metadata: authors: 0: author: Farazi,Subika
count: World
docna: 0: docna: Informal firms and financial inclusion :
            status and determinants
docty: Policy Research Working Paper
subtopic: Labor Markets,Educational Sciences,Employment and Unemployment,Financial Sector Policy,Access to Finance
teratopic: Industry,Finance and Financial Sector Development
abstracts: cdata!: Many firms in the developing world --
            including a majority of micro, small, and medium enterprises
            -- operate in the informal economy. The informal firms face
            a variety of constraints, making it harder for them to do
            business and grow. Lack of access to finance is often cited
            as the biggest operational constraint these firms face. This
            paper documents the use of finance and financing patterns of
            informal firms, highlights differences between use of
            finance by formal and informal firms, and identifies the
            most significant characteristics of informal firms that are
            associated with higher use of financial services. The
            analysis shows that use of loans and bank accounts for
            business by informal firms is very low and a vast majority
            finances their day-to-day operations and investments through
            sources other than financial institutions (internal funds,
            moneylenders, family, and friends). A majority of informal
            firm owners would like their firms to become formal but do
            not do so as it would require them to pay taxes. Registered
            firms are 54 percent more likely to have a bank account and
            32 percent more likely to have loans. Results also show that
            firm size, the level of education of the owner, and whether
            the owner has a job in the formal sector are significantly
            associated with financial inclusion of informal firms.
repnme: repnme: Informal firms and financial inclusion :
            status and determinants
display_title: Informal firms and financial
            inclusion : status and determinants
listing_relative_url: /research/2014/02/18937100/informal-firms-financial-inclusion-status-determinants
topicv3: Informal Sector m1326258 1168,Education m1327048 470,Financial Inclusion m1327456 363,Access to Finance m1327464 1249,Enterprise Surveys m1504072 2762
publishtoextweb_dt: 2014-02-01T00:00:00Z
historic_topic: Industry,Finance and Financial Sector Development
no_of_pages: 33
author_keys: 0: author_key: 780464
model_extractions: WPS6778 Policy Research Working Paper 6778 Informal Firms and Financial Inclusion Status and Determinants _Subika Farazi_ The World Bank Development Research Group Finance and Private Sector Development Team February 2014
Policy Research Working Paper 6778

# **Abstract**

Many firms in the developing world—including a majority of micro, small, and medium enterprises— operate in the informal economy. The informal firms face a variety of constraints, making it harder for them to do business and grow. Lack of access to finance is often cited as the biggest operational constraint these firms face. This paper documents the use of finance and financing patterns of informal firms, highlights differences between use of finance by formal and informal firms, and identifies the most significant characteristics of informal firms that are associated with higher use of financial services. The analysis shows that use of loans and bank accounts for business by informal firms is very low and a vast majority finances their day-to-day operations and investments through sources other than financial institutions (internal funds, moneylenders, family, and friends). A majority of informal firm owners would like their firms to become formal but do not do so as it would require them to pay taxes. Registered firms are 54 percent more likely to have a bank account and 32 percent more likely to have loans. Results also show that firm size, the level of education of the owner, and whether the owner has a job in the formal sector are significantly associated with financial inclusion of informal firms.

This paper is a product of the Finance and Private Sector Development Team, Development Research Group. 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://econ.worldbank.org. The author may be contacted at sfarazi@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
# **Informal Firms and Financial Inclusion: Status and Determinants**

# **Subika Farazi**<sup>**1**</sup>

Keywords: Informal sector, financial inclusion, firm registration JEL codes: O12, O17, L20 Sector Board: Financial Sector (FSE)

> 1 Development Economics Research Group and Financial and Private Sector Development, The World Bank. Email: sfarazi@worldbank.org. The opinions expressed in this paper do not necessarily represent the views of the World Bank, its Executive Directors or the countries they represent. This paper was prepared as part of the background work for the 2014 Global Financial Development Report. I would like to thank Oya Pinar Ardic Alper, Nancy Claire Benjamin, Miriam Bruhn, Martin Cihak, David McKenzie, Martin Hommes, Anushe Khan, and Claudia Ruiz Ortega for their valuable comments. I would also like to thank Judy Yang and Mohammad Amin who provided very useful insights pertaining to data from the survey of informal firms. The usual disclaimer applies.
# **1. Introduction**

Like its formal counterpart, the informal economy is multi-faceted comprising different sectors or markets and engaging in diverse activities. It can include – but not necessarily be limited to - informal labor markets, informal financial sectors and informal corporate or business sectors. Because of its heterogeneous nature, researchers have found it difficult to come up with a precise single definition of informality. Researchers and policy makers usually tend to focus on a particular definition of informality based on a specific aspect of informality they are interested in analyzing. If for example informality is approached from the social protection point of view then researchers tend to focus on employment and see how some legal requirements (e.g. contributions to pension schemes or social security) are not met. If fiscal considerations of informality are the focus then a more useful definition will look at tax revenue losses associated with firms and individuals engaged in untaxed activities. If on the other hand, accurate estimation of gross domestic product (GDP) is the objective then a more comprehensive definition of informality will be needed.

