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Does Trade Liberalization Effect Energy Consumption?
Gairuzazmi M. Ghani, Department of Economics, Kulliyyah of Economics and Management
Sciences, International Islamic University Malaysia, P.O. Box 10, 50728, Kuala Lumpur,
Malaysia.
email: [email protected]
Telephone: 60-3-61964627
Abstract
The effect of trade liberalization on the environment can be directly linked to energy
consumption, because energy consumption and production are the underlying cause of most
pollutants that harm the environment. The descriptive statistics show that average annual growth
of energy consumption per capita after trade liberalization varies among countries; hence it is a
possibility that the effect of trade liberalization is conditional on factors other than liberalization
per se. The regression results show that trade liberalization per se does not effect the growth of
energy consumption of the developing countries analyzed, but its interaction with capital per
labor reduces the growth of energy consumption as capital per labor increases. However, the
effect is only significant after a certain minimum threshold level capital per labor is reached. On
the other hand, economic growth increases energy consumption and its effect is not conditioned
on trade liberalization. These two different effects mean that, with regards to energy
consumption, countries at a higher level of economic development are more likely to reap the
benefit of liberalization relative to less developed countries.
Keywords: Energy consumption; Trade liberalization.
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1. Introduction
The effects of trade openness and liberalization on the quality of the environment have been
widely examined (see Grossman and Krueger, 1993; Antweiler et al., 2001; Frankel, 2009).
However, discussion on a related issues the effect of trade liberalization on energy
consumption has been sparse, even though it is as important (Cole, 2006). Energy
consumption, especially the burning of fossil fuels is the major underlying cause of most
pollutants (Doney et al., 2009; Tan, 2009; Jacobsen, 2009). Carbon dioxide, sulfur dioxide, and
nitrogen oxides, among others, are released into the air when gasoline is burned in cars and when
electricity is generated from burning coal or natural gas. These gases harm the environment if
released uncontrollably. This means, at least partially, that the effect of trade liberalization
(henceforth liberalization) on the environment is a consequence of energy consumption. Instead
of studying the consequence, this paper examines the effect of liberalization on one of the causes
of pollutants and environmental degradation: energy consumption.1
Liberalization may affect energy consumption because it induces change in trade policies
that are related to energy use, such as reduction in tariff and non-tariff barriers on energy
efficient products. Liberalization may also affect energy consumption indirectly through changes
in economic growth, environmental regulations, implementation of ecologically beneficial
management practices, reallocation of resources, etc. It is also expected liberalization will bring
about institutional changes which will affect the transfer of energy-saving technologies that can
help to improve energy efficiency.
The method used for analysis is based on Kneller et al. (2008), Calderona and Poggio
(2010) and Ghani (2011). The method takes into account the problem of measuring liberalization
date by grouping the years of liberalization into the five-year period before, during, and after
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liberalization. This is important, as liberalization processes are usually gradual; it takes a few
years to complete instead of being a one-period shock to the economy. The method also
differentiates between liberalization, which is the exercise that leads to market openness; and
trade openness, which measures the level of market openness of an economy.
2. Background
Liberalization leads to and consists of policies that reduce and/or remove tariff and non-tariff
barriers for the free exchange of goods. It may also include policies that open up the economy to
foreign investment. It has been argued that liberalization increases economic growth and
improve welfare because of the static and dynamic gains from trade. Static gain may result from
the reduction in costs due to economies of scale, efficiency gains from exploiting comparative
advantage, reduction in distortion from imperfect competition and increased product variety.
