The International Wage Flexibility Project - PowerPoint PPT Presentation

1 / 37
About This Presentation
Title:

The International Wage Flexibility Project

Description:

On the other hand, inflation may distort usefulness of price signals thus ... panel meta-analysis of causes and consequences of rigidity and sand ... – PowerPoint PPT presentation

Number of Views:94
Avg rating:3.0/5.0
Slides: 38
Provided by: wdic
Category:

less

Transcript and Presenter's Notes

Title: The International Wage Flexibility Project


1
The International Wage Flexibility Project
  • Presentation at Workshop on Downward Nominal Wage
    Rigidity
  • Norges Bank, 12 June 2003

2
What?
  • 13 Country study of wage inflation
  • Using micro data on individual and occupational
    wages
  • Intent is to study the nature, extent, and
    implications of wage rigidity in the presence and
    absence of inflation

3
Country Teams
  • Austria
  • Belgium
  • Denmark
  • Finland
  • France
  • Germany
  • Italy
  • Norway
  • Portugal
  • Sweden
  • Switzerland
  • United Kingdom
  • United States

4
Who Is On Norwegian Team?
  • Jan Morten Drystad Norwegian Institute of Science
    and Technology
  • Steinar Holden University of Oslo
  • Kjell Salvanes Norwegian School of Economics and
    Business

5
Starting Point for Some History GS
  • Groshen and Schweitzer / Grease and Sand
  • As some have suggested, inflation may grease
    economy and facilitate relative price adjustment
  • On the other hand, inflation may distort
    usefulness of price signals thus fouling the
    works (sand)

6
What Groshen and Schweitzer Did
  • Analyze firm level data on wages paid in
    different occupations.
  • Estimate an analysis of variance model of within
    firm occupational wage changes with firm and
    occupation effects (ie. regression with firm and
    occupation dummy variables).

7
What they Were Looking For
  • If firms make more errors in setting wages when
    inflation is high, the variance of the
    coefficients on the firm dummies should grow with
    the rate of inflation.
  • If inflation facilitates relative wage
    adjustments then the variance of the coefficients
    on the occupation dummies should increase with
    inflation.

8
What They Found
  • Both the variance of the coefficients of
    occupations and firms increased with inflation
  • Welfare effects of sand and grease comparable and
    roughly offsetting
  • Several tests suggest the identification strategy
    is appropriate

9
History of Project(continued)
  • Erica and Mark begin recruiting project teams
    (Fall 2000).
  • Erica and Mark share plans for project with me
    and I suggest broadening the range of questions
    to be addressed (Winter 2001)

10
History of Project(continued)
  • Im invited to help with project planning
  • In line with new concept of project we recruit
    additional country teams
  • Organizational meeting held at ECB 22-23 October
    2001

11
At The Meeting
  • Country teams presented
  • descriptions of data available
  • descriptions of wage setting institutions
  • preliminary attempts to replicate Groshen-
    Schweitzer
  • wage change histograms
  • Some Very Interesting Patterns Emerged

12
Observations
  • Preliminary analysis suggested sand more
    important than grease, but data werent uniformly
    good for replication of G-S (few and inconsistent
    occupational categories)
  • Nearly all countries had micro data on individual
    wage histories
  • Several country teams expressed concern that G-S
    identification strategy wouldnt work given their
    wage setting institutions
  • It became clear that focusing on Sand and Grease
    alone would miss much of what is important about
    wage rigidity in Europe.

13
(No Transcript)
14
(No Transcript)
15
(No Transcript)
16
(No Transcript)
17
Five Types of Wage Rigidity
  • Nominal Rigidity
  • Menu costs
  • Downward nominal rigidity
  • Real Rigidity
  • Downward real rigidity
  • Insensitivity to fundamentals (unemployment and
    productivity)
  • Bargained or legislated wage floors

18
(No Transcript)
19
First Attempt To Estimate Rigidity Had Several
Problems
  • We tried to adapt Altonji and Deveraux ML method
    to include real rigidity
  • Couldnt tell real rigidity or measurement error
    from non-normality in notional wage distribution
    (this became obvious at authors meeting in Bonn
    last October).
  • Also, discussions at meeting last fall suggested
    that in many countries real rigidity didnt take
    form assumed in model.

20
New ApproachUse information in correlation
between years
  • Abowd and Card (1989) suggest that wage changes
    have two components
  • permanent changes
  • transient (one period) changes (which result in
    negative serial correlation of wage changes)
  • New method identifies transient changes as errors
    and uses covariance and frequency of sign
    switching in changes to identify error rate and
    error variance.
  • This information is used to identify
    non-parametric estimate of true wage
    distribution.

21
Validating Primary Assumption
  • Results for US largely fit with those of other
    studies (nearly complete downward nominal
    rigidity).
  • German data has virtually no errors and estimated
    covariances are tiny and sometimes positive
    (implied sd of error when cov lt 0 is about 1.5)
  • Will shortly check time series properties of
    Gottschalk true wage changes.

22
We assume that process generating
observed wage changes is
where uU-c,1-c This implies
We can then estimate c by matching theoretical
number of switchers and actual number of
switchers (method of moments)
23
Now we assume that underlying true distribution
is a sequence of point masses at specific
intervals and that the error is normal when
present. From that we can compute the expected
fraction of observations in any interval of the
observed wage distribution given the fraction of
observations at each mass point. We can then write
Where mo is the vector of observed fractions of
observations in each range, m is the fraction of
observations in the true distribution at each
mass point and T is the matrix which has columns
containing the fraction of observations from each
mass point that are expected to be observed in
each interval of the true distribution. We keep
T square for simplicity so...
is an estimate of the true distribution.
24
Example Using PSID Datat
  • Only wage earners
  • Use reported wages and not PSID computed wages

25
(No Transcript)
26
(No Transcript)
27
(No Transcript)
28
(No Transcript)
29
Nominal Rigidity Estimates
  • Spike vs tail (with and without correction for
    menu costs)
  • Lower tail vs. upper tail (symmetry)
  • Below zero vs. same category above zero in
    another year (constant distribution as in Kahn
    (1997) -- not yet implemented)

30
Menu Cost Rigidity
  • Categories around zero vs. reflection to other
    side of median (symmetry)
  • Categories around zero vs. same categories in
    other years when they arent around zero
    (constant notional distribution Kahn)

31
Real Rigidity
  • Downward real rigidity by symmetry method (use
    different estimates of expected rate of inflation
    and compare mass below to mass above)
  • Downward nominal by constant distribution
    (estimate reduction in mass by contrasting values
    in different periods -- not yet implemented).
  • Asymmetry After removing spike
  • measure skew
  • measure difference between mean and median
  • excess mass in spikes other than zero

32
Real RigidityInsensitivity to Fundamentals
  • Estimate Phillips Curve with median instead of
    mean
  • Estimate mean of notional wage distribution using
    modified Kahn method

33
(No Transcript)
34
(No Transcript)
35
Real Rigidity Measures
36
Whats Next?
  • Country Teams
  • finish descriptions of wage setting institutions
  • replications of G-S (where possible)
  • histograms of wage change distributions for each
    year data are available
  • discussion of data reliability
  • run program to do rigidity estimates
  • unique country projects

37
Whats Next (continued)
  • Project leaders, in cooperation with country
    teams,
  • develop hypothesis about institutional sources of
    rigidity
  • develop data set on institutions
  • panel meta-analysis of causes and consequences of
    rigidity and sand
  • Culminating in meeting in Winter 2003
Write a Comment
User Comments (0)
About PowerShow.com