The Informaion Conen of he ISM Purchasing Managers Survey Daniel Bachman U.S. Deparmen of Commerce * This Version: 8/3/2010 1. Inroducion A he beginning of every monh, he business press focuses briefly on he survey published by he Insiue for Supply Managemen (ISM). Press descripions and he ISM iself describe he survey as providing informaion abou he sae of U.S. manufacuring. Press repors in recen years have herefore ended o conflae he ISM wih he manufacuring secor. For example, an Associaed Press (AP) aricle on Sepember 3, 2008, described a decline in he ISM composie index his way: he laes economic indicaors, released on Tuesday, showed ha manufacuring shrank in Augus. Researchers do no use he ISM survey as a fundamenal measure of manufacuring aciviy, however. Insead, hey urn o official governmen daa series such as he Federal Reserve s indusrial producion index or he Census Bureau s Manufacuring Shipmens, Invenories, and Orders survey. Mos analyss believe ha hese series are more comprehensive and have more scienifically accurae samples and mehdologies han he ISM, and herefore beer measure acual economic aciviy. The main value of he ISM survey is raher in is anicipaion of laer official daa, because i is published significanly The views in his paper are hose of he auhor alone, and do no reflec official opinions of he U.S. Commerce Deparmen.
earlier han he official daa. For boh privae economic acors and public policymakers, here is value in learning somehing abou he sae of he manufacuring secor wo o four weeks before he firs official measures are published. The Sepember 2008 experience provides an ineresing example of he difference beween hese wo uses of daa. In he release ha is he subjec of he AP aricle quoed above, he ISM index fell slighly (from 50.0 in July o 49.9) in Augus bu i was noeworhy ha he index was below 50. Hence he AP s suggesion ha manufacuring shrank (a number below 50 indicaing ha more han half of he respondens believed ha aciviy was lower in Sepember han in he previous monh). In conras, he Federal Reserve s measure of manufacuring indusrial producion released wo weeks laer dropped by a very subsanial 1.0% over he same period. Today, mos sudens of he business cycle would accep as a given ha manufacuring producion fell subsanially in Augus 2008, based on he Federal Reserve measure. I am no aware of any analyss who would find addiional informaion in he ISM composie index for his series. In his paper, I es and measure wha he manufacuring ISM has old us in he pas abou he acual sae of manufacuring as measured by official daa. I base my ess on he improvemen in shor-erm forecass of official daa when ISM survey informaion is included in he forecasing equaion. Previous research eiher used he ISM survey o predic GDP raher han manufacuring aciviy or looked a correlaions of one published elemen of he ISM survey he ISM composie index and indusrial producion. In conras, I repor on a simulaion of he experience an acual user migh have had she incorporaed he ISM survey daa ino her forecass. I also use he individual indexes published by he ISM o predic specific relaed official governmen daa series such as Page 2 of 20
manufacuring invenories and producer prices. This allows me o draw conclusions abou he accuracy of specific quesions of he ISM survey. The ISM also collecs and publishes a survey of nonmanufacuring firms. In his paper, however, I focus exclusively on he ISM manufacuring survey. 2. The ISM Survey and he PMI The ISM manufacuring survey is one of he mos venerable privae secor measures of economic aciviy. The original survey by he Purchasing Managemen Associaion (now called he Insiue for Supply Managemen) daes back o 1931, alhough consisen daa is only available from 1948. The ISM currenly repors on he resuls of quesions in en areas. (see Table 1). I also publishes a composie of five of he indexes called he Purchasing Managers Index (PMI) which is normally he subjec of media repors. Table 1 liss he welve ISM indexes (eleven on specific opics and he PMI index, Table 1: ISM indexes and corresponding official daa series ISM index Official daa series and source Purchasing Managers Composie Indusrial producion (Fed) Producion Indusrial producion (Fed), manufacuring