SSRN-Id1955949 Effects of Dollar in Ecuadot

7/27/2019 SSRN-Id1955949 Effects of Dollar in Ecuadot

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Effect of Official Dollarization on a Small Open Economy: Ecuador

Bedri Kamil Onur Tas1 and Selahattin Togay2

Abstract

This paper investigates the effects of dollarization on the macroeconomic performance of a small

open economy, Ecuador, using a time series perspective. More specifically, we investigate how

dollarization effects inflation, GDP, inflation uncertainty and money-price relationship in Ecuador.

There are four main findings of this study. First, inflation is lower after dollarization. Second, GDP

growth is higher after dollarization when several other factors like rising oil prices and increase in

the equity markets of emerging economies are controlled. Third, inflation uncertainty measured by

inflation variance through GARCH is lower during dollarization. Finally, money supply is

endogenous after dollarization and exogenous before dollarization. A new test is proposed and

implemented to investigate endogeneity of money. As a result, we conclude that dollarization

improved the macroeconomic performance of Ecuador and changed the money-price relationship in

Ecuador. The results are robust to different arguments about the empirical methodology.

1 (Corresponding Author) TOBB University of Economics and Technology, Department of Economics, Email:

[email protected]

2

Gazi University Department of Economics, Email: [email protected]


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1 Introduction

The fact that many emerging countries faced currency crises with devastating negative economic

effects caused an intense debate on exchange rate policies for emerging countries. Many economists

proposed hard pegs (Summers (2000) and Fischer (2001)). Dollarization, in the sense that the

country should abandon its national currency and adopt an advanced nation's currency as legal tender

(US Dollar for Ecuador), has been implemented by many countries3. Ecuador undertook official

dollarization in March 20004 by dropping its own currency, the sucre, and adopting the US dollar.

This paper empirically investigates the effects of dollarization on the macroeconomic performance of

Ecuador. As mentioned by Jameson (2003a), Ecuador is the longest-lasting of the recent dollarizers

and has the most extreme contemporary dollarization program. This makes Ecuador an excellent

candidate to investigate the effects of dollarization on emerging economies. As presented in table I,

we find that dollarization has significant positive effects on the economic performance of Ecuador5.

Table I

Summary of the Empirical Results

Effect of Dollarization

CPI Inflation Lower after dollarization

GDP Growth Higher after dollarization

Inflation Uncertainty Lower after dollarization

Money-Price Relationship Money becomes endogenous after dollarization

The theoretical analyses of Calvo (2001) and Minda (2005) present that there are pros and

cons of dollarization. Thus, extensive empirical analysis is required to investigate whether

dollarization achieves what it promises: improvements in macroeconomic conditions through

3Edwards and Magendzo (2003) lists 13 independent and 15 non-independent countries for the 1970-1998 period.

4After a serious economic crisis in 1998-1999 period, President Jamil Mahuad announced the dollarization program on

January 9 2000.5During the current financial crisis in 2008, Ecuador has significant financial problems. The current financial crisis is out

of the scope of this paper and available macroeconomic data for Ecuador ends at 2007.


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financial and exchange rate stability. Alesina and Barro (2001, p.382), have argued that adopting

another nations currency eliminates the inflation bias problem of discretionary monetary policy.

Dornbusch (2001) indicates that countries that give up their currency will tend to grow faster than

non-dollarized countries6. Starting from these theoretical arguments, we investigate the effects of

dollarization on the macroeconomic performance of Ecuador using a time series perspective. More

specifically, we investigate how dollarization effects inflation, GDP growth, inflation uncertainty and

money-price relationship (endogeneity of money). There are four main results of this study. First,

inflation is lower after dollarization. Second, GDP growth is higher after dollarization. These results

persist after controlling other factors that might cause these improvements besides dollarization: oil

production growth, rise in oil prices, increase in the MSCI emerging market index, improvement in

institutional quality. Third, inflation uncertainty measured by inflation variance through GARCH is

lower during dollarization. Finally, money supply is endogenous after dollarization and exogenous

before dollarization.

Quispe-Agnoli and Whisler (2006) indicate that the expected benefits of full dollarization

include the elimination of exchange rate risk, contributing to the decline of the country risk premium

and interest rates, as well as the reduction of the inflation rate and inflationary expectations. Some

initial conditions could be relevant in the decision to implement official dollarization. Minda (2005)

and Edwards and Magendzo (2006) observe that small countries with close trade or financial ties to

the United States could favor official dollarization, as Panama did in 1904. Ecuador, El Salvador,

and Panama, the largest countries that have implemented official dollarization, are still relatively

small and are very open to U.S. trade and finance, with an average gross domestic product (GDP) of

$11 billion (in 2000 dollars) and an average population of 7 million in 2004.

6As mentioned in Edwards and Magendzo (2003), this growth effect is supposed to take place through two channels:

(a) dollarization will mean lower interest rates, higher investment, and faster growth (Dornbusch, 2001); and (b), byeliminating exchange rate volatility, dollarization is supposed to encourage international trade and this, in turn, will

result in faster growth. (Rose (2000), and Rose and van Wincoop (2001))


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The empirical analysis about the effects of dollarization is limited. Previous studies in the

literature are conducted using annual data. For example, Edwards and Magendzo (2006) examines

the effect of dollarization using a yearly panel of 169 countries that covers 1970 through 1998. They

find that GDP growth is not statistically different in dollarized and in non-dollarized ones. Since the

dataset of Edwards and Magendzo (2006) ends in 1998, it does not identify Ecuador as dollarized.

The dollarized countries in their dataset is mostly non-independent countries and independent

countries are small countries. In their dataset 20 out of 169 countries are identified as dollarized. In

our study, we use monthly and quarterly data and analyze the effects of dollarization on a relatively

large independent country, Ecuador, using a time series perspective.

