This document analyzes the decline in labor productivity in Italy from 2000-2018 using a vector autoregression (VAR) framework. It discusses previous studies that have examined the relationship between productivity shocks and hours worked in other countries. The document provides context on structural imbalances in Italy's labor market and various reforms that have been undertaken to address issues like low employment levels, regional disparities, and rigid wage bargaining. It aims to explore potential explanations for Italy's ongoing slowdown in productivity growth through different VAR specifications.

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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