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Decline in Labor Productivity in Italy: A Macroeconomic Perspective

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Josue Diwambuena
PhD Candidate in Economics
Faculty of Economics
Free University of Bozen

Francesco Ravazzolo
Full Professor of Econometrics
Department of Economics
Free University of Bozen

Bank of Estonia, 30 January 2020

Published in: Economy & Finance
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Decline in Labor Productivity in Italy: A Macroeconomic Perspective

  1. 1. Decline in Labor Productivity in Italy: A Macroeconomic Perspective Josue Diwambuena1 Francesco Ravazzolo2 1PhD Candidate in Economics Faculty of Economics Free University of Bozen 2Full Professor of Econometrics Department of Economics Free University of Bozen Bank of Estonia, 30 January 2020 Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 1 / 47
  2. 2. Contents 1 CONTEXT 2 DATA 3 EMPIRICAL FRAMEWORK 4 IDENTIFICATION AND ESTIMATION IDENTIFICATION BAYESIAN ESTIMATION 5 BASELINE: VAR with Labor Productivity 6 VAR with Total Hours 7 VAR with Participation rate 8 VAR with Price mark-up Shock 9 VAR with Mismatch Shock 10 CONCLUSION Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 2 / 47
  3. 3. CONTEXT Labor Productivity Growth in Italy (2000Q1-2018Q4) 2000-04 2002-04 2004-04 2006-04 2008-04 2010-04 2012-04 2014-04 2016-04 2018-04 Year -2 -1 0 1 2 3 4 5LaborProductivityGrowth(%) Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 3 / 47
  4. 4. CONTEXT Labor Productivity in Level Italy-US (2000Q1-2018Q4) 2000-04 2002-04 2004-04 2006-04 2008-04 2010-04 2012-04 2014-04 2016-04 2018-04 Year 3.7 3.8 3.9 4 4.1 4.2 4.3 4.4 LaborProductivity -0.3 -0.2 -0.1 0 0.1 Italy US Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 4 / 47
  5. 5. CONTEXT CONTEXT During the last twenty years, Italy experiences a slowdown in labor productivity growth (Daveri et al., 2005; Hall et al., 2009). Several potential explanations: (i) decline Total Factor Productivity (Daveri et al., 2005); (ii) exhaustion of capital deepening (Pianta and Vaona, 2007); (iii) input reallocation due to changes in relative price of labor w.r.t capital following labor reforms (Brandolini et al., 2007); (iv) insufficient R&D investment by Italian firms (Commission, 2006). Italy undertook several reforms to mitigate labor market segmentation and improve labor market conditions (see Schrader and Ulivelli, 2017; Pinelli et al., 2017). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 5 / 47
  6. 6. CONTEXT CONTEXT During the last twenty years, Italy experiences a slowdown in labor productivity growth (Daveri et al., 2005; Hall et al., 2009). Several potential explanations: (i) decline Total Factor Productivity (Daveri et al., 2005); (ii) exhaustion of capital deepening (Pianta and Vaona, 2007); (iii) input reallocation due to changes in relative price of labor w.r.t capital following labor reforms (Brandolini et al., 2007); (iv) insufficient R&D investment by Italian firms (Commission, 2006). Italy undertook several reforms to mitigate labor market segmentation and improve labor market conditions (see Schrader and Ulivelli, 2017; Pinelli et al., 2017). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 5 / 47
  7. 7. CONTEXT CONTEXT During the last twenty years, Italy experiences a slowdown in labor productivity growth (Daveri et al., 2005; Hall et al., 2009). Several potential explanations: (i) decline Total Factor Productivity (Daveri et al., 2005); (ii) exhaustion of capital deepening (Pianta and Vaona, 2007); (iii) input reallocation due to changes in relative price of labor w.r.t capital following labor reforms (Brandolini et al., 2007); (iv) insufficient R&D investment by Italian firms (Commission, 2006). Italy undertook several reforms to mitigate labor market segmentation and improve labor market conditions (see Schrader and Ulivelli, 2017; Pinelli et al., 2017). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 5 / 47
  8. 8. CONTEXT CONTEXT During the last twenty years, Italy experiences a slowdown in labor productivity growth (Daveri et al., 2005; Hall et al., 2009). Several potential explanations: (i) decline Total Factor Productivity (Daveri et al., 2005); (ii) exhaustion of capital deepening (Pianta and Vaona, 2007); (iii) input reallocation due to changes in relative price of labor w.r.t capital following labor reforms (Brandolini et al., 2007); (iv) insufficient R&D investment by Italian firms (Commission, 2006). Italy undertook several reforms to mitigate labor market segmentation and improve labor market conditions (see Schrader and Ulivelli, 2017; Pinelli et al., 2017). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 5 / 47
  9. 9. CONTEXT CONTEXT Structural imbalances in labor market: (i) low level of employment for women and young people; (ii) regional disparity between North-Center and South; (iii) skill mismatch; (iv) highly centralized rigid wage bargaining (Ciccarone et al., 2016; Adda et al., 2017; Schrader and Ulivelli, 2017). Reforms: reform of collective bargaining framework and wage indexation; Treu Package (1997); Biagi Law (2003); Fornero reform; Job Act. Treu Package (1997); Biagi Law (2003): Employment growth ↑ on average to 1.4% per year between 1997-2007; Unemployment ↓ by 6.1% in 2007. Job Act: relaxation of EPL; reduction of atypical contracts; emphasis on active policies to enhance job matching efficiency but labor productivity ↓ still slows down. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 6 / 47
  10. 10. CONTEXT CONTEXT Structural imbalances in labor market: (i) low level of employment for women and young people; (ii) regional disparity between North-Center and South; (iii) skill mismatch; (iv) highly centralized rigid wage bargaining (Ciccarone et al., 2016; Adda et al., 2017; Schrader and Ulivelli, 2017). Reforms: reform of collective bargaining framework and wage indexation; Treu Package (1997); Biagi Law (2003); Fornero reform; Job Act. Treu Package (1997); Biagi Law (2003): Employment growth ↑ on average to 1.4% per year between 1997-2007; Unemployment ↓ by 6.1% in 2007. Job Act: relaxation of EPL; reduction of atypical contracts; emphasis on active policies to enhance job matching efficiency but labor productivity ↓ still slows down. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 6 / 47
  11. 11. CONTEXT CONTEXT Structural imbalances in labor market: (i) low level of employment for women and young people; (ii) regional disparity between North-Center and South; (iii) skill mismatch; (iv) highly centralized rigid wage bargaining (Ciccarone et al., 2016; Adda et al., 2017; Schrader and Ulivelli, 2017). Reforms: reform of collective bargaining framework and wage indexation; Treu Package (1997); Biagi Law (2003); Fornero reform; Job Act. Treu Package (1997); Biagi Law (2003): Employment growth ↑ on average to 1.4% per year between 1997-2007; Unemployment ↓ by 6.1% in 2007. Job Act: relaxation of EPL; reduction of atypical contracts; emphasis on active policies to enhance job matching efficiency but labor productivity ↓ still slows down. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 6 / 47
