Economic freedom and the effects of
corruption in Latin
America
After decades of economic management with solid social progress,
Latin America has reached certain levels of development. This improvement of
social and economic conditions over time might improve the national level of
corruption perception, even though the region consistently performs poorly in
the CPI (corruption perception index). Recently much attention has been devoted
to testing the relationship between economic freedom and corruption, with the
assumption that economic freedom leads to reduce level of corruption. Thus,
this paper examines the effect of economic freedom and economic globalization
on corruption perception across the Latin American region over the period 1995
to 2013, since I believe that political and trade liberalization lead to a
decrease in corruption.
As part of the globalization
process and as a response to the Latin American debt crisis, the region moved
toward political and trade reform during the 80s and 90s. The economic effects
of economic reforms have been subject of complex and holistic studies. However,
the analysis of the effect on components of corruption perception is limited.
Even though economists have argued that lack of competition
fosters corruption and empirical findings confirm that
democracy and economic freedom alone does reduce corruption; there is no
cross-country study which captures the interaction effect of these two factors
in Latin America over time. Therefore, this paper pretends to fill this gap of
analysis due to the fact that economic freedom and corruption are factors that
undermine the development growth of the region.
The theory and literature suggest that among the most corrupt
nations, greater economic freedom does not reduce corruption and may even
exacerbate it, because nations respond differently to levels of economic
freedom, depending on their level or stage of development conditions (Billger et
al, 2009). Thus, the effect of economic freedom on corruption may depend on how
efficient government intervention is in countries which are more highly
“regulated” or “have high levels of economic freedom”. In line with this
argument, Giavazzi and Tabellini (2005), who use panel
data to look at the relationship between economic and political liberalizations
and their effects on growth, investment, inflation, institutional quality, and
corruption find that in isolation, increased economic and political
liberalization decrease corruption. Therefore, greater openness may reduce
corruption, but the more corruption there is, the more rent-generating trade
barriers there will be (Treisman, 2000). The degree to which a country
is open to trade, then, is clearly endogenous; however, whether or not a
country is open to trade, as well as whether the country decides to liberalize
or not, is less likely to depend on the perceived levels of corruption.
Now focusing on Latin America, in order to examine the effect
of economic freedom on corruption perception, I use data from the World Bank
and the Quality of Governance Institute for the 20 countries of the Latin
America region for the period 1995 to 2013. In this case, corruption perception
(CPI) is the depended variable of the model
and the main independent variables are economic freedom and economic
globalization. Also, since I’m using the CPI I might include measurements of
political participation and income size (GDP per capita) because they can cause
a variation on CPI and economic freedom .(for more details see table B).
Furthermore, in order to
have some idea of the probable relation with corruption, Figure A shows the Economic
Freedom index and the CPI corruption index across the 20 countries of the Latin American region for the year
2000, and illustrates the clear positive association between the indices,
implying that higher economic freedom is associated with lower corruption
Additionally, I examine the
relationship of economic freedom and their interaction effect on corruption
using Pooled Time-Series Cross-national Regressions with Fixed Effects[1].
I regress corruption (log) on prior corruption and prior scores of the Independent
variables. Table A. presents the results.
I found that using previous years of corruption perception, on average and
controlling for Trade freedom index (column 2) 1% increase on economic freedom
is associated with a reduction of 17% of corruption perception index. The
results is statistical significant. However, even though the results confirm the
hypothesis that Economic freedom reduces corruption perception; the results are
not always significant. Column 1 shows that controlling for other variables
such as income, political participation and economic globalization, economic freedom
index does not have statistical significant on corruption perception. The only variable
that remains significant is the Income. In this sense, it may be suggested that
economic size (Income) is also associated with a decrease on levels of corruption
perception with statistical significance.
Table
A. Pooled Time-Series Cross-national Regressions with Fixed Effects.
(1 year
Lag)
DV: Corruption Perception (log),
from 1995 to 2013
|
(1)
|
(2)
|
(3)
|
Corruption Perception (Log)
|
0.61***
|
0.62***
|
0.64***
|
(13.91)
|
(15.40)
|
(15.68)
|
|
Economic Freedom Index (Log)
|
-0.17
|
-0.17*
|
-0.17*
|
(-1.80)
|
(-2.46)
|
(-2.37)
|
|
Income (GDP) (Log)
|
-0.049*
|
||
(-2.01)
|
|||
Political Participation (Log)
|
0.034
|
||
(0.73)
|
|||
Economic Globalization
|
-0.00039
|
||
(-0.31)
|
|||
Trade Freedom Index (Log)
|
0.24**
|
0.18**
|
|
(2.96)
|
(3.28)
|
||
Constant
|
0.55
|
0.41
|
1.13***
|
(1.21)
|
(1.14)
|
(3.91)
|
|
R-squared
|
0.41
|
0.43
|
0.41
|
Observations
|
276
|
325
|
325
|
Note: Absolute value of t statistics in
parentheses. * p < 0.05, ** p < 0.01,
*** p < 0.001
It is important to note that
while cross-country time series regressions of economic freedom and corruption
give results in line with the argument that corruption is reduced by an
increase in economic freedom, this may hide heterogeneity at sectoral level,
particularly in the degree and nature of government intervention (Graeff et al, 2003). In
other words, I notice an ambiguous correlation among the components of
economic freedom and corruption. This suggests that the weight of the
components of the aggregate index influences the effect on corruption, implying
that the results are sample-sensitive.
