The Effectiveness of Monetary Policy on Exchange
Rate Stabilization
Adam Gabrielsen
1. Introduction.
This paper examines the effectiveness of monetary policy on exchange rates. Our
increasingly globalized economy has placed much attention on exchange rates and the important
role it plays in international commerce. Exchange rates influences the level of trade and global
competitiveness of countries and can be used as vital signals for global investors. Specifically
this paper looks at how monetary policy influences the competitiveness of countries by
examining exchange rates. To fully attempt to understand the impacts of policy, my research
explores the real effective exchange rates of three emerging economies in addition to three
developed economic systems; defined by the World Bank as low income and high income
countries, respectively.
In order to move forward it is important to define the term competitiveness and the
appropriate monetary policy which is implemented as a result of the country specific goals;
which can be broken down according to imports and exports. A country which aims to increase
net exports would prefer a higher real effective exchange rate and pursue expansionary monetary
policy to increase the money supply and encourage growth. Increasing the money supply leads
to a deprecated currency which makes the total goods and services cheaper to foreign consumers.
On the contrary a currency which is appreciated would follow a contractionary policy to curtail
growth by reducing the money supply by targeting interest rates and reserve requirements. This
results in more expensive goods and services decreasing global competitiveness, leading to an
increase in imports because of the stronger currency.
The paper is organized as follows. Section 2 describes the classical assumptions and
themes of previous literature. Section 3 breaks down the theoretical explanations from the
previous section. Section 4 explains the empirical model and examines the data used to approach
the research question. Section 5 discusses the results of the empirical model. Section 6
concludes.
2. Literature Review
Traditional theory from previous literature supports the concept that higher interest rates
support exchange rates by discouraging capital outflows and encouraging domestic investment
which increases the costs of speculating against the currency (Eiffinger and Goderis, 2008).
More so, higher interest rates can also demonstrate the monetary authorities’ commitment to
support exchange rates in the future, increasing confidence in the currency.
Recently opponents to conventional theory have proposed a new concept. Exchange rate
instability is usually preceded by a broad range of economic indications that vary across counties
(Cumperayot and Kouwenberg, 2013). A growing literature has proposed that higher interest
rates may have adverse effects on exchange rates. Eiffinger and Goderis (2008) and Eiffinger
and Karatas (2012) propose that higher interest rates weaken the currency rather than strengthen
it for advanced economies. Significant relationships have been identified between monetary
policy’s effects on exchange rates. Eijffinger and Karatas (2012) proved that the monetary
policy’s response for emerging economies should be different from the advanced economies,
stating that appropriate policy is often a function of the vulnerability of the country and the
stability of the economy therein.
Opponents to conventional theory argue that the decrease in investor confidence leads to
a decrease in the overall attractiveness in the market. The main critic states that despite the fact
interest rates would increase enough to cover any chances of default, the temporary increase in
discount rates coincides with lower future returns on investments. Lower future returns leads to
depreciation in today currency (Eiffinger and Karatas, 2012). Cumerayot and Kouwenberg
(2013) concluded that high interest rates are considered as symptoms of weak economic and
financial conditions. This may set in motion future economic slowdown and reduce investor
confidence. Eifffinger and Goderis (2008) find empirical evidence to support that higher interest
rates are effective in economies which illustrate weak economic indicators, which are
specifically observed in developing economies.
In regards to developed economies Eiffinger and Goderis (2008) propose that tight
monetary policy increases the probability that real appreciation of the exchange rate occurs
through a nominal appreciation rather than an increase in inflation. In addition to decreasing the
money supply, capital outflows will result in a nominal depreciation and decrease in reserve
assets (Cumperayot and Kouwenberg, 2013). Eiffinger and Karatas (2012) concluded that tight
monetary policy is effective for advanced economies and detrimental in the emerging economies.
3. Theoretical Analysis
The following section elaborates on the recent theoretical implications that were
discussed in section 2.
RER=ƒ(GDP, M)
Where real exchange rates are a function of total expenditures and money supply. The
law of demand can be applied to the exchange rate as follows. The more currency is demanded
the more expensive it us, captured by lower values in nominal exchange rates. The smaller the
RER is the fewer units of domestic currency are needed to purchase an equivalent amount of
foreign currency. The total expenditure of a country is captured by GDP. Higher gross domestic
product is a signal of more international commerce. We assume that more global trade increases
the demand there is for a given currency, strengthening the exchange rate relative to that country.