Among the dynamics gains are the transfer and adoption of better management practices and
energy-efficient technologies. However, conclusions from theoretical and empirical studies have
been mixed on the relationship between liberalization and economic growth. Grossman and
Helpman (1991) theoretically show a positive association, while Redding (2002) shows
otherwise. Empirically, Wacziarg (2001) and Greenaway et al. (2002) estimate a positive
relationship, but Rodriguez and Rodrik (2001) argue that the positive relationship between
liberalization and economic growth is less robust than claimed. This is due to the difficulties in
measuring openness, statistical sensitivity of specifications, collinearity of protectionist policies
with other bad policies, and other econometric difficulties. Kneller et al. (2008) shows that
improvement in economic growth after liberalization episodes have been conditioned upon
myriad of factors such as level of education, human capital, and institutionals and physical
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barriers to trade. Furthermore, even if there are improvements in welfare, liberalization is
expected to create potentially difficult adjustment costs, especially in the short run.
Studies directly examine the impact of liberalization on energy consumption is sparse.
However, as most pollutants that negatively affect the environment are a consequence of energy
consumption, the effect of liberalization on energy consumption should be similar to the effect of
liberalization on the environment, and this has been studied extensively. This means that the
literature on the nexus between liberalization and the environment can be followed in postulating
the effect on energy consumption (see Cole, 2006; Hbler and Keller, 2010). Following
Grossman and Krueger (1993) and Antweiler et al. (2001), there are three ways in which the
environment can be affected by liberalization. The three ways are through changes in the growth
of the economy (scale effect), through changes in the structure of the economy (composition
effect), and through changes in the techniques and technologies used for production (techniques
effect).
These three effects influence energy consumption differently. It is posited that
liberalization will increase economic activities because of static and dynamic gains from trade.
The increase in economic activities, which increases energy consumption, is the scale effect. The
direction of the composition effect on energy consumption depends on how the structure of the
economy is affected after liberalization. And this depends on the comparative advantage of the
country. A country with comparative advantage in energy-intensive industries will increase its
energy consumption, and vice versa. In most cases, the technique effect reduces energy
consumption as improvements in technology due to technology transfer improves energy
efficiency.2
Liberalization may also induce the technique effect indirectly through the increase in
income because of static and dynamic gains from trade. Higher income may change consumer
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preferences, inducing the government to reform environmental and energy regulations such that
they benefit the environment.
The relative strength of these three different effects determines the total effect of
liberalization on energy consumption. Following the environmental Kuznet curve (EKC)
hypothesis, the relative strength of these three effects are related to the level of economic
development or income per capita of the country at a lower level of per capita income, the
scale effect generally dominates; therefore, increases in income will increase energy
consumption. At higher levels of development, structural change towards information-intensive
industries and services, coupled with increased environmental awareness, enforcement of
environmental regulations, better technology and higher environmental expenditures result in the
leveling off and gradual decline of environmental degradation (Panayotou, 1993). Using
Antweiler et al.s (2001) theoretical framework, Cole (2006) shows that trade openness increases
energy use. However, liberalization and openness are not the same, as liberalization involves the
exercises of changing policies and structure of the economy.
Liberalization may also induce the flows of foreign direct investment (FDI) into the
economy. Following the pollution haven hypothesis (PHH), reallocation of resources and
transfer of technology through FDI may lead to more energy use and/or pollution either as a
result of relocation of energy intensive and/or polluting industries from countries with strict
environmental policy or due to increased production in energy intensive and/or dirty industries
(Mukhopadhyay and Chakraborty, 2005). Using data from 20 developing countries, Mielnik and
Goldemberg (2002) shows that FDI reduces energy intensity, however, using panel data
techniques Hbler and Keller (2010) show no robust energy reducing effect of FDI inflows in
developing countries. The interactions of FDI inflows with country-specific characteristics also
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yield no significant results. One possible explanation is that the energy-saving technology
transfer from aggregate FDI inflows is too small to yield significant effects in the macro analysis.
Another important related study focuses on the impact/causality of economic growth on energy
consumption. Similarly, the results have been inconclusive; causality studies have shown both
bi-directional and unidirectional causality either from energy consumption to growth or from
growth to energy consumption (Belke et al., 2011).
The conflicting influences of liberalization on the environment and energy consumption
mean that the effect of liberalization on energy consumption requires empirical investigation.