The empirical analysis of dollarization is less complicated compared to the analysis of other

policy changes because dollarization does not suffer from the epidemic case of fear of floating as

identified by Calvo and Reinhart (2002). In other words, it is not possible for the countries to

announce a policy and do not follow that policy. Calvo and Reinhart (2002) find that countries that

say they follow their exchange rate to float mostly do not. In the case of dollarization, Ecuador

dropped sucre and adopted the US dollar in March 2000. Since the sucre is not valid after March

2000, we can safely claim that dollarization is implemented exactly at this date. In other exchange

rate regimes like floating and monetary policy regimes like inflation targeting the exact date of

implementation and the degree of adoption might not be determined exactly which complicates the

empirical analysis.

The economic crisis in 1998-1999 period that led to dollarization in Ecuador initiated many

empirical papers about macroeconomic performance of Ecuador. Nazmi (2001), Jacome (2004),

Beckerman (2001), Beckerman (2002) and Martinez (2006) analyzed the process that led to this

economic crisis. They argue that mainly institutional weaknesses, rigidities in public finances, and

high financial dollarization amplified the financial crisis in Ecuador. Beckerman and Douglas (2002)

and Solimano (2002) examines the pros and cons of dollarization in Ecuador. Jameson (2004) argues


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that orthodox perspectives are inadequate to explain dollarization decision of Ecuador and uses a

post-keynesian institutionalism explanatory framework. Dean (2003) compares Canada and

Ecuador from six different aspects: dangers of liability dollarization, currency and default risk

premiums on interest rates, lower predictability of domestic money supply, stronger monetary

shocks, currency substitution irreversibility and impotence of exchange rate policy. He conducts a

descriptive analysis and concludes that dollarization is suitable for Ecuador but not Canada. Hanke

(2003) argues that dollarization is suitable for Ecuador but the following refoms should be conducted

for successful implementation of dollarization: financial integration with international financial

system, fiscal transparency and control, tax simplification, supermajority voting, deregulation and

privatization.

On the other side of the debate, some studies argue that dollarization is not favorable for

Ecuador. Jameson (2003a and 2003b) argues that dollarization is not suitable for Ecuador and will

lead Ecuador to crisis since it does not solve any fundamental economic problems about the structure

of the economy. Jameson (2003a) examines how a process of de-dollarization might be

implemented. Jameson (2003b) analyzes the macroeconomic performance of Ecuador using yearly

data from 1997 till 2002. This paper argues that macroeconomic performance of Ecuador has

improved during 2000-2002 period. Dollarization played a role in this improvement by encouraging

both private and capital flows. From a political-economic standpoint, dollarization has succeeded in

providing access to international dollar resources. Jameson (2003b) indicates that although

dollarization improved the economic performance of Ecuador, the fundamental structural economic

problems like political instability and disappearance of independent monetary policy remain. These

problems leave Ecuador susceptible to crisis. These studies use only yearly data because of data

limitations and do not conduct a time series investigation of macroeconomic performance of

Ecuador.


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Our analysis differs from other related studies in the literature in several aspects. First of all,

this study is the first extensive time-series analysis of the effects of dollarization on the

macroeconomic performance of Ecuador. We use high frequency data to investigate effects of

dollarization. Earlier studies could not conduct these studies because of data limitations7,8. To verify

that our results are robust and correctly gauge the effect of dollarization, we use control variables

like oil price, institutional quality and MSCI Emerging Markets Index. Also, the alternative Quandt-

Andrews Statistic methodology makes sure that our empirical results correctly measure the effects of

dollarization and not any other change that occurred before dollarization. Second, to best of our

knowledge, this is the first study that analyzes the impact of dollarization on inflation uncertainty

using a GARCH model. Third, we investigate the impact of dollarization on money-price

relationship in Ecuador which has not been done in the literature before. Fourth, we propose and

implement a test of endogeneity of money in the context of GMM and instrumental variables, C

statistic, which has not been used in the literature before to investigate money-price relationship. We

use this methodology to investigate the endogeneity of money in Ecuador before and after

dollarization. Compared to previous methods9, the C statistic method directly examines whether

money is endogenously determined or not. To sum up, using several time-series methods, we

contribute to better understanding of the macroeconomic effects of dollarization using monthly and

quarterly data.

The rest of the paper is organized as follows: In section 2, we describe the conditions that led

to dollarization. Section 3 explains the data and methodology used in this study. In section 4, we

present the results about the macroeconomic performance of Ecuador namely inflation and output

7Those studies did not have enough monthly and yearly data points after dollarization to conduct time-series analysis.

Alesina and Barro (2001) indicates that data availability limits empirical research about monetary unification.8

Soto (2009) investigates the impact of dollarization on the labor market in Ecuador. Specifically, he investigates the

following research questions: What are the causes of the slow growth in employment after dollarization in Ecuador?

and How does employment respond to shocks in production, wages, and interest rates?. 9Previous studies mostly implement Granger causality methodology which only approximately tests endogeneity of

money.


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growth. In section 5, we analyze the effects of dollarization on inflation uncertainty. In section 6, we

examine the impact of dollarization on money-price relationship in Ecuador. Finally, section 6

presents the concluding remarks and policy implications of the results.

