Distortions in Firm Selection During Recessions

Transcription

1 LUISS Gudo Carl School of European Poltcal Economy Dstortons n Frm Selecton Durng Recessons A Comparson Across European Countres Fabo Landn Workng Paper 4/2016

2 LUISS Gudo Carl / School of European Poltcal Economy Workng paper n. 4/2016 Publcaton date: October 2016 Dstortons n Frm Selecton Durng Recessons: A Comparson Across European Countres 2016 Fabo Landn ISBN Ths workng paper s dstrbuted for purposes of comment and dscusson only. It may not be reproduced wthout permsson of the copyrght holder. LUISS Academy s an mprnt of LUISS Unversty Press Pola s.r.l. a soco unco Vale Pola 12, Roma Tel e- mal lup@luss.t Edtoral Commttee: Leonardo Morlno (char) Paolo Boccardell Matteo Carol Govann For Danele Gallo Ncola Lupo Stefano Manzocch Guseppe Mels Marcello Messor Ganfranco Pellegrno Govann Pccrll Arlo Polett Andrea Prencpe Petro Rechln

3 Dstortons n Frm Selecton Durng Recessons: A Comparson Across European Countres Fabo Landn School of European Poltcal Economy LUISS Unversty Italy ICRIOS Boccon Unversty Italy October 2016 Abstract Recent evdence documents the weakness of market selecton based on productvty dfferentals and the absence of cleansng durng recessons. Ths paper argues that a possble explanaton les n the role of compettve rents,.e., market advantages due to dosyncrases of the frm s demand. Compettve rents allow frms to sustan proft ndependently of ther nternal effcency, creatng a selecton advantage. Durng an economc recesson, ths advantage ncreases because compettve rents operate as a reslence factor. The process of frm selecton can thus be dstorted wth relatvely neffcent frms that manage to survve. These predctons are tested on a sample of French, Italan, and Spansh manufacturng frms, lookng at the selecton that took place durng the Great Recesson. Ceters parbus, frms wth compettve rents are less lkely to ext than frms wthout compettve rents. Ths effect s stronger n countres more severely mpacted by the downturn. The mplcatons of these results for polcy nterventons to sustan aggregate productvty growth are dscussed. Keywords: frm selecton, proft, productvty, compettve rents, Great Recesson. JEL codes: D24; L11; L25. 1

4 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/ Introducton Startng from late 2008 the Eurozone has experenced a prolonged perod of economc recesson (the so- called Great Recesson), whch only recently s gvng way to weak sgnals of recovery. The European Unon (EU) polcy makers have thus devoted ncreasng attenton to practcal ways of sustanng productvty growth, especally n the EU perphery. The economc lterature usually nforms these ntatves by relyng on models that attrbute an mportant role to processes of frm selecton based on productvty dfferentals (Jovanovc, 1982; Hopenhayn, 1992; Meltz, 2003; Asplund and Nocke, 2006; Meltz and Ottavano, 2008). In these models aggregate productvty movements orgnate from the reallocaton of market shares to more effcent producers, ether through market share shfts or through entry and ext. Frms wth hgh productvty levels are more lkely to survve and grow than ther less effcent counterparts, creatng selecton- drven aggregate productvty ncreases. Therefore, the theores pont to the exstence of a drect productvty- survval lnk as a crucal drver of productvty growth (Foster et al., 2008). The theoretcal approaches underlyng these vews and the related polcy recommendatons, however, are dffcult to reconcle wth two emprcal facts. The frst one concerns the exstence of wdespread and persstent wthn- ndustry heterogenety n frm performances. Syverson (2004), for nstance, shows that wthn four- dgt SIC ndustres n the U.S. manufacturng sector, plant n the 90 th percentle of the productvty dstrbuton makes on average twce as much output wth the same measured nputs as the 10 th percentle plant and these dfferences are persstent. Smlar results have been obtaned for several European countres (Bartlesmam et al., 2013) as well as for Chna and Inda, wth average productvty rato that n the latter two cases reach over 5:1 (Hseh and Klenow, 2009). Hgh and persstent varablty exsts n other frm- level measures as well, such as frm sze (Bottazz et al., 2007; Dos, 2007) and ntangble nvestments (Arrghett et al., 2014). In sum, n almost every ndustry and country one observes few hghly productve and nnovatve frms that co- exst wth many relatvely neffcent compettors. Ths evdence contrasts wth the vew of markets as accurate selectve envronments: f long tals of relatvely neffcent frms can persstently survve, one should conclude that selecton based on productvty dfferentals works at best mperfectly (f workng at all). 1 The second emprcal fact that contrasts wth a drect productvty- survval lnk s related to the effect of economc recessons. If hghly productve frms enjoy a selecton advantage durng upturns of the busness cycles, ths advantage should become even greater durng downturns, when addtonal compettve pressure drves unproductve arrangements out of busness, freeng up resources for more productve uses. Such cleansng effect, whch dates as far back as Schumpeter (1939), features promnently n several economc models (Hall et al., 1995; Caballero and Hammour, 1994; Gomes at al., 2001). In ths case too, however, the avalable evdence partally contradcts the hypotheszed effect. Some recent papers hghlght that rather than cleansng, recessons can scar the economy and destroy relatvely productve frms (Barlevy, 2002; Ouyang, 2009; Hallward- Dremeer and Rjkers, 2013). Certanly ths 1 Several studes usng the between component n the decomposton of productvty change as a proxy for selecton dynamcs fnd that the reallocaton pressure due to dfferental productvtes operates very slowly and sometme s even perverse. Accordng to Bottazz et al. (2010: 1955) when the between component has the expected postve sgn, dosyncratc learnng (the wthn term) generally offers a comparatvely larger contrbuton to productvty growth. Moreover, some studes fnd not sgnfcant (Baldwn and Gu, 2006) and even negatve between effect (Dsney et al., 2003), whch suggests that reallocaton can go n favour of less productve plants or frms. 2