M represents the money supply, which is known to be increased by decreasing interest rates,
making money more available because it is less expensive to borrow. However as section 2
eludes, higher interest rates may have adverse effects on exchange rates dependant on prior
economic development.
REERi = (NBERtp)W1*(NBERtp)W2*……(NBERtp)Wi
Where REERi represents the real effective exchange rate for a given country indicated by
i. NBERtp denotes the nominal bilateral exchange rate between the domestic country and a
foreign trading partner.
W
is the assigned weight of each NBER based on the amount of total
commerce that occurred between country i and the trading partner. The REER is dissimilar to
the RER in that the REER is a representation of the purchasing power, relative to the trading
partners of country i. It is for this reason the REER is used in my model as it a more accurate
representation of exchange rates taking into account purchasing power.
Consequently, the effects of interest rates on the real effective exchange rate can be
justified as follows. Decreasing the money supply, in the form increasing interest rates, holding
demand of the currency constant decreases the exchange rate, effectively appreciating the
currency. As the nominal exchange rate decreases for country i the real effective exchange rate
will also decrease and a smaller quantity of domestic currency can now be exchanged for the
equal amount of foreign currency prior to the interference of monetary policy.
4. Empirical Justification
The empirical model examines a panel data set. The study covers six countries – Brazil,
China and Mexico to account for emerging economies; and Japan, Norway and the United States
to account for developed economies. The model consists of seven indicators covering the ten
year period from January 1st of 2000 to January 1st of 2010. All the data used in the regression
was compiled from the Federal Reserve Bank of St. Louis economic research database. The
database is maintained by the research division, which covers a wide range of economic
indicators. The panel data was compiled by the Federal Reserve and collected from Unites
States government agencies such as the Bureau of Labor Statistics and the U.S. Census.
To the test the effectiveness of monetary policy on exchange rates I have constructed the
following empirical model, which is based off previous literature and macroeconomic theory as I
believe it pertains to my research question.
Real Effective Exchange Rate =B0 + B1Inflation + B2Unemployment + B3 Interest rates
+B4Current Account Balance + B5GDP per capita + B6Bank reserves + B7 Nominal spot
exchange rate + B8 interestrate2 + B9Country_2 + B10Country_3 + B11Country_4 +
B12Country_5 + B13Country_6 + B14CountryXRealIS_2 + B15CountryXRealIS_3 +
B16CountryXRealIS_4 + B17CountryXRealIS_5 + B18CountryXRealIS_6 + e
I hold the Real Effective Exchange Rate dependant; and investigate the monthly
percentage change for each country. According to the International Monetary Fund the real
effective exchange rate provides economists and policy makers with a measure of currencies
overall alignment. The measure indicates an average of bilateral real exchange rates between the
country and each of its respective trading partners, which exposes the purchasing power of each
currency. A value of zero for a country’s real effective exchange rate indicates the currency is in
parity. The higher the value for exchange rates the more depreciated the currency is, as it takes
more of one currency to exchange for an equivalent quantity of another currency. Conversely the
lower the value the more appreciated the currency is.
Government faces a tradeoff between exchange rate stability and other policy goals,
specifically targeting inflation, output growth which is measured as gross domestic product per
capita and unemployment (Eijffinger and Karatas, 2012). Inflation provides an accurate measure
of economic and country specific stability. The measure is scaled using a 100 point scale, with
2005 representing the base year for each country. Theory proposes that lower levels of inflation
are signs of domestic economic stability, which is attractive to foreign investor. As investor
confidence increases the demand for the currency increases appreciating the currency.
Consequently a negative coefficient estimate correlates to the appreciation of currency.
Gross domestic product per capita is used as a measure of economic stability and country
risk and is measured in terms of US dollars. A lower growth rate may weaken foreign investor
confidence on expectations of future returns and could affect the ability to meet foreign debt
obligations; which would lead to a decrease in the demand for the domestic currency resulting in
a depreciation of the currency. We expect higher values to coincide with negative coefficient
estimates which would appreciate currency and decrease the real effective exchange rate.
