Introduction
Problem statement
Corruption occurs in both developed and developing countries with various degrees and has impacted on almost all parts of society (Lawal, 2007; Rohwer, 2009) Amundsen
Corruption is often likened to a disease or cancer that undermines the cultural, political, and economic foundations of society, severely impairing its essential functions (1999) The World Bank has also recognized corruption as one of the most significant barriers to both economic and social development (2009).
In Vietnam, this problem is seriously alarmed for the government‟s failure to reduce corruption over past years In particular, the Corruption Perceptions Index (CPI)
In 2014, Transparency International ranked Vietnam 119th out of 175 globally and 18th out of 28 in the Asia Pacific region, with its Corruption Perception Index (CPI) score remaining unchanged from 2012 to 2014, while neighboring countries saw improvements Additionally, the 2014 Provincial Competitiveness Index (PCI) report highlighted a troubling rise in informal costs, revealing that the percentage of companies paying bribes increased from 41% in 2013 to 66% in 2014 Notably, 10% of firms reported spending over 10% of their revenue on bribes, underscoring the persistent corruption challenges in Vietnam despite ongoing anti-corruption efforts.
Recent academic research on corruption over the past decade has focused on two main areas: the factors that contribute to corruption and its impact on economic growth Notable studies, such as those by Ades and Di Tella, have explored the determinants of corruption, shedding light on the underlying causes of this pervasive issue.
(1997, 1999), Svensson (2000), Persson, Tabellini, and Trebbi (2003) Related to the effect of corruption, a list of study can be seen Mauro (1995), Wei (1997) and Johnson et al
Most studies conducted prior to 1997 exhibit three common characteristics: they primarily focus on cross-country analyses, rely on perceptive data instead of quantitative data, and often avoid quantitative methods due to the high costs associated with data collection.
1 For a review and summary, refer to Bardhan (1997), Jain (2001), Reinikka, Svensson (2002) and Aidt
(2003) one Third, the interpretation of corruption was based on a function of macro-factors such as countries‟ policy or institutional environment
Kaufmann and Wei (1998) explored the relationship between informal costs, specifically the time managers spend with bureaucrats, and the cost of capital, utilizing firm-level data from three surveys across 48 to 73 countries Their analysis relied on perception indices related to corruption derived from various country characteristics Similarly, Hellman et al (2000) conducted a study involving a sample of 3,300 firms from 20 countries, sourced through collaboration between the World Bank and the Office of the Chief Economist.
1999 They explained the validation of corruption based on the function of the political- institutional environment, including protection of property rights and civil liberties
Existing literature has significantly advanced our understanding of the aggregate determinants of corruption; however, cross-country analyses and the reliance on perceptual data present notable drawbacks One major issue is the potential bias in perception data, with studies indicating that smaller firms often perceive their environments as more corrupt compared to larger firms (Batra, Kaufmann, & Stone, 2003; Bennedsen et al., 2009) Additionally, more productive companies tend to voice greater concerns about their business environments than their less productive counterparts (Malomo, 2013) Furthermore, macro-level determinants of corruption limit the ability to interpret variations in corruption within a country, as country-level research fails to account for differences in corruption levels across individual firms (Svensson, 2002).
To address issues related to corruption, Svensson (2003) utilized quantitative data from the 1998 Uganda enterprise survey, which aimed to represent private enterprises in the manufacturing and processing sectors Notably, the dataset revealed two key observations: not all firms indicated a necessity to pay informal costs, and there was considerable variation in bribe amounts among firms subjected to similar policies To elucidate this variance, the study introduced a straightforward bargaining model, allowing firms the option to either pay the requested bribe or exit the market when confronted with demands from public officials.
This study, inspired by Svensson (2003), examines corruption in Vietnam from 2005 to 2013, utilizing quantitative data on corruption alongside financial insights from Small Medium Enterprises (SMEs) surveys It aims to address two critical questions: who is required to pay bribes and the amounts involved The research employs the control rights hypothesis, which posits that the level of interaction with public officials influences the necessity of bribe payments, and the bargaining hypothesis, which suggests that a firm's bargaining power, determined by sunk costs and financial capacity, affects the bribe amounts paid.
Research objectives
This study aims to identify the factors that affect both the occurrence of bribery and the amount of bribe payments made by firms in Vietnam Specifically, it has two primary objectives: to analyze the determinants influencing bribery incidents and to examine the size of bribe payments in the Vietnamese business context.
(i) Specify the factors that affect the propensity to pay a bribe of formal and informal firms in Vietnam
(ii) Specify the factors that influence the variation in bribe amount across bribe-reporting firms in Vietnam
(iii) Give some policy implications in order to reduce corruption in Vietnam.
Research questions
This thesis aims to answer the following questions:
(i) Do the factors related to firm characteristics such as firm size, informal status, profit, firm‟s choice of technology, etc have influence the incidence of bribery?
(ii) Why do some firms have to pay more bribes than others?
(iii) What should be done to reduce corruption in Vietnam?
The scope of the study
This study analyzes data from SME surveys conducted in Vietnam between 2005 and 2013, encompassing approximately ten provinces and cities The research focuses on non-state manufacturing enterprises, categorizing them into formal firms with legal business registration and informal firms without such licenses While the surveys cover over twenty manufacturing industries, the thesis specifically examines the 14 largest sectors by the number of enterprises, including food and beverage products, fabricated metal products, wood and wood products, furniture manufacturing, leather tanning and dressing, textiles, wearing apparel, paper and paper products, publishing and printing, chemical products, rubber and plastic products, non-metallic mineral products, and various machinery and equipment, as well as water treatment.
