Financing Barriers and Performance of Micro, Small, and Medium Enterprises (MSMES)
Author:
International Monetary Fund. Asia and Pacific Dept
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Publication Date:
07 Aug 2024
eISBN:
9798400284663
Language:
English
Keywords:
firm performance; firms number; firm age; IMF staff estimate; x log; Export diversification; Productivity; Employment
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Using the World Bank Enterprise Survey (WBES), we analyze SMEs’ access to finance in Indonesia and determinants of export diversification and firm performance. Our findings reveal that young, domestically owned firms, and those that face inadequate infrastructure experience significant barriers to financial access. Firm age, foreign ownership, and website availability positively affect export diversification. Limited financial access adversely affects sales growth and labor productivity, particularly for domestic firms, although managerial experience can mitigate these effects.

Financing Barriers and Performance of Micro, Small, and Medium Enterprises (MSMES)

Using the World Bank Enterprise Survey (WBES), we analyze SMEs’ access to finance in Indonesia and determinants of export diversification and firm performance. Our findings reveal that young, domestically owned firms, and those that face inadequate infrastructure experience significant barriers to financial access. Firm age, foreign ownership, and website availability positively affect export diversification. Limited financial access adversely affects sales growth and labor productivity, particularly for domestic firms, although managerial experience can mitigate these effects.

A. Introduction

1. Micro, Small, and Medium Enterprises (MSMEs) are pivotal to the economic fabric. International evidence suggests that MSMEs generally serve as a significant source of employment and innovation, and have a critical role in fostering economic growth and reducing poverty (Beck and Demirguc-Kunt, 2006). However, these enterprises often face substantial barriers to financial access, which hampers their potential for expansion. The primary constraints include stringent lending criteria, lack of collateral, and insufficient credit history, which disproportionately affect smaller firms compared to larger ones (Ayyagari et al., 2014). Additionally, the lack of access to finance is intricately linked to lower rates of export orientation and suboptimal performance among MSMEs. Research indicates that MSMEs with better access to financial services tend to engage more in export markets and exhibit improved business performance (Abor et al., 2014). Addressing these financial barriers could unleash the potential of MSMEs to contribute more robustly to economic development and job creation in developing economies.

uA002fig01

MSME’s Contribution to Exports, 2023 (In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: Ministry of Cooperatives and SMEs; and CEIC Data Co. Ltd; and IMF staff calculations.

2. MSMEs dominate Indonesia’s economy and their performance will be key to achieving the Golden Vision 2045. According to Statistics Indonesia data, MSMEs contribute 61 percent of Indonesia’s GDP, absorb 97 percent of the nation’s workforce, and represent 99 percent of all business units. These statistics represent a larger MSME presence than in peer countries. However, Indonesia’s MSMEs encounter formidable challenges hindering their growth: 67 percent operates within the informal sector, exhibit low levels of productivity growth and innovation, and limited access to global export markets. Specifically, Indonesia’s MSMEs contribute only 15.8 percent to exports, which is relatively low compared to other countries (Figure 1). This reflects barriers, particularly in human capital, logistics, regulatory complexity, market access, and financing.

3. Access to finance for MSMEs lags peers and is a primary hurdle for their development (Figure 2). Higher borrowing costs than peer countries (Figure 3) and the uneven distribution of financing across sectors (Figure 4) exacerbate the challenge, leaving a substantial credit gap with 47 percent of demand unmet (EY Parthenon, 2023). State-owned banks, particularly Bank Rakyat Indonesia, dominate the lending landscape to MSMEs (Figure 5), with loan disbursements concentrated in Java. MSMEs face high interest rates, lack of collateral, low financial literacy, and complex application processes, often resulting in rejected proposals (Statistics Indonesia, 2019). Financial institutions also struggle to assess MSMEs’ creditworthiness, worsened by MSMEs’ low participation in training programs and poor financial management, complicating the financing landscape further (Ministry of Trade of Indonesia, 2019).

