Ryan Banerjee, Enisse Kharroubi, Fabrizio Zampolli BIS-IMF-OECD productivity conference 10-11 January 2018, Paris

1. Monetary policy, factor allocation
and growth
Ryan Banerjee, Enisse Kharroubi, Fabrizio Zampolli
BIS-IMF-OECD productivity conference
10-11 January 2018, Paris
Disclaimer: the views expressed are those of the presenters and not
necessarily those of the BIS

2. Motivation
 10 years after Great Financial Crisis (GFC) productivity growth
remains weak
 Key crisis factors seem less relevant
 Credit conditions loose
 Banks have largely repaired their balance sheets
 Global growth is picking up
 What are the effects of monetary policy?
 Easier monetary policy essential to stabilise demand in the depths of
the crisis
 But what are the effects on resource allocation?
- Especially during extended period of exceptionally low interest
rates
2

3. This paper
 How does monetary policy affect resource allocation?
 Could go in either direction
 Good: Easy monetary policy may help highly productivity
firms expand by alleviating credit constraints
 Bad: Easy monetary policy can slow productivity enhancing
reallocation if it reduces pressure on non-viable firms to exit
 New method to analyse contribution of factor reallocation to
productivity
 Show the relationship between a productivity
decomposition and panel regressions
 Use this insight to examine impact of monetary policy on
contribution of reallocation to productivity growth
3

4. Main results
 Sectoral reallocation closely linked to the slope of the yield curve
 Rather than either short or long-term rates alone
 Shocks which flatten the yield curve
 Reduce the contribution of factor reallocation across sectors
to aggregate productivity growth
 Evidence holds for both capital and labour reallocation but
stronger for labour
 Not driven by properties of yield curve signalling the phase of
the cycle
 Different way monetary policy conducted pre and post GFC
 Pre-crisis: yield curve flattening monetary tightening
 Post-crisis: yield curve flattening monetary easing
 May indicate state-dependency (credit market functioning,
financial vs. real shocks, etc…)
4

5. Related literature
 Factor reallocation boosts productivity growth in
downturns eg Cabellero and Hammour (1994, 1996), Davis
and Haltiwanger (1992), Mortensen and Pissarides (1994)
 Cleansing effect may be weaker if young productive firms
exit eg Baden-Fuller (1989), Dunne et al (1989), Eslava et al
(2010)
 Reallocation in US less intense during 2008-09 recession
than in previous recessions Foster et al (2016)
 Productivity decompositions eg Baily et al (2001), Olley and
Pakes (1996), Borio et al (2015)
5

6. Decomposing total factor productivity growth
 Assume aggregate TFP is an average of sectoral TFPs (𝐴𝐴𝑠𝑠𝑠𝑠)
weighted by their shares in aggregate input (𝑥𝑥𝑠𝑠𝑠𝑠) (eg labour)
𝐴𝐴𝑡𝑡
𝑥𝑥
= ∑𝑠𝑠 ⁄𝑥𝑥𝑠𝑠𝑠𝑠 𝑥𝑥𝑡𝑡 𝐴𝐴𝑠𝑠𝑠𝑠
 TFP growth can be decomposed into common and allocative
components
(where 𝑎𝑎𝑡𝑡
𝑥𝑥
= ⁄𝑥𝑥𝑠𝑠𝑠𝑠 𝑥𝑥𝑡𝑡 𝐴𝐴𝑠𝑠𝑠𝑠/𝐴𝐴𝑡𝑡
𝑥𝑥
)
6
Average relative rate
of labour
accumulation across
sectors
Average size-weighted
TFP growth across
sectors
Covariance of relative rate of labour
accumulation and size-weighted TFP
growth across sectors
Common component Allocation component

7. From decompositions to regressions
 Could follow two stage approach eg Borio et al (2015)
 Compute common and allocation components
 Run cross-country, cross-time panel regression
 Alternative: use cross-sector variation in a single stage regression
 Note that the ̂𝛽𝛽 is proportional to allocation component
7

