Determinants underlying incidence and amount of bribery an evidence from manufacturing firms in vietnam

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 that undermines the cultural, political, and economic foundations of society, leading to the dysfunction of essential systems According to the World Bank, it stands as one of the most significant barriers to both economic and social development.

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 119 out of 175 globally and 18 out of 28 in the Asia Pacific region, with its Corruption Perceptions Index (CPI) score remaining unchanged from 2012 to 2014, unlike neighboring countries that saw improvements Additionally, the 2014 Provincial Competitiveness Index (PCI) report highlighted a significant increase in informal costs for businesses, with the percentage of companies paying bribes rising from 41% in 2013 to 66% in 2014 Notably, 10% of firms reported that over 10% of their revenue was spent on bribes, underscoring the persistent corruption challenges in Vietnam despite ongoing anti-corruption efforts.

In the past decade, extensive academic research on corruption has been categorized into two main areas: the factors that drive corruption and its impact on economic growth Notable studies, such as those conducted by Ades and Di Tella, have focused on identifying the determinants of corruption.

(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 predominantly rely on cross-country analyses, and they utilize perceptive data instead of quantitative data, primarily due to the higher costs associated with collecting the latter.

1 For a review and summary, refer to Bardhan (1997), Jain (2001), Reinikka, Svensson (2002) and Aidt (2003)

12 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 surveys across 48 to 73 countries Their research relied on perception indices related to corruption derived from country characteristics Similarly, Hellman et al (2000) analyzed a sample of 3,300 firms across 20 countries, using data collected by 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 offers valuable insights into the aggregate factors influencing corruption; however, cross-country analyses and reliance on perceptual data present certain limitations One major issue is the potential bias in perception data, as studies indicate that smaller firms often view their environments as more corrupt compared to larger firms (Batra, Kaufmann, & Stone, 2003; Bennedsen et al., 2009) Additionally, more productive companies tend to express greater dissatisfaction with their business environments than their less productive counterparts (Malomo, 2013) Furthermore, macro-level determinants of corruption restrict the understanding of variations in corruption within a country, as country-level research fails to account for differences in corruption levels among individual firms (Svensson, 2002).

To address issues related to corruption in Uganda's private enterprises, Svensson (2003) analyzed quantitative data from the 1998 Uganda enterprise survey, which focused on manufacturing and processing sectors The dataset revealed two notable characteristics: 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 account for this discrepancy, the study introduced a straightforward bargaining model, illustrating that firms can either choose to pay the bribe or exit the market when confronted with a public official's bribery request.

This study examines corruption in Vietnam from 2005 to 2013, building on Svensson's (2003) research Utilizing quantitative data on corruption and financial insights from Small Medium Enterprises (SMEs), the paper seeks to address two key questions: who is required to pay bribes and the amounts involved To explore these issues, the study employs the control rights and bargaining hypotheses The control rights hypothesis posits that the level of interaction with public officials influences whether a firm must pay a bribe, while the bargaining hypothesis suggests that a firm's bargaining power, determined by its sunk costs and financial capacity, affects the amount paid in bribes.

Research objectives

This study aims to identify the factors that affect the occurrence of bribery and the amount of bribe payments made by firms in Vietnam, focusing on two primary objectives.

(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?

1.4 4 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 sample includes non-state manufacturing enterprises, categorized as formal firms with legal business registration licenses and informal firms without such licenses, excluding foreign-owned enterprises While the surveys cover over twenty manufacturing industries, the focus of this thesis is on the 14 largest sectors by the number of enterprises, which include food products and beverages, 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, other machinery and equipment, and water treatment.

1.5 5 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 definitions, forms, and measurement, along with empirical studies and theoretical models related to bribery Chapter 3 focuses specifically on the issue of corruption in Vietnam Chapter 4 outlines the data used and presents descriptive statistical analyses, along with the econometric models and their variables The econometric results are discussed in Chapter 5 Finally, Chapter 6 summarizes the main findings, addresses limitations, and offers policy implications and suggestions for future research.

The structure of the study

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.” Similarly, Jain (2001) characterizes it as the misuse of public office for personal gain in violation of established rules Transparency International (2009) expands this definition to include the “misuse of entrusted power for private gain,” applicable to both public and private sectors The Oxford Advanced Learner's Dictionary (2000) highlights the interplay between authority and morality, defining corruption as “dishonest or illegal behavior” by those in power, which leads to a shift from moral to immoral standards Additionally, the Vietnamese Law on Anti-Corruption (2005) defines it as actions by individuals in positions of power that abuse their authority for personal interests.

In the field of economics, corruption can be understood through various equations Klitgaard (1988) defines corruption as the sum of monopoly power and discretion, minus accountability Similarly, the United Nations Development Program (2004) presents another equation, framing corruption as the combination of monopoly power and discretion, reduced by accountability, integrity, and transparency.

According to Awartani (2009), corruption involves two main parties: the demand-side and the supply-side Demand-side corruption occurs when public officials solicit bribes from individuals or companies in exchange for public services.

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) characterizing it as "the abuse of public power for private benefit." Jain (2001) describes it as the misuse of public office for personal gain that violates established rules Transparency International (2009) expands this definition to encompass both public and private sector corruption, defining it as "misuse of entrusted power for private gain." The Oxford Advanced Learner's Dictionary (2000) highlights the connection between authority and morality, defining corruption as "dishonest or illegal behavior" by those in power and the alteration of moral standards Additionally, the Vietnamese Law on Anti-Corruption (2005) defines it as actions taken by individuals in positions of power who exploit their authority for personal interests.

