Transcript Comments on “The Link between Product Market Reforms and Macro-Economic Performance” by Rachel Griffith and Rupert Harrison Stephen Nickell Bank of England Monetary Policy.

Comments on “The Link between Product Market
Reforms and Macro-Economic Performance” by Rachel
Griffith and Rupert Harrison
Stephen Nickell
Bank of England Monetary Policy Committee
November 2005
European Commission Workshop on
Structural Reforms and Macroeconomic
Performance, Brussels, 18 November, 2005
• This paper makes a significant contribution to
the expanding literature on product market
regulation and macroeconomic performance.
• The strategy is first to relate product reforms to a
measure of the mark-up of price over marginal
cost. Second, this is then related to various
performance measures. In some cases, these
two steps are merged.
• The reported results suggest that product
market reforms are associated with
increased employment and investment.
• However, the lower mark-ups generated
by reforms seem to be associated with
lower levels of productivity and reductions
in R and D and productivity growth rates.
• These latter results are based essentially on
time series correlations. Some of the crosssection correlations tend to tell the opposite
story in the sense that countries with lower rents
tend to have higher productivity. However,
cross-section correlations are easily corrupted
by omitted variable bias.
• On the other hand, some of the time series
results must also be treated with caution. In
particular, identifying shifts in trend productivity
growth rates from 15 years of data is highly
problematic.
 Some of the empirical modelling omits important variables. Consider
employment.
 A basic model can be written as follows.
Production : Y  Af K , L 
(1)
Profit max. : Af L K , L   W / P
(2)
(W = wage, P = price,  = mark up)
Assuming constant returns, labour demand is
L  Kg W / PA, g '  0
(3)
How do we eliminate W/P?
 A long-run wage equation is
L /   g1 W / P, Z w 
(4)
- where Z w are wage pressure factors (eg. benefits, unions, labour
taxes etc.) and  is the population of working age or the labour
force.
 Using this to eliminate W/P yields
L  h A /  , K /  , Z w 
(5)
+ + -
 Key points are that employment in each country is driven by the population of
working age and all the Z w variables are important. The employment
equations estimated in the paper omit all these variables.
 Turning to investment, the model above implies that the long-run capital stock
will be determined by
(6)
K  g 2 c / AP Y , g 2'  0
where c is the cost of capital. This sort of model suggests that the
investment equation is a dynamic version of
(7)
I   o   , lnC / P    2 ln / A   3  ln Y e
Again, the investment equations in the paper omit most of the relevant
variables
 Any productivity models should be based on the production function. In logs,
we might have
(8)
y     k     a  skillmix, hours, cycle, dynamics
 , trend TFP, might be specified as
a   o  1    2   3  t
Taking differences yields
 y     k  l   a  skillmix, hours, cycle, dynamics
where a  1    2   3 t 
Points to note.
(i) When analysing these models, the levels equation (8) and the growth equation
(9) should always be consistent. This is not the case in the paper.
(ii) Data on skill mix is important here. The education composition of the
workforce is available.
(iii) Annual hours per worker is crucial. The rate of decline of this variable since
1983 varies significantly. For example, it is 0.5% pa in France, Germany,
Italy, 0.2% in Scandinavia, 0.1% pa in UK.
(iv) I would specify  as a long moving average in the equation explaining trend
TFP. Indeed, in the growth term, I would personally take  as a constant for
each country since I do not see how we can detect changes in trend TFP
growth in 15 observations.
• Finally, when computing the rents, I would not
use a constant cost of capital over a period
when long-term real interest rates have declined
significantly.