shipmens (Census M3) Employmen Payroll employmen in manufacuring (BLS) New Orders Manufacuring new orders (Census M3) Supplier Deliveries N/A Backlog Manufacuring unfilled orders (Census M3) Invenories Manufacuring invenories (Census M3) Cusomers Invenories Prices Producer prices for finished goods (BLS) New Expor Orders Real merchandise expors (Census FT) Impors Real merchandise impors (Census FT) Buying Policy N/A Noe: N/A means ha here is nobvious official daa corresponding o he ISM s quesion. Sources: Fed=Federal Reserve Board, Census M3=Census Bureau Manufacuring Shipmens, Invenories and Orders, BLS=Bureau of Labor Saisics,Census FT=Census Bureau Foreign Trade. Page 3 of 20
which is a composie of five of he ISM indexes). The able also shows relaed fundamenal official series. Noe ha here are wo possible official series relaed o he producion concep he Federal Reserve s indusrial producion in manufacuring, and he Census Bureau s manufacuring shipmens. In mos cases, he indexes ask abou aciviy during he same period covered by he daa. The relaionship beween he ISM expor new orders and real expors, however, may be looser han he oher relaionships posied in he able. For expors, he ISM asks abou orders in a paricular monh, which could well urn ino acual expor flows as measured by he Census Bureau s monhly rade daa wih a lag of several monhs. ISM daa is repored as he percenage of posiive responses, so a value of 50 for he producion index means ha half of respondens increased producion in he reporing monh, and half decreased producion. (No change responses are proporionaely allocaed.) The ISM survey reaches abou 300 members of he Insiue, and responses are weighed by NAICS indusry. 3. Pas Research The prominence of he ISM index has led o a considerable lieraure discussing he relaionship beween i and official measures of economic aciviy. Since 2000, a number of aricles have found some relaionship beween he PMI index and measures of overall economic aciviy. Roland F. Pelaez [2002] examined he abiliy of he PMI index o forecas GDP. Pelaez compared a forecasing model using he PMI (essenially consraining he weighs of he subindexes in he forecas) o a model in which he five subindexes in he PMI are used Page 4 of 20
o direcly forecas GDP (which amouns o removing he consrains). Palaez found ha an index consising of jus hree subindexes new orders, employmen, and supplier deliveries ouperformed he sandard ISM index in forecasing GDP. M. Harris, R. Owens, and P.D. Sare [2004] found ha he ISM is effecive in racking movemens of GDP in real ime (i.e., considerably ahead of he GDP release). They calculaed ha he ISM index improves he curren quarer forecas of GDP by abou 12%, and he one-quarer-ahead forecas of GDP by 31%. They also argue ha he ISM and is individual componens generally represen a reliable, albei imperfec, signal of fuure recessions. In a relaed paper, R. Owens and P.D. Sare [2005] use specral echniques o answer similar quesions. They concluded ha diffusion indexes including he ISM index show business-cycle lengh frequencies, which suppors he view ha moneary policymakers can use he informaion o beer shape policy. Owens and Sare argue agains he view ha surveys such as his one are fundamenally flawed: while surveys allow for much discreion in he way respondens answer quesions, his discreion does no obscure he informaional conen of he responses in such a way as o simply produce saisical noise. Timohy Schiller and Michael Trebing [2003] compare forecass of indusrial producion using he PMI, he ISM manufacuring index, and a variey of oher variables and relaed models. They claim ha by hemselves, he diffusion indexes from he ISM survey explain 29 o 36 percen of he monh-o-monh variabion of he monhly changes in he IP-M [monhly indusrial producion index].. Shiller and Trebing noe ha adding diffusion indexes o oher predicive series, such as hours worked in manufacuring, can increase he Page 5 of 20