2 Ecuador Before Dollarization

Although Ecuador met few of the criteria for entering an optimal currency area in 2000 (Panizza,

Stein and Talvi 2003) it adopted dollarization. It was a small, open economy and its central bank had

low credibility which made it suitable for dollarization. The deterioration in economic performance

after 1997 forced Ecuador to adopt dollarization. The process that led to the economic crisis in 1998-

1999 period can be summarized by the following factors:

a) Political Instability: The conflicts between the mountainous and coastal regions caused instability

and decreased the ability of the country to implement structural reforms. This is caused by the fact

that the monetary and fiscal policy actions could have opposite effects on these two regions. Jacome

(2004) indicates that the depreciation of the real exchange rate had favorable effects on the coast

whereas has adverse effects on the mountainous regions. An important indicator of the instability is

presented by Beckerman (2002); there were 5 different cabinets and 7 different finance ministers

during the 1995-1998 period.

b) Natural Disasters: Ecuadorian economy suffered significantly because of several natural disasters

like earthquakes, volcanic eruptions and storms. These had adverse effects on revenues from tourism

and energy production. For example, El Nino storm in 1998 had devastating impact on production

and infrastructure.

c) High Dependence on Export (Oil) Revenues: The public revenues and export revenues of Ecuador

depend highly on oil revenues. Thus, significant movements in oil prices causes distortions on public

finance. For example, the decrease of oil prices to $9 per barrel had adverse effects on export


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revenues and public finance. Table II presents two most important items of export revenues, oil and

banana. The structure of production significantly changed after dollarization. One of the most

significant feature of the Ecuadorian economy is the high share of oil production in GDP. This

feature leaves Ecuador susceptible to oil price shocks.

(Table II about here.)

d) High Degree of Financial Dollarization: After 1992 the Central Bank of Ecuador started a

stabilization program based on pegged exchange rate. Between 1994 and 1998 the credibility of this

system deteriorated and high levels of inflation and exchange rate uncertainty caused a significant

increase in financial dollarization. In that period the saving accounts in dollars surpassed the national

foreign reserves10.

The fourth factor is eliminated after dollarization but other three factors currently exist in

Ecuador. Also, the production structure of Ecuador changed significantly. As displayed in Table III,

the portion of mining and oil production significantly increased.

(Table III about here.)

Additionally, the structure of investment and savings changed significantly after dollarization

as presented in figure I below. Figure I indicates that dollarization had positive impacts on the

structure of savings and investment. Investment and national savings increased whereas foreign

savings significantly diminished. This represents the increased trust in the Ecuadorian economy.

10The ratio of saving accounts in dollars to aggregate savings raised from %13.3 in 1990 to %53.7 in 1999. Also, The

ratio of loans in dollars to aggregate loans raised from %1.5 in 1990 to %66.5 in 1999. (Beckerman, 2002)


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-10

-5

0

5

10

15

20

25

30

99 00 01 02 03 04 05 06 07 08

National Savings/GDP

Investment/GDP

Foreign Savings/GDP

Saving and Investment

4

6

8

10

12

14

16

88 90 92 94 96 98 00 02 04 06 08

Unemployment Rate

Figure I: Investment and savings and the unemployment rate in Ecuador

Figure I also displays the unemployment rate in Ecuador. As indicated by Soto (2009),

unemployment remained stubbornly high after dollarization. In this section we briefly summarized

the Ecuadorian economy. In the following sections, we will investigate the effects of dollarization on

the economic structure of Ecuador in detail.

3 Data and Methodology

3.1 Data:

We use monthly and quarterly data for 1990-2007. The source of the data is IFS, the FRED database

of the St. Louis Fed, Reuters Ecowin and Polity IV databases. The variables used in this study are:

CPI inflation, real GDP, GDP growth, oil production growth, money supply, spot oil price, MSCI

Emerging Markets Index growth and institutional quality measure of the Polity index. The data is

explained in detail in the Appendix. Oil production growth, spot oil price, MSCI index growth and

institutional quality are used as control variables in regressions that measure the effect of

dollarization on real GDP and real GDP growth.

3.2 Methodology


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This study investigates three important aspects of the Ecuadorian economy: macroeconomic

performance (inflation and GDP growth), inflation uncertainty and money-price relationship.

3.2.1 Macroeconomic Performance

Artificial regressions that are designed to measure the change before and after dollarization (March

2000) are used. We implement an OLS methodology with dollarization dummy to measure the exact

effects of dollarization on macroeconomic performance variables of Ecuador. The dollarization

dummy takes the value of 1 after March 2000 (2nd quarter of 2000 for quarterly data) and zero

before March 2000. The same methodology is implemented by Mishkin and Schmidt-Hebbel (2007)

to measure effects of inflation targeting on macroeconomic performance. The coefficient of the

dollarization dummy variable gauges the exact effect of dollarization. We use several control

variables to make sure that changes in GDP growth is caused by dollarization and not by other

variables that can affect GDP. As a result, the following regression specification is estimated:

Yt=

0 +

1Dt+

2Ct+

t(1)

Where Yt denotes the macroeconomic variables. Dt is the dollarization dummy variable which takes

the value 0 before dollarization (March 2000) and 1 after dollarization. Ct denotes the control

variables other than dollarization that might affect the macroeconomic performance of Ecuador.

One can argue that the changes in the macroeconomic performance of Ecuador might be

caused by the improvement in the government institutions after the stabilization policy initiated after

the 1998-1999 economic crisis. We use the Polity IV institutional quality measure as employed by

Acemoglu and Johnson (2005) as a control variable11. This controls for the effect of changes in

11

Figure A.1 in the Appendix displays the institutional quality measure, constraint on executive, for 1990-2008 period.Interestingly, the institutional quality of Ecuador did not improve despite the stabilization policy actions taken after

1999.


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institutional quality and helps us correctly measure the impact of dollarization on the macroeconomic

performance of Ecuador12.

Another important feature that we consider while implementing these empirical methods is

the robustness of our results. Thus, we designed an alternative econometric specification and

implemented several stability tests to test for changes in macroeconomic performance of Ecuador.

Since1 in equation 1 measures the change in the conditional mean of the macroeconomic variable

(Yt), testing the stability of the following regression equation is equivalent of testing the changes in

the conditional mean of those variables.