In the field of economics, corruption can be understood through various equations Klitgaard (1988) defines corruption as the sum of monopoly power and discretion, minus accountability Similarly, the United Nations Development Program (2004) presents another equation, framing corruption as the combination of monopoly power and discretion, reduced by the factors of accountability, integrity, and transparency.

According to Awartani (2009), corruption occurs through two main parties: the demand side and the supply side Demand-side corruption involves public officials soliciting bribes from individuals or companies to facilitate public services or regulations Conversely, supply-side corruption occurs when individuals or firms offer bribes to corrupt officials for their own advantage.

Corruption in the public sector is commonly defined as the illegal abuse of public trust or office for personal gain This misuse of public office undermines integrity and accountability, leading to significant societal consequences.

Corruption manifests in numerous forms, as highlighted by Transparency International (TI, 2009) Common types include bribery, embezzlement, fraud, extortion, cronyism, nepotism, patronage, and graft These definitions provide a comprehensive understanding of the various ways corruption can occur.

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 This unethical practice occurs in both private enterprises and public sectors, where payments are made to employees, officials, or politicians to expedite processes or gain favorable treatment within government bureaucracies.

Collusion refers to a covert agreement between individuals or organizations, whether in the public or private sector, to engage in deceptive practices or fraud for the purpose of obtaining illegal financial benefits Those involved in such schemes are commonly known as "cartels."

Individuals and organizations, including governments, businesses, media outlets, and civil society groups, often face dilemmas where they must balance their professional responsibilities with personal interests.

Nepotism is a form of favoritism where individuals in positions of power use their authority to grant jobs or favors to family members or friends, regardless of their qualifications or merit This practice can also extend to other factors, such as race, religion, or shared origins, including 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 legally permissible, lobbying can lead to distortions in decision-making when certain companies, interest groups, associations, organizations, or individuals exert disproportionate influence.

A person who transitions between public office and private sector roles often leverages their government experience to benefit the companies they previously regulated This practice raises concerns about conflicts of interest and the ethical implications of using public service for personal or corporate gain.

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, as highlighted by Rohwer (2009) and Transparency International (TI, 2015) Petty corruption refers to the everyday abuse of power by low- and mid-level public officials during interactions with citizens seeking public services, such as healthcare and education, often involving small monetary transactions (TI, 2009) In contrast, grand corruption involves high-level government actions that distort policies and undermine the state's core functions, allowing leaders to exploit resources for personal gain at the public's expense (TI, 2015).

Corruption is a complex social, political, and economic issue that is difficult to measure directly Over the last decade, public awareness of corruption has increased, leading to the development of various measurement tools Since the mid-1990s, perception-based indices have become the primary method for assessing corruption, including the Corruption Perception Index (CPI), Bribe Payers Index (BPI), and Global Corruption Barometer, all created by Transparency International Additionally, the World Bank Group's Worldwide Governance Indicators (WGI) include a Control of Corruption element as another aggregate measure Table 1 summarizes the key features of these corruption measurement tools.

Due to the absence of a global consensus on the definition and nature of corruption, accurately measuring it remains a challenge (Rohwer, 2009) Nonetheless, it is essential to categorize corruption indicators into three types: perception-based indicators, which reflect the views of citizens and experts; experience-based indicators, derived from the actual experiences of individuals or businesses; and proxy indicators, which assess corruption indirectly by aggregating various opinions and signals or by evaluating related aspects 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 research at the firm level has identified key factors influencing bribery and the magnitude 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 an effective indicator for understanding the prevalence of bribery.

This article analyzes the prevalence of corruption in business environments where firms may encounter bribery requests from officials It highlights that corrupt officials possess discretionary power, which can impact firms positively or negatively The review focuses on empirical studies that identify key factors influencing the likelihood of firms paying bribes, categorizing these factors 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 burdensome nature of regulations imposed by governments, such as licenses and permits, which are essential for societal and economic management However, these regulations, combined with the monopoly power held by government officials, create opportunities for bribery, as officials can demand payments from individuals seeking necessary authorizations The author highlights that these regulations necessitate frequent and direct interactions between citizens and government officials, leading to significant time investments for citizens This time commitment can be substantially reduced by opting to pay informal costs.

According to Svensson (2003), building on Tanzi's (1998) findings, the relationship between control rights and corruption is significant, where control rights signify the dynamics between businesses and government entities This research evaluates the extent of engagement with public officials through two key variables, including regulations that indicate the percentage of

2 See, Svensson (2002), Lee, S H., Oh, K K., & Eden, L A., (2010); Rand, J., & Tarp, F (2012) and Malomo,

Administrators dedicate an average of 23 hours each month to navigating government regulations, incurring significant costs for accountants and lawyers who assist with compliance and tax matters Additionally, Rand and Tarp (2012) highlight a strong correlation between the number of government inspectors and the time management spends interacting with public officials, indicating the extent of regulatory engagement.

Svensson (2003) reveals a direct correlation between the likelihood of bribery and the extent of interactions with public officials Businesses often incur informal costs when engaging with officials who hold sway over their operations, leading to increased time spent navigating public regulations Additionally, companies face higher expenses for accountants and specialized service providers to manage compliance with regulations and taxes.

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) indicates that the type of taxes firms are required to pay may influence corruption, although initial findings were hindered by multicollinearity issues By employing principal components analysis, Svensson reveals a significant positive relationship between tax types and corruption Similarly, Malomo (2013) demonstrates that companies declaring higher percentages of sales for tax purposes are more inclined to engage in bribery.

Lecraw (1984) and Luo (2007) highlight that some firms focus on domestic sales, while others primarily earn revenue through exports Domestic-oriented firms tend to engage more closely with local suppliers, customers, and officials, increasing their risk of encountering corrupt practices This heightened interaction with the local environment exposes these businesses to various legal vulnerabilities associated with regulatory requirements.

Kobrin (1987) argues that exporting firms with advanced technical and managerial capabilities, which are enhanced over time through learning and innovation in the global market, are less susceptible to government corruption This resilience contributes to their profitability and strengthens their bargaining power with government entities.

In developing countries, particularly those facing balance of payments issues, export activities are crucial for generating foreign exchange and creating jobs This significance of export-oriented firms leads public officials to reduce their demands for bribes to avoid potential repercussions, highlighting a negative relationship between export activities and corruption.

Lee, Oh, and Eden (2010) argue that competition among national governments to attract export-oriented firms enhances these firms' bargaining power As a result, they hypothesize that export-oriented firms are less likely to encounter informal costs and are required to pay smaller bribes to government officials.

The dependence of firm’s profitability on government

Pfeffer and Salancik (1978) highlighted that firm-level profitability varies based on dependence on government revenue, with companies reliant on government contracts often more susceptible to public officials' influence This reliance becomes problematic in environments where corruption affects state contract awards (Dela Rama, 2012) Given the critical nature of these contracts for corporate survival, firms may adopt strategies to sway political decisions in their favor, necessitating the development of internal resources to swiftly gather information on government dynamics (Hillman & Hitt, 1999; Hillman, 2005).

Research by Hansen et al (2009) suggests that when state-owned enterprises become key clients, it positively influences firm performance This relationship may foster an informal benefit-sharing arrangement between firms and government officials Additionally, studies by Rand and Tarp (2012) and Malomo (2013) utilize a dummy variable to assess the impact of government as a customer on bribery occurrences, hypothesizing 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 subsidized goods However, limited supply can lead to shortages, making ration coupons a necessary solution Consequently, individuals seeking to access these goods may resort to informal payments to public officials responsible for managing the allocation of these limited resources.

Svensson (2003) and Malomo (2013) investigate how the utilization of public services—such as electricity, water, telephones, and waste disposal—correlates with the likelihood of bribery Their findings suggest that entities reliant on public services face 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 divided into three main sections The first section offers an overview of corruption, defining it as a complex social, political, and economic issue that cannot be measured directly It emphasizes that corruption measurement relies on three types of indicators: perception-based, experience-based, and proxy indicators The second section reviews academic studies on the factors influencing bribery and the amount of bribes, highlighting the limited literature on firm-level corruption within specific country contexts These studies primarily utilize control rights and bargaining hypotheses to analyze bribery incidence and variation, revealing a positive correlation between interactions with government officials, regulatory burdens, and the likelihood of bribery Additionally, firm size and informal status are identified as key indicators of bribery incidence, while variations in bribe amounts are linked to firms' ability to pay and their negotiation power The third section presents a fundamental framework for estimating both the incidence and level 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 now poses a serious threat to the nation's sustainable development.

A 2012 sociological survey by the World Bank revealed that corruption ranks among the top three concerns for the population in Vietnam Conducted across ten provinces and cities, the survey targeted citizens, businesses, and officials, highlighting their perceptions of corruption as a significant societal issue Notably, officials identified corruption as the most pressing problem, while businesses ranked it second, following the cost of living Citizens placed corruption third, behind the cost of living and traffic accidents This data underscores the critical challenges Vietnam faces, as illustrated in Figure 1.

Figure 3 1: The most serious Economic & Social Issues for Vietnam 4

A recent survey highlights the pervasive nature of corruption in Vietnam, revealing its occurrence in various forms across multiple sectors Notably, a significant consensus among public officials, enterprises, and citizens indicates a widespread recognition of corruption, with over 75% of respondents identifying four sectors as the most affected by corrupt practices.

4 The most serious Economic & Social Issues for Vietnam, according to public officials, Enterprises and citizens (%)

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 reached alarming levels, as evidenced by the Corruption Perceptions Index 2014 (CPI 2014), which highlights the country's low ranking With a score of 31 on a scale of 0 to 100—where 0 indicates high corruption and 100 signifies a clean reputation—Vietnam's struggle with corruption is increasingly concerning.

Despite efforts to combat corruption, perceptions of corruption among citizens in 119 out of 175 countries, including 18 out of 28 in the Asia-Pacific region, have remained unchanged over three consecutive years (2012-2014) This stagnation highlights a significant lack of trust 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)

50% Government uses compliance with local regulations to extract rents

Over 10% of revenue in informal payments

The PCI 2014 Survey highlights a concerning decline in the perception of informal cost criteria among surveyed firms, revealing increased pessimism compared to 2006 Specifically, while 66% of respondents reported paying informal costs for smooth business operations in 2008, this trend reversed in 2014, indicating a significant rise in such payments Additionally, the report reveals that 10% of businesses that engage in bribery allocate over 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 from 41% in 2013 to 66% in 2014, as highlighted in 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 a significant portion of bribes is directed towards tax collectors and facilitating easier access to public services Notably, approximately 20 percent of these payments are made specifically for tax-related purposes.

30% of payment for latter one Comparing to previous years (2009 and 2011), tax services show improvement while public service access has poorer performance.

To getTo get licenses To deal with connected toand permitstaxes and tax To gainTo deal with Other government contracts public procurement customs public services collectors

Figure 3 4: The purpose of bribe payment

According to Transparency International's 2013 report, bribe amounts in Vietnam vary significantly across 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, the informal costs associated with land services average 1,437,500 VND (about 70 USD), which can represent 4% to 124% of the average monthly salary in Vietnam as of 2014 In critical sectors like medical and educational services, bribery costs also account for nearly 10% of expenses, highlighting a pressing concern for bribery control in the country.

Table 3 2: Average cost of bribes paid, by sector

Sector Average (VND) Average (USD equivalent)

Numerous studies highlight the root causes of corruption in Vietnam, with CIEM (2005) identifying four key factors: the misuse of public authority, arbitrary decision-making in policies and administration, and deficiencies in transparency and accountability.

6% 2% very efficient efficient normal ineffcient very inefficient

According to a report by Nguyen & Van Dijk (2012), 39% of officials and government agencies exhibit weaknesses in the implementation and monitoring of state functions The report highlights that variations 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.

Despite government initiatives to combat corruption in Vietnam, public perception remains largely negative A 2013 Transparency International survey revealed that only 24% of respondents believe the government's anti-corruption efforts are effective, while 38% consider them inefficient or very inefficient Additionally, 38% of participants found the effectiveness of these programs unclear 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

Public apprehension about corruption in Vietnam has remained significant over the years According to Transparency International (2013), 62% of respondents expressed reluctance to report corrupt incidents, with urban citizens showing an even higher rate of 66% This marks a notable shift from 2010, when 65% of respondents were willing to report corruption.

In a comparison of corruption disclosure among Southwest Asian nations, Vietnamese citizens demonstrate the lowest willingness to report corruption cases According to Transparency International (2013), the percentage of Vietnamese respondents willing to expose corruption is notably twice as low as that of their regional counterparts.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 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 remains a significant issue, particularly within sectors such as traffic police, land administration, customs, and construction The misuse of authority by public officials and arbitrary policy decisions are primary contributors to this problem Despite the Vietnamese government's ongoing efforts to combat corruption, these initiatives have proven largely ineffective, leading to widespread public skepticism regarding the anti-corruption programs in place.

Data and Econometric Model

Data

This study analyzes data from SME Surveys in Vietnam conducted between 2005 and 2013 by various organizations, including the Central Institute for Economic Management (CIEM) and the Ministry of Planning and Investment (MPI) The surveys encompassed approximately 2,500 small and medium enterprises, focusing on non-state manufacturing across ten cities and provinces The research highlights the differences in sample sizes between formal and informal private companies and utilizes information on financial performance, interactions with public officials, and bribe payments to address its research questions.

Household Private Partnership/ co-operative Limited Joint stock

Table 4.1 outlines the panel data structure, highlighting that all firms in the cleaned sample must have been operational for at least three consecutive years The final dataset comprises 1,919 firms and 7,873 observations, representing various ownership types Notably, approximately 70% of these firms are classified as household businesses, while 14% are limited liability companies, and the remaining 16% consist of other ownership forms.

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

Firms vary in size, measured by the natural logarithm of total employment The sunk cost is represented as the natural log, reflecting the log of the capital-labor (KL) ratio, where K denotes the market value of machinery, vehicles, and equipment, and L signifies total employment The natural log of profit per employee (ln_eprofit) indicates a company's financial health, calculated by subtracting operating costs and interest payments from total sales on a per-employee basis Additionally, the natural log of export value per employee (ln_eexp) highlights a firm's export performance relative to its workforce.

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 is used to indicate whether a firm receives financial or technical assistance from the government, with a value of 1 for assistance and 0 for no assistance The tax percentage reflects the proportion of a firm's sales allocated for tax purposes Additionally, the regulation metric measures the percentage of a manager's time dedicated to navigating government regulations on a monthly basis Lastly, the term "informal" refers to firms that operate without formal registration.

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 key descriptive statistics regarding bribe amounts paid by firms across ten provinces and cities Notably, Ho Chi Minh City exhibits the highest average bribe payments, the most significant total bribe amounts, and the greatest number of reported bribery cases, indicating severe corruption in this region.

In Ho Chi Minh City, firms typically pay officials an average of approximately 20.5 million dong, while in Khanh Hoa, the lowest payment recorded is around 3.7 million dong Similarly, companies in Long An, Quang Nam, Phu Tho, and Nghe An exhibit comparable payment trends 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 Hanoi ranging between 6 million to 8 million dongs.

In Vietnam, the highest recorded bribe amount is found in Ho Chi Minh City, reaching an astonishing 5.1 trillion dong, while Long An reports a significantly lower figure of just 23 million dong.

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

Table 4.4 reveals a notable disparity in bribe payments across different legal ownership types, with joint stock companies averaging over 72 million dongs—nearly 30 times higher than household companies The potential for even greater payments is indicated by a standard deviation exceeding 500 million dongs, highlighting a broad range of bribe amounts Additionally, a survey of 48 joint stock companies shows a maximum informal payment of approximately 5.1 billion dongs, compared to a 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 Notably, the food products and beverages sector reports the highest average bribe, while the water treatment sector shows 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 highlights that the majority of bribery cases are linked to public services (28.3%) and tax services (27.1%), indicating that these are the most common areas of concern In contrast, only about 12% of surveyed firms reported attempts to secure government contracts through bribery.

Table 4.6: The summary statistics of key variables

Variable Obs Median Mean Std.

Revenue from government/employee (log)

The value of input from government/ employee (log)

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.

Table 4.6 reveals that micro and small firms represent approximately 74% and 20% of the total firms in the cleaned sample, while medium and large firms account for more than 5% According to government decree No.90/2001/CP-ND, micro enterprises have 1 to 10 employees, small enterprises have 11 to 50 employees, and medium enterprises have 51 to 300 employees Notably, around one-third of the total firms lack business licenses at the district or provincial level, and over 19% of these firms have received government assistance.

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 gauged by the percentage of management's time dedicated to government regulations each month, averaging around 8% of total management working hours Additionally, firms typically allocate approximately 1.5% of their sales to tax payments, with some companies facing tax burdens as high as 32% of their sales.

Table 4.7 presents the pairwise correlation coefficients, with p-values indicated 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 exhibits a perfect correlation of 1.0000 with itself.

Table 4.7 highlights the pairwise correlations among various variables influencing bribery propensity It reveals a strong positive correlation (approximately 0.36) between firm size, measured by the logarithm of total employment, and the incidence of bribery Conversely, the correlation with firm informality is negative (-0.32), suggesting that larger firms are more inclined to incur informal costs, while unregistered companies may attempt to evade government scrutiny and consequently avoid bribery.

There is a significant correlation between firm size, profitability, and the amount of bribe payments, with correlation coefficients of approximately 28% and 26% This indicates that larger bribe payments may be positively associated with a firm's current capacity to pay bribes, while there is a negative relationship between the amount of bribe paid and the size of the firm.

The pairwise correlation coefficients indicate that there is minimal correlation among the independent variables, suggesting that multicollinearity is not a concern when conducting the regression analysis.

Econometric model

Sample selection bias poses a significant challenge in estimating behavioral relationships, particularly when the dependent variable is only observed in non-randomly selected samples (Heckman, 1979) This issue is especially relevant when analyzing bribe incidence and amounts, as it arises from the use of non-random samples in SMEs surveys and missing information on bribe payments from several surveyed companies Consequently, applying OLS regression to the entire sample can lead to biased coefficients To address this selection bias, the Heckman Two-step procedure, introduced by Heckman (1979), is a widely used classical method.

Heckman model comprises two equations, including selection equation and outcome equation In this study, the bribe equation (outcome equation) is as follows:

Selection equation (participation equation) is given by: where: bi is the bribe amount

In the context of bribe-reporting firms, Xi represents observable characteristics that explain the differences in bribe amounts, applicable only to firms incurring informal costs The term ԑi encompasses all unmeasured factors influencing the size of a bribe, while bi is relevant solely for firms that are required to pay a bribe Additionally, the variable d equals 1 for firms that pay a bribe and 0 for those that do not, with nd indicating unknown parameter vectors.

Zi: 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.

- 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 methodology involves estimating the selection model by applying a probit model (d on Z) to the entire dataset Subsequently, the inverse Mills ratio for each observation is computed using the estimated coefficients (β) obtained from this probit model.

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, represented by the probability density function and cumulative distribution function of the standard normal distribution N(0,1) This ratio is influenced by the covariance between the variables involved.

In the second step, the outcome equation is estimated using ordinary least squares regression (OLS), 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 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 ( )

) 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

The results of the first stage reveal the factors influencing bribery payments, with the first column displaying findings from the Heckman two-step model and the second column illustrating outcomes from the Heckman Maximum Likelihood Estimation, which clusters at the firm level to address heteroskedasticity.

Overall, the results in column (1) and (2) are very consistent In particular, two columns indicate that the “exposure /visibility” variable presented by firm size and

Research indicates that informal or unregistered businesses show statistically significant results at the 1% level, aligning with expected trends Specifically, larger firms are positively correlated with a higher likelihood of bribery, while companies operating without a business registration license are negatively correlated with bribery incidence The findings reveal that a 1% increase in firm size correlates with an approximate 0.38% rise in the probability of paying bribes, all else being equal Conversely, businesses in informal status experience a 0.5% reduction in the risk of engaging in bribery.

Rand and Tarp (2012) suggest that Vietnamese firms with an informal status tend to avoid interactions with corrupt public officials, resulting in a lower risk of bribery This finding contrasts with Tenex et al (2003), which identified a positive correlation between formality and bribery rates Additionally, Rand and Tarp (2012) note that larger firms are more likely to incur informal costs.