accuracy of a forecas. They appear o measure accuracy here by R 2, since hey repor neiher forecass nor any measure of forecas error. Evan F. Koenig [2002] ran a regression of he PMI on indusrial producion. He concluded ha facory oupu depends abou equally on he level of he PMI and he PMI s mos recen change. He based his saemen on he significan -saisics for boh coefficiens. Mr. Koenig also esed o see wheher he PMI has predicive power by calculaing real-ime forecasing regressions for GDP using employmen, reail sales, and indusrial producion along wih PMI, and found ha, even wih he oher variables, he PMI has marginal predicive power. I seems a bi odd ha he PMI index would have explanaory power for GDP beyond ha provided by he Indusrial Producion Index. However, he PMI subindexes do include some informaion (such as orders, invenories, and expor orders) which are no par of he official indusrial producion measure. 4. Tess 4.1 Characerisics of he daa Figure 1 shows he ISM producion index since 1948. The mean value of he index, 55.7, indicaes ha, on average, more firms experience growh han falling producion. Tha is consisen wih he simple fac ha, over he long erm, he economy experiences growh. There is no suggesion here ha he level of he ISM series changes over ime. The oher ISM indexes have similar properies. The ISM index is designed o measure he level of change in he underlying variable (i.e., he change in producion, employmen, invenories, ec.). Thus i makes sense o measure he corresponding official series mos of which are published in level form as Page 6 of 20
90 80 70 60 50 40 30 20 10 Figure 1: ISM Producion Index 0 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 8.0 6.0 4.0 2.0 0.0-2.0-4.0 Figure 2: Indusrial Producion, Manufacuring Percen Change -6.0 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 raes of change. Figure 2 shows he percenage change in manufacuring IP, he variable ha he ISM producion index should be able o predic. Noe ha he rae of change appears saionary. Thus, is unlikely ha coinegraion exiss and ha a uni roo would pose problems for esimaion and esing. Neveheless, I calculaed Dickey Fuller ess and augmened Dickey Fuller ess for uni roos. In all cases, he hypohesis ha he series as used here have a uni roo can be rejeced wih a high degree of cerainy. 4.2 Tesing sraegy Formally, we can hink of wo series, wrien here in saionary form: (1) x y = a x = a x x 1 y 1 + ε + η x + ε + η y where 0<a<1, he η erms are idiosyncraic shocks unique o he respecive processes, and ε is a shock common o boh processes. Early in he monh, we know he curren period value of y, bu no of x. Clearly we should be able o use he informaion in y o obain a beer predicion of x han we would obain knowing only pas informaion (defined here as pas values of x. Page 7 of 20
The key quesion for a ypical daa user is wheher he ISM index helps o forecas he subsequen official daa. Consider he following wo forecas equaions, where x is he official governmen measure and y is he relaed ISM index: (2) x x = C + = C + n = 1 n = 1 A x A x 1 1 + ε + By + ε The firs equaion in (2) projecs x based on pas values of iself. The second equaion adds he conemporaneous ISM index, since i is known before x. A simple es of he informaion conen of he ISM index is ha adding i o he forecasing equaion will resul in improved forecass of he curren value of x, or essenially, wheher he model in equaion (1) is correc. 4.3 Forecas Improvemen I esimaed forecass from he equaions in (2) for each pair of ISM indexes and official measures. I esimaed each equaion on a rolling basis, using en years of pas hisory. I sared he forecass in January, 1998 and ran hem hrough December, 2009. Afer esimaing he equaion for each ending period, I hen calculaed he projecion from he equaion for he economic measure in he nex period, based on he acual value of he ISM indicaor. I herefore creaed 12 years (144 observaions) of prediced one-period ahead forecass for he official series.. The process in effec simulaes he experience a forecaser migh have in using he ISM erm o predic he subsequen economic indicaor for each monh. However, I used revised and no vinage daa for his experimen. Page 8 of 20
