Measuring Micro and Macro

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16 Νοε 2013 (πριν από 4 χρόνια και 1 μήνα)

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Measuring Micro and Macro
Productivity Dynamics

Remarks By John Haltiwanger

Overview


Objectives:


Measure productivity at micro and macro levels in
consistent fashion


Reallocation dynamics at micro level important for aggregate


Track firm dynamics including entry and exit to
measure and analyze importance of static and
dynamic allocative efficiency vs. “within firm
productivity” growth


Challenges:


TFP difficult to measure


Firm dynamics difficult to measure


Methodological Issues



CAPITAL
MATERIALS
LABOR
OUTPUT
TFP
materials
labor
materials
labor
ln
1


ln


ln
ln
ln












Challenges:


1. Difficult to measure outputs and inputs especially capital



a. Capital


b. Prices especially at micro level


2. Estimating factor elasticities:



a. OLS


b. Cost Shares


c. Proxy methods (Olley
-
Pakes; Levinsohn
-
Petrin)


d. IV






Mixed Messages on Challenges…


Labor productivity and TFP often highly
correlated


More important to get representative sample and firm
dynamics than TFP?


Capital measurement difficult and potentially
important for policies/institutions


Price/output measurement difficult given data
limitations and very important for positive and
normative implications

Table

III
.
1

(B)

Definitions

of

Measures

Estimation

methodology
:

1

Net

book

value

of

total

capital,

Share

of

total

output

2

Net book value of machinery and equipment, Share of total output

3

Replacement value of total capital, Share of total output

4

Replacement value of machinery and equipment, Share of total output

5

Net

book

value

of

total

capital,

Share

of

total

cost

6

Net book value of machinery and equipment, Share of total cost

7

Replacement value of total capital, Share of total cost

8

Replacement value of machinery and equipment, Share of total cost

9

Net

book

value

of

total

capital,

OLS

10

Net book value of machinery and equipment, OLS

11

Replacement value of total capital, OLS

12

Replacement value of machinery and equipment, OLS

Source: Haltiwanger and Schweiger (2004)

Table III.2 Average Pairwise Correlation of TFP Measures Using Alternative Estimation and
Measurement Methods

r(lnprod,lntfp10p)

0.6834*

r(lntfp1p,lntfp10p)

0.8093*

r(lntfp2p,lntfp10p)

0.8679*

r(lntfp3p,lntfp10p)

0.7889*

r(lntfp4p,lntfp10p)

0.7995*

r(lntfp5p,lntfp10p)

0.9826*

r(lntfp6p,lntfp10p)

0.9897*

r(lntfp7p,lntfp10p)

0.9784*

r(lntfp8p,lntfp10p)

0.8599*

r(lntfp9p,lntfp10p)

0.9951*

r(lntfp11p,lntfp10p)

0.9718*

r(lntfp12p,lntfp10p)

0.9784*

Note: Reported correlations are based upon pooled data. See Table III.1 (B) for definitions of
measures. Lntfp is log TFP so using Table III.1 (B) we can see that ntfp10p is the log TFP using
pooled production function estimated via OLS using net book value of machinery and equipment.

Source: Haltiwanger and Schweiger (2004)

PRODUCTIVITY SHOCKS


TFP
-

residual from KLEM production function:




where the production function is estimated in logs:











Inputs may be correlated w/ productivity, so use IVs:

(a)

Output of downstream producers.

(b)

Regional governments expenditures.

(c)

Energy and materials prices.



Estimated

factor

elasticities

by

sector

using

cost
-
share

approach

and

results

are

robust

(e
.
g
.
,

correlation

between

two

measures

is

0
.
88

and

moments

very

similar)
.


jt
jt
jt
jt
jt
jt
jt
V
M
E
H
L
K
Y




)
(

jt
jt
jt
jt
jt
jt
jt
M
E
H
L
K
Y
TFP
log
ˆ
log
ˆ
)
log
(log
ˆ
log
ˆ
log










Source: Eslava et al. (2005)

TABLE 2: PRODUCTION FUNCTION

TABLE 3: DIFFERENT TFP MEASURES

TABLE 6: DETERMINANTS OF EXIT PROBABILITY

Specification:

[1]

[2]

[3]

[4]

[5]

[6]

[7]

Revenue TFP

-
0.062

0.011

Physical TFP

-
0.031

0.010

-
0.059

0.012

-
0.028

0.009

Prices

-
0.034

0.014

-
0.078

0.017

Demand Shock

-
0.038

0.002

-
0.038

0.002

U.S. Exit Selection Results

Source: Foster, Haltiwanger and Syverson (2005)

Aggregate productivity and allocation



Olley and Pakes (1996) static decomposition:





where: N: # of firms in a sector;


The first term is the unweighted average of firm
-
level productivity,


The second term reflects allocation of resources: do firms with higher
productivity have greater market share.



