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Corruption & Shadow Economy

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Ingrid Lamperstorfer

on 10 June 2013

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Transcript of Corruption & Shadow Economy

photo credit Nasa / Goddard Space Flight Center / Reto Stöckli Emanuela Perinetti & Ingrid Lamperstorfer Corruption & Shadow Economy Introduction Two different issues with common characteristics:

- powered by an unhealthy culture of secrecy
- related to economic growth & development
- widespread around the world Corruption 1/3 Eight Questions about Corruption
Jakob Svensson

Journal of Economic Perspectives
—Volume 19, Number 3—
Summer 2005 1
What is corruption? No definition of corruption is completely clear-cut

The emphasis in this paper is on public corruption

A common definition of public corruption is the misuse of public office for private gain 2
Which countries are the most corrupt? 3
What are the Common Characteristics
of Countries with High Corruption? a) Income level
b) Human Capital
c) Openess
d) Institutional Factors Corruption
a) Income Level b) Human Capital c) Openess d) Regulation of Entry 4
What is the magnitude
of corruption? Literature on quantifying corruption is still at its infancy and the existing contributions are often context specific

The magnitude of corruption had to be assessed using anecdotal or case-study evidences
- Surveys (UGANDA , Svensson 2003)
- Price Comparisons (ARGENTINA, Di Tella 2003) 5
Do Higher Wages for Bureaucrats Reduce Corruption? Historical example of this policy (Sweden, Lindbeck 1975)

Ambiguous systematic evidence on the relationship:
In cross-country studies, Rauch and Evans (2000) and Treisman (2000) find no robust evidence that higher wages deter corruption, while Van Rijckeghem and Weder (2001) find that it does.

The effectiveness depends on the existence of an honest third party that can monitor the agent (ARGENTINA,Di Tella 2003) 6
Can Competition
Reduce Corruption? Increase competition among firms = no excess profits from which to pay bribes (Ades and Di Tella,1999)

However, the connections between competition, profits and corruption are complex

Thus, deregulation may reduce corruption not so much by increasing competition, but by reducing the extent to which public officials have the power to extract bribes. 7
Why Have There Been So Few (Recent)
Successful Attempts To Fight Corruption? The vicious cycle of the enforcement of rules and regulations

Hong Kong and Singapore successfull cases:
- anti corruption agency
- reforms
- political leadership commitment
- citizens enforcement & access to information 8
Does Corruption Adversely
Affect Growth? “Efficient Corruption”: It could conceivably have a positive effect on economic growth (Leff, 1964 - Lui, 1985)

Other theories link corruption to slower economic growth:

a) corruption and growth at the micro level (Svensson 2001, Evidences from Uganda): Both the rate of taxation and bribery are negatively correlated with firm growth.

1 percentage point increase in the bribery rate is associated with a reduction in firm growth of 3 percentage points, an effect that is about 3 times greater than that of taxation b) corruption and growth at the macro level Findings seem to lead to a puzzle:

Case studies and micro evidences suggest that corruption severely retards development

But to the extent we can measure corruption in a cross-country setting, it does not affect growth
- Econometric problems
- Many forms not equally harmful for growth

- Indirect Effects Corruption and Economic Growth
Pak Hung Mo

School of Business, Hong Kong Baptist University
November 8, 1999 Based on the ideas of previous researchers and employing data similar to Mauro (1995), a new analytical framework to estimate the effects of corruption and the channels through which it affects the rate of GDP growth

The channels under consideration include:
- investment
- human capital
- political instability Data & Estimations Period from 1970 to 1985

The measure of the corruption from the Transparency Int. Corruption Perception Index

46 observations in regressions
Ordinary least squares method (OLS) Analysis of all plausible channels simultaneously Conclusions This new perspective generates the estimations of the impact of corruption on growth and the relative importance of the channels of transmission.

A 1% increase in the corruption level reduces the growth rate by about 0.72% or, expressed differently, a one-unit increase in the corruption index reduces the growth rate by 0.545 percentage points.

Political instability = the most important channel. It accounts for about 53% of the overall effect. Lobbying, Corruption and Political Influence

Nauro F. Campos
Brunel University, CEPR and IZA Bonn 

Francesco Giovannoni
CMPO, University of Bristol Conclusions Lobbying is the preferred mean for exerting political influence in rich countries and payment of bribes the preferred one in poor countries

This paper provides a theoretical framework that focus on the relationship between lobbying and corruption

Lobbying can be both an activity that makes bribing irrelevant if it succeeds in influencing policy and an activity that makes bribing easier if it succeeds in undermining law enforcement.

In other words, lobbying can be a substitute for, or a complement to, corruption.