Table 2: Forecas Improvemen Percen improvemen over forecas wihou ISM measure Economic Measure ISM Index MAE MSE Indusrial Producion PMI Composie 9.0 8.7 Indusrial Producion Producion 11.0 11.8 Manufacuring Shipmens Producion 2.4 7.8 Payroll employmen, manufacuring Employmen 0.0 5.4 Manufacuring new orders New orders 5.0 6.7 Manufacuring unfilled orders Backlog 1.0 0.6 Manufacuring invenories Invenories 0.3 1.2 Producer prices for finished goods Prices 9.1 11.3 Real merchandise expors Expors 7.4 7.0 Real merchandise impors Impors 5.0 5.9 Noe: bold indicaes he improvemen is significan a he 5% level according o he Diebold-Mariano Tes. Table 2 shows he percen improvemen in he forecas for he 10-year period when he ISM indicaor is included in he forecasing equaion. The able shows wo merics: he mean absolue error (MAE) and he mean squared error (MSE). For example, he average forecas error of he Federal Reserve s manufacuring indusrial producion index was 11% smaller when he ISM producion index was included in he forecasing equaion. This essenially measures wha a pracical user of he daa would wan o know: i answers he quesion, how much does he ISM index help forecas relevan official daa. Alhough I ve included an indicaion of he resuls of significance ess, he reader should be wary of reading oo much ino hem. The 5% confidence limi is arbirary and likely does no represen he acual loss funcion faced by forecasers. I suspec ha a large improvemen in forecasing power which was significan a he 30% level migh be of grea ineres o financial marke paricipans, while a 5% improvemen ha is significan migh no be of much use o analyss. (See Sephen T. Ziliak and Deirdre N. McCloskey (2007) for a complee polemic on his poin.) Page 9 of 20
I would be hard o characerize he improvemens in Table 2 as large. The bes improvemen comes in forecasing indusrial producion and ha jus over 10%. There is a similar improvemen in he forecas of producer prices. On he oher hand, here is less improvemen in forecasing employmen or he various componens of he Census Bureau s manufacuring shipmens, orders, and invenories (M3) survey. These series (shipmens, new orders, unfilled orders, and invenories) are all nominal, so i is cerainly possible ha he addiional variaion in price in he arge series has reduced he forecasing abiliy of he ISM survey index. A furher ineresing feaure of Table 2 is ha he forecas improvemens end o be larger when he forecas error is measured by mean squared error. This suggess ha he ISM indexes are mos useful a imes when pas values of he official series are mos misleading perhaps during urning poins, for example, if (as seems likely) errors in he univariae ime series model are larges a urning poin.. Neverheless, he resuls in Table 2 sugges ha he informaion in he ISM indexes provides a bes a modes improvemen over a univariae forecas. This is paricularly sriking since he univariae forecas is likely a relaively weak compeior. Srucural forecasing equaions for each of hese series based on economic heory are very likely o be more accurae han he univariae forecas, which migh well reduce or eliminae he usefulness of he informaion in he ISM indexes. 4.4 Forecas Performance in he 1960s and 1970s The srucure of he U.S. economy and he U.S. manufacuring secor has changed subsanially over ime. The ISM series migh have conained more, differen, or less Page 10 of 20
Table 3: Forecas Improvemen in he 1960s and 1970s Percen improvemen over forecas wihou ISM measure Economic Measure ISM Index MAE MSE (Forecas Period: 1960-1969) Indusrial Producion PMI Composie 15.5 17.9 Indusrial Producion Producion 11.9 16.2 Payroll employmen, manufacuring Employmen 18.0 15.8 Producer prices for finished goods Prices 1.4 1.1 (Forecas Period: 1970-1979) Indusrial Producion ISM Composie 7.8 10.0 Indusrial Producion Producion 14.2 13.5 Manufacuring Shipmens Producion 2.8 6.2 Payroll employmen, manufacuring Employmen 9.2 17.7 Manufacuring new orders New orders 11.8 11.7 Manufacuring invenories Invenories 6.3 5.5 Producer prices for finished goods Prices 5.4 4.7 Noe: bold indicaes he improvemen is significan a he 5% level according o he Diebold-Mariano Tes. informaion in he pas, even hough he relaionship is no longer as srong oday. Table 3 shows he resuls of running a forecasing exercise like he one described above for daa during he 1960s and 1970s. I was impossible o forecas he full se of economic series because some of hese series do no exis during his period. The Census M3 series sar in 1958, so here are no enough observaions o esimae forecas equaions for he shipmens, new orders, unfilled orders, and invenories series for he 1960s. Census publishes real impors and expors series currenly saring only in 1994, and he ISM survey quesion on unfilled orders sars in 1993, so i is impossible o creae forecasing equaions for he rade series or unfilled orders in eiher he 1960s or he 1970s. The ISM survey indexes improved forecass of he official series slighly more during he 1960s and 1970s han during he 1998-2009 period. The improved abiliy in forecasing Page 11 of 20