5 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 sullyng effect cannot be general and may depend on the specfc nature of recessons. Nevertheless, Foster et al. (2016), Kehrng (2015) and Callgars et al. (2016) suggest that durng the Great Recesson the sullyng effect has been predomnant, wth wthn- ndustry dsperson n productvty levels that has on average ncreased. Ths evdence suggests that more research nto the process of frm selecton s needed, especally durng recessons. How do we make sense of the prolonged survval of relatvely neffcent frms n almost every ndustry and country? Why are recessons unable to purge these neffcences out of the system? The answer matters for polcy: dependng on the explanaton gven for the weakness of the cleansng mechansm, dfferent polcy recommendatons to sustan productvty growth may follow. Ths paper nvestgates the nature of dstortons n the process of frm selecton durng the Great Recesson. In dong so t contrbutes to the lterature that nvestgates devatons from effcency- enhancng selecton dynamcs durng recessons. Barlevy (2002, 2003), for nstance, suggests that durng downturns the cleansng effect can be reversed n presence of credt market mperfectons, because effcent frms may be hurt dsproportonally due to ther hgher fnancal needs. Ouyang (2009) focuses on the uncertanty surroundng a frm s real qualty and argues that recessons may worsen resource allocaton because they destroy potentally superor frms durng ther nfancy. A seres of papers also suggest that labour market regulatons and polces governng frm dynamcs can be partcularly relevant n dstortng the process of frm selecton n presence of negatve shocks, because they allow relatvely neffcent frms to survve (Haltwanger et al., 2008; Coller and Goders, 2009; Hallward- Dremeer and Rjkers, 2013). Compared to these contrbutons the present paper provdes an alternatve, and to some extent complementary, explanaton. Based on the recent and growng lterature on demand factors as determnants of ndustry dynamcs (e.g. Foster et al., 2008, 2016) the paper suggests that, rather than by mperfectons on the market for nputs or uncertanty, the weakness of the cleansng effect can be explaned by demand dosyncrases. The latter may derve from dfferent factors such as specfctes of nche and local markets, long- term buyer- suppler tes as well as market protecton. In all these cases frms wth postve demand dosyncrases enjoy compettve rents, whch allow them to sustan proft ndependently of ther nternal effcency. In presence of an economc recesson such addtonal proft strengthen the frm s capacty to resst the shock and thus create a selecton advantage. Frms wth large compettve rents can survve despte of ther relatve neffcency and the cleansng effect s ultmately attenuated. To provde some structure to the above argument I present a two- stage entry and producton model where frms dffer along two dmensons: productvty and compettve rents. The basc structure of the model s taken from Foster et al. (2008). Startng from the same long- perod equlbrum I study what happens when a negatve shock ht the economy, reducng the proft of all frms. The model yelds two man predctons: a) after the negatve shock frms wth large compettve rents are more lkely to survve than frms wth low compettve rents; and b) the selecton advantage of frms wth large compettve rents gets larger the stronger the shock (.e. the more severe the recesson). The predctons of the model are tested on a sample of European manufacturng frms taken from the EFIGE- Amadeus matched dataset. Data refers to selecton processes takng place durng the Great Recesson. The latter s well suted to ths am because t was both a deep and relatvely unexpected recesson, especally for the European manufacturng sector. Moreover, although global n nature, the Great Recesson had a heterogeneous mpact across countres, 3

6 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 whch can be exploted to estmate ts effect on frm selecton. Due do data avalablty the analyss s restrcted to three countres: France, Italy and Span. Overall, the emprcal analyss provdes results that are consstent wth theoretcal predctons. Frms wth compettve rents enjoy a selecton advantage and ceters parbus are less lkely to ext than frms wthout compettve rents. Moreover, the sze of the selecton advantage s stronger n the countres that were more severely ht by the downturn,.e. Italy and Span relatve to France. Ths work contrbutes to several streams of research. Frst, t extents the lterature on demand- related ndustry dynamcs (e.g. Foster et al., 2008, 2016) by focusng on the role that demand dosyncrases and the related compettve rents play n dstortng the process of frm selecton durng recessons. Second, the paper makes a contrbuton to the lterature on the cleansng vs. sullyng effect of recessons (e.g. Barlevy 2002, 2003; Ouyang, 2009; Haltwanger et al., 2008; Coller and Goders, 2009; Hallward- Dremeer and Rjkers, 2013) by hghlghtng that, alongsde supply factors, there can be also demand factors that help explanng the lack of cleansng durng downturns. Fnally, at a more general level, the argument developed n ths paper opens new lnes of research concernng the determnants of frm selecton n market economes. In partcular, the paper provdes a possble explanaton for the recent fndngs that show that market share reallocaton s slower and less systematc that t s assumed n most selecton- based theores of competton (e.g. Coad, 2007; Bottazz et al., 2010; Dos et al., 2015). From a polcy perspectve the results have two man mplcatons. Frst, alongsde nterventons that am at strengthenng the flexblty of nput markets (whch s the current focus to mprove resource allocaton), polcy makers should devote more attenton to polces that foster frm competton and elmnate the sources of compettve rents (be ether physcal such as transportaton costs or nsttutonal such as long- term buyer- suppler tes). In fact, even n presence of nput flexblty, frms wth compettve rents can contnue to operate ndependently of ther relatve neffcency, retanng resources that could be freed up for more productve uses. Second, the fact that the selecton dstorton due to compettve rents s more acute n the countres that are severely ht by the downturn mples that recovery can be partcularly dffcult n those contexts. In partcular, the effect of standard market- based economc nterventons can be weakened and non- standard polcy nterventons may be needed. The paper s organzed as follows. The next secton dscusses the theoretcal framework and derves the model predctons. Secton 3 presents the data and varables used n the emprcal analyss. Secton 4 dscusses some descrptve statstcs on compettve rents. Secton 5 shows the results on the frm- level determnants of ext durng the Great Recesson. Secton 6 dscusses the polcy mplcatons. Secton 7, fnally, concludes. 2. Theoretcal framework 2.1 Productvty, proftablty and frm selecton Does frm selecton depend on productvty or proft? Although ths queston may seem trval, there are reasons to beleve t s not. Accordng to well- establshed streams of research n the economc lterature proft s the man drver of frm survval. Ths s the case n the Schumpeteran framework, where the proft surplus ensured by successful nnovatons s what leads more nnovatve frms to thrve and less nnovatve frms to shrnk and eventually ext the market (Schumpeter, 1934, 1939). Ths same vew s shared by the more recent Neo- 4

