metadata: authors: 0: author: Hapsari,Indira Maulani
1: author: Shu Yu
2: author: Pape,Utz Johann
3: author: Mansour,Wael
count: Indonesia
docna: 0: docna: Informality in Indonesia: Levels, Trends,
            and Features
docty: Policy Research Working Paper
theme: Inclusive Growth,Job Creation,Economic Policy,Economic Growth and Planning,Private Sector Development,Jobs,Macroeconomic & Structural Policy Modelling
abstracts: cdata!: Informality is a multidimensional
            development challenge with features that potentially differ
            across workers, firms, and countries. This paper first
            briefly summarizes the literature, discusses the multiple
            existing definitions of informality, and adapts the
            cross-country analytical framework on informality to the
            context of Indonesia. It then uses several novel datasets
            and a range of modeling approaches to capture the levels and
            trends of both output and employment informality in
            Indonesia. It further contributes to the existing literature
            by estimating informality in Indonesia at the regional,
            provincial, and sectoral levels. Those estimates were then
            benchmarked to the levels, trends, and features of the
            informal sector in emerging markets and developing economies
            to examine whether the major features of the informal sector
            in Indonesia deviate from those observed in other emerging
            markets and developing economies. The paper finds that
            despite the declining trend, both output and employment
            informality remain elevated and broadly above the comparator
            countries in the region. Informality in Indonesia is mostly
            concentrated in agriculture and low-skilled services and is
            associated with higher poverty at the provincial level.
            There also appear to be productivity, education, and salary
            gaps between formal and informal workers. Moreover, markets
            are not segregated as informal firms compete strongly with
            formal ones. Finally, informality seems to pose
            macroeconomic challenges as tax efforts and financial sector
            depth remain below the averages for emerging markets and
            developing economies.
display_title: Informality in Indonesia: Levels,
            Trends, and Features
listing_relative_url: /research/2023/10/34176024/informality-indonesia-levels-trends-features
topicv3: Poverty m1326687 695,Growth and Lagging Regions m1326921 462,Growth, Poverty and Inequality m1327633 1091,Informal Sector Productivity m1504064 2882,Economic Growth Analytics m1583361 467
publishtoextweb_dt: 2023-10-06T00:00:00Z
dois: 10.1596/1813-9450-10586
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
author_keys: 0: author_key: 999576
1: author_key: NA
2: author_key: 1154467
3: author_key: 878924
model_extractions: Policy Research Working Paper 10586

# Informality in Indonesia

Levels, Trends, and Features _Indira Maulani Hapsari Shu Yu Utz Johann Pape Wael Mansour_ Macroeconomics, Trade and Investment Global Practice October 2023
Policy Research Working Paper 10586

# **Abstract**

Informality is a multidimensional development challenge with features that potentially differ across workers, firms, and countries. This paper first briefly summarizes the literature, discusses the multiple existing definitions of informality, and adapts the cross-country analytical framework on informality to the context of Indonesia. It then uses several novel datasets and a range of modeling approaches to capture the levels and trends of both output and employment informality in Indonesia. It further contributes to the existing literature by estimating informality in Indonesia at the regional, provincial, and sectoral levels. Those estimates were then benchmarked to the levels, trends, and features of the informal sector in emerging markets and developing economies to examine whether the major features of the informal sector in Indonesia deviate from those observed in other emerging markets and developing economies. The paper finds that despite the declining trend, both output and employment informality remain elevated and broadly above the comparator countries in the region. Informality in Indonesia is mostly concentrated in agriculture and low-skilled services and is associated with higher poverty at the provincial level. There also appear to be productivity, education, and salary gaps between formal and informal workers. Moreover, markets are not segregated as informal firms compete strongly with formal ones. Finally, informality seems to pose macroeconomic challenges as tax efforts and financial sector depth remain below the averages for emerging markets and developing economies.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at ihapsari@worldbank.org; syu2@worldbank.org; upape@worldbank.org; wmansour@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Informality in Indonesia: Levels, Trends, and Features**

_Authors: Indira Maulani Hapsari, Shu Yu, Utz Johann Pape, Wael Mansour_ _All World Bank Staff_

## **JEL classification:**

E2 Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy; O1 Economic Development; O4 Economic Growth and Aggregate; J2 Demand and Supply of Labor Productivity; R1 General Regional Economics

**Keywords:** Informality, Indonesia, Growth, Employment, Macroeconomics.
|**Contents**|
|---|
|1.<br>Introduction ........................................................................................................................................... 3|
|2.<br>Adapting the multidimensional approach of informality analysis to Indonesia .................................... 4|
|2.1<br>Definitions of informality: Global vs Indonesia ........................................................................... 4|
|2.2<br>Informality data and estimation methods description: Cross-country and Indonesia-specific<br>databases ................................................................................................................................................... 6|
|3.<br>Levels and trends of informality: EMDEs vs Indonesia ....................................................................... 8|
|3.1<br>Informality in EMDEs .................................................................................................................. 8|
|3.2<br>Informality in Indonesia ................................................................................................................ 9|
|3.3<br>Informality at the regional level in Indonesia ............................................................................. 10|
|4.<br>Policy and development challenges associated with informality: EMDEs vs Indonesia .................... 12|
|4.1<br>Development challenges associated with informality ................................................................. 12|
|4.1.1<br>Underdevelopment, poverty and productivity gaps ............................................................ 12|
|4.1.2<br>Poor governance, unfriendly business climates, and heavy-handed regulations leading to<br>high-cost investment. .......................................................................................................................... 18|
|4.2<br>Policy challenges associated with pervasive informality ............................................................ 19|
|4.3<br>The COVID-19 shock and the informal sector in Indonesia ....................................................... 22|
|5.<br>Conclusion .......................................................................................................................................... 25|
|Reference .................................................................................................................................................... 27|
|Annex 1: Examples of common definitions of informality in the literature ............................................... 31|
|Annex 2: Definitions of informality from SAKERNAS ............................................................................. 33|
|Annex 3: Description of informality dimensions ........................................................................................ 34|
|Annex 4: MIMIC Model Estimation Results (1993-2021) ......................................................................... 36|
|Annex 5: The impact transmission channels of the COVID-19 shock on the informal sector ................... 37|

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# **1. Introduction**

1. **Informality is a broad development challenge with multiple features and different layers of analysis.** Informality is associated with many development challenges, such as lower productivity firms, less protected workers, and tax leakages (Loayza 2018; Ohnsorge and Yu 2021; Ulyssea 2020). At the same time, the informal sector provides livelihoods, creativity, and buffers against shocks. The latter was exemplified by the recent shock induced by the COVID-19 pandemic. Despite the significance of informality in emerging markets and developing economies (EMDEs), it remains difficult to measure and study, mainly due to the presence of multiple definitions for informality and the lack of estimates (Elgin et al. 2021a). This is particularly the case in Indonesia where a limited number of  studies have focused on the informal sector.<sup>1</sup>

2. **Against this backdrop, this paper uses several novel datasets and various modeling approaches to measure the extent and nature of informality in Indonesia.** It first briefly summarizes the literature, discusses the multiple existing definitions of informality, and adapts the cross-country analytical framework on informality to the context of Indonesia. It then uses several novel datasets, including an updated cross-country database on informality provided by Elgin et al. (2021a), and a range of modeling approaches to capture the levels and trends of both output and employment informality. It further contributes to the existing literature by estimating output and employment informality in Indonesia at the regional, provincial, and sectoral levels, using a series of labor force surveys (SAKERNAS surveys) provided by Badan Pusat Statistik (BPS). Those estimates were then benchmarked to the levels, trends, and features in EMDEs to examine whether the major features of the informal sector in Indonesia deviate from those in EMDEs.

3. **Despite the recent development, informality remains pervasive in Indonesia.** While being slightly lower than the average of other EMDEs, output informality in Indonesia averaged around 35 percent of GDP in the decade before 2020, slightly above the average level in East Asia and the Pacific region (EAP). Informal employment in Indonesia, amounting to more than half of total employment, is higher than the average levels in other EMDEs and the EAP region. Like in other EMDEs, Indonesia witnessed a general declining trend in both output and employment informality during the past few decades. Nevertheless, both informality indicators remain elevated and broadly above comparator countries, creating both development and policy challenges.

4. **The informal sector in Indonesia exhibits several features, some of which are commonly documented in the literature and seen in the informal sectors in other EMDEs.** First, informality in Indonesia is mostly concentrated in the agriculture and low-skilled service sectors, similar to what has been observed in other EMDEs. Second, it is associated with a higher level of poverty at the provincial level, in line with the existing literature. Combinig evidence at the macro and micro levels, there appear to be productivity, education, and salary gaps between formal and informal workers. Moreover, markets are not segregated as informal firms compete

> 1 Some of the existing literarture on Indonesia includes ADB (2010), Baddiet, Brown and Mazaheri (2015), OECD (2010), and Comola and de Mello (2011).

3
strongly with formal ones. Finally, informality seems to pose macroeconomic challenges as tax efforts and financial sector depth in Indonesia remain below the EMDE averages.

5. **The paper makes several contributions to the existing literature.** It is the first study on informality in Indonesia that uses a multidimensional approach adapted to the country’s specific conditions. Following Elgin et al. (2021a), the paper looks at output, employment, and firm informality, and utilizes all existing data series that can be used to capture the extent of informality in Indonesia. Second, it is the first to estimate informality for Indonesia at the regional, provincial, and sectoral levels. No existing study has attempted to understand the informal sector in Indonesia at the sub-national level. Third, it is also the first paper that utilizes the various labor force surveys (SAKERNAS surveys) to estimate both output and employment informality. Lastly, it provides a systematic examination of the features of the informal sector in Indonesia, highlighting what is also commonly seen in other EMDEs (or documented in the literature) and what is not.

6. **The paper has limitations as many questions about the informal sector in Indonesia remain unanswered** . Limited studies have looked at the informal sector systematically in Indonesia. The existing ones tend to focus on one or two dimensions of informality. While this paper helps deepen the understanding of the informal sector in Indonesia via a multidimensional approach, it does not provide additional information on the drivers of informality, nor does it try to establish any causality relationships, nor provide policy recommendations.

7. **The paper is divided into five sections** . Section 2 highlights the literature behind the multiple informality analytical frameworks and discusses definitions and data used in this study. Section 3 depicts the levels and trends of informality in EMDEs (as well as the EAP region) and Indonesia. Section 4 summarizes the correlates of informality documented in the literature and other EMDEs and examines whether those correlates of informality also exist in Indonesia. In particular, it highlights the policy challenges associated with informality and examines the role of informality in Indonesia during an external shock like COVID-19. Section 5 concludes.

**2. Adapting the multidimensional approach of informality analysis to Indonesia**

- **2.1 Definitions of informality: Global versus Indonesia**

8. **The nature of informality differs across workers, firms, and countries.** Some workers and firms are “excluded” from the modern economy due to burdensome entry regulations and lack of human capital (de Soto 1989; Loayza, Oviedo, and Servén 2006). This type of informality is frequently associated with underdevelopment, low productivity, and poorly paid employment (La Porta and Shleifer 2014; Loayza 2018).<sup>2</sup> Other informal workers and firms voluntarily “exit” the formal sector and choose the informal sector for its flexibility, independence, and lower compliance burdens (Blanchflower, Oswald, and Stutzer 2001; Maloney 2004; Günther and Launov 2012; Falco and Haywood 2016). Both “excluded” and “exiting” types of informality could coexist in an economy (Bosh and Maloney 2008, 2010; Lehmann and Pignatti 2007;

> 2 This typically occurs in lower-income countries where the informal sector is a major source of income for low‐ skilled workers whose income would otherwise fall below subsistence (Docquier, Müller, and Naval 2017).

4
Nordman, Rakotomanana, and Roubaud 2016). As a result, the informal sector consists of both high-productive and low-productive workers and firms. While the latter stay in the informal sector out of necessity, the former join the informal sector to avoid various costs associated with “being formal”. As a result, the definition of informal workers as well as informal firms is largely context and country-specific (see Annex 1 for more details).

9. **Multiple definitions of informal workers exist for cross-country comparison.** According to the International Labour Organization (ILO), informal employment covers all workers of the informal sector and informal workers outside the informal sector (Perry et al. 2007; ILO 2018). The former comprises all persons who were employed in at least one informal firm. The latter group includes self-employed and workers not employed in formal contractual arrangements or not subject to social protection or employment benefits. In practice, the most frequently used informal employment measure is the share of self-employment in total employment (La Porta and Shleifer 2014; ILO 1993).

10. **In the context of Indonesia, labor force surveys also provide several definitions of informal employment.** For instance, the labor force surveys (SAKERNAS surveys) carried out by Badan Pusat Statistik (BPS) report data on self-employment twice a year. BPS provides three definitions of informal employment: simplified, old, and new.<sup>3</sup> The simplified definition mainly reflects job-based informal employment, covering casual workers, (i.e. those without formal labor contracts), part-time workers, and unpaid household workers. Both new and old definitions use information on sectors and types of employment to classify workers, making sectoral estimates hard to interpret. While the simplified definition overlaps with self-employment, it is less linked with sectoral distribution and is preferred for the analyses in this paper (See Annex 2 for details).