The structure of the study
This paper is structured into six chapters, beginning with an introduction in Chapter 1 Chapter 2 provides a comprehensive overview of corruption, detailing its definition, various forms, and measurement techniques, along with empirical studies and theoretical models that analyze bribery incidence and levels Chapter 3 offers insights into the state of corruption in Vietnam Chapter 4 presents the data and descriptive statistical analyses, including the econometric models and their variables Chapter 5 discusses the results obtained from the econometric analysis Finally, Chapter 6 summarizes the main findings, addresses limitations, discusses policy implications, and offers suggestions for future research.
Literature review
Corruption
The term of “corruption” originates from the Latin word “corruption”, meaning
“moral decay, wicked behavior, putridity or rottenness” (Milic, 2001) However, it is difficult to give a globally accepted definition because corruption is a complex social, legal, economic and political phenomenon (Rohwer, 2009)
Corruption is defined in various ways, with the World Bank (1997) describing it as "the abuse of public power for private benefit." Jain (2001) expands on this by stating it involves using public office power for personal gain against established rules Transparency International (2009) similarly defines corruption as "misuse of entrusted power for private gain," applicable to both public and private sectors The Oxford Advanced Learner's Dictionary (2000) highlights two key elements of corruption: authority and morality, characterizing it as "dishonest or illegal behavior, especially of people in authority." Additionally, the Vietnamese Law on Anti-Corruption (2005) defines it as actions by individuals in positions of power that exploit their roles for personal interests.
In the realm of economics, corruption can be defined by the equation proposed by Klitgaard (1988): Corruption = Monopoly Power + Discretion – Accountability Similarly, the United Nations Development Program (2004) offers a different perspective, presenting corruption as: Corruption = (Monopoly Power + Discretion) – (Accountability + Integrity + Transparency) These equations highlight the critical factors contributing to corruption, emphasizing the roles of power, discretion, and the lack of accountability and transparency.
According to Awartani (2009), corruption involves two key parties: the demand-side and the supply-side Demand-side corruption occurs when corrupt public officials solicit bribes from individuals or companies in exchange for public services or favorable regulatory treatment Conversely, supply-side corruption involves individuals or firms offering bribes to public officials for their own advantage.
Corruption in the public sector is defined as the illegal exploitation of public trust or office for personal benefit, often characterized as the misuse of public positions for private gain (Fantaye, 2004).
Corruption manifests in various forms, as highlighted by Transparency International (TI, 2009) Common types include bribery, embezzlement, fraud, extortion, cronyism, nepotism, patronage, and graft A detailed overview of these prevalent forms of corruption is provided in Table 1.
Table 2 1: Definitions of corrupt activities
Bribery refers to the corrupt exchange of money or favors, often involving kickbacks, commercial arrangements, or pay-offs It encompasses the illicit payments made to employees in private sectors, public officials, and politicians to expedite processes or gain favorable outcomes within government bureaucracies.
Collusion refers to a covert agreement between individuals or groups, either in the public or private sector, aimed at engaging in deceptive practices or fraud for the purpose of illicit financial gain Those involved in such conspiracies are commonly known as "cartels."
Individuals and organizations, including governments, businesses, media outlets, and civil society groups, often face dilemmas when balancing their professional responsibilities with personal interests This conflict can lead to challenging decisions that impact ethical conduct and overall integrity in their roles.
Nepotism is a form of favoritism where individuals in positions of power leverage their authority to grant jobs or favors to family members or friends, regardless of their qualifications This practice can also extend to favoritism based on shared characteristics such as race, religion, or common origins, like being from the same village or nationality.
Fraud The act of intentionally deceiving someone in order to gain an unfair or illegal advantage (financial, political or otherwise)
Gifts and hospitality (e.g vacations, luxury dinner, etc.) that could affect or be perceived to affect the outcome of business transactions and are not reasonable and bona fide
Lobbying refers to efforts aimed at influencing the policies and decisions of governments or institutions to favor a particular cause or outcome While legal, lobbying can lead to distortions in the political process when certain companies, interest groups, or individuals exert disproportionate influence.
A revolving door politician is someone who transitions between public office and private sector roles, leveraging their government experience to benefit the companies they previously oversaw This practice raises concerns about conflicts of interest and regulatory integrity, as these individuals may prioritize corporate interests over public welfare.
The situation where a person is selling his/her influence over the decision process involving a third party (person or institution)
Patronage Patronage refers to favouring political supporters, for example with government employment
Corruption can be classified into two main categories: petty corruption and grand corruption According to Transparency International (TI), petty corruption refers to the everyday abuse of power by low- and mid-level public officials during interactions with citizens seeking access to public services, such as healthcare and education, often involving small monetary transactions In contrast, grand corruption involves high-level government officials whose actions distort state policies and operations, allowing them to profit at the expense of the public good.
Corruption is a complex issue encompassing social, political, and economic dimensions that is difficult to quantify directly Over the past decade, public awareness of corruption has increased, leading to the development of various measurement tools focused on perceptions Key indices for assessing corruption include the Corruption Perception Index (CPI), the Bribe Payers Index (BPI), and the Global Corruption Barometer, all created by Transparency International, as well as the Business Environment and Enterprise Performance Surveys (BEEPS) Additionally, the World Bank Group's Worldwide Governance Indicators (WGI) feature the Control of Corruption element as another aggregate measure.
The absence of a global consensus on the definition and nature of corruption makes it challenging to provide an accurate measurement of this complex issue (Rohwer, 2009) To address this, three types of corruption indicators can be distinguished: perception-based indicators, which reflect the opinions of citizens and experts; experience-based indicators, which are grounded in the actual experiences of individuals or businesses; and proxy indicators, which assess corruption indirectly by aggregating various opinions and signals or by evaluating related factors such as anti-corruption efforts and good governance (UNDP 2008, 8 ff.).
Table 2 2: Summary of features of measures of corruption
(composite) and some measures of corruption control
Statistical summary of expert assessments (e.g expatriate business executives, senior business leaders, assessment by the US, regional, and in-country experts )
Almost global depending on having sufficient sources Annual (though not all data sources annual)
Cross-sectional ranking of perception of corruption focusing on business environment
Perceived corruption (composite) and some business and public opinion survey evidence and corruption control assessment
Similar sources to CPI but with some survey evidence
Almost global depending on having sufficient sources
Biannual (though not all data sources annual or biannual)
Cross-sectional ranking of perception of corruption Sources may be somewhat wider than business environment focus of
Overall institutional the environment for controlling corruption
Absolute ranking (in principle allows assessment of change over time)
Perceived willingness of companies from different countries to pay bribes, and sectors in which bribery most prevalent
21 countries based on evidence from main emerging market economies Last carried out 2002
Ranking of perceived willingness to pay bribes in different countries The validity of perceptions and weighting uncertain
Bribe payments by households and public perceptions of corruption prevalence
Public opinion surveys and partial household surveys
69 countries in 2005, though not nationally representative in
Comparative prevalence and amounts of bribe payments though the quality of survey data
International many cases needs validation
Bribe payments by firms Surveys of businesses 62 countries, various years
Quantitative comparisons of bribe prevalence and cost
Bribe payments by households Household surveys 16 countries Quantitative comparisons of bribe prevalence and cost
Source: Oxford Policy Management (OPM), 2007
Empirical studies
2.2.1 Factors influencing the propensity to bribe
Previous studies at the firm level have identified key factors influencing bribery and the amount of bribes, highlighting the significance of interactions with public officials and various firm characteristics Additionally, Rand and Tarp (2012) propose that a firm's informality status serves as a valuable indicator for understanding the prevalence of bribery.
This article explores the incidence of corruption in business environments where firms may encounter bribery requests from officials Corrupt officials, wielding discretionary power, can engage in actions that either benefit or harm these firms The review focuses on empirical studies that identify key factors influencing the likelihood of bribery, categorized into three main groups: (i) the control rights of public officials over businesses, (ii) the bargaining power of firms, and (iii) the visibility of the firm's operations.
(i) Control right: includes several indicator variable capturing the degree of interaction level with public officials and the regulatory burden that the firm faces
Tanzi (1998) posits that bribery often stems from the weight of regulatory burdens imposed by governments, which, while essential for managing societal and economic activities, can create opportunities for corruption The monopoly power held by government officials over licenses and permits enables them to solicit bribes from individuals seeking necessary authorizations Furthermore, the implementation of these regulations necessitates frequent interactions between officials and citizens, leading to significant time investments for the latter This time commitment can often be mitigated through informal payments, highlighting a troubling intersection of bureaucracy and corruption.
According to Svensson (2003), as supported by Tanzi (1998), control rights significantly impact corruption levels, highlighting the relationship between firms and government interactions This study assesses the extent of engagement with public officials through two key variables, including regulations that represent the percentage of
2 See, Svensson (2002), Lee, S H., Oh, K K., & Eden, L A., (2010); Rand, J., & Tarp, F (2012) and Malomo,
According to F (2013), administrators allocate significant time each month to manage government regulations, incurring costs for accountants and lawyers who assist with compliance and taxation Additionally, Rand and Tarp (2012) highlight that the number of government inspectors is closely linked to the time management spends interacting with public officials, serving as a measure of regulatory engagement.
Svensson (2003) reveals a direct correlation between the likelihood of bribery and the level of interaction with public officials Businesses often incur informal costs when engaging with officials who hold influence over their operations, resulting in increased time spent navigating public regulations Additionally, companies face higher expenses for accountants and specialized service providers to manage compliance with regulations and taxes effectively.
The burden of regulation that firm faces (Tax)
Svensson (2003) and Malomo (2013) suggested that the burden of regulation caused the firm to facing a higher risk to pay a bribe To measure the burden of regulation, Svensson
Research by Svensson (2003) and Malomo (2013) highlights the relationship between taxation and corruption Svensson identifies a significant positive correlation between the type of taxes firms pay and corruption after addressing multicollinearity through principal components analysis Malomo further supports this by demonstrating that companies declaring higher percentages of sales for tax purposes are more inclined to engage in bribery.
According to Lecraw (1984) and Luo (2007), some firms focus on domestic sales while others derive their income from exports Domestic-oriented firms often engage more closely with local suppliers, customers, labor forces, and public officials, increasing their exposure to corrupt practices This heightened interaction with the internal environment exposes these firms to a broader spectrum of potential legal vulnerabilities related to regulatory compliance.
Kobrin (1987) indicates that exporting firms with advanced technical and managerial capabilities, which improve over time through learning and innovation in the global market, are less susceptible to government corruption This resilience enhances their profitability and strengthens their bargaining power against governmental entities.
In developing countries, particularly those facing balance of payments issues, export activities are crucial for generating foreign exchange and creating jobs As a result, export-oriented firms hold significant national importance, leading public officials to reduce their demands for bribes to avoid potential repercussions.
Lee, Oh, and Eden (2010) argue that competition among national governments to attract and support export-oriented firms enhances these firms' bargaining power Consequently, they hypothesize that export-oriented firms are less likely to incur informal costs and will have to pay smaller bribes to government officials.
The dependence of firm’s profitability on government
Pfeffer and Salancik (1978) identified that firm-level profitability varies based on dependence on government revenue, with companies heavily reliant on government contracts being more susceptible to the influence of public officials This reliance poses challenges, especially in environments where corruption affects contract awards (Dela Rama, 2012) To ensure their survival, these firms may adopt strategies aimed at swaying political decisions in their favor, necessitating the development of internal resources to swiftly gather information on governmental dynamics (Hillman & Hitt, 1999; Hillman, 2005).
Research by Hansen et al (2009) suggests that when state-owned enterprises become key clients of a firm, it positively influences the firm's performance This relationship may create an informal benefit-sharing arrangement between the firm and government officials Additionally, studies by Rand and Tarp (2012) and Malomo (2013) utilize a dummy variable to assess the impact of government contracts on bribery incidence They hypothesize that firms reliant on government contracts are more prone to corrupt practices involving public officials.
The dependence of firm’s input on government
According to Tanzi (1998), the state sector in many countries provides goods and services at prices lower than market rates, including essentials like foreign exchange, credit, public housing, electricity, and healthcare This access allows certain groups to benefit significantly from trading these below-market goods However, limited supply can lead to shortages, making solutions like ration coupons necessary Consequently, individuals seeking to access these goods may resort to informal payments to public officials responsible for allocating the scarce resources.
Svensson (2003) and Malomo (2013) investigate the correlation between the usage of public services—such as electricity, water, telephones, and waste disposal—and the likelihood of bribery Their findings suggest that individuals and businesses utilizing these public services are at an increased risk of engaging in bribery.
In line with Svensson (2003) and Malomo (2013), Rand and Tarp (2012) prove that when the government as firms‟ main supplier, they face a higher probability of paying a bribe
Conceptual framework
Research by Svensson (2002), Hansen et al (2009), Rand and Tarp (2012), and Malomo (2013) indicates that factors such as the level of interaction between companies and public officials, regulatory burdens, visibility proxies, refusal power, and financial capacity significantly impact both the incidence and amount of bribery.
Chapter summary
This chapter is structured into three key sections The first section offers a comprehensive overview of corruption, defining its various forms and discussing the challenges of measuring this complex social, political, and economic phenomenon Corruption measurement relies on three main types of indicators: perception-based, experience-based, and proxy indicators The second section reviews academic studies that investigate the factors influencing bribery and the amounts involved, highlighting the limited literature on firm-level corruption within specific country contexts, with most studies focusing on control rights.
- Firm size (The log of total employment)
Studies show a positive correlation between the level of interaction with government officials and regulatory burdens, leading to an increased likelihood of bribery Additionally, factors such as firm size and informal status serve as indicators of bribery incidence Previous research indicates that variations in bribe amounts can be attributed to a firm's financial capacity and their ability to refuse payment The article concludes by presenting a foundational framework for estimating both the incidence and magnitude of bribery.
Corruption in Vietnam
Vietnam's ongoing battle against corruption, initiated with the Anticorruption Law of 2005, has faced significant challenges over the past decade, as corruption increasingly undermines the nation's sustainable development efforts.
A 2012 World Bank sociological survey revealed that corruption ranks among the top three critical issues concerning the Vietnamese population Conducted across ten provinces and cities, the survey gathered insights from citizens, businesses, and officials regarding their perceptions of corruption Notably, officials identified corruption as the most pressing issue, while businesses ranked it as the second concern, following the cost of living Citizens placed corruption third, after the cost of living and traffic accidents Figure 1 illustrates the serious challenges Vietnam faces, highlighting the significant impact of corruption on society.
Figure 3 1: The most serious Economic & Social Issues for Vietnam 4
A recent survey highlights the widespread nature of corruption in Vietnam, revealing its various forms and varying degrees across multiple sectors Notably, public officials, enterprises, and citizens all show a strong consensus on the prevalence of corruption, with over 75% of respondents identifying the four most corrupt sectors.
Vietnam comprise traffic police, land administration, customs, and construction Meanwhile, post and telecommunication, media, treasury, and the ward/commune police were recorded as the four least corrupt sectors (Figure 3.2)
Figure 3 2: Perceptions of the prevalence of corruption across sectors 5
Corruption in Vietnam has intensified, as evidenced by the low ranking in the Corruption Perceptions Index 2014 (CPI 2014) The country received a score of 31 on a scale from 0 to 100, where 0 indicates high corruption and 100 signifies a very clean status.
Out of 175 countries globally, 119 are perceived to have corruption issues, with 18 of 28 countries in the Asia-Pacific region similarly affected Despite ongoing efforts to combat corruption, public perceptions have remained unchanged for three consecutive years (2012-2014), indicating a significant lack of trust among citizens in the effectiveness of public administration.
Table 3 1: Vietnam‟s annual CPI result
5 Perceptions of the prevalence of corruption across sectors according to public officials, enterprises, and citizens (% saying prevalent, among those with opinions)
The PCI 2014 Survey reveals a concerning decline in informal cost criteria scores, highlighting a growing pessimism among surveyed firms compared to PCI 2006 Specifically, in 2008, 66% of respondents reported regularly paying informal costs to maintain smooth business operations However, after years of decline, this trend reversed in 2014, with a significant number of firms exceeding the threshold for informal payments Additionally, the report indicates that 10% of businesses that pay bribes allocate more than 10% of their revenue to these illicit payments.
A growing number of companies report experiencing harassment from public officials during administrative procedures, with incidents rising to 66% in 2014, compared to 41% in 2013, as indicated by the PCI-FDI Survey.
Figure 3 3: Key Indicators of Informal Charges (2006 to 2014)
Source: The Provincial Competitiveness Index (PCI), 2014
Figure 3.4 highlights the primary reasons for informal payments, revealing that 20% of bribes are directed towards tax collectors, while 30% facilitate easier access to public services When comparing these findings to previous years (2009 and 2011), it is evident that tax services have improved, whereas access to public services has deteriorated.
