Determinants of firm exit in vietnam

UNIVERSITY OF ECONOMICS HO
CHI MINH CITY
VIETNAM

ERASMUS UNVERSITY ROTTERDAM
INSTITUTE OF SOCIAL STUDIES
THE NETHERLANDS

VIETNAM – THE NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DETERMINANTS OF FIRM EXIT IN VIETNAM

BY

TRAN THI LAM

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY, MAY 2017

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UNIVERSITY OF ECONOMICS HO
CHI MINH CITY
VIETNAM

INSTITUTE OF SOCIAL STUDIES
THE HAGUE
THE NETHERLANDS

VIETNAM – THE NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DETERMINANTS OF FIRM EXIT IN VIETNAM
A thesis submitted in partial fulfilment of requirements for the degree of
MASTER OF ARTS IN DEVELOPMENT ECONOMICS

By

TRAN THI LAM

Academic Supervisor:
DR. TRUONG DANG THUY

HO CHI MINH CITY, MAY 2017
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TABLE OF CONTENTS
ACKNOWLEDGEMENT ................................................................................................................... 1
ABSTRACT ......................................................................................................................................... 2
LIST OF FIGURE AND TABLES ...................................................................................................... 3
CHAPTER 1: INTRODUCTION ....................................................................................................... 4
1.1. Problem Statement ..................................................................................................... 4
1.2. Research objectives .................................................................................................... 6
1.3. Research questions ..................................................................................................... 6
1.4. Scope of research........................................................................................................ 7
CHAPTER 2: LITERATURE REVIEW ............................................................................................. 8
2.1. Literature Review ....................................................................................................... 8

2.1.1. Firm exit behavior .............................................................................................................. 8
2.1.2 Determinants of the decision to exit .................................................................................... 9
2.2. Review of empirical studies on firm survival/exit ................................................... 17
2.2.1. Approaches of analyzing firm exit and survival ............................................................... 17
2.2.2. Emprical analyses of firm survival ................................................................................... 18
2.2.3 Emprical analyses of firm Exit .......................................................................................... 20
CHAPTER 3: RESEARCH METHODOLOGY ............................................................................... 23
3.1. Conceptual framework and the econometric model ................................................. 23
3.1.1. Conceptual framework ..................................................................................................... 23
3.1.2. Theoretical reviews........................................................................................................... 24
3.1.3. The econometric model .................................................................................................... 25
3.2. Data and variables .................................................................................................... 27
CHAPTER 4: RESEARCH RESULT ............................................................................................... 29
4.1. Descriptive Statistic .................................................................................................. 31
4.2. Regression results ..................................................................................................... 34
4.2.1. Bivariate analysis .............................................................................................................. 34
4.2.2. Multivariate analysis......................................................................................................... 36
4.2.3. Multicollinearty analysis .................................................................................................. 37
4.2.4. Results of random-effect logistic regressions………………………………………...…38
4.2.5 Marginal effects ................................................................................................................. 41
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CHAPTER 5: CONCLUSION……………………………………………………………………...43
5.1. Conclusion ................................................................................................................ 43
5.2. Policy Implications ................................................................................................... 44
5.3. Thesis limitations and suggestion for further researches ......................................... 44
REPERENCE..................................................................................................................................... 46
APPENDICES ................................................................................................................................... 56

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ACKNOWLEDGEMENT
Firstly, I would like to express my sincere gratitude to my advisor Dr. TRUONG DANG
THUY for his enthusiastic assistance. He has not only several insightful comments based on his
immense knowledge helps me to solve all my problems, but also encourages me to finish my thesis.
I would like to express my thanks to my friends in MDE class 19, and 20, especially Duy
Chinh (class 19), Do Luat (class 20), Duy Lap (class 20), Nguyen Thai Duong (class 20) and one
special friend who have given their limited time to help me solved the difficulties in the process.
I also would like to send love to my family and my close friends for always being beside
me, spiritually encouraging me and letting me know that I am not alone in all difficult situations.
Finally, my special thanks also to my husband and my baby who help me to have a strong
motivation to finish my thesis.

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ABSTRACT
This paper examines the determinants of firm exit in Vietnam using SME data from 2005 to
2011. Using panel data from 10 provinces and cities in Vietnam and applying the logistic regression
method, this study finds that total asset and leverage have positive impacts on firm exit while the
size, age, investment and total gross profit negatively affect firm exit.
Keywords: Small and medium enterprise, total asset, firm exit, firm size, firm age, debt leverage,
investment, total gross profit, random effects logistic regression.

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LIST OF FIGURE AND TABLES
Figure 1.1: Number of registered enterprises and stop business over period 2007-2015
Figure 3.1: Conceptual framework
Table 3.1: List of surveyed province/city
Table 3.2: Descriptive variables
Table 4.1: Descriptive Statistic
Table 4.2: The number of survey exit firms in each city/province
Table 4.3: Overview of firm exit in Viet Nam
Table 4.4: Firm exit in province/city
Table 4.5 A comparison between Firm non-exit and Firm exit in term of variables
Table 4.6: Covariance matrix
Table 4.7: VIF index
Table 4.8 Results of three Random – effect logistic regressions
Table 4.9 Marginal effect results

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CHAPTER 1: INTRODUCTION
1.1. Problem Statement
The stable development and growth of firms are key factors what influence directly the
socioeconomic development. On the other hand, firm’s activities affect almost all respects of
economy and society such as rate of unemployment, national budget, activity of trade, and other
macroeconomic indicators.
The role of small and medium enterprises (SMEs) in economic growth has been recognized

through many studies in the world recently. An article by Joshua and Quartey (2010) describes that
SMEs play important roles to an economic development as creating efficient and productive jobs,
the seeds of large corporations and the fuel maintaining the national machine. In advanced
economies, the number of firms in the SME sector, which has substantial labors, is larger than the
multinational one (Mullineux, 1997). In addition, Feeney and Riding (1997) reveal that
governments in most countries have conducted several policies to encourage the development of
SMEs. Whereas, the growth of SMEs promotes the process of redistribution of both inter and intraregional division of the firm and they also become a countervailing force again the influence of
large-scale corporations. There is approximately 91% of the enterprises is Small, Medium and
Micro Enterprises (SMMEs) in South Africa (Hassbroeck 1996, Berry et al. 2002). They create
about 61% jobs for labor source and also represent for 52%- 57% of GDP (CSS 1998, Ntsika 1999,
Gumede 2000, Berry et al. 2002). In additional, Small and medium enterprises also account over
90% of the private business sector and play a crucial role in contributing GDP in most African
countries (UNIDO 1999).
Viet Nam has changed from a centralized planned economy to a socialist-oriented market
economy after “Đổi Mới” reform period since mid-1980. Undergoing a period of formation and
development, the Vietnam economy continues to grow and get many substantial achievements. A
private ownership sector contributes a vital role for Vietnam economic growth. According to
Vietnam General Statistics Office, Vietnam attains around 7% GDP growth over the period 2000 to
2005 and continues to grow at 7.01 percent from 2005 to 2010. The process of developing keeps in
stable until now, especially SMEs sector. Small and medium enterprises (SMEs) have an essential
role to play in motivating growth, generating jobs and contributing to poverty reduction. The
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contribution of SMEs is a major tax resource for Vietnam budget annually. Furthermore, according
to the report of the Vietnam Chamber of Commerce and Industry (VCCI), we have 543,963
enterprises in 2011, about nearly 513,000 enterprises in 2015, but there is nearly 97 percent of small
and medium firm, mainly private businesses. The important role of SME is increasing thanks to not

only contributing significantly to the Gross domestic product (GDP), reducing poverty, enhancing
security society, but also creating more than one million new jobs per year.
According to Ministry of Science and Technology, there are 692 thousand enterprises
registered business in the period 2007 – 2015. However, there are too many enterprises not enough
power to survive in globalized market and international integration and move out of market every
year. According to General Statistics Office of Vietnam, more and more firms exit and stop activity
in annual reports (2015: 80,900 firms; 2014: 67,800 firms; 2013: 70,500 firms and 2012: 63,500
firms). Figure 1.1 shows that the number of firms that ceased operations is increasing in the recent
years.
100.000,00
90.000,00
80.000,00
70.000,00
60.000,00
50.000,00

Registration of operations

40.000,00

Stop business

30.000,00
20.000,00
10.000,00
2007 2008 2009 2010 2011 2012 2013 2014 2015

Figure 1.1: Number of registered enterprises and stop business over period 2007-2015

(Source: Administrative Department of Business Registration - Ministry of Science and Technology)

Therefore, this is a crucial problem requires a reaction from government official and policy
makers to decrease the number of firm stopping business every year.

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In recently, the determinant impacts the ratio of birth - death enterprises and issue of firm
survival in the developed countries have been attracting a lot of attention of scholars around the
world (Parker 2004, Strotmann 2006). In addition, the issue about entrepreneurial activities, which
has mentioned in empirical literatures recently, is a crucial factor affects to speed of economic
progress (Stel et al. 2005). Some empirical studies focus on relationship between characteristics of
firm, policy, an environment, the process of international trade liberalization and rate of firm exit.
Most of studies focus on the topic of firm exit is conducted at the firm or industry level (Hannan
and Carroll 1992, Sarkar et al. 2006). They study on effect of the determinants on exit probability of
small and medium enterprises (SMEs). Many other empirical studies also reveal that the
perseverance of small firms has an important role in economic development in a context of
increasing import competition from low-cost nations (Colantone et al. 2014).
However, in both the theoretical and practical sides, most of the articles are empirically
carried out on foreign firms in developed countries and studies about survival of enterprise are less
mention in developing countries (Parker 2004). There are a few researches studied directly on exit
issue in developing countries, especially in Viet Nam.
Thus, from the obtained results of this research will contribute to understand deeply about
the determinants influence on firm exit in Viet Nam as practical part. They can make policies
priority and influence debates on firm’s activity to reduce firm exit.
1.2. Research objectives
The main objective of this study is to identify factors influence on the decision of firm exit.
Using the SME data from 2005 to 2011, this study applies a logit model with the decision to exit as
the dependent variable and total asset, firm age, total gross profit, firm size, investment and debt

leverage as explanatory variables.
1.3. Research questions
This research examines how the determinants affect the exit probability of Small and
Medium Enterprise in Vietnam. To identify and understand the dimension clearly, the research is
developed based on following questions:


What factors influence probability of firm exit?

