ACCOUNTING FOR CRISES * Venky Nagar University of Michigan venky@umich.edu. Gwen Yu Harvard University gyu@hbs.edu. June 2011.

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1 ACCOUNTING FOR CRISES * Venky Nagar Unversty of Mchgan venky@umch.edu Gwen Yu arvard Unversty gyu@hbs.edu June 2011 Abstract We provde one of the frst tests of recent macro global-game crss models that show that the precson of publc sgnals can coordnate crses (e.g., Angeletos and Wernng 2006; Morrs and Shn 2002, 200). In these models, self-fulfllng crses (ndependent of fundamentals) can occur only when publcly dsclosed fundamental sgnals have hgh precson; fundamentals are thus the sole drver of crses n low-precson settngs. We affrm ths proposton for 9 currency crses by explotng a key publcly dsclosed fundamental that drves fnancal markets, namely, accountng data. We fnd that fundamental accountng sgnals are stronger n-sample predctors of crses n lowprecson countres. * A study such as ths wll lkely generate more skeptcs than belevers. We are therefore very grateful to awrence Summers for strongly apprecatng our study, and for encouragng us to contnue pursung t. CORRESPONDING AUTOR: Venky Nagar, Unversty of Mchgan Ross School of Busness, 701 Tappan Street Ann Arbor, MI 48109, Tel: , Fax: , Emal: venky@umch.edu Electronc copy avalable at:

2 1. Introducton Economy-wde crses are trggered when agents n an economy wthdraw demand from markets for most goods and collectvely rush to money, bonds, or other safe securtes. Understandng the source of ths collectve and coordnated acton s one of the central goals of modern economc theory. Whereas tradtonal macroeconomcs looked to macro polces and aggregate ndcators for explanatons, the feld has recently experenced two sgnfcant paradgm shfts. Frst, macroeconomcs has begun to mplcate fnancal markets over tradtonal macro factors as the cause of ths collectve acton (Bernanke 2010; Blanchard et al. 2010; Krugman 2010; Mankw and Ball 2010, Secton VI). 1 Second, a new body of theory and emprcs justfes ths shft n emphass by drectly showng that large frms, whch are a prmary reason for fnancal markets to exst, are crucal drvers of aggregate fluctuatons. For example, Gabax (2011) shows that the dosyncratc movements of the largest 100 frms n the Unted States explan about one-thrd of varaton n output growth. Ths paper contnues ths new drecton of macroeconomcs by provdng one of the frst emprcal tests of recent macroeconomc theores that produce crses as a result of coordnaton and collectve acton problems n fnancal markets (Angeletos and Wernng 2006; Angeletos et al. 2006; Angeletos et al. 2007; Atkeson 2000; Morrs and Shn 2002, 200; Rey 2000). These so-called global-games theores have generated clear equlbrum predctons of when collectve nvestor behavor s drven by fundamentals and when by selffulfllng belefs, a result that had always eluded semnal non-mathematcal studes of crses (e.g., Kndleberger 1978, Ch. 4). Global games key predcton, at frst nonntutve, can be stated colloqually as too much nformaton can unnecessarly spook nvestors. Ths equlbrum predcton s what we successfully test: fundamentals are more lkely to predct crses when publc nformaton has low precson. 1 For example, Mankw and Ball (2010, Fgure 19.2) shows how a drop n fnancal asset prces can be selffulfllng by reducng consumers wealth and thus consumer spendng and frm nvestment and thus aggregate demand. 1 Electronc copy avalable at:

3 To ntroduce the ntuton of global games models, consder a stuaton n whch nvestors have lmted wealth and have to jontly fund an asset the true fundamental strength s unknown to all. Investors receve both publc and prvate nosy sgnals of the asset s fundamental strength. If the publc sgnal s precse enough relatve to nvestors prvate sgnals, t can coordnate multple self-fulfllng nvestor belefs that are ndependent of economc fundamentals. For example, suppose an nvestment needs nterm captal for proftable completon and the true measure of nvestors requred to provde fundng s 0%. Ths 0% s thus the ntal fundamental strength of the asset. Consder the case when ths nformaton s precsely released. If every nvestor beleves every other nvestor wll fal to supply captal (.e., attack), everyone wll attack. The nvestment wll then fal, for the measure of attackers s 100%, whch exceeds 0%. On the other hand, f every nvestor beleves that no one wll attack, a small ndvdual attack mposes opportunty costs only for that nvestor. Therefore, no one wll attack and the nvestment wll contnue. The accurate publc sgnal thus supports two self-fulfllng equlbra over ts realzaton range (0%, 100%), that s, any realzaton of the ntal fundamentals n ths range can lead to ether the attack or no-attack outcome. The above example assumes that the publc sgnal s precse. If ths s not the case, the global-game crss models show that nvestors wll wegh ther prvate nformaton more heavly. Because ths prvate nformaton vares across nvestors, each nvestor s unsure what the other nvestors are thnkng. Each ndvdual nvestor s then more fearful of losng money n an unsuccessful uncoordnated attack. In such settngs, poor ntal fundamentals become the man pont of coordnaton, and thus the man drver of crses. The above consderatons lead to a robust equlbrum predcton that fundamentals are more lkely to predct crses when publc nformaton has low precson. Craftng an approprate emprcal test of ths predcton requres locatng an nsttutonal settng that s amenable to global games. That s, the underlyng market should be too large for any ndvdual speculator, should be prone to collectve actons such as coordnated wthdrawal of captal, and should contan a fundamental publc sgnal the precson of 2

