Questions and Answers • What forces drove real quantities in the Great Recession? — Shocks to financial markets key drivers, even for variables like labor force participation. — Government shocks not important: because of size and timing (consistent with zero lower bound (ZLB) literature). • Mismatch in the labor market? — Not a first order feature of the Great Recession.
Questions and Answers • What forces drove real quantities in the Great Recession? — Shocks to financial markets key drivers, even for variables like labor force participation. — Government shocks not important: because of size and timing (consistent with zero lower bound (ZLB) literature). • Mismatch in the labor market? — Not a first order feature of the Great Recession. • Low labor force participation reflects response to bad labor market prospects.
Questions and Answers • What forces drove real quantities in the Great Recession? — Shocks to financial markets key drivers, even for variables like labor force participation. — Government shocks not important: because of size and timing (consistent with zero lower bound (ZLB) literature). • Mismatch in the labor market? — Not a first order feature of the Great Recession. • Low labor force participation reflects response to bad labor market prospects. — We account for ‘shift’ in the Beveridge curve without resorting to structural shifts in the labor market.
Questions and Answers • Why was the drop in inflation so moderate?
Questions and Answers • Why was the drop in inflation so moderate? — Prolonged slowdown in TFP growth during the Great Recession.
Questions and Answers • Why was the drop in inflation so moderate? — Prolonged slowdown in TFP growth during the Great Recession. — Rise in cost of firms’ working capital as measured by spread between corporate-borrowing rate and risk-free interest rate.
Questions and Answers • Why was the drop in inflation so moderate? — Prolonged slowdown in TFP growth during the Great Recession. — Rise in cost of firms’ working capital as measured by spread between corporate-borrowing rate and risk-free interest rate. — Both forces exert countervailing pressure on inflation.
Outline • Provide a very crude outline of the model. — focus on the novel labor market features.
Outline • Provide a very crude outline of the model. — focus on the novel labor market features. • Very rough description of the results.
Outline • Provide a very crude outline of the model. — focus on the novel labor market features. • Very rough description of the results. • For details, see the paper.
Labor Market
Labor Market Employment* E* Unemployment* Non,par/cipa/on* U* N*
Labor Market X 1 t U ( ~ Employment* E 0 C t ) ; E* t =0 h # " i 1 " (1 ! ! ) ( C t ) " + ! ! ~ C H C t = t Unemployment* Non,par/cipa/on* U* N* ,Household*labor*force*decision* ,Split*between*U*and*E*determined*by*job,finding*rate.*
Labor Market X 1 t U ( ~ Employment* E 0 C t ) ; E* t =0 h # " i 1 h " # i " (1 ! ! ) ( C t ) " + ! ! ~ C H C t = ! t C H = � 1 � ! � L t t Unemployment* Non,par/cipa/on* U* N* ,Household*labor*force*decision* ,Split*between*U*and*E*determined*by*job,finding*rate.*
Labor Market X 1 t U ( ~ E 0 C t ) ; max 1 Employment* f C t ;L t ;C H t ;B t +1 ;K t +1 ;I t ;l t g t =0 t =0 E* P t C t + P I;t I t + B t +1 ! " R K;t K t + ( L t ! l t ) P t D t + l t W t + R t ! 1 B t ! T t K t +1 = (1 ! $ K ) K t + I t Unemployment* Non,par/cipa/on* U* N* ,Household*labor*force*decision* ,Split*between*U*and*E*determined*by*job,finding*rate.*
Labor Market Employment* E* Unemployment* Non,par/cipa/on* U* N* Bargaining* Three*types*of*worker,firm*mee/ngs:* *i)*E*to*E*,*ii)*U*to*E,*iii)*N*to*E**
Modified version of Hall-Milgrom
Modified version of Hall-Milgrom • Nature of bargaining between workers and firms has the consequence that sensitivity of wages to general business conditions is reduced somewhat.
