Discussion Papers In Economics
And Business

Productivity, Capital Intensity and ISO14001
Adoption―Theory and Evidence from Vietnam
Bin NiDiscussion Paper 15-26

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANProductivity, Capital Intensity and ISO14001
Adoption―Theory and Evidence from Vietnam
Bin NiDiscussion Paper 15-26
October 2015

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANProductivity, Capital Intensity and ISO14001
Adoption—Theory and Evidence from Vietnam
Bin Ni∗[2015/10]

Abstract
The determinants of ISO14001 adoption have been considered to fall into two categories:
the external pressure from environment-oriented stakeholders or customers; the internal
need due to expected future benefits. In this paper we take a step further to elaborateon the mechanism of firms’ adoption by investigating the interrelationship among firms’
productivity, capital intensity and the decision-making of the adoption. Applying a generalequilibrium model, we show that under optimal condition, highly productive firms can benefit
more from the adoption. In the meantime technology advancement potentially drives up thecapital intensity of the firms, and this factor will positively aﬀect firms’ incentive of adoption
as well. The empirical practice using the firm-level data in Vietnam verifies our predictions
with robustness. In addition, we find that the phenomenon outlined above becomes evenmore obvious in the manufacturing sectors.
Keywords: productivity, capital intensity, ISO14001, Vietnam, environmental protection.
JEL Classification Numbers: D22, F21, F64, Q56.

∗

Corresponding author. The Graduate School of Economics, Osaka University (jiadaniel@hotmail.com)

1

Introduction

Due to a rising awareness of environmental protection, there has been an increasing literature to study the determinants of ISO14001, a voluntary environmental management program. Research on external factors indicates that pressure from environmentally conscious
customers plays a important in firms’ adoption of ISO14001 (Nishitani, 2010). Whereasinternal determinants such as firm size, the status of having quality management system andmarket scope of the industry that the firm belongs to are shown to be important factors(Arimura et al., 2008, 2011; Nakamura et al., 2001; Welch et al., 2002).
Nevertheless, all these studies try to locate the determinants of ISO14001 adoption froma relatively objective perspective. From the point view of the firms themselves, what are thesystematic incentives for them to spend substantial cost on adopting this standard even if it
is voluntary rather than compulsory? What is the starting point for firms to think about the
adoption originally? It is natural to assume that when firms are technologically struggling,
usually they can’t aﬀord to spend extra money on self-regulated environmental activities.
In other words, firms with technology advancement will have better chance to engage inenvironmental protection activities, In fact, recent studies by Levinson (2009), Shapiro andWalker (2015) have shown a negative relationship between firms’ productivity (technology)
and pollution intensity in US.
Following this logic, we pay a special attention to the relationship between firms’ initialtechnology level and their participation rate in the voluntary environmental program. Drawnfrom the firm-level survey data in Vietnam, Figure-1 indicates the diﬀerence in total factor
productivity (TFP) for diﬀerent groups of firms prior to ISO14001 adoption. As we can see,the average TFP for ISO14001 adopted firms is higher than that for non ISO14001 adopted
ones. Consistent with the previous studies, it occurs to us that the heterogeneity in TFP
tends to be an important decisive factor for firms to adopt the standard.

Figure-1 is inserted here
On the other hand, factor endowment hypothesis, brought forward by Copeland andTaylor (2004), presents as another interesting theory to describe the relationship between
factor intensity and pollution behavior in the context of international trade1 . However,research on the direct relationship between a firm’s factor intensity (we focus on capitalintensity in this paper) and its decision to engage in environmental protection, is very scare.
1

The hypothesis argues that when trade liberalizes, countries that are abundant in factors used in clean
industries will grow cleaner.

1Some of the existing studies mention the positive correlation between capital intensity andpollution (Mani and Wheeler 1997), but none has taken a step further to investigate howcapital intensity matters for firms’ commitment to environmental protection. Our interest
thus lies in the question that under the same pollution level, will capital-intensive firms havehigher/lower incentive to participate in environmental protection program voluntarily?
To answer the above questions and make clear the interrelationship among firms’ productivity, capital intensity and their adoption of ISO14001, we employ an analytical generalequilibrium model. Driven by the stylized fact as in Figure-1, we put additional assumption
on firms’ heterogeneity, which is modeled by their diﬀerential productivity. Each firm draws
a unique productivity level, which leads firms to diﬀer in their equilibrium price markup and
expected total profits. Meanwhile the equilibrium productivity level will aﬀect the capitalintensity of a firm2 , and ultimately aﬀects the firm’s decision of adopting ISO14001. We thentake the model to the data. Relying upon the detailed firm-level data taken from annual
enterprise survey in General Statistics Oﬃce in Vietnam, we find that productive firms andcapital-intensive firms have higher incentive to adopt ISO14001, which is consistent withthe predictions from our theoretical model. Other control variables such as firm size andforeign capital share also play significant role in shaping the decision on ISO14001 adoption.
In the subgroup estimation, we find that the influence of productivity and capital intensity
becomes stronger for manufacturing firms to adopt ISO14001 than for non manufacturing
ones. Whereas foreign capital share turns out to be insignificant for non manufacturing firms
to make the decision.
Our paper contributes to the existing literature in several ways. First, the theoreticalmodel weaves together the factors from industrial organization and environmental economics,
using the framework of international trade literature. To our best knowledge, it is the pioneer
one of its kind. Second, we concentratedly analyze the role of the productivity and capitalintensity in shaping a firm’s decision-making of ISO14001 adoption. This is one of the few
studies that attempt to clarify the mechanism behind firms’ participation in a voluntary
environmental program. Third, by far there has been no research to study the determinantsof ISO14001 in the context of Vietnam. We aim to fill in this blank by making use of thefirm-level information in Vietnam.
The paper is organized as follows: in the next section we talk briefly about the ISO14001
and why it is important to be concerned about environmental protection in the context ofVietnam. Literature review comes after. In section 4 we apply a theoretical model to show
how firms’ decisions are made. In section 5 we describe the data and estimation strategy,
followed by robustness check and findings. The final section concludes.
2

