The Impact of Credit Crunch on Enterprise Financing in Emerging                              Markets: Does Firm Size Matte...
BAFA 2011 Conference at Aston Business School and BAFA North 2011 at University ofSalford, for useful comments and suggest...
Our study also links the BEEPS measure of financing constraints with relative changes in thecomposition of investment fina...
The required funding was also difficult to raise via bank borrowing given theunderdeveloped and inefficient financial syst...
Belarus,Kyrgyzstan, Tajikistan and Uzbekistan) in both areas of the financial institutionalreforms. Overall, after the yea...
finance was an obstacle to their operations and the averages for the individual countries inthe dataset are shown in Figur...
According to Cull (2007) trade credit can be seen as substitute for loans for private firms’trading partners that are shut...
the firm (Arnold 2008). More recent literature on firm financing started to look closer at, andemphasize the importance of...
and it would be very important for them to try and hedge against these risks. Zou and Adams(2008) look at the effect of pr...
same time, as larger firms use more finance and tend to rely more on external funding theymay be hit harder by financial c...
3.3 Firm- and industry- level factors      As far as the firm-level and industry-level variables are concerned, we expect ...
we concentrate on two institutional factors: the degree of protection of property rights and thesize of the formal financi...
4.1 Sample      To explore the determinants of the financial structure of small businesses, we use the2002-2009 Business E...
To test our main hypothesis of the effect of a firm size on firms’ perception of financialconstraints we introduce a dummy...
considered to be superior to other indicators, including the index of property rights reportedby the Heritage Foundation –...
In this study we employ a number of estimators to obtain robust results. Morespecifically, we use a probit model to invest...
equity) using a SURE framework within which we specify a set of five tobit regressions withcorrelated residuals.     We em...
Finally, In Table 6 we attempt to condition the determinants of financing constraintsdeclared by SMEs on the relative perc...
the last crisis. We could explain this striking difference by the peculiarities of the SMEsfunctioning in new emerging eco...
in the period of crisis. While the latter finding is partly in line with some other studies – suchas Klapper and Randall (...
Pressure from domestic competition and customers on a firm to develop a newproduct, which may be a characteristic of oligo...
6. Conclusions      Our key results may be summarized as follows.      Consistent with the literature smaller businesses g...
times. However, in the situation of external shocks and financial contraction, the authoritiesshould focus on promoting tr...
Private Equity and Debt Markets in the Financial Growth Cycle, Journal of Bankingand Finance, 22, 613–73.Berglof, E. and B...
International Review of Economics and Finance, 16, 400-415.Didier, T, Hevia, C., and Schmukler, S.L. 2011. How Resilient W...
Klapper, L. F. and Randall, D. 2010. “The Impact of the Financial Crisis on Supply-ChainFinancing”. World Bank Group. Ente...
Pissarides, F. ,1998. Is Lack of Funds the Main Obstacle to Growth? EBRD Working PaperNo. 33.Pissarides, F. 1999. Is Lack ...
Welter, F. and D. Smallbone, 2011. Institutional Perspective on Entrepreneurial Behaviour inChallenging Environments. Jour...
Figure 1: Domestic Credit to Private Sector (as % of GDP) in Transition Economies andComparator Countries selectively, 199...
200.00 180.00 160.00 140.00 120.00 100.00  80.00  60.00  40.00  20.00   0.00               1991   1993           1995   19...
Figure 3: Percentage of SMEs vs Large firms that perceive access to finance as a majorobstacle in operating business, 2002...
Figure 4: Sources of financing SMEs’ investmentsSource: Authors’ calculations based on BEEPS 2002 09. Respondents were ask...
Table 1: Descriptive statistics and definitions of variables   Variable                            Definition             ...
Private loan          Private loan as a % of firm financing of fixed     12.68   27.63   13,246                      asset...
Table 2: Correlation Matrix for the dependent and macro-level variables    Variables      Percep.     Retained   Private  ...
Table 3 Perception of Financial Constraints: probit estimation results and marginal effectsDependent variable:            ...
Table 4. SURE Tobits results for Firms’ Financing Choices (based on whole sample)Dependent variable          Retained     ...
Paper_The Impact of Credit Crunch on Enterprise Financing in Emerging Market: Does Firm Size Matter
Paper_The Impact of Credit Crunch on Enterprise Financing in Emerging Market: Does Firm Size Matter
Paper_The Impact of Credit Crunch on Enterprise Financing in Emerging Market: Does Firm Size Matter
Paper_The Impact of Credit Crunch on Enterprise Financing in Emerging Market: Does Firm Size Matter
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Paper_The Impact of Credit Crunch on Enterprise Financing in Emerging Market: Does Firm Size Matter

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NES 20th Anniversary Conference, Dec 13-16, 2012
Article "The Impact of Credit Crunch on Enterprise Financing in Emerging Market: Does Firm Size Matter?" presented by Yulia Rodionova at the NES 20th Anniversary Conference.
Authors: Julia Korosteleva, Natalia Isachenkova and Yulia Rodionova

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Paper_The Impact of Credit Crunch on Enterprise Financing in Emerging Market: Does Firm Size Matter

  1. 1. The Impact of Credit Crunch on Enterprise Financing in Emerging Markets: Does Firm Size Matter? Julia Korostelevaa , Natalia Isachenkovab and Yulia Rodionovac a Dr Julia Korosteleva, Lecturer in Business Economics, Department of Social Science, Schoolof Slavonic and East European Studies, University College London, 16 Taviton Street, London, WC1H0BW, UK; tel.: + 44(0) 20 7679 7590; e-mail: j.korosteleva@ucl.ac.uk (corresponding author). b Dr Natalia Isachenkova, Faculty of Business and Law, Kingston University London, Kingston Hill, Kingston upon Thames, Surrey, KT2 7LB, United Kingdom, tel.: +44(0) 20 8547 8206, Fax: +44(0) 20 8547 7026; e-mail: n.isachenkova@kingston.ac.uk c Dr Yulia Rodionova, Senior Lecturer in Finance, Department of Accounting and Finance,Leicester Business School, De Montfort University, The Gateway, Leicester, LE1 9BH, UK; tel: +44 (0)11 6257 6098; e-mail: yrodionova@dmu.ac.uk . This draft 30 January 2012 Abstract Using panel data on 21,867 firms from the 2002-2009 Business Environment andEnterprise Performance Surveys (BEEPS) we examine how firm-level characteristics andeconomy-wide institutional settings influence firms’ perceptions of financial constraints andtheir choices of investment finance. The data enables a perspective on the effects of theglobal financial crisis that in 2008 hit hard the emerging markets of Europe and Central Asia.Our analysis of relative percentages of types of investment finance used by the small andmedium-sized firms (SMEs) in the region, vis-à-vis the financing mix of large firms, points toa greater flexibility of the SMEs in responding to a sharp credit supply shift: smaller firms areable to respond by increasing relative percentages of alternative financing sources such astrade credit and external equity. As evidenced by the BEEPS data, in the midst of the globalcredit crunch, differences between small and large firms in the degree to which firms saythey are constrained are largely eliminated. Tests confirm that it is switching to trade credit ata time of crisis that can soften financing constraints. In particular, the relative percentage oftrade credit in the financing mix appears to pick up a significant difference in perceivedfinancing constraints across the size categories and positively affects the propensity of SMEsto declare themselves as less financially constrained.Keywords: financing constraints, SMEs’ financing choices, trade credit, crisis.Acknowledgements: We are enormously grateful to David Roodman for his invaluableadvice on the technical part of the project. We also thank Mike Adams, David Crowther, JohnHolland, Stas Kolenikov Fred Mear, Tomek Mickiewicz, Ivan Shaliastovich, Oleh Tsyvinskiand other participants at the BEROC 2010 International Economics Conference in Minsk, 1