uA002fig02

Credit to MSMEs to Total Credit, 2023

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: Ministry of Finance; Bank Indonesia; and CEIC Data Co. Ltd.
uA002fig03

Average MSMEs Credit Interest Rate, 2023

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: Indonesian Financial Service Authority; and CEIC Data Co. Ltd.
uA002fig04

MSMEs Loan by Sector, 2023

(In percent of total loan)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: Bank Indonesia; and IMF staff estimates.
uA002fig05

Loan Disbursed to MSMEs by Bank Types, 2023

(In percent of total)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: Indonesian Financial Service Authority; and IMF staff estimates.

4. This paper is structured as follows. First, using the World Bank Enterprise Survey (WBES), we provide the descriptive landscape of Indonesian enterprises. Second, utilizing the WBES, we follow Hosny (2020) to analyze firm characteristics associated with more access to finance and export diversification; and we quantify the impact of these structural factors on firm performance. We conclude with policy recommendations.

B. Indonesian Enterprises Landscape

5. WBES Indonesia provides a comprehensive and representative landscape of Indonesian enterprises1. WBES is a survey conducted by the World Bank on firms’ perceptions of their business environments. WBES has taken place three times in Indonesia (2009, 2015, 2023) with the number of firms at 1,444, 1,320, and 2,955 respectively. The WBES’s samples are randomly selected and comprise three levels of stratification: size, industry classification, and region. For firm size, we use the number of full-time equivalent workers (i.e., permanent workers plus seasonal workers in a full-time scale)2 unless the number of workers is fewer than five, in which case size is determined from the administrative data. Java, particularly Jakarta, dominates the economy. Almost one-sixth of all non-agricultural firms in Indonesia are based in Jakarta. Most Indonesian firms operate in retail services, representing about 45 percent of the economy. Small and medium-sized firms are largely sole proprietorships.

uA002fig06

Distribution of Indonesian Firms by Region

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig07

Distribution of Indonesian Firms by Sector

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates

6. SMEs tend to be younger than large firms and face low human capital, although they provide more managerial opportunities for women. In the sample, SMEs are relatively mature, having been in operation for 15–18 years on average. Foreign ownership is low at 1–2 percent compared to about 7 percent for large firms. Although SMEs have proportionally fewer female workers, more small firms are managed and fully or partly owned by females compared to medium and large firms. Smaller firms have lower educational attainment and offer less on-the-job training, while managers also have less experience than in medium and large firms.

7. Available evidence suggests that governance weaknesses affect larger firms more than smaller firms, although this may reflect that the latter are under the radar through informality. The graph indicates that gratification payments and bribery are more prevalent among large firms compared to small and medium firms; this result should be caveated as it is possible that governance issues in smaller firms are not captured as these tend to operate more in the shadow economy.

uA002fig08

Age of The Establishments by Firms’ Size

(In years)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates
uA002fig09

Female Participation by Firms’ Size

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates
uA002fig10

Workforce Education by Firms’ Size

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig11

Top Manager Experience by Firms’ Size

(In years)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig12

Corruption Index by Firms’ Size

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig13

Informality by Firms’ Size

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.

8. Small firms suffered most during COVID-19. The outbreak of COVID-19 in March 2020 shrunk firms’ sales from 2019 to 2021, with disproportionally higher impact among small firms. Nonetheless, Indonesian firms hired more employees in the same period, resulting in negative productivity growth. Meanwhile, all firms experienced improved performance in nearly all indicators from 2020 to 2022, indicating a major comeback after the pandemic. Overall, 95 percent of Indonesian firm’s products are sold in the domestic market reflecting the inwards orientation of SMEs and barrier to accessing financing.

uA002fig14

Firms Performance, 2019 to 2021

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig15

Firms Performance, 2020 to 2022

(In percent)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig16

Firms Exporting at Least 10 Percent of Sales by Firms’ Size

(In percent of total firms number)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2009, 2015, 2023, and IMF staff estimates.
uA002fig17

Top 5 Obstacles for Small Firms

(In percent of total firms number)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.

9. Smaller firms spend less on R&D and are less likely to introduce new products or processes to the market. R&D spending has broadly stagnated for SMEs; these also bring fewer breakthrough products to the market. R&D spending by small firms may be crowded out by their expenditure on machinery, vehicles, and equipment which, at 136 percent, exceeds their gross revenue. High spending on land and buildings also indicates high financing needs.

uA002fig18

Top 5 Obstacles for Medium Firms

(In percent of total firms number)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig19

Firms that Spend on Research and Development

(In percent of total firms number)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2015, 2023; and IMF staff estimates.
uA002fig20

Firms with New Product/Process is New to The Main Market

(In percent of total firms number)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig21

Annual Expenditure for Machinery, Vehicles, and Equipment

(In percent of sales)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig22

Annual Expenditure for Lands and Buildings

(In percent of total sales)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.

10. Financial inclusion for small firms has improved, but access to finance is still a top obstacle for SME, especially in Eastern Indonesia. The proportion of small firms with a checking or savings account increased from 43 percent in 2009 to almost 76 percent in 2023. Nonetheless, small firms remain more prone to liquidity constraints, with only 6.3 percent having an overdraft facility. While access to finance has improved overall in Indonesia, there remains a significant disparity between East and West Indonesia, as illustrated by fewer checking/savings accounts in East Indonesia. Furthermore, among small firms with insufficient capital (about 35 percent of total) cited complex procedures as a reason not to apply for a loan or credit.

uA002fig23

Firms with A Checking or Saving Account

(In percent of total firms number)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2009, 2015, 2023; and IMF staff estimates.
uA002fig24

Access to Finance Across Region

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

uA002fig25

Firms with a Checking or Savings Account

(In percent of total firms number)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.
uA002fig26

Main Reasons not to Apply for a Loan

(In percent of firms with insufficient capital)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Sources: World Bank Enterprise Survey 2023; and IMF staff estimates.

C. Determinants of Firms’ Access to Finance

11. This section examines factors affecting access to finance. As seen in Section B, access to finance is a top obstacle for SMEs in Indonesia. Using an ordered/binary logit model, we extend our scope to which firms perceive access to finance as a constraint to business. The dependent variable is “Access to finance” constructed from the ordinal responses to the question: To what degree is access to finance an obstacle to their current operations of this establishment? Responses ranged from “No obstacle” (a value of 0) to “Very severe obstacle” (a value of 4). Estimation is done by maximum pseudo-likelihood:

AccessToFinanceis = f(Xis)

where the dependent variable AccessToFinanceis of firm i in sector (or sector x region) s is a function of Xis, a set of explanatory variables representing firm characteristics. AccessToFinanceis would range from 0 to 4 in the ordered logit, while we also suppress the responses into a binary variable (0/1) for the use in a binary logit. Firm characteristics, the independent variables, come from survey questions covering aspects such as firm age, size and ownership structure, top manager characteristics, and infrastructure. The choice of explanatory variables builds on recent research by Hosny (2020) and Islam and Meza (2023). Interpretation, especially for causality, should be approached with caution due to the limitations inherent in cross-sectional data analysis.

12. The empirical results are broadly in line with expectations (Table 1).

  • Mature firms—having run their business longer than 20 years—are less likely to report access to finance as a business obstacle, compared to firms in a growth phase (6–20 years). The coefficient on the indicator of young firms (equal or less than 5 years) consistently also indicates a negative relationship but is statistically insignificant throughout the variation of model specifications.

  • Foreign firm ownership shows some evidence of easier access to finance (Table 1 column 3–4), in line with some literature (e.g. Beck et al. 2006; Mertzanis 2017)3.