1999 survey data for 3,954 firms in 25 transition economies Abstract (a) what are the factors that determine the likelihood of a firm being a member of a lobby group?

(b) what is the relative role of corruption and lobby membership in explaining the probability of a firm seeing itself as influential vis-à-vis government laws, regulations and policies? Results Positive correlation between firm-level corruption and per capita GDP A negative relationship between aggregate corruption and per capita GDP ( -7) Abstract Corruption 2/3 Corruption 3/3 The dependent variable in both cases is a dichotomous variable

In question (a), it takes the value of 1 if the firm is a lobby member and of zero if not

In question (b) it takes the value of 1 if the firm perceives itself as influential, zero otherwise Additional questions: - lobbying is more effective for large companies
- large lobbying groups with few members are more effective
- firms that are foreigner owned = higher probability of joining lobby group
- Economic development leads to seeing lobbyin more positive
- Companies in the capital of a country are more likely to join lobby group
- Corruption has a negative significant impact on decision
- Stable political systems have a significant positive impact Conclusion Data of 4000 firms from 25 conomies was used.
Main finding: Joining a lobby groups is positively correlated to the frims size and economic development.

Firms who join a lobby see themselves as more
able to influence decision makers by:
- a lobby group’s ability to exert influence is very big
- that while lobbying may be increasingly effective as a country develops (that is, becomes richer), it already matters a lot even in less developed (in our case, transition) countries.
- firms believe lobbying is more effective then corruption Shadow Economy 1/2 New Estimates for the Shadow Economies all over the World

Friedrich Schneider, Andreas Buehen &Claudio. E. Montenegro

Research in Shadow Economy is a scientific passion for knowing the unknown! Goals of Paper: •To undertake the challenging task of estimating the shadow economy for 162 countries all over the world

•To provide some insights into the main causes of the shadow economy and a unique database of the size and trends of the shadow economy for 162 countries between 1999 and 2007

•Explicit goal to have comparable results by using the MIMIC estimation Definition Shadow Economy The shadow economy includes all market-based legal production of goods and services that are deliberately concealed from public authorities to avoid payment of income, value added or other taxes; to avoid payment of social security contributions; having to meet certain legal labor market standards, such as minimum wages, maximum working hours, safety standards, etc; and complying with certain administrative procedures, such as completing statistical questionnaires or administrative forms. Intensity of Regulations More regulations = less freedom = increase Shadow Economy

The following causal variables are used:
•Business freedom: measure the time and efforts of business activity (negative sing expected)
•Economic freedom (negative sign expected)
•Regulatory quality, includes market unfriendly policies, such as price controls or inadequate bank supervision (negative sign expected) Public Sector Services Increase Shadow Economy = increase in tax rates & worse quality of public goods (infrastructure)

The following causal variables are used:
•Government effectiveness from the World Ban´s Worldwide Governance Indicators. (negative sign expected) Official Economy Situation of official economy = crucial role whether people work or do not work in Shadow Economy
Usually during recession = increase Shadow Economy

The following causal variables are used:
•GDP per capita based on Purchasing Power Parity (PPP) (negative sing expected)
•Unemployment rate Total unemployment in percentage of total labor force (positive sign expected)
•Inflation rate (positive sign expected)
•Openness corresponding to trade (negative sign expected) Monetary Indicators People who work in Shadow Economy do not want to be traced = payment is in cash

The following indicators are used:
•M1 is M0 plus deposits
•Currency/M2 this is corresponding to the currency outside the banks as a proportion of M2 Labor Market Indicators Shadow economy has huge impact on labor market

The following indicators are used:
•Labor force participation rate
•Growth rate of the total labor force
Shadow economy is also reflected in the official economy

The following indicators are used:
•GDP per capita
•Growth rate of GDP per capita per anno State of the Official Economy Size of the Shadow Economy for 162 Countries Estimating size & trend = difficult

Model used = Multiple Indicators Multiple Causes (MIMIC)
- structural equation Model (SEM)
- examines relationships between unobserved variables
- Goals:
- measuring the relationship of a set of observed causes & indicators to SE
- testing if the researchers theory/hypotheses fit the data Econometric Results Size of Shadow Economies for 162 Countries from 1999 to 2007 MIMIC = relatively estimated sizes
To calculate size & Trend:
- MIMIC --> real world figures
- benchmarking or calibration
- MIMIC index + structural equation =index into absolute values base year is 2000 Results according World Bank regions Conclusions Estimation of size & trend of SE of 162 countries was made
MIMIC model & benchmarking procedure for calibrating was done lead to 3 conclusions:
- all countries reached a large size of weighted average of 17.1%of official GDP over 162 countries over 1999 to 2007. luckily there is a negative trend of Shadow Economy

- Shadow Economy is a complex phenomenon which exists in developing, transition and highly developed countries for different reasons most important reason government action (taxation & regulation)

- there are regional disparities in the level of informality, but obvious regional clusters. Shadow Economy 2/2 Shadow Economy - The Impact of Regulation in OECD-countries

Dominik H. Enste Introduction Recent findings lead to a further analysis of the influencing factors on the size of Shadow Economy.
With a focus on those recent findings hypotheses wer developed.
Subsequently, the structure of the regulation index and some findings of the impact of regulation on official labor force were described.
Then the link between Shadow Economic activities, regulations, the quality of institutions and several control variables was explored through multivariate analysis. Hypotheses 1. Overall regulation: The most intense is the overall regulation in a country, the larger is the shadow economy, ceteris paribus.

2. Labor: The more intense labor regulation is in a country, the larger is the shadow economy, ceteris paribus.

3. Product market regulation: The more intense product market regulation is in a country, the larger is the shadow economy, ceteris paribus.

4. Quality of official institutions: Several studies show that better official institutions lead to smaller shadow economies, ceteris paribus. Control variables C1-5 Chosen base on the results of 30 studies by Kröner & Strotmann, Schneider & Enste:

C1 - Tax burden: measured based on total tay & social wedge of an average single earner + VAT
higher tax burden = larger SE = positive impact

C2- Tax morale: less civic virtue and loyalty toward public institutions + a declining tax morale because of corruption and poor quality of public institutions
better tax morale = smaller SE = negative impact

C3-GNP per capita: main findings in many studies; show poorer countries have bigger SE
higher GNP per capita = smaller SE = negative impact

C4-Unemployment rate: relationship between SE and unemployment rate is ambiguous
higher unemployment rate = larger SE = positive impact Definition of Shadow Economy used: In general, the shadow economy can be seen as the decision of individuals and firms for economic activity against official norms, formal institutions and regulations. From the economic policy’s point of view, those shadow economic activities are particularly relevant, as they create additional value and are basically based on voluntary contracts between two persons (e.g. illicit work). The shadow economy includes unreported income resulting from the production of legal goods and services, either from monetary or barter transactions – and, hence, includes all economic activities that would generally be taxable were they reported to the (tax) authorities. Results Measuring Regulation Density Estimates of the Impact of Regulation on Shadow Economies - Regulation and Shadow Economy Estimates of the Impact of Regulation on Shadow Economies - Quality Institutions and Shadow Economy Results of Random Effects Models 1. Overall Regulation: Regulation has a positive impact on the size of the Shadow Economy.

2. Labor and product market regulation: More regulation of labor or product markets lead to more irregular activities.

4. Tax burden: Is all models used tax burden has a significant influence on the size of Shadow Economy.

5. Tax morale: has significant influence in all models. the higher the tax morale, the smaller the size of the Shadow Economy

6. GNP per capita: is relevant for the size of SE in poorer countries than in wealthier countries

7. Unemployment rate: Higher unemployment rate is related to a larger Shadow Economy

8. Quality of institutions: is not significant in the random models because its strongly correlated with the regulation. Results Graph Conclusion Using a comprehensive regulation index covering five major fields (labor, product and capital market; education/innovation and the quality of institutions), the impact of regulation on the shadow economy has been analyzed.

The empirical results of 25 OECD countries show that regulations are – apart from tax wedge and tax morale – the main causes for the size of the Shadow economy.

The multivariate analysis as well as the simulation results show that deregulation can help to reduce the size of the Shadow Economy considerably.

The decrease of regulation density can provide additional opportunities to work, invest or innovate in the official economy and hence can boost structural change there, making the Shadow Eeconomy less attractive. Our Considerations - If secrecy is the common and underlying problem --> transparency can be a solution
- Transparency = technology
- In a globalized & networked world technology becomes a powerful engine to combat corruption
- Paper: relationship between technology, corruption & economic growth
- rethinking of regulations (quality vs quantity) Burden of tax & social security = main reason for Shadow Economy
The higher the difference of total cost of labor in the official economy & the after tax earnings = incentive for Shadow Economy
Difficult to find same criteria because tax & social security system vary from country to country

The following causal variables are used:
•Indirect taxes as proportion of total overall taxation (positive sign expected)
•Share of direct taxes (positive sign expected)
•Size of government, general government final consumption expenditures ( positive sign expected)
•Fiscal freedom (negative sign expected) Tax and Social Security Contribution Burdens The effect of corruption on growh
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