Corruption and foreign direct investments in developing countries


Master's Thesis, 2019

72 Pages, Grade: 1,7


Excerpt


Table of content

LIST OF FIGURES AND TABLES

LIST OF ABBREVIATIONS

1. INTRODUCTION

2. CORRUPTION
2.1 Definition of corruption
2.2 Forms of Corruption
2.3 Psychology behind corruption
2.4 Measuring Corruption
2.4.1 Limitations of Measurements of Corruption
2.4.2 Magnitude of Corruption
2.5 Causes of corruption
2.5.1 Natural Resource Endowment
2.5.2 Shadow Economy
2.5.3 Wages
2.5.4 Transparencyand freedom of the press
2.5.5 Political competition and free market
2.5.6 Historical Background (primarily colonial)
2.5.7 Gender
2.5.8 Religion
2.5.9 Migration
2.6 Corruption and economic growth
2.7 Corruption and its effect on firms
2.8 Corruption and its consequences in developing countries
2.9 Fighting corruption

3. FOREIGN DIRECT INVESTMENT
3.1 Definition and a historical perspective of FDI
3.2 Forms of FDI
3.3 Motives for FDI
3.4 FDI and growth
3.4.1 Crowding out
3.4.2 Crowding in
3.5 Poverty reduction through external channels
3.6 Importance of FDI in developing countries
3.7 FDI in numbers

4. NEXUS BETWEEN FDI AND CORRUPTION

5. CONCLUSION AND OUTLOOK

REFERENCES

List of figures and tables

FIGURE 1: SURVEY CORRUPTION, WEF (2019)

FIGURE 2: PRINCIPAL-AGENT THEORY CORRUPTION, BASED ON LAMBSDORFF (2007)

FIGURE 3: CORRUPTIVE TRIANGLE, OWN GRAPHIC BASED ON (CRESSEY 1953)

FIGURE 4: CPI WORLD MAP TRANSPARENCY INTERNATIONAL (2018)

FIGURE 5: CORRUPTION BY INSTITUTION: TRANSPARENCY INTERNATIONAL (2013)

FIGURE 6: CORRUPTION GROWTH NEXUS (IMF, 2016)

FIGURE 7: WORLD BANK GOVERNANCE INDICATORS, (WORLD BANK 2019)

FIGURE 8: SHARE OF BRIBES, OWN GRAPHIC BASED ON: WORLD BANK (2011)

FIGURE 9: NATURAL RESOURCE RENTS, OWN GRAPHIC BASED ON (WORLD BANK 2019)

FIGURE 10: MODEL OF INTERNATIONAL CAPITAL FLOWS (PROTESENKO 2004)

FIGURE 11: INVESTORS FRAMEWORK, KUSEKAND SILVA(2017)

FIGURE 12: POLITICAL FRAMEWORK FDI (UNCTAD 2018)

FIGURE 13: GDP PER CAPITA, BASED ON: WORLD BANK (2018)

FIGURE 14: FDI IN AND OUTFLOWS, BASED ON WORLD BANK (2018)

FIGURE 15: EFFECTS OF FINANCIAL FLOWS, BASED ON: BOSWORTH ET AL. (1999)

FIGURE 16: FDI INFLOWS 2017, BASED ON UNCTAD (2018)

FIGURE 17: FDI OUTFLOWS 2017, BASED ON UNCTAD (2018)

FIGURE 18: FRAMEWORK EFFECTS OF CORRUPTION, OWN GRAPHIC

TABLE1: INWARD FDI RATES OF RETURN 2017 (UNCTAD 2018) 45

TABLE 2: LITERATURE OVERVIEW FDI & CORRUPTION 52

List of abbreviations

Abbildung in dieser Leseprobe nicht enthalten

1. Introduction

Corruption is generally accepted as a phenomenon which is occurring worldwide. Nev­ertheless, the data which is quantifying its manifestation showcase stark geographical as well as cultural differences. Unscrupulous governments, non-existing economic prosperity, a high degree of political instability and a population deeply afflicted by pov­erty are the most conspicuous explanations for elevated levels of corruption.

In order to tackle the corruption issue, all notable multinational institutions made the fight against corruption one of their foremost important priorities. Even though corrup­tion is repeatedly portrayed as “persistent over time and space” one would assume, given the enormous efforts, which are put into combatting corruption that the problem should be on its verge to extinction. Contrariwise, this is not necessarily the case. Even nowadays, huge parts of Africa, South America and East Asia bear the heavy burden of corruption.

