The rational expectations hypothesis states that when people are expecting things to happen, using the available information, the predicted outcomes usually occur. This study utilized survey data provided by the Business Expectations Survey of Limited Companies to test whether forecasts of the Malaysian retail sector, based on gross revenue and capital expenditures, are rational. The empirical evidence illustrates that the decision-makers expectations in the retail sector are biased and too optimistic in forecasting gross revenue and capital expenditures.REH, Unbiasedness, Non-serial Correlation, Weak-form Efficiency

Chong, Lucy Lee-Yun

Jais, Mohamad

Puah, Chin-Hong

English

Research Papers in Economics

1 
 
Testing the Rational Expectations Hypothesis on the Retail Trade 
Sector Using Survey Data from Malaysia 
 
Chin-Hong Puah
♣
Faculty of Economics and Business, Universiti Malaysia Sarawak, Malaysia 
, Lucy Lee-Yun Chong and Mohamad Jais 
 
 
Abstract 
The rational expectations hypothesis states that when people are expecting things 
to happen, using the available information, the predicted outcomes usually occur. 
This study utilized survey data provided by the Business Expectations Survey of 
Limited Companies to test whether forecasts of the Malaysian retail sector, based 
on gross revenue and capital expenditures, are rational. The empirical evidence 
illustrates that the decision-makers expectations in the retail sector are biased and 
too optimistic in forecasting gross revenue and capital expenditures. 
 
Keywords: REH, Unbiasedness, Non-serial Correlation, Weak-form Efficiency 
  
 
I.  Introduction 
 
  Expectations affect the behavior of people in firms, households and the government. 
The incentive to use expectations becomes stronger as the potential “profits” begin rising 
(Sargent, 2008). Investors decide to invest when they expect a stock will yield superior 
returns; consumers decide to consume less when they expect the recession will persist; 
firms decide to expand their business when they expect the profit opportunities to be 
higher; and the government decides to use a monetary, or fiscal, policy when they expect 
the policy to boost economic performance. 
                                                            
♣ Corresponding author: Chin-Hong Puah, Department of Economics, Faculty of Economics and Business, 
Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia. E-mail: chpuah@feb.unimas.my 2 
 
  The rational expectations hypothesis (REH) states that when people expect things to 
happen, with the available information, the predicted outcomes will occur, on average. 
This occurs because the avoidable errors were adjusted when the current forecast took 
place, considering feedback from past outcomes, as highlighted by Sargent (2008), Muth 
(1961) and Friedman (1980). Albeit the future is not fully predictable, the systematical 
error can be minimized, as people will adjust their expectations, from time to time, using 
all available information in forming expectations. Thus, although the economic variables 
were created by a systematical process, the forecasted outcomes will be the same as those 
predicted by the REH. As noted by Mishkin (1983) and Zarnowitz (1992), not all market 
participants need to be rational to display rational  expectations, indicating that the 
behavior of an individual is not necessarily the same as the behavior of the market. The 
market will behave as if those expectations are rational, rather than irrational, as long as 
the unexploited profit opportunities are eliminated by the  rational participants in the 
market.  
 
  Recent studies have focused on testing the rationality of inflation expectations in 
industrialized countries (see for example, Mestre, 2007; Henzel and Wollmershaeuser, 
2008;  Schmeling and Schrimpf,  2008).  Few studies have  examined  the REH of the 
financial and commodities markets in the business sector in developing countries.  In 
2009, the retail business in Malaysia had increased by 29.7 percent, as compared to 2002. 
This increase was partially driven by market liberalization, an increase in food demand, 
and an expansion of hypermarket and tourism sectors. Unlike merchant trade that focuses 
on  the international market, the business in retail trade concentrates on  the domestic 
market  (Lim et al., 2003).  As such, retail trade is  one of the main value  added 
components  to consumption in a nation. It also acts as  the engine of growth,  since 
incomes generated by retailers have a multiplier effect that will boost the economy. For 
that reason, it is crucial to investigate whether the decision-makers in this sector are 
rational in making business expectations. 
 
 3 
 
  This paper  aims  to investigate whether data from the Malaysian  Business 
Expectation Survey of Limited Companies could  provide the basis for prediction that 
supports  the rationality of expectations in the sense of unbiasedness, non-serial 
correlation  and efficiency.  The rest of this paper is structured as follows. Section 2 
presents the theoretical framework related to the  REH, Section  3  explains  the 
methodology used to test the REH, Section 4 provides the empirical results, and lastly, 
Section 5 concludes. 
 
