WORKING PAPER NO FRONTIERS OF REAL-TIME DATA ANALYSIS. Dean Croushore

Transcription

1 WORKING PAPER NO FRONTIERS OF REAL-TIME DATA ANALYSIS Dean Croushore Associae Professor of Economics and Rigsby Fellow Universiy of Richmond and Visiing Scholar Federal Reserve Bank of Philadelphia March 2008

2 FRONTIERS OF REAL-TIME DATA ANALYSIS Dean Croushore Associae Professor of Economics and Rigsby Fellow Universiy of Richmond Visiing Scholar Federal Reserve Bank of Philadelphia March 2008 Paper prepared for he Euro Area Business Cycle Nework workshop on Using Euro Area Daa: Issues and Consequences for Economic Analysis, Universiy of Cambridge, March This paper was wrien in par while he auhor was a visiing scholar a he Federal Reserve Bank of Philadelphia. The views expressed in his paper are hose of he auhor and do no necessarily represen he views of he Federal Reserve Bank of Philadelphia or he Federal Reserve Sysem. This paper is available free of charge a Please send commens o he auhor a Robins School of Business, 1 Gaeway Road, Universiy of Richmond, VA 23173, or dcrousho@richmond.edu.

3 FRONTIERS OF REAL-TIME DATA ANALYSIS ABSTRACT This paper describes he exising research (as of February 2008) on real-ime daa analysis, divided ino five areas: (1) daa revisions; (2) forecasing; (3) moneary policy analysis; (4) macroeconomic research; and (5) curren analysis of business and financial condiions. In each area, subsanial progress has been made in recen years, wih researchers gaining insigh ino he impac of daa revisions. In addiion, subsanial progress has been made in developing beer real-ime daa ses around he world. Sill, addiional research is needed in key areas, and research o dae has uncovered even more fruiful areas worh exploring.

4 FRONTIERS OF REAL-TIME DATA ANALYSIS The analysis of real-ime daa daes back o Garaganis-Goldberger (1955), who found ha he saisical properies of he discrepancy beween gross naional produc (GNP) and gross naional income differed afer he daa were revised in 1954, compared wih he 1951 vinage of he daa. Real-ime daa analysis refers o research for which daa revisions maer or for which he iming of he daa releases is imporan in some way. Researchers have examined he properies of daa revisions, how daa revisions affec forecasing, he impac of daa revisions on moneary policy analysis, how macroeconomic research is affeced by daa revisions, and he use of real-ime daa in curren analysis. I began developing a large daa se conaining U.S. real-ime daa in he mid-1990s and made i widely available online in 1999, as discussed in Croushore-Sark (2001). Developmen of his real-ime daa se is ongoing, wih cooperaion beween he Federal Reserve Bank of Philadelphia and he Universiy of Richmond, and is available on he Philadelphia Fed s websie a Similar daa ses have subsequenly been developed all over he world, hough he need remains for insiuional suppor for such effors. Such daa ses are a club good, being nonrival bu excludable. If insiuions, such as he Federal Reserve in he Unied Saes, provide suppor for daa developmen, he daa can be made available o all ineresed researchers. Unforunaely, many producers of such daa have chosen o resric use o members of he club, and some governmen agencies have chosen o resric access as well. In he Unied Saes, rivalry beween he Federal Reserve Banks of Philadelphia and S. Louis has hasened he developmen of he daa, and boh 1

5 insiuions have allowed unresriced access o heir daa as soon as hey have been produced. The OECD recenly made heir daa available o everyone, wih daa for all OECD counries and a few ohers, wih vinages beginning in 1999, based on daa ha appear in Main Economic Indicaors. Researchers a he Bank of England produced a real-ime daa se in 2001 and recenly updaed i in 2007, wih vinages beginning in 1990; see Casle-Ellis (2002). A daa se wih somewha resriced access was produced and is updaed by he EABCN for he euro area, wih vinages beginning in Individual researchers have developed smaller daa ses for many oher counries, hough as far as I know hey do no provide ready access o heir daa. Clearly, insiuional suppor helps o promoe good daa. Wihou i, many daa ses die and are never updaed afer a researcher finishes work on he opic. Analysis of daa revisions should no be aken as criicism of he governmen saisical agencies, merely as a fac of life when he governmen does no have unlimied resources for collecing daa. The developmen of real-ime daa ses may help governmen saisical agencies undersand he revisions beer and may lead o modificaions of he process for producing daa. For example, predicable revisions of U.S. indusrial producion led he Federal Reserve o modify is procedures for compiling he daa, and he predicabiliy disappeared; see Kennedy (1990). Revisions o daa ofen reflec informaion from censuses ha are aken every five or 10 years; i would be oo cosly o ake such censuses more frequenly. As a resul, every five or 10 years, he governmen saisical agencies make large changes in he weighs applied o differen secors of he economy in measuring GDP and prices, a process ha leads o large revisions. Generally, revisions improve he qualiy of he daa. For example, he U.S. consumer price index, which is no revised (in is seasonally unadjused form), is inferior o he personal 2

6 consumpion expendiures price index, which is revised; he revisions o he PCE price index incorporae improved mehods, more-curren weighs, and more-recen daa. The ypical srucure of a real-ime daa se is demonsraed in Table 1. Each column represens a differen vinage of daa (a dae a which he daa are observed), while each row shows a differen dae for which he economic aciviy is measured. The las daa value shown in each column is he iniial release of he daa poin for he dae shown in he firs column. As ime passes, we move o he righ in erms of vinages. So, we can race ou he daa value for any paricular dae by moving from lef o righ across a row, which shows us he value for ha dae in successive vinages of he daa. Moving down he main diagonal (he diagonal connecing he las daa values in each column) shows he iniial daa release for each dae. Table 1 Real-Time Daa Srucure Real Oupu Vinage: 11/65 2/66 5/ /07 2/08 Dae 47Q Q Q Q Q4 NA Q1 NA NA Q1 NA NA NA Q2 NA NA NA Q3 NA NA NA Q4 NA NA NA... NA

7 For example, someone in November 1965 who looked up he values of real GDP would observe he values shown in he column headed 11/65; ha is, real GDP would have been seen as increasing from (all numbers in billions of consan dollars) in he firs quarer of 1947, o in he second quarer, o in he hird quarer, and so on, while he value for he hird quarer of 1965 of was he mos recenly released daa poin. Three monhs laer, in February 1966, ha value for he hird quarer of 1965 was revised up o 613.0, and he firs release of he daa for he fourh quarer of 1966 came ou a The large jump in he numbers as you move across he firs row of Table 1 shows he effecs of benchmark revisions. Such changes are no meaningful for real GDP, as hey simply represen changes in he (arbirary) base year. Noice ha in daa vinage November 2007, he daa value for he hird quarer of 1947 is below he value for he second quarer, unlike he vinages in he 1960s. DATA REVISIONS The mos common applicaion of real-ime daa is in he analysis of daa revisions. Researchers have examined (1) wha daa revisions look like; (2) characerizaion of he revision process as adding news or reducing noise; (3) wheher he governmen is using informaion efficienly; (4) if revisions are forecasable; and (5) how he daa revision process should be modeled. The underlying heme of all his research is: Are daa revisions economically large enough o worry abou? One of he bes examples of papers ha analyze daa revisions is Diebold-Rudebusch (1991), who showed ha he U.S. index of leading economic indicaors does a fine job a 4

8 predicing recessions ex-pos, bu only because i was consruced o explain he pas. Is rack record in real ime is very poor because iniial releases of he daa may look very differen from laer releases and because he index mehodology changed over ime afer he real-ime index failed o predic recessions. Wha do daa revisions look like? Much research has simply ried o caalog some basic saisics on daa revisions, beginning wih Zellner (1958). In he shor erm, daa revisions can be subsanial. For example, Figure 1 shows he hisory over vinage ime of he growh rae of real personal consumpion expendiures (PCE) for 1973Q2. The daa poin was firs released in lae July 1973, and a ha ime he governmen announced ha real PCE grew 0.8% in he second quarer. Bu one monh laer, ha was revised down o 0.4%. In he annual revision released in lae July 1974, he growh rae for real PCE for 1973Q2 was up o 0.6%. The benchmark revision of January 1976 brough he growh rae down o 0.2%, bu hen he annual revision of July 1976 dropped i o negaive erriory for he firs ime, a -0.5%. Afer ha, i was mainly revised in benchmark revisions, bu as he char shows, hose revisions sill changed i subsanially, o -1.1% in December 1980, o -1.3% in July 1982 (correcing an error in he benchmark release), o -0.6% when he base year changed in he benchmark revision of December 1985, o -0.4% in he benchmark revision of November 1991, back o -0.5% (where i had been 20 years earlier) in he swich o chain weighing in February 1996, o -0.4% in he correcion o ha benchmark revision in April 1997, and finally o -0.2% in he benchmark revision of December Noe ha his daa poin was mos recenly revised over 30 years afer is iniial release. Daa in he Naional Income and Produc Accouns are never final, hough 5

9 under chain weighing, he changes should occur only when here are redefiniions of variables, so perhaps his number will never be changed again (hough I wouldn coun on i). Figure 1 Real Consumpion Growh for 1973Q2 (as viewed from he perspecive of 138 differen vinages) Percen Vinage All hese wiggles in he growh rae of his variable sugges ha daa revisions can considerably affec any analysis in he shor run. For example, if he quarerly growh rae of consumpion was he jumping off poin for a forecasing model, forecass are likely o be very sensiive o he vinage of he daa ha is used. If moneary policy depends on shor-erm growh raes, hen clearly policy misakes could be made if he cenral bank does no accoun for daa uncerainy. We migh no worry oo much abou daa revisions if shor-run revisions offse each oher in subsequen periods. Tha is, if consumpion spending ges revised up 0.5% one quarer bu 6

10 revised down 0.5% he nex quarer, hen all ha has happened is a change in iming, bu we end up in abou he same place a he end of he wo quarers. If subsequen errors offse each oher, hen relevan economic aggregaes, such as he average inflaion rae over a year or he average annual growh rae of GDP over five years, would no be affeced much. Bu we find insead ha daa revisions can be subsanial, even for five-year averages of he daa. Table 2 gives an example, for real consumpion spending, of growh raes over five-year periods and how much hey can change across vinages. Looking across vinages of he daa jus before benchmark revisions shows subsanial changes in he growh rae of real consumpion spending. For example, he average annual growh rae of real consumpion spending from 1975 o 1979 was 4.4% per year, as measured in he November 1980 or November 1985 vinages, bu only 3.9% as measured in November 1991 or November To some exen, large revisions in five-year growh raes arose because of he naure of fixed-weigh indexes used in he Unied Saes before Bu even in he chain-weighed era, some large revisions have occurred. For example, he average annual growh rae of real consumpion spending from 1990 o 1994 was 2.1% per year, as measured in he Augus 1999 vinage, bu revised up o 2.6% as measured in he Augus 2007 vinage. 7