he Census M3 series, such as new orders and invenories, in he earlier period is paricularly sriking. These series are nominal values, while he ISM series are bes inerpreed as real series. Thus, he 1970s, a period of high and variable inflaion, should have seen a deerioraion in he forecasing abiliy of he ISM relaive o he more recen period when inflaion was low. These improvemens, however, are relaively small. The bes forecas improvemens are in he 10% o 20% range. Employmen in he 1960s provides he larges forecas improvemen, wih a mean absolue error 18% smaller when he ISM payroll index is included in he forecasing equaion. 4.5 Why aren he ISM surveys beer predicors? The ISM indexes do appear o provide some informaion abou subsequen economic measures, bu he relaively modes forecas improvemens are somewha surprising. There are wo broad reasons why he ISM indexes migh have only a limied abiliy o improve forecass of official variables. 1. The ISM indexes conain measuremen error relaive o he official series. As noed, he ISM surveys abou 300 firms which are members of he organizaion. Membership is volunary, so here is no guaranee ha firms surveyed are represenaive of he aciviy of all manufacuring firms. While he ISM aemps o accoun for some of his problem by he NAICS weighing, he survey migh also be biased by firm size and even, wihin indusry, by producion mehod. In conras, he Census Bureau repors ha he M3 survey panel includes nearly all manufacuring companies wih $500 million or more annual shipmens and a selecion of Page 12 of 20
smaller firms (Census Bureau [2010]). Thus, he Census sample includes a much larger share of he oal manufacuring secor, and includes firms regardless of wheher hey are members of he ISM. I also makes a specific allowance for small firms, and benchmarks he sample o he Economic Census. Many of he oher relevan governmen daa series, such as he Fed s Indusrial Producion or he BLS payroll employmen, are aken from acual physical oupu measures or adminisraive sources. While his daa is no wihou problems, i ends o be more likely o cover a larger share of he manufacuring secor, and o provide informaion which allows more accurae exrapolaion of areas which are no covered. This comparison of governmen daa wih he ISM indexes should no be seen as a criicism of he ISM survey iself. Clearly, here is a radeoff beween obaining he more complee official measures and he imeliness of he ISM daa, and here is nohing inrinsically wrong wih he ISM s survey of is members. Bu he imeliness likely does come a he cos of addiional measuremen error ha may obscure he acual direcion of he manufacuring secor. 2. Parameer insabiliy and overall measuremen error makes forecasing difficul. Todd E. Clark and Michael w. McCracken [2006,2007] have observed ha, for forecass of inflaion using he oupu gap, despie seemingly good in-sample fis, he ou-of-sample forecas performance of Phillips curve models is mixed. [2006, p1129] Mr. Clark and Mr. McCracken aribue his mainly o he high noise-o-signal raio in he (relaively) small daa ses ypically used in such esimaes. They also show ha parameer insabiliy migh reduce he ou-of-sample forecasing abiliy of he model. Alhough hey do no aribue much of he specific problem of esimaing Phillips curves parameer insabiliy problem, hey Page 13 of 20