  2. 2. BAFA 2011 Conference at Aston Business School and BAFA North 2011 at University ofSalford, for useful comments and suggestions. The usual caveat applies. Yulia Rodionovagratefully acknowledges funding from the De Montfort University ECR Scheme. 1. Introduction Finance availability and cost have been cited as one of the major constraints forsmall and medium-sized enterprises (Beck et al., 2005; 2006; 2008). Given the small scaleof their projects and higher risk associated with the higher asymmetry in information arisingfrom small and medium-sized businesses’ (SMEs) lack of accounting records and crediblereputation, financial institutions find it costly to monitor small businesses, even iftechnological progress particularly in part of the risk scoring techniques have enabled thebanking sector to handle the SMEs’ finance better than in the past (de la Torre et al. 2008). A large body of literature documents that financial constraints hinder SMEs’ growthand development (Klapper et al., 2002, Pissarides et al. 2003; Beck et al. 2005;Gorodnichenko and Schnitzer, 2010). More specifically, Gorodnichenko and Schnitzer(2010) propose the theoretical model showing that financial constraints reduce the ability ofdomestically owned firms to innovate and export with further adverse implications forproductivity growth in the economy. Their empirical results based on the 2002-2005Business Enterprise Environment and Performance Survey data conform to their theoreticalpropositions implying that policymakers should focus on addressing the problem of financialmarket frictions to enhance productivity at both micro and macro levels. Financial constraints may get particularly severe in the period of crisis with small andmedium-sized businesses expected to suffer disproportionally more than their largerbusiness counterparts given the overall financial contraction in the domestic economies (assuggested by the financial accelerator theory of real business cycles) and the inability ofsmaller-sized firms to draw upon the international financial markets. The 2007-2009 globalcredit crunch that severely affected international payments and trade credit hit hard across allthe transition countries, especially the exports and production in Eastern Europe (Calderonand Didier, 2009; Didier et al, 2011). In this paper we analyse the perceptions of financialconstraints of SMEs and the SMEs’ choice of investment finance for the transition economiesover the period of 2002-2009, focusing in particular on the effects of the crisis for SMEsfinancing vis-à-vis large firms. More specifically, using the 2002-2009 Business Environmentand Enterprise Performance Survey (BEEPS) data of 21,867 firms in Emerging Markets ofEurope and Central Asia, we undertake a panel data study to investigate how various firmcharacteristics and institutional settings affect firms’ perceptions of financial constraints. Wefurther analyse the implications of the 2007-2009 financial crisis for SMEs’ financing choices. 2
  3. 3. Our study also links the BEEPS measure of financing constraints with relative changes in thecomposition of investment finance. In particular, we examine whether an increase in therelative percentage of alternative sources of finance such as trade credit has an impact onthe degree of financing constraints More specifically, we first look at the effect of our variables of interest on the firms’perceptions of access to finance in a probit model. We find that SMEs though morefinancially constrained in general, are less so during the crisis, so that their perceptions of thefinancial constraints do not significantly differ from those of larger firms. We furtherinvestigate their financing choices and our findings suggest that the reduction in the degreeof perceived financial constraints between small and large firms may be attributed to SMEsbeing more flexible in the choice of the sources of financing such as trade credit and owner’scontribution. This finding sheds new light on the role of SMEs vs. large firms as channels ofpropagating of monetary and real shocks during a recession. Our work is organised as follows. Section Two discusses the peculiarities of firmfinancing in transition economies with a specific focus on small businesses. Section Threediscusses theoretical and empirical issues pertaining to the determinants of smallerbusinesses’ financing, including in the context of financial crisis. Based on that, we postulateour hypotheses. Section Four describes the data and the methodology. Empirical resultsfollow in Section Five. Finally, Section Six presents conclusions and policy implications. 2. The stylised facts about SME financing in Transition Economies To launch and operate new ventures entrepreneurs require financial resources that caneither come from their own savings or are external: borrowed in formal and informal financialmarkets, or raised through issuance of equity shares. Empirical studies on SME financingshow that smaller businesses typically rely predominantly on their own equity and informalfinance (primarily family and friends’ funds and investment of other individuals comprisingbusiness angels), and exhibit a moderately low level of formal external financing (Bates,1997; Ravid and Spiegel, 1997; Huyghebaert, 2001; Bygrave, 2003). The situation with SME finance in transition economies is more complex given thatneither of these sources was widely available in the early stage of transition (Estrin andMickiewicz, 2010). Although individuals were allowed to deposit their savings in the statesavings banks, the accumulation of wealth was low. Furthermore, the savings that individualskept with the state savings bank were eroded by hyperinflation at the start of transition. Forthese reasons internal finance and funds from family and friends were relatively scarce at thestart of transition and were likely to play less prominent role than in non-transition countries,and in the period of crisis even more so, given high sensibility of individuals’ savings toexternal shocks. 3
  4. 4. The required funding was also difficult to raise via bank borrowing given theunderdeveloped and inefficient financial system inherited from the planned economy wherethe role of finance was passive, for finance served as a monetary counterpart of planningdirectives. Despite the emergence of new private banks, the competition in the bankingsector across the region remained low, which can partly be explained by the capitalweakness of new banks, making the market very segmented. The dominance of state-ownedor (partly) privatised commercial banks made the banking environment very concentratedwith these banks expressing preference for large state-owned or privatised enterprises at thecost of discouraging new entrants (Rostowski 1995, Berglof and Bolton 2002). A number ofnewly established banks did not have enough experience in private sector lending(Pissarides 1998) and in the situation of a great economic uncertainty preferred occupyingsome niches to riskier lending to the real sector, in particular to SMEs. Such niches, forexample, included foreign currency transactions, short-term lending on the inter-bank market,and operations with governmental securities (Korosteleva and Lawson 2010). Other newbanks, so-called ‘pocket banks’, were mainly established by privatised larger enterprises toserve the purpose of financing their own activities, bringing to the surface the problem ofconnected lending. Given all these peculiarities of banks’ establishment at the start oftransition, small de novo firms were severely restricted in their access to the formal creditmarket. The situation was aggravated further by the credit crunch that was a result ofmacroeconomic stabilisation measures taken by transition governments to curb inflation.High nominal interest rates were a far larger problem for new ventures, which typically facean initial period of negative profitability1. The progress in reforming the financial sector was slow. This is confirmed by the EBRDannual transition indicators measuring the progress in reforms. They include (1) the bankingreform and interest rate liberalisation and (2) the securities market and non-bank financialinstitutions. For those two, the average scores for the region reached only 2.4 and 2.1respectively on the scale from 1 (little progress) to 4.3 (developed market economiesstandards), the decade after the transition began. In 2009 only the Central and EasternEuropean countries (CEECs) which joined the EU scored as high as 4 in both areas offinancial institutional reforms with Latvia, Lithuania, Slovakia, Slovenia, Bulgaria andRomania still being one score down in the area of securities markets. The latter threecountries also scored lower than their CEE counterparts in the area of banking sector reform.Some CIS countries such as Belarus, Turkmenistan and Uzbekistan, viewed as the laggardsin transition, still have rankings as low as 1 (Turkmenistan) and 2 (Azerbaijan,1 Pissarides (1998) argues that SMEs often reinforce banks’ perceptions of them being unreliableborrowers, given frequent under-reporting of profits due to tax avoidance purposes or failure toregister ownership of assets, prompting lenders to penalise SMEs by charging them higher premium. 4
  5. 5. Belarus,Kyrgyzstan, Tajikistan and Uzbekistan) in both areas of the financial institutionalreforms. Overall, after the years of the financial sector reform the majority of transitioneconomies still have rather shallow domestic credit systems (Figure 1) and relativelyunderdeveloped capital markets with market capitalisation ratio varying from as low as 1.6per cent of GDP in Kyrgyzstan and Armenia2 to as high as 40-50 per cent in Croatia &Kazakhstan respectively in 2009 with Montenegro and Russia standing out compared withthe rest of the region3. {Figures 1 & 2 to be inserted here} A number of empirical studies further confirm that financial constraints in transitioneconomies constitute one of the main obstacles for start-up entry and growth (Pissarides1998, 1999, 2001; Pissarides et al. 2003; Klapper et al. 2002). Pissarides (2001) concludesthat lack of access to finance is more binding for SMEs than larger businesses with theseverity of this constraint being stronger in South-East Europe compared to other transitioneconomies, including the Commonwealth of Independent States (CIS). In their study of SMEgrowth in Russia and Bulgaria, Pissarides et al. (2003) find that financial constraints hamperSME growth and that SMEs resort to the use of internal funds to overcome constraints onexternal finance. This is similar to Johnson’s et al. (2002) findings suggesting that internalfinance can substitute for external finance (see also Lizal and Svejnar (2002) for similarconclusions). Pissarides et al. (2003) also show that financial constraints affect SMEs morethan barriers related to property rights issues. Drawing on the data on 15 Eastern Europeancountries Klapper et al. (2002) show that financial constraints affect SMEs longer-term abilityto grow. Finally, Gorodnichenko and Schnitzer (2010) show that financial constraints restrainthe ability of domestically-owned firms to innovate and export thus inhibiting productivitygrowth. They also argue that this negative effect is magnified due to financial constraintsforcing export and innovation activities to become substitutes whereas they are commonlyfound to be complements. We complement these studies with the most recent empirical evidence on thedeterminants of SMEs’ perception of financial constrains in transition economies, whichcomes from the 2002-09 BEEPS dataset. The BEEPS self-reported measure of financingconstraints unites in one, termed ‘access to finance’, metric both quantity and priceconstraints. In the surveys, firms were directly asked to indicate the extent to which access to2 In fact, it goes as low as 0.2 per cent of GDP in Uzbekistan in 2005 following the World DevelopmentIndicators data with no data reported for subsequent years.3 Montenegro and Russia emerge as outliers, given their far higher ratios of market capitalisation.These are 104 and 70 per cent respectively and they are far above of some West European countries’ratios, including Germany, and comparable to the ones in China and USA. 5