It is widely accepted as conventional wisdom, that corruption is a detriment to the eco­nomic prosperity ofa society (Mauro, 1995). Besides other reasons, corruption is said to undermine investments due to the uncertainty which it creates underneath the in­vestors. Consequently, external capital formation as a catalysator for growth becomes less prominent in countries which are experiencing high levels ofcorruption. Transpar­ency international which positions itself on the forefront of the fight against corruption repetitively reminds its audience of the aforementioned negative nexus between cor­ruption and human progress:

“If we hope to reach the Millennium Development Goal of halving the number of people living in extreme poverty governments need to seriously tackle corrup­tion in public contracting."Peter Eigen, Chair of Transparency International

Even though this reasoning appears to be coherent and logical, there are some notable publications within the scientific community which question the above-mentioned strictly negative relationship between corruption and investments (Shaw et al., 2011).

It is not solely a contemporary strand of literature which elucidate why corruption might be a necessary evil under specific circumstances. The pioneering work from Hunting­ton in the 1970's elaborates why corruption might be a prerequisite for economic pro­gress in countries which are dealing with slow and burdensome democracies (Huntington, 1968).

If nations are not able to raise themselves out of poverty, economist speak of the so- called low-level equilibrium trap1. Scholars habitually refer to increased capital for­mation as one ofthe foremost important prerequisites for economic prosperity. Arche- typically, nations can increase their capital stock either through domestic saving or either foreign direct investment (hereinafter referred to as FDI) or official development aid (hereinafter referred to as ODA). Since domestic saving is normally not a viable option for those countries, FDI has been frequently hailed as an instrument to alleviate poverty.

The effect of corruption on FDI has archetypically, within the scientific community, been described as negative (Bardhan, 1997). The necessity to pay bribes in order to be able to invest in a specific country is an additional cost factor which reduces the attractive­ness of that investment. Additionally, potentially even more pivotal when it comes to assessing investments, is the legal framework which should protect the investment.

However, even the inflow of FDI into developing countries is not solely seen as a boon for the recipient nations. Recurrently, academics and in some instances multinational institutions alike have warned that FDI comes with the innate threat to undermine do­mestic investments through a crowding out effect (Shaw et al., 2011).

Consequently, the aim of this thesis is to analyze the interplay between corruption and FDI inflows. The principal question is hereby under which circumstances investors seem to “overlook” potential grievances in the recipient countries and which effect el­evated FDI inflows have on the prosperity ofthe beneficiary economy. By exploring the repercussions FDI has on economic growth, in the further course and in a separate section, the thesis devotes special attention to developing countries.

The structure of this thesis is as follows: the subsequent 2nd chapter elucidates the term corruption and deals with its implications, reasons and measurement. This chap­ter ends with the consequences corruption has on developing countries and the meas­urements which are taken by various institutions in order to successfully confine world­wide corruption.

The succeeding 3rd chapter puts its emphasize on FDI and the intertwined opportuni­ties and challenges. The abovementioned chapter concludes with a stance on the sig­nificance of FDI for poverty reduction in developing countries as well as an overview ofthe magnitude ofworldwide FDI.

The penultimate 4th chapter sheds light on the nexus between FDI and corruption. An extensive literature review as well as classification is going to walk the reader through the main scientific contributions dealing with the aforementioned nexus.

The fifth and final section concludes with a summary ofthe main findings of section 3 and 4 and will expound a brief outlook of future challenges which developing countries have to face if they want to appropriately utilize FDI to their advantage.

2. Corruption

“Corruption is a persistent feature of human societies over time and space (Aidt, 2003)”

This quotation, despite its simplicity, describes corruption very precisely. The most re­cent news coverage regarding corruption once again highlights how corruption albeit in different forms and magnitudes, doesn’t stop at country boarders and seems to be quite literally a persistent feature of human societies. There is on the one hand, the President of Zimbabwe, Emmerson Mnangagwa who just recently said that corruption is “deeply rooted” in “various institutions ofthe state”(Newsday, 2019). And on the other hand, far away from the crisis inflation plagued Zimbabwe, the major of New York, Mr. De Blasio is fighting with his own corruption scandal (NewYork Post, 2019).