emphasize ha i remains a poenial source of rouble in comparisons like hose presened here. The ulimae argumen here is ha he es of forecasing abiliy used here is a very difficul one for ypical macroeconomic daa o pass. While Clark and Mr. McCracken are saisfied ha he heoreical consruc of he Phillips curve can survive he esimaion problem, i is hard o see how his is he case for he somewha simpler problem I ve encounered in his paper. The null hypohesis is simple: he ISM indexes should predic subsequen official daa. The resuls presened here indicae ha he ISM indexes improve forecass a bes only modesly. There are a number of reasons why his migh no be he case: he ISM daa migh be flawed, he official daa migh be flawed, or parameer insabiliy coupled wih he small size of he sample may preven analyss from obaining useful esimaes. The conclusion in all cases would be he same: he ISM indexes are of limied usefulness o analyss primarily ineresed in using hem o forecas official daa. 5. Two Simple Exensions 5.1 Sign Tess Anoher, simpler, and easier es is o ask wheher he ISM a leas predics he direcion of change of he official variables. Table 4 shows he percenage of monhs when he ISM index correcly prediced he direcion of he subsequen movemen of he relaed official series. I have assumed ha a value of he diffusion index above 50 should ranslae ino a posiive movemen in he fundamenal series (since more respondens are hen saying ha aciviy in his area is rising). The reader should keep in mind ha, if he level of he Page 14 of 20
Table 4: Sign Predicion Resuls Percen of oal observaions wih correc sign predicion Enire 1950 s 1960 s 1970 s 1980 s 1990 s 2000 s Period Indusrial Producion 78% 78% 80% 76% 71% 68% 75% Manufacuring Shipmens 68% 75% 73% 64% 65% 65% Manufacuring Employmen 83% 83% 81% 79% 66% 71% 77% New Orders 57% 73% 64% 58% 63% 62% Unfilled orders 59% 54% Invenories 57% 64% 48% 31% 47% 36% Producer Prices 45% 44% 80% 62% 55% 60% 58% Real Expors 64% 63% Impors 62% 63% ISM index is compleely unrelaed o he subsequen direcion of movemen of he official series, he predicion will be correc 50% of he ime. The sign predicion abiliy varies widely among he differen indexes. The employmen index go he sign righ 77% of he ime over he enire period, while he invenory index acually ended o predic he wrong sign (wih a correc predicion rae of 36%, some 64% of he sign predicions of he invenory index were wrong). The sign predicion abiliy also varied over ime. The ISM indexes ended o have he mos accurae sign predicion abiliy in he 1950s, 1960s and 1970s, when he producion and employmen indexes were correc abou he direcion of movemen of indusrial producion as much as 4/5 of he ime. In conras, he price index preformed poorly during he low-inflaion 1950s and 1960s, hen no surprisingly prediced he sign of he PPI very well in he 1970s when inflaion was high. More recenly, predicion success raes for almos all series are in he 60% o 70% range excep for invenories. The resuls here sugges ha analyss should be very wary of connecing he ISM invenory index o he Census Bureau s invenory series, as he ISM index will predic he direcion of movemen incorrecly more ofen han i will predic he direcion correcly. Page 15 of 20
The sign predicions of he ISM in mos cases are large enough o allow rejecion of he null hypohesis ha he rue disribuion of resuls is 50%. 5.2 Anicipaing Business Cycle Turning Poins Predicion on a monh-o-monh basis is one hing, bu ofen he mos imporan quesion is wheher a series can predic a business cycle urning poin. If he small error reducion noed earlier is concenraed in business cycle urning poin periods, he value of he ISM series migh be subsanially greaer han he improvemen in he average forecas over he enire period migh indicae. ISM Composie Index Business Cycle Predicion Record Peak Monhs Before Peak Trough Monhs Before Trough May-48 False signal Nov-48 3 Oc-49 3 Aug 51 o Jul 52 False signal Jul-53 1 May-54 2 Aug-57 5 Apr-58-1 Apr-60 0 Feb-61-1 Jan 967 o Jul 19 False signal Dec-69-2 Nov-70-3 Nov-73-12 Mar-75-4 Jan-80 5 Jul-80-1 Jul-81-1 Nov-82-2 Apr-85 False signal Jul-89 False signal Jul-90 2 Nov-82-2 Jan-92 False signal Oc-95 False signal Aug-98 False signal Mar-01 6 Nov-01-2 Apr-03 False signal Dec-07-4 Summary Early Signals 6 2 Lae Signals 4 8 False Signals 9 n/a Table 5 summarizes he preformance of he ISM composie index around NBER-defined business cycle urning poins. For his able, he ISM is assumed o give a urning poin signal when i regiseres 3 monhs of values below 50. This is arbirary, alhugh consisen wih boh he NBER s definiion of a business cycle as a period of conracion of economic aciviy and he ISM as a diffusion index (when more han half of surveyed firms are reporing Page 16 of 20