In summary, this paper assesses the
effect that economic freedom has on corruption perception across Latin America.
I found a linear relationship that supports the hypothesis that trade
liberalization leads to a decrease on perception corruption since the results
are statistical significant. Therefore, I might think that, after the trade and
openness reforms in the 80’s and 90’s, the region trends to reduce the
corruption perception. However, the historic trend of high corruption
perception on countries of this region may cause the slowly change on
corruption perception. It is likely that as long as in the region enters into
the global economy, the level of corruption would decrease.
Bibliography
* Pieronia, L.; d'Agostinob,
G. (2013). Corruption and the effects of economic freedom. European Journal of Political Economy. Volume 29, March 2013, Pages 54–72. Retrieved from: http://www.sciencedirect.com/science/article/pii/S0176268012000456?np=y
* Costa Tavares, Samia (2007). Do rapid
political and trade liberalizations increase
corruption?. European Journal of Political Economy. Volume 23, Issue 4, December
2007, Pages 1053–1076. Retrieved from: http://www.sciencedirect.com/science/article/pii/S017626800600053X
Appendix
Table
B. Descriptive Statistics
Variables
|
Mean
|
Std. Dev.
|
Min.
|
Max.
|
Detail
|
Economic Freedom Index
|
57.80
|
9.94
|
19.5
|
85.3
|
Index
score range from 0 to 100, where 100 represents the maximum economic freedom
|
Corruption perception index
(CPI)
|
3.44
|
1.39
|
1.4
|
7.9
|
10-point
scale in which a score of 10 indicates very little corruption and a score of
0 indicates a very corrupt government.
|
Economic Globalization
|
57.80
|
9.94
|
19.5
|
85.3
|
Scale from 0 for non-flows of
trade and investments and 100 for highly integration to global economy
|
Trade freedom
|
70.51
|
8.29
|
44.4
|
88.0
|
Index
scores range from 0 for minimum degree of trade freedom to 100 for maximum
degree of trade freedom.
|
Income
|
3928.10
|
2707.84
|
314.2
|
13559.1
|
GDP
per capita in current US$
|
Political participation
|
0.41
|
6.00
|
-99.0
|
1.0
|
Index scores range from 0 for completely
absent or disrespected political participation rights to 1 for their full
presence and respect
|
Observations
|
277
|
Table C. Hausman Test
(b)
|
(B)
|
(b-B)
|
|
Fixed
|
Random
|
Difference
|
|
Economic freedom (log)
|
-.1652047
|
-.0019991
|
-.1632057
|
Income (GDP) (log)
|
-.0492979
|
.0146905
|
-.0639884
|
Political Participation (log)
|
.0335217
|
.0788459
|
-.0453242
|
Economic Globalization
|
-.0003927
|
.0004396
|
-.0008323
|
Trade freedom (log)
|
.23913
|
.0992944
|
.1398356
|
Chi2(6) =
|
79.23
|
||
Prob>Chi2 =
|
0.0000
|
**Luz Angela Serrano
** SIS-750- Spring 2015
**Blogpost 2
**********
* Preamble
set
more off
ssc
install estout
cd
"G:\"
**What is the effect of trade freedom and economic
globalization on corruption across LA?
** ID: Economic freedom index: eco_freedom
** ID: Economic globalization: dr_eg
** DV: Corruption perception: corrup_index
** Z1: Income: gdp_pp
** Z2: Political participation: political_p
*Test for skew:
sktest
corrup_index eco_freedom dr_eg gdp_pp political_p eco_freedom
sum
corrup_index eco_freedom dr_eg gdp_pp political_p, detail
* Transforms variables,
gen
log_gdp = ln(gdp_pp)
gen
log_trade = ln(fr_trade)
gen
log_politics = ln(political_p)
gen
log_corrup = ln(corrup_index)
gen
log_eco_freedom = ln(eco_freedom)
**Use panel data
encode country, gen(country1)
xtset country1 year
sort country1 year
***Estimate the CSTS model w/FE estimator (with lag DV)
xtreg log_corrup l1.log_corrup l1.log_eco_freedom l1.log_gdp
l1.log_politics l1.dr_eg l1.log_trade, fe
* Test for the appropriateness of RE vs FE (Hausman test)
xtreg
log_corrup l1.log_corrup l1.log_eco_freedom l1.log_gdp l1.log_politics l1.dr_eg
l1.log_trade, fe
estimates
store fixed
xtreg
log_corrup l1.log_corrup l1.log_eco_freedom l1.log_gdp l1.log_politics l1.dr_eg
l1.log_trade, re
estimates
store random
hausman
fixed random // note that p<0.05. MUST USE FE!!! RE BAD!
**** Table (regression).
quietly xtreg log_corrup l1.log_corrup l1.log_eco_freedom
l1.log_gdp l1.log_politics l1.dr_eg l1.log_trade, fe //
eststo clear
eststo:
quietly xtreg log_corrup l1.log_corrup l1.log_eco_freedom l1.log_gdp
l1.log_politics l1.dr_eg l1.log_trade, fe
eststo:
quietly xtreg log_corrup l1.log_corrup l1.log_eco_freedom l1.log_trade, fe
eststo:
quietly xtreg log_corrup l1.log_corrup l1.log_eco_freedom, fe
esttab
using file_name1.rtf, replace label /// creates a table in the file
"file_name1.rtf"
stats(r2_a
N, fmt(2 0) labels("R-squared" "Observations")) /// adds
R-sq and N
legend
varlabels(_cons Constant) ///
addnote("Note:
Absolute value of t statistics in parentheses.") ///
b(a2)
t(2) /// "b(a2)" will allow the slope coefficient to go to 2
significant digits if necessary. **only 2 decimals for each number.
title({\b
Table 1. Pooled Time-Series Cross-national Regressions, with Fixed Effects})
eststo
clear
***Table: Descriptive statistics
eststo clear
estpost
tabstat dr_eg eco_freedom corrup_index gdp_pp political_p, ///
listwise
statistics(mean sd min max) columns(statistics)
esttab
using ps4sum.rtf, replace label ///
cells("mean(fmt(2)
label(Mean)) sd(fmt(2) label(Std. Dev.)) min(fmt(1) label(Min.)) max(fmt(1)
label(Max.))") ///
nonumbers
extracols(5) ///
title({\b
Table 1. Summary Statistics})
eststo
clear
*** Question: Does economic freedom impact in corruption
perception (2000)?
* Inspect the variables
codebook
corrup_index eco_freedom
* Is there evidence of covariation?
twoway
(scatter corrup_index eco_freedom) (lowess corrup_index eco_freedom) (lfit corrup_index
eco_freedom)
*Is
the line a good representation of the non-parametric regression? NO!
twoway
(scatter log_corrup log_eco_freedom) (lowess log_corrup log_eco_freedom) (lfit
log_corrup log_eco_freedom)
* Estimate the regression of log(Y) on log(X): log(Yi) =
alpha + beta(log(Xi)) +ui (reg logY logX)
*
H0: beta=0; HA: beta!=0
reg
log_corrup log_eco_freedom
* Display your estimates! reg logY logX; pred yhat; gen
ylin=exp(yhat); (line ylin X, sort)
reg
log_corrup log_eco_freedom
predict
mort_hat
gen
mort_lin = exp(mort_hat)
twoway
(scatter corrup_index eco_freedom) (lowess corrup_index eco_freedom) (line
mort_lin eco_freedom, sort)
twoway (scatter corrup_index eco_freedom, jitter(2)
msize(small) mcolor(black)) ///
(lowess
corrup_index eco_freedom, lcolor(blue) lpattern(dash)), ///
title("Figure
A. Effect of Economic Freedom Index on Corruption perception",
size(medium) color(black)) legend(off), ///
(line
mort_lin eco_freedom, sort clcolor(red)), ///
ytitle("Corruption
Perception Index (CPI)", size(small)) ///
xtitle("Economic
Freedom Index", size(small)) ///
note("Source:
World Bank World Development Indicators and Quality of Governance",
size(vsmall)) ///
caption("Note:
Dashed line is lowess estimate (bandwidth = 0.7). Solid line is OLS
prediction", size(vsmall)) ///
graphregion(fcolor(white)
lcolor(white)) ///
plotregion(fcolor(white)
lcolor(black)) //
[1] I used
the Hausman test to determine the appropriateness of Fix Effects over Random
Effects. The model includes
country fixed-effects (p<0.05) to allow any trends in corruption perception to vary from
country to country. (without fixed-effects, the results are unchanged)
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