  • Firms that experienced power outages in the previous year and that do not have their own website appear to be associated with lower access to finance, suggesting firms situated in the worse infrastructure tend to report access to finance as an obstacle. Managers’ capacity could also impact on both setting up a website and applying for a loan.

  • There is some evidence that credit--constrained firms are likely to report access to finance as a business obstacle, in line with Islam and Meza (2023).

  • However, we could not find clear evidence on the relationship between export orientation and access to finance. Coefficients are not statistically significant, and signs of them are mixed in ordered logit analysis. This might reflect that the pandemic impact could confound the relationship between two variables as exporters could be hit harder4.

  • Controlling for firm characteristics, we could not find a significant different perception of financial access by firm size. However, while our estimates indicate that firm age, foreign ownership, and availability of website are negatively associated with the perception of access to finance as a major constraint, positive relationships of firm size with those characteristics are observed. This suggests that larger firms would less likely report access to finance as constraints, which is in line with expectations.

  • Additionally, concerning behavioral differences by firm size, limiting the estimation sample only to SMEs does not significantly change these results (Table AI.1).

uA002fig27

Relationship with Firm Size 1/ 2/

(Coefficient of a regression of firm size on firm characteristics 3/)

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

Source: IMF staff calculations.1/ Firm size: 1=Small; 2=Medium; 3=Large.2/ Solid bar indicates the coefficient is significant at 10 percent.3/ Estimation is done using survey weights. Included sector and region fixed effects.
Table 1.

Indonesia: Determinants of Access to Finance

article image
Standard errors in parentheses. Estimation is done using survey weights. Constant and dummies are not reported. * p<0.10, ** p<0.05, *** p<0.01

D. Drivers of Firm’s Export Diversification

13. In this section, we analyze what factors are associated with firm’s efforts on export diversification. SMEs in Indonesia appear to be less likely to commit the export diversification. To find which firm characteristics are associated with export diversification, we estimate a logit model, where the dependent variable is a binary export diversification. The export diversification is an interaction variable of export orientation multiplied by an indicator of diversification (1 for R&D or process improvement in last year; otherwise 0), following Hosny (2020). The explanatory variables include firm characteristics and variables for access to finance. This analysis is also not immune to the limitations of cross-sectional data analysis, especially for the interpretation of causality.

14. The results show that some firm characteristics, such as firm age, foreign ownership and availability of a firm’s website, are associated with export diversification efforts (Table 2).

  • The relationship between firm age and the likelihood of export diversification appears to be U-shaped. Both young and mature firms are more likely to put their efforts on export diversification, compared to firms in a growth phase (Table 2 columns 1–3). The U-shape is also evidenced in a quadratic form of the log value of firm age (columns 4 and 6). Combined with the estimated relationship with firm age and access to finance, mature firms would have easier access to finance, resulting in more activities in export diversification. As regards young firms, export diversification could be driven by the necessities for the transition to the next stage, rather than the access to finance.

  • Foreign ownership shows a significant positive relationship with export diversification, likely due to advantages such as better access to international networks or knowledge transfers from a foreign owner.

  • There is also clear evidence that export diversification is positively associated with availability of website, which can facilitate reaching external markets.

  • There is weak evidence that banked firms are more likely to spend for export diversification. However, the indicator for firms that reported access to finance as major constraints does not clearly show any significant relationship with export diversification.

  • Limiting the estimation sample only to SMEs does not significantly change these results (Table AI.2).

Table 2.

Indonesia: Determinants of Export Diversification

article image
Standard errors in parentheses. Estimation is done using survey weights. Constant and dummies are not reported. * p<0.10, ** p<0.05, *** p<0.01

E. Firm Performance and Financial Access

15. In this section, we investigate the impact of limited access to finance on firm performance. Financial constraints can directly affect firm’s growth (Ayyagari et al., 2006). Given the importance of SMEs in Indonesia’s economy and difficulties in accessing credit for SMEs, it is imperative to better understand the relationship of firm performance with access to finance constraints.

16. A linear regression model for firm performance is specified:

Yirst = b1AccessToFinanceirst + B’Xirst + as + ar + at + eirst

where the dependent variable Yist is a measure of firm performance—the annualized growth rate of nominal and real sales (nominal sales deflated by GDP deflator), productivity (real sales per employee), and employment for last two years—of firm i of sector s in region r at time t. The time dimension is added as the relevant year t for a firm’s performance can be either 2022 or 2021, depending on the timing of the interview. The measures of performance are imputed based on the comparison with two previous year’s, that is, 2020 or 2019. Any different impact of COVID-19 on the performance measures during these periods would be controlled by a time fixed effect at. The variable of interest is AccessToFinanceirst, and the coefficient b1 would show the weighted average of the difference in performance measure between firms that reported access to finance as a major constraint and those not. Control variables Xirst include firm characteristics and variables for export diversification. Region-specific effect as is also included.

17. We use an endogenous treatment effects estimator to estimate causal effects from observed data. The treatment group constitutes firms facing limited access to finance. The perception of access to finance (reported access to finance as major or very severe constraints) is used for the treatment but could be formed endogenously, resulting in a selection bias problem. Particularly, a reverse causality cannot be ruled out, based on the survey design. However, it is not deterministic whether the bias is downward: for instance, a firm with good performance is expected to be offered better credit by banks, whereas the firm’s perception on access to finance can be worsened if expanding investments driven by a good performance lead to significant financing needs. The endogenous treatment effects model (Heckman 1976, 1978; Cameron and Trivedi 2005; Wooldridge 2010) can mitigate this problem, by assigning treatment based on the estimated probability of a treatment, including at least an exogenous variable that is included in the model for treatment and excluded in the main regression model (of firm performance). In our first stage equation, region X sector average value of AccessToFinanceirst, i.e. the probability of treatment in the region-sector (AccessToFinancers), is added as an instrumental variable to the set of firm characteristics variables specified in Section A.5 This follows Ayyagari et al. (2006) to isolate the exogenous part of the possibly endogenous perception of access to finance.6 For example, a major concern is reverse causality such that firm’s performance can affect the perception of access to finance. When we consider the perception of financial access at the region-sector level of aggregation, the causality is likely to run from the average degree of perception of access to finance to individual firms, not vice versa (Ayyagari et al 2006). Nevertheless, caution in the interpretation of causality is warranted if endogeneity arises beyond the scope of these efforts. The estimation is done by the maximum likelihood method.

18. The estimation results suggest that firms with better financial access likely have a better performance (Table 3). The firms that report access to finance as a major constraint experience lower (annualized) nominal sales growth by 17 percentage points, compared to other firms (column 1–2). The estimate on sales growth inches up by inflation adjustment but still stands around 17 percentage points (column 3–4). This negative impact of financial access constraints is mainly channeled through loss of labor productivity (real sales per employee), with the coefficient of financial obstacles at 24 percentage points (column 5–6), instead of softening employment, whose coefficient is insignificant, albeit negative (column 7–8). We find that this pattern is clear in domestic firms—by adding an interaction term of the variable of interest and a dummy for foreign ownership (≥ 10 percent), while foreign-owned firms appear to be less sensitive to financial constraints in real sales and productivity with a negative relationship with constrained financing and employment (Figure 1 left panel). Additionally, another estimation with an interaction term with manager experience (years) suggests that experienced manager could mitigate the negative impact of constrained access to finance on real sales (Figure 1 right panel). The size of negative relationship between financial access constraints and real sales (black line) decreases over year in manager experience, and the coefficient become insignificant in 25 years of manager experience, with 10 percent of significance level. The gains from manager experience appear to benefit employment (orange line), resulting in no significant change in loss of productivity (green line).

Table 3.

Indonesia: Endogenous Treatment Regression: Firm Performance

article image
Standard errors in parentheses. Estimation is done using survey weights, except for LR test for independent equations. Constant and dummies are not reported. * p<0.10, ** p<0.05, *** p<0.01
Figure 1.
Figure 1.

Indonesia: Financial Access Constraints and Performance, by Ownership and Management Experience

Citation: IMF Staff Country Reports 2024, 271; 10.5089/9798400284663.002.A002

19. Coefficients for control variables are broadly in line with expectations. The coefficient for export-oriented firms turns out negative, likely reflecting vulnerability to the pandemic shock7. Nevertheless, better firm performance is associated with higher export diversification efforts, especially for the export-oriented firms with the efforts for the process improvement8 mainly through enhanced productivity (column 6). Young and mature firms appear to record lower productivity growth, compared to firms in a growth phase (column 5–6). Young firms’ employment tends to grow faster than other firms, partly due to their small size. However, sales growth does not show any significant difference over firm age. There is evidence that foreign ownership is negatively associated with employment. This might reflect a heterogenous response of foreign-owned firms— tends to be more sensitive to external shocks than domestic firms (Meriküll and Room 2014)—to the pandemic shock. There is strong evidence that the growth rate for the period of 2020–2022 is much higher than the one for 2019–2021 in terms of both sales and productivity (column 1–6). This is natural such that the latter reflects the impact of COVID-19, while the former shows the developments since COVID-19.

20. The statistics for the endogeneity of the treatment suggests that the treatment and firm performance can be correlated even conditional on the control variables. The estimated correlation between the treatment-assignment errors and the outcome errors, Rho, is positive in all models. The likelihood ratio test (LR test for Rho=0) rejects the null hypothesis of no correlation between the errors of the treatment and performance equations.9

21. Limiting the estimation sample only to SMEs does not significantly change these results, except for export orientation and exporter’s R&D effort (Table 4). The coefficients of export orientation for sales are estimated around -20 percentage points in the SMEs sample (column 1–4), double from the one in the whole sample, and the coefficients of export diversification efforts by R&D turn significantly negative. The two changes suggest that exporting SMEs could be more vulnerable to the pandemic shock than large exporters. On the other hand, efforts for process improvement by exporting SMEs are still associated with better performance, as seen in the whole sample.

Table 4.

Indonesia: Endogenous Treatment Regression: Firm Performance, SMEs Only

article image
Standard errors in parentheses. Estimation is done using survey weights, except for LR test for independent equations. Constant and dummies are not reported. * p<0.10, ** p<0.05, *** p<0.01

F. Conclusions and Policy Recommendations

22. We analyze the determinants of SMEs’ access to finance in Indonesia and factors influencing export diversification and firm performance. Our findings reveal that young, domestically owned firms, and those that face inadequate infrastructure experience significant barriers to financial access, highlighting the challenges that especially smaller firms encounter. Firm age, foreign ownership, and website availability positively affect export diversification. Limited financial access adversely affects sales growth and labor productivity, particularly for domestic firms, although managerial experience can mitigate these effects. Improving access to finance and hence firm performance, could be facilitated by establishing adopting a national credit reporting system strategy and simplification of registration for the collateral registry,10 improving the ease of doing business to stimulate foreign participation, and improving connectivity through infrastructure and digitalization.

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Appendix I. Additional Estimation Results

Table AI.1.

Indonesia: Determinants of Access to Finance, SMEs only

article image
Standard errors in parentheses. Estimation is done using survey weights. Constant and dummies are not reported. * p<0.10, ** p<0.05, *** p<0.01
Table AI.2.

Indonesia: Determinants of Export Diversification, SMEs only

article image
Standard errors in parentheses. Estimation is done using survey weights. Constant and dummies are not reported. * p<0.10, ** p<0.05, *** p<0.01
Table AI.3.

Indonesia: Endogenous Treatment Regression: Firm Performance, First Stage Regression

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Standard errors in parentheses. Estimation is done using survey weights, except for LR test for independent equations. Constant and dummies are not reported. * p<0.10, ** p<0.05, *** p<0.01
Table AI.4.

Indonesia: OLS Regression: Firm Performance

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Standard errors in parentheses. Estimation is done using survey weights. Constant and dummies are not reported. * p<0.10, ** p<0.05, *** p<0.01
1

The size of the enterprises includes small, medium, and large.

2

Two full-time seasonal workers working for 6 months are equivalent to one full-time permanent worker.

3

Foreign-owned enterprises are expected to report lower financing obstacles as they likely have easier access to external financing (Sembenelli and Schiantarelli 1996; and Harrison and McMillan 2003).

4

Weighted average of sales growth for export-oriented firms stood at -7.5 percent in the sample, while that for the non-exporters at 1.5 percent.

5

For estimation results for the first stage equation, see Table AI.3.

6

Ayyagari et al. (2006) uses average value of the financial obstacles for each country-size group as an instrumental variable to mitigate the concern on reverse causality.

7

For instance, Lebastard et al. (2023) shows a negative impact of COVID-19 pandemic shock on French exporting firms and a more persistent impact on GVC participants.

8

During the last three years, has this establishment introduced any new or improved process? These include: methods of manufacturing products or offering services; logistics, delivery, or distribution methods for inputs, products, or services; or supporting activities for processes?

9

Without addressing the endogeneity, the estimates appear to be lower but still significantly negative for sales, while those for productivity become insignificant (Table AI.4).

10

See FSAP (2024).

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Cover IMF Staff Country Reports
Indonesia: Selected Issues
Author:
International Monetary Fund. Asia and Pacific Dept
Volume/Issue:
Volume 2024: Issue 271
Publisher:
International Monetary Fund
ISBN:
9798400284663
ISSN:
1934-7685
Pages:
52
DOI:
https://doi.org/10.5089/9798400284663.002

MSME’s Contribution to Exports, 2023 (In percent)

Credit to MSMEs to Total Credit, 2023

(In percent)

Average MSMEs Credit Interest Rate, 2023

(In percent)

MSMEs Loan by Sector, 2023

(In percent of total loan)

Loan Disbursed to MSMEs by Bank Types, 2023

(In percent of total)

Distribution of Indonesian Firms by Region

(In percent)

Distribution of Indonesian Firms by Sector

(In percent)

Age of The Establishments by Firms’ Size

(In years)

Female Participation by Firms’ Size

(In percent)

Workforce Education by Firms’ Size

(In percent)

Top Manager Experience by Firms’ Size

(In years)

Corruption Index by Firms’ Size

(In percent)

Informality by Firms’ Size

(In percent)

Firms Performance, 2019 to 2021

(In percent)

Firms Performance, 2020 to 2022

(In percent)

Firms Exporting at Least 10 Percent of Sales by Firms’ Size

(In percent of total firms number)

Top 5 Obstacles for Small Firms

(In percent of total firms number)

Top 5 Obstacles for Medium Firms

(In percent of total firms number)

Firms that Spend on Research and Development

(In percent of total firms number)

Firms with New Product/Process is New to The Main Market

(In percent of total firms number)

Annual Expenditure for Machinery, Vehicles, and Equipment

(In percent of sales)

Annual Expenditure for Lands and Buildings

(In percent of total sales)

Firms with A Checking or Saving Account

(In percent of total firms number)

Access to Finance Across Region

Firms with a Checking or Savings Account

(In percent of total firms number)

Main Reasons not to Apply for a Loan

(In percent of firms with insufficient capital)

Relationship with Firm Size 1/ 2/

(Coefficient of a regression of firm size on firm characteristics 3/)
Figure 1.

Indonesia: Financial Access Constraints and Performance, by Ownership and Management Experience