Indonesian Economic Transformation and Employment

Public Disclosure Authorized Public Disclosure Authorized Indonesian Economic Transformation and Employment Policy input for an Indonesia Jobs Strategy Public Disclosure Authorized Public Disclosure Authorized

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Report No: AUS13186. Republic of Indonesia Economic Transformation and Employment Policy input for an Indonesia Jobs Strategy June 2016 GTC02 EAST ASIA AND PACIFIC Standard Disclaimer: This volume is a product of the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this paper do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Copyright Statement: The material in this publication is copyrighted. Copying and/or transmitting portions or all of this work without permission may be a violation of applicable law. The International Bank for Reconstruction and Development/ The World Bank encourages dissemination of its work and will normally grant permission to reproduce portions of the work promptly. For permission to photocopy or reprint any part of this work, please send a request with complete information to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA, telephone 978-750-8400, fax 978-750-4470, http://www.copyright.com/. All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA, fax 202-522-2422, e-mail pubrights@worldbank.org. 2

This report is part of the World Bank s support to the Government on an Indonesia Jobs Strategy. This report is prepared by Claire H. Hollweg, Maria M. Wihardja, Massimiliano Calì, Milan Nedeljkovic, Julian L. Clarke, and Brasukra G. Sudjana. It also includes data and inputs by Ali Zafar, Arif Khan, Ahsan Tariq Butt, Agnesia A. Hasmand, Daim Syukriah, Bagus Arya Wirapati, and Michaelino Mervisiano. It also benefited from inputs and guidance from Vivi Alatas (Lead Economist, Poverty GP), Truman Packard (Lead Economist, Social Protection & Labor), Ndiame Diop (Lead Economist, Macro Economics & Fiscal Management), Mona Haddad (Practice Manager, Trade & Competitiveness), and Tatiana Nenova (Program Leader, World Bank Office Jakarta), as well as comments from peer reviewers: Elizabeth Ruppert Bulmer (Lead Economist, Jobs CCSA) and Marc Tobias Schiffbauer (Senior Economist, Macro Economics and Fiscal Management). The team acknowledges the inputs provided by a number of government officials, private sector businesses, and labor union activists. 3

Contents EXECUTIVE SUMMARY... 6 1. INTRODUCTION: INDONESIA S ECONOMIC TRANSFORMATION... 8 THE JOBS OBJECTIVE: SHIFTING TOWARDS QUALITY AND PRODUCTIVE JOBS... 8 INDONESIA S COMMODITY BOOM... 8 CREATED A TWENTY-FIRST CENTURY DUTCH DISEASE... 9 WITH ADVERSE IMPACT ON JOBS... 10 IS THERE AN OPPORTUNITY FOR ANOTHER STRUCTURAL TRANSFORMATION?... 11 2. LABOR TRANSITION TRENDS: RESULTS FROM THE IFLS... 13 SERVICES SECTORS CONTINUED TO ABSORB LARGE SHARES OF WORKERS... 13 LARGE COUNTRY, LOW MOBILITY... 15 HAVING THE RIGHT SKILLS AND INITIAL ENTRY INTO FORMAL/INFORMAL EMPLOYMENT MATTER... 16 ADVANTAGE: YOUNG AND MALE... 17 3. DRIVERS OF LABOR TRANSITION: RESULTS FROM LABOR MOBILITY COST AND EMPLOYMENT ELASTICITY ANALYSES... 18 LABOR MOBILITY COSTS IN INDONESIA ARE RELATIVELY HIGH... 19 BUT, HAVE BEEN DECLINING ACROSS SECTORS AND REGIONS... 21 THE RIGHT SKILLS MIX AND INFORMALITY REMAIN IMPORTANT... 22 DO REAL WAGES MATTER?... 25 EVIDENCE FROM EMPLOYMENT ELASTICITY... 26 4. LABOR CONTENT OF EXPORTS: POTENTIAL SOURCES OF DEMAND FOR LABOR?... 34 DO EXPORTS SUPPORT EMPLOYMENT?... 34 WHICH SUB-SECTORS CONTRIBUTE SIGNIFICANTLY TO WAGES AND EMPLOYMENT?... 35 5. POLICY IMPLICATIONS... 38 ANNEX 1 LABOR MOBILITY COST METHODOLOGY... 42 METHODOLOGY... 42 DATA... 44 ANNEX 2 LABOR CONTENT OF EXPORTS METHODOLOGY... 46 4

Figures FIGURE 1 SECTORAL CONTRIBUTION TO GDP (%)... 8 FIGURE 2 SECTORAL CONTRIBUTION TO EMPLOYMENT (%)... 8 FIGURE 3 SHARES OF TOTAL EXPORTS, 1989-2013... 9 FIGURE 4 INDONESIA CPI RER VIS-À-VIS USD, JAN 2002-DEC 2015... 10 FIGURE 5 RER DECOMPOSITION - ANNUAL CONTRIBUTIONS TO INDONESIAN RER CPI CHANGE (VS. USD): TRADABLE PRICES BASED ON EXPORT AND IMPORT INDICES, 2002-2015... 11 FIGURE 6 RER DECOMPOSITION ANNUAL CONTRIBUTIONS TO INDONESIAN RER CHANGE (VS. USD): FOOD VS. NON FOOD PRICES, 2002-2015... 12 FIGURE 7 LABOR SHARES (%), AGED 15 AND ABOVE, ACROSS SECTORS AND REGIONS, 1997-2007... 13 FIGURE 8 LABOR MOBILITY COSTS VS. GDP PER CAPITA IN INDONESIA AND OTHER TPP COUNTRIES... 20 FIGURE 9 LABOR MOBILITY COSTS, WAGES, AND EMPLOYMENT, ACROSS SECTORS AND ACROSS REGIONS, 1997-2007... 22 FIGURE 10 LABOR MOBILITY COSTS ACROSS SECTORS BY WORKER TYPES, 2000-2007... 24 FIGURE 11 LABOR MOBILITY COSTS ACROSS SECTORS BY JOB TYPE, 2000-2007... 25 FIGURE 12 REAL WAGES ACROSS SECTORS, 1997-2007... 25 FIGURE 13 REAL WAGES ACROSS REGIONS, 1997-2007... 26 FIGURE 14 EMPLOYMENT BY GENDER AND BY 3-SECTOR OF EMPLOYMENT, 1990-2015... 30 FIGURE 15 EMPLOYMENT BY AGE GROUPS AND 3-SECTOR OF EMPLOYMENT, 1990-2015... 31 FIGURE 16 EMPLOYMENT BY FORMALITY AND 3-SECTOR, 1990-2015... 33 FIGURE 17 DIRECT AND TOTAL LABOR VALUE ADDED OF EXPORTS, 1995-2011... 34 FIGURE 18 TOTAL LABOR VALUE ADDED OF EXPORT SHARE, SELECT COUNTRIES, 1995-2011... 34 FIGURE 19 TOTAL NUMBER OF JOBS (DIRECT AND INDIRECT) SUPPORTED BY EXPORTS (IN 000), 2007... 35 FIGURE 20 DIRECT AND INDIRECT LABOR VALUE ADDED OF EXPORTS, 2011... 36 FIGURE 21 DIRECT AND INDIRECT LABOR VALUE ADDED OF EXPORTS (FORWARD LINKAGES), 2011... 36 FIGURE 22 NUMBER OF JOBS IN EXPORTS ACROSS MORE REFINED SECTORS, 1997 VS. 2011... 37 Tables TABLE 1 TRANSITIONS ACROSS SECTORS AND INTO AND OUT OF LABOR FORCE STATUS (%), 2000-2007... 15 TABLE 2 TRANSITIONS ACROSS SECTORS AND INTO AND OUT OF LABOR FORCE STATUS (%), 1997-2000... 15 TABLE 3 TRANSITIONS ACROSS REGIONS (%), 2000-2007... 16 TABLE 4 TRANSITIONS ACROSS AGGREGATE SECTORS BY SKILL LEVEL (%), 2000-2007... 16 TABLE 5 TRANSITIONS ACROSS AGGREGATE SECTORS BY FORMALITY (%), 2000-2007... 17 TABLE 6 SHARE OF EMPLOYMENT (%), 1990-2015... 26 TABLE 7 SECTORAL EMPLOYMENT ELASTICITY, 1993-2006 VS. 2007-2015... 28 TABLE 8 LABOR PRODUCTIVITY GROWTH RATE/GDP GROWTH RATE, 1993-2006 VS. 2007-2015... 28 TABLE 9 SECTORAL EMPLOYMENT ELASTICITY, BY GENDER, 1993-2006 VS. 2007-2015... 29 TABLE 10 SECTORAL EMPLOYMENT ELASTICITY, BY AGE GROUP, 1993-2006 VS. 2007-2015... 31 TABLE 11 SECTORAL EMPLOYMENT ELASTICITY, BY FORMALITY/INFORMALITY OF JOBS, 1993-2006 VS. 2007-2015... 32 TABLE 12 REGIONAL EMPLOYMENT ELASTICITY, 1993-2006 VS. 2007-2015... 33 Boxes BOX 1 DEFINING LABOR MOBILITY COSTS... 18 BOX 2 EMPLOYMENT ELASTICITY METHODOLOGY NOTE... 27 5

Executive summary The commodities boom in the early 2000s reversed the expansion of Indonesia s industrialization that had begun in the 1980s. The commodities boom led to an increase in the export share of agriculture; mining and mineral commodities expanded at the expense of manufactured exports and services. This was accompanied by an appreciation of the real exchange rate (RER), which reduced the relative competitiveness of Indonesia s tradeable sectors and contributed to sluggish performance in noncommodity exports. This reversal in economic transformation had an adverse impact on jobs. Most jobs created during the commodities boom were in trade and retail as well as social and personal services. These sectors exhibit low productivity jobs. Today, around 70 percent of workers are employed in agriculture and these lowend services. Meanwhile, increasing labor productivity is crucial to boosting growth (World Bank, 2014). The end of the commodities boom and recent depreciation in the nominal value of the Rupiah suggest the possibility that Indonesia could retrace the path back to manufacturing and high productivity activities. Stickiness in the depreciation of the Rupiah relative to other commodity exporters, however, implies that this transformation will only be possible if accompanied by policy reforms that target local retail prices and food price inflation. Domestic prices have been rising faster than border prices relative to US and Asian peers, due to increased protectionism in the form of higher tariff and non-tariff barriers as well as increased logistics and distribution costs. While a depreciation of the Rupiah will enable firms to regain competitiveness and thus create jobs, it will not be enough labor mobility costs will also have to be reduced. Labor mobility costs reflect what a worker perceives to be his or her welfare cost of moving between industries to find alternative employment, and capture the various costs that explain why workers do not move into higher-wage sectors. To unleash the economic transformation that is waiting to happen, labor needs to be able to move from the sectors/firms with low productivity to those with higher productivity. This labor mobility is typically hindered by several factors; typical impediments to job switching are skills mismatches (wages forgone because of lower productivity), limitations to geographic mobility (administrative procedures for internal migration and direct relocation costs), and severance and hiring costs (including those imposed by laws or regulations). Other factors may be location preferences, job search costs, and even the psychological costs of changing jobs. Looking at how workers transition from one sector to the other sectors of the economy, there is greater fluidity in Indonesia s labor market, but it is defined by transitions towards low productivity services. From 1997 and up until 2007, services sectors have been the largest absorbers of workers that changed sectors of employment, consistent with services being the most important for job creation. The labor absorption of the manufacturing sector continued to be limited in comparison. There has also been little movement of workers across regions. The right skills mix appears to be an important factor behind job matching in the Indonesian labor market. Over the past two decades labor mobility costs to move between manufacturing sectors were higher in Indonesia compared with the average of 47 countries worldwide. Workers in Indonesia also face higher welfare losses from job changes across manufacturing sectors than other countries in Asia-Pacific. Within Indonesia, the labor mobility cost to move into manufacturing is lower in than to move into other sectors (including social services and agriculture), except in trade, retail and accommodation. 6