Modified version of Hall-Milgrom • Nature of bargaining between workers and firms has the consequence that sensitivity of wages to general business conditions is reduced somewhat. • After expansionary shock, rise in wages is relatively small. — Important for capturing the dynamic e § ects of monetary policy and technology shocks.
Estimated Medium-Sized DSGE Model
Estimated Medium-Sized DSGE Model • Standard empirical NK model (e.g., CEE, ACEL, SW): — Calvo price setting frictions, but no indexation. — Habit persistence. — Variable capital utilization. — Working capital. — Adjustment costs: investment, labor force. — Taylor rule.
Estimated Medium-Sized DSGE Model • Standard empirical NK model (e.g., CEE, ACEL, SW): — Calvo price setting frictions, but no indexation. — Habit persistence. — Variable capital utilization. — Working capital. — Adjustment costs: investment, labor force. — Taylor rule. • Our labor market structure.
Estimated Medium-Sized DSGE Model • Standard empirical NK model (e.g., CEE, ACEL, SW): — Calvo price setting frictions, but no indexation. — Habit persistence. — Variable capital utilization. — Working capital. — Adjustment costs: investment, labor force. — Taylor rule. • Our labor market structure. • Estimation strategy: Bayesian impulse response matching. — Shocks to monetary policy, neutral and investment-specific technology. — Our model performs well relative to this metric.
The U.S. Great Recession
The U.S. Great Recession Log Real GDP Inflation (%, y − o − y) Federal Funds Rate (%) Unemployment Rate (%) 5 2.5 9 − 2.76 4 8 2 − 2.78 3 7 1.5 − 2.8 2 6 − 2.82 1 1 5 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 Employment/Population (%) Labor Force/Population (%) Log Real Investment Log Real Consumption 64 67 − 5.6 − 5.5 63 66 62 − 5.7 − 5.52 61 65 − 5.54 − 5.8 60 64 59 − 5.56 − 5.9 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 Log Real Wage Log Vacancies Job Finding Rate (%) G − Z Corporate Bond Spread (%) 4.62 7 8.4 70 4.6 6 8.2 5 4.58 60 4 8 4.56 3 50 2 4.54 7.8 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012 Log TFP Log Gov. Cons.+Investment 4.64 − 4.34 4.62 Data − 4.36 2008Q2 4.6 − 4.38 4.58 4.56 − 4.4 4.54 − 4.42 4.52 2002 2004 2006 2008 2010 2012 2002 2004 2006 2008 2010 2012
U.S. Great Recession: Target Gap Ranges
U.S. Great Recession: Target Gap Ranges The Great Recession in the U.S. Data (Min − Max) Data (Mean) GDP (%) Inflation (p.p., y − o − y) Federal Funds Rate (ann. p.p.) Unemployment Rate (p.p.) 0 0 1 − 0.5 4 0 − 5 − 1 − 1 2 − 10 − 1.5 − 2 0 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 Employment (p.p.) Labor Force (p.p.) Consumption (%) Investment (%) 0 0 0 0 − 1 − 10 − 2 − 1 − 5 − 3 − 20 − 2 − 4 − 30 − 10 − 5 − 3 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 Real Wage (%) Job Finding Rate (p.p.) Vacancies (%) G − Z Spread (ann. p.p.) 0 0 − 5 0 4 − 10 − 5 − 15 − 20 2 − 20 − 40 − 25 0 − 10 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 2009 2010 2011 2012 TFP (%) Gov. Cons. & Invest. (%) 0 0 − 2 − 5 − 4 − 10 − 6 2009 2010 2011 2012 2009 2010 2011 2012 2013
Shocks Driving the Recession • Two financial shocks.
Shocks Driving the Recession • Two financial shocks. • A TFP shock.
Shocks Driving the Recession • Two financial shocks. • A TFP shock. • A government spending shock.
Shocks Driving the Recession • Two financial shocks. • A TFP shock. • A government spending shock. • All shocks are computed from the data.
Shocks Driving the Recession • Two financial shocks. • A TFP shock. • A government spending shock. • All shocks are computed from the data. — But, we must assume time series representations for the shocks, so that agents agents can forecast them in real time.