8. Regression specification
 Baseline regression:
(𝑥𝑥𝑠𝑠/𝑥𝑥)𝑐𝑐𝑐𝑐+1
(𝑥𝑥𝑠𝑠/𝑥𝑥)𝑐𝑐𝑐𝑐
= 𝛼𝛼𝑠𝑠𝑠𝑠 + 𝛼𝛼𝑐𝑐𝑐𝑐 + 𝛼𝛼𝑠𝑠𝑠𝑠 + 𝛽𝛽1 + 𝛽𝛽2 𝑀𝑀𝑐𝑐𝑐𝑐 1 +
∆𝐴𝐴𝑠𝑠𝑠𝑠𝑠𝑠+1
𝐴𝐴𝑠𝑠𝑠𝑠𝑠𝑠
𝑎𝑎𝑠𝑠𝑠𝑠𝑠𝑠
𝑥𝑥
+ 𝛽𝛽0 𝑍𝑍𝑠𝑠𝑠𝑠𝑠𝑠 + 𝜀𝜀𝑠𝑠𝑠𝑠𝑠𝑠
 where 𝑀𝑀𝑐𝑐𝑐𝑐 is a vector of current and past macro variables
including
 Interest rate surprises: 1 and 2 year lagged
 Sales growth: Current and 1 year lagged
 Credit growth: Current and 1 year lagged
 We are interested in the element of 𝛽𝛽2 which measures the
sensitivity of factor allocation growth to the interaction between
sectoral TFP growth and interest rate surprises
8

9. Data
 EU-KLEMS
 10 countries 2000-2015. Austria, Belgium, Denmark, Finland,
France, Germany, Italy, Netherlands, Sweden, United States
 Aggregate and sectoral value added, sales, employment,
hours worked, capital stock and total factor productivity
growth
 13 sectors
 Additional datasets
 OECD: 1-year ahead forecast errors in policy rates and 10-y
government bond yields as interest rate surprises
 BIS: aggregate data on credit to the non-financial corporate
sector
9

10. 10
Summary statistics – productivity growth
 Common component accounts for most of average labour and capital productivity
growth, but allocation component accounts for most of average TFP growth
 Allocation component volatility is about 1/3 of (total factor) productivity growth
volatility.
Mean Std. dev.
Labour productivity growth 1.03% 2.24%
Allocation component 0.06% 0.70%
Common component 0.97% 2.31%
Capital Productivity growth -0.55% 1.99%
Allocation component 0.02% 0.60%
Common component -0.56% 2.01%
TFP growth (weighted by employment shares) 0.13% 1.68%
Allocation component 0.11% 0.56%
Common component 0.03% 1.70%
TFP growth (weighted by hours shares) 0.20% 1.71%
Allocation component 0.13% 0.54%
Common component 0.07% 1.70%

11. 11
Interest rate shocks
 Interest rate shocks: 𝐹𝐹𝐸𝐸{𝑆𝑆𝑆𝑆,𝐿𝐿𝐿𝐿} = 𝑖𝑖{𝑆𝑆𝑆𝑆,𝐿𝐿𝐿𝐿}𝑡𝑡 − 𝐸𝐸𝑡𝑡−1(𝑖𝑖{𝑆𝑆𝑆𝑆,𝐿𝐿𝐿𝐿}𝑡𝑡)
 (positive accommodation)
 Post 2010 most action from long-term interest rates

12. 12
Dependent variable: Relative employment growth
Variable (1) (2)
log(𝑒𝑒𝑒𝑒𝑒𝑒 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠)𝑐𝑐𝑐𝑐𝑐𝑐−1 -0.0955*** -0.0951***
(0.0186) (0.0185)
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑐𝑐𝑐𝑐𝑐𝑐 0.127*** 0.127***
(0.0382) (0.0381)
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑐𝑐𝑐𝑐𝑐𝑐−1 0.0656*** 0.0679***
(0.0209) (0.0210)
𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊)𝑐𝑐𝑐𝑐𝑡𝑡 0.161 0.189*
(0.111) (0.112)
𝐹𝐹𝐹𝐹𝑆𝑆𝑆𝑆,𝑐𝑐𝑡𝑡−1 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑐𝑐 10.35***
(3.321)
𝐹𝐹𝐹𝐹𝑆𝑆𝑆𝑆,𝑐𝑐𝑡𝑡−2 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑐𝑐 3.032
(3.207)
𝐹𝐹𝐹𝐹𝐿𝐿𝐿𝐿,𝑐𝑐𝑡𝑡−1 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑡𝑡 -8.829**
(3.762)
𝐹𝐹𝐹𝐹𝐿𝐿𝐿𝐿,𝑐𝑐𝑡𝑡−2 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑡𝑡 1.854
(3.365)
𝐹𝐹𝐹𝐹𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆 𝑐𝑐𝑡𝑡−1 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑡𝑡 -9.158***
(2.822)
𝐹𝐹𝐹𝐹𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆 𝑐𝑐𝑡𝑡−2 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑡𝑡 -2.507
(2.587)
𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 ( 𝛼𝛼𝑠𝑠𝑠𝑠, 𝛼𝛼𝑐𝑐𝑐𝑐, 𝛼𝛼𝑠𝑠𝑠𝑠) Yes Yes
Obs 1,651 1,651
R-squared 0.562 0.562
 Short-rates: Monetary
easing t-1
 Higher growth
contribution from
reallocation
 Yield curve flattening
reduces contribution
from reallocation
 F-test cannot reject
hypothesis: sum of short
and long interest rate
coefficients is zero
 Robust to inclusion of
credit gap and sales
growth (current + 1 lag)
Baseline results – employment reallocation