4 whch can be credbly measured. We argue that currency crses and accountng nformaton for the publcly traded sector n that country together consttute a powerful settng that meets these crtera. Currency crses occur when foregn nvestors collectvely wthdraw captal from a country and rush to safe harbors. As we explan n detal n Secton 2, research on currency crses orgnally tred to locate the trgger of the collectve acton n specfc monetary and exchange rate polces, but then swtched to countres productve goods and servces sectors and the supportng fnancal markets at large. To gve one example, n Martn and Rey s (2006) trade-based crss model, an ntal negatve aggregate demand shock mpars frm profts; the resultng mpact on asset prces and frm fnancng n the country s fnancal markets then becomes one mportant channel for transmutng ths shock nto a currency crss. Models such as these nevtably rase the queston of when asset prces and frm fnancng are based on fundamentals lke frm profts, and when on self-fulfllng nvestor belefs. We therefore focus on the fnancal market supportng the publcly held ndustral sector as a crtcal market that affects nternatonal captal flows nto a country. We next turn to the notons of fundamentals and ther publc sgnals n a country s fnancal market. Although a natural canddate mght appear to be the stock prce, ths measure has severe emprcal shortcomngs. Frst, to accurately test our theory we need a measure of the precson of the nose n the publc sgnal. The varance of the stock prce ncludes the varance n the actual economc actvty of the frm, the varance n nose, and the varance n the supply of the rsky asset (Angeletos and Wernng (2006), equaton 9). 2 It s dffcult to convncngly extract the varance of the nose component from ths total varance. On a related note, stock prces ncorporate nformaton not just about the underlyng asset s payoffs, but also about other nvestor characterstcs, such as ther expectatons of the future and the assocated dscount rates; our nterest s n the frst type of nformaton. We therefore delve more deeply nto the prce dscovery process, and 2 Angeletos and Wernng (2006) s equaton (9) clearly llustrates the dffculty n testng global games models head-on: t s dffcult to convncngly estmate the underlyng precson prmtves from observed prces.

5 turn to measures of the economc fundamentals of the frm that the prce dscovery process uses to arrve at the frm s market value. Specfcally, we look to the frm s accountng reports. The mportance of the accountng system to the nformaton acquston process that drves prce dscovery has led observers such as Summers (2000, p.10) and Rajan and Zngales (1998, p. 569) to nomnate the accountng system as central to the workngs of fnancal markets. A good measure of a frm s fundamental operatng strength s economc profts (hghly proftable frms can more lkely self-fnance), and an obvous publc sgnal of ths fundamental strength s accountng profts. Accountng profts are not only a publc sgnal of the operatng fundamentals of the frm, but also a natural measure of the precson of the nose n ths sgnal. Ths latter measure s key to testng the central predcton of global-game models. The man reason nvestors demand (and prefer) accountng data over and above cash flows s because current cash flows do not fully reflect current perod economc actvty (Dechow 1994). For example, certan accounts recevables may have gone bad ths perod and are unlkely to be collected. Such developments are crtcal current-perod economc events that affect current economc profts, but do not affect current operatng cash flows; they are nstead estmated as accountng accruals (Fama and French 2006; Sloan 1996). As a result, an extensve body of accountng lterature uses the noton of accountng qualty, or the precson wth whch accountng measures reflect economc realty. In partcular, ths lterature argues that there s consderable varaton n the precson of accountng nformaton across countres due to varatons n legal, enforcement, and rule-makng nsttutons (Ball et al. 2000; a Porta et al. 1998). Such nsttutonal varaton s essental to our emprcs. More mportant, accountng research suggests that our proxy for accountng data qualty measures publc sgnal precson relatve to prvate sgnal precson; ths publc-prvate relatvsm s a crtcal feature of the noton of precson n the global-game crss models. See euz and Verreccha (2000) and Daske et al. (2008). Daske et al. (2008) show that when countres shft to a hgher qualty fnancal reportng regme, both bd-ask spreads and tradng costs of the frms n the 4

6 In conductng our analyses, we recognze the rch emprcal early warnngs lterature on currency crses. Ths lterature s settng, ts posted crss predctors, and ts emprcal specfcatons form the obvous baselne for our emprcal tests. Specfcally, our settng ncludes 9 currency crses n 21 countres from 1981 to We construct a composte score of accountng precson for each country based on all ts publcly held frms. We use our composte score of accountng precson to splt the countres nto two groups: hgh precson and low precson. We then aggregate all the frms n each country every year to yeld three annual, country-based measures of realzed performance: earnngs, accountng accruals (accountng adjustments to cash flows to yeld earnngs), and volatlty of earnngs. We then test the n-sample power of realzed accountng performance measures to predct crses. We control for a rch lst of other leadng ndcators as well as country fxed effects and contemporaneous cross-sectonal shocks (contagon). In the overall sample, the ncluson of accountng measures sgnfcantly mproves our n-sample ablty to predct crses one year n advance: the explanatory power ncreases from to 0.28, a 15% ncrease. Much of the predctve power arses from accruals, or accountng adjustments to cash flows to measure accountng operatng profts. More specfc analyss suggests that t s the accountng estmates of declne n operatng assets (.e., wrte-offs of captalzed assets) that drve the downward movements n accruals pror to a crss. Ths s a partcularly nterestng result, for t shows that the applcaton of accountng rules to the measure of frm operatons s what generates crtcal asset-prcng nformaton. We then demonstrate the valdty of the global-game models by showng that most of the predctve mprovement comes from the sub-sample of countres wth low accountng precson. The F-statstc for the realzed accountng performance measures one year pror to crses s n low precson countres, but 1.1 for the hgh precson countres. By contrast, when we examne accountng data one year after the crss onset year, we fnd that both low precson and hgh precson accountng countres show country declne by 12 bass ponts. Informaton asymmetry among nvestors thus appears to declne, consstent wth an mprovement n the relatve precson of publc sgnals. 5

7 sgnfcance: the F-stats are now and 26.62, respectvely. So accountng data n hgh precson countres do appear to reflect the consequences of a crss; they just don t have ex ante predctve power. We then conduct a seres of comparatve statcs nvolvng nsttutons, the nature of the crses, the specfc precson thresholds, and specfc ndustry sectors such as the tradable sector. We also restrct each country to have only one crss. Our man results contnue to hold n all these tests. Our fndngs make three contrbutons to the lterature. Frst, we emprcally valdate a key predcton of global-game crss models, namely, that fundamentals are more mportant than self-fulfllng belefs n precptatng crses when fundamentals have low precson. Second, and perhaps more mportant, t s dffcult to test self-fulfllng belefs drectly: one can only show that fundamentals don t matter. But then, t s not clear f the result s due to self-fulfllng belefs or lack of statstcal power. By showng settngs where fundamentals matter as well as settngs where they don t, our study overcomes ths objecton. Fnally, our very use of accountng data s an nnovaton n emprcal crses studes, whch have typcally used macro, nsttutonal, and trade factors to predct crses (Martn and Rey 2006; Rancere et al. 2008). Our results ndcate that accountng data offer sgnfcant ncremental power beyond these factors to predct crses. The paper proceeds as follows. Secton 2 places our research queston n the context of pror lterature. Secton descrbes our data and our emprcal constructs. Secton 4 presents the man results. Secton 5 presents addtonal analyses. Secton 6 concludes. 2. Background Currency crses occur when nvestors suddenly and collectvely wthdraw captal from a country, leadng to a precptous drop n the exchange rate. The determnants of exchange rates therefore form the startng pont for all models of currency crses. 4 owever, dfferent generatons of models dffer n the choce of exchange rate determnants used to abstract the true underlyng crss generatng processes. 4 These determnants are well-studed all the way from reduced-form ntroductory macroeconomc models (Mankw 200, Ch. 1 Appendx) to advanced nter-temporal dynamc models (Obstfeld and Rogoff 2002). 6

8 Much of frst-generaton analytcal and emprcal crss research focused on monetary and exchange rate polces as the determnants of crses (Blanco and Garber 1986; Krugman 1979). Subsequent studes shfted to mperfectons n fnancal ntermedaton as the cause. 5 Ths so-called 2 nd generaton crss channel promptly rased ssues of coordnaton and multple equlbra based on self-fulfllng belefs. Concludng hs survey of ths lne of research, Blanchard (2000, Secton IV.4) notes that coordnaton s the key drver underlyng multplctes; expectatons therefore needed to be modeled more carefully to better understand the role of self-fulfllng belefs versus fundamentals. Whereas ntal studes of multplctes focused specfcally on banks, t became evdent that multplctes could happen due to coordnaton and ncreasng returns ssues n producton as well (Blanchard 2000, Secton IV.). Other studes --- the so-called rd generaton crss models --- mplcated very specfc fnancng channels, such as debt denomnated n foregn currences. More recent arguments have further broadened the scope of fnancal markets: Blanchard et al. (2010) note that lttle attenton was pad, however, to the rest of the fnancal system [other than banks] from a macro standpont, and Krugman (2010) notes that crses need not necessarly arse from specfc fnancal markets, such as the nternatonal exchange rate markets or corporate debt fnanced n foregn currency (.e., the balance sheet effect); collapse n the prces of any asset market that prevents frms from securng fnancng for ongong operatons s suffcent to trgger a crss. Because the prmary role of fnancal markets s to fnance the producton sector, an mmedate consequence of broadenng the fnancal markets n a currency crss context s that the country s producton sector comes to the forefront. 6 Modern models of crss, n contrast to ther frst-generaton counterparts, emphasze the producton sector and the economy at large (Martn and Rey 2006; Rancere et al. 2008; Tornell and Westermann 5 Early 20 th century accounts of crses had mplcated fnancal ntermedaton as a key cause of crses (Blanchard 2000, Secton IV.2; Samuelson 2009), but the focus shfted away wth the emergence of the IS- M model and ts descendants. 6 It s ndsputable that a country s ablty to produce tradable goods and servces s a crtcal factor n determnng the exchange rate (Obstfeld and Rogoff 2002, Ch. 4 & 5; Mankw 200, Ch. 12). If a country produces nothng for the rest of the world, ts currency s of lttle value abroad. 7

9 2005). For example, n Martn and Rey (2006), ntal aggregate demand shock trggers a proft drop; the resultng asset prces and nvestment levels determned by the fnancal markets play an mportant role n convertng the orgnal shock nto a currency crss. The models above rase the queston of when collapses of asset prces n fnancal markets are based on fundamentals, such as economc profts, and when on nvestors self-fulfllng belefs. Ths queston found ts most detaled nvestgatons n the so-called global-game models (e.g., Angeletos and Wernng (2006), Angeletos et al. 2006, 2007; Morrs and Shn 1998, 2002, 200). All these studes model a generc market n whch wealth-constraned nvestors collectvely coordnate to provde nterm fnancng to a generc asset. The fundamental strength of the asset s represented by the level of coordnated fnancng necessary to contnue the asset s productve actvtes (e.g., a hghly proftable asset lkely has lower demand for nterm external fnancng). When nvestors collectvely wthdraw fundng, the asset s unable to contnue operatons, and ts prce plummets. The models then examne the extent to whch publcly dsclosed nformaton about the asset fundamentals determnes the mportance of nvestors selffulfllng belefs n coordnatng fnancng actvty. A strkng feature of the models, across all ther varatons, s that the precson of the publc nformaton about fundamentals s the key determnant of multplctes (.e., the possblty of self-fulfllng crses unrelated to fundamental strength). Specfcally, the robust result all these studes obtan overall s that multplctes occur when the precson of publcly dsclosed fundamentals rses above a certan threshold relatve to the precson of nvestors prvate nformaton. 7 We therefore do not attempt to buld our own model n ths paper, but nstead drectly test ths robust equlbrum predcton. As dscussed n the Introducton, currency crses and accountng data form a powerful settng for testng ths predcton. Despte these advantages, there has been no attempt n 7 Multplctes of fxed- or equlbrum-ponts are an nherent property of smooth surfaces (Gullemn and Pollack 1974, Ch. 2). One can obtan unqueness of the fxed pont by mposng geometrc restrctons on the problem (whch global games acheve by lowerng the precson of the publc sgnal), but once these restrctons are relaxed or perturbed (e.g., by homotopy), multplctes are nevtable. The topology of fxed ponts on smooth surfaces s the key mathematcal reason why the multplcty property n global games s so robust. 8

