How frequent a BEER? Assessing the impact of data frequency on real exchange rate misalignment estimation
| Published date | 01 July 2021 |
| Author | Claire Giordano |
| Date | 01 July 2021 |
| DOI | http://doi.org/10.1111/sjpe.12274 |
Scott J Polit Econ . 2021;68:365–404. wileyonlinelibrary.com/journal/sjpe
|
365
© 2021 Scottish Ec onomic Society
1 | INTRODUCTION
The price compet itiveness of a countr y is generally proxied by i ts real effecti ve exchange rate (REER), a weighte d
geometric average of its bilateral real exchange rates (RERs) vis- à- vis the currency of each of its main trading
partners . The REER captures the develop ments in domestic prices o r costs relative to the weighted aver age of
those of its comp etitors, all expresse d in a common currency. Prices or co sts are generally expr essed as indices:
they hence provid e information solely on pri ce- competitiveness dyn amics, and not on how competi tive a coun-
try is at a given point in time relative to a benchmark, “equilibrium” level. Various empiric al models have been
Accepted: 25 Jan uary 2021
DOI: 10 .1111/sjpe.1 2274
ORIGINAL ARTICLE
How frequent a BEER? Assessing the impact
of data frequency on real exchange rate
misalignment estimation
Claire Giordano
Economics, St atistics and Res earch DG,
Balance of Paym ents Analysis Div ision,
Bank of Italy, Rome , Italy
Correspondence
Claire Giordano, Economics, Statistics and
Research DG , Balance of Payment s Analysis
Division, Ba nk of Italy, Rome, Italy.
Email: claire.giordano@bancaditalia.it
Abstract
This article explores the robustness of Behavioural
Equilibrium Exchange Rate models, employed to estimate
real effective exchange rate misalignments, to the fre-
quency of the underlying data. It compares misalignments
stemming from an ann ual model, estimated since 1980, and
a comparable quarterly model, estimated since 1999. The
two sets of estimates are similar. Moreover, the in- sample
power of quarterly R EER misalignments in explaining su bse-
quent REER development s is higher than that of the annual
estimates. This ar ticle therefore suggests tha t the “optimal”
frequency of a BEER model depends on whether its result-
ing estimates are employed for research purposes or for
policy- making activities.
KEYWORDS
real effect ive exchange rate, equilibr ium exchange rate, BEER
model, data frequency
JEL CLASSIFI CATION
F00; F31
366
|
GIORDANO
employed to operationalise the theoretical concept of this unobservable equilibrium value and to derive the
resulting REER mis alignment, yet no approach h as been found to achieve a superio r performance to the other s
(Ajevskis et al ., 2014; Driver & Westaway, 2004; MacDonal d, 2000). The most comm on methodologies are the
following.
The Behaviour al Equilibrium Exchange Rate (B EER) methodology is labe lled this way due to the fact tha t it is
based on the assum ption that the “behaviour” of a R EER is determined by the “behaviou r” of its macroeconomic
drivers in the lo ng run (Clark & MacDonald , 1998). It involves direct estimat ion of the reduced- form coin tegrating
relationship be tween the REER and a set of relev ant economic fundament als, which leads to the def inition of the
REER equilibriu m value. This modelling tech nique does not generally have a ny comprehensive theoreti cal under-
pinning and is a posi tive approach, since it is not b ased on any normative assump tion.
The Permanent Eq uilibrium Exchange Rate (PEER) a pproach, described in Cl ark and MacDonald (200 4), can
be seen as an evolut ion of the BEER model in which cointegr ation techniques are employe d in order to extract
the permanen t, as opposed to transitor y, components of both the REER an d the economic fundament als, which
are then compare d to each other. This exercise is sim ilar in spirit to a BEER model w hen filtered (i.e. tren d) values
of the economic fundamentals are employed in lieu of their actual values in order to compute the equilibrium
REERs.
Another approach is the Natural Real Exchange Rate (NATREX) methodology, originally formulated by
Stein (1990). It is theoretic ally grounded on a dynami c stock- flow model. In particul ar, it defines the “natural”
REER as the REER that ens ures both the internal and th e external equilibrium si multaneously in the long r un.
The internal equilibrium is achieved when the out put gap is zero; the external equili brium is obtained when
the current account balance is “sustainable” given a country's desired net foreign asset position. Although
there have been some attempts to measure the structural model underlying the NATREX (e.g. Gandolfo &
Felettigh, 1998; Siregar & Rajan, 20 06), this approach often boils down to estimating a reduced- form equa-
tion. In this case, the main difference between the BEER and the NATREX is only that the latter is more
explicitly th eory- based (Stein, 2006). A gain, similarly to the BEER m ethodology, the NATREX model ad opts a
positive approach.
The last approach is the Fundamental Equilibrium Exchange Rate (FEER) methodology, advocated by Wren-
Lewis (1992) and Williamson (1994). Simila r to the NATREX approach, the FEER is the R EER that simultaneously
attains inter nal and external balance . In its most popular appl ications (Cline & Williamso n, 2010; Isard, 2007; Lee
et al., 2008), t he FEER method is based on a partial e quilibrium model and, in par ticular, on the computation of
the REER adjustm ent required to close the gap b etween the cyclically a djusted current account and t he “current
account norm,” whic h represents an optimal v alue of the current account over a m edium- term horizon. The no rm
is either set in a normative manner or is derived from “behavioural” reduced- form regressions that estimate an
equilibrium re lationship between the cu rrent account and a set of plausibl e fundamentals. The cal ibration of the
required REER adj ustment is, however, highly sensiti ve to the assumptions made conce rning both exchange- rate
pass- through coeff icients and price elasti cities of trade (Schnatz, 2011). The FE ER model can be reconciled wit h
the NATREX approa ch by estimating a target level for t he net foreign asset position rath er than for the current
account balance.