13. 13
Dependent variable: Relative capital growth
Variable (1) (2)
log(𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠)𝑐𝑐𝑐𝑐𝑐𝑐−1 -0.0611*** -0.0614***
(0.0180) (0.0184)
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑐𝑐𝑐𝑐𝑐𝑐 0.0272 0.0259
(0.0501) (0.0504)
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑐𝑐𝑐𝑐𝑐𝑐−1 0.0161 0.0172
(0.0366) (0.0365)
𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊)𝑐𝑐𝑐𝑐𝑡𝑡 0.0493 0.105
(0.279) (1.117)
𝐹𝐹𝐹𝐹𝑆𝑆𝑆𝑆,𝑐𝑐𝑡𝑡−1 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑐𝑐 8.071*
(4.179)
𝐹𝐹𝐹𝐹𝑆𝑆𝑆𝑆,𝑐𝑐𝑡𝑡−2 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑐𝑐 3.640*
(2.158)
𝐹𝐹𝐹𝐹𝐿𝐿𝐿𝐿,𝑐𝑐𝑡𝑡−1 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑡𝑡 -8.181*
(4.260)
𝐹𝐹𝐹𝐹𝐿𝐿𝐿𝐿,𝑐𝑐𝑡𝑡−2 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑡𝑡 -4.039
(4.512)
𝐹𝐹𝐹𝐹𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆 𝑐𝑐𝑡𝑡−1 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑡𝑡 -7.269
(4.605)
𝐹𝐹𝐹𝐹𝑆𝑆𝑆𝑆𝑆𝑆 𝑆𝑆𝑆𝑆 𝑐𝑐𝑡𝑡−2 ∗ 𝑇𝑇𝑇𝑇𝑇𝑇𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔(𝑆𝑆𝑆𝑆)𝑐𝑐𝑐𝑐𝑡𝑡 -3.743*
(2.033)
𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 ( 𝛼𝛼𝑠𝑠𝑠𝑠, 𝛼𝛼𝑐𝑐𝑐𝑐, 𝛼𝛼𝑠𝑠𝑠𝑠) Yes Yes
Obs 1,651 1,651
R-squared 0.559 0.562
 Yield curve flattening
reduces contribution from
reallocation
 F-test cannot reject
hypothesis: sum of short
and long interest rate
coefficients is zero
 Weaker significance than
labour regressions
(measurement issues)
 Demand (real sales
growth) less influence on
capital allocation
Baseline results – capital reallocation

14. Just the signalling properties of the yield curve?
14
 Flatter yield curve forecasts slower growth (eg Estrella and
Hardouvelis (1991) and productivity tends to be procyclical
 BUT: fluctuations in productivity driven by common component
 Signalling fluctuations in yield curve slope affect average
productivity across all sectors – not reallocation between
sectors
 Correlation between
forecast errors in the
yield curve slope and
TFP growth in the
following two years is
close to zero

15. Conclusions
 Slope of the yield curve closely linked to contribution of
reallocation to productivity growth
 Surprise flattening of the yield curve reduces contribution of
reallocation
 As monetary policy operations have changed with short-
rates hitting the ZLB
 May suggest some state dependency
 Two possible interpretations
 Pre-crisis, tighter credit conditions reduce growth of high
productivity entrants but post-crisis, loose conditions slow
exit of unproductive firms.
 Higher productivity growth sectors hold more short term
debt.
15

