Neil McCulloch Amit Grover ESRC Development Economics Conference Effects of the Global Economic Crisis on Developing Countries – 21/22 January 2010 Estimating the impact of the financial crisis in Indonesia: combining rapid qualitative studies with nationally representative surveys

Qualitative study of the financial crisis In February 2009 IDS undertook a set of rapid qualitative assessments in five countries including Indonesia. One urban and one rural village were selected for in depth interviews and focus group discussions Urban village: Gandasari (Jakarta) is a major Industrial Park with a large population migrant workers. Rural village: Simpang Empat (South Kalimantan) heavily dependent on local rubber plantations and coal industry

Key findings from the qualitative survey High prices for food, agricultural inputs and transport persisted in both locations Rural village: Reduced worker income from declining production Subsequent decline in other economic activities Some shifts to working in the service sector Urban village: Reduction in working hours in the factories Temporary lay off of permanent workers Discontinuation of contract workers

Indonesian macroeconomic context Growth % (y-o-y)3 rd Quarter st Quarter rd Quarter 2009 GDP Inflation Exports Imports Exchange rate (Rp/US$) 9,33111,5179,633 Investment This was no East Asian Crisis However large falls in exports in the third quarter of 2009 Possible higher impact on commodity dependent communities 1 Inflation figures are y-o-y figures for the end of the last month of each quarter. 2 Jan-Oct 2009 over Jan-Oct Source: BPS, World Bank (2009)

Data source Statistics are constructed using the 2008 and 2009 Indonesian Labour Force Survey (Sakernas) 218,833 individuals (69,114 households) sampled in Feb ,890 individuals (291,689 households) sampled in Aug ,689 individuals (68,535 households) sampled in Feb 09 February surveys are random subset of the August sample Data collected for individuals who are 10 that live in a physical building Lodgings with > 10 people & people whose needs are provided by an organisation are not sampled

Were children withdrawn from school ? No longer in schoolIn school last week Age and gender Feb-08Aug-08 Feb-09 Feb-08Aug-08 Feb ** *0.065** ** ***0.112** ***0.881*** ** ***0.605 Male * Female ** ***0.856 Total (10-17) **0.85 Source: Sakernas data for respective years Note: Asterisks in each column indicates statistical significant changes from February 2008; * = significant at 10%; ** = significant at 5%; *** = significant at 1%

Fall in labour participation for under 18s Participation Age and genderFeb-08Aug-08 Feb *** ***0.043*** ***0.07*** ***0.111*** ***0.238*** *** ***0.801*** ***0.549 Male (15+) Female (15+) Total (15+) Source: Sakernas data for respective years

Unemployment fell for older workers but rose for younger ones Unemployment Age and genderFeb-08Aug-08 Feb ** *** *** *** ***0.214*** * * ***0.043*** ***0.016*** ***0.008 Male (15+) **0.077 Female (15+) *0.088* Total (15+) *

Hours worked unchanged during the crisis Hours of work Age and genderFeb-08 Aug-08 Feb *** *** Male (15+) Female (15+) Total (15+) Source: Sakernas data for respective years

Share of employment and hours worked by sector Share of EmploymentHours of work Sector of the individualFeb-08Aug-08 Feb-09 Feb-08 Aug-08 Feb-09 Agriculture *** ***32.6 Mining and Quarrying Industry Electricity, Gas and Water Construction *** *45.8 Trade Restaurant and Acc * Transport and Comm Financial Inst, Real Estate Social Services, Social & Pers ** ***43.3 Source: Sakernas data for respective years

Share of employment and hours worked by work category Share of workersHours worked Category of workFeb-08Aug-08 Feb-09 Feb-08Aug-08 Feb-09 own business *** ***41.8 business owners with non permanent or unpaid workers ** business owners with permanent or paid workers employee **46.2 casual work agriculture ***34.5 casual work non agriculture *** unpaid work *** ***31.1***

Wages increased during the crisis Percentage changes Real Wage (Rupiah per month)Nominal Wage (Rupiah per month)Real WagesNominal wages Age and gender Feb-08Aug-08Feb-09 Feb-08Aug-08 Feb-09 Feb08- Aug08 Feb08- Feb09 Feb08- Aug08 Feb08- Feb ,651470,892487, ,976502, ,973 0%4%2%7% ,545700,371766, ,080747, ,871 -3%6%-2%9% ,005,889998,3531,079,065*1,056,6691,065,434 1,171,276***-1%7%1%11% ,311,0451,332,8891,465,920***1,377,2361,423,376 1,591,641***2%12%3%16% ,608,7411,641,4811,789,487***1,689,1701,752,972 1,943,712***2%11%4%15% 56+1,243,4241,216,6401,497,141**1,305,1011,298,746 1,623,825**-2%20%0%24% Male1,162,3481,173,3851,293,014***1,221,1631,252,976 1,404,218***1%11%3%15% Female886,075909,449984,577***930,151970,307 1,068,290***3%11%4%15% Total1,070,2001,082,3601,190,994***1,124,0991,155,490*1,293,105***1%11%3%15%