However, corruption is not only perceived as a pressing problem within the scientific community. An analysis in which millennials (18-34) were surveyed also produced the following unambiguous results.

Abbildung in dieser Leseprobe nicht enthalten

Figure 1: Survey corruption, WEF (2019)

In another survey, conducted in 34 countries, 76 % ofthe 38.620 interviewed partici­pants identified corruption as a major threat for developing countries2 (PEW, 2014). The following chapter is going to walk the reader through the main aspects which are necessary to understand in order to grasp the magnitude of the worldwide corruption issue.

2.1 Definition ofcorruption

Since corruption is broadly perceived as a many-faced phenomenon there is not one unique definition which is used within the scientific literature (Aidt, 2003). The majority of the characterizations however emphasize the dishonest or unlawful aspect which is inherit to any form of corruption.

The definition which is used by Transparency International is coined by Kaufmann who expresses corruptive behavior as „the abuse of public office for private gain” (Kaufmann, 1997, p. 114).

Jain characterizes corruption as an action in which the influence of a public department is utilized for private advantage in a manner that disobeys the policies of the sys­tem (Jain, 2001). Based on the previous definition, Aidt (2003) consequently derives three circumstances which are required for a corruption plagued environment:

1. Discretionary power: a given individual must be entitled to alter or change reg­ulations, laws or policies to his favor
2. Economic rents: the discretionary power has to be utilized to obtain rents
3. Weak institutions: the motivations which are represented by the political, admin­istrative or legal institutions are not attractive enough to avoid corruption

Even if it might appear negligible to discuss the precise semantic of the term corruption it certainly has an impact on the perception of corruption in general and the focus of the scientific literature. This assertion might become more tangible when both of the former quoted definitions are reassessed. Both of the cited characterizations of cor­ruption put a strong emphasize on the public aspect of the definition. Consequently, all corruptive behaviour which takes place in the private sector is not incorporated in those characterizations.

Knowing for certain that corruption logically also occurs within the private sector, Tanzi formulates the following definition for corruption:

“Corruption is the intentional non-compliance with the arm’s-length principle aimed at deriving some advantage for oneself or for related individuals from this behaviour(Tanzi, 1995).”

The subsequent chapter is going to elucidate the different forms and manifestations of corruption.

2.2 Forms of Corruption

Besides the arguably most well-known form of corruption, bribery (broadly speaking exchanging payments for favors (Lambsdorff, 2007), there are also other, often more subtle, forms of corruption.

Clientelism as one of them, explains asymmetric interactions amongst dissimilar groups of people with an advantageous outcome for all involved parties (Roniger, 2004). The underlying principle in this kind of collaboration is “give here and take there” (Graham, 1997). Political clientelism (exchanging beneficial treatment and democratic backing) is eminent in today’s governmental landscape particularly in developing coun­tries (Larreguy, 2012).

Embezzlement on the other hand, is generally defined as an exploitation of com­mended properties or means by a person who has been appointed to manage them. Green (1993) gives the following concise definition of embezzlement: “theft-after-trust offense”.

Corruption is frequently categorized according to the involved volume of capital or as­sets. A frequently cited distinction is the “grand” and “petty” corruption division. Grand corruption hereby implicates an often less frequent, but financially more extensive transaction. Typically, this kind of corruption is eminent in the higher tiers of the gov­ernmental administration. In contrast to the “grand” corruption, “petty” corruption pre­dominantly takes place in the subordinate levels of administrations who tend to have more frequent and direct contact points with their municipal community (Morris, 2011).

The principal-agent model is commonly used in the scientific literature to portray cor­ruptive interactions. Hereby, corruption is viewed as a trade of favours amongst two persons (agent and client) (Andvig et al., 2001). The agent3 is delegated with power by a third party, the so-called principal.4 This principal sets a framework of rules in which the agent can interact. In a corruptive act, the agent exploits his public authority in order to attain personal advantages from the principal. The latter is hereby incapable of supervising the whole set5 and thus cannot reprimand his agent (Groenendijk, 1997).

Abbildung in dieser Leseprobe nicht enthalten

Figure 2: Principal-Agent Theory Corruption, based on Lambsdorff(2007)

2.3 Psychology behind corruption

Arguably one of the most significant contributions to the psychology of corruptive be­havior is the pioneering paper “Other people's money” from Cressey (1953). The scholar herein developed a triangle model (subsequent figure) which showcases how individuals are led to fraudulent misconduct. According to Cressey, fraudulent behavior can be usually explained by the interplay ofthe three conditions: pressure, opportunity and rationalization.

Abbildung in dieser Leseprobe nicht enthalten

Figure 3: Corruptive triangle, own graphic based on (Cressey 1953)

The pressure to commit a serious misconduct can have various explanations. Besides the obvious explanation of pure greed, other scenarios are similarly conceivable. Es­pecially in developing countries medical expenses for instance can be an unbearable burden for many families and might be a reason why individuals engage in fraudulent behavior. The latter explanatory variables of the fraud triangle are deeply intertwined. On the one hand the opportunity, which led the individual believe that the chances of getting convicted are very slim. Those circumstances are often a testament of poor governance and legal oversight.

And on the other hand, rationalization which is similarly often connected to circum­stances which are predominantly found in developing countries. Those aforementioned conditions include: corruption is common underneath the perpetrators peers, the wage level in the respective country is low or fraud was the last available option in order to provide for my family (Mansor, 2015). Conclusively, it therefore comes as no surprise, given the qualitative theoretical background, that corruption levels are noticeably higher in developing countries.

An additional often cited explanation for fraudulent behavior is that actions which are criminal by law are not noticed as such by the individuals who are engaging in them. For instance, granting permissions and concessions not in accordance with the re­spective guidelines might not be seen as reprehensible. Prerequisite therefore is that the wrongdoer sees the beneficiary as a genuinely good person or friend and thus rationalizes his actions with doing good for a deserving person (Mazar, Amir and Ariely, 2008).

Additional psychological research affirmed the so-called self-fulfilling prophecies prin­ciple wherein a prediction either through direct or indirect mechanisms, effects its ful­fillment. This described principle can likewise be utilized to explain corruption. A self­fulfilling prophecy is ordinarily described as an essential mechanism that those who believe in the prognostication behave in a way that is contributing to its fulfillment (Wayne, Shore and Liden, 1997). Verifying evidence underpinning the suitability of this hypothesis in the corruption context stems inter alia from Corbacho et al., (2016). In a survey experiment in Costa Rica, the scholars informed the participants about the fact that corruption (supposedly) rose over a certain time period. Subsequently, the partak­ers attitude towards the payment of bribes was assessed. Congruent with the initial hypothesis participants who were exposed to the material about growing rates of cor­ruption were between 5 and 10% more susceptible to bribery (ibid.).

Another interesting perspective on the psychology underlying corruptive behavior can be described with the help of the “prisoners dilemma”. Even though the aforementioned model originally stems from game theory, it is likewise applicable in the corruption con­text. Archetypically, corruptive behavior is seen as individually coherent and benefi­ciary, however corruption is arguably uneconomical for a society at whole. A psycho­logical meta-analysis from the Yale University revealed, that people who score higher on IQ scores tend to evaluate situations over a more extended timeframe (Shamosh and Gray, 2008). Picking up on that research, Potrafke (2012) tested the hypothesis that countries which are reported to have high IQ scores on average should experience lower levels of corruption. The scholar could indeed identify a significant correlation between the IQ scores and the CPI. However, it is noteworthy that there is also an extreme stark correlation between IQ scores and economic growth and equality in countries as shown by Meisenberg (2012). Consequently, IQ and economic prosperity become statistically so similar that it is hard to distinguish which of the aforementioned variables really influenced the level of corruption.

2.4 Measuring Corruption

The arguably most commonly used assessment for corruption is the Corruption Per­ception Index (hereinafter referred to as CPI) (Lambsdorff, 2005). The CPI is an­nounced at a yearly basis and rank orders all countries of the world according to the perceived level of corruption in that given state. Hereby, the data is retrieved from sev­eral different sources. Those sources consist mainly of surveys and expert assess­ments from different NGOs or economical organizations (Transparency International, 2018). As outlined in the succeeding chapter, the main point of critique concerning the validity ofthe CPI stems from the subjectivity ofthe sources.