  12. 12. CONTEXT CONTEXT Structural imbalances in labor market: (i) low level of employment for women and young people; (ii) regional disparity between North-Center and South; (iii) skill mismatch; (iv) highly centralized rigid wage bargaining (Ciccarone et al., 2016; Adda et al., 2017; Schrader and Ulivelli, 2017). Reforms: reform of collective bargaining framework and wage indexation; Treu Package (1997); Biagi Law (2003); Fornero reform; Job Act. Treu Package (1997); Biagi Law (2003): Employment growth ↑ on average to 1.4% per year between 1997-2007; Unemployment ↓ by 6.1% in 2007. Job Act: relaxation of EPL; reduction of atypical contracts; emphasis on active policies to enhance job matching efficiency but labor productivity ↓ still slows down. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 6 / 47
  13. 13. CONTEXT CONTEXT Structural imbalances in labor market: (i) low level of employment for women and young people; (ii) regional disparity between North-Center and South; (iii) skill mismatch; (iv) highly centralized rigid wage bargaining (Ciccarone et al., 2016; Adda et al., 2017; Schrader and Ulivelli, 2017). Reforms: reform of collective bargaining framework and wage indexation; Treu Package (1997); Biagi Law (2003); Fornero reform; Job Act. Treu Package (1997); Biagi Law (2003): Employment growth ↑ on average to 1.4% per year between 1997-2007; Unemployment ↓ by 6.1% in 2007. Job Act: relaxation of EPL; reduction of atypical contracts; emphasis on active policies to enhance job matching efficiency but labor productivity ↓ still slows down. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 6 / 47
  14. 14. CONTEXT SELECTIVE LITERATURE Previous studies analyze co-movement of productivity shocks and hours in US using DSGE and VAR frameworks (Gali, 1999; Christiano et al., 2004; Cantore et al., 2017; Canova et al., 2006; Gambetti, 2006; Peersman and Straub, 2009). Findings are sensitive to VAR specification of hours (i.e. hours in level vs. growth). When in level, hours increases (RBC view) while it falls when otherwise (NK-DSGE view) (Francis and Ramey, 2005; Gali, 1999). Seminal studies like Gali (1999); Christiano et al. (2004) rely on long-run restriction `a la Blanchard and Quah (1989). Uhlig (2004); Peersman and Straub (2009); Canova et al. (2006); Furlanetto et al. (2014) use sign restriction identification. Gal´ı and Gambetti (2009), Cantore et al. (2017) observe time-varying patterns in hours and apply TVP-VAR with long-run restrictions. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 7 / 47
  15. 15. CONTEXT SELECTIVE LITERATURE Previous studies analyze co-movement of productivity shocks and hours in US using DSGE and VAR frameworks (Gali, 1999; Christiano et al., 2004; Cantore et al., 2017; Canova et al., 2006; Gambetti, 2006; Peersman and Straub, 2009). Findings are sensitive to VAR specification of hours (i.e. hours in level vs. growth). When in level, hours increases (RBC view) while it falls when otherwise (NK-DSGE view) (Francis and Ramey, 2005; Gali, 1999). Seminal studies like Gali (1999); Christiano et al. (2004) rely on long-run restriction `a la Blanchard and Quah (1989). Uhlig (2004); Peersman and Straub (2009); Canova et al. (2006); Furlanetto et al. (2014) use sign restriction identification. Gal´ı and Gambetti (2009), Cantore et al. (2017) observe time-varying patterns in hours and apply TVP-VAR with long-run restrictions. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 7 / 47
  16. 16. CONTEXT SELECTIVE LITERATURE Previous studies analyze co-movement of productivity shocks and hours in US using DSGE and VAR frameworks (Gali, 1999; Christiano et al., 2004; Cantore et al., 2017; Canova et al., 2006; Gambetti, 2006; Peersman and Straub, 2009). Findings are sensitive to VAR specification of hours (i.e. hours in level vs. growth). When in level, hours increases (RBC view) while it falls when otherwise (NK-DSGE view) (Francis and Ramey, 2005; Gali, 1999). Seminal studies like Gali (1999); Christiano et al. (2004) rely on long-run restriction `a la Blanchard and Quah (1989). Uhlig (2004); Peersman and Straub (2009); Canova et al. (2006); Furlanetto et al. (2014) use sign restriction identification. Gal´ı and Gambetti (2009), Cantore et al. (2017) observe time-varying patterns in hours and apply TVP-VAR with long-run restrictions. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 7 / 47
  17. 17. CONTEXT SELECTIVE LITERATURE Previous studies analyze co-movement of productivity shocks and hours in US using DSGE and VAR frameworks (Gali, 1999; Christiano et al., 2004; Cantore et al., 2017; Canova et al., 2006; Gambetti, 2006; Peersman and Straub, 2009). Findings are sensitive to VAR specification of hours (i.e. hours in level vs. growth). When in level, hours increases (RBC view) while it falls when otherwise (NK-DSGE view) (Francis and Ramey, 2005; Gali, 1999). Seminal studies like Gali (1999); Christiano et al. (2004) rely on long-run restriction `a la Blanchard and Quah (1989). Uhlig (2004); Peersman and Straub (2009); Canova et al. (2006); Furlanetto et al. (2014) use sign restriction identification. Gal´ı and Gambetti (2009), Cantore et al. (2017) observe time-varying patterns in hours and apply TVP-VAR with long-run restrictions. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 7 / 47
  18. 18. CONTEXT SELECTIVE LITERATURE Previous studies analyze co-movement of productivity shocks and hours in US using DSGE and VAR frameworks (Gali, 1999; Christiano et al., 2004; Cantore et al., 2017; Canova et al., 2006; Gambetti, 2006; Peersman and Straub, 2009). Findings are sensitive to VAR specification of hours (i.e. hours in level vs. growth). When in level, hours increases (RBC view) while it falls when otherwise (NK-DSGE view) (Francis and Ramey, 2005; Gali, 1999). Seminal studies like Gali (1999); Christiano et al. (2004) rely on long-run restriction `a la Blanchard and Quah (1989). Uhlig (2004); Peersman and Straub (2009); Canova et al. (2006); Furlanetto et al. (2014) use sign restriction identification. Gal´ı and Gambetti (2009), Cantore et al. (2017) observe time-varying patterns in hours and apply TVP-VAR with long-run restrictions. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 7 / 47
  19. 19. CONTEXT MAIN CONTRIBUTION MAIN CONTRIBUTION We attempt to provide a plausible macro explanation of the decline in labor productivity in Italy. We apply a large SVAR to understand the behavior of labor productivity to many shocks hitting at same time and do not impose that a given shock is more important a priori. We offer a methodological contribution on how to estimate effects of shocks on labor productivity. We use Italian data since Italy seems an interesting application Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 8 / 47