 
II.  Theoretical Framework 
 
  Based on Beach et al. (1995), the REH model is implied by: 
 
  0 } { } { = Ω − = Ω + + + t
e
h t t h t t h t x x E E ε                        (1) 
                                                                                                                                                                                                                                 
  0 } { = Ω Ω • + t t h t E ε                             (2) 
 
where: 
e
h t t x +  is the subjective (quantitative) expectation of xt+h formed at time t=1,2,…,T, 
E  is the mathematical expectations operator,  ε  is the forecast error, and Ωt  is the 
information set available to the economic agent at time t. 
 
  The realizations xt+h are subjected to data revisions unknown by individuals when 
forming the expectations (Pesaran and Weale, 2006).  Next, the data revisions and 
conversion errors are abstracted by assuming
e
h t i t x + , and the associated expectations errors 
are observed to be free of measurement errors. Beach et al. (1995) point out that the 
REH is often tested by setting h=1 in Equations (1) and (2): 
 
 
e
t t t x x 1 1 0 1 + + + = β α                               (3) 
 
  t t Χ = + 1 1 γ ε                                 (4) 4 
 
where Xt ⊆ Ωt is a vector that corresponds to all relevant information available to an 
economic agent at time t. The REH entails the forecasting to be unbiased and consistent. 
In addition, the null hypothesis of unbiasedness is accepted if α0=0 and β1=1. According 
to Pesaran and Weale (2006), if the Ei (xt+h │Si, t+ℓ) is equal to Ei (xt+h │Sit) for all of ℓ, the 
subjective expectations Ei (xt+h │Si, t+ℓ) formed at time t+ℓ for period t+h (h>ℓ) tend to be 
consistent under the REH.  
 
 
III. Methodology 
 
  This paper used bi-annual survey data published by the Department of Statistics 
Malaysia in the Business Expectations Survey of Limited Companies, from June 1991 
until  June  2006,  to examine the rationality  of  retail  firm expectations toward a 
macroeconomic trend based on the gross revenue (GR) and capital expenditures (CE). 
The econometric testing procedures  employed  in this study include  the  Augmented 
Dickey-Fuller (ADF) unit root test, Engle-Granger cointegration test, unbiasedness test, 
non-serial correlation  test, as well as the  Mullineaux weak-form efficiency test. 
Consequently, the Breusch-Godfrey Autocorrelation LM test will be employed to support 
the rationality test results. 
 
 
Preliminary Test 
 
  A unit root test examines  the stationarity properties  of  a  time series  dataset. 
Generally, time series data for macroeconomic variables are non-stationary in the level 
form. However,  most of the data becomes  stationary after the  first differencing. 
Stationarity implies that the lag effect of the variable (Yt-1) will not influence the current 
value of it (Yt).  On the other hand, the cointegration test has some meaningful 
implications for testing the REH, particularly in establishing the long-run relationship 
between the realized and anticipated series. The “optimal forecast” and the actual value 5 
 
of the series being predicted must be cointegrated under a relatively general condition; 
otherwise these series will not result in similar long-run properties (Granger, 1986). 
 
 
Unbiasedness Test 
 
  The rational expectations must be unbiased in Muth’s sense of the subjective 
expectation. This expectation is identical to the corresponding mathematical expectations 
(Friedman, 1980) shown by: 
 
  st
e
t s t t u r r + = −                                (5) 
 
where: rt is the observed value at time t, 
e
t s t r − is the expectations of rt at time t-s, and ust  
is  a zero mean finite-variance disturbance term uncorrelated with 
e
t s t r − ,  but may be 
serially correlated with  an (s-1) order moving-average process. The equation used to 
regress the survey expectations on the realizations following the unbiasedness test is: 
 
  st
e
t s t t u r r + + = − β α                             (6)                 
 
and the null hypothesis of unbiasedness is defined as H0: (α, β) = (0, 1). The acceptance 
of the joint hypothesis above implies that the expectations are an unbiased predictor of 
the actual incidence. 
 
 
Non- Serial Correlation Test 
 
  The non-serial correlation test is applied to examine the presence of serial correlation 
between the forecast errors and its lag forecast errors. Based on Evans and Gulamani 
(1984), the regression model to test the serial correlation is: 
 6 
 
  t i t
p
i
i t ε η δ δ η + + = −
=
∑
1
0                             (7) 
 
where ηt is the forecast error, p is the lag length and i ∈ {1,2,3,… p}. The rejection of the 
joint null hypothesis H0: (δ0, δi) = 0, i ∈ { 1,2,3,… p} denotes that ηt is correlated with its 
lagged values. 
 
 
The Mullineaux Weak-Form Efficiency Test  
 
  The Mullineaux weak-form efficiency test is used to examine whether the forecast 
errors are unpredictable.  This implies that they are  uncorrelated with any variables 
contained in the information set available at the time of forming the expectations (Beach 
et al., 1995).  According to  Raja  et al. (2009), the strong form efficiency reflects all 
publicly or privately (monopolistic insiders) available information that is incorporated 
with the complete model. The semi-strong  form efficiency,  in contrast,  reflects the 
publicly available information incorporated  with the complete model;  the weak-form 
efficiency reflects the partial information contained in the historical sequence 
incorporated with the incomplete model.  
 
