Will the real inflation rate please stand up overlooked quirks of a favoured chain-linking technique

Transcription

1 Wll the real nflaton rate please stand up overlooked qurks of a favoured chan-lnkng technque Dr Jens Mehrhoff*, Head of Secton Busness Cycle, Prce and Property Market Statstcs * Jens Ths Mehrhoff, presentaton Deutsche represents Bundesbank, the author s Statstcs personal Department opnons and does not necessarly reflect the vews of the Deutsche Bundesbank or ts staff. Meetng of the Group of Experts on Consumer Prce Indces Page 1

2 Outlne 1. Background & motvaton 2. Sources of devatons 3. Basc ndex theory 4. Understandng the qurk 5. Effect on prce ndex levels 6. Effect on year-on-year rates 7. Effect on average annual nflaton 8. Impact quantfcaton 9. Dscusson & mplcatons 10. Possble way forward 0.8% (Eurostat s flash estmate of euro-area annual nflaton n December 2013) Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 2

3 1. Background & motvaton The Oxford Dctonary of Englsh defnes qurk as a pecular aspect of a person s character or behavour. Clare Jones, Fnancal Tmes, 8 January (p 3): A methodologcal qurk n the calculaton of holday costs n the currency bloc's largest economy helped push core nflaton n the eurozone to an all-tme low n December... Maro Dragh, Presdent of the ECB, 9 January (press conference Q&A): The data that came out n December 2013 were essentally the result of a techncal ssue, what some people would call a qurk, n the statstcs on servces nflaton n Germany. Nota bene: The so-called qurk was nether due to seasonal adjustment nor some peculartes of the German prce statstcs but t was the outcome of the legally bndng lnkng procedures n the HICP; t, hence, seems lkely that such twsts happened n other countres as well but were not detected. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 3

4 2. Sources of devatons Accommodaton servces, COICOP group 11.2, 2013 weght : Because nternet surveys now allow data to be collected from smaller servce provders, whch are less lkely to charge seasonal premums than larger provders, the results show sgnfcantly smaller seasonal fluctuatons than prevously. In partcular, the July-August and December prce peaks of holday flats have been largely elmnated. Package holdays, COICOP group 09.6, 2013 weght : Instead of observng ndvdual tour operators, consumptons segments are now defned by the geographcal destnaton and the type of package holday (e.g. seasde, mountan). In addton, round trps and cruses have been ncluded newly n the sample; especally prces of round trps are less subject to seasonal fluctuatons. As a consequence, seasonalty, even n the month of December, s dampened consderably. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 4

5 3. Basc ndex theory The Harmonsed Index of Consumer Prces (HICP) s defned as a chaned Laspeyres-type prce ndex wth annual weght updatng, weghtng reference perod average year y 1 (prce-updated to December), prce reference perod December of the prevous year, and current ndex reference perod Short-term monthly Laspeyres prce ndex: P 12, y 1: m, y L n 1 p p m, y 12, y 1 p q 12, y 1 y 1 n n 12, y 1 y 1 p 1 1 q 12, y 1 Long-term annually chan-lnked monthly Laspeyres prce ndex: P m, y w Y 1 ~ : m, Y ~ 0:12, Y 1 12, Y 1: m, Y 0:12,1 12, y 1:12, y 12, Y 1: m, PL PL PL PL PL PL 0 Y y 2.. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 5

6 4. Understandng the qurk Wthout loss of generalty assume, for the sake of smplcty, that the HICP subndces consst of a sngle good only but stll apply chan-lnkng va December of the prevous year. Observed prce of tem n month m of year y: p m,y. Decomposton nto non-seasonal and seasonal part: p m,y π m,y m,y, where π m,y s the seasonally-adjusted prce and m,y s the (multplcatve) seasonal component, respectvely, of tem n month m of year y. Note: Seasonalty here refers to the usual seasonal fluctuatons of observed prces p m,y,.e. those movements whch recur wth smlar ntensty n the same season each year and not to Regulaton (EC) No 330/2009 layng down detaled rules for the treatment of seasonal products that are not avalable for purchase for certan perods n a typcal cyclcal pattern. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 6

7 5. Effect on prce ndex levels Calculate the chan-lnked prce (ndex) of tem n month m n 2013, wth perod 0 equal to December 2011: p~ p π π p p 12, ,2011 p p, 12, ,2011 p p π π 12, ,2011 π π where p s the monthly prce accordng to the new seasonal profle. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 7

8 6. Effect on year-on-year rates The change from December 2012 to December 2013 n the chan-lnked seres does not ntroduce a step n the seres: ~ 12, , ,2013 p π p π 12, ,2013 π π 12,2013 p. p Observe that the change from month m n 2012 to month m n 2013 (m 12) n the chan-lnked seres dffers from the correspondng change: ~ p π m,2012 m,2012 m,2012 p π m,2012 p. m,2012 m,2012 p Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 8