Yt= 0 + 1Ct+ut (2)

Ones is a vector of ones. By testing the stability of0 in equation 2 using Chow and Quandt-

Andrews breakpoint tests we can test the impact of dollarization on the conditional mean of these

macroeconomic variables. The Chow test fits the equation separately for each subsample and

examines whether there are significant differences in the estimated equations. To check for

robustness of our results, we also implement the Quandt-Andrews Breakpoint Test which tests for

one or more unknown structural breakpoints in the sample for a specified equation. The idea behind

the Quandt-Andrews test is that a single Chow Breakpoint Test is performed at every observation

between two dates, or observations13. The Quandt-Andrews test also provides us the most likely

12Acemoglu and Johnson (2005) use the constraint on executive variable in Polity IV as a measure of institutional

quality. They explain the variable as the following:

A seven category scale, from 1 to 7, with a higher score indicating more constraint. Score of 1 indicates unlimited

authority; score of 3 indicates slight to moderate limitations; score of 5 indicates substantial limitations; score of 7

indicates executive parity or subordination. Scores of 2, 4, and 6 indicate intermediate values.13

The Quandt-Andrews test is essential to check for the robustness of our results. The date of the structural change is

not imposed in the Quandt-Andrews test and the test searches for one or more unknown structural breakpoints in the

sample. As a result, the test is immune to the argument that structural break tests have low power because the breakdate is chosen based on the knowledge of events that some change occurred. By using stability tests in the alternative

regression specification we validate that our results are robust to these arguments.


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dates of structural change. The Quandt-Andrews is selected because the structural break point is

determined by the test and not imposed on the test. Thus, this test is immune to the argument that a

known date of structural change is used and this might cause a bias.

3.2.2 Inflation Uncertainty

As in Fountas (2001), we implement a GARCH (1,1) model14 to investigate the impact of

dollarization on inflation uncertainty. Consider an ARMA model of inflation, t, with time-varying

conditional variance:

t is the information set available at time t. As in Andersen et al. (2003), we use the dummy

variable as an explanatory variable in the variance equation and investigate effect of dollarization on

inflation uncertainty. Andersen et al. (2003) use announcement dummies in the variance equation of

exchange rates to measure the effects of macroeconomic announcements on exchange rate volatility.

The coefficient of the dollarization dummy, t, shows the effect of dollarization on inflation

uncertainty in Ecuador.

3.2.3 Money-Price Relationship

In this study, we also make a methodological contribution by proposing an alternative test of

endogeneity of money. Many studies like Pinga and Nelson (2001) and Ozmen (2003) use Granger

causality or cointegration tests to investigate the relationship between money supply and price level

or inflation. But these methods test causality not exogeneity of a variable. As argued in Togay and

14Akaike and Schwarz information criterions pick GARCH (1,1). Table IX and section C of the Appendix display AIC and

SBC values for alternative GARCH specifications.


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Kose (2008), the existing causality studies do not make a clear distinction between exogeneity and

causality. Thus, the presence of causal relationship from price to money supply is neither necessary

nor a sufficient condition for testing endogenous money hypothesis. As recommended by Baum et al.

(2007), we implement a test of overidentifying restrictions to test endogeneity of money 15.

As shown in Hayashi (2000), a regressor is endogenous if it is not predetermined (i.e., not

orthogonal to the error term), that is, if it does not satisfy the orthogonality condition. Following this

argument, we test whether money is endogenous using the C statistic (also known as a GMM

distance or difference-in-Sargan statistic). Under the null hypothesis that the specified endogenous

regressors can actually be treated as exogenous, the test statistic is distributed as chi-squared with

degrees of freedom equal to the number of regressors tested. The endogeneity test is, like the C

statistic, defined as the difference of two Sargan-Hansen statistics: one for the equation with the

smaller set of instruments, where the suspect regressor(s) are treated as endogenous, and one for the

equation with the larger set of instruments, where the suspect regressors are treated as exogenous.

Also like the C statistic, the estimated covariance matrix used guarantees a nonnegative test statistic.

Under conditional homoskedasticity, this endogeneity test statistic is numerically equal to a

Hausman test statistic; see Hayashi (2000, 233-234). We conduct the test for the pre and post-

dollarization periods and analyze whether money supply is endogenous in these periods or not.

4 Macroeconomic Performance of Ecuador and Dollarization

This section investigates the effects of dollarization on inflation and GDP growth. Table IV presents

the summary statistics of monthly inflation for dollarization and non-dollarization periods and the

summary statistics for Real GDP and Real GDP growth using quarterly data.

(Table IV about here.)

15This test is also known variously as the Sargan statistic, Hansen J statistic, Sargan-Hansen J test. The value J of the

GMM objective function evaluated at the efficient GMM estimator \beta_{EGMM} is distributed as \chi^{2} with (L K)degrees of freedom under the null hypothesis that the full set of orthogonality conditions are valid. (Baum et. al.

(2007))


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Following the methodology in Mishkin and Schmidt-Hebbel (2007), tables V and VI measure

the change in inflation and GDP growth before dollarization and after dollarization. In table V of

monthly data, the coefficient of the dollarization dummy variable is negative and significant for the

inflation equation. Analysis of quarterly data in table VI indicates that the coefficient of dollarization

dummy variable is negative and significant for the inflation equation. For the analysis of Real GDP

and Real GDP growth, table VI displays alternative regression specifications with different sets of

control variables. Table VI shows that the dollarization dummy is significant with positive

coefficient for the Real GDP and Real GDP growth equations. Thus, we conclude that inflation is

significantly lower in Ecuador after dollarization and Real GDP and Real GDP growth is

significantly higher after dollarization. These results are robust to different regression specifications

with alternative control variables.

(Tables V and VI about here.)

Tables V and VI present that after dollarization the macroeconomic conditions of Ecuador

improved significantly. Different regression specifications control for the rise in the oil prices, oil

production growth, the improvement in institutional quality and trend of growth in the emerging

economies. Thus, independent of these factors, dollarization helped Ecuador to achieve better

macroeconomic conditions.

