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1 Wha Do We Know (And No Know) Abou Poenial Oupu? Susano Basu and John G. Fernald Poenial oupu is an imporan concep in economics. Policymakers ofen use a one-secor neoclassical model o hink abou long-run growh, and hey ofen assume ha poenial oupu is a smooh series in he shor run approximaed by a medium- or long-run esimae. Bu in boh he shor and he long run, he one-secor model falls shor empirically, reflecing he imporance of rapid echnological change in producing invesmen goods; and few, if any, modern macroeconomic models would imply ha, a business cycle frequencies, poenial oupu is a smooh series. Discussing hese poins allows he auhors o discuss a range of oher issues ha are less well undersood and where furher research could be valuable. (JEL E32, O41, E60) Federal Reserve Bank of S. Louis Review, July/Augus 2009, 91(4), pp The concep of poenial oupu plays a cenral role in policy discussions. n he long run, faser growh in poenial oupu leads o faser growh in acual oupu and, for given rends in populaion and he workforce, faser growh in income per capia. n he shor run, policymakers need o assess he degree o which flucuaions in observed oupu reflec he economy s opimal response o shocks, as opposed o undesirable deviaions from he ime-varying opimal pah of oupu. To keep he discussion manageable, we confine our discussion of poenial oupu o neoclassical growh models wih exogenous echnical progress in he shor and he long run; we also focus exclusively on he Unied Saes. We make wo main poins. Firs, in boh he shor and he long run, rapid echnological change in producing equipmen invesmen goods is imporan. This rapid change in he producion echnology for invesmen goods implies ha he wo-secor neoclassical model where one secor produces invesmen goods and he oher produces consumpion goods provides a beer benchmark for measuring poenial oupu han he one-secor growh model. Second, in he shor run, he measure of poenial oupu ha maers for policymakers is likely o flucuae subsanially over ime. Neiher macroeconomic heory nor exising empirical evidence suggess ha poenial oupu is a smooh series. Policymakers, however, ofen appear o assume ha, even in he shor run, poenial oupu is well approximaed by a smooh rend. 1 Our model and empirical work corroborae hese wo poins and provide a framework o discuss oher aspecs of wha we know, and do no know, abou poenial oupu. As we begin, clear definiions are imporan o our discussion. Poenial oupu is ofen used 1 See, for example, ongressional Budge Office (BO, 2001 and 2004) and Organisaion for Economic o-operaion and Developmen (2008). Susano Basu is a professor in he deparmen of economics a Boson ollege, a research associae of he Naional Bureau of Economic Research, and a visiing scholar a he Federal Reserve Bank of Boson. John G. Fernald is a vice presiden and economis a he Federal Reserve Bank of San Francisco. The auhors hank Alessandro Baraieri and Kyle Maoba for ousanding research assisance and Jonas Fisher and Miles Kimball for helpful discussions and collaboraion on relaed research. They also hank Bar Hobijn, had Jones, John Williams, Rody Manuelli, and conference paricipans for helpful discussions and commens. 2009, The Federal Reserve Bank of S. Louis. The views expressed in his aricle are hose of he auhor(s) and do no necessarily reflec he views of he Federal Reserve Sysem, he Board of Governors, or he regional Federal Reserve Banks. Aricles may be reprined, reproduced, published, disribued, displayed, and ransmied in heir enirey if copyrigh noice, auhor name(s), and full ciaion are included. Absracs, synopses, and oher derivaive works may be made only wih prior wrien permission of he Federal Reserve Bank of S. Louis. FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

2 o describe relaed, bu logically disinc, conceps. Firs, people ofen mean somehing akin o a forecas for oupu and is growh rae in he longer run (say, 10 years ou). We will ofen refer o his firs concep as a seady-sae measure, alhough a decade-long forecas can also incorporae ransiion dynamics oward he seady sae. 2 n he shor run, however, a seady-sae noion is less relevan for policymakers who wish o sabilize oupu or inflaion a high frequencies. This leads o a second concep, explici in New Keynesian dynamic sochasic general equilibrium (DSGE) models: Poenial oupu is he rae of oupu he economy would have if here were no nominal rigidiies bu all oher (real) fricions and shocks remained unchanged. 3 n a flexible price real business cycle model, where prices adjus insananeously, poenial oupu is equivalen o acual, equilibrium oupu. n conras o he firs definiion of poenial oupu as exclusively a long-erm phenomenon, he second meaning defines i as relevan for he shor run as well, when shocks push he economy emporarily away from seady sae. n New Keynesian models, where prices and/or wages migh adjus slowly oward heir long-run equilibrium values, acual oupu migh well deviae from he shor-erm measure of poenial oupu. n many of hese models, he oupu gap he difference beween acual and poenial oupu is he key variable in deermining he evoluion of inflaion. Thus, his second definiion also corresponds o he older Keynesian noion ha poenial oupu is he maximum producion wihou inflaionary pressure (Okun, 1970, p. 133) ha is, he level of oupu a which here is no pressure for inflaion o eiher increase or decrease. n mos, if no all, macroeconomic models, he second (flexible price) definiion converges in he long run o he firs seady-sae definiion. 2 n some models, ransiion dynamics can be very long-lived. For example, Jones (2002) inerpres he pas cenury as a ime when growh in oupu per capia was relaively consan a a rae above seady sae. 3 See Woodford (2003) for he heory. Neiss and Nelson (2005) consruc an oupu gap from a small, one-secor DSGE model. Ye a hird definiion considers poenial oupu as he curren opimal rae of oupu. Wih disorionary axes and oher marke imperfecions (such as monopolisic compeiion), neiher seady-sae oupu nor he flexible price equilibrium level of oupu needs o be opimal or efficien. Like he firs wo conceps, his hird meaning is of ineres o policymakers who migh seek o improve he efficiency of he economy. 4 (However, decades of research on ime inconsisency sugges ha such policies should be implemened by fiscal or regulaory auhoriies, who can arge he imperfecions direcly, bu no by he cenral bank, which ypically mus ake hese imperfecions as given. See, for example, he seminal paper by Kydland and Presco, 1977.) This aricle focuses on he firs wo definiions. The firs par of our aricle focuses on long-erm growh, which is clearly an issue of grea imporance for he economy, especially in discussions of fiscal policy. For example, wheher promised enilemen spending is feasible depends almos enirely on long-run growh. We show ha he predicions of wo-secor models lead us o be more opimisic abou he economy s long-run growh poenial. This par of our aricle, which corresponds o he firs definiion of poenial oupu, will hus be of ineres o fiscal policymakers. The second par of our aricle, of ineres o moneary policymakers, focuses on a ime-varying measure of poenial oupu he second usage above. Poenial oupu plays a cenral, if ofen implici, role in moneary policy decisions. The Federal Reserve has a dual mandae o pursue low and sable inflaion and maximum susainable employmen. Maximum susainable employmen is usually inerpreed o imply ha he Federal Reserve should srive, subjec o is oher mandae, o sabilize he real economy around is flexible price equilibrium level which iself is changing in response o real shocks o avoid inefficien flucuaions in employmen. n New Keynesian models, deviaions of acual from poenial oupu pu pressure on inflaion, so in 4 Jusiniano and Primiceri (2008) define poenial oupu as his hird measure, wih no marke imperfecions; hey use he erm naural oupu o mean our second, flexible-wage/price measure JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

3 he simples such models, oupu sabilizaion and inflaion sabilizaion go hand in hand. The firs secion of his aricle compares he seady-sae implicaions of one- and wo-secor neoclassical models wih exogenous echnological progress. Tha is, we focus on he long-run effecs of given rends in echnology, raher han rying o undersand he sources of his echnological progress. 5 Policymakers mus undersand he naure of echnological progress o devise policies o promoe long-run growh, bu i is beyond he scope of our aricle. n he nex secion, we use he wo-secor model o presen a range of possible scenarios for long-erm produciviy growh and discuss some of he quesions hese differen scenarios pose. We hen urn o shor-erm implicaions and ask wheher i is plausible o hink of poenial oupu as a smooh process and compare he implicaions of a simple one-secor versus wosecor model. The subsequen secion urns o he curren siuaion (as of lae 2008): How does shor-run poenial oupu growh compare wih is seady-sae level? This discussion suggess a number of addiional issues ha are unknown or difficul o quanify. The final secion summarizes our findings and conclusions. THE LONG RUN: WHAT SMPLE MODEL MATHES THE DATA? A common, and fairly sensible, approach for esimaing seady-sae oupu growh is o esimae growh in full-employmen labor produciviy and hen allow for demographics o deermine he evoluion of he labor force. This approach moivaes his secion s assessmen of seadysae labor produciviy growh. We generally hink ha, in he long run, differen forces explain labor produciviy and oal hours worked echnology along wih induced 5 Of course, oal facor produciviy (TFP) can change for reasons broader han echnological change alone; improved insiuions, deregulaion, and less disorionary axes are only some of he reasons. We believe, however, ha long-run rends in TFP in developed counries like he Unied Saes are driven primarily by echnological change. For evidence supporing his view, see Basu and Fernald (2002). capial deepening explains he former and demographics explains he laer. The assumpion ha labor produciviy evolves separaely from hours worked is moivaed by he observaion ha labor produciviy has risen dramaically over he pas wo cenuries, whereas labor supply has changed by much less. 6 Even if produciviy growh and labor supply are relaed in he long run, as suggesed by Elsby and Shapiro (2008) and Jones (1995), he analysis ha follows will capure he key properies of he endogenous response of capial deepening o echnological change. A reasonable way o esimae seady-sae labor produciviy growh is o esimae underlying echnology growh and hen use a model o calculae he implicaions for capial deepening. Le has over a variable represen log changes. As a maer of ideniies, we can wrie oupu growh, ŷ, as labor-produciviy growh plus growh in hours worked, ĥ: We focus here on full-employmen labor produciviy. Suppose we define growh in oal facor produciviy (TFP), or he Solow residual, as where α is capial s share of income and 1 α is labor s share of income. Defining where lq is labor qualiy (composiion) growh, 7 we can rewrie oupu per hour growh as follows: (1) +. yˆ = yˆ hˆ hˆ fp = yˆ αkˆ 1 α ˆl, lˆ hˆ + lq, = + ( ) + yˆ hˆ fp α kˆ lˆ lq. As an ideniy, growh in oupu per hour worked reflecs TFP growh; he conribuion of 6 King, Plosser, and Rebelo (1988) sugges a firs approximaion should model hours per capia as independen of he level of echnology and provide necessary and sufficien condiions on he uiliy funcion for his resul o hold. Basu and Kimball (2002) show ha he paricular non-separabiliy beween consumpion and hours worked ha is generally implied by he King-Plosser- Rebelo uiliy funcion helps explain he evoluion of consumpion in poswar U.S. daa and resolves several consumpion puzzles. 7 See foonoe 7 on p FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

4 capial deepening, defined as α kˆ lˆ ; and increases in labor qualiy. Economic models sugges mappings beween fundamenals and he erms in his ideniy ha are someimes rivial and someimes no. The One-Secor Model Perhaps he simples model ha could reasonably be applied o he long-run daa is he onesecor neoclassical growh model. Technological progress and labor force growh are exogenous and capial deepening is endogenous. We can derive he key implicaions from he exbook Solow version of he model. onsider an aggregae producion funcion Y = K α AL 1 α, where echnology A grows a rae g and labor inpu L (which capures boh raw hours, H, and labor qualiy, LQ henceforh, we do no generally differeniae beween he wo) grows a rae n. Expressing all variables in erms of effecive labor, AL, yields (2) where y = Y/AL and k = K/AL. apial accumulaion akes place according o he perpeual-invenory formula. f s is he saving rae, so ha sy is invesmen per effecive worker, hen in seady sae (3) y = k α, sy = n + δ + g k. Because of diminishing reurns o capial, he economy converges o a seady sae where y and k are consan. A ha poin, invesmen per effecive worker is jus enough o offse he effecs of 7 Labor qualiy/composiion reflecs he mix of hours across workers wih differen levels of educaion, experience, and so forh. For he purposes of his discussion, which so far has focused on definiions, suppose here were J ypes of workers wih facor shares of income β j, where βj = ( 1 α). Then a reasonable definiion of TFP would be j fp = yˆ αkˆ j β j hˆ j. Growh accouning as done by he Bureau of Labor Saisics or by Dale Jorgenson and his collaboraors (see, for example, Jorgenson, Gollop, and Fraumeni, 1987) defines ˆl = β hˆ 1 α, h ˆ dln H, and qˆ ˆl h. ˆ j j j = j = j depreciaion, populaion growh, and echnological change on capial per effecive worker. n seady sae, he unscaled levels of Y and K grow a he rae g + n; capial deepening, K/L, grows a rae g. Labor produciviy Y/L (i.e., oupu per uni of labor inpu) also grows a rae g. From he producion funcion, measured TFP growh is relaed o labor-augmening echnology growh by = ( ) fp = Yˆ αkˆ 1 α Lˆ 1 α g. The model maps direcly o equaion (1). n paricular, he endogenous conribuion of capial deepening o labor-produciviy growh is αg = α fp / 1 α. Oupu per uni of labor inpu grows a rae g, which equals he sum of sandard TFP growh, 1 α g, and induced capial deepening, αg. Table 1 shows how his model performs relaive o he daa. uses he mulifacor produciviy release from he Bureau of Labor Saisics (BLS), which provides daa for TFP growh as well as capial deepening for he U.S. business economy. These daa are shown in he firs wo columns. Noe ha in he model above, sandard TFP growh reflecs echnology alone. n pracice, a large segmen of he lieraure suggess reasons why nonechnological facors migh affec measured TFP growh. For example, here are hardo-measure shor-run movemens in labor effor and capial s workweek, which cause measured (alhough no acual) TFP o flucuae in he shor run. Nonconsan reurns o scale and markups also inerfere wih he mapping from echnological change o measured aggregae TFP. Bu he deviaions beween echnology and measured TFP are likely o be more imporan in he shor run han in he long run, consisen wih he findings of Basu, Fernald, and Kimball (2006) and Basu e al. (2008). Hence, for hese longer-erm comparisons, we assume average TFP growh reflecs average echnology growh. olumn 3 shows he predicions of he one-secor neoclassical model for α = 0.32 (he average value in he BLS mulifacor daase) JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