The analysis indicates that both tax percentage and regulation have positive and significant coefficients at the 1% level, highlighting their impact on bribery likelihood Specifically, an additional percentage of sales allocated for tax purposes increases the probability of bribery by nearly 3 percentage points Furthermore, an increase in the time senior managers spend on public regulations correlates with a 0.3 percentage point rise in bribery probability These findings underscore the notion that the prevalence of corruption is influenced by the extent of interactions with public officials, aligning with the conclusions of 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 indicates that firms heavily reliant on government transactions, either through selling their products or purchasing inputs, are at a greater risk of engaging in bribery Specifically, a 1% increase in sales per employee from government contracts correlates with a nearly 2 percentage point rise in the likelihood of bribery This finding aligns with previous research by Hansen et al (2009), Rand and Tarp (2012), and Malomo (2013) Additionally, the table highlights that when state-owned enterprises serve as the primary suppliers of inputs, firms face an increased probability of incurring informal costs, a phenomenon supported by Tanzi's research.

Engagement in international trade reveals two contrasting outcomes, particularly highlighting that export value per employee is negatively correlated with the incidence of bribery This indicates that exporters tend to incur fewer informal costs compared to firms operating solely within their domestic markets These findings align with the 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, there is no evidence to suggest that the value of imports per employee influences corruption rates in either scenario.

This study analyzes the bargaining framework concerning firms' ability to pay bribes, measured by profit per employee and the K/L ratio, which reflects firms' refusal power The findings, presented in Table 1, indicate that both profit per employee and the K/L ratio are statistically significant with positive correlations in the models analyzed Higher profits correlate with an increased likelihood of incurring informal costs, while a lower K/L ratio suggests reduced exit costs, thereby enhancing firms' refusal power and decreasing their likelihood of paying bribes These results align with previous studies by Svensson (2003) and Rand and Tarp (2012) Specifically, an increase in profit per employee raises the probability of paying informal costs by approximately 0.14%, while a decrease in sunk costs corresponds to a 0.01% increase in the likelihood of bribe payments.

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, focusing on determining the amount of bribe required Most variables from the first stage are retained in this analysis, with only one variable omitted to streamline the identification process using Heckman's two-step method (Heckman, 1979) The dependent variable examined is the logarithm of the bribe amount per employee.

The analysis reveals a strong correlation between control right variables and the size of bribes, with significant findings at the 1% level Specifically, factors such as tax percentage, revenue from government employees, input value from government employees, and government assistance are positively linked to reported informal costs A 1% increase in sales allocated for tax purposes corresponds to a 0.06% rise in bribes per employee, while a 1% increase in sales to the government per employee leads to a 0.02% increase in bribes Additionally, a 1% increase in the value of government-provided inputs results in a 5 percentage point increase in bribes per employee Furthermore, government assistance is associated with a 0.2% increase in bribes paid per employee These findings suggest that the level of interaction and dependence on government significantly influences firms' bribery decisions.

Table 5.1 illustrates a strong correlation between a firm's ability to pay, as indicated by profit per employee, and the size of the bribe This finding implies that an increase in profit per employee leads to a higher likelihood of larger bribe amounts.

On average, the bribe paid per employee increases by 0.3% for every 1% rise in bribery This aligns with the conclusions drawn by Svensson (2003) and Malomo (2013) Additionally, the data suggests 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 The marginal effect suggests that firms operating informally pay approximately 0.6% less in bribes per employee.

The t-test analysis of 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 may differ if there is a feedback loop from bribery to profit Specifically, it raises the question of 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 higher profits may lead to increased bribery.

In 2002, it was observed that politicians and bureaucrats engage in rent-seeking behaviors by offering government favors like subsidies and tax relief, significantly impacting company profitability (Mbaku, 1992) Furthermore, Bliss and Di Tella (1997) developed an extortion model indicating a positive relationship between bribery and profit, highlighting the pervasive nature of rent-seeking in the political and economic landscape.

In 2003, evidence indicated that corruption does not yield feedback to profit Causal empiricism suggests that large firms with political power dominate the regulatory process, overshadowing smaller firms, which constitute the majority in the sample These insights imply that demonstrating a direct link between corruption and profit is challenging.

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.

Similar to Svensson's approach, this study employs lagged values of profit per employee as an instrumental variable for current profit per employee This instrumental variable meets two critical criteria: it exhibits a strong correlation with profit per employee (correlation coefficient = 0.3) and, as a past variable, 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 show a strong consistency 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, maintaining 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 instrumental technique Furthermore, most coefficients of the statistically significant variables in Table 5.2 are larger than those reported in Table 5.1, which did not utilize the instrumental technique.

The analysis of bribe amounts reveals that several statistically significant variables are key indicators of their variation These include profit per employee, tax percentage, revenue from government per employee, input value from government per employee, receipt of government assistance, and whether the entity is informal or not registered.

Establishing a causal relationship between profit and bribery is inherently challenging; however, this section presents evidence suggesting that the observed results are not influenced by a feedback loop from bribery to profit.

Conclusion

Main findings

This study, similar to Svensson (2002), utilizes control rights and bargaining frameworks to investigate the factors influencing bribe incidence and payment sizes among approximately 2,500 SMEs in Vietnam By employing the Heckman two-step procedure, the research reveals that firm characteristics—such as visibility (firm size and informal status), ability to pay (profitability), refusal power (sunk costs), and interaction levels with government employees—are significantly linked to both the occurrence of bribery and variations in bribe amounts These results align with findings from Svensson (2002), Rand and Tarp (2012), and Malomo (2013).

This paper highlights that interactions with public officials increase the likelihood of bribery, particularly for firms facing significant tax burdens or high sunk costs Conversely, companies operating informally tend to avoid engaging in bribery.