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1.4. Scope of research
The study will examine the relationship between firm exit and related determinants using
the panel data of 2005-2011. This is a full-scale survey covering small and medium-scale
enterprises in Viet Nam (SMEs) in the rural and urban area of Vietnam and conducted by
collaboration between the Institute of Labour Studies and Social Affairs (ILSSA) in the Ministry of
Labour, Invalids and Social Affairs (MOLISA) and Department of Economics, University of
Copenhagen with funding from DANIDA in the period from 2005 to 2011. To collect data by
choosing the key questions in the main questionnaire for every surveyed year, we have the panel
data to run the logistic model.

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CHAPTER 2: LITERATURE REVIEW

2.1. Literature Review
2.1.1. Firm exit behavior
Understanding increasingly about exit behavior and reasons for exit out market help
managers making a comfortable decision for their survival and increasing their evaluation
efficiency with insights into the reasons for the failure of a product (Witteloostuijn 1998, Sheppard
1994, Dixit et al. 2007). In addition, thanks to the exit process, the manager can learn about their
actual essential productivity levels (Yang and Temple 2012).
Because of the significant importance of exit decision, we are necessary to consider the
reasons why firm decided to exit which help me understanding about the decision and its possible
drivers forced firm to exit.
The firm decides to either survive or decline and exit depends in many respects and their
evaluation and expectation. According to Jovanovic (1982), firm’s productivity is a key determinant
which manager bases on to decide whether to start up a new company or exit the market. Harada
(2007) produces the main reasons for exit of small firm in Japan. Among these reasons, despairing
perception for further business accounts for 38%, followed by aging of the manager (20%) and the
injury or sickness of the manager (15%). He presents more detail about despairing perception of
further business which indicated through the reduction of sales (71%) and having a deficit (only
9%). Therefore, the diminution in sale plays an important role. He supposes that exit also
sometimes happens because owner desires to have an easier life or to take a position doing work or
to begin a new business. According to several researchers, each company acts basing on the aim of
profit maximization, and whenever the profit (or realized/expected profit) declines below some
threshold, they would exit the market (Das and Das 1996, Klepper 1996, Frank 1988, Ghemawat
and Nalebuff 1985, Jovanovic 1982). Investigating a set of data from Botswana, Kenya, Malawi,
Swaziland, and Zimbabwe, paper was researched by Liedholm et al. (1994, 1178) indicates that the
reasons of company exit are not only business reasons but also related to personal reasons. He finds
that only about one-half of rural firms in these countries shut their business because of business
failures and approximately one-quarter firms do it due to some individual reasons (e.g. retirement or
poor health) while the rest decides to close owing to the availability of better business opportunities
or obligation imposed by the government. Other result was proposed by Hopenhayan (1992) shows
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that firm decides to exit when it experiences series of unfavorable productivity shocks. The
companies having a least productive are easy to exit because of lacking competition and not enough
capacity to remain their business, while the most efficient ones try to expand their activities to
increase sale and profit.
On the other hand, Colantone and Sleuwaegen (2010) suppose that each entrepreneur will
evaluates the basis of risk-reward and assess the outside choices regarding to scrap value of
companies and market wages to have decision about staying in or leaving out the market. Following
Baggs (2005), the firm’s prospects for profits, which is affected not only by the characteristics of
the firm itself but also the characteristics of the business environment, is a key determinant to
remain or exit in an industry. Frazer (2005) shows other reasons made the enterprises closed as
personal reason or because of the closure order from the government.
According to several suppositions, incumbent enterprises will consider to continue operation
or exit belong to their health. In general, they will be less likely to exit when performance is
stronger and more likely to stop operations when prior performance is poor (McCann and Vroom
2010). In the view of Yang and Temple (2012), the firms consider about moving out the market
when they expect sufficiently future operating profits and exit will be their least costly option.
Many surveys on enterprise survival report that the probability to survive of efficient firms is higher
than the probability of inefficient ones (Baggs 2005). According to Kovenock et al. (1997), the exit
is a decision made by the owner or manager of firms regarding the use of inherited arrangement of
capital and he separates exit into three types, including strategic reallocation, restructuring, and
corporate form and structure.
2.1.2 Determinants of the decision to exit
There are considerable a number of studies investigate the firm exit and survival, not only in
developed countries but also in developing countries recently (Roberts et al. 1996a, Das et al. 1997,
Frazer 2005). Determinants influence firm on exit and survival and the duration of one survival in
developed countries have been interesting numerous researchers and scholars in recent years. The

exit issue is also concerned with a common part of the landscape of business (Geroski 1995).
Recently, the crucial determinants which effect on the ratio of business dissolution are being
examined more and more in body of literature which used in modeling to express structural
motivation, barriers to exit and firm features. According to Baggs (2005), firm’s profit prospect is a

