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Introduction

THE EURO AND FIRM RESTRUCTURING Matteo Bugamelli (BoI), Fabiano Schivardi (Univ. Cagliari) and Roberta Zizza (BoI) “La competitività dell’industria europea: analisi e prospettive” IX Workshop SIEPI - Roma, 27 gennaio 2011. Introduction.

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Introduction

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  1. THE EURO AND FIRM RESTRUCTURINGMatteo Bugamelli (BoI), Fabiano Schivardi (Univ. Cagliari) and Roberta Zizza (BoI)“La competitività dell’industria europea: analisi e prospettive”IX Workshop SIEPI - Roma, 27 gennaio 2011

  2. Introduction Promotion of economic efficiency crucial driver of the European integration process Euro a milestone along this path In this paper We define euro as the end of competitive devaluations We consider whether it has induced significant changes in the productive structure of MS

  3. Main idea Before the euro: competitive devaluations (CD) help to cope with intern. competition, particularly from low wage countries Reliance on CD heterog. at country-sector level Countries adopted different exchange rate policies vis-a-vis the DM (Giavazzi e Giovannini, 1989) Price competition more relevant in some sectors: devaluations more helpful there. Focus on manuf. Euro affected entrepeneurs’ expectations: now CD are precluded within EA but also externally due to a stronger currency Restructuring stronger, the higher reliance on CD?

  4. Preview of the results [1] Little evidence of reallocation across sectors Within sector restructuring (sectoral analysis): stronger productivity growth after the euro in country-sectors that relied more on CD (structural break) This begs the question of what restructuring is and what its effects are

  5. Preview of the results [2] Within sector restructuring - firm-level evidence for Italy Case studies: in successful stories a shift of business focus away from production and toward upstream and downstream activities (design, advertising, marketing, distribution) Matched by changes in the workforce composition Deeper restructuring in low tech sectors Restructuring correlated with better performance

  6. The aggregate data and the sample 12 EA countries + Denmark, Sweden and UK Shortcomings of the control group: small, not random Sectoral data from EU KLEMS: 2 digits Measure of price competition: skill intensity at the sectoral level: if high HK content, competition is on technology & quality more than on prices Reliance on CD: nominal vs real EER devaluation wrt the DM, 80-98 Crucial: entrepreneurs, knowing CD possible to respond to a crisis, postpone costly restructuring Using devaluations over ‘70-’80 similar pattern: country characteristic

  7. Little evidence of cross sectoral reallocation Little modification of the productive structure btw 1998 and 2005 fig Confirmed by dissimilarity indexes fig Countries with higher DEVNOM specialized in low skill activities fig Correlation with reallocation modest fig

  8. Within sector reallocation: the empirical approach Interaction btw country-level (DEV) and sector level (S) reliance on devaluations (Rajan and Zingales, 98) Include country and sector dummies, as well as initial value and lagged growth (95-98) Still open to criticism of omitted variables (competition from emerging economies) Include the 3 non-EA countries (EA dummy) and estimate:

  9. Main variables We proxy restructuring (dep var) with productivity growth (real value added per hour worked) Country indicator on CD: nominal or real? Both ok in theory; empirically little difference, focus on real Sectoral indicators of price competition: 1-skill content (share of hours workerd by persons with college degree). Try also with R&D and ICT: high correlation btw indicatorstable Use US measures to avoid endogeneity issues

  10. Sectoral analysis: results [1] Observations weighted by sectoral employment in 1998 both to estimate population effect and to address potential measurement error Results for skill intensity table Size of the effect (Growth Differential): Spain vs France and non metallic products vs other transportation: implied effect of 1.7% Did it come at the expense of employment? table

  11. Sectoral analysis: results [2] Similar results with R&D and ICT To exclude unobserved autocorrelated process, run the same regression in the pre-euro era: no significant effect Conclude: euro had a positive productivity effect on those country-sectors pairs that relied more on devaluations Next question: how did restructuring occurred? Exploit Italian data: traditional sectors in Italy are one of those pairs

  12. Italian manucturing: case studies In Spring 2007 the Bank of Italy conducted in-depth interviews with entrepreneurs and CEOs of some 40 firms, similar to NBER/Sloan “Pin Factory” project Main goal: assess whether firms were restructuring and how Banca d’Italia (2009) “Reports on Trends in Italian Productive System”, QEF no. 45

  13. Insights from case studies Successful firms enjoy some degree of market power: competition based only on costs is unsustainable Heterogeneous ways of achieving mkt power, but with common feature: shift the focus away from production upstream activities – prodct creation and branding organization of production downstream activities – sale network, post-sales assistence Insights for empirical analysis importance of non production workers process more intense in low-tech sectors ongoing process

  14. Strategy and data Basic idea (Lilien, 82): periods of restructuring characterized by factor reallocation and increased dispersion of firms’ performance Data: Invind survey of manufacturing firms 50+, run yearly by BoI We study time series behavior of restructuring indicators, checking for breaks in 1999 Regression analysis

  15. Quantitative evidence [1] Clear increase in the cross section dispersion fig Did this lead to reallocation? Job creation, job destruction and job reallocation (Davis, Haltiwanger and Schu, 96): no evidence of adjustment (contrary to 1993) fig

  16. Quantitative evidence [2] Changes within the firm? From case studies: reduction in the importance of blue collar workers constant after devaluations, declines quickly afterwards fig Standard deviation also increases Patterns more marked in low tech (LOW) activities fig

  17. Regression analysis Diff-in-diff regressions “alfa1” measures the change in the share of blue-collar workers in the LOW group before and after the euro, as a deviation from the control group Results in line with graphical analysis table Robust to changes in the specification Not reflecting trends in the occupational mix: before the euro, low tech firms reducing blue-collar workers less than others

  18. Restructuring and performance Was restructuring effective in terms of firm performance? Rely on cross sectional analysis to detect correlations Productivity growth 2000-06 on indicators of restructuring Proxies of restructuring Share of blue collar workers (level and change) “Newstrat”: qualitative question in Invind Intensity of product change: within the same sector (SMALLCH) and outside it (LARGECH) Results: support view that restructuring firms recorded higher productivity growth

  19. Conclusions The euro has had a positive impact on restructuring and productivity growth, particularly on those activities that relied more on devaluations Mostly occuring within the firm Surely ongoing process; the effect of the recent crisis? Is the micro evidence specific to Italy?

  20. SECOND PART A statistical digression Banca d’Italia (2009) “Reports on Trends in Italian Productive System”, QEF no. 45

  21. Labor productivity

  22. TFP

  23. Firms’ profits

  24. Export market shares correnti costanti

  25. The Question Is it likely that, due to increasing statistical difficulties in a radiply changing world, the official description of the Italian economy may have exaggerated the actual, worrying situation?

  26. Export deflators Export unit values (UVX) approximation of prices, more imprecise, more intense are composition effects Before revisions: anomalous growth of Italian UVX wrt main European countries and domestic production prices After revisions: more similar dynamics to FR e GE fig smaller decrease in export volume market shares higher growth rate of VA and productivity (in manufacturing +0,6 p.p. per year 1996-2005) fig Since 2005, still problems? New export production prices are (PPIX) more in line with GE e FR and domestic production prices

  27. Capital stock More flexibility in the use of labor input, wage moderation and immigrations (cheaper labor): is all this consistent with reduction in capital productivity? In manufacturing: diverging developments since 2000 wrt to GE, UK, US fig Istat methodoloy in line with international standards Reduction in average duration of capital goods? Sale of capital goods abroad?

  28. Nominal value added and underground economy Istat’s method high quality, but still possible that the estimate of underground economy biases level and growth of productivity? Less ability to quantify the underground economy? High growth of family income among small entrepreneurs in Bank of Italy’s Survey Internationalization, transfer pricing…

  29. Back of envelope calculations: only supply-side, 2000-08 Correction of nominal values: i) Δ (Y/L) in manuf. as in Invind (20+); ii) deflators as Nat Acc.; iii) Δ (Y/L) in rest of private sector = 50% of manufacturing (historical figure) +0,7 pp Δ(Y/L) manufact; +0,4 pp Δ(PIL) Correction of deflators: i) Δ (export deflator) = Δ (PPIX); ii) only smaller correction on import side  +1 pp Δ(Y/L) manufact; +0,2 pp Δ(PIL)

  30. Statistical effect or reality? Statistical effect: upper bound in correction of annual Δ(PIL) in 2000-08: +1,5%: Italy’s performance remains low within OECD tav

  31. GRAZIE PER L’ATTENZIONE matteo.bugamelli@bancaditalia.it

  32. Valori medi unitari all’export dei principali paesi back(a prezzi e cambi costanti)

  33. Revisioni delle stime della produttività del lavoro back(migliaia di euro a prezzi 2000)

  34. Produttività apparente del capitale nel settore manifatturieroback(indice: 1993=100)

  35. Tasso di crescita medio annuo 2001-08back

  36. Share of value added by skill content back

  37. Dissimilarity index wrt EA back

  38. Share of low skill activities and DEVNOM back

  39. Dissimilarity index by skill intensity and DEVREAL back

  40. Sectoral indicators back

  41. Productivity growth back

  42. Employment growth back

  43. Standard deviation of productivity and profits back

  44. Job creation & destructionback

  45. Share of blue collar workers back

  46. Share of blue collar workers by tech intensity back

  47. Share of blue collar workers back

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