Requires representative cross sectional samples but does not require accurate
longitudinal linkages


Cannot quantify directly importance of entry and exit


By construction, cross term takes out country effects so abstracts from some
aspects of measurement error






















i
i
t
it
t
it
it
t
t
P
p
p
N
P
)
)(
(
)
/
1
(
_
_


The cross
-
sectional efficiency of the
allocation of activity









0.0
0.2
0.4
0.6
0.8
Argentina
Chile
Colombia
UK old
Finland
Netherlands
France
West Germany
Portugal
USA
Taiwan
Korea
Indonesia
Slovenia
Latvia
Romania
Hungary
Estonia
Data for Hungary, Indonesia and Romania use Three-Year Differencing.
Excluding Brazil and Venezuela.
Five-Year Differencing, Real Gross Output, Manufacturing
The Gap Between Weighted and Un-Weighted
Labor Productivity, 1990s
Source: Bartelsman, Haltiwanger and Scarpetta (2005)

The cross
-
sectional efficiency of the
allocation of activity









0.0
0.2
0.4
0.6
0.8
Estonia, 1995
Estonia, 2001
Hungary, 1992
Hungary, 1995
Hungary, 2001
Latvia, 1996
Latvia, 2001
Romania, 1995
Romania, 1999
Slovenia, 1992
Slovenia, 1995
Slovenia, 2001
Five-Year Differencing, Real Gross Output, Manufacturing.
Data for Hungary and Romania use Three-Year Differencing.
in Transition Economies over the 1990s
The Evolution of the Gap Between Weighted
and Un-Weighted Labor Productivity
Source: Bartelsman, Haltiwanger and Scarpetta (2005)

Olley-Pakes Decomposition for Colombian
Manufacturing
0.80
0.90
1.00
1.10
1.20
1.30
1.40
1.50
1.60
1.70
1.80
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
Year
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Aggregate (Weighted)
Simple Average
Cross-term
Source: Eslava et al. (2005)

Dynamic decomposition of productivity growth



















Advantages:


Explicit measure of contribution of entry and exit


Disadvantages:


Horizon dependent


Experimentation, learning and selection may make especially dynamic
economies have a low contribution of net entry at short horizons but high
contribution at long horizons


)
(
)
(
)
(
k
t
k
it
X
i
k
it
k
t
it
N
i
it
C
i
it
it
k
t
C
i
k
it
it
it
C
i
k
it
t
P
p
P
p
p
P
p
p
P



































Within
-
firm productivity growth
dominates at five
-
year horizons in Mfg

-0.5
0.0
0.5
1.0
1.5

Argentina
Chile
Colombia
Estonia
Finland
France
Korea
Latvia
Netherlands
Portugal
Slovenia
Taiwan
UK
USA
West Germany
Argentina: 1995-2001. Chile: 1985-1999. Colombia: 1987-1998. Estonia: 2000-2001.
Finland: 2000-2002. France: 1990-1995. West Germany: 2000-2002. Korea: 1988 & 1993.
Latvia: 2001-2002. Netherlands: 1992-2001. Portugal: 1991-1994. Slovenia: 1997-2001.
Taiwan: 1986, 1991 & 1996. UK: 2000-2001. USA: 1992 & 1997.
Excluding Brazil and Venezuela.
Labor Productivity - Five-Year Differencing, Real Gross Output
FHK Decomposition Shares - Manufacturing
Within
Between
Cross
Entry
Exit
Firm Turnover(i)
Source: Bartelsman, Haltiwanger and Scarpetta (2005)
Contribution of Net Entry to Productivity
Growth (10-year horizon)
-1
-0.5
0
0.5
1
1.5
2
Retail-All
Dept
Stores
Gen
Merch
Mfg-All
Share
Continuing Estabs
Net Entry
Source: Foster, Haltiwanger and Krizan (2005)

Variable

Weighted Regression

Exit Dummy

Entry Dummy

Revenue TFP

-
0.0340

0.0049

0.0448

0.0055

Physical TFP

-
0.0305

0.0058

0.0999

0.0064

Price

-
0.0035

0.0040

-
0.0551

0.0045

Demand Shock

-
0.6364

0.0293

-
0.0927

0.0326

Differences Between continuing, entering and exiting


establishments in U.S. Manufacturing

Source: Foster, Haltiwanger and Syverson (2005)

Total

Growth

Components of Decomposition (FHK/BHC)

Within

Between

Cross

Entry

Exit

Net Entry

Revenue

5.09

3.38

-
0.51

1.32

0.71

0.19

0.90

Physical

5.09

3.45

-
0.40

0.70

1.22

0.12

1.34

Components of Decomposition (GR)

Within

Between

Entry

Exit

Net Entry

Revenue

5.09

4.04

0.13

0.54

0.37

0.91

Physical

5.09

3.80

-
0.07

1.04

0.31

1.35

Sensitivity of U.S. Manufacturing Decomposition to Prices

Source: Foster, Haltiwanger and Syverson (2005)

Guidance?


Micro/macro links critical


Large fraction of level of productivity associated with allocative
efficiency


Important contribution of changes in allocative efficiency and/or
reallocation/net entry components for productivity growth


Measurement of TFP challenge in general and especially
at micro level


Greater weight on representative sample with
micro/macro links than TFP vs. Labor productivity?


But measurement matters:


Prices and market structure matter and are often missing piece in
micro/macro link