5 Table 1 One-Secor Growh Model Predicions for he U.S. Business Secor Prediced capial Acual capial deepening conribuion Period Toal TFP deepening conribuion in one-secor model NOTE: Daa for columns 1 and 2 are business secor esimaes from he BLS mulifacor produciviy daabase (downloaded via Haver on Augus 19, 2008). apial and labor are adjused for changes in composiion. Acual capial deepening is α(kˆ lˆ), and prediced capial deepening is α fp / ( 1 α ). A comparison of columns 2 and 3 shows he model does no perform paricularly well. slighly underesimaes he conribuion of capial deepening over he enire period, bu i does a paricularly poor job of maching he lowfrequency variaion in ha conribuion. n paricular, i somewha overpredics capial deepening for he pre-1973 period bu subsanially underpredics for he period. Tha is, given he slowdown in TFP growh, he model predics a much larger slowdown in he conribuion of capial deepening. 8 One way o visualize he problem wih he one-secor model is o observe ha he model predics a consan capial-o-oupu raio in seady sae in conras o he daa. Figure 1 shows he sharp rise in he business secor capial-o-oupu raio since he mid-1960s. The Two-Secor Model: A Beer Mach A growing lieraure on invesmen-specific echnical change suggess an easy fix for his 8 Noe ha oupu per uni of qualiy-adjused labor is he sum of TFP plus he capial deepening conribuion, which in he business secor averaged = 2.15 percen per year over he full sample. More commonly, labor produciviy is repored as oupu per hour worked. Over he sample, labor qualiy in he BLS mulifacor produciviy daase rose 0.36 percen per year, so oupu per hour rose 2.51 percen per year. failure: apial deepening does no depend on overall TFP bu on TFP in he invesmen secor. A key moivaion for his body of lieraure is he price of business invesmen goods, especially equipmen and sofware, relaive o he price of oher goods (such as consumpion). The relaive price of invesmen and is main componens are shown in Figure 2. Why do we see his seady relaive price decline? The mos naural inerpreaion is ha here is a more rapid pace of echnological change in producing invesmen goods (especially highech equipmen). 9 To realize he implicaions of a wo-secor model, consider a simple wo-secor Solow-ype model, where s is he share of nominal oupu ha is invesed each period. 10 One secor produces invesmen goods,, ha are used o creae capial; he oher secor produces consumpion goods,. The wo secors use he same obb-douglas producion funcion bu wih poenially differen echnology levels: 9 On he growh accouning side, see, for example, Jorgenson (2001) or Oliner and Sichel (2000); see also Greenwood, Hercowiz, and Krusell (1997). 10 This model is a fixed saving rae version of he wo-secor neoclassical growh model in Whelan (2003) and is isomorphic o he one in Greenwood, Hercowiz, and Krusell (1997), who choose a differen normalizaion of he wo echnology shocks in heir model. FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

6 Figure 1 apial-o-oupu Raio in he Unied Saes (equipmen and srucures) Raio Scale ndex, 1948 = SOURE: BLS mulisecor produciviy daabase. Equipmen and srucures (i.e., fixed reproducible angible capial) is calculaed as a Tornquis index of he wo caegories. Sandard ndusrial lassificaion daa (from are spliced o Norh American ndusry lassificaion Sysem daa (from saring a 1988 (daa downloaded Ocober 13, 2008). α 1 α α 1 α K A L = = QK A L n he consumpion equaion, we have implicily defined labor-augmening echnological change as A = Q 1/ 1 α A o decompose consumpion echnology ino he produc of invesmen echnology, A, and a consumpion-specific piece, Q 1/ 1 α. Le invesmen echnology, A, grow a rae g and he consumpion-specific piece, Q, grow a rae q. Perfec compeiion and cos minimizaion imply ha price equals marginal cos. f he secors face he same facor prices (and he same rae of indirec business axes), hen P P M = = Q. M. The secors also choose o produce wih he same capial-o-labor raios, implying ha K /A L = K /A L = K/A L. We can hen wrie he producion funcions as We can now wrie he economy s budge consrain in a simple manner: (4) A L K A L = = QA L K A L nv. Unis Y [ + Q]= A L + L K A L or y y nv. Unis nv. Unis = Y α = k, where nv. Uni s Oupu here is expressed in invesmen unis, and effecive labor is in erms of echnology in he invesmen secor. The economy mechanically invess a share s of nominal inves- α α. α A L and k = K A L., JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

7 Figure 2 Price of Business Fixed nvesmen Relaive o Oher Goods and Services Raio Scale, 2000 = Equipmen and Sofware Business Fixed nvesmen Srucures NOTE: Oher goods and services consiues business GDP less business fixed invesmen. SOURE: Bureau of Economic Analysis and auhors calculaions. men, which implies ha invesmen per effecive uni of labor is i = s. y nv. Unis. 11 apial accumulaion hen akes he same form as in he one-secor model, excep ha i is only growh in invesmen echnology, g, ha maers. n paricular, in seady sae, (5) nv. Unis sy = n + δ + g k. The producion funcion (4) and capialaccumulaion equaion (5) correspond exacly o heir one-secor counerpars. Hence, he dynamics of capial in his model reflec echnology in he invesmen secor alone. n seady sae, capial per uni of labor, K/L, grows a rae g, so he conribuion of capial deepening o labor-produciviy growh from equaion (1) is 11 nv. Unis s y = P P + P + P P AL = A L. αg = α fp 1 α. onsumpion echnology in his model is neural in ha i does no affec invesmen or capial accumulaion; he same resul carries over o he Ramsey version of his model, wih or wihou variable labor supply. (Basu e al., 2008, discuss he idea of consumpion-echnology neuraliy in greaer deail. 12 ) To apply his model o he daa, we need o decompose aggregae TFP growh (calculaed from 12 Noe also ha oupu in invesmen unis is no equal o chain oupu in he naional accouns. hain gross domesic produc (GDP) is n conras, in his model nv. Unis Y = sˆ + 1 s ˆ 1 s q. Hence, nv. Unis Ŷ = Y + 1 s q. Yˆ = sˆ + 1 s ˆ. ( ) FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

8 chained oupu) ino is consumpion and invesmen componens. Given he condiions so far, he following wo equaions hold: Hence, hey allow us o decompose aggregae TFP growh ino invesmen and consumpion TFP growh. 13 Table 2 shows ha he wo-secor growh model does, in fac, fi he daa beer. All derivaions are done assuming an invesmen share of 0.15, abou equal o he nominal value of business fixed invesmen relaive o he value of business oupu. For he and periods, a comparison of columns 5 and 6 indicaes ha he model fis quie well and much beer han he one-secor model. The improved fi reflecs ha alhough overall TFP growh slowed very sharply, invesmen TFP growh (column 3) slowed much less. Hence, he slowdown in capial deepening was much smaller. The seady-sae predicions work less well for he periods afer 1995, when acual capial deepening fell shor of he seady-sae predicion for capial deepening. During hese periods, no only did overall TFP accelerae, bu he relaive price decline in column 2 also acceleraed. Hence, implied invesmen TFP acceleraed markedly (as did oher TFP). Of course, he ransiion dynamics imply ha capial deepening converges only slowly o he new seady sae, and a decade is a relaively shor ime. (n addiion, he pace of invesmen-secor TFP was paricularly rapid in he lae 1990s and has slowed somewha in he 2000s.) So he more imporan poin is ha, quali- fp = s fp + ( 1 s) fp, P P = fp fp. These are wo equaions in wo unknowns fp and fp. 13 The calculaions below use he official price deflaors from he naional accouns. Gordon (1990) argues ha many equipmen deflaors are no sufficienly adjused for qualiy improvemens over ime. Much of he macroeconomic lieraure since hen has used he Gordon deflaors (possibly exrapolaed, as in ummins and Violane, 2002). Of course, as Whelan (2003) poins ou, much of he discussion of biases in he consumer price index involves service prices, which also miss many qualiy improvemens. aively, he model works in he righ direcion even over his relaively shor period. Despie hese uncerainies, a boom-line comparison of he one- and wo-secor models is of ineres. Suppose ha he raes of TFP growh coninue o hold in boh secors (a big if discussed in he nex secion). Suppose also ha he wo-secor model fis well going forward, as i did in he period. Then we would projec ha fuure oupu per hour (like oupu per qualiy-adjused uni of labor, shown in Tables 1 and 2) will grow on average abou 0.75 percenage poins per year faser han he onesecor model would predic (1.38 versus 0.63), as a resul of greaer capial deepening. The difference is clearly subsanial: is a significan fracion of he average 2.15 percen growh rae in oupu per uni of labor (and 2.5 percen growh rae of oupu per hour) over he period. PROJETNG THE FUTURE Forecasers, policymakers, and a number of academics regularly make srucured guesses abou he likely pah of fuure growh. 14 No surprisingly, he usual approach is o assume ha he fuure will look somehing like he pas bu he challenge is o decide which pars of he pas o include and which o downplay. n making such predicions, economiss ofen projec average TFP growh for he economy as a whole. However, viewed hrough he lens of he wo-secor model, one needs o make separae projecions for TFP growh in boh he invesmen and non-invesmen secors. We consider hree growh scenarios: low, medium, and high (Table 3). onsider he medium scenario, which has oupu per hour growing a 2.3 (las column). nvesmen TFP is a bi slower han is average in he pos-2000 period, reflecing ha invesmen TFP has generally slowed since he burs of he lae 1990s. Oher TFP slows o is rae in 14 Oliner and Sichel (2002) use he phrase srucured guesses. n addiion o Oliner and Sichel, recen high-profile examples of projecions have come from Jorgenson, Ho, and Siroh (2008) and Gordon (2006). The BO and he ouncil of Economic Advisers regularly include longer-run projecions of poenial oupu JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

9 Table 2 Two-Secor Growh Model Predicions for he U.S. Business Secor Relaive price of Prediced business fixed invesmen Acual capial deepening o oher capial deepening conribuion Period Toal TFP goods and services nvesmen TFP Oher TFP conribuion in wo-secor model :Q4 2006:Q :Q4 2008:Q NOTE: Oher goods and services consiues business GDP less business fixed invesmen. apial and labor are adjused for changes in composiion. Acual capial deepening is α(kˆ lˆ), and prediced capial deepening is. fp / ( 1 ) α α SOURE: BLS mulifacor produciviy daase, Bureau of Economic Analysis relaive-price daa, and auhors calculaions. The final wo rows reflec quarerly esimaes from Fernald (2008); because of he very shor sample periods, we do no show seady-sae predicions. FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

10 Table 3 A Range of Esimaes for Seady-Sae Labor Produciviy Growh apial deepening Labor Oupu per Growh scenario nvesmen TFP Oher TFP Overall TFP conribuion produciviy hour worked Low Medium High NOTE: alculaions assume an invesmen share of oupu of 0.15 and a capial share in producion, α, of olumn 3 (Overall TFP) is an oupu-share-weighed average of columns 1 and 2. olumn 4 is column 1 muliplied by α/(1 α). olumn 5 is oupu per uni of composiion-adjused labor inpu and is he sum of columns 3 and 4. olumn 6 adds an assumed growh rae of labor qualiy/ composiion of 0.3 percen per year, and herefore equals column 5 plus 0.3 percen. he second half of he 1990s, reflecing an assumpion ha he experience of he early 2000s is unlikely o persis. Produciviy growh averaging abou 2.25 percen is close o a consensus forecas. For example, in he firs quarer of 2008, he median esimae in he Survey of Professional Forecasers (SPF, 2008) was for 2 percen labor-produciviy growh over he nex 10 years (and 2.75 percen gross domesic produc [GDP] growh). n Sepember 2008, he ongressional Budge Office esimaed ha labor produciviy (in he nonfarm business secor) would grow a an average rae of abou 2.2 percen beween 2008 and As Table 3 clearly shows, however, small and plausible changes in assumpions well wihin he range of recen experience can make a large difference for seady-sae growh projecions. As a resul, a wide range of plausible oucomes exiss. n he SPF, he sandard deviaion across he 39 respondens for produciviy growh over he nex 10 years was abou 0.4 percen wih a range of 0.9 o 3.0 percen. ndeed, he curren median esimae of 2.0 percen is down from an esimae of 2.5 percen in 2005, bu remains much higher han he one-year esimae of only 1.3 percen in alculaed from daa in BO (2008). 16 The SPF has been asking abou long-run projecions in he firs quarer of each year since The daa are available a survey-of-professional-forecasers/daa-files/prod10/. The wo-secor model suggess several key quesions in making long-run projecions. Firs, wha will be he pace of echnical progress in producing informaion echnology (T) and, more broadly, equipmen goods? For example, for hardware, Moore s law ha semiconducor capaciy doubles approximaely every wo years provides plausible bounds. For sofware, however, we really have very lile firm ground for speculaion. Second, how elasic is he demand for T? The previous discussion of he wo-secor model assumed ha he invesmen share was consan a Bu an imporan par of he price decline refleced ha T, for which prices have been falling rapidly, is becoming an increasing share of oal business fixed invesmen. A some poin, a consan share is a reasonable assumpion and consisen wih a balanced growh pah. Ye over he nex few decades, very differen pahs are possible. Technology opimiss (such as DeLong, 2002) hink ha he elasiciy of demand for T exceeds uniy, so ha demand will rise even faser han prices fall. They hink ha firms and individuals will find many new uses for compuers, semiconducors, and, indeed, informaion, as hese commodiies ge cheaper and cheaper. By conras, echnology pessimiss (such as Gordon, 2000) hink ha he greaes conribuion of he T revoluion is in he pas raher han he fuure. For example, firms may decide hey will no need much more compuing power in he fuure, so ha as prices coninue o fall, he nominal share JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

11 17 See, for example, Basu e al. (2003) for an inerpreaion of he broad-based TFP acceleraion in erms of inangible organizaional capial associaed wih using compuers. Of course, an inangiblecapial sory suggess ha he measured share of capial is oo low, and ha measured capial is only a subse of all capial so he model and calibraion in he earlier secion are incomplee. of expendiure on T will also fall. For example, new and faser compuers migh offer few advanages for word processing relaive o exising compuers, so he replacemen cycle migh become longer. Third, wha will happen o TFP in he non-tproducing secors? The range of uncerainy here is very large larger, arguably, han for he firs wo quesions. The general-purpose-echnology naure of compuing suggess ha faser compuers and beer abiliy o manage and manipulae informaion migh well lead o TFP improvemens in compuer-using secors. 17 For example, many imporan managemen innovaions, such as he Wal-Mar business model or he widespread diffusion of warehouse auomaion, are made possible by cheap compuing power. Produciviy in research and developmen may also rise more direcly; auo pars manufacurers, for example, can design new producs on a compuer raher han building physical prooype models. Tha is, compuers may lower he cos and raise he reurns o research and developmen n addiion, are hese sors of TFP spillovers from T o non-t secors bes considered as growh effecs or level effecs? For example, he Wal-Marizaion of reailing raises produciviy levels (as more-efficien producers expand and less-efficien producers conrac) bu i does no necessarily boos long-run growh. Fourh, he effecs noed previously migh well depend on labor marke skills. Many endogenous growh models incorporae a key role for human capial, which is surely a key inpu ino he innovaion process wheher refleced in formal research and developmen or in managemen reorganizaions. Beaudry, Doms, and Lewis (2006) find evidence ha he inensiy of personal compuers use across U.S. ciies is closely relaed o educaion levels in hose ciies. We hope we have convinced readers ha i is imporan o ake a wo-secor approach o esimaing he ime pah of long-run oupu. Bu as his (non-exhausive) discussion demonsraes, knowing he correc framework for analysis is only one of many inpus o projecing poenial oupu correcly. Much sill remains unknown abou poenial oupu, even along a seady-sae growh pah. The bigges problem is he lack of knowledge abou he deep sources of TFP growh. SHORT-RUN ONSDERATONS General ssues in Defining and Esimaing Shor-Run Poenial Oupu Tradiionally, macroeconomiss have aken he view expressed in Solow (1997) ha, in he long-run, a growh model such as he ones described previously explains he economy s long-run behavior. Facor supplies and echnology deermine oupu, wih lile role for demand shocks. However, he shor run was viewed very differenly, when as Solow (1997) pu i, flucuaions are predominanly driven by aggregae demand impulses (p. 230). Solow (1997) recognizes ha real business cycle heories ake a differen view, providing a more unified vision of long-run growh and shorrun flucuaions han radiional Keynesian views did. Early real business cycle models, in paricular, emphasized he role of high-frequency echnology shocks. These models are also capable of generaing flucuaions in response o nonechnological demand shocks, such as governmen spending. Since early real business cycle models ypically do no incorporae disorions, hey provide examples in which flucuaions driven by governmen spending or oher impulses could well be opimal (aking he shocks hemselves as given). Neverhe - less, radiional Keynesian analyses ofen presumed ha poenial oupu was a smooh rend, so ha any flucuaions were necessarily subopimal (regardless of wheher policy could do anyhing abou hem). Fully specified New Keynesian models provide a way o hink formally abou he sources of business cycle flucuaions. These models are generally founded on a real business cycle model, albei one wih real disorions, such as firms FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

12 having monopoly power. Because of sicky wages and/or prices, purely nominal shocks, such as moneary policy shocks, can affec real oucomes. The nominal rigidiies also affec how he economy responds o real shocks, wheher o echnology, preferences, or governmen spending. Shor-run poenial oupu is naurally defined as he rae of oupu he economy would have if here were no nominal rigidiies, ha is, by he responses in he real business cycle model underlying he sicky price model. 18 This is our approach o producing a ime series of poenial oupu flucuaions in he shor run. n New Keynesian models, where prices and/or wages migh adjus slowly oward heir long-run equilibrium values, acual oupu migh well deviae from his shor-erm measure of poenial oupu. n many of hese models, he oupu gap he difference beween acual and poenial oupu is he key variable in deermining he evoluion of inflaion. Kuner (1994) and Laubach and Williams (2003) use his inuiion o esimae he oupu gap as an unobserved componen in a Phillips curve relaionship. They find fairly subsanial ime variaion in poenial oupu. n he conex of New Keynesian DSGE models, is here any reason o hink ha poenial oupu is a smooh series? A a minimum, a low variance of aggregae echnology shocks as well as inelasic labor supply is needed. Roemberg (2002), for example, suggess ha because of slow diffusion of echnology across producers, sochasic echnological improvemens migh drive long-run growh wihou being an imporan facor a business cycle frequencies See Woodford (2003). There is a suble issue in defining flexible price poenial oupu when he ime pah of acual oupu may be influenced by nominal rigidiies. n heory, he flexible price oupu series should be a purely forward-looking consruc, which is generaed by urning off all nominal rigidiies in he model, bu saring from curren values of all sae variables, including he capial sock. Of course, he curren value of he capial sock migh be differen from wha i would have been in a flexible price model wih he same hisory of shocks because nominal rigidiies operaed in he pas. Thus, in principle, he poenial-oupu series should be generaed by iniializing a flexible price model every period, raher han aking an alernaive ime-series hisory from he flexible price model hi by he same sequence of real shocks. We do he laer raher han he former because we believe ha nominal rigidiies cause only small deviaions in he capial sock, bu i is possible ha he resuling error in our poenial-oupu series migh acually be imporan. Neverheless, alhough a priori one migh believe ha echnology changes only smoohly over ime, here is scan evidence o suppor his posiion. Basu, Fernald, and Kimball (2006) conrol economerically for nonechnological facors affecing he Solow residual nonconsan reurns o scale, variaions in labor effor and capial s workweek, and various reallocaion effecs and sill find a purified echnology residual ha is highly variable. Alexopoulos (2006) uses publicaions of echnical books as a proxy for unobserved echnical change and finds ha his series is no only highly volaile, bu explains a subsanial fracion of GDP and TFP. Finally, variance decomposiions ofen sugges ha innovaions o echnology explain a subsanial share of he variance of oupu and inpus a business cycle frequencies; see Basu, Fernald, and Kimball (2006) and Fisher (2006). When producing a ime series of shor-run poenial oupu, i is necessary no only o know he correc model of he economy, bu also he series of hisorical shocks ha have affeced he economy. One approach is o specify a model, which is ofen complex, and hen use Bayesian mehods o esimae he model parameers on he daa. As a by-produc, he model esimaes he ime series of all he shocks ha he model allows. 20 Because DSGE models are srucural in he sense of Lucas s (1976) criique, one can perform counerfacual simulaions for example, by urning off nominal rigidiies and using he esimaed model and shocks o creae a ime series of flexible price poenial oupu. We do no use his approach because we are no sure ha Bayesian esimaion of DSGE models always uses reliable schemes o idenify he relevan shocks. The full-informaion approach of hese models is, of course, preferable in an efficiency sense if one is sure ha one has specified 19 A recen paper by Jusiniano and Primiceri (2008) esimaes boh simple and complex New Keynesian models and finds ha mos of he volailiy in he flexible-wage/price economy reflecs exreme volailiy in markup shocks. They sill esimae ha here is considerable quarer-o-quarer volailiy in echnology, so ha even if he only shocks were echnology shocks, heir flexible price measure of oupu would also have considerable volailiy from one quarer o he nex. 20 See Smes and Wouers (2007) JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

13 he correc srucural model of he economy wih all is fricions. We prefer o use limiedinformaion mehods o esimae he key shocks echnology shocks, in our case and hen feed hem ino small, plausibly calibraed models of flucuaions. A wors, our mehod should provide a robus, albei inefficien, mehod of assessing some of he key findings of DSGE models esimaed using Bayesian mehods. We believe ha our mehod of esimaing he key shocks is boh more ransparen in is idenificaion and robus in is mehod because i does no rely on specifying correcly he full model of he economy, bu only small pieces of such a model. As in he case of he Basu, Fernald, and Kimball (2006) procedure underlying our shock series, we specify only producion funcions and coss of varying facor uilizaion and assume ha firms minimize coss all sandard elemens of curren medium-scale DSGE models. Furher - more, we assume ha rue echnology shocks are orhogonal o oher srucural shocks, such as moneary policy shocks, which can herefore be used as insrumens for esimaion. Finally, because we do no have he overhead of specifying and esimaing a complee srucural general equilibrium model, we are able o model he producion side of he economy in greaer deail. Raher han assuming ha an aggregae producion funcion exiss, we esimae indusry-level producion funcions and aggregae echnology shocks from hese more disaggregaed esimaes. Basu and Fernald (1997) argue ha his approach is preferable in principle and solves a number of puzzles in recen producion-funcion esimaion in pracice. We use ime series of purified echnology shocks, similar o hose presened in Basu, Fernald, and Kimball (2006) and Basu e al. (2008). However, hese series are a an annual frequency. Fernald (2008) applies he mehods in hese aricles o quarerly daa and produces higherfrequency esimaes of echnology shocks. Fernald esimaes uilizaion-adjused measures of TFP for he aggregae economy, as well as for he invesmen and consumpion secor. n brief, aggregae TFP is measured using daa from he BLS quarerly labor produciviy daa, combined wih capialservice daa esimaed from deailed quarerly invesmen daa. Labor qualiy and facor shares are inerpolaed from he BLS mulifacorproduciviy daase. The relaive price of invesmen goods is used o decompose aggregae TFP ino invesmen and consumpion componens, using he (ofen-used) assumpion ha relaive prices reflec relaive TFPs. The uilizaion adjusmen follows Basu, Fernald, and Kimball (2006), who use hours per worker as a proxy for uilizaion change (wih an economerically esimaed coefficien) a an indusry level. The inpu-oupu marix was used o aggregae indusry uilizaion change ino invesmen and consumpion uilizaion change, following Basu e al. (2008). 21 To produce our esimaed poenial oupu series, we feed he echnology shocks esimaed by Fernald (2008) ino simple one- and wo-secor models of flucuaions (see he appendix). Tech - nology shocks shif he producion funcion direcly, even if hey are no amplified by changes in labor supply in response o variaions in wages and ineres raes. f labor supply is elasic, hen a foriori he changes in poenial oupu will be more variable for any given series of echnology shocks. Elasic labor supply also allows nonechnology shocks o move shor-run, flexible price oupu disconinuously. Shocks o governmen spending, even if financed by lump-sum axes, cause changes in labor supply via a wealh effec. Shocks o disorionary ax raes on labor income shif labor demand and generally cause labor inpu, and hence oupu, o change. Shocks o he preference for consumpion relaive o leisure can also cause changes in oupu and is componens. The imporance of all of hese shocks for movemens in flexible price poenial oupu depends crucially on he size of he Frisch (wealh-consan) elasiciy of labor supply. Unforunaely, his is one of he parameers in economics whose value is mos conroversial, a leas a an aggregae level. Mos macroeconomiss assume values beween 1 and 4 for his crucial 21 Because of a lack of daa a a quarerly frequency, Fernald (2008) does no correc for deviaions from consan reurns or for heerogeneiy across indusries in reurns o scale issues ha Basu, Fernald, and Kimball (2006) argue are imporan. FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

14 parameer, bu no for paricularly srong reasons. 22 On he oher hand, ard (1994) reviews boh microeconomic and aggregaive evidence and concludes here is lile evidence in favor of a nonzero Frisch elasiciy of labor supply. The canonical models of Hansen (1985) and Rogerson (1988) aemp o bridge he macro-micro divide. However, Mulligan (2001) argues ha he srong implicaion of hese models, an infinie aggregae labor supply elasiciy, depends crucially on he assumpion ha workers are homogeneous and can easily disappear when one allows for heerogeneiy in worker preferences. We do no model real, nonechnological shocks o he economy in creaing our series on poenial oupu. Our decision is parly due o uncerainy over he correc value of he aggregae Frisch labor supply elasiciy, which as discussed previously is crucial for calibraing he imporance of such shocks. We also make his decision because in our judgmen here is even less consensus in he lieraure over idenifying rue innovaions o fiscal policy or o preferences han here is on idenifying echnology shocks. Our decision o ignore nonechnological real shocks clearly has he poenial o bias our series on poenial oupu, and depending on he values of key parameers, his bias could be significan. One-Secor versus Two-Secor Models n he canonical New Keynesian Phillips curve, derived wih alvo price seing and flexible wages, inflaion oday depends on expeced inflaion omorrow, as well as on he gap beween acual oupu and he level of oupu ha would occur wih flexible prices. To assess how poenial and acual oupu respond in he shor run in a one- versus wosecor model, we used a very simple wo-secor New Keynesian model (see he appendix). As in he long-run model, we assume ha invesmen 22 n many cases, i is simply because macro models do no work ha is, display sufficien amplificaion of shocks for smaller values of he Frisch labor supply elasiciy. n oher cases, values like 4 are raionalized by assuming, wihou independen evidence, ha he represenaive consumer s uiliy from leisure akes he logarihmic form. However, his resricion is no imposed by he King-Plosser-Rebelo (1988) uiliy funcion, which guaranees balanced growh for any value of he Frisch elasiciy. and consumpion producion uses a obb-douglas echnology wih he same facor shares bu wih a (poenially) differen muliplicaive echnology parameer. To keep hings simple, facors are compleely mobile, so ha a one-secor model is he special case when he same echnology shock his boh secors. We simulaed he one- and wo-secor models using he uilizaion-adjused echnology shocks esimaed in Fernald (2008). Table 4 shows sandard deviaions of seleced variables in flexible and sicky price versions of he one- and wosecor models, along wih acual daa for he U.S. economy. The model does a reasonable job of approximaing he variaion in acual daa, considering how simple i is and ha only echnology shocks are included. nvesmen in he daa is slighly less volaile han eiher in he sicky price model or he wo-secor flexible price model. This is no surprising, given ha he model does no have any adjusmen coss or oher mechanisms o smooh ou invesmen. onsumpion, labor, and oupu in he daa are more volaile han in he models. 23 Addiional shocks (e.g., o governmen spending, moneary policy, or preferences) would presumably add volailiy o model simulaions. An imporan observaion from Table 4 is ha poenial oupu he flexible price simulaions, in eiher he one- or wo-secor varians is highly variable, roughly as variable as sicky price oupu. The shor-run variabiliy of poenial oupu in New Keynesian models has been emphasized by Neiss and Nelson (2005) and Edge, Kiley, and Lafore (2007). These models, wih he shocks we have added, show a very high correlaion of flexible and sicky price oupu. n he wo-secor case, he correlaion is Neverheless, he implied oupu gap (shown in he penulimae line of Table 4 as he difference beween oupu in he flexible and sicky price cases) is more volaile han would be implied if poenial oupu were esimaed wih he one-secor model (he final line). 23 The relaive volailiy of consumpion is no ha surprising, because he models do no have consumer durables and we have no ye analyzed consumpion of nondurables and services in he acual daa JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

15 Table 4 Sandard Deviaions, Model Simulaions, and Daa Variable nvesmen onsumpion Labor Oupu One-secor, flexible price Two-secor, flexible price One-secor, sicky price Two-secor, sicky price Daa Oupu gap (wo-secor sicky price less wo-secor flexible price) One-secor esimaed gap (wo-secor sicky price less one-secor flexible price) NOTE: Model simulaions use uilizaion-adjused TFP shocks from Fernald (2008). Two-secor simulaions use esimaed quarerly consumpion and invesmen echnology; one-secor simulaions use he same aggregae shock (a share-weighed average of he wo secoral shocks) in boh secors. All variables are filered wih he hrisiano-fizgerald bandpass filer o exrac variaion beween 6 and 32 quarers. Figure 3 shows ha he assumpion ha poenial oupu has no business cycle variaion which is anamoun o using (Hodrick-Presco filered) sicky price oupu iself as a proxy for he oupu gap would overesimae he variaion in he oupu gap. This would no maer oo much if he oupu gap were perfecly correlaed wih sicky price oupu iself hen, a leas, he sign, if no he magniude, would be correc. However, as he figure shows, he rue wo-secor oupu gap in he model (wo-secor sicky price oupu less wo-secor flexible price oupu) is imperfecly correlaed wih sicky price oupu indeed, he correlaion is only So in his model, policymakers could easily be misled by focusing solely on oupu flucuaions raher han he oupu gap. mplicaions for Sabilizaion Policy f poenial oupu flucuaes subsanially over ime, hen his has poenial implicaions for he desirabiliy of sabilizaion policy. n paricular, policymakers should be focused only on sabilizing undesirable flucuaions. Of course, he welfare benefis of such policies remain conroversial. Lucas (1987, 2003) famously argued ha, given he flucuaions we observe, he welfare gains from addiional sabilizaion of he economy are likely o be small. n paricular, given sandard preferences and he observed variance of consumpion (around a linear rend), a represenaive consumer would be willing o reduce his or her average consumpion by only abou ½ of 1 /10h of 1 percen in exchange for eliminaing all remaining variabiliy in consumpion. Noe ha his calculaion does no necessarily imply ha sabilizaion policy does no maer, because he calculaion akes as given he sabilizaion policies implemened in he pas. Sabilizaion policies migh well have been valuable for example, in eliminaing recurrences of he Grea Depression or by minimizing he frequency of severe recessions bu addiional sabilizaion migh no offer large benefis. This calculaion amouns o some $5 billion per year in he Unied Saes, or abou $16 per person. ompared wih he premiums we pay for very parial insurance (e.g., for collision coverage on our cars), his is almos implausibly low. Any poliician would surely voe o pay $5 billion for a policy ha would eliminae recessions. Hence, a sizable lieraure considers ways o obain larger coss of business cycle flucuaions, wih mixed resuls. Argumens in favor of sabilizaion include Galí, Gerler, and López-Salido (2007), who argue ha he welfare effecs of booms FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

16 Figure 3 Oupu Gap and Sicky Price Oupu Percen Two-Secor Sicky Price Model Two-Secor Oupu :Q3 1952:Q3 1957:Q3 1962:Q3 1967:Q3 1972:Q3 1977:Q3 1982:Q3 1987:Q3 1992:Q3 1997:Q3 2002:Q3 2007:Q3 NOTE: Bandpass-filered (6 o 32 quarers) oupu from wo-secor sicky price model and he corresponding oupu gap (defined as sicky price oupu less flexible price oupu). and recessions may be asymmeric. n paricular, because of wage and price markups, seady-sae employmen and oupu are inefficienly low in heir model, so ha he coss of flucuaions depend on how far he economy is from full employmen. Recessions are paricularly cosly welfare falls by more during a business cycle downurn han i rises during a symmeric expansion. Barlevy (2004) argues in an endogenousgrowh framework ha sabilizaion migh increase he economy s long-run growh rae; his allowed him o obain very large welfare effecs from business cycle volailiy. This discussion of welfare effecs highlighs ha much work remains o undersand he desirabiliy of observed flucuaions, he abiliy of policy o smooh he undesirable flucuaions in he oupu gap, and he welfare benefis of such policies. WHAT S URRENT POTENTAL OUTPUT GROWTH? onsider he curren siuaion, as of lae 2008: s poenial oupu growh relaively high, relaively low, or close o is seady-sae value? 24 The answer is imporan for policymakers, where saemens by he Federal Open Marke ommiee (FOM) paricipans have emphasized he impor- 24 We could, equivalenly, discuss he magniude or even sign of he oupu gap, which is naurally defined in levels. The level is he inegral of he growh raes, of course, and growh raes make i a lile easier o focus, a leas implicily, on how he oupu gap is likely o change over ime JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

17 ance of economic weakness in reducing inflaionary pressures. 25 Moreover, a discussion of he issue highlighs some of wha we know, and do no know, abou poenial oupu. Some of he consideraions are closely linked o earlier poins we have made, bu hese consideraions also allow a discussion of oher issues ha are no included in he simple models discussed here. Several argumens sugges ha poenial oupu growh migh currenly be running a a relaively rapid pace. Firs, and perhaps mos imporanly, TFP growh has been relaively rapid from he end of 2006 hrough he hird quarer of 2008 (see Table 2). During his period oupu growh iself was relaively weak, and hours per worker were generally falling; hence, following he logic in Basu, Fernald, and Kimball (2006), facor uilizaion appears o have been falling as well. As a resul, in boh he consumpion and he invesmen secors, uilizaion-adjused TFP (from Fernald, 2008) has grown a a more rapid pace han is pos-1995 average. This fas pace has occurred despie he reallocaions of resources away from housing and finance and he high level of financial sress. Second, subsanial declines in wealh are likely o increase desired labor supply. Mos obviously, housing wealh has fallen and sock marke values have plunged; bu ax and expendiure policies aimed a sabilizing he economy could also sugges a higher presen value of axes. Declining wealh has a direc, posiive effec on labor supply. n addiion, as he logic of ampbell and Hercowiz (2006) would imply, rising financial sress could lead o increases in labor supply as workers need o acquire larger down paymens for purchases of consumer durables. And if here is habi persisence in consumpion, workers migh also seek, a leas emporarily, o work more hours o smooh he effecs of shocks o gasoline and food prices. Neverheless, here are also reasons o be concerned ha poenial oupu growh is currenly lower han is pace over he pas decade or so. Firs, Phelps (2008) raises he possibiliy ha because of a secoral shif away from housingrelaed aciviies and finance, poenial oupu growh is emporarily low and he naural rae of unemploymen is emporarily high. Alhough qualiaively suggesive, i is unclear ha he secoral shifs argumen is quaniaively imporan. For example, Vallea and leary (2008) look a he (weighed) dispersion of employmen growh across indusries, a measure used by Lilien (1982). They find ha as of he hird quarer of 2008, he degree of secoral reallocaion remains low relaive o pas economic downurns. Vallea and leary (2008) also consider job vacancy daa, which Abraham and Kaz (1986) sugges could help disinguish beween secoral shifs and pure cyclical increases in unemploymen and employmen dispersion. The basic logic is ha in a secoral shifs sory, expanding firms should have high vacancies ha parially or compleely offse he low vacancies in conracing firms. Vallea and leary find ha he vacancy rae has been seadily falling since lae Third, Bloom (2008) argues ha uncerainy shocks are likely o lead o a sharp decline in oupu. As he pus i, here has been a huge surge in uncerainy ha is generaing a rapid slow-down in aciviy, a collapse of banking prevening many of he few remaining firms and consumers ha wan o inves from doing so, and a shif in he poliical landscape locking in he damage hrough proecionism and ani-compeiive policies (p. 4). His argumen is based on he model simulaions in Bloom (2007), in which an increase in macro uncerainy causes firms o emporarily pause invesmen and hiring. n his model, produciviy growh also falls emporarily because of reduced reallocaion from lower- o higherproduciviy esablishmens. Fourh, he credi freeze could direcly reduce produciviy-improving reallocaions, along he lines suggesed by Bloom (2007), as well as Eisfeld and Rampini (2006). Eisfeld and Rampini argue ha, empirically, capial reallocaion is procycli- 25 For example, in he minues from he Sepember 2008 FOM meeing, paricipans forecas ha over ime increased economic slack would end o damp inflaion (Board of Governors, 2008). 26 Vallea and leary do find some evidence ha he U.S. Beveridge curve migh have shifed ou in recen quarers relaive o is posiion from 2000 o FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

18 cal, whereas he benefis (reflecing cross-secional dispersion of marginal producs) are counercyclical. These observaions sugges ha he informaional and conracual fricions, including financing consrains, are higher in recessions. The siuaion as of lae 2008 is one in which financing consrains are paricularly severe, which is likely o reduce efficien reallocaions of boh capial and labor. Fifh, here could be oher effecs from he seize-up of financial markes in Financial inermediaion is an imporan inermediae inpu ino producion in all secors. f i is complemenary wih oher inpus (as in Jones, 2008), for example, you need access o he commercial paper marke o finance working capial needs hen i could lead o subsanial disrupions of real operaions. Finally, he subsanial volailiy in commodiy prices, especially oil, in recen years could affec poenial oupu. Tha said, alhough oil is a crucial inermediae inpu ino producion, changes in oil prices do no have a clear-cu effec on TFP, measured as domesic value added relaive o primary inpus of capial and labor. They migh, neverheless, influence equilibrium oupu by affecing equilibrium labor supply. Blanchard and Galí (2007) and Bodensein, Erceg, and Guerrieri (2008), however, are wo recen analyses in which, because of (sandard) separable preferences, here is no effec on flexible price GDP or employmen from changes in oil prices. So here is no a priori reason o expec flucuaions in oil prices o have a subsanial effec on he level or growh rae of poenial oupu. A difficuly for all hese argumens ha poenial oupu growh migh be emporarily low is he observaion already made, ha produciviy growh (especially afer adjusing for uilizaion) has, in fac, been relaively rapid over he pas seven quarers. is possible he produciviy daa have been 27 Noe also ha he daa are all subjec o revision. For example, he annual revision in 2009 will revise daa from 2006 forward. n addiion, labor-produciviy daa for he nonfinancial corporae secor, which is based on income-side raher han expendiure-side daa, show less of a slowdown in 2005 and 2006 and less of a pickup since hen. Tha said, even he nonfinancial corporae produciviy numbers have remained relaively srong in he pas few years. mismeasured in recen quarers. 27 Basu, Fernald, and Shapiro (2001) highligh variaions in disrupion coss associaed wih angible invesmen. omparing 2004:Q4 2006:Q4 (when produciviy growh was weak) wih 2006:Q4 2008:Q3 (when produciviy was srong), growh in business fixed invesmen was very similar, suggesing ha imevarying disrupion coss probably explain lile of he recen variaion in produciviy growh raes. Basu e al. (2004) and Oliner, Sichel, and Siroh (2007) discuss he role of mismeasuremen associaed wih inangible invesmens, such as organizaional changes associaed wih T. Wih greaer concerns abou credi and cash flow, firms migh have deferred organizaional invesmens and reallocaions; in he shor run, such deferral would imply faser measured produciviy growh, even if rue produciviy growh (in erms of oal oupu, he sum of measured oupu plus unobserved inangible invesmen) were consan. Basu e al. (2004) argue for a link beween observed invesmens in compuer equipmen and unobserved inangible invesmens in organizaional change. Growh in compuer and sofware invesmen does no show a noable difference beween he 2004:Q4 2006:Q4 and 2006:Q4 2008:Q3 periods. f anyhing, he invesmen rae was higher in he laer period so ha his proxy again does no imply mismeasuremen. Given wealh effecs on labor supply and srong recen produciviy performance along wih he failure of ypical proxies for mismeasuremen o explain he produciviy performance here are reasons for opimism abou he shor-run pace of poenial oupu growh. Neverheless, he major effecs of he adverse shocks on poenial oupu seem likely o be ahead of us. For example, he widespread seize-up of financial markes has been especially pronounced only in he second half of We expec ha as he effecs of he collapse in financial inermediaion, he surge in uncerainy, and he resuling declines in facor reallocaion play ou over he nex several years, shor-run poenial oupu growh will be consrained relaive o where i oherwise would have been JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

19 ONLUSON This aricle has highlighed a few hings we hink we know abou poenial oupu namely, he imporance in boh he shor run and he long run of rapid echnological change in producing equipmen invesmen goods and he likely ime variaion in he shor-run growh rae of poenial. Our discussion of hese poins has, of course, poined oward some of he many hings we do no know. Taking a sep back, we have advocaed hinking abou policy in he conex of explici models ha sugges ways o hink abou he world economy, including poenial oupu. Bu here is an imporan inerplay beween heory and measuremen, as he discussion suggess. Every day, policymakers grapple wih challenges ha are no presen in he sandard models. No only do hey no know he rue model of he economy, hey also do no know he curren sae variables or he shocks wih any precision; and he environmen is poenially nonsaionary, wih he coninuing quesion of wheher srucural change (e.g., parameer drif) has occurred. Theory (and pracical experience) ells us ha our measuremens are imperfec, paricularly in real ime. No surprisingly, cenral bankers look a many of he real-ime indicaors and filer hem analyically relying on heory and experience. Esimaing poenial oupu growh is one modes and relaively ransparen example of his inerplay beween heory and measuremen. REFERENES Abraham, Kaharine G. and Kaz, Lawrence K. yclical Unemploymen: Secoral Shifs or Aggregae Disurbances? Journal of Poliical Economy, June 1986, 94(3), pp Alexopoulos, Michelle. Read All Abou! Wha Happens Following a Technology Shock. Working Paper, Universiy of Torono, April Barlevy, Gadi. The os of Business ycles Under Endogenous Growh. American Economic Review, Sepember 2004, 94(4), pp Basu, Susano and Fernald, John G. Reurns o Scale in U.S. Producion: Esimaes and mplicaions. Journal of Poliical Economy, April 1997, 105(2), pp Basu, Susano and Fernald, John G. Aggregae Produciviy and Aggregae Technology. European Economic Review, June 2002, 46(6), pp Basu, Susano; Fernald, John G. and Kimball, Miles S. Are Technology mprovemens onracionary? American Economic Review, December 2006, 96(5), Basu, Susano; Fernald, John G.; Oulon, Nicholas and Srinivasan, Sylaja. The ase of he Missing Produciviy Growh: Or, Does nformaion Technology Explain Why Produciviy Acceleraed in he Unied Saes bu No he Unied Kingdom? in M. Gerler and K. Rogoff, eds., NBER Macroeconomics Annual ambridge, MA: MT Press, 2004, pp Basu, Susano; Fernald, John G. and Shapiro, Mahew D. Produciviy Growh in he 1990s: Technology, Uilizaion, or Adjusmen? arnegie- Rocheser onference Series on Public Policy, December 2001, 55(1), pp Basu, Susano; Fisher, Jonas; Fernald, John G. and Miles, Kimball S. Secor-Specific Technical hange. Unpublished manuscrip, Universiy of Michigan, Basu, Susano and Kimball, Miles. Long Run Labor Supply and he Elasiciy of neremporal Subsiuion for onsumpion. Unpublished manuscrip, Universiy of Michigan, Ocober 2002; cee_oc02-3.pdf. Beaudry, Paul; Doms, Mark and Lewis, Ehan. Endogenous Skill Bias in Technology Adopion: iy-level Evidence from he T Revoluion. Working Paper No , Federal Reserve Bank of San Francisco, Augus 2006; publicaions/economics/papers/2006/wp06-24bk.pdf. Blanchard, Olivier, J. and Galí, Jordi. The Macroeconomic Effecs of Oil Price Shocks: Why FEDERAL RESERVE BANK OF ST. LOUS REVEW JULY /AUGUST

20 Are he 2000s So Differen from he 1970s? Working Paper No , MT Deparmen of Economics, Augus 18, Bloom, Nicholas. The mpac of Uncerainy Shocks. NBER Working Paper No , Naional Bureau of Economic Research, Sepember 2007; Bloom, Nicholas. The redi runch May ause Anoher Grea Depression. Sanford Universiy Deparmen of Economics, Ocober 8, 2008; Board of Governors of he Federal Reserve Sysem. Minues of he Federal Open Marke ommiee. Sepember 16, 2008; monearypolicy/fomcminues hm. Bodensein, Marin; Erceg, hrisopher E. and Guerrieri, Luca. Opimal Moneary Policy wih Disinc ore and Headline nflaion Raes. nernaional Finance Discussion Papers 941, Board of Governors of he Federal Reserve Sysem, Augus 2008; 2008/941/ifdp941.pdf. alvo, Guillermo. Saggered Prices in a Uiliy- Maximizing Framework, Journal of Moneary Economics, Sepember 1983, 12(3), pp ampbell, Jeffrey and Hercowiz, Zvi. The Role of ollaeralized Household Deb in Macroeconomic Sabilizaion. Working Paper No , Federal Reserve Bank of hicago, revised December 2006; publicaion_display.cfm?publicaion=6&year= 2000%20AND% ard, David. neremporal Labor Supply: An Assessmen, in.a. Sims, ed., Advances in Economerics. Volume 2, Sixh World ongress. New York: ambridge Universiy Press, 1994, pp ongressional Budge Office. BO s Mehod for Esimaing Poenial Oupu: An Updae. Augus 2001; PoenialOupu.pdf. ongressional Budge Office. A Summary of Alernaive Mehods for Esimaing Poenial GDP. March 2004; GDP.pdf. ongressional Budge Office. Key Assumpions in BO s Projecion of Poenial Oupu (by calendar year) in The Budge and Economic Oulook: An Updae. Sepember 2008, Table 2-2; fpdocs/97xx/doc9706/background_table2-2.xls. ummins, Jason G. and Violane, Giovanni L. nvesmen-specific Technical hange in he US ( ): Measuremen and Macroeconomic onsequences. Review of Economic Dynamics, April 2002, 5(2), pp DeLong, J. Bradford. Produciviy Growh in he 2000s, in M. Gerler and K. Rogoff, eds., NBER Macroeconomics Annual ambridge, MA: MT Press, Edge, Rochelle M.; Kiley, Michael T. and Lafore, Jean-Philippe. Naural Rae Measures in an Esimaed DSGE Model of he U.S. Economy. Finance and Economics Discussion Series , Board of Governors of he Federal Reserve Sysem, March 26, 2007; feds/2007/200708/200708pap.pdf. Eisfeld, Andrea and Rampini, Adriano. apial Reallocaion and Liquidiy. Journal of Moneary Economics, April 2006, 53(3), pp Elsby, Michael and Shapiro, Mahew. Sepping Off he Wage Escalaor: A Theory of he Equilibrium Employmen Rae. Unpublished manuscrip, April 2008; Fernald, John G. A Quarerly Uilizaion-Adjused Measure of Toal Facor Produciviy. Unpublished manuscrip, Fisher, Jonas. The Dynamic Effecs of Neural and nvesmen-specific Technology Shocks. Journal of Poliical Economy, June 2006, 114(3), pp Galí, Jordi; Gerler, Mark and Lopez-Salido, David J. Markups, Gaps, and he Welfare oss of Business JULY/AUGUST 2009 FEDERAL RESERVE BANK OF ST. LOUS REVEW

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