Or the capital intensity can be modeled as exogenous, depending on the functional assumption.

2

2

Background

2.1

About ISO14001

The International Organization for Standardization (ISO) was founded in 1946, whichhas 162 members3 by far, each representing a country. It is the most prominent developer ofstandards in the world. In 1980s, ISO introduced ISO9000 standards for quality manufacturing practices. Building on this system, ISO set up ISO14001 environmental standards in19964 . According to the definition by ISO, this standard enables firms to adopt the policy
following the legal requirements and provides them with update environmental information.
In other words, it forces the organizations to raise self-awareness of maintaining a healthy
environment and assure themselves of conformity with their stated policies. The benefits of
ISO14001 include, but not limited to: reduced cost of waste management and distribution;savings in consumption of energy and materials; improved corporate image among regulators, customers and the public (ISO Homepage). Despite all the merits, ISO14001 does notcome for free. Due to complicated application procedure, the standard practice is to entrustan ISO-accredited third party with all the evaluation and paperworks. According to Jiang
and Bansal (2003), the initial consulting fee usually ranges from 24,000 to 128,000 USD. The
additional spending will include training expenses, application fee, auditing fee, etc. Though
the total cost varies from country to country, it can become quite a burden, especially forsmall and medium sized firms. Thus firms need to weigh the benefits against the expenditure
discreetly before making the decision to apply.

2.2

Why is the issue important in Vietnam?

The pollution level in Vietnam is highly proportionate to its economic growth that depends on the fast industrialization. From Figure 2, we can see that the total pollution in
Vietnam has risen by nearly 150 percent over five years. Decomposing the contents, we findthat most of the increase comes from air and solid waste, most of the discharge comes fromindustrial activities. Take air pollution, for instance, nearly half of Nitrogen dioxide (N O2 )emission is due to industrial development. When it comes to Sulfur dioxide (SO2 ), manufacturing industry turns out to be the major source (Vietnam: Air Quality Profile 2010).
These two kinds of pollutants are detrimental to both human health and the environment.

3

http://www.iso.org/iso/about/iso member.htm Accessed on 2015/10/19.
In recent years, ISO22000 food safety standards, ISO26000 social responsibility standards, ISO36000
risk management standards, and ISO50001 energy management systems are also introduced.
4

3

Figure-2 is inserted here
The pollution in Vietnam is on the verge of eruption and urgent solutions are sought toprevent the situation from getting worse. By using ISO14001—a voluntary environmental
program as the benchmark, we would like to investigate what are the most important factors
to aﬀect firms’ engagement in this program. Because such international standard, among
many others, is proved to be eﬀective in curbing the pollution behavior of firms (Arimura
et al., 2008, 2011, 2014). And we expect to gain some inspiration from this practice, which
would help to raise the overall firms’ awareness of environmental protection in Vietnam.

3

Literature Review

By far there have been quite a few of studies to investigate the determinants of ISO14001,
mainly from two perspectives: external and internal. External factors are usually derived
from the demand side, such as the pressure from the stakeholder, customer and the government, or environmental preference. As known as signaling theory (Potoski and Prakash2005), firms are joining voluntary environmental management programs to show their capability of dealing with environmental pollution. Representative empirical studies all indicate
a positive relationship between foreign stakeholders and firms’ earlier adoption of ISO14001.
Chiristmann and Taylor (2001) with Chinese firm data, Wu et al. (2007) with Taiwanesemanufacturing firm data, Arimura et al. (2008) and Nishitani (2009) with Japanese firm data
all verify this finding. On the other hand, in terms of environmental preference, Nishitani(2010) uses a sample of 155 countries over eight years to show that customers in environmentally conscious markets are more likely to promote suppliers to adopt ISO14001.
Internal factors refer to firms’ internal competence that can also promote firms’ engagement in environmental protection. Arimura et al. (2008, 2011), Nakamura et al. (2001),
Welch et al. (2002) reach a unanimous conclusion that larger firms, having quality management system and wider market scope of the industry where the firm locates are all important
determinants that are associated with firms’ capability. In the meantime foreign ownership isfound to have a positive connection with energy eﬃciency (Eskeland and Harrison, 2003; He,2006; Wang and Jin, 2002). This is interpreted by the advanced waste-processing technology
adopted by foreign firms and their higher awareness to achieve corporate social responsibilities (Lyon and Maxwell, 2008). Recent studies such as Tambunlertchai et al. (2013) andArimura et al. (2014) use Thai and Malaysian firm data respectively to show that foreign
direct investment (foreign-owned firm or not) is positively related with firms’ adoption of
ISO14001. Similar result is achieved (Prakash and Potoski, 2006) in the macro level verification. On the other hand, capital-intensive industries are relatively pollution-intensive,4