7 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 Schumpeteran tradton, whch expands the sources of proft varaton across frms to nclude also routnes and capabltes (Nelson and Wnter, 1982). Fnally, the fact that frm selecton s on proft s a common assumpton n most canoncal models of ndustry dynamcs wth dfferentated producers (Jovanovc, 1982; Hopenhayn, 1992; Meltz, 2003; Asplund and Nocke, 2006; Meltz and Ottavano, 2008). Nevertheless, most of the scentfc and polcy debates on the determnants of frm selecton concentrate on productvty and not proft. The reason for ths s twofold. On the one hand the majorty of formal models takes productvty as the sngle dosyncratc factor that explans the persstent heterogenety of frm proft. As a result whle the models stck to the assumpton of a proft- survval lnk, productvty often becomes the unque dosyncratc factor that entrely medates such lnk (Foster et al., 2008). On the other hand a large number of emprcal contrbutons has documented that frms wth hgher measured productvty levels tend to grow faster and are more lkely to survve than ther less productve ndustry cohorts (for a comprehensve survey see Syverson, 2011). These results have favoured the vew accordng to whch the productvty- survval lnk s a good approxmaton of how frm selecton actually takes place. However, none of these vews s exempt from crtques. Wth respect to the sources of proft heterogenety, Foster et al. (2008) ponts out that productvty s only one of several possble dosyncratc factors that determne profts, a key alternatve beng demand dosyncrases. In presence of hgh enough transportaton costs, for nstance, frms wth prvleged access to local markets that happened to be characterzed by partcularly hgh demand are lkely able to set hgher prces (or sell more at a gven prce) than frms n low- demand markets. Ths dosyncratc spatal dfferentaton may thus translate nto hgh proft dfferentals that are however unrelated to frms producton effcency. A smlar result can obtan n presence of hstory- laden and customzed relatonshps between supplers and ther consumers. For example, some consumers may decde to enter nto a contract wth a specfc suppler because of some match- specfc factor (e.g. past hstory wth the same suppler, customzaton), rather than the suppler s product beng consdered superor by all possble consumers. In ths case too, just as wth spatal dfferentaton, such suppler benefts of a market power that s ndependent of ts productvty but nevtably affects proft. Other factors that may produce smlar results nclude poltcal connectons (Cngano and Pnott, 2013) and more generally dfferent forms of market protectons. In addton to the sources of proft heterogenety also the emprcal evdence on the relatonshp between productvty and survval presents some weakness (Maresse and Jaumandreu, 2005; Katayama et al., 2009). Most of the research usng busness mcrodata to measure productvty lacks nformaton on frm- level prces. As a consequence frm output s measured as revenue dvded by a common ndustry- level deflator, wth the result that prce dfferences are emboded n the measures of productvty. However, f prces reflect dosyncratc demand shfts or market power rather than dfferences n output qualty or effcency, then frms wth hgh measured productvty levels may not be partcularly effcent. Under these condtons, the postve relatonshp between the measured productvty and frm survval should be treated as evdence of selecton on proft, but not necessarly productvty (Foster et al., 2008). Startng from these consderatons a growng lterature has began to document how demand- related factors nteract wth productvty and proft to shape ndustry dynamcs. Foster et al. (2008) use establshment- level data on a set of eleven US commodty- lke products to show that demand dosyncrases are a domnant factor as opposed to output- based productvty 5

8 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 measures n determnng frm survval. By relyng on smlar data, Foster et al. (2016) nvestgate why new busnesses are typcally smaller than ther establshed ndustry compettors and show that these patterns reflects more dfferences n demand- sde fundamentals than productvty gaps. Smlar contrbutons wth a focus on demand- sde effects on frm s growth and survval nclude Das et al. (2007), Eslava et al. (2008), Kee and Krshna (2008), De Loecker (2011), Roberts et al. (2011), Pozz and Schvard (2012) and De Loecker and Goldberg (2014). None of these contrbutons, however, studes the effect of demand dosyncrases on the process of frm selecton durng recessons. Ths s precsely the am of the next secton. 2.2 A smple model In ths secton I present a two- stage entry and producton model provdng some ntutons on how dosyncratc productvty and demand factors can dstort the process of frm selecton durng recessons. The model s a smplfed verson of the one presented by Foster et al. (2008). Lke them I abstract from dynamcs so that the results can be nterpreted as hghlghtng selecton effects takng place across long- run equlbra. Moreover, I consder the same demand system, whch combnes product dfferentaton wth demand dosyncrases at the frm level. Although smple, the model makes t possble to derve testable predctons. The qualtatve features of the results hold usng other demand structures as well. An ndustry conssts of L (>0) consumers and a contnuum of frms of measure N (>0). Frms are ndexed by I, where I s the set of frms. Each frm supples a dstnct varety of the ndustry product. Preferences are defned over varetes and a homogeneous good chosen as numerare. All consumers share the same utlty functon, whch s gven by U = y + C 1 2 C 1 C ( + δ ) q d η( q d) γ ( q ) I I α d (1) 2 2 I 2 C where y and q are the consumpton level of the numerare and each varety, respectvely. The parameters α (> 0) and η (> 0) are standard demand shfters of dfferentated varetes relatve to the numerare. The parameter γ ( 0) captures the extent to whch varetes are dfferentated. When γ s hgher consumers experence a greater utlty loss from consumng C dosyncratcally large or small quanttes of any q and product dfferentaton ncreases. As γ C C 0 consumers only care about ther consumpton level over all varetes, Q = q d, and I substtutablty becomes perfect. For a smlar approach to the modelng of product dfferentaton see Melltz and Ottavano (2008). The most mportant feature of the utlty depcted n equaton (1) s parameter δ. The latter s a varety- specfc mean- zero taste shfter, whch shfts demand for varety relatve to α. The actual value of δ reflects demand dosyncrases that can be due to several factors, such as specfctes of nche markets, long- term buyer- suppler tes as well as market protecton (see above). In all these cases frms enjoyng a postve δ have some degree of market power, because they are able to set hgher prces, or sell more at a gven prce, than those wth zero or negatve δ. In ths sense δ reflects what I defne as a demand- based compettve rent. The role 6