Unemployment is measured in terms of the percentage of total population and adjusts for
persons under fifteen. Macroeconomic theory suggests lower unemployment is another sign of
economic stability which is, which is attractive to foreign investors. As investor confidence
increases the demand for the currency increases appreciating the currency. Positive parameter
estimates for unemployment should transfer to an appreciation of currency.
Interest rates are used a means for measuring monetary policy, where the ultimate goal is
to manage the money supply for a given currency. Recent theoretical evidence supports the
concept that higher interest rates have adverse affects on exchange rates through their impact on
economic fundamentals (Eijffinger and Goderis, 2008). Noting that decreasing interest rates
increases consumer confidence more so than rising interest rates support the probability of
default and overall attractiveness. Interest rate may have a curvilinear effect. Because interest
rates can only decrease so far; at one point they will be too low to have an effect on exchange
rates. This is indicative of a change in slope for the curvilinear effect; however when alone
interest rates measured should exhibit negative slope coefficients.
Reserve assets can be used to support the exchange rate; therefore higher reserves are can
be expected to strengthen the currency and increase confidence because of low default risk. The
indicator is measured in terms of US dollars. Therefore negative parameter estimates are
associated with higher appreciated currencies.
The nominal spot Exchange rate is used to account for the nominal monthly changes in
exchange rates and is quoted in term of the domestic currency to the USD. To accurately
measure the USD my research compiled data from the US trade weighted index. An increase in
the exchange rate implies a loss of competitiveness and increases the chances of deprecation to
restore the economies competitive long run position from both a theoretical and speculative
standpoint. The smaller the exchange rate is the stronger the currency is, relative to its
comparative currency. More over as the parameter estimate for exchange rates decreases and
becomes more negative, the change should imply an appreciate in the real effective exchange
rate.
Another indicator which affects the valuation of currency is the current account balance.
The variable was chosen to collectively represent the effects of imports and export on exchange
rates. Prior literature indicates the importance of capital outflows as it pertains to the demand of
currency. Positive currency balances are indicative of net capital inflows to the country,
indicating depreciation in exchange rates. Hence a positive coefficient estimate is associated
with depreciation in the real effective exchange rate.
To accurately examine the country specific impacts it is important to include a set of
dummy variables accounting for each country. Country_1 (=1 or 0), Country_2 (=1 or 0),
Country_3 (=1 or 0), Country_4 (=1 or 0), Country_5 (=1 or 0), Country_6 (=1 or 0). Where
country 1 represents Brazil, country 2-China, country 3-Japan, country 4-Mexico, country 5Norway and country 6-USA. I have purposefully omitted variable Country_1 to avoid the
dummy variable trap and avoid “mushy” results. The use of dummy variables is to distinguish
between the country specific indictors and respective effects on the real effective exchange rates.
To address prior literature conclusions regarding the effectiveness on monetary policy on
exchange rates, I interact the country specific dummy variables with interest rates to distinguish
between the effects of interest rates specifically by country. Country_1XIR (=1 or 0),
Country_2XIR (=1 or 0), Country_3XIR (=1 or 0), Country_4XIR (=1 or 0), Country_5XIR (=1
or 0), Country_6XIR (=1 or 0). The variable indicators operate on the same scale used above,
where Country_1XIR was purposely omitted. Furthermore, to test the interest rate effect on
country specific factors I derive the interest rate from the base empirical model.
BREALIS + 2BISsq*IScountry + BCountry
Using IScountry to denote the countries average interest rate, BCountry to measure the country
specific effects of the economy, and the BREALIS + 2BISsq as the measure of the overall effect of
interest rates.
5. Empirical Results
To examine the effects of monetary policy on exchange rate stability; pooled OLS
estimation methods have been used. Six independent variables are significant before further
analysis was conducted to test for the presence of multicollinearity, heteroscedasticity and serial
correlation. The effects of nominal spot exchange rates, unemployment and reserve assets on the
real effective exchange rate are found to be significant at the 90% level. Interest rates effects on
exchange rates are significant at the 95% level. At the 99% significant level the quadratic effect
of interest rates and the country effects of Mexico were found to be significant. The adjusted R
squared is 0.0378, meaning that 3.78% of the variation in the real effective exchange rate is
explained through the variation in the independent variables while taking into account the loss in
degrees of freedom. On possibility for the low adjusted R squared in evident when examining
the data. Most of the data was manipulated into percent changes to equalize country specific
factors; namely reserve assets, GDP per capita, inflation and current account balances. The
remaining data was already in the form of percentages.
My empirical model includes several more complex variables. I believe Interest rates
may have a curvilinear effect and included IRsq to account for this effect. Interest rates can only
decrease so far; at one point they will be too low to have an effect on exchange rates. This
indicates a change in slope i.e. a curvilinear effect. To measure the country specific economic
indicators I include each country as a dummy variable, where 1= the domestic country and thus
the domestic economic indicators, and 0=foreign country where economic factors have no
presence. To measure the interest rate effect on country specific indicators I created a dummy
variable interaction between interest rates and country specific factors. To quantify these
interactions I derived all indications of interest rates from the base empirical model to capture the
change in the real effective exchange rate over the change in interest rates.
BREALIS + 2BISsq*IScountry + BCountry
Too test for multicollinearity I used the variance inflation indicator. The results of this
test concluded that every variable, with the exception of the country specific interaction of Japan
on interest rates and reserve assets were found to be highly correlated with the other independent
variables. The effects of multicollinearity on my model explain the loss of efficiency which is
found in the higher standard errors for each country. Although it does not explain the low
adjusted R squared.
A deeper look into the effects of multicollinearity conclude the significant of the effects
of inflation and current account balances on exchange rates at the 95% significance level when a
joint test is preformed. In addition a joint test between GDP per capita and the country specific
effects indicates a statistically significant effect is present at the 95% level for all countries
expect Mexico. Furthermore Mexico as both a country specific indication and as a dummy
interaction if not found to be statistically significant when the joint test was preformed. It is
important to note that multicollinearity exists in my model. Tests of joint significance were
preformed; however I do not drop any variables to increase the explanatory power of my model.
It is unlikely that heteroscedasticity is present in my model. In addition to using a panel
data set, the data accounts for large differences in size using percentages and base values which
may be used as indications of the illness (Halcoussis, 2005). Ultimately, the white test allows for
the failure to reject the null hypothesis, which states that heteroscedacitiy is present.
There is evidence to ascertain the existence of serial correlation in my regression. The
low adjusted R squared indicates that there are important variables missing from my model
which increases the error term as well as the possibility that serial correlation exists (Halcoussis,
2005). However no efforts were made to test for illness, dismissing any possibilities of the
presence of serial correlation on the basis that no tests were conducted.
Specific and significant coefficient estimates are explained herein. It is also important to
acknowledge that following explanations are only true when holding all other variables constant.
Beginning with the most significant independent variable, for every one percent increase in
interest rates the real effective exchange rate will appreciate by 0.997 in terms of purchasing
power. To test for a curvilinear effect of interest rates, as the interest rate squared increases by
one percent, the currency will depreciate the purchasing power by 0.023. For every ten billion
USD increase in the current account balance will result in a depreciation of the respective
currencies purchasing power by 0.0022 which is inconsistent theory. For every one percent
increase in monthly reserve assets the real effective exchange rate will depreciate by 0.675 in
regards to purchasing power and is also found to be inconsistent to prior theory. Using 2005 as a
base year, every one basis point increase in the consumer price index will depreciate purchasing
power by 0.027. Every one percent increase in unemployment will appreciate the purchasing
power of exchange rates by 0.245. For every one thousand USD increase in GDP per capita the
purchasing power will appreciate by 0.136. For every one unit of currency increase in the
nominal spot exchange rate the real effective exchange rate will appreciate by 0.033 in regards to
purchasing power.
When measuring country specific effects, Chinese economic factors will appreciate the
purchasing power of the Chinese Yuan by 16.021. Japanese country specific economic factors
will appreciate the purchasing power of the yen by 8.297. Country specific factors for Mexico
will appreciate the peso by 7.147, regarding purchasing power. Country specific economic
factors for Norway will appreciate the currency’s purchasing power by 4.289. The USD will
appreciate by 6.206 for country specific economic factors.