thus firms in such industries are faced with more scrutiny from the customers and local
government (Mani and Wheeler 1997; Gallagher 1999). Acquiring ISO14001 might help signal pollution-intensive firms’ environmental capability and maintain their company image
especially for capital-intensive firms.
However, to our best knowledge, few studies have attempted to elaborate on the realsource of incentive for firms to rush for this standard in spite of its high cost. Levinson(2009) uses data in USA to show that most of firms’ improvement in environmental protection activities comes with technology progress. While Copeland and Taylor (2003) verify
that firms with higher technology tend to engage in more environment-friendly activities.
Evidence seems to point to the direction that the diﬀerence of technology (or firm’s productivity) is the key to variation in firms’ behaviors. Taking advantage of the voluntary natureof ISO14001 adoption, we want to make clear what is behind the scene.
First in its kind, this paper is positioned as the one to study the real determinants offirms’ strategic decision to participate in the voluntary environmental program. We will startwith an analytical general equilibrium model which can lead to our estimable predictions.

4

Theoretical Model

4.1

General setting

In this section we outline a simple model of firms that produce diﬀerentiated goods andare faced with the choice of adopting ISO14001 while realizing the costly nature of thisenvironmental standard. The basic settings are in analogous to the standard models in theliterature of international trade, such as Melitz (2003), Bernard et al. (2007), Bernard et al.
(2010,2011) (BRS hereafter), but diﬀers in that firms have the new alternatives: apply or
not apply for ISO14001. In contrast to the single-factor endowment setting in these studies,
we assume there are two kinds of inputs used for production to rationalize our empiricalprediction. Since our purpose is to introduce a simple and practical model that can leadto the data analysis, we try to simplify several assumptions. For example, we ignore theproduct heterogeneity and firms’ trade status, since such information is not available in theactual dataset. Our model can be extended to the open economy case if trade information
is to be included.

4.2

Endowments and Preference

Consumers with identical preferences try to maximize their utility by consumption overa continuum of diﬀerentiated products i ∈ [0,1]:
5

∫ 1

1

(Ci )ρ di] ρ , 0 < ρ < 1

U =[

(1)

0

where σ = 1/(1 − ρ) is the constant elasticity of substitution (CES) across products.
In accordance with the domestic-export decision-making literature that emphasizes firms’
heterogeneity in ability, we assume that firms diﬀer in their productivity. In a monopolisticcompetitive market with free entry and exit, a firm draws its productivity φ randomly from apareto distribution g(φ) upon paying the fixed cost (sunk) fe to start production regardlessof its ownership (foreign or domestic). For simplicity, we think of φ as firm-specific andconstant across industries. Meanwhile a firm has the right to acquire the environmental
standard ISO14001 by paying a larger cost which is proportionate to its total production
cost, i.e. it is the linear combination of the fixed consulting cost fx which includes theconsulting fee and application fee, and the unit cost of the input. We can also regard theextra expense as the preparation fee used on additional personnel and capital to apply for the
standard. To cover the extra expenditure, ready-to-adopt firms have the incentive to raise
the price of the product. And since ISO14001-adopting firms spend more eﬀorts on improving
the “corporate image” of the products, they are justified to set the new price as p∗x (wherep∗x =τ ·px , px is the price of the same product before the firm with same productivity applies
for ISO14001)5 . We model the extra cost in such a manner that it can be comparable to theiceberg transportation cost used in international trade. Thus, if the productivity draw φx islarge enough so that the firm has enough capacity to cover the extra cost used for ISO14001
acquirement and still make profit, the firm will have more incentive to adopt ISO14001
actively.
To take into account capital intensity, we need to deviate from the existing literature that
focuses on the labor input only. Firms use two kinds of factors for manufacturing: labor andcapital inputs. Following BRS, we assume that their supply is inelastic. The unit price foreach factor input are w and r, whereas w stands for wage rate and r represents rental rate.
Based on the modeling method used in Ma et al. (2014), we assume the total cost of thefirm is:T C e = [fe +qe 1−s s
]w r
φe

(2)

For simplicity, we omit the superscript for the firm. We choose w as the numeraire (w=1).
s indicates the capital intensity and we will consider two cases. In the first case, we do not
5

At this moment, we assume τ is exogenous. However, it can also be modeled as an endogeneous factor
which depends on firms’ characteristics. Since we are focusing on the endogeneity of productivity and capitalintensity, such possibility is not discussed in this paper.

6

impose any assumption on s and regard it as exogeneous. The second case is that we assume
s is increasing in a firm’s productivity. Since φx >φe , s(φx )>s(φe ) and the inequality stillholds in equilibrium. We will discuss the scenario in the first case and come back to thesecond one. The profits for a firm to produce without and with ISO14001 respectively are:πe = pe qe − rs (fe +

qe
)
φe

(3)

πx = px qx − rs (fx +

qx
)
φx

(4)

Firm profit maximization helps us derive the optimal price setting in the status beforers
τ rs
and after acquiring ISO14001: pe = ρφand px = ρφ
. Thus the cutoﬀ productivity πe∗ex(before acquiring ISO14001) above which the firm keeps producing, is determined by thezero-profit condition:rsRπe∗ = ( ∗ )1−σ P σ−1 − rs fe = 0
(5)
ρφe
σ
where R is the total expenditure used for production and P is the aggregated price index ofpe . In the same way, we can derive the cutoﬀ productivity πx∗ above which the firm chooses
to adopt ISO14001 and continues producing:
πx∗ =

4.3

rs τ
τ rs −σ σ−1
(
−
1)R(
) P
− r s fx = 0
φ∗x ρ
ρφ∗x

(6)

Equilibrium conditions

In equilibrium, we can derive the cutoﬀ value φ∗e and φ∗x , and the relationship between
the two can be expressed as:φ∗x = Λφ∗e , Λ = ρ · (

1
fx
σ−1
τ
τ −σ )σfe ( ρ − 1)( ρ )(7)Apart from the zero-profit condition, the free entry condition should also be cleared. In
other words,π̄e + π̄x=0(8)fe = [1 − G(φ∗e )] ·δ
where G(φ) is the cumulative distribution function of g(φ), and δ is the surviving rate. For
the convenience of calculation, we assume that it takes a specific form such that G(φ) =1−( φφ0 )k , and k > 1. This is a standard function form of Pareto Distribution. π̄e and π̄x eachstands for the expected average profit of a firm conditional on the status before and after
adopting ISO14001. Because of law of large number, π̄e and π̄x can be represented as the7

function of φ∗e and φ∗x respectively6 . Thus we can solve two unknowns with two Equations(7) and (8), and the diﬀerence is:π̄x − π̄e = rs [F (φ∗x ) − F (φ∗e )](9)where F (·) is the expected average profit excluding the factor of rs in equilibrium. From
the assumed function form of Equations (7) and (8), we can derive F (·) as an monotonicallyincreasing function in φ∗i , i ∈ {e, x}, because σ − 1 > 0. For a firm to apply for ISO14001
given the higher fixed cost, it is reasonable to expect that π̄x > π̄e , thus F (φ∗x ) > F (φ∗e ).
Together with the increasing nature of F (·), we can conclude that φ∗x > φ∗e . In other words, itis the diﬀerence in the expected equilibrium productivity under diﬀerent status (non-adopted
and adopted) that leads to firms’ incentive to acquire the standard7 .
On the other hand, when the impact of productivity gap is excluded and ceteris paribus,
the diﬀerence between π̄x and π̄e solely depends on rs . Since we have defined w as 1 andcapital input is basically more costly than labor input, we can assume that r > 1. As s
increases, the expected profit gain after the adoption of ISO14001 will be enlarged, which
gives the firm more incentive to apply for this standard. Based on the above arguments, wegive the following proposition, which will be verified in the empirical estimation section.
Proposition 1: In a closed economy, holding other characteristics unchanged, higher productivity will increase a firm’s willingness to adopted ISO14001. In the meantime, the more
a firm is capital intensive, the more likely it is to adopt ISO140018 .

4.4

Other control variables

Although not the key focus of this paper, we would like to discuss in brief how to model
the other factors that might aﬀect its decision to adopt ISO14001. We have mentioned
in the earlier section that foreign-owned firms care more about their corporation social
responsibility because the eﬀort towards environmental protection will in fact aﬀect thecompany image. Empirical evidence can be found in Prakash and Potoski (2011)9 . In themeantime, foreign-owned firms are faced with more scrutiny from the foreign shareholders
who have higher preference of “green” products (Bui and Kapon 2012). Therefore, the6