The commonly used definitions of informality (or informal economy) in the literature include Schneider et al. (2010) that define informal economy as comprising of market-based legal production of goods and services deliberately concealed from public authorities to avoid paying taxes, social security contributions, and to meet legal obligations/requirements and market standards. Smith (1994) defines it as “market-based production of goods and services, whether legal or illegal, that escapes detection in the official estimates of GDP”. Del’Anno and Schneider (2004) and Del’Anno (2003) define informality as those economic activities and the income derived from them that evade government regulation, taxation or observation. Loayza et al. (2009) rely on the definition put forward by de Soto (1989) whereby informal economy is defined as collection of firms, workers, and activities that operate outside legal and regulatory frameworks. One central feature of informal economy observed in these various definitions is that it is unregulated by the institutions of a society. Participants of informal sectors avoid the burden of taxes and regulations but at the same time, do not get a chance to fully utilize the protection and services that the law and the state provide.

Informal activities are a major part of the overall economy in developing countries and deserve attention for a number of reasons. The informal sectors in developing countries are estimated to be around 40-50 percent of official GDP (Schneider et al. 2010). This shows that economic agents working in the informal sector contribute extensively to the overall economic activity. Informal economies are 2
also significant in terms of the labor force they employ. They provide livelihood to large segments of the population and can absorb around 60 percent of the labor force engaged in non-agricultural activities in many developing countries (ILO 2012). Such high levels of informality can have an impact on growth and productivity of a country.<sup>2</sup> Informality can often generate inefficiencies in the production process since firms, in order to avoid detection limit their size to below optimal efficiency scale. They also tend to use less advanced production technologies (Dabla-Norris et al. 2007). The costs they avoid through noncompliance of regulations and tax evasion may help them stay in business despite their low productivity, potentially generating inefficient competition (Perry et al. 2007). Informal firms may also find it difficult to access finance through conventional sources, which can result in sub-optimal levels of investment in physical capital, research, technology and innovation and training programs for improving skills of their employees. Informal workers – which include people working in the informal sector and those employed by the formal sector but working informally, lack social protection, job security, on-job training and insurance. Informality can thus impact their income prospects and productivity. Large informal sectors can also have substantive fiscal implications regarding erosion of tax revenue. A high degree of informality means that for any given level of public expenditure, incomes and profits generated by the formal sector will be taxed at a higher rate (Spiro 2005). Also if public investments in infrastructure have a positive impact on growth then use of already congested public infrastructure for informal activities without contributions towards their replenishment can lower growth (Loayza et al. 2009). Large informal sectors also imply that certain transactions are omitted from official economic statistics rendering macroeconomic indicators vital for policy inaccurate and possibly leading to sub-optimal policy decisions.

On the other hand, informal economies can potentially play a positive role, especially in developing countries where they may be viewed as the nursery of future economic growth in the formal economy (IMF 2012). In economies and business environments mired by overly excessive barriers and poorly designed regulations, informality can provide an alternative to entrepreneurs and small firms. In such situations the absence of an informal sector can result in a far greater waste of resources (Loayza et al. 2009). If costs to start and run a business are binding, the informal sector can benefit firms – to the extent that they may grow to be successful formal sector firms – by helping them avoid excessive costs

> 2 Empirically, it is not very clear whether informality lowers growth and productivity or whether it is a symptom of low growth and productivity.

3
of being formal (e.g. taxes, pension contributions, and minimum wages).<sup>3</sup> Another obstacle formal sector firms might face is the high level of corruption among law enforcement authorities, financial agencies, and regulators. This can increase the cost of creating a new business and staying in business in the formal sector and can make working in the informal sector an attractive alternative (Dutta et al. 2011). The informal sector can also provide buffers against economic uncertainty and underdevelopment in the formal sector as it can provide livelihood to a large number of people. Moreover the incomes generated in the informal sector, insofar they would not have been generated otherwise when spent in the formal sector can provide a boost to the formal economy (Frey and Schneider 2000).

Whether one views the informal sector as a burden or takes it as a sector that contributes positively to the overall economy, there is no doubt that informality is a pervasive and substantive phenomenon in developing countries. It is thus important to explore different aspects of informal economies, especially the working of informal firms. According to the IFC (2012), around 80 percent of total micro, small and medium sized enterprises (MSMEs) are informal today. Firms in the informal sector face a number of challenges that can negatively impact their operations and growth. These challenges can be related to public infrastructure (power, land and water); they can represent weak institutions (property rights, legal protection, and corruption) or lack of access to benefits associated with participation in the formal sector (access to credit, new technologies, and greater visibility of business through publicity). According to data collected by the World Bank through Informal Enterprise Surveys, firms in the informal sector identify lack of access to finance as the biggest obstacle they face (Figure 1).

A lot of recent research around informal firms has focused on understanding different aspects of the business environment that discourages these firms from formalizing. These can include rule of law, property rights, corruption and regulatory requirements for formalization. Previous research has shown that countries with more burdensome entry regulations have larger informal sectors (Djankov et al. 2002). However, many recent randomized experiments which made the formalization process easy, by providing firms with information on how to register and the potential benefits of registration and by lowering costs associated with registration found very few informal firms formalize as a result (de Mel et

> 3 The impact of start-up costs on aggregate productivity is unclear, since high start-up costs will prevent the entry of inefficient firms in the first place (Bartelsman et al. 2004).

4
<!-- Start of picture text --> 40 a7<br>E 30<br>i 25<br>i<br>So<br>Bo | 20<br>£ 15<br>S 11<br>=S40 4 6<br>o<br>Lirnited access Crime, theft Restricted Other Poor public = Corruption<br>tofinance anddisorder access to land infrastructure<br><!-- End of picture text -->
deeper look at issues around financial inclusion of informal firms.<sup>4</sup> In particular, the paper i) documents the use of finance by informal firms and their financing patterns, ii) compares the use of finance by firms both in the formal and informal sector and iii) identifies the most significant characteristics of informal firms that are associated with higher use of financial services.

