Transcript Total Factor Productivity Growth and Structural Change in

Total Factor Productivity Growth
and Structural
Change in Transition Economies
El-hadj Bah
Arizona State University
and
University of Auckland
Josef C. Brada
Arizona State University
and
Macedonian Academy of Sciences and Arts
Closing pcy Differences Between
Old and New Members
• Growth accounting literature (Solow
(1957), Prescott (1998) and Hall and
Jones (1999), etc.) stresses:
– Changes in total factor productivity (TFP)
account for the largest part of economic
growth.
– International differences in TFP account for
the bulk of international differences in pcy.
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Income/Productivity Convergence
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Source: EU
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Contributions to “potential” growth
(period average) of:
EU
10
EU
15
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Capital
1998-2000
Labor
Hours
-0.8
2.3
TFP
Change
2.2
2001-2005
-0.4
1.8
2.1
1998-2000
0.3
0.8
1.3
2001-2005
0.4
0.6
1.0
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Source: EU
Income/Productivity Convergence is
Accompanied by Structural Change
• Kuznets (1966) – pervasive pattern of
structural change accompanying economic
development.
• Over-industrialization, over-“agrarianism”
and neglect of service sector under
Communism (Gregory, 1970; Ofer, 1976)
due to ideology and “common sense”.
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Agriculture’s Share of Employment
Country
1991
2001
Czech Rep
Estonia
8.6
18.9
4.7
6.8
Hungary
Poland
Slovakia
17.9
25.4
12.7
6.1
18.8
6.1
Slovenia
8 New EU
8.2
15.1
5.1
9.8
5.2
3.5
12 rich EU countries
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Source: EU
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Industry’s Share of Employment
Country
1991
2001
Czech Rep
Estonia
Hungary
Poland
31.5
25.0
26.1
24.7
27.6
23.0
24.4
20.1
Slovakia
Slovenia
8 new EU
26.9
39.0
27.1
25.9
28.9
23.0
12 rich EU countries
21.2
17.9
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Market Services’ Share of
Employment
Country
1991
2001
Czech Rep
Estonia
Hungary
Poland
24.7
24.4
28.5
19.0
31.9
34.9
33.6
28.8
Slovakia
Slovenia
8 new EU
26.2
26.9
25.4
30.4
33.2
31.9
12 rich EU countries
33.1
37.0
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Why worry?
• Can TFP growth continue?
• What are the effects of structural change
on TFP growth?
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Barriers to Continued TFP Growth
in New Members
• Reforms cease – better institutions yield
higher TFP.
• Outward opening slows – globalization
and FDI inflows raise TFP.
• Granick - Prescott effects wear off.
• EE has a poor record of TFP growth.
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EE’s record of TFP
• Slowdown in Soviet TFP growth noted in 1960s
(Kaplan, 1968).
• We were confused by Weitzman (1970) and
Easterly and Fischer (1995).
• Studies of EE economies used variety of models
& statistical techniques but all came to the same
conclusion. By the early 1980s, only source of
growth was “extensive” – TFP was zero.
• If determinants of the level of TFP are slow to
change, current TFP growth may be temporary
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Structural Change
• Is the structural change we have seen in
EE a source of positive change in TFP?
• Development literature (e.g.,Herrendorf
and Valentinyi (2006); Hsieh and Klenow
(2007); Bah(2008)) suggest that TFP
levels differ among sectors.
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Why Not Apply Growth Accounting
to Transition Economies ?
• Sectoral Data Not Available.
• Even Aggregate Capital Stocks Suffer from
Major Defects (Campos and Coricelli (2002)).
– Large but unmeasured depreciation and
abandonment
– Moral depreciation – large changes in pattern of
production and in technology
• Estimates of TFP depend critically on “revisions”
of “official” data (Izumov and Vahaly (2006,
2008))
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This Paper
• Builds a dynamic 3 sector (Agriculture,
Industry, Services) model
• Calibrates the model using US data
• Calculates Austrian sectoral TFP using
Austrian sectoral labor allocation
• Compares Austrian TFPs to those of
transition economies
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The Model
• Key features for labor reallocation across
sectors:
– Non-homothetic preferences and agricultural TFP
growth drive labor out of agriculture
– TFP growth differential and elasticity of substitution
between industrial and services output drive labor
reallocation in those 2 sectors.
• Closed economy
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
At
if

U ( t At )  

log( t )  A if
At  A
At  A
Preferences
• Household lives forever, supplies labor to
3 sectors, earns income.
• Utility

A
if A  A
t

U ( t At )  
log( )  A if
t

t
At  A
 1
 1




 t   M t  (1   ) S t 


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
 1
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Technologies
• Agriculture uses only labor and land (L=1),
and is only used for consumption. With NA
the agricultural labor,

1
t
At  Aat N at L
where
Aat  Aa (1   at )
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t
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Technologies
• Industrial output can be consumed or invested.

1
M t  X t  Amt K mt
N mt
where
Amt  Am (1   mt ) t
• The law of motion of the aggregate capital stock
(K) in the economy is given by:
Kt 1  (1   ) Kt  X t
where δ is the depreciation rate.
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Services
• Services are only consumed.

S t  Ast K st N
1
st
where
Ast  As (1   st )
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t
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Solving the Model
• A competitive equilibrium is a set of allocations
and prices such that:
(i) Taking prices as given, the household
maximizes lifetime utility subject to its budget
constraint
(ii) Taking prices as given, the representative
firm in each sector maximizes profits
(iii) Markets clear
Equivalent to a social planner’s (SP) problem
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SP Model
Choose ( K t , K mt , K st , N at , N mt , N st , S t , Lt )

max   t T (log( t )  A
t T
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Calibration to US Data 1950 - 2000
Aa = 1 in 1950
Am = 1 in 1950
As =1 in 1950
Ãa = 0.24
α = 0.70 (T)
β = 0.975
δ = 0.05
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ε = 0.335 (U)
γm = 0.019 (T)
γs = 0.009 (T)
λ = 0.01 (U)
Θ = 0.03 (U)
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Apply Model and Calibrated Values
to Austria and New EU Members
• Austria as a comparator
Per Capita Incomes as % of EU-15 Average
Country
Austria
Czech Republic
Estonia
Latvia
Lithuania
Hungary
Poland
Slovak Republic
Slovenia
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1997
112.9
61.9
35.0
29.8
33.3
45.5
40.1
42.3
64.5
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2005
113.3
67.8
51.7
43.1
47.1
57.2
46.0
50.1
75.0
(source: EU)
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Intuition for Solution
At a heuristic level, given the calibrated preference
parameters:
Employment in agriculture determines agricultural
TFP.
Relative employment between industry and
services determines relative TFP between them.
Aggregate GDP per capita determines the levels of
TFP in industry and services.
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Austria
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Bulgaria
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Czech Republic
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Estonia
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Hungary
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Latvia
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Lithuania
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Poland
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Slovak Republic
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Slovenia
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AG TFP vs Austria
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IND TFP vs Austria
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SERVICES TFP vs Austria
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Rankings of Sectoral TFPs Relative
to the US -1950
Country
Ranking
Bulgaria
IND>SER>AGR
Czech Republic AGR>IND>SER
Estonia
AGR>IND>SER
Hungary
AGR>IND>SER
Latvia
IND>AGR>SER
Lithuania
IND>SER>AGR
Poland
IND>SER>AGR
Slovak Republic AGR>IND>SER
Slovenia
IND>SER>AGR
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Loss of GDP per capita due to structural
transformation (as % of 1995 GDP per capita)
Country
% Loss
Austria
1.28
Bulgaria
0.95
Czech Republic 2.29
Estonia
3.83
Hungary
2.31
Latvia
4.47
Lithuania
6.55
Poland
2.74
Slovak Republic 4.44
Slovenia
3.16
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Policy Implications
• Sectoral differences are important
– In some countries catch up is hampered by poor
performance in one or more sectors
– Structural change not a major drag
• Specific policy measures depend on how we
believe TFP is determined
• Research question: Is sectoral TFP
performance linked to nature of reforms such as
privatization, governance, regulation, etc. ?
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Thank you.
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