9 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/ played by such compettve rent n the process of frm selecton s the man focus of the analyss. For all goods consumed n postve quanttes (.e. 0 > C q ), utlty maxmzaton mples the followng nverse demand functon for each varety C C Q q p η γ δ α + =. (2) Equaton (2) can be shown to mply that frms face the followng lnear market demand (see Foster et al., 2005, Meltz and Ottavano, 2008): C L L N N p L N N p L N L Lq q δ γ δ γ γ η η γ γ η η γ γ η α = (3) where = * ) (1/ I p d N p and = * ) (1/ I N δ d δ (wth I I * ndcatng the subset of frms whose varetes are consumed) are average prce and compettve rent among ndustry producers (notce that δ need not be zero n equlbrum). The technology s represented by a sngle- nput producton functon x q ω = (4) where x s the nput and ω ( 0) s a frm- specfc productvty. The producton nput can be purchased at a prce w, whch s assumed constant for all frms. It follows that the frm s total cost and margnal cost s respectvely q w wx TC = = ω and w MC ω =. (5) Ths settng can thus generate wthn- ndustry heterogenety along two dmensons: demand (δ) and productvty (ω). The frm s proft can be wrtten as: = w p q ω π. (6) By replacng equaton (3) nto (6) I can rewrte the proft functon as follows = w p L L N N p L N N p L N L ω δ γ δ γ γ η η γ γ η η γ γ η α π. (7) Gven the contnuum of compettors, frms maxmze equaton (7) takng as gven the average prce level p and number of frms N. Ths gves the followng optmal prce ( ) [ ] = w p N N p ω δ δ η γα γ η *, (8)

10 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 whch s decreasng n ω and ncreasng n δ. The frst effect captures the standard argument that more effcent frms enjoy a cost advantage over compettors, allowng them to set lower prces. The second effect s nstead assocated wth the explotaton of market power, whch allow frms wth compettve rents to set hgher prces. Notce that f dfferentaton s null (.e. γ=0) and compettve rents are absent (.e. δ=0 for all ) all frms set prce equals margnal cost. Substtutng equaton (8) nto (3) gves the frm s optmal quantty q * L 1 = 2γ ηn + γ [ γα + ηn( p δ )] w + δ. (9) ω Ths result neglects the fact that some goods may not be purchased at the prce gven by equaton (8). In fact, equaton (1) suggests the margnal utlty for any partcular varety s bounded at α + δ so that only varetes such that p α + δ are purchased. However, t s possble to show that any frm that s actve n equlbrum (.e., havng π 0 and q > 0) satsfes ths condton (see Foster et al., 2005). Replacng equatons (9) and (8) nto (6) gves the maxmzed proft [ γα + ηn( p δ )] π * L 1 w = + δ 4γ ηn + γ ω, (10) whch s ntutvely ncreasng n both compettve rent (δ) and productvty (ω). Provded that wthn- ndustry heterogenety n proft exsts, frms wth ether hgher compettve rents or hgher productvty (or both) wll also enjoy relatvely hgher profts and wll thus fnd t more convenent to operate. In partcular, from equaton (10) t s possble to derve a cutoff proft condton below whch frms make negatve profts and ext. The latter s gven by [ γα + ηn( p δ )] ϕ δ w 1 ω ηn + γ = 2. (11) Usng equaton (11) t s then possble to wrte the maxmzed proft n terms of the cutoff 2 * L w π = δ ϕ 4γ ω. (12) The process of entry s modeled as follows. A large set of potental entrants decdes whether to pay a sunk cost of entry s (>0). Frms who pay s receve compettve rent and productvty draws from a jont dstrbuton wth probablty densty functon f ( δ,ω). Margnal dstrbutons of δ and ω are defned respectvely over [ δ e, δ e ] and [ ω l, ω u ], where δ e < α and ω l > 0. After havng observed the draws, frms decde whether to begn producton and earn the correspondng proft as from equaton (12). Obvously, only potental entrants wth draws that satsfy the cutoff condton wll choose to produce n equlbrum. Hence, the expected value of entry V e s the expected value of (12) over f ( δ,ω) condtonal on drawngs that satsfy (11) mnus the cost of entry s. Under a free- entry condton ϕ must then set V e equal to zero, so that no new entry occurs. In other words, ϕ must satsfy V e ω L 4γ ( δ, ω) e = + w δ ϕ f dδ dω s = u ω l δ ϕ ω w ω 2 0. (13) 8

