The Economic Ripple Effects of COVID-19 Francisco J. Buera 1 Roberto - PowerPoint PPT Presentation

The Economic Ripple Effects of COVID-19 Francisco J. Buera 1 Roberto N. Fattal-Jaef 2 Hugo Hopenhayn 4 P. Andrés Neumeyer 3 Yongseok Shin 1 1 Washington University in St. Louis 2 World Bank 3 Universidad Torcuato Di Tella 4 UCLA Universidad Torcuato Di Tella June 3, 2020

Motivation • COVID+non-pharmaceutical interventions (NPIs): ⊲ largest (transitory ?) aggregate shock since... ⊲ more permanent reshuffling of what/how we consume • This paper: ⊲ Ripple effects of a LARGE transitory shock, e.g., Lockdown? ⊲ Ripple effects of a pure reallocation shock? ⊲ How effects depend on policies/institutions?

Motivation: How Bad, For How Long?

Motivation: How Bad, For How Long?

Motivation: Neoclassical Dynamics of Lockdown

Related Literature • See NBER Working Papers 26867-27281

This Paper • Heterogeneous Agents model ⊲ occupational choices ⊲ stochastic ability � with prob. ψ t z t − 1 z t = z ∼ 1 − z − η otherwise ⊲ credit friction: collateral constraints, k t ≤ λ a t ⊲ labor friction: matching friction w/ rest unemployment • Deterministic dynamics following unanticipated shocks: ⊲ Lock-down: fraction φ of all firms becomes Non-Essential (shut-down). ⊲ Reallocation shock: 10% of individuals redraw their productivity, 0 . 87 = ψ 1 < ψ = 0 . 97 • Buera, Fattal-Jaef & Shin (2015)+ (simple version of) Alvarez & Shimer (2011)

Roadmap • Analyze macro and micro implicatons of: 1. one-period lockdown shock, three cases: 1.1 non-essential firms have no income, liable for rental/debt payments (baseline) 1.2 also liable for wage payments, i.e., no wage subsidies/furloughs 1.3 small open economy with tighter credit constraints... 2. Pure reallocation shock...

Agent’s Optimization Problem: Essential � � [ c t ] 1 − σ � z ′ , a ′ � v t ( z , a ) = max a ′ , oc 1 − σ + β Ev t + 1 c t + a t + 1 = max { w t , π t ( z , a t ; r t , w t ) } + ( 1 + r t ) a t − T t where k , l zk α l θ − ( r t + δ ) k − w t l π t ( z , a ; r , w ) = max subject to k ≤ λ a • Full replacement unemployment insurance: w t • Lump-sum taxes with budget balance, T t = w t U t

Agent’s Optimization Problems: Non-Essential • Businesses � � [ c t ] 1 − σ � z ′ , a ′ � v NE ( z , a ) = max a ′ 1 − σ + β Ev 2 1 c 1 + a 2 = − ( r + δ ) k 1 − + ( 1 + r 1 ) a 1 − T 1 • Workers � � [ c t ] 1 − σ � z ′ , a ′ � v W 1 ( z , a ) = max a ′ 1 − σ + β Ev 2 c 1 + a 2 = w 1 + ( 1 + r 1 ) a 1 − T 1 • Non-essential entrepreneurs only pay rental cost, − ( r + δ ) k 1 − ⊲ employment at will (US) or generous government wage subsidies (Europe) • non-essential become essential for t ≥ 2

Labor Market Friction • M t unemployed workers matched to the hiring market M t = γ ( U t + JD t ) • Evolution of Unemployment U t + 1 = U t + JD t − M t • Job Destruction � � � dG E t + dG NE JD t = [ max { l − 1 − l t ( a , z ) , 0 } ] + exiting entrep. t • Walrasian Hiring Market Clearing � � � dG E t + dG NE l t ( a , z ) > 0 [ 1 + l t ( a , z )] = 1 − U t + 1 t � �� � � �� � labor supply labor demand

Labor Market Friction with Rest Unemployment • non-essential workers are not reallocated in the first period • but can be rehired frictionlessly by their previous employers in the second period ⊲ only by surviving firms ⊲ if their net-worth constraint does not bind

Labor Market Friction with Rest Unemployment • M t unemployed workers matched to the hiring market M 1 = γ ( U 1 + JD 1 − R 1 ) M 2 = γ ( U 2 + JD 2 − RH 2 ) where R 1 = job destruction by surviving non-essential firms in t = 1 and � l 0 > 0 max { min { l 2 ( a , z ) , l 0 } − l 1 , 0 } dG NE RH 2 = ψ 2 ⊲ i.e., job destruction by non-essential can be re-hired the following period • Evolution of Unemployment U 2 = U 1 + JD 1 − M 1 U 3 = U 2 + JD 2 − M 2 − RH 2

Calibration Strategy • Parameter values set to match ⊲ distribution and dynamics of U.S. establishments ⊲ unemployment rate in U.S. ( γ ) ⊲ external finance to fixed capital in non-corporate sector in U.S. ( λ ) ◮ also calibration to external finance in developing countries

Roadmap • Analyze macro and micro implicatons of: 1. one-period lockdown shock, three cases: 1.1 non-essential firms have no income, liable for rental/debt payments (baseline) 1.2 also liable for wage payments, i.e., no wage subsidies/furloughs 1.3 small open economy with tighter credit constraints... 2. Pure reallocation shock...

The Lock-Down Shock • Start from stationary allocation • Unexpected shock: fraction φ of businesses considered Non-Essential ⊲ magnitude and persistence of φ still open question ⊲ assume φ = 0 . 3 , 1-period shock → emphasize model’s propagation ⊲ shock realized after occupation and factor demand decisions, but before production • two assumptions about labor costs in the first period: ⊲ are not paid by the firm, e.g., wage subsidies (Europe), furlough (US) ⊲ firm must paid wage bill

Propagation Forces 1. Burst of job destruction+matching friction → rise in Unemployment 2. Imperfect insurance → heterogeneous effect on net-worth 3. Financial Frictions → TFP , investment, rehiring dynamics

Roadmap • Analyze macro and micro implicatons of: 1. one-period lockdown shock, three cases: 1.1 non-essential firms have no income, liable for rental/debt payments (baseline) 1.2 also liable for wage payments, i.e., no wage subsidies/furloughs 1.3 small open economy with tighter credit constraints... 2. Pure reallocation shock...

Lockdown: Aggregate Variables I

Lockdown: Aggregate Variables II

Micro Implications I: Employment by Age Young: less than 5 year old

Micro Implications II: Consumption

Lockdown: Role of Rest Unemployment

Roadmap • Analyze macro and micro implicatons of: 1. one-period lockdown shock, three cases: 1.1 non-essential firms have no income, liable for rental/debt payments (baseline) 1.2 also liable for wage payments, i.e., no wage subsidies/furloughs 1.3 small open economy with tighter credit constraints... 2. Pure reallocation shock...

No Wage Subsidies: Aggregate Variables I

No Wage Subsidies: Aggregate Variables II

Micro Implications: Employment by Age Young: less than 5 year old

Roadmap • Analyze macro and micro implicatons of: 1. one-period lockdown shock, three cases: 1.1 non-essential firms have no income, liable for rental/debt payments (baseline) 1.2 also liable for wage payments, i.e., no wage subsidies/furloughs 1.3 small open economy with tighter credit constraints... 2. Pure reallocation shock...

Small Open Economy: Aggregate Variables I

Roadmap • Analyze macro and micro implicatons of: 1. one-period lockdown shock, three cases: 1.1 non-essential firms have no income, liable for rental/debt payments (baseline) 1.2 also liable for wage payments, i.e., no wage subsidies/furloughs 1.3 small open economy with tighter credit constraints... 2. Pure reallocation shock...

Pure Reallocation Shock • Start from stationary allocation • Unexpected shock: 10% of individuals redraw their productivity, 0 . 87 = ψ 1 < ψ = 0 . 97 ⊲ ∼ 10% of old businesses need to be replace by new ones ⊲ in a neoclassical world there are no aggregate consequences ⊲ process slow by financial and labor frictions • It captures more permanent reshuffling of what/how we consume/produce ⊲ online person academic/business conference ⊲ changes in type of recreation and vacations

Pure Reallocation Shock: Aggregate Variables I

Pure Reallocation Shock: Aggregate Variables II

Summary of Results 1. Fast aggregate recovery (with wage support/flexible employment & rest) 2. but large, persistence effects for young firms 3. fall of interest rate ( ∆ aggregate demand< ∆ aggregate supply) 4. large ripple effect without wage support/inflexible employment 5. capital outflows from financially underdeveloped, small open economies

Work in Progress, Further Extensions • Distribution of welfare costs ⊲ Who gain from wage subsidies, milder ripple effects? • Lockdown of different duration ⊲ Are cost convex in the length? • Capital irreversibility, K t + 1 ≥ ( 1 − δ ) K t ⊲ Extension relevant for the case without wage subsidy, SOE with tighter credit constraint ⊲ Initial drop in the price of capital, further tighten constraints, e.g., Kiyotaki & Moore (1997) • Debt financed support policies ⊲ Further depress investment ⊲ Ameliorate initial fall in consumption of constrained agents