The analysis in the paper does not provide any causal evidence and attempts to identify significant associations between financial inclusion of informal firms and different firm and country characteristics. Its goal is to add to and complement the literature already available on informal firms, and hopes that readers would interpret the results with the caveat in mind that they do not show causal relationships. Also, it is not claimed that informality is the only barrier firms’ face in their use of finance. Previous literature has identified a number of other factors that affect firms’ use of finance. For example, de Soto's (1989) work focuses on lack of property rights as the reason small firms cannot use their assets as collateral to obtain financing, while Field and Torero (2008) look at the impact of land titling on getting credit. However, as shown in Figure 1, informal firms claim lack of access to finance as the most important barrier they face in their operations and the paper aims to take a deeper look at the dimension of informality and its link to use of finance by firms. The objective of the paper is to provide estimates of actual use of finance by informal firms, while identifying key characteristics significantly associated with financial inclusion and to quantify the differences of use of finance between formal and informal firms.

The rest of the paper is structured as follows. Section 2 explains the methodology used for data collection and describes the dataset used for the analysis. Section 3 provides a snapshot of different characteristics of an average informal firm in the sample to identify any common traits observed among informal firms across different countries. Section 4 provides a comparative analysis of formal and informal firms. This is done in two parts. First, a simple bivariate analysis is done to document the differences in financial inclusion of formal and informal firms. Second, a multivariate regression analysis is done to see the robustness of the results obtained from the bivariate analysis after controlling for a number of firm and country level characteristics. Section 5 provides a regression analysis that explains informal firms’ use of finance and their financing pattern while highlighting the significant factors that are important for financial inclusion of informal firms. Section 6 concludes.

> 4 Financial inclusion is defined as the share of firms that use of financial services (The Global Financial Development Report 2014).

6
# **2. The Data Set**

The paper focuses on one sector of the informal economy, the corporate or business sector and defines informal firms as those firms that are not registered with the registration office, municipality or tax authority. This definition is used by the Enterprise Survey unit of the World Bank and the motivation behind its simplicity is to facilitate the standardization of methodology for data collection and its comparability across countries.<sup>5</sup> The data used in this paper are from World Bank Informal Enterprise Surveys.<sup>6</sup> These surveys collect data on non-registered business activities and are implemented in parallel to World Bank Enterprise Surveys, which interview formal, private, nonagricultural firms. The Informal Enterprise Surveys are conducted using a uniform sampling methodology in order to minimize measurement error and yield data that are comparable across the world’s economies. In each country, the Informal Enterprise Surveys are conducted in two selected urban centers, which are intended to coincide with the locations for the implementation of the main Enterprise Surveys. The overall number of interviews is pre-determined, and the interviews are distributed between the two urban centers according to criteria such as the level of business activity and each urban center’s population. These urban centers are geographically divided to get the sampling areas and Informal Enterprise Surveys are conducted within clearly identified sampling areas. The total number of sampling areas and the geographical areas they contain are chosen such that firms from different sectors have balanced representation.<sup>7</sup> Moreover the placement of sampling areas in each city is determined based on local knowledge regarding the concentration of informal business activity.

The format of both surveys is very similar with a number of overlapping questions. In terms of differences between the two surveys, the first major difference is that of country coverage. Informal Enterprise Surveys do not cover as many countries as covered by Enterprise Surveys. While Enterprise Surveys cover small, medium and large firms, the Informal Enterprise Surveys do not include any large-

> 5 Defining informality in such a simple way can result in loss of important information about the firms we want to study and understand. For example, firms might be registered for imports and pay import taxes, but not be registered for sales or income taxes. Similarly there can be firms that are registered and pay fees to local market administrators but not be registered with other authorities. Nevertheless, the paper has to follow the definition used by the database utilized for the analysis and readers, while interpreting the results should keep in mind the caveat about this definition.

> 6 The Informal Enterprise Surveys are a good source of data on informal firms and deserve credit for making such data readily available for a cross-section of countries. Still, additional efforts are needed to improve the quality and availability of data on informal enterprises. The National Statistics Departments of countries should increase their effort to collect data on the informal sector to gain a better understanding of different interventions that would be most appropriate for the sector.

> 7 The sample by design has equal number of firms from services and manufacturing sectors.

7
<!-- Start of picture text --> a BssA4 554<br>BLAC<br>wLac<br><!-- End of picture text -->
<!-- Start of picture text --> 0.04 (2012)<br>Low Mid<br><!-- End of picture text --> <!-- Start of picture text --> BE Micro (0-5<br>employees)<br>BSmall (6-20<br>employees)<br><!-- End of picture text --> <!-- Start of picture text --> M25<br>Bétolo<br>ee 15<br>q @litols<br><!-- End of picture text -->
<!-- Start of picture text --> 50 46 a7 av<br>39<br>40 36<br>a 3a a2<br>—<br>= 25<br>—_<br>o<br>Be 20<br>a<br>e<br>oa<br>2 10<br>a<br>a<br>a<br>Micro Small <=l0 years >10 years SSA LAC Yes No<br>Size Age Location Like to register<br><!-- End of picture text -->
major constraint.<sup>9</sup> A greater percentage of firms in the SSA region (47 percent) identify access to finance as a major obstacle. For LAC region, this number is around 25 percent. Lastly, firms are categorized according to their desire to get registered. The figure shows that in comparison to firms with no desire to register (32 percent), a higher proportion of firms cite lack of access as a constraint among the group that wants to register (47 percent).

The section now presents an analysis that looks at some of the features of informal firms across countries. Even though the sample at hand is not entirely representative of the informal sectors in the respective economies, we think it is important to have an overall look at some of the basic characteristics of informal firms to get a better sense of how they look like.

Table 1 provides a summary of features of informal firms in the sample and the first panel looks at some of the more general firm characteristics. As already highlighted in the previous section, majority of informal firms are micro-sized (89 percent), employing not more than 5 people. Also, most of them are 10 years of age or younger (74 percent of the sample). In terms of level of education around 6 percent of firm owners have no education, implying that most of the owners have some level of education or vocational training. Around 8 percent of firm owners have a job with an established formal sector business.<sup>10</sup> The next panel highlights the level of use of finance by informal firms. Around 23 percent of firms identify having a bank account to run their business, while only 11 percent claim having a loan.<sup>11</sup> Not surprisingly, majority of informal firms use internal funds, families or moneylenders (MLs) for financing purposes. This amounts to 80 percent working capital financing and 84 percent investment financing from these sources.

> 9 Despite some similarities, the LAC and SSA environments for informal sectors are significantly different. Factors that can improve business conditions and inclusion for informal firms will be substantially different in the two regions. Same can be said about each specific country in the sample. However the objective of the paper is to provide readers with an overall picture of financial inclusion of informal firms and has attempted to take into account regional and country level differences in the analysis presented later.

> 10 Unfortunately the surveys do not provide any information regarding the status of their job with formal sector business. We do not know if they work informally with the formal business or whether they work as formal employees.

> 11 Even though the paper equates financial inclusion with the use of bank accounts and loans, these two financial products are can be quite different as far as financial inclusion is concerned. For example, countries might require firms to open bank account as part of ‘starting a business’ (see footnote 13 for country examples), so having a bank account may not necessarily translate into financial inclusion per se.

11
|General Charateristics|Firms<br>(%|
|---|---|
|Sige -Mera (0-5 emplovecs}|ag|
|Age-<br>Tdveers orless||
|Level of education oflargest owner -No Education|6|
|Largest ownerhaz ajobin aformal business<br> <br>|8<br>|
|Use ofFinance<br>|Po|
|Use of accounts|2a|
|Use ofloans|11|
|Working capital finance -Jnternal funds, familyand money lenders|80|
|Investmentfinance - Internal funds, famulyand money lenders<br><br>|54<br>|
|Business Registration<br>|Po|
|Registered at startup|4|
|Like to register|5g|
|Mainreasonfornotregistering - Texes|26|
|Mostimportantbenefitfromregistering-Accesstofinence|52|
|GeneralCharateristics|MicroFirms (%) ||StaalFirms (%|
|---|---|---|
|Age- Ittyearsarless|74|7|
|Level ofeducation oflargestowner -NoEducedon|||
|Largestownerhas ajobinaformalbusiness<br>|?<br>|14<br>|
|UseofFinance|||
|<br>Use ofaccounts|19|D3|
|Use ofloans|11|11|
|Working capitalfinance - Internal funds, fomily and moneylenders|al|70|
|Investmentfinance<br>- Internal funds, familyand money lenders|BG|76|
|BusinessRegistration||a|
|Registered atstartup|3|6|
|Like toregister|o4|72|
|Mainreasonfornotregistering|ab [Taxes]|29 (Information)|
|Mostimportantbenefitfromregistering-Accesstofinance|50|58|
|General Charateristics|LACFirms<br>(%p|SSAFirms (%|
|---|---|---|
|Size -Micro (0-5employees)|48|Bl|
|Age- I0-veers arless|||
|Level ofeducation oflargestowner -No£ducetion|5|8|
|Largest ownerhas ajob inaformal business<br>|4<br>|12<br>|
|UseofFinance|r|r|
|<br>Use of accounts|b|30|
|Use ofloans|14|3|
|Working capitalfinance - Internal funds, femilyand moneylenders|af|75|
|Investmentfinance - /nternalfunds, familyand money lenders<br>|AB<br>|Da<br>|
|BusinessRegistration|||
|Realstered at startup|4|3|
|Like to register||59|
|Mainreasonfornotregistering - Taxes||26|
|Mostiraportantbenefitfromregistering-Accesstafinance||52|
|GeneralCharateristics|Wanttoregister (4)||Donotwanttoregister (4|
|---|---|---|
|Size -Micro (0-5employees}|69|ag|
|Age - [0vearsorless|78|fh|
|Level ofeducation oflargestowner -NoEducation|il|8|
|Largestownerhas ajobinaformalbusiness<br>|18|10|
|UseofFinance|||
|<br>Use of accounts|47|a4|
|Use ofloans|7|6|
|Working capital finance - /nternal funds, family and moneylenders|71|fh|
|Investment finance - Intertal funds, femilyand moneylenders<br>|85|a5|
|BusinessRegistration|||
|<br>Registered atstartup|1|6|
|Mainreasonfornotregistering|32 (Information)|42 (Nobenefit)|
|Mostimportantbenefitfromregistering<br>-Accesstofinance|58|4g|
# **4. Use of Finance: Formal vs. Informal Firms**