4.1 Robustness

There are several arguments that can be made about the empirical results of the paper presented

above. First, one can argue that the regression methodology is responsible for the favorable results

about dollarization. To analyze whether the results of tables V and VI are robust to selection of

empirical methodology we implemented two alternative methods: Chow and Quandt-Andrews

breakpoint tests. Table VII examines the robustness of the results presented in table V. Both the

Chow and Quandt-Andrews tests reject the null hypothesis that there are no structural breaks in the


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conditional mean of monthly inflation. Also, Quandt-Andrews test identifies February and March

2001 as the date of structural break which is the date of dollarization.

(Table VII about here.)

Table VIII presents the alternative Chow and Quandt-Andrews test statistics for all the

regression specifications of table VI. For all regression specifications, the Chow test concludes that

the conditional mean of the variables are different before and after the second quarter of 2000. The

Quandt-Andrews test concludes that there is a structural break in the dataset and all of the break

dates coincide with dollarization

16

. As a result, using alternative methods, we conclude that there has

been a structural change in macroeconomic variables of Ecuador. In other words, the results of the

paper are robust to alternative empirical methods.

(Table VIII about here.)

Second, it can be claimed that macroeconomic factors other than dollarization might have

improved after March 2000 and this might have affected our results. As presented in tables II and III,

oil production is an incremental component of the Ecuadorian economy. Thus, increases in oil prices

and oil production have significant positive effects. So, we included oil prices and oil production as a

control variables. Also, after the countries started to recover from the global crisis in 1999, all

emerging countries experienced positive economic growth. To control for this effect we used MSCI

Emerging Markets Index. After the crisis, important structural changes are undertaken in Ecuador as

a part of the recovery program. To make sure that these improvements do not affect our empirical

results we include institutional quality as a control variable in our regressions. We believe that these

variables represent most of the important economic changes for the Ecuadorian economy other than

dollarization. By using these variables as control variables, we confirm that the empirical

methodology used in the paper correctly measure the direct effects of dollarization.

16The test either exactly identifies 2nd quarter of 2000 as the break date or identifies a date after 2nd quarter of 2000.


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Third, it is also possible that improvements that occurred before dollarization already had

positive effects and the empirical results depict these effects associated with previous changes. The

Quandt-Andrews test can be used to examine the robustness of out results to this argument. The test

searches for an unknown structural breakpoint in the data17. Tables VII and VIII presents that all of

the structural break dates identified by the test are either exactly first quarter of 2000 (March 2000

for monthly analysis) or after 2000 and very close to the date of dollarization adoption. All of the

dates identified by the test are after dollarization meaning that the results of table V and VI are not

biased by previous events before dollarization.

Finally, empirical analysis of structural change is susceptible to the critique of Hansen (1992)

who claims that ... the date of structural change may be selected by appeal to events known a priori.

... it is essential that the researcher can argue that the events are selected exogenously. The

robustness check conducted using the Quandt-Andrews test also provides answers for this critique.

Since the test first identifies the structural break date and then tests whether there is a break at that

date the break date is exogenous. In other words, we did not impose a known date but the test itself

picked that date. Thus, tables VII and VIII presents that the results of table V and VI are robust to the

critique of Hansen. The Quandt-Andrews test identifies dates that exactly match the date of

dollarization or dates that are 2 or 3 quarters ahead. To sum up, robustness analyses of the main

results of the paper indicate that the results are not biased and robust to alternative specifications.

5 Inflation Uncertainty and Dollarization

It has been found that inflation uncertainty significantly affects macroeconomic performance like

inflation and GDP growth. Cukierman and Meltzer (1986) construct a game-theoretic model and

show that higher inflation uncertainty will raise average inflation rate. Using GARCH methodology

and Granger causality tests, Apergis (2004) provides empirical support that inflation uncertainty

17The test is explained in detail in Hansen (2001) and Perron (2006).


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increases inflation in the G7 countries. Grier and Perry (1998) find that a rise in inflation uncertainty

significantly affects inflation in more than half of the countries they analyze. Elder (2004)

theoretically and empirically investigates the effects of inflation uncertainty on real economic

activity. He finds that a shock to inflation uncertainty decreases output growth. Friedman (1977)

indicates that uncertainty about future inflation distorts the efficient allocation of resources and this

leads to lower output. Stockman (1981) showed that anticipated inflation reduces the demand for real

balances, implying that the demand for capital and output growth decreases. His results find

empirical support in Zhang (2000). As a result, lower inflation uncertainty is crucial for economic

well-being. In this section, we investigate whether dollarization helped Ecuador to achieve lower

inflation uncertainty.

As mentioned in Fountas (2001), autoregressive conditional heteroskedasticity (ARCH) and

generalized ARCH (GARCH) approaches can be employed to proxy uncertainty. Fountas (2001)

uses annual data and implements a GARCH (1,1) model to investigate inflation uncertainty in UK.

Daal et al. (2005) use monthly inflation rates based on log differences of CPI. They implement

PGARCH methodology to estimate inflation uncertainty and use Granger causality tests to

investigate the relationship between inflation and inflation uncertainty for both developed and

emerging countries. In this section, we implement the GARCH methodology described in section 2

to investigate the effect of dollarization on inflation uncertainty.

First, we conduct an ARCH LM test and unit root tests to verify whether the necessary conditions for

the implementation of the GARCH methodology are satisfied. The ARCH LM test shows the

presence of ARCH effects for inflation18. Unit root tests reject the null hypothesis of a unit root for

inflation at 1 percent. Table in Appendix B presents the test statistics which show that inflation does

not have unit root.

18The F statistic is 51.6 and the Obs*R-squared statistic is 41.3. Both statistics have p values of 0.00. Thus, we reject the

the null hypothesis that there is no ARCH.


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-.02

.00

.02

.04

.06

.08

.10

.12

.14

90 92 94 96 98 00 02 04 06

Year

MonthlyInflatio

n

Dollarization

Figure II: Variability of Inflation

Figure II displays monthly inflation of Ecuador. It can be seen that variability of inflation is

lower after dollarization (March 2000).