  20. 20. CONTEXT MAIN CONTRIBUTION The macro literature on the interaction between technology shock and hours worked in Italy is not exhaustive. (See Gavosto and Pellegrini, 1999; Gambetti and Pistoresi, 2004; Di Giorgio and Giannini, 2012). Gavosto and Pellegrini (1999); Gambetti and Pistoresi (2004) apply small SVAR model and mainly identify productivity shock using long-run restriction. We complement literature by applying a large SVAR model on Italy’s recent data using identification based on sign restrictions. We disentangle supply shocks from demand shocks and labor market shocks (Furlanetto et al., 2014; Foroni et al., 2018). We quantify the role of shocks in driving volatility in the business cycle, labor productivity and other variables. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 9 / 47
  21. 21. CONTEXT MAIN CONTRIBUTION The macro literature on the interaction between technology shock and hours worked in Italy is not exhaustive. (See Gavosto and Pellegrini, 1999; Gambetti and Pistoresi, 2004; Di Giorgio and Giannini, 2012). Gavosto and Pellegrini (1999); Gambetti and Pistoresi (2004) apply small SVAR model and mainly identify productivity shock using long-run restriction. We complement literature by applying a large SVAR model on Italy’s recent data using identification based on sign restrictions. We disentangle supply shocks from demand shocks and labor market shocks (Furlanetto et al., 2014; Foroni et al., 2018). We quantify the role of shocks in driving volatility in the business cycle, labor productivity and other variables. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 9 / 47
  22. 22. CONTEXT MAIN CONTRIBUTION The macro literature on the interaction between technology shock and hours worked in Italy is not exhaustive. (See Gavosto and Pellegrini, 1999; Gambetti and Pistoresi, 2004; Di Giorgio and Giannini, 2012). Gavosto and Pellegrini (1999); Gambetti and Pistoresi (2004) apply small SVAR model and mainly identify productivity shock using long-run restriction. We complement literature by applying a large SVAR model on Italy’s recent data using identification based on sign restrictions. We disentangle supply shocks from demand shocks and labor market shocks (Furlanetto et al., 2014; Foroni et al., 2018). We quantify the role of shocks in driving volatility in the business cycle, labor productivity and other variables. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 9 / 47
  23. 23. CONTEXT MAIN CONTRIBUTION The macro literature on the interaction between technology shock and hours worked in Italy is not exhaustive. (See Gavosto and Pellegrini, 1999; Gambetti and Pistoresi, 2004; Di Giorgio and Giannini, 2012). Gavosto and Pellegrini (1999); Gambetti and Pistoresi (2004) apply small SVAR model and mainly identify productivity shock using long-run restriction. We complement literature by applying a large SVAR model on Italy’s recent data using identification based on sign restrictions. We disentangle supply shocks from demand shocks and labor market shocks (Furlanetto et al., 2014; Foroni et al., 2018). We quantify the role of shocks in driving volatility in the business cycle, labor productivity and other variables. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 9 / 47
  24. 24. CONTEXT MAIN CONTRIBUTION The macro literature on the interaction between technology shock and hours worked in Italy is not exhaustive. (See Gavosto and Pellegrini, 1999; Gambetti and Pistoresi, 2004; Di Giorgio and Giannini, 2012). Gavosto and Pellegrini (1999); Gambetti and Pistoresi (2004) apply small SVAR model and mainly identify productivity shock using long-run restriction. We complement literature by applying a large SVAR model on Italy’s recent data using identification based on sign restrictions. We disentangle supply shocks from demand shocks and labor market shocks (Furlanetto et al., 2014; Foroni et al., 2018). We quantify the role of shocks in driving volatility in the business cycle, labor productivity and other variables. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 9 / 47
  25. 25. DATA DATA We use quarterly time series data spanning the period 2000Q1 to 2018Q4. We extract data from 3 main Sources: ISTAT, EUROSTAT, OECD. Macro variables of interest : GDP, Labor Productivity, Hours, Real Wage, Unemployment rate, Vacancies, Participation rate, Investment-Output ratio. All variables are expressed in natural logs (except Unemployment rate, Vacancies and Participation rate) and seasonally adjusted. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 10 / 47
  26. 26. DATA DATA We use quarterly time series data spanning the period 2000Q1 to 2018Q4. We extract data from 3 main Sources: ISTAT, EUROSTAT, OECD. Macro variables of interest : GDP, Labor Productivity, Hours, Real Wage, Unemployment rate, Vacancies, Participation rate, Investment-Output ratio. All variables are expressed in natural logs (except Unemployment rate, Vacancies and Participation rate) and seasonally adjusted. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 10 / 47
  27. 27. DATA DATA We use quarterly time series data spanning the period 2000Q1 to 2018Q4. We extract data from 3 main Sources: ISTAT, EUROSTAT, OECD. Macro variables of interest : GDP, Labor Productivity, Hours, Real Wage, Unemployment rate, Vacancies, Participation rate, Investment-Output ratio. All variables are expressed in natural logs (except Unemployment rate, Vacancies and Participation rate) and seasonally adjusted. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 10 / 47
  28. 28. DATA DATA We use quarterly time series data spanning the period 2000Q1 to 2018Q4. We extract data from 3 main Sources: ISTAT, EUROSTAT, OECD. Macro variables of interest : GDP, Labor Productivity, Hours, Real Wage, Unemployment rate, Vacancies, Participation rate, Investment-Output ratio. All variables are expressed in natural logs (except Unemployment rate, Vacancies and Participation rate) and seasonally adjusted. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 10 / 47
  29. 29. DATA DATA We use quarterly time series data spanning the period 2000Q1 to 2018Q4. We extract data from 3 main Sources: ISTAT, EUROSTAT, OECD. Macro variables of interest : GDP, Labor Productivity, Hours, Real Wage, Unemployment rate, Vacancies, Participation rate, Investment-Output ratio. All variables are expressed in natural logs (except Unemployment rate, Vacancies and Participation rate) and seasonally adjusted. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 10 / 47
  30. 30. EMPIRICAL FRAMEWORK FRAMEWORK Consider the following reduced form VAR: Yt = C + P i=1 AiYt−i + µt (1) (1) is the VAR(P) where Yt is a (N × 1) vector containing all N endogenous variables. C is a (N × 1) vector of constants, Ai for i = 1, ..., P are (N × N) matrices of parameters. P denotes optimal number of lags and µt is a (N × 1) vector of reduced-form residuals with µt ∼ N(0, Σ) where Σ is a (N × N) covariance matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 11 / 47
  31. 31. EMPIRICAL FRAMEWORK FRAMEWORK Consider the following reduced form VAR: Yt = C + P i=1 AiYt−i + µt (1) (1) is the VAR(P) where Yt is a (N × 1) vector containing all N endogenous variables. C is a (N × 1) vector of constants, Ai for i = 1, ..., P are (N × N) matrices of parameters. P denotes optimal number of lags and µt is a (N × 1) vector of reduced-form residuals with µt ∼ N(0, Σ) where Σ is a (N × N) covariance matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 11 / 47