Government uses compliance with local regulations to extract rentsOver 10% of revenue in informal payments
Figure 3 4: The purpose of bribe payment
According to Transparency International's 2013 report, the average bribe amounts in Vietnam vary significantly across different sectors, with the judiciary facing the highest average bribe of 4,600,000 VND (approximately 230 USD), while registry and permit services have the lowest at 166,666.7 VND (around 8 USD) Additionally, informal payments for land services average 1,437,500 VND (about 70 USD), representing 4% to 124% of the average monthly salary of Vietnamese workers in 2014 Even essential sectors like medical and educational services see bribe proportions nearing 10%, highlighting a critical challenge for bribery control in Vietnam.
Table 3 2: Average cost of bribes paid, by sector
Sector Average (VND) Average (USD equivalent)
Research identifies key factors contributing to corruption in Vietnam, as highlighted by CIEM (2005) These factors include the abuse of public power, arbitrary decision-making in policies and administration, and significant weaknesses in transparency and accountability.
To get connected to public services
To get licenses and permits
To deal with taxes and tax collectors
To gain government contracts public procurement
The report highlights that the disparities in corruption levels among countries can be attributed to the effectiveness of their judicial systems, adherence to the rule of law, and the competence of public governance personnel (Nguyen & Van Dijk, 2012) Additionally, it points out weaknesses in the implementation and monitoring by state officials and government agencies from 2009 to 2013.
Despite government initiatives to combat corruption, public perception in Vietnam remains largely negative According to a 2013 Transparency International survey, only 24% of respondents believe that the government's anti-corruption efforts are effective, while 38% view these efforts as inefficient or very inefficient Additionally, 38% of participants expressed uncertainty regarding the effectiveness of anti-corruption programs The report highlights a growing public mistrust, with 60% of respondents expressing negative views in 2013, a significant increase from 35% in 2010.
Figure 3 5: Awareness about the government's anti-corruption efforts
A 2013 report by Transparency International highlights a growing public reluctance in Vietnam to report corruption, with 62% of respondents unwilling to denounce corrupt activities, and this figure rises to 66% among urban residents This marks a significant shift from 2010, when 65% of respondents expressed a willingness to report such incidents.
Comparing such results among Southwest Asia shows that Vietnamese citizens appear to be the least voluntary to reveal cases of corruption The TI (2013) points out that the
6% very efficient efficient normal ineffcient very inefficient less than those of Malaysian responses Vietnamese figure is even lower than the average number of 63%
Figure 3 6: Willingness to report an incident of corruption (Southeast Asia)
Corruption in Vietnam presents a significant challenge, particularly within sectors such as traffic police, land administration, customs, and construction The misuse of power by public officials and arbitrary policy decisions are primary contributors to this issue Despite the Vietnamese government's attempts to combat corruption in recent years, these efforts have proven ineffective, leading to public skepticism regarding the anti-corruption program.
Data and Econometric Model
Data
This study analyzes data from SME Surveys conducted in Vietnam between 2005 and 2013, involving contributions from several organizations, including the Central Institute for Economic Management (CIEM), the Ministry of Planning and Investment (MPI), and the Institute of Labour Science and Social Affairs (ILSSA) The surveys encompassed approximately 2,500 small and medium enterprises across ten cities and provinces, focusing on both formal and informal private companies of varying sizes To address the research questions, the study examines factors such as firms' financial performance, interactions with public officials, and instances of bribe payments.
Household Private Partnership/ co-operative Limited Joint stock
Table 4.1 outlines the panel data structure, which mandates that all firms in the cleaned sample must be present for a minimum of three consecutive years Consequently, the final sample comprises approximately 70% household businesses, 14% limited liability companies, and 16% other forms of ownership.
All the currency value in the study is measured in 1,000 VND The measurement of all variables is primarily in line with Svensson (2002), Rand and Tarp (2012) and Malomo
(2013) Table 4.2 will define clearly about variables used in this paper
Variable Variable name Definition bribe Bribe A dummy variable indicating whether firm report a positive or zero in informal cost ln_ebribe Bribe amount per employee (log)
Natural log of reported informal cost per employee
In analyzing firm performance, several key metrics are considered: the natural logarithm of total employment (ln_sunkc) reflects firm size, while the natural log of sunk costs indicates investment stability The KL ratio, represented as the natural log of capital (K) and labor (L), assesses the market value of machinery, vehicles, and equipment relative to total employment Profitability is measured through ln_eprofit, which calculates profit per employee by taking the natural log of total sales minus operating costs and interest payments Additionally, ln_eexp evaluates export value per employee, providing insight into a company's export capabilities and overall financial health.
Natural log of export revenue per employee that is sold through direct exports ln_eimp Total value of imports per employee (log)
Natural log of total value of imports per employee gov_ass Received government assistance
A dummy variable indicates whether a firm receives financial or technical assistance from the government, with a value of 1 for assistance and 0 for none The tax percentage reflects the portion of the firm's sales allocated for tax purposes Additionally, the regulation metric measures the percentage of a manager's time dedicated to handling government regulations each month Lastly, the informal status signifies whether the firm is registered or operates informally.
A dummy variable taking the value 1 if the firm has an official business registration license and zero otherwise ln_egovc Revenue from gov/employee (log)
Natural log of revenue per employee that receive from the selling of firm‟s output to government ln_egovs Buying input from gov/employee (log)
Natural log of the value of input per employee that firm buy from government
Descriptive statistical analyses
Tables 4.3- 4.7 provide a brief look over the key variables and initial relationships among them
Table 4 3: The descriptive statistics of the size of bribe payment by location
Province/ City Mean Std.Dev Min Max Obs
Table 4.3 presents descriptive statistics on bribe amounts paid by firms, categorized by region across ten provinces and cities Notably, Ho Chi Minh City exhibits the highest levels of corruption, marked by the largest average bribe payments, the greatest total bribe amounts, and the highest number of documented bribery cases.
