The impact of news in the dollar/deutschmark
exchange rate: Evidence from the 1990’s
Stefan Krause∗
December 2004
Abstract
In this paper I analyse three specifications of spot exchange rate models by using an
alternative approach in defining the news variable. In particular, I employ quarterly
data of the U.S. dollar / German Deutschmark exchange rate for the period 1991-1998
in order to determine whether the effect of news announcements on the exchange rate
is still present in the decade of the 1990’s.
The empirical evidence suggests that news do not seem to provide explanatory
power for justifying deviations from either the efficient markets hypothesis or the uncovered interest rate parity. Nevertheless, newspaper announcements and news about
inflation do contribute significantly in explaining short run departures from purchasing
power parity (PPP) with the expected sign, supporting the view that deviations from
PPP will arise from new information available in the market.
JEL classification: F31, F41, G15
Keywords: Spot and forward exchange rates, news, unanticipated inflation, efficient
market hypothesis, purchasing power parity.
∗
Department of Economics, Emory University. I want to thank Nelson Mark and Juan Muñoz for useful
discussion. All errors are mine. For comments, please contact me at skrause@emory.edu, 404-727-2944
(phone), or 404-727-4639 (fax).
1
Introduction
Since the late 1970’s several authors have tested the hypothesis that announcements
of new information have an effect on the spot exchange rate market, as it is the case with
other asset prices. Looking at evidence from the 1970’s, Frenkel (1981) points out that new
information, rumours and “news” in general will affect expectations and hence, the behaviour
of the spot exchange rate. Furthermore, he claims that these resulting fluctuations in the
exchange rate cannot be predicted by the lagged forward rate. In his model he defines
“news” as unexpected changes in the interest rate differential, and finds statistical evidence
that news affect the dollar/pound and dollar/frank exchange rates, but not the dollar/mark
spot rate.
For the period between October 1979 and August 1984, Hardouvelis (1988) models
the percentage change in a foreign currency price in a given business day as a function of the
unanticipated component of fifteen economic series, finding in the case of the dollar/mark
price a significant effect of unexpected changes in the following indicators: M1, bank reserves,
surcharge rates, durable goods and retail sales.
Hogan, Melvin and Roberts (1991) study yet another news variable: U.S. trade
balance announcements. For the decade of the 1980’s, using daily data, they find that the
forecast error (based on the survey expectations statistics) is significant in explaining changes
in the spot rate for the dollar/mark, dollar/pound and dollar/frank exchange rates, with the
expected sign (i.e., an unexpectedly high trade deficit causes the dollar to depreciate).
Karfakis and Kim (1995) also look at current account news for the case of the
Australian dollar, finding as well that worse than expected announcements result in a depreciation of the currency. Krause (1996) uses a similar approach to analyze the impact of
news announcements and changes in foreign currency reserves on the nominal exchange rate
in Costa Rica.
Finally, Edison (1997) considers expectation errors of the following U.S. indicators:
consumer price index (CPI), producer price index (PPI), industrial production (IP), retail
1
sales (RS), unemployment rate (UN) and non-farm enrolment (NF), and finds that the
dollar/mark rate responds to news in UN and NF for the entire sample (1980-1995) at or
below 10% significance level. The author further separates into “good” and “bad” news,
which results in a significant effect of RS news to the exchange rate as well.
In this paper I analyse three specifications of spot exchange rate models, to determine whether the effect of news on the exchange rate is still present in the decade of the
1990’s, by using an alternative approach in defining the news variables. Section 2 describes
the construction of the news indices and section 3 presents the empirical results, with the
dollar/mark exchange rate level and its first difference as the dependent variables. Section
4 summarises the main findings and discusses the limitations of the approach used.
2
Constructing the news indices
Hardouvelis (1988) and Hogan, Melvin and Roberts (1991) consider daily information to
construct the news indices, whereas Edison (1997) and Cavaglia and Wolff (1996) focus on
monthly and quarterly data, respectively. I will follow the latter approach, since I’m interested in considering the effect of published newspaper articles on the behaviour of “partially
uninformed agents”. By partially uninformed agents I mean agents that do not receive the
information about market developments and changes of indicators immediately after they
have been published, but rather react to newspaper articles and headlines about the general
state of the economy and, specifically, about the foreign trade balance. In general, there
will be “good news about the economy” when paper articles and editorials comment on the
economy blooming, unemployment falling, and a better than average growth in the leading indicators index, whereas there will be “bad news about the economy” if the contrary
happens. Similarly, “good news about the trade balance” will arise when papers refer to a
decrease in the trade deficit and conversely when defining “bad news about trade balance”.