Wages changes by sector Percentage changes Real Wage Rupiah per monthNominal Wage Rupiah per monthReal WageNominal wages Sector of the individual Feb-08Aug-08 Feb-09 Feb-08Aug-08 Feb-09 Feb08- Aug08 Feb08- Feb09 Feb08- Aug08 Feb08- Feb09 Agriculture717,624795,119***723, ,034851,767***788,112 11%1%13%4% Mining and Quarrying2,015,3962,102,264 1,840,817***2,125,9652,258,565*2,015,873 4%-9%6%-5% Industry920,908869,769***1,002,005***966,614927,115**1,085,574***-6%9%-4%12% Electricity, Gas and Water 1,848,2311,767,199 1,806,329 1,941,7461,888,439 1,959,084 -4%-2%-3%1% Construction1,084,0871,024,250*1,218,448***1,138,9291,093,257 1,324,231***-6%12%-4%16% Trade Restaurant and Acc 902,201914, ,810**946,907974,677 1,035,862***1%6%3%9% Transport and Comm1,273,1831,277,662 1,569,649***1,337,0791,362,912 1,703,966***0%23%2%27% Financial Inst, Real Estate 1,744,7261,652,934**1,831,938**1,830,4551,761,249 1,984,687***-5%5%-4%8% Social Services, Social & Pers 1,181,9871,246,432***1,344,543***1,241,5381,331,335***1,461,161***5%14%7%18%

Compositional changes affect Wages changes

Income did not rise for other work categories Real Income/Real Wage Category of workFeb-08Aug-08 Feb-09 own business706,257825,304***722,141 business owners with non permanent or unpaid workers business owners with permanent or paid workers employee1,070,2001,082,360 1,190,994*** casual work agriculture362,462385, ,935 casual work non agriculture588,261607, ,252 unpaid work

Reasons for ending employment Reason for ending work/changing jobAug-08Feb-09 Fired/Made redundant *** No demand or firm went bankrupt *** Income too low * Unsuitable work environment Contract finished Other *** Redundant or No demand Sector of the individualAug-08Feb-09 Agriculture, Plant, Hunt *** Mining and Quarrying *** Industry *** Electricity, Gas and Water Construction *** Trade Restaurant and Acc Transport, Storage and Comm ** Financial Inst, Real Estate Social Services, Social & Pers ***

Multivariate analysis: school enrolment School Dropout rates are higher for: older males large households with high dependency ratios rural areas households headed by casual workers household headed by agriculture workers children in households where the head and spouse achieve lower education qualifications Large differences in dropout rates between provinces. Virtually no change in dropout rates before or during the crisis

Labour participation and unemployment Labour participation Labour participation increases with age and education Women and large urban households less likely to participate Small reductions in labour participation over time after controlling individual and household characteristics Unemployment Unemployment increases with household size and education Older workers and households with higher dependency ratio less likely to be unemployed Unemployment may have increased for young workers and reduced for older workers

Qualitative vs. Quantitative results Qualitative (Feb 2009)Quantitative (Feb08-Aug08-Feb09) School AttendanceNo change, but some arrears in payment No change or continued improvement for 13/14 year olds. possible seasonal withdrawal in August for girls and 17 year olds. Female labour participation No change Child labourNo change Significant falls in the participation of year olds in the labour force Unemployment Increase for young migrant industrial workers; and workers associated with the rubber industry Rising for year olds; falling for year olds Hours of workReduced for contract workers Virtually no significant changes by age or sector InformalitySome suggestions of increased informality Evidence for increased own business and casual non-agricultural work in 2008, but little overall change Wages and Income Large falls in take home pay for contract workers; reductions in income for local businesses Significant and large increases in real wages for employees; but little change in incomes in the informal sector

Summary and conclusions Indonesia weathered the financial crisis comparatively well In spite of dramatic exports declines little evidence of subgroups being particularly affected Parents kept children in school as labour market for younger worker deteriorated Unemployment rose for workers between 18 and 25 but fell for workers above this age Surprising increase in real wages of employees A lesser dependence on international trade and good macroeconomic management are possible reasons why Indonesia fared better during the financial crisis

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