  32. 32. EMPIRICAL FRAMEWORK FRAMEWORK Consider the following reduced form VAR: Yt = C + P i=1 AiYt−i + µt (1) (1) is the VAR(P) where Yt is a (N × 1) vector containing all N endogenous variables. C is a (N × 1) vector of constants, Ai for i = 1, ..., P are (N × N) matrices of parameters. P denotes optimal number of lags and µt is a (N × 1) vector of reduced-form residuals with µt ∼ N(0, Σ) where Σ is a (N × N) covariance matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 11 / 47
  33. 33. EMPIRICAL FRAMEWORK FRAMEWORK Consider the following reduced form VAR: Yt = C + P i=1 AiYt−i + µt (1) (1) is the VAR(P) where Yt is a (N × 1) vector containing all N endogenous variables. C is a (N × 1) vector of constants, Ai for i = 1, ..., P are (N × N) matrices of parameters. P denotes optimal number of lags and µt is a (N × 1) vector of reduced-form residuals with µt ∼ N(0, Σ) where Σ is a (N × N) covariance matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 11 / 47
  34. 34. EMPIRICAL FRAMEWORK FRAMEWORK The structural VAR model is as follow: B0Xt = B(L)Xt−1 + ηt (2) ηt is (N × 1) vector of structural-form innovations with ηt ∼ N(0, Ω) where Ω is a (N × N) covariance matrix and Ω = I. B0 is a (N × N) matrix of parameters containing contemporaneous relationships among endogenous variables. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 12 / 47
  35. 35. EMPIRICAL FRAMEWORK FRAMEWORK The structural VAR model is as follow: B0Xt = B(L)Xt−1 + ηt (2) ηt is (N × 1) vector of structural-form innovations with ηt ∼ N(0, Ω) where Ω is a (N × N) covariance matrix and Ω = I. B0 is a (N × N) matrix of parameters containing contemporaneous relationships among endogenous variables. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 12 / 47
  36. 36. EMPIRICAL FRAMEWORK FRAMEWORK The structural VAR model is as follow: B0Xt = B(L)Xt−1 + ηt (2) ηt is (N × 1) vector of structural-form innovations with ηt ∼ N(0, Ω) where Ω is a (N × N) covariance matrix and Ω = I. B0 is a (N × N) matrix of parameters containing contemporaneous relationships among endogenous variables. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 12 / 47
  37. 37. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION We use Sign restriction identification in order to disentangle supply shocks from demand shocks and labor market shocks. µt can be written as a linear combination of structural-form innovations ηt such that µt = B−1 0 ηt. This implies that the covariance matrix has the following structure Σ = SS . Σ has N(N+1) 2 distinct parameters whereas S has N2. To identify structural shocks, we must impose N(N−1) 2 restrictions on S . Chol(S) applies the Cholesky decomposition and implies that S becomes a lower triangular matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 13 / 47
  38. 38. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION We use Sign restriction identification in order to disentangle supply shocks from demand shocks and labor market shocks. µt can be written as a linear combination of structural-form innovations ηt such that µt = B−1 0 ηt. This implies that the covariance matrix has the following structure Σ = SS . Σ has N(N+1) 2 distinct parameters whereas S has N2. To identify structural shocks, we must impose N(N−1) 2 restrictions on S . Chol(S) applies the Cholesky decomposition and implies that S becomes a lower triangular matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 13 / 47
  39. 39. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION We use Sign restriction identification in order to disentangle supply shocks from demand shocks and labor market shocks. µt can be written as a linear combination of structural-form innovations ηt such that µt = B−1 0 ηt. This implies that the covariance matrix has the following structure Σ = SS . Σ has N(N+1) 2 distinct parameters whereas S has N2. To identify structural shocks, we must impose N(N−1) 2 restrictions on S . Chol(S) applies the Cholesky decomposition and implies that S becomes a lower triangular matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 13 / 47
  40. 40. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION We use Sign restriction identification in order to disentangle supply shocks from demand shocks and labor market shocks. µt can be written as a linear combination of structural-form innovations ηt such that µt = B−1 0 ηt. This implies that the covariance matrix has the following structure Σ = SS . Σ has N(N+1) 2 distinct parameters whereas S has N2. To identify structural shocks, we must impose N(N−1) 2 restrictions on S . Chol(S) applies the Cholesky decomposition and implies that S becomes a lower triangular matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 13 / 47
  41. 41. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION We use Sign restriction identification in order to disentangle supply shocks from demand shocks and labor market shocks. µt can be written as a linear combination of structural-form innovations ηt such that µt = B−1 0 ηt. This implies that the covariance matrix has the following structure Σ = SS . Σ has N(N+1) 2 distinct parameters whereas S has N2. To identify structural shocks, we must impose N(N−1) 2 restrictions on S . Chol(S) applies the Cholesky decomposition and implies that S becomes a lower triangular matrix. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 13 / 47
  42. 42. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION Sign-restriction has recently emerged as a popular identification strategy in the literature (Faust, 1998, Canova and De Nicolo, 2002, Peersman, 2005, Uhlig, 2005, Fry and Pagan, 2011). In Cholesky decomposition, The covariance matrix has the following structure Σ = SIS where I = QQ and Q is an orthonormal matrix. Sign-restriction involves specifying a set of admissible Q matrices (Caldara et al., 2016; Furlanetto et al., 2014). To impose sign-restrictions, we follow Rubio-Ramirez et al. (2010)’s algorithm. Restrictions are imposed on impact only. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 14 / 47
  43. 43. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION Sign-restriction has recently emerged as a popular identification strategy in the literature (Faust, 1998, Canova and De Nicolo, 2002, Peersman, 2005, Uhlig, 2005, Fry and Pagan, 2011). In Cholesky decomposition, The covariance matrix has the following structure Σ = SIS where I = QQ and Q is an orthonormal matrix. Sign-restriction involves specifying a set of admissible Q matrices (Caldara et al., 2016; Furlanetto et al., 2014). To impose sign-restrictions, we follow Rubio-Ramirez et al. (2010)’s algorithm. Restrictions are imposed on impact only. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 14 / 47
  44. 44. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION Sign-restriction has recently emerged as a popular identification strategy in the literature (Faust, 1998, Canova and De Nicolo, 2002, Peersman, 2005, Uhlig, 2005, Fry and Pagan, 2011). In Cholesky decomposition, The covariance matrix has the following structure Σ = SIS where I = QQ and Q is an orthonormal matrix. Sign-restriction involves specifying a set of admissible Q matrices (Caldara et al., 2016; Furlanetto et al., 2014). To impose sign-restrictions, we follow Rubio-Ramirez et al. (2010)’s algorithm. Restrictions are imposed on impact only. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 14 / 47