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fundamental factor affecting the company’s decision whether exit or remain in an industry. Both the
characteristics of competitive industry or environment and the characteristics belong to the
company influence on this prospect. All most papers regularly use explanatory variables on their
researches that have been used in the literature are expressed below:
FIRM SIZE
In the relevant literature, there are many approaches to find the factors affecting firm exit or
firm survival. Building on the existing literature, Audretsch and Mahmood (1995) report that age
and firm’s size, capital intensity, the innovation rate at the industry level and new firms with new
branches are key determinants affect the likelihood of survival firm. Firm size is also explored
closely connected with analysis of industry dynamics (Baldwin and Gorecki 1989, Mata and
Machado 1996, Fariñas and Moreno 2000). Audretsch and Mahmood (1995) find that size,
innovation rate, and price-cost margin influence the decision to exit. Mata et al. (1995) also argue
that size is a crucial factor of chances for survival. The other considerable empirical papers reveal a
difference in the relationship between exit and firm’s size.
Regarding to their production capacity and fixed assets, Yang and Temple (2012) divide
firms into three size types: small, medium, and large. Size is estimated by total labors of the firm in
each year (Dimara et al. 2008). Liedholm and Mead (1999) investigate a data set of micro firms
(fewer than 10 workers). Other research finds that large and small firms faced various competitive
conditions due to operating on markets of a dissimilar scope and applying different technologies
(e.g. Audretsch et al. 1999).

The majority of researches show a negative relationship between firm size and ratio of firm
exit such as Segarra and Callejón (2002), Mahmood (2000), Audretch et al. (2000), Baldwin
(1995), Audretch and Mahmood (1995), Wagner (1994), Dunne and Hughes (1994), Hall (1987). In
contrary, other researchers divided enterprises into different types of size to find the relationship
between firm exit variable and size variable. Lieberman (1990) reveals a positive relationship
between small firm size and firm exit probability. Most papers also show a positive correlation
between size of small firm and exit probabilities and vice versa. Other researchers also report that
firm size is negatively correlated with probability of company exit (Lieberman 1990, Cohen and
Klepper 1996, Yang and Temple 2012, Lieberman 1990, Frazer 2005, Liedholm and Mead 1999).
Studying in a completely different way, a large number of researchers suppose that the company at
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the lowest production level often has a tendency to the exit behavior. On the other hand, if the exit
is the result of a market selection process, the inefficient firm will be high probability of exit
(Blanchard et al. 2012).
Following the previous authors, we will investigate the reasons to explain why size variable
effect on the firm’s exit behavior. According to Cohen and Klepper (1996), the bigger enterprises
tend to invest in Research and Development (R & D) that tries to explore methods to improve
existing products, and to develop new ones. In addition, they are supplied with necessary amounts
of physical, financial, human and other resources that protect company from failure and enhance the
possibility of exploiting scale economies and dealing with outside shocks. Thus, bigger enterprises
are also likely to survive in shakedown process.
A negative correlation between firm size and the probability of exit can be explained by
several reasons. Firstly, the company with higher level of size is easier to make the closure decision
if their level of production is at minimum efficient scales. Secondly, because larger firms are easier
to access to capital markets and have higher possibility to employ qualified and skilled workers,
thus they have a higher capability of being survival in comparison with small firms (Ferragina et al.

2012).
FIRM AGE
Another determinant is concentrated in the papers recently is a firm age variable. Dunne et
al. (1988), Thompson (2005) finds that the pattern of failure is systematically correlated with the
firm age and the failure rate of non-failing enterprise declines with age. Everything else constant,
the firm’s probability of exit decreases with firm age (Agarwal 1997, Agarwal and Gort 1996,
Audretsch 1991, Audretsch and Mahmood 1995, Olley and Pakes 1992). When researching on firm
activity, the empirical studies examine the impact of age on exit and propose the ratio of exit
diminishing with one (Agarwal 1997; Agarwal and Gort 1996; Wagner 1994; Mata and Portugal
1994; Mahmood 1995; Audretch 1991, 1994, 1995; Dunne et al. 1988). Other studies also report a
different relationship between the probability of exit and age of firm. They reveal an inverted Ushaped relationship between failure rate and age which can be predicted by the liability of
“adolescene” (Fichman and Levinthal, 1991; Bruderl and Schussler, 1990).

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Firm Age is accounted from official year of a firms’ starting activity to year t (Ferragina et
al. 2012). According to Dimara et al. (2008), age also is calculated in years from the time of
foundation for each enterprise.
Older firms are harder to exit due to characteristics which help them in preventing the exit in
the past (Ferragina et al. 2012). While Dunne et.al. (1988) and Disney et al. (2003), in their
empirical researches, show that younger firms have higher probability to exit because they are
learning about their true productivity levels, they do not have much practical experience. Moreover,
older firms which have survived in the long time are recognized themselves in the market hence
they might be better in surviving after adverse shock of given size (e.g. through their goodwill,
trademarks or the close connections to suppliers or to the capital market.).
PROFIT
Recent empirical studies have examined on the affection of Profit on the exit of enterprises,

which determine whether to exit or continue to market rests essentially on the enterprise’s prospects
for profits (Baggs 2005). The companies in both manufacturing and service sectors have a lower
ratio of exit if the one has more profit, while lower profits encourage the decision to exit (Ferragina
et al. 2012). Many researchers suppose that the firm with high profit has a negative influence on
firm exit proportion. However, other authors (Austin et al. 1990, Evans and Siegfried 1994) find no
connection between profitability and ratio of exit.
Pérez and Castillejo (2008) also reveal that the longer or shorter survival times of enterprise
might depend on the firm profitability. On the one hand, it is expected that profitable company will
have a better survival opportunities if high profit comes from market power. From provided profit
resources, companies can invest on assets by means of advertising and innovation that might
alleviate firm survival. On the other hand, high profitability might relate to shorter survival because
of some reasons. Firstly, innovative activities which bring high returns also increase the risk of
failure due to its uncertainty. Secondly, profitable firms might have higher possibility to be
involved in mergers or to be acquired (Pérez and Castillejo 2008).
Even though such this correlation would seem obvious to economics, the practical results
are mixing. Just like the conclusions from previous papers, we are expectation that the profit
variable will negatively influence to probability of exit.
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Overall, the activity of the enterprise has a functions and goals differently in every time
period. However, the final target is to obtain earning, which decides to the business plan of the
owner with expanding business operation in the competitive market condition. If the firm’s profit
does not cover all fees and costs to maintain the business operation, the company will fall into
financial crisis. Approach the model in perfect competition environment, enterprisers will consider
plan to go out business operation if they do not control and cover their fixed cost. Maximize the
profitability of firm’s business is chosen if their profit is above their opportunity cost (Agarwal
1997).

INVESTMENT
Investment activity is understood as the sacrifice of financial resources in the present to
obtain higher results for future investors. There are different investment activities such as:
development investment, commercial investment and financial investment. For a business, the
enhancement of competitiveness is achieved through a form of development investment which uses
financial resources, physical resources, labor and intellectual resources to build and repair buildings
and infrastructure, to train human resources to make regular expenditures associated with the
operation of these assets in order to maintain, enhance and expand the production. Other previous
studies have explored the effect of the investment on firm exit, which is considered a proxy for
expanding restructure, capability building and opportunities for investment in the business
(Colantone and Sleuwagen 2010). Other researching at Japanese firms reveals that oversea
investment and probability of firm survival have a negative relation (Kimura and Kiyota 2006).
If the business makes a profit in this financial year, they will have a tendency to set a plan
for investment on building, equipment, research and development (R&D), workforce and other
investments in next time. Other articles basing on the standard economic theory report that an
investment decision made by business owners could be treated as a risk with the ability of success
or failure (Rahaman 2009). Mistakes in investment can make a larger debt, thus causing serious
consequences for the business. Therefore, the investment activity can affect directly to development
of company and decide survival or exit of firm.
Geroski (1995) and Colantone et al. (2014) use an investment variable by accounting
logarithm of the net spending on tangible assets over sales at the industry level. However,
Khandelwal (2010) defines the investment as standing for net investment per one employee at the
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industry level. In my study, I use total investments of the last survey is an explanatory variable in
model. We expect that my result shows an impact positively on exit from an investment variable as
previous empirical studies.