16. EXTRA SLIDES
16

17. Dependent variable: Relative employment growth
Variable (1) (2) (3) (4)
Log(emp share)cst-1 -0.0955*** -0.0924*** -0.0955*** -0.0951***
(0.0187) (0.0185) (0.0186) (0.0185)
Real sales growthcst
0.124*** 0.127*** 0.127*** 0.127***
(0.0385) (0.0392) (0.0382) (0.0381)
Real sales growthcst-1 0.0657*** 0.0653*** 0.0656*** 0.0679***
(0.0214) (0.0211) (0.0209) (0.021)
Size-weighted TFP growthcst 0.137 0.163 0.161 0.189*
(0.111) (0.117) (0.111) (0.112)
FESR,ct-1×Size-weighted TFP growthcst 7.478** 10.35***
(2.938) (3.321)
FESR,ct-2×Size-weighted TFP growthcst 2.233 3.032
(2.478) (3.207)
FELR,ct-1×Size-weighted TFP growthcst -3.581 -8.829**
(2.816) (3.762)
FELR,ct-2×Size-weighted TFP growthcst 2.271 1.854
(2.899) (3.365)
FESLOPE,ct-1×Size-weighted TFP
growthcst
-9.158***
(2.822)
FESLOPE,ct-2×Size-weighted TFP
growthcst
-2.507
(2.587)
Fixed effects (𝛼𝛼𝑠𝑠𝑠𝑠 , 𝛼𝛼𝑐𝑐𝑐𝑐 , 𝛼𝛼𝑠𝑠𝑠𝑠) Yes Yes Yes Yes
Observations 1,651 1,651 1,651 1,651
R-squared 0.559 0.556 0.562 0.562
17
 Short-rates:
Monetary easing t-1
 Higher growth
contribution from
reallocation
 Yield curve flattening
reduces contribution
from reallocation
 F-test cannot reject
hypothesis: sum of
short and long
interest rate
coefficients is zero
Baseline results – employment reallocation

18. Dependent variable: Relative capital growth
Variable (1) (2) (3) (4)
Log(emp share)cst-1 -0.0611*** -0.0617*** -0.0613*** -0.0614***
(0.0180) (0.0185) (0.0185) (0.0184)
Real sales growthcst 0.0272 0.0255 0.0259 0.0259
(0.0501) (0.0502) (0.0505) (0.0504)
Real sales growthcst-1 0.0161 0.0175 0.0179 0.0172
(0.0366) (0.0354) (0.0356) (0.0365)
Size-weighted TFP growthcst 0.0493 0.0401 0.0728 0.105
(0.279) (0.117) (1.264) (1.177)
FESR,ct-1×Size-weighted TFP growthcst 8.071* 8.321* 6.974
(4.179) (4.344) (5.276)
FESR,ct-2×Size-weighted TFP growthcst 3.640* 3.529 3.632*
(2.158) (2.220) (2.188)
FELR,ct-1×Size-weighted TFP growthcst -8.181* -7.996** -7.728*
(4.260) (4.030) (4.262)
FELR,ct-2×Size-weighted TFP growthcst -4.039 -4.784 -5.022
(4.512) (4.483) (4.616)
FESLOPE,ct-1×Size-weighted TFP
growthcst
-7.269
(4.605)
FESLOPE,ct-2×Size-weighted TFP
growthcst
-3.743*
(2.033)
Fixed effects (𝛼𝛼𝑠𝑠𝑠𝑠 , 𝛼𝛼𝑐𝑐𝑐𝑐 , 𝛼𝛼𝑠𝑠𝑠𝑠) Yes Yes Yes Yes
Additional controls interacted with
size-weighted TFP growth
None Credit gap
Credit gap
Sales growth
Observations 1,651 1,651 1,651 1,651
R-squared 0.559 0.556 0.562 0.562
18
 Yield curve flattening
reduces contribution
from reallocation
 F-test cannot reject
hypothesis: sum of
short and long interest
rate coefficients is zero
 Weaker significance
than labour regressions
(measurement issues)
 Demand (real sales
growth) less influence
on capital allocation
Baseline results – capital reallocation