3. Empirical Method
The method used for analysis follows the approach of Kneller et al. (2008), Calderona and
Poggio (2010) and Ghani (2011). The method takes into account countries heterogeneity in
studying the effect of liberalization on economic growth. The approach focuses on changes
within country across time for countries that have liberalized their trading regime. The empirical
model tests whether there is a difference in the growth of energy consumption in the five-year
period before, during, and after liberalization. The following base model is used: 3
Eit= 0 + 1i +2t+ 3 LIBit+it, (1)
whereEis the average growth of energy consumption for the three five-year periods. LIB is the
liberalization dummy, which equals zero for the five-year period before liberalization and equals
one for the five-year period during and after liberalization. The coefficient
3 indicates whether
the average growth of energy consumption is significantly different before and after
liberalization. If the liberalization process increases energy consumption, 3 will be positive, and
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vice versa; 1i and 2t are the country-fixed and time-fixed effects, respectively; and it is the
error term.
The time periods of liberalization are divided into: 19701974, 19751979, 19801984,
19851989, 19901994, and 19951999. For example, in the case of Albania, the liberalization
date is 1992, hence the during liberalization period is 1990-1994; the period before liberalization
is 1985-1989; and the period after liberalization is 1995-1999. The division into five-year periods
controls for the fact that liberalization exercises are usually spread over a few years instead of
being only in the year when they are announced. A period of five years is chosen because
Greenaway et al. (2002) shows that the J-curve effect, which is due to liberalization, is
completed in about five years. The division also helps in measuring medium-term effects instead
of short-term adjustments of the liberalization process. Fifty-four developing countries that have
gone through the liberalization processes since the 1970s are analyzed. The selection of countries
was subjected to data availability (see Appendix I and II for the countries and liberalization
dates).
The descriptive statistics of energy consumption for the countries studied (Table 1) show
that there are big differences in the average growth and standard deviation of energy
consumption across countries for the periods during and after liberalization; there are countries
where average energy consumption increases, but there are also countries where average energy
consumption decreases. This suggests that the impact may be conditional upon other factors,
rather than liberalization per se.
4
To take into account the variations, the paper includes the
growth of GDP per capita which captures the scale and technique effects; the interaction between
the liberalization dummy with economic growth, which help determines whether the effect of
liberalization is conditional on economic growth; the ratio of capital per labor which captures the
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composition effect; and the interaction between capital per labor with the liberalization dummy
which help determines whether the effect on liberalization is conditional on the structure of the
economy. Thus, Equation (1) becomes,
Eit= 0+ 1i + 2t+ 3LIBit+ 4Yit+ 5LIBit*Yit+ 6KLit+ 7 LIBit*KLit+ it, (2)
where Yis the growth of GDP per capita (henceforth economic growth) and KL is the capital per
labor ratio.LIB*Yis the interaction between liberalization and the growth of GDP per capita and
LIB*KL is the interaction between liberalization and capital per labor.
The data for energy consumption per capita (in kg of oil equivalent per capita) and GDP
per capita in constant 2000 U.S. dollars are from the World Banks World Development
Indicators. Ratios of capital per labor (in thousand-PPP 2000) are from the Penn World Table
extended version (Marquetti and Foley, 2008) and the liberalization dates are from Wacziarg and
Welch (2008), which is an extension of Sachs and Warner (1995).
4. Results
Table 1 reports the descriptive statistics for average growth of energy consumption before,
during and after liberalization. The arithmetic mean for the average growth of energy
consumption increases after liberalization and its standard deviation decreases. The mean growth
before liberalization is negative at -1.23% but it is positive 5-10 years after liberalization at
1.12%. The standard deviation also differs at 5.62% and 2.45% for the periods before and after
liberalization, respectively. However, there are countries where the average annual growth of
energy consumption increases after liberalization, and there are also countries where it decreases.
Before liberalization, there are 23 countries with negative average annual growth of energy
consumption, while 22 countries are positive. In the period 5-10 years after liberalization, there
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are 17 countries with average annual growth of energy consumption that are negative, while 37
countries are positive. Consequently, even if the mean increases, it cannot generally be
concluded that the growth of energy consumption increases after liberalization. The descriptive
statistics provide support for the contention that the effect of liberalization on energy
consumption may be conditional upon factors other than liberalization per se.
Table 1: Descriptive Statistics for Average Annual Growth of Energy Consumption per Capita
(%) for the Five-Year Period Before, During, and After Trade Liberalization
Before
Liberalization
During
Liberalization
After
Liberalization
Mean -1.23 -1.85 1.12Standard Deviation 5.62 5.21 2.45
Maximum 5.20 7.57 8.02Minimum -30.89 -22.20 -6.26
Number of Countries with Negative Growth* 23 35 17
Number of Countries with Positive Growth* 22 18 37Note: * Summations of countries with positive and negative growth are not equal for the period before, during and
after liberalization because of missing data for some countries.
Table 2 reports the regressions results with robust standard errors. The base regression with
country-fixed effects (column 1) shows that the growth of energy consumption is 1.9% higher
per annum for the period during and after liberalization. However, the inclusion of the time-fixed
effects (column 2) renders liberalization dummy statistically insignificant. Hence, the other
regressions (column 3-7) include both country- and time-fixed effects. Column 3 adds economic
growth to the regression; in this case, economic growth is the only significant variable, with a
value of 0.64. This means that a 1% increase in economic growth increases the growth of energy
consumption by 0.64%. The insignificant of the liberalization dummy implies that liberalization
does not influence energy consumption. However, there is a possibility that the impact of
liberalization on energy consumption is conditional upon the magnitude of economic growth;
hence in column 4 the interaction between liberalization and economic growth is included in the
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regression. Column 4 shows that except for economic growth, with a coefficient of 0.62, the
other variables are not significant. Given that there is an interaction term, the significant of the
interaction at different values of economic growth needed to be examined. Therefore, we need to
examine the conditional effect further.
Table 2: Effect of Trade Liberalization, Economic Growth and Capital per Labor on Energy
Consumption
Base
Base
E
conomic
Growth
E
conomic
Growth
Ca
pital/Labor
Ca
pital/Labor
E
conomic
G
rowth&
Ca
pital/Labor
Liberalization 0.019**(2.01)
-0.011
(-0.62)
-0.010
(-0.71)
-0.001
(-0.06)
-0.022**
(-2.55)
-0.012
(-1.45)
-0.009
(-1.08)
GDP Growth 0.639***(5.09)
0.621***
(3.55)
0.400***
(3.30)
Liberalization x
GDP Growth
0.045
(0.24)
Capital/Labor
-0.001
(-0.94)
-0.002
(-1.20)
-0.001
(-0.40)
Liberalization xCapital/Labor
-0.001**
(-2.71)
-0.001**
(-1.99)
Constant -0.026**(-2.29)
0.049
(1.45)
-0.003
(-0.11)
-0.002
(-0.10)
-0.022
(-1.49)
-0.023
(-1.67)
0.005
(0.32)
Fixed Effect Country Country& Year
Country &
Year
Country &
Year
Country
& Year
Country &
Year
Country &
Year
Observations 156 156 152 152 110 110 108
R2 0.42 0.57 0.78 0.78 0.56 0.59 0.65
Notes: t-statistic from robust standard error in parenthesis. *, **, *** denote significance at 10%, 5%, and 1%
respectively.
The addition of the interaction term means that the marginal effect of liberalization on
energy consumption is the summation of the coefficient for liberalization with the multiplication
of the coefficient for the interaction term and economic growth. However, unlike our initial
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contention, the marginal effect of liberalization is not significant for the full range of economic
growth (covariance between interaction term and economic growth is -0.026). Furthermore, the
incremental F-test statistic is 0.36; which means that both liberalization and its interaction with
economic growth are not significant in explainig the growth of energy consumption.
In the case of the effect of economic growth on energy consumption, the marginal effect
for the period before liberalization is the coefficient for economic growth by itself; for the period
after liberalization, the marginal effect is the summation of the coefficient for economic growth
with the coefficient for the interaction term. Given that the liberalization dummy and the
interaction term are not significant, it can be concluded that economic growth by itself effects
energy consumption, meaning that column 3 is the better model compared to column 4.
The ratio of capital per labor replaces economic growth in column 5. Unlike the results in
column 3 and 4, liberalization is significant but negative. However, capital per labor is not
significant. Column 6 includes the interaction between liberalization and capital per labor. The
inclusion of the interaction term renders liberalization insignificant. Similar with column 5
capital per labor is insignificant, but its interaction with liberalization is significant. The
incremental F-statistic testing the appropriateness of the inclusion of liberalization and the
interaction term together is 6.06, which indicates the need to include both variables. Given the
importance of the interaction between liberalization and capital per labor, Figure 1 shows the
conditional marginal effect of liberalization on energy consumption at different values of capital
per labor with its standard error band. The coefficient is significant if the band does not include
zero. It shows that the marginal effect is significant for capital per labor greater than about 1,000.
Table 3 shows the descriptive statistics for the capital per labor ratio data, where more than 90%
of the capital per labor are greater than 1,000.
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Figure 1: The Effect of Liberalization on the Growth of Energy Consumption conditioned on
Capital per Labor
Table 3: Descriptive Statistics for Capital per Labor RatioMean 11127.5 Minimum 270.4
Standard Deviation 9447.0 Maximum 47694.0
5th
percentile 510.6 10th
percentile 1611.5
35th
percentile 5497.9 50th
percentile 8447.6
In the case of capital per labor; the marginal effect of capital per labor on the growth of
energy consumption before liberalization is the coefficient for capital per labor by itself, and the
marginal effect of capital per labor after liberalization is the summation of the coefficient for
capital per labor with the coefficient for the interactive term between capital per labor and
liberalization. Hence, for the period before liberalization, capital per labor is not significant in
explaining the growth of energy consumption. After liberalization the marginal effect is -0.003
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with a standard error of -1.81. Hence, a one unit increase in capital per labor reduces the growth
of energy consumption after liberalization by 0.3%.
Based on the results in column 1 through 6, column 7 includes economic growth, capital
per labor, and the interaction between liberalization and capital per labor. It shows that
liberalization by itself is still insignificant, economic growth is significant however, its
magnitude decrease from 0.64 to 0.40, capital per labor by itself is not significant, but the
interaction between capital per labor and liberalization is significant.
Figure 2 (based on column 7) shows the conditional marginal effects of liberalization on
the growth of energy consumption conditioned on capital per labor. The different with Figure 1
is that the marginal effect is significant when capital per labor is about 5000. Following Table 3,
about 30% of the capital per labor ratios are less than 5000. This means that the effect of
liberalization is insignificant for countries with low level of capital per labor. In the case of the
effect of capital per labor on the growth of energy consumption, the marginal effect is not
significant before and after liberalization.
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Figure 2: The Effect of Liberalization on the Growth of Energy Consumption Conditioned on
Capital per Labor
5. Conclusion
Developing countries liberalize their trading regime expecting that it will improve economic
growth and welfare through static and dynamic gain of trade openness and liberalization. One of
the widely examined effects of liberalization is on the quality of the environment. However, the
general underlying cause of most pollutants which affect the quality of the environment is energy
consumption; thereby, the effect of liberalization on the environment can be linked to energy
consumption. This paper empirically examined the extent to which energy consumption is
effected by liberalization; discussing whether the interactions between liberalization, economic
growth, and capital per labor which capture the scale, composition and technique effects
influence the growth of energy consumption.
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The empirical analyses show that the growth of energy consumption is not effected by
liberalization per se. The effect is conditioned on the magnitude of capital per labor, and it is
insignificant at lower levels of capital per labor. Only after reaching the minimum threshold of
capital per labor, liberalization is significant in reducing the growth of energy consumption. This
minimum threshold means that liberalization may not benefit less developed countries energy
consumption. A number of reasons may explain the threshold. Less developed countries may not
have the absorptive capacity to benefit from technological transfer of energy-saving
technologies, products and/or processes brought about by liberalization. Given that capital per
labor is related to economic development, only after a certain minimum level of economic
development a country has the capability to absorb the transferred technologies. In addition,
public environmental awareness of less developed countries is less than the more developed
countries (Somanathan, 2010; Sodhi et. al., 2008), hence at lower levels of economic
development, environmental issue may not be brought up in liberalization discussion and
exercise. Thereby, reduction in tariff and non-tariff barriers of energy efficiency improving and
environementally friedly related products may not be included, or prioritized in the agenda of
liberalization.
Unlike our initial contention, the effect of liberalization on energy consumption is not
conditioned on economic growth. Instead, economic growth by itself increases the growth of
energy consumption; the effect is not conditioned on whether liberalization process has taken
place or not. Taking into consideration that economic growth by itself increases energy
consumption, a less developed country that liberalizes its market may suffer from environmental
degradation before it can reaps the benefit of liberalization. In order to reach the minimum
threshold level of capital per labor, the economy needs to grow, and the growth will induce
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greater energy consumption. In fact following the pollution haven hypothesis, less developed
countries are posited to be worse off by liberalization as their comparative advantage is in
pollution intensive industries.
These effects suggest that liberalization discusssion and exercise need to take into
account the implications of trade liberalilzation on energy consumption and consequently on the
environment. For example, there is a need to set higher priority on tariff and non-tariff barriers of
products and technologies that improve energy efficiency during liberalization discussion and
exercise. Indeed, energy-efficient product standards and labeling are an important tool and policy
mechanism to reduce greenhouse gas emissions (ICF International, 2011). The minimum
threshold of capital per labor suggest that countries and international organisations that promote
trade liberalisation in developing countries need to take great care in the sequencing of
liberalization.5
Acknowledgements
I would like to extend my gratitude to the two anonymous referees of the journal for their useful
comments and suggestions. Any errors and/or omissions in this work are attributable solely to
the author.
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Footnotes
1. Green energy may not pollute the environment, but for the developing countries andtime period investigated, green energy accounted for a very negligible share of energy
production and consumption.
2. However, there is a possibility that newly introduced technologies are more energy-intensive than the old technologies; hence, the change in technique increases energy
consumption.
3. This is equivalent to a first-difference regression in growth or a difference-in-differenceregression in the level of income. We refer the reader to Kneller (2008) for other
advantages of the method.
4. The literature on trade liberalization has also raised the issue of the validity of theliberalization date used, and that the use of dummy to indicate trade liberalization may
not measure the intensity of liberalization. Other studies have used the ratio export plus
imports to GDP to control for the liberalization measurement issue.
5. Santos-Paulina and Thirlwall (2004) argue that liberalization has had a net positive effecton income growth but the balance of trade consequences may reduce growth. They
conclude that countries and international organisations that promote trade liberalization in
developing countries need to carefully sequence the liberalisation of exports and imports
in order to achieve a balance between export and import.