11 Table 2 Average Growh Raes of Real Consumpion over Five Years Benchmark Vinages Annualized percenage poins Vinage Year: Period 49Q4 o 54Q Q4 o 59Q Q4 o 64Q Q4 o 69Q Q4 o 74Q Q4 o 79Q4 NA Q4 o 84Q4 NA NA Q4 o 89Q4 NA NA NA Q4 o 94Q4 NA NA NA NA Q4 o 99Q4 NA NA NA NA NA NA Does he revision process add news or reduce noise? Researchers have suggesed ha governmen daa agencies could behave in one of wo ways: adding news or reducing noise. If daa revisions conain news, ha means ha when he daa are iniially released, hey are opimal forecass of he laer daa, so revisions are orhogonal o each daa release. Tha is, where * v v y = y + e, (1) * y is he rue value of he variable, v y is he daa released by he governmen saisical agency for period in he daa release a vinage ime v, where v >. The variable v e is he error erm for ha daa release, showing he difference beween he rue value of he variable and he governmen s daa release for ha variable, and is independen of he governmen s daa release, so ha 8

12 ha is, v v y e, (2) v y is orhogonal o v e. In his case, revisions o he daa will no be predicable because he revision beween vinages v and v (where v > v) equals: r v', v = y y = e e. (3) v' v v v' By consrucion, boh erms on he righ-hand side of (3) are orhogonal o anyhing in he informaion se for vinage v, so he projecion of he revision on anyhing in he informaion se is zero. Thus he revision is no predicable. Alernaively, if daa revisions reduce noise, hen each vinage release equals he ruh plus a measuremen error: y v * v = y u, (4) where variable v u is he measuremen error, which is independen of he ruh, so ha y * v u. (5) Now, he revision equals: r v', v = y y = u u. (6) v' v v v' Bu he righ-hand side of (6) is predicable because i is correlaed wih daa known a v, namely v y. Various auhors have examined wheher paricular variables are characerized as having revisions ha reduce noise or add news. Mankiw-Runkle-Shapiro (1984) found ha revisions o he money supply daa reduced noise, while Mankiw-Shapiro (1986) found ha GDP revisions added news. Mork (1987) used GMM mehods o show ha final NIPA daa conain news, 9

13 while oher vinages are inefficien and neiher add news nor reduce noise. Using U.K. daa, Paerson-Heravi (1991) found ha revisions o mos componens of GDP reduce noise. Is he governmen using informaion efficienly? The resuls of he news-noise research raise he quesion of wha he governmen should repor o he public, as explored by Sargen (1989). Consider, for example, he governmen agency reporing GDP. One opion is for he agency o simply repor is sample informaion alone. An alernaive would be o look a oher daa o help i guess wha will happen o GDP as is sample becomes more complee. For example, suppose he sample informaion on he componens of GDP suggess ha i will grow 1.2% for he quarer (a an annual rae). However, suppose he agency observes ha employmen, which is highly correlaed wih GDP, grew a a 1.5% rae, and recenly produciviy has been growing a a 1.0% rae. Also, he agency observes ha gross domesic income has increased a a 0.8% rae. The governmen could make is release of GDP equal o is sample informaion alone, which would be a 1.2% growh rae. Then, as ime passes and he sample of daa improves, he noise in he daa is reduced; bu he iniial daa release is no an opimal forecas of he laer releases. Or, based on he relaionship in he pas beween GDP, employmen, and income, he agency could release a measure ha is an opimal forecas of laer revised daa. For example, an opimal forecas of laer releases of GDP migh show ha he agency should equally weigh is sample informaion, he growh rae of employmen plus recen produciviy growh, and he growh of income. So, i releases GDP growh as: 1/3[1.2% + (1.5% + 1.0%) + 0.8%] = 1.5%. This makes he iniial GDP release an opimal forecas of laer vinages of GDP. Revisions add news, and because a forecas is smooher han he objec being forecas, he sandard deviaion of laer vinages of he daa is higher han ha of earlier vinages. 10

14 A complicaing facor in he governmen s decision abou how o develop daa is he radeoff beween imeliness and accuracy. The governmen could produce beer daa if i waied unil is sample was more complee. Bu policymakers, especially hose a he cenral bank, need daa quickly if hey are o engage in acivis sabilizaion policy, and he public needs he daa wihou a long delay o make consumpion and invesmen decisions. Zarnowiz (1982) evaluaed he qualiy of differing series, wih mixed resuls. McNees (1989) found ha he wihin-quarer (flash) esimae of GDP ha he U.S. governmen produced for a few years was as accurae as he esimae released in he monh following he quarer. Despie ha resul, he governmen disconinued he series. In he U.K., Garra-Vahey (2004) found ha many daa series were biased and inefficien based on ex-pos ess, while Aruoba (2008) found he same resul for U.S. daa. To some exen, he findings ha iniial daa releases are biased and inefficien relaive o laer releases could be simply an arifac of he way ha seasonal adjusmen is performed, as suggesed by Kavajecz-Collins (1995) and Swanson-Ghysels-Callan (1999). Of course, i may be convenien for he governmen daa agencies o revise heir seasonal facors only once each year, as opposed o coninuously revising hem, which would lead o some small predicabiliy of revisions. In some cases, he revisions o seasonal facors are larger (in erms of mean absolue revisions) han revisions o he non-seasonally adjused esimaes; for example, see Fixler- Grimm-Lee (2003). Bu he size of he predicable revisions is likely oo small o be economically imporan, especially since such revisions mus, by definiion, wash ou over he year. 11

15 If iniial daa are based on incomplee informaion, or hey are forecass ha are smooher han he laer daa will be, hen he sae of he business cycle could be relaed o laer daa revisions. Tha is, daa revisions could be sysemaically relaed o business-cycle condiions. Dynan-Elmendorf (2001) found evidence ha GDP was misleading a urning poins, while Swanson-van Dijk (2004) found ha he volailiy of revisions o indusrial producion and producer prices increases in recessions. Are revisions forecasable? If daa revisions reduce noise, hen daa revisions are predicable. Given he finding ha many variables are characerized as having noise revisions, i should be possible o use real-ime daa o predic revisions. Bu here have been relaively few papers ha were acually able o do so. In par, ha may be because bias ha is observed afer he fac could arise because of redefiniions during benchmark revisions ha were no predicable in real ime. The papers ha have been able o documen explicily ha revisions were forecasable in real ime are: (1) Conrad-Corrado (1979), who used a Kalman filer o improve he governmen s daa on reail sales; (2) Guerrero (1993), who combined hisorical daa wih preliminary daa on Mexican indusrial producion o ge improved esimaes of final daa; and (3) Faus-Rogers-Wrigh (2005), who found ha among he G-7 counries, revisions o GDP in Japan and he U.K. were forecasable in real ime; and (4) Aruoba (2008), who used similar mehods o predic revisions for many differen variables. How should daa revisions be modeled? In par, research ino daa revisions is designed o help us discover how o model such revisions for use in macroeconomic models, for forecasing models, or for use in moneary policy. For U.S. daa, Howrey (1978), Conrad- Corrado (1979), and Harvey-McKenzie-Blake-Desai (1983) describe models of revisions. For 12

16 U.K. daa, Holden-Peel (1982), Paerson (1995), and Kapeanios-Yaes (2004) esablish he key properies of daa revisions. There are now an increasing number of papers ha describe daa revisions in various counries. Perhaps he only fruiful area in his line of research is showing he predicabiliy of revisions (beyond hose induced by revisions o seasonal facors) beween iniial and inermediae releases of he daa, which could help daa agencies improve heir mehods, if hey desire o release daa wih revisions ha add news. FORECASTING Revisions o daa may affec forecass considerably. The lieraure on forecasing wih real-ime daa has focused mainly on model developmen, in which researchers are aemping o build a new and improved forecasing model. They wan o compare forecass made wih a new model wih forecass made wih oher models or forecass repored in real ime. We examine five main areas: (1) How do forecass differ beween real-ime and laes available daa? (2) Does i maer wheher he forecass are in levels or growh raes? (3) How is model selecion affeced by daa revisions? (4) Does he predicive abiliy of variables depend on revisions? (5) How should forecass be made when we know ha he daa will be revised? Forecass are affeced by daa revisions because he revisions change he daa ha are inpu ino he model, he change in he daa affecs he esimaed coefficiens, and he model This secion summarizes he more deailed discussion in Croushore (2006) and discusses some addiional recen research. 13

17 iself may change, given he use of some procedure for model specificaion. Sark-Croushore (2002) perform a variey of experimens ha illusrae how each of hese mechanisms works in pracice. One issue ha arises in all of he forecasing lieraure wih real-ime daa is: Wha version of he daa should be used as acuals? Afer all, daa may coninue o ge revised forever, so we may never know he rue value of a variable. The bes overall measure of he ruh may be he laes available daa, as such daa presumably reflec he bes economic mehodology o arrive a a measure ha maches he heoreical concep for ha variable. Bu ha may no have been a good idea in he era of fixed-weighing of real aggregaes, which is known o disor growh raes in years disan from he base year. Under chain-weighing, his is no a problem. However, even hough we migh hink ha he laes available daa are as close as possible o he ruh, ha does no mean hey are useful for evaluaing forecass. Forecasers generally produce forecass of variables based on currenly exising mehodologies and canno be expeced o predic fuure changes in mehodology. We should no expec forecasers o anicipae redefiniions of variables ha will no occur for many years in he fuure. For example, in 2008, he U.S. Bureau of Economic Analysis announced ha saring in 2013, i is considering capializing expendiures on research and developmen, a move ha would likely cause real GDP o be revised up, on average, over ime. No forecaser oday is going o modify her forecass o accoun for he possibiliy five years hence; nor should anyone do so. Thus, evaluaions of forecass should usually focus on early releases of he daa, or he las vinage of he daa afer a forecas is made bu prior o a benchmark revision ha changes base years or redefines variables. Sill, mos evaluaions of forecas exercises are based on laes available daa for convenience, 14

18 even hough hey may provide a disored view of forecas abiliy. Wih real-ime daa ses becoming more readily available, here is less need o do his, so we should see more papers in he forecasing lieraure based on using some real-ime concep as acuals for evaluaing he forecass. How do forecass differ beween real-ime and laes-available daa? The idea ha riggered he creaion of he real-ime daa se for macroeconomiss was a forecasing paper ha claimed ha a new forecasing model could bea he U.S. Survey of Professional Forecasers (SPF) ha I had creaed by aking over he defunc ASA-NBER survey in A researcher buil a beer mouserap and showed ha i provided beer forecass han he SPF. Bu, of course, he new model used only he laes available daa and was no esed on real-ime daa because no such daa se exised in he Unied Saes. Bu clearly he righ way o es he new model agains he SPF would be o run he real-ime daa hrough he new model o simulae how he model would forecas in real ime. The firs paper o engage in an exercise of comparing forecass based on real-ime daa versus forecass based on laes-available daa was Denon-Kuiper (1965). They found significan differences in he forecass made for Canadian daa depending on wheher real-ime daa or laes-available daa were used. Cole (1969) found ha daa errors reduced forecas efficiency and led o biased forecass. Trivellao-Reore (1986) showed ha daa errors (using Ialian daa) in a simulaneous-equaions model affeced everyhing, including he esimaed coefficiens and forecass, bu did no affec he forecas errors oo much. However, Faus-Rogers-Wrigh (2003) showed ha for exchange-rae forecasing, he forecass were exremely sensiive o he vinage of he daa. Some vinages showed ha i was possible o forecas exchange raes in real ime; bu 15