10 the early warnngs lterature (at least to our knowledge) to use accountng nformaton to predct currency crses. 8 Instead, pror lterature has prmarly followed earlergeneraton models of crses and focused on macro measures to predct crses. For example, Rancere et al. (2008) and Martn and Rey (2006) show that countres wth hgh growth skewness and hgh tradng costs are more lkely to suffer crses. We nclude country ndcators to account for such cross-country varaton. That s, our tests are tmng tests that operate on a wthn-country model. We also conduct our analyses usng only the tradable sectors. Yuan (2005), among others, shows that correlaton across equty markets can propel crses (contagon). We use cross-sectonally correlated errors to account for contagon. Fnally, Jeanne (1997) and Jeanne and Masson (2000) used non-lnear emprcal tests wth Markov swtchng to dentfy these belefs n the devaluaton of the French franc n Our contrbuton to ths class of estmaton models s that we show both where fundamentals work and where they don t.. Data and Varable Defntons.1 Currency Crses and Fnancal Data Because our goal s to predct n-sample crses, we lmt ourselves to countres that have experenced crses. We use all the currency crses as our sample, nclude a rch control set of prevously posted determnants, and then conduct senstvty analyses over specfc subsets of crses. 9 Kamnsky and Renhart (1999) defne a currency crss as an event of a steep decrease n exchange rates and/or reserves. They provde an extensve lst of crss events (Kamnsky and Renhart 1999, Table II), whch Capro et al. (2005) and Kamnsky (200) subsequently update. We defne the crss onset year as the year a 8 Swanson and Juarez -Valdes (200) study the nformaton content of accountng fgures followng the 1994 Mexcan currency devaluaton. 9 Kndleberger (1978, p.x) succnctly summarzes the perennal debate on the smlarty and dfferences across crses by notng that some nternatonal economsts are clumpers and others are spltters. 9

11 crss started n the Kamnsky (200) and Capro et al. (2005) datasets. Ths procedure yelds 68 crses epsodes from 21 dfferent countres as shown n Table Table 1 classfes the dfferent types of crses based on Kamnsky (200, Table IV). Table 1 shows that 78% of the crses events can be classfed as ether fnancal excess or soveregn debt. These types of crses typcally arse from fnancal llqudty problems followng a perod of hgh expansonary credt growth (Tornell and Westerman 2005). Fnancal markets are thus mportant drvers of these crses, makng them an approprate settng for our study. We collect frm level fnancal data from Thompson Datastream, whch contans accountng nformaton from annual reports of publcly traded companes around the world. To be ncluded n the sample, a country must have more than fve frm-year observatons wth non-mssng values for a number of accountng varables, such as total assets, current assets, current lablty, and net operatng ncome. Thompson Datastream defnes each frm observaton by the unt of equty t ssues. Thus, f a frm ssues equtes on two dfferent exchanges, t wll count as two frm observatons. Because securtes lsted on a foregn exchange can also be subject to accountng rules of the foregn country, we delete securtes cross-lsted on the U.S. stock exchanges. Ths deleton ensures that the accountng sgnals of each country are an outcome of the local accountng standards. 11 Our procedure yelds 101,492 frm-year observatons from 21 countres n our fnal sample. The lmted avalablty of frm-year observatons n earler years restrcts our analyss to crss epsodes after Ths truncaton removes some early reserves based crses and makes the sample more relevant to our fnancal market based hypothess. We then aggregate the frm-years nto country-years (we do not over-wegh country-years wth more frm-year observatons). Ths aggregaton yelds 1 to 71 observatons dependng on the regresson. These country-years nclude 9 crses. 10 Some countres experence multple types of crses n the same year. Our analyses count these events as one event. 11 The results are robust to ncludng the cross-lsted frms. 10

12 Table A1 reports the onset year of each crss as well as the number of publc frms n our sample for each of the country-years. There s consderable varaton n the number of frm-year observatons across countres, reflectng dfferences n level of ndustralzaton, fnancal market development, and data avalablty. The shaded areas n Table A1 show consderable varaton n the spread of crses across countres and tme. Crses have a slght tendency to be clustered n the early and late 1990s, reflectng the exstence of the well known contagon effect (Allen and Gale 2000; Kamnsky et al. 200; Yuan 2005)..2 Precson of Accountng Sgnals.2.1 Measures Our man predcton s that accountng fundamentals are a stronger predctor of crses n countres wth low accountng precson. We now descrbe our composte measure of accountng precson for each country. The accountng lterature --- see summares n Dechow and Sknner (2000) and ealy and Wahlen (1999) --- has extensvely researched the precson or ablty of accountng measures to capture economc fundamentals. The source of accountng (m)precson arses from the followng problem: perod t cash flows are not perod t economc earnngs. For example, the manager may have spent cash on nvestments that wll pay back n the future, so the cash outflow s not a pure economc loss. Alternatvely, assets may have declned n value leadng to an economc loss, but there s no cash flow mpact because the assets are not sold. Accountng therefore adjusts the operatng cash flows to construct a measure of operatng earnngs or profts. Ths adjustment s called accruals. The nose n these adjustments s our proxy for the precson of the publc sgnals. Note agan that we are not measurng the varance of the overall performance sgnal; we are measurng the nose n the accountng adjustments. Ths s precsely the measure that the crss models requre. To users of fnancal statements, these accrual adjustments are relevant, but ther relablty can be mperfect. Specfcally, the relablty, or precson, can be mpared 11

13 because management can make estmaton mstakes or can msuse ts dscreton over accruals to conceal economc realty (both these factors are evdent n the current U.S. mortgage crss, for example). But what factors restran management accountng choces? Recent accountng research ndcates that the deeper nsttutonal factors that determne frms accountng choces are accountng rules, legal enforcement, and the legal regme (e.g., Ball et al. 2000). These factors vary across countres, yeldng nsttutonally drven cross-country varaton n the accountng precson n our data. Although recognzng accountng precson s conceptual and nsttutonal mportance, the accountng lterature has not converged on a unversally accepted measure of accountng precson. Dfferent accountng studes pck dfferent propertes of accruals to deduce the precson of accountng measures. We employ sx commonly used measures that capture varous dmensons along whch accountng nformaton relably reflects relevant frm fundamentals. Table 2 defnes n detal these sx measures as well as ther sources n the lterature. We aggregate each measure to the country level by usng the medan of the frm-year observatons. We sgn the measures so that lower values reflect hgher precson. Our frst measure of accountng precson, accruals qualty (=AQ 1 ), captures the estmaton errors n the accountng process by measurng how well accrual estmates map nto cash flow realzatons. Followng Dechow and Dchev (2002), we operatonalze ths measure as the standard devaton of the resdual from a country-level regresson of current accruals on mult-perod operatng cash flow. ow standard devaton mples hgher accountng precson. Our second measure, AQ 2, proxes for the level of management dscreton, often known as the smoothng behavor (Fudenberg and Trole 1995; Trueman and Ttman 1988). Smoothng refers to managers msusng ther reportng dscreton to conceal economc shocks by over-reportng poor performance and under-reportng strong performance. The accountng lterature has tradtonally used a strong negatve correlaton between changes n accruals and operatng cash flows to proxy for 12

14 management nterventon over and above the natural level of accruals accountng (e.g., Francs et al. 2005). The negatve of ths correlaton s then our AQ 2 measure. The remanng four measures of accountng precson (=AQ, AQ 4, AQ 5, and AQ 6 ) are varous measures of the magntude of accruals. Sloan (1996) suggests that large accruals nvolve a hgher degree of subjectvty that can often result n both ntentonal and unntentonal reportng errors. euz et al. (200), on the other hand, argue that the larger the absolute magntude of accruals, the more room the manager has to exercse dscreton n reportng earnngs. We measure these two concepts both wth current accruals (=AQ, AQ,4 ) that arse from operatng actvtes, and total accruals (=AQ 5, AQ 6 ) that nclude accruals from both operatng and fnancng actvtes. We scale the accruals as per the orgnal papers. Then, as defned n Table 2, we construct a composte measure of accountng precson from the sx AQ measures to elmnate potental measurement error. We rank each measure across all countres and take the mean of the sx ranks as a composte country ndex of accountng precson. Ths s our country-based measure of the precson of the publc sgnal. 12 Table sorts the countres n ascendng order based on the composte ndex, wth lower scores reflectng hgher accountng precson. All sx ndvdual measures exhbt large varaton across countres, but smlar rankngs n terms of relatve magntudes. The magntudes of the measures conform to pror lterature (Bhattacharya et al. 200, Table I and III; euz et al. 200, Table II), wth small dfferences due to dfferent sample perods. The crss models n Secton 2 have a specfc precson threshold at whch selffulfllng belefs are feasble. We therefore need to partton the sample based on ths precson threshold. Because the models offer no gudance on how to translate the analytcal precson threshold to the data, we dchotomze the sample at the medan nto countres wth hgh and low accountng nformaton precson (Table ) In Secton 5, we report the robustness of our man results to alternatve measures of accountng precson. 1 We test the robustness of the results to alternatve dchotomes n Secton 5 and show that countres near the threshold boundary are not drvng the results. 1

15 In-sample rankng can dstort the relatve rankng of our 21 crss countres f accountng precson makes countres more (or less) prone to crses. ence, we reexamne the accountng precson rankng of the 21 sample countres after ncludng 27 addtonal countres that dd not suffer any crss. Untabulated results show that ncludng the 27 countres has a mnor effect on the relatve rankng of the 21 sample countres. In partcular, the expanded sample places 10 of our 21 sample countres n the upper half of accountng precson. In addton, wth some exceptons, such as Australa, the country classfcaton of hgh and low accountng precson groups confrms pror studes that suggest that nsttutonal characterstcs (a Porta et al. 1997) and enforcement of contracts (Ball et al. 2000) are related to the accountng nformaton envronment. For example, Table shows hgh ranks for European countres, such as Denmark, Fnland, Span, and Sweden, whereas developng countres lke Argentna, Brazl, and Greece rank among the countres wth low accountng precson. The fact that some countres from common law orgn are classfed n the low precson group (e.g., Malaysa and Thaland) s consstent wth Ball et al. (2000), who argue that common law nfluence does not guarantee accountng nformaton qualty when the enforcement of legal contracts s weak. In the followng secton, we drectly examne the relatonshp between our measure of accountng precson and varous nsttutonal characterstcs..2.2 Sources of varaton n accountng precson across countres and over tme In Table 4, we drectly examne the relatonshp between our accountng precson measures and varous proxes for the legal and nsttutonal envronment culled from pror lterature. Table 4, Panel A shows the country ranks of each nsttutonal varable sorted by the level of accountng precson. We use the well-known ant-drector ndex (Djankov et al. 2008; a Porta et al. 1998) and credtor rghts aggregate score (Djankov et al. 2007; a Porta et al. 1997) to proxy for the level of nvestor protecton (EGA c ). To address the frequently made pont that t s law enforcement rather than the rules that defne the legal envronment, we also examne varous measures of law enforcement 14

