Labor Markets and Inflation: The International Wage Flexibility Project

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Labor Markets and InflationThe International
Wage Flexibility Project

• Presentation at
• National Bank of Belgium Conference on Wage and
  Price Rigidities in an Open Economy
• 13 October, 2006

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What is the IWFP?

• 13 Country study of wage inflation Sponsored by
  the ECB and directed by Erica Groshen (NY Fed.)
  and me
• using micro data on individual and occupational
  wages analyzed by teams in each country familiar
  with the data to be used
• meta-analysis of country level results by team
  including directors plus Lorenz Goette, Steinar
  Holden, Julian Messina, Mark E. Schweitzer,
  Jarkko Turunen, and Melanie E. Ward
• broader than just analyzing wage rigidity (sand
  and grease), but that is the part that Im going
  to talk about today

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Where to Find Full Paper

• Results http//brookings.edu/es/research/projects
  /iwfp_jep.pdf
• Methodology http//brookings.edu/es/research/proj
  ects/200509_iwfp.pdf
• Or navigate to brookings.edu
• then go to list of scholars
• then go to my page
• then look under current projects for 13 country
  study of wage rigidity and click through to that
  page
• all the papers for this project are linked to
  that page

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Country Teams

• Austria
• Belgium
• Denmark
• Finland
• France
• Germany
• Italy

• Norway
• Portugal
• Sweden
• Switzerland
• United Kingdom
• United States

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Disclaimer!

• Opinions expressed in this presentation are mine
  and mine alone. They should not be attributed to
  any other individuals in the IWFP, their
  employers, or associates, nor should they be
  attributed to the organizations sponsoring the
  IWFP.

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My Motivation

• Today many central banks have chosen to
  explicitly target inflation (and the ones that
  dont often do it implicitly).
• Many of these targets are very low (2 or less).
• In 1996 article with Akerlof and Perry (ADP) we
  showed that low inflation in the presence of
  downward nominal rigidity could lead to
  substantial unemployment in the long run.
• Is overly low inflation causing considerable
  unemployment (particularly in Europe where
  unemployment rates have been stubbornly high)?
• Although ADP model fits well for US and Canada,
  it fits very poorly for Britain and continental
  European countries. Is real rigidity a
  confounding problem that makes ADP model
  inappropriate?

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Motivation(Continued)

• Most previous (pre IWFP) studies of European wage
  rigidity use macro data to determine extent (and
  concept of rigidity measured is slow adjustment
  to economic circumstances rather than downward
  rigidity)
• Early exceptions include Smith (2000) and Nickell
  and Quintini (2001) who both analyze British
  micro wage data and find much less evidence of
  DNWR than in US data
• Biscourp et al. (2004) find mixed results for
  France
• Knoppik and Thomas Beissinger (2003) find
  substantial DNWR in Germany
• Fehr and Gotte (2004) find substantial DNWR in
  Switzerland
• Is there really substantial variation across
  countries or do differences reflect
  methodological differences?

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How To Measure Rigidity?

• Initially we were unsure about how to get at
  presence of different types of rigidity.
• I was mainly interested in looking at the extent
  of DNWR across countries using consistent
  methodology.
• At first meeting some very interesting results
  emerged examining wage change histograms.

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What We Are Going to See

• Histograms of wage percentage wage changes
• We are looking only at job stayers
• In some cases we are looking at reported hourly
  wages
• In other cases a measure of income divided by
  hours of work
• Some are from surveys, some from social security
  data, some from other types of administrative
  records

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Can we use wage change histograms to diagnose the
nature and extent of wage rigidity?
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Big Problem is Measurement Error

• If people make mistakes reporting their wages
  then we see wage changes where there are none.
• If we compute wageincome/hours we see wage
  changes due to overtime, bonuses, or mistakes in
  reporting hours.
• If we use SS data we have similar problems since
  almost no country has data that allow us to
  accurately identify base wage.
• All evidence suggests that for most data sets
  frequency and extent of errors make this a very
  serious problem (evidence suggests that in many
  data sets most reported wage cuts are actually
  errors of these sorts).

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Correcting for ErrorsUse information in
correlation between years

• Abowd and Card (1989) suggest that wages 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 auto-covariance and frequency of sign
  switching in changes to identify error rate and
  error variance.
• This information is used to identify
  semi-non-parametric estimate of true wage
  distribution (that is we estimate the histogram
  of wage changes we would see if there were no
  errors).

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How Do We Know Frequency and Severity of Errors?

• First crucial assumption is that errors are only
  important source of covariance in wage changes
  from one year to next.
• With that assumption we can identify the
  frequency of errors, and the variance of those
  errors when they are made, by looking at the
  auto-covariance of wage changes and the number of
  people who have sequential large wage changes of
  opposite signs.
• We estimate a statistical model of the wage
  change distribution and the error process using
  method of moments.

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Validating Primary Assumption

• Results applying new method to US largely fit
  with those of other studies (a very high degree
  or downward nominal rigidity).
• Finnish and German data has virtually no errors
  and estimated covariances are tiny and sometimes
  positive.
• Portuguese have good and bad data and (as we will
  see) the correction doesnt change the good data,
  but makes the bad data look like the good data.