conracion). The able shows ha he ISM index gives a large number of false signals. I is cerainly possible o argue ha he arbirary signal I ve chosen is oo sensiive. However, a less sensiive signal would likely be evne worse a picking up acual business cycle urning poins, as his sensiive signal is lae in four of he eleven peaks (and eigh (!) of he 10 roughs) in he period since he daa sared. A less sensiive signal would very likely be even laer in predicing he urning poin. Of course, he NBER s definiion of he business cycle urnin poin may no precisely coincide wih he urning poin in indusrial producion. (Alhough he NBER business cycle daing commiee cies indusrial producion as one of five daa series ha help deermine recession iming, so i is possible o overemphasize he differnce beween a recession and a susained decline in indusrial producion.) An comparison of he signal provided by he ISM index wih periods of susained decline in indusrial producion doesn provide much evidence ha his is he problem, however. In 1973-74, for example, i ook he ISM 11 quarers afer indusrial producion sared falling o drop below 50. In he mid- 90s, when he economy slowed wihou undergoing a recession, indusrial producion sared a susained decline in 1995, bu i ook nine monhs before he ISM composie showed hree monhs of below-50 values. 6. Conclusion The manufacuring ISM surveys provide a view of he curren sae of manufacuring aciviy compleely separae from official governmen daa. Because he surveys are published wo o four weeks before official daa, analyss ineresed in curren economic condiions assume Page 17 of 20
ha hey are a useful indicaor of he official daa. There is some ruh in his assumpion, as he indexes provide a modes improvemen in forecasing relaed official series on a monho-monh basis. However, he key word is modes. The bes resuls obained in predicing manufacuring indusrial producion and producer prices are an improvemen of abou 10%. This is a bi worse han in he pas, bu, even in he 1960s, he forecas improvemen obained wih he ISM appears o be modes. The ISM may have some abiliy o a leas predic he direcion of subsequen official series, alhough some analyss may find an error rae of 30% for some series o be relaively high. A simple es suggess ha he ISM may no be paricularly good a predicing urning poins. While more informaion abou he sae of he economy is always beer, analyss of he business cycle should realize ha he ISM surveys do no supercede or fully anicipae more comprehensive official daa. Page 18 of 20
Bibliography 1. --. 2010 Insrucional Manual for Reporing on he Monhly Survey M3: Manufacurers Shipmens, Orders, and Invenories. Washingon: Bureau of he Census, 2010. 2.. Manufacuring and Consrucion Slowed in Augus. Associaed Press, Sepember 3. 3. Clark, Todd E, and McCracken, Michael. The Predicive Conen of he Oupu Gap for Inflaion: Resolving In-Sample and Ou-of-Sample Evidence, Journal of Money Credi and Banking, 38(5), Augus 2006. 4. Clark, Todd E. and McCracken, Michael. Combining Forecass from Nesed Models. Washingon: Federal Reserve Board (Finance and Economics Discussion Series 2007-43), 2007. 5. Harris, Mahew, Raymond E. Owens, and Pierre-Daniel G. Sare. Using Manufacuring Surveys o Assess Economic Condiions, Federal Reserve Bank of Richmond Economic Quarerly 90/4, Fall 2004, 65-92. 6. Koenig, Evan F. Using he Purchasing Mangers Index o Assess he Economy s Srengh and he Likely Direcion of Moneary Policy, Federal Reserve Bank of Dallas Economic and Financial Review 1:6, 2002, 1-15. 7. Owens, Raymond E., and Pierre-Daniel G. Sare. How Well Do Diffusion Indexes Capure Business Cycles? A Specral Analysis, Federal Reserve Bank of Richmond Economic Quarerly 91/4, Fall 2005, 23-42. 8. Peláez, Roland. A Reassessmen of he Purchasing Mangers Index, Business Economics, Ocober 2003, 35-41. 9. Schiller, Timohy, and Michael Trebing. Taking he Measure of Manufacuring, Philadelphia Federal Reserve Business Review, Q4 2003, 24-37. 10. Ziliak, Sepen T. and Deirdre N. Mccloskey. The Cul of Saisical Significance. Ann Arbor: Universiy of Michigan Press, 2009. Page 19 of 20
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