The Government has been addressing the competitiveness of manufacturing firms by reducing import licenses, developing infrastructure and increasing the efficiency of ports. To the extent that these reforms lead to lower distribution costs in the future, Indonesia s manufacturing competitiveness is likely to improve over time, as will the demand for labor in the manufacturing sector. Manufacturing could be one of the drivers of future employment, especially through exports, and outside services employment. In 2011, exports generated US$60 billion in direct (production of exported goods) and indirect (production of inputs for exported goods) wages in Indonesia. But the number of jobs generated by exports has been on the decline since 2001, in line with the commodity boom it rose from 18 million in 1997 to 29 million in 2001, and is now back to 19 million. With the new potential for growth in manufacturing, a similar pattern of job creation from exports can be triggered nearly 3 million jobs per year. There are also new manufacturing sub-sectors with higher sources of wages that are on the rise, including chemical, rubber, and plastic products. Besides manufacturing, services sectors are likely to remain the biggest source of employment. Between 2001 and 2011, 17 million out of 20 million new jobs were created in services sectors. Services sectors also provide inputs into manufacturing production, as well as exports. High-end services such as finance and transport and logistics, are becoming more important in supporting other sectors as well as employment. For example, out of the 16 million jobs supported by exports in manufacturing, three quarters are supported through backward linkages, which are services supplied to the manufacturing sector. In order to adjust to the end of the commodity boom and allow manufacturing and high-end services sectors with competitive potential to emerge, policy makers will need to facilitate labor mobility and reduce its cost. Given that manufacturing and high-end services sectors will boost economic growth and help the economy to structurally transform into high-productivity economy, policy makers will need to ensure that worker skills match the requirements of available jobs. Movement of workers into higher productivity jobs within a sector, in particular agriculture where youth are exiting the sector due to low wages relative to wages in other sectors of the economy, should also be facilitated. To accelerate the transition of labor, skills training and upgrading should be a priority. Assessing the labor regulatory framework to identify measures that reduce the costs of transitioning between sectors and between geographic areas will also be needed. 7

1980 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008 2012 % of GDP % of total employment 1. Introduction: Indonesia s economic transformation The jobs objective: shifting towards quality and productive jobs The current downturn in commodity prices provides an opportunity for Indonesia to shift away from its dependence on commodity-driven growth towards higher value-added activities in manufacturing and services. However, Indonesia faces both global and structural challenges in making this transition. Global challenges include competition from regional trade agreements, especially the TPP, but also from structurally lower global trade growth. In addition, Indonesia s manufacturing sectors have also been losing competitiveness to regional competitors, while most job creation in the 2000s took place in low productivity sectors. This report aims to show the patterns of economic transformation in Indonesia in the past decade and a half, especially in terms of jobs and employment. The report highlights barriers to labor movement and macroeconomic sources of demand for labor. The report seeks to contribute to the design of a jobs strategy that emphasizes the transition of workers from low to high productivity sectors. While Indonesia has, so far, relied on job creation in low-productivity, and even vulnerable, employment, future challenges would require the country to shift to higher productivity and quality jobs. Indonesia s commodity boom Indonesia underwent a structural transformation from agriculture to industry prior to the Asian crisis in late 1990s. The contribution to GDP of agriculture fell sharply in the 1970s, while industry s share, including manufacturing, rose sharply and continued into the 1980s and 1990s. However, in terms of employment, industrial share of workers peaked at around 20 percent since the mid-1990s. And, while services increasingly employ a larger share of workers, it wasn t until 2008 that services sectors overtook agriculture (Figure 1 and Figure 2). Figure 1 Sectoral contribution to GDP (%) 60 50 40 30 20 10 Figure 2 Sectoral contribution to employment (%) 60 50 40 30 20 0 10 Agriculture Manufacturing Source: World Development Indicators Industry Services 0 Agriculture Industry Services Source: World Development Indicators However, since recovering from the Asian economic crisis in the late 1990s, Indonesia reversed its pattern of industrialization, and increasingly relied on agricultural and mining commodities. By 2010, the share of agricultural commodities in total exports has increased to 20 percent, from 10 percent in 2000. The share of mining and mineral commodities has also increased from 8 percent in 2000 to 22 8

% of total export percent in 2010. 1 In fact the total share of raw commodities exports overtook manufactured products in 2008 (Figure 3). Indonesia s share of ASEAN manufactured exports has also fallen from 25 percent in 1980s to 10 percent by 2015. 2 Figure 3 Shares of total exports, 1989-2013 60 50 40 30 20 10 0 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 Raw commodities Processed commodities Manufacturing Source: World Development Indicators Created a twenty-first century Dutch disease One of the most prominent effects of commodity booms is the appreciation of the Real Exchange Rate (RER), which decreases the relative competitiveness of the non-booming tradable sector. The experience of Indonesia during the first decade of 2000s is no exception, with the Indonesian Rupiah RER (vis-à-vis the US) appreciating over 80 percent between 2002 and 2011(Figure 4) 3. This pattern has also been in line with other commodity exporting countries as Brazil and South Africa. 4 This RER appreciation played a major role in the relative decline of Indonesian non-commodity exports, manufacturing in particular, during that period. The RER appreciation has only been partly reversed during the dramatic decline in commodity prices over the past 4-5 years, and it has been more sticky downwards than other commodity exporting countries. This has contributed to the sluggish performance of the non-commodity exports, which have yet not bounced back to the pre-boom period. 1 World Bank, 2012. 2 Data source: WDI. 3 Calì and Nedeljkovic, 2016. 4 Calì and Nedeljkovic (2016) compares Indonesia s RER to Brazil, South Africa, China, India, Malaysia, Philippines, Thailand, and Vietnam. 9