Table IX displays the formal test of the impact of dollarization of inflation uncertainty. It

shows different specifications results of GARCH(1,1) for inflation. We estimated various ARCH and

GARCH models. The Akaike Information Criterion (AIC) and Schwarz Bayesian Criterion (SBC) of

these alternative models are displayed in section C of the Appendix19. GARCH(1,1) specification for

the variance of inflation in Ecuador is selected by the SBC. Several studies of inflation uncertainty

like Apergis (2004), Fountas (2001) and Grier and Perry (1998) implement GARCH(1,1)

specifications. As in Andersen et al. (2003) and Fountas (2001), we investigate changes in the

variance of inflation by using the variable of interest (dollarization dummy) as an explanatory

variable in the variance equation. In all of the regression specifications of table IX, the coefficient of

the dollarization dummy is significant and negative. This result concludes that inflation uncertainty

(variance) is significantly lower after dollarization.

19In all of the alternative models the dollar ization dummy variable in the variance equation is significant with a negative

coefficient.


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(Table IX about here.)

Figure III displays a graphical presentation of the results of Table IX. The conditional

standard deviation of inflation is much lower after dollarization. As a result, the results of this section

infer that dollarization helped Ecuador to achieve lower inflation uncertainty.

.00

.02

.04

.06

.08

.10

90 92 94 96 98 00 02 04 06

Conditional standard deviation

Figure III: Conditional Variance of Inflation Before and After Dollarization

6 Money-Price Relationship in Ecuador

Is inflation a monetary phenomenon? This question has been extensively analyzed theoretically and

empirically. Several studies in the literature investigate money-price relationship empirically: Belrs

and Jones (1993) for Algeria; Pradhan and Subramanian (1998) for India; Sun and Ma (2004) for

China and Pinga and Nelson (2001) for 26 countries. Vymyatnina (2006) conducts the analysis from

a post-Keynesian perspective for Russia. To the best of our knowledge, there are no studies that

investigates money-price relationship for Ecuador and this study is the first study that examines

effect of dollarization on money-price relationship.

Dollarization is expected to effect money-price relationship because in the full dollarization

system a country abandons its monetary and exchange rate policies. The amount of money is

determined internally (endogenously) according to balance of payments. In other words, as Schuler


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(2005) argues the supply demand dynamics in the exchange rate market determines the money

supply. This argument indicates that dollarization endogenizes money supply. In that context, we

expect and find money supply to be endogenous after dollarization (after March 2000). Before

dollarization, (1990-2000 period) there has been different exchange rate regimes in Ecuador. During

pre-dollarization period, we expect and find money supply to be exogenous in Ecuador. This is partly

caused by the fact that most of the money supply is determined by financing government

expenditures and financing troubled banks20. In this section, we empirically investigate the validity

of this argument.

We conducted the endogeneity tests explained in section 3.2.3 using different measures of

money supply: M1, M2 and reserve money. Different specifications and estimations techniques are

implemented (2SLS, GMM). The lagged values of dependent and independent variables are used as

instruments. The underidentification tests of all regressions have p-values of 0.00 indicating that

instruments are significantly related with the endogenous variable. The Sargan and Hansen J

statistics of all the regressions have p-values between 0.38 and 0.99. Thus, for all of the instrumental

variable regression specifications, we accept the null hypothesis that the instruments are valid

instruments, i.e., uncorrelated with the error term21.

Table X displays the GMM test of exogeneity of monetary aggregates before and after

dollarization. Table X shows that the null hypothesis that money is exogenous is accepted before

dollarization and rejected after dollarization. Thus, we conclude that money is endogenous after

dollarization for all measures of money supply.

(Table X about here.)

20For the 1995-1999 period the average cash deficit of Ecuador is 748.44 million dollars. (Source: IFS yearly statistics)

21

The regression outputs of all the IV regressions are displayed in the previous versions of the paper. Since the resultsof the endogeneity tests are of interest, we do not show the regression results in this version to save space. The

regression outputs are available from the authors upon request.


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Finally, using the endogeneity tests conducted for M1, M2 and reserve money, we deduce

that money is endogenous after dollarization and exogenous before dollarization in Ecuador. As

explained above, dollarization endogenizes money. The results presented in table X provides

empirical evidence for the arguments of Schuler (2005). This section expresses another significant

impact of dollarization that has not been described in detail in the literature before.

7 Conclusion and Policy Implications

This paper contributes to the literature by investigating the effects of dollarization using a time series

perspective. More specifically, we investigate how dollarization effects inflation, GDP growth,

inflation uncertainty and money-price relationship (endogeneity of money) in Ecuador. There are

four main results of this study. First, inflation is lower after dollarization. Second, GDP growth is

higher after dollarization. Third, inflation uncertainty measured by inflation variance through

GARCH is lower during dollarization. Finally, money supply is endogenous after dollarization and

exogenous before dollarization. As explained in Section 6, this is caused by the fact that the amount

of money is determined internally (endogenously) according to balance of payments .

The results of this paper has many policy implications. We provide evidence that

dollarization improves macroeconomic performance of Ecuador by lowering inflation, increasing

GDP growth and lowering inflation uncertainty. Endogeneity of money in Ecuador after dollarization

raises some arguments about economic policy in Ecuador. Production in Ecuador highly depends on

oil production. As displayed in table III, the percent of oil production in GDP is significantly higher

for the 2000-2006 period. Thus, during the dollarization period the Ecuadorian economy depends

more on oil production. Rising oil prices help Ecuadorian government financing. In that sense,

endogenous money supply and inability of Ecuador to use money supply as a policy tool do not

cause any serious economic problems when Ecuador is earning high oil revenues.