Abbildung in dieser Leseprobe nicht enthalten

Figure 4: CPI World Map Transparency International (2018)

However, several studies have shown an approvingly significant correlation between the CPI[6] and the GDP per capita in a given country. Wilhelm (2002) analyzed 85 coun­tries and finds a very strong correlation between the CPI and GDP per capita. The CPI explains, according to the mentioned study, 86 % of the GDP variance, which is an extraordinarily high outcome especially for inter country data (ibid.). Similar findings are presented by Podobnik et al. (2008). In their paper, which evaluates data from 1999 till 2004, an increase ofthe CPI score by one (10)[7] point(s) results in an increase in the yearly GDP per capita of about 1,7%. When assessing only transitioning6 Euro­pean countries a one-point increase even yields 2,4% more GDP per capita (ibid.).

The strong correlation between GDP per capita and CPI becomes obvious by taking a look on the previous world map. Besides the severe economic consequences which are interconnected with a low CPI score, there are also straightforward civil rights is­sues. Transparency International reports that out of the 3687 journalists who have been killed worldwide between 2012 and 2017 more than 95% have been murdered in coun­tries which score below the CPI average. Furthermore, 70 of the 368 killed journalists were investigating corruptive behavior (Transparency International, 2018).

Besides the perceived level of corruption, it is also important to understand where the majority of corrupt behaviors occur. The subsequent graph lists the institutions which are most likely to be affected by any form of corruption (Transparency International, 2013).

Corruption by institution

Abbildung in dieser Leseprobe nicht enthalten

2.4.1 Limitations of Measurements of Corruption

Since corruption is often times an illegal act, determining and quantifying its costs be­comes intensely challenging and vague. Consequently, the prevailing method in the academic literature is tracking the perception of corruption (Olken, 2009). Conse­quently, the CPI (Lambsdorff, 2005) became undoubtedly the most eminent gauge of corruption worldwide. However, due to its perceptive nature the CPI as the main de­terminant for corruption is confronted with doubts to which level the index represents the true level of corruption.

A study by Olken (2009) however, finds some statistic evidence for a correlation be­tween the perceived levels of corruption and the actual measured corruption. The au­thor therefore calculates the real costs for a road building project in Indonesia and compares it with the costs which were officially indicated. The difference between both expenses must have been artificially created either through overestimated pricing and or excess material. Households (n= 3.500) in proximity to the road projects have been asked to evaluate corruption in this infrastructure project. The awareness of corruption of the surveyed participants was positively linked with the actual magnitude corruption. However, this correlation also comes with its limitations. Olken also discovers that per­sons in heterogenous communities tend to distrust their fellow citizens.8 Lesser levels oftrust might therefore intensify the perceived corruption in a given group.9

The statistics which are used in order to estimate costs of corruption typically come from one of the two sources:

1. Perception surveys: professional assessments or open surveys
2. Direct observations: administrative records and audits

The foremost problem which is inherit to the perception surveys is the unclear definition of corruption and its effect on the responds of the surveyed persons. Some surveyed participants might have a completely different perception of corruption than others. Es­pecially results comparing different countries become consequently prone to flaws and hard to compare.

The direct observation comes likewise with its limitations. Corruptive behaviour which is tracked by law enforcement most probably only represents a small fraction of all the corruptive activities in a given country. This limitation gets even more relevant when the different law enforcement systems in the distinctive countries are considered.

Despite the stated imperfections regarding the data quality, both of the mentioned methods deserve their merit within in their scope of suitable application. Using data which stems from direct observation is perfectly reasonable when the institutions and law enforcements entities are subject to the same laws and regulations.10

2.4.2 Magnitude of Corruption

Quantifying the exact costs of corruption is, as described in the previous chapter, ex­tremely tedious and even vague. The International Monetary Fund (hereinafter referred to as IMF) estimates the total costs of corruption to be around $1.5 to $2 trillion each year11 (Kaufmann, 2005; IMF, 2016). This estimation refers just to bribery alone, the total consequences of all different facets of corruption are most probably even worse. This fact alone highlights which detrimental effects corruption has on the global econ­omy and welfare overall (ibid.). Extremely problematic is furthermore the point, that corruption seems to hamper economic growth in general. A tragic example for this is the continent of Africa. It ranks continuously the worst in the CPI and estimates from the Economic Commission of Africa (2016) approximate the total costs of corruption in Africa to about 25 % of its total GDP. The next chapter is going to shed some light on the corruption growth nexus and provides a distilled summary over the most important findings in the scientific literature.

