The High Yield Spread as a Predictor of Real Economic Activity: Evidence of a Financial Accelerator for the United States

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1 The High Yield Spread as a Predicor of Real Economic Aciviy: Evidence of a Financial Acceleraor for he Unied Saes Ashoa Mody Research Deparmen Inernaional Moneary Fund Mar P. Taylor Universiy of Warwic and Cenre for Economic Policy Research Absrac Sudies find he nominal erm spread he difference beween long and shor raes on governmen paper o predic real economic aciviy in he Unied Saes. We find, however, ha his relaionship appears o be unique o he 1970s and 1980s, in ha i appears o brea down for he US during he 1990s and was only very wea during he 1960s. We sugges ha he predicive abiliy in he 1970s and 1980s may have been due o he presence of high and volaile inflaion during ha period. We find, furher, ha he spread beween below invesmen grade corporae deb and he governmen bond yield i.e. he high-yield spread does predic real aciviy well during he 1990s. In addiion, we find evidence of some nonlineariy in ha abnormally high levels of he high yield spread have significan addiional shor-erm predicive power. Furher, when he indusrial oupu series is purged of, alernaely, demand disurbances, and supply disurbances, he predicive abiliy of he high yield spread remains srong a all horizons. We inerpre he predicive abiliy of he high yield spread as evidence in suppor of a financial acceleraor mechanism for he Unied Saes. Keywords: High yield spread; Real aciviy; Permanen emporary decomposiion; Financial acceleraor. JEL classificaion: E33; E44 The research repored in his paper was underaen while Mar Taylor was a Visiing Scholar in he Research Deparmen of he Inernaional Moneary Fund. The views expressed here are hose of he auhors and should no be aribued o he Inernaional Moneary Fund or o any of is member counries.

2 1. Inroducion The slope of nominal yield curve, or he erm spread, was shown by sudies published in he lae 1980s and early 1990s o have significan predicive conen for fuure real economic aciviy, boh in he Unied Saes and in Europe. 1 Following he early wor by Soc and Wason (1989) and Esrella and Hardouvelis (1991), 2 however, confidence in he predicive power of he erm spread waned a lile when i failed o predic he US recession (see, e.g., Dosey, 1998). Neverheless, furher wor by, iner alios, Esrella and Mishin (1997), Plosser and Rouwenhors (1994), and Dombrosy (1996) seemed o esablish ha is power as a leading indicaor of real economic aciviy had no evaporaed. This somewha mixed evidence on he forecasing performance of he yield spread remains in he lieraure. Dosey (1998, p. 50), for example, in a paper ha is generally supporive of he view ha he erm spread does indeed conain predicive informaion, noes ha ha conclusion mus be empered, however, by he observaion ha over more recen periods he spread has no been as informaive as i has been in he pas. Gerler and Lown (1999), drawing on he heory of he financial acceleraor (see, for example, Bernane and Gerler, 1989; Bernane, Gerler and Gilchris, 1998, and he references cied herein), argue ha an alernaive financial variable should also have predicive power for real economic aciviy his is he premium required on non-invesmen grade bonds (also referred o as high yield or jun bonds) over governmen deb or AAA-raed corporae bonds. Gerler and Lown (1999) provide some empirical suppor for his view based on correlaion and impulse-response analysis, using daa on he high-yield spread and a measure of he US oupu gap. We see o conribue o his lieraure in a number of ways. Firs, we examine he robusness of he erm spread as a predicor of economic aciviy by esimaing long-horizon regressions covering broadly hree periods he 1960s, he 1970s and 1980s, and he 1990s. In brief, we find ha he erm spread does no predic real economic aciviy well for he mos recen period, alhough i does perform well in his capaciy for he 1970s and 1980s. Ineresingly, however, we find ha he predicive conen of he erm spread appears o be unique o he 1970s and 1980s, in ha we also find ha i does no appear o be presen in he daa for he 1960s. We hen move on o examine he predicive conen of he high yield spread, in wha we believe is he firs analysis of his variable as a predicor of real economic aciviy using longhorizon regression, which has been he sandard ool by which he predicive conen of he 1 See, for example, Soc and Wason (1989), Harvey (1989), Chen (1991), Esrella and Hardouvelis (1991), Hu (1993), Caporale (1994), Peel and Taylor (1998), and Bernard and Gerlach (1998). 2 See also Lauren (1988).

3 2 erm spread has generally been judged. We find ha he predicive conen of he high yield spread appears o be very significan. In addiion, we find evidence of some nonlineariy, in ha abnormally high levels of he high yield spread have significan addiional shor-erm predicive power. Finally, we brea down our measure of real economic aciviy real indusrial producion ino emporary and permanen componens, using a varian of an economeric echnique developed by Blanchard and Quah (1989). Afer esimaing he long-horizon regressions wih oupu purged of, respecively, is permanen (or supply ) and emporary (or demand ) componens, we find ha he high yield spread reains is predicive abiliy. The resuls sugges, however, ha he permanen or supply effecs conribue more o he predicive abiliy of he high yield spread. The remainder of he paper is se ou as follows. In Secion 2, we briefly discuss he heoreical bacground o boh he slope of he nominal yield curve and he high-yield spread as predicors of fuure real economic aciviy. In Secion 3, we describe he daa, while in Secion 4 we repor he resuls of long-horizon regressions of cumulaive real oupu growh movemens ono he lagged nominal erm spread and he high-yield spread. In Secion 5, we very briefly ouline a mehod for isolaing he permanen and emporary componens of real oupu movemens which is hen applied o he daa. In Secion 6, we repea he long-horizon regressions for he high-yield spread, using real oupu daa which has been alernaely sripped of movemens due o permanen, or supply shocs, and of movemens due o emporary, or demand shocs. A concluding secion discusses he prospecs for hese financial predicors of real aciviy. 2. Predicing real economic aciviy: heoreical bacground 2.1 The erm spread as a predicor of real aciviy Though several sudies have found he erm spread o conain informaion wih respec o fuure economic aciviy, he heoreical basis for his relaionship has remained unclear, as noed, for example, by Plosser and Rouwenhors (1994) and Dosey (1998). Thus, Esrella and Hardouvelis (1991), while documening he predicive abiliy of he erm spread, also cauioned ha he relaionship could easily wane. The slope of he yield curve o be influenced by facors such as expeced real ineres raes, curren and expeced inflaion, and ris or erm premia. A saring poin for he lin beween he erm spread and real economic aciviy could be he heoreical relaionship beween real ineres raes and macroeconomic aciviy, for example hrough consumpion and invesmen (see Taylor, 1999, for a survey). One can use, for example, a simple opimizing model of consumpion o derive a heoreical model of he lin beween fuure consumpion and he real erm srucure as follows. Consider a represenaive agen whose real consumpion in period is C, whose insananeous uiliy funcion is U (.), and whose subjecive rae of ime

4 3 preference is ρ. If he j-period real ineres rae is i (j), hen, maing he usual assumpions such as addiive separabiliy of preferences and, for simpliciy, perfec foresigh, we can derive among he firs-order condiions for he agen s opimal consumpion plan Euler equaions of he form: (1) 1 U ( C ) (1+ i )(1+ ρ ) U '( C ) (1) ' = + 1 (2) 2 U ( C ) (1+ i )(1+ ρ ) U '( C ) (2) ' = + 2 where U '(.) denoes he fis derivaive of he uiliy funcion and hence marginal uiliy. The inuiion is sandard: if he agen is opimizing, hen i is impossible o improve he plan by, say reducing consumpion slighly oday [a a cos of U '( C ) ], invesing for j periods a he real ineres rae i (j), and increasing consumpion in period j [yielding a gain, in period- (j) j presen value erms, of [ (1+ i )(1+ ρ ) U '( C + j ) ] he cos jus offses he gain. From (1) and (2) we can, however, derive: (1+ i (1+ i (2) (1) ) ) U '( C + 1) = (1+ ρ ), (3) U '( C ) + 2 or alernaively, o a close approximaion: ( i (2) i (1) U '( C ) = (1+ ρ) U '( C ) 1. (4) ) Equaion (4) hus describes a very simple possibiliy of how movemens in he real yield curve may affec fuure economic aciviy. An increase in he slope of he real erm srucure will induce opimizing agens o ae advanage of he beer yield available a longer mauriies by reducing consumpion in he shor erm and increasing consumpion in he long (2) (1) erm. Wih diminishing marginal uiliy, a rise in ( i i ) requires a reducion inc + 1 and an increase inc + 2. In so far as movemens in he nominal erm spread move wih he real erm spread, herefore, and in so far as increased consumpion demand raises economic aciviy, his framewor predics ha rises in he nominal erm spread will indeed be associaed wih increases in fuure economic aciviy. Noe, however, ha his analysis is based on a consideraion of Euler equaions raher han proper reduced forms: hese are condiions ha mus hold a he margin, raher han being reduced form equaions. Moreover, he issue becomes complicaed when he move is made from considering he behavior of he represenaive agen o considering he behavior of he economy in aggregae. In fac, he implicaion of a large empirical lieraure on consumpion is ha he saisical lin beween real ineres raes and aggregae consumpion is exremely enuous (Deaon, 1992; Taylor, 1999), suggesing ha i is unliely ha he nominal erm