This section first presents some basic bivariate analysis to document the differences in use of finance, financing patterns and reasons for not applying for loans between formal and informal firms. The section then presents multivariate regression analysis that builds upon and strengthens the conclusions obtained from the bivariate analysis. This analysis verifies whether differences in the use of finance by firms based on their registration status hold once various firm level and country level characteristics are controlled for.<sup>15</sup> Data pertaining to formal firms is obtained from the Enterprise Surveys. To make the comparison between formal and informal firms more aligned and meaningful, only small-sized firms from the 13 countries in the original sample are used from the Enterprise Surveys. This results in a sample of approximately 1500 formal firms. Similarly the sample on informal firms is also restricted to small-sized firms only. Also for each country in the sample, it is made sure that the year in which surveys for both formal and informal firms were conducted is similar.

# **_4.1    Bivariate Analysis_**

Looking at the use of bank accounts by firms, Figure 9 shows that on average 53 percent of informal firms have bank accounts to run their business compared with 86 percent of firms in the formal sector. These percentages highlight a significant difference in the use of bank accounts between registered and non-registered firms. Figure 9 shows a similar picture for use of loans by firms in the formal and informal sector.<sup>16</sup> Only 12 percent of firms in the informal sector have loans compared to 47 percent formal sector firms.

> 15 The analysis in this section shows a positive correlation between formalization and financial inclusion and besides confirming our a priori knowledge, the results obtained quantify for the first the differences between the use of finance among formal and informal firms for a cross-sectional sample of countries. 16 For formal sector, loans include loan and/or an overdraft facility from a financial institution. Loans for informal firms refer to loan from any of the following source: Bank, moneylenders, MFIs and trade credit.

16
<!-- Start of picture text --> 100<br>86 Bi Informal Bf Formal<br>£0<br>wi<br>E<br>= 60<br>o<br>w 47<br>i<br>=<br>o 40<br>a<br>u<br>io<br>20<br>0<br>Bank Accounts Loans<br><!-- End of picture text -->
<!-- Start of picture text --> 80<br>7O<br>@ Informal @ Formal<br>63<br>u 60<br>=<br>=<br>—<br>a<br>a 40<br>=<br>2 23 24 24<br>a 20<br>* 6<br>o<br>Internal Funds/ Trade Credit Banks MIFIS/NBFIs<br>Family! Moneylenders<br><!-- End of picture text --> <!-- Start of picture text --> 80 76 Informal @ Formal<br>65<br>uw 60<br>E<br>=<br>—<br>a<br>ao 40<br>&<br>[<br>is 24<br>m<br>ao 70<br>a<br>Internal Funds,’ Trade Credit Banks MIFIs/NBFIS<br>Family Moneylenders<br><!-- End of picture text -->
<!-- Start of picture text --> 20<br>18<br>17 17<br>16<br>15<br>wE 12 12<br>=<br>vat=]<br>mp 10<br>= & &<br>wu<br>pa<br>wu<br>=<br>5 4 ‘\<br>0<br>Complex Highinterest Lacking Not Other High interest High Complex Wouldn'tbe Informal Losn size<br>applications rates guamtees registered rates collateral applications approved paymentstoand maturity<br>Informal Formal getloans bank<br><!-- End of picture text -->
# FIic = ac + b1Registeredic + b2Fic + b3Xic+ eic

where _FI_ is an indicator of financial inclusion for firm _i_ in country _c_ . _FI_ indicators are binary variables and are proxied by i) firms with bank accounts (equals 1 if firm has an account and 0 otherwise), firms with loans (equals 1 if firm has a loan and 0 otherwise) and iii) different sources firms use for financing working capital (equals 1 if firm uses a given source and 0 otherwise). _Registered_ , is a dummy variable which equals 1 if firm _i_ in country _c_ is registered and 0 otherwise. Firm and country level control variables are represented by _F_ and _X_ . Besides registered dummy variable, other firm level controls include: _age_ , which is the logarithm of firm age; _female owner_ , equals 1 if firm’s largest owner is a female and 0 otherwise and _manufacturing_ , equals 1 if firm works in the manufacturing sector and 0 if it is part of the services sector. Country level variables include private credit to GDP and financial freedom as proxies of financial sector development and contract viability, law and order, and property rights to proxy for quality of legal framework.<sup>17</sup> The regressions also control for a regional dummy, LAC which equals 1 if firm is located in LAC region and 0 if it is in the SSA region. Country fixed effects are captured by ac. Table A1 in the appendix presents detailed definition and sources of variables used in the analysis.

Regression results are reported in Table 5. The way results are presented is that in each column the coefficients of firm level variables and regional dummy variable correspond to a regression which controls for country dummies and no country level variable. The results reported for each country level variable (private credit to GDP, financial freedom, contract viability, law and order, and property rights) represent a separate regression that controls for a specific country level variable and no country dummies. Since all the dependent variables are binary in nature, a probit model is estimated and marginal effects are reported.