11 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 Equaton (13) summarzes the ndustry equlbrum. All frms make nonnegatve proft and entry contnues untl potental entrant frms receve productvty and compettve rent draws such that the expected value of entry s zero. In equlbrum all actve frms satsfy the cutoff condton descrbed above. The actual value of the cutoff wll depend on the dstrbuton of the compettve rent and productvty draws as well as the other parameters of the model (ncludng the equlbrum number of actve frms). Wthout loss of generalty let the value of the cutoff that satsfes equaton (13) be ϕ *. The equlbrum proft for any frm can thus be wrtten as * L ~ w * π = δ 4 ~ ϕ γ ω 2 0, (14) where ~ δ and ~ ω are s actual compettve rent and productvty draws upon entry. Startng from ths condton I study what happens to the process of frm selecton when a negatve shock hts the economy. There are many ways of modelng such shock ncludng decreases n demand and/or productvty shocks. 2 In all cases the man effect of the shock s to reduce the proft margn and thus create a tougher envronment for frm survval. To capture ths effect n a smple and ntutve way I choose to model the negatve shock as a cost ζ (>0) that hts all frms operatng n equlbrum ndependently of productvty and compettve rent. We could nterpret ζ as a generalzed ncrease n the cost of fnancng frm operatons. After the shock occurred some of the frms operatng at the lower end of the proft dstrbuton,.e. those makng small equlbrum proft, wll turn nto negatve proft and wll be forced to ext. The queston of nterest s how the combnaton of productvty and compettve rent affects such process of ext. Usng equaton (14) the new proft after the negatve shock can be wrtten as S π = L ~ w * δ ϕ γ ~ ω 4 2 ζ. (15) Clearly both compettve rent and productvty strengthen the frm s reslence to the negatve shock. In partcular, equaton (15) can be exploted to derve a productvty threshold that yelds nonnegatve post- shock proft: π 0 S ~ w * ω ~ ~ = ω * 1/ 2 (16) δ ϕ ( ζ 4γ / L) All frms whose productvty satsfes condton (16) survve after the shock. Conversely, the frms wth productvty levels below ~ * ω ext. Ths expresson yelds three results of nterest: ~* 1) ω / ζ > 0, 2) ~ * 2 ~* ω / δ < 0 and 3) ω / ζ δ < 0. The frst result suggests that the larger the negatve shock, the hgher the productvty threshold and thus the stronger the selectve pressure aganst frms wth relatvely low productvty. Ths s the standard cleansng effect hypothess, whch s therefore confrmed by the model results. The second results shows that the level of productvty that ensures survval s not the same across all frms, rather t decreases wth the compettve rent. In other words, frms wth relatvely low productvty can stll survve after the shock provded that they enjoy suffcently hgh 2 Models that are drven by demand and productvty shocks nclude respectvely Caballero and Hammour (1994) and Kehrng (2015). 9

12 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 compettve rent. Fnally, the thrd result hghlghts that the rate at whch the productvty threshold ncreases after the shock s lower the greater the compettve rents, meanng that the selectve pressure s lower for frms wth hgh compettve rent. The latter reflects what can be nterpreted as a dstorton effect n the process of frm selecton because t leads frms wth relatvely low productvty but hgh compettve rent to enjoy a selecton advantage durng recessons. Fgure 1 provdes a graphcal representaton of condton (16). The three lnes show the value of the productvty threshold as a functon of compettve rent for dfferent szes of the negatve shock, where ζ < ζ' < ζ''. As one can see, on average, the negatve shock makes the productvty thresholds more strngent, forcng low productvty frms to ext. However, whle such cleansng effect s partcularly strong for frms that exhbt relatvely small compettve rent (.e. those close to the orgn), t s weaker for frms enjoyng large rents. The latter beneft of a selecton advantage wth respect to compettors that s unrelated to ther productvty level and t becomes larger the stronger the shock. I call the latter a dstortonary effect of economc recessons. Fgure 1 Compettve rent and dstortons of frm selecton Productvty, Ω 8 6 Ω*(Ζ') Ω*(Ζ'') 4 Ω*(Ζ) Compettve rent, Note: productvty thresholds as a functon of compettve rent for dfferent sze of the negatve shock. Curves have been drawn for w = 2; ϕ * = - 1; γ = 0.9; ζ = 1; ζ' = 1.5; ζ'' = 2; L = 10. Based on the above results t s possble to derve two testable predctons: Predcton 1: Durng an economc recesson, frms wth large compettve rent ( δ ) enjoy a selecton advantage and are less lkely to ext than frms wth small compettve rents. Predcton 2: The selecton advantage of frms wth large compettve rent s greater, the stronger the recesson (.e. the larger ζ). The man am of the followng sectons s to provde an emprcal test of these predctons. 10

13 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/ Context, data and varables 3.1 Context The Great Recesson, whch orgnated n the US n 2008 and then spread to Europe (as well as worldwde) n the followng years, s a sutable context to test the predctons derved n Secton 2.1 for three reasons. Frst of all, the Great Recesson represents the deepest downturn n the hstory of captalsm snce the Great Depresson of the 1930s. 3 Secondly, the Great Recesson happened to be a relatvely unexpected event, especally for the European manufacturng sector. Accordng to Claessens et al. (2012) ts negatve mpact on ndustral performance was manly due to the sudden nterrupton of fnancal and trade flows at the global level and t can thus be consdered unrelated to frm decsons taken before that perod. 4 Fnally, although the Great Recesson was certanly global n nature, t dd not affect all countres n the same way. Wthn the Eurozone the crss mpacted the so- called perpheral countres more severely than the so- called core countres, especally f one consders the protracted perod of recesson that followed the outbreak of the crss (Groot et al., 2011). In ths sense the Eurozone represents a quas- expermental settng, where the heterogenety of the crss across countres can be exploted to estmate the effect of recessons on frm selecton. 3.2 Data The analyss n ths paper reles on EFIGE data, a unque dataset of manufacturng frms n seven European countres: Germany, France, Italy, Span, Unted Kngdom, Austra and Hungary. The EFIGE dataset has several unque features (for detals see Altomonte and Aqulante, 2012). Frst, t s a stratfed sample bult to be representatve of the manufacturng structure of the countres covered. Second, t contans data that are fully comparable across countres, snce t s derved from responses to the same questonnare, admnstered over the same tme span. Thrd, t provdes both qualtatve and quanttatve nformaton on the frm s nternal structure (e.g. property structure, workforce, nvestments, technologcal nnovaton, R&D, nternatonalzaton, fnance, market and prcng), whch allow a deeper analyss than just balance sheet nformaton. Fnally, most of the questons n the survey refer to 2008; they thus allow one to control for frm s characterstcs at the begnnng of the recesson (Altomonte et al., 2013). EFIGE data were ntegrated wth nformaton retreved from the Amadeus- BVD database for the perod In addton to balance sheet and proft and loss statement nformaton, Amadeus data contans nformaton on the present status of the frms (actve vs. non- actve 3 Accordng to the Internatonal Monetary Fund (IMF) between 2008 and 2009 the GDP of advanced economes dropped on average by 3.4%, wth peak drops n the US and the Eurozone of respectvely 2.8% and 4.5% (IMF, 2016). Durng the same perod the volume of world trade collapsed by 10.5% and unemployment rate rose by 40% (advanced economes) (IMF, 2009, 2010). Moreover, especally n the Eurozone, these short- term effects were followed by a protracted perod of stagnaton wth an average GDP growth that n perod was only 0.6%, far below the 2% growth regstered by the US (IMF, 2016). 4 Accordng to Eurostat (2016) n 2006, the year before the outbreak of the mortgage crss n the US, the producton of manufacturng actvtes wthn the Eurozone was growng at 7%. Ths went together wth hgh level of confdence n the economy, as measured by the Eurostat s economc sentment ndcator, whch scored n the last quarter of 2006 the hghest value snce the early Then, n 2008 manufacturng producton dropped by nearly 14% and the economc sentment ndcator reduced by 36%, reachng the lowest value over the last 20 years. 11

14 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 and merged vs. acqured), whch s exploted to dstngush between actve and extng frms (see below). The qualty of the Amadeus data vares by country, and not all the varables are avalable on all balance sheets. France, Italy and Span are the countres wth the best coverage and I thus restrct the analyss to them. After havng matched EFIGE data wth Amadeus data I reman wth a restrcted sample of 6,865 frms (compared to the 8,826 frms n the unrestrcted sample), wth the followng dstrbuton by country: 2,252 frms n France, 2,642 frms n Italy and 1,971 frms n Span. Altomonte et al. (2012) provde detaled dscusson of the characterstcs of the restrcted EFIGE- Amadeus matched sample and fnd no major dfference wth respect to the unrestrcted sample. Overall, I obtan an unbalanced panel wth nformaton n three tme- horzons. Frst, I have frm- level nformaton on the nternal characterstcs of the frms n concdence wth the outbreak of the Great Recesson,.e., Second, I have access to the balance sheet of all frms before the Great Recesson,.e., from 2001 to Fnally, I can dentfy the frms that are stll actve and those that exted the market by Usng these data I can estmate the determnants of frm ext durng the recesson, payng partcular attenton to the role of compettve rents. 3.3 Frm ext The dependent varable dstngushes between survvng and extng frms. Informaton contaned n the Amadeus- BVD database makes t possble to detect frms that are actve n 2008 but have changed ther status before On ths bass, I rely on the same algorthm used n Arrghett et al. (2015) and Landn et al. (2016) (see Appendx) to dentfy frms that have effectvely exted the market. In contrast to prevous lterature (see Agarwal and Audretsch, 2001; Cefs and Marsl, 2005), I can dstngush between ext resultng from the death of the frm and ext occurrng through merger and acquston. In ths paper, I focus only on the former; the frms subject to mergers and acqustons are removed from the sample. Unfortunately, the Amadues- BVD database does not provde relable nformaton on the year n whch ext actually occurs. Therefore, the dependent varable that I consder (EXIT) s a dummy varable that takes value 1 f a frm has exted the market before 2015, and zero otherwse. 3.4 Compettve rents The key varable n the analyss s the measure of compettve rents. Dfferently from Forster et al. (2008), who estmate a verson of the model descrbed n Secton 2.2, I do not have access to dstnct nformaton for frm- level prces and quanttes. Therefore, I have to rely on a proxy varable that explots value measures to capture the frms that are most lkely enjoyng compettve rents. Along these lnes, I base my analyss on two man varables: labour productvty (LABPROD) measured as the logarthm of value added per employee; and proft (PROFIT) measured as the rato of value added mnus wages over sales. Snce compettve rents are conceved as a persstent feature of the frms, I compute both LABPROD and PROFIT consderng the mean of the year- specfc varables over the pre- crss perod Then for each frm n the sample, I construct the a proxy of compettve rents, whch I call H PROFIT- L LABPROD, as follows: H PROFIT - L LABPROD = 1, f PROFIT > PROFIT = = 0, otherwse 12 and LABPROD < LABPROD

15 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 where PROFIT and LABPROD s the ndustry mean (NACE 3 dgts classfcaton) of PROFIT and LABPROD respectvely. In other words, H PROFIT- L LABPROD s a dummy varable selectng the frms that durng the pre- crss perod present hgher- than- ndustry- mean proft but lower- than- ndustry- mean labour productvty. Snce these frms are lkely beng less effcent than ther drect compettors, ther postve proft gap must derve from some alternatve factors, ncludng compettve rents. On ths respect, t s mportant to notce that t s only dosyncratc factors that are potentally captured by ths measure gven that the measure devates from ndustry means. Therefore, although t s not possble to drectly assocate H PROFIT- L LABPROD to demand dosyncrases of the type dscussed n Secton 2, t s hghly lkely that the latter play an mportant role n determnng whether or not a frm s classfed as H PROFIT- L LABPROD. A possble shortcomng of ths classfcaton, however, s that t does not take nto account the heterogenety of producton nputs, whch may affect the measured values of both productvty and proft. For nstance, t s possble for a frm to adopt a low cost strategy that nvolves hrng low qualfed labour and nvestng n low qualty captal goods. In ths case the relatvely low cost of producton nputs may mply a relatvely hgh measured proft, wthout ths necessarly mplyng that the frm s neffcent. For ths reason I consder also a refned measure of compettve rents that controls for ths effect. In partcular, I splt the frms classfed as H PROFIT- L LABPROD nto two groups. The frst one, whch I call LOW- COST, s captured by a dummy varable takng the followng values: LOW - COST = 1, f H PROFIT - L LABPROD = = 0, otherwse = 1andW < W and INV < INV where W s the total labor cost n 2008 and INV s the cost of nvestments n plants, machne and equpment as the share frm s turnover n 2008, wth W and INV beng the correspondent ndustry means. In other words ths varable dentfes the frms that whle beng characterzed by relatvely hgh proft and low labour productvty, they also exhbt relatvely low costs for producton nputs compared to ther ndustry compettors. Followng the above dscusson these are frms whose hgh measured proft s lkely to derve more from ther low cost structure than from compettve rents. The second group of frms that I consder conssts nstead of the frms that are most lkely enjoyng compettve rents. The latter are captured by a dummy varable selectng the resdual group of frms that are classfed as H PROFIT- L LABPROD but do not exhbt relatvely low costs: COMP - RENT = 1, f H PROFIT - L LABPROD = = 0, otherwse = 1and LOW - COST = 0. In other words ths varable dentfes the frms whose relatvely hgh proft and low labour productvty cannot be explaned by supply- sde factors such as the purchase of low qualty nputs. Rather, ther postve proft gap most lkely derves from demand- sde dosyncrases such as compettve rents. These frms are the man focus of the analyss. 13

16 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/ Compettve rents across countres, regons and ndustres Ths secton presents some descrptve statstcs on compettve rents. Fgure 2 shows the correlaton between ndustry mean devatons of PROFIT and LABPROD. Panel (a) s computed by poolng all observatons n a sngle dataset (pooled dataset) and then by calculatng each varable as devaton from the pooled ndustry means. Panel (b), (c) and (d) refer nstead to the dataset of each country separately and the varables are computed as devaton from the country- specfc ndustry means. As expected the mean devatons of PROFIT and LABPROD are postvely correlated n all datasets, wth a coeffcent that ranges from for the pooled data to for Span (p- value<0.001). Ths evdence s consstent wth the results of the model that predcts a postve assocaton between dosyncratc productvty and proft. Nonetheless, there exst frms that exhbt at the same tme hgher- than- ndustry- mean proft and lower- than- ndustry- mean labour productvty (red dots n the pctures). Accordng to the above classfcaton, these are the frms that are lkely enjoyng compettve rents. Fgure 2 Correlaton between proft and productvty (mean devatons) across countres (a) Pooled, PROFIT and LABPROD (b) France, PROFIT and LABPROD (c) Italy, PROFIT and LABPROD (d) Span, PROFIT and TFP Note: Correlatons between proft and labour productvty. All varables are computed consderng the devaton from the ndustry mean over the perod Colors dstngush the frms wth hgher- than- ndustry- mean proft and lower- than- ndustry- mean labour productvty. Estmated correlaton coeffcents are: (a) Pooled 0.398; (b) FRA 0.430; (c) ITA 0.418; (d) SPA For all coeffcents p- value <

17 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 Fgure 3 reports the dstrbuton of the frms classfed as H PROFIT- L LABPROD, LOW- COST and COMP- RENT across countres. In all countres around 14% of frms presents hgher- than- ndustry- mean proft and lower- than- ndustry- mean labour productvty (H PROFIT- L LABPROD). Nearly half of them sustan proft va the low cost of nputs (LOW- COST) and the other half va compettve rents (COMP- RENT). In partcular, the share of frms classfed as COMP- RENT s around 6% n France, 8% n Italy and 7% n Span. Therefore, whle compettve rents seem to be a farly wdespread phenomenon n all countres, there do exst some slght dfference n the dstrbuton across countres, wth compettve rents beng relatvely more common n Italy and Span than n France. Fgure 3 Compettve rents: comparson across countres Note: Cross- country comparson of frms wth- hgher- than- ndustry- mean proft and lower- than- ndustry- mean labour productvty. The fgure dstngushes between frms that support proft va low costs of nputs and frms that support proft va compettve rents. Some addtonal nformaton on the geographc dstrbuton of compettve rents s provded by Fgure 4, whch shows the share of frms classfed as H PROFIT- L LABPROD (panel a) and COMP- RENT (panel b) across NUTS 2 regons. In France the concentraton of frms wth compettve rents s stronger n the Northwestern regons as well as n Corse. An even greater degree of geographc dfferentaton exts n Italy, where the frms classfed as H PROFIT- L LABPROD and COMP- RENT tend to be more frequent n the Southern regons as well as n Scly and Sardna. In Span, on the contrary, the dstrbuton across the natonal terrtory seems more homogeneous. The causes of ths dfferent geographc dstrbuton among countres can be several, ncludng the exstence of dfferent sources of compettve rents. In Italy, for nstance, the fact that compettve rents are partcularly common n the Southern regons may be due to the well- known nsttutonal dvde between North and South that characterzes the country (Felce, 2013). 15

18 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 (a) H PROFIT- L LABPROD Fgure 4 Compettve rents: dstrbuton across regons (b) COMP- RENT Note: Share of frms wth compettve rents across regons (NUTS2). Colors dstngush across dfferent degrees of concentraton: the darket the greater the share of frms wth compettve rents. 16

19 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 To deepen the analyss, Fgure 5 plots the regonal share of frms classfed as H PROFIT- L LABPROD and COMP- RENT aganst two possble sources of compettve rents, namely transportaton costs measured as the regonal dffuson of motorways (panels a and b) and the qualty of local nsttutons measured by the European Qualty of Government Index (EQI) (panels c and d). The EQI s an ndex that captures the qualty of the publc servces admnstered by the publc sector along several dmensons, ncludng: the degree of corrupton, the rule of law, the protecton of property rghts and the government bureaucratc effectveness n mpartally admnsterng publc goods and servces (Charron et al., 2015). The data on both transportaton costs and EQI s derved from the Qualty of Government dataset avalable from the Unversty of Gothenburg. 5 Fgure 5 Compettve rents, transportaton costs and qualty of nsttutons across regons (a) H PROFIT- L LABPROD, transportaton costs (b) COMP- RENT, transportaton costs (c) H PROFIT- L LABPROD, qualty of government (d) COMP- RENT, qualty of government Note: Correlatons between share of frms wth compettve rents and transportaton costs/qualty of governement at the regonal level (NUTS2). Estmated correlaton coeffcents are: (a) ; (b) ; (c) ; (d) For coeffcents (a), (c) and (d) p- value < 0.001; for coeffcent (b) p- value <

20 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 All graphs suggest that the hgher the transportaton costs (.e. the lower the regonal dffuson of motorways) and the lower the qualty of local nsttutons, the greater the dffuson of frms wth compettve rents. Ths correlaton s n lne wth the above dscusson on the sources of compettve rents: n regons where transportaton costs are hgh and nsttutons can be subject to elte capture, frms are more lkely to enjoy postve demand dosyncrases and compettve rents are more common. In addton to dfferences across countres and regons one may wonder whether compettve rents are specfc to some types of ndustres as opposed to others. Fgure 4 shows the share of frms classfed as LOW- COST and COMP- RENT across ndustres (NACE 2 dgts classfcaton). In all sectors, wth the only excepton of 17. Manufacture of paper and paper products, the share of frms that enjoy compettve rents s greater than 5% and n some cases ( 19. Manufacture of coke and refned petroleum products and 33. Repar and nstallaton of machnery and equpment ) t s greater than 10%. A smlar dstrbuton characterzes the frms that are classfed as LOW- COST. Therefore, rather than beng ndustry- specfc, compettve rents appear as a phenomenon that cuts across all manufacturng sectors. Fgure 4 Compettve rent: comparson across ndustres Note: Cross- ndustry comparson of frms wth- hgher- than- ndustry- mean proft and lower- than- ndustry- mean labour productvty. The fgure dstngushes between frms that support proft va low costs of nputs and frms that support proft va compettve rents. The varables are computed usng the pooled dataset. 18

21 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 Fnally, Table 1 reports some frm- level descrptve statstcs dstngushng among H PROFIT- L LABPROD frms (column 1), LOW- COST frms (column 2), COMP- RENT frms (column 3) as well as other frms (column 4). For all frm types the Test column shows the results of an F- test comparng the mean dfference between each frm type (columns 1, 2 and 3) and the other frms (column 4). In general, frms wth compettve rents (COMP- RENT) are younger (AGE), smaller (SIZE), less nvolved n export actvtes (EXPORT), less lkely to be part of a group (GROUP) and more lkely to be famly frms (FAMILY) than the other frms. Smlar dfferences characterze also the frms classfed as LOW- COST frms. Qute nterestngly, however, COMP- RENT and LOW- COST frms dffer for the last three varables ncluded n the table, whch refer to the share of workers wth unversty degree (DEGW), the captal to labour rato (CAPTOLAB) and the share of frms that n the survey declare to be fxng prces as demand- based margns over costs (PMARGDEM). LOW- COST frms dffer from the other frms n terms of the low qualty of producton nputs,.e. lower DEGW and CAPTOLAB, but not n terms of the prcng strategy,.e. PMARGDEM. On the contrary, COMP- RENT frms exhbt no sgnfcant dfference wth respect to the nput structure, but a larger fracton of them declare to be fxng prces as demand- based margns over costs. Ths result confrms that COMP- RENT selects frms that ndeed enjoy some degree of market power, whch s lkely be due to demand- based factors such as compettve rents. In sum the descrptve analyss reveals four nterestng results. Frst, frms wth compettve rents tend to be farly wdespread and are slghtly more common n Italy and Span than n France. Second, the dstrbuton of compettve rents across regons presents some degree of dfferentaton, whch seems to be drven by both physcal factors (e.g. transportaton costs) and nsttutonal factors (e.g. qualty of local nsttutons). Thrd, frms wth compettve rents exst n all manufacturng sectors and ther presence does not seem to be a specfc feature of any ndustry n partcular. Fnally, frms wth compettve rents tend to be small and young famly frms that are actve manly n local markets. Ther nput structure s not dfferent from that of the other frms and ther prcng strategy reflects some postve degree of market power due to specfctes of demand. Based on ths descrptve evdence, the next sectons wll rely on a multvarate analyss to explore f and how compettve rents affect the process of frm selecton durng recessons. 19

22 F. Landn LUISS School of European Poltcal Economy WORKING PAPER 10/2016 Table 1 Compettve rent and frm characterstcs, pooled dataset (1) H PROFIT L ABPROD (2) COMP- RENT (3) LOW- COST (4) Other frms Mean Sd N Test Mean Sd N Test Mean Sd N Test Mean Sd N AGE *** *** *** SIZE *** *** *** PROFIT *** *** *** LABPROD *** *** *** EXPORT (d) *** *** *** GROUP (d) *** *** *** FAMILY (d) *** *** *** DEGW * *** CAPTOLAB ** *** PMARGDEM ** *** Note: Descrptve statstcs for frm characterstcs dstngushng among frm types. AGE s the frm s age n SIZE s the frm s total number of employees n PROFIT s the rato of value added mnus wages over sales, average between 2007 and 2008 values. LABPROD s the logarthm of value added per employee, average between 2007 and 2008 values. EXPORT s a dummy takng value equal to one for the frms whose export counts for more than the 50% of ther total sales n GROUP s a dummy takng value equal to one for the frms that belong to a group n FAMILY s a dummy takng value equal to one for the frms that are famly owned n DEGW s the share of workers wth a unversty degree n CAPTOLAB s the captal to labour raton n PMARGDEM s a dummy varable takng value equal to one for the frms that declare to be fxng prces as margn over (varable or toal) costs and that responsveness of demand for the product to varaton n prces s the most mportant factor n determnnng the sze of such margn n The Test column reports the results of a mean- comparson F- test between the relatve frm type (columns 1, 2 and 3) and the other frms (column 4): *=sg. 10%; **=sg. 5%; ***=sg. 1%. 20