OSIPP Discussion Paper : DP-2011-E-005

Effect of ISO Standards on Exports of Firms in Eastern Europe andCentral Asia: An Application of the Control Function Approach

June 8, 2011

Tsunehiro Otsuki
Associate Professor, Osaka School of International Public Policy (OSIPP)【Keywords 】Control Function, international standards, international trade,self-selection【JEL Codes】C34, F10, L15【Abstract】
Growing number of firms in developing countries have earned certifications such
as International Standards Organization (ISO) as it enhances reputation of theircompany or brand and attract buyers particularly in export market. This studyevaluates the effect of international standards certification on firm’s export
performance in Europe and Central Asia by applying the control function approachwith endogenous treatment effect to firm-level data. Certification is found toincrease export share in firm’s sales by 44.9% on average. The results suggest that
ignoring the effect of self-selection of certification leads to a substantial bias in theestimated treatment effect.

Correspondence: Tsunehiro Otsuki, The Osaka School of International Public
Policy, Osaka University, 1-31 Machikaneyama-cho, Toyonaka, Osaka 560-0043
Japan.
E-mail address: otsuki@osipp.osaka-u.ac.jp
Acknowledgement: I am grateful for financial support from the Japan Society for
the Promotion of Science, Grant-in-Aid for Scientific Research (B), 2010-2013.

1.

Introduction

One of the recognized roles of international standards is to mitigate trade losses
associated with the mandatory standards imposed by importing countries as thosestandards are set based on each country’s safety or quality criteria which do notnecessarily conform with the international norm (Maskus and Wilson, 2000).
International standards certification may be particularly important for exporters indeveloping economies, who compete with firms in developed countries that have longer
histories and better reputations in export markets. Firms that are certified as meetinginternational standards create favorable perceptions of their company or brand andattract buyers (Acharyya, 2005). For example, the number of firms in Central andEastern Europe and Central Asia (Europe and Central Asia, hereafter) that earned ISO
9001 rose 6.6 times to 109,000 from 2002 to 2008, according to ISO surveys (ISO, 2006,2008).
On the other hand, costs to attain international certification—application fees, monetaryand human effort, and maintenance—may limit the ability of developing country firmsto export. Thus, a firm’s decision on acquisition of international standards depends on
net benefit to firms. Benefits of certification may be difficult to predict because thebenefits depend on many uncertain factors such as consumer’s valuation of certification.
Several studies found a higher sales and export for firms certified with internationalstandards (for example, Heras, Dick, and Casadesús (2002), Naveh and Marcus (2005),Ferro (2011)). But the previous studies do not consider the endogeneity of certification;firms that pursue certification are self-selecting with the expected returns in mind. This
study applies a control function (CF) approach with endogenous treatment variable
based on Heckman’s selection model. The CF approach yields a consistent estimator of
the effect of treatment (certification) by correcting for the sample selection bias as wellas controlling for covariates that affect the outcome. In addition, the previous studies do
not consider heterogeneity in effects across firms. This study also allows the treatment
effect to vary across firms.

We estimate the benefit of international standards certification on exports ofmanufacturing and service sector firms in the developing economies of Europe andCentral Asia in 2002, 2005, and 2008/2009. The countries in this region are integrating
or seeking to be integrated into the EU, and it is important that firms meet international
standards when accessing to and competing in the EU market. We use firm-level data of
25 countries from the Enterprise Survey of the World Bank for production, sales andexport performance, certification and business environment.
The reminder of the paper is organized as follows. Section 2 develops the empiricalmodel. Section 3 describes the data used for the estimation. Section 4 presents anddiscusses the estimation results. Section 5 concludes.

2.

Model

This study uses firm-level data of 25 countries to evaluate the effect of earninginternational standards certification on a firm’s export performance. This analysis faces
a problem that is typical in nonexperimental data; the samples were not madecomparable between treated (certified) and untreated (uncertified) firms with identicalcharacteristics as in the experimental data. The literature regarding program evaluation
has addressed problems associated with using nonexperimental data throughrandomization. The randomization makes individuals in a treatment group (the group
participating in the program) and a comparison group (group not participating in theprogram) comparable. Matching methods introduced by Rosenbaum and Rubin (1983)
have been widely used and they randomize the data through a propensity score (aprobability of participation determined by individual characteristics).