Results in Table 5 confirm the results of the bivariate analysis and show that registered firms have higher financial inclusion, both in terms of bank accounts and loans. In particular, first two columns of Table 2 show that registered firms are 54 percent more likely to have bank accounts and 32 percent more likely to have loans.<sup>18</sup> These results hold even after controlling for firm level characteristics like gender of the owner, age and activity of firms and country level factors like the level of financial

> 17 Country level variables controlling for institutional quality and financial freedom, which are based on assessments of “industry experts” may not necessarily include viewpoint of the informal sector. 18 To check the robustness of results for accounts as a dependent variable, separate regressions were estimated for a sample excluding countries that have paid-in minimum capital requirement (see footnote 13). The results obtained are very similar to those shown in Table 2 and hence are not reported. They are available from the author upon request.

20
||||Sources ofFina|ncing Worki|ng Capital|
|---|---|---|---|---|---|
||Bank Account|Loan||||
|Registered|0.54°TM|0.32"|4.137"|0.15°*|4.09*|
||(O.71)|(5.64)|(2.95)|(3.67)|C175)|
|Female OQwner/Decision Maker|0.01|0.04|0.02|0.02|0.01|
||(0.75)|(1.56)|(0.80)|(0.87)|(-0.55)|
|Manufacturing|0.0001|4.06TM|4.08"|0.005|0.04*|
||(0.04)|¢2.20)|(2.63)|(0.23)|(12)|
|Li Age|0.02|0.02|0.002|0.01|0.03*|
||(1.973|(1.13)|(0.10)|(0.43)|(1.86)|
|Lac Region|0.51°*|0.26°*|0.10"|0.05|0.22"|
||(5.73)<br>|(2.67)<br>|(2.75)<br>|(0.72)<br>|21)<br>|
|Private CredittoGDP|4.0009<br>|0.003*+<br>|4.00007<br>|0.002<br>|4.003<br>|
||C1215<br>|(4.32)<br>|-0.03)<br>|(2.99)<br>|(3.45)<br>|
|Financial Freedom|0.001<br>|0.004-*<br>|4.003"<br>|0.0057*<br>|0.0006<br>|
||(-1.60)<br>|(4.31)<br>|(2.54)<br>|(6.115<br>|(0.673<br>|
|ContractViabilityExpropriation|0.14°TM|4.03|0.01|0.02|-0.04*|
||(-F.S5)<br>|-1.413<br>|60.25)<br>|(1.33)<br>|1.913<br>|
|Law and Order|0.13°=<br>|0.11°*<br>|.06*<br>|0.13°*<br>|0.0007<br>|
||(8.30)|(5.15)|(3.19)|ray|(0.04)|
|PropertyRights|0.001<br>|0.004"<br>|4.001<br>|0.0047<br>|4.002*<br>|
||(-1.55)|(3.25)|(0.83)|(4.53)|61.73)|
|PseudoR2|o.21|0.19|0.08|0.10|o.12|
having bank accounts and loans. It is also positively associated with the use of banks for financing working capital, while it shows a negative association with the use of internal funds, families or moneylenders. Among variables used to proxy for strength of the legal framework, law and order shows the most robust results. It is on average positively correlated with the use of bank accounts, loans and bank financing for working capital. It is negatively associated with the use of internal funds/families/moneylenders for working capital financing.

# **_5._ Use of Finance by Informal Firms**

This section presents a multivariate regression analysis to study the use of finance by informal firms. The sample used includes micro and small-sized firms. The regression analysis controls for different firm level and country level variables, most of which were used in the analysis presented in the previous section. Also, the specification used in the previous section is utilized again for the analysis of informal firms. However, the dummy variable capturing the registration status of firms is excluded. This gives us the following specification: where _FI_ represents indicators of financial inclusion for firm _i_ in country _c_ . These indicators are proxied by i) firms with bank accounts, ii) firms with loans and iii) different sources firms use for financing working capital. The dependent variables are binary in nature and follow the definition provided in the previous section. Firm and country level control variables are represented by _F_ and _X_ . Firm level controls include: _age_ , which equals to the logarithm of firm age; _female owner_ , equals 1 if firm’s largest owner is a female and 0 otherwise and _manufacturing_ , equals 1 if firm works in the manufacturing sector and 0 if it belongs to the services sector. Three additional firm level variables are introduced which include _micro_ , _owner’s education_ and _owner’s job in formal sector_ . Micro captures the size of a firm and equals 1 if firm is micro-sized and 0 if it is small-sized. Owner’s education equals 1 if owner of a firm has secondary school, university training or vocational training and 0 otherwise (= no education or primary education). Owner’s job equal 1 if firm’s owner has a job with an established formal sector business and 0 otherwise. Country level variables used are the same that were used in the previous section and include proxies of financial sector development and quality of legal framework. Regressions also control for a regional dummy, LAC which equals 1 if firm is located in LAC region and 0 if it is in the 22
<!-- Start of picture text --> Use of Bank Accounts<br>(1) (2) (3) (4) (S) Li]<br>Micro -0.16%* * -O.1 7 #** -0.18*** -0.16*** -0.16*** -O.19***<br>(-5.544 (-5.904 (-6.56) (-5.73) (-5.55) (-6.60)<br>Owner's Education 0.10*** 0.08 *** 0.05 *** 0.07 *** 0.07 *** 0.05 ***<br>(-4.594 (-231) (-229) (-3.75) (-3.92) (-.58)<br>Owner's Job in Formal Sector 0.06* o.08** 0.09*** 0.13*** O.12*** 0.09**<br>(-1.76) (-2.34) (-2.58) (-3.58) (-3.34) (-2.55)<br>Lig Age 0.003 0.002 0.0035 0.01 0.005 0.003<br>(-0.354 (-0.21) (-O.31) (-0.60) (-0.28) (-0.36)<br>Female OwnerDectision Maker -0.01 -0.01 -0.01 -0.005 -0.0003 -0.01<br>(-0.353 €-0.813 (-O.37) €-0.25) €-0.02) (-0.34)<br>Manufacturing -0.01 0.004 -0.01 -0.004 o.0035 -0.01<br>(-0.524 (-0.20) (-0.48) (-O.21) -0.16 (-0.38)<br>Lac Region -0.16 %* * -O..2 7 ee -0.20%*** -0.26*** -0.26*** -O.27 ***<br>(-3.514 (-12.75) (-14.28) (-11.69) (-11.76) [(-13.29)<br>Private Credit to GDP 0.00***<br>(-3.413<br>Financial Freedom o.003***<br>(-4.46)<br>Contract ViabilitExpropriation 0.05 ***<br>(-3.83)<br>Law and Order o.02*<br>(-Ley7)<br>Property Rights 0.002 ***<br>(-3.15)<br>Pseudo R2 O.21 O.21 0.19 O.22 O.21 0.19<br><!-- End of picture text -->