  6. 6. finance was an obstacle to their operations and the averages for the individual countries inthe dataset are shown in Figure 3. With exception of Bosnia and Uzbekistan4, SMEs in alltransition economies are more financially constrained than larger firms, although as ourempirical results show (see Section 5) the difference in perception of financial constraintshas been largely eliminated between smaller and larger firms during the recent globalfinancial crisis. {Figure 3 to be inserted here} It has previously been argued that a low reliance on outside financing, scarce use ofequity finance5 and low level of inter-firm trade financing is a common feature of small firmsacross the transition region of Europe and Central Asia (Klapper et al., 2002; Pissarides,1998; 2001). Furthermore, Klapper’s et al (2002) find almost no use of long-term debt,attributing this to the underdevelopment of the banking sector, weak collateral law and poorcredit information registries. Their evidence also shows virtually zero reliance of SMEsacross the 15 Eastern European countries on trade credit, with the exception of Hungary andto a lesser extent of the Czech Republic, Poland and Romania. They explain this byinsufficiency of partner firms’ internal funds or their inability to access external borrowings tobecome able to finance extension of trade credit. Low reliance on trade credit may be alsoattributed to low foreign presence in some countries of the region, as multinationals couldextend trade credit to local firms, including SMEs (Klapper et al.,2002). Figure 4 shows the relative importance of financing sources used for purchase of fixedassets by SMEs in the transition economies. The data underlying this figure are the relativepercentages of the financing sources firms used in the year preceding a BEEPS survey yearin the BEEPS 2002-2009 surveys. The surveys group financing sources into the following sixtypes: internal funds or retained earnings, owners’ contribution or issued new equity shares,[funds] borrowed from private banks, [funds] borrowed from state-owned banks, purchaseson credit from suppliers and advances from customers, and other (moneylenders, friends,relatives, non-banking financial institutions). Figure 4 suggests that SMEs in the transitioneconomies tend to largely rely on their internal funds or retained profits in funding theirinvestment. Only about 23 per cent of small and medium-sized firms rely on borrowing fromprivate banks. Trade credit and equity finance occupy similar shares in funding SME’sinvestment decisions and account for the mere 9 per cent of total purchase of fixed assets.4 In Bosnia & Uzbekistan larger firms are marginally more constrained than smaller ones (at 10percent level of significance).5 Small firms may also decide to limit their issuance of outside equity to avoid reduction in control oftheir firms (Scherr et al.,1990 and Hamilton and Fox, 1998 cited in Klapper et al., 2002). 6
  7. 7. According to Cull (2007) trade credit can be seen as substitute for loans for private firms’trading partners that are shut out of financial credit market. Other sources include borrowingfrom informal money lenders and family and these emerge as the third important source offunding SMEs’ investment after internal funds and bank credit. We expect the informalfinance to be mostly comprised of equity provided by family and friends, as funding obtainedfrom informal private money lenders was overly expensive with the premium standing at least20 percentage points above that charged by local intermediaries (Pissarides, 1998). {Figure 4 to be inserted here} In conclusion, we note that the number of studies of the financing decisions of smalland medium-sized enterprises in emerging markets and, in particular, in the former centrallyplanned economies or previously heavily regulated economies such as India has been ratherlimited (see, e.g., Nivorozhkin, 2005; Delcoure, 2007; Crnigoj, 2007; Chakraborty, 2008;Girma et al, 2008; Li et al, 2009; Correa et al 2010, Love and Zaidi, 2010). We contribute tothis literature by analysing for SMEs in these countries the determinants of the following fivefinancing options: retained earnings, private loan (loan finance from private banks), tradecredit, private equity (owners’ equity) and informal finance. In this study, the phrase ‘informalfinance’ is an umbrella term that helps condense in one category funds from moneylenders,friends, relatives, non-banking financial institutions. Our results allow us to shed more lighton whether and how the theories of financing choices apply to transition countries in thecredit crunch environment. The following section discusses theories pertaining to small firm financing and how thismay be affected by a financial crisis. 3. Small Firm Financing and the Effect of Crisis: Theoretical Considerations and Hypotheses. 3.1 Theoretical arguments When analysing financing choices of SMEs, we first turn to the two cornerstonetheories of explaining leverage: the trade-off theory and the pecking order hypothesis (POH).While the former states that firms may prefer debt to equity in the presence of corporate tax,subject to the costs of potential financial distress stemming from borrowing large amounts(Modigliani and Miller 1958), the latter suggests that the firms first finance their investmentout of retained earnings as this is the cheapest and the most readily available alternative,then out of debt, and lastly, via issuing equity, which is seen as the most expensive option to 7
  8. 8. the firm (Arnold 2008). More recent literature on firm financing started to look closer at, andemphasize the importance of other sources, such as trade credit, especially for the small andmedium firms, using mostly the data on developed economies. For instance, Berger & Udell(1998) stress the importance of trade credit to the short-term financing of small firms. Bevanand Danbolt (2002) estimate that trade credit account for 62 per cent of total liabilities of UKfirms. The role of trade credit has been seen by some researchers as a substitute of banklending for liquidity-constrained firms (Cull 2007) such as SMEs. One of the benefits of tradecredit compared to the bank lending is that it allows to partly get around the informationasymmetry problem between the lender and the borrowing SME, as business partners wouldhave more information about the ability of the borrower to repay and about such reputation ofthe borrower in the industry. Meltzer (1960), Nielsen (2002) and Petersen and Rajan (1997)argue that trade credit may also provide a means of alternative financing under the tightmonetary conditions such as credit crunches when financial institutions are less able orwilling to provide loans to SMEs. In support of this hypothesis, Atanasova and Wilson (2003,2004) and Mateut et al. (2006) find that under tight monetary conditions, firms tend tosubstitute bank loans with trade credit. However, the findings in Bernanke and Gertler (1995)and Gertler and Gilchrist (1993) do not agree with this hypothesis. In line with these authors,Taketa and Udell (2007), using a sample of Japanese SMEs after the crisis years, find thatbank lending and trade credit are complements rather than substitutes. Love and Zaidi(2010) report that the use of trade credit by East Asian firms has declined after the 1998financial crisis, together with the use of bank loans. Finally, interesting enough, there issome empirical evidence which suggests that in the context of transition economies theremay be a higher reliance of SMEs on trade credit in the period of crisis. More specifically,focusing on the panel of 1,686 firms in Bulgaria, Hungary, Latvia, Lithuania, Romania, andTurkey in 2007 and 2009, Klapper and Randall (2010) find that during periods of contractionsin bank credit, buyers might depend more on trade credit (although primarily to be used forshort-term financing) that may be particularly true for small firms. This provides some supportfor the hypothesis that the two sources of finance, namely bank loans and trade credit, in thecontext of transition and emerging economies can be seen as substitutes in period of crisis. Another source of firm financing that has recently received increased attention isprivate equity. Private equity consists of investments by private individual investors or firms(business angels, investments funds) as well as business owners’ contributions to theirequity. The ‘business angels’ type of private equity is currently on the rise in the developedcountries as well as emerging markets such as India, Brazil, China, Malaysia. However,owners’ contribution is a far more widespread type of private equity in countries underconsideration. Generally SMEs are prone to various types of business and financial risks, 8
  9. 9. and it would be very important for them to try and hedge against these risks. Zou and Adams(2008) look at the effect of property insurance on the public firms’ borrowing capacity inChina, while Matthews and Scott (1995) in the US and Herbane (2011) in the UK investigatethe types of risk management used by the SMEs. The findings point to a rather limited use bythe small and medium-sized enterprises of the risk management assessment and hedgingtechniques. In the emerging markets of the post-Soviet bloc, the use of risk management techniquessuch as hedging with financial derivatives is virtually non-existent. However, an informal riskmanagement practice of accumulating cash out of profits, and also of using informal lendingfrom family and friends, to serve as a cushion in the times of financial distress, as protectionagainst possible bankruptcy and as an instrument of insurance against risks, has been oneway of accounting for the risky nature of SMEs in these countries. Secondly, many SMEssometimes use bankruptcy when they find themselves in the situation of financial distressand then open a new firm without losing much of their personal assets (Radygin et al. 2005).These SMEs are oftentimes are registered as belonging to a relative, or the SMEs could beregistered as founded by an artificially created third party with no links to the actual owner’spersonal assets. Recently banks in the new emerging economies such as Russia started apractice of compulsory purchase of loan insurance if the SME is to take a loan from the bank.This serves as a risk insurance mechanism to a certain extent, at the same time howeverincreasing the cost of bank financing. However, more recently this practice has attracted theattention of the Federal Antimonopoly Service that ruled that there is evidence of collusionbetween banks and insurance companies. Overall, we could conclude that the use of riskmanagement practices is very narrow and of a rather informal nature. The next sub-section explores in greater detail the institutional context of financing in thesituation of economic crisis. Empirical studies on small firm financing in the years of crisis are primarily motivated bythe informational asymmetries theories. One of the most important contributions in the studyof the role of SMEs during business cycle has been the real business cycle (RBC) theory(Bernanke and Gertler 1995; Bernanke, Gertler & Gilchrist 1998). The argument put forwardby the RBC theory is that SMEs face tighter liquidity constraints in terms of external financingdue to higher informational asymmetries associated with their activities, the low value oftheir assets to serve as collateral, the high cost of monitoring small businesses given a smallscale of their investment projects, and subsequently, the unwillingness of banks to lend toSMEs. During economic slowdowns, when small businesses are even more in need of externalfinance, bank lending to them diminishes even further, which tends to propagate the crisis ifthe SMEs then go out of business (see, for example, Tornell and Westermann 2005). At the 9
  10. 10. same time, as larger firms use more finance and tend to rely more on external funding theymay be hit harder by financial contraction in the situation of global crises when internationalfinancial markets dry up, so preventing larger firms from drawing upon them when required.They are also less flexible and it is more costly for them to restructure and downsize whenthey are hit with external shocks. Furthermore, while SMEs tend to be more flexible in relyingon other sources of finance, including trade credit, contributed equity and informal finance,the financial structure of larger firms generally tends to be less diversified with a preferenceoften given to retained profits and bank finance following the pecking order theory. Takentogether, we may argue that both supply and demand for finance is more affected for largerfirms in the situation of external shocks. Based on the discussion presented in Sections 2 and 3.1 we further discuss three maingroups of factors which are likely to affect firms’ perception of financial constraints and theirfinancing choice strategy. These are as follows: (1) firm size in general and in the period ofcrisis; (2) other firm- and industry-specific characteristics including foreign ownership, exportorientation, firms’ social capital and the degree of competition and its pressure on the firm todevelop a new product; and (3) country-level institutional parameters, including the degree ofprotection of property rights and the development of the financial sector. 3.2 Size of the enterprise and the effect of crisis With regards to the effect of firm size based on the general discussion in the literature(see sections 2-3.1), we expect , SMEs to be more financially constrained in their access toexternal lending, and respectively more reliant on internal funds. This is due to insufficientinformation that the bank can obtain about a particular SME, as well as due to a potentiallylower size of collateral. However, this lower reliance of SMEs on external debt can potentiallybe a source of flexibility during the crisis when formal financial markets dry up, and wheneven large well-established firms have difficulty obtaining bank credit. Furthermore, followingAtanasova and Wilson (2003, 2004), Mateut et al. (2006) and Klapper and Randall (2010) weexpect that under tight monetary conditions SMEs in transition economies are more likely toswitch to alternative forms of financing such as trade credit. We also hypothesize that SMEsare more likely to rely on owners’ contributed equity which they tend to accumulate in goodtimes as part of their risk management strategy to use it as a cushion in the times of financialdistress. In summary, we expect the difference between the SMEs and large firms in theirreliance on bank finance to diminish during the crisis years, and second, SMEs to be moreflexible and rely more on other sources of finance such as trade credit and private equity, inthe period of financial contractions. 10
  11. 11. 3.3 Firm- and industry- level factors As far as the firm-level and industry-level variables are concerned, we expect thefollowing results: first, the level of social capital of a firm, as proxied by the inverse of the timespent dealing with government regulations to indicate possible established connections withpublic officials, can positively affect its access to trade credit. Next, the industry-levelpressure on a firm from competitors to develop a new product may increase the firm’schances of obtaining a bank loan, as the bank may perceive the firm’s operations as morediversified and less risky (Isachenkova et al. 2011). We also expect foreign competition andthe pressure it exerts on a firm innovation capability to play less important role for firmfinancing decisions as SMEs are more likely to operate in market niches and they areunlikely to compete with multinational enterprises. In contrast, we expect a pressureoriginated from customers on a firm to innovate to increase a firm’s probability to rely moreon external sources of funding. This may be attributed to the fact that a firm does not onlydifferentiate itself from other firms further with developing a new product but also assures ademand for this product by responding to the needs of its existing customers. Theguaranteed demand for a new product would be one of the most crucial factors taken intoaccount by bank managers or potential investors in decision-making concerning projectfinancing. Thirdly, international product certification may play a similar role with regards tobank loans, increasing the access to external funds. Fourth, we investigate the effect on thechoice of financing of the firm age, with a square term. Generally, older firms may haveeasier access to bank loans as more information is available about them to the lender (Becket al. 2006; Canton et al. 2010), however, due to the particulars of the transition period,sometimes older firms may be less economically viable and unable to get a loan, therefore,the sign of this coefficient is uncertain here. Lastly, we also look at the firm’s exportorientation, which is expected to increase the reliance on bank lending, and its ownershiptype, where we single out foreign and domestic private firms. In the case of foreign firms,they are less likely to use private loans, and rely instead on retained earnings and intra-company funds transfers in the case of MNCs. 3.4 Institutional environment The impact of institutional variables on the financing choices of firms has been of theutmost interest to economists and policy-makers during the period of transition (see, forexample, Stijn and Tzioumis 2006, Mitra et al. 2008, see also Commander and Svejnar(2009) for an in-depth and comprehensive analysis of the impact of various businessenvironment factors on firm performance using BEEPS 2002 - 2005 panel). In our analysis, 11
  12. 12. we concentrate on two institutional factors: the degree of protection of property rights and thesize of the formal financial sector which have been claimed to be of key importance for firms’financing decisions (see Korosteleva and Mickiewicz (2011) for overview of the relatedliterature). As far as the property rights protection is concerned it is found to play crucial rolefor firm growth and access to external finance (Aidis et al. 2008, 2010, Korosteleva andMickiewicz 2011, Estrin, Korosteleva and Mickiewicz, 2011). In the environment with weakprotection of property rights, financial contracts are less likely to be concluded, leading to theunderdevelopment of finance and credit rationing with small firms to be disproportionallyaffected the most (Acemoglu and Johnson 2005). Beck et al. (2004) show that, in terms ofaccess to external finance, small firms benefit disproportionally from higher levels of propertyrights protection. Lack of secure property rights may also discourage SMEs from taking fulladvantage of opportunities to invest (Johnson et al. 2002). In a survey of private smallmanufacturing firms in Poland, Russia, Ukraine, Romania and Slovakia, Johnson et al.(2002) find that small firms tend to reinvest less of their earnings when they perceive theirproperty rights insecure. They also find that the effect of the property rights system is of moreparamount importance for entrepreneurs’ decisions to reinvest their earnings than availabilityof formal finance. Moreover, if property rights are well-protected, this lessens the extent ofpotential threat of being expropriated by raiders/bank lenders in an artificial bankruptcyprocedure, which has been quite a significant issue for firms in Russia and other FSU states(Radygin et al. 2005; Sprenger 2002). Based on this, we expect that strong property rightsare likely to encourage SMEs to use more debt as well as to use their own funds andretained profits for investing in investment projects. With regards to the size of the formal finance as measured by the share of privatecredit to GDP, the relationship between financial depth and financial constraints has beenextensively studied (Beck et al. 2006; also see for example Love 2003, who, employing asample of 36 countries, finds that financial development affects firms’ investment byincreasing the availability of external finance). Financial intermediaries facilitate the riskamelioration in the presence of problems created by information and transaction frictions, bydeveloping expertise in risk assessment and in monitoring (Levine 1997; Barth et al. 2006;Barth et al. 2008). Developed financial institutions are found to be particularly beneficial forsmall firms compared to large ones (Barth et al. 2006; Beck et al. 2005; 2006; 2008).Pissarides et al. (2003) show that financial constraints affect SMEs even more thandeficiency of the property rights protection. Accordingly, the size of the formal financialsystem is expected to be positively related to the use of bank finance, as a better functioningfinancial system should help ease up borrowing constraints. 4. Data and Methodology 12
  13. 13. 4.1 Sample To explore the determinants of the financial structure of small businesses, we use the2002-2009 Business Environment and Enterprise Performance Survey (BEEPS) data6 of21,867 firms covering 26 transition economies of Europe and Central Asia (ECA)7. The sample is primarily comprised of small and medium-sized businesses8 whichaccount for 89.3 per cent of the sample. The sample is representative in terms of industrialcoverage, with the majority of SMEs of the sample operating in manufacturing; wholesaleand retailing industries. BEEPS dataset provides rich information on firm characteristics, investmentbehaviour and firms’ perception of business environment, including financial constraintswhich are of a primary interest for our investigation of the effect of the recent financial crisison firms’ perception of financial constraints. Potentially, we could use other micro-level datacharacterising various domains of business environment captured by firms’ perceptions forinvestigating the effects of the institutional settings. However, using these micro-levelindicators as explanatory variables would make our study plagued with a problem ofendogeneity. To avoid this we merge our firm-level data with country-level indicatorscharacterising various institutional domains. The country level data were obtained from theWorld Development Indicators (World Bank) and Polity IV databases (for further discussionsee below). Finally, the BEEPs dataset contains other useful information which allows us toshed light of the effect of, for example, social capital, as proxied by the indirect measure ofpossible connections with the authorities (see below for the definition of the variable) on firmfinancing. 4.2 Variable Definition and Measurement Explanatory variables6 This data is a joint project of the European Bank for Reconstruction and Development and WorldBank. The first survey was launched in 1999. The dataset used in the present study is an unbalancedpanel covering the years of 2002, 2005, 2007-2009.7 The sample includes the following countries: Albania, Armenia, Azerbaijan, Belarus, Bosnia,Bulgaria, Croatia, Czech Republic, Estonia, FYROM, Georgia, Hungary, Kazakhstan, Kyrgyzstan,Latvia, Lithuania, Moldova, Montenegro, Poland, Romania, Russia, Serbia, Slovakia, Slovenia,Tajikistan and Ukraine. We exclude Uzbekistan as an outlier from our sample. We also excludeTurkey as, it is not classified as a post-communist country undertaking transition from a planned to amarket economy.8 We utilize the EU employment criterion to define small and medium-sized businesses. Morespecifically, businesses are defined as micro if they employ 9 and less employees, small – between 10and 49, medium – between 50 and 249, and large – over 250 employees. Respectively, SMEs aredefined as firms employing less than 249 firms. 13
  14. 14. To test our main hypothesis of the effect of a firm size on firms’ perception of financialconstraints we introduce a dummy variable denoting small and medium-sized business,coded as 1 if firms are classified as small or medium-sized businesses according to the EUdefinition based on the employment criterion. For robustness of our results we also use acontinuous variable denoting a size of employment as measured by the natural logarithm ofemployment9. The obtained results are consistent with the ones using the SME indicators. To capture the effect of the recent financial crisis we introduce a crisis dummy codedas 1 if the year of survey is equal to 2008 or 200910. We also introduce a number of firm-level controls which include age of firm11, type ofownership, including private and foreign ownership, export orientation, and whether a firmhas an internationally certified product all equal to 1 if a business has a respectively listedcharacteristic, and zero otherwise. We also examine the effect of various sources of pressureon firms to innovate – the indicators which are considered to be important for firm investmentdecisions. Respectively, the pressure for innovation may stem from domestic competition,foreign competition, and customers. To capture the effect of a firm’s social capital weintroduce an indicator which indirectly may capture some possible connections of a firm withauthorities. It is proxied by time spent by each firm on dealing with government regulations.We assume the less time firms spend dealing with government regulations the more likelythey have some established connections with public officials which allow them to avoidburdensome regulation procedures. In our study we also introduce a number of country-level variables which characterizethe institutional environment in the countries covered by our sample. More specifically weinclude an indicator of the financial development as measured by the ratio of domestic creditto private sector to GDP (one year lag, to avoid potential endogeneity), obtained from theWorld Bank World Development Indicators (World Bank 2011). This measure has been usedin previous studies (Klapper et al. 2006) and it is expected to be of a primary importance fortransition economies where firms tend to rely more on bank finance rather than capitalmarkets. We also introduce a measure of property rights protection (a one year lag), proxiedby the indicator of effective constraints imposed on the executive branch of the governmentand obtained from Polity IV project12. This measure of property rights protection is9 These results are not reported here to save some space. However, they can be obtained fromauthors upon request.10 Here it is important to note that although the financial crisis has started in 2007 in the USA, it spreadto transition economies in 2008-2009.11 Some studies find a non-monotonic relationship between age and firm decision-making. In thisstudy we introduce a squared term of age along with a age variable to capture this possible non-linearity.12 Available from http://www.systemicpeace.org/polity/polity4.htm. 14
  15. 15. considered to be superior to other indicators, including the index of property rights reportedby the Heritage Foundation –Wall Street Journal (for further discussion see Acemoglu andJohnson 2005; Glaeser et al. 2004; Estrin, Korosteleva and Mickieiwcz, 2011). In the present study we also introduce macroeconomic controls including cyclicaleconomic performance, as measured by the one year lag of the GDP annual growth rate,and the level of economic development, as proxied by a set of GDP pc dummies denotingthe five quintiles of its distribution to address the problem of potential multicollinearity with themeasure of financial development. Finally, we include industry and country controls in all our specifications. Introducingcountry dummies into analysis allows to control for cross-country heterogeneity. For further definition of all variables, their descriptive statistics and correlation matrixsee Tables 1-2. 4.3 Dependent variables To investigate the effect of a firm’s size on its perception of financial constraints weconstruct a dummy variable coded as 1 capturing a major and very severe obstacle foraccess to finance and 0 otherwise. The firm financing choices are defined by the five individual dependent variablesassociated with tobit financial choice equations in the seemingly unrelated regressionequations model. One important thing to mention here is the inability to distinguish betweenown/internal funds and external private equity considered as one of the limitations of the2002-2009 BEEPS dataset. In the period under investigation BEEPS offers two questionswhich aim to capture the use of equity. The first one centres around retained earnings andthe second one shows owners’ contributions and private equity or issued new equity.Following some theoretical considerations discussed in sections 2 and 3 in the context ofSMEs we expect the second element of equity to be primarily comprised of existing owners’new contributions rather than private equity. Thus the indicator of financial choices represents a set of five individual dependentvariables, including retained earnings, contributed earnings, private borrowing, informalfinance, trade credit with each of them constructed as a share in total financing of SME’sinvestment decisions (see Table 1). 4.4 Methods 15