LEVERAGE
An important determinant in exit model is a leverage variable. According to Bagg (2005), he
presents that several authors in recent literatures have focused on debt leverage as crucial
determinant in studying survival of enterprise in general and in the globalization context in
particular.
Several empirical articles give a positive relation between the likelihood of exit and leverage
(Fotopoulos and Louri 2000, Tsionas 2006). Baggs et al. (2005) show that higher debt leverage
increases firm exit compare to firm with lower one level. This means that the firm with higher
leverage level is negative relationship with survive. With the same result with other authors, Bags
(2005) shows firms having higher leverage are more likely to exit. However, less leveraged firms
see a lower probability of survival.
Like previous studies, Zingales (1998) also reports that the leverage is relevant to the ability
survival of enterprises in competitive environment conditions is positive relationship which is likely
to described results in papers of Heiss et al. and Huyghebaert et al (2004).
An Empirical study by Lang et al. (1994) points a definition of leverage is debt divided by
the total asset. In this paper, we use lagged leverage which is accounted by total debt per total assets
in last year (t-1) and expect to have a significant positive relationship with a probability of firm exit.
The firm’s manager always considers a decision in tradeoff advantage between the equity
and cost debt. Stockholders and bondholders also can happen to several conflicts when the firm
makes a choice between investment and financing policies. The reason for higher risk is that firm
using high debt leverage has to payment a large interest amount. Thus, they reduce the probability
of survival (Lang et al. 1994). The level of debt or the decision about financing instrument is
affected by many factors such as operating risk, firm size, the company's assets structure, and the
rate at which retentions are generated (Krugman and Paul 1980). When the firm has a high
leverage, firm’s capital's self-control ability is lessened because it relies so much on debt. Zingales
and Luigi (1998) reveal that enterprises with higher leverage have a tendency for less investment on
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the exogenous shock. Thus, the firms can be active to control their finance, which contributes to
reduce the exit ability. The company will reduce the probability of survival in case of a high level
of debt because of high interest payments. On the paper which published in 2000, Fotopoulos and
Louri said that the rate of debt to total assets is more likely to probability of exit.
ASSET
Baggs (2005) tests hypothesis about relation between firm survival, firm exit and several
variables: levels of employment, total revenue, total assets, debt leverage and tariffs for all
enterprises. He finds that the important result that asset will effect positively on ratio of exit if sales
are hold remain constant. Macus (2016) also comments to total asset as size variable in his research
when he focuses on determinants effecting on firms’ exit rate. The firm size impacts negatively on
the likelihood of exit, said Tsionas (2006). He used the firm size variable is the logarithm of the
firm’s total asset.
OTHER DETERMINANTS
RESEARCH AND DEVELOPMENT (R&D)
Research and development (R&D) is considered as a special spending regarding firm’s sunk
cost. It sets a barrier helps company less likely to exit. Doi (1999) reveals that (R&D) impacts
negatively to firm exit. In contrary with above result, Audretch et al. (2000) and Segarra and
Callejón (2002) find the positive relation between exit and (R&D). Audretch et al. (2000) also show
that R&D on high specialization industries is more increasing exit rate because it relates to bigger
uncertainty level. Besides, Mahmood (2000) also uses the R&D variable, which is collected data
from varies across industries, to measure an influence level on firm exit.
SUNK COSTS
The enterprise, which operates in several industries having a large level of sunk cost in total
asset, has a tendency to less probability of exit than other firms. Because the characteristics of asset
are durability and specificity create a barrier when business owner considers cost to exit. Other
evidence is provided by Fotopoulos and Louri in 2000 reveals that sunk cost variable and
probability of exit exist a negative relationship.

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CAPITAL REQUIREMENT
There are many papers in the world provide evidence about negative relationship between
ratio of exit and capital intensity such as: Audretch et al. (2000), Austin and Rosenbaum (1990),
Dunne and Roberts (1991), and MacDonald (1986). The capital requirement in one manufacture is
desirable to make decreasing exit because enterprises having a large capital level are more
responsibility with their resources. It makes a barrier to exit when owner consider a decision about
your business activity.
MARKET CONCENTRATION
Flynn (1991) and Doi (1999) show a hypothesis about relationship between market
concentration and likelihood of firm closure which has a negative relation. The main reason is
because enterprises operate in highly concentrated markets usually are applied monopoly policies
from this market segment which do not use for other firms.
INDUSTRY GROWTH
There are varied different results from researches in the world when they study about
relation between industry growth and firm exit. The downtrend of market is expected to increase
probability of exit. This result is consistent with conclusions are provided by Audretch et al. (2000),
Dunne and Roberts (1991), Segarra and Callejón (2002), Austin and Rosenbaum (1990), and Doi
(1999). Several papers present the opposite result such as: Evans and Siegfried (1993), Shapiro
(1983) and MacDonald (1986). A few other researches reveal no relationship between exit and
industry growth.
ECONOMIES OF SCALE
The minimum efficient scale (MES) is a lowest production point which one company needs
to achieve to produce a product at a competitive price compare to competitors. When they operate
below at MES level, they fall in disadvantageous situation compare to other companies in the same
industry because it takes more costs to produce goods. Thus, MES is an important determinant to
decrease exit ratio. Some articles give a same argument such as: Audretch et al. (2000), Mahmood

(2000), Wagner (1994) and Dunne and Hughes (1994).

