National Institutions and the Impact of
Bribery on Foreign Firms
Master Thesis International Business and Management
Theme: Emerging Economies
Mihail Yonkov, S2435802
e-mail: m.yonkov@student.rug.nl
phone: 0617 329282
First Supervisor: Dr. S. Gubbi
Second Supervisor: Dr. I.Kalinic
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Abstract
This research is focused on the impact of institutional environment on foreign firms’
propensity to engage in bribery behavior. The study is focused on 734 firms from 21 countries from Central and Eastern Europe. The results of the regression analysis proved a significant relationship between perceived level of corruption and propensity to bribe, while
bureaucratic government inefficiency and propensity to bribe did not. Results show that informal institutions have a significant influence on foreign firm’s behavior – the more
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Table of contents
1. Introduction .………..………..… 5
2. Theory building ………..……….……….. 8
2.1 Bribery………..……… 8
2.2 Theoretical Framework ……….… 9
2.2.1 Regulatory dimension ……… 11
Bureaucracy ………..……… 11
Corruption ……….………... 12
2.2.2 Normative Dimension ……… 13
2.2.3 Cognitive Dimension ………..………… 15
3. Methodology ……….… 17
a) Data Description ……….. 17
b) Definition of Variables ………... 19
Dependent variable ………..……….……… 19
Institutional variables ……….……….. 20
Control variables ……….. 20
c) Statistical Model ……….……….… 21
4. Results ………..……….... 24
Descriptive Statistics ……….………. 24
Regression analysis ……….………..……. 25
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a. Regulatory dimension ……….………. 28
b. Normative dimension ……….. 29
c. Cognitive dimension ……….. 30
d. Implications ………. 32
e. Limitations ……… 32
f. Venues for future research ……….. 32
References ……….. 33
Appendix ……….. 40
Table 1 List of the 21 countries with according CPI indexes and ranks for
inefficient government bureaucracy inefficiency ………. 40
Table 2 Definition of Variables ………..………..…. 41
Table 3 List of industry dummy variables …….………. 42
Table 4 Skewness and Kurtosis ………. 42
Table 5 Descriptive statistics and Pearson correlations ………..…… 43
Table 6 Regression Analysis ………. 44
Table 7 Tests for multicolinearity and heteroscedasticity ………. 45
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1.
Introduction
Although formal and informal rules and regulations were established on a national and international level by governments and non-profit organizations, corruption is still a major issue for multinational enterprises (Spencer and Gomez, 2011). Corruption is most commonly defined as misuse of public power for private gains (Habib and Zurawicki, 2002). Over time, corruption was decomposed more precisely to its particular dimensions (Habib and Zurawicki, 2010), the most prominent of which and most often referred to is bribery. Focusing on the issue of paying bribes Rose-Ackermann (1999) concluded that they are very akin to paying blackmail. Although
a bribe can help to win a contract, the firm becomes exposed to further extortion attempts,
especially when bribing to obtain investment opportunities. Also, after a substantial investment was made, the costs of refusing to pay bribes increase.
Furthermore, Lui (1985) introduced the “efficient grease” hypothesis which suggests that bribery can reduce the time required for some interaction between an economic agent and the state. On one hand, Kaufmann and Wei (1999) find that firms that pay more often bribes spend more management time with bureaucrats and face higher cost of capital. De Rosa et al. (2010), on the other hand, prove that in developing economies regular bribe payment can be a second best outcome, because management spends less time dealing with red tape and thus, can focus on productivity issues.
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transition countries (Habib and Zurawicki, 2002). Moreover, the MNEs need more answers on dealing with institutional environments which are on the other side of the ever-broadening income gap between rich and poor regions of the world. This research provides insights on a region that is very close to the “rich countries”, but still institutionally quite remote from it, namely the developing economies of Central and Eastern Europe (CEE). A research on bribery and its interaction effects with local institutional environment can provide answers on MNEs’ decision-making processes and appropriate behavior in a developing country. Only a few researches have focused on corruption and its impact on MNE performance in CEE (Kuznetsov et al, 2010, De Rosa et al, 2010). Little is known about the different institutional-specific effect of bribery and its consequences on foreign multinational’s performance. The research measures the combined effect of regular bribery behavior and inefficient formal and informal institutions and its harmfulness to the performance of MNEs in developing economies. The problem attracts high level of interest because (according to Thomas’s classification, 2004) of its composition – bribery behavior seems a homogenous phenomenon, but it is in fact intermingled through formal and informal social networks and organizations, followed by ambiguous consequences for the foreign firm.
Following the institutional line of logic, the paper aims to produce common understandings about what is appropriate and, fundamentally, meaningful behavior (Zucker, 1983: 5) in institutionally weak environments of developing economies of CEE. MNE decision makers are provided with answers how to deal with such environments instead of avoiding unstable countries with poor formal and informal rule enforcement, as it happens especially to firms with strong anti-corruption home country policies.
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Development (EBRD) and the World Bank. 12000 firms from 29 countries from Central and Eastern Europe and Former Soviet Union with poor public services sector and low regulatory enforcement have participated. Additionally, Global Competitiveness Report’s indexes 2008-2009 and Transparency International’s Corruption Perception Index (CPI )are used to measure the level of bureaucracy and corruption on country level.
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2.
Theory building
2.1
Bribery. Literature Review.
Bribery is a type of corruption connected with the act of giving money or gift giving that alters the behavior of the recipient. Bribery behavior has attracted the attention of scholars on various fields and is usually studied on country- or individual level (Luo, 2004). Firm-specific rationale to bribe is considered important, especially in host-country context, as it is firm’s choice whether to bribe or not (de Jong et al, 2010). Although payment of bribes has been acknowledged by many companies in emerging markets as a way to get things done (Spenser and Gomez, 2011), studies have barely focused on institutional-specific effects of bribery and its consequences on firms’ behavior. This is an important issue to address because literature has hardly focused on supplier side of bribery in different institutional environments (Martin et al. 2007).
In emerging economies, there are large institutional gaps of normative regulative and cognitive type that can impede subsidiary’s performance. In the regulatory country context of Central and Eastern Europe, a strong control over natural resources, bank loans and business formation and operation is observed. In order to make it through, the foreign firm has to choose whether to comply or defect the local “rules of the game”. Relationships with government or public officials can be a tempting and logic choice to make. By involving in bribery behavior, host-country managers are likely to obtain easily resources, win orders or deal with bureaucratically imposed constraints to business. As Peng and Heath (1996) argue, such behavior can be interpreted as an “investment” in institutionally weak environment. Nevertheless, such relationships in Graeff’s (2005) “shared belief of reciprocity” between government officials and managers can result in excessive bribe extraction or further demands.
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impose a “time tax” connected with the time managers spend on bureaucratic procedures. The time of interaction with these officials and overcoming bureaucratic hurdles is ultimately linked to the frequency of bribe payments (De Rosa, 2011). Furthermore, the combination of regulatory requirements and power of the officials to collect bribes increases the overall prevalence of corruption (Djankov, La Porta, Lopez de-Silanes and Shleifer, 2002). That’s why connection between bureaucracy, corruption and propensity to bribe is further explored in this paper.
On normative level bribery behavior is determined by informal rules, values and expectations of the environment a firm interacts with. Especially in a developing country, where the legal enforcement is poor alternative means of action can determine foreign firm’s behavior. DiMaggio and Powell (1983) argue that a foreign firm is likely to undergo an isomorphic change and adopt local model of behavior in order to comply with the host reality. Hence, in an institutionally unstable environment with considerable level of informal activity and where bribery is not perceived as wrongdoing, propensity to bribe for foreign firms should be easier to observe.
On cognitive level, bribery activity is a matter of subjective interpretation of the foreign firm. It has to understand the specific actions it needs to take in objective conditions to achieve particular results in the foreign institutional environment. MNEs are more likely to resist bribery because of more resources, better know-how and business ethics and norms. Unlike the local SMEs which are more likely to perceive corruption as “the usual way to go” because they have less resources to tap (de Jong et al, 2010), foreign firms’ decision making does not necessarily overlap with local environment and hence, can reach other decisions to act which include avoiding regular bribing activity.
2.2 Theoretical framework
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structure of a society and the political and economic institutions are the underlying determinants of economic performance.”(North, 1994) The behavior of organizations is a reflection of the opportunities of the institutional matrix. Moreover, institutions govern societal transactions in the areas of politics, law and society (Peng, Wang and Jiang 2008). Often they restrict the logic of market forces and deal solely with distribution conflicts (Ogilvie, 2007). Therefore, if the institutional framework provides incentives for bribing behavior, than organizations are likely to adapt accordingly. One should think of bribery as part of this framework rather than a “bad” outcome, as institutions are created for the sake of rules, rather than efficiency (North, 1994). Furthermore, Eggerston (1990) argues that same institutions can explain both the success and failure of collective actions. They can promote and constrain economic performance in different periods of time (Eggerston, 2005). Thus, bribery shouldn’t be perceived as a core factor for underperformance, but just as one of the many idiosyncrasies of a country that influences firms’ behavior and decision-making.
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2.2.1 Regulatory dimension
Regulatory dimension is the system of existing laws and rules in a particular national environment which formally promote certain types of behavior and restrict others. It concerns official regulations and persons who enforce them. The differences in corruption toleration and bureaucracy impediments are strong determinants of foreign firm’s behavior in a developing country context. The efficiency of regulatory framework determines the perceived fairness of the system (Schneider and Enste, 2000) and hence – the extent to which a foreign firm should comply with local formal rules. If the rule enforcement is poor (as is the case in the countries of CEE), additional pressure can be exerted by public officials, who can consciously force foreign companies to pay more bribes (Spencer and Gomez, 2011). Hence, regulatory pillar has a tremendous influence on foreign firm’s propensity to bribe. Perceived level of corruption and bureaucracy impediments are further explored as the major problems firms face in a developing country.
Bureaucracy
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opportunities for public officials. Three elements stem from bureaucracy and can create opportunities for corruption – institutional imperfections in monitoring, monopoly power, and discretion of the public official. Bribery is mostly connected with the third element, because it is an effective way for a firm to circumvent rules and accelerate approvals (Getz and Volkema, 2001). In an emerging economy, these effects are likely to be more pronounced due to relatively bigger institutional inefficiencies.