19 oher vinages showed ha such forecass performed worse han a naïve model. Molodsova (2007) found ha combining real-ime daa wih a Taylor rule for moneary policy in numerous OECD counries shows ha exchange raes can be prediced. Similarly, Molodsova-Nikolsko- Rzhevskyy-Papell (2007) found ha he dollar/mark exchange rae was predicable using only real-ime daa, no wih revised daa. Overall, he lieraure shows ha he impac of using real-ime daa compared wih laes available daa in forecasing depends on he specific exercise in quesion someimes such a difference in he daa maers, bu oher imes i makes no difference. Levels versus growh raes. Howrey (1996) found ha level forecass of real oupu were more sensiive o daa revisions han forecass of growh raes, so he suggesed ha policy should feed back on growh raes, no levels (a resul similar o ha found in he moneary-policy lieraure on policy making wih analyical revisions). Kozicki (2002) showed ha he choice of forecasing wih real-ime or laes-available daa is imporan for variables wih large revisions o levels. Model selecion and specificaion. Given ha daa are revised, how do alernaive vinages of he daa affec he specificaions of forecasing models? Swanson-Whie (1997) explored model selecion wih real-ime daa. The sensiiviy of model specificaion o he vinage of he daa may depend on he variable in quesion, as Roberson-Tallman (1998) found ha specificaion of he model for indusrial producion was sensiive o he vinage of he daa, bu he same was no rue for GDP. Harrison-Kapeanios-Yaes (2005) showed ha i may be opimal o esimae a model wihou using he mos recen preliminary daa because hose daa have no been revised as much as earlier daa. This is a subjec o which I will reurn laer. 16

20 The predicive conen of variables. In forecasing ou-of-sample, does i maer wheher a forecaser bases a model on real-ime daa or laes available daa? Tha is, would we draw he same conclusions abou wheher one variable is helpful in forecasing anoher variable when we use real-ime daa compared wih laes-available daa? Croushore (2005) suggesed ha consumer confidence indicaors have no ou-of-sample predicive power for consumpion spending. The real-ime naure of he daa maers, since using laes available daa or examining in-sample predicive power increases he abiliy of consumer confidence indexes o predic consumer spending. How should forecass be made when we know daa are going o be revised? Can forecasing models be modified in a sensible way when we know ha daa will be revised, o accoun for he greaer uncerainy abou more recen daa? Howrey (1978) showed how daa can be adjused for differing degrees of revisions using he Kalman filer. This suggess ha raher han ignoring recen daa, he forecasing model should use i, bu filer i firs. Harvey e al. (1983) used sae-space mehods wih missing observaions o accoun for irregular daa revisions and found a large gain in efficiency from doing so, compared wih ignoring daa revisions. Paerson (2003) illusraed how o combine he measuremen process wih he daa generaion process o improve upon forecass for income and consumpion. However, some aemps a using hese mehods in pracice found lile scope for improvemen. For example, Howrey (1984) found ha using sae-space models o improve forecass of invenory invesmen yields lile improvemen. One issue in he lieraure ha has only been addressed sparingly is how much of he informaion se o use in rying o improve forecass. Typically, forecasers use laes-available 17

21 daa in consrucing and esimaing heir forecasing models. Bu Koenig-Dolmas-Piger (2003) and Kishor-Koenig (2005) argue ha forecasers could make beer forecass by focusing on he diagonals of he real-ime daa marix, so ha hey are modeling daa in a consisen way depending on how much each piece of daa has been revised. Thus, forecasers need o rea daa ha have no been revised differenly from daa ha have gone hrough one annual revision, which should in urn be reaed differenly from daa ha have gone hrough a benchmark revision. Overall, here are someimes gains o accouning for daa revisions. Bu he predicabiliy of revisions may be small relaive o he forecas error. To some exen, he predicabiliy of revisions is a funcion of he procedure ha saisical agencies use for seasonal adjusmen. They seldom adjus seasonal facors conemporaneously bu insead change he seasonal facors only once each year. As a resul, such revisions are easily predicable bu small and usually no economically significan, as Swanson e al. (1999) showed. A roublesome issue in he saespace modeling approach is specifying an ARIMA process for daa revisions because benchmark revisions end o be idiosyncraic. Also, forecasers need o ask hemselves wheher he coss of dealing wih real-ime issues are worh he benefis. Are daa revisions small relaive o oher problems in forecasing? MONETARY POLICY Given he real-ime naure of policymaking, i is naural ha much research wih realime daa is geared oward moneary policy. I will disinguish beween daa revisions and revisions o measures of analyical conceps. The former is wha we normally hink of when we 18

22 consider he governmen releasing daa wih larger samples. Bu he laer may be more imporan because macroeconomic models depend on analyical conceps, especially he oupu gap and he level of poenial GDP, he naural rae of unemploymen, and he equilibrium real ineres rae. I begin by looking a research on daa revisions, including: (1) How much does i maer ha daa are revised? (2) How misleading is moneary policy analysis based on final daa insead of real-ime daa? (3) How should moneary policymakers handle daa uncerainy? How much does i maer ha daa are revised? Daa revisions clearly maer for moneary policy. The Federal Reserve s main indicaors of inflaion are he PCE inflaion rae and he core PCE inflaion rae (excluding food and energy prices). Bu revisions o hese variables are subsanial and could mislead he Fed, as Croushore (2008) shows. If moneary policymakers know ha daa will be revised, hey may opimally exrac he signal from he daa, so daa revisions may no significanly affec moneary policy, as Maravall-Pierce (1986) show. Kugler e al. (2005) show how he Swiss cenral bank s reacion funcion should change in he presence of GDP revisions, showing ha he economy would be more volaile if he cenral bank reaced oo srongly o iniial daa. How misleading is moneary policy analysis based on final daa insead of real-ime daa? If daa are revised, bu researchers do no ake ha fac ino accoun, hen i is possible ha heir research resuls will be misleading. However, Croushore-Evans (2006) find ha daa revisions do no significanly affec measures of moneary policy shocks. However, in a simulaneous sysem of equaions, idenificaion is a difficul problem when daa revisions exis. How should moneary policymakers handle daa uncerainy? Given ha he daa are likely o be revised, wha can policymakers do? One possibiliy is o use informaion on 19

23 addiional variables. Coenen-Levin-Wieland (2001) show ha policymakers facing uncerainy abou oupu can use daa on money supply o help hem make beer decisions. More recenly, many researchers have suggesed ha moneary policymakers use facor models o summarize he informaion in large numbers of variables, in he hopes ha uncerainy in any paricular daa series washes ou across many variables. Bernanke-Boivin (2003) find ha such a facor model is useful and ha wheher he daa used in he model are real-ime or laes-available does no have much impac on he resuls. In a similar vein, Giannone-Reichlin-Sala (2005) show how a dynamic facor model can be used o exrac real-ime informaion, finding ha wo facors are presen in U.S. daa: one nominal and one real. Moneary policymakers should respond o shocks o hese wo facors. Theoreically, in siuaions in which here is no cerainy equivalence, policymakers facing poenial daa revisions should be less aggressive wih moneary policy, as Aoki (2003) illusraes. Similar resuls obain when here is uncerainy abou poenial oupu and oher analyical conceps, as I discuss in he nex secion. Analyical revisions. Models of he economy ofen rely on analyical conceps, such as he oupu gap, he naural rae of unemploymen, and he equilibrium real federal funds rae. Such conceps are never observed, bu policymakers and heir saffs may esimae such conceps in real ime. If heir esimaes are far from he mark, policy decisions may be poor. The lieraure on he consequences for moneary policymaking of revisions o concepual variables begins wih Orphanides (2001), who finds ha he Fed overreaced o bad measures of he oupu gap in he 1970s, causing moneary policy o be much oo easy. Had he Fed known he rue value of he oupu gap, which would have required i o cach on more quickly o he 20

24 1970s slowdown in produciviy, i would no have eased policy nearly as much, and he Grea Inflaion of he 1970s migh have been avoided. If policymakers do no respond o he possibiliy of analyical revisions a all, hey are likely o be overly aggressive in heir policy acions. Research shows ha his leads o overly volaile movemens in oupu and inflaion. For example, using Taylor rules o explain he cenral bank s behavior, he consequences of policy making ha ignores analyical revisions can be seen in research ha plugs alernaive daa vinages ino he Taylor rule o see how differen policy would be. Kozicki (2004) does so wih U.S. daa and Kamada (2005) does he same for Japan. Rudebusch (2001) does some reverse engineering of he Taylor rule o show ha daa uncerainy maers significanly in deermining why he rule has he coefficiens i does. If he daa were no uncerain, he opimal Taylor rule would be much more aggressive han i is in he daa. Orphanides (2003) shows ha if policymakers adop opimal rules based on revised daa, hen in real ime hey will make subsanial policy errors. The opimal rules are oo aggressive given he difficuly in measuring inflaion and he oupu gap in real ime. Cukierman-Lippi (2005) sugges ha he Fed was oo aggressive given he naure of he daa in he 1970s, bu was appropriaely conservaive in response o he iniial daa in he 1990s, which explains he beer macroeconomic performance of he laer period. Boivin (2006) used real-ime daa o find ha he Fed changed policy parameers over his period, and ha he poor performance in he 1970s occurred when he Fed emporarily reduced is response o inflaion. Issues concerning he measuremen of various naural raes have been explored in several papers. Orphanides-Williams (2002) find ha here are large coss o ignoring poenial mismeasuremen of he naural rae of unemploymen and he naural rae of ineres. Saiger- 21

