1

Signalling through the noise: Private certification,

information asymmetry and Chinese SMEs’ access to finance

Paul Minard*

Abstract

Information asymmetry between Chinese banks and small and medium-sized domestic private

enterprises (SMEs) is a source of credit constraints. This paper investigates whether obtaining

an internationally-recognized private certification standard can credibly signal unobserved firm

quality, reducing information asymmetry and improving access to finance. Examining World

Bank survey data, I find that firms that certified firms are 1.68 times as likely as comparable

uncertified firms to receive bank loans. This effect is strongest among smaller firms, for whom

information asymmetry is likely a more severe constraint. China’s promotion of certification as

a tool of regulatory policy has had the unintended consequence of mitigating policy

shortcomings in another domain.

Keywords: information asymmetry; private certification; signaling; China; company finance

*School of Conflict Studies, Saint Paul University, Ottawa, ON, Canada

*This is a preprint of an article currently under review

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1. Introduction

Recent years have seen the rapid adoption of private management certification standards by

business enterprises. By the end of 2012, for instance, the International Standards Organization

had issued more than 1 million ISO 9001 quality management in 184 countries. Adoption of

these private management standards is not limited to firms in the developed world. By 2012,

over 300,000 ISO 9001 certificates had been awarded to Chinese firms (ISO Survey, 2012). The

rise of these “meta-standards” (Uzumeri, 1997), which apply to “broad processes (rather than

individual products)” (Corbett and Yeung, 2008), has been accompanied by a substantial

academic literature investigating the effects of private certification adoption on firm

performance. The adoption of ISO 9001 certification has been positively associated with

productivity enhancements (Jang and Lin, 2008), quality improvement (Escanciano et al., 2001),

and employee motivation (Kunnanatt, 2007).1

Though the certification process may lead to learning within the firm which improves

performance, a puzzle remains as to why, given that the requirements of these standards are

publicly available, firms nevertheless endure the costly process of certification. One explanation

is that firms perceive certification as a credible signal of their underlying, unobserved quality

under conditions of information asymmetry between themselves and potential contracting

parties. That information is costly to obtain and not evenly distributed amongst potential parties

to a transaction has long been recognized by scholars working in a transaction costs framework

(North, 1990; Williamson, 1979). Information asymmetry results when the seller of a good or

service is better informed about its unobservable quality than is the potential buyer, and the cost

1 For a comprehensive review, see Heras-Saizarbitoria and Boiral (2013).

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to the buyer of obtaining this information is prohibitive. Information asymmetries thus take

deals off the table which, in a world of costless information, would be consummated to mutual

advantage, since buyers are unable to distinguish high quality sellers from low quality sellers.

This problem has applications in many markets, including firm financing, which is the focus of

the present analysis.

Given the potential relevance of signalling to the adoption of private certification standards, it is

surprising that the signalling aspect of private certification standards has been comparatively

understudied (Montiel, Husted and Christmann, 2012). Some empirical findings do suggest the

signalling value of private credentials as a driver of their adoption. Terlaak and King (2006), for

instance, find that firms which adopt ISO 9000 quality certification grow faster after

certification, and that these improvements are not explained by changes in firm operations. This

paper provides the first evidence of the signaling value of private certifications standards in the

context of firm financing under information asymmetry.

China is an important venue for empirical study of the signaling value of private certification in

this context. That the Chinese domestic private sector, composed mostly of small and medium-

sized enterprises (SMEs), faces financing barriers is well documented (Poncet et al., 2010) and

both information asymmetries and a policy-driven bias toward state-owned enterprises appear to

be important factors (Firth et al., 2008; Ruan and Xiang, 2013). China has also been the scene of

the rapid diffusion of certification standards, driven in part by government policy. Employing

data from a 2011 survey of 2700 Chinese private enterprises in 25 cities, I show that certified

firms are 1.67 times as likely to report access to bank finance as otherwise comparable firms

without certification. Moreover, this effect is stronger among smaller enterprises than larger

enterprises (in terms of firm employment). Whereas for a firm with 80 employees, for instance,

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certification increases the predicted probability of accessing finance from 32% to 34%, the

corresponding effect for a firm with 10 employees is an increase from 14% to 20%. This

suggests that the policy of encouraging private certification adoption has had unintended, though

favourable, effects on SMEs’ access to finance.

The remainder of this paper is structured as follows. Section 2 presents a selective review of

literature on information asymmetries in financial markets, signalling theory and barriers to

finance faced by Chinese SMEs. The sample and estimation strategy are described in Section 3.

Results are presented in Section 4, and Section 5 concludes.

