Housing and the Labor Market: Time to Move and Aggregate Unemployment

Transcription

1 Housing and the Labor Market: Time to Move and Aggregate Unemployment Peter Rupert 1 Etienne Wasmer 2 1 University of California, Santa Barbara 2 Sciences-Po. Paris and OFCE search class April 1, 2011

2 Motivation How do relocation frictions and commuting costs affect: Job acceptance decisions? Unemployment? Job creation?

3 Application Accounting for unemployment rates across countries: Mortensen-Pissarides (1999): Benefits and taxes.

4 This Paper Job acceptance depends crucially on commuting time/costs and housing frictions. Strategy depends on distance. Low mobility Job offers less attractive (difficult to relocate) Might commute longer distances High commuting costs an obstacle

5 Findings Low mobility, higher benefits and commute costs More job offers rejected Shorter commute times Higher unemployment Longer unemployment duration Fewer vacancies are created

6 Quantitative findings Taxes and benefits Account for about 1/2 of the differences in unemployment. Can not explain mobility differences. Adding commute costs and frictions: With low commute costs, housing frictions not that important. With high commute costs, housing frictions play a large role. Can account for high unemployment and low mobility in Europe relative to the U.S.

7 Mobility Facts Big difference in mobility rates for the U.S. and E.U.: US Europe Total 15.5% 4.95% Employed workers 17.1% 5.38% Unemployed workers 25.2% 10.94% Out of labor force 11.3% 2.63% Between counties / areas 42% 20.5% U.S.: Census 2000; E.U.: European Community Household Panel ( )

8 Reasons for moving US All pop. (1+) Work related 16.2% Family related 26.3% House related 51.6% Others 6.0% All reasons 100% EU15 Job related 14.3% Personal Reason 31.3% House Related 52.7% Not Available 1.8% All reasons 100%

9 Housing Market Regulation and Mobiliy Regulation index from Djankov, et. al., QJE (2003) 8% Geographic mobility and housing market regulation 7% 6% Mobility rate 5% 4% 3% 2% 1% 0% Housing market regulation

10 Importance of Commuting? Happiness study Kahneman and Krueger, JEP, 2006 Day Reconstruction Study 909 women in Texas

11 Index (0-5) Time (hrs/week) Sex Socialising after work Dinner Relaxing Lunch Exercising Praying Socialising at work Shopping, Cooking Computer at home Housework Childcare Evening commute Working Morning commute

12 Environment: Simplified Model, No Family Shocks Adwelling:bundleofservicesgeneratingutility,fixedata particular location. Commuting time, ρ. Space is symmetric (isotropy): the unemployed have the same chance of finding a job wherever their current residence. ρ will be a sufficient statistic.

13 Model Time is continuous. Individuals discount at r > 0.

14 Model Time is continuous. Individuals discount at r > 0. Can be in one of two states: Employed or Unemployed.

15 Model Time is continuous. Individuals discount at r > 0. Can be in one of two states: Employed or Unemployed. Employed Receive exogenous wage w. Face an exogenous separation rate s. Search (for closer housing).

16 Model Time is continuous. Individuals discount at r > 0. Can be in one of two states: Employed or Unemployed. Employed Receive exogenous wage w. Face an exogenous separation rate s. Search (for closer housing). Unemployed Receive flow b. Receive job offers, indexed by distance to work ρ. Find jobs at Poisson rate p.

17 Search with Frictions in the Housing Market Unemployed: Arrival rate of job offers is Poisson with intensity p Draw from commute time distribution F (ρ) Employed Arrival rate of new housing opportunities: λh. Distributed as G N (ρ).

18 Bellman Equations E(ρ): Valueofemploymentatdistanceρ. U: Valueofunemployment. (r + s)e(ρ) = w τρ+ su + λ H max [0, (E(ρ ) E(ρ))] dg N (ρ ) (r + p)u = b + p max[u, E(ρ )]df (ρ ), where τρ is the total commuting cost.

19 Reservation Strategies Job acceptance, moving strategies: E downward sloping in ρ, E ρ = τ r + s + λ H G N (ρ), E(ρ) ismonotonic,soawell-definedreservationstrategy. For those employed, ρ E (ρ) =ρ. Accept any housing offer that is closer. For those unemployed, E(ρ u )=U. Accept any job offer closer than ρ u.

20 ...Reservation Strategies ρ U determines: job acceptance F (ρ U ); residential mobility rate λ H G N (ρ) overthedistributionof commute distance of employed workers.

21 ...Reservation Strategies Using the fact that E(ρ U )=U, b+p Then, ρ u 0 ρ U [E(ρ ) U]dF (ρ )=w τρ U +λ H [E(ρ ) U]dG N (ρ ). ρ U = w b τ + ρ U 0 λ H G N (ρ) pf (ρ) r + s + λ H G N (ρ) dρ. 0 Higher λ H leads to a higher acceptance rate: Easy to relocate.

22 ...Reservation Strategies Asset values E, U E (! ) U F"!# F"! U ): equilibrium acceptance rate

23 Equilibrium Higher p implies lower ρ U (lower job acceptance). Workers can wait for a closer job! Implies a negative link between ρ U and labor market tightness p (or θ = V U ).

24 ...Equilibrium Assuming free entry of firms job advertising cost, c; output of the match, y; q(θ) probability of the firm meeting a worker: y w r + s = c q(θ)f (ρ U ) This generates a positive link between θ and F (ρ U ): higher job acceptance by workers makes firms more willing to post vacancies.

25 ...Equilibrium F U ): equilbrium job acceptance rate H Labor demand (vacancy supply) Reservation strategy for U

26 Effects of Housing Frictions Proposition 1: An increase in λ H makes the unemployed less choosy about jobs: ρ U / λ H > 0. Proposition 2: An increase in λ H increases job creation: θ/ λ H > 0. Or, firms won t create jobs where people can t find houses!

27 Unemployment Let p = p(θ) =θq(θ), the unemployment rate is: u = s s + p(θ)f (ρ U ),

28 Effects of Housing Frictions on Unemployment Proposition 3: An increase in λ H has two effects on unemployment: raises the job acceptance rate of workers (through a higher thresehold ρ U ), u. raises θ (Proposition 2) and thus job creation, u.

29 ...Unemployment and the Beveridge Curve V Equilibrium H Beveridge curve H u

30 Mobility Rate Steady-state distribution of employed workers living at a distance closer than ρ: Φ(ρ) Φ(ρ) = λ HG N (ρ)+pf (ρ) u 1 u λ H G N (ρ)+s = λ HG N (ρ)+ F (ρ) F (ρ u ) s λ H G N (ρ)+s 1 Φisgovernedbythefollowinglawofmotion: (1 u) Φ(ρ) t = upf (ρ)+(1 u)(1 Φ(ρ))λ H G N (ρ) (1 u)φ(ρ)s

31 Extension: Family Shocks For calibration purposes we add a family shock Moves necessitated by marriage, divorce, children, etc. Poisson arrival with parameter δ Draw from the existing stock of housing vacancies, G S (ρ).

32 Calibration Time period is a month, r = 4% annually. Distributions (note: incorporated a family shock ): G S,thestockofhouses,G N,newhousingoffersandF,job offers in terms of commute time, ρ. Assume F = G N =1 e αρ and G S =1 e (α/3)ρ exponential distribution (α). Use data on commute times to find α.

33 Calibration...Distribution of Commute Times Cumulative probability commute times exponential fit Data

34 Calibration...Distribution of Commute Times Table: Commute time as a fraction of total hours worked US Fr Mean th percentile th percentile Median th percentile th percentile From median commute time and α =9.77 τ = 0.083/2 (w/y) ln 2/α =0.585

35 ...Calibration Each hour of commute time has a utility cost estimated to be half of the hourly wage of workers Vanommeren, Van den Berg, and Gorter (2000) Median commute cost: 0.083/2 (w/y)

36 Gas Prices Cost of commuting higher in Europe? US$/gal. United States 1.80 France 5.60 Belgium 6.17 Germany 5.79 Italy 5.79 Hungary 7.51 Netherlands 6.47 Norway 6.09 Source: German Technical Corporation, 2007

37 More Facts IRS, 2007: standard mileage rate for the use of a car is: 0.485$ per mile 0.21 euro per kilometer Tax authority France (BO Impôts Janvier 2007): for less than 5000 km, euro per kilometer for a 6CV car (rate is progressive with power! from 0.37 to 0.67)

38 ...Calibration The program then finds the parameters of the model to match: U.S. unemployment: 4.2% (average between 1999:Q1 and 2000:Q1). Job hiring rate: pf (ρ U )=1/2.4 monthly = unemployment duration of 2.4 months, which imposes, separation rate = s + quits = Mobility target of 17.1% annually. Matching: p(θ) =Aθ 0.5 and q(θ) =Aθ 0.5. y =1,w =0.6 (exogenous),b =0.25.

39 ...Calibration: Wages, Taxes and Benefits Mechanically adjust wages to account for taxes, t. Labor cost: w(1 + εt) Net wage: w(1 (1 ε)t) Where ε =0.35: A 10% increase in taxes increases labor cost by 3.5% and decreases net wages by 6.5%. and t =0.22. Also allow benefits to affect wages directly w(b) =w US +(1 β)(b b US ) Where β =0.5 isthebargainingpoweroftheworker.

40 Findings: Table: U.S. Calibration Benchmark Higher b Higher b, tax τ 1.5 λ h /2.1 θ h ρ U Unemp Un. Dur Reject Mobility (x 100) Column 1: 24.4 corresponds to 17.7% annual rate Last column:.082 represents one-third of that, the EU rate. Robustness

41 Conclusion Tractable model of the labor market and housing market. Two spatial margins: Commuting Relocation Big effects if both are difficult. Suggests housing policy reform as well as labor market reforms. Future work Allow for anisotropy Long distance vs. short distance moves Cyclical behavior

42 Benchmark Higher b Higher b, tax τ 1.5 λ h /2.1 Changes in β β = β = β = β = β = Changes in = = = = = Changes in α α = α = α = α = α = Back to findings