2.5 Causes of corruption

There are several factors which influence the magnitude of corruption in a direct or rather indirect manner. Those causes are extremely diverse not only in their nature but also in their expected effect on corruption in general. Many studies have examined causes of corruption and tried to decipher what specific factors and ramification facili­tate corruption. However, there seems to be a general dissension whether some of the factors are rather causes or effects ofcorruption (Enste and Heldman, 2017). It is also worth mentioning that, since many of the studies use measures for perceived level of corruption12, especially results from cross country studies have to be viewed with cau­tion (Tanzi, 1998). Fortunately, there is an existing strand of literature which accounted for this possible bias and presents robust findings13. The following chapters are going to walk through the main causes of corruption.

2.5.1 Natural Resource Endowment

More and more empirical studies are noticing the nexus between corruption and en­dowment of natural resources as a subject worthy of academic consideration. The lit­erature dealing with the aforementioned connection is of major importance especially for an assessment of developing countries due to the high reliance on natural re­sources in the respective countries14.

Intuitively one might think that a large endowment with natural resources such as oil gas or gemstones, should grant countries an advantage and help them foster their economic development. However, archetypically, one of the most commonly described theories regarding natural resources endowment and the development of the related economy is the “resource curse”. First portrayed by Richard Auty in 1993 the resource curse has to this point been investigated by a large number of economists (Auty, 2002).The underlying principle is, that countries which are endowed with a sizeable portion of natural resources often cannot economically and socially benefit from them. Even it might appear paradoxical, countries which have barely any natural resources manage to surpass them regularly (Sachs and Warner, 1995).

Bhattacharyya & Hodler fitted a regression model to visualize potential correlations between an abundancy of natural resources and key figures for political corruptness. The authors certainly found evidence that the levels of corruption tend to be more de­veloped in countries which are endowed with a huge share of natural resources. Fur­thermore, they revealed, with the help of a game theoretical approach, that enlarged resource rents correlate with increased levels of corruption just if the constitution of the domestic democratic government is in a very bad condition. Consequently, the authors identified democratization as a viable instrument to fight corruption in those high-re­source countries (Bhattacharyya and Hodler, 2010).

Further research from Okada et al., focused especially on the relationship between oil rents and corruption. Their study, a quantile regression study, indicated a correlation between higher oil rents and enlarged levels of corruption. Interestingly, the influences of other natural resources besides oil (gold, iron, copper) were not from statistical im­portance in their model. The authors justify this with the fact that the countries which are rich in gold, iron and copper are largely located in the sub Saharan region where corruption is already omnipresent (Okada and Samreth, 2017).

Zhan focused his research on the effects of resource endowment and corruption es­pecially in China. His discoveries also emphasized a correlation between corruption and resource abundant regions. The creator also named the insufficiencies of the Chi­nese governmental commercial system as an important factor which promotes corrup­tion (Zhan, 2017)

The paper from Leite and Weidmann focuses on the effects of increased rent seeking activities due to a large endowment of natural resources and which effects this has on the corruption level. Similar to the other findings of later research, the authors found evidence that huge amounts of natural resources indeed tend to rise the levels of cor­ruption. Furthermore, their findings highlight yet again the importance of strong and reliable political institutions to combat corruption (Leite and Weidmann, 1999).

Aslaksen explored in her research that, both oil extraction as well as the general min­eral income are very likely to be linked with increased levels of corruption. Interestingly, the effect for oil holds true for democratic as well as non-democratic countries. The effects of corruption seem to be primarily noticeable in the government (Aslaksen, 2007).

Additional research from Kronenberg also investigated, amongst other things, the cor­relation between natural resource abundance and corruption. Repeatedly, a strong correlation between the two variables was obtainable (Kronenberg, 2004).

Busse et al., also found clear evidence for the linkage between corruption and natural resources. This regression was overall robust and statistically significant. However, the effects of high resource exports on quality of bureaucracy, as well as the effects on law and order were not that robust respectively not obtainable at all. This underlines once again the distinct coherence between an abundance of natural resources and corrup­tion (Busse and Groning, 2013).

Conclusively, the concordant opinion of the reviewed literature, undeniably perceives a correlation between high resource countries and corruption. The sheer value of the resources alone makes them prone for any kind of corruption. The temptation of fast and easy rent seeking opportunities seems to act like a curse for the natural resources under distinctive political conditions. While there are certainly differences between the various resources and their effects on corruption, especially large oil corks seem to drive corruption levels explicitly.

“Rents on oil are obviously much largerthan rents on agricultural commodities, and this may be why oil is differentially important in conflict risk” (Collier and Hoeffler, 2005, p. 628)

2.5.2 Shadow Economy

Similar to the resource endowment, the effects of the shadow economy15 on corruption have likewise been subject to a multitude of scientific investigations. Hereby, there seems to be a well-defined correlation between the size of shadow economy and the CPI (Schneider, 2012).

A viable way to estimate the consequences of an expanded shadow economy on cor­ruption is to track the deviations in tax returns. Friedmann and colleagues emphasized the negative effect of corruption on tax profits. Due to the higher (real) tax load firms tend not to shift their business into the unofficial economy and consequently evade taxation. This leads to an inferior overall tax returns for the government with all its negative consequences (Friedman etal., 2000).

Schneider and Buehn revealed, that in wealthier countries the connection between the size of the shadow economy and corruption is positively correlated, thus the shadow economy reduced corruptive behavior in those given countries. The exact opposite was observed for poor and deprived states, in those countries the shadow economy facilitated corruption (Buehn and Schneider, 2009).

Consequently, with the previous findings in mind, is it from major importance to distin­guish between high- and low-income countries whenever the connection between the shadow economy and corruption is examined. In countries which are plagued by pov­erty, corruption might be a “compliment” to the shadow economy. However in rather rich countries, which offer a considerable amount of public goods and services, cor­ruption may be rather a substitute to the shadow economy (Dreher and Schneider, 2010). Scientific evidence therefore is provided by different authors. Choi and Thum's (2005) hypothesis which describes the shadow market and corruption as substitutes has been confirmed in a subsequent report (Dreher et al.,2009). Dell’Anno and Teobaldelli (2015) analyzed 145 countries and discovered a positive correlation be­tween the size of the shadow economy and corruptive behavior.

Conclusively, the literature offers robust empirical backing for the interconnection be­tween corruption and the shadow economy. However, it remains unclear if this con­nection is reciprocal or how the causation needs to be interpreted (Enste and Heldman, 2017).

2.5.3 Wages

Archetypically, it is assumed, that higher salaries lead to lower rates of corruption. Due to the stable income, the necessity for corruptive behavior diminishes.

Van Rijckeghem and Weder (1997) confirmed this hypothesis. Their paper finds a cor­relation between higherwages and lower rates ofcorruption in emerging countries. In a later review, the authors once again confirmed the connection between higherwages and lower corruption markers16. Even though, they point out, that in order to remove

[...]


1 Defined as a situation in which the citizens income is too low to save and invest, and this low level of investment results in low rate ofgrowth in a national context (Nelson, 1956).

2 Only crime (83%) has been named more frequently than corruption (76%) as a major threat (PEW, 2014)

3 Typically, somebody with authority e.g. members or the government etc.

4 Normally a representative ofthe public

5 For instance, due to too high monitoring costs

6 Typically, countries which are shifting towards a more market oriented system are called transitioning economies (Protsenko, 2004).

7 The cited primary source for the number of murdered journalists states that there were 377 killed journalist in that given timeframe (Committee to Protect Journalists, 2018)

8 The effect was reportedly vice versa for homogenous communities, the author found increased trust within those neighborhoods

9 These findings are also congruent with those of La Porta et al. (1999)

10 Typically done in intra country studies for instance (Glaeser and Saks, 2006; Ferraz and Finan, 2011)

11 Equals about 2% of the total global GDP (Kaufmann, 2005)

12 Which might vary considerably between different countries

13 For instance, through comparing countries from a comparable social and ethnic context.

14 For a comparison please refer to Figure 9.

15 Defined as “the market-based production ofgoods and services, whether illegal or legal that es­capes detection in the official estimates ofthe GDP” (Schneider and Enste, 2013)

16 Similar findings are also presented by (Azfar and Nelson, 2007)

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Details

Title
Corruption and foreign direct investments in developing countries
College
University of Paderborn
Grade
1,7
Author
Year
2019
Pages
72
Catalog Number
V536745
ISBN (eBook)
9783346133939
ISBN (Book)
9783346133946
Language
English
Keywords
corruption
Quote paper
Jens Nolte (Author), 2019, Corruption and foreign direct investments in developing countries, Munich, GRIN Verlag, https://www.grin.com/document/536745

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