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Appendix I
Average Annual Growth of Energy Consumption per Capita (%) for the Five-Year Period
Before, During, and After Trade Liberalization
CountryBefore
Liberalization
During
Liberalization
After
Liberalization
CountryBefore
Liberalization
During
Liberalization
After
Liberalization
1. Albania -2.64 -11.62 6.32 28. Kyrgyz Rep. -22.20 -3.39
2. Argentina 0.06 1.45 1.23 29. Latvia -10.48 -2.48
3. Armenia -30.89 7.57 3.08 30. Lithuania -14.38 0.92
4. Azerbaijan -11.05 -7.58 1.92 31. Macedonia -0.29 1.74
5. Bangladesh 1.48 2.16 3.25 32. Mexico 2.29 0.38 0.63
6. Benin -0.90 -1.44 1.88 33. Moldova -16.63 -6.26
7. Bolivia 2.68 -2.20 3.42 34. Morocco 5.20 0.11 2.12
8. Botswana -0.72 35. Mozambique -2.63 -0.87 1.57
9. Brazil 1.67 -0.20 2.30 36. Nepal -0.42 0.68 0.87
10. Bulgaria 0.16 -5.46 -2.25 37. Nicaragua -0.25 -0.36 1.21
11. Cameroon -0.26 -1.00 -0.23 38. Panama 3.76 3.27 -1.62
12. Chile 0.41 -0.51 39. Paraguay 4.36 0.08
13. Colombia 1.83 0.47 1.71 40. Peru -3.66 -1.42 1.91
14. Costa Rica -2.28 1.12 -0.23 41. Philippines -1.78 1.70 1.63
15. Cote d'Ivoire 0.61 -0.45 3.65 42. Poland 0.38 -4.97 -0.66
16. Czech Rep -0.01 -3.76 -0.84 43. Romania 0.89 -8.68 -2.85
17. Jamaica -1.85 -0.94 2.08 44. Slovak Rep 0.82 -4.27 0.09
18. Egypt -0.45 4.67 2.16 45. Slovenia -0.13 2.93
19. El Salvador -1.44 -3.33 3.85 46. South Africa -0.94 -0.50 -0.67
20. Ethiopia -1.21 -0.21 0.23 47. Sri Lanka 0.15 0.17 4.66
21. Georgia -19.35 -8.23 1.39 48. Tajikistan -13.82 -1.22 -0.33
22. Ghana 0.11 -2.67 2.76 49. Tanzania -1.29 1.19 2.15
23. Guatemala -4.40 -0.01 1.68 50. Trin and Tob 1.47 2.96 8.02
24. Honduras 0.21 -0.34 -0.08 51. Tunisia 3.42 -0.68 3.67
25. Hungary 1.38 -3.55 0.68 52. Turkey 1.98 3.88 1.02
26. Jamaica -6.05 2.74 5.10 53. Uruguay 3.93 -1.73 -1.08
27. Kenya 0.92 -0.79 0.49 54. Zambia -0.75 -1.74 -1.65
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Appendix II
Date of Liberalization
Country
Liberalization
Date
Country
Liberalization
Date
Country
Liberalization
Date
Country
Liberalization
Date
1. Albania 1992 15. Cote d'Ivoire 1994 29. Latvia 1993 43. Romania 1992
2. Argentina 1991 16. Czech Rep 1991 31. Lithuania 1993 44. Slovak Rep 1991
3. Armenia 1995 17. Jamaica 1989 31. Macedonia 1994 45. Slovenia 1991
4. Azerbaijan 1995 18. Egypt 1995 32. Mexico 1986 46. South Africa 1991
5. Bangladesh 1996 19. El Salvador 1989 33. Moldova 1994 47. Sri Lanka 1991
6. Benin 1990 20. Ethiopia 1996 34. Morocco 1984 48. Tajikistan 1996
7. Bolivia 1985 21. Georgia 1996 35. Mozambique 1995 49. Tanzania 1995
8. Botswana 1979 22. Ghana 1985 36. Nepal 1991 50. Trin and Tob 1992
9. Brazil 1991 23. Guatemala 1988 37. Nicaragua 1991 51. Tunisia 1989
10. Bulgaria 1991 24. Honduras 1991 38. Panama 1996 52. Turkey 1989
11. Cameroon 1993 25. Hungary 1990 39. Paraguay 1989 53. Uruguay 1990
12. Chile 1976 26. Jamaica 1989 40. Peru 1991 54. Zambia 1993
13. Colombia 1986 27. Kenya 1993 41. Philippines 1988
14. Costa Rica 1986 28. Kyrgyz Rep. 1994 42. Poland 1990
Source: Wacziarg and Welch (2008)