25 Sock-Wason (1997) show how much uncerainy here is abou he naural rae of unemploymen, while Clark-Kozicki (2005) demonsrae he remendous uncerainy abou naural raes of ineres. Daa from he Unied Saes on he oupu gap has been sudied mos frequenly because of daa availabiliy; Orphanides-van Norden (2002) demonsrae how uncerain is he U.S. oupu gap in real ime. Bu as daa become more readily available in oher counries, new research on oupu gaps in oher counries has been produced. Nelson-Nikolov (2003) find ha errors in he oupu gap were even greaer in he U.K. han hey were in he U.S. and may have led policymakers asray. Gerberding-Seiz-Worms (2005) show ha he Bundesbank responded o real-ime daa on he oupu gap, inflaion, and deviaions of money growh from arge, whereas previous sudies using only laes available daa found no role for money growh. Gerdesmeieir- Roffia (2005) show how differen Taylor rule esimaions are for he Euro area depending on wheher revised daa or real-ime daa are used. Analysis focused on he implicaions of differen vinages of oupu gaps in various counries includes Bernhardsen e al. (2005) for Norway; Cayen-van Norden (2005) for Canada; and Döpke (2005) for Germany. Revisions in analyical conceps may lead he models used by moneary policymakers o change significanly. As Telow-Ironside (2007) show, changes in he Fed s FRB-U.S. model from he mid-1990s o he early 2000s caused subsanial changes in he inpu ha he model provided o policymakers. A key issue in his lieraure is how policymakers and heir advisers can opimally use real-ime daa o make some inference abou he oupu gap or some oher forward-looking concep given he uncerainy in real ime. The oupu gap or naural rae of unemploymen or 22

26 naural rae of ineres is much easier o calculae for he pas, bu nearly impossible o pin down very well in real ime. Much of he research described above uses some mehod o ry o calculae he analyical concep a he end of he sample, bu he accuracy of a gap or rend measure improves dramaically as ime passes. As Wason (2007) noes: One-sided esimaes necessary for real-ime policy analysis are subsanially less accurae han he wo-sided esimaes used for hisorical analysis. This may no be an area ha will be fruiful for fuure research, as here may be no beer soluion han hose ha have already been ried. Wha hasn been examined, however, is a more heoreical approach o creaing a model of he evoluion of analyical conceps; insead, much of he work is purely saisical. MACROECONOMIC RESEARCH Macroeconomic research can be influenced by daa revisions in a number of ways. Firs, we explore he quesion of wheher research resuls are robus o alernaive vinages of he daa. Second, we ask if daa revisions are imporan enough o he economy ha hey should become an explici par of large macroeconomic models. Third, we look a wheher daa revisions affec economic aciviy. The robusness of research resuls. One paricularly beneficial use of real-ime daa is ha i gives us a chance o perform some simple replicaion experimens. Empirical macroeconomic research has esablished a number of imporan resuls, bu here has been relaively lile research replicaing hose resuls. We would like o know how robus hose resuls are o he use of alernaive daa ses and hus how general he resuls are. 23

27 One way o es robusness was explored by Croushore and Sark (2003). They reran a number of major macroeconomic sudies using differen vinages of he daa. The idea is ha he original research was based on a paricular daa se. Bu over ime, he daa used in he sudy become revised. Wha if he research was done again using a more recen daa se? If he resuls are robus, he change of daa se should no cause a problem; bu if he resuls are sensiive o he paricular daa se, hen he major resuls of he research should change. Croushore and Sark esed a number of major macroeconomic sudies. Firs, hey used he same sample period bu more recen vinages of daa. Then, hey used boh a more recen vinage as well as a larger sample. They found ha while RBC business-cycle facs were robus o a change in he daa se, evidence for he life-cycle permanen-income hypohesis was no nor were impulse responses of oupu and unemploymen o demand shocks. There have been few oher ess of he robusness of research resuls o daa revisions. The firs paper o do so was Boschen-Grossman (1982), which used daa revisions in an analysis of he neuraliy of money under raional expecaions; his paper provided key evidence agains equilibrium models in he classical radiion. Boschen-Grossman explicily modeled he daa revision process o develop a model ha shows how he economy would reac o preliminary daa subjec o laer revisions. One hypohesis of raional-expecaions equilibrium macroeconomics is ha he conemporaneously observed money supply should no affec oupu or employmen. Tess based on final, revised daa suppor he hypohesis, bu Boschen- Grossman s ess using real-ime daa rejec he hypohesis. A second hypohesis is ha revisions o money supply daa should be posiively correlaed wih oupu and employmen; bu again real-ime daa are no consisen wih he hypohesis. Thus, he Boschen-Grossman analysis 24

28 showed ha empirical resuls ha were based on laes-available daa led o subsanially differen resuls han hose based on real-ime daa. A paper by Amao-Swanson (2001) found ha ess confirming he predicive conen of money for oupu, which used laes-available daa, do no hold up when real-ime daa are used. In real-ime, and in ou-of-sample forecasing exercises, money is no useful for predicing fuure oupu. Should macroeconomic models incorporae daa revisions? If daa revisions are large and no whie noise, hen incorporaing hem ino macroeconomic models may be a desirable sep o ake. One approach, developed by Aruoba (2004), is o incorporae daa revisions ino a DSGE model. Aruoba finds ha business-cycle dynamics are beer capured in such a framework han in one ha does no incorporae daa revisions. Edge-Laubach-Williams (2004) examine uncerainy abou ransiory and permanen shocks o produciviy growh. The ransiory-permanen confusion affecs agens, especially because daa on produciviy are revised subsanially, and helps o explain cycles in employmen, invesmen, and long-erm ineres raes in a DSGE model. Do daa revisions affec economic aciviy? Oh-Waldman (1990) hypohesize ha, based on a model of sraegic complemenariy, an announcemen of a forecas of srong fuure economic aciviy will lead people o produce more, simply because hey believe he announcemen and hey desire o produce a lo when he economy is sronger. This is rue even if he daa are subsequenly revised down. Thus, false announcemens ha he economy is doing well sill lead o increased economic aciviy. Oh-Waldman es his using daa on he index of leading indicaors and indusrial producion. They find ha oupu is higher when he leading 25