See Appendix A-1 for detailed derivation.
See Appendix A-2 for details
8
As for the case when s is endogeneously determined by each value of φ, it does not change our qualitative
prediction. See Appendix A-1 for detailed discussion.
9
Though their practice is from the macro perspective by exploring FDI stock’s impact on the number of
ISO14001 adoption in developing countries.
78

more foreign capital a firm has, the more cost it is willing to spend on environment-friendly
activities including ISO14001 adoption. Apart from that, the size of the firm and the waste
management department might also matter.
In previous section we have assumed that τ is exogenous. Suppose τ in fact consists ofthe potential determinants outlines above, and an unobserved term. From Equation (7) and
derivation in Appendix A-3, we know that:s(φ∗e )
∗r∗
φx = φe s(φ∗ ) · ρ · (
x

r

1
fx
σ−1
τ
τ −σ )σfe ( ρ − 1)( ρ )∗Using some algebra and φφ∗e can be approximately expressed as:
x

φ∗e
∗
∗
= rs(φx )−s(φe ) · κ · τ (F DI share, f irm size, waste management, unobserved)∗
φxwhere κ = F (ρ, σ, fe , fx ) and is constant. Since the probability of adopting ISO14001 is∗∗∗( φφ∗e )k = (rs(φx )−s(φe ) ·κ·τ )k , we take logarithm on both sides and come up with the expressionxwhich leads to our emipirical estimation:φ∗e∗∗= lnκ+β1 ·lnrs(φx )−s(φe ) +β2 ·ln(F DI)+β3 ·ln(f irm size)+β4 ·ln(waste management)+ϵ
∗
φx
(10)
where the last term is the unobserved firm characteristics that might aﬀect a firm’s decision of
ISO14001 adoption. In the next section, we will use matched data from Vietnam to estimate
Equation (10). β1 and β2 are of our research interest. β1 is expected to have positive sign,and the signs of β2 -β4 are to be determined via empirical tool.

ln

5

Estimation Strategy and Data

5.1

Data

This paper uses a panel dataset, constructed from the Vietnam Enterprise Survey at firmlevel. The data was collected by the General Statistics Oﬃce of Vietnam for all sectors andindustries, as on March 1st annually. It covers all 22 manufacturing sectors out of the total 42.
Since most ISO14001 adopters are concentrated in manufacturing industries (81%), we will
limit our analysis to manufacturing firms only. Company characteristics such as ownership,labor, capital stock, turnover, assets, FDI share, average wage rate, intermediate materials
are also available. Apart from the above, GSO has taken a census of all multinational
9enterprises (MNEs), which are defined firms that have foreign capital, regardless of theshare. The advantage is that investment behavior of these foreign capitalized firms can be
captured over time. Census is also taken for firms with more than 10 employees. Each firm
has an exclusive enterprise code. We use it together with province code to identify the firms.
Another uniqueness of this dataset is that it collects information on firms’ engagement inenvironmental protection, including the cost spent on environmental protection, whether thefirm carries out environmental management system, whether it follows the clean manufacturing process, etc. And above all, whether the firm has ISO14001 certification is recorded.
Since it is relatively objective criteria that is free of measurement error, we use it to create
our ISO adoption dummy. Unfortunately, the ISO information is only accessible from 2007
to 2009, we have to limit our analysis to this time period. Finally, the detailed data on waste
discharge categorized by form (air, liquid, solid) is also available.
There are also some limitations concerning the data, for instance, the incomplete information about export and import, missing data for materials and other variables, inconformity ofunits among diﬀerent years, etc. As a result, we have to deal with an unbalanced panel data
here. We remove the missing observations, and delete outliers. After these arrangements,
the total number of observations for estimation is 28274 over three years.

Table 1 is inserted here
In practice, we will replace capital intensity and foreign capital share with their one period
lag respectively to alleviate reverse causality concern. We will change the specifications tosee how robust it is.

5.2

Baseline estimation and results

The dependent variable is a binary choice. Thus in the baseline estimation we apply
the random-eﬀect panel Logit or Probit, and model a firm’s decision making of ISO14001
adoption as the conditional mean of firms’ observed idiosyncratic characteristics. In practice,
to alleviate the reverse causality concern, we replace the variables of interest with their one
period lags.
In the first two columns of Table 2, we would like to verify the sole influence of a firm’s
productivity on its decision making, as predicted in the first part of Proposition 1. Since we
don’t have enough information on the intermediate goods, Levinsohn and Petrin style TFP
can not be fully applied. As an alternative, we adopt the stochastic frontier method. See thedetails in Lovell and Kumbhakar (2000). We only include year dummy, industry dummy and10waste department dummy as control variable. In either specification, TFP is positive andstrongly significant. Though the coeﬃcient varies between models, the robustness provides
suﬃcient evidence that it is one of the most important determinants for a firm to adopt
ISO14001.
We show the results of estimating Equation (10) in Columns (3) and (4). While productivity maintains its significancy, foreign capital share, total employment, waste department
dummy and capital labor ratio, are all statistically significant at the 1% level. The estimatedcoeﬃcient of foreign capital share is positive, which means that firms with foreign capital
actively adopt ISO14001. The positive sign of total employment indicates that the larger
a firm is, the more likely it is to adopt ISO14001. One explanation might be that larger
firms have more capacity to participate in such voluntary programs. In accordance with ourtheoretical prediction, capital labor ratio is positive, implying that capital-intensive firms
have more incentive to adopt ISO14001.

Table 2 is inserted here

5.3

Robustness check and further issues

Robustness check
Though reverse causality is considered in the baseline estimation, another source of endogeneity might arise: the sample selection. It is natural to assume that firms with higher
productivity (or capital intensity) might select to adopt ISO14001 to gain further profits,
and the selection bias will aﬀect our estimation of the coeﬃcients of the variables. To alleviate the bias, we adopt the “ivprobit” model. The instrument needs to be correlated withproductivity or capital intensity, but does not aﬀect the decision of ISO14001 adoption. In
practice, we use the number of workers whose education levels are equal to or above college, as the instrumental variable (IV). This measurement is quite likely to aﬀect a firm’s
productivity level, but less possible to determine the ISO14001 acquirement.
We make additional eﬀorts to test the robustness of other control variables as well. Apartfrom applying waste department dummy as the determinant of ISO14001 adoption, we use
total cost environmental and environmental system as proxies alternatively. Furthermore,
to disentangle the potential impact that the existing pollution level might have on firms’
willingness to apply, we include the amount of liquid and solid waste discharge as additional
control variables. Such practice does not change the qualitative results concerning the roles
that capital intensity and foreign capital share of a firm play. Due to space constraint, we
11

do not present all the estimation results but they are available upon request.
Diﬀerence across industries
Given the fact that most firms adopting ISO14001 are in the manufacturing industry, we
have the reason to believe that the incentive for the firms from other industries to adopt
ISO14001 can be diﬀerent. We are thus motivated to confirm how the impact of the determinants of ISO14001 adoption diﬀers across industries. Accordingly, we further divide samples
by industry and conduct the estimation as in Equation (10). The upper panel of Table 3
shows the results when we use the samples in food industry only and the lower panel is forthe manufacturing industry.
Productivity is positive and significant for both industries. However, the magnitude of
its influence in the manufacturing industry is larger than that in the food industry, showingthat the technology is crucial for manufacturing firms to care more about their engagement
in environmental activities. Meanwhile, when we limit the samples to food industry, foreign
capital share lost its significance. This indicates that foreign firms in those industries otherthan manufacturing might not value the corporate social responsibility as much as those in
the manufacturing industry. It is also likely that foreign-owned firms from manufacturingexcluded industries in Vietnam do not respond actively to the shareholders’ expectation of“green products”. On the other hand, capital labor ratio is still significant, but its marginal
eﬀect is reduced to half of that as in the manufacturing industry. The interpretation isthat since in manufacturing sectors, firms produce products that heavily rely on usage oflabor, machines and tools, the costs and benefits of applying more eco-friendly inputs will
be weighed in a more serious way by each firm. Consequently capital intensity plays arelatively more important role in firms’ decision of ISO14001 adoption. The post-estimation
likelihood-ratio test ensures the appropriateness of the model (rejection of the null).

Table 3 is inserted here

6

Conclusion

We use the firm level survey data from 2007-2009 in Vietnam to investigate the determinants of the adoption of ISO14001, a voluntary environmental standard. We try to uncover
the mechanism of how firms form the decision of adoption. Theoretically, by employing ageneral equilibrium model, we show that more productive and capital intensive firms will
12

systematically have higher incentive to adopt because of the larger expected benefits, despitea higher fixed and variable cost. In the empirical verification, a random-eﬀects Probit (Logit)
model is applied to confirm our prediction. Some robustness checks are conducted and thequalitative results remain unchanged.
Furthermore, we try to verify the diﬀerential influence that the above determinants might
have on ISO14001 adoption of firms in diﬀerent industries. Both productivity and capitalintensity have higher decisive impact on the ISO14001 adoption of firms from non-foodmanufacturing industry that those from other industries. In the meantime, foreign capitalshare shows its significancy particularly in manufacturing industries, which to some extent
oﬀers the evidence to refute the critics of “pollution haven hypothesis” due to foreign firms’
active investment activities.
The above findings can lead to some policy implications that are especially critical toVietnam because the country is faced with serious pollution problem. Due to the notion that
ISO14001-adopting firms have generally higher awareness of environmental protection, it isurgent that Vietnamese government explore more eﬃcient ways to promote all firms’ engagement in voluntary environmental program (not limited to ISO14001). Technology progressposes as a solution (which reduces firms’ abatement cost), but it needs be supplemented bysuch policies as subsidies and tax exemption provided to domestic firms that show capability
to engage in environmental protection.
Last but not least, our paper can be improved in many ways. For example, it would
be more practical to take into account the influence of international trade, because a firm’s
eﬀort towards adoption environmental standard is also associated with its export destinationand how much it trades. Further extension can take into account industrial and regional
heterogeneity as well.

7

AppendixA-1: Derive a firm’s average profit as a function of its equilibrium productivity
level φ∗ .
The productivity distributions for non ISO14001-adopted and adopted firms are: µe (φ) =And the average profits of a firm before
and after adopting ISO14001 can be expressed as follows:
g(φ)
g(φ)
∗
if φ ≥ φ∗e and µx (φ) = 1−G(φ∗ ) if φ ≥ φx .
1−G(φ∗e )
x

∫ ∞
π̄e =

πe (φ)g(φ)
dφ∗φ∗e 1 − G(φe )

13

(11)

∫ ∞
π̄x =

πx (φ)g(φ)
dφ∗
φ∗x 1 − G(φx )(12)where we can rewrite Equation (11) as:∫ ∞[(ρφe P )σ−1 (rs )−σ R − rs fe ]g(φ)
dφ1 − G(φ∗e )
φ∗e

(13)

Let ϕ be the firm’s revenue, i.e. p ∗ q. Following BRS (2010), we haveϕ(φ′′ )
φ′′ σ−1)=(ϕ(φ′ )φ′ϕe (φ∗x )φ∗x σ−1)⇒=(ϕe (φ∗e )φ∗e(14)
Substituting Equation (14) into (13), we get:π̄e =∫ ∞ [( φ )σ−1 rs f − rs f ]g(φ)
φ∗e

φ∗e

e

e

1 − G(φ∗e )dφThe zero profit condition indicates that rs fe is equal to ϕ(φ∗e ), thus π̄e can also be represented by φ∗e ’s function. In the same way, π̄x can be written as a function of φ∗x as well.
A-2: Numerical example to show a firm’s incentive to adopt ISO14001.
We focus on the general profit conditions: Equations (5) and (6). After rearranging, thefirst terms on the right hand side of both equations become the following:1· (φ∗e )σ−1 (rs )1−σ RP σ−1
ρσ

(15)

τ
( − 1)τ −σ · (φ∗x )σ−1 (rs )1−σ RP σ−1
ρ

(16)

1
For simplicity, we leave out the common factor and only have to compare ρσ· (φ∗e )σ−1
with ( τρ − 1)τ −σ . Following Balistreri et al. (2011), we let σ = 3.8, then ρ = .74. We further
assume that τ < 1.1, since In reality, it is hard to imagine that firms are willing to pay
an extra 10% (or larger) of its total operation cost to acquire the voluntary environmental
standard. Though a larger τ over 1.1 will not change our prediction.

14

1· (φ∗e )σ−1 ≈ .356 andSubstituting the values into the above expressions and we get ρσ( τρ −1)τ −σ ≈ .338. Because the profit function is increasing in φ∗ , to satisfy Equation (5) and(6), a larger φ∗x will be necessary so that the value of the term in Equation (16) surpasses thatof the term in Equation (15)10 . This lends support to the notion that without the growth of
productivity, a firm will have little chance to start considering the adoption of ISO14001.

A-3: Discussion on the case when capital intensity s is also the function of thefirm’s productivity φ.
As shown by Yeaple (2005), Harrigan and Reshef (2012), Verhoogen (2008), productive∂sfirms are usually more capital-intensive. Thus it is natural to make the assumption that ∂φ>
0. Since r > 1, rs is therefore a monotonically increasing function of a firm’s idiosyncratic
productivity. Accordingly, Equation (7) becomes:
∗

φ∗x =

1
rs(φe )fx∗
) σ−1∗ ) · Λφe , Λ = ρ · (
τ
τ
s(φ
−σ
r x
σfe ( ρ − 1)( ρ )∗From Equation (9), we know that π̄x − π̄e = rs [F (φ∗x ) − F (φ∗e )] > 0, and since rs(φx ) >∗∗∗rs(φe ) , we will have rs(φx ) F (φ∗x ) > rs(φe ) F (φ∗e ) as long as φ∗x > φ∗e . Another way to confirm
firms’ decision-making is to calculate the probability of ISO14001 adoption. Similar to theprobability of export in Melitz (2003), a firm’s willingness to adopt ISO14001 PISO can be∗)x, where φ∗x and φ∗e are cutoﬀ values for ISO14001 adoption and initiating
expressed as: 1−G(φ1−G(φ∗e )production. Given the specific function form of G, we have the following expression:∗∗φ∗rs(φx )−s(φe ) k
PISO = ( ∗e )k = () ,k > 1φxΛBecause Λ is assumed to be constant, as s increases, PISO will be enlarged as well,indicating that the capital intensity level determines a firm’ propensity to adopt ISO14001.

1
When τ approaches 1 from above, ( τρ − 1)τ −σ will be enlarged to get close to ρσ. In the special casewhen τ = 1, which indicates that fx = fe , Equations (5) and (6) will converge.
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18

Figure-1

The difference in firms’ TFP in Vietnam

Pre-TFP for ISO14001-adopted firms

Pre-TFP for non ISO14001-adopted firms

	
  	
  	
  	
  	
  Source: Annual Enterprise Survey, GSO Vietnam* TFP is calculated using Stochastic Frontier Method.

19

Figure-2

ISO14001 adoption rate by capital intensity

Year 2007-2009 in total
10.00%

8.91%

9.00%
8.00%

6.88%

7.00%
5.54%

6.00%
5.00%
4.00%

3.43%

3.00%
2.00%
1.00%
0.00%
0-25

25-50

50-75

75-100Each year
12.00%
10.00%
8.00%
Year2007
6.00%

Year2008
Year2009

4.00%
2.00%
0.00%
0-25

25-50

50-75

75-100Source: Annual Enterprise Survey, GSO Vietnam

20

Figure-3

Pollution Level in Vietnam (tons)	  Source: GSO, Vietnam and World Bank IPPS
	
  

21

22

N
28274
28274
28274
28274
28274
28274
28274
28274
28274
28255
28268
28265

Source: General Statistics Office, Vietnam

Variableliquidsolid
total_employment
ISO14001
FDI_capital_sharecapital_labor_ratio
food_manufacturing dummy
manufacturing dummy
totalcost_environment
waste_department dummy
environmental_system
environmental_standard

Table 1 Statistical Summary
Mean
19.95423
23.00456
236.2577
0.058216
17.57954
167.0986
0.1333734
0.5108934
1199.974
0.2725535
0.2772747
0.2619848

S.D.
26.67161
24.83821
873.1979
0.2341556
37.33238
1096.249
0.3399839
0.4998902
120352.4
0.4452809
0.4476612
0.4397222

Min
0
0
1
0
0
0
0
0
0
0
0
0

Max
100
99.900161297
1
10098623.28
11201000001
1
1

Definition
treated liquid waste/total liquid waste (%)
treated solid waste/total solid waste (%)
number of employees at the beginning of the year (Person)
whether the firm has ISO14001
foreign capital/total capital (%)
the ratio of capital/total employment
if the firm is in the food-manufacturing industry, the dummy takes 1
if the firm is in the food-excluded-manufacturing industry, the dummy takes 1
total costs for environmental protection (Mill. Dongs)
whether the firm has environmental protection department
whether the firm carries out environmental management system
whether the firm meets requrements of environmental standard

Table 2

Baseline Estimation Results

Model
Dependent Variable
Lag (TFP)

(1)

(2)

(3)

(4)

Logit

ProbitLogit

ProbitISO14001 Dummy

ISO14001 Dummy

ISO14001 Dummy

ISO14001 Dummy

7.450***

4.094***

6.102***

3.338***(0.892)(0.493)(0.875)(0.485)0.00793***0.00438***

Lag (foreign capital share)(0.00201)(0.00112)

Total number of workers

0.000467***0.000262***(6.96e-05)(3.81e-05)

Lag (capital labor ratio)

0.000280***0.000155***(9.25e-05)(5.00e-05)

Manufacturing industry dummy

Food industry dummy

0.786***

0.430***

0.530**

0.286**(0.230)(0.128)(0.241)(0.133)

0.243

0.134

0.299

0.162

(0.283)(0.157)(0.287)(0.158)2.810***

1.534***

2.556***

1.388***(0.248)(0.117)(0.236)(0.115)Observations

8,283

8,283

8,283

8,283

Number of id

5,961

5,961

5,961

5,961

Waste department dummy

Note: Random-effects Logit and Probit models are applied.
Standard errors in parentheses. Year dummies are included.
*** p<0.01, ** p<0.05, * p<0.1

23

Table 3

Industry Comparison
(1)

(2)

(3)

(4)

Logit

ProbitLogit

ProbitISO14001 Dummy

ISO14001 Dummy

ISO14001 Dummy

ISO14001 Dummy

5.652***

3.041***

4.785***

2.557***(1.124)(0.617)

Model
Dependent Variable

Food industry
Lag (TFP)

Lag (foreign capital share)

Total number of workers

Lag (capital labor ratio)(1.125)(0.612)0.00200

0.00114(0.00381)(0.00208)

0.000319***0.000180***(0.000117)(6.47e-05)

0.000199**

0.000109**(9.95e-05)(5.28e-05)

2.267***

1.212***

2.102***

1.118***(0.299)(0.159)(0.300)(0.159)Observations

3,166

3,166

3,166

3,166

Number of id

2,333

2,333

2,333

2,333

Waste department dummy

Manufacturing industry
Lag (TFP)

8.918***

4.943***

7.382***

4.089***(1.336)(0.727)(1.295)(0.722)0.00915***0.00508***

Lag (foreign capital share)(0.00252)(0.00140)

Total number of workers

0.000529***0.000297***(9.10e-05)(4.97e-05)

Lag (capital labor ratio)

0.000381**

0.000215**(0.000157)(8.57e-05)

Waste department dummy

3.147***

1.745***

2.886***

1.594***(0.381)(0.163)(0.364)(0.166)

Observations

5,028

5,028

5,028

5,028

Number of id

3,582

3,582

3,582

3,582

Note: Random-effects Logit and Probit models are applied. Standard errors inparentheses. Year dummies are included.

*** p<0.01, ** p<0.05, * p<0.1

24