||||Use of Bank|Accounts|||
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(S)|Li]|
|Micro|-0.16%* *|-O.1 7 #**|-0.18***|-0.16***|-0.16***|-O.19***|
||(-5.544|(-5.904|(-6.56)|(-5.73)|(-5.55)|(-6.60)|
|Owner's Education|0.10***|0.08 ***|0.05 ***|0.07 ***|0.07 ***|0.05 ***|
||(-4.594|(-231)|(-229)|(-3.75)|(-3.92)|(-.58)|
|Owner's Job in Formal Sector|0.06*|o.08**|0.09***|0.13***|O.12***|0.09**|
||(-1.76)|(-2.34)|(-2.58)|(-3.58)|(-3.34)|(-2.55)|
|Lig Age|0.003|0.002|0.0035|0.01|0.005|0.003|
||(-0.354|(-0.21)|(-O.31)|(-0.60)|(-0.28)|(-0.36)|
|Female OwnerDectision Maker|-0.01|-0.01|-0.01|-0.005|-0.0003|-0.01|
||(-0.353|€-0.813|(-O.37)|€-0.25)|€-0.02)|(-0.34)|
|Manufacturing|-0.01|0.004|-0.01|-0.004|o.0035|-0.01|
||(-0.524|(-0.20)|(-0.48)|(-O.21)|-0.16|(-0.38)|
|Lac Region|-0.16 %* *|-O..2 7 ee|-0.20%***|-0.26***|-0.26***|-O.27 ***|
||(-3.514|(-12.75)|(-14.28)|(-11.69)|(-11.76)|[(-13.29)|
|Private Credit to GDP||0.00***|||||
|||(-3.413|||||
|Financial Freedom|||o.003***||||
||||(-4.46)||||
|Contract ViabilitExpropriation||||0.05***|||
|||||(-3.83)|||
|Law and Order|||||o.02*||
||||||(-Ley7)||
|Property Rights||||||0.002 ***|
|||||||(-3.15)|
|PseudoR2|O.21|O.21|0.19|O.22|O.21|0.19|
||||Use of|Loans|||
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Micro|-0.03|0.0006 *|-0.03|-0..02|10.102|-'0..03|
||(-1.09)|(-2.24)|(-1.29)|(-0.87)|(-0.69)|(-1.27)|
|Qwner's Education|10.106 FFF|0.02|0.06* **|0.06***|0.05***|10.1006 °F|
||(-3.99)|(-1.26)|(-3-91)|(-3.53)|(-2.83)|(-4.27)|
|Owners Job in Fonmal Sector|0.017<br>|0.04<br>|O.01<br>|0.02<br>|0.02<br>|O.01<br>|
||(-0.28)|(-1.29)|(-0.50)|(-0.69)|(-0.65)|(-0.40)|
|Ln Age|0.01|0.01|0.01*|o.01*|0.01|0.01**|
||(-1.54)|(-1.46)|(-1.89)|(-1.84)|(-1.44)|(-2..00)|
|Female Owner/Decision Maker|0.03*|0.03**|0.03**|0.03**|0.03**|0.03**|
||(-1.93)|(-2..06)|(-2.12)|(-2.07)|(-2.08)|(-2.16)|
|Manufacture|-0.007<br>|-0.01<br>|0.01<br>|0.0<br>|10.0 F<br>|0.101<br>|
||-0.06|(-0.53)|-0.42|(-0.14)|-'0.23|-0.44|
|LAC Region|10.00|0.08|0.06***|0.08***|o.07***|0.008"<br>**|
||(-4.53)|(-1.53)|(-4.22)|(-4.33)|(-3.74)|(-4.92)|
|Private Credit to<br>GDP||0.001*|||||
|||(-1.87)|||||
|Financial Freedom|||0.002***||||
||||(-4.99)||||
|Contract Viability/Expropration||||oO.04+**|||
|||||(-3.32)|||
|Law and Order|||||0.03***||
||||||(-3.21)||
|Property Rights||||||o.001***|
|||||||(-3.12)|
|PseudoR2|0.09|0.04|0.06.|0.04|0.05|o.04|
|InternalFamiyyML|s<br>Banks<br>|Trade Credit|MFIs|
|---|---|---|---|
|Micro<br>0.01|-0.07***|-0,.03|-0.04***|
|(-0.32)|(-3.24)|(-1.27)|(-2.68)|
|Owner's Education<br>-0,.06***|0.01|0.03*|0.01|
|(-2,66)|f-1.08)|(-1.65)|(-1.33)|
|Owner's Job in Formal Sector<br>-0.07 *|0.04**|0.04|0.01|
|(-1,93)|(-2.08)|f-1.06)|(-0.70)|
|Lng Age<br>-0.02**|0.002|0.01|0.01 **|
|(-2,32)|f-0.56)|(-1.44)|(-2.06)|
|Female Owner Decision Maker<br>0.05**|-0.001|-0.02|0.01|
|(-2,34)|f-0.13)|(-1.49}|(-0.91)|
|Manufacturing<br>-0.04*|-D.002|0.02|0.01|
|(-1.81)|f-0.29)|(-1.43)|(-0. 78)|
|LAC Region<br>0.12***|0.05**|-0.02|0.0003|
|(-5,58)|f-2,06)|(-0.36)|f-0.01)|
|Private Credit to GDP<br>-0.002***|0.002***|0.001**|0.00027|
|(-2,78)|(-5,18|-2,06)|f-0.53)|
|Financial Freedom<br>-0,004***|0.002***|g9.003***|O.001***|
|(-5.52)|{-4,96)|(-5,26)|{-4,35)|
|Contract Viabilitviexpropriation<br>-0.05***|0.02***|0.04***|0.03***|
|(-3,33)|(-2,.89)|(-3.16)|(-4,30)|
|Law and Order<br>-0.05***|0.02***|0.03***|0.02***|
|(-4,60)|(-2,64)|(-3.36)|(-2.83)|
|PropertyRights<br>-0.002**|0.001 ***|0.001 ***|0.0004*|
|(-2,52)|f-4,54)|(-2,79)|(-1.75)|
|PseudoR2<br>a.08|0.08|0.09|a.o9|
Column 1 of Table 8 reports results pertaining to use of internal funds, families and moneylenders as a source of working capital financing. Estimates show owners with more education and a job in the formal sector are less likely to rely on these sources. With more developed financial and legal systems, reliance on these sources also decreases. Next, column 2 shows results for bank financing. Likelihood of a firm using bank financing decreases if it is micro-sized, while owner’s job in the formal sector and country’s level of financial and legal sector are positively associated with using banks for financing. Correlation between trade credit financing and firm level characteristics are not very strong; however, it is positively associated with owner’s level of education and financial and legal sector development of a country. MFI financing is also positively associated with level of owner’s education and financial and legal sector development of a country. MFI financing is negatively associated with firm size.