Monetary Policy in the Great Recession • From 2008Q3 to 2011Q2: — Taylor-type feedback rule subject to the ZLB.
Monetary Policy in the Great Recession • From 2008Q3 to 2011Q2: — Taylor-type feedback rule subject to the ZLB. • After 2011Q2: ‘forward guidance’ — following 1 year transition, ‘Evans rule’
Monetary Policy in the Great Recession • From 2008Q3 to 2011Q2: — Taylor-type feedback rule subject to the ZLB. • After 2011Q2: ‘forward guidance’ — following 1 year transition, ‘Evans rule’ — keep funds rate at zero until either unemployment falls below 6.5% or inflation rises above 2.5%.
Solving the Model • Very substantial nonlinearity due to monetary policy — Zero lower bound and forward guidance.
Solving the Model • Very substantial nonlinearity due to monetary policy — Zero lower bound and forward guidance. • We do stochastic simulation on the actual nonlinear equations, starting in 2008Q3. — Agents forecast future values of shock given history of past shocks.
Solving the Model • Very substantial nonlinearity due to monetary policy — Zero lower bound and forward guidance. • We do stochastic simulation on the actual nonlinear equations, starting in 2008Q3. — Agents forecast future values of shock given history of past shocks. — Use a version of extended path to do the calculations (see paper).
The U.S. Great Recession: Data vs. Model
The U.S. Great Recession: Data vs. Model Figure 8: The U.S. Great Recession: Data vs. Model Data (Min − Max Range) Data (Mean) Model GDP (%) Inflation (p.p., y − o − y) Federal Funds Rate (ann. p.p.) 0 0 1 − 0.5 0 − 5 − 1 − 1 − 10 − 1.5 − 2 2009 2011 2013 2015 2009 2011 2013 2015 2009 2011 2013 2015 Unemployment Rate (p.p.) Employment (p.p.) Labor Force (p.p.) 0 0 4 − 2 − 1 − 2 2 − 4 − 3 0 2009 2011 2013 2015 2009 2011 2013 2015 2009 2011 2013 2015 Investment (%) Consumption (%) Real Wage (%) 0 0 0 − 10 − 5 − 5 − 20 − 30 − 10 − 10 2009 2011 2013 2015 2009 2011 2013 2015 2009 2011 2013 2015 Vacancies (%) Job Finding Rate (p.p.) 0 0 − 10 − 20 − 20 − 40 2009 2011 2013 2015 2009 2011 2013 2015
The U.S. Great Recession: Data vs. Model Figure 8: The U.S. Great Recession: Data vs. Model Data (Min − Max Range) Data (Mean) Model GDP (%) Inflation (p.p., y − o − y) Federal Funds Rate (ann. p.p.) 0 0 1 − 0.5 0 − 5 − 1 − 1 − 10 − 1.5 − 2 2009 2011 2013 2015 2009 2011 2013 2015 2009 2011 2013 2015 Unemployment Rate (p.p.) Employment (p.p.) Labor Force (p.p.) 0 0 4 − 2 − 1 − 2 2 − 4 − 3 0 2009 2011 2013 2015 2009 2011 2013 2015 2009 2011 2013 2015 Investment (%) Consumption (%) Real Wage (%) 0 0 0 − 10 − 5 − 5 − 20 − 30 − 10 − 10 2009 2011 2013 2015 2009 2011 2013 2015 2009 2011 2013 2015 Vacancies (%) Job Finding Rate (p.p.) 0 0 − 10 − 20 − 20 − 40 2009 2011 2013 2015 2009 2011 2013 2015
Decomposing What Happened into Shocks
Decomposing What Happened into Shocks • Our shocks roughly reproduce the actual data.
Decomposing What Happened into Shocks • Our shocks roughly reproduce the actual data. • We investigate the e § ect of a shock by shutting it o § . — Resulting decomposition is not additive because of nonlinearity.
Decomposing What Happened into Shocks • Our shocks roughly reproduce the actual data. • We investigate the e § ect of a shock by shutting it o § . — Resulting decomposition is not additive because of nonlinearity. • Results: — Financial shocks - account for the biggest e § ects on real quantitites. • especially the financial shock measured by interest rate spreads.
Decomposing What Happened into Shocks • Our shocks roughly reproduce the actual data. • We investigate the e § ect of a shock by shutting it o § . — Resulting decomposition is not additive because of nonlinearity. • Results: — Financial shocks - account for the biggest e § ects on real quantitites. • especially the financial shock measured by interest rate spreads. — Government spending - relatively small role.
Decomposing What Happened into Shocks • Our shocks roughly reproduce the actual data. • We investigate the e § ect of a shock by shutting it o § . — Resulting decomposition is not additive because of nonlinearity. • Results: — Financial shocks - account for the biggest e § ects on real quantitites. • especially the financial shock measured by interest rate spreads. — Government spending - relatively small role. — TFP - plays an important role in preventing drop in inflation.
Decomposing What Happened into Shocks • Our shocks roughly reproduce the actual data. • We investigate the e § ect of a shock by shutting it o § . — Resulting decomposition is not additive because of nonlinearity. • Results: — Financial shocks - account for the biggest e § ects on real quantitites. • especially the financial shock measured by interest rate spreads. — Government spending - relatively small role. — TFP - plays an important role in preventing drop in inflation.
Conclusion • Bulk of movements in economic activity during the Great Recession due to financial frictions interacting with the ZLB. — ZLB has caused negative spending shocks to push the economy into a prolonged recession.
Conclusion • Bulk of movements in economic activity during the Great Recession due to financial frictions interacting with the ZLB. — ZLB has caused negative spending shocks to push the economy into a prolonged recession. • Findings based on looking through lens of a NK model: — firms face moderate degrees of price rigidities, — no sticky wages. — endogenous labor force participation, standard labor market variables.
Conclusion • Bulk of movements in economic activity during the Great Recession due to financial frictions interacting with the ZLB. — ZLB has caused negative spending shocks to push the economy into a prolonged recession. • Findings based on looking through lens of a NK model: — firms face moderate degrees of price rigidities, — no sticky wages. — endogenous labor force participation, standard labor market variables. • No (or little) evidence for ‘mismatch’ in labor market.
Conclusion • Bulk of movements in economic activity during the Great Recession due to financial frictions interacting with the ZLB. — ZLB has caused negative spending shocks to push the economy into a prolonged recession. • Findings based on looking through lens of a NK model: — firms face moderate degrees of price rigidities, — no sticky wages. — endogenous labor force participation, standard labor market variables. • No (or little) evidence for ‘mismatch’ in labor market. • Modest fall in inflation is not a puzzle once fall in TFP and risky working capital channel are taken into account.
Royal Economic Society
Unemployment Fluctuations, Match Quality, and the Wage Cyclicality of New Hires Mark Gertler 1 , Christopher Huckfeldt 2 , Antonella Trigari 3 1 New York University, NBER 2 Cornell University 3 Bocconi University, CEPR, IGIER, and Baffi center March 31, 2015 Royal Economic Society Conference 2015
What we do 1. Present new panel data evidence on the cyclical behavior of wages for new hires versus existing workers 2. Develop model of unemployment fluctuations consistent with this evidence 3. Model is variant of Mortensen/Pissarides that features: ◮ Wage stickiness via staggered multi-period contracts (with Nash bargaining) ◮ Job-to-job flows with endogenous procyclical match quality 1 / 25
Why we do it ◮ Long (and controversial!) tradition of incorporating wage stickiness in macro models to improve empirical performance ◮ True for DSGE models (e.g. CEE, SW, GST, GSW, CET) ◮ Also for searching and matching models (e.g, Shimer, Hall) ◮ Pissarides critique: Existing evidence suggests greater cyclicality of wages for new hires than for existing workers (e.g., Bils, 1985) ◮ Most cyclical movement in hours is along the extensive margin ◮ New hires’ wages relevant to this margin ◮ Wages of existing workers may not be allocational for either margin ◮ Justification for wage rigidity based on aggregate data may be misplaced 2 / 25
Addressing the Pissarides critique ◮ Our take: evidence reflects compositional effects associated with procyclical movements in match quality for job changers ◮ Typical regression recover estimate of new hire effect by pooling new hires from unemployment and new hires from other jobs ◮ Job-to-job changes important source of wage growth (Topel and Ward, 1992) ◮ Workers searching on-the-job more likely to find suitable match during expansion (Barlevy, 2002) ◮ Implication: New hire contract effect not separately identified from composition effect 3 / 25
Our approach and main findings ◮ Construct new panel data set that permits distinguishing new hires that are job changers vs. those coming from unemployment ◮ Show no new hire effect for workers hired from unemployment ◮ Key margin for unemployment fluctuations ◮ Suggestive job changers new hire effect due to composition bias ◮ Develop a search and matching model with staggered wage contracting and on-the-job search to explain ◮ Aggregate evidence on unemployment and wage cyclicality ◮ Panel data evidence on new hire wage cyclicality for job changers vs. from unemployment ◮ Current work: results robust with complementarity btwn leisure and consumption (Chodorow-Reich and Karabarbounis, 2014) 4 / 25
Data ◮ Survey of Income and Program Participation, 1990-2012 ◮ 1990-1993, 1996, 2001, 2004, and 2008 panels ◮ Large, representative sample ◮ Interviews every four months ◮ High-frequency structure allows for construction of precise measurements of job tenure and wages ◮ Can separate new hires between job changers and those coming from unemployment ◮ Correct for recalls (Fujita and Moscarini, 2014) 5 / 25
Existing econometric framework, e.g. Bils (1985) log w ijt = x ′ ijt π x + π u · U t + π n · I ( new ijt )+ π nu · I ( new ijt ) · U t + α i + e ijt ◮ x ijt : observables for individual i in job j at time t ◮ I (new ijt ): indicator for new hire ◮ α i : person fixed effect Key finding: π nu < 0 Two observations: 1. New hire interaction does not vary by type of job transition 2. Unobserved match quality ⇒ possible estimation bias for job changers 6 / 25
“Bils regressions” and new hire effect 1990-2012 sample (1) (2) Unemployment rate -0.162*** -0.448*** (0.0582) (0.0920) Unemp. rate · I ( new ) -1.247*** -0.997** (0.2477) (0.4465) Estimator FE FD No. observations 379,104 321,397 Robust standard errors in parenthesis * p < 0.10, ** p < 0.05, *** p < 0.01 ◮ Pissarides (2009) interpretation: flexible wages for new hires 7 / 25
Our econometric framework log w ijt = x ′ ijt π x + π u · U t + π EE · I ( new ijt & EE ) + π ENE · I ( new ijt & ENE ) n n + π EE nu · I ( new ijt & EE ) · U t + π ENE · I ( new ijt & ENE ) · U t nu + α i + e ijt ◮ Allow separate coefficients for new hires from employment (EE) and new hires from non-employment (ENE) ◮ Estimate in fixed effects and first differences ◮ Several measures of EE and ENE 8 / 25
Job changers (EE) vs. new hires from unempl. (ENE) 1990-2012 sample (1) (2) (3) (4) UR -0.160*** -0.160*** -0.159*** -0.159*** (0.0582) (0.0582) (0.0582) (0.0582) UR · I ( new & EE ) -1.921*** -1.927*** -1.920*** -1.926*** (0.4696) (0.4403) (0.4696) (0.4403) UR · I ( new & ENE ) -0.326 0.120 -0.487 0.005 (0.5086) (0.5636) (0.5616) (0.6353) UR · I ( new & LTU ) – – 0.963 0.964 – – (1.1325) (1.1325) P ( π EE nu = π ENE ) 0.019 0.004 0.046 0.011 nu Unemp spell for ENE 0+ 1+ (0,9] (1,9] No. observations 375,649 375,649 375,649 375,649 No. of fixed effects 56,878 56,878 56,978 56,878 Robust standard errors in parenthesis * p < 0.10, ** p < 0.05, *** p < 0.01 9 / 25
Composition bias and new hire effect for job changers log w ijt = x ′ ijt π x + π u · U t + π n · I ( new ijt ) + π nu · I ( new ijt ) · U t + α i + e ijt e ijt = q ij + ε ijt ◮ q ij : unobserved match quality ◮ Procyclical match quality ⇒ Cov(∆ q ij , I ( new ijt ) · ∆ U t ) < 0 ◮ Cov(∆ q ij , I ( new ijt ) · ∆ U t ) < 0 ⇒ ˆ π nu biased downward Diagram 10 / 25
Model ◮ Starting point: RBC with search and matching, perfect consumption insurance (Merz, 1995; Andolfatto, 1996) ◮ Variations: ◮ On-the-job search with variable match quality (Barlevy, 2002; Moscarini and Postel-Vinay, 2013) ◮ Staggered Nash wage bargaining (Gertler and Trigari, 2009) ◮ No wage flexibility for new hires! ◮ Evaluate model’s ability to match micro and macro data 11 / 25
Vacancies, searchers and matching ◮ Each firm employs n t workers in good matches and b t workers in bad matches ◮ Labor quality l t l t = n t + φb t 0 < φ < 1 with γ t = b t = (1 + φγ t ) n t with n t ◮ Posts υ t vacancies ◮ Random search: learns quality after match ◮ Probability of good match, ξ ◮ Exogenous separation probability, 1 − ν 12 / 25
Vacancy, searchers and matching, cont. ◮ Searchers: � � + νς bt ¯ n t + ¯ ¯ s t = u t ¯ b t + νς n ¯ n t + (1 − ν ) ς u ¯ b t ���� � �� � � �� � unemployed OTJ search separated within period ◮ Matching function: s σ υ 1 − σ m t = σ m ¯ ¯ t ¯ t ◮ Job finding rates for good and bad: p n = ξ ( ¯ m t / ¯ s t ) t p b = (1 − ξ ) ( ¯ m t / ¯ s t ) t ◮ Job filling rates for good and bad: q n = ξ ( ¯ m t / ¯ υ t ) t � � 1 − νς bt ¯ b t + νς n ¯ n t q b = (1 − ξ ) ( ¯ m t / ¯ υ t ) t ¯ s t 13 / 25
Firms ◮ Firms choose hiring rate x t and capital k t to max firm value F t � �� � − w t l t − r t k t − κ t l 1 − α z t k α 2 x 2 F t = max t l t + E t Λ t,t +1 F t +1 t x t ,k t Laborforce: l t +1 = ( ρ t + x t ) l t ( ρ t is retention rate) more s.t. Composition: γ t +1 = γ ( γ t , x t , ρ n t , ρ b t , q n t , q b t ) ( γ t ≡ b t /n t ) ◮ Optimal hiring and capital: κx t = E t { Λ t,t +1 J t +1 } r t = αz t ˇ k α − 1 t with J t ( γ t , w t , s t ) ≡ F ( l t , γ t , w t , s t ) k t ≡ k t ˇ and l t l t 14 / 25
Workers ◮ Value of unemployment � � �� t ¯ t ¯ p n V n t +1 + p b V b U t = u b + E t Λ t,t +1 t +1 + (1 − p t ) U t +1 ◮ Value of worker in a match of type i = n, b V i = w it − [ νc ( ς it ) + (1 − ν ) c ( ς u )] t � � � � t ¯ (1 − ς it p n t ) V i t +1 + ς it p n V n + E t Λ t,t +1 ν t +1 � ��� ς u p n t ¯ V n t +1 + ς u p b t ¯ V b + (1 − ν ) t +1 + (1 − ς u p t ) U t +1 15 / 25
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