When measuring for the effect of interest rates on country specific factors, the effect of
interest rates on Brazil will depreciate the purchasing power of the Brazilian Real by 9.304. The
effect of interest rates on China will depreciate the Chinese Yuan by 2.399 in regards to
purchasing power. The effect of interest rates on Mexican country specific economic factors will
depreciate the peso by 2.129. The effect of interest rates on the Japanese will depreciate the Yen
by 0.788 in regards to purchasing power. The effect of interest rates on Norway’s economy will
depreciate Norwegian currency by 1.840 in regards to purchasing power. The effects of interest
rates on the United States economy will depreciate the USD by 1.382, regarding purchasing
power.
Accurately testing the effects of monetary policy on the real effective exchange rate
requires including a vast array of independent variables to measure the countless economic
indicators which influence purchasing power. My model most likely suffers from omitted
variable bias. The low explanatory power of adjusted R square ascertains that the error term
includes relevant independent variables, therefore violating classical assumption of OLS. Other
variables which are relevant include corporate debt, country debt and investor speculation.
Based on previous literature I predict lower levels of corporate and country debt to decrease
speculative attacks against the domestic currency. Investor speculation is measured through
investor confidence level; where higher levels of confidence would appreciate the currency
through an increase in demand for the risk averse currency.
Bais = Bomit * Bincluded ,
Bais = (-) * (-),
Bais = (+)
I predict the omitted relevant variables to appreciate the real effective exchange rate and
indicate a negative slope coefficient. Thus the bias will be systematically larger than the true
coefficients.
From the regression results in table 1 we can make the following conclusions. The
interest rate effect on country specific factors is far greater for countries with higher interest
rates. Emerging economies will therefore be subject to more volatility the purchasing power,
measured by the change in the real effective exchange rate as a result of higher, on average
interest rates. Conversely, interest rates have a much smaller effect on the developed economies
in the sample, which is most likely due to lower average interest rates. The emerging economies
of Mexico and Brazil have on average, higher interest rates than the Japan, Norway and the
United States. However, China’s relative lower interest rates coincide with similar interest rate
effects on country specific factors. This provides evidence to conclude that countries which have
higher interest rates have a larger interest rate effect on country specific economic factors;
regardless of their level of economic development. Furthermore, my results to not find evidence
that link adverse purchasing power effects to developed economies with higher interest rates.
6. Conclusion
This paper examines the effectiveness of monetary policy on exchange rates, looking at
six different economic systems from 2000 to 2010. To quantify the results this paper use OLS
regression analysis to estimate and interpret the country specific effects of monetary policy. In
response to previous literature’s unconventional approach and dispute to prior macroeconomic
theory, proposing that adverse effects arise from higher interest rates in more developed country.
The results of my empirical analysis do not conclude that there is evidence of adverse affects.
The results do however; conclude that higher overall interest rates have a larger affect on the
purchasing power than economies with lower overall interest rates, regardless of the level of
economic development. The effect can be interpreted that lower interest rates correlate to less
volatility and therefore more exchange rate stability. It is not unreasonable to conclude that an
increase in stability leads to increased investor confidence, which can be translated into increased
demand for that currency and ultimately an appreciation of the currency. Based on the
regressions it can also confirm that different monetary policy should be used to achieve policy
goals based on the level of economic development.
Further research to examine exchange rate stability should include variables that measure
investor confidence, as speculation plays an important role in the demand of currency. It is
possible that my sample data was not large enough, in regards to both duration of observations
and the total countries observed. A larger sample may have indicated more clearly that higher
interest rates do have adverse effects on developed economies which could support recent
theoretical findings.