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Portugese Data
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More ValidationAnalysis of Gottschalk Data

• Gottschalk uses regression discontinuity analysis
  of individual micro data to discriminate between
  true wage changes and errors in SIPP quarterly
  data (finds almost no negative wage changes) .
• We analyzed his data and found that all
  auto-covariance in wage changes due to errors
  (validating our identifying assumption).

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Three Ways to Estimate Three Types of Rigidity

• Problem is to generate counterfactual
  distribution (or notional wage change
  distribution) with which to compare actual wage
  change distribution.
• Three possibilities
• Assume an ideal form for the notional
  distribution
• Assume that the notional distribution is
  symmetric
• Assume that the notional distribution has
  constant shape over time
• We use the ideal form method (2-sided Weibull)

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Ideal Distribution(only method Im going to
discuss today)

• In general, two-sided Weibull fits upper tail of
  nearly all distributions very well and
  Gottshalks true wage changes (upper tail) have
  two-sided Weibull shape.
• So we will assume that notional wage change
  distribution is 2-sided Weibull and estimate its
  parameters along with
• A fraction r of workers are subject to downward
  real wage rigidity and if their notional wage
  change lt expected inflation they get expected
  inflation
• A fraction n of workers are subject to downward
  nominal wage rigidity and if their notional wage
  change lt0 they get wage freeze.
• A fraction of workers are subject to symmetric
  nominal rigidity and get no wage change if their
  notional wage change is within 2 of zero on
  either side

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Aside What Sort of Process Gives Rise to Weibull?

• Wage increases (above some average level) result
  from tournament with winners at each level
  getting an increase of a fixed size and then
  competing only with winners of first round for a
  larger increase in next round.
• Size of increase from winning a round grows
  exponentially.
• This is notably different from normal
  distribution that would result if workers were
  evaluated on many independent criteria and then
  given raises depending on how many they
  satisfied.

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International Comparisons

• Considerable variation across countries in the
  extent of downward nominal and downward real wage
  rigidity despite correction for differences in
  data quality
• Some tendency for countries to have either DNWR
  or DRWR but not both (tendency is stronger when
  we restrict comparison to the 90s)
• How do our estimates compare to those of others
  and between different data sources in our own
  sample?
• ECHP results with other data sets correlate .53
  for both real and nominal rigidity
• Wouldnt expect perfect correlation since time
  periods dont overlap and we do see some changes
  over time
• Country averages for nominal rigidity correlate
  .55 with simple measures constructed from
  uncorrected data
• Country averages for real rigidity correlate .25
  with simple measure used in JEP paper constructed
  from uncorrected data

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What is Correlated with Downward Nominal Rigidity?
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What is Correlated with Downward Real Wage
Rigidity?
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What is Correlated with Rigidity?

• Nothing consistently statistically significant at
  conventional levels.
• Union membership and bargaining coverage
  variables statistically significant at .1 level
  (we are getting better results now using time
  series variation).
• Notable case is US where real rigidity was
  notable in 1970s but disappears in the 1980s
  after the breakdown of pattern bargaining.

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Does Rigidity Affect Unemployment?

• According to Akerlof, Dickens and Perry 1996 a 1
  percent increase in in nominal wages due to
  rigidity should create somewhere between a 1 and
  5 percentage point increase in unemployment
• We compute estimates of the impact of each type
  of rigidity on wages and estimate a series of
  models of the impact of rigidity.
  

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Table 3 Effects of Rigidity on Unemployment Table 3 Effects of Rigidity on Unemployment Table 3 Effects of Rigidity on Unemployment Table 3 Effects of Rigidity on Unemployment Table 3 Effects of Rigidity on Unemployment
Dependent Variable/Specification Dependent Variable/Specification Dependent Variable/Specification Dependent Variable/Specification
Unemployment Unemployment Change in Inflation (Phillips Curve) Change in Inflation (Phillips Curve)
Unemployment Effect (b/a) 1.26 .90 2.99 2.90
Standard Error (.35) (.32) (1.28) (2.09)
p for null hypothesis 0 ? b/a (one tail test) .00 .01 .01 .08
Controls for year (all contain controls for dataset (country)) no yes no yes
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Conclusions on Unemployment

• Unemployment effects generally statistically
  significant.
• Cant reject the hypothesis that unemployment
  effects are in the range predicted by ADP model.
• Cant reject the hypothesis that effects of real
  and nominal rigidity are equal (as theory
  predicts).

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(Tentative) Policy Implications

• Most Euro-zone countries characterized by
  downward real wage rigidity rather than downward
  nominal wage rigidity. Benefits of increased
  inflation may not be so great in those countries
  compared to US and Canada (recent nominal wage
  cuts in Germany are example of how corporatist
  countries can overcome nominal wage rigidity).
• Several Euro-zone countries have substantial
  downward nominal wage rigidity so allowing
  inflation to move to bottom end of ECB target
  zone could be very costly. Should this happen
  these countries might be better off if they left
  EMU. Though gains would be minor given ECB policy
  to date.

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More Policy Conclusions

• No evident effect of EMU on rigidity in these
  data (though most data dont go back far enough
  to tell if there are effects of Maastricht
  treaty).
• No Evidence that persistent low inflation reduces
  the incidence of downward nominal wage rigidity.
  Thus no evidence that institutions adapt to low
  inflation.
• For US new method confirms results of previous
  studies significant DNWR. New finding is that
  there is no evidence of DRWR by 1990s. Thus Fed
  should avoid very low inflation.