2. Literature review

2.1. Information asymmetry and signalling theory in financial markets

Levine (1997) emphasizes information asymmetries among the primary drivers of the rise of

financial markets. Where asymmetries persist, it is difficult for savers to distinguish high from

low quality firms. Firms know their ability to repay loans better than does the lender, and banks

may thereby ration access to credit since, knowing their inability to distinguish high from low

quality firms, they fear that a market-clearing interest rate may increase the riskiness of the pool

of borrowers, attracting ever more firms whose viability is worse than that of the average firm

(Hillier and Ibrahimo, 1993). An adverse selection problem as described by Akerlof (1970) is

the result. Overcoming these asymmetries enables a more efficient allocation of capital, and thus

enhanced growth (Levine, 1997: 695).

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Both lenders and high quality firms (but not low quality firms) would have an interest in

reducing this information asymmetry if the firm could send credible signals of quality. The

relevance of signalling as a response to information asymmetries in markets was first formalized

by Spence (1973). In the context of the signalling value of education credentials in labor

markets, Spence noted that potential employees are better informed about their underlying ability

than are employers. Educational credentials, provided they are less costly to obtain for high

ability individuals than for low ability individuals, are a credible signal of ability to employers

which reduces information asymmetry and enables a mutually beneficial labor contract. This

logic can be extended to a number of domains, including buyers looking for credible signals of

underlying quality so as to choose among a large number of potential suppliers, and lenders with

a demand for information on the underlying quality of loan-seeking firms. Private certifications,

awarded by independent auditors, may be a signal of quality in these domains as well, provided

they are less costly to obtain for firms whose underlying quality is high.

In the context of firm financing, standard signalling models (i.e., Kirmani and Rao, 2000, as

described by Connelly et al., 2011) assume two types of firms: those of high quality and those of

low quality. It is assumed that firms know whether they themselves are high quality firms, but

lenders do not, and firms have the choice to signal their true quality or abstain from doing so.

The choice for the high quality firm can be represented by Payoff A for signalling and Payoff B

for not signalling. The low quality firm receives Payoff C for signalling and Payoff D for not

signalling. Provided A>B and D>C, high quality firms have an incentive to signal. An essential

feature of this dynamic is the costliness of signalling, since if signalling quality were costless, all

firms would signal and lenders would be unable to differentiate firms by quality. It is thus

essential both that signalling be costly and that the firms best able to bear this cost are those

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whose otherwise unobservable quality is high on the margins of concern to the lender (in this

case, the unobservable determinants of long run profitability. The presence of these

determinants should be taken as synonymous with quality in the present context).

Numerous signals might satisfy these conditions and enable lenders to distinguish firms by

quality. Connelly et al. (2011) summarize signalling mechanisms identified in the existing

literature. These include firms’ issuance of debt and dividends, which are effective signals

because of their costliness and the differential ability of firms of differing levels of quality to

bear these costs. If a signal is to be effective in the face of information asymmetry, then, it must

be both observable and costly.

2.2. SME access to finance in China

China’s remarkable economic transformation since the reforms of the late 1970s has in part been

enabled by a sea change in government policy toward the private sector. The legality of

household private enterprises (getihu) was recognized by the State Council in 1981, and larger

private firms (siying qiye) in 1988 (Young, 1989). Private property attained the same de jure

status as public property in 2007 (Zhang, 2008). The private sector today accounts for

approximately 50% of China’s economy (Firth et al. 2009), and the dynamism of SMEs has been

well documented (Huang, 2008). Nevertheless, the domestic private sector faces continued

challenges in China, including barriers to entry into protected markets, onerous registration

processes, a fragmented regulatory environment (Pearson, 2007) and the discretion of

government officials to extract extralegal fees (Choi, 2009; Minard, 2015). Moreover, numerous

studies have demonstrated that the private sector, composed mostly of SMEs, is credit

constrained (e.g., Poncet et al, 2010). Despite its share in economic output, only 7% of loans are

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made to the private sector (Firth et al, 2009). The literature has identified two main sources of

this credit constraint. The first we might broadly call political, and derives from the extent of

government control of the largest banks (Allen et al, 2013). These banks, though

commercialized in 1995, favor state-owned enterprises (SOEs) in lending (Brandt and Li, 2003).

When private firms do gain access to bank finance, these loans must typically be backed by

collateral in the form of immovable assets (Ayyagari et al., 2010: 3052). As a result, Chinese

private firms often rely on retained earnings and private moneylenders to finance new

investment. Though informal finance networks built on family relationships have been

important for SMEs (Tsai, 2004) firms with formal financing have been found to outperform

otherwise similar firms that are informally financed, even after controlling for selection effects

(Ayyagari et al, 2010).

Banks may discriminate against the private sector owing to the historical sensitivity of private

enterprise, government policy goals beyond banking profit maximization (including the

maintenance of employment in SOEs), government’s residual profits from state-owned

enterprises, or the fear that insecure property rights increase the risk of expropriation of firm

assets, reducing the likelihood of repayment (Bai et al, 2006). Information asymmetry is

another important source of this credit constraint. The private sector being relatively new and

state banks only recently commercialized, lenders lack soft qualitative information on SMEs

which are also less likely to adopt formal accounting processes. Yeung (2009), in a survey of

Chinese bankers, finds that personal knowledge of applicants and the existence of “mutual trust

(xinyong)” between lenders and applicants is perceived as vitally important in the lending

decision (2009: 290). Building such relationships is one way to reduce information asymmetry,

though this process carries an opportunity cost in that time spent building relationships with one

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applicant is time not spent learning about another. Though a credit rating system has grown in

response to market demand in recent years, the reliability of rating agencies has been questioned,

as ratings tend to be upwardly biased (Korkeamäki et al, 2014). Even where ratings may be

more reliable, this does little to help SMEs access finance. Among high quality SMEs

especially, then, there should be a clear demand for credible signals of firm quality so that they

can distinguish themselves from firms of lower quality in the eyes of lenders. As Firth et al

conclude, “it is crucial that Chinese banks find signals or indicators to infer the quality of the

potential borrowers” (Firth et al, 2009: 1146).

2.3. Private certification standards as costly signals

Private international certification standards are typically outlined by international organizations

such as the International Organization for Standards. The standards themselves are freely

available, and certification is undertaken by local certification bodies which in most countries are

themselves accredited by a national-level body. The organizations which develop these

standards do not oversee these processes.

Several studies have remarked that the costs of complying with international standards

certification are considerable. In the developed world, Stevenson and Barnes (2002) note that

the costs registration, training and implementation of ISO 9000 reached as much as US$ 1

million. Among smaller firms (sales of about US$25 million), the equivalent figure was, on

average, around US$250,000. Registration alone can be costly. In the case of ISO standards, the

ISO accredits national standards organizations to certify organizations that themselves certify

firms’ compliance. Stevenson and Barnes obtained quotes from a sample of auditors for a

hypothetical automotive supplier with 250 employees. The average quote was US$10,290, and

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could reach US$40,000 for a larger site. Certification costs are high in the developing world as

well. Maskus, Otsuki and Wilson (2005) examine firm-level data from 16 developing countries

and determine that adopting foreign product standards adds significantly to firms’ fixed and

variable costs, the former at the rate of 4.7% of value added on average (Maskus, Otsuki and

Wilson, 2005, p.2). Potoski and Prakash (2009) similarly note that “small- and medium-sized

firms routinely cite auditing costs as an important factor for not pursuing ISO 9000 certification”

(Potoski and Prakash, 2009, p.225). Provided such costs are more easily borne by firms of

higher underlying quality, private certification may be a credible signal by which firms can

distinguish themselves from competitors in the eyes of lenders.

Some certifications have become widespread in China owing in part to government policy. For

instance, in the case of ISO14001 (an environmental management system (EMS) process

assurance standard), government has been active in publicizing the standard’s merits, and

encouraged its adoption in state-owned enterprises as part of pilot projects. Regulatory control

of all private certification standards is located in the Certification and Accreditation

Administration of the People’s Republic of China (CNCA). The accreditation and certification

process in China are considered relatively strict by international standards (Fryxell et al, 2004).

Certifiers are often housed within municipal economic development bureaus (Cushing et al,

2005). Taking the broad view, scholars have emphasized that the Chinese government has seen

voluntary adoption of certification standards as an important regulatory policy tool in the

environmental sector and in quality management more generally (Fryxell et al, 2004: 47; Wang

et al, 2009: 575).

Though international certifications have become widespread in China, the certification process

remains costly. Geng and Cote (2003) cite ISO 14001 certification costs ranging from RMB

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109,100 to RMB 191,000 where consultation is required. In present terms, the higher estimate

equates to nearly RMB 250,000. This is before the additional costs of internal restructuring.

Cushing et al (2005) note that though ISO 14001 auditors are sometimes housed within local

economic development or provincial standartdization units, certification activities are their chief

source of funds. In a case study of the costs of Hazard Analysis and Critical Control Point

(HACCP) certification borne by a large Chinese poultry company, (HACCP standards are

integrated into ISO 22000 certification) Wang et al (2009) cite setup costs equal to 5.7% of the

value of the company’s assets and 2% of 2005 gross income (Wang et al, 2009, p.580). Monthly

operating costs associated with meeting HACCP requirements were estimated at US$288,087.