11. **From a firm’s perspective, past informality studies tend to use the following three criteria to identify informal firms (ILO 2018).** First, it is not a legal entity separate from its owners, has its own complete set of accounts, and is not owned or controlled by one or a few household members. Second, it is a market enterprise that sells its goods or services. Third, it falls into one of the following categories: it keeps the number of workers employed below a threshold determined by business regulations; it is not registered; or it hired workers informally. Other studies provide an alternative definition of informal firms as a continuum depending on size, registration, accounting standards, tax payments, mobility of workplace, and access to bank credit (Benjamin and Mbaye 2012; Mbaye, Benjamin, and Gueye (2017). In firm surveys such as World Bank Informal Sector Enterprises Surveys, informal firms are typically defined as a business without the possession of a firm registration (or tax) number.

12. **Indonesia follows the global standard in defining formal and informal businesses.** Specifically, a formal enterprise is defined as a business in possession of a firm registration number ( _TDP-Tanda Daftar Perusahaan_ ) or firm unique ID ( _NIB-Nomor Induk Berusaha_ ), whereas an informal enterprise is a business that does not possess either of these.

> 3 The BPS moved from the old to the new definition of informality in 2016.

5
13. **A multidimensional approach to informality should be taken to have a deeper understanding of informality in Indonesia.** As summarized by Elgin et al. (2021a), there are three dimensions of informality, with most of the available data capturing the following three dimensions: output informality, employment informality, and firm/perceived level of informality.

# **2.2 Informality data  and estimation methods description: Cross-country and Indonesiaspecific databases**

14. **The paper carries out two sets of analyses.** The first set of analyses (section 3) compares the levels and trends of informality in EMDEs with those in Indonesia. The EMDE estimates are taken from a comprehensive informality database provided by Elgin et al. (2021a) and updated to 2021. The estimates for Indonesia mainly use data from the labor force surveys, referred to as SAKERNAS, which is provided by the official statistics agency BPS over the period 2000-22. In particular, estimates on output and employment informality at the regional and sectoral levels are also estimated using SAKERNAS surveys. The second set of analyses (section 4) explores policy and development challenges associated with informality across EMDEs. The findings from crosscountry analyses will be compared with specific features of informality in Indonesia.

15. **The cross-country analyses rely on one of the most comprehensive cross-country databases of informal economic activity.** The updated database (from Elgin et al 2021a) covers more than 160 economies for the period 1990-2021. The database includes model-based and survey-based measures of informality, which capture the three dimensions of informality: output informality, employment informality, and perceived level of informality. The model-based measures cover output informality (often expressed in percent of official GDP), while surveybased estimates capture employment informality (in percent of total employment) and the perceived level of informality (especially by firms and by households). Annex 3 provides a detailed description of the three dimensions of informality and their construction. In this paper, when conducting cross-country analyses, preference is given to measures that are constructed using the same statistical standard (and definition) and have better country-and-year coverage.<sup>4</sup> 16. **The paper considered two model-based estimates to compute output informality and three survey-based estimates for employment informality.** First, two model-based estimates are considered for the cross-country comparisons. One is the multiple indicators multiple causes model (MIMIC), which is a type of structural equation model that takes into account both the multiple possible causes of informal activity and the outcome indicators of it. The other one is a dynamic general equilibrium model (DGE) created by Elgin and Oztunali (2012) where production in the informal sector is determined by how households optimize their labor allocation between formal and informal economies in each period and how the allocation changes over time. Both models provide estimates of informal output in percent of official GDP. Second, three surveybased informal employment measures are considered here to capture employment informality:

> 4 For instance, self-employment shares are often used as a proxy for informal employment here, given its wide country-and-year coverage and consistency across countries.

6
self-employment, informal employment, and employment outside the formal sector. All informal employment measures are expressed as a share of total employment.

17. **For output informality estimates in Indonesia, the paper prefers the MIMIC-based estimates.** In the case of output informality in Indonesia, the model-based MIMIC estimates are used mainly in cross-country comparisons, while the SAKERNAS estimates are used in the withincountry comparison (see below for details). The MIMIC model, detailed in Schneider et al. (2010), is estimated in the paper (see Annex 4). According to Feige (2016), one of the limitations of Schneider et al. (2010) is that the base year value used for benchmarking is taken from an unspecified currency demand model. To overcome this limitation, the paper uses SAKERNAS estimates on output informality in 2000 to re-benchmark MIMIC estimates on output informality in Indonesia. It is also worth noting that MIMIC estimates are preferred here as they seem to capture the variation of informality better than DGE estimates in the case of Indonesia, while they are highly correlated with the DGE estimates in cross-country comparisons.

18. **SAKERNAS surveys are used to construct output and employment informality in Indonesia for national, regional, and sectoral level analyses.** These estimates are mainly used for within-country analyses. In addition to national-level estimates, output informality and employment informality are estimated for 34 provinces, 3 major sectors, and 9 subsectors over the period 2000-2022. The estimations use data on informal employment status and monthly income from Sakernas. The following equations are used to compute the share of output informality at the national (excl. i), regional (region =i), or sectoral (sector=i) level in year t:

1. Informal output (% total GDP, simple)it =

2. Informal output (% total GDP, weighted)it = j=nit ∑j=0 informal employment status dummyjit∗monthly incomejit∗weightjit j=nit . ∑j=0 employment status dummyjit∗monthly incomejit∗weightjit The share of informal employment at the regional (region =i) or sectoral (sector =i) level in year t is computed as follows: 3. Informal employment (% total employment, simple)it = 4. Informal employment (% total employment, weighted)it = 7
Here the (informal) employment status dummy equals 1 when worker j in region i (or sector i) and year t is employed (informally employed), and 0 otherwise. Weights capture the extent of representativeness of worker j in the whole sample. Both simple and weighted measures are constructed with the latter giving more weight to more representative observations in the sample. As shown above, while BPS provides three definitions of informal employment, the simplified definition is preferred for the analyses as it is less linked with Indonesia’s sectoral composition. These data series are then used to show the levels, trends, and features of informality in Indonesia.

**3. Levels and trends of informality: EMDEs versus Indonesia**

# **3.1 Informality in EMDEs**<sup>**5**</sup>

19. **Informal economic activity is more pervasive in EMDEs than in advanced economies (AEs).** In AEs, it accounted for less than one-fifth of official GDP and total employment in 2019, whereas about one-third of economic activities and employment in EMDEs happens in the informal sector (Elgin et al. 2021). Informality is common in all EMDE regions but takes different forms. On average, the informal economy’s share of output is highest in Sub-Saharan Africa (SSA), Europe and Central Asia (ECA), and Latin America and the Caribbean (LAC). The share of self-employment, however, is highest in SSA, South Asia (SAR), and East Asia and the Pacific (EAP).

20. **The share of informal output and employment has contracted in EMDEs since the 1990s.** The downward trend is observed both in AEs and EMDEs (Ohnsorge and Yu 2022). In the case of EMDEs, the downward trend is more prominent in output informality, whereas employment informality fell more noticeably during the recent two decades than during the 1990s.

