M PRA
Munich Personal RePEc Archive
Productivity Spillovers in the Russian
Federation: The Case of Chemical
Market
Anastasia Kuzyaeva and Alexander Didenko
September 2014
Online at https://mpra.ub.uni-muenchen.de/59349/
MPRA Paper No. 59349, posted 21 October 2014 07:37 UTC
Review of Business and Economics Studies
Volume 2, Number 3, 2014
*
Anastasia kuzyAevA
International Finance Faculty, Financial University, Moscow
an.kuzyaeva@gmail.com
Alexander DiDenkO, Ph. D.
Deputy Dean, International Finance Faculty, Financial University, Moscow
alexander.didenko@gmail.com
Over the last decades, much attention has been drawn to the question of productivity variation
across countries. The differences in cross-country productivity could be explained by both foreign and domestic
be considered. Foreign direct investment (FDI) and international trade are suggested to be major conduits
of international technology transfer. The present paper aims to extend the current empirical literature by
determining the effect and the source of productivity spillover in Russia in case of chemical industry. In order
developed by Ericson and Pakes (1995) and Olley and Pakes (1996). The econometric model was tested on
the companies from chemical industry for the period 2007–2012. The empirical results show that FDI and
international trade productivity spillovers are present in Russian chemical industry. The size of FDI spillovers is
economically more important than imports-related spillovers. Based on the empirical results, we may predict
that Russia’s accession to the World Trade Organization in 2012 should result in productivity growth. However,
further research on this topic will be possible when the statistical data becomes available for several years after
accession.
Productivity spillover, FDI, trade liberalisation, Russia.
Electronic copy available at: http://ssrn.com/abstract=2498833
Review of Business and Economics Studies
Volume 2, Number 3, 2014
the question of productivity variation across countries.
-
et al�
-
-
-
- allocations of resources away from the least productive
et al�
- diates, skills and machinery investments. Evidence for
et al�
-
-
-
associated with lower output tariffs. Moreover, they also
et al�, port-intensive downstream sectors. The overall evidence,
-
’
firms’ characteristics or host countries’
- of research of productivity spillovers. The results of the
-
sideration accession of the Russian Federation to World
of productivity spillover in Russia in case of chemical
Electronic copy available at: http://ssrn.com/abstract=2498833
Review of Business and Economics Studies
Volume 2, Number 3, 2014
industry. In order to achieve the stated aim and answer
- as suppliers, consumers or competitors. On the other
sults. Finally, conclusions are made.
-
tively affected, with a very small overall positive effect.
tivity level. Productivity spillovers diffusion is thus a
ers to domestic ones. As mentioned previously, there are
two main sources of productivity spillovers, namely FDI
-
-
- tions.
and in access to international markets that allow them
-
et al�
-
whereas cheaper imported inputs can raise productivity
-
imported varieties.
-
-
Review of Business and Economics Studies
Volume 2, Number 3, 2014
-
-
zontal and vertical spillovers. On the one hand, technol-
-
to local upstream firms. Positive horizontal spillover
earliest empirical industry-level analyses found posi-
’
et al�,
-
policy implications. More recently, some cross-section-
’ pro-
et al
-
of the market.
fect the productivity performance of domestic firms
-
-
et al�
-
-
ferent empirical studies have analyzed the correlation
-
et al�
On the other hand, other studies have reported incon- conditional effects of intra-industry FDI spillovers on
Most empirical studies have mainly focused on the
-
-
Review of Business and Economics Studies
tion and skill level in the sector.
Volume 2, Number 3, 2014
-
et al�
International trade is one of the primary avenues for
wide. This is particularly true and important for devel-
-
-
in their review of various studies conclude that there
several mechanisms. Firstly, the competitive pressure
-
-
alization than in the previous decade. A study conducted
-
-
trical machinery, non-electrical machinery, electronics
-
incentives when it reduces the plant’s market share. Fi-
ment sector.
-
FDI and international trade on the host-country pro-
reallocation of output to more productive plants, con-
concluded that there are no systematic differences
-
and discussion of the results, it is important to make
-
part of daily life in today’s world. There is hardly any
industry where chemicals are not used and there is no
(
20
20
Year
Review of Business and Economics Studies
Volume 2, Number 3, 2014
Figure 2: Chemical Industry Output:
Developing Regions* & Countries with Economies in Transition
3500
Central & South America
Other Asia
Central & Eastern Europe
India
Africa & Middle East
China
Central & South America
(E
ST
.)
10
20
00
19
20
98
90
19
19
80
Other Asia
70
2000
3500
1500
3000
1000
2500
500
2000
0
1500
Africa & Middle East
Figure 2: Chemical Industry Output:
Developing Regions* & Countries with Economies in Transition
2500
19
India
0
1000
20
2
Output (BillionsOutput
USD) (Billions USD)
Central & Eastern Europe
3000
Year
China
500
(E
ST
.)
10
20
2
0
20
00
19
20
98
90
19
80
19
19
70
0
Year
important role.
Industries, which produce and use chemicals, have a
fects on human health and the environment. A variety of
-
development of domestic industry will require funda-
rapid increase of end-users;
-
increased investment;
new project development;
try’s industrial capital assets work in the chemical and
petrochemical industries in Russia (Enterprise Europe
cal producers in Russia.
-
procure similar materials from more than one producer.
- conscious. There are only a few isolated cases where a
investment activity and restriction of access of Russian one manufacturer. The producer’s control over the enchemical products to the markets of certain countries, tire supply chain is common on the Russian market. The
and the deterioration of the world market under increased competition. Russia’s accession to the WTO in
chemical production.
Review of Business and Economics Studies
Volume 2, Number 3, 2014
Major chemical producers.
Petrochemical
Petrochemical
Nizhnekamskneftehim (Republic of Tatarstan)
Petrochemical
Fertilizer Production
Potassium Fertilizer
Akron (Veliky Novgorod)
Mineral fertilizer
-
-
- the producers enjoy.
unlikely to occur, as consumers need to purchase prodThe chemicals industry is heavily reliant on the oil and
pharmaceutical products, and chemicals for use in the
manufacturers of plastic products, pharmaceuticals,
consumer chemical manufacturers, as well as utility
centralized.
-
tions with respect to key producers.
industry have chemical and petrochemical manufacChemical products are traditionally divided into two
chemical producers that do not have their own natural
The power of suppliers, on the other hand, is concomposition. At the same time, in view of the myriad strained due to the lack of differentiation in raw materials supplies. The materials a particular chemical manu-
versity of product application, in turn, can work to curSpecialty chemicals constitute one more set of chemicals industry products that have a diverse application
-
compound can do, not what chemicals it contains. The
versatility of application of specialty chemicals means
that these products are easy to sell, or to transform for
There also are chemicals that are not dependent on
then used to create other sodium compounds. Another
chemical producers to reduce output volumes. These
Review of Business and Economics Studies
Volume 2, Number 3, 2014
terials.
While chemicals do have inherent value and may
terms of FDI and imports. Based on the previous research
-
intensity of investment and the size of most chemical
operations in Russia narrow the class of companies that
These authors develop a framework for
timally choose sales and investment, as well as entry
-
ket attractive. The products of the chemical industry are
-
producer. The processes and formulas used to manufacaround for decades, in many cases without intellectual
property restrictions.
yit 0 l lit m mit k kit uit
where yit
, mit, and kit
it
on the Russian chemicals market. Because producers
of chemicals sell commodities, it is not easy for market
,
it
parts,
uit it it
investment. The dominant players on the Russian mar-
Consider the case when neither
and
. The term
it
-
it
it
-
it
it
it
it
function of
is known
it
E uit lit 0 . If the term
it
is constant over time,
-
-
approach.
-
section.
with it than capital, then OLS will tend to overestimate
underestimate k.
l
and
Review of Business and Economics Studies
it
Volume 2, Number 3, 2014
i
lead to consistent parameter estimates. But in our framework,
it
allows
us
to
it
it
it
of
, which is assumed to evolve ac-
it
.
t
-
t
realizations of
it
it
and kit
-
, whereas capital kit
it
choice at time t. Provided that it
t
for any kt.
t ht (it , kt )
yt l lt m mt t it , kt t
with t it , kt 0 k kt ht (it , kt ) . Because
t
t
= ht
l
tion t
With consistent estimates of
and
m
on the
-
l
and
,
m
that kt is uncorrelated with the innovation in
k
, t t t 1 or,
t
t
is a random walk4
ˆ l
ˆ m k
ˆ t 1 k kt 1 t t
yt
l t
m t
k t
where ̂t 1
̂t 1 k kt 1 is an estimate of
.
and
on a fourth-order polynomial
4
A random walk is a mathematical formalization of a path that consists of a succession of random steps.
Review of Business and Economics Studies
step is to estimate
Volume 2, Number 3, 2014
P̂t
k
ˆ l
ˆ m k g (
ˆ t 1 k kt 1 , Pˆt ) t t
yt
l t
m t
k t
̂t 1 k kt 1 and P̂t ;
then estimated non-linearly across all terms that contain it.
ˆ l
ˆ m
ˆ k
tfpit yit
l it
m it
k it
it
’ TFP, it is tfpit
k
is
-
FIit
tfpit X 'it 1 IM it 2 FI it eit
where X 'it
eit
X 'it
’ annual reports.