This study reveals that firms experiencing higher profits or facing significant tax burdens are more inclined to pay larger bribes Additionally, the frequency of interaction with public officials serves as a strong indicator of bribe amounts, with increased engagement leading to above-average bribe payments.

This study meticulously analyzed the causal link between bribery and profit, employing lagged profit values as instrumental variables The findings remain consistent across various econometric models.

Policy implications

To effectively combat corruption, a multifaceted approach is essential due to its complex nature Key policy recommendations include minimizing direct regulatory burdens, as the control right hypothesis suggests that the level of interaction with public officials impacts bribery rates Additionally, increasing penalties for corrupt acts can serve as a deterrent, ultimately contributing to a reduction in corruption levels within a country.

Government assistance, including financial and technical support, can inadvertently foster corruption, particularly when public officials have discretionary power To enhance competitiveness among businesses and effectively address corruption, policymakers should decrease government aid to firms and instead focus on establishing a fair and equitable environment for all enterprises.

This study demonstrates that companies engaged in exporting are less susceptible to the risks associated with government corruption compared to non-exporting firms The findings indicate that policymakers should implement strategies designed to attract and bolster export-oriented businesses as a means to mitigate corruption.

Limitations and further research

This research faces several limitations that impact its findings Firstly, the quality of data is compromised due to the sensitive nature of the topic, making it challenging for respondents to provide honest accounts of their bribery experiences and the amounts involved, which raises concerns about the reliability of the dependent variables related to bribery payments Secondly, the limited number of consecutive years of firm observations restricts the ability to identify clear trends Lastly, the measurement of the sunk cost component, which reflects capital mobility, poses an issue; while Svensson (2003) estimated this component using reported resale and replacement values of capital stock, the SMEs surveys only offer information on replacement values To address this limitation, Rand and Tarp have proposed alternative methods.

In 2012, the measurement of sunk cost was approached by analyzing the ratio of the replacement value of capital stock to labor, following the methodology of Rand and Tarp However, the SME survey's sampling scheme presents limitations, as it focuses solely on non-state enterprises, including household, private, partnership/collective, limited liability, and joint-stock companies, while excluding foreign-owned enterprises This exclusion hinders the analysis of how ownership structure influences bribery incidence and the size of bribes Additionally, the lack of data regarding a firm's competitiveness prevents an examination of whether the number of competitors for a firm's main product impacts corruption levels.

To address the identified limitations, further research should explore the influence of competitors' informal payments on a firm's profitability and willingness to engage in bribery, enhancing the understanding of bribery supply dynamics Additionally, examining how informal payments affect future profitability and competitiveness will provide deeper insights into the relationship between profit levels and bribery occurrences Furthermore, given the sensitivity of the Heckman Model to variable selection in the selection equation, future studies may benefit from the development of improved models to effectively address sample selection bias.

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Appendix 1: Heckman two-step regression on the incidence of bribery and the size of bribe

Heckman selection model two-step estimates Number of obs = 7139

(regression model with sample selection) Censored obs = 5236

| Coef Std Err z P>|z| [95% Conf Interval] -+ -

The analysis reveals significant relationships among various economic factors, with bribes negatively impacting economic performance (eexp_ln: -0.0183, p=0.007) and informal employment showing a strong negative correlation (-0.5669, p=0.000) Regulations positively influence economic outcomes (0.0028, p=0.001), while tax percentage also has a positive effect (0.0265, p=0.000) Industries such as textiles (-0.6196, p=0.000) and food (-0.5112, p=0.000) exhibit substantial negative effects, indicating challenges in these sectors Employment is positively correlated with economic profit (eprofit_ln: 0.1344, p=0.000), suggesting that increased employment contributes to better economic performance The model's lambda value (1.5756, p=0.000) indicates a significant relationship between the variables analyzed, with rho (0.88797) and sigma (1.7744) further supporting the robustness of the findings.

Appendix 2: Heckman two-step regression on the incidence of bribery and the size of bribe (corrects errors for heteroscedasticity)

Heckman selection model Number of obs = 7139

(regression model with sample selection) Censored obs = 5236

Uncensored obs = 1903 Wald chi2(23) = 278.24 Log pseudolikelihood = -6572.269 Prob > chi2 = 0.0000

(Std Err adjusted for 1955 clusters in id) -

The analysis reveals significant relationships between various economic factors and their impacts on different sectors Notably, a strong negative correlation exists with informal employment, indicating a detrimental effect on economic growth Conversely, regulations positively influence estate-related activities, while tax percentages also show a beneficial impact Industries such as textiles, food, and wearing apparel exhibit substantial negative coefficients, suggesting challenges in these sectors Additionally, the findings indicate that certain materials, including wood and rubber, face adverse effects, highlighting the need for strategic interventions to enhance sectoral performance Overall, these insights underscore the importance of regulatory frameworks and economic policies in shaping industry outcomes.