  16. 16. In this study we employ a number of estimators to obtain robust results. Morespecifically, we use a probit model to investigate the effect of a firm size and the recentfinancial crisis on firms’ perception of financial constraints. The effect of a firm size in thesituation of crisis is captured by the introduction of the interaction term between firm size, asproxied by the SME indicator, and a financial crisis dummy. We further employ the seemingly unrelated regression equations model combinedwith the tobit approach for studying firms’ financial structure. Probit model of perception of financial constraints In the probit model, the probability of a firm’s perception of financial constraints asmajor(j = 1) can be written as follows: (α +X β j + u i ) -1/2  2  ( ) Pr y it = j | X it , u i = π it j = ∫ j it (2 π ) exp  − 1 / 2 * (α  j + X it β j + u i )   −∞   Where yit is our measure of financial constraints as perceived by firms, and X it is aset of our explanatory variables discussed in detail in sections 3-4. Here, it is important tonote that the interaction term in a probit model cannot be interpreted in a similar way as inlinear models, and disregarding this may lead to misleading estimates of the interactioneffect which is of crucial importance for our study (Norton, Wang and Ai, 2004). Respectively,for robustness of our results here we follow the framework suggested by Norton, Wang andAi (2004) to account for the model nonlinearity. The adjusted marginal effects for theinteraction term are reported in the note to Table 313. Simultaneous Model of Financing Choices As mentioned above, we next model the choice of all five financing choices explicitly.We also hypothesise (following Isachenkova et al. 2011) that firm financing choices are likelyto be determined jointly. A standard way of modelling jointly determined indicators is asystem of equations - SURE – seemingly unrelated regression equations, where equationsare linked only by their errors (Zellner 1962). We therefore model the five types of sources offinance (internal funds, private bank borrowing, informal finance, trade credit and private13 We also run a probit regression for a split sample of (1) SMEs and (2) large firms to check therobustness of our results (based on the interaction term) while addressing a problem ofmulticollinearity between a crisis variable and its interaction term with a SME variable The correlationcoefficient between a crisis variable and its interaction term with a SME variable is equal to 93%. Thiscan be attributed by the problem of a sample being overrepresented by SMEs which constitute 90% ofall surveyed firms. The results remain robust and can be available from authors upon request. 16
  17. 17. equity) using a SURE framework within which we specify a set of five tobit regressions withcorrelated residuals. We employ the STATA cmp module which allows to it Seemingly Unrelated Regressionsusing the simulated likelihood method such as the Geweke, Hajivassiliou, and Keane (GHK)algorithm (for further discussion see Roodman 2008). We utilise a tobit equation to modeleach individual financial choice of firms because our dependent financing choices variablesare continuous, but their range is constrained (censored) with a substantial number ofobservations either equal to zero, denoting those who do not use the respective source offinance, or to 100, showing the opposite. Other observations are positive and may producemany different outcomes (Verbeek 2000). Each tobit equation uses a set of identicalexplanatory variables that proxy factors which could possibly be associated with firm’sfinancing choices, including industry and country dummies. We also considered the bias caused by potential interdependence between the choice ofwhether to invest and firm’s financing choices. We accounted for the potential selection biasby introducing into the financial choices SURE Tobit equations (second stage outcomeequations14) the inverse Mill’s ratio calculated based on modelling the choice to invest infixed assets (first stage or selection equation). To identify the first stage of the Heckmanselection model, we chose a variable which is correlated with the first stage dependentvariable (investment decision) but not with the second ones (financing choices). We used therate of capacity utilization as part of our identification strategy. Capacity utilization shows thepercentage of capital stock in use; the higher is the rate the more likely firms will increaseinvestment. Batyaeva and Aukutsionek (2001) show that the rate of capacity utilization ishigher in the group of investing firms than in the group of non-investing firms in Russia15. Wecalculated the inverse Mill’s ratio, based on the above selection equation16 and included it asa control in the second stage SURE Tobit equations. The inverse Mill’s ratio has only provedto be statistically significant in the private bank loan equation pointing to the potentialselection bias arising from the possibility that the factors determining the decision to investmight differ from those determining the use of bank financing in purchasing fixed assets.14 We also attempted to estimate an investment equation jointly with Tobit financial choices equationswithin the SURE framework using. However, given the overall complexity of the model we failed to dothis. We proceeded further with a two-stage approach by estimating an investment probit equation andcalculating the inverse Mill’s ratio that we add into the outcome financial choices equations at thesecond stage of the analysis to test for the selection bias.15 We performed an independent sample t-test to check whether the rate of capacity utilization isstatistically significantly higher for investing firms compared to non-investing firms for our sample. Thenull hypothesis of no difference was rejected at 1% level of significance.16 To economize on space we do not report the results of the investment probit equation but they areavailable from authors’ upon request. 17
  18. 18. Finally, In Table 6 we attempt to condition the determinants of financing constraintsdeclared by SMEs on the relative percentage increase of trade credit in total funds used forreal investment. As mentioned above in Section 2, the timings of measuring the compositionof financing sources precede by a year the timings of measuring the perceptions of financingconstraints. That feature of the BEEPS’ design allays a likely concern about the endogeneityof the relative proportion of trade credit and enables causal inference. We, too, report in threnote to Table 4 the adjusted marginal effects for the interaction term of the SME dummy withthe trade credit variable. In the next section we discuss our empirical results. 5. Empirical Results Table 3 reports the results of the probit model with the marginal effects for firms’perception of financial constraints, while Tables 4-5 summarize the results of SURE tobits fora more detailed breakdown of five financing choices. More specifically, Table 4 reports theresults based on the whole sample to give a comparative perspective on SME’s financingstrategy vis-a-vis large businesses, whereas Table 5 reports the results based on asubsample of small and medium-sized firms to shed some light on their financing choices inthe period of crisis. Perception of financial constraints Table 3 shows that generally small and medium-sized enterprises feel more financiallyconstrained with the coefficient for SME dummy in relation to the large firms being positiveand significant which is consistent with our discussion in sections 2-3. However, thecoefficient of the interaction term with the Crisis dummy turns out to be negative andsignificant in relation to the perception of financial constraints as a major obstacle, and ittends to outweigh the effect of a SME dummy when we calculate marginal effects. The effectof the interaction terms with the crisis remains robust after we adjust for non-linearity usingthe framework proposed by Norton, Wang and Ai (2004)17. Overall, these results confirmthat small and medium-sized enterprises are much less financially constrained during thecrisis years, with their perceptions close to those of the large firms. This result is a polaropposite to that obtained for the SMEs in the UK (Fraser, 2009), which finds that not only doSMEs generally feel more financially constrained, but they report to be even more so during17 We also check the robustness of our results to the potential problem of multicollinearity between acrisis dummy and its interaction term with SME by splitting a sample and testing the samespecification separately for SMEs and large firms. We also perform another robustness check bybreaking a SME dummy into three subsequent dummies, namely micro-, small- and medium-sizedfirms. The difference in perception of financial constraints gets almost eliminated in the case of smallfirms, and is largely reduced in the case of micro firms, whereas it is less so for medium-sized firms. 18
  19. 19. the last crisis. We could explain this striking difference by the peculiarities of the SMEsfunctioning in new emerging economies. The lower reliance of SMEs on external debt ingood times (as shown by results which are discussed below) gives SMEs some flexibilityduring the crisis when formal financial markets dry up. Jointly with overall flexibility to makenecessary cost cuts and to restructure a business, this overall lower reliance on externalfunding and the use of alternative sources of financing makes SMEs feel less financiallyconstrained under the crisis as compared to larger firms. We also find that a more developed financial sector as proxied by domestic privatecredit as proportion of GDP helps ease up financial constraints. This is in line with thegeneral literature suggesting that better functioning financial intermediaries facilitate the riskamelioration in the presence of problems created by market frictions (Levine 1997; Barth etal. 2006; Barth et al. 2008). Unfortunately, we fail to find any significant effect of the property rights protection onfirms’ perception of financial constraints that may be explained by the fact that the effect of amore developed financial sector is likely to outweigh the effect of the property rightsprotection. Finally, we also find that foreign ownership and international product certificate mayreduce firms’ borrowing constraints, while any pressure from domestic or foreign competition,so is pressure from the customers to innovate will increase firm’s perception of financialconstraints as major given that firms envisage the need to secure external funding for R&Dor any other innovation-related activities. Financing choices for investment in fixed assets The results in Table 4 indicate that small enterprises tend to rely more on internal fundsand less on bank loans, but they are no different from larger firms in respect of using informalfunds, trade credit or private equity which is generally consistent with our discussion inSections 2 and 3. The results of Table 5 suggest, however, that under crisis small andmedium-sized firms tend to switch to other sources of finance such as trade credit andowner’s contributed equity, and to respectively reduce the reliance on retained earningsperhaps because they decrease due to the negative impact of crisis internal funds. Withregards to our discussion of SMEs’ risk management, we note that the use of private equity(owner’s contribution) during the crisis years increases which could indicate that the owner’sfunds are used as a cushion in the period of financial distress. An interesting insight regarding the use of trade credit emerges for SMEs in oursample: although in non-crisis years small and medium-sized businesses are not significantlydifferent from larger firms in terms of reliance on trade credit, SMEs tend to finance asignificantly higher proportion of their fixed asset investment by trade credit than large firms 19
  20. 20. in the period of crisis. While the latter finding is partly in line with some other studies – suchas Klapper and Randall (2010) using BEEPS data, it is in stark contrast with similar studiesof the UK private firms (Rehman 2011), for which the use of trade credit is found to havedried up in crisis. This could partly be due to the passed legislation in the UK tightening tradecredit regulation as the result of the abuse of trade credit by large firms in relation to smallfirms which forced many SMEs out of the market. With regards to the other firm-level characteristics, international certification makes thefirm rely more on private bank loans and informal finance (Table 5), while SMEs with foreignownership rely less on private debt, but more on retained earnings. Both results areconsistent with our hypotheses discussed above. Export-oriented small and medium-sizedbusinesses tend to have greater reliance on trade credit, and they use less of internal funds.We find a non-monotonic relationship between age and private equity with both younger andolder firms being more reliant on this source of funding. We find some fragmentary supportfor private domestic SMEs relying more on informal finance, while tending to use less tradecredit and private equity (Table 5). Interestingly, our results (Tables 4-5) suggest that firms which lack some socialconnections with governmental officials, proxied by the higher amount of time spent dealingwith government regulations, are more likely to rely on informal finance, trade credit andprivate equity. In turn, businesses which are connected to governmental officials use moreretained profits to fund investment in fixed assets. This may be attributed to their connectionsserving as a guarantee from expropriation of assets by all sort of rent-seeking individualsakin private contracting to secure property rights protection. This result should be interpretedjointly with the property rights protection results. We expected that better property rightsprotection is likely to facilitate firms’ access to bank loan, but we failed to confirm this.Perhaps, regardless some attempts at a constitutional level to prevent arbitrary government(which is proxied by our measure of property rights) expropriation culture is still deeplyembedded in the society of post-communist countries and it may manifest in different ways.Welter and Smallbone (2011) argue that entrepreneurs in transition economies have learnthow to respond to institutional deficiencies, in particular weak property rights protection. Forexample, some businesses experiencing high growth choose to invest in unrelatedbusinesses instead of growing their core businesses for the reason they do not want tobecome too noticeable to attract too much attention of the wrong sort. In our instance, havingsome connections with officials seems also to serve as protection against arbitrarygovernment or individual rent-seeking that makes businesses more keen on re-investing theirretained profits (see Johnson et al. (2002) on the discussion of how more secure propertyrights can make small firms reinvest more of their earnings). 20
  21. 21. Pressure from domestic competition and customers on a firm to develop a newproduct, which may be a characteristic of oligopolistic or monopolistic competition structure,makes a firm more likely to rely more on bank finance. Interestingly, we find the use of outsourcing by SMEs (Table 5) strongly and robustlysignificant in explaining access to external funding. Our results show that SMEs in countries with low GDP per capita (the first threequartiles up to the level of USD 10,468 at ppp) tend to rely more on internal funds and lesson bank finance.We also investigate whether an increase in the relative percentage of trade credit in thefinancing mix affects small firms’ perceptions of financing constraints. To this end, weestimate a probit model that conditions on relative share of trade credit and includes aninteraction term for the SME dummy and trade credit. Reported in Table 6, this modelconfirms that during a crisis, flexibility in switching to alternative sources of finance such astrade credit could be a possible determinant of perceptions of financing constraints. Inparticular, the increase in a relative percentage of trade credit in the firm’s financing mix,picks up a significant difference in financing constraints across the size categories andpositively affects the propensity of SMEs to declare themselves as less financiallyconstrained. Overall, our findings regarding firm- and industry-specific characteristics and the impactof the institutional variables in all three specifications are generally consistent with thehypotheses and literature discussed in Sections 2 and 3 with some exceptions which we willsummarise in the next section. 21
  22. 22. 6. Conclusions Our key results may be summarized as follows. Consistent with the literature smaller businesses generally feel more financiallyconstrained in accessing external funding given the small scale of their investment projects,inability to provide good collateral and higher risk implying that financial institutions find itcostly to monitor small businesses. However, in the situation of crisis, as exemplified by the recent financial crisis which inthe 2008-09 spread to the transition economies, the difference in perception of financialconstraints between smaller and larger firms is largely eliminated. Our analysis suggests thatSMEs are more flexible in that they also rely on other sources of finance such as trade creditand owners’ contributed equity, which may make them more flexible than large firms duringthe years of crisis. Furthermore, smaller firms overall require less finance given the smallscale of their projects. So they may be hit less by financial contraction compared to largerfirms, the financial position of which is particularly undermined in the situation of global criseswhen international financial markets dry up, thus preventing larger firms from drawing uponthem when required. Smaller firms are also more flexible and it is less costly for them torestructure and downsize when they are hit with external shocks. Our second set of results relate to the firm characteristics. Consistent with the literaturefirm’s export orientation increases the reliance on trade credit and reduces the reliance oninternal funds, while foreign ownership diminishes the reliance on bank lending. Foreign firmstend to rely more on retained earnings and intra-company funds’ transfers in the case ofmultinational businesses. In our empirical study we also find that international productcertification increases the access to private loans and informal funding. Our results alsosuggest that social capital in the form of connections with officials is used by SMEs toovercome deficiency of the property rights system and facilitate reinvestment of earnings bysmall businesses. Finally, our third set of the results is related to the role financial institutionalarrangements play for firm perception of financial constraints and financing decisions. Withthe development of the financial institutions, the transactions costs of financial intermediationmay decrease reducing the cost of finance and increasing its availability. Indeed, we find thata higher share of private credit to GDP is associated with firms relying more on private creditin financing their investment decisions. We also show that a size of the formal credit marketplays more prominent role in firms’ perception of financial constraints. Our findings have some policy implications. Overall, a more developed financial sectorcan mitigate market frictions to make bank finance more accessible by SMEs in good timesand to provide some incentives for small businesses to reinvest their earnings. This may alsofacilitate accumulation of cash by owner-managers which can be used as a cushion in bad 22