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FIRM PRODUCTIVITY
Production capacity decides efficiency and effectiveness of enterprise. Thus, it impacts on
possibility of survival. This result is provided by several researchers when they studied in
enterprises product at lowest-productive level such as: Jovanovic (1982), Melitz (2002) and Ericson
and Pakes (1995).
2.2. Review of empirical studies on firm survival/exit
2.2.1. Approaches of analyzing firm exit and survival
Researchers approach issues about exit and survival follow many different perspectives.
Many of the works on the firm survival or firm exit have analysis at macro level. Some other
studies examine the effect of determinants on exit at the industry level. They collected data from
manufacturing industries, services industries or focus on several important industries at their
countries or across countries.
Colantone and Sleuwaegen (2010) put a lot of emphasis on ratio exit of firm at the twelve
manufacturing each country in eight European countries, during the period 1997 -2003. Kneller and
McGowan (2012) find the effects of tax policy on the enterprise entry and exit which was
conducted at 19 OECD countries over the time-span 1998 - 2005.
On the contrary, other scholars only focus on exit at the firm or industry, which exit is
considered as dependent variable in country level. Baggs (2005) considers both firms survive, and
exit based on firm information within 15 years, from 1984 to 1998 at manufacturing firms which is
supplied by Statistic Canada. Acs and Audretsch (1989) show that a ratio of return at the industry
level is likely positive to probability of entry and exit. There are many empirical researches recently
present a relation positively between ratio of exit at year (t) and ratio of entry at year (t-1) at same
industry such as: Backer and Sleuwaegen (2003), Mata and Portugal (1995), Dunne et al. (1988),

Siegfried and Evans (1994). Colantone and Sleuwaegen (2010) also put a lot of emphasis on ratio
exit and entry of the firm at the industry - country level. Other articles also focus on studying on
probability of enterprise exit at the industry level, such as: Brian & Vroom (2014), Blanchard et al.
(2013), Dunne (1988), Ferraginaa et al. (2011), Dimara et al., (2007).

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A large number of researches recently access enterprises operation through survive and exit.
They also use the different estimation models to evaluate the influence of determinants on firm
survival or firm exit.
Almost articles approach the effect of explanatory variables on the rate of firm survival
through using hazard model such as: Cefis and Marsili (2005), Agarwal and Gort (2002), Pérez et
al. (2008), Musso and Schiavo (2008), Görg and Strobl (2000).
The same with papers studied on firm survival, many other research articles around the
world use hazard models to study relationships between business and non-business factors and the
rate of firm exit (Dimara et al. 2008, Ferragina et al. 2012, Yang and Temple 2012). However, A
large number of recent papers have used probit regression (Blanchard et al. 2012, Frazer 2005,
Baggs 2005). Specially, Tsionas et al. (2006) use both logit model and probit model to examine the
relation between technical inefficiency (TI) and firm exit.
2.2.2. Emprical analyses of firm survival
Because of the important of enterprises in social and economic development, so there are
many discussions of firm survival base on its determinants and other characteristics not belong to
firms.
Cefis and Marsili (2005) imply proportional hazards Cox model with databases was
surveyed by the Central Bureau of Statistics in Netherlands. Company’s survival time is used as
crucial variable, which was excluded observes happened exit event. Independent variables include
innovation, firm size, firm age, firm growth, and industrial classification. The same results with

previous papers in the literature part, they confirm that age, size, and growth rate are more likely to
survive for longer. In addition, when they controlled for the influence of other variables such as
age, size, sale’s growth, and character of technology, innovation variable affect positively the
survival probability.
Besides that, Agarwal and Gort (2002) use three main determinants including: net
investment, disparity of initial endowments’ quality, and learning by firm to reduce cost, to increase
return, and to improve productivity. They also imply the overall hazard-rate function to focus on
simultaneously effect of independent variables, the variation in the probability of survival is
illustrated through three main determinants of firms, such as net investment, disparity of initial
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endowments’ quality, and learning by firm to reduce cost, to increase return, and to improve
productivity. Like with previous authors, they use the Cox proportional-hazards regression model
which was applicant mostly in survival analysis. They detect the positive correlation between
technology intensity and probability of survival, while ratio of high capital labor and firm survival
is contrary.
Moreover, Pérez et al. (2008) investigate the determinants of firm survival by using the
manufacturing firms data which was collected every year by Ministry of Industry in Spain. The
hazard model is implied to find the impact of hypotheses on survival based on the enterprise’s
Resource-Based Theory. This study describes that large, highly-productive and conducting R&D
firms are significantly better possibility of survival than other firms at a 1% significance level. They
also indicate that the firm operates in factors with high and low innovation levels are significantly
more difficult than in the intermediate level ones. The result is found by Audretsch (1995) and
Segarra and Callejon (2002) is the relatively unusual relationship between survival chance and age,
and the ratio of exit raises in the first period of a firm, then reduces and increase later.
In 2008, Muss and Schiavo implied a new approach explored the influences of financial
constraints on firm survival and development. In the line with previous researches, Muss and