Figure 4 Indonesia CPI RER vis-à-vis USD, Jan 2002-Dec 2015 240 220 200 180 160 140 142 120 100 80 60 jan.02 jan.09 dec.15 Source: World Bank staff s calculations based on IMF and IFS data With adverse impact on jobs Most of the jobs created during the commodity boom were in informal and casual work. Informality is defined as own-account work (self-employed with workers), self-employed with unpaid family workers or temporary workers; casual worker in agriculture or non-agriculture; and unpaid family work. Formality is defined as self-employed with permanent worker, government workers, or private workers. Out of the 20 million jobs created between 2001 and 2011, 82 percent of these were in non-tradable services. Most of the jobs created were in social and personal services, trade and retail, and construction. Manufacturing created 4 million jobs, while agriculture shed 860,000 jobs during the same period. This trend was also happening with new labor market entrants the share of new workers who found employment in manufacturing declined from 25 percent in 1997 to 17 percent in 2007. Wholesale/retail trade and personal services share of young workers increased from 20 to 26 percent in the same period. 5 This wrong type of specialization has contributed to low growth of labor productivity and stagnant real wages. Between 1990 and 2009, Indonesian manufacturing experienced a 20 percent cumulative increase in average TFP index. 6 However, labor productivity of manufacturing grew by 2.9 percent between 2001 and 2012; while labor productivities of transportation, trade, and agriculture grew by 21.5 percent, 4.8 percent, and 4.5 percent, respectively. During this time, real wages of both formal and informal workers were stagnant or declining for most sectors. 7 Indonesia s real wages are also among the lowest in the region. 8 This specialization has also been associated with declining returns to schooling over time, which helps to perpetuate the lack of incentives for younger cohorts to acquire skills. Coxhead (2014) found that, in 2007, the returns to schooling for younger workers (15-28 years old) in the formal sector were between 4 and 7 percent for each additional year of schooling, and between 1.5 and 3.9 percent in the informal 5 World Bank, 2014. 6 When further disaggregated, sectors such as machinery and instrument and textiles, clothing and footwear experienced higher TFP growth, while resource-based sectors experienced flat TFP growth (Fitriani et al., 2012). 7 Tadjoeddin (2016) presented real wages for self-employed, casual workers in agriculture and non-agriculture, and regular employees, based on Sakernas classifications. 8 Diop (2016) compares Indonesian real wages to China, Malaysia, the Philippines, Thailand, and Vietnam. 10

sector. These were lower than returns to schooling for older workers and lower than average returns in 1997 for all workers, which were between 7 and 9.3 percent. These declining returns to schooling over time helped to perpetuate the lack of incentives to acquire skills for younger cohorts. 9 Is there an opportunity for another structural transformation? Recent drops in commodity prices and nominal Rupiah depreciation seem to suggest that Indonesia has another shot at a structural transformation toward manufacturing or other higher productivity activities. But, as mentioned earlier, RER depreciation over the past four to five years has been stickier downwards compared to other commodity exporters and relative to the size of the nominal depreciation of the Rupiah. Calì and Nedeljkovic (2016) investigate the reasons behind this stickiness in the Indonesian RER by performing a novel decomposition of the bilateral RER across two dimensions. These analyses show that Indonesia s RER stickiness in 2014-2015 is mainly due to local retail prices rising faster than border prices, relative to the US and Asian peers (Figure 5). This could be due to increases in tariffs and non-tariff barriers as well as in distribution costs, which in turn is consistent with increased protectionism vis-à-vis foreign investments, and with the rise in domestic fuel prices associated with the reductions in fuel subsidy. Another decomposition shows that the food prices component of the RER is also the one putting most upward pressure to the RER (Figure 6). Among comparator countries, Indonesia had the second highest average annual relative food price inflation over 2003-2015 and this food price inflation has determined a slower pace of RER depreciation over the entire period, including the most recent one. This confirms the role of protectionist food trade policy in undermining the price competitiveness of Indonesian exports. On the other hand their analysis suggests that changes in the relative unit labor cost have not played any significant role in the slow rate of the recent Indonesian RER depreciation. 10 Figure 5 RER decomposition - Annual contributions to Indonesian RER CPI change (vs. USD): tradable prices based on export and import indices, 2002-2015 0.20 0.15 0.10 0.05 0.00-0.05-0.10-0.15 RER USA_INDONESIA 2003 2005 2007 2009 2011 2013 2015 rer_n rer_t rer_d rer _cpi Legend: rer_n: non-tradeables; rer_t: tradeables; rer_d: distribution wedge; rer_cpi: CPI RER 9 Declining returns to schooling could also be caused by low labor force growth. Between 1997 and 2007, Indonesia faced declining employment growth. Even during a job recovery period in 2003-2007, the employment ratio fell by 0.1 percent per year. At the same time, higher shares of workers are educated. In 2007, 21 percent of workers graduated from high school, compared to only 11.5 percent in 1990 (World Bank, 2010). 10 Indonesia s unit labor cost in 2014 was higher than Malaysia, the Philippines, and Vietnam (Diop, 2016). However, the quarterly trend in Calì and Nedeljkovic (2016) is decreasing since 2012. 11

Source: World Bank staff s calculations, based on IMF and IFS data Figure 6 RER decomposition Annual contributions to Indonesian RER change (vs. USD): food vs. non food prices, 2002-2015 0.20 0.15 0.10 0.05 0.00-0.05-0.10-0.15-0.20 2002 2004 2006 2008 2010 2012 2014 ner cpi_food cpi_nonfood rer Legend: ner: nominal exchange rate; cpi_food: food CPI; cpi_nonfood: non-food CPI; RER: real exchange rate Source: World Bank staff s calculations, based on IMF and IFS data This lack of further depreciation also hinders manufacturing firms to regain competitiveness and, therefore, their employment potential. However, since the middle of 2015 the Government has been addressing some of the sources of the distribution wedge, by reducing some import licenses and by pushing on infrastructure development and port efficiencies. Should further reforms continue, their impact in lowering distribution costs are likely to improve the competitiveness of the manufacturing sector and, eventually, its demand for labor. On the labor supply side, the ability of workers to transition across sectors is important to make this process of structural transformation unfold. Workers need to be able to relocate across sectors of the economy in response to these changing opportunities. Indonesia is a country that is geographically divided across remote islands with high transportation costs, as well as spatially divided in terms of sectoral locations. This makes labor mobility all the more difficult for workers to move from agriculture to manufacturing, for example. Thus there are reasons to believe that the labor supply side may present a significant challenge for Indonesia, and should also be the focus of policy. The rest of the paper looks at the labor transition trends in the past two decades. It then looks at a number of possible explanations across both the supply and demand side of labor. The analyses draw on a number of background work, including labor mobility cost, employment elasticity, and labor content of export. 12

2. Labor transition trends: results from the IFLS How does labor reallocate across sectors of the economy in Indonesia in response to changing incentives? Using the World Bank s Trade and Labor Adjustment Costs toolkit, the implicit costs that workers face when moving across sectors and regions of the Indonesian economy are measured, by type of worker, and over time. High labor mobility costs can slow down the process of structural transformation. This section is based on the Indonesia Family Life Survey (IFLS), with comparisons between 1997-2000 and 2000-2007 (waves 2, 3, and 4). 11 Services sectors continued to absorb large shares of workers Between 1997 and 2007, the share of workers in low-productivity services increased in Indonesia since the start of the commodity boom. Figure 7 presents recent employment trends in Indonesia across sectors (top) as well as geographic areas (bottom). The most notable shift in employment trends is the increase in the share of workers in social services, as well as trade and accommodation services. On the other hand, the share of workers in manufacturing declined. Despite these changes in sectoral labor shares, there has been relatively little change in labor shares across islands in Indonesia. Sumatra has seen a slight increase in the share of employed persons aged 15+ between 1997 and 2007 and Java slight decreases, but other provincial shares have changed by less than 1 percent. There is also a large variation in employment within sectors across regions. Figure 7 Labor shares (%), aged 15 and above, across sectors and regions, 1997-2007 100 90 Social services 80 70 60 50 40 30 20 10 0 1997 2000 2007 Finance, other business Transport, communications Trade, accommodation Construction Utility supply Manufacturing Mining, quarrying Agriculture, forestry, fishing 11 Wave 1 (1993) is not included due to different parameters, making it incomparable to the subsequent waves. Wave 5 (2014) is not yet included since the results of this wave still need to be verified. 13

100 90 80 70 60 50 40 30 20 Sulawesi Kalimantan Lesser Sunda Islands East Java Central Java West Java Jakarta Sumatra 10 0 1997 2000 2007 Source: World Bank staff s calculations using data from Waves 3 and 4 of the IFLS. Between 2000 and 2007, as well as between 1997 and 2000, there was high incidence of workers changing sectors of employment in Indonesia. Transition matrices provide the basis for estimating labor mobility costs, and we estimate worker transitions between sectors using panel data from Waves 2 and 3 as well as Waves 3 and 4 from the Indonesia Family Life Survey (IFLS) on gross labor flows between sectors and different states of work (including unemployed and out of the labor market). We distinguish the effects for different worker-types, disaggregating by skill level, age and gender, and we include the entire labor force including self-employed and own account workers. These transitions are reported in Table 1 and Table 2. Each cell reports the share of workers transitioning from each origin sector (row) to all other destination sectors (column) between 2000 and 2007. The cells on the diagonal indicate the shares of workers remaining in their current work/sector status. The transition statistics give a sense of the fluidity of the Indonesian labor market. Mining and quarrying, manufacturing, utility supply, construction, trade and accommodation services, transport and communication services, and social services all witnessed high worker turnover rates, which in part may be driven by the long time horizon between waves of the IFLS. Services sectors have been the largest absorbers of transitioning workers, consistent with services being the most important for job creation. 12 For example, between 1997 and 2000 as well as between 2000 and 2007, 38 percent of transitioning workers found employment in trade and accommodation and social services, while less than 1 percent found employment in finance and other business services. 13 Jobless workers in 2000 were also more likely to have found jobs in trade and accommodation services in 2007, followed by social services and agriculture (Table 1 and Table 2). The trade and accommodation sector absorbed most unemployed or inactive workers (16 percent of those exiting unemployment or of new labor force entrants flowed into trade and accommodation services). 12 See also World Bank, 2014. 13 These statistics are calculated by excluding the stayers on the diagonal, and summing across all rows within the column, to measure which sectors workers are entering. They cannot be re-constructed directly from the tables shown. 14

The labor absorption of the manufacturing sector continued to be subdued. The manufacturing sector absorbed 12 percent of workers between 1997 and 2000 as well as 2000 and 2007. The decline in agriculture, forestry and fishing continued: it absorbed 26 percent of transitioning workers between 1997 and 2000 and 17 percent between 2000 and 2007. It should also be noted that there was increased turnover between 1997-2000 and 2000-2007: for the most part, the share of stayers those workers who moved jobs within the same sectors declined for most sectors, except finance. Table 1 Transitions across sectors and into and out of labor force status (%), 2000-2007 2000-2007 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S1 Agriculture, forestry, fishing 65.6 0.3 4.7 0.1 2.2 6.9 0.9 0.2 4.8 14.4 S2 Mining, quarrying 35.1 16.9 3.9 0.0 3.9 6.5 3.9 0.0 18.2 11.7 S3 Manufacturing 11.7 0.4 35.4 0.2 2.6 15.9 2.1 0.4 12.9 18.5 S4 Utility supply 7.5 0.0 7.5 27.5 7.5 5.0 0.0 0.0 40.0 5.0 S5 Construction 16.6 0.2 9.2 0.2 35.2 12.6 4.0 0.0 11.6 10.6 S6 Trade, accommodation 9.4 0.1 6.6 0.1 1.9 51.2 1.4 0.5 8.7 20.1 S7 Transport, communications 13.2 1.8 6.7 0.0 3.5 12.6 32.5 1.0 23.2 5.5 S8 Finance, other business 4.1 0.0 1.4 1.4 1.4 19.2 0.0 34.2 28.8 9.6 S9 Social services 9.2 0.5 7.7 0.2 2.9 13.1 2.8 0.8 49.1 13.7 S10 Jobless 12.3 0.2 7.1 0.2 1.8 15.9 1.1 0.6 12.6 48.1 Source: World Bank staff s calculations using data from Waves 3 and 4 of the IFLS. Note: Each cell reports the share of workers transitioning from each origin sector (row) to all other destination sectors (column) between 2000 and 2007. The cells on the diagonal indicate the shares of workers remaining in their current work/sector status. Table 2 Transitions across sectors and into and out of labor force status (%), 1997-2000 1997-2000 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S1 Agriculture, forestry, fishing 73.3 0.3 4.0 0.1 1.0 5.1 0.9 0.0 3.7 11.7 S2 Mining, quarrying 19.7 32.4 9.9 0.0 4.2 4.2 5.6 0.0 21.1 2.8 S3 Manufacturing 14.4 0.2 45.4 0.1 2.7 11.6 1.8 0.2 10.8 12.9 S4 Utility supply 6.4 0.0 8.5 36.2 6.4 2.1 8.5 0.0 23.4 8.5 S5 Construction 18.6 0.9 6.8 0.4 43.2 5.9 4.5 0.5 13.2 5.9 S6 Trade, accommodation 9.3 0.0 5.5 0.1 1.6 60.1 1.3 0.5 9.4 12.1 S7 Transport, communications 11.0 0.7 4.3 0.0 3.4 10.3 49.7 0.2 14.6 5.7 S8 Finance, other business 2.5 0.0 3.8 0.0 1.3 6.3 0.0 33.8 41.3 11.3 S9 Social services 7.1 0.2 4.9 0.4 2.3 7.6 1.9 0.5 66.3 8.8 S10 Jobless 15.8 0.2 6.7 0.1 1.2 12.0 0.7 0.2 7.7 55.5 Source: World Bank staff s calculations using data from Waves 2 and 3 of the IFLS. Note: Each cell reports the share of workers transitioning from each origin sector (row) to all other destination sectors (column) between 1997 and 2000. The cells on the diagonal indicate the shares of workers remaining in their current work/sector status. Large country, low mobility However, there had been little movement of workers across regions. Most regions (islands or island groups, except for Jakarta, in this study) retained between 90 and 99 percent of their workers, between 2000 and 2007 (Table 3). The most likely workers to move were from Jakarta, but mostly to West Java or other parts of Java. Likewise, workers moving to Jakarta were also more likely to have come from other regions in Java. The low likelihood of geographic movement may be due to lower degrees of regional inequality in the 1990s. Tadjoeddin et al. (2001) found that inter-provincial inequality of per capita RGDP (regional GDP) in 1996, would be reduced by about 60 percent if oil and gas incomes and the 13 richest districts were excluded. In addition, welfare outcomes such as health, education, purchasing power, and human development index were less unequal than inequality of per capita RGDP. A more recent analysis 15

found that the inter-provincial coefficient of variation (CV) 14 of unemployment rates increased slightly from 0.32 in 2001 to 0.33 in 2007, before peaking at 0.41 in 2011. Table 3 Transitions across regions (%), 2000-2007 S1 S2 S3 S4 S5 S6 S7 S8 S1 Sumatra 97.91 0.6 1.3 0.1 0.1 0.0 0.0 0.0 S2 Jakarta 0.8 90.0 6.7 1.9 0.2 0.4 0.0 0.1 S3 West Java 0.5 1.3 97.3 0.5 0.3 0.0 0.1 0.0 S4 Central Java 0.6 1.2 1.2 96.3 0.6 0.0 0.1 0.1 S5 East Java 0.1 0.2 0.4 0.4 98.5 0.1 0.3 0.0 S6 Lesser Sunda Islands 0.1 0.1 0.1 0.0 0.3 99.4 0.0 0.0 S7 Kalimantan 0.0 0.0 0.0 0.1 0.8 0.0 98.9 0.1 S8 Sulawesi 0.0 0.0 0.2 0.2 0.0 0.2 1.0 98.4 Source: World Bank staff s calculations using data from Waves 3 and 4 of the IFLS. Note: Each cell reports the share of working age individuals transitioning from each origin region (row) to all other destination r egions (column) between 2000 and 2007. The cells on the diagonal indicate the shares of workers remaining in their current region. Having the right skills and initial entry into formal/informal employment matter The right skills mix appears to be an important factor behind job matching in the Indonesian labor market. Skilled workers defined as those having attended university were more likely to have found a job in 2007, while unskilled workers with only a secondary degree were more likely to have remained jobless (Table 4). The likelihood of exiting agriculture also increases as individuals skills level increases, with unskilled workers having the highest incidence of staying and skilled workers the highest incidence of exiting. Students having graduated from vocational training instead had a higher likelihood of entering manufacturing than skilled or unskilled workers, while both university and vocational graduates were able to access services jobs better than unskilled workers. Skilled workers transitioning across sectors and into services had a much higher incidence of entering social services than vocational or unskilled workers. Skilled workers also had a slightly higher incidence of entering finance than vocational, but higher than unskilled workers. There was instead a lower incidence for skilled workers to enter transport and communications and trade and accommodation. Table 4 Transitions across aggregate sectors by skill level (%), 2000-2007 Skilled Vocational Unskilled S1 S2 S3 S4 S1 S2 S3 S4 S1 S2 S3 S4 S1 Primary 20.9 4.5 61.2 13.4 42.5 7.8 38.0 11.7 67.2 4.9 15.6 12.3 S2 Manufacturing 4.1 21.6 64.9 9.5 4.3 35.9 41.4 18.4 12.5 37.1 32.1 18.3 S3 Services 3.0 5.8 85.9 5.3 4.4 10.7 70.1 14.8 12.4 6.7 65.0 15.9 S4 Jobless 3.0 5.5 61.8 29.7 4.7 9.8 45.6 40.0 13.8 7.3 28.2 50.8 Source: World Bank staff s calculations using data from Waves 3 and 4 of the IFLS. Moving across sectors as either formal or informal worker seemed more likely to be determined by an individual s previous formality status. In 2007, individuals entering primary activities from any sector or from joblessness were more likely to do so as informal workers than formal workers (Table 5). The same holds for workers entering services, but not manufacturing, where workers were more likely to enter as formal than informal. Informal manufacturing, services and primary sector workers changing sectors were also more likely to remain informal than enter formal employment. Thus informality may not act as a stepping stone sector into formal employment. 14 CV is defined as the ratio of the standard deviation to the mean (Tadjoeddin, 2015). 16

Table 5 Transitions across aggregate sectors by formality (%), 2000-2007 S1 S2 S3 S4 S5 S6 S7 S1 Primary, formal 44.5 16.5 5.9 1.1 13.7 8.1 10.2 S2 Primary, informal 1.8 77.2 0.9 1.3 2.8 7.4 8.7 S3 Manufacturing, formal 2.4 4.2 48.7 2.9 13.5 11.5 16.7 S4 Manufacturing, informal 0.7 8.7 6.2 52.3 5.1 17.4 9.6 S5 Services, formal 1.3 4.1 4.4 1.1 65.0 11.7 12.5 S6 Services, informal 0.6 6.5 1.6 2.2 7.7 71.7 9.7 S7 Jobless 2.7 14.2 9.7 3.5 26.8 24.4 18.6 Source: World Bank staff s calculations using data from Waves 3 and 4 of the IFLS. Advantage: young and male Females were more likely to remain jobless than males, while males were more likely to stay employed within their aggregate sector (primary, manufacturing and services). This reflects a higher incidence of females exiting employment from either of the primary, manufacturing or services sectors. Both males and females were most likely to find jobs in services if entering employment. Young people exiting unemployment or idleness were also more likely to find jobs in the services sector (as opposed to the primary or manufacturing sectors) than their middle-aged or older-aged counterparts. Rural workers in manufacturing or services moving to urban areas were most likely to find jobs in the services sector. The exception is individuals who were jobless in rural areas. If transitioning to urban areas, these individual were more likely to remain unemployed than find a job in the services sector. 17

3. Drivers of labor transition: results from labor mobility cost and employment elasticity analyses In moving across sectors, geographic areas, even across sectoral-formality work arrangements, workers might face costs that hinder their mobility. Labor mobility refers to the ability of workers to move between firms and industries in search of alternative employment opportunities, such as in response to wage differences. Labor mobility costs reflect what a worker perceives to be his or her welfare cost of finding alternative employment. They are defined as the costs perceived by a worker to move to a different firm or industry, independent of the reason for the move. Typical impediments to job switching are skills mismatches (wages forgone because of lower productivity), limitations to geographic mobility (administrative procedures for internal migration and direct relocation costs), and severance and hiring costs (including those imposed by laws or regulations). Other factors may be location preferences, job search costs, and even the psychological costs of changing jobs. This section discusses impediments to labor mobility, drawing on results from labor mobility costs, based on IFLS data, and employment elasticity analyses, based on the Indonesian labor force survey (Sakernas) data. 15 Box 1 Defining labor mobility costs It is not possible to measure labor mobility costs directly, because they are not readily observable. Instead, we use an indirect method that combines the observed worker transitions between sectors with the inter-sectoral wage gaps to estimate the labor mobility cost to explain why workers do not transition into higher wage sectors to the extent that wage gaps are eliminated. There may be multiple reasons why wage gaps persist, e.g., on the labor supply side (when it is physically or technically difficult due to skills mismatch to obtain a job in a certain sector), or on the labor demand side (such as a lack of new private sector job openings). Both are obstacles to matching labor supply with labor demand at a market clearing wage, and both therefore imply a high cost of transitioning to said job. The methodology of this model differs from standard models of trade, which assume no frictions in the adjustment of labor. For example, workers are assumed to move without frictions from importcompeting sectors to export-expanding sectors, after an economy opens to trade. But in reality, workers respond slowly to trade-related shocks. When there are low transition rates across sectors of the economy despite high wage gaps, we interpret this to mean that it is costly for workers to move. We estimate the welfare costs for a worker to switch industries/jobs using a dynamic rational-expectations model of costly labor adjustment. 16 In each period, a worker can choose to move from her current industry to another one, but must pay a cost in doing so. The decision for a worker to move depends on her expected welfare gain, net of the welfare cost of moving. So for a sector that is difficult to access, we would assign a high labor mobility cost for entering that type of job. Combining the transition data with the observed wage gaps between sectors leads to estimates of labor mobility costs for entering each sector, expressed as a ratio of the annual average wage. These transition costs are estimated for all workers, as well as for skilled and unskilled workers, and for men and women. 17 The methodology used here is sensitive to the level of 15 Please see Annex I for a more detailed note on the methodology of labor mobility costs. 16 See the Trade Shocks and Labor Market Adjustments toolkit developed by the World Bank (Hollweg et al. 2014). The Annex provides details of the methodology and data. 17 The cost has a common component, which does not vary across similar type workers in an industry, and an idiosyncratic component. By solving the dynamic rational-expectations model of costly labor adjustment, it is possible to derive an 18

disaggregation: the higher degree of sectoral disaggregation, the fewer the observed transitions, the higher the estimated mobility costs. It is therefore crucial to exercise caution when interpreting the results. This type of exercise is most useful for comparing the relative mobility costs across different sectors of an economy particularly those most closely affected by trade shocks and different types of workers. How could labor mobility costs influence Indonesia s economic adjustment in response to falling international commodity prices, and ultimately the country s structural adjustment in the future? Changes in prices in global markets can affect the relative prices faced by domestic firms that consume or produce traded goods, which in turn affects the demand for labor as sectors expand or contract. Indonesia, as a large commodity exporter, is even more vulnerable to global price changes of few commodities that make up the majority of its exports. These types of trade-related shocks affect the relative return to labor across industries as well. The resulting wage implications will also induce supplyside labor reallocations across sectors. Large mobility costs mean sluggish reallocation of labor, reducing the potential benefits to workers and the economy as a whole. They may be high enough to dissuade labor supply to certain sectors, but these sectors may be the most productive and with the highest wages. This has implications for how Indonesia s economy will adjust to large external shocks, including the large decline in commodity prices that Indonesia is facing today. Labor mobility costs in Indonesia are relatively high Labor mobility costs in Indonesia are high even among other countries at a similar level of economic development. Artuc et al. (2013) measure the average labor mobility cost for workers to transition across 8 broad manufacturing sectors for 47 countries worldwide over the period 1995-2007. 18 Labor mobility costs in Indonesia s manufacturing sector are among the highest in the sample. Richer countries tend to have lower mobility costs in manufacturing, and the cross-country correlation with GDP per capita is negative and robust (Figure 8). Yet costs in Indonesia continue to be high relative to other countries, even after accounting for Indonesia s GDP per capita level. Workers in Indonesia also face higher welfare losses to change jobs across manufacturing sectors than other countries in the Asia-Pacific. While Chile also departs from expected levels given the country s GDP per capita, other countries such as Japan, the United States and Singapore have among the lowest labor mobility costs in the sample, significantly below other developed countries. For countries with high labor mobility costs, changes in market access would induce greater trade opportunities in some sectors while at the same time imposing import-competing pressures on other sectors of the economy. Countries with lower labor mobility costs domestically would be better positioned to realize these opportunities in the short term. equilibrium condition that is a kind of Euler-equation, which lends itself to estimation. The structural model identifies workers transitions across sectors of an economy that depend on the wage gaps between those sectors and the mobility costs of entering a sector. From observed data on sectoral transitions and sectoral wage gaps, we are able to estimate the labor mobility cost using GMM-type estimations. 18 Artuc et al. (2013) use employment and wage data across 8 aggregated manufacturing sectors for the period 1995-2007 from UNIDO Industrial Statistics Database. Although transitions across manufacturing sectors exclude transitions between services sectors, for example, Artuc et al. (2013) is the only source of internationally comparable labor mobility cost estimates across a wide range of countries. This international comparison still provides useful insights for Indonesia, despite it being a specific case for manufacturing. 19

Labor mobility cost Figure 8 Labor mobility costs vs. GDP per capita in Indonesia and other TPP countries 9.00 8.00 7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00 IDN PER CHL CAN JPN SGPUSA 4 5 6 7 8 9 10 11 12 log GDP per capita (constant 2005 US$) Source: Adapted from Hollweg et al., (2014) calculated using data from Artuc et al. (2013) and World Bank World Development Indicators. Note: This figure plots the correlation between the estimated aggregate labor mobility cost for each country s manufacturing sector expressed as a ratio of the annual average manufacturing wage (vertical axis) and economic development (horizontal axis). Level of economic development is measured as the average log of GDP per capita (constant 2005 US$) for 1995-2007. Labor mobility costs are correlated with aggregate indicators related to a country s well-being, labor market characteristics, educational attainment, and regulatory distortions. Based on cross-country labor mobility cost estimates of Artuç et al. (2013), richer countries tend to have lower mobility costs, but not because the adjustment costs of firms are lower. While there is a weak correlation between mobility costs and firing costs, the correlation with GDP per capita is quite negative and robust. These results are consistent with the assertion that distortions affecting firm labor adjustments (captured by firing costs) are not the main driver of mobility costs. There are also positive correlations with the poverty head-count and the poverty gap, but no obvious correlations with inequality. Mobility costs also tend to be lower in countries more highly specialized in non-primary sectors or with highly educated work forces. Countries with lower educational quality (a higher pupil-teacher ratio) tend to have higher mobility costs. Labor market rigidities are more prevalent in countries characterized by other types of rigidities and distortions. Labor mobility costs are positively correlated with other frictions and constraints, such as time to export. Countries where labor mobility costs are high tend to obstruct trade more than countries with more nimble labor markets. Case studies that examine labor mobility costs across aggregate sectors within countries find that firm size, informality, sector-specific knowledge, and education level also affect labor mobility costs. In Brazil, Mexico and Morocco, it is relatively less costly to move into an informal than a formal job, but also less costly to move into a formal job from an informal job in the same industry, which acts as a stepping stone for formality. Industry-specific skill requirements help explain the finding that it is always less costly to become formal in the same industry than to become formal by switching industries. Evidence from Morocco shows that finding employment in large firms is less costly than in small firms. In Lao PDR, skilled workers face lower costs to transition across sectors compared to unskilled workers, although the results vary by sector. This also suggests that employers may prefer workers with sectorspecific knowledge. Understanding what is driving Indonesia s relatively high labor mobility cost can help identify policy responses to address these costs. Could Indonesia s relatively high costs to labor mobility internationally be the result of policy-relevant factors, such as skills mismatches, sectoral characteristics, or geographic dispersion? We measure labor mobility costs to enter different sectors and regions within 20