IM it , it FI it , and
-
-
industry.
Yit 0 1 Lit 2 K it 3 M it 4 FM it 5 IM it 6 FI it 7 Invit uit
uit
-
Review of Business and Economics Studies
Volume 2, Number 3, 2014
Net sales
Number of employees
Value of property, plant and equipment, net of depreciation
Materials (M)
Firm-level year-end materials inventory stocks
Firm mark-up (FM)
Import share (IM)
Value of imported goods
FDI share (FI)
Investment (Inv)
Descriptive statistics of the data.
Variable
Mean
Std. Dev.
Min
Max
Observations
ynetsa~s overall
between
within
16282.94
37104.5
37227.03
7460.019
40.9
380.1
-20632.73
141452
117998.7
39736.27
N =
n =
T =
108
18
6
imimpo~e overall
between
within
3.01
2.734568
2.731948
.6025656
.01
.5
1.463333
11.4
9.75
4.66
N =
n =
T =
108
18
6
2321.141
5181.064
62.22667
-5914.75
7286.343
35884.87
n =
T =
18
6
between
within
random effects. Then the most appropriate model was chosen to estimate the panel data.
-
Review of Business and Economics Studies
Volume 2, Number 3, 2014
-
-
Model
Residual
302.192893
6.45854026
7
96
43.1704132
.067276461
Total
308.651433
103
2.99661585
F( 7,
96)
Prob > F
R-squared
Adj R-squared
Root MSE
= 641.69
= 0.0000
= 0.9791
= 0.9775
= .25938
lllabour
lkcapital
lmmaterials
-.1087084
.4583853
.4237243
.0935847
.057005
.076147
-1.16
8.04
5.56
0.248
0.000
0.000
-.2944726
.3452313
.2725737
.0770558
.5715392
.5748749
limimports~e
.086404
.090191
0.96
0.340
-.0926236
.2654317
linvestment
.0327922
.0142688
2.30
0.024
.0044689
.0611156
_cons
.4223255
.6080333
0.69
0.489
-.7846112
1.629262
R
is
-
Another important assumption of the FE model is that those time-invariant characteristics are unique to the
Review of Business and Economics Studies
Volume 2, Number 3, 2014
Yit 1 Lit 2 K it 3 M it 4 FM it 5 IM it 6 FI it 7 Invit i uit
where i
FE model.
overall = 0.9543
corr(u_i, Xb)
max =
6
=
=
37.75
0.0000
F(7,79)
Prob > F
= -0.6427
lllabour
lkcapital
lmmaterials
-.0654411
.1492522
.3996918
.1897335
.1201148
.1140372
-0.34
1.24
3.50
0.731
0.218
0.001
-.4430962
-.0898305
.1727065
.312214
.3883348
.6266771
limimports~e
.5103775
.1592608
3.20
0.002
.1933768
.8273782
linvestment
_cons
.0109556
.2298174
.0125719
1.915348
0.87
0.12
0.386
0.905
-.0140681
-3.582587
.0359794
4.042222
F test that all u_i=0:
F(17, 79) =
6.74
Prob > F = 0.0000
Review of Business and Economics Studies
Volume 2, Number 3, 2014
The overall R
-
-
Yit 1 Lit 2 K it 3 M it 4 FM it 5 IM it 6 FI it 7 Invit i uit it
it
where uit
RE assumes that the entity’s error term is not correlated with the predictors which allows for time-invariant
used in the model.
Regression model with random effects.
overall = 0.9744
corr(u_i, X)
max =
6
=
=
1492.84
0.0000
Wald chi2(7)
Prob > chi2
= 0 (assumed)
lllabour
lkcapital
lmmaterials
-.1169475
.3232325
.408037
.1233432
.0797434
.0943266
-0.95
4.05
4.33
0.343
0.000
0.000
-.3586958
.1669384
.2231603
.1248008
.4795267
.5929137
limimports~e
.2679408
.1194744
2.24
0.025
.0337753
.5021063
linvestment
_cons
.0162339
.9876227
.0128974
.8314596
1.26
1.19
0.208
0.235
-.0090445
-.6420082
.0415123
2.617254
Review of Business and Economics Studies
Volume 2, Number 3, 2014
The overall R
-
ferences across panels.
and international trade spillovers on Russian chemical market.
F test that all u_i=0: F (17, 79) = 6.74 Prob > F = 0.0000
Estimated results:
Var
lynetsa~s
e
u
Test:
sd = sqrt(Var)
2.996616
.0333638
.0251273
1.731074
.1826576
.1585161
Var(u) = 0
chibar2(01) =
Prob > chibar2 =
13.85
0.0001
From theoretical point of view, to determine whether we should use a FE model or a RE model we have to quesi
E (i it X it ) 0 , where i
use the FE model.
.i We could think that some of these
it the error term. Under this hypothesis
Review of Business and Economics Studies
Volume 2, Number 3, 2014
ˆ]
[b
̂
ˆ
ˆ Var b Var
ˆ
ˆ
Var b
Cov b , Cov[b ,]
ˆ
ˆ
Cov
b , Var 0.
ˆ Var b Var
ˆ
Var b
ˆ ]'
ˆ]
ˆ 1[b
W [b
Hausman test.
lllabour
lkcapital
lmmaterials
-.0654411
.1492522
.3996918
-.1169475
.3232325
.408037
.0515064
-.1739804
-.0083452
.1441709
.0898252
.0640857
limimports~e
.5103775
.2679408
.2424367
.1053085
linvestment
.0109556
.0162339
-.0052783
.
=
Prob>chi2 =
22.28
0.0023
market.
whether the model shows adequate results.
Review of Business and Economics Studies
Volume 2, Number 3, 2014
To detect whether a phenomenon of heteroscedasticity is present in our data we can perform a test of Wald
the error is the same for all individuals.
Test for heteroscedasticity.
chi2 (18) = 110.44
Prob>chi2 = 0.0000
-
als. A phenomenon of heteroscedasticity is present.
-
relation in the errors.
Test for autocorrelation.
F(
1,
17) =
Prob > F =
54.794
0.0000
The null value of the P value leads us to reject the null hypothesis and to validate the presence of autocorrelation
-
FE model with robust standard errors.
overall = 0.9543
corr(u_i, Xb)
= -0.6427
Wald chi2(7)
Prob > chi2
max =
6
=
=
.
.
(Replications based on 18 clusters in company)
Review of Business and Economics Studies
Volume 2, Number 3, 2014
FE model with robust standard errors.
Observed
Bootstrap
lllabour
lkcapital
lmmaterials
-.0654411
.1492522
.3996918
.2324586
.1509844
.1139047
-0.28
0.99
3.51
0.778
0.323
0.000
-.5210515
-.1466719
.1764426
.3901694
.4451762
.622941
limimports~e
.5103775
.2011871
2.54
0.011
.1160581
.904697
linvestment
_cons
.0109556
.2298174
.0102039
2.944158
1.07
0.08
0.283
0.938
-.0090437
-5.540626
.030955
6.000261
We see, with the R
Normal-based
-
ties on Russian chemical market in the form of FDI and international trade leads to increase of productivity within
the whole industry.
-
-
-
-
Review of Business and Economics Studies
Volume 2, Number 3, 2014
-
-
International Journal of the Economics of Business, 12
-
World Development, 35
London
Routledge.
Based on the empirical results, we may predict that
Economica, 41
-
World development, 36
-
The economic journal
Journal of Econometrics, 46
-
other issue is whether the literature so far has taken
’ en-
tors.
Journal of Industrial
Organization, 22
-
Oxford Economic Papers
54
-
fare. Another important question, of course, is whether
The World Bank Economic Review,
the political-economic realities of local electoral competition.
14
, 69
International Economic Review, 40
-
-
Review of Economic Studies, 62,
The American
Economic Review, 89
The American
Economic Review
Journal of Development
Economics, 75
-
-
Economic and
political weekly
Journal of International Economics, 71
The Quar-
Weltwirtschaftliches Archiv, 138
terly Journal of Economics
Review of Business and Economics Studies
Volume 2, Number 3, 2014
Scottish Journal of Political
Economy, 48
The Review of Economic
Studies, 70
-
Review of Economics and Statistics, 57
Econometrica, 71
Journal of Development Economics, 62
Journal of Productivity Analysis, 6
Econometrica, 64, pp.
The
World Bank Research Observer, 19
sterdam.
-
-
The economic journal, 111
The Review of Economic
Studies, 69
The Scandinavian
journal of economics, 107
Economic and Political Weekly,
MA, March.
-
The Review of Economic Studies, 58
Bank.
The Quarterly Journal of Economics, 106
Econometrica, 55
, 47
-
-
Journal of Development Studies, 44
-
The World Bank Research Observer, 23
The American Economic Review, 94
Journal of
Development Economics, 87
Delhi.
American Economic Review, 92
-
Herald of the Russian Academy of Sciences, 83
-
Economic Research.
Journal of International Economics, 31
Journal of Development Economics, 56
Journal of Development Economics, 80
European Economic Review, 48
European Economic Review, 38
74
Отзывы:
Авторизуйтесь, чтобы оставить отзыв