  45. 45. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION Sign-restriction has recently emerged as a popular identification strategy in the literature (Faust, 1998, Canova and De Nicolo, 2002, Peersman, 2005, Uhlig, 2005, Fry and Pagan, 2011). In Cholesky decomposition, The covariance matrix has the following structure Σ = SIS where I = QQ and Q is an orthonormal matrix. Sign-restriction involves specifying a set of admissible Q matrices (Caldara et al., 2016; Furlanetto et al., 2014). To impose sign-restrictions, we follow Rubio-Ramirez et al. (2010)’s algorithm. Restrictions are imposed on impact only. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 14 / 47
  46. 46. IDENTIFICATION AND ESTIMATION IDENTIFICATION IDENTIFICATION Sign-restriction has recently emerged as a popular identification strategy in the literature (Faust, 1998, Canova and De Nicolo, 2002, Peersman, 2005, Uhlig, 2005, Fry and Pagan, 2011). In Cholesky decomposition, The covariance matrix has the following structure Σ = SIS where I = QQ and Q is an orthonormal matrix. Sign-restriction involves specifying a set of admissible Q matrices (Caldara et al., 2016; Furlanetto et al., 2014). To impose sign-restrictions, we follow Rubio-Ramirez et al. (2010)’s algorithm. Restrictions are imposed on impact only. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 14 / 47
  47. 47. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION BAYESIAN ESTIMATION The model is estimated using Bayesian estimation techniques; all variables are in level and P = 5. We specify diffuse/flat priors so that the information in the likelihood function becomes dominant Priors lead to a Normal-Inverse Wishart posterior with mean and variance parameters corresponding to OLS estimates. We simulate posterior IRFs using 100 draws. Simulations are carried out using Matlab codes of Furlanetto et al. (2014). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 15 / 47
  48. 48. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION BAYESIAN ESTIMATION The model is estimated using Bayesian estimation techniques; all variables are in level and P = 5. We specify diffuse/flat priors so that the information in the likelihood function becomes dominant Priors lead to a Normal-Inverse Wishart posterior with mean and variance parameters corresponding to OLS estimates. We simulate posterior IRFs using 100 draws. Simulations are carried out using Matlab codes of Furlanetto et al. (2014). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 15 / 47
  49. 49. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION BAYESIAN ESTIMATION The model is estimated using Bayesian estimation techniques; all variables are in level and P = 5. We specify diffuse/flat priors so that the information in the likelihood function becomes dominant Priors lead to a Normal-Inverse Wishart posterior with mean and variance parameters corresponding to OLS estimates. We simulate posterior IRFs using 100 draws. Simulations are carried out using Matlab codes of Furlanetto et al. (2014). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 15 / 47
  50. 50. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION BAYESIAN ESTIMATION The model is estimated using Bayesian estimation techniques; all variables are in level and P = 5. We specify diffuse/flat priors so that the information in the likelihood function becomes dominant Priors lead to a Normal-Inverse Wishart posterior with mean and variance parameters corresponding to OLS estimates. We simulate posterior IRFs using 100 draws. Simulations are carried out using Matlab codes of Furlanetto et al. (2014). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 15 / 47
  51. 51. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION BAYESIAN ESTIMATION The model is estimated using Bayesian estimation techniques; all variables are in level and P = 5. We specify diffuse/flat priors so that the information in the likelihood function becomes dominant Priors lead to a Normal-Inverse Wishart posterior with mean and variance parameters corresponding to OLS estimates. We simulate posterior IRFs using 100 draws. Simulations are carried out using Matlab codes of Furlanetto et al. (2014). Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 15 / 47
  52. 52. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION SUMMARY OF FINDINGS Labor market shocks (i.e. wage bargaining and labor supply shocks) are the main drivers of business cycle and labor productivity fluctuations. view view view view view The contribution of labor market shocks in slowing down labor productivity is substantial. The responses of labor productivity to labor market shocks are protracted albeit restrictions are imposed on impact only. The role of mismatch shock in driving volatility in business cycle and vacancies is limited but significant for real wage. Results may have interesting policy implications: to be discussed. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 16 / 47
  53. 53. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION SUMMARY OF FINDINGS Labor market shocks (i.e. wage bargaining and labor supply shocks) are the main drivers of business cycle and labor productivity fluctuations. view view view view view The contribution of labor market shocks in slowing down labor productivity is substantial. The responses of labor productivity to labor market shocks are protracted albeit restrictions are imposed on impact only. The role of mismatch shock in driving volatility in business cycle and vacancies is limited but significant for real wage. Results may have interesting policy implications: to be discussed. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 16 / 47
  54. 54. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION SUMMARY OF FINDINGS Labor market shocks (i.e. wage bargaining and labor supply shocks) are the main drivers of business cycle and labor productivity fluctuations. view view view view view The contribution of labor market shocks in slowing down labor productivity is substantial. The responses of labor productivity to labor market shocks are protracted albeit restrictions are imposed on impact only. The role of mismatch shock in driving volatility in business cycle and vacancies is limited but significant for real wage. Results may have interesting policy implications: to be discussed. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 16 / 47
  55. 55. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION SUMMARY OF FINDINGS Labor market shocks (i.e. wage bargaining and labor supply shocks) are the main drivers of business cycle and labor productivity fluctuations. view view view view view The contribution of labor market shocks in slowing down labor productivity is substantial. The responses of labor productivity to labor market shocks are protracted albeit restrictions are imposed on impact only. The role of mismatch shock in driving volatility in business cycle and vacancies is limited but significant for real wage. Results may have interesting policy implications: to be discussed. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 16 / 47
