sulawesi rose by about 0.03 per cent between 15 2019 and 2020 (Figure 3). 10 In April 2020, an online BPS survey 5 collected information from more than i i i i 87,000 people nationwide on the 0 i T g g a a a a a a a a a n h u n n n n u n B s s s s s t t r r r v v v T n n e e a a a a u a t t t r r e e e e e al o ul u t t t a a c u p Bal i N a NT a a impacts of the government’s COVID-19 k Ria u A and s pu a apu a k k g l li t a w a w an t an t Jamb i on t P P a s n al J a m st J st J

r Ban I Malu k Malu k Ja y r policy on their social life and economic t

a a e o I g s L h Be E Sul a w G o W t a B e e ali m aliman ali m aliman t aliman K t h Sum h Sum a h Su l h Sul a w en t r st Sum a Y t k al Sul a w s st Sul t

circumstances. K K K K K D W r r o

e C r Riau g e a l t o h h o N e DI a st s W t W r N Sou t h r N a e Sou t en t t o Ba n E C u W N Sou t en t o C S 2020 2019 Indonesia 2000 Indonesia 2019 Figure 3: Poverty rate at Provincial Level, March 2019 & March 2020 Notes: This figure depicts the poverty rate at the provincial level in Indonesia. The blue horizontal line represents the national poverty rate in March 2020, while the red horizontal line is for March 2019.

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Table 2 reports people’s response to Measures Non-Youth Youth Difference government policy on large-scale social SE restrictions. BPS measures responses Mean SD Mean SD (1) - (3) using a Likert scale from 0 to 10, where (1) (2) (3) (4) (5) (6) 0 is the lowest response. For example, Knowledge the first line shows most people know of physical 8.933 1.668 8.671 1.793 -0.262*** [0.016] about the physical distancing policy. distancing policy Interestingly, young people (aged 15-24) Abide by physical 8.183 2.139 8.008 2.160 -0.175*** [0.020] are significantly less likely to follow social distancing distancing measures and practise hygiene. Wearing of face 8.853 2.135 8.126 2.782 -0.728*** [0.025] masks This survey also looked at the impact of COVID-19 on income. Approximately Wearing of gloves 2.540 3.496 2.246 3.256 -0.294*** [0.030] 42 per cent of the total respondents Hand sanitising 7.718 2.957 6.789 3.331 -0.929*** [0.030] Hand washing for reported a decline in income, while 57 per 8.741 2.007 8.180 2.393 -0.561*** [0.022] cent reported no change and 1 per cent 20-30 seconds reported an increase (Figure 4). Stop touching 7.280 2.588 6.555 2.750 -0.726*** [0.025] face Our analysis (Figure 5) showed that while Stop all income groups were likely to experience 8.571 2.627 8.225 2.659 -0.346*** [0.025] handshaking a drop in income, the highest earners Avoid crowds or (those with income of more than IDR 7.2 standing in long 8.312 2.734 8.070 2.771 -0.242*** [0.026] million per month) were most likely to see queues a decrease. Avoid using The survey also found that more than public 8.468 3.235 8.410 3.166 -0.058** [0.029] 25 per cent of individuals in the lowest transportation income category (those with income Keep a distance below IDR 1.8 million per month) reported of at least 2 7.805 2.375 7.189 2.628 -0.616*** [0.024] a decrease in their income due to metres COVID-19. This suggests the pandemic is Let other people likely to lead to an increase in the number know when you 8.343 2.628 8.121 2.725 -0.222*** [0.025] of poor people. are not well Number of 73363 13926 People SD = Standard Deviation; SE = Standard Error

Table 2: COVID-19 and People’s Responses Decrease 42%

Same 57%

Increase 42% Figure 4: The impact of COVID-19 on income Pr(Income Decrease = 1) Notes: This figure presents the responses to the question: What was the effect of

COVID-19 on your income? .26 .28.24 .3 Low High Lowest Highest Medium Income Level Figure 5: The Effect of COVID-19 on Income Decrease in Different Income Levels, Predictive Margins

Notes: This figure presents the marginal prediction of the impact of COVID-19 on income among individuals at different income levels.

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Our investigation further showed that people in trades and services – those most affected by the large-scale social restrictions – were more likely to experience a fall in income (Figure 6).

Finally, we investigated the impact of COVID-19 on the economic life of households, using changes in income, expenditure and online shopping (see Table 3).

In South Sulawesi, we saw a statistically significant increase in income of about 2 per cent, compared Pr(Income Decrease = 1) with other Indonesian provinces. However, household consumption decreased by about 3 per cent. .2 .25.15 .3 .35

Interestingly, young people (15-24 years) also ICT Trade Health Mining experienced a statistically significant increase in Others FInance Housing Services Industrial Education Agriculture income of about 2 per cent, but we could not see any Other Serv. Waste Man. Government Elect. & Gas Construction statistically significant effect on their consumption and Transportation Accommodation online shopping behaviour. Livelihood Economic Sectors Figure 6: The Effects of COVID-19 on Income across Livelihood Sectors, Consultation with key stakeholders in three PAIR districts Predictive Margins (Officials at the Vice District Office, Bappeda Maros and Health Office of Maros; the Head of Bappeda of Notes: This figure presents the marginal prediction of the impact of COVID-19 on Pangkep and District Secretary of Barru) showed their the decrease in income in different livelihood economic sectors COVID-19 responses were influenced by national and provincial government policies and instructions. 6

Some unique factors influenced the local COVID-19 incidence, such as Maros’ and Pangkep’s proximity to 4 Makassar, which has the most cases in South Sulawesi. Stakeholders highlighted the need to build capacity in COVID-19 related programs such as laboratory testing, and strengthen the role of puskesmas (health facilities) 2 in contact tracing and promoting COVID-safe behaviours.

3.2 DISABILITY AND POVERTY 0 Barru Pangkajene & Maros PAIR South National Disability is a development issue: disability may increase Kepulauan Distrcits Sulawesi the risk of poverty, and poverty in turn may increase the Figure 7: The Average Number of PWD in PAIR Districts compared to Provincial risk of disability (Sen 2009). There is growing empirical and National Number. Source: PODES, 2018. evidence that people with disability (PWD) and their families are more likely than others to experience economic and social disadvantage (WHO 2011).

Purely medical definitions of disability are giving way to Pangkajene & Kepulauan definitions that incorporate continuous measures of the activities that people can undertake, the extent of their participation in society and social and civic life, and the role of adaptive technologies (Mont 2007).

We used the Village Potential Statistics (PODES) 2018 dataset to map the incidence of PWD in our study areas. Since 1980, PODES has provided information about more than 65,000 villages across Indonesia, with data about the prevalence of PWD included since 2000. On average, villages in PAIR districts (Figure 7) have a higher proportion of PWD than South Sulawesi and Indonesia generally. Villages in Pangkep municipalities (3,40] each have, on average, more than four PWD. (1,3] (0,1] No data Figure 8 shows how PWD are distributed across Pangkep Figure 8: Spatial Distribution of PWD in Pangkajene and Kepulauan municipality. Some villages have more than three PWD; Municipality. Source: PODES, 2018 one has more than 30.

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Table 3: COVID-19 and Change to Income, Consumption and Online Shopping

Notes: This table presents regression results using an OLS model. The dependent variables include percentage change in: income (Column 1), expenditure (Column 2), and online shopping (Column 3) respectively.

Dependent Variable: Income Expenditure Online Shopping (1) (2) (3) South Sulawesi 0.026*** -0.032*** -0.027*** [0.005] [0.007] [0.009] Income Level (base = Lowest) Low 0.173*** -0.013*** 0.075*** [0.004] [0.005] [0.006] Medium 0.237*** -0.033*** 0.128*** [0.004] [0.005] [0.007] High 0.273*** -0.081*** 0.193*** [0.004] [0.005] [0.006] Highest 0.279*** -0.133*** 0.291*** [0.004] [0.005] [0.006] Education level (base = Primary School) Junior school -0.028 0.068* -0.065* [0.032] [0.042] [0.039] Senior school 0.086*** 0.115*** -0.009 [0.028] [0.036] [0.032] Diploma 0.142*** 0.150*** 0.046 [0.028] [0.037] [0.032] Diploma IV 0.206*** 0.097*** 0.058* [0.028] [0.037] [0.033] Undergraduate 0.162*** 0.135*** 0.071** [0.028] [0.036] [0.032] Master 0.172*** 0.126*** 0.147*** [0.028] [0.036] [0.032] Doctor 0.183*** 0.117*** 0.186*** [0.028] [0.037] [0.034] Marital status (base = single) Married -0.002 0.056*** -0.001 [0.003] [0.004] [0.006] Divorced -0.050*** 0.084*** 0.013 [0.007] [0.009] [0.012] Youth 0.018*** -0.003 -0.010 [0.005] [0.006] [0.009] Household Size -0.008*** 0.007*** -0.005 [0.002] [0.002] [0.004] Household Size Square 0.000 0.000 0.000 [0.000] [0.000] [0.000] Age -0.001 0.013*** -0.017*** [0.001] [0.001] [0.002] Age Square -0.000 -0.000*** 0.000*** [0.000] [0.000] [0.000] Constant -0.466*** -0.183*** 0.127*** [0.034] [0.043] [0.045] Observations 65,243 65,243 61,499

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Table 4 shows the village characteristics and the average number of PWD in our study area. For example, almost half of all villages in Barru and Pangkep municipalities are coastal, with fisheries as the main livelihood. Some 3.9 percent of the Pangkep villages are seaweed producers. The Pangkep villages are farthest on average from a puskesmas (about 15km). There are also more people with malnutrition in the villages of Maros municipality than Barru and Pangkep.

Table 4: Village indicators and People with Disability

Barru Pangkep Maros

Variable Mean SD Mean SD Mean SD (1) (2) (3) (4) (4) (6)

Coastal village 0.527 0.504 0.485 0.502 0.058 0.235

Sea used for: Fisheries 0.527 0.504 0.476 0.502 0.058 0.235

Sea used for: Culture fisheries 0.000 0.000 0.000 0.000 0.000 0.000

Seaweed producing villages 0.000 0.000 0.039 0.194 0.000 0.000

Number of households 911 337 1050 816 943 673

Percentage of households without electricity 0.026 0.064 0.047 0.148 0.031 0.113

Defecation used by most of the households 1.000 0.000 1.165 0.612 1.301 0.884

Distance to the nearest junior high school 2.835 1.066 3.546 2.981 2.876 1.677

Distance to the nearest senior high school 9.176 8.786 11.935 21.805 6.072 7.421

Distance to the nearest hospital 20.387 13.490 29.610 31.971 22.089 22.514

Distance to the nearest maternity hospital 48.531 24.254 39.322 31.053 34.069 23.373

Distance to the nearest puskesmas 5.683 4.374 15.460 30.782 5.799 5.127

Distance to the nearest policlinic 27.540 25.793 29.872 32.263 19.940 22.833

Number of physicians living in the village 0.564 1.214 0.379 0.865 0.340 1.071

Number of dentists living in the village 0.218 0.459 0.194 0.486 0.175 0.473

Number of midwives living in the village 3.255 4.351 5.087 5.219 3.398 3.440

Number of other health workers in the village 9.273 15.255 6.592 8.149 17.010 11.791

The village has a village midwife (Bidan Desa) 0.982 0.135 0.757 0.431 0.981 0.139

Number of people with malnutrition 0.073 0.325 0.087 0.346 0.311 0.767 Number of people who are blind 1.764 1.587 2.320 2.478 1.447 1.643 Number of people who are deaf 3.727 6.671 2.913 4.361 1.728 4.218 Number of people who are mute 1.491 1.990 1.699 2.347 0.825 1.465 Number of people who are deaf and mute 1.636 1.994 2.136 2.755 1.320 2.193

Number of people who are physically disabled 3.073 4.337 4.621 6.830 1.718 1.982

Number of villages 55 103

SD = Standard Deviation

Notes: This table presents the village characteristics and the average number of people with disabilities in our study area. Source: PODES, 2018.

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There is a well-established link between Rastra program (or Beras Sejahtera, hampered by serious implementation and disability and poverty (Mitra, Posarac, literally ‘prosperous rice’) currently targeting issues. and Wick 2011; Kelles-Viitanen 1999; provides rice to 62 million people. Elwan 1999). Filmer (2008) found But Indonesia also now has a voucher The government launched BPNT in 2017 a strong association between adult program – BPNT. As Indonesia is the as part of its reform of Rastra. Under disability and lower levels of educational only country where both kinds of support the BPNT, Rastra beneficiaries no longer attainment. In Indonesia, PWD are more are targeted at the same group of poor receive rice, but instead a voucher worth likely to fall below the national poverty households, we were able to compare IDR 110,000 per month. It aims to give line than their non-disabled peers (see their effectiveness. them better access to nutritious food Larasati, et al. (2019) for more details). by providing more choice and control The empirical evidence on whether in- over what they buy, and more effectively PODES does not provide information kind food subsidies or food vouchers target households in the bottom 25 per on households’ socio-economic and are better at improving household food cent of the income ladder. demographic characteristics, or the security and dietary diversity (the number living circumstances of PWD. It also only of different food groups consumed in a In the first year of the BPNT captures severe forms of disability, with household, and a good measure of the implementation, more than 1.43 million little information on functional disability nutrient adequacy of individuals’ diet) households received vouchers for some levels, or the type or length of disability. remains ambiguous. 14,000 merchants in 44 cities. By These are areas for future research. 2020, the BPNT system was in place In-kind food subsidies are criticised for nationwide. The key stakeholders we consulted in the high cost of delivery, lower benefits three districts (Maros, Pangkep and relative to costs (Jacoby 1997), leakages, BPNT vouchers can only be used at Barru) are starting to recognise the mismanagement of resources, political e-warong (a kind of small store owned importance of addressing the needs interference and failures in getting by local people) to buy eligible food. The of PWD – the result of provincial and entitlements to intended beneficiaries. initial plans for BPNT restricted the use of national government instructions, and vouchers to rice and eggs (Government of increased advocacy on disabled issues Studies on food vouchers use have Indonesia 2017), but some beneficiaries by community organisations. They also produced varied results: for example a also used them to purchase vegetables acknowledged the need to strengthen 2014 study by Hidrobo et al found that and other staple foods. the capacity of government agencies and vouchers significantly increased dietary The BPNT is targeted at the same employees to fulfil the specific needs diversity among Colombian refugees, households as Rastra but has been of PWD and implement more inclusive but Aker (2017) found that a voucher implemented based on how ready a programs. program for displaced households in Congo failed to improve the quality of the municipality is in terms of cashless and 3.3 DIETARY DIVERSITY AND food consumed. physical infrastructure, as presented GOVERNMENT POLICY below. While in-kind food subsidies help Governments in several developing households meet their food security Dimensions Indicators Source of countries support poor households needs, the focus on staple cereals Data through ‘food-oriented social assistance’ has meant they do not necessarily Cashless The availability of PODES (FOSA). This assistance is either in-kind, address dietary diversity. Kumar et al. Infrastructure store 2014 through the public distribution of food, or (2015) noted that food consumption The availability of PODES market 2014 in the form of vouchers or food stamps in low-income settings was dominated (Alderman et al. 2018). by cheap, starchy foods with limited The availability Banks of government consumption of energy-rich fruits, bank But undernutrition remains a problem vegetables and animal protein. Physical The proportion of PODES in many developing countries, including Infrastructure electrification 2014 Indonesia. According to a recent FAO Rastra is one of Indonesia’s core safety Road access PODES report, Indonesia faces a triple burden of nets. It was first introduced in July 1998 for 4-wheels 2014 malnutrition: child undernutrition, adult as a response to the Asian Financial transportation overweight or obesity, and micronutrient Crisis1 and is the country’s largest social mode deficiencies. assistance program, benefiting 15.5 Internet PODES connectivity 2014 million poor households. Theoretically Rice provides 70 per cent of the dietary each household should receive 15kg rice Table 5: Implementation of BPNT energy needs of Indonesians, and the per month, but the program has been

Initially named OPK for (Operasi Pasar Khusus or Special Market Operation), in the subsequent years of the implementation, the program has changed its name several times. In 2002, to reflect the nature of the program, the government changed the name to Raskin (for beras untuk keluarga miskin or rice for poor families). The name Raskin continued to be used, but during 2006-11, its full title shifted to beras untuk rumah tangga miskin (rice for poor households) and then to subsidi beras bagi masyarakat berpendapatan rendah (rice subsidised for low-income communities) in 2012-15. In 2016, another name change – to Rastra or beras sejahtera (literally ‘prosperous rice’).

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To evaluate the effect of BPNT on dietary diversity, we used two common measures: Household Dietary Diversity Score (HDDS) and Women’s Dietary Diversity Score (WDDS). Both are qualitative measures of food consumption that reflect household access to Log(HDDS) a variety of foods.

Administrative Data Our first dataset comprises administrative Municipalities Index data from the Government of Indonesia, which Panel a: Log (HDDS) 2017 details the readiness for BPNT for each city and municipality in Indonesia, the year in which the implementation of the BPNT was planned in each region and BPNT cutoff (the threshold separating villages that receive Rastra or BPNT).

SUSENAS Surveys Log(HDDS) We used data from the 2017 and 2019 waves of the National Socioeconomic Survey (SUSENAS) to evaluate if the BPNT improves the dietary diversity and intake of nutritious Municipalities Index food by poor households. SUSENAS is a Panel b: Log (HDDS) 2019 cross-sectional, nationally representative dataset. In addition to key demographic and health information, SUSENAS collects the expenditure and value of home production of every food item separately, over a week.

The survey now covers more than 315,000 households and one million individuals in each Log(HDDS) semester. We used the SUSENAS datasets to measure our outcome variables, predict the poverty level of each household, and estimate the social protection eligibility and household Municipalities Index characteristics. Panel c: Log (WDDS) 2017

Village Census (PODES) The last data source is the 2018 PODES, which provides information on all (around 80,000) villages in Indonesia. It includes the main sources of income, population and

labour force characteristics, socio-culture, Log(HDDS) type of village administration and other relevant village-level information. We also used the 2014 PODES dataset to test the fidelity of the administrative data on the BPNT Municipalities Index program. Panel d: Log (WDDS) 2019

Figure 9 shows the local averages of HDDS Figure 9: Illustration of the Effect of BPNT on Dietary Diversity (panels a and b) and WDDS (panels c and d) against the normalised municipalities index Notes: The graphs show the change of HDDS (Panel a for 2017 and Panel which is used by the government to select b for 2019) and WDDS (Panel c for 2017 and Panel d for 2019). The solid BPNT municipalities. line represents the predicted lines and the outer grey lines mark 95 percent confidence intervals. The vertical red dash line is the government cutoff for BPNT 2018.

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Figure 9 (Panels a and b) for HDDS confirms the positive association between the implementation of the BPNT and the improvement of dietary diversity in poor households. The most striking feature of this graph, however, Non-South Sulawesi South Sulawesi Difference is the significant positive jump around Mean SD Mean SD (1) - (3) SE the cutoff of BPNT in 2019. We could (1) (2) (3) (4) (6) (7) not see any significant jump in the Dietary Diversity Index HDDS in 2017. We observed similar HDDS Index 9.545 2.035 9.321 1.663 -0.224*** [0.026] evidence with the WDDS index (Panels WDDS Index 6.461 1.500 6.326 1.350 -0.135*** [0.021] c and d), although the jump is smaller compared to that in HDDS. We also Essential Nutrients Intake estimated the association between Protein 4.092 0.368 4.140 0.344 0.048*** [0.006] BPNT and HDDS. Figure 9 illustrates Calories 7.656 0.292 7.680 0.292 0.024*** [0.005] that the implementation of the BPNT Fats 3.916 0.445 3.816 0.444 -0.100*** [0.009] has improved the dietary diversity of Carbohydrate 5.746 0.300 5.842 0.288 0.096*** [0.005] poor households by about 12.4 per Consumption by groups cent using the HDDS measure; this Cereal 0.975 0.156 0.989 0.107 0.014*** [0.001] finding is statistically significant at 5 White tubers and 0.521 0.500 0.400 0.490 -0.121*** [0.008] per cent. root Our analysis shows that the BPNT Rich vegetables 0.409 0.492 0.482 0.500 0.073*** [0.008] has also improved the consumption Dark green leafy 0.911 0.285 0.883 0.322 -0.028*** [0.005] of essential nutrients by poor vegetables households, except the intake of Other vegetables 0.953 0.211 0.973 0.163 0.019*** [0.002] daily fat. It has also increased the Rich fruits 0.447 0.497 0.315 0.464 -0.132*** [0.009] daily consumption of calories and Other fruits 0.714 0.452 0.907 0.291 0.193*** [0.005] carbohydrates. Poor households Organ meats 0.038 0.192 0.003 0.052 -0.035*** [0.001] who receive the BPNT experience a Flesh meats 0.512 0.500 0.257 0.437 -0.256*** [0.007] daily calorie intake increase of more than 20 per cent, compared to poor Eggs 0.845 0.362 0.838 0.369 -0.008 [0.005] households on the rice program. Fish and 0.889 0.314 0.972 0.164 0.083*** [0.002] Seafood It is clear that the implementation of Legumes 0.753 0.431 0.645 0.478 -0.108*** [0.007] the BPNT has improved the targeting Milk 0.388 0.487 0.388 0.487 -0.000 [0.007] performance of social protection Oil and Fats 0.964 0.187 0.972 0.164 0.009*** [0.002] programs in Indonesia. Sweets 0.932 0.252 0.958 0.200 0.027*** [0.002] Knowing that BPNT implementation Spices, 0.983 0.129 0.991 0.092 0.008*** [0.001] has improved dietary diversity condiments, and and essential nutrients intake, we beverages investigated the situation in South Number of 301490 14093 Sulawesi (Table 6). Households in Households South Sulawesi have a lower HDDS and WDDS index, suggesting a lower Table 6: Dietary Diversity and Nutrients Intake – South Sulawesi vs Non South Sulawesi diversity of consumption. This is backed by evidence that households in South Sulawesi are less likely than households elsewhere in Indonesia to consume meat.

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Our analysis of the results suggests a statistically significant correlation between gender, marital status, health status, religiosity and social capital on mental health.

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3.4 MAPPING THE from more than 30,000 individuals 4.0 CONCLUSION AND INCIDENCE OF MENTAL from 12,000 households and is RECOMMENDATIONS H E A L T H representative of about 83 per cent of the entire Indonesian population. The findings from each of our four Poor mental health is a major issue projects are described in detail for both developed and developing In the IFLS survey, each respondent above. Given the time constraints countries (WHO 2011). Approximately was asked to report how often they and COVID-related restrictions, we 7 per cent of the total burden of experienced the listed 10 depressive have been unable to work on the disease in 2010 was attributed symptoms in the week prior to the qualitative survey component. The to various forms of mental health survey. secondary data analysis has informed disorders (5 per cent in 2000, 4 the design of our next major project, per cent in 1990; IHME 2013). The Our analysis of the results suggests the Strategic Integrated Project (SIP) prevalence of common mental health a statistically significant correlation to be delivered under the Partnership disorders in developing countries between gender, marital status, for Australia-Indonesia Research. In is approximately 6-7 per cent in health status, religiosity and social particular, the lack of available detail the general population (Rai, Zitko, capital on mental health. For on people with disability and mental Jones, Lynch, & Araya 2013). Mental instance, a male aged 24-46 years health in secondary datasets has disorders ranked 19th among the has a lower incidence of mental helped us design our SIP. leading causes of disability in 2016, disorders compared to females up from 29th in 1990. in the same age group. Several The next stages of our research studies linked the lower incidence will enable further important study The Indonesian 2018 Basic Health of mental disorders among males and lead to greater knowledge Survey (Riskesdas), conducted by with males’ common reluctance to and understanding of Indonesia’s the Ministry of Health, estimated acknowledge and report their mental development needs. that 0.67 per cent of Indonesian health problems, acknowledging that households had at least one vulnerabilities related to health and member with psychotic disorders. mental health contradict cultural An estimated 6.1 per cent of the norms of being masculine (Courtenay population aged 15 years and 2000; Connell and Messerschmidt older were categorised as having 2005). depression. South Sulawesi has among the highest prevalence of Another interesting finding was that mental disorders in Indonesia (Idaiani unmarried individuals were found to et al. 2019). have a 5 per cent higher depression score than their married counterparts. A number of studies including Healthy individuals were estimated to Riskesdas 2013 and 2018 show have a 10 per cent lower depression the increasing prevalence of mental score than unhealthy people. health problems in Indonesia such as Interestingly, we found no statistically anxiety and depression. Women are significant correlation between among the most vulnerable to mental religiosity and mental health. health problems. The puskesmas and hospitals in Indonesia were found to The key stakeholders we consulted – be ill-equipped to address mental the officials at the Vice District Head health issues (Prastyani 2019), with of Maros, Bappeda Maros, Health postnatal women and young women Office Maros; the Head of Bappeda suffering from financial stress and a of Pangkep and District Secretary lack of support particularly affected. of Barru – told us that while mental health is important, their districts To map the characteristics and the have limited human resources (such environment of adults with a mental as psychiatrists, psychologists, disorder, we used the 2007 and 2014 mental health nurses and health datasets from Indonesian Family promotion staff) to address mental Live Surveys (IFLS) from RAND. The disorders. IFLS is a multi-purpose longitudinal household survey that collects data

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5.0 REFERENCES

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POLICY PARTNERS:

PARTNERS FOR IMPACT:

Program Management Team: Dr Hasnawati Saleh, PAIR Acknowledgements South Sulawesi Village and Research Coordinator, The The Australia-Indonesia Community Empowerment Dr Eugene Sebastian, Australia-Indonesia Centre Centre (AIC) acknowledges Office PAIR Program Director Professor Heri Hermansyah, the Australian Government South Sulawesi Manpower Helen Fletcher-Kennedy, AIC Acting Director of Research and for its generous support of and Transmigration Office Chief Operating Officer Community Engagement, the Partnership for Australia- Dr Leonardo Pegoraro, Ministry of Research and Indonesia Research (PAIR) Government of Makassar City PAIR Program Manager Technology, Republic of through the Department of Dr Hasnawati Saleh, Indonesia Foreign Affairs and Trade. Government of Maros PAIR Research Coordinator Dr Ishak Salim, Co-Founder The AIC also gratefully Regency acknowledges the Government Dr Martijn van der Kamp, PAIR Indonesian Diffable Movement Government of Pangkep of Indonesia’s support for Team Capability Coordinator for Equality Regency PAIR through its Ministry of Professor Jamaluddin Jompa, Marlene Millott, Research and Technology. PAIR Program Officer Advisor for Marine Ecology Government of Barru Regency at the RI Ministry of Maritime Fadhilah Trya Wulandari, We also extend our Government of Parepare Affairs and Fisheries PAIR Program Officer gratitude for the support we Municipality Jana Hertz, Team Leader at the receive from the following Research Advisory Panel: Knowledge Sector Initiative organisations: South Sulawesi Health Office Alison Duncan, Muhammad Sani Azis, and the COVID-19 Task Force Minister-Counsellor (Economic, Government of South Regional Coordinator (South Investment and Infrastructure), Sulawesi Makassar Health Office and Sulawesi), Indonesian Seaweed Australian Embassy, Jakarta the COVID-19 Task Force Association (ARLI) Ministry of Research and Professor Budu, the Dr Musdhalifah Machmud, Technology / National Maros Health Office and the South Sulawesi Provincial Deputy Minister for Food and Research and Innovation COVID-19 Task Force Government’s Development Agriculture, RI Coordinating Agency, Indonesia Acceleration Team (TGUPP) Ministry for Economic Affairs Pangkep Health Office and Bronwyn Robbins, Australian Agency of Health Research the COVID-19 Task Force Prakosa Hadi Takariyanto, Consul General in Makassar and Development, Ministry of Technical Director PT Pelabuhan Barru Health Office and the Dr Elan Satriawan, Chief of Health, Indonesia Indonesia IV (Persero) COVID-19 Task Force Policy Working Group, National Pratiwi Hamdhana, Founder National Team for the Team for the Acceleration of Parepare Health Office and and Managing Director, Tenoon, Acceleration of Poverty Poverty Reduction (TNP2K) the COVID-19 Task Force Driver Engagement, Gojek Reduction (TNP2K), Indonesia Dr(HC) Erna Witoelar, Former Makassar UN Special Ambassador for Agency for Planning, The Sulsel Independent Youth Professor Wihana Kirana Jaya, Millennium Development Goals Research and Development Alliance (ARI Sulsel) Special Staff to the RI Minister (BAPPELITBANGDA), South (MDGs) in the Asia Pacific Indonesian Diffable Movement for Economic Affairs and Sulawesi Dr Eugene Sebastian, Transportation Investment, for Equality (PerDIK) Executive Director, The Ministry of Transportation Governor’s Team for the Australia-Indonesia Centre Association of Indonesian Development Acceleration Women with Disabilities (TGUPP), South Sulawesi (HWDI)