Title: The International Wage Flexibility Project
1The International Wage Flexibility Project
- Presentation at Workshop on Downward Nominal Wage
Rigidity - Norges Bank, 12 June 2003
2What?
- 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
3Country Teams
- Austria
- Belgium
- Denmark
- Finland
- France
- Germany
- Italy
- Norway
- Portugal
- Sweden
- Switzerland
- United Kingdom
- United States
4Who 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
5Starting 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)
6What 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).
7What 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.
8What 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
9History 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)
10History 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
11At 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
12Observations
- 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.
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17Five 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
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19First 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.
20New 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.
21Validating 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.
22We 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)
23Now 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.
24Example Using PSID Datat
- Only wage earners
- Use reported wages and not PSID computed wages
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29Nominal 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)
30Menu 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)
31Real 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
32Real RigidityInsensitivity to Fundamentals
- Estimate Phillips Curve with median instead of
mean - Estimate mean of notional wage distribution using
modified Kahn method
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35Real Rigidity Measures
36Whats 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
37Whats 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