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Unstable oil prices and very low oil price (9 dollars per barrel in 1999) were among the

reasons of economic crisis in 1999. Besides, as mentioned in Jameson (2003a and 2003b) the

instable political conditions and fundamental structural problems still remain in Ecuador. These

inadequate economic conditions for dollarization might lead Ecuador into another crisis unless

economic reforms are made. To sum up, macroeconomic conditions significantly improved after

dollarization but instable oil prices might be followed by a decline in oil prices which might lead to

economic crisis. To avoid crisis, Ecuadorian authorities should rapidly conduct structural economic

reforms which are compatible with dollarization. These reforms are required to maintain the

improved macroeconomic conditions achieved by dollarization.

APPENDIX

A Data

CPI Inflation: Inflation is calculated as the log difference of CPI. The source is the IFS.

Real GDP: Level of GDP at 2000 prices in US Dollars is used as the Real GDP. It is from the IFS.

GDP Growth: GDP growth is calculated as the log difference of Real GDP.

Oil Production Growth: Log difference of quarterly total oil production which is taken from the IFSdatabase is used.

Money Supply: Reserve money, M1 and M2 are used for the analysis of money supply. The

variables are from the IFS.

Spot Oil Price: Crude oil price of the West Texas Intermediate. (FRED)

MSCI Emerging Markets Index Growth: Index growth is calculated as the log difference of the

index created by Morgan Stanley Capital International (MSCI). MSCI is designed to measure equitymarket performance in global emerging markets. (Reuters Ecowin)

Institutional Quality: The constraint on executive variable in Polity IV index is used as a measureof institutional quality as employed by Acemoglu and Johnson (2005). They explain the variable asthe following:

A seven category scale, from 1 to 7, with a higher score indicating more constraint. Score of 1indicates unlimited authority; score of 3 indicates slight to moderate limitations; score of 5 indicatessubstantial limitations; score of 7 indicates executive parity or subordination. Scores of 2, 4, and 6indicate intermediate values.


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The Polity IV dataset is available at http://www.systemicpeace.org/inscr/inscr.htm. Figure A.1 belowpresents the constraint on executive index of Ecuador for 1990-2008 period.

Figure A.1: Constraint on executive index of Ecuador

B Unit Root Tests of Monthly CPI Inflation

Test Statistic P-Value

ADF = -6.7 0.00

Phillips-Perron = -6.7 0.00


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C Alternative Empirical Models for Inflation Uncertainty

Akaike Info Criterion Schwarz Bayesian Criterion

Akaike Info Criterion Schwarz Bayesian Criterion

ARCH(1) -4.96 -4.93

ARCH(2) -5.04 -4.99

ARCH(3) -5.05 -4.99

ARCH(4) -5.05 -4.97

GARCH(1,1) -5.14 -5.09

GARCH(1,2) -5.13 -5.07

GARCH(1,3) -5.15 -5.08

GARCH(2,1) -5.14 -5.07

GARCH(2,2) -5.13 -5.05

GARCH(2,3) -5.16 -5.07

GARCH(3,1) -5.13 -5.05

GARCH(3,2) -5.12 -5.02GARCH(3,3) -5.16 -5.05

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TABLESTable II

Ratio of Oil and Banana Revenues to Total Revenues

Year Crude Petroleum Bananas including plantains

1990 46.4 17.42001 37.1 18.2

2007 53.8 9.4

Table III

Structure of GDP as Ratio of GDP (1990 = 100)

Year Agriculture Mining (Including Oil) Industrial Production Services

1990-1999 11.6% 14.6% 58% 15.8%2000-2006 8.4% 20.4% 5.6% 65.6%

Source: The UNDP web site.

Table IV

Summary Statististics of CPI Inflation and GDP Growth in Different Periods

Whole Period Non-Dollarization DollarizationMean 0.02 0.03 0.01

Standard 0.02 0.021 0.015

Whole Period Non-Dollarization DollarizationReal GDP Mean 4374 3912 4758

Standard Dev. 578 147 517Real GDP Mean 0.008 0.002 0.01

Standard Dev. 0.016 0.02 0.01


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Table V

Analysis of Changes in Inflation (Monthly Data)

CPI Inflation

Dollarization_Dummy -0.02

(-7.74)**

-0.01

(-3.94)**

Lag of Dependent 0.55

Constant 0.03

(17)**

0.01

(0.002)**

R-Squared 0.22 0.46

Number of Obs. 212 211

Notes: Dollarization_Dummy =1 after Q1 2000. t-

statistics are presented in parantheses. * denotes

significant at 5 percent and ** denotes significant at 1

percent.


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Table VI

Analysis of Changes in Macroeconomic Variables (Quarterly Data)

CPI Inflation Real GDP Real GDP Growth

(1) (2) (3) (1) (2) (3) (4) (5) (1) (2) (3) (4) (5)

DollarizationDummy

-0.06(-5.1)**

-0.03(-3.3)**

-0.05(-3.14)**

846.2(7.9)**

67.4(2.7)**

234.6(3.1)**

795.9(7.45)**

580(2.76)**

0.01(2.3)**

0.01(2.05)*

0.01(2.08)*

0.01(2.73)**

0.01(2.11)*

Lag of DependentVariable

0.62(7.2)**

0.63(7.33)**

0.98(43.8)**

0.03(0.22)

Oil ProductionGrowth

-38(-0.15)

0.02(1.82)

World Oil Price25.2

(11.4)**24.13

(9.42)**-0.000(-0.58)

-0.000(-0.69)

MSCI EmergingMarket Index

Growth

216.4(0.96)

255.97(0.96)

-0.003(-0.17)

0.016(0.75)

InstitutionalQuality(Polity IV)

-0.02(-1.51)

360(1.71)

0.00(0.96)

Constant0.09

(12)**0.04

(3.7)**0.16

(1.93)3912.2

(49.5)**108

(1.22)**3429.2

(57.8)**3914

(50.6)**942.4(0.64)

0.002(0.69)

0.002(0.66)

0.004(0.89)

0.001(0.4)

R-Squared 0.28 0.59 0.61 0.54 0.99 0.88 0.54 0.85 0.09 0.09 0.1 0.16 0.11

Number of Obs. 69 68 68 55 54 55 53 52 54 53 54 52 51

Notes: Dollarization_Dummy =1 after Q1 2000. t-statistics are presented in parantheses. * denotes significant at 5 percent and ** denotes significant at 1 percent.