Given the evident costliness of obtaining international certification standards, this practice has

the potential to signal firm quality on the assumption that these costs are more easily borne by

high quality firms. The value of this signal in terms of access to finance should be highest where

information asymmetry is highest. After investigating the effect of certification on access to

finance in the full sample, I determine whether this effect is strongest among smaller firms, about

whom, from the point of view of lenders, information on their intrinsic viability is costlier to

obtain.

3. Data description and estimation strategy

3.1. Sample

On the basis of the preceding discussion, I hypothesize that firms which report holding an

internationally recognized private certification standard will be more likely to have access to

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bank finance than uncertified firms, all else equal. Moreover, since this effect is expected to

derive from the information asymmetry-reducing signal sent by certification, I predict that the

strength of the effect will be higher where information asymmetry is highest. We therefore

expect the effect of certification on access to finance to be stronger among smaller enterprises.

These hypotheses are evaluated using data from the China 2012 Enterprise Surveys Data Set.

Enterprise Surveys, a joint initiative of the International Finance Corporation and the World

Bank, has been conducting firm-level assessments of the business climate in developing

countries since 2002. To date, over 130,000 surveys have been undertaken in 135 countries.

The present survey covered 2,700 privately owned firms in twenty-five Chinese cities and

referred to their operations in the fiscal year 2011.2 Enterprises were selected for participation

using stratified random sampling from the population of non-agricultural firms with at least five

employees. The levels of stratification employed were industry, establishment size and region,

the latter consisting of twenty-five cities.3 It should be noted that though this sampling approach

helps ensure the sampled firms reflect the distribution of manufacturing and services activity

within China, larger firms (in terms of sales revenue) appear to be overrepresented in the sample

relative to smaller firms. This has important implications for the generalization of our results to

all Chinese firms.4

3.2. Variables

2 96% of sampled firms report zero government ownership. 3 Further details on the sampling procedure are available from the “China 2012 Implementation Report”,

downloadable from www.enterprisesurveys.org. 4 China’s National Bureau of Statistics distinguishes between above- and below-scale firms, the former being those

with sales revenue in excess of 5m RMB. As reported in Brandt, Van Biesebroeck and Zhang (2014), the 2008

Economic Census reported that approximately 22% of firms are “above scale”. In the current sample,

approximately 20% are below scale.

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Summary statistics for all variables can be found in Table 1. Operational definitions for all

variables are included in Appendix A.

3.2.1. Certification

Our main independent variable, private standard certification, is a dummy variable taking the

value of 1 when the firm responds affirmatively to the question, “Does this establishment have

an internationally-recognized quality certification?” The questionnaire manual instructs

interviewers that “the question refers exclusively to internationally recognized certifications”,

followed by several examples, and notes that “certifications granted only nationally not

recognized in international markets are not included”.5

3.2.2. Access to finance

Our main dependent variable, loan, is a dummy variable taking the value of 1 when the firm

responds affirmatively to the question, “At this time, does this establishment have a line of credit

or a loan from a financial institution?”

3.2.3. Firm Size

To determine whether the effect of certification on access to finance is stronger where

information asymmetry is likely to be highest, I include the natural logarithm of firm

employment as both a level term and interacted with certification. Using the log value

normalizes the employment variable. This is important as the sample includes a number of very

5 The questionnaire manual is downloadable from:

http://microdata.worldbank.org/index.php/catalog/1559/related_materials. As an exhaustive list of all certifications

obtained by sampled firms is not available, we cannot determine whether responses were in compliance with

interviewer instructions in all cases. Were respondents, despite interviewer instructions, unclear as to which

standards the question referred, this may introduce some noise into the variable.

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large firms which, being outliers, may bias interpretation of the effect of firm size on access to

finance.

3.2.4. Control variables

A number of control variables are included in the analysis. These include measures of firm age

and productivity. Older firms have a longer track record from which banks can infer firm

percentage. Additional factors which may have a signalling effect similar to that of private

certification are included so as to help isolate the unique effect of certification. These are

whether the firm employs an external auditor and the percentage of the firm’s products that are

sold as exports. The analysis below also includes dummy variables indicating the industry in

which the firm operates. Though there is little variation in access to finance across industries,

there is substantial variation in the share of firms which report holding a certification. This

likely reflects the sector-specific nature of some standards covered by the survey question on

certification. Clearly a different signal is sent by certification when a given certification has

diffused more widely within an industry.6 Both certification levels and access to finance vary

considerably across cities in the sample. I therefore include city fixed effects, which act as a

control for all unobserved, city-level characteristics that may affect access to finance.7

(Insert Table 1 about here)

3.3. Estimation strategy

6 For instance, Hazard Analysis and Critical Control Points (HACCP), the principles of which are also covered by

ISO 22000 certification, though general in that it applies to the process of food production, is more likely to be

adopted by firms in the food industry. HACCP is also one of the certifications explicitly referenced in the survey’s

questionnaire manual. I return to across-industry variation in the effects of interest in section 4.3. 7 Numerous studies of Chinese firm financing emphasize the different lending environments in cities across China

(e.g., Ayyagari et al., 2010; Bai et al., 2005; Ruan and Xian, 2013; Wang and Niu, 2014). Considerable variation in

access to finance across cities is also found in the present sample.