  56. 56. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION SUMMARY OF FINDINGS Labor market shocks (i.e. wage bargaining and labor supply shocks) are the main drivers of business cycle and labor productivity fluctuations. view view view view view The contribution of labor market shocks in slowing down labor productivity is substantial. The responses of labor productivity to labor market shocks are protracted albeit restrictions are imposed on impact only. The role of mismatch shock in driving volatility in business cycle and vacancies is limited but significant for real wage. Results may have interesting policy implications: to be discussed. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 16 / 47
  57. 57. IDENTIFICATION AND ESTIMATION BAYESIAN ESTIMATION SUMMARY OF FINDINGS Labor market shocks (i.e. wage bargaining and labor supply shocks) are the main drivers of business cycle and labor productivity fluctuations. view view view view view The contribution of labor market shocks in slowing down labor productivity is substantial. The responses of labor productivity to labor market shocks are protracted albeit restrictions are imposed on impact only. The role of mismatch shock in driving volatility in business cycle and vacancies is limited but significant for real wage. Results may have interesting policy implications: to be discussed. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 16 / 47
  58. 58. BASELINE: VAR with Labor Productivity VAR with Labor Productivity Table 1: Sign Restrictions Supply Demand Wage Labor Supply Investment GDP + + + + + Labor Productivity NA NA NA NA NA Price - + - - + Wage + NA - - NA Unemployment NA - - + - Investment/GDP NA - + NA + Table describes the restrictions used for each variable (in rows) to identified shocks (in columns) in our VAR. + and - denote positive and negative restriction respectively. NA denotes unrestricted. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 17 / 47
  59. 59. BASELINE: VAR with Labor Productivity VAR with Labor Productivity: Variance Decomposition Go Back GDP 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Labor Productivity 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Prices 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Wage 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Unemployment 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Investment/Output 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Supply Residual Demand Wage Bargaining Labor Supply Investment Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 18 / 47
  60. 60. BASELINE: VAR with Labor Productivity VAR with Labor Productivity: Historical Decomposition Job Act 2002 2004 2006 2008 2010 2012 2014 2016 -0.03 -0.025 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 Supply Residual Demand Wage Bargaining Labor Supply Investment GDP Growth (w/o Baseline) Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 19 / 47
  61. 61. BASELINE: VAR with Labor Productivity VAR with Labor Productivity: Technology Shock 1 5 10 15 20 25 30 35 -0.01 0 0.01 GDP 1 5 10 15 20 25 30 35 -0.01 0 0.01 0.02 Labor Productivity 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 Investment/Output Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 20 / 47
  62. 62. BASELINE: VAR with Labor Productivity VAR with Labor Productivity: Wage Bargaining Shock 1 5 10 15 20 25 30 35 -5 0 5 10 10-3 GDP 1 5 10 15 20 25 30 35 -0.01 0 0.01 Labor Productivity 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 Investment/Output Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 21 / 47
  63. 63. BASELINE: VAR with Labor Productivity VAR with Labor Productivity: Labor Supply Shock 1 5 10 15 20 25 30 35 -0.01 0 0.01 GDP 1 5 10 15 20 25 30 35 -0.01 0 0.01 0.02 Labor Productivity 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -4 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 Investment/Output Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 22 / 47
  64. 64. VAR with Total Hours Table 2: Sign Restrictions Supply Demand Wage Labor Supply Investment GDP + + + + + Total hours NA NA NA NA NA Price - + - - + Wage + NA - - NA Unemployment NA - - + - Investment/GDP NA - + NA + Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 23 / 47
  65. 65. VAR with Total Hours VAR with Total Hours: Variance Decomposition Go Back GDP 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Total Hours 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Prices 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Wage 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Unemployment 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Investment/output 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Supply Residual Demand Wage Bargaining Labor Supply Investment Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 24 / 47
  66. 66. VAR with Total Hours VAR with Total Hours: Historical Decomposition Job Act 2002 2004 2006 2008 2010 2012 2014 2016 -0.03 -0.025 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 Supply Residual Demand Wage Bargaining Labor Supply Investment GDP Growth (w/o Baseline) Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 25 / 47
  67. 67. VAR with Total Hours VAR with Total Hours: Technology Shock 1 5 10 15 20 25 30 35 -0.01 0 0.01 GDP 1 5 10 15 20 25 30 35 -0.02 0 0.02 Total Hours 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 Investment/output Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 26 / 47
  68. 68. VAR with Total Hours VAR with Total Hours: Wage Bargaining Shock 1 5 10 15 20 25 30 35 -5 0 5 10-3 GDP 1 5 10 15 20 25 30 35 -0.02 0 0.02 Total Hours 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.4 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 Investment/output Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 27 / 47
  69. 69. VAR with Total Hours VAR with Total Hours: Labor Supply Shock 1 5 10 15 20 25 30 35 -5 0 5 10 10-3 GDP 1 5 10 15 20 25 30 35 -0.02 0 0.02 Total Hours 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -4 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.4 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 Investment/output Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 28 / 47
  70. 70. VAR with Participation rate Table 3: Sign Restrictions Supply Demand Wage Labor Supply Investment GDP + + + + + Price - + - - + Wage + NA - - NA Unemployment NA - - + - Investment/GDP NA - + NA + Participation NA NA - + + Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 29 / 47
  71. 71. VAR with Participation rate VAR with Labor Force Participation: Variance Decomposition Go Back GDP 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Prices 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Wage 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Unemployment 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Investment/GDP 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Labor force participation 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Supply Demand Wage Bargaining Labor Supply Investment Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 30 / 47