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Table VII

Stability Test Results of the Coefficient of the Constant for Monthly Regressions

(Robustness tests of table V)

Null Hypothesis: No breaks at March

2000

Chow Test Statistic

(1) (2)

F-statistic 52.47 14.56

Log likelihood ratio 47.28 14.28Wald Statistic 52.47 14.56

Notes: P-values of the test statistics are

displayed in parantheses. (1) is the model with

the contant term and (2) is the model with both

the constant term first lag of inflation.

Null Hypothesis: No breakpoints within trimmed data

Number of breaks compared: 148

Quandt-Andrews Statistic

(1) (2)

Maximum LR F-statistic 107.09Maximum LR F-statistic 26.91

Exp LR F-statistic 49.61 9.73

Ave LR F-statistic 38.93 8.59Note: P-values of the test statistics are displayed in parantheses. (1) is

the model with the contant term and (2) is the model with both theconstant term first lag of inflation.


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Table VIII

Stability Test Results of the Coefficient of the Constant for Quarterly Regressions

(Robustness tests of table VI)

CPI Inflation Real GDP Real GDP Growth

(1) (2) (3) (1) (2) (3) (4) (5) (1) (2) (3) (4)

Chow Test

Statistic

F-statistic 14.21

(0.00)

10.82

(0.00)

9.65

(0.00)

50.34

(0.00)

5.54

(0.02)

4.77

(0.04)

41.14

(0.00)

9.76E-15

(1.00)

4.44

(0.04)

3.45

(0.07)

3.33

(0.07)

4.89

(0.03)

Log likelihoodratio

13.28

(0.00)

10.42

(0.00)

9.55

(0.00)

36.22

(0.00)

5.57

(0.02)

4.93

(0.03)

36.12

(0.00)

1.14E-13

(1.00)

4.42

(0.04)

3.54

(0.06)

3.49

(0.06)

4.95

(0.03)

Wald Statistic14.21

(0.00)

10.82

(0.00)

9.65

(0.00)

50.34

(0.00)

5.54

(0.02)

4.77

(0.03)

49.14

(0.00)

9.76E-15

(1.00)

4.44

(0.04)

3.45

(0.06)

3.33

(0.07)

4.89

(0.03)

Quandt-Andrews Statistic

Maximum LRF-statistic

67.72

(0.00)

14.25

(0.00)

13.15

(0.00)

206.97

(0.00)

13.83

(0.00)

43.74

(0.00)

212.32

(0.00)

36.66

(0.00)

5.06

(0.29)

4.01

(0.37)

4.21

(0.34)

5.31

(0.22)

Break PeriodDetermined

2001Q2 2001Q2 2000Q3 2003Q3 2003Q3 2001Q4 2003Q3 2001Q3 2000Q2 2000Q2 2000Q2 1999Q4

Notes: P-values of the test statistics are displayed in parantheses. The stability statistics of each regression specification in table VII is displayed. The breakpoint is the first

quarter of 2000 for the Chow statistic. 48 breaks are compared with the Andrews-Quandt test for inflation and 45 breaks are compared for real GDP. The stability tests can

not be calculated for the fifth regression specification of Real GDP Growth.


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Table IX (GARCH(1,1))Inflation Uncertainty and Dollarization

Inflation Equation

(1) (2) (3) (4)

C

0.0046

(0.02)*

0.004

(0.34)

0.03

(0.5)

AR(1)0.74

(0.00)**0.78

(0.00)**0.97

(0.00)**

MA(1)-0.72

(0.00)**

Variance Equation

C0.001

(0.01)**0.00005(0.00)**

0.0002(0.00)**

0.00003(0.00)**

RESID(-1)^20.12

(0.02)*0.017(0.14)

0.03(0.55)

0.05(0.00)**

GARCH(-1)0.8

(0.00)**0.88

(0.00)**0.2

(0.18)0.87

(0.00)**

DOLLARIZATIONDUMMY-0.0001(0.01)**

-0.00005(0.00)**

-0.0002(0.00)**

-0.00003(0.00)**

CPI INFLATION0.002(0.00)

Adjusted R-square 0.36 0.36 0.4AIC -5.2 -5.92 -5.99 -6.06SIC -5.1 -5.83 -5.88 -5.96

Notes: (P-values are presented under the coefficients in parantheses.)

Table XEndogeneity Test of Money:

The C statistic (also known as a GMM distance or difference-in-Sargan statistic)

Before March 2000 After March 2000

Ho: M1 is Exogenous

Regressor Test Statistic Chi-sq P-Value Test Statistic Chi-sq P-Value2SLS without lag Inflation 0.477 0.4896 48.2 0.0002SLS with lag Inflation 0.006 0.94 16.7 0.000GMM without lag Inflation 0.5 0.48 6 0.01GMM with lag Inflation 0.12 0.73 4.5 0.03

Ho: M2 is Exogenous2SLS without lag Inflation 0.003 0.96 47.9 0.0002SLS with lag Inflation 0.6 0.43 16.7 0.000

GMM without lag Inflation 0.042 0.84 5.2 0.02GMM with lag Inflation 0.6 0.43 4.6 0.03

Ho: Reserve Money is Exogenous

Regressor Test Statistic Chi-sq P-Value Test Statistic Chi-sq P-Value2SLS without lag Inflation 1.14 0.27 53 0.00

2SLS with lag Inflation 2.5 0.11 22.5 0.00GMM without lag Inflation 0.84 0.36 4.5 0.03GMM with lag Inflation 2 0.16 7.1 0.01

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