In addition to randomization, the CF approach with endogenous treatment variableaccommodates the self-selection of participating firms while the matching estimatorssuffer from bias due to the violation of mean conditional independence (see, forexample, Cameron and Trivedi, 2005). Because seeking international certification is afirm’s decision, acquiring these standards is endogenous. The CF approach explicitly
corrects for the potential bias in the fashion of Heckman’s (1979) selection model.
Further, randomization is conducted through the selection equation in the CF methods,
which is equivalent to that in matching methods using a propensity score. Thus, in ourstudy, it is appropriate to use the CF approach because of the need for randomizationand the endogenous nature of participation.
Let y denote the outcome (export performance in our case) and d denote a dummy
treatment variable (international standards certification in our case) with value of 1 if
treated and 0 otherwise. The two outcomes y1 and y0 are associated with the treatedstate ( d  1 ) and the untreated state ( d  0 ), respectively.
Let z denote the variables that determine participation. The expected outcome is afunction of x and d .
E[ui | xi , d ]  E[ui | xi , di , z i ](1)Consider the following model:
y1i  xi ' 1  u1i(2a)y0 i  x i '  0  u 0 i(2b)di*  w i '    i(2c)where (2a) and (2b) are the outcome equation, and (2c) is the selection equation. The
variable d i* is a latent variable such that1 iff di*  0di  *
0 iff di  0and w  {x, z} . The vector z is a vector of the variables not contained in the outcome
equations and is included in the selection equation. It is assumed thatE[u1 | x, z ]  E[u0 | x, z ]  0 . It is also assumed that the error terms (u1i , u0i ,  i ) follow a
joint trivariate normal distribution with zero mean and covariance matrix 11  10  1    10  00  0  .
 1  0
1 The variance of  is normalized to 1 for identification. The nonzero covarianceparameters  1 and  0 reflect the endogeneity of the treatment variable.

The benefit of treatment can be evaluated in two ways. The average treatment effect(ATE) measures the population average of the treatment effects. By definition, the ATEis given by
ATE  E[ y1  y0 | x]  E[x]( 1   0 ) .

(3)

The average treatment effect on treated (ATT) measures the effect of treatment on thetreated samples, and hence, the benefit of participation. According to Maddala (1983),
the treatment effect for the treated sample i is given byTTi  E[ y1i  y0i | xi , di  1]  E[ y1i | xi , di  1]  E[ y0i | xi , di  1]
 x( 1   0 )  ( 0   1 )

 (w '  ).
 (w '  )(4)The second term represents the effect of selection, and  0   1  0 if the program
produces a greater benefit under self-selection than under random assignment. The
average of TT over the treated individuals gives the ATT.
The treatment effects can be estimated by applying Heckman’s (1979) two-stepestimation separately to the subsample with d  1 and d  0 (Maddala, 1983) as ityields a consistent estimator by controlling for the effect of sample selection. The probit
model is used to estimate the contribution of x and z in the self-selection of a firm toacquire certification.

3.

Data

We use firm-level data for 25 countries in Europe and Central Asia in 2002, 2005,2008/2009 from the Enterprise Survey of the World Bank. It includes data forestablishments of all sizes in manufacturing and service industries and provides aselection of information regarding production and marketing performance, and thebusiness environment in all establishments. Some firms were interviewed more thanonce, but the data will not allow us to explore the nature of panel data since two-thirdsof the firms were interviewed only once. The descriptive statistics are presented inTable 1. Out of the entire cleaned sample of 25,554 firms, we use 2164 observations
after eliminating samples with missing data.

Share of export in total sales is used to measure export performance. Acquisition ofinternational standards is a dummy variable with the value 1 if acquire, and 0 otherwise;
thus, it represents the treatment status. The outcome-equation covariates ( x ) and thevariables in the selection equation that are excluded from the outcome-equation ( z ) arealso included in the table.

Table 1. Summary statistics for the variables used in the estimation (N = 2164)
Variable

Mean

Std. Dev.

MinMaxShare of export in sales

0.163

0.284

01

Acquisition of internationally recognized standards such as ISO

0.326

0.468

01

Share of foreign ownership

0.138

0.315

01

Firm size as the number of workers

63.68836.4806100

Firm age as the number of years since the firm is established21.46023.411

2184

Ratio of expenditure on R&D to sales

0.035

0.066

00.8

Visit of external auditors to check financial statements

0.6730.469

01

Percentage of production workers who received training program

24.53731.5050100

Percentage of nonproduction workers who received training program

11.36323.794

0100

2.373

1.168

14

2.982

0.984

14

Explanatory variables x

Explanatory variables z

Degree of importance of pressures from foreign market in decisions todevelop new products or services (1=Not at all important, 2 =Slightlyimportant, 3=Fairly important, 4=Very important)Degree of importance of pressures from domestic consumers in decisions
to develop new products or services (the same as above)

Source: Author’s calculation based on 2002, 2005 and 2008/2009 Enterprise Surveys.

4.

Results

Table 2 presents the results of the estimation of the CF model with and without therestriction of homogeneous treatment effects across the samples. The results of ordinary
least squares (OLS) are also presented for the comparison purpose.

The lower portion of the table shows the results of the selection equation which iscommon between the two CF models. It is found that the probability of acquiring
international certification is greater for larger firms, possibly reflecting that the fixed
cost of acquiring certification is a great obstacle for smaller firms. It is also found thatfirms inspected by external auditors tend to acquire international certification. In
addition, the provision of training of production and nonproduction workers, and thepresence of pressure in foreign markets and from domestic consumers will foster
certification.