9 7. Effect on average annual nflaton Recall: Cov[X, Y] E[X Y] E[X] E[Y]; f Cov[X, Y] 0 and E[Y] 1, then E[X Y] E[X] ~, , m p m p m 1 12,2012, m m p,2012, m m m π m 1 m, p m, m, p m 1 m, p, 2012 p where X p 2012 and Y 2012 / 2012 ; hence, changes n seasonalty are assumed to be unrelated wth prce levels and the volatlty of the new seasonal pattern s not too hgh. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 9

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11 8. Impact quantfcaton Impute the estmated 2013 seasonal pattern to December 2011-November 2012 fgures and chan-lnk n order to acheve consstent year-on-year rates throughout the year (please note that ths analyss s subject to revsons): Table: 2013 average annual nflaton n Germany (n %) Group Offcal data New season Dfference* Accommodaton servces Package holdays Overall HICP Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page * In percentage ponts. Expected values from changes n seasonalty are percentage ponts for accommodaton servces and +2.1 percentage ponts for package holdays.

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15 9. Dscusson & mplcatons There was no underestmaton of nflaton due to the qurk n December 2013! (Snce then the temporary effect on nflaton rates has vanshed.) Qute the contrary, annual nflaton had been overestmated n Germany from January to November 2013 (see Deutsche Bundesbank, Monthly Report, Aprl 2013, p 7); totallng to a dscrepancy of just under +0.1 percentage pont on average from 2012 to 2013 n the euro area. Rather than deceleratng from 0.9% n November 2013, euro-area annual nflaton actually accelerated from 0.7% n November to 0.8% n December. Channg the new prce seres to the seasonal hgh of the old prce seres generated a permanent upward devaton n overall HICP levels, whch, n turn, gves wndfall benefts to the holders of ndex-lnked debt. Because the annual sub-ndces for the HICP are chan-lnked va the month of December wthout performng back-calculatons, ths led to marked statstcal dstortons whch serously hampered the nterpretablty of the HICP fgures. Potentally, other countres results are adversely affected, too. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 15

16 10. Possble way forward Any change n defntons, methods, or practces such as that on the treatment of seasonal products can result n problems wth chan-lnkng. We, thus, need an early warnng system for the methodologcally more nvolved chan ndces along wth a reflecton on European regulatons n terms of how the annual lnkng s performed and the stance on data revsons. A dfferent approach to channg that had been dscussed would be annual overlap,.e. the same procedure that s n place for the System of Natonal Accounts. Hence, we would rely on an annual prce reference perod that, per defntonem, shows no seasonalty. Of course, before such a major change can be ntroduced nto the HICP, we need much more emprcal analyses n order to support ths prelmnary mpresson and ensure, based on euro-area wde facts, that a changeover would sgnfcantly ncrease the nformaton value of HICP fgures. In ths sense, ths presentaton seeks to trgger a dscusson on the subject rather than beng defntve on the matter. Partcularly, experences from Member States wth a natonal CPI that follows a dfferent lnkng strategy than the HICP would be very valuable. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 16

17 Annex 1 In January 2012 Statstcs Netherlands (CBS) ntroduced new methods for the observaton of prces for arlne tckets and package holdays n the CPI. As a result, the seasonal patterns of both product groups changed. These changes had sgnfcant mpacts on the publshed ndces n some months. In order to ensure correct nflaton rates, CBS re-calculated the CPI for the year Reducto ad absurdum: If the sole am was unbased annual nflaton measurement, there would be two and only two approaches fxed base ndces and the over-the-year-technque. Frst, tradtonal fxed base ndces are less representatve of the economc condtons for perods farther away from the base year, whch s why the CPI Manual suggests movng to annually chan-lnked measures. Second, the over-the-year technque can result n dstorted seasonal patterns n the lnked seres; the 2008 SNA, thus, recommends that t should be avoded (cf. paragraph 15.50). Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 17

18 Annex 2 Even wthout a change of the seasonal pattern, the chan-lnkng technque can adversely affect the results from ndrect seasonal adjustment. Indrect seasonal adjustment means performng seasonal adjustment of a tme seres by combnng the ndvdual estmates for two or more components. Ths approach s preferred when components seres show seasonal patterns dfferng n a sgnfcant way, such as those for food or clothng and footwear. Walschots (2013, Ottawa Group) gave some emprcal evdence that weghts for the seasonally adjusted seres should be adjusted, too, albet the mpact mght be small n practce at least for the euro-area headlne HICP but maybe not so for Member States and components seres. The seasonal pattern s n the prces only but not n the weghts (although annual weghts are prce-updated to the month of December). Components seres may have stable and dentfable seasonal patterns where the overall HICP seasonal pattern changes due to annual chan-lnkng. Jens Mehrhoff, Deutsche Bundesbank, Statstcs Department Meetng of the Group of Experts on Consumer Prce Indces Page 18