The news indices are constructed by collecting the newspaper abstracts on articles
2
relating to economic indicators in the journal index of the OHIOlink database, which engulfs
information published since 1989. The search was limited to the period from 1991:1-1998:12,
given that Germany joined the European Monetary Union in January 1999. This search
resulted in a total of 2883 headlines of economic news. After eliminating the non-relevant
headlines, the number of abstracts was reduced to 1148.
The economic news index was constructed in the following way: For every month, a
value of ‘1’ was assigned in case there have been overall “good news about the economy”,
as defined above; for practical purposes, a month in which only “good news” or a ratio at
or above 3-to-1 between “good news” and “bad news” were published, was assigned a value
of ‘1’. Analogously, a month in which either only “bad news” or the ratio of “bad news” to
“good news” was equal or greater than 3, was assigned a value of ‘-1’. Finally, for months in
which there were “mixed news” (ratios smaller than 3) or no news, the value was set equal
to ‘0’.
For the current account news index the process was simpler, since during the analysed
period there were no mixed or contradictory statements. On months in which there were
announcements of a smaller trade and/or current account deficit, the assigned value was ‘1’
and months in which newspapers were writing about bigger trade and/or current account
deficits were given a value of ‘-1’. Consistently, a value of ‘0’ was assigned for months in
which no news were published.
Given that the alternative specifications were tested using quarterly data, the data
in both indices was aggregated to obtain quarterly news dummies; each dummy variable
would then have an integer value between —3 and 3, depending on the number of months per
quarter where good and/or bad news appeared on the headlines.
Finally, I also included a continuous variable of news: the difference between expected
and actual inflation. For expected inflation I used the data of the University of Michigan
Consumer Surveys of Consumers, Survey Research Center (http://www.isr.umich.edu/src),
and considered the discrepancy between the actual and expected annual inflation for the last
3
month of each quarter.
3
Estimation Method and Empirical Results
In this section I consider three different specifications of spot exchange rate models, and
proceed to test whether the three news variables defined above have any impact on the level
of the exchange rate or the change thereof. The first model looks at the efficient market
hypothesis (EM); the second considers uncovered interest parity (UIP) and the last one
focuses on deviations from purchasing power parity (PPP). In all cases I use the quarterly
dollar-mark rate and define the exchange rate as the Deutschmark value of the U.S. dollar.1
Hence, an increase in the exchange rate represents an appreciation of the dollar.
3.1
News and Efficient Markets
Following Frenkel (1981), and Baillie and McMahon (1989), the relevance of news in the
EM model can be tested using the following equation:
st = a0 + a1 ft−1 + a02 news + ε1,t ,
(1)
where st is the log of the spot exchange rate at the end of the quarter; ft−1 is the log value of
the 3-month forward rate, also at the end of the quarter; news is as vector composed of the
variables NC (news about the trade/current account deficit), NE (news about the overall
state of the economy), UI (unexpected inflation, as defined in Section 2); and ε1,t is the
residual. The results of estimating (1) through ordinary least squares (OLS) are presented
in Table 1.
For this particular specification, the news variables appear with the expected sign
(good news about the trade deficit and the state of the economy cause an appreciation of the
1
Quarterly data for the spot and forward exchange rates, consumer prices, industrial production indices,
money supply and interest rates were obtained from Datastream (1991:I-1998:IV).
4
dollar; while higher than expected inflation causes a depreciation), but are not significant
at a 10% level. Another interesting feature is that the coefficient of the lagged forward rate
is significantly less than one and the intercept is different than zero, which differs from the
findings described by Frenkel (1981). However, since the objective of this paper is to analyse
the role of news, I will omit any further characterisation and discussion of this result.
3.2
News and Uncovered Interest Parity
The second model incorporates news in the UIP specification. Hence, the equation to
be estimated is given by (2)
st+1 = b0 + b1 (i∗t − it ) + b02 news + ε2,t ,
(2)
where it is the 3-month U.S. Treasury-Bill interest rate; i∗t is the 3-month German FIBOR
rate; and news and ε2,t are as above defined. Results of the OLS estimation of the model
are displayed in Table 2.
For this particular model, neither of the news variables is significant at the 10%
level and, furthermore, the unexpected inflation regressor appear with the opposite sign.
Hence, we cannot conclude that the inclusion of these variables provides an explanation for
deviations in UIP.