# **6. Conclusion**

The objective of the paper was first, to document salient features of informal firms, their use of finance and their financing patterns. Second, to compare and quantify the differences that exist in the use of finance by firms in the formal and informal sector, and lastly to identify the most significant characteristics of informal firms that are associated with higher financial inclusion. The paper utilizes data on informal firms collected by World Bank’s Enterprise Surveys.

The analysis shows that firms in the informal sector are on average micro-sized and relatively younger, less than 11 years of age. Most of the owners of informal firms have some form of educational or vocational training and a very small proportion have jobs in an established formal business. Use of loans and bank accounts for business by informal firms is very low and a significant majority of firms finance their day-to-day operations and investments through sources other than financial institutions (internal funds, moneylenders, family and friends). Most of the firms would like to register but tend not to opt for it due to tax reasons and state that relatively easier access to finance would be the most important benefit they could obtain from registering.

A comparative analysis between formal and informal small-sized firms shows, not surprisingly, a higher use of bank accounts and loans by registered firms. Firms in the formal sector are 54 percent more likely to have a bank account and 32 percent more likely to have a loan. On average, registered firms rely less on internal funds, families and friends and on moneylenders for financing their working 26
capital and their use of bank financing is higher in comparison to informal firms. These results hold even after controlling for various firm level and country level characteristics.

The paper also shows that firm size, the level of education of the owner and whether the owner has a job in the formal sector are significantly associated with financial inclusion of informal firms. Micro firms vis-à-vis small firms have lower use of bank accounts, rely less on banks and more on microfinance institutions for working capital financing. Size is not significantly associated with the use of loans. Owner’s level of education and whether he/she has a job in the formal sector are positively associated with the use of bank accounts and negatively associated with the use of internal funds and financing from family and moneylender for working capital. Higher education levels of owners are also positively associated with the use of loans by informal firms.

The results presented in this paper highlight correlations that hold on average, however, informal sector firms are very diverse. Some firms might be part of the informal sector due to necessity while others operate in this sector because of an opportunistic entrepreneurial activity (see for example Brhun, 2013). Therefore the way firms operate and how willing would their owners be to become integrated into the formal economic and financial system in the future would differ a lot. Also, the factors that firms consider important in their decision to formalize may vary as well. Recent research has highlighted that registration costs and knowledge of registration procedures are not particularly important for firms while deciding whether to formalize (de Andrade, Bruhn and McKenzie 2013 and De Giorgi and Rahman 2013). It might be true that variable costs associated with becoming formal like tax payments (as pointed out in the present analysis) are considered more important by informal firms. Unless firms that are interested in entering the formal sector grow and become profitable enough to cover such costs it would be very difficult for them to formalize. Enhancing financial inclusion of informal firms interested in registering can potentially help them grow and pave their path toward formalization.

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