Schiavo used proportional hazards form with panel data over the time period from 1996 to 2004.
They only focused on manufacturing firms in French. They found that the financial constraint is
positive relation with the likelihood of firm exiting.
Another recently study, Görg and Strobl (2000) focus on Multinational companies (MNCs),
using firm level data for Irish manufacturing industries for time survey from 1973 to 1996, study
the effect of multinationals on firm survival using a Cox proportional hazard model. They
investigate that MNCs influence positively in firm’s survival chance through technology spillovers,
but contrary through the crowding out of rivals. They do not detect any influence of MNCs
presence on domestic low tech companies and foreign companies in high tech sectors, while they
find a negative impact of MNCs on the survival of foreign firms at low tech industries.
A large number of papers use panel data of enterprises in varied country to find out the
factors affected to firm survival such as: Agarwal and Audretsch (2001), Mata and Portugal (2002),
Mata, Portugal and Giumaraes (1995), Audretsch and Mahmood (1995), Dunne et al. (1989). They
use the data at the firm level, and most explanatory variables have an influence negatively on ratio
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of firm survival such as: number of labor, the number of businesses that own their factories; a
competitive advantage of ownership; level of diversity; ability of learning by doing and
management experience. When they researched at the industrial level, the variables as process of
increasing industry, industry’s life cycle, development of technology have positive relationship with
firm of survival.
2.2.3 Emprical analyses of firm Exit
Consistent with many previous papers, Colantone and Sleuwaegen (2010) put a lot of
emphasis of international trade on ratio exit and entry of the firm at the industry- country level. This
rate is determined as the rate of the firm sum of shut down or birth at survey year over the sum of
surveyed firms in the given period. Furthermore, he also uses other variables to explain the
changing annual firm exit rate of the manufacturing sector, such as investment, capital intensity,

total factor productivity (TFP), index of change in trade, etc. This survey is conducted in eight
European countries. The author researches on two key dependent variables including the rate of
industry-level firm exit and rate of firm entry based on using the least Squares estimation. They also
use the lagged entry and lagged exit rate in their regression model. As expected, exit is more likely
with previous entry. Many other research’s results in the papers by Mata & Portugal (1994),
Siegfried & Evans (1994), Caves (1998), Dunne et al. (1988) show that entry and exit have a
positive relationship. On the contrary, this rate has the negative relation with a variable which
presents forward changing comparative advantage. By contrast, it is not significant with capital
sensitivity and multi-factor productivity. The variation in the trade openness at the first lag has
significant relation positively in firm exit, while the second lag is insignificant. This result is
consistent with previous papers show an effect negatively between trade openness and rate of firm
survival (Biernard et al. 2006a).
Viewing in another side, Huyghebaert et al. (2004) used hazard model to emphasis on the
effect of competition, debt leverage, and characteristics of financial market on the probability of
startups’ firm exit This research also reveals the correlation between competition ability and the exit
of entrepreneurial start-ups. Data and information for this analysis were collected from 235
entrepreneurial startups in Belgium over the years 1992–1999. The research has also shown the
negative significant effect between employees and exit in the year following start-up. The firm size
is a good sign for firm exit but debt leverage is not significant.
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By another study, Baggs (2005) suggests that exist the interaction in empirically modeling
exit/ survival between exit/survival and explanatory variables such as age, size, rate of firm entry,
and operation efficiency. Using a unique data set of Canadian manufacturing firms at the firm-level
control variables, he estimates an equation by using a probit technique to find the effect between
exit/ survival of firm and firm-level control variables, especially Canadian tariff reductions issue
when Canada agreed on Canada-US Free Trade Agreement. They found that lager firms in term of

labor and sales have an ability to survive better than other firm. It is likely with result showed by
Gu et al. (2002). However, lager firms in terms of assets have a lower probability of survival. By
other hand, if author held sales constant, the enterprises with higher assets increase ratio of exit. If
author estimated without sales as independent variable, we have a result inversely. They also find
that probability of firm survival has a significantly negative relation on leverage variable and highly
positive correlation with age. They also investigate that enterprises with higher leverage are more
likely to exit than enterprises with lower one levels.
Add a study was conducted in European countries by Colantone et.al (2014) also uses the
method of least squares to fit a model to their data with Dummy Variables, divide into small
companies and large companies group, over time-span 1997-2003. The dependent variable in this
empirical model is the industry level exit rate which is affected by the change in import competition
condition. In particular, they find the same result with previous studies. Large enterprises with
larger production scale increase the probability of exit when global competition environment is
higher level. The empirical also give the positive relation between exit and previous entry. This
result is showed by De Backer and Sleuwaegen (2003), Mata and Portugal (1994), Dunne et al.
(1988). They also investigated a positively relationship between exit and lagged sectoral TFP
growth, but only true for large firms (Malerba 2007). Additionally, the effect of import competition
variable on firm’s exit is heterogeneous. Dunne et al. (1994) point that large enterprises operate in
large scale production increase exit if import competition was higher but the exit of small firm is
not impacted by imports factor in low-cost nations. However, the relation between exit of small
firms and import competition in developed economies countries is vice versa.
Yang and Temple (2012) use labor Productivity as the indicator of firm performance.
Similar to the empirical model in previous papers, they use hazard rate model to evaluate effect of
determinants on firm exit by using data collected all firms belong to manufacturing sector in China

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