**Figure 1. Informality in EMDEs**

<!-- Start of picture text --> A. Informality across EMDE regions B. Trend of informality in EMDEs<br>Percent of GDP / employment Percent of GDP/ employment<br>55<br>80 Output Employment Output Employment<br>50<br>60<br>45<br>40 40<br>35<br>20<br>30<br>0<br>EAP ECA LAC MNA SAR SSA<br>Sources: Elgin et al. (2021, updated), International Labor Organization (2023), World Bank.<br>1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 2019<br><!-- End of picture text -->

> 5 In this section, output informality for EMDEs is captured by MIMIC-based estimates. The DGE-based estimates are highly positively correlated with the MIMIC-based estimates and give similar results. The discussion here is restricted to the period before 2020 to avoid the impact of COVID-19.

8
Notes: Informal output is based on the MIMIC model, in percent of official GDP. Informal employment is based on the share of self-employment in total employment.

A. Bars show the average share of informal output during 2011-19 (in blue; average self-employment rate in red). B. Lines show unweighted group averages.

**3.2 Informality in Indonesia**

# _Output informality_

> 21. **Indonesia generally exhibits lower output informality compared to the average of other EMDEs.** Output informality in Indonesia averaged around 38 percent of GDP in 2000-2007 before sliding down slightly to an average of 36 percent of GDP in the decade before 2020.<sup>6</sup> This is smaller than the average level in EMDEs by about 0.5 percentage point of GDP, while being slightly above the average level in EAP (figure 2). The declining trend in output informality in Indonesia was also accompanied by rising GDP per capita, which rose almost by six times from USD 770.9 in 2000 to USD 4,333 in 2021, a consistent trend observed across EMDEs.

**Figure 2. Output informality in Indonesia**

<!-- Start of picture text --> A. Levels of output informality B. Evolution of output informality<br>Percent of GDP Percent of GDP<br>2001-07 2011-19 42 Indonesia EMDEs EAP<br>40<br>40<br>35 38<br>36<br>30<br>34<br>25 32<br>30<br>20<br>Indonesia EMDEs EAP<br> Source: Elgin et al. (2021a), updated and benchmarked the MIMIC-model-based estimates by World Bank staff. BPS; World<br>Bank Staff Calculation. Bars (or lines) show simple group averages. Here EMDEs and EAP averges do not include Indonesia.<br>The shaded area is capturing the COVID-19 years.<br>2000 2003 2006 2009 2012 2015 2018 2021<br><!-- End of picture text -->

# _Employment informality_

22. **Informal employment in Indonesia has also declined but remained higher than the average levels in other EMDEs and the EAP region.** Using self-employment as a proxy for informal employment, Indonesia has experienced a steady decline in informal employment since the 1990s (figure 3). However, there seems to be a reversal starting in 2016. A reversal that has been accelerated by the COVID-19 shock. Indeed, self-employment as a share of total employment increased from 49.9 percent in 2019 to 53.4 percent during the pandemic in 2020. Despite the historical decline, the level of employment informality in Indonesia is consistently higher than the level in the EAP region and other EMDEs. Using data on informal employment provided by ILO - a broader measure than self-employment - four out of five workers are informally employed in Indonesia, notably higher than the average informal employment rate in EAP or EMDEs (i.e., about 56 percent of total employment).

> 6 As shown in section 2, Output informality is proxied by MIMIC-based estimates or LFS estimates as elaborated in the previous section. The model-based MIMIC estimates are used mainly in cross-country comparisons, while the LFS estimates are used in the within-country comparison.

9
**Figure 3. Employment informality**

<!-- Start of picture text --> A. Evolution of employment informality B. Levels of employment informality<br>Percent of total employment Indonesia (ILO) Percent of total employment 2019<br>70 Indonesia (NSO) 80 EMDEs (2019)<br>EMDEs<br>65 EAP 70 EAP (2019)<br>2021<br>60 60 2020<br>50<br>55<br>40<br>50<br>30<br>45<br>20<br>40 Self- Informal Employment<br>employment employment outside the<br>formal sector<br>Source: Elgin et al. (2021, updated), ILO (2023), and SAKERNAS from Indonesia NSO.<br>A. Shaded areas are capturing recession years. The blue lines show values for Indonesia (solid from ILO, dashed from NSO).<br>Other lines show the simple averages for East Asia and the Pacific excl. Indonesia (EAP, in orange) and EMDEs excl. Indonesia<br>(in red). Here self-employment (% total employment; ILO 2022) is used as a proxy for informal employment.<br>B. The dark blue bars show values for Indonesia in 2019 (the light blue horizontal bar shows the value in 2020, and the diamond<br>shows the value in 2021). The other bars show the simple averages for East Asia Pacific excl. Indonesia (EAP; in orange) and<br>EMDEs excl. Indonesia (in red) in 2019.<br>1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021<br><!-- End of picture text -->

# _Firm informality_

23. **Firms in Indonesia are dominated by Micro Small and Medium Enterprises (MSMEs).** The 2016 Economic Census, the last one available, classifies 99 percent of firms in the country as MSMEs. A large share of these MSMEs are micro firms, almost 60 percent, with fewer than 5 workers. This is in contrast to peer countries like Malaysia and Vietnam, which also have a large share of firms categorized as MSMEs. In those two countries, the informal sector is significantly smaller at around 9 percent (2016) and 27 percent (2019), respectively.

<!-- Start of picture text --> Figure 4. Percent of firms registered when they Figure 5. Percent of firms competing against<br>started operations informal firms<br>Percent of firms Avg. over 2009-19 Percent of firms Avg. over 2009-19<br>EMDEs 80<br>EMDEs<br>EAP<br>100 60 EAP<br>80<br>60 40<br>40<br>20<br>20<br>0<br>0<br>Source: World Bank Enterprise Survey, World Bank Staff Calculation.<br>India Brazil Turkey India Brazil<br>Turkey<br>Thailand<br>Indonesia Thailand<br>Philippines Indonesia<br>Philippines<br><!-- End of picture text --> 24. **Indonesia’s firms are predominantly informal and seem to compete with the formal sector firms.** Only 45 percent of Indonesia’s firms were legally registered when they started operations, a significantly lower share than EMDEs, EAP region, and peer-country averages 10
(figure 4). Moreover, economic activity in the formal and informal markets seems to be intertwined. According to the latest enterprise survey in 2015, around 65 percent of formal firms in Indonesia are competing with informal firms. This contrasts for example with Thailand where only 25 percent of formal firms compete with informal firms. It is also a larger share compared to EMDEs and EAP averages (respectively 54 and 47 percent) (figure 5).<sup>7</sup> Across the country, this practice is most prevalent in Bali, where almost all firms (98 percent) report competing with informal firms. Bali is a province particularly known for its dominant service sector, especially in tourism and hospitality as well as other low-value-added services.