Table 1: Analysis Sample Descriptive Statistics
Variable Name
N
Mean
Minimum
Maximum
Interest Rate
630
6.664
0.100
33.898
Reserve Assets
720
0.027
-0.529
5.458
Interest Rate Squared
630
107.958
0.010
1149.084
Nominal Spot Exchange Rate
726
38.142
1.590
133.643
Current Account Balance
726
-3.64e+10
-7.98e+11
3.58e+11
Inflation (Consumer Price Index)
726
86.775
52.532
103.193
Unemployment
726
5.840
1.717
12.748
Gross Domestic Product Per Capita
726
26168.450
949.178
64772.000
China
726
0.167
0
1
Mexico
726
0.167
0
1
Japan
726
0.167
0
1
United States
726
0.167
0
1
Norway
726
0.167
0
1
China*Interest Rates
630
0.604
0
4.140
Mexico*Interest Rates
630
0.260
0
8.250
Japan*Interest Rates
630
0.059
0
0.750
Norway*Interest Rates
630
0.879
0
7.520
United States*Interest Rates
630
0.642
0
6.250
Table 2: Regression Model Results (Dependent variable= Real Effective Exchange Rates)
Variable Name
Parameter Estimate
-0.997**
Interest Rates
0.414
-0.032*
Nominal Spot Exchange Rate
0.018
0.674*
Reserve Assets
0.347
0.023***
Interest Rates Squared
0.008
2.210
Current Account Balance
1.300
0.267
Inflation (Consumer Price Index)
0.020
-0.245*
Unemployment
0.126
-0.000
Gross Domestic Product Per Capita
0.000
-16.021***
China
5.200
-7.148
Mexico
4.996
-8.297
Japan
5.325
-6.206
United States
5.976
-4.289
Norway
6.999
1.911***
China *Interest Rates
0.685
0.051
Mexico *Interest Rates
0.443
1.641
Japan * Interest Rates
1.037
0.692*
Norway * Interest Rates
0.354
0.811**
United States *Interest rates
0.385
Adjusted R-Square
Sample Size
0.0378
625
Appendix.
The following justification discusses the independent variables.
The Real Effective Exchange Rate, based on Manufacturing Consumer Price Index- Used as the dependent
variable. Measured monthly in percentage change. Not seasonally adjusted.
Nominal Spot Exchange Rate- measured the monthly average exchange rate between each country in terms of
United States Dollars. To measure the USD, a trade weighted index was used.
Interest Rates- the Discount Rate measured monthly by levels as a percent. Not seasonally adjusted.
Unemployment- an annual measure of those aged 15 years and old as a percentage of total population per country.
Not seasonally adjusted.
Gross Domestic Product Per Capita- measured annually in current USD. Not seasonally adjusted
Current Account Balance- an indication of the total trade of goods and services, measured annually and in USD.
Seasonally adjusted.
Reserve Assets- measured monthly and converted into percentage change to equalize exchange rates. Not
seasonally adjusted.
Consumer Price Index- Used as an indicator of inflation. Measured annually using 2005=100 as the base year.
The data is not seasonally adjusted.
Variance Inflation Factor- used to test for Multicollinearity.
Variable
VIF
1/VIF
realIS
1224.48 0.000817
_ICountry_5
903.25 0.001107
_ICountry_6
789.28 0.001267
GrossDomes~a 707.57 0.001413
_ICountry_3
633.32 0.001579
_ICountry_2
475.72 0.002102
ISsq
372.57 0.002684
_ICountry_4
107.52 0.009301
realNSER
84.31
0.011861
_ICouXreal~2 82.85
0.012070
_ICouXreal~5 56.78
0.017611
_ICouXreal~6 41.34
0.024188
_ICouXreal~4 38.48
0.025988
Unemployment 20.59
0.048573
CurrentAcc~t
17.66
0.056615
Inflation
5.59
0.178935
_ICouXreal~3 3.21
0.311899
realBK
1.05
0.954939
Mean VIF
309.20
Joint Tests
test GrossDomestProductperCapita _ICountry_3
( 1) GrossDomestProductperCapita = 0
( 2) _ICountry_3 = 0
F( 2, 606) = 3.40
Prob > F = 0.0339
. test GrossDomestProductperCapita _ICountry_4
( 1) GrossDomestProductperCapita = 0
( 2) _ICountry_4 = 0
F( 2, 606) = 2.59
Prob > F = 0.0761
. test GrossDomestProductperCapita _ICountry_5
( 1) GrossDomestProductperCapita = 0
( 2) _ICountry_5 = 0
F( 2, 606) = 4.87
Prob > F = 0.0080
. test GrossDomestProductperCapita _ICountry_6
( 1) GrossDomestProductperCapita = 0
( 2) _ICountry_6 = 0
F( 2, 606) = 3.46
Prob > F = 0.0320
White Test for Heteroscedactisty
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Ho: Constant variance
Variables: fitted values of realREER
chi2(1) = 8.62
Prob > chi2 = 0.003
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