Discussion of KahnRich on Tracking the New Economy

1
Discussion of Kahn-Rich on Tracking the New
Economy

• Robert J. Gordon
• Northwestern University and NBER
• Federal Reserve of San Francisco,
• November 7, 2003

2
Productivity Growth is the Hot Topic in
Macroeconomics

• Look at the numbers, 6.8 in 2003Q2, 8.1 in
  2003Q3
• How much of this is an unusual cyclical event?
  How much of this is an acceleration of trend?
• Advertisement Read another paper, Exploding
  Productivity Growth Historical Context,
  Possible Causes, Future Implications BPEA
  20032, forthcoming
• Brookings disallows NBER Yellow-covered Papers
• Will be on my web site by Monday morning. Search
  Google (not that Scottish University).
• 97 double-spaced pages

3
Two New Ideas in Kahn-Rich Paper

• Idea 1. Productivity growth shifts between
  regimes. High and Low productivity growth.
• Idea 2. We can do better in estimating the
  trend of productivity growth by using outside
  information going beyond productivity growth
  itself
• Info A Real compensation per hour
• Info B Real consumption per hour

4
Does their Approach Signal Increase in late 90s
Trend Earlier than Other Methods?

• Their claim
• One could not decisively conclude that there was
  a return to a higher growth regime on the basis
  of productivity alone.
• Only the corroborating evidence from other
  cointegrated series can swing the balance
  strongly in favor of a regime switch.
• Does Their Series Detect Post-1995 Acceleration
  Faster than Alternatives?

5
Motivations for the Kahn-Rich Reevaluation of
Growth Trends

• One can be skeptical about both ideas
• We treat that trend as a stochastic process
  whose mean growth rate has two regimes.
• Why two?
• Why not high medium low?
• Why not four regimes? Ten regimes?
• Use two additional series to provide additional
  information
• Skeptic Why do these two series provide
  independent information? Why do the authors not
  take us through the arithmetic of labors income
  share?

6
Additional justifications for their approach

• Criterion for use of two additional variables,
  consumption and real wage
• 1 We show that aggregate productivity data
  alone do not provide as clear . . . a signal of
  changes in trend growth as does the joint signal
  from the series we examine.
• What aspect of time-series dynamics provide an
  additional contribution from those two series?
• 2 We do not have to choose break dates
• Nor do H-P filter nor Kalman time-varying
  coefficient
• 3 How long regimes last (contingent on only two
  regimes?)

7
Arithmetic of Labors Share

• Does their real compensation variable provide
  additional information?
• S (WH/PY)
• Change in log labors income share
• ?s ?w ?p (?y ?h)
• Usual cyclical behavior, labors share rises in
  recessions, shrinks in recoveries (like now).
• In using compensation per hour as a proxy for the
  productivity trend, they are making a statement
  about the cyclical behavior of labors share.
  But they have no model.

8
Consumption/Hour

• How is Consumption/Hour related to productivity?
• C/H (C/Y) (Y/H)
• So now we need a model of the share of
  consumption in GDP. Lots of models Keynesian,
  RBC, but not in this paper.

9
Alternative Productivity Trends to Compare to
Kahn-Rich

• 1 Hodrick-Prescott (H-P) filter
• Parameter value meaning
• Everyone uses 1600. This is the square of
  5/(1/8) 40. When detrending GDP, a 5 percent
  GDP gap causes the trend to decelerate by 1/8
  percent per quarter.
• Great Depression 25 percent GDP gap, trend
  decelerates at 5/8 percent per quarter, 2.5
  percent per year, 10 percent after four years.
• Starting at 3 percent per year in 1929, trend by
  1933 is growing at 3 25 percent or -22 percent
  per year.
• H-P parameter 6400 is much better than 1600

10
2 Kalman Filter with Time-Varying Coefficients

• The Kalman filter explains the change in
  productivity growth (?pt) by a time-varying
  constant and any set of other explanatory
  variables (ßXt)
• (5) ?y - ?h(t) a(t) ßX(t) w(t)
• The next step is to specify a time-series process
  for the time-varying productivity trend, and the
  most straightforward is a random walk
• (6) a(t) a(t-1) v(t)

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Implementation of Kalman Filter Productivity
Trend with Time-Varying Coefficient

• Replace ßX(t) by change in output deviation from
  trend (or change in unemployment rate).
• Could also use supply-shock variables, e.g.,
  change in oil prices, that cause temporary
  changes in productivity
• Kalman filter can use more info than H-P
• Compare K-filter with H-P filter
• Without output variable they are identical, same
  smoothness coefficient

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Kalman with Output vs. H-P
13
Kahn-Rich Compared
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Summary Problems with their Productivity Growth
Trend

• Problem 1. Why is it so Jagged?
• Problem 2. Why must there be only two regimes?
• Problem 3. Why does the behavior of the real
  wage tell us something about the productivity
  trend?
• What if super-normal productivity growth goes
  into profits? How long does it take for real
  wage growth to catch up?
• Problem 4. Why does consumption tell us
  anything about the productivity trend. What is
  the theory of the behavior of the C/Y ratio?

15
Thanks to the Authors

• For bringing the Productivity Growth Trend to the
  Attention of this Audience one day after the
  announcement of 8.1
• For helping to focus attention on the strengths
  and weaknesses of Hodrick-Prescott and Kalman
• And for reminding us that there is a lot of
  macroeconomics devoted to explaining the change
  in labors income share and the C/Y ratio