On average, companies in Ho Chi Minh City pay officials approximately 20.5 million VND, while the lowest payment recorded in Khanh Hoa is about 3.7 million VND Similarly, firms in Long An, Quang Nam, Phu Tho, and Nghe An exhibit comparable payment figures to those in Khanh Hoa.
In recent reports, it has been revealed that approximately 4 million dongs were paid in bribes, with unofficial payments in Lam Dong, Ha Tay, and Ha Noi ranging between 6 million and 8 million dongs.
In Vietnam, the highest recorded bribe amount is 5.1 trillion dong in Ho Chi Minh City, significantly surpassing the mere 23 million dongs found in Long An.
Table 4 4: The descriptive statistics of the size of bribe payment by the legal ownership form and sector
Obs Mean Std.Dev Min Max
Household establishment/ business 1,103 2,448.952 4,458.827 0 41,000 Private (Sole proprietorship) 219 7,854.384 22,592.720 0 300,000 Partnership/collective/co-operative 81 9,709.852 16,836.990 0 120,000 Limited liability company 442 13,127.180 34,504.960 98 500,000
Paper and paper products 75 12,493.950 30,045.870 99 240,000 Publishing, printing etc 70 11,483.270 26,993.450 99 150,000
Rubber and plastic products 131 10,623.230 29,596.330 99 296,000 Non-metallic mineral products 97 7,629.948 13,529.410 0 100,000
Table 4.4 reveals a significant disparity in bribe payments across different types of legal ownership, with joint stock companies averaging over 72 million dongs—nearly 30 times the amount paid by household companies The high standard deviation exceeding 500 million dongs indicates a wide variation in bribe amounts, with a maximum informal payment reported at approximately 5.1 billion dongs for joint stock companies, in stark contrast to the more modest 120 million dongs for partnership companies.
Table 4.4 presents descriptive statistics on bribe amounts across various manufacturing industries, revealing significant disparities in average informal payments The food products and beverages sector exhibits the highest average bribe amounts, while the water treatment sector reports the lowest These variations may be attributed to factors associated with firm characteristics.
Table 4 5: The purpose of bribe payment
Purpose of bribe payment Obs Percent of firm
To get connected to public services 661 28.345
To get licenses and permits 115 4.931
To deal with tax and tax collectors 633 27.144
Table 4.5 reveals that the primary reasons for bribery payments are linked to public services (28.3%) and tax services (27.1%), highlighting these as the most common areas of corruption In contrast, only about 12% of surveyed firms indicated that their bribery attempts were aimed at securing government contracts.
Table 4.6: The summary statistics of key variables
Revenue from government/employee (log) 7,857 0.000 1.402 8.755 0.000 100.000 The value of input from government/ employee (log) 7,853 0.000 3.011 10.885 0.000 100.000
Export value per employee (log) 7,852 0.000 1.876 12.415 0.000 100.000 Import value per employee (log) 7,866 0.000 0.787 7.136 0.000 99.000
Table 4.6 presents summary statistics of the key variables which explain the bribe incidence and the size of bribe payment
According to Table 4.6, micro and small firms represent approximately 74% and 20% of the total, respectively, while medium and large firms are categorized based on the government decree No 90/2001/CP-ND, which defines micro enterprises as having 1 to 10 employees, small enterprises as having 11 to 50 employees, and medium enterprises as having 51 to 300 employees Additionally, the data reveals that nearly one-third of all firms lack business licenses at the district or provincial level, and over 19% of these firms have received government assistance on average.
Statistics of a set of variables that reflect a firm‟s ability to pay a bribe (profit per employee) and its refusal power (KL ratio) are also included in Table 4.6
The interaction between public officials and companies is quantified by the percentage of management's monthly time dedicated to government regulations On average, managers allocate approximately 8% of their total working hours to navigate these regulations Additionally, firms typically spend around 1.5% of their sales on taxes, with some companies dedicating nearly 32% of their sales for tax obligations.
Table 4.7 presents the pairwise correlation coefficients, with the corresponding p-values shown in parentheses The correlation analysis includes variables such as bribe, ebribe_ln, eexp_ln, eimp_ln, regulations, estate_ln, instate_ln, informalr, employment_ln, gov_ass, sunkcost_ln, eprofit_ln, and tax_percentage Notably, the bribe variable has a correlation coefficient of 1.0000, indicating a perfect correlation with itself.
Table 4.7 presents the pairwise correlation among variables related to bribery propensity It reveals a statistically significant correlation between firm size, measured by the logarithm of total employment, and the informality of firms with bribe incidence Specifically, larger companies exhibit a positive correlation coefficient of approximately 0.36, indicating they are more likely to engage in bribery Conversely, firms operating informally show a negative correlation of -0.32, suggesting that unregistered companies may attempt to evade government scrutiny and avoid bribery.
There is a significant correlation between firm size and profit in relation to bribe payments, with correlation coefficients of approximately 28% and 26% These statistics indicate that larger bribe payments may be positively associated with a firm's current capacity to pay bribes, while a negative relationship exists between the amount of bribe and the firm's size.
The analysis of pairwise correlation coefficients indicates that the independent variables exhibit weak relationships with one another Consequently, multicollinearity is not a concern when conducting the regression model.
Econometric model
Sample selection bias is a significant econometric issue when estimating behavioral relationships, particularly in the context of bribe incidence and amounts This bias arises when the dependent variable is only observed in a nonrandomly selected subset of samples, as noted by Heckman (1979) In surveys of small and medium-sized enterprises (SMEs), this problem is exacerbated by the use of non-random samples and the absence of complete information on bribe payments from several surveyed companies Consequently, applying ordinary least squares (OLS) regression to the entire sample can lead to biased coefficient estimates A well-established method to address selection bias is the Heckman Two-step procedure, which provides a systematic approach to correct for these biases in the analysis.
Heckman model comprises two equations, including selection equation and outcome equation In this study, the bribe equation (outcome equation) is as follows: bi = Xi + ԑi
Selection equation (participation equation) is given by: where: b i is the bribe amount
In the analysis of bribery among firms, the observed variables Xi represent firm characteristics that account for variations in bribe amounts among those that report such payments These variables are only applicable to firms incurring informal costs Additionally, ԑi encompasses all unobserved factors influencing the size of a bribe, while bi is relevant solely for firms that actually pay bribes The parameter d is set to 1 for firms required to pay a bribe and 0 for those that do not, with nd representing unknown parameter vectors.
Z i : a set of observed variables related to firm characteristics thought to determine whether or not a firm has to pay a bribe
Some assumptions are required when applying Heckman model
- Error terms nd u follow jointly the normal distribution with mean 0, the indicated variances as σ 2 ε, σ 2 u The error terms are correlated where ρ εu is the correlation coefficient (ε,u) ~ N(0,0,σ 2 ε, σ 2 u ,ρ εu ) (1)
- Both error terms are independent of both sets of explanatory variables
- The variance of u is equal 1 refers that the standard normalization for the probit selection equation, which is identified only up to scale
The initial phase of the two-step approach involves estimating the selection model by implementing a probit model (d on Z) across the entire sample Using the estimated coefficients (β) from this probit model, the inverse Mills ratio is subsequently computed for each observation.
Recall the selection and outcome equation:
With above assumptions the model (4) can be rewritten to:
The inverse Mill's ratio is derived from the bivariate normal distribution, where it is defined using the probability density function and cumulative distribution function of the standard normal distribution, N(0,1) This ratio also incorporates the covariance between the variables involved.
In the second step, the outcome equation is estimated using ordinary least squares (OLS) regression, incorporating both the original vector Xi and the calculated inverse Mills ratio as explanatory variables.
It is noted that in order to facilitate the identification purpose, the outcome equation should contain at least one variable that does not appear in the selection equation (Heckman, 1979)
In this paper, the Heckman two-step model is constructed as follows:
(i) Selection model (Propensity to bribe)
Probit (d = 1|Zi) =α α ln KL tio α ln employment α ln ( ) α ln (
) α egul tions α ln ( ) α ln ( ) α info m l α gov_ ssist nce α t x_pe c u
(ii) Regression model (Size of bribe)
E ln eb ibe X ) = Z σ = ln KL tio ln ( ) ln (
) egul tions ln ( ) ln ( ) info m l gov_ ssist nce t x_pe c u σ Z ξ
The selection equation is estimated by using the full sample whereas the outcome equation uses the sample which consists of bribing firms
Table 4 8: The Expected Variables in Heckman two-step
The incidence of bribe The size of bribe
Export value per employee (log) - -
Import value per employee (log) + +
Revenue per employee from selling firm‟s output to government (log)
The value of input per employee that buying from government (log)
Empirical results
Factors influencing the propensity to bribe
This section discusses the findings from the first stage of the analysis, which includes two key columns examining the factors influencing bribery payments The first column presents results derived from the Heckman two-step model, while the second column showcases outcomes from the Heckman maximum likelihood estimation, adjusted for heteroskedasticity at the firm level.
The findings in columns (1) and (2) show a strong consistency, highlighting that the "exposure/visibility" variable, represented by firm size and informal/not registered status, is statistically significant at the 1% level with expected signs Specifically, larger firms are positively associated with an increased likelihood of paying bribes, while companies operating informally are negatively associated with bribe incidence The results indicate that a 1% increase in firm size correlates with an approximate 0.38% rise in the probability of bribe payment, all else being equal Conversely, firms without a business registration license experience a 0.5% reduction in the risk of engaging in bribery.
Rand and Tarp (2012) found that Vietnamese firms with an informal status are less likely to engage with corrupt public officials, resulting in a reduced risk of bribery This contrasts with the findings of Tenex et al (2003), which suggest a positive correlation between formality and bribe rates Additionally, Rand and Tarp (2012) highlight that larger firms are more likely to incur informal costs.
The analysis indicates that both tax percentage and regulatory time spent by senior managers significantly influence bribery likelihood, with coefficients showing a positive correlation at the 1% level Specifically, an increase of 1% in sales allocated for tax purposes raises the probability of bribery by nearly 3 percentage points, while additional time spent on public regulations correlates with a 0.3 percentage point increase in bribery likelihood These findings underscore the notion that greater interaction with public officials heightens corruption risk, aligning with previous studies by Rand and Tarp (2012) and Malomo (2013).
Additional variables supporting control right hypothesis are the selling a part of firm‟s output to the government, buying input from government and the engagement in trade
Table 5.1 reveals that firms heavily reliant on government for sales or inputs face an increased risk of bribery Specifically, a 1% increase in sales per employee from government contracts correlates with a roughly 2 percentage point rise in the likelihood of bribery This finding aligns with the research of Hansen et al (2009), Rand and Tarp (2012), and Malomo (2013) Additionally, the table indicates that when the state sector serves as the primary supplier of inputs, firms are also more likely to incur informal costs, a conclusion supported by Tanzi.
Engagement in international trade reveals contrasting outcomes, particularly in the relationship between export value per employee and the incidence of bribery The findings indicate that exporters are less inclined to incur informal costs compared to firms operating solely within domestic markets This observation aligns with previous research conducted by Lee, Oh, and Eden.
Research by Galang, Lavado, and Domingo (2013) indicates that companies focused on the domestic market engage more frequently with local government officials compared to exporting firms In contrast, exporting companies, which possess advanced technical and managerial skills, tend to have greater bargaining power with the government, potentially reducing their likelihood of engaging in bribery (Kobrin, 1987) Additionally, the study found no correlation between import value per employee and the occurrence of corruption across various models.