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Given our binary dependent variable, logistic regressions are employed to estimate the model

below via maximum likelihood estimation (MLE).

0 1 2 3

4

*

_

ij ij ij ij

ij i j ij

Loan Certified Employment Certification Employment

Other Controls

The subscripts i and j denote the city and industry in which the firm operates, respectively.

ijLoan is a dummy variable taking the value of 1 when the firm has access to finance. ijCertified

is a dummy variable taking the value of 1 when the firm reports holding an internationally

recognized certification standard. ijEmployment is the firm’s employment level in logarithmic

form. * ijCertification Employment interacts certification with firm size. A negative coefficient

on this variable indicates that as firm size increases, the effect of certification on access to

finance declines. _ ijOther Controls refers to the firm-level covariates described above, and i

and j indicate the inclusion of dummy variables for each city and industry. ij is an error term

assumed to have a zero mean.

To facilitate interpretation, odds ratios have been constructed by exponentiatting the log-odds

coefficients returned by MLE.8 The reported ratios should be interpreted as the odds of a firm

accessing finance when the independent variable increases by one unit. In the case of

certification, the coefficient on the certification dummy estimates the odds of certified firms,

relative to uncertified firms, of having access to finance. An odds ratio of 1 would indicate no

difference in the likelihood of access to finance across certified and uncertified firms. To further

facilitate interpretation of results, in some cases I describe the effects of interest with reference to

8 The exponentiation to odds ratios is computed using Stata’s logistic command.

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changes in the predicted probability of access to finance across certified and uncertified firms.

This is especially important where our question of interest is variation in the effect of

certification on access to finance by firm size, as the interpretation of interaction effects in terms

of odds ratios is cumbersome.

The possibility that regression results can be biased by endogeneity generally arises from the

non-random assignment of the variables of interest. In the case of private certification, however,

signalling theory requires non-random assignment of private certification. Indeed, were

certification adoption random with respect to unobserved firm characteristics, certification would

not serve a signalling function. The empirical challenge, rather, is to identify the unique effect of

certification over and above the firm-level characteristics with which it is necessarily correlated.

The approach taken here is to use available data to control for these characteristics as completely

as possible. A preferable approach would be to measure the “sheepskin effect” of certification

by comparing certified firms with those whose certification is currently in process.9 While the

current survey does enable firms to indicate whether their certification is in process, as only 14

firms respond affirmatively, this approach is not pursued. The greater danger of endogeneity

arises from our inability to date the firm’s certification using the available cross-sectional data.

It may be, for instance, that some firms in the sample received access to finance prior to adopting

certification. This possibility is an important caveat to the results reported below, and further

research using firm-level panel data on Chinese firms would help to address this limitation.

Further, there is also the danger that other unobserved firm characteristics that are not correlated

with firm quality, such as political connections, may predict access to finance. Future research

9 Identification of this effect has been of interest to those evaluating the signalling effects of education in labor

markets. See, for instance, Belman and Heywood (1997).

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using panel data would also help to address this concern, and the cross-sectional nature of the

data employed here must be kept in mind.

4. Results

4.1. Main results

Estimates of the effects of certification on access to finance are reported in column (1) of Table

2. Certified firms are 1.68 times as likely to report access to finance as otherwise equal

noncertified firms. The effect is statistically significant at the one percent level. Larger, more

productive firms who employ external auditors are also more likely to report access to finance.

Whether this effect is conditional on firm size is investigated in column (2). The negative

coefficient on the interaction term indicates that as firm size increases, the effect of certification

on access to finance decreases. Put differently, the gap between certified and uncertified firms in

the predicted probability of accessing finance is decreasing with firm size.