5 4 spread, by acing as a proxy for he real erm spread, is predicing fuure shifs in consumpion demand. A huge amoun of empirical wor on aggregae invesmen also concludes ha he saisical lin beween real ineres raes and invesmen demand is wea (Chirino, 1993; Taylor, 1999), moreover, suggesing ha searching for a heoreical lin beween he erm spread and invesmen is also liely o be fruiless. Alernaively, we migh explore he avenue ha he erm spread reflecs expeced fuure inflaion. However, he long-erm ineres raes ypically used in his connecion are quie long-horizon of he order of en years or more. Given ha he erm spread appears o have predicive conen for a mos a few years, i herefore seems unliely ha his forwardlooing elemen plays a large role in his respec. Wih respec o erm or ris premia, empirical wor on erm or ris premia has ypically found no evidence of srong and saisically sable models (see for example Taylor, 1992). There seem o be wo oher remaining avenues hrough which he erm spread may predic fuure real aciviy. Firs, in so far as a general moneary easing will be refleced in a fall in shor-erm ineres raes and hence a seepening of he yield curve, he erm spread will be posiively correlaed wih fuure movemens in real aciviy brough abou by he expansionary policy. The second possibiliy is ha he erm spread also reflecs movemens in he curren rae of inflaion. If a rise in curren inflaion leads o a rise in shor-erm ineres raes and, hence, a flaening of he yield curve and if inflaion and real aciviy are negaively correlaed, a fall in he erm spread will predic slower fuure real aciviy. The proposiion ha high inflaion is liely o be associaed wih a weaening of economic aciviy is suppored by recourse o sandard economic heory. In a simple aggregae supply-aggregae demand framewor, for example, reducions in real oupu brough abou by shifs in aggregae supply will be accompanied by a rise in prices and inflaion as he economy moves along he aggregae demand schedule. If we inroduce nominal wage ineria and a long-run verical supply curve ino such a framewor, hen aggregae demand shifs may also lead o negaive correlaion beween inflaion and growh since, while he shor-run effec of a posiive demand shoc will be o raise oupu, prices will iniially be largely unaffeced because of nominal ineria. If he supply curve is verical in he long-run, moreover, hen afer a few periods he iniial rise in oupu will begin o decline, jus as he rise in prices is beginning o feed hrough, so ha inflaion and he change in oupu will end o correlae negaively. In he appendix, we se ou a formal macroeconomic model wih long-run moneary neuraliy and nominal wage ineria induced hrough wage conracing, in which we show ha he overall covariance beween inflaion and oupu growh may be negaive. 3 3 Fama (1981) argues ha he fac ha real soc price reurns and inflaion end o be negaively correlaed may be because inflaion and (curren and expeced) real oupu may be negaively correlaed.

6 5 If, furher, we allow for he negaive effecs on economic aciviy from inflaionary uncerainy and oher disorions induced by an environmen of high and volaile inflaion, hen a negaive correlaion beween inflaion and growh seems even more liely a leas in a period of high inflaion. In Figure 1 we have graphed he welve-monh consumer price index inflaion rae and he welve-monh percenage growh in real indusrial producion for he US over he period 1958M1-2001M12 (see Secion 3 for daa sources). Two aspecs of he graph are paricularly sriing. Firs, he rae of inflaion is higher and more volaile during he 1970s and 1980s han i was during eiher he 1960s or he 1990s. Second, here appears o be sronger evidence of negaive correlaion beween inflaion and he rae of growh of indusrial producion during he 1970s and 1980s. In addiion, as argued above, while demand shocs may induce, in cerain circumsances, negaive correlaion beween oupu growh and inflaion, supply shocs will unambiguously do so, and his effec appears o be paricularly mared following he firs and second oil shocs of 1974 and In conras, he behavior of inflaion during he 1990s appears o have much more in common wih ha of he 1960s, in ha i is generally much lower, less volaile, and apparenly less negaively correlaed wih oupu growh. In ligh of our discussion of he possible underlying causes of he lin beween he erm spread and fuure real aciviy, herefore, his suggess esing for he srengh of he lin during he 1960s as well as during he 1990s, o see if he lin is in fac significanly weaer during hese wo periods. 2.2 The high yield spread as a predicor of real aciviy The heoreical underpinning of he high yield spread as a predicor of real economic aciviy primarily relaes o he heory of he financial acceleraor (see for example Bernane and Gerler 1989; Bernane, Gerler and Gilchris 1998, and he references herein). While he deails of hese models differ, heir cenral feaures are reasonably uniform and heir ey elemens may be se ou informally as follows. There is some fricion presen in he financial mare, such as asymmeric informaion or coss of conrac enforcemen, which, for a wide class of indusrial and commercial businesses, inroduces a wedge beween he cos of exernal funds and he opporuniy cos of inernal funds he premium for exernal funds. This premium is an endogenous variable, which depends inversely on he balance shee srengh of he borrower, since he balance shee is he ey signal hrough which he crediworhiness of he firm is evaluaed. However, balance shee srengh is iself a posiive funcion of aggregae real economic aciviy, so ha borrowers financial posiions are procyclical and hence movemens in he premium for exernal funds are counercyclical. Thus, as real aciviy expands, he premium on exernal funds declines, which, in urn, leads o an amplificaion of borrower spending, which furher acceleraes he expansion of real aciviy. This is he basic mechanism of he financial acceleraor.

7 6 A problem in esing he heory of he financial acceleraor empirically in he pas has, however, been he lac of any reliable daa on a ey cenral variable in he heory he premium on exernal funds. This is because firms which are subjec o imporan financial consrains of his ind have ypically relied on commercial ban loans as he chief source of exernal finance, and ime series of relevan ban borrowing raes are no available. Moreover, as Gerler and Lown (1999) poin ou, even if hey were, he fac ha ban loans ypically conain imporan non-price erms would render hese series very imperfec and noisy signals of he premium on exernal funds. Since he mid 1980s, however, he US mare for below invesmen grade deb, someimes referred o as high yield bonds or, less euphemisically, jun bonds, has developed enormously. Gerler and Lown (1999) noe ha firms raising funds in he high yield bond mare are liely o be precisely hose ha face he ype of mare fricions ha he heory of he financial acceleraor describes. Moreover, since he opporuniy cos of inernal funding for firms is liely o be close o he safe rae of ineres such as ha on governmen or AAA raed deb, he spread beween high yield bonds and governmen deb or AAA raed deb is liely o be a good indicaor of he premium on exernal finance. If he heory of he financial acceleraor wors in pracice, herefore, one would expec he high yield spread o be a counercyclical predicor of fuure real aciviy. 3. Daa Monhly daa for he US for he period 1964M1-2001M12 were obained on real indusrial producion, he consumer price index, he hree-monh Treasury bill rae, and he en-year governmen bond yield, from he Inernaional Moneary Fund s Inernaional Financial Saisics daabase. A monhly series on he high yield spread was consruced as follows. Firs, we obained daa from he Merrill Lynch Global Bond Indices daa base an index (in annualized yield erms) of he yields on corporae bonds, publicly issued in he US domesic mare wih a year or more o mauriy which were raed BBB3 or lower. We hen subraced he en-year governmen bond yield from his o consruc he spread. Because he mare for below invesmen grade deb only developed during mid-1980s, a reliable series for he high yield spread could only be consruced for he period of he 1990s. 4. Long-horizon regressions The dependen variable in he basic long-horizon regressions is he annualized cumulaive percenage change in real indusrial producion: 1200 y + = ( y y ) (5) +

8 7 where denoes he forecasing horizon in quarers and y is he logarihm of an index of real indusrial producion a ime. The -period change in he logarihm of indusrial oupu is muliplied by (1200/) o ensure ha he percenage growh rae is expressed in annualized erms, as he ineres raes are. The slope of he nominal yield curve is measured by he difference beween he yield on en-year US governmen bonds (R ) and he hree-monh US Treasury bill rae (r ), while he high yield spread is measure as he difference beween he jun bond yield (Q ) and he en-year governmen bond yield (R ). The basic regression equaions are herefore of he form: for he erm spread regressions, and y + = α + β R r ) + η + y + = γ + δ Q R ) + ε + (, (6) (, (7) for he high yield spread regressions, whereη + and ε + are he forecas errors. As is well nown, even under he assumpion of raional expecaions, he fac ha he sampling inerval is smaller han he forecasing horizon generaes a moving average forecas error of order one less han he number of sampling periods in he forecas horizon, because of common news iems generaing successive forecas errors. Hence, he forecas errors may be assumed o have a moving average represenaion of order -1. This was allowed for by using an appropriae mehod-of-momens correcion o he esimaed covariance marix (Hansen, 1982). 4.1 Term spread regressions The resuls of esimaing equaions (6) for forecas horizons up o weny-four monhs ahead are given in Tables 1-3 for various sample periods. In Table 1, we repor he long-horizon regressions for he 1970s and 1980s i.e., for he sample period 1970M1-1990M12. These resuls are consisen wih hose repored in he lieraure for similar sample periods: he slope coefficien is srongly significanly differen from zero, wih -raios in every case of he order of around four. In Table 2, we repor resuls for he same regressions applied o daa for he mid o lae 1960s i.e. 1964M1-1970M12. Alhough he erm spread does have some predicive power for real aciviy during his period, he slope coefficiens are significanly differen from zero a he five percen level only for horizons ranging from six o welve monhs (wih only marginal significance of he coefficien a he eigheen monh horizon). The value of he - raios, even for he significan esimaed coefficiens, is also much lower han for he 1970s and 1980s, ranging beween 2 and 2.9.

9 8 Table 3 shows he resuls of esimaing he long-horizon erm spread regressions for he mos recen period, 1991M1-2001M12. Alhough he slope coefficiens are significanly differen from zero a he five percen level for horizons of up o wo monhs, he -raios ail off afer ha so ha none of hem is significanly differen from zero a he five percen level beyond he wo-monh horizon. The goodness of fi of he long-horizon regressions has also fallen dramaically a all horizons, relaive o he corresponding levels for he 1970s and 1980s. Overall, herefore, he srong predicive conen of he erm spread wih respec o fuure real economic aciviy seems o be largely confined o he period of he 1970s and 1980s. For he 1960s, he relaionship appears o be much weaened, while for he 1990s he predicive power of he erm spread appears o have virually disappeared alogeher. 4.2 High yield spread regressions Given ha he mare for below invesmen grade deb only developed in he US in he mid 1980s, lac of availabiliy of daa on he high yield spread forced us o consider only he mos recen of he hree sample periods, i.e. 1991M1-2001M12. The resuling long-horizon regressions are repored in Table 4. The sign of he esimaed slope coefficien is negaive every case: a larger spread predics a slowdown, exacly as suggesed by he heory of he financial acceleraor. The predicive conen of he high yield spread is quie sriing. In every case, he esimaed slope coefficien is srongly significanly differen from zero a he one percen level, wih -raios ranging in absolue value from around hree o around nine. The goodness of fi, as measured by he coefficien of deerminaion, is in nearly every case very much higher han he corresponding R 2 for he erm spread regressions, even during he heyday of he erm spread during he 1970s and 1980s, he wo excepions being a he eigheen and weny-four monh horizons. Finally, since he heory of he financial acceleraor suggess he possibiliy of non-linear ineracions beween financial variables and real aciviy, we examined wheher unusual levels of high yield spreads convey addiional informaion on real aciviy. Our proxy for unusual levels is a spread ha is more han 1.5 sandard deviaions away from he sample mean. To es for his, we adjused he long-horizon regression (7) o: y + = γ + δ Q R ) + θ I ( Q R ) ε + (, (8) where I is a dummy variable ha aes he value uniy if he high yield spread is more han 1.5 sandard deviaions away from is mean over he sample period. The resuls of esimaing his equaion are shown in Table 5, and reveal ha such abnormally high spreads do indeed predic an addiional slowing down in growh, alhough only over he shorer horizons of up o hree monhs.

10 9 5. Supply and demand innovaions in real oupu Given he apparen imporance of he high yield spread as a predicor of real economic aciviy during he las decade or so, we carried ou some furher invesigaions as o wheher he spread is able o predic he cumulaive growh in oupu when i is sripped of, alernaely, is demand-side and supply-side componens or, o be precise, is emporary and permanen componens. Permanen and emporary oupu movemens may be variously inerpreed according o he underlying heoreical framewor employed. In he radiional aggregae demand-aggregae supply (ADAS) model wih a long-run verical supply curve, for example, aggregae demand disurbances resul in a emporary rise in oupu, while aggregae supply disurbances permanenly affec he level of aggregae oupu. Blanchard and Quah (1989) use an ADAS framewor in heir analysis, and associae aggregae supply shocs wih permanen shocs and aggregae demand shocs wih emporary shocs. In his paper we shall follow heir axonomy. While i is possible ha demand disurbances may have permanen effecs on he real side of he economy, we concur wih Blanchard and Quah ha shocs having a permanen effec on oupu are liely o be due mosly if no wholly o supply-side facors, while hose having only a emporary effec are liely o be due mosly if no wholly o demand-side facors. If he permanen long-run effecs of demand disurbances are small relaive o he long-run permanen effecs of supply disurbances, hen he Blanchard Quah axonomy is a useful organizing principle for empirical purposes. Readers rejecing his axonomy, however, may simply reinerpre our analysis as invesigaing wheher nominal spreads affec he permanen or he emporary componens of real oupu movemens. Given his axonomy of permanen and emporary shocs o oupu, supply and demand shocs o real economic aciviy can be idenified by imposing appropriae resricions on he Wold represenaion of ime series for real and nominal macroeconomic variables. In paricular, consider he Wold represenaion for changes in he logarihm of oupu and he logarihm of prices: 1 y 1 p = φ φ φ j 11 j 12 j L j = 1 21 j φ22 j ς1 ς 2 (9) where he φlmj are he parameers of he mulivariae moving average represenaion and ς 1 and ς 2 are whie noise innovaions. We can idenify ς 1 and ς 2 as demand and supply innovaions in he following way. Wrie ς =(ς 1 ς 2 ), and denoe he bivariae vecor of innovaions recovered from he vecor auoregressive represenaion for ( 1 y 1 p )' as υ Since he VAR represenaion is simply an inversion of he Wold represenaion (9), υ will in general be a linear funcion of ς, υ =A ς say, where A is a 2x2 marix of consans. To

11 10 recover he underlying demand and supply innovaions from he VAR residuals hen requires ha he four elemens of A be idenified, which requires four idenifying resricions. Three resricions can be obained by normalizing he variances of ς 1 and ς 2 o uniy and seing heir covariances o zero (see Blanchard and Quah, 1989, for a defense of hese resricions). The fourh, crucial idenifying resricion, which effecively idenifies ς 1 as he demand innovaion (or emporary oupu innovaion), is he requiremen ha ς 1 have no long-run effec on he (log-) level of real oupu, alhough i may affec he long-run price level. The laer resricion on he Wold represenaion (9) may be wrien: j = 1 φ 11 j = 0. (10) These four resricions are hen sufficien o recover he underlying emporary and permanen innovaions o oupu, which, as we discussed above, may be inerpreed as underlying demand and supply innovaions respecively. 4 Having idenified he supply and demand innovaions, we can hen pariion he moving average represenaion for real indusrial oupu ino counerfacual series, corresponding o he pah ha would have obained in he absence of demand innovaions and he pah ha would have obained in he absence of supply innovaions over he esimaion period. We can hen uilize hese counerfacual series in ess of he predicive power of he high yield spread. We applied his mehod o he monhly series in he logarihm of indusrial producion and he consumer price index for he whole sample period, 1964M1-2001M12. Preliminary uni roo (augmened Dicey Fuller) ess on he daa (no repored) showed he change in he logarihm of real indusrial oupu, and he change in he logarihm of he consumer price index o be saionary processes. There was also no evidence of coinegraion beween indusrial producion and prices. This implies ha oupu growh and inflaion can be modeled as a bivariae moving average represenaion, which can be invered o a pure auoregression no involving error correcion erms. We herefore proceeded o esimae a vecor auoregressive represenaion for he vecor ime series ( 1 y 1 p )'. The order of he VAR was chosen by sequenially excluding he highes lags of boh series, saring from a welfh-order VAR, and esing he exclusion resricions on he sysem using a lielihood raio es. This process was sopped when he exclusion resricions were joinly significan a he five percen level. This led o a choice of lag deph of six. The residuals from he esimaed equaions were judged o be approximaely whie noise, using eiher individual 4 For furher deails of he decomposiion, see Blanchard and Quah (1989), Bayoumi and Taylor (1995) or Taylor (2002). Taylor (2002) discusses recursive resricions of his ype in he general muli-variable case.

12 11 Ljung Box saisics, or Hosing s mulivariae pormaneau saisic. In fac, his choice of lag deph coincided wih he lag deph chosen by minimizing he Aaie Informaion Crierion. In Figure 2 we have graphed he impulse response funcions for he log-levels of oupu and prices in response o he idenified supply and demand innovaions. By consrucion, he long-run impac of demand shocs on real oupu is zero, bu he shape of each of he impulse response funcions in each case accords wih simple economic priors in ha a posiive demand shoc raises boh oupu (in he shor run) and prices (in boh he shor run and he long run), while a posiive supply shoc raises oupu and depresses prices (in boh he shor run and he long run) Counerfacual analysis We hen used he Blanchard Quah esimaion resuls o brea down he series for US real indusrial producion ino counerfacual series, corresponding o he pah ha would have obained in he absence of demand innovaions in he moving average represenaion and he pah ha would have obained in he absence of supply innovaions. Effecively, his involves using he esimaed VAR o recover he moving average represenaion (9), and hen calculaing a counerfacual series for y by alernaely holding he idenified supply and demand shocs consan a zero over he sample period. We hen used his series in esimaes of he long-horizon regression using he high yield spread, he resuls of which are given in Tables 6 and 7. The resuls are ineresing and supporive of he financial acceleraor heory. We would expec he financial acceleraor process o operae hrough boh he supply and he demand sides of he economy. In paricular, a posiive supply, or produciviy, shoc ha leads o a permanen change in oupu will increase he collaeral value of he fuure sream of oupu. The reduced premium for exernal funds will, herefore, be associaed wih fuure oupu growh. The resuls srongly confirm his relaionship. When he indusrial oupu series is purged of demand disurbances, leaving he supply or permanen shocs in, he predicive abiliy of he high yield spread remains srong a all horizons (Table 6). Temporary demand shocs can also generae an acceleraor. Indeed, following a permanen shoc, induced invesmen demand can generae addiional cyclical effecs. The high yield spread does indeed predic he demand-driven componen of indusrial producion (Table 7). 5 Taylor (2002) noes ha, in general, here will be muliple soluions o recursive resricions of he ype suggesed by Blanchard and Quah (1989), and ha informal or qualiaive idenifying resricions of his ind are necessary in order o achieve full idenificaion.

13 12 7. Conclusion Why did he erm spread become a much weaer predicor of economic aciviy in he 1990s? Gerler and Lown (2000) sugges ha changes in US moneary policy may have had somehing o do wih his. In paricular, a more robus defense of inflaion saring in he mid-o-lae 1980s may have changed privae secor expecaions wih respec o fuure inflaion. While he shif in moneary policy may have been influenial, i is relevan ha he predicive abiliy of he erm spread was also weaer prior o The period during which he erm spread was informaive wih respec o real aciviy he 1970s and 1980s was he period of he wo oil shocs and characerized by high inflaion (and possibly, herefore, greaer inflaion uncerainy) and volaile growh. We should expec in such a period ha he negaive covariance beween curren inflaion and real aciviy would be mos pronounced. A rise in curren inflaion, associaed wih a rise in shor-erm raes, would lead o a flaening of he erm spread and lower real aciviy. However, in periods when inflaion is low and more predicable hese effecs may be weaer. In conras, he financial acceleraor creaes a more robus foundaion for he high yield spread as a predicor of fuure real macroeconomic aciviy. Tha relaionship is based on financial fricions ha amplify he business cycle. While such fricions, in paricular, asymmeric informaion, may decline over ime, ha seems unliely o occur in he immediae fuure. The robusness of his relaionship is also suggesed by he finding ha he high yield spread capures boh he supply-side (or permanen) shocs and he demand-side (emporary shocs).

14 13 Appendix: The negaive covariaion of inflaion and oupu growh in a model wih nominal wage ineria and long-run moneary neuraliy Consider he following simple, log-linear macroeconomic model, which displays long-run moneary neuraliy and shor-run nominal wage ineria induced hrough a wage formaion equaion in which wages are se in a wo-period overlapping conracs framewor: y = m p (A1) y p w = + θ (A2) n w = θ (A3) = w { E 2n n*} (A4) = Equaion (A1) represens he aggregae demand side of he economy as a funcion of real balances. The producion funcion (A2) relaes oupu o he level of employmen, n, and produciviy θ. The price level is shown in (A3) o be a funcion of he nominal wage and produciviy, while in (A4) he nominal wage conrac is se wo periods in advance a he level expeced o generae full-employmen level, n*. The model is closed by assuming ha money and produciviy are deermined by he evoluion of demand and supply shocs, e d and e s respecively, as follows: m = m 1 + e (A5) = θ 1 s d θ + e. (A6) Assume ha he covariance of e d and e s is zero and ha he supply and demand shocs have consan variances. Solving he model for inflaion and oupu growh as a funcion of he exogenous demand and supply disurbances yields: 1 p = ed 2 es (A7) 1 y = ed ed 2 + es, (A8) where 1 denoes he firs-difference operaor. Noe ha only supply shocs have a permanen effec on oupu, while boh supply and demand shocs can affec long-run prices. Using (A7) and (A8), he covariance of growh and inflaion is easily seen o be negaive: Cov p, y ) = [ Var ( e ) + Var ( e )] 0. (A10) ( 1 1 d s <

15 14 References Bayoumi, Tamim, and Mar P. Taylor (1995). Macroeconomic Shocs, he ERM, and Tri- Polariy. Review of Economics and Saisics 77: Bernane, Ben S., and Mar Gerler (1995). Inside he Blac Box: The Credi Channel of Moneary Policy. Journal of Economic Perspecives 9: Bernane, Ben S., and Mar Gerler (2001). Should Cenral Bans Respond o Movemens in Asse Prices? American Economic Review 91: Bernane, Ben S., Mar Gerler, and Simon Gilchris (1999). The Financial Acceleraor in a Quaniaive Business Cycle Framewor. In John B. Taylor and Michael Woodford (Eds.) Handboo of Macroeconomics 1C.: Amserdam; New Yor and Oxford: Elsevier Science, Norh-Holland. Bernard, Henri, and Sefan Gerlach (1998). Does he Term Srucure Predic Recessions? The Inernaional Evidence. Inernaional Journal of Finance and Economics 3: Blanchard, Olivier, and Danny Quah (1989). The Dynamic Effecs of Aggregae Demand and Supply Disurbances. American Economic Review 79: Caporale, Guglielmo M., (1994). The Term Srucure as a Predicor of Real Economic Aciviy: Some Empirical Evidence. Discussion Paper DP-4-94, Cenre for Economic Forecasing, London Business School. Chen, N. (1991). Financial Invesmen Opporuniies and he Real Economy. Journal of Finance 46: Chirino, Rober S. (1993). Business Fixed Invesmen Spending: Modeling Sraegies, Empirical Resuls, and Policy Implicaions. Journal of Economic Lieraure 31: Deaon, Angus (1992). Undersanding Consumpion. Oxford: Clarendon Press. Dosey, Michael (1998). The Predicive Conen of he Ineres Rae Term Spread for Fuure Economic Growh. Federal Reserve Ban of Richmond Economic Quarerly 84: Esrella, Aruro, and Gias A. Hardouvelis (1991). The Term Srucure as a Predicor of Real Economic Aciviy. Journal of Finance 46: Esrella, Aruro, and Frederic S. Mishin (1998) Predicing US Recessions: Financial Variables as Leading Indicaors. Review of Economics and Saisics 77:

16 15 Esrella, Aruro, and Frederic S. Mishin (1995b) The Predicive Power of he Term Srucure of Ineres Raes in Europe and in he Unied Saes: Implicaions for he European Cenral Ban. European Economic Review 41: Fama, Eugene F. (1981). Soc Reurns, Real Aciviy, Inflaion and Money. American Economic Review 71: Gerler, Mar, and Cara S. Lown (1999). The Informaion in he High Yield Bond Spread for he Business Cycle: Evidence and Some Implicaions. Oxford Review of Economic Policy 15: Hansen, Lars P., (1982). Large-Sample Properies of Generalized Mehod of Momens Esimaors. Economerica 50: Harvey, Campbell R., (1989). Forecass of Economic Growh from he Bond and Soc Mares. Financial Analyss Journal Sepember Ocober: Hu, Z., (1993). The Yield Curve and Real Aciviy. Inernaional Moneary Fund Woring Paper 93/19, Washingon D.C. Lauren, Rober (1988). An Ineres Rae Based Indicaor of Moneary Policy. Federal Reserve Ban of Chicago Economic Perspecives 12: Peel, David A., and Mar P. Taylor (1998) The Slope of he Yield Curve and Real Economic Aciviy: Tracing he Transmission Mechanism. Economics Leers 59: Plosser, Charles I., and K.Geer Rouwenhurs (1994). Inernaional Term srucures and Real Economic Growh. Journal of Moneary Economics 33: Soc, James H., and Mar Wason (1989). New Indexes of Coinciden and Leading Indicaors. In: Olivier J. Blanchard and Sanley S. Fischer (Eds.) NBER Macroeconomics Annual Cambridge MA: MIT Press Taylor, Mar P. (1992). Modeling he Yield Curve. Economic Journal 102: Taylor, Mar P. (1999). Real Ineres Raes and Macroeconomic Aciviy. Oxford Review of Economic Policy 15: Taylor, Mar P. (2002). Esimaing Srucural Macroeconomic Shocs Through Long-Run Recursive Resricions on Vecor Auoregressive Models: The Problem of Idenificaion. Mimeo, Deparmen of Economics, Universiy of Warwic.

17 16 Table 1: Term Spread Predicions of Indusrial Producion Growh, 1971M1-1990M12 Forecas Horizon β R 2 s.e. (%) (4.080) (3.566) (3.625) (3.734) (3.833) (3.870) (3.954) (3.938) (3.868) (3.928) (3.864) (4.565) Noes: Esimaion is by ordinary leas squares, wih a mehod-of-momens correcion o he esimaed covariance marix. is he forecas horizon in monhs, R 2 denoes he coefficien in deerminaion and se denoes he sandard error of he regression. Figures in parenheses below coefficien esimaes are asympoic -raios. An inercep erm was also included in he regressions.

18 17 Table 2: Term Spread Predicions of Indusrial Producion Growh, 1964M1-1970M12 Forecas Horizon β R 2 s.e. (%) (0.428) (0.536) (0.709) (1.027) (1.470) (2.127) (2.912) (2.893) (2.414) (1.996) (1.947) (1.530) Noes: Esimaion is by ordinary leas squares, wih a mehod-of-momens correcion o he esimaed covariance marix. is he forecas horizon in monhs, R 2 denoes he coefficien in deerminaion and se denoes he sandard error of he regression. Figures in parenheses below coefficien esimaes are asympoic -raios. An inercep erm was also included in he regressions.

19 18 Table 3: Term Spread Predicions of Indusrial Producion Growh, 1991M1-2001M12 Forecas Horizon β R 2 s.e. (%) (1.981) (2.031) (1.888) (1.729) (1.595) (1.520) (1.497) (1.479) (1.450) (1.416) (1.538) (1.696) Noes: Esimaion is by ordinary leas squares, wih a mehod-of-momens correcion o he esimaed covariance marix. is he forecas horizon in monhs, R 2 denoes he coefficien in deerminaion and se denoes he sandard error of he regression. Figures in parenheses below coefficien esimaes are asympoic -raios. An inercep erm was also included in he regressions.

20 19 Table 4: High Yield Spread Predicions of Indusrial Producion Growh, 1991M1-2001M12 Forecas Horizon δ R 2 s.e. (%) (-9.195) (-8.355) (-6.813) (-5.482) (-4.820) (-4.375) (-3.994) (-3.739) (-3.543) (-3.428) (-3.974) (-2.934) Noes: Esimaion is by ordinary leas squares, wih a mehod-of-momens correcion o he esimaed covariance marix. is he forecas horizon in monhs, R 2 denoes he coefficien in deerminaion and se denoes he sandard error of he regression. Figures in parenheses below coefficien esimaes are asympoic -raios. An inercep erm was also included in he regressions.

21 20 Table 5: Threshold Effecs in High Yield Spread Predicions of Indusrial Producion, 1991M1-2001M12 Forecas Horizon δ θ R 2 s.e. (%) (-2.901) (-2.981) (-3.306) (-3.353) (-3.191) (-3.221) (-3.023) (-2.446) (-2.260) (-1.919) (-1.841) (-2.310) (-2.140) (-2.487) (-2.056) (-1.576) (-1.175) (-0.729) (-0.510) (-0.633) (-0.645) (-0.082) (1.339) (1.442) Noes: Esimaion is by ordinary leas squares, wih a mehod-of-momens correcion o he esimaed covariance marix. is he forecas horizon in monhs, R 2 denoes he coefficien in deerminaion and se denoes he sandard error of he regression. Figures in parenheses below coefficien esimaes are asympoic -raios. An inercep erm was also included in he regressions.

22 21 Table 6: High Yield Spread Predicions of Indusrial Producion Growh wih Indusrial Producion Purged of Demand-Side Disurbances, 1991M1-2001M12 Forecas Horizon δ R 2 s.e. (%) (-2.366) (-1.923) (-1.799) (-1.851) (-2.026) (-2.142) (-2.213) (-2.293) (-2.400) (-2.700) (-3.966) (-2.330) Noes: Esimaion is by ordinary leas squares, wih a mehod-of-momens correcion o he esimaed covariance marix. The series for indusrial producion has been purged of demand-side disurbances using he Blanchard-Quah mehod described in he ex. is he forecas horizon in monhs, R 2 denoes he coefficien in deerminaion and se denoes he sandard error of he regression. Figures in parenheses below coefficien esimaes are asympoic -raios. An inercep erm was also included in he regressions.

23 22 Table 7: High Yield Spread Predicions of Indusrial Producion Growh wih Indusrial Producion Purged of Supply-Side Disurbances, 1991M1-2001M12 Forecas Horizon δ R 2 s.e. (%) (-6.189) (-5.009) (-4.141) (-3.620) (-3.282) (-3.155) (-3.167) (-3.171) (-3.183) (-2.994) (-2.758) (-1.904) Noes: Esimaion is by ordinary leas squares, wih a mehod-of-momens correcion o he esimaed covariance marix. The series for indusrial producion has been purged of supply-side disurbances using he Blanchard-Quah mehod described in he ex. is he forecas horizon in monhs, R 2 denoes he coefficien in deerminaion and se denoes he sandard error of he regression. Figures in parenheses below coefficien esimaes are asympoic -raios. An inercep erm was also included in he regressions.

24 Figure 1: US Inflaion and Oupu Growh, monh inflaion rae 12-monh growh in oupu M1 1962M1 1966M1 1970M1 1974M1 1978M1 1982M1 1986M1 1990M1 1994M1 1998M1 2002M1

25 Figure 2: Impulse Responses Response of Oupu o Demand Shoc Response of Oupu o Supply Shoc Response of Prices o Demand Shoc Response of Prices o Supply Shoc