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  29. 29. Figure 1: Domestic Credit to Private Sector (as % of GDP) in Transition Economies andComparator Countries selectively, 1991-2010 250.00 200.00 150.00 100.00 50.00 0.00 1991 1993 1995 1998 2001 2004 2007 2008 2009 2010 China Czech Rep Estonia Germany Hungary Kazakhstan Lithuania Poland Russian Federation Slovenia United StatesSource: World Bank (2011)Figure 2: Market Capitalisation (as % of GDP) in Transition Economies andComparator Countries selectively, 1991-2010 29
  30. 30. 200.00 180.00 160.00 140.00 120.00 100.00 80.00 60.00 40.00 20.00 0.00 1991 1993 1995 1998 2001 2004 2007 2008 2009 2010 China Czech Rep Estonia Germany Hungary Kazakhstan Lithuania Poland Russian Federation Slovenia United StatesSource: World Bank (2011)Source: World Bank (2011) 30
  31. 31. Figure 3: Percentage of SMEs vs Large firms that perceive access to finance as a majorobstacle in operating business, 2002 2002-2009Source: Authors’ calculations based on BEEPS 2002 09. Respondents were asked whether 2002-09.access to of finance (incl. its availability and cost) is No Obstacle, a Minor Obstacle, a Obstacle,Moderate Obstacle, a Major Obstacle, a Very Severe Obstacle to the current operations oftheir firms. The figure shows only percentage of firms which find access to finance as both amajor and very severe obstacle. Please note firms were classified by size on the basis of firmsemployment criterion in accordance with Eurostat criteria: micro firm - 0-9 employees, small-sized - 10-49 employees, medium 49 medium-sized - 50- 249 employees, and large - 250 employeesand over. SMEs are respectively defined as employing less than 250 employees. defined 31
  32. 32. Figure 4: Sources of financing SMEs’ investmentsSource: Authors’ calculations based on BEEPS 2002 09. Respondents were asked to 2002-09.estimate the proportion of their firms’ total purchase of fixed assets tha was financed over thatthe previous year from each of the sources listed on the diagram diagram. 32
  33. 33. Table 1: Descriptive statistics and definitions of variables Variable Definition Mean S.D. No of obsEXPLANATORY variables:Institutional variables and macroeconomic controls:Property rights Polity IV ‘Executive Constraints’; scores from 5.72 1.75 21,867(t-1) 1=”unlimited authority” to 7=”executive parity”; higher value denotes less arbitrarinessDomestic credit Ratio of credit to private sector to GDP (WB WDI 32.11 18.78 21,477as a % of GDP April 2009)(t-1)GDP per capita GDP per capita at purchasing power parity, 9947.2 5430.73 21,867(t-1) constant at 2005 $USD (WB WDI April 2009)GDP growth Annual GDP growth rate (WB WDI April 2009) 6.29 3.24 21,867(t-1)Firm and industry-level characteristicsSmall & medium- 1=small firms with a number of employees being .893 .309 21,835sized firms >=1 and <250, 0 otherwiseCrisis 1=2008 & 2009, 0 otherwise .26 .44 21,867Age Age of firm in 2008 or in 2009, years 20.84 102.68 21,859Age squared Age squared - - 21,859International 1=firm in a process of applying or it has an .35 .76 21,766product certification international product certificate, 0 otherwiseForeign ownership Percent owned by foreign individuals, 9.82 27.46 21,469 companies or organisationsExport orientation Percent of sales exported directly or indirectly 11.37 25.77 21,828Privately owned 1=firm is private from inception .75 .43 18,767from inceptionTime spent on Percent of time spent on dealing with 8.43 13.48 20,701dealing with government regulationsgovernmentregulationsPressure to 1=Yes, 0 otherwise 2.83 1.03 20,186innovate originatesfrom domesticcompetitionPressure to 1=Yes, 0 otherwise 2.08 1.14 19,707innovate originatesfrom foreigncompetitionPressure to 1=Yes, 0 otherwise 2.9 1.04 20,093innovate originatesfrom customersDEPENDENT variables:Probit model:Perception of 1=firm perceives financial constraints as major .22 .42 20,934financial or very severe, 0 otherwiseconstraintsSURE tobit model:Retained profits Retained profits as a % of firm financing of fixed 66.92 40.39 14,491 assets 33
  34. 34. Private loan Private loan as a % of firm financing of fixed 12.68 27.63 13,246 assetsTrade credit Trade credit as a % of firm financing of fixed 3.67 14.83 14,267 assetsPrivate/contributed Private/contributed equity as a % of firm 4.15 17.68 14,257equity financing of fixed assetsInformal funding Money from family, friends and other money 9.98 25.51 13,279 lenders as a % of firm financing of fixed assets Source: BEEPS 2002-2009 unless specified otherwise 34
  35. 35. Table 2: Correlation Matrix for the dependent and macro-level variables Variables Percep. Retained Private Informal Trade Private SME Crisis Property Domestic GDP pc GDP of profits loan finance credit equity rights credit ppp growth financial const-s Perception 1 of financial constraints Retained -0.08 1 profits Private loan 0.03 -0.53 1 Informal 0.04 -0.47 -0.12 1 finance Trade credit 0.03 -0.29 -0.04 -0.05 1 Private 0.03 -0.33 -0.06 -0.07 -0.03 1 equity SME 0.03 0.05 -0.06 -0.01 -0.02 0.02 1 Crisis 0.09 -0.12 0.15 -0.16 0.12 0.11 0.02 1 Property 0.00 -0.13 0.10 0.05 -0.02 0.04 0.01 -0.05 1 rights (t-1) Domestic 0.002 -0.16 0.17 -0.08 0.06 0.09 0.01 0.52 0.43 1 credit (t-1) GDP pc ppp -0.02 -0.13 0.06 0.002 0.02 0.04 -0.01 .19 0.46 0.64 1 (t-1) GDP growth -0.01 0.11 -0.08 -0.001 -0.02 -0.01 0.01 -0.17 0.44 -0.50 -0.55 1 (t-1) Source: BEEPS 2002-2009; WB WDI Apr 2009; Polity IV. 35
  36. 36. Table 3 Perception of Financial Constraints: probit estimation results and marginal effectsDependent variable: probit results probit marginal effectsPerception of financial Coef. Robust Std. Coef. Robust Std.constraints as a major Err. Err.obstacleSmall and Medium-sizedenterprises 0.203*** 0.058 0.052*** 0.014Crisis 0.890*** 0.126 0.301*** 0.047Small and Medium-sized_x_Crisis -0.273** 0.113 -0.069** 0.026International ProductCertification -0.057*** 0.020 -0.016*** 0.005Privately owned from inception 0.012 0.036 0.003 0.010Time spent on dealing withgovernment regulations 0.005*** 0.001 0.001*** 0.0003Pressure to innovate originatesfrom domestic competition 0.071*** 0.015 0.020*** 0.004Pressure to innovate originatesfrom foreign competition 0.078*** 0.016 0.022*** 0.004Pressure to innovate originatesfrom customers 0.048*** 0.013 0.013*** 0.004Foreign Ownership -0.005*** 0.001 -0.001*** 0.0001Export orientation -0.0001 0.001 -0.000018 0.0002Age -0.001 0.001 -0.0002853 0.0003 -07Age squared x 10 4.97 5.25 1.37 1.45Domestic Credit as % of GDP(t-1) -0.009*** 0.003 -0.003*** 0.001Property Rights (t-1) 0.028 0.058 0.008 0.016GDP growth (t-1) -0.023*** 0.008 -0.006*** 0.002Outsourced product 0.024 0.043 0.007 0.012GDP per capita ppp (t-1):Quartile1 0.257 0.210 0.075 0.065GDP per capita ppp (t-1):Quartile 2 0.338** 0.160 0.100** 0.050GDP per capita ppp (t-1):Quartile 3 0.091 0.123 0.026 0.036GDP per capita ppp (t-1):Quartile 4 0.180** 0.079 0.052** 0.023Constant -2.094*** .433 n/a n/aIndustrial controls Yes Yes Yes YesCountry controls Yes Yes Yes YesNumber of obs 12,807 12,807Pseudo R2 0.0673 0.0673Source: BEEPS 2002-2009, WB WDI Apr 2009, Polity IV. Note: significance levels: *** - 1%; ** - 5%; * - 10%.For the interaction term of SME and crisis the marginal effect is different from the one reported in the tableabove. After controlling for non-linearity following Norton et al. 2004, the coefficient of the interaction term atmean is equal to -0.074; standard error is equal to 0.038 and z statistic is equal to -1.90 indicating significanceat 0.01 level. 36
  37. 37. Table 4. SURE Tobits results for Firms’ Financing Choices (based on whole sample)Dependent variable Retained Private Informal Trade Private profits Loan Finance Credit EquityExplanatory variables Coef. Coef. Coef. Coef. Coef.Crisis -14.68*** 14.429 -34.767*** 43.68*** 73.231*** (3.48) (6.410) (7.329) (9.464) (11.454)SME 4.30** -13.399*** -1.525 -3.524 -4.729 (1.879) (3.438) (3.489) (5.247) (7.219)International ProductCertification -0.697 4.192*** 4.165** 1.884 -0.852 (0.720) (1.306) (1.311) (2.107) (2.728)Privately owned frominception 0.866 2.911 5.778** -8.569** -4.307 (1.276) (2.541) (2.486) (3.825) (4.811)Time spent on dealingwith governmentregulations -0.133*** -0.018 0.323*** 0.246** 0.346*** (0.042) (0.081) (0.076) (0.112) (0.134)Pressure to innovateoriginates from domesticcompetition -1.28** 3.166** 3.024** 2.552 -2.404 (0.522) (1.052) (1.029) (1.644) (1.99)Pressure to innovateoriginates from foreigncompetition -0.499 0.746 2.258** 0.056 .845 (0.463) (1.14) (1.131) (1.745) (2.195)Pressure to innovateoriginates from customers -.952 2.428** 1.38 2.339* 3.297* (0.581) (0.915) (0.864) (1.41) (1.762)Foreign Ownership 0.050*** -0.094** -0.045* -0.013 -0.003 (0.017) (0.033) (0.032) (0.050) (0.064)Export orientation -0.072*** 0.118** 0.026 0.153** -0.035 (0.022) (0.04) (0.04) (0.063) (0.080)Age 0.042 -0.039 -0.127 -0.05 -0.28* (0.037) (0.07) (0.074) (0.109) (0.149) -04Age squared x 10 -0.204 0.246 0.453 .213 1.43* (0.189) (0.35) (0367) (.539) (0.70)Domestic credit as % ofGDP (t-1) 0.445*** 0.516** -0.976*** -0.840** -1.578*** (0.120) (0.230) (0.227) (0.349) (0.457)Property Rights (t-1) -.818 7.486 -6.239 -.741 -22.129** (2.44) (5.232) (5.211) (7.244) (10.025)GDP growth (t-1) 0.149 1.198** -0.923 -0.623 2.098* (0.335) (0.615) (0.669) (.906) (1.19) 37

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