(Insert Table 2 about here)

The estimated effects of certification on the predicted probability of access to finance at different

firm sizes is reported in Table 3. Though the fixed effect model employed above is preferable

where industry and city-specific intrinsic characteristics are important factors, presenting the

effects of certification on access to finance in terms of predicted probabilities within each city

and industry becomes cumbersome. For ease of explication, I pool all firms into a single logistic

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regression to present these estimates.10 Keep in mind also that firm employment has undergone a

natural logarithmic transformation before probabilities are calculated. The real employment

values corresponding to evenly-spaced increases in the logarithmic scale appear in the first

column of Table 3. All other variables are held at their mean levels in calculating these predicted

probabilities. Moving to larger firms as the rows descend, the second column reports the

probability of an uncertified firm of a designated size receiving finance. In the third column, a

similarly sized certified firm’s probability of receiving finance is reported. The difference is

calculated in the final column. We can see that the effect of certification on the likelihood of

receiving finance is particularly strong for small firms. This effect is represented graphically in

Figure 1, in which the solid line represents the predicted probability of access to finance among

certified firms as employment increases. The dashed line conveys the same information for

uncertified firms.

(Insert Table 3 about here)

(Insert Figure 1 about here)

5. Discussion

Previous research has indicated the need for credible signals of firm quality in order to reduce the

information asymmetry that contributes to the credit constraints faced by Chinese SMEs. This

paper presents evidence consistent with the view that the adoption of internationally recognized

certification standards can enable firms to credibly signal their underlying quality to lenders.

10 The parameter estimate (0.835) and standard error (0.070) on the interaction term are similar to those estimated

via the fixed effects model as seen in column (2), Table 2.

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Moreover, the strength of the association between certification and the likelihood of access to

bank finance is strongest among small firms. Improved access to finance for SMEs seems to be

an unanticipated consequence of Chinese policy publicizing international certification standards

and regulating the certification process. Imagined as a tool to ensure firm compliance with

environmental and management standards, the policy has inadvertently improved SMEs access

to finance.

These findings have limitations that, given the nature of the signalling dynamic, are difficult to

overcome. As noted above, signalling theory requires the non-random assignment of

certification. Indeed, any sources of variation in the likelihood of certification which are

exogenous to the firm may, if they amount to reductions in the cost of certification for all firms

seeking finance, make it more difficult for lenders to assess the signal’s credibility. The signal’s

information content would then be reduced. The cross-sectional nature of our dataset preclude

observing changes in firm financing in the advent of a firm’s certification. Even were firm level

panel data at hand, however, we would still face the prospect that firms are more likely to pursue

certification when their intrinsic quality improves. Such firm-level changes violate the

identifying assumption underlying inference based on panel data, namely constant intrinsic

characteristics.

The question of whether these results imply that the further diffusion of certification standards

could lead to still greater reductions in information asymmetry and improved access to finance

must be approached with care. Recall that information asymmetry is reduced by credible signals

of otherwise unobservable firm quality. In order to credibly differentiate firms, the signal must

not merely be costly from the firm’s point of view, but must be perceived as such by lenders.

Though the continued diffusion of certification standards would seem to offer opportunities for

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firms to credibly signal their quality, the signalling dynamic may impose natural limits to the

signaling value of certification. If lenders assess the costliness of certification retrospectively on

the basis of certified and uncertified firms’ loan repayment rates, increasing diffusion may lead

them to adjust downward their perception of the signal’s credibility. The more commonly a

signal is sent, the less information it conveys. This would suggest there is an optimal level of

certification diffusion from the point of view of firm access to finance. From the lender’s

perspective, efficiency is attained when signal is costly enough to be worth sending only for

firms with a sufficiently high probability of loan repayment, but not so costly that high quality

firms (firms likely to repay a loan), find signalling costs prohibitive. With a view toward

continued diffusion of certifications and firm finance, the key question is whether what prevents

further diffusion is certification’s costliness or lack of awareness of certification’s signalling

potential. If the latter, firms may continue to derive unintended benefits from government policy

encouraging certification diffusion.

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References

Allen, F., Qian, J., Zhang, C., & Zhao, M. (2012). China's financial system: Opportunities and

challenges. Capitalizing China (pp. 63-143) University of Chicago Press.

Akerlof, G. A. (1970). The market for" lemons": Quality uncertainty and the market

mechanism. The quarterly journal of economics, 488-500.

Ayyagari, M., Demirgüç-Kunt, A., & Maksimovic, V. (2010). Formal versus informal finance:

Evidence from China. Review of Financial Studies, 23(8), 3048-3097.

Bai, C., Lu, J., & Tao, Z. (2006). Property rights protection and access to bank loans. Economics

of Transition, 14(4), 611-628.

Belman, D., & Heywood, J. S. (1997). Sheepskin effects by cohort: Implications of job matching

in a signaling model. Oxford Economic Papers, 49(4), 623-637.

Brandt, L., & Li, H. (2003). Bank discrimination in transition economies: ideology, information,

or incentives?. Journal of comparative economics, 31(3), 387-413.Choi, E. K. (2009). The

politics of fee extraction from private enterprises, 1996-2003. The China Journal, 79-102.