The upper portion of Table 2 presents the results of the outcome equation. Among theslope coefficients, that for the share of foreign ownership is positive and significant in
the CF models as is expected. The model of homogenous treatment effects impose

0  1 and  0   1 in the CF model, implying a constant ATE and ATT. The ATE
is estimated to be 0.428 as shown in Table 3.1 This implies that certification will raise
the share of export in total sales of a firm by 42.8%. This ATE is much larger than thecoefficient for international standards (0.084) in the OLS model, illustrating that theOLS tends to under-estimate the effect of certification both by not randomizing thesamples and by ignoring the effect of self-selection. The same inference applies to theprevious studies that ignore the self-selection nature of certification.

1The estimated ATE is statistically significant at the 1 percent level based on Wooldridge’s (2010)
estimation procedure using OLS with the pooled samples.

Table 2. Results of the Heckman two-step estimation (N = 2164)
Outcome equation(y=Share of export in total sales)

Foreign ownership
Firm size
Firm age

Homogeneous
treatment
effect0.14365(0.02174)
0.00033(0.00026)-0.00002(0.00031)

Heterogeneous
treatment
effectEquation (2a)***0.12742(0.03615)
0.00082(0.00056)
0.00018(0.00050)

OLS
Equation (2b)***0.15333(0.02441)
0.00012(0.00029)-0.00017(0.00035)***

International standards
Constant-0.01696(0.01445)

Selection equation (d=acquisition ofinternational standards)
Foreign ownership
Firm size
Firm age
R&D
Auditors
Training of production workers
Training of non-production workers
Pressures from foreign market
Pressures from consumers
Constant

 j , j  0,1
Model  2 ( P-value)

0.05072(0.09407)
0.00855(0.00096)
0.00238(0.00129)0.16610(0.44942)
0.22929(0.06895)
0.00391(0.00102)
0.00675(0.00135)
0.12948(0.02713)
0.07813(0.03243)-1.98551(0.12716)-0.22104

0.33287(0.08591)***-0.18204***-0.01883(0.01602)

0.1617(0.0187)
0.0014(0,0002)0.0003(0.0003)0.0840(0.0128)0.0137(0.0119)

***
*

***
***
***
***
**
***

***

0.25445(0.03271)(0.04917)(0.04302)

248.47 (0)14.84 (0)42.44 (0)***Note: Inside the parenthesis is standard error. “*”, “**”, and “***” denote 10, 5 and 1 percent
significance.

adj R2=0.11
7

***
***

***
***

In the model of heterogeneous treatment effects, the mean ATE is 0.449, which is close
to that in the model of homogeneous treatment effects. Its low standard deviation(0.030) implies a low variation of the ATE that is caused by the observable factors. The
ATE is higher for the manufacturing sector (0.456) than for the service sector (0.442)
presumably because the former is more actively involved in export. Among the studiedcountries, Turkey holds the highest mean ATE (0.460), and Latvia holds the lowest
mean ATE (0.436). The mean ATT is 0.833 with a moderate standard deviation (0.138).
It is far larger than the mean ATE, and this difference is mainly accounted for by theselection effect.2 The positive selection effect implies that firms that have unobservableadvantage in export—for example, superior managerial skill and knowledge about
consumer’s preference regarding certification—tend to acquire international standards.
Those firms acquire certification knowing that they can potentially expand their sales inforeign market with it.

Table 3. The estimated effect of international standards
MeanStd. Dev.

MinMax

OLS
0.0840
CF with homogeneous treatment effect
ATE, ATT

0.4283

CF with heterogeneous treatment effectATE

0.44910.02970.38010.5343ATT

0.83300.13770.51401.2667

Robustness of the results of the CF model regarding the treatment effect can be
examined by comparing the current result with predicted results based on different
subsample. We predict ATE and ATT for the 2005 and 2008/2009 subsamples using themodel estimated using only the 2002 subsample. The mean predicted ATE is slightlyhigher—0.525 in 2005 and 0.531 in 2008/2009. In contrast, the mean predicted ATT isconsiderably high and beyond the upper limit—1.189 in 2005 and 1.126 in 2008/2009
2The maximum ATT exceeds 1 because the standard calculation of the ATT does not impose bounds.

although correlation between the current and predicted ATT is reasonably high (0.946in 2005 and 0.883 in 2008/2009). Thus, the degree of the endogeneity of certification is
not constant over time, and it is weaker in the recent years, possibly reflecting thedeclining brand effect certification over time.

5.

Conclusions

This study evaluates the effect of international standards certification on firm’s export
performance in Europe and Central Asia by applying the control function approach withendogenous treatment effect to firm-level data. Certification is found to increase export
share in firm’s sales by 44.9% on average. The results demonstrate that ignoring theeffect of self-selection of certification leads to a substantial bias in the estimatedtreatment effect.

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