  72. 72. VAR with Participation rate VAR with Labor Force Participation: Historical Decomposition 2002 2004 2006 2008 2010 2012 2014 2016 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 Supply Demand Wage Bargaining Labor Supply Investment residual GDP Growth (w/o Baseline) Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 31 / 47
  73. 73. VAR with Participation rate VAR with Labor Force Participation: Technology Shock 1 5 10 15 20 25 30 35 -5 0 5 10-3 GDP 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -2 0 2 4 10-3 Wage 1 5 10 15 20 25 30 35 -0.4 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.01 0 0.01 0.02 Investment/GDP 1 5 10 15 20 25 30 35 -0.2 -0.1 0 Labor force participation Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 32 / 47
  74. 74. VAR with Participation rate VAR with Labor Force Participation: Wage Bargaining Shock 1 5 10 15 20 25 30 35 -5 0 5 10-3 GDP 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.01 0 0.01 Investment/GDP 1 5 10 15 20 25 30 35 -0.2 -0.1 0 0.1 Labor force participation Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 33 / 47
  75. 75. VAR with Participation rate VAR with Labor Force Participation: Labor Supply Shock 1 5 10 15 20 25 30 35 -5 0 5 10-3 GDP 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.2 0 0.2 0.4 Unemployment 1 5 10 15 20 25 30 35 -0.02 -0.01 0 0.01 Investment/GDP 1 5 10 15 20 25 30 35 0 0.1 0.2 Labor force participation Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 34 / 47
  76. 76. VAR with Price mark-up Shock Table 4: Sign Restrictions Supply Demand Wage Labor Supply Investment Price mark-up GDP + + + + + + Price - + - - + - Wage + NA - - NA + Unemployment NA - - + - NA Investment/GDP NA - + NA + NA Participation - NA NA NA NA + Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 35 / 47
  77. 77. VAR with Price mark-up Shock VAR with Price mark-up Shock: Variance Decomposition Go Back GDP 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Prices 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Wage 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Unemployment 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Investment/GDP 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Labor force participation 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Supply Demand Wage Bargaining Labor Supply Investment Price Mark-up Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 36 / 47
  78. 78. VAR with Price mark-up Shock VAR with Labor Force Participation: Historical Decomposition 2002 2004 2006 2008 2010 2012 2014 2016 -0.03 -0.025 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 Supply Demand Wage Bargaining Labor Supply Investment Price Mark-up GDP Growth (w/o Baseline) Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 37 / 47
  79. 79. VAR with Price mark-up Shock VAR with Price markup Shock: Price markup Shock 1 5 10 15 20 25 30 35 -0.01 0 0.01 GDP 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -5 0 5 10-3 Wage 1 5 10 15 20 25 30 35 -0.5 0 0.5 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 Investment/GDP 1 5 10 15 20 25 30 35 -0.2 0 0.2 0.4 Labor force participation Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 38 / 47
  80. 80. VAR with Price mark-up Shock VAR with Price markup Shock: Wage Bargaining Shock 1 5 10 15 20 25 30 35 -5 0 5 10-3 GDP 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -4 -2 0 2 10-3 Wage 1 5 10 15 20 25 30 35 -0.2 0 0.2 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 Investment/GDP 1 5 10 15 20 25 30 35 -0.2 0 0.2 0.4 Labor force participation Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 39 / 47
  81. 81. VAR with Price mark-up Shock VAR with Price markup Shock: Labor Supply Shock 1 5 10 15 20 25 30 35 -0.01 0 0.01 0.02 GDP 1 5 10 15 20 25 30 35 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -0.01 0 0.01 Wage 1 5 10 15 20 25 30 35 -0.5 0 0.5 Unemployment 1 5 10 15 20 25 30 35 -0.02 0 0.02 0.04 Investment/GDP 1 5 10 15 20 25 30 35 -0.2 0 0.2 0.4 Labor force participation Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 40 / 47
  82. 82. VAR with Mismatch Shock Table 5: Sign restrictions with mismatch shock Supply Demand Wage Mismatch GDP + + + + Price - + - - Wage + NA - - Vacancies NA NA + - Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 41 / 47
  83. 83. VAR with Mismatch Shock VAR when identifying mismatch shock: Variance Decomposition Go Back GDP 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Prices 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Wage 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Vacancies 1 5 10 15 20 25 30 35 0 0.2 0.4 0.6 0.8 1 Supply Demand Wage Bargaining Matching Efficiency Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 42 / 47
  84. 84. VAR with Mismatch Shock VAR when identifying mismatch shock: Historical Decomposition -0.035 -0.03 -0.025 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 Supply Demand Wage Bargaining Matching Efficiency GDP Growth (w/o Baseline) Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 43 / 47
  85. 85. VAR with Mismatch Shock VAR when identifying mismatch shock: Technology Shock 1 5 10 15 20 25 30 35 0 0.02 0.04 0.06 GDP 1 5 10 15 20 25 30 35 -4 -2 0 10-3 Prices 1 5 10 15 20 25 30 35 -10 -5 0 10-3 Wage 1 5 10 15 20 25 30 35 0 0.5 1 Vacancies Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 44 / 47
  86. 86. VAR with Mismatch Shock VAR when identifying mismatch shock: Wage Bargaining Shock 1 5 10 15 20 25 30 35 0 0.05 0.1 GDP 1 5 10 15 20 25 30 35 -4 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -10 -5 0 10-3 Wage 1 5 10 15 20 25 30 35 0 0.5 1 Vacancies Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 45 / 47
  87. 87. VAR with Mismatch Shock VAR when identifying mismatch shock: Mismatch Shock 1 5 10 15 20 25 30 35 -0.01 0 0.01 0.02 GDP 1 5 10 15 20 25 30 35 -4 -2 0 2 10-3 Prices 1 5 10 15 20 25 30 35 -5 0 5 10-3 Wage 1 5 10 15 20 25 30 35 -0.1 0 0.1 0.2 Vacancies Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 46 / 47