H1a. In a developing country higher bureaucratic burden is positively correlated to foreign firm’s propensity to bribe.
Corruption
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Perceived level of corruption is a factor that denotes foreign firm’s propensity to bribe. If a host country becomes more or less corrupt that is likely to affect firms’ decisions connected with time efficiency and interaction with public officials. The increase of corruption levels can impede foreign firm’s performance and create further obstacles to its normal operation.
Some of the reasons for higher level of corruption are the stable social welfare structures and legal enforcement. If they are absent or inefficiently functioning, they cannot prevent the relation system of self-interested agents where everybody looks after his own interest (Messner & Rosenfeld, 1997). When institutional safeguards are in place in the form of protective services and resources received as entitlements, rather than from success in cut-throat competition on the market, there is less need to achieve desired ends using deviant means (e.g. Messner & Rosenfeld, 1997; Savolainen, 2000). The more the host-country institutions resemble a stable regulatory environment, the lower the perception of corruption and intentions for wrongdoing will be. The enhanced perception of institutional security diminishes the temptation for foreign managers to resort to illegitimate means like regular bribery for sustaining their firms and achieving basic security for themselves and their employees (Merton, 1964, 1968). Thus, if the host-country institutional environment don’t presuppose engaging in corrupt practices, foreign firms are less likely to engage in frequent bribery.
H1b. In a developing country foreign firms are less likely to bribe if the perceived level of corruption is lower.
2.2.2 Normative dimension
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institutions and the influence of informally institutionalized practices. Local companies exert influence on foreign firms and thus affect their decision-making processes. In a developing country, where informal behavior and bribery are more common and informally institutionalized, foreign firm may change its attitude to paying bribes. Here, other informal activities than bribery are omitted, relying on Spencer and Gomez’s findings (2011) that foreign firms are unlikely to engage in a broad informal activity.
Normative behavior is a projection of the regulative one, although not always a function of it. Every player on the market plays to a certain extent to the formal rules no matter of the institutional framework stability and legal enforcement. Nevertheless, normative-driven behavior differs a lot from the regulative-driven one and is characterized by diverse reactions to institutional environment and more heterogeneity in the decision-making. Part of this normative behavior is the decisions connected with informality. Mishra and Ray (2013) argue that there is a strong connection between informal behavior and bribes. Something more, some local firms prefer to stay informal and the bribes are the means to guarantee their status. Such a behavior can influence MNE on its propensity to bribe.
Informality stems from inequality within an institutional context and “rules of the game” enforcement. Such weak institutions which generate equality in a poor manner sooner or later are followed by increased level of informal activity. Local firm decision-makers are likely to go informal when they still have incentives to run their business, but costs associated with formality are more than legally obtained revenues. In a system with perceived unfairness, certain “accepted levels” of informality emerge.
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social security and tax burden on firms. Thus a vicious circle is thus created in which more and more firms go into the informal economy.
Schneider and Enste (2000) describe the factors that are the main causes for increasing informality. They point out increased tax burden, excessive regulation in the official economy, unemployment and decline of the civic virtue and loyalty towards public institutions combined with declining tax morale as the most important ones. From and interdisciplinary perspective, other sociological and psychological factors can be identified like the perceived fairness of the system amongst the economic agents and the propensity to circumvent rules.
Operating in such an environment, one can expect that behavior of foreign MNEs is likely to change, and the host country managers will be more likely to bribe on regular basis. A similar connection as the one of Collins and Uhlenbruck (2004) is expected to be found, who find an empirical support that managers who perceived that corruption is just reflecting “the way things are done” are more likely to engage in bribery practices, even though they perceive them as wrong and immoral. When the rules of the game are loose and poorly enforced, foreign-owned firms will “slack” and adopt a similar not-so-strict way of conduct.
H2: in a developing country context, foreign firms are less likely to bribe regularly if the local firms are not engaged in informal behavior.
2.2.3 Cognitive dimension
The cognitive dimension draws on the idea that social actors act because they attach meanings to their actions. Meanings are socially created through communication and interaction. The cultural cognitive pillar emphasizes on particular types of actors and scripts for action over roles and obligations. As MNEs have well established principles, business ethics and codes of
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There is a risk for a foreign firm to start acting like local ones though, and this is described by the isomorphic pressures. Isomorphism is the process that makes organizations in a specific institutional environment more similar through time (DiMaggio and Powell, 1983). The higher the isomorphic pressures in an environment are, the more likely for a foreign firm is to
resemble local firms’ behavior. Hence, if local firms’ behavior includes the social practice of bribing to “get things done” on regular basis, then a foreign firm ceteris paribus is likely to apply decision-making processes that include such actions.
Two interconnected factors that can explain the firm decisions on cognitive level are size of the company and difference in perception to bribe. They can explain to a certain extent the
resistance of the foreign firm to the isomorphic pressure in the host environment. Spencer and Gomez (2011) find that the more a foreign firm interacts with local partners, the more the difference in perception of corrupt behavior is mitigated. But as foreign-owned firms are usually bigger and outperform local ones in an emerging market context, (Chang, Chung and Moon, 2013) the mimetic pressure will be of less significance. Moreover, due to cultural differences in perception of bribery, MNEs can reject the local taken-for-granted way of operating and thus deny engaging in typical local practices, including paying regular bribes. As bigger companies, MNEs are able to resist isomorphic pressures by having superior
administrative heritage, organizational practices, know-how and technology. Last, but not least, most MNEs are socially responsible or humane-oriented firms, and are concerned with
relationships and the ways people treat one another in a society (Martin et al., 2007). Lack of local support to the idea of humane orientation or basic social support can make the big foreign firm oppose local practices, as they contradict their ethic code and can result in legitimacy spillovers (Kostova and Zaheer, 1999). Hence,
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3 Methodology
a. Data Description
In order to test the hypotheses the publicly available database BEEPS 2009 is used. It is a joint initiative of European Bank for Reconstruction and Development (EBRD) and the World Bank. The survey covers 27000 companies from 29 countries (Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Former Yugoslav Republic of Macedonia, Georgia, Hungary, Kazakhstan, Kyrgyz Republic, Latvia, Lithuania, Moldova, Mongolia, Montenegro, Poland, Romania, Russia, Serbia (including Kosovo under UNSCR 1244), Slovak Republic, Slovenia, Tajikistan, Turkey, Ukraine and Uzbekistan). The data helps to receive a feedback from foreign-owned enterprises on the state of the private sector in each country. It deals with delicate questions of corruption, bribery, competition from the informal sector, etc. As De Rosa et al. (2010) argue the sample is interesting to observe, due to its diversity. The countries present a substantial variation ranging from low-income former soviet countries of Middle Asia to the high-income new-EU members from Central and Eastern Europe. In order to obtain more consistent results, some countries from Former Soviet Union were dropped from observation. Thus, at the end the research is focused on 21 countries - Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Former Yugoslav Republic of Macedonia, Hungary, Latvia, Lithuania, Moldova, Montenegro, Poland, Romania, Russia, Serbia, Slovak Republic, Slovenia, Turkey and Ukraine.
Only firms with 10+ employees are included. This is because small firms “tend to be more nimble and adaptive to changes in the competitive environment” (De Rosa et al, 2010). Even after this restriction, the variety of firm size remains high. In the final sample the number of permanent workers in a firm ranges from 10 to 10,000, while the total annual sales range from 30,000 USD to 3,45 billion USD.
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might not be enough. On the other extreme, Sytse, Rejie and Rezaul, (2006) define foreign-owned firms as ones with less than 50% local partner ownership. Otherwise, they can ostensibly be regarded as local firms. This statement is not completely sound, because much smaller ownership share can determine firm’s performance and behavior. Implementation of foreign-owned technology and know-how, for example, can force the firm to behave in very different way. According to Claessens and Tzioumis (2006) in emerging economies blockholders have to hold 25 or more percent of ownership to be considered significant. That’s why the paper treats a firm as foreign if it has more than 25% foreign ownerhip.
Entries from the database that did not provide enough information were removed (for example when interviewee has answered with “not applicable” or “I don’t know”). Initially, there were 1048 foreign firms with foreign ownership above 25% in the BEEPS 2009 database, but after careful filtering for suitable information, 734 entries for 21 countries remained to test the hypotheses. Detailed information about them is provided in the Appendix, table 1.
Furthermore, Corruption Perception Index of Transparency International (TI) is introduced as additional source of data. The index represents how corrupt the public sectors are by their perceived levels of corruption, as determined by expert assessments. The survey is being conducted since 1995. For the purpose of the research data for year 2008 has been implemented.
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b. Definition of Variables
Dependent variable
The measure of propensity with which foreign firms bribe is introduced to this research as a dependent variable. At first this variable was planned to be constructed according to Spencer and Gomez’s approach (2011), who use factor analysis and varimax rotation to estimate the dependent variable as a function of data, based on answers considering specific situations that may require bribing behavior (such as construction permission, obtaining of licenses for operation and import/export, electricity, heating, water permissions etc.) In their research though, they are using BEEPS 2000 which provides more detailed information on these questions. However, they are not present for all countries in BEEPS 2009, and that’s why other measurements of propensity to bribe had to be estimated. Unfortunately, there was very low level of response on some direct measurements like “Total annual gift payment” and “percent of total annual sales paid in bribes”. The simple explanation is that for most researches of corruption the items have to be rephrased indirectly and thus the respondents don’t feel implicating themselves in wrongdoing (Svensson, 2003). In other words, only a few of the interviewed managers are ready to share directly such information, although the questionnaires are anonymous.
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Institutional Variables
The detailed description of each variable is provided in the Appendix, table 2. A simple distinction is made between institutional and the “other” control variables. The institutional variables in this study describe the different institutional influences of the host environment on the foreign firm. First, the firms were categorized according to their country of operation. The national institutional environment has a crucial significance on the firm. Based on it, the research is able to compare the specific institutional peculiarities of the examined countries. CPI index is an explanatory variable imported additionally to the BEEPS dataset and its purpose is to give a quantifiable measure of the perceived level of corruption. It will contribute to the comparison of firm’s propensity to bribe and the according behavior. The use of more data sources is expected to provide more robust results. CPI was re-codified because the official results from Transparency International’s survey suppose that countries with highest corruption score lowest.
