RATIONALITY OF SURVEY BASED INFLATION EXPECTATIONS FOR FOURTY FOUR
COUNTRIES
SUMMARY
This research proposes to test the rational expectation hypothesis of inflation expectations of 46 developed and
developing countries, using consensus survey data published by a source (www.Fx4casts.com, formerly
Financial Times Currency Forecaster) previously unexploited by researchers. Survey data on expectations are
useful in testing various economic hypotheses. Survey data is used as a proxy to unobservable expectations in
economic and finance models. It is also used by Central Banks, practitioners in business and financial markets
and policy makers to understand the influence of expectations on agents’ behaviour.
Because of its importance, consensus survey data is now collected by many central banks, businesses, and
academic institutions on different macroeconomic variables, like, interest rate, exchange rate, GDP growth
rates, inflation rates, current account, unemployment rate, etc. Unlike regular survey data or individual
analyst’s expectations, consensus survey data is unique because it surveys the opinions of a group of experts,
not the public in general. Consensus forecasts are found to be more accurate than individual forecasts. The
data can provide valuable information about the efficiency of expectations by economic agents. Thus, it has
caught attention of many researchers in economics and finance in the recent past.
Fx4casts.com provides monthly consensus forecasts of GDP growth rate, inflation rate, exchange rate, and
current account for 44 countries. It is a major source of consensus survey data, and the publisher surveys 48
experts each month from major banks, multinational corporations, insurance companies, etc. Data on actual
rates are also provided in the publication. The time period of the study will cover ten years of most recent data
available from the journal.
Following the literature in this area, current study proposes to conduct an unbiasedness test. The unbiasedness
test examines whether the expected rate is an unbiased predictor of the future actual rate. This test is also
known as a weak form test of rationality. A stronger form of rationality requires that forecasters also use all
available information at the time of forecast efficiently. The null hypothesis of rational expectations
(unbiasedness) implies that a=0 and b=1 in a regression of an equation of the following form:
Xt+k – Xt = a + b (Et Xt+k – Xt) + et+k
The dependent variable in the left hand side of the equation is the actual change in the variable of interest and
the independent variable in the right hand side is the expected change in the variable, and et+k is a random error.
This test will be performed for all the three variables separately using a panel study approach.
The results of this study will enhance our understanding of forecast efficiency, which will be useful to both
researchers and policy makers. This research will contribute to the area significantly as the study includes a
large sample of countries, and there are very few studies on the issue.
PROJECT OBJECTIVES
The fundamental objective of this study is to understand the following questions:
1. Are the inflation forecasts unbiased? This question will investigate weak form rational expectations
hypothesis for all the country individually and also a panel study will be conducted.
2. Is there a difference in the results between developed and developing economies? If so why?
The proposed study will add a better perspective on the rationality of expectations as the current data set is
unique, and covers a large number of countries.
LITERATURE REVIEW
There are many studies related to rationality of survey expectations of inflation using both survey of experts as
well as general public. The general conclusion of the literature in this area is mixed. Examples of a few studies
are Oral at el (2011), Curtis (2006), Bakshi (1998), Keane and Runkle (1990). Oral (2011) used survey data
collected from professionals published by Turkish Central Bank, and they could not find evidence of rationality
of expectations. Curtin (2006) concluded that consumers do not fulfill rational expectations hypothesis while
forming inflation expectations. Bakshi (1998) also found similar results using inflation expectations drawn
from a survey of UK employees by Gallup. Keane and Runkle (1990) tested the rationality of individual price
forecasts in a panel of professional forecasters. Rational expectation hypothesis in this case was accepted. He
argues that the difference in result is due to (1) using individual forecasts rather than mean of the individual
forecast, (2) avoidance of bias due to data revision, (3) use of professional forecasters as opposed to general
public opinion, and (4) use of a new covariance matrix estimator consistent when forecast errors are correlated
across individuals is used. Rational expectations hypothesis has been tested widely using exchange rate
expectations data. The most recent survey of literature in this area is available in Jongen, Verschoor and Wolf
(2008). A general conclusion of these studies indicates that consensus survey data is not rational. Dominguez
(1986), Ito (1990), Chinn and Frankel (1994) tested the unbiasedness hypothesis using different data sources,
and the results were mixed. Dominguez (1986) used data from the Money Market Services. Her results
strongly reject unbiasedness hypothesis with one-week, one-month, and three-month data. Cavaglia, et al.
(1993a) found similar results using EMS exchange rates published by Business International Corporation at the
three, six and twelve month horizon. Ito (1990) used data from Japanese Center for International Finance for
the period 1985-87 at the one, three and six month horizons. Unbiasedness was rejected for the longer horizon
and was accepted for the shorter horizon. There are a few studies available on interest rate expectations using
consensus survey data, for example, (Friedman (1980), Froot (1989), MacDonald and McMillan (1994), and
Jongen and Verschoor (2008) that investigated the properties of survey data on interest rate expectations. The
general conclusion of these studies is that survey data is a biased predictor of future change in interest rates, and
that agents do not incorporate all available information in forming their expectations. Friedman (1980) uses
survey data published by Goldsmith Nagan Bond and Money Market Letter. He performs unbiasedness and
efficiency tests for six US interest rates at the three and six month horizon from 1969 to 1976 time period, and
he concluded that survey respondents did not make unbiased predictions and they did not incorporate all
available information contained in common macroeconomic and macro-policy variables, like, unemployment
rate, growth of industrial production, inflation, growth in money stock, and federal government budget deficit.
Froot (1989) analysed data from the same source from 1969 to 1086, and found that expectations hypothesis
does not hold for short term and long term securities. He decomposed the error into two components: error due
to term premia and error due to failure of rational expectations. He found that both errors contribute to the bias
in the forecast. MacDonald and Macmillan (1994) conducted a similar analysis with UK interest rate data
(1989 – 1992), and found similar results in general. The data set allowed them to investigate expectations of
individual forecasters, and they found some evidence of heterogeneous behaviour, in terms of the importance of
term premia. Jongen and Verschoor (2008) used data from Consensus Economics of London for the period
1995 -2004 to test the unbiasedness and orthogonality propositions of the interest rate expectations of 20
countries at the three and twelve month horizon, and they also found that interest rate forecasts are not rational
and that agents do not use all available information in making their predictions. They also found that forecast
errors on EMS interest rates are smaller and less volatile than errors on non-EMS interest rates. There are also
studies available using survey forecast of other variables, like, unemployment rate, industrial production,
corporate profit, etc.
RESEARCH METHODOLOGY
Current study proposes to perform the weak form test of rationality by conducting an unbiasedness test. The
unbiasedness test examines whether the expected rate is an unbiased predictor of the future expected rate. The
null hypothesis of rational expectations implies that a=0 and b=1 in a regression of an equation of the following
form:
Xt+k – Xt = a + b (Et Xt+k – Xt) + et+k
The dependent variable in the left hand side of the equation is the actual change in the variable of interest and
the independent variable in the right hand side is the expected change in the variable, and et+k is a random error.
This test will be performed for all the three variables separately using a panel study approach. Since the data is
only available for tem years and actual realization of the variable happens once a year, a panel study is more
appropriate for this study. We will perform all necessary investigation of data and also manipulation required
for a penal study, which is widely available in the econometric literature. We will also perform a general
descriptive analysis to look for any pattern in the data set.
The results of this study will enhance our understanding of forecast efficiency of three major macroeconomic
variables, which will be useful to both researchers and policy makers. The study can also be used to compare
the results with other related studies.
DATA DESCRIPTION AND EMPIRICAL RESULTS
Data is already being purchased from the vendor. The authors are at present examining the data. The authors
expect that the empirical investigations will be completed within the next five months. Thus, the complete
paper will be ready for presentation at the conference.
REFERENCES
Bakshi, H. and A. Yates, (1998), Are UK Inflation Expectations Rational? Bank of England Working Paper No.
81.
Cavalgia, S. W., F. C. Verschoor and C. C. P. Wolff (1993a) Further Evidence on Exchange Rate Expectations
Journal of International Money and Finance, 12 (1), pp. 78-98.
Cavalgia, S. W., F. C. Verschoor and C. C. P. Wolff (1993b) Asian Exchange Rate Expectations Journal of the
Japanese and International Economics, 7(1), pp. 57 – 77.
Chinn, M. and Frankel J. A. (1994) Patterns in Exchange Rate Forecasts for Twenty-Five Currencies Journal of
Money, Credit and Banking, 26 (4), pp. 759- 770.
Curtis, R. (2006), Price Expectations: Theoretical Models and Empirical Tests, in The Role of Inflation
Expectations in Modeling and Monetary Policy, ed. Thomas Lyziak, NBP: Poland
Dominguez, K. M. (1986) Are Foreign Exchange Forecasts Rational?
Economic Letters, 21(3), pp. 277-81.
New Evidence from Survey Data
Friedman, B. (1980) Survey Evidence on the Rationality of \interest Rate Expectations, Journal of Monetary
Economics 6, 453 - 465
Froot, K. A. (1989), New Hope for the Expectations Hypothesis of the Term Structure of Interest Rate, Journal
of Finance 44, 283 – 305
Ito, T. (1990) Foreign Exchange Rate Expectations: Micro Survey Data American Economic Review, 80, pp.
489-510.
Jongen, R. and Verschoor, W. F. C. (2008), Further Evidence on the Rationality of Exchange Rate
Expectations, Journal of International Financial Markets, Institutions, and Money 18, 438 – 448
Keane, M. & Runkle, D. (1990), ‘Testing the Rationality of Price Forecasts: New Evidence from Panel Data’,
American Economic Review 80, 714–735.
MacDonald, R. and Mcmillan, P. (1994), On the Expectations View of the Term Structure, Term Premia and
Survey-based Expectaions, The Economic Journal 104, 1070 – 1086
Oral, Ece, Hulya Saygili, Mesut Sayfili, S. Ozage Tuncel, Inflation Expectations in Turkey: Evidence from
Panel Data, OECD Journal: Journal of Business Cycle Measurement and Analysis, Vol. 2011/1, Pages 5- 27.
Pesaran, M. Hashem, and Martin Weale, Survey Expectations, in Handbook of Economic Forecasting by G
Elliot, C. W. J. Granger, and A. Timmermann (eds), North-Holland, 2006