These approa ches, far from being op posed to each other, are comple mentary, both becaus e they are all based
on restrictive (albeit different) assumptions and because they may be interpreted as assessing equilibrium ex-
change rates over dif ferent time horizons (Bénassy-Queré et al., 2010). Indeed, the FEER, for instance, may be
considered as cor responding to a medium- run concept of equilibriu m, whereas the (filtere d) BEER, and even more
so the PEER, to a long- run concept.
This paper focu ses solely on one methodolog y, namely the BEER approach. Yet, even wh en focusing on one
method only, many mod elling choices arise, concernin g the selection of the country sample, the estimation pe-
riod, the data f requency, the weights and th e deflator employed to constr uct the REERs, the numer aire currency
against which to e xpress the bilateral R ERs underlying the REER s, the relevant set of econ omic fundamentals , the
|
367
GIORDANO
appropriate pr oxies of these economic fund amentals, as well as several e conometric aspects , in particular linked
to accounting for country heterogeneity and tackling cross- sectional dependence.
Few studies amongst the many that estimate BEER models systematically address these manifold method-
ological issues. Recent exceptions are the following. Bussière et al. (2010) focuses largely on the appropriate
econometric techniques to be employed in estimating BEER models. Bénassy- Queré et al. (2010) discusses the
correct measurement of the relevant economic fundamentals, namely the Balassa- Samuelson effect, and the
choice of the numer aire country. Adler and G risse (2017) is centred on the se lection of fundament als, the country
sample and the e stimation methodo logy. Fidora et al. (2020) ad opts various price an d cost indicators to const ruct
the REERs, as well as employing alternative Balassa- Samuelson proxies, carefully selecting the set of relevant
explanatory variables and using different estimation techniques.
Adding to these s tudies, this article is con cerned with the robustne ss of equilibrium REERs and of the co rre-
sponding misalignments alo ng one dimension only, namely the choice of the data frequency (i.e. annual versus.
quarterly), a d imension which thus fa r has not been investigate d by the existing litera ture. Various methodol ogical
aspects de pend on this choice, such as the sel ection of the sample perio d and of the relevant set of fundamen-
tals. All othe r modelling choices are hel d fixed between the ann ual and the quarterly m odels, namely the count ry
sample, the r ange of price and cost indicators e mployed to compute the REER, the nu meraire currency, and the
econometric technique used for estimation.
A priori, quar terly models have two main ad vantages. First, the hig her number of observatio ns relative to an
annual dataset estimated over the same time span implies that quarterly models may be estimated more effi-
ciently.1 Second, estimating a BEER model at quarterly frequency is of paramount importance for surveillance,
early- warning and policy- making purposes, since it allows tracking infra- annual imbalances in a timely manner
(Giordano, 2018, 202 0a). Conversely, the main drawbac k is the restriction of the e stimation window to a shor ter
time span, coveri ng only the most recent years , for which quarterly dat a are available. This limit ation, in turn, ex-
acerbates two si gnificant shortcomi ngs underlying the BEER m ethodology.
The first sho rtcoming concerns the nee d to include country fixed e ffects amongst th e regressors included in
a panel BEER model , due to the fact that the de pendent variable, the R EER is generally an index numb er (Adler &
Grisse, 2017; Cubeddu e t al., 2019; Fischer & Hossfeld, 2014; Mano et al . 2019).2 T he inclusion of country fixe d
effects is i ndeed a means to account for count ry- specific price levels in th e base year. Yet, by including fixed ef-
fects, the predicted (i.e. equilibrium) REERs are by construction on average equal to the long- run actual REER
means, or in othe r terms each countr y's regression resid uals— and thus REER mis alignments— are forced to average
to zero over the sampl e period. The fixed- effect estimation s hence make estimates les s reliable for countrie s with
short time dat a spans; moreover, “persis tent” deviations of REER s from their equilibr ium value are by constr uction
not envisaged in f ixed- effects pan el BEER models.
The second draw back of the BEER methodo logy is that it implicit ly assumes that the eco nomic fundamenta ls—
against which the actual REER is appraised— are at their equilibrium values. This is less likely to be the case for
short time sp ans. Moving to annual dat a implies being able to s ignificantly ex tend the sample peri od and therefore
making both the a ssumptions of zero misalignm ents and of economic fund amentals at their equili brium values on
average over the est imation horizon more palat able.
In order to assess t he impact of data frequ ency on REER misalignme nt estimates, this ar ticle first describ es an
annual BEER mode l since 1980 for a vast sample of advance d and emerging countries, u sing recently developed
techniques bot h to select the relevant ec onomic fundamentals (B ayesian model averaging, B MA) and to estimate
1As well as enha ncing effici ency, the higher n umber of obser vations under lying a quart erly model all ows more flexibi lity in modell ing the mean
reversion to e quilibrium, f or example lead ing to the possib ility of addre ssing the exist ence of potential n onlinear mea n reversion, whi ch has been
found to be pre sent in the case of r eal exchange rat es referred to so me currencies (e .g. Chorta reas, Kapeta nios and Shin, 20 02).
2An alternat ive would be to focu s on time- series analyses of ind ividual count ries, yet these a nalyses suf fer from a limited n umber of obser vations;
panel esti mation is hence ge nerally empl oyed in this liter ature, as discus sed in Section 2 .
Get this document and AI-powered insights with a free trial of vLex and Vincent AI
Get Started for FreeStart Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting