Empirical and policy aspects of labour supply by nikeborome

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									  Topic 1 - Empirical and policy
    aspects of labour supply
   Professor Christine Greenhalgh
P Cahuc and A Zylberberg (2004) Labor Economics,
  Chapter 1 Labor Supply, part 2.
D Bosworth, P Dawkins and T Stromback (1996)
  The Economics of the Labour Market Chapter 5
A Manning (2003) Monopsony in Motion, Chapter 4:
  The Elasticity of the Labor Supply Curve to an
  Individual Firm.
T Boeri and J van Ours (2008) The Economics of
  Imperfect Labour Markets, Chapter 5: Regulation
  of Working Hours; Chapter 7: Family Policies.
   Estimating aggregate labour
 supply elasticities – why useful?
• Future planning/projection of employment
  and unemployment under changing policy
• Responses to fiscal policy affecting net pay
  – Will a more progressive income tax affect
    average hours of work?
  – Does income support for lone parents affect
    decisions to participate in work?
• Policies towards working hours, retirement
  – Should we relax mandatory retirement?
Trends in Male and Female
    Participation (US)
  Patterns of work in G5 countries
          Source: Boeri and van Ours Table 5.2

           1955   2005     %    Weekly Weeks
          Annual Annual Change hours (2002)
France     2040   1434   - 12.1  36.2   40.5
Germany   2265      1437       - 16.6     36.5   40.6
Japan     2081      1775       - 6.1
UK        2156      1624       - 10.6     38.2   40.5
US        2030      1790       - 4.8
Weekly working hours of women
 and men aged 18-64 in Britain
         Source: G Paull in Economic Journal Feb 2008

          No          Pre-         Sch          Post
          Kids        Sch          Age          Kids
           W     M     W      M     W      M     W      M

Hours
per        38    43    25     47    28     47    33     47
week
% FT
(>31h)     85    91    34     96    41     97    58     96
     Basic labour supply theory
Supply of work responds to the hourly wage but sign
  of this effect is ambiguous because
   – Substitution effect is positive (higher wage
     leads to more work)
   – Income effect is negative (higher income leads
     to less work and more leisure)
   – So may observe ‘backward-bending’ supply
     curve if plotting Wage v Hours Worked
   – Or ‘hump-shape’ if plotting Hours Worked v
     Wage (Cahuc and Zylberberg)
 Econometrics - Issues with Data
       and Estimation
Necessary variables:
  hours of work, h
  the individual’s hourly wage, w
  income other than the wage, R
  vector of personal characteristics, θ
  (e.g. married, children)
Estimate:
      ln h = αw ln w + αR ln R + x.θ + ε
      Tricky bits in relation to
    the wage elasticity of hours
• Hours and wages are not observed for those
  choosing zero hours of work
• Observed ε is a random error but without a fully
  observed distribution (observe all positive
  elements but not larger negative ones)
• If estimate by OLS this gives biased estimate as
  violates basic assumption of statistical model
• Can use estimation techniques that deal with these
  ‘truncation biases’
• Can estimate jointly a model of decision to
  participate and hours worked
• Then have to estimate a potential wage for all
  those who chose not to work (based on their θ)
      Tricky bits in relation to
    the ‘other income’ elasticity
• Other income R is f(wealth) so depends on the
  age/ stage of life cycle of person, past job history
  and savings, not all exogenous
• Again OLS model relies on lack of correlation
  between RHS variables and the error term ε, so
  more biases
   – Use a more complex inter-temporal model
   – Replace R with an estimate of MU of wealth
   – Take first differences of equation (panel data)
 Tricky bits in relation to the tax
             structure
• Both the net wage received and the level of
  income other than the wage are affected by
  taxes and benefits
• Replace w with w(1- t) and R with R+S
• Those with high w.h will have a high t and a
  low S and vice versa
• Problem for estimation is that each person
  has chosen where on these schedules to put
  themselves by working more or less hours
    Priors about relative wage
  elasticity for men v. women?
• Suppose labour supply is backward bending
  (hump–shaped in hours v wages)
• Know that men tend to earn more than
  women per hour due to more continuous
  work experience
• Expect men to be on the flat part of curve
  (i.e. zero wage elasticity?)
• Expect women to be on the upward sloping
  part (i.e. positive wage elasticity?)
 Aggregate supply elasticities for
    married women and men
      Source: Cahuc and Zylberberg Tables 1.1 & 1.2

            MW         MW          MM          MM
            wage      Income       wage      income
US         0.97 to    - 0.12 to    0.0 to     0.0 to
            0.99        - 0.33      0.05      - 1.03
UK         0.09 to     - 0.2 to     0.02      - 0.29
            2.03         - 0.4
EU         0.05 to     -0.2 to    0.08 to    - 0.01 to
(miscel)    1.00        - 0.3      0.12        - 0.04
           Uncompensated and
        compensated wage elasticity
      Source: Bosworth, Dawkins & Strombach Tables 5.1, 5.2

      Women Women Women               Men        Men      Men

      Wage      Pure       Income     Wage       Pure     Income
                Subn                             Subn
Ist   0.2 to    0.1 to     - 0.1 to   0.0 to     0.0 to   0.0 to
Gen   0.9       2.0        - 0.2      - 0.4      0.4      - 0.2
2nd   0.6 to    0.7 to     - 0.1 to   - 0.2 to   0.1 to   - 0.1 to
Gen   1.1       1.2        - 0.2      - 0.5      0.2      - 0.4
   Interpretation of trends using
   wage and income elasticities
• Over time men’s and women’s wages have
  increased with productivity growth
• Women’s wages have increased relative to
  those of men in advanced countries
• At the same time average non-wage income
  from assets has tended to increase (more
  home owners and more saving for
  retirement)
• Prediction using sum of wage and income
  elasticities is that men will work less and
  women will work more – fits the facts
Implications for income taxation
• Most countries use progressive rather than
  proportional taxation
• Larger wage elasticities for women suggest
  higher proportional responses in female
  labour supply (absolute responses similar,
  as noted in Bosworth et. al)
• Estimates (Sweden) of effect of existing
  taxes - % decrease in hours worked - cp.
  with: Proportional No tax Lump Sum
    Males      -6.2    -13.4     -13.6
    Females    -9.3    -23.0     -23.3
 Implications for income support
• Many countries support incomes of the low
  paid e.g. supplementary income payments
  or tax benefits for families with children
• Historical problem of disincentive to work
  or to increase hours if working
• UK has moved strongly to Welfare to Work
  approach to avoid trade-offs in participation
• System makes benefits higher if in work
  rather than non-participant
• Lower marginal rates of withdrawal of
  benefits as weekly earnings rise
Estimating labour supply to firms
      What are the issues?
• Competition v Monopsony – which model
  fits labour supply to firms?
• If firm has no monopsony power then it
  pays going wage – elasticity of labour
  supply is infinite to the firm
• General presumption is that men are mobile
  between firms, but women are less so
• If true, this reverses above estimates, with
  higher labour supply elasticity to firms for
  men
• Need to know for estimating effects of
  minimum wages and union bargaining
       Monopsony evidence?
• Employer size wage effect – consistent
  empirical evidence that larger firms pay
  higher wages
• Competitive labour market => firms
  employing more or fewer workers should
  pay same wage
• Other features can explain size-wage effect
     - Higher labour quality in large firm
     - Compensation for disamenity of size
     - Rent sharing by larger profitable firm
  Manning’s estimates of labour
    supply elasticity to firms
• Regressions of employer size on wages
• Controls for personal characteristics,
  education, region, industry and occupation
• In US 1.0 to 1.6; in UK 1.9 to 2.7
     (Manning Table 4.5 col. 3)
• More complex estimation using model of
  separations into other jobs and non-
  employment
• In US 0.7 to 1.4; in UK 0.8
      (Manning Table 4.10 row 3)
   Implications of these supply
            elasticities
Under monopsony:
      Wage = [1/(1+e)] . MPL
      e = 1/ αw
where αw is supply elasticity to firm
(Perfectly comp. αw infinite and wage = MPL)
  UK most elastic case is αw = 2.7
  Wage is only 73% of MRP
  Lower values of αw give worse ratios
Even Manning thinks these αw are too low!
Firm Supply Elasticity Differences
   between Women and Men?
• Heterogeneous preferences for ‘leisure’? In
  truth much leisure is spent in home work
• Women have greater compar. advantage in
  home work? Combining home care and
  work leads to constraints on job mobility
• Travel-to-work times are lower for women
  than men and lowest for women with kids
• Motivation for work differs – men place
  higher value on monetary reward; women
  more influenced by non-pecuniary factors
          Policy aspects (1)
     Regulation of Working Hours
European Working Time Directive:
• limit of average 48 hours a week which a worker can be
  required to work (can voluntarily work more if want to)
• limit of an average of eight hours’ work in 24 which
  nightworkers can be required to work
• right to at least one day off each week
• right to a rest break if working day is longer than six
  hours
• right to 11 hours of rest per day
• right to four weeks of paid leave per year
NB Table 5.1 of Boeri and van Ours is out of date re UK
      Policy aspects (2)
 Work-Life Balance in Families
• Should there be more opportunities for
  parents to work shorter hours?
• Are women happy to work part-time?
• Are men happy to work part-time?
• What jobs are available to part-timers?
• What can legislation do to change what is
  on offer?
  Part-time Employment in G5
          Source: Boeri and van Ours Table 5.3

               % PT      % PT      Invol. PT %
                 M         W         M           W
France           5         23        53          39
Germany          7         39        18          13
Japan            14        42        19          4
UK               10        39        24          10
US               8         18         7          8

								
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