# **3.3 Informality at the regional level in Indonesia**

25. **Across the region, most of the provinces in the eastern part of Indonesia show a relatively higher informal economy.** Papua province has the highest informal output, comprising almost 80 percent of its economy (figure 6). This is followed by three other provinces in the eastern region (East and West Nusa Tenggara, West Sulawesi) with around 70 percent of informal output. However, with unweighted computation,<sup>8</sup> Lampung province has the highest level of informal output with the informal output capturing almost 45 percent of total economic output. Different methods of measurement of informality also resulted in a significantly different informality level. For example, an Informal Sector Survey conducted by the Statistics Agency in 2010 in two pilot provinces (Yogyakarta and Banten) used questionnaires to determine output produced by production units in the informal sector. Output informality was estimated at 37 percent and 27 percent in Yogyakarta and Banten respectively, lower than the estimation produced by the model.<sup>9</sup>

**<u>Figure 6 Output informality by regions or by provinces</u>**

<!-- Start of picture text --> A. Regional informality B. Provincial informality<br>Percent of total output Percent of total output<br>45 2019 2020 2021 2019 national lvl 50 2019 2020 2021 2019 national lvl<br>40 40<br>35 30<br>30 20<br>25 10<br>Sumatera Java/Bali Kalimantan Sulawesi Nusa Tenggara Maluku Papua Kep Riau DKI Jakarta Banten East Kalimantan Bali DI Yogjakarta Central Kalimantan West Papua West Java Bangka-Belitung East Sumatera South Kalimantan Southeast Sulawesi West Kalimantan North Maluku Maluku South Sulawesi Riau East Nusa Tenggara NAD Gorontalo South Sumatera East Java Central Java Bengkulu Papua Central Sulawesi West Sumatera Jambi North Sulawesi West Sulawesi Lampung West Nusa Tenggara<br><!-- End of picture text --> Source: BPS; World Bank Staff Calculation.

26. **The regional pattern of informal employment seems to mimic the regional pattern of output informality** (figures 7) **.** Informal employment is most prevalent in Nusa Tenggara and Papua regions, which could be explained by the nature of jobs in that province (i.e., agriculture

> 7 World Bank Enterprise Survey, 2015.

> 8 The weighted computation is accounting for the weight of the observation in the survey, while the unweighted computation is excluding the weight. See section 2 for the formula.

> 9 While the model calculated data for 2020 which could potentially show different figures, the result is significantly different where Yogyakarta informal output reached more than 50 percent of the economy and Banten informal output comprised more than 40 percent of the economy using the model.

11
<!-- Start of picture text --> Percent of total ermployment<br>80 2019 420202021 —2019 national Iv = A —<br>TO 2<br>7 &<br>60 tar a4 a+ 4 a<br>50 a* 4<br>4A) a *<br>= cs © s w © S<br>© © = x a = 3<br>e® <¢- € 2 = §& 8<br>icsray—§=& 3& a5A<br>>3 @ OF<br>“ si<br>fa<br>a<br>Zz<br><!-- End of picture text -->
their incomes grow (Saracoglu 2008). Moreover, limited access to credit, often associated with lower development, constrains firms’ ability to overcome barriers to entry into the formal sector.<sup>10</sup> 29. **Informality is more pervasive in countries with a lower level of per capita income, regardless of the measure of informality.** As a result, informality tends to be considerably more pervasive in EMDEs than in advanced economies (figure 8, La Porta and Shleifer 2014). In 2019, informal output and informal employment in advanced economies fell below the levels in EMDEs by 16 percentage points of GDP and 29 percentage points of total employment, respectively.

30. **Informality is associated with a large rural population and a lack of urbanization.** As shown in Loayza (2016), a developing economy passes through three stages of development. In the first phase, modern informal employment expands as the falling relative cost of urban living encourages rural workers (in the rudimentary informal sector) to migrate to cities. In the second phase, rural-urban migration slows, and the relative shares of the modern informal and formal sectors stabilize, but the relative size of the rudimentary informal sector shrinks. In the third phase, modern informal employment declines as rural-urban migration stalls and a rising capital-labor ratio reduces the relative (and absolute) size of the modern informal sector.<sup>11</sup> In EMDEs with above-median informality, about half of the population still resided in rural areas during the past decade, while the ratio fell to two-fifths or one-third in EMDEs with below-median informality (Ohnsoge and Yu 2021).

31. **Informality tends to be concentrated in the agriculture sector, especially in EMDEs.** About 90 percent of employment in the agriculture sector is informal in EMDEs (Ohnsorge and Yu 2020). Consequentially, in EMDEs with above-median informality, the agriculture sector accounted for about 20 percent of GDP and nearly 40 percent of total employment on average over the period 2011-2019. This is almost twice as much as in EMDEs with below-median informality. Meanwhile, informal firms in EMDEs tend to be small, less productive, and concentrated in laborintensive sectors, such as low-value-added service sectors (Amin, Ohnsorge, and Okou 2019).

32. **Informal workers tend to be less skilled and lower paid than their formal counterparts (Loayza 2018; Perry et al. 2007).** A meta-analysis of worker-level empirical studies shows that informal workers are, on average, paid 19 percent less than formal workers, which largely reflects the fact that informal workers tend to be less skilled and inexperienced (World Bank 2019). The negative link between informality and labor productivity is also supported by data, which could be driven by the significantly lower school attainment in EMDEs with abovemedian informality than in other EMDEs (figure 8).

> 10 See, for instance, Ferreira-Tiyaki (2008), D’Erasmo and Moscoso Boedo (2012), and Capasso and Jappelli (2013). 11  As modeled in Loayza (2016), a developing economy consists of two co-existing economies: a modern economy that is organized in firms and uses high-productive technology and a rudimentary, informal economy that captured the self-employed who only use labor and low-productive technology. The former further consists of two sectors: a capital-intensive modern formal sector and a modern informal sector that is more labor-intensive.

13
<!-- Start of picture text --> Figure 8. Output informality and underdevelopment<br>A. Informality and GDP per capita (2019) B. Informality, labor productivity, and human<br>capital<br>10,000 2017 PPP $ / Year<br>EMDE (in blue) 12 EMDEs with below-median informality<br>EMDEs with above median informality<br>10<br>Indonesia 8<br>6<br>AEs (in red) 4<br>2<br>6 8 10 12 0<br>Ln GDP per capita Labor productivity Years of schooling<br>60<br>50<br>40<br>30<br>20<br>10<br>MIMIC-based output informality (% GDP)<br><!-- End of picture text --> Sources: World Bank World Development Indicators, Elgin, et al. (2021 updated), and World Bank Staff estimates. A. Informality is captured by MIMIC-based informal output as a share of GDP. B. The sample is constrained to EMDEs, and data are averaged over 2011-19 to avoid the impact of the global recession around 2020 and 2008/09. EMDEs are grouped into “above-median” and “below-median” self-employment as a share of total employment.

33. **The link between informality and underdevelopment is supported by evidence in Indonesia.** First, output informality in Indonesia is most prevalent in the agriculture sector, followed by labor-intensive low-value-added service sectors (such as wholesale, retail, and hospitality sectors). Informal output in the agriculture sector is almost double the share of total informal output in the economy. It has declined slightly compared to its level in 2001 (figure 9). Wholesale, retail trade and hospitality sectors also pose a relatively larger share of informal output compared to other sectors though the share declined significantly compared to 2001. This is similar to a broad informality trend in other countries where informality tends to be higher in sectors that are labor-intensive, low-skilled, less productive, and with relatively low wages.

<!-- Start of picture text --> Figure 9. Output informality in Indonesia, simple definition (share, weighted)<br>Percent of total output in the corresponding sector<br>80 2019 2020 2021 2001<br>60<br>40<br>20<br>0<br>Agriculture, Wholesale Transportation, Constr- Mining Community, Manuf- Electricity, Finance,<br>forestry, and retail trade, storage and uction and social and acturing gas, and insurance,<br>livestock, restaurants communications quarrying personal srv water supply real estate<br> and fishing and hotels and bus.srv<br>Source: BPS, WB staff estimation.<br>Note: weighted estimates (using the sample weights from the SAKERNAS) are used.<br><!-- End of picture text --> 34. **The regions with the largest output informality are also regions with the largest rural population, weaker urbanization, prevalence of agriculture, and lower income.** For example, West Sulawesi and West Nusa Tenggara are two provinces in the top five largest output and employment informality. The share of the agriculture sector in those two provinces is the largest 14
<!-- Start of picture text --> The agricultural sector vs Informality (2019)<br>=a 80<br>Ey Prov. Papua<br>: y<br>= 60<br>ri§§ ¢ Prow RonkguDinten, Baygeary Trice<br>‘ op. STB RebePpapianies: Barat<br>aFI ® Prov. Kalymanta Atatypart IR eee é ta .<br>Hl © PR bse* Poop SavRSReNE a eOSHtera Barat<br>®y D : Aisaa o ye tien PRE© Semdorms AS;esr EP EgeNusaNusa Tenggara- B<br>e * Prov. Jawa Tengah<br>=$ 2 Prov. MBbe Bal Yiegwakarta<br>8zE * Prov. KepulauaryoP.Resa Banteantes© Prov, Jawa Barat ted values<br>Ho Prov. DKI Jakarta ~<br>20 25 30 35 40 45<br>Informal output (% total GDP, weighted, simple definition)<br><!-- End of picture text --> <!-- Start of picture text --> Economic development vs Informality (2019)<br>195 # Prov. DEI: Jakarta<br>9 Prov. Kalimantan Timur<br>=s&. 185ass eProv. Kepulauan Riau * Prov, Kalimantan Utara© Prov. Prow. RiauRis<br>= # Prov. Papua Barat<br>feaa 18 “Ps « . ; -: iasibTengah<br>49q *Prov. Bantea'»F Brow rtanfyspuhiaa fev Gaver eaei RaecbiiBAvesi— Utara<br>os *Prov.* Prov.DIYogyakartaeRea Babuliantpfalejp Bio"BaarHesght ESEPLSElowest LampungB<br>© Paspafaluget. Ssoronta tara Tow Sulawesi Barat<br>- # Prov. Maluku Pro<br>Prov. Nusa Tenggara Timur<br>20 25 30 35 40 45<br>Informal output (% total GDP, weighted, simple definition)<br><!-- End of picture text -->
<!-- Start of picture text --> Poverty vs Informahty (2019)<br>40. @ East Musa Tengparca<br>oq 3 @ Papoa<br>=|a @® Wet Sdlawesi<br>«© Gorompieutheast Selivesi<br>E<br>Fso 20 5 © Wee de . ca. atepte aSaeed" @ West Nusa Tenggara<br>iE ww = apla_—@ SoocH ‘Simatampuns<br>Py @ D1 “otmakecds Wem (Geulteabhtlawesi<br>£ © Yqathematesd Bengkolu<br>107) © Banten Banca almantan @ Weer Sumaterca<br>@ Riau a<br>@ Rian islands @ East Kobe - Seomh Ralmantan — Fitted; values<br>» Jakaers<br>an @ Bangka Belrong islads * Provinces<br>a0 40 50 eo 70 50<br>Informal output (%> total GDP, weighted, sumple definition)<br>Informal share in employment<br>100%<br>90%<br>80%<br>70%<br>60%<br>SO%<br>40%<br>30%<br>20%10%O% |<br>All Rural Urban Female Male Agriculture Manufacturing Other Low-End High-End<br>Industries Services Services<br>All Location Gender Sector<br>m2014 TM2019 mTM 2020 2021<br>Ee<br><!-- End of picture text -->
<!-- Start of picture text --> 120%<br>100%<br>an 40%<br>oe— = ae 80%ms<br>m% d a<br>LLL9”SOQO?PQD?© LQD’dDFYD’ SS’AYKPoYn> YYOH9 d'AN HYY’0DPCVAd Soa ;:& :"45 4g&”=<br>a<br>Education Sector<br><!-- End of picture text -->
|Ranking of the Top Business Environment Obstac<br>% firms choosing the informal sector as the biggest obstacle|le for Finms<br>se.7|
|---|---|
|% firms choosing tax rates as the biggest obstacle|14.35|
|% firms choosing political instability as the biggest obstacle|12.2|
|> firms choosing business licensing as the biggest obstacle|68|
|SS firms choosing access to finance as the biggest obstacle|63|
|% firms choosing trade regulations as the biggest obstacle|6.2|
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are unrelated and serve different markets or consumers (Harris & Todaro, 1970). The second biggest challenge is tax, which suggests that many firms in Indonesia might choose to stay informal to avoid paying taxes or given regulatory issues linked to the perceived complexity of the taxation system. Firm-level features will be updated and analyzed more thoroughly though as soon as the new business enterprise survey is completed in late 2023.

**4.2 Policy challenges associated with pervasive informality**

44. **Fiscal challenges are associated with more pervasive informality.** Over the period 2000-19, government revenues in EMDEs with above-median output informality were, on average, 4-5 percentage points of GDP below those with below-median output informality (figure 17; Ghossein, Yu, and Rana 2022). The composition of tax revenues is also tilted toward trade taxes in economies with more pronounced informality, making the tax system less progressive but facilitating tax collection when income underreporting is widespread. Similarly, in EMDEs with more pervasive output informality, government expenditures were 4-5 percentage points of GDP lower than in those with less output informality.

45. **Constrained government spending in EMDEs with more pervasive informality is reflected in the limited provision of public services, contributing to poorer human development outcomes** . During 2000-19, EMDEs with above-median output informality spent 2.6 percent of GDP on health, which was about 1 percentage point of GDP lower than in EMDEs with below-median output informality (figure 17; Ghossein, Yu, and Rana 2022). Similarly, governments in EMDEs with below-median output informality spent 1 percentage point of GDP more on education than EMDEs with above-median output informality. The lack of spending on education and health led to limited public resources in these sectors.<sup>18</sup> Meanwhile, compensation of government employees amounts to about a third of government expenses in EMDEs with abovemedian output informality, which is above the level in other EMDEs by 6 percentage points.

**Figure 17. Fiscal policies and informality**

<!-- Start of picture text --> A. Government revenues B. Government (primary) expenditure<br>Percent of GDP Percent of GDP / expenses<br>25 Below-median informality 35 Below-median informality<br>Above-median informality 30 Above-median informality<br>20 25<br>20<br>15<br>15<br>10<br>10<br>5<br>5 0<br>Total Education Health Gov. emp.<br>0 Compensation<br>Total Tax Income tax Trade tax (% expenses)<br><!-- End of picture text --> Sources: Elgin et al. (2021a) and Ghossein, Yu, and Rana (2022) .

Notes. Bars are simple averages over the period 2011-19 for EMDEs with above-median (high in blue; below-median, low in red) output informality. In all cases, blue bars are statistically different from red bars.

18 The average number of pupils per teacher in primary schools was about 35 in EMDEs with above-median informality—significantly higher, by eight students per teacher, than in EMDEs with below-median informality (Ohnsorge and Yu 2021). Access to medical resources, such as physicians and nurses, was also significantly more limited in EMDEs with a more pervasive informal sector (World Bank 2020).

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46. **The tax effort in Indonesia is significantly smaller than regional comparators or even EMDEs.** Over the decade preceding the pandemic, general government revenue averaged around 14 percent of GDP in Indonesia in the past 10 years before the pandemic. This is well below the median in EAP (and EMDEs) by 13.5 percentage points of GDP (9.4 percentage points of GDP) (figure 18). About half of this gap was due to weaker tax revenues. Indeed, revenues from income taxes, general services taxes, and trade taxes were all lower in Indonesia than EAP and EMDEs median. The weak tax effort can be attributed to multiple factors. This includes tax policy considerations, such as the prevalence of tax exemptions and high tax thresholds, or inefficiencies in tax administration that lead to low compliance rate. Nevertheless, pervasive informality also plays a role in such outcomes since informal employment and informal firms typically fall outside the taxation net (for income and general sales taxes). Formalizing firms outside of the tax net while lowering the threshold and improving compliance is likely to increase revenue in the medium term.

# **Figure 18. Fiscal indicators in Indonesia**

<!-- Start of picture text --> A. Government revenues B. Government spending<br>Percent of GDP Percent of GDP / expenses<br>30 Indonesia EAP EMDEs 35 Indonesia EAP EMDEs<br>25 30<br>25<br>20<br>20<br>15<br>15<br>10 10<br>5 5<br>0<br>0<br>Total Tax Income GST Trade tax Total Education Health Gov. emp<br>tax compensation<br>(% expenses)<br><!-- End of picture text --> Sources: IMF GFS (2023), WEO (2022 Oct), World Bank WDI, and World Bank Staff calculation. Notes: EAP=East Asia Pacific region; EMDEs=emerging market and developing economies. Medians over the period 2011-2019.

47. **Low tax effort constrains Indonesia’s growth-related public spending, a feature also observed in countries with high pervasive informality.** Primary expenditure in Indonesia averaged around 16 percent of GDP over the period 2011-2019, which was only three-fifths of the median in EAP and EMDEs. The limited fiscal resources led to lower public spending on education, health, social protection, and public investment relative to peers. Those programs all have implications for the country’s future growth potential. Nevertheless, unlike other countries with high informality, Indonesia has had an adequate response to recent economic downturns. This was evident by the successful support package put in place during the COVID-19 pandemic. A package that was made possible given the country’s prudent fiscal policy stance and adherence to the 3 percent fiscal deficit target, which enabled the gradual build-up of fiscal buffers.

48. **The informal sector is excluded from financial markets, hence limiting the reach of banking credit in the economy** (Alberola and Urrutia 2020). About one-third of firms in EMDEs with above-median informality identified access to finance as a major constraint—8 percentage points higher than EMDEs with below-median informality (Ohnsorge and Yu 2021). By weakening the banking sector's performance (figure 19), the informal sector further dampens the transmission channel of monetary policy and makes it less effective in stabilizing inflation 20
<!-- Start of picture text --> aa<br>a a<br><!-- End of picture text --> <!-- Start of picture text --> Net Interest Margin<br>6%<br>5% = m2021 mTM2020 m2019<br>4% 4 =<br>2% a=<br>0% ==<br>cod od ca z > <<br>RSSs wwx es ee; RS Ss “aSs ~s; —<br><!-- End of picture text -->
<!-- Start of picture text --> Coefficient Coefficient<br>0.6 KK aes 0.6 HK RK<br>KKK AK<br>0.4 0.4<br>0.2 0.2<br>0 0<br>World EMDEs World EMDEs -0.2<br>DGE-based MIMIC-based World EMDEs World EMDEs<br>informal output informal output Formal employment Informal employment<br><!-- End of picture text -->
both trade for goods and services as well as investment flows were affected.<sup>20</sup> Accordingly, Indonesia experienced its deepest contraction in two decades during the second quarter of 2020.

52. **In the early days of the pandemic, workers – especially in urban areas – lost their jobs while others had to work fewer hours and earned less.** In the first six months of the pandemic, more than 5 million people (2.5 percent of the working-age population) lost their jobs and 24 million workers (11.8 percent of the working-age population) had to work reduced hours, with urban areas being the most affected. The unemployment rate rose by 1.8 percentage points to 7.1 percent in the third quarter of 2020 (yoy), mainly driven by urban unemployment increasing from 6.3 to 9 percent, while rural unemployment only increased from 4 to 4.7 percent. Underemployment increased by 7.3 percentage points to 28.9 percent. The intensity of underemployment was exacerbated by the pandemic, reducing average working hours by 0.5 hour, and earnings by about 5 percent.