The bargaining framework highlights the relationship between a firm's ability to pay bribes and its financial metrics, specifically profit per employee and the capital-to-labor (K/L) ratio Statistical analysis in Table 1 confirms that higher profits correlate with an increased likelihood of incurring informal costs, while firms with a lower K/L ratio exhibit greater refusal power, reducing their propensity to pay bribes These findings align with previous research by Svensson (2003) and Rand and Tarp (2012) Notably, each increase in profit per employee raises the probability of paying informal costs by approximately 0.14%, whereas a decrease in sunk costs correlates with a 0.01% increase in bribery likelihood.
The t-test for industry dummies suggests that except for chemical products, there seems likely to appear a variation in the propensity to bribe among remaining industries and water treatment industry.
Factors influencing the size of bribe payment
This section analyzes the results of the second stage, as presented in the third and fourth columns, addressing the question of the required bribe amount Most variables from the first stage are retained in the second stage, with the exception of one variable, to streamline identification in the Heckman two-step model (Heckman, 1979) The dependent variable focuses on the logarithm of the bribe amount per employee.
The analysis reveals a strong correlation between control variables and the size of bribes, with significant findings at the 1% level Key factors such as tax percentage, revenue from government employees, input value from government employees, and received government assistance all exhibit positive relationships with reported informal costs Specifically, a 1% increase in sales allocated for tax purposes leads to a 0.06% rise in bribes per employee, while a 1% increase in sales to the government results in a 0.02% increase in bribes Additionally, a 1% increase in government-provided input value correlates with a 5 percentage point rise in bribes per employee, and government assistance is associated with an average increase of 0.2% in bribes paid per employee These findings underscore the significance of government interaction and dependency in firms' bribery decisions.
Table 5.1 illustrates a strong correlation between a firm's ability to pay, measured by profit per employee, and the size of the bribe This indicates that as the profit per employee increases, so does the amount of the bribe offered.
On average, the bribe paid per employee increases by 0.3%, aligning with the conclusions of Svensson (2003) and Malomo (2013) Additionally, the data reveals that the refusal power, measured by capital stock per employee, does not significantly explain the variation in bribe amounts.
The analysis indicates that informal status has a significant negative impact on visibility, with a coefficient that is statistically significant at the 1% level in both models Specifically, the marginal effect shows that firms operating informally experience a reduction of approximately 0.6% in the amount of bribe paid per employee.
The t-test for industry dummies reveals significant variations in bribery amounts across most industries, with the exception of the paper, publishing, printing, chemical products, rubber, and plastic products sectors, as well as the water treatment industry.
Robustness
An important consideration is how the results might shift if there is a feedback loop from bribery to profit Specifically, we must explore whether a reverse causality exists between bribery and profit The rent-seeking and regulatory capture framework suggests a positive correlation between profits and corruption, indicating that increased profits may lead to higher levels of bribery.
In a competitive environment, politicians and bureaucrats engage in rent-seeking by offering government favors, including subsidies and tax relief, which significantly influence corporate profitability This dynamic leads to widespread rent-seeking behavior among businesses Additionally, research by Bliss and Di Tella indicates a positive correlation between bribery and profits, highlighting the complexities of corruption in economic systems.
In 2003, evidence indicated that corruption does not lead to increased profits, as large firms with political influence tend to dominate the regulatory process, overshadowing smaller firms Given that most firms in the sample were small, this raises challenges in demonstrating a direct link between corruption and profitability.
Besides, Svensson (2003) suggests that it is questionable when treating profit as exogenous As a robustness test, the author uses two sets of instrument variable for profits
This study employs lagged values of profit per employee as an instrumental variable, similar to Svensson's approach This instrument meets two essential criteria: it demonstrates a strong correlation with current profit per employee (correlation coefficient = 0.3) and, being a past value, it is not influenced by present errors The main findings of the Heckman two-step regression utilizing this instrumental variable technique are summarized in Table 2 below.
Table 5.2: Regression Results of Heckman Two – Steps and Heckman Maximum
Likelihood with Clustered, without instrument variables, using instrument variable
The incidence of bribery The size of bribery
Heckman Maximum Likelihood with Clustered
Heckman Maximum Likelihood with Clustered
(3.360) (3.400) (4.770) (4.170) Revenue from gov/employee (log) 0.023 *** 0.025 *** 0.035 *** 0.032 ***
(4.350) (4.610) (3.930) (3.090) Input value from gov/employee (log) 0.001 -0.002 0.025 *** 0.023 **
***, **, and * present statistical significance level at 1%, 5%, and 10%, respectively t- values are reported in parentheses
The results presented in Table 5.2 closely align with those in Table 5.1, particularly regarding the factors influencing the propensity to pay bribes Notably, seven out of nine variables from Table 5.1 remain statistically significant at the 1% level in Table 5.2, consistently showing the same sign across all specifications These variables include firm size, profit per employee (log), tax percentage, revenue from government per employee, export value per employee, regulation in real-time, and informal/not registered status The two remaining variables, KL ratio (log) and input value from government per employee (log), do not demonstrate statistical significance when employing the instrument technique Additionally, most coefficients for the statistically significant variables are larger in Table 5.2 compared to those in Table 5.1, which did not utilize the instrument technique.
The analysis of bribe amounts reveals that several statistically significant variables, including profit per employee, tax percentage, revenue from government per employee, input value from government per employee, receipt of government assistance, and informal or unregistered status, serve as effective indicators for understanding the variations in bribe amounts.
Establishing a causal link between profit and bribery is inherently challenging; however, this section presents evidence suggesting that the observed outcomes are not influenced by a reverse relationship from bribery to profit.