Brandt, L., Van Biesebroeck, J., & Zhang, Y. (2014). Challenges of working with the Chinese

NBS firm-level data. China Economic Review, 30, 339-352.

Connelly, B. L., Certo, S. T., Ireland, R. D., & Reutzel, C. R. (2011). Signaling theory: A review

and assessment. Journal of Management, 37(1), 39-67.

Corbett, C. J., & Yeung, A. C. (2008). Special issue on meta-standards in operations

management: Cross-disciplinary perspectives. International Journal of Production

Economics, 113(1), 1-2.

Cushing, K. K., McGray, H., & Lu, H. (2005). Understanding ISO 14001 adoption and

implementation in China. International journal of environment and sustainable

development, 4(3), 246-268.

Escanciano, C., Fernández, E., & Vázquez, C. (2001). ISO 9000 certification and quality

management in Spain: Results of a national survey. The TQM Magazine, 13(3), 192-200.

21

Firth, M., Lin, C., Liu, P., & Wong, S. M. (2009). Inside the black box: Bank credit allocation in

China’s private sector. Journal of Banking & Finance, 33(6), 1144-1155.

Fryxell, G. E., Chung, S. S., & Lo, C. W. (2004). Does the selection of ISO 14001 registrars

matter? Registrar reputation and environmental policy statements in China. Journal of

environmental management, 71(1), 45-57.

Geng, Y., & Côté, R. (2003). Environmental management systems at the industrial park level in

China. Environmental management, 31(6), 784-794.

Heras‐Saizarbitoria, I., & Boiral, O. (2013). ISO 9001 and ISO 14001: Towards a research

agenda on management system standards. International Journal of Management

Reviews, 15(1), 47-65.

Hillier, B., & Ibrahimo, M. V. (1993). Asymmetric information and models of credit

rationing. Bulletin of Economic Research, 45(4), 271-304.

Huang, Y. (2008). Capitalism with Chinese characteristics: Entrepreneurship and the state (Vol.

1). Cambridge: Cambridge University Press.

International Standards Organization. (2012). The ISO survey of management system standard

certifications – 2012. http://www.iso.org/iso/iso_survey_executive-summary.pdf

Jang, W., & Lin, C. (2008). An integrated framework for ISO 9000 motivation, depth of ISO

implementation and firm performance: The case of Taiwan. Journal of Manufacturing

Technology Management, 19(2), 194-216.

Kirmani, A., & Rao, A. R. (2000). No pain, no gain: A critical review of the literature on

signaling unobservable product quality. Journal of Marketing, 64(2), 66-79.

Korkeamäki, T., Pöyry, S., & Suo, M. (2014). Credit ratings and information asymmetry on the

Chinese syndicated loan market. China Economic Review,31, 1-16.

Kunnanatt, J. T. (2007). Impact of ISO 9000 on organizational climate: Strategic change

management experience of an Indian organization. International Journal of

Manpower, 28(2), 175-192.

Levine, R. (1997). Financial development and economic growth: views and agenda. Journal of

Economic Literature, 688-726.

Maskus, K. E., Otsuki, T., & Wilson, J. S. (2005). The cost of compliance with product

standards for firms in developing countries: An econometric study World Bank

Publications.

Minard, P. (2014). Government discretion: how high a barrier to entry for Chinese private

enterprises?. Journal of Asian Public Policy, (ahead-of-print), 1-15.

22

Montiel, I., Husted, B. W., & Christmann, P. (2012). Using private management standard

certification to reduce information asymmetries in corrupt environments. Strategic

Management Journal, 33(9), 1103-1113.

North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge

university press.

Pearson, M. M. (2007). Governing the Chinese economy: regulatory reform in the service of the

state. Public Administration Review, 67(4), 718-730.

Poncet, S., Steingress, W., & Vandenbussche, H. (2010). Financial constraints in China: Firm-

level evidence. China Economic Review, 21(3), 411-422.

Potoski, M., & Prakash, A. (2009). Information asymmetries as trade barriers: ISO 9000

increases international commerce. Journal of Policy Analysis and Management, 28(2), 221-

238.

Ruan, W., & Xiang, E. (2013). Which companies find it easier to obtain bank loans? Evidence

from China. Corporate Ownership and Control, 10(3), 389-401.

Stevenson, T. H., & Barnes, F. C. (2002). What industrial marketers need to know now about

ISO 9000 certification: A review, update, and integration with marketing. Industrial

Marketing Management, 31(8), 695-703.

Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355-374.

Tsai, K. S. (2004). Imperfect substitutes: the local political economy of informal finance and

microfinance in rural China and India. World Development, 32(9), 1487-1507.