  88. 88. CONCLUSION CONCLUSION We document the decline in labor productivity (in growth and level) in Italy over the last two decade We provide a plausible macro explanation by applying a large SVAR on Italian recent data using sign identification. Labor market shocks have the largest contributions in driving fluctuations in the business cycle and labor productivity. Findings may have appealing policy implications Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  89. 89. CONCLUSION CONCLUSION We document the decline in labor productivity (in growth and level) in Italy over the last two decade We provide a plausible macro explanation by applying a large SVAR on Italian recent data using sign identification. Labor market shocks have the largest contributions in driving fluctuations in the business cycle and labor productivity. Findings may have appealing policy implications Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  90. 90. CONCLUSION CONCLUSION We document the decline in labor productivity (in growth and level) in Italy over the last two decade We provide a plausible macro explanation by applying a large SVAR on Italian recent data using sign identification. Labor market shocks have the largest contributions in driving fluctuations in the business cycle and labor productivity. Findings may have appealing policy implications Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  91. 91. CONCLUSION CONCLUSION We document the decline in labor productivity (in growth and level) in Italy over the last two decade We provide a plausible macro explanation by applying a large SVAR on Italian recent data using sign identification. Labor market shocks have the largest contributions in driving fluctuations in the business cycle and labor productivity. Findings may have appealing policy implications Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  92. 92. CONCLUSION CONCLUSION We document the decline in labor productivity (in growth and level) in Italy over the last two decade We provide a plausible macro explanation by applying a large SVAR on Italian recent data using sign identification. Labor market shocks have the largest contributions in driving fluctuations in the business cycle and labor productivity. Findings may have appealing policy implications Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  93. 93. References Adda, J., Monti, P., Pellizzari, M., Schivardi, F., and Trigari, A. (2017). Unemployment and skill mismatch in the italian labour market. IGIER Bocconi. Blanchard, O. J. and Quah, D. (1989). The dynamic effects of aggregate demand and aggregate supply. The American Economic Review, 79(4):655–73. Brandolini, A., Casadio, P., Cipollone, P., Magnani, M., Rosolia, A., and Torrini, R. (2007). Employment growth in italy in the 1990s: institutional arrangements and market forces. In Social pacts, employment and growth, pages 31–68. Springer. Caldara, D., Fuentes-Albero, C., Gilchrist, S., and Zakrajˇsek, E. (2016). The macroeconomic impact of financial and uncertainty shocks. European Economic Review, 88:185–207. Canova, F. and De Nicolo, G. (2002). Monetary disturbances matter for business fluctuations in the g-7. Journal of Monetary Economics, 49(6):1131–1159. Canova, F., Lopez-Salido, D., and Michelacci, C. (2006). On the robust Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  94. 94. References effects of technology shocks on hours worked and output. Available at SSRN 1002872. Cantore, C., Ferroni, F., and Leon-Ledesma, M. A. (2017). The dynamics of hours worked and technology. Journal of Economic Dynamics and Control, 82:67–82. Christiano, L. J., Eichenbaum, M., and Vigfusson, R. (2004). The response of hours to a technology shock: Evidence based on direct measures of technology. Journal of the European Economic Association, 2(2-3):381–395. Ciccarone, G., Dente, G., and Rosini, S. (2016). Labour market and social policy in italy: challenges and changes. Sim Europe. Policy Brief 2016/02. Commission, E. (2006). European trend chart on innovation. country report, italy. Technical report, Enterprise Directorate-General. Daveri, F., Jona-Lasinio, C., and Zollino, F. (2005). Italy’s decline: Getting the facts right [with discussion]. Giornale degli economisti e annali di economia, pages 365–421. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  95. 95. References Di Giorgio, C. and Giannini, M. (2012). A comparison of the beveridge curve dynamics in italy and usa. Empirical Economics, 43(3):945–983. Faust, J. (1998). The robustness of identified var conclusions about money. In Carnegie-Rochester Conference Series on Public Policy, volume 49, pages 207–244. Elsevier. Foroni, C., Furlanetto, F., and Lepetit, A. (2018). Labor supply factors and economic fluctuations. International Economic Review, 59(3):1491–1510. Francis, N. and Ramey, V. A. (2005). Is the technology-driven real business cycle hypothesis dead? shocks and aggregate fluctuations revisited. Journal of Monetary Economics, 52(8):1379–1399. Fry, R. and Pagan, A. (2011). Sign restrictions in structural vector autoregressions: A critical review. Journal of Economic Literature, 49(4):938–60. Furlanetto, F., Ravazzolo, F., and Sarferaz, S. (2014). Identification of financial factors in economic fluctuations. The Economic Journal. Gali, J. (1999). Technology, employment, and the business cycle: do Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  96. 96. References technology shocks explain aggregate fluctuations? American economic review, 89(1):249–271. Gal´ı, J. and Gambetti, L. (2009). On the sources of the great moderation. American Economic Journal: Macroeconomics, 1(1):26–57. Gambetti, L. (2006). Technology shocks and the response of hours worked: time-varying dynamics matter. Universit`a degli studi di Modena e Reggio Emilia, Dipartimento di Economia . . . . Gambetti, L. and Pistoresi, B. (2004). Policy matters. the long run effects of aggregate demand and mark-up shocks on the italian unemployment rate. Empirical Economics, 29(2):209–226. Gavosto, A. and Pellegrini, G. (1999). Demand and supply shocks in italy:: An application to industrial output. European Economic Review, 43(9):1679–1703. Hall, B. H., Lotti, F., and Mairesse, J. (2009). Innovation and productivity in smes: empirical evidence for italy. Small Business Economics, 33(1):13–33. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  97. 97. References Peersman, G. (2005). What caused the early millennium slowdown? evidence based on vector autoregressions. Journal of Applied Econometrics, 20(2):185–207. Peersman, G. and Straub, R. (2009). Technology shocks and robust sign restrictions in a euro area svar. International Economic Review, 50(3):727–750. Pianta, M. and Vaona, A. (2007). Innovation and productivity in european industries. Economics of Innovation and New Technology, 16(7):485–499. Pinelli, D., Torre, R., Pace, L., Cassio, L., Arpaia, A., et al. (2017). The recent reform of the labour market in italy: A review. Technical report, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission. Rubio-Ramirez, J. F., Waggoner, D. F., and Zha, T. (2010). Structural vector autoregressions: Theory of identification and algorithms for inference. The Review of Economic Studies, 77(2):665–696. Schrader, K. and Ulivelli, M. (2017). Italy: A crisis country of tomorrow? Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47
  98. 98. CONCLUSION insights from the italian labor market. Technical report, Kiel Policy Brief. Uhlig, H. (2004). Do technology shocks lead to a fall in total hours worked? Journal of the European Economic Association, 2(2-3):361–371. Uhlig, H. (2005). What are the effects of monetary policy on output? results from an agnostic identification procedure. Journal of Monetary Economics, 52(2):381–419. Diwambuena and Ravazzolo (FUB) Decline in Labor Productivity in Italy: A Macroeconomic PerspectiveBank of Estonia, 30 January 2020 47 / 47

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