The analysis reveals significant relationships among various economic factors A positive correlation is observed between ebribe_ln and eprofit_ln, with a coefficient of 0.2949, indicating a strong significance (p < 0.001) The instate_eln also shows a notable positive impact (0.0515, p < 0.001), while tax_percentage contributes positively (0.0623, p < 0.001) However, regulations do not demonstrate a significant effect (p = 0.171) In contrast, informalr has a substantial negative association (-0.5911, p < 0.001), along with significant negative impacts from sectors like foods (-0.6964, p = 0.001), textiles (-1.0020, p < 0.001), wearing (-0.8587, p = 0.001), and leather (-0.8857, p < 0.001) Non-metallic products also show a significant negative correlation (-0.6166, p = 0.011) The overall model indicates that several factors significantly influence economic outcomes, emphasizing the importance of addressing issues related to informal sectors and specific industries.

- Wald test of indep eqns (rho = 0): chi2(1) = 213.25 Prob > chi2 = 0.0000

/athrho | 1.04534 0715835 14.60 0.000 9050389 1.185641 /lnsigma | 4646773 0340876 13.63 0.000 3978668 5314877 rho | 779988 0280334 7187425 829222 sigma | 1.591501 0542504 1.488646 1.701462 lambda | 1.241351 0820975 1.080443 1.402259

Appendix 3: Heckman two-step regression on the incidence of bribery and the size of bribe (using instrument variable)

Heckman selection model two-step estimates Number of obs = 7139 (regression model with sample selection) Censored obs = 5236

| Coef Std Err z P>|z| [95% Conf Interval] -+ -

The analysis reveals significant relationships between various factors and economic outcomes A notable negative correlation exists with informal employment, indicating a substantial impact on economic performance Conversely, employment levels show a strong positive association, suggesting that higher employment correlates with better economic results Additionally, tax percentages and regulatory frameworks exhibit positive effects on economic indicators, while certain sectors such as food, textiles, and leather demonstrate negative influences The results also highlight the importance of capital investments, with machinery and equipment showing a positive relationship with economic performance Overall, the findings underscore the complexity of economic interactions influenced by both formal and informal sectors.

Appendix 4: Heckman two-step regression on the incidence of bribery and the size of bribe (correct heteroscedasticity and using instrument variable)

Heckman selection model Number of obs = 7139

(regression model with sample selection) Censored obs = 5236

Wald chi2(23) = 280.57 Log pseudolikelihood = -6567.933 Prob > chi2 = 0.0000

(Std Err adjusted for 1955 clusters in id) -

-+ - bribe | eexp_ln | -.0158691 0072776 -2.18 0.029 -.0301329 -.0016053 eimp_ln | -.015786 0106601 -1.48 0.139 -.0366794 0051073 regulations | 0028626 000771 3.71 0.000 0013514 0043737 estate_ln | 0252141 0054655 4.61 0.000 0145019 0359263 instate_eln | -.0016981 0060798 -0.28 0.780 -.0136143 010218 informalr | -.535521 0461881 -11.59 0.000 -.6260481 -.4449939 employment_ln | 4078376 0214447 19.02 0.000 3658066 4498685 gov_ass | 0317423 0467687 0.68 0.497 -.0599227 1234073 sunkcost_ln | 0087916 0068666 1.28 0.200 -.0046667 0222499 eprofitln1hat | 44813 0707831 6.33 0.000 3093977 5868623 tax_percentage | 0251381 0074013 3.40 0.001 0106318 0396443 foods | -.383215 1209359 -3.17 0.002 -.6202449 -.1461851 textiles | -.4126085 1471962 -2.80 0.005 -.7011079 -.1241092 wearing | -.3810781 1519294 -2.51 0.012 -.6788543 -.0833019 leather | -.125751 1200564 -1.05 0.295 -.3610573 1095553 wood | -.1587594 1271418 -1.25 0.212 -.4079528 0904339 paper | -.2967856 1454504 -2.04 0.041 -.5818632 -.011708 printing | -.2433042 1482412 -1.64 0.101 -.5338517 0472433 chemicals | -.0594006 1438301 -0.41 0.680 -.3413024 2225013

The analysis reveals significant relationships between various factors and economic outcomes Notably, ebribe_ln shows a strong positive correlation with eprofitln1hat (coef 0.8818, p < 0.001), indicating that bribery impacts profits significantly In contrast, informalr has a substantial negative effect (coef -0.5472, p < 0.001), suggesting that informal practices detrimentally affect economic performance Additionally, government assistance (gov_ass) positively influences outcomes (coef 0.3198, p < 0.001) Other factors such as tax_percentage (coef 0.0582, p < 0.001) and estate_ln (coef 0.0322, p = 0.002) also show positive significance, while sectors like textiles (coef -0.5783, p = 0.030) and leather (coef -0.6479, p = 0.003) demonstrate negative impacts Overall, these results underscore the complexities of economic interactions, highlighting both beneficial and adverse influences on profitability and growth.

- Wald test of indep eqns (rho = 0): chi2(1) = 137.69 Prob > chi2 = 0.0000

/athrho | 9610621 0819019 11.73 0.000 8005373 1.121587 /lnsigma | 4254585 0381801 11.14 0.000 3506268 5002902 rho | 7447503 0364748 6643371 8081202 sigma | 1.530292 0584268 1.419957 1.6492 lambda | 1.139685 0951066 9532799 1.326091

Appendix 5: Heteroskedasticity test using Breusch-Pagan / Cook-Weisberg - the Heckman two-stage model

Variables: fitted values of ebribe_ln chi2 (1) = 35.51

Appendix 6: Heteroskedasticity test using Breusch-Pagan / Cook-Weisberg - the Heckman two-stage model when using instrument variable