Terlaak, A., & King, A. A. (2006). The effect of certification with the ISO 9000 quality

management standard: A signaling approach. Journal of Economic Behavior &

Organization, 60(4), 579-602.

Uzumeri, M. V. (1997). ISO 9000 and other metastandards: Principles for management

practice? The Academy of Management Executive, 11(1), 21-36.

Wang, C., & Niu, T. (2014). Bank finance heterogeneity in China: Micro-level evidence. Applied

Economics Letters, 21(2), 103-106.

Wang, Z., Yuan, H., & Gale, F. (2009). Costs of adopting a hazard analysis critical control point

system: case study of a Chinese poultry processing firm.Review of Agricultural

Economics, 31(3), 574-588.

Williamson, O. E. (1979). Transaction-cost economics: The governance of contractual

relations. Journal of Law and Economics, 22(2), 233-261.

23

Yeung, G. (2009). How banks in China make lending decisions. Journal of Contemporary

China, 18(59), 285-302.

Young, S. (1989). Policy, practice and the private sector in China. The Australian Journal of

Chinese Affairs, 57-80.

Zhang, M. (2008). From public to private: The newly enacted Chinese property law and the

protection of property rights in China. Berkeley Business Law Journal, 5.

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Table 1. Descriptive statistics

Variable Mean SD Min Max Obs

Loan 0.313 0.464 0 1 2588

Loan private 0.296 0.457 0 1 2700

Loan state 0.250 0.433 0 1 2532

Collateral as

percent

2.024 6.178 0.14 135.714 498

Certification 0.620 0.485 0 1 2669

Firm employment 4.152 1.367 1.386 10.308 2699

External auditor 0.710 0.454 0 1 2658

Firm age 7.601 0.004 7.543 7.609 2627

Export status 6.932 20.469 0 100 2698

Productivity 1381343 9733346 6764.706 450m 2539

City certification 62.111 16.240 27 97.5 2700

Notes: Variation in observations for each variable reflects non-response. For purposes of this analysis, those survey

responses categorized as “don’t know” have been translated into non-response.

Table 2. Determinants of firm access to finance: regression results

(1) (2)

Certification 1.678***

(0.230)

4.439***

(1.867)

Employment 1.555***

(0.077)

1.846***

(0.160)

Certification*Employment - 0.785**

(0.077)

External auditor 2.567***

(0.374)

2.540***

(0.371)

Firm age 0.230

(3.309)

0.016

(0.226)

Export status 1.004

(0.003)

1.003

(0.003)

25

Productivity 1.313***

(0.067)

1.321***

(0.068) 2R 0.288 0.290

Observations 2333 2333

Notes: Standard errors in parentheses. *, ** and *** indicate statistical significance at the 10, 5 and 1% levels,

respectively. Dependent variable is Loan. All columns include city and industry fixed effects. Details on

construction and sources of all variables available in Appendix A. Estimates are derived from maximum likelihood

estimation.

Table 3. Effect of certification on access to finance at employment levels

Employment

level

Pr (finance),

Certification = 0

Pr (finance),

Certification = 1

Difference

4 8.8% 15.4% 6.6%

7 11.1% 17.8% 6.7%

11 14.0% 20.5% 6.5%

18 17.5% 23.4% 5.9%

30 21.6% 26.7% 5.1%

50 26.4% 30.2% 3.8%

81 31.9% 34.0% 2.1%

134 37.8% 38.0% 0.2% Notes: Coefficient estimates derived by calculation of simple slope.

26

Figure 1. Predicted probability of access to finance

APPENDIX A: VARIABLE OPERATIONALIZATIONS

Variable Description

Loan Dummy variable: value 1 if firm

reports access to bank loan,

otherwise 0

Certification Dummy variable: value 1 if firm has

private certification, otherwise 0

Firm

employment

Natural logarithm of firm

employment

External auditor Dummy variable: value 1 if firm uses

external accounting auditor,

otherwise 0

Firm age Logarithm of firm age in years

Export status Variable indicating percent of firm’s

sales which are direct exports

Productivity Logarithm of two-year sum of firm

sales divided by number of

employees

.1.2

.3.4

Pr

(Access to

Fin

ance

)

1.39 1.89 2.39 2.89 3.39 3.89 4.39 4.89Employment (natural log scale)

Uncertified Certified

Predicted probability of access to finance

27

Certification

interaction

Variable interacting certification

dummy variable with Firm

employment

City fixed

effects

Series of dummy variables indicating

firm operation in one of 25 cities.

Industry fixed

effects

Series of dummy variables indicating

firm operation in one of 26 industries

Notes: Firms instructed to respond to survey questions with reference to fiscal year 2011 except where

specified. Source for all variables is China 2012 Enterprise Survey.