29 indicaors are iniially released and hen laer revised down, han if he iniial release of he leading indicaor was correc. So, oupu ends o respond posiively o he leading indicaor announcemen. Bomfim (2001) asks wheher economic agens are beer off if daa is of higher qualiy. In his real-business-cycle-framework, agens mus make facor allocaion decisions before hey know wha produciviy is. Laer, hey can observe produciviy bu canno disinguish beween permanen and ransiory shocks o produciviy. As a resul, hey mus engage in signal exracion, based on he daa hey observe. Ineresingly, if daa qualiy improves, and if agens use opimal signal-exracion mehods, hen economic aggregaes become more volaile. The increased volailiy occurs because he daa are more reliable, so agens do no discoun new releases of he daa bu respond more srongly o hem. On he oher hand, if agens naively believe ha he iniial releases of he daa are accurae and do no perform any signal exracion, hen improvemens in daa qualiy would lead o a reducion of economic volailiy. In all hree areas (esing robusness of research resuls, incorporaing daa revisions ino macroeconomic models, and examining how or wheher daa revisions affec economic aciviy) he lieraure is in is infancy and here is grea need for addiional exploraion. CURRENT ANALYSIS As economiss in real ime sif hrough he macroeconomic daa o discover urning poins, does he real-ime naure of he daa lead us o pay aenion o variables in a manner differen han if we were looking a revised daa? 26

30 Chrisoffersen-Ghysels-Swanson (2002) show ha researchers should use real-ime daa o properly evaluae announcemen effecs in financial markes; prior sudies based on laes available daa were misleading. The use of real-ime daa provides a more accurae view of he rewards in financial markes o aking on macroeconomic risks. A number of papers have examined he issue of idenifying urning poins in he business cycle in real ime. Chauve-Piger (2003) use a Markov-swiching model applied o real-ime daa on oupu growh and payroll employmen o see if hey can idenify NBER urning poins in real ime. They are able o mach he NBER business-cycle daes fairly accuraely and idenify business-cycle roughs (bu no peaks) on a more imely basis. Chauve-Piger (2005) exend his approach wih addiional daa (on he main four variables used by he NBER iself) and a nonparameric model as well as he Markov-swiching model used in heir 2003 paper; hey confirm he resuls of heir earlier paper. Chauve-Hamilon (2006) hen use he Markovswiching model and he four main NBER variables o develop a monhly model ha produces a recession-probabiliy index. The index calls business cycle urning poins very similarly o he NBER s chronology bu declares urning poins on a more imely basis. In a relaed paper, Nalewaik (2007) finds ha he use of gross domesic income (GDI) in a Markov-swiching model produces more accurae recession probabiliies han he same model using gross domesic produc (GDP). To dae, here has been relaively lile research on curren analysis in real ime, wih much scope for addiional work. 27

31 CONCLUSIONS The field of real-ime daa analysis is a ferile one, and here are many unanswered quesions. The mos promising areas are in macroeconomic research, since here has been relaively lile incorporaion of daa revisions ino macroeconomic models and in curren analysis of business and financial condiions. Exploraions of he naure of daa revisions, of forecasing, and of moneary policy have reached a more maure sage, so new papers in hese areas will need o be more refined. 28

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33 Chauve, Marcelle, and Jeremy Piger. A Comparison of he Real-Time Performance of Business Cycle Daing Mehods. Federal Reserve Bank of S. Louis Working Paper A, March Chrisoffersen, Peer, Eric Ghysels, and Norm Swanson. Le s Ge Real Abou Using Economic Daa. Journal of Empirical Finance 9.3 (2002) pp Clark, Todd E., and Sharon Kozicki. Esimaing Equilibrium Real Ineres Raes in Real Time. Norh American Journal of Economics and Finance 16 (December 2005), pp Coenen, Guner, Andrew Levin, and Volker Wieland. Daa Uncerainy and he Role of Money as an Informaion Variable for Moneary Policy. Federal Reserve Board FEDS working paper (2001). Cole, Rosanne, Daa Errors and Forecasing Accuracy, in Jacob Mincer, ed., Economic Forecass and Expecaions: Analyses of Forecasing Behavior and Performance. New York: Naional Bureau of Economic Research, 1969, pp Conrad, William, and Carol Corrado. Applicaion of he Kalman Filer o Revisions in Monhly Reail Sales Esimaes. Journal of Economic Dynamics and Conrol 1 (1979), pp Croushore, Dean. Do Consumer Confidence Indexes Help Forecas Consumer Spending in Real Time? Norh American Journal of Economics and Finance 16 (December 2005), pp Croushore, Dean. Forecasing wih Real-Time Macroeconomic Daa. In: Graham Ellio, Clive W.J. Granger, and Allan Timmermann, eds., Handbook of Economic Forecasing (Amserdam: Norh-Holland, 2006). Croushore, Dean. Revisions o PCE Inflaion Measures: Implicaions for Moneary Policy. Manuscrip, Universiy of Richmond, March Croushore, Dean, and Charles L. Evans. Daa Revisions and he Idenificaion of Moneary Policy Shocks. Journal of Moneary Economics 53 (Sepember 2006), pp Croushore, Dean, and Tom Sark. A Real-Time Daa Se for Macroeconomiss. Journal of Economerics 105 (November 2001), pp Croushore, Dean, and Tom Sark, A Real-Time Daa Se for Macroeconomiss: Does he Daa Vinage Maer? Review of Economics and Saisics 85 (Augus 2003), pp Cukierman, Alex, and Francesco Lippi. Endogenous Moneary Policy wih Unobserved Poenial Oupu. Journal of Economic Dynamics and Conrol (November 2005), pp