53. **For 3.4 million new labor market entrants, the economy added only 1.9 million jobs in 2020.** To compensate for losses in households’ livelihoods and the loss of jobs for men, women’s entry into the labor force increased by 2.8 million women in 2020. This was substantially more than the previous 5-year average when women’s entry into the labor force grew by 1.1 million. At the same time, 330,000 men left the labor force, in stark contrast to the customary number of 1.3 million men entering the labor force yearly. Jobs became less secure, with 4.5 million formal jobs vanishing, while 6.4 million informal jobs being created (figure 22A). Some of them were in the digital economy as gig workers to buffer the impact of job loss (Word Bank 2023). However, 4 million of the new jobs were unpaid family work and often in agriculture, mostly filled by women. Net job losses among men were particularly prevalent in manufacturing while service jobs became informal.<sup>21</sup> Overall, COVID-19 increased women’s employment in 2020, compensating for employment losses by men, while informality helped as a buffer.

54. **Informality acted as a buffer for job losses, but only to a limited extent and at the aggregate level of the economy.** The large increase in informal jobs during the pandemic compensated for the loss of formal jobs. However, the compensation acted at the aggregate level of the economy rather than the individual level. While men lost their formal jobs, most informal jobs were taken up by women. This suggests that women sought informal work to compensate for income loss at the household level. These losses might have occurred for formal as well as informal jobs, at the intensive margin due to lower working hours and at the extensive margin by job losses.

55. **COVID-19 also affected the youth by leading to school dropouts and part-time work, while diminishing work opportunities for older youth.**<sup>22</sup> The youngest (aged 15 to 18) were more likely due to COVID-19 to work while being in school, more often above 20 hours per week. In addition, the pandemic increased the number of younger youth neither in school nor employed. For the older cohort of youth aged 19 to 24, the pandemic similarly led to school dropouts but led

> 20 World Bank, Indonesia Economic Prospects, December 2020.

> 21 Putra, Ovsiannikov, and Kotani, “COVID-19-Associated Income Loss and Job Loss.” 22 Halim, Hambali, and Purnamasari (2023).

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<!-- Start of picture text --> 4<br>a<br>s<br>8<br>8 0<br>=<br>2<br>a<br>B2DB 2 |<br>&<br>4<br>6<br>All 19-29 30-44 45-54 55-64<br>(15-64)<br>Age Groups<br>© Male e Female<br><!-- End of picture text -->
57. **Despite the rebound, lingering impacts are still felt on employment and incomes of poorer and urban households.** While employment and income impacts were widespread, those already economically insecure prior to the pandemic were hit harder. Among primary breadwinners, household heads with lower education were initially more likely to experience work stoppages (Purnamasari et al 2020). Those and households with young children more often reported an income shock. Two years into the pandemic, these households – as well as households in the bottom 40 percent – were recovering more slowly than other households. The lack of resilience of bottom 40 households exacerbates the impact, and, hence, pre-existing inequalities.

# **5. Conclusion**

58. **Informality trends observed in EMDEs were upheld in Indonesia to a large extent.** Like in other EMDEs, Indonesia witnessed a general decline in informality during the past few decades but it remains elevated and broadly above comparator countries. At 35 percent of its output and 54 percent of its employment, informality remains an important development challenge for Indonesia. First, informality in Indonesia is mostly concentrated in the agriculture and low-skilled service sectors. Second, it is associated with a higher level of poverty at the provincial level. Combing evidence at the macro and micro levels, there appear to be productivity, education, and salary gaps between formal and informal workers. Moreover, markets are not segregated as informal firms compete strongly with formal ones. Finally, informality seems to pose macroeconomic challenges as tax efforts and financial sector depth in Indonesia remain below the EMDE averages. Table 1 summarizes the main findings of the paper and compares the country’s informality features to findings in the literature on informality in EMDEs.

**Table 1: Summary of informality features in EMDEs and Indonesia**

|**#**|**Feature of Informality in EMDES**|**Feature of Informality in Indonesia**|
|---|---|---|
|1|Informality is more pervasive in countries with<br>a lower level of per capita income.|Trend upheld. Informality declined in<br>Indonesia overall with rising GDP per capita.<br>Moreover, provinces with lower sub-regional<br>GDP per capita had more pervasive output and<br>employment informality.|
|2|Informality is associated with a large rural<br>population and a lack of urbanization.|While this is the case, informality is also<br>dominant in some urban areas like those with<br>large mining sector activity.|
|3|Informal participants tend to be concentrated in<br>the agriculture sector, especially in EMDEs.|Informality is higher in regions with a larger<br>agriculture sector. However, informality is also<br>strong in regions with a large low-skilled<br>service sector such as trade, transport and<br>construction.|
|4|Informal workers tend to be less skilled and<br>lower paid than their formal counterparts.|Trend upheld. There appears to be a<br>productivity gap, an education gap, and a<br>salary gap between formal and informal.<br>Moreover, informality seems to be associated<br>with higher poverty at the sub-regional level.|

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|5|Poor governance, unfriendly business climates,<br>and heavy-handed regulations can drive<br>informality.|N/A|
|---|---|---|
|6|Higher business registration and operational<br>costs, ranging from heavy firm startup costs to<br>fiscal burdens, increase firms’ costs of being<br>formal.|Firms identified competition from the informal<br>sector and taxes as the major obstacles to the<br>business environment. However, the large<br>share of unregistered firms also points to a<br>potentially burdensomeregistrationprocess.|
|7|Greater corruption, rent-seeking bureaucracies,<br>less effective government-to-business services,<br>and weaker rule of law increase informality.|N/A|
|8|<br>In EMDEs with more pervasive informality,<br>formalizing is often not associated with a range<br>of benefits.|Trend upheld. COVID pandemic areas suggest<br>informality was a buffer on an aggregate level.<br>However, it is not the case from an individual<br>perspective. Informality is also a drag during<br>recovery given potentially the lack of access to<br>government support and credit.|
|9|Fiscal challenges are associated with more<br>pervasive informality, especially with lower tax<br>revenues and less progressive tax schemes.|Trend upheld. Limited government revenues in<br>Indonesia are partially attributed to the<br>pervasive informal sector where both informal<br>firms and informal employment falls outside of<br>the tax nets (namely for income and general<br>sales taxes).|
|10|Constrained government spending in EMDEs<br>with more pervasive informality is reflected in<br>the limited provision of government services,<br>contributing to poorer human development<br>outcomes.|Trend upheld. Limited revenues in Indonesia<br>constrain public spending on pro-growth<br>programs and limit the government’s ability to<br>conduct countercyclical fiscal policies.|
|11|The informal sector is often excluded from<br>financial markets, hence limiting the scope for<br>a credit channel inthe economy.|Trend upheld. Access to credit and financial<br>sector depth is more limited in Indonesia than<br>in itsEAPcomparators.|
|12|Additional policy challenges are posed by the<br>interactions between formal and informal<br>business cycles.|The dual economy theory does not seem to be<br>upheld in Indonesia. Formal and informal<br>firms’ economic activities seem to intertwine.<br>There is an uptick though in employment<br>informality during economic recessions.<br>COVID-19period was a case inpoint.|

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