Measuring Unobserved Expected Inflation

Date01 April 2016
DOIhttp://doi.org/10.1111/infi.12080
AuthorRafi Melnick
Published date01 April 2016
Measuring Unobserved Expected
Ination
RaMelnick
The Interdisciplinary Center Herzliya, Herzliya, Israel.
Abstract
The aim of this study is to develop an eclectic but robust model that
allows for a better measure of expected ination and facilitates testing
for all sorts of biases. Improving the measure of expected ination is of
critical importance for conducting monetar y policy. In many circum-
stances, indicators of expected ination move in opposite directions,
and this divergence may be critical for the setting of the interest rate. I
estimate the model for a special set of Israeli data via the Kalman lter
methodology and then test for systematic biases, a better normalization
of the model, liquidity problems and ination risk which could all be
present in current measures of expected ination.
I. Introduction
Assessing the r ate of expected inatio n is of critic al importance for the task of
designing and carryi ng out monetary policy. Uncertain economic futures makes
choosing the appropriate forward-looking monetary p olicy a constant chal lenge for
This paper was motivated by t he responsibilities I had a s a member of the Monetary Comm ittee of
the Bank of Israel. I would like to thank Jacob Boudou kh, Alex Cukierman, Stanley Fischer, Alex Ilek,
Roy Stein and Mark Watson for helpful discussions; two anonymous referees for t heir comments and
suggestions; and Roy Stein an d Aviel Shpitalnik for help with the data.
International Finance 19:1, 2016: pp. 222
DOI: 10.1111/infi.12080
© 2016 John Wiley & Sons Ltd
monetary authorit ies. The purpose of th is paper is to offer an econometri c approach
to obtain an operat ional measure of expec ted ination.
The implementati on of a proper forward-looking ination targeting regime,
1
with
or without a Taylor-type interest -rate rule, requ ires a quantitat ive measure of
expected ination. This is of crit ical importance be cause the adoption of an in ation
targeting strateg y for the conduct of monetary polic y
2
has become the preferred
strategy of an increasing number of countries.
3
Therefore, the approach develope d
here may have broad application s.
Expected ination is not directly observed ; therefore, practically spe aking, the
execution of monetar y policy requi res an estimate of it. There are va rious estimates
of expected inati on as indicators, includin g ination forecasts, e xpert surveys and
expectations de rived from nancial markets.
Monetary pol icy decisions base d on these indicators could b e problematic
because they may be subje ct to various sorts of errors, su ch as:
Biases in surveys and forecasts: Carg ill and Meyer (1985) examine the Living-
ston Survey and nd a systematic 10% bias in its forecasts; Laster e t al. (1999)
discuss the p ossible rati onal bias in macro economic forecast s; Stock and
Watson (2007) explore why US ination has become more difcu lt to forecast;
and Frenkel et al. (2013) discuss the strategic behaviour of professional
forecasters.
Risk and liquid ity problems for in dicators based on nan cial markets: Kandel
et al. (1996) estimate an ination risk premium in n ominal interest rates; and
Pueger and Viceira (2011) nd a high liquidity premium, a large average real
interest rate risk premium and a sm aller ination ri sk premium.
Model dependence and possibly misspecication.
Measurement errors and pure noise.
In many circumstances, the in dicators move in opposite directi ons. This diver-
gence may pose a chal lenge for the settin g of the interest rate.
4
In real world
situations, polic y makers need to identif y, by alternative methods, the correct level
and change of inationary expec tations to avoid mone tary pol icy mistakes.
The approach in this pap er requires a numb er of indicators that encomp ass
expected ination as a common fac tor. I draw on a cross-section of indicators of
1
Ination targeting is the current framework for mon etary policy in Israel.
2
In a forward-looking inati on targeting regime, the rate of i nterest is set according to the difference
between expected inat ion and the ination target.
3
Appendix 1 presents a list of 29 countries, f rom Roger (2009), that have adopted inat ion targeting
along with their approximate dates of adoption.
4
In most cases, the central ban k sets a short-term interest rate.
Measuring Unobserved Expected Inflation 3
© 2016 John Wiley & Sons Ltd

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT