Poverty and distributional impact of Covid-19 Crisis in Indonesia - PowerPoint PPT Presentation

Poverty and distributional impact of Covid-19 Crisis in Indonesia Arief Anshory Yusuf SDGs Center, Universitas Padjadjaran http://sdgcenter.unpad.ac.id Presented at How is COVID-19 changing development? WIDER Webinar Series, UNU/WIDER, 12 May 2020

• A brief update on the covid-19 pandemic in Indonesia I will talk • Its impact on economic growth and policy responses about • Translating economic growth into poverty impact: Accounting for non-neutral distributional effect

By today, Indonesia officially report 14,749 case and 1007 death

Yet, testing rate and its under-reporting is among the world’s lowest

There is still risk of catastrophic number of death Number of death with different scenarios 1400000 1,157,729 1200000 1000000 762,192 800000 653,804 600000 339,539 400000 200000 58,302 0 Unmitigated Enhanced social Social distancing Supression - 1.6 Supression - 0.2 strategy distancing of elderly whole population deaths per 100,000 deaths per 100,000 (43%) (45%) per week trigger per week trigger Source: MRC Centre for Global Infectious Disease Analysis, Imperial College London (March 2020)

Containment measures applied in selected regions in the form of “large-scale social restriction”, a softer version of lockdown. JAKARTA INDONESIA INDIA Source: Google Mobility Report

Economic growth in 2020 is projected to be -3.5 to 2.3% (Baseline is 5%). Recovery profile varies. Institution Growth in 2020 Recovery path Kementerian keuangan -0.4% sd 2.3% Not estimated Oxford Economics -0.8% V-shaped (2021: 8.5%) World Bank -3.5% sd 2.1% Not estimated IMF 0.5% V-shaped (2021 8.2%, 2 year) Economist Intelligence Unit 1.0% U-shaped (2021: 5.0%)

Fiscal stimulus and social assistance • Increase budget deficit from 2.5 to 5.07% GDP • Allocate Rp405 trillion ($27B/2.5%GDP) for Covid-19 response • Rp110T social assistance, Rp75T health spending, Rp70T Industry support, Rp150T economic recovery • Social assistance

Close to 70% of Indonesian are poor or vulnerable. Among the highest in the region. 35.6 70.4 32.0 22.3 97.0 81.4 24.8 43.9 89.0 66.5 78 75 68 64 56 b 33 30 19 11 3 Source: World Bank (2018); Note: Economically secure > PPP2011$5.5/person/day

Social assistance, given to the poor AND vulnerable. Source: Ministry of Finance

Impact on poverty (Previous estimates) 2019:9.22%, impact: +0.44% to +3.2% (1.16M to 9.6M) Lower bound Upper bound Method Ministry of Finance* +0.44% +1.41% Unpublished +1.16 M people +3.78 M people Smeru** +0.56% +3.2% Growth++ +1.3 M people +8.4 M people 2005-2006 episode ADB +2.6% +3.6% Growth++ +6.9 M people +9.6M people Source: *) Presentation by Dr. Febrio Kacaribu, Head of Fiscal Policy Office, MoF; **) Smeru Research Institute

Distributional effect of Covid-19 Crisis: Literature • Pandemic create labor shortage: equalizing (Scheidel’s Great leverer) • Spanish flu decrease returns on stock (Barro et al, 2020) ? • … yet current pandemic is not as deadly. • Pandemics of the past 2 decades: inequalizing (Furceri et al, 2020)

The shape of growth incidence curve (GIC) from Covid-19 crisis will depend on various factors, such as: • It’s not distributional effect of pandemic per se, it’s about containment (vary widely by countries) Crisis will hit everyone. GIC will be all below zero. • Unlikely to create labor shortage (“the great leveler”) • Medium term may involve scarring effect (precautionary saving) • Lockdown effect will most likely predominantly urban. Agriculture may be hit less. • Services, like transport/travel, will be hit hard but WFH may help. In Indonesia, services growth tend to be income- • inequalizing. • Manufacturing, especially labor intensive, will be hit hardest. Urban poor, and national middle class will be hit hard. • Region and sectors heavily dependent on tourism is on the ‘natural’ lockdown that last longer. Tourism has extensive repercussion effect. Its effect may be neutral. Lockdown is hard to enforced in informal sector, yet, informal activity sustain only on daily basis. • Social safety net matters, yet fiscal space is limited. • Indonesian geography is unique too. • Hard to verdict, but in the sort term the sectoral impact may tend toward inequality reducing. Similar to 1997/98 financial crisis in Indonesia.

Analysis with Indonesian CGE model: Effect on sectoral output from various channels Source: Simulation with IndoTERM CGE model

Sectoral growth projection of 2020 (EIU) February forecast April forecast -4.1% - GDP Impact of COVID-19 -0.9% - Agriculture -4.5% - Industry -4.8% - Services

A “pragmatic” reduced-form expenditure per capita equation Preliminary analysis: ignoring within sector’s distribution Household expenditure per capita is a function of household head’s human capital, job characteristics, and his/her labor supply + ∑ � � (� � � ℎ) + + ∑ � � (� � � ℎ) + ln � = � + �ℎ + ∑ � � � � ∑ � � � � ⋯ � � � � + ∑ � � (� � � ℎ) + ⋯ + ∑ � � � � ∑ � � � � + � � � � � : monthly expenditure per capita ℎ : hour of works in a month � � : sector of employment (dummies) � � : status of employment (dummies) � � : skill level (dummies) � � : area (urban/rural), number of family members, number of working family members, years of education, province-fixed effect � : error term Estimated using 2019 National social economic survey (SUSENAS) data.

Sector-biased 4.1% reduction in growth (relative to 5.0% baseline growth) in 2020 (EIU, April 2020) Agriculture-biased Industry-biased Service-biased Source: Author’s estimation

Distributional impact of EIU 2020 forecast of -4.1% reduction in growth with -1% in agriculture, -4.5% in industry and -4.8% in services sector-biased growth incidence The case of distribution-neutral (based on EIU projection) over-estimating poverty impact distribution-neutral sector-biased baseline Source: Author’s estimation

Poverty impact of EIU 2020 projection on poverty Distribution-neutral Sectoral-biased With With Baseline Change Baseline Change Covid Covid National poverty line Percent 9.2 10.6 1.3 9.2 10.2 0.9 M Population 24.6 28.2 3.6 24.6 27.1 2.5 PPP$1.9 Percent 2.0 2.7 0.7 2.0 2.4 0.4 M Population 5.3 7.1 1.8 5.3 6.4 1.0 PPP$3.2 Percent 17.2 19.2 2.0 17.2 18.8 1.5 M Population 46.0 51.4 5.4 46.0 50.2 4.1 PPP$5.5 Percent 48.68 51.11 2.43 48.68 50.77 2.10 M Population 130.0 136.5 6.5 130.0 135.6 5.6 Gini coefficient 0.382 0.382 0.00 0.382 0.378 -0.004 Source: Author’s estimation

Final remarks • Indonesia is still struggling to mitigate the covid-19 pandemic. Serious health/fatality risk remains. • Due to high poverty vulnerability, not only that health system is under-pressure, but the social safety net system is under pressure. Past reform and progress in the improvement of the social safety net system is currently under heavy test. • Using national line, 2.5M people will become poor (Almost 3 years reduction). Using PPP$3.2 line, 4.1M people will become poor. • Distributional effect of Covid-19 economic crisis is uncertain. In Indonesia its sectoral impact may tend to reduce inequality slightly. • Urgent research agenda: the growth incidence of economic recovery.

http://sdgcenter.unpad.ac.id Thank you Arief Anshory Yusuf SDGs Center, Universitas Padjadjaran