  Friedman (1980) states that rational expectations and the corresponding realizations 
share a common autoregressive representation. In addition, the estimation of the paired 
regressions employed in the efficiency test is illustrated as follows:  
 
  ∑
=
− + + =
N
s i
st i t i t r r υ β β0                             (8) 
          
  ∑
=
− − ′ + ′ + ′ =
N
s i
st i t i
e
t s t r r υ β β0                           (9) 
 
where: the υst and υ′st are the random error terms. 
 7 
 
IV. Empirical Results 
 
  The ADF unit root test results illustrate that both of the realized and anticipated GR 
and CE are non-stationary in levels, but stationary after the first differencing, indicating 
that they are integrated of order one, or I(1).
 The results for the unit root test are available 
upon request from the authors.  We  then  proceeded to conduct a cointegration test, 
unbiasedness test and LM test. The evidence drawn from the Engle-Granger cointegration 
test in Table 1 denotes that there is a long running co-movement between the realized and 
anticipated GR and CE. In addition, the LM test shows that all the disturbance terms are 
white noise. 
 
Table 1: Results of Engle-Granger Cointegration Test and Unbiasedness Test 
  GR  CE 
Cointegration Test     
ADF      -6.186***       -4.981*** 
     
Unbiasedness Test     
Constant (α)   2.295*      1.990*** 
Slope (β)      0.699***      0.481*** 
F-statistic (α=0, β=1)   2.670*      5.048*** 
LM(2)  0.371  0.924 
Note: Asterisk (***), (**) and (*) denote statistically significant at the1%, 5% and 10% levels, 
respectively. 
 
  Even the F-statistic of the joint hypothesis that imposed the restriction for α=0 and 
β=1 in Table 1  illustrates  that GR and CE are biased  as  the null hypothesis of the 
unbiasedness test is rejected, the non-serial correlation test and the Mullineaux weak-
form efficiency test results, presented in Table 2, denotes that the GR and CE are not 
correlated with past forecast errors. We failed to reject the null hypothesis in both of the 
non-serial correlation and the  Mullineaux weak-form efficiency tests, indicating the 
decision-makers are efficient in utilizing all available information. 
 8 
 
Table 2: Results of Non- Serial Correlation Test and Weak Form Efficiency Test 
 
NSC  WF 
1 
GR  1.104[0.346]  1.330[0.281] 
CE  0.317[0.731]  0.791[0.464] 
  2 
GR  1.123[0.358]  0.868[0.471] 
CE  0.361[0.782]  0.979[0.419] 
  3 
GR  1.140[0.362]  0.888[0.487] 
CE  0.410[0.799]  0.749[0.569] 
Notes: Figures in square brackets indicate the p-value. NSC refers to non-serial correlation test while 
WF refers to weak-form efficiency test.  
 
 
V.  Conclusions 
 
  Business survey expectations had significant implications for the respondent firm, 
society, and government. Empirical results illustrate that the gross revenue and capital 
expenditures passed the non-serial correlation and weak-form efficiency tests. Even so, 
the predictions made by the decision-makers in the retail sector tend to be biased and are 
too optimistic in forecasting their gross revenue and capital expenditures. This might 
imply  that  decision-makers in the  retail trade sector in Malaysia had tried to utilize 
available information in formatting their expectations towards economic  trends. 
Nevertheless, their forecasts were still biased. Based on Baillie et al. (1983), the biased 
results may be attributable to an uncertain future. In addition, the variety of non-linear 
feedback caused by the heterogeneity group will also lead to biased results. Likewise, 
Dovern and Weisser (2008) point out that a bias can be caused by large structural shocks 
or gradual changes in the variable trends.  
 
 
 
 9 
 
Acknowledgments:  
Financial support from the Universiti Malaysia Sarawak (UNIMAS) and Fundamental 
Research Grant Scheme [FRGS/05(27)/781/2010(62)] are gratefully acknowledged. All 
remaining flaws are the responsibilities of the authors. 
 
 
References: 
 
Baillie, R.T., Lippens, R.E. and McMahon, P.C. (1983). Testing Rational Expectations 
and Efficiency in the Foreign Exchange Market. Econometrica, 51(3), 553-563. 
 
Beach, E.D., Fernandez-Cornejo, J. and Uri, N.D. (1995). Testing the Rational 
Expectations Hypothesis Using Survey Data from Vegetable Growers in the USA. 
Journal of Economic Studies, 22(6), 46-59. 
 
Department of Statistics Malaysia. Business Expectations Survey of Limited Companies, 
various issues. Putrajaya: Department of Statistics Malaysia. 
 