The bureaucratic government inefficiency is described as the extent to which it is a problematic factor for making business in the particular country. The results are re-codified to a scale of 1 to 5, where 1 stands for no or minor problem, and 5 stands for major problem.
Ranking and detailed information for CPI and bureaucratic inefficiency variables are provided in Appendix, table 1.
Informal behavior variable provides answers to the question “how much of an obstacle are the informal sector competitors to your operations?” This variable has values from 0 to 4, where 0 is codified for “no obstacle” and 4 is “very severe obstacle”. As argued before, the perceived as informal behavior of competitors is likely to influence firm’s bribery decisions.
Control Variables
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experienced firms obtain more learning benefits and usually have first mover advantage. On the other hand, Sytse, Rejie and Rezaul (2006) find that old firms are more prone to inflexibility and inertia and they can be slow in adaptation to competitive pressures. Due to huge variance in the responses of these variables, heteroscedasticity issues were eliminated beforehand by creating logarithmic versions, namely LOG Firm Size, LOG Years of Operation and LOG Annual Sales.
Industry variables (INDVARD2-60) describe the industry a firm belongs to. Thus, the results will be checked for industry-specific effects. Dummy variable for each of the 18 industries present in BEEPS is created. Codification of the dummy variables is available in Appendix 1, table 3. According to Transparency International’s Bribe Payers Index (2011), there is a substantial difference in bribing activity across different sectors. The study determines the public works, contracts and construction, utilities and consulting services as the sectors with the highest likelihood for foreign investors to bribe.
c. Statistical model
The research studies the frequency of decisions to bribe on performance and decision-making of a foreign-owned firm. The general form of the estimated regression is:
Propensity to engage in bribery= f(institutional variables, control variables) (1)
The specification uses the results for perceived frequency of bribe payment PROPBR as dependent
variable. The different institutional dimensions of each country are used as explanatory variables. The final model of logit regression model for testing hypothesis 1-3 has the following expression:
Logit Propensity to Bribe(y=1)= f(β0 +β1(Bureucratic government inefficiency) + β2(CPI) +
β3(Informal Behavior) + β4(LOG Years of Operation)+ β5(LOG Firm Size)+ β6(LOG Annual Sales)+
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Where y indicates whether firm bribes, l stands for the number of industry dummies and εi is
the error term. β0 is the intercept. β1,- β6 measure the average impact of institutional
environmenton firm performance and propensity to bribe. The regression coefficients show
how an independent variable varies with each unit change of the associated independent variable (Blumberg, Cooper and Schindler, 2008). This model is run with all 734 entries of foreign firms.
First, tests for multicollinearity and heteroscedasticity and normality are conducted to secure the provision of best linear unbiased estimates. Although these assumptions are commonly made for ordinary least square analysis, they still apply for logit regressions. When testing for multicolinearity the variance inflation factor (VIF) for all variables is in the range of 1.1-5.8, and the mean is 2.46. According to Neter, Wasserman & Nachtsheim (1985) multicollinearity is not a problem if VIF has value below 10. The results show that independent variables are not perfectly correlated in a way that they are not linear functions of other explanatory variables (Hill et al., 2009). Detailed results are provided in Appendix, Table 8.
Homoscedasticity assumption states that variance of error term is the same for all observations. The test is important because heteroscedastic dataset can result in giving more weight to observations with larger error terms. In this sample heteroscedasticity is expected for annual sales, firm age and firm size. Breusch-Pagan test is run for all of them; the results (available in Appendix, table 7) reject the null hypothesis and prove that the variance is similar
for all types of firms, as the chi2 is above 5% of significance.
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4 Results
Stata 12 software is used to run the statistical analysis. The descriptive statistics are presented in Table 5 of the Appendix, while regression analysis is available in Table 6.
Descriptive Statistics
Some interesting observations can be noted. First, the ownership share on average is very high – nearly 83% and standard deviation of 24% According to Rousova’s study (2004) on European multinationals investing in Central and Eastern Europe, successful performance of German and Austrian multinationals in that region is achieved through transplantation of organization or centralization. Both options require substantial investments. That’s why the fact that foreign-owned firms have very high percent of foreign ownership on average is not surprising. Moreover, in institutionally weak environment with low-efficient markets and restricted access to local resources, MNEs are more likely to prefer creation of a new entity or partnership with a local firm to the extent to which it will secure the access to local resources (Meyer et al., 2009). Hence, most of the firms from the sample are either fully foreign-owned or with very small local participation. The firms with foreign ownership between 25% and 50% are only 82. One could argue that foreign investors prefer to have majority share of the foreign subsidiary in Central and Eastern Europe. Geographical proximity can be one of the possible explanations. The countries from Central and Eastern Europe have institutional similarities on all 3 levels (normative, regulative, and cognitive) with the major FDI investors from Western Europe and the US. Prior to the conduction of the survey (2009) 10 of the countries had joined the EU, while the others had signed multilateral trade agreements and liberalized their market systems. Also, CPI and BUREAU means show that on average there is a considerable regulatory pressure in the data sample countries (3.36 and 3.29 respectively). Foreign firms face moderately high corruption levels and government bureaucratic inefficiencies.
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bribe is 2 with standard deviation of 1.3; this implies that the foreign firms face significant difficulties in these countries that deserve to be examined. As they are actively involved in the host environment, the MNEs are required to spend considerable amount of time, complying with government regulations, which is described by de Rosa et al. (2010) as “time tax”. How do they tackle the problems though, is yet to be examined. Furthermore, there’s a great variance between the entries for size, age and annual sales per firm. The smallest foreign-owned firms have at least 10 workers and more than 30000USD annual sales. Nevertheless, the standard deviations and means report that on average the foreign firms generate high total sales on yearly basis, with as many employees as for the firm to be considered medium or large enterprise.
Table 5 provides analysis of the correlations between variables as well. As Taylor (1990) argues, in a larger sample a correlation of 0.2+ can be considered significant. Only the CPI index is strongly and positively correlated to the propensity to bribe (0.32). Very strong relation (0.48) between CPI and inefficient bureaucracy is observed as well. Apparently, in the developing economies from the data sample weak institutional environments are marked by a combination of ineffective and/or excessive regulation and strong perception for corruption. Strong expected correlations (above 0.60) are observed between the log-ed values for firm size, and total annual sales. This observation is quite intuitive and corresponds to the general idea that a bigger company with more employees is able to generate higher amount of annual sales.
Regression analysis
5 models of logit regression are run. Confidence level intervals are at 95%. Each regression is controlled for industry effects, firm size, annual sales and age of the company.
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squared value is low but the predictors are statistically significant, one can still draw important conclusions about how changes in the predictor values are associated with changes in the response value. Regardless of the R-squared, the significant coefficients still represent the mean change in the response for one unit of change in the predictor while holding other predictors in the model constant. Hence, this type of information can be valuable.
Second, it’s the nature of the dataset that had been used. The responses on institutional environment are codified in small scales between 0 to 4 and 1 to 6. This results in large and stepwise variance in responses. Hence, a small change in these variables can turn a never-bribing firm into a regularly never-bribing one.
Moreover, a lot of dummy variables are used to test for ownership level and industry effects. If the dummy variables were substituted with other metric variables, than the r-squared could have been significantly higher. Last, but not least, in some models there are only few variables used and the other determinants that explain behavior of a foreign firm in emerging market can be omitted. That is the reason why the r-squared is highest in the model with most variables. P value is significant, so the models have some prediction value.
Dummy variables were also included to measure industry-specific effects because difference on these dimensions can influence the relative performance of the firm (Sytse, Rejie and Rezaul, 2006). Detailed description of the industry variables is provided under Table 2 of the Appendix. Table 6 of the Appendix provides the summarized results of the regression analysis. Hypothesis 1a checks if in a developing country higher bureaucratic burden is positively correlated to foreign firm’s propensity to bribe. Surprisingly, the results from Model 3 of the regression analysis table show that there is strong and negative relation between the two variables (-0,156), significant at 1% level. Thus, the first hypothesis is rejected.
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and significant, or firms are more likely to bribe regularly if the CPI index is higher. Hypothesis 1b is confirmed.
The effects of normative institutional dimension of a developing country environment over foreign firms is explored by hypothesis 2, which states that foreign firms are less likely to bribe if the local firms are engaged in informal behavior. Model 5 provides the required regression and supports the notion that with every 1 point increase in informal behavior, firms become 50% more likely to engage in regular bribing. Thus, hypothesis 2 is confirmed.
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5. Discussion and Conclusion
In this research the influence of the institutional environment on foreign-owned firms in 21 developing countries from Central and Eastern Europe was observed. The institutional environment (following the classification of Kostova (1997)) is divided into 3 dimensions: normative, regulative and cognitive. 734 companies with foreign ownership share above 25% were chosen from BEEPS 2009 database to test the research assumptions.
Descriptive statistics show that in a weaker institutional environment foreign firms on average have high ownership share (83%) and relatively high total annual sales. Strong correlation was observed between propensity to bribe, Informal behavior, and perceived level of corruption, as well as between perceived level of corruption and government bureaucratic inefficiency.
Regulatory dimension
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Moreover, findings suggest that inefficient government bureaucracy is not a factor that is always influencing negatively foreign firm’s decisions and especially the propensity to bribe. The statistical results show that inefficient government bureaucracy has a significant and negative effect on foreign firm’s propensity to bribe (-0,156). It is very likely that the measurement for government bureaucracy inefficiency did not adequately capture all qualities of bureaucracy. Going further, one can assume that this inefficiency is not “one-sided” - bureaucracy does not mean only obtaining licenses and permissions and spending time dealing with public administration, but also monitoring and rule enforcement. If the latter are not present, and hence, the firm interacts less with government officials, it will be less likely to engage in regular bribing behavior. This insight is consistent with Mishra and Ray’s model (2013), according to which firm’s choice to pay bribes is connected with the probability for inspection by official and the chance for him to report the non-compliant firm.
Normative Dimension
Normative institutional dimension refers to the informal rules that exist within a certain country/society. The effect of this dimension on foreign firms in the developing markets of Central and Eastern Europe was conceptualized by the informal behavior. The results from the logistic regression provide support to the assumption that a foreign firm is more likely to bribe if the informal behavior amongst its competitors is high. One could argue that to a certain extent foreign managers have to adapt their practices to local environment to “get things done”. As Collin and Uhlenbruck (2004) state, foreign managers can involve in regular bribing if it is not perceived as a wrongdoing and if it has less or no harmful effects for the operation of the firm.
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is stronger in developing countries with higher social inequality and institutional imperfections. The hypothesis 2 confirmation is in line with Mishra and Ray’s (2013) findings that a “shadow or underground economy” (Schneider and Ernste, 2000) and “unofficial activities” (Friedman, et al., 2000) play a significant role in developing countries.
Cognitive dimension
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developing country or the financial stability have no meaning over time, more likely it’s the moral and perception for wrongdoing in management team.
Another interpretation is connected with the fact that for the purposes of the analysis age and number of employees of the firm is connected to its ownership, but in fact the decisions of how often to bribe are barely connected in a straightforward manner with the ownership and the board of directors. These decisions are taken by managers and on operational level. Probably the better question to ask is whether a foreign partner influences the decision to engage in a bribery behavior in general or what are the boundaries of wrongdoing (in terms of prestige, moral, business ethics etc.)
Implications
The findings of this research can have important implications for MNE managers. They have strong interest to understand better what type of institutional pressure they are facing when operating in a developing country market and what is the impact of eventual bribery behavior might be. According to the specific pressure managers have a clearer idea how to react and mitigate the effects of bribery. The worse a foreign-owned firm performs in host environment, the more likely it is to engage in bribery behavior to mitigate the “time tax” effect or avoid red tape. Firms that encounter prevalent bribery may experience higher unpredictability and higher business operation costs (Kaufmann and Wei, 1999). MNEs that strongly rely on their business ethics and reputation may have to reconsider their entry mode strategy or behavior mode in the more corrupted host country. Last , but not least, the subsidiary has to get to know better the local environment and adjust to it, as this is the only chance to secure good subsidiary performance.
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Measures connected with reducing the effects of the aforementioned are likely to improve business climate and attract more FDIs. Furthermore, some MNEs are by no means going to engage in corrupt behavior due to CSR, ethics or principle of fairness. Additional administrative pressure on such companies can have negative effect on the country’s reputation as an investment destination.
Limitations
Certain limitations should be acknowledged as well. Firstly, it’s the variables from the BEEPS dataset that are perceptual in nature. There could be different perceptions of the honesty interpretation, as any type of bribery or corrupt behavior can be interpreted as wrongdoing and thus - underreported (Spencer and Gomez, 2011). The overall effect of bribes might be underestimated due to selection bias, as foreign firms that had to pay the largest bribes may had been driven out of business and hence, not included in the dataset (De Rosa).
Furthermore, the research on bribery is only one-sided, as the focus is put on propensity to bribe only. Due to limitations in the data sample it was not possible to obtain enough information on amount of bribes paid or bribes as a percentage of the total annual sales.
The nature of the topic of bribery and corruption in general is always connected with a certain level of discrete and mysteries. This is something that is seldom openly discussed. This creates further impediments, as may be the respondents were not ready to open up and speak on this issue. Thus, having only 734 reliable responses mean an average of 20-30 responses per country, which can be considered as not enough reliable.
Venues for future research
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destinations that provide lucrative returns of assets and investments, but are as well associated with similar levels of corruption, informality and bureaucracy inefficiency. On the other hand, more can be contributed to this field of study if the MNEs’ origin is known and home-country effects are observed. That can provide researchers with important information on the predetermination of managers’ decisions or eventual caveats that exist due to difference in the corruption level perceptions and institutional background. The spectrum of research can be further broadened, as bribery is in most of the cases by-product, or an issue that exists along with other institutional problems as tax burden, administration burden, poor legal enforcement and informal behavior. More insights on the connection between these factors can help the researchers better frame the general problems of institutional environments of the developing economies.
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Appendix
Table 1 List of the 21 countries with according CPI indexes and ranks for inefficient government bureaucracy inefficiency Country CPI index CPI Ranking Level of Corruption Inefficient government bureaucracy (1-no/minor problem, 5-major problem) No of Firms Albania 3,4 4 High 4 29
Belarus 2 5 Very High - 22
Ukraine 2,5 5 Very High 1 48
Russia 2,1 5 Very High 3 55
Poland 4,6 3 Moderate 4 38
Romania 3,8 4 High 3 59
Serbia 3,4 4 High 3 42
Moldova 2,9 5 Very High 1 34
Bosnia 3,2 4 High 4 22
FYROM 3,6 4 High 2 40
Estonia 6,6 1 Very Low 2 43
Czech Republic 5,2 2 Low 5 40 Hungary 5,1 2 Low 3 53 Latvia 5 2 Low 4 51 Lithuania 4,6 3 Moderate 4 21 Slovakia 5 2 Low 5 30
Slovenia 6,7 1 Very Low 4 30
Bulgaria 3,6 4 High 4 28
Croatia 4,4 3 Moderate 4 14
Montenegro 3,4 4 High 5 6
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Table 2 Variable Definitions Variable name in
the regression model
Measure Description
Propensity to Bribe Binary How often do firms like you pay additional
payments/informal gifts?
CPI index Metric CPI per country for year 2008.
CPI Ordinal Codified CPI Index. 1 for low corruption
and 6 for very high
Country String Country of Operation
Bureaucratic government inefficiency
Ordinal To what extent is the bureaucracy
considered a problematic factor for running business in this country? 1 for no/minor problem till 5 for major problem
Informal Behavior Ordinal How much of an obstacle are the informal
sector competitors to your operations?
Firm Size Metric Number of permanent, full-time
employees of this firm at end of last fiscal year
LOG Firm Size Metric Natural logarithm of (Firm Size)
Annual Sales Metric In last fiscal year, what were this
establishment’s total annual sales?
Annual Sales in USD Metric Annual Sales divided by the exchange rate
of firm' currency of operation
LOG Annual Sales Metric Natural logarithm of Annual Sales in USD
INDVAR Metric Industry screener sector
INDVARD2 - INDVARD60
Metric Dummy variables for every industry sector
Year of Establishement
Metric In what year did this establishment begin
operations in this country?
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Table 3 List of industry dummy variables INDVAR dummies description
INDVAR2 Other manufacturing
INDVAR15 Food
INDVAR17 Textiles
INDVAR18 Garments
INDVAR24 Chemicals
INDVAR25 Plastics & rubber
INDVAR26 Non-metallic mineral products
INDVAR27 Basic metals
INDVAR28 Fabricate metal products
INDVAR29 Machinery and equipment
INDVAR31 Electronics (31 & 32)
INDVAR45 Construction section
INDVAR50 Other services
INDVAR51 Wholesale
INDVAR52 Retail
INDVAR55 Hotel and restaurants
INDVAR60 Transport section
Table 4 Skewness and Kurtosis Propensity
To Bribe
Bureaucratic Government Inefficiency
Table 5 Descriptive statistics and Pearson correlations
Variable Mean Std. Dev. Min Max
Propensity to Bribe CPI Index Inefficient Government Bureaucracy Informal Behavior LOG Years of Operation LOG Annual Sales LOG Firm Size Propensity to Bribe 2 1.301 1 6 1.000 CPI Index 3.131 1.334 1 5 0.342 1.000 Inefficient Government Bureaucracy 3.298 1.245 1 5 -0.187 0.482 1.000 Informal Behavior 1.176 1.293 0 4 0.199 0.119 -0.004 1.000 LOG Years of Operation 1.078 .349 0 2.214 0.013 -0.028 0.041 0.041 1.000 LOG Annual Sales 6.900 .829 4.481 9.537 -0.151 -0.325 0.261 -0.066 0.219 1.000 LOG Firm Size 2.046 .574 1 3.954 -0.042 -0.062 -0.071 -0.111 0.232 0.608 1.000 Firm Size 269.833 655.826 10 9000 Years of
Operation 4.34e+07 1.77e+08 30303 3.45e+09
Annual Sales
in USD 16.201 18.534 1 164
Ownership
Table 6 Regression Model
Dep.Var. Propensisty to Bribe
Logit Regression
Model 1 Model 2 Model 3 Model 4 Model 5
Inefficient Government Bureaucracy 0.167 -0.156* (0.121) (0.088) CPI Index 0.626*** 0.524*** (0.127) (0.092) Informal Behavior 0.341*** 0.391*** (0.086) (0.081) LOG Years of Operation 0.126 0.360 0.167 0.118 0.314 (0.300) (0.331) (0.302) (0.303) (0.327)
LOG Annual Sales -0.650*** -0.374* -0.544*** -0.287 -0.663***
(0.171) (0.204) (0.183) (0.185) (0.180)
LOG Firm Size 0.413* 0.283 0.289 0.195 0.425*
(0.243) (0.276) (0.256) (0.251) (0.255)
Industry variables YES YES YES YES YES
Constant YES YES YES YES YES
Number of obs 550 506 536 550 518
LR chi2 40.83(19) 99.45(22) 43.28 (20) 77.14(20) 69.85(20)
Prob > chi2 0.0025 0 0.0019 0 0
Pseudo R2 0.0626 0.1672 0.0683 0.1183 0.1144
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Table 7 Tests for multicolinearity
Variable VIF 1/VIF
LOG Annual Sales 2.42 0.413539
LOG Firm Size 2.17 0.46065
CPI Index 1.53 0.655608
Inefficient Government
Bureaucracy 1.48 0.675948
LOG Years of Operation 1.12 0.891257
Informal Behavior 1.1 0.911898 INDVARD52 5.8 0.172316 INDVARD2 4.64 0.215533 INDVARD51 3.91 0.25554 INDVARD8 3.65 0.273608 INDVARD28 3.41 0.292851 INDVARD15 3.04 0.329131 INDVARD60 2.79 0.358965 INDVARD29 2.74 0.364709 INDVARD45 2.67 0.374125 INDVARD55 1.93 0.518126 INDVARD17 1.66 0.601864 INDVARD25 1.65 0.606139 INDVARD31 1.65 0.606511 INDVARD50 1.61 0.621433 INDVARD27 1.2 0.830058 INDVARD26 2.27 0.441442 INDVARD24 2.21 0.451842
Table 8 Test for heteroscedasticity
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance
Variables: fitted values of PROPBRNEW LOG Firm Size
LOG Years of