3.3
News and Purchasing Power Parity
For the last model I incorporate the news variables as a means to explaining deviations
from PPP. Hence, the specification starts with equation (3):
st = p∗t − pt + χ0 news ,
5
(3)
where pt and p∗t represent the CPI in the U.S. and Germany, respectively, expressed in
logarithms.
Using the conventional money market equilibrium conditions (Engel and Frankel,
1984) and assuming that both the elasticity of income (φ) and the semi-elasticity of interest
rate (λ) are the same for both countries, we have:
mt − pt = φyt − λit ,
(4)
m∗t − p∗t = φyt∗ − λi∗t ,
where mt , m∗t , yt and yt∗ are the logs of U.S. and German money supply and output for each
country, respectively.2
Finally, assuming covered interest parity (CIP) holds results in the following:
ft − st = (i∗t − it ) .
(5)
Combining equation (3) and equation (4) yields:
st = m∗t − mt − φ(yt∗ − yt ) + λ(i∗t − it ) + χ0 news .
(6)
Substituting the CIP condition of equation (5) into equation (6):
st = m∗t − mt − φ(yt∗ − yt ) + λ(ft − st ) + χ0 news ,
which implies
st = ψ(m∗t − mt ) − φψ(yt∗ − yt ) + (1 − ψ) ft + ψχ0 news ,
2
(7)
For the estimation, I consider for both countries the monetary aggregate M1 as the money supply variable
and total industrial production index as a proxy for output.
6
1
where ψ= 1+λ
.
Assuming that the relationship in equation (7) holds up to a constant term we proceed
to estimate the following specification through OLS:
st = c0 + c1 (m∗t − mt ) + c2 (yt∗ − yt ) + c3 ft + c4 news + ε3,t .
(8)
The results of estimating (8) are presented in Table 3a. For this specification all news
variables are significant at the 10% level, with UI significant at the 1% level, and all three
coefficients have the expected signs. These findings support the view that deviations from
PPP will arise from new information available in the market and these innovations will not
be completely reflected in CPI changes.
Finally, in order to verify the robustness of the above results, I proceed to compute
the White corrected standard errors and also consider a model specification that relaxes the
assumption that the elasticity of income and the semi-elasticity of interest rate are the same
for both countries. The results are presented in Table 3b.
These results allow us to note two important observations. First, we find that our
previous results are robust to heteroskedasticity corrected errors and the described changes
in the assumptions of the money equilibrium parameters. Second, news about the current
account and news about the economy become significant at the 1% and 5% level respectively,
which contributes in reinforcing the above described results. These observations lead us to
conclude that newspaper announcements regarding the economy and unanticipated inflation
explain quite robustly deviations from PPP.
4
Conclusions
The main results of this paper, as well as some limitations of the analysis, can be
summarised in the following points:
7
• The news variables, as defined in section 2, do not seem to provide explanatory power
for justifying deviations from either the efficient markets hypothesis or the uncovered
interest rate parity.
• Newspaper announcements and news about inflation, however, do explain significantly
short run departures from purchasing power parity with the expected sign, supporting
the view that deviations from PPP will arise from new information available in the market. These results are robust to corrected errors and modifications in the assumptions
of the money market equilibrium parameters.
• One major limitation of the study is that, given that the expected inflation index is
constructed by considering the median expected price change over the twelve months
after the survey, inflationary surprises of either sign tend to be positively correlated
on a month-by-month basis, which entails systematic error by the agents. Hence, if we
are willing to assume that consumers adjust to these errors in a smaller time frame,
the interpretation of the significance of the coefficient has to be careful.
8
5
Appendix: Data Sources
Data for the spot and forward Deutschmark/U.S. dollar exchange rates, and con-
sumer prices, industrial production indices, M1 and interest rates for the U.S. and Germany were obtained from Datastream. The information used to compute the news indices
was collected from newspaper abstracts on articles relating to economic indicators in the
journal index of the OHIOlink database. Expected inflation was computed using the data
of the University of Michigan Consumer Surveys of Consumers, Survey Research Center
(http://www.isr.umich.edu/src).
9
References
[1] Baillie, R. and McMahon, P. (1989). The foreign exchange market: Theory and econometric evidence. Cambridge University Press.
[2] Cavaglia, S. and Wolff, C. (1996). "A note on the determinants of unexpected exchange
rate movements", Journal of Banking and Finance, 20, pp. 179-188.
[3] Edison, H. (1997). "The reaction of exchange rates and interest rates to news releases",
International Journal of Financial Economics, 2, pp. 87-100.
[4] Engel, C. and Frankel, J.A. (1984). "Why interest rates react to money announcements:
An explanation from the foreign exchange market", Journal of Monetary Economics, 13,
pp. 31-39.
[5] Frenkel, J. (1981). "Flexible exchange rates, prices and the role of ‘news’", Journal of
Political Economics, 89, pp. 665-705.
[6] Hardouvelis, G. (1988). "Economic news, exchange rates and interest rates", Journal of
International Money and Finance, 7, pp. 23-35.
[7] Hogan, K., Melvin, M. and Roberts, D.J. (1991). "Trade balance news and exchange
rates: is there a policy signal?", Journal of International Money and Finance, 10, pp.
S90-S99.
[8] Karfakis, C. and Kim, S-J. (1995). "Exchange rates, interest rates and current account
news: some evidence from Australia", Journal of International Money and Finance, 14,
pp. 575-595.
[9] Krause, S. (1996). "Influencia de las noticias en el comportamiento del tipo de cambio
nominal: El caso de Costa Rica (1990-1995)", Instituto de Investigaciones en Ciencias
Económicas (IICE), Documento de Trabajo No. 190, San José, Costa Rica.
10
Table 1: News and Efficient Markets
Explanatory variable
Spot rate (w/o news
variables)
Spot rate (with news
variables)
Intercept
• t-statistic
• (p-value)
0.080
2.475
(0.019)
0.101
2.753
(0.011)
Lagged forward rate
• t-statistic
• (p-value)
0.839
12.51
(0.000)
0.787
9.700
(0.000)
NC
• t-statistic
• (p-value)
0.014
1.397
(0.174)
NE
• t-statistic
• (p-value)
0.005
1.436
(0.163)
-0.643
-0.640
(0.528)
UI
• t-statistic
• (p-value)
Adjusted R2
0.838
0.839
Durbin-Watson
1.905
1.901
31
31
No. of observations
11
Table 2: News and Uncovered Interest Parity
Explanatory variable
Change in the spot rate
(w/o news variables)
Change in the spot rate
(with news variables)
Intercept
• t-statistic
• (p-value)
0.003
0.359
(0.722)
0.012
1.053
(0.302)
Interest rate differential
• t-statistic
• (p-value)
-0.058
-0.251
(0.844)
-0.152
-0.499
(0.622)
NC
• t-statistic
• (p-value)
0.017
1.147
(0.262)
NE
• t-statistic
• (p-value)
0.007
1.518
(0.141)
2.161
1.587
(0.528)
UI
• t-statistic
• (p-value)
Adjusted R2
-0.033
0.198
Durbin-Watson
1.575
1.588
31
31
No. of observations
12
Table 3a: News and Purchasing Power Parity
Explanatory variable
Spot rate (w/o news
variables)
Spot rate (with news
variables)
Intercept
• t-statistic
• (p-value)
0.113
1.590
(0.123)
0.115
2.256
(0.033)
Forward rate
• t-statistic
• (p-value)
0.783
8.154
(0.000)
0.730
10.68
(0.000)
M1 differential
• t-statistic
• (p-value)
0.036
0.513
(0.612)
-0.008
-0.161
(0.873)
IP index differential
• t-statistic
• (p-value)
-0.048
-0.562
(0.578)
0.035
0.549
(0.588)
0.014
1.883
(0.071)
NC
• t-statistic
• (p-value)
0.005
1.861
(0.075)
NE
• t-statistic
• (p-value)
-3.938
-5.693
(0.000)
UI
• t-statistic
• (p-value)
Adjusted R2
0.778
0.898
Durbin Watson
1.518
2.48
32
32
No. of observations
13
Table 3b: News and Purchasing Power Parity
(Specification with White Standard Errors)
Explanatory variable
Spot rate (with news
variables, φ=φ*, λ=λ*)
Spot rate (with news
variables, φ≠φ*, λ≠λ*)
Intercept
• t-statistic
0.115
2.582
1.254
1.117
Forward rate
• t-statistic
0.730
11.83
0.659
12.25
M1 differential
• t-statistic
-0.008
-0.164
IP index differential
• t-statistic
0.035
0.639
US M1
• t-statistic
-0.049
-0.657
German M1
• t-statistic
0.302
1.440
US IP index
• t-statistic
-0.464
-1.411
German IP index
• t-statistic
-0.120
-0.585
NC
• t-statistic
0.014
2.636
0.015
2.783
NE
• t-statistic
0.005
2.069
0.005
2.288
UI
• t-statistic
-3.938
-6.195
-4.039
-6.460
Adjusted R2
0.898
0.899
Durbin Watson
2.48
2.52
32
32
No. of observations
14