Dovern, J. and Weisser, J. (2008). Are They Really Rational? Assessing Professional 
Macro-Economic Forecasts from the G7-Countries. Kiel Institute for the World 
Economy, Working Papers, No. 1447. 
 
Evans, G.W.  and Gulamani, R. (1984). Tests for Rationality of  the Carlson-Parkin 
Inflation Expectations Data. Oxford Bulletin of Economics and Statistics, 46(1), 
1-19. 
 
Friedman,B.M.  (1980). Survey Evidence on the ‘Rationality’ of Interest Rate 
Expectations. Journal of Monetary Economics, 6(4), 453-465. 
 
Granger, C.W.J. (1986). Developments in the Study of Cointegrated Economic Variables. 
Oxford Bulletin of Economics and Statistics, 48(3), 213-228. 10 
 
Henzel, S. and Wollmershäuser, T. (2008). The New Keynesian Phillips Curve and the 
Role of Expectations: Evidence from the CESifo  World Economic Survey. 
Economic Modelling, 25(5), 811-832. 
 
Lim, Y.M., Badarulzaman, N. and Ahmad, A.G. (2003). Retail Activity in Malaysia: 
From Shophouse to Hypermarket. Paper presented at the Pacific Rim Real Estate 
Society 9
th Annual Conference, Australia. 
 
Mestre, R. (2007).  Are Survey-Based Inflation Expectations in the EURO Area 
Informative? European Central Bank, Working Paper Series No. 721. 
 
Mishkin, F.S. (1983). A Rational Expectations Approach to Macroeconomics: Testing 
Policy Ineffectiveness and Efficient-Markets Models. Chicago and London: The 
University of Chicago Press. 
 
Muth, J.F. (1961). Rational Expectations and the Theory of Price Movements. 
Econometrica, 29(3), 315-335. 
 
Pesaran, M.H. and Weale, M.R. (2006). Survey Expectations. In G. Elliott, C.W.J. 
Granger, and A. Timmermann (Eds.), Handbook of Economic Forecasting 
(pp.715-776). North-Holland. 
 
Raja, M., Sudhahar, J.C. and Selvam, M. (2009). Testing the Semi-Strong Form 
Efficiency of Indian Stock Market with Respect to Information Content of Stock 
Split Announcement: A Study in IT Industry. International Research Journal of 
Finance and Economics, 2009(25), 7-20. 
 
Sargent, T.J. (2008). Rational Expectations. The Concise Encyclopedia of Economics. 
Library of Economics and Liberty.  Retrieved May 7, 2009, from 
http://www.econlib.org/library/Enc/RationalExpectations.html. 
 11 
 
Schmeling, M. and Schrimpf, A. (2008). Expected Inflation, Expected Stock Returns, and 
Money Illusion: What Can We Learn from Survey Expectations?  Deutsche 
Forschungsgemeinschaft, SFD 649 Discussion Paper 2008-036. 
 
Zarnowitz, V. (1992). Business Cycles: Theory, History, Indicators, and Forecasting. 
Chicago and London: The University of Chicago Press. 
 

A Rational Expectations Approach to Macroeconomics: Testing Policy Ineffectiveness and Efficient-Markets Models. Chicago and London:

Are Survey-Based Inflation Expectations in the EURO Area Informative? European Central Bank, Working Paper Series No.

Are They Really Rational? Assessing Professional Macro-Economic Forecasts from the G7-Countries. Kiel Institute for the World Economy, Working Papers,

Business Cycles: Theory, History, Indicators, and Forecasting. Chicago and London:

Developments in the Study of Cointegrated Economic Variables.

Expected Inflation, Expected Stock Returns, and Money Illusion: What Can We Learn from Survey Expectations? Deutsche Forschungsgemeinschaft,

Rational Expectations and the Theory of Price Movements.

Rational Expectations. The Concise Encyclopedia of Economics.

Retail Activity in Malaysia: From Shophouse to Hypermarket. Paper presented at the Pacific Rim Real

Survey Evidence on the ‘Rationality’ of Interest Rate Expectations.

Survey Expectations. In

Testing the Rational Expectations Hypothesis Using Survey Data from Vegetable Growers in the USA.

Testing the Semi-Strong Form Efficiency of Indian Stock Market with Respect to Information Content of Stock Split Announcement: A Study in IT Industry.

Tests for Rationality of the Carlson-Parkin Inflation Expectations Data.

The New Keynesian Phillips Curve and the Role of Expectations: Evidence from the CESifo World Economic Survey.

Testing the Rational Expectations Hypothesis on the Retail Trade Sector Using Survey Data from Malaysia

Testing the Rational Expectations Hypothesis on the Retail Trade Sector Using Survey Data from Malaysia

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics