Study on capital misallocation and skill mismatches in Italy: the productivity conundrum

Transcription

1 Study on capital miallocation and kill mimatche in Italy: the productivity conundrum Reference Number: DG ECFIN, European Commion FINAL REPORT

2 LSE Enterprie contact detail LSE Enterprie Limited London School of Economic and Political Science Eighth Floor, Tower Three Houghton Street London WC2A 2AZ Tel: +44 (0) Fax: +44 (0) Web: le.ac.uk/enterprie

3 Table of content 1 Introduction Productivity and it ource Why productivity matter Productivity in Italy againt benchmark countrie Relevant global hock nce the Relevant reform in Italy nce the Literature review Methodological contribution International tudie Studie with an Italian focu Meauring miallocation Data: CERVED Methodological approach Miallocation acro different dimenon Manufacturing ector Non-manufacturing The impact of miallocation to aggregate TFP Productivity, miallocation, and firm characteritic: Methodology Firm relative productivity Further analy of the role of marker for miallocation Productivity, miallocation, and firm characteritic: Finding Data: INVIND and CB Marker of miallocation

4 5.2.1 Corporate ownerhip/control and governance Finance Workforce compotion Internationaliation Cronyim Innovation Cro-cutting reult Concluon and policy implication Reference ANNEX a. Definition of miallocation b. A meaure of miallocation c. Miallocation and aggregate TFP

5 1 Introduction Italy i often regarded a the leeping beauty of Europe, a country rich in talent and hitory, but uffering from a long lating tagnation (Haan and Ottaviano, 2013). The broad conenu i that the beginning of uch tagnation can be traced back to the 1990 and that faltering productivity growth lie at it root. Thi paper analye the microeconomic apect of thi productivity lowdown. In particular, it emphaze a deteriorated allocation of reource among Italian firm and invetigate the poble ource of thi miallocation problem. The final aim i to provide policy relevant inght on how to tackle the problem thereby contributing to the awakening of the leeping beauty. The paper i organized in five ection. The ret of thi ection introduce the concept of productivity and miallocation we ue throughout the paper and highlight the relevance of productivity dynamic for undertanding it lowdown. It then provide a very concie ummary of the main global hock and relevant reform that may have affected the Italian productivity nce the Section 2 provide a elective review of the relevant literature on miallocation pinpointing key tudie at both the national and the international level. Building on the methodological contribution urveyed on the previou ection, Section 3 firt operationalize the concept of miallocation we ue and detail how we implement it empirically. It then dicue the evolution of miallocation in Italy nce the 1990 acro region, ector and firm ze clae. Section 4 develop a new methodology to identify firm characteritic ( marker ) that are aociated with miallocation. Thi methodology i applied in Section 5 where we can a rich et of economic and intitutional characteritic. Section 6 conclude the paper ummarizing it main finding and ditilling ome policy implication. 3

6 1.1 Productivity and it ource The concept of productivity we ue i Total Factor Productivity (henceforth mply TFP), which meaure how efficiently given amount of input are ued. Clearly the economy aggregate TFP i a weighted average of it firm TFP (hence we will ue aggregate TFP and average TFP interchangeably). A uch it depend on their TFP along two dimenon. On the one hand, given the amount of productive factor - like capital and labour - ued by each firm, aggregate TFP grow when individual firm TFP grow thank to the adoption of new technologie and better bune practice. If firm are generally unable to take thee opportunitie, the economy productive apparatu i expoed to obolecence and enecence with a negative impact on aggregate TFP. On the other hand, in the preence of friction in the market for productive factor, aggregate TFP alo depend on how thoe factor are allocated acro firm. In particular, a long a market imperfection hamper the flow of factor from le productive firm (where factor return are lower) to more productive firm (where factor return are higher), they reult in lower aggregate TFP compared to an ideal tuation of frictionle factor market. Thi ditorted allocation of reource toward lower productivity firm i what we call miallocation and, a we will dicu in greater detail in Section 3, it can be meaured by the oberved gap ( wedge ) in factor return between firm. Quantifying the impact that miallocation on aggregate Italian productivity and identifying the main firm characteritic aociated with uch miallocation i the aim of our analy. In doing o, we will ditinguih between characteritic potentially relevant for the allocation of capital (uch a the involvement of firm with bank and financial market) and thoe potentially relevant for the allocation of labour (uch a the kill compotion of the labour force and management practice). 4

7 1.2 Why productivity matter It i well undertood that TFP i the main driver of long-run growth (ee, e.g., Caelli, 2005). In fact a growth proce baed on increang productivity and efficiency i more utainable in the long run than a proce baed on the accumulation of the factor of production capital and labour which are characterized by decreang return to cale. It ha alo been hown that Italian firm tend to under-repond to TFP hock becaue of friction in the economy like the ability of manager to implement change in a firm (Pozzi and Schivardi, 2015). Figure 1-1 i quite emblematic of the relevance of TFP dynamic for aggregate growth. It how a growth accounting decompotion for Italy in the pat four decade. TFP growth hrank throughout the decade, turning negative in the 2000 (Haan and Ottaviano, 2013). Accordingly, undertanding the origin of uch decline i crucial in order to degn appropriate policie that can enhance future growth. 1.3 Productivity in Italy againt benchmark countrie The TFP decline that we oberve in Italy eem to be country pecific. Figure 1-2 how the evolution of TFP for the manufacturing ector in Italy, France, and Germany. It reveal a clear lowdown in Italy nce the middle of the 1990, wherea in France and Germany TFP continued to grow up to the global financial cri (Haan and Ottaviano, 2013). Recently a debate on the productivity lowdown of the United Kingdom, which occurred after the global financial cri, ha alo emerged. In thi repect, undertanding the Italian cae may provide ueful methodological and policy guidance on how to tackle productivity iue in other countrie. 1.4 Relevant global hock nce the 1990 The rie of globaliation and the revolution of ICT ( information and communication technology ) are the two key global hock that occurred in the Moreover, the introduction of the euro i a relevant regional hock at the end of the decade that we alo take into account. 5

8 Thee type of hock caued a radical change of the competitive context in which firm operate. Italian firm, typically of maller ze than the European average, ued to be particularly efficient in ector with low technological intenty, low return to cale, and tandardized product. It i likely that the Italian firm were not relient to the hock that occurred in the 1990 becaue: i) globaliation introduced new economic actor with lower production cot; ii) the euro prevented nominal devaluation that could have been ued to help the adjutment; iii) the ICT revolution, which ha been a key driver of recent TFP growth (Bloom et al., 2012), benefited larger firm that had ufficient cale for thi type of technological invetment. 1.5 Relevant reform in Italy nce the 1990 In the period under conderation, the Italian economy underwent important regulatory reform in a number of area, from the labour market to bankruptcy law, from corporate governance to retail trade, from the ocial ecurity to the chool ytem. A complete decription of the equence of reform, a well a an appraial of their effect, i beyond the cope of thi paper. The OECD ha compiled a erie of publication on thi iue, and we refer the intereted reader to them (ee for example OECD 2010). Two uch reform might have played a particularly important role in the proce of reource allocation. Firt, Italy underwent a large privatization proce. On one hand, uch proce hould have improved the efficiency of formerly publicly owned indutrial companie or utilitie. Firt, Italy underwent a large privatization proce. On one hand, uch proce hould have improved the efficiency of formerly publicly owned indutrial companie or utilitie. On the other, A for privatiation, thi proce may have hifted reource from indutrial or ervice activitie with a high level of productivity to ervice characterized by low competition low productivity and high rent. Thi may have contributed to the productivity lowdown through the miallocation of reource between ector rather than between firm within the ame ector. 6

9 A econd important equence of reform relate to the labour market, which wa progrevely made more flexible. On the one hand, higher flexibility hould reult in a better allocation of labour acro ector and firm. On the other, it ha been argued that in Italy the reform ha created dual labour market where ome worker are highly protected while other highly flexible. The conequent different labour effort and behaviour may eventually lead to more labour miallocation and to a deanchoring of wage from labour productivity (Manae and Manfredi, 2014). Quantifying econometrically the role of global hock and Italian reform for miallocation goe beyond the cope of thi paper a it would require harmonized cro-country firm level data that are not readily available. Neverthele, we dicu the potential relevance of uch hock focung on the timing of the hock and the productivity lowdown. 7

10 2 Literature review Thi ection provide a elective overview of the relevant literature on miallocation. More pecifically, the firt ubection mention the main methodological contribution to the quantification of miallocation; the econd ubection urvey the paper that apply thoe methodologie to variou countrie and context; the third ubection review ome tudie aimed at undertanding the Italian tuation and the poble caue of the Italian productivity lowdown. A the literature on miallocation i evolving at a very rapid pace, thi ection ha no aim of being comprehenve, but rather focue on apect that are central to our analy Methodological contribution There i a wide literature on the inefficient allocation of reource acro firm. Among them, the mot relevant methodological contribution for our project are Heh and Klenow (2009) (HK, henceforth), Olley and Pake (1996) (OP, henceforth) and Bartelman, Haltiwanger and Scarpetta (2013). The increang interet in miallocation can largely be attributed to the contribution of HK, who provide an analytical framework to quantify the effect of miallocation on productivity. The bac intuition of HK i that, in a world where factor are allocated efficiently, the marginal value product of input hould be equalized acro firm. Diperon in the marginal value product of input can then be een a a meaure of the extent of miallocation of factor of production. HK contruct a model that, baed on rather tandard aumption on technology (e.g. Cobb-Dougla with contant return to cale) and market tructure (monopolitic competition with contant demand elaticity, aumed to be the ame for all firm in the economy), allow to quantify the loe in productivity deriving from the fact that marginal value product are not equalized acro firm. Under the aumption of homogeneou technology and demand acro firm, the only reaon why marginal value product might not be 1 For a recent urvey, ee Retuccia and Rogeron (2013), a well a the paper in the ame pecial iue of the Review of Economic Dynamic. The author divide the literature on miallocation into direct approach, which focue on pecific mechanim that could reult in reource miallocation, and indirect approach, which focue on the net effect of the entire bundle of underlying factor on miallocation without reference to a pecific one. Another ueful urvey i Hopenhayn (2014). 8

11 equalized acro them i the preence of ditortion in the factor and/or product market. A a conequence diperon in marginal product i a meaure of uch ditortion. They apply their framework to meaure the impact of factor miallocation acro manufacturing firm on aggregate TFP in China, India and the US. They find that miallocation i much more prominent in China and India than in the US, and that, if uch countrie had the ame degree of allocative efficiency a the US economy, manufacturing TFP would grow by between 30 and 60%. HK propoe a ummary meaure of the effect of diperon in the marginal product, that i, TFP revenue (TFPR), which i a weighted average of the marginal revenue product of capital and labour. Diperon in TFPR meaure the total effect of miallocation on productivity. Other tudie have focued alo eparately on the marginal product of each input, which gnal eparately capital and labour miallocation. Aker, Collard-Wexler and De Loecker (2014) focu on capital miallocation. They criticize the HK model by howing that productivity volatility and invetment adjutment cot can explain a large fraction on diperon of the marginal revenue product of capital. Under thi condition, heterogeneity in the marginal revenue product of capital i not necearily evidence of miallocation, but of an optimal repone of firm conditional on productivity volatility and adjutment cot. Olley and Pake (1996) propoe a decompotion of indutry productivity into the unweighted average of firm productivitie and the ample covariance between productivity and ze. The miallocation meaure i provided by the covariance term: the more efficient the allocative proce, the larger more productive firm hould be. An application of the Olley and Pake decompotion can be found in Bartelman, Haltiwanger and Scarpetta (2013) who rely on the fact that heterogeneity in firm-level performance i accompanied by ubtantial heterogeneity in the ze of firm and that the ditribution of productivity and ze of firm exhibit a potive correlation. We will come back to thi paper in the next ubection. 9

12 2.2 International tudie A number of author have meaured the ze of overall ditortion by applying the HK procedure to other countrie and period. Analye baed on the HK framework how that in recent year miallocation increaed ubtantially in Spain (Garcia- Santana et al., 2015; Gopinath et al. 2015) and in Portugal (Dia et al., 2014), remained pretty contant in France (Bellone and Mallen-Piano, 2013), while it declined in Germany (Crepo and Segura-Cayuela, 2014), Chile (Chen and Irarrazabal, 2014). In addition, comparing France, Italy, Germany and Spain, Crepo and Segura-Cayuela (2014) find that potential TFP gain from eliminating miallocation in Spain are larger than thoe in France but maller than thoe in Germany and Italy. In parallel exercie, Brandt et al. (2013) conder the allocation of the Chinee economic activity acro region a well a between the public and the private ector; Ziebarth (2013) et the HK exercie in a hitorical context by contructing a firm-level data et for manufacturing in the U.S. in the late 19th century; Bollard et al. (2013) tudy a much longer period for India than HK ranging from 1980 to Ung the OP covariance between TFP and/or labour productivity and market hare in the US and even European countrie, Bartelman, Haltiwanger and Scarpetta (2013) find that the ze/productivity relationhip i tronger in more advanced economie and became tronger in Central and Eatern European countrie, with miallocation remaining roughly contant in more advanced countrie and decreang in the trantion one. In their aforementioned tudy of Spain, together with the HK approach, Garcia-Santana et al. (2015) ue alo the OP covariance decompotion a a meaure of miallocation obtaining largely content reult. In term of pecific channel that can give rie to miallocation of reource in the economy, the mot tudied apect i arguably finance. In a eminal paper, Caballero et al. (2008) document that Japanee bank during the ninetie directed credit toward zombie firm, that i, low productivity firm, keeping them artificially alive. Thi proce depreed factor reallocation and productivity growth. Midrigan and Xu (2004) build a model of firm dynamic in the preence of financial friction. They how that financial friction affect productivity growth motly by reducing entry and 10

13 technology adoption. Gopinath et al. (2015) explain the low productivity growth in Italy and Spain by the decreae in the interet rate following the Euro adoption. They build a model in which, due to difference in net worth, ome firm are financially contrained and cannot acce the capital market, while other are not contrained and therefore can borrow. Following a decreae in the cot of capital (uch a the one experienced by Spain and Italy after the Euro adoption) only firm that are not financially contrained can increae invetment, which widen the wedge between the marginal product of capital of uncontrained and contrained firm. Moreover, a high net worth firm are not necearily the mot productive, capital inflow i not allocated to the mot productive firm. Caggee and Cunat (2013) tudy the interaction between financing contraint and export activity. Ung firm level data for Italy, they how that credit contraint at the level of the firm reduce the productivity gain deriving from trade liberaliation, a contrained firm are le likely to enter the export market. Another ource of miallocation that can play a role in the Italian cae i the allocation of talent. Heh et al. (2013) analye the effect of race and gender dicrimination on the miallocation on talent and, through thi, on productivity. They conclude that 15 to 20 percent of growth in aggregate output per worker between 1960 and 2008 may be explained by the improved allocation of talent that follow a reduction in dicrimination. Bloom et al. (2012) document difference in the quality of managerial practice (and therefore in productivity) acro firm with different ownerhip tructure, howing that family run firm (a oppoed to family owned, but managed by external manager) tend to be le effectively managed. Caelli and Gennaioli (2013) argue that, when the market of corporate control doe not properly function, firm might remain family owned and managed even if the owner do not have the bet kill to efficiently run the firm. Some paper have alo tudied the effect of policie that ditort the ze ditribution of firm. Guner et al. (2008) ue a growth model with endogenou ze ditribution of firm to tudy the effect of ze-contingent policie, uch a firing cot applying only above a certain threhold. They document that uch policie can have large effect on aggregate productivity. Bento and Retuccia (2015) how that average 11

14 firm ze increae with development. They contruct a model in which ze correlated ditortion are more prevalent in poor countrie, and how that uch ditortion can generate ubtantial productivity loe. Thee type of ditortion can be particularly relevant for the Italian productive tructure, characterized by the prevalence of SME (Bartelman et al., 2005). 2.3 Studie with an Italian focu The mot triking feature of the recent development in the Italian economy i the emergence of a marked productivity lowdown nce the mid-ninetie. Report by the European Commion give an overall picture of luggih Italian productivity (Country Report Italy 2015, Council Recommendation on the 2015 National Reform Programme of Italy, Macroeconomic Imbalance, Italy 2014). Figure 2-1, drawn from Lunyan e Muir (2013), illutrate a growth accounting exercie for Italy and the EU15 countrie. Two fact emerge clearly: the Italian lowdown tart in the ninetie and become more pronounced in the 2000; it main driver i the lowdown in TFP growth, which in the 2000 turn negative. Thi evidence ha purred a lively debate on the caue of the productivity lowdown, which we briefly ummarize in thi ubection. In thi debate, the role of miallocation ha been analyed only recently. An early line of interpretation, due among other to Faini and Sapir (2005), attribute the caue of the lowdown to the Italian model of pecialiation, characterized by traditional ector with low human-capital intenty and low technology. According to thi view, the way out of the lowdown would be a change in the ectoral compotion of the Italian productive ytem. Thi view ha been challenged by a erie of ubequent contribution. Firt of all, it ha been hown that the productivity lowdown characterize all ector and, if anything, tend to be tronger in high-tech ector (Idee per la crecita, 2013). Moreover, cro-firm diperon in the level of productivity i mainly accounted for by the within-ector rather than the between ector component (Bugamelli et al., 2010). Rather, an important role i repreented by the firm ze ditribution. The Italian productive ytem i characterized by the prevalence of SME, which diplay a lower level of productivity when compared to large firm. De Nardi (2014) perform a productivity decompotion exercie that how that eentially the whole difference in 12

15 productivity level between Italy and Germany can be explained by the difference in firm ze ditribution, while ectoral compotion play a maller role. A milar reult i obtained by Barba-Navaretti et al. (2010) when condering export performance. A related iue that ha received growing attention i the role of corporate ownerhip and control. A in mot European countrie, family ownerhip i the predominant ownerhip mode; what i peculiar of Italian family firm i that they tend alo to be controlled and cloely managed by family member (Bugamelli et al., 2012). Thi might be a ource of miallocation of talent, if the mot appropriate managerial kill are not found within the family owning the firm. The contribution that invetigate pecific channel of the productivity lowdown have focued on thee apect. Pellegrino and Zingale (2014) find that labour productivity growth flattened due to mall firm inability to repond appropriately to the challenge of Chinee competition and to the failure of exploiting the ICT revolution. Thee failure, in turn, are hown to be due to the lack of meritocracy in managerial election and promotion, a well a to familyim and cronyim. Daveri and Pari (2015) argue that Italy productivity lowdown can be explained by a 1997 labour market reform that introduced temporary employment contract, producing a rightward hift to labour upply. In addition, managerial age appear to be either potively correlated or uncorrelated with productivity growth for noninnovative firm, but it i robutly negatively correlated with productivity growth for the innovative one. Lippi and Schivardi (2014) and Bandiera et al. (2014) how that Italian family firm tend to elect their manager more baed on loyalty than capabilitie and that they employ le power-incentive remuneration cheme with repect to other firm. Ung cro-country data on OECD countrie, Michelacci and Schivardi (2013) how that family firm tend to elf-elect into lower rik-lower return project, with negative conequence on productivity growth. Giordano et al. (2015a, 2015b) highlight the negative impact of public ector inefficiency. Firm ze, ownerhip tructure and labour market dualim are recognized by Bugamelli et al. (2012) a key driver of the innovation gap that characterize the Italian productive ytem when compared to that of the other indutrialized economie. Giordano et al (2015) ue difference in the degree of public ector efficiency at the local level and 13

16 in the need for efficient public ervice acro ector to how that the inefficiency of the public ector i an important factor in hindering firm productivity. There i alo ome evidence that kill mimatch i a ource of productivity loe in Italy. The OECD Survey on Adult Skill (PIAAC) how that Italy i characterized both by a large hare of under-killed and of over-killed worker with repect to the competencie required by their job. In addition, Italy eem to be the country in which a reduction of kill mimatch to the lowet cro-country level would be aociated with the highet increae in the allocative efficiency with repect to the other countrie (OECD, 2015). The reaon behind thi kill mimatch can be attributed to the education ytem and/or the functioning of the labour market. Montanari et al. (2015) invetigate the proce of allocation of graduate in the Italian labour market. They how that the lack of adequate kill and experience i a major ource of kill mimatch. At the ame time, the widepread ue of informal election procedure among companie, particularity SME, a well the rigiditie in the labout market, may alo contribute to kill mimatch. On thee iue, ee alo the Country Report on Italy 2016 (European Commion 2016). Our tudy contribute to thi literature by quantifying the level of miallocation in Italy and by providing evidence of uch miallocation. In fact, the role of miallocation ha only recently been invetigated in explaining the productivity lowdown. In recent work following the HK approach, Gopinath et al. (2015) find that between 1999 and 2008 in Italy (a well a in Portugal and Spain) the diperon of the return to capital acro firm increaed gnificantly while the diperon of the return to labour did not change gnificantly over time. They alo find that the increang diperon of the return to capital wa in ome cae accompanied by gnificant productivity loe becaue ome productive and high-return firm were contrained from increang their invetment. In parallel work on Italy, Calligari (2015) document an increae in the extent of miallocation nce the early 1990 that explain a large part of the productivity lowdown. We innovate with repect to both Calligari (2015) and Gopinath et al. (2015). Our accounting framework build on Calligari (2015). However, while Calligari (2015) 14

17 focue only on manufacturing firm, we extend the analy to non-manufacturing. In addition, we further invetigate which firm characteritic or pecific mechanim could reult in reource miallocation. Similarly, while meauring miallocation and relating it to credit friction, alo Gopinath et al. (2015) focu on manufacturing only and do not explore whether other firm characteritic are alo aociated with miallocation. Compared with Gopinath et al. (2015), there are alo three additional difference. Firt, we ue a dataet that cover a longer time pan (nce 1993 rather than 1999). 2 Second, in addition to documenting an increae in diperon in productivity and marginal product, we apply the HK methodology to ae the productivity loe coming from miallocation. Third, we ue another dataet that cover a repreentative ample of manufacturing firm and include a large et of firm characteritic, o that we can relate miallocation to a large et of potential marker. 2 Gopinath et al. (2015) ue data from Amadeu, while we ue data from CERVED. Both provider ue information from the Chamber of Commerce a original ource. 15

18 3 Meauring miallocation Thi ection dicue in detail how we meaure miallocation. In particular, we firt introduce the data we ue. We then explain the conceptual framework behind our meaure of miallocation. Latly, we dicu what our meaure reveal for the evolution of Italian miallocation nce the Data: CERVED We conder the Italian manufacturing and non-manufacturing (i.e. ervice, energy indutrie and contruction firm) ector recorded in the CERVED dataet, which account for the univere of limited companie ( ocietà di capitali ) in Italy. We group manufacturing firm into nine 2-digit ector ung the ATECO 2002 clafication. The manufacturing ector are Textile and leather, Paper, Chemical, Mineral, Metal, Machinery, Vehicle, Food and tobacco, and Wood. 3 A for non-manufacturing, we group firm at the 1-digit clafication becaue a 2-digit clafication 4 would be excevely detailed and would raie problem of low firm number in ome finer ubdivion. The ervice ector we conder are Electricity, ga, water, Contruction, Wholeale and retail trade, Hotel and retaurant, Tranport, torage, communication, Real etate, Health and Social work, Other ervice, Profeonal, cientific and technical activitie, Support ervice. We exclude financial intermediation from our ervice ector, a well a coke and petroleum product and other manufacturing n.e.c. from manufacturing. Thee ector have peculiar behaviour, whoe tudy lie outde the cope of thi paper. A we will dicu in Section 3.2, in order to compute firm-level meaure of TFP, we need meaure of output a well a of labour and capital input. Hence we meaure the labour input ung the cot of labour and the capital tock ung the book value of fixed capital net of depreciation while we take firm value added a a 3 A further level of diaggregation i not adviable given the low number of firm that would characterize many ector at three-digit. 4 1-Digit clafication include ector like contruction, hotel and retaurant, and whole and retail trade. 16

19 meaure of total output. Thee variable are deflated through ector-pecific deflator (with bae year 2007). We clean the databae from outlier by dropping all obervation with negative value for real value added, cot of labour or capital tock. We are left with a pooled ample of 1,555,000 firm-year obervation for manufacturing and 3,677,000 for non-manufacturing over the period The average number of obervation per firm i 12 for manufacturing and 10 for non-manufacturing. To compute firm-level TFP we alo need capital and labour hare at indutry level. We compute the labour hare by taking the indutry mean of labour expenditure on value added meaured at the firm level. We then et the capital hare a one minu the computed labour hare. Table 3-1 and 3-2 preent ectoral decriptive tatitic for average real value added, capital tock and cot of labour over the our period of obervation, both in abolute term and in percentage with repect to the total. The table reveal a higher difference in value added acro ector in non-manufacturing than in manufacturing, reflecting a higher degree of heterogeneity within non-manufacturing. In manufacturing machinery, metal and textile and leather are the ector with the larget number of firm and repreent 62% of the total number of manufacturing firm. Real value added range from a mean of around 0.8m euro in wood to around 4.4m euro in vehicle. Variation in the average capital tock i zable, ranging from around 1m euro in textile and leather to around 4.9 euro in vehicle. The cot of labour varie notably too, ranging between 0.5m euro in wood and 3.2m euro in vehicle. Looking at non-manufacturing, wholeale and retail trade and contruction are the mot numerou ector and repreent 61% of our non-manufacturing ample. Health and ocial work, other ervice and electricity and ga are, intead, an extremely mall fraction of non-manufacturing, le than 1%. Overall, both value added and the cot of labour are around half thoe in manufacturing, but alo in thi cae they exhibit a zable variation: value added range between 0.52m euro for 17

20 hotel and retaurant and 19.4m euro for electricity and ga, while the cot of labour range from 0.3m euro in real etate activitie to 5.6m euro in electricity and ga. The capital tock i alo on average lower for non-manufacturing than for manufacturing, with an average of 1.4m euro, excluding electricity and ga. In order to better undertand the pattern of miallocation, we divide the dataet into geographic and firm ze cell. In particular, we group firm within each indutry into four main Italian macro-area: Northwet, Northeat, Centre, South and Iland 5. We alo divide the firm in the dataet into four group according to firm ze: micro, mall, medium and big 6. We report the ummary tatitic of the main variable divided by geographic area and ze, both in abolute term and percentage, in Table 3-3 (for manufacturing) and Table 3-4 (for non-manufacturing). Around two third of manufacturing firm and half of non-manufacturing firm are located in the Northern area of the country. In thee area, manufacturing firm value added, capital tock and cot of labour are higher than the average. For non-manufacturing, intead, after the Northwet, the Centre i the region that exhibit value added and capital higher than the average. Looking at firm ze, more than 88% of manufacturing firm and almot 95% of non-manufacturing firm are micro or mall, while only 2.2% of manufacturing firm and 1% of non-manufacturing firm are big. However, micro and mall firm account for only around 30% of total value added and input cot, wherea big firm account for around 45%. In Table 3-5 and 3-6 we preent the ummary tatitic of firm clutered by ectorarea and by ector-ze. For mot of the indutrie in manufacturing, the majority of firm are located in the North. Moreover, practically all ector are compoed mainly by micro and mall firm, with the majority of bigger manufacturing firm in concentrated in chemical, food and tobacco and vehicle indutrie. The 5 We ue the ISTAT (National intitute of Statitic) clafication of macro-area. Northwet include the region Liguria, Lombardy, Piedmont and Aota Valley; Northeat include Emilia- Romagna, Friuli-Venezia Giulia, Trentino-South Tyrol and Veneto; Centre include Lazio, Marche, Tucany and Umbria; South and Iland include Abruzzi, Balicata, Calabria, Campania, Molie, Apulia, Sicily and Sardinia. 6 We ue the European Commion clafication of firm according to their turnover. Micro are firm with a turnover 2m Euro, mall 10m Euro, medium 50m Euro, big >50m Euro. See 18

21 ditribution of non-manufacturing firm i much more uniform over the country than in manufacturing. Furthermore, for non-manufacturing the percentage of micro and mall firm i even higher than for manufacturing, and big firm are nearly inexitent. Table 3-7 and 3-8 how the relevance of firm ze by geographic area. In the Northwet more than half of the value added in the manufacturing and the ervice ector come from big firm. Big firm in the ervice ector are particularly relevant alo in the Centre where they account for almot 60% of value added. Finally, Table 3-9 and 3-10 look at the ditribution of value added by firm ze acro geographical area. About 56% of value added produced by big firm in the manufacturing ector come from the Northwet, thi confirm a trong overlap between the Northwet region and big firm. 3.2 Methodological approach Having dicued how firm in Italy are ditributed acro geographic area, ector and ze clae, we now decribe the conceptual framework within which we meaure miallocation at the firm level. A anticipated in the previou ection, we follow Heh and Klenow (2009) (HK) in defining miallocation a the inefficient allocation of productive factor acro firm with different TFP. Inefficiency i determined with repect to the ideal allocation of factor that would reult in a world of frictionle factor market where factor owner worker and owner of capital - were free to provide their ervice to the firm offering them the highet return. In thi ideal allocation, a long a firm face either decreang return or a downward loping demand curve, the value of the marginal product of each factor i equalized acro firm o that the factor remuneration ( price ) i the ame for all firm. Thi i an allocative equilibrium a no factor owner ha an incentive to change the allocation of her factor ervice. It i alo a table allocative equilibrium a any exogenou hock creating gap in the value of a factor marginal product acro firm would trigger a reallocation of that factor from le to more productive firm until it remuneration i again equalized acro all firm. 19

22 Shock that can create uch gap are idioyncratic hock that increae the TFP of ome firm relative to other. A firm with relatively higher TFP are able to offer relatively higher factor remuneration at the pre-hock allocation, they have the opportunity to expand by attracting additional factor ervice away from relatively le productive firm until convergence in the value of factor marginal product retore the equaliation in factor remuneration acro firm. In thi repect, any oberved gap in the value of factor marginal product acro firm reveal a ditorted allocation of factor acro them. Thi inefficient allocation of reource i what we call miallocation and it extent can be meaured by the width of the oberved gap ( wedge ) in the value of factor marginal product between firm. Notice that an increae in miallocation i not necearily aociated with a decreae in firm average TFP. The reaon i that idioyncratic hock that increae the TFP of ome firm, relative to other, can come in two type. Thoe that increae the weight of the right tail of the firm TFP ditribution lead to higher diperon (i.e. higher miallocation) but alo higher average TFP. Shock that, intead, increae the weight of the left tail of the firm TFP ditribution (that i the productivity of the le productive firm) lead to higher diperon (i.e. higher miallocation) but alo lower average TFP. In other word, decreang miallocation can be aociated with either lower or higher average TFP in a given ector, depending on whether the latter i driven by (repectively) a decreae or an increae in the relative number of more productive firm. The problem with thi approach i how to aggregate the gap in the value of the marginal product of the different factor o a to obtain an overall meaure of miallocation. A aggregation require a weighting cheme, the olution require ome aumption on the underlying production tructure. Following again HK, we aume that the production pobilitie of a firm i in ector can be repreented by the contant-return-to-cale Cobb-Dougla production function Y = A K 1 L, where K and L are capital and labour input, α and 1-α (ranging between 0 and 1) are their repective cot hare, and A i the firm TFP meauring how much output the firm can obtain from given input. Under thi aumption the value of TFP i proportional to a geometric average of the value of the marginal product of capital and labour with geometric weight α and 1-α 20

23 repectively. Accordingly, aggregate miallocation can be meaured by looking at the gap in the value of TFP between firm. In particular, it can be captured by diperon of the ditribution of thoe value. Thi diperon ha a direct impact on the ectoral TFP, a the latter can be expreed a a mple function of firm TFP and of the variance of the ditribution of the value of TFP ( TFPR ). Specifically, a detailed in Annex 1, ectoral TFP i a weighted geometric average of firm TFP with weight determined by firm TFPR: 1 M 1 TFPR TFP= A =. A i=1 TFPR 1 Thi can be rewritten a an unweighted geometric average of firm TFP minu the variance of firm TFPR: ln TFP 1 = ln 1 i A 1 var(ln TFPR 2 ) The two term on the right hand de correpond to the two dimenon along which aggregate TFP i determined by firm productivitie a dicued in Section 1.1. On the one hand, given the amount of productive factor - like capital and labour - ued by each firm, aggregate TFP grow when individual firm TFP (the firt term) grow thank to the adoption of new technologie and better bune practice. On the other hand, in the preence of friction in the market for productive factor, aggregate TFP alo depend on how thoe factor are allocated acro firm (the econd term). Formally, the value of TFP for firm i in ector i defined a 7 : TFPR PY = PA = 1 K L. (3.1) 7 The output price P i allowed to differ acro firm a HK aume that firm upply horizontally differentiated product under monopolitic competition. 21

24 Note that thi expreon can be evaluated without econometric etimation a the value of output PY, the capital tock K and the labour input L are directly oberved while the capital hare α can be obtained from α = 1 WL L P Y (ee previou ection). Once TFPRi ha been evaluated for all firm in the ample, we can meaure the aggregate miallocation in the economy a the variance of it ditribution acro firm. However, we are alo intereted in undertanding the extent to which aggregate variance i driven by variation between ector, geographical area and firm ze group or by variation within them. For thi reaon, we clafy firm not only in term of ector but alo in term of geographical area and ze category they belong to. Operationally, we ue ubcript i to index firm, ubcript to index ector and ubcript g to denote area/ze group. Accordingly, TFPRg will refer to the TFPR of firm i in ector and area/ze group g with Ng counting the number of firm in that ector and area/ze group. The aggregate TFPR diperon in the economy can then be decompoed into within-group and between-group component a follow: TotalVar ( TFPR) = 2 N G g VA S g VAg VAg TFPR g TFPR g g=1 VA =1 VAg i=1 VAg Var( TFPR ) g Var( TFPR ) g WITHIN GROUP G VA g VA S VA VA g TFPR g=1 =1 g BETWEEN GROUP g TFPR where G i the number of area/ze group and S i the number of ector. In (2) the overall TFPR variance i decompoed in two part: a weighted average of the 2 (3.2) within-group quared deviation from the group mean TFPR g and a weighted average of the quared deviation of the group mean from the overall mean TFPR. 22

25 Specifically, the within-group component repreent a weighted average of the G group-pecific variance Var ( TFPR ) g, in turn expreed in term of weighted average of the variance within the S ector-pecific TFPR ditribution within the group. The weight are calculated in term of value added ( VA ). When the economy i condered a ngle area/ze group (o that the number of group i equal to one), the within-group component boil down to a mple withinector component, conting of a weighted average of the within-ector variance: Var( TFPR) = S =1 VA VA g g 2 TFPR TFPR. N VA i=1 VA Var( TFPR ) (3.3) Thi i the expreon we ue to meaure aggregate miallocation for the economy Miallocation acro different dimenon We are now ready to apply our conceptual framework to the aement of the pattern of miallocation in the Italian economy during from 1993 to Manufacturing ector We firt invetigate the miallocation pattern in the whole manufacturing ector by computing the TFPR variance a decribed in Equation (3.3). The output of thi exercie i depicted in Figure 3-1, where we alo report the average TFPR baed on the ame weighting cheme ued for the variance. The figure how that: A huge decline in average TFPR occurred in the mid-ninetie, followed by a temporary recovery from 2005 to 2007 and a new fall aociated with the economic cri; Miallocation (a meaured by the variance of TFPR) teadily and teeply increaed between 1995 and 2009 and lightly decreaed, after it peak in 2009, until The ame meaure i ued by HK (2009), although they do not weight acro unit (i.e. the hare ). Thu, compared to HK, our meaure agn more importance to the miallocation in large firm. VA VA 23

26 The order of magnitude of thee trend can be read in Table 3-11, where we report the growth rate of the computed TFPR average and variance, ung two-year average in early and late period. Looking at the different ub-period, we ee that: The drop in average TFPR aociated with the economic cri i ubtantial (-10.5%); Aggregate miallocation increaed by almot 69% between 1995 and 2013 with mot of the increae taking place in the firt decade. Thee reult are motly in line with the preliminary analy in Section 2.3 (baed on the EU-KLEMS data), where in Figure 1-2 aggregate TFP tart declining in A in that figure, we alo find here evidence of a recovery, which i however more ubtantial and bring average TFPR back to it 1995 level. Neverthele, the recovery uddenly topped in 2007 when the economic cri hit the Italian economy. To better undertand the firm-level dynamic behind the aggregate pattern diplayed in Figure 3-1, we compare the firm-level ditribution of TFPR in 1995 with that in Thi comparion, reported in Figure 3-2, how quite clearly that the evolution of TFPR highlighted above (i.e. decreang average and increang variance) mainly occurred through a ring hare of low productivity firm. When the comparion i made, intead, between 2007 and 2013 (ee Figure 3-3), the difference in the hare of low productivity firm i much le pronounced. In fact, recalling what we have een in Figure 3-1, 2007 repreent a critical year for average TFPR but not for it variance a thi keep on growing until Thi ugget that the aggregate decreae in TFPR occurred in the lat year compound a ecular increae in miallocation with a cri-related fall in average firm productivity. In principle, the increang miallocation pattern documented in the aggregate might hide ubtantial difference acro ector, area and firm ze categorie. However, before going into the detail of each dimenon, we implement the decompotion in Equation (3.2) in order to undertand to what extent aggregate miallocation can be traced back to difference in term of TFPR diperon acro the categorie. In 24

27 Figure 3-4 we report the computed within and between component of aggregate TFPR variance for the three dimenon, along the whole period under conderation ( ). The meage i clear-cut a the between component i alway mall compared with the within component with only light difference emerging acro the three dimenon (ee Figure 3-5 and 3-6). Moreover, nce the between component tart growing only after 2000, the increae in aggregate variance occurred between 1995 and 2000 i almot entirely driven by the within component. In order to have ome inght about the trend of miallocation before 1993, we ue the INVIND databae from the Bank of Italy, which cover the period However, thi more extended databae, which we introduce more in detail in Section 5, involve only manufacturing firm above 50 employee for the ector x major manufacturing ector: textile and leather, paper, chemical, mineral, metal, machinery. Figure 3-7 how that for thi reduced ubample of firm, miallocation had a harp increae in 1992 at the time of Italy devaluation and exit from the EMU, but it then went back to the pre-cri level and it bacally remained table between 1987 and Thi confirm that the rie of miallocation i a phenomenon that tarted in the mid- 90 and it wa not a previouly undergoing trend. We now go back to our main databae bae, CERVED, which involve the univere of firm. To better undertand the geographical ditribution of the aggregate pattern, we report the evolution of miallocation within each macro-region - i.e. the term Var ( TFPR ) g - in Figure 3-9 and the correponding evolution of average TFPR in Figure 3-8. It i quite intereting to note that: TFPR in the South i on average alway lower than in the ret of Italy; Miallocation in the Northwet and the Centre grew at a conderably higher rate compared to the other area; Miallocation in the South wa higher than in the ret of Italy at the beginning of the period but, being quite table over time, end up being lower than in the North Italy at the end of the period. 25

28 Thi evidence i confirmed by a graphical inpection of the group-pecific ditribution reported in Figure 3-10 and 3-11, where the increae in the hare of le productive firm on the left tail occurred between 1995 and 2013 i more pronounced in the North, alo after The ame analy can be carried out in term of firm ze categorie (ee Figure 3-12 and 3-13). While mall and medium ze group behave quite milarly in the period under conderation, ome pecificity eem to characterie the TFPR pattern of big firm. In particular: Big firm were relatively le productive (lower TFPR) on average, at the beginning of the period; While the average TFPR of mall and medium zed firm decreaed between 1995 and 2011, the average TFPR of big firm increaed progrevely overcoming that of mall and medium zed firm in the mid-2000; Miallocation grew in all group but grew more within the group of the bigger firm. Condered together, thee finding reveal that the widepread increae in miallocation that took place independently of firm ze received a diproportionate contribution by the TFPR trajectory of big firm. Thi evidence i corroborated by Figure 3-14 and 3-15, where the leftward hift in the ditribution of mall and medium ze firm i more evident but the ditribution look more milar in term of diperon. Since the peak in term of average TFPR within the group of large firm i in 2007, thi difference would have been even more pronounced if one had plotted the ditribution intead of the one. The fact that both the miallocation and the average TFPR of big firm grew between 1995 and 2007 ugget the prominent role played by the more productive among the big firm: their TFPR increaed relatively more than the le productive firm within the ame group, and thi would have required a diproportional increae in their hare of capital and labour. Becaue uch a reource rehuffling did not take place, miallocation grew. 26

29 It ha been often argued that the peculiar pecialiation of the Italian economy i one of the main factor reponble for the productivity lowdown (Faini and Sapir, 2005). To hed light on thi apect, we adopt a ectoral perpective and look at the evolution by indutry of our computed TFPR mean and variance (the term Var ( TFPR) in equation (3.3)). Reult are preented in Figure 3-16 and Important difference in term of ectoral dynamic eem to emerge. To better analye them, we alo report, in Table 3-11, the ectoral growth rate of both the TFPR average and the TFPR variance in different ub-period (tarting and ending with two-year average to mooth over the bune cycle). If we exclude the year after the cri, and compare the average with the average, ome key compotion effect can be highlighted in the miallocation upurge (and productivity lowdown) occurred in the 1990: Cro-indutry heterogeneity in the miallocation pattern i ubtantial; The increae in miallocation in the firt decade after 1995 i more pronounced in the paper, vehicle, chemical and machinery indutrie; The increae in miallocation in paper, vehicle and machinery indutrie coincide, however, with ring average TFPR, and thu it i likely to be driven by the thickening of the right tail of the TFPR ditribution; The average TFPR increae in indutrie uch a paper, vehicle and mineral, whoe relative importance for the economy alo increaed (ee the weight at the bottom of Table 3-11), arguably contrated the general economy-wide downward tendency. A a conequence of the economic cri, average TFPR plummeted in all ector but chemical and textile, and all ector experienced ring miallocation, with the exception of the paper indutry. Indutrie uch a mineral and wood, which were relatively le concerned by the increae in miallocation in the 1990, are the mot affected by the upurge in miallocation in the year of the cri. It i finally worth noting how, during the cri, the indutrie in which miallocation grew the mot are alo the indutrie in which average TFPR decreaed the mot. 27