16 from the pror lterature. The enforcement varable (ENFORCE c ) s a combnaton of the rule of law ndex from the Internatonal Country Rsk Gude and debt contract enforcement measure from Djankov et al. (2006). Fnally, we collect the measure of dsclosure qualty (DISCOSE c ) from a Porta et al. (2006). The correlatons n Table 4, Panel B show that accountng precson s ndeed postvely correlated wth the qualty of legal nsttutons and levels of law enforcement. Specfcally, the accountng precson measures (AQ c ) show a strong postve assocaton wth level of enforcement (ENFORCE c, = 0.505). owever, the legal rule tself (EGA c, = 0.067) s weakly correlated. One possble explanaton for ths weak correlaton s the addtonal varaton n accountng precson due to frm-level ncentves, such as nvestment opportuntes, external fnancng, and ownershp structure (Durnev and Km, 2005). Fnally, the DISCOSE c measure s postvely assocated ( = 0.226) wth our accountng precson measure, provdng addtonal construct valdaton. We aggregate each of our AQ c measures across frms and across tme to create country specfc measures. owever, accountng polces themselves can evolve n response to crses (Angeletos et al. 2006; Angeletos et al. 2007). As countres mplement such rule changes, temporal shfts n the cross-secton of accountng precson can occur. We drectly examne our precson measures tme seres stablty wth AR(1) correlatons. Table 4, Panel C shows the AR(1) tme seres correlaton for each AQ measure for 21 countres spannng the years 1981 to Across all AQ measures, the assocaton between each AQ measure n successve, non-overlappng sub-perods of three or fve years s sgnfcantly postve, suggestng that the accountng precson s persstent --- t s nsttutonally dffcult to change accountng rules and enforcement quckly (unlke, say, monetary polcy nstruments lke nterest rates). Indvdual accountng rules may change, but overall accountng precson s unlkely to change rapdly n a country. That sad, the three year AR(1) correlatons are much stronger than the fve-year AR(1) correlatons, suggestng that the fve-year shfts n the data are more substantve. We therefore repeat our man analyses wth the fve-year aggregaton perod. 15

17 . Macroeconomc eadng Indcators n Pror terature The general concluson n the crss predcton lterature s that an effectve warnngs system should consder a large varety of ndcators (Kamnsky and Renhart 1998). We adopt the leadng ndcators proposed n Kamnsky and Renhart (1998, Table IVA) and Edson (200, Table V). Followng Edson (200), we group the lst nto fve major categores: current account ndcators, captal account ndcators, real sector ndcators, domestc fnancal ndcators, and global ndcators. Table A2, Panel A provdes defntons for all seventeen leadng ndcators, ther data sources (prmarly the Internatonal Fnancal Statstcs), and the predcted drecton of changes pror to a currency crss. All ndcators are defned as a percentage change from the prevous year, except for the ndcators that already measure devaton from a trend. 14 The descrptve statstcs for all the leadng ndcators are reported n Table A2, Panel B. Some leadng ndcators have extreme values. The extreme values for the currency overvaluaton varable are from Indonesa and Mexco durng perods of hgh nflaton. The extreme values for excess real M1 balances are due to EU countres that experenced a dscontnuty n M2 measures n To ensure that these extreme observatons do not domnate our emprcal tests, we repeat all emprcal tests excludng these two varables and fnd smlar results. Table A2, Panels C and D provde descrptve statstcs for each leadng ndcator varable across dfferent countres, along wth addtonal country nformaton, sorted by the countres accountng precson. A comparson of the cost of crses, measured by foregone outputs as well as the actual loss of reserves ncurred n defendng the speculatve attack (Bordo et al. 2001), ndcates that countres wth low accountng precson appear to have suffered more severe crses. Countres wth low accountng precson also tend to have hgher nflaton and GDP growth over the sample perod. Gven that volatle and unstable countres are more lkely to have nsttutonally weaker accountng regmes (e.g., Ball et al. 2000), ths table provdes addtonal support for our accountng precson partton method. 14 The two ndcators are excess real exchange rate and excess real M1 balances. 16

18 .4 Realzed Accountng Fundamentals avng descrbed the precson of the publc accountng nformaton, we now turn to measurement of the nformaton tself. Table 5 provdes defntons of the three accountng sgnals we use to operatonalze the realzaton of fundamentals. These measures are a) accruals, b) accountng earnngs or profts, and c) volatlty of earnngs. These measures are partcularly well suted to the global-games noton of fundamental strength because hghly proftable enttes lkely have lower demand for nterm external fnancng. Note that our measures pertan to operatons because our prmary object of nterest s asset fundamentals, not nvestor propensty to contnue fnancng. 15 We obtan the medan of each measure separately for each country year and nomnate t as the countrywde measure for that year. The three measures we choose are wdely recognzed as key accountng measures of frm performance (Dechow 1994; Dechow and Schrand 2004). In partcular, Dechow (1994) shows that nvestors perceve accountng earnngs to be a more mportant performance measure than operatng cash flows. More detaled accountng measures and ratos may not be equally vald across a dverse set of frms and countres, and also have lmted data avalablty. Realzed Accountng Sgnal: Operatng Accruals: The frst accountng sgnal we employ, Accruals t, represents the adjustment to cash flows to yeld accountng earnngs (all based on operatng actvtes). These adjustments play a key role n reportng frm performance, especally n tmes of rapd downturns and upturns, for cash flows are not yet affected. For example, frms may wrte off nvestments and accounts recevables n downturns. kewse, n upturns, frms may recognze revenue before the cash flows from customers have materalzed. Recent studes such as rshlefer et al. (2009) fnd that, at the aggregate level, accruals are postvely assocated wth growth and future 15 The termnal asset value n global games models depends both on current operatng fundamentals and nvestor propensty to provde the requste refnancng. For a study that emprcally dstngushes the frst factor from the second n a manner smlar to ours, see Andrade and Kaplan (1998). 17

19 performance. We therefore expect accruals to be large and negatve pror to a downturn or crss. Our focus on operatng accruals has substantve precedence n the valuaton lterature (e.g., Dechow et al. 1995; Fama and French 2006; Jones 1991; Sloan 1996). In addton to changes n current operatng assets and labltes, our defnton of operatng accruals ncludes the reversal of certan non-current operatng asset accruals by subtractng deprecaton and amortzaton. We compute accruals from balance sheet and ncome statement nformaton, and then compute cash flows as operatng ncome mnus accruals. We do not use the cash flow statement to compute accruals because of lmted avalablty of cash flow nformaton across countres and tme. Table 5, Panel B ndcates that the mean of accruals s -0.01, smlar to Sloan (1996, Table I) who reports accruals of Note that accruals, although aggregated n an entrely dfferent manner, also form the bass of our measure of the precson of accountng nformaton. Although the emprcal measure s dentcal, t s mportant to note that we mplement the two n very dfferent ways. The level of accrual as a proxy for accountng precson captures the varaton across countres. On the other hand, the accruals level as a sgnal for fundamentals s employed to capture wthn-country varaton over tme. Therefore, our defnton of accruals as an accountng fundamental apples only wthn each country. Realzed Accountng Sgnal: Operatng Proftablty: Operatng proftablty, or operatng earnngs, requres lttle motvaton. We defne operatng proftablty as the country medan of frm-level net operatng ncome scaled by begnnng total assets. Table 5, Panel B ndcates that operatng profts average a reasonable 8.5% of assets. Realzed Accountng Sgnal: Earnngs Volatlty: Followng studes such as Rancere et al. (2008), whch mplcate hgher moments as the predctors of crses, we nclude volatlty of the reported earnngs as our last accountng sgnal. Volatlty s the standard devaton of operatng ncome (scaled by begnnng total assets) over a threeyear, backward rollng wndow. Crses are troubled perods wth hgh uncertanty; we therefore predct a postve assocaton between crss onset and earnngs volatlty. 18

20 .5 Correlatons Table A, Panel A presents the correlaton matrx of all crss predctors ncludng accountng sgnals and leadng ndcators from pror lterature. Smple examnaton of the correlaton ncreases our confdence n the valdty of our measures. For example, ndustry output s postvely correlated wth equty prces (= 0.4, Spearman), and commercal bank depost s postvely assocated wth domestc real nterest rates (= 0.4, Spearman). Also, the assocatons of our accountng sgnals are plausbly sgned: accruals and proftablty show a postve relaton (0.7, Spearman). More mportant, there appears to be lttle evdence of multcollnearty; our three accountng sgnals thus capture dfferent dmensons of realzed fundamentals. Table A, Panel B presents the tme seres correlaton of all three accountng sgnals. The assocaton of the contemporaneous and lagged accountng measures s stable. For example, the correlaton between Proftablty t-2 and Proftablty t-1 (= 0.549, Spearman) s close to the correlaton between Proftablty t-1 and Proftablty t (= 0.559, Spearman). More mportant, the AR(1) effect n the realzed accountng fundamental measures s sgnfcant. Our emprcal tests therefore ncorporate varous lead-lags of the realzed accountng fundamentals to get a better understandng of the predctve tmng effects. We turn to these tests next. 4. Results 4.1 The Story n Pctures We frst present a graphcal representaton of the movements n accountng sgnals for the perods leadng up to and mmedately followng a currency crss. Followng Echengreen et al. (1995), we compare the behavor of each accountng sgnal durng tranqul perods as well. Fgure 1 reports the movement n accountng sgnals three years before and after the 9 currency crses. The horzontal axs represents the number of years before and after 19

21 the crss (or tranqul) year. The bands represent the upper and lower 25% quartles of the realzaton of each accountng sgnal. Accountng sgnals show much movement durng crses, especally for low accountng precson countres. Profts declne for these countres. Accruals do so as well, and enter negatve terrtory, suggestng consderable wrte-offs. Volatlty of proft ncreases as predcted. By contrast, n the tranqul years the data are ndeed tranqul across both sets of countres, suggestng that the movement durng crss years s not entrely spurous. The unvarate nature of the fgures necesstates cauton n any nference. For example, the movement of accountng sgnals n low precson countres also comes wth larger confdence ntervals. We therefore turn to multvarate analyss of the data. 4.2 Multvarate Analyss of Crss Predcton We examne the relaton between accountng varables and the occurrence of a currency crss n a regresson framework. Our unt of observaton s a country-year. The majorty of the early warnngs lterature takes the sgnals approach (Kamnsky and Renhart 1998), where ndcators ssue a sgnal whenever they move beyond a certan threshold. owever, our ablty to estmate the optmal threshold s mpared by the lmted frequency of annual accountng data. Thus, we use multvarate probt models as n Frankel and Rose (1996) to test the n-sample statstcal power of accountng sgnals to predct currency crses. Berg and Pattllo (1999) also use the probt model to assess the out-of sample performance of bnary ndcators, and fnd that the probt model outperforms the sgnal approach n terms of scores and goodness-of-ft. We estmate the followng probt model for the full sample of country-years. We nclude country fxed effects, a common tme trend, and contemporaneous cross-sectonal correlatons. Table 6 reports the results for varous lead-lags n the full sample. The coeffcents represent the margnal effect averaged over all observatons. Results show that accountng sgnals two years pror have no ablty to predct crss onsets. owever, the 20

22 stuaton s dfferent for a one-year lead. Accountng sgnals are now collectvely sgnfcant, and the F-statstc for the three accountng measures s (p-value <0.001). Goodness-of-ft, measured usng McFadden s pseudo R-square, ncreases from to 0.28 wth the ncluson of accountng sgnals. 16 Fnally, contemporaneous accountng sgnals n the last column are also sgnfcant. owever, because the crss has already occurred, ths sgnfcance could partally reflect the toll of the crss on frm performance. Interestngly, Table 6 shows that many of the leadng ndcators also do not have statstcally sgnfcant coeffcents. Among the leadng ndcators, some domestc fnancal varables, such as commercal bank depost and Excess real M1 balances, appear to be statstcally sgnfcant n the predcted drecton. On the other hand, coeffcents of real nterest rate dfferental, domestc real nterest rate, and lendng/depost rate show reverse sgns. 17 Ths s consstent wth the early warnngs systems fndng that even the best model has lmted predctve power (Kamnsky and Renhart 1998, Table I). 4. The Accountng Precson Dchotomy We now compare coeffcents across the two groups of accountng precson n two ways. We frst specfy the followng stacked probt model: 18 k k D_ crss [I Acc.Sg. ] [I Acc.Sg. ] ead.indc. (1) I I ) s an ndcator equal to 1 when the crss s n a country wth hgh (low) C t C tn C tn tn c.t 1 1 k1 ( C 18 accountng precson and 0 otherwse (there s no ntercept term). The coeffcents 16 Snce McFadden s pseudo R-square can ncrease even wth an ncluson of rrelevant varables, we also assess the model s explanatory power usng adjusted-mcfadden s R-square. Unreported results show that ncludng accountng sgnals one year pror to the crses ncreases adjusted-mcfadden s R-square by 8%. 17 Ths fndng s consstent wth other emprcal research n the early warnngs system lterature. In partcular, Edson 200 (Table XIV) fnds that the real nterest dfferental and real nterest rates have the lowest probablty of ssung a sgnal durng the 24-month perod pror to a crss. 18 See Maddala (2001) for a dscusson of stacked regressons. Under the assumpton that the error terms from each regresson have the same dstrbuton, ths technque captures any (potental) correlatons across the error terms. Stackng also allows statstcal tests of coeffcents across the stacked equatons. 21

23 ( ) measure the assocatons between accountng sgnals from countres wth hgh (low) accountng precson and the onset of a crss. Panel A of Table 7 presents the results of the probt estmatons. As n Table 6, accountng sgnals two years n advance have no power to predct crses. owever, the one-year pror F-tests clearly show that accountng sgnals have more statstcal power to jontly predct crses among countres wth low accountng precson. In partcular, the power of n-sample predcton power of realzed accountng sgnals s sgnfcant for low accountng precson countres (F-stat = 14.17, p-value = 0.00), and nsgnfcant (F-stat = 1.1, p-value = 0.726) for hgh precson countres. Ths s precsely the predcton of models such as Angeletos and Wernng (2006). An alternatve explanaton for the nsgnfcance of the accountng sgnals n the hgh precson countres s lack of power. The aftermath model n the last column of Table 7, Panel A dspels ths possblty. For the frst year followng the onset of a crss, the accountng sgnals appear to be jontly sgnfcant for both the hgh (F-stat= 26.62, p- value< 0.001) and low (F-stat= 17.67, p-value< 0.001) accountng precson sub-samples. Accountng sgnals n hgh precson countres thus reflect the consequences of crses: they smply cannot predct them. In Panel A of Table 7, coeffcent estmates of all other leadng ndcators are restraned to be dentcal for the hgh and low accountng precson countres. ence, the dfferental explanatory power of accountng sgnals could be capturng the dfferent predctve power of other leadng ndcators n each sub-sample of hgh and low accountng precson countres. Therefore, n Panel B of Table 7 we repeat the estmaton of equaton (1) after separatng the sample nto hgh and low accountng precson countres. Estmatng the predcton model separately for each group of hgh and low accountng precson countres allows the coeffcent estmates to vary for every regressor. Our man result contnues to hold. The predctve power of realzed accountng sgnals s sgnfcant for low accountng precson countres (F-stat = 20.81, p-value < 0.001), and nsgnfcant (F-stat = 1.49, p-value = 0.684) for hgh precson countres. As before, n 22

24 the frst year followng the onset of a crss, the accountng sgnals are jontly sgnfcant for both groups Understandng the predctve power of each accountng sgnal The ndvdual coeffcents of the realzed accountng sgnals n Table 7 lend themselves to the followng nterpretaton. oldng profts constant, low accruals n low precson countres are a sgnfcant harbnger of crses. That s, holdng profts constant, the composton of profts based on accountng adjustments matters. 19 On the other hand, holdng accruals constant, proftablty n low precson countres s postvely sgnfcant. One explanaton s that pror-year cash flows are stll boomng (and ths s precsely what Rancere et al suggest), causng total accountng profts to ncrease before the crss even though frms are antcpatng the slowdown n ths proft boom and makng the necessary accountng adjustments. But once the crss hts, ths boom dsappears. Commensurately, the proftablty n crss years (Table 6) does sgnfcantly declne. To further explore the nformaton content of accruals n low precson countres, we decompose the accruals nto the respectve asset and lablty components. Intutvely, operatng accruals declne f there s a large reducton n assets and/or ncrease n current labltes. For example, when managers wrte-off assets (e.g., obsolete nventory or doubtful recevables) or decrease ther nventory buldup, accruals declne. Also, advancng cash recepts from customers (.e., deferred revenue) wll lead to greater current labltes and a declne n accruals. Table 8 examnes the explanatory power of each accrual component pror to a crss. Followng Rchardson et al. (2005), we decompose accruals nto current operatng asset (ΔCA), current operatng lablty (ΔC), and deprecaton We defne each accrual sgnal as the country-year medan of the respectve frm-level accrual components. Therefore, the three accrual components do not add up to total accruals across each 19 Table A4 supports the robustness of these fndngs n regressons that nclude accruals and profts separately. 20 Due to data lmtaton, we only nclude a subset of non-current operatng accruals by subtractng deprecaton expense. In other words, we gnore the orgnaton of non-current accruals.