Description
The purpose of this paper is to study the efficiency of capital allocation, across levels of
ownership, in the aftermath of pro-market reforms in India.
Journal of Financial Economic Policy
Pro-market reforms and allocation of capital in India
Sameeksha Desai J ohan Eklund Andreas Högberg
Article information:
To cite this document:
Sameeksha Desai J ohan Eklund Andreas Högberg, (2011),"Pro-market reforms and allocation of capital in
India", J ournal of Financial Economic Policy, Vol. 3 Iss 2 pp. 123 - 139
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Pro-market reforms and
allocation of capital in India
Sameeksha Desai
Indiana University, Bloomington, Indiana, USA, and
Johan Eklund and Andreas Ho¨gberg
Jo¨ nko¨ ping International Business School, Jo¨ nko¨ ping University,
Jo¨ nko¨ ping, Sweden
Abstract
Purpose – The purpose of this paper is to study the ef?ciency of capital allocation, across levels of
ownership, in the aftermath of pro-market reforms in India.
Design/methodology/approach – The paper measures investment ef?ciency using the accelerator
principle and examines the effect of ownership type on capital allocation.
Findings – No signi?cant improvement in capital allocation during the period studied is found.
The ?ndings suggest ?rms face signi?cant costs in adjusting their capital stock.
Originality/value – The paper uses unique data to estimate the elasticity of capital with respect
to output.
Keywords Capital, Cost allocation, Economic reform, Corporate ownership, India
Paper type Research paper
Introduction
A trend in the economic development of countries is the move towards an open
economy. This is the case for countries that have been self-governing for decades after
colonial rule as well as more recently independent countries. Many respond to strong
external signals that an open economy is both politically and economically desirable.
While timing varies, almost every developing country at some point or another does
pursue pro-market reforms. The goals of reforms are often clear, but their effects on
speci?c institutional arrangements and resource allocation are nuanced.
India is an interesting case because of its economic trajectory since independence
(1947). India immediately embraced state-directed planning and, inspired by Fabian
socialism, established an intricate system of industry licensing and regulations called
the License Raj. For almost three decades, average growth rates of 1.25 percent lagged
behind “less promising” Asian economies. More recent success, marked by high growth
in the mid-2000s, has been attributed to adoption of pro-market reforms. Few would
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
JEL classi?cation – E22, E23, G18, G20, E44, L50
The authors would like to thank Zoltan Acs, A
?
ke E. Andersson, David Audretsch,
Per-Olof Bjuggren, Bo¨rje Johansson, Charlie Karlsson, Prashanth Mahagaonkar, Roger Stough,
Daniel Wiberg, Ryan Woolsey, the Ratio Institute in Stockholm and participants at seminars
held at Jo¨nko¨ping International Business School. Sameeksha Desai thanks the Kauffman
Foundation and Institute for Entrepreneurship and Innovation for research support. Financial
support for Andreas Ho¨gberg’s dissertation from Jan Wallanders and Tom Hedelius Foundation
and Tore Browaldhs Foundation via Handelsbanken is gratefully acknowledged. They also
thank three anonymous reviewers for their comments on the paper.
Pro-market
reforms
123
Journal of Financial Economic Policy
Vol. 3 No. 2, 2011
pp. 123-139
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381111133606
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dispute India’s place among the most important economies in the world today. Yet we
know little about speci?c impacts of reforms on ?rm resources, such as capital.
The purpose of this study is to examine how ef?ciently Indian ?rms allocate capital,
across ownership structures, in the aftermath of pro-market reforms. We use the
accelerator principle to derive a measure of how swiftly ?rms respond to changes in
demand and supply conditions: elasticity of capital with respect to output. This is in fact
a measure of functional ef?ciency of capital markets (Tobin, 1984). We ?nd relatively
low elasticity of capital and no general improvement in capital allocation since the
gradual introduction of reforms in 1991. We ?nd industry variation and ownership
structure matter for capital allocation, but in economic terms, the effects are relatively
small. Our research demonstrates that previous reforms have been inadequate in terms
of resource ef?ciency, and that improvements in capital allocation can come from
further deregulation.
In the next section, we discuss the relevant literature. We discuss our method in the
third section, followed by our data. We present results and conclude in the ?fth section.
Literature review
Reforms are expected to improve the functional ef?ciency of capital markets, a process
which allocates (Tobin, 1984) capital to its most productive, value-creating end.
Resources tied up in ?rms with poor prospects should be able to move to ?rms with
high expected future returns. The speed and ease of this process is an important
contributor to overall economic performance and growth (Levine, 1997).
Ultimately, all ?rms have owners. Dispersed ownership (Berle and Means, 1932)
presents the classic agency problem, where managers and owners may have different
goals. Although concentrated ownership (La Porta et al., 1999) may motivate owners to
be more active in ?rm operations ( Jensen and Meckling, 1976; DeMarzo and Urosevic,
2006), it also enables exploitation of small investors (Stulz, 1988). If small investors have
weaker protection, only large owners can realistically expect returns on investment
(La Porta et al., 1998). Therefore, expectations of poor protection may incentivize
concentrated ownership (Shleifer and Vishny, 1997). Pro-market economic reforms
therefore include measures to protect minority investors and increase the ability of more
people to invest in ?rms. The ability of small investors to con?dently invest is a driver
of economic growth and capital availability.
In India, regulation of capital dramatically affects the private sector because of
historic dominance of small and informal businesses (?rms with more than ten
employees account for only 3.75 percent of total employment[1]). Policies governing
capital evolved as economic priorities changed[2] since independence[3], with clear
pro-market reorientation by 1991. The newindustrial policy of 1991 sought to gradually
reduce the industrial licensing burden on ?rms, and to encourage stronger performance
and competitiveness in public enterprises (Sa´ez and Yang, 2001).
Financial sector deregulation has been an important part of India’s growth strategy
after 1991. For example, legislative requirements for certain levels of investment in
government securities were reduced. Large loans no longer require individual approval
from the Reserve Bank of India; the system for interest rate controls has been
dismantled (Ahluwalia, 2002).
Privatization and foreign investment began at the end of the 1990s, and the ?rst
public company was sold to foreign investors in 1999. Privatization policies focused
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on the sale of minority stakes in ?rms, as opposed to transferring control. Today,
100 percent ownership is allowed in all sectors except banking, insurance,
telecommunications and aviation. State ownership remains in some key sectors.
Ahluwalia (2002: 82) notes:
[. . .] even if the government does not interfere directly in credit decisions, government
ownership means managers of public sector banks are held to standards of accountability
akin to civil servants, which tend to emphasize compliance with rules and procedures and
therefore discourage innovative decision making[4].
This adds another facet to the agency problem[5].
Sa´ez and Yang (2001) examine effects of deregulation in the banking, energy and
telecommunications sectors. They conclude that despite improvement, change was
observed primarily in relatively smaller ?rms. The changes occurred at a sub-national
rather than national level. Also, ?rms in the telecommunications and energy sectors are
still subject to heavy regulations.
Kumbhakar and Sarkar (2003) examine deregulation, ownership and productivity of
?rms in the Indian banking industry between 1985 and 1996. They estimate the growth
of total factor productivity (TFP). The TFP is divided into sub-components: technical
change, scale and miscellaneous. Using data for public and private banks, and for
periods before and after deregulation, they do not ?nd an increase in the growth of
TFP. This is interpreted as lack of change on the part of short- and medium-term
bank-level policies despite deregulation. However, they ?nd improved performance in
private banks while public banks did not respond strongly to deregulation.
Banking reforms have strengthened performance but may still be necessary to
achieve further gains (Aziz et al., 2006). Speci?c dynamics of capital allocation remain
largely unclear, but given the extent of policy reforms, it is reasonable to expect ?rms
to have become gradually more responsive to shifts in supply and demand conditions.
Method
Our method is based on the accelerator principle, which holds that investments are
determined by changes in output. If output grows, this is taken to re?ect growing need
for capital. The simple accelerator model assumes output is proportional to capital. By
the same token, any level of output will also be associated with the stock of capital.
This method is a way to measure what Tobin (1984) called the functional ef?ciency of
capital markets. The accelerator model is also closely associated with Samuelson’s
(1939) accelerator-multiplicator model of business cycles. Our method is similar to
Wurgler (2000) and Desai and Eklund (2008) though modi?ed to be consistent with
investment theory. Given our data (accounting data), this is preferable over other
methods, such as data envelopment analysis.
The accelerator model with a desired level of capital denoted K
*
t
is determined by
the output Y
t
:
K
*
t
¼ kY
t
ð1Þ
In equation (1), k, is the capital coef?cient. Assuming desired level of capital is equal to
actual capital, denoted K
t
, changes in desired stock of capital are proportional to net
investments, I
t
and ðK
t
2K
t21
Þ. Net investments I
t
can be denoted as:
I
t
¼ K
t
2K
t21
¼ lðY
t
2Y
t21
Þ ð2Þ
Pro-market
reforms
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Given the formulation of net investments in equation (2), these are proportional to
change in output over time and an accelerator l. Since we assumed desired capital
equals actual capital, then l ¼ k. However, this assumption is not normally ful?lled.
The following equation is obtained by dividing both sides of the equation with
K
t21
:
I
t
K
t21
¼ l
DY
t
K
t21
ð3Þ
Since K
t
¼ kY
t21
we can substitute K
t21
with kY
t21
in equation (4), giving the
following:
I
t
K
t21
¼ l
* DY
t
Y
t21
ð4Þ
Now l
*
represents l=k, or elasticity of capital with respect to output (re?ected by
sales). The normalization allows us to make empirical estimations of equation (4).
By assuming that K
*
t
¼ K
t
, over time we will get l ¼ k, resulting in l
*
¼ 1. If the
adjustment is incomplete and partial, then K
*
t
– K
t
and elasticity of capital with respect
to output, l
*
, will be , 1. This means l
*
re?ects the cost ?rms face in adjusting their
capital stock: costlier adjustment will be re?ected by lower elasticity, all else equal[6].
An alternative to using net investments is gross investments (GI), obtained by
adding replacement investments (depreciation of assets). Assuming proportionality to
the old capital stock, we can denote this as dK
t21
. GI are thus de?ned as: equation (2)
plus dK
t21
, GI
t
¼ dK
t21
þlDY
t
. Mutatis mutandis, the corresponding equation for
GI is GI
t
=K
t21
¼ d þl
*
DY
t
=Y
t21
. In empirical applications, this means the only
difference between net and GI will be captured by the intercept.
We estimate the following:
I
i;t
K
i;t21
¼ a þ h
i
þ u
t
þl
*
DS
i;t
S
i;t21
þ 1
i;t
ð5Þ
In equation (5), elasticity of capital with respect to sales is represented by l
*
, where I
represents investments made by the ?rmi in time period t. Capital stock in period t 2 1
is denoted as Kand S denotes sales in period t. To control for unobserved heterogeneity,
we include a ?xed effect h
j
where j represents industry or ?rm effects. We include u
t
to
control for business cycle ?xed year effects.
Using panel data with ?xed effects, we add interaction variables (dummies) to
capture different types of ?rm owners. We also use time dummies for time-speci?c
effects. Using interaction terms, the empirical equation will have following functional
form:
I
i;t
K
i;t21
¼ a þ h
i
þ u
t
þb
1
DS
i;t
S
i;t21
þ b
2
DS
i;t
S
i;t21
£ X
1;i;t
þ · · ·
þb
n
DS
i;t
S
i;t21
£ X
n21;i;t
þ1
i;t
ð6Þ
where the X’s denote explanatory variables. Thus, the elasticity of capital, l*,
corresponds to the marginal effect in equation (6):
l
*
¼ b
1
þ b
2
£ X
1
þ · · · þ b
n
£ X
n21
ð7Þ
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We use interaction explanatory variables with sales growth in order to determine how
these variables affect elasticity of capital.
Data
We collect ?rm-level accounting data on investments, capital stock and sales from the
Prowess India database[7]. Total assets are used as a measure of capital stock, K
t
, and
sales are used as our measure of output. We use net investments (DK
t
), measured as
change in total assets[8]. De?nitions and sources of variables are listed in Table I.
We exclude the ?nancial sector since investments made by ?nancial ?rms are of a
different nature than in other sectors. All accounting ?gures have been adjusted for
in?ation with consumer price index (CPI) from IMF.
Ownership data available from the Prowess database is subdivided into broad
categories. There are two main ownership categories: promoters and non-promoters.
Promoters are de?nedbyIndianlegislation[9] andis basicallysynonymous to controlling
owner. Apromoter is legallyde?ned as a personwho is in control of the company andhas
the right to appoint directors or control management. Non-promoters refers to a dispersed
ownership stake, i.e. no controlling owner. Apart from distinguishing between Indian
Component De?nition
Sales Sum of industrial sales and income from non-?nancial
services
a
Capital Total assets
a
In?ation Measured with average CPI
b
Capital intensity Capital divided by sales
Ownership categories
Promoters holding (%) The dominant/controlling owner. Indian law de?nes
promoters as the person in control of the company. All
ownership categories are measured as percentage share of
equity capital
Indian promoters (%) Domestic controlling owners
a
Foreign promoters (%) Foreign controlling owner
a
Persons acting in concert (%) –
promoters
Persons/owners acting in concert as controlling owners
a
Non-promoters holding (%) Non-promoters are the shares held by non controlling
owners, i.e. dispersed ownership
a
Institutions – non-promoters (%) Institutional non-promoters are the sum of the shares held by
mutual funds, banks and foreign institutional investors
a
Mutual funds/UTI (%) – non-
promoters
Includes non-promoting mutual funds
a
Banks, FI’s, insurance companies (%)
– non-promoters
Includes non-promoting banks, ?nancial institutions and
insurance companies
a
Foreign institutional
investors (%) – non-promoters
Includes non-promoting foreign institutional investors
a
Non-institutions (%) – non-promoters Includes non-promoter non-institutional investors
a
Corporate bodies (%) – non-promoters Includes non-promoter corporate bodies
a
Individuals (%) – non-promoters Includes non-promoting individual investors
a
Other non-institutions (%) –
non-promoters
Non-promoters not elsewhere de?ned
a
Sources:
a
Prowess;
b
IMF, World Economic Outlook Database 2007
Table I.
Variables
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promoters and foreign promoters, it is not possible to further subdivide the promoter
category[10]. Thus, the following are included within the promoter category and cannot
be extricated: individual/family promoters, state and government promoters, corporate
promoters and institutional promoters. It is possible, however, to subdivide
non-promoters into subcategories. This is meaningful as non-promoters represent the
mirror image of promoters (promoters being a measure of ownership concentration).
Few ?rms in India are characterized by dispersed ownership. In 2006, only 126 of
2,050 ?rms had dispersed ownership, where no owner controlled 20 percent or more of
the shares. Table II presents data on promoter and non-promoter holdings.
95 percent of the ?rms had an Indian promoter (controlling owner) and 86 percent
had an Indian promoter owning more than 20 percent of shares[11]. Some 10 percent of
?rms had some degree of state or government ownership, and about 4 percent had a
state or government promoter. On average, Indian promoters own about 46 percent of
shares, whereas average ownership of foreign promoters is about 28 percent. However,
the overall average promoter holding is just above 50 percent. Total promoter holding
is larger than Indian and foreign promoters separately because, in a number of cases,
foreign and domestic promoters act in concert and are thus jointly de?ned as
promoters. Since it is not possible to distinguish various promoter categories, the data
are problematic and do not add up precisely.
In contrast to data on promoters, data on various categories of non-promoters are
available. Non-promoters are divided into institutional non-promoters and
non-institutional promoters. The institutional non-promoter group is further split into:
.
mutual funds;
.
banks, ?nancial institutions and insurance companies; and
.
foreign institutional investors.
It is not possible to identify the extent to which banks, ?nancial institutions and
insurance companies are state or governmental controlled. Summary statistics of the
ownership data and correlations are presented in Appendices 1 and 2.
We construct an unbalanced panel of more than 7,000 companies for 1991-2006.
Since we use growth in sales and capital stock from previous periods, we have data
Average ownership per year
Type of owner 2002 2003 2004 2005 2006
Promoters holding (%) 50.62 51.80 51.23 50.32 50.40
Indian promoters (%) 39.37 40.29 39.28 38.71 43.87
Foreign promoters (%) 5.93 6.08 5.86 5.95 6.53
Persons acting in concert (%) – promoters 5.32 5.44 6.09 5.66 0
Non-promoters holding (%) 49.38 48.16 48.77 49.59 49.23
Institutions (%) – non-promoters 6.85 6.44 6.22 6.85 7.14
Mutual funds/UTI (%) – non-promoters 1.81 1.54 1.45 1.63 1.74
Banks, FI’s, insurance companies (%) – non-promoters 4.34 3.77 3.37 2.94 2.80
Foreign institutional investors (%) – non-promoters 0.70 1.14 1.38 2.27 2.65
Non-institutions (%) – non-promoters 42.53 41.71 42.57 42.79 41.82
Corporate bodies (%) – non-promoters 9.99 10.15 10.92 11.22 9.03
Individuals (%) – non-promoters 31.42 30.31 30.28 30.11 30.41
Other non-institutions (%) – non-promoters 1.12 1.24 1.36 1.45 2.38
Table II.
Mean share of
ownership per type of
owner and per year
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for 15 years. In total, the panel includes 48,623 observations. Unfortunately, the data do
not follow a normal distribution: the skewness and kurtosis test for normality clearly
indicates non-normality, mainly due to extreme outliers. A less skewed distribution is
achieved by removing the 2.5th and 97.5th percentiles of our dependent and independent
variables. After this, 6,457 companies and 45,443 observations remain. Ownership data
are only available from 2001 until 2006, corresponding to 12,423 observations.
We use industry effects in all regressions to control for unobserved heterogeneity
across ?rms. This is theoretically appropriate because much unobserved heterogeneity
across ?rms can be attributed to industry differences and regulatory differences across
industries. However, the empirical results are unaffected by the choice between ?xed
industry and ?xed ?rm effects. To further control for ?rm speci?c effects, we include
controls for ?rm size and capital intensity. Both size and capital intensity can be
expected to impact the adjustment of the capital stock, and thus, elasticity of the
capital stock. In particular, we expect capital intensity to be important for the speed
of adjustment. Consequently, we also include our measure of capital intensity
as an interaction term with sales growth. Our results are robust with inclusion or
omission of these controls[12].
In addition to the sales accelerator, overall elasticity of capital has been estimated
using a pro?t accelerator and value-added accelerator. The value-added accelerator was
insigni?cant. The pro?t accelerator was signi?cant but economically negligible.
A possible explanation is the quality of accounting data, rendering pro?ts and value
added incomparable across ?rms. Using ?xed effects estimation, the overall R
2
for the
pro?t accelerator was less than 1 percent. An interpretation is relative reliability of sales
(fairly consistent reporting across ?rms) versus likely variation (e.g. underreporting) in
reporting of pro?ts and value added. The measure of investment used solves some of
these problems by including depreciation and all items in the income statement and
balance sheet that can be counted as investment.
Results
We estimate overall elasticity of capital for India as approximately 0.20, lower than
could be expected. This suggests it takes at least ?ve years for the average ?rmto adjust
to changes in demand and supply. From investment theory, one would expect elasticity
of capital to equal one. Lower elasticity indicates ?rms only partially adjusting capital
stock to changes in output, implying that investments are not expanded to the point
where marginal return on capital equals its opportunity cost.
Table III reports results for ownership categories and contains regular ?xed effects
results.
The estimates show signi?cant, minor, positive effects on allocation of capital for
promotors and negative effects from non-promotors. However, breaking down
ownership into sub-levels shows only Indian promoters having a positive signi?cant
effect on allocation of capital. The picture is mixed for non-promotors. All effects on
allocation of capital are signi?cantly different from zero, but only institutions overall,
mutual funds and foreign institutions have a positive effect. The controls for size and
capital intensity all show high signi?cance levels and expected signs.
Industry dummies were interacted with DS
t
/S
t21
and the coef?cients constrained to
sumto zero, suchthat industryspeci?c elasticities are obtained. This means anysigni?cant
effect of ownership on elasticity of capital cuts across industries. As a robustness check,
Pro-market
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T
)
R
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5
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1
9
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(
6
.
2
5
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(
7
.
6
0
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9
.
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3
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9
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7
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9
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6
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6
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2
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5
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4
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5
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2
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4
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2
5
.
0
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4
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6
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1
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n
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s
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t
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*
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S
t
/
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2
1
(
2
3
.
9
9
)
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2
4
.
1
5
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4
.
3
1
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2
3
.
9
8
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2
4
.
0
8
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(
2
3
.
9
8
)
(
2
4
.
3
8
)
(
2
3
.
8
4
)
(
2
3
.
6
7
)
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2
3
.
5
1
)
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2
4
.
3
1
)
P
r
o
m
o
t
e
r
s
0
.
0
0
1
*
(
4
.
6
1
)
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n
d
i
a
n
8
.
7
£
1
0
2
4
*
p
r
o
m
o
t
e
r
s
(
4
.
3
5
)
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o
r
e
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g
n
1
.
4
£
1
0
2
4
p
r
o
m
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t
e
r
s
(
0
.
4
7
)
N
o
n
-
p
r
o
m
o
t
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s
2
0
.
0
0
1
*
(
2
4
.
6
1
)
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n
s
t
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t
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t
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n
s
0
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0
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3
*
(
6
.
3
6
)
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u
t
u
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l
f
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n
d
s
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0
1
4
*
(
1
0
.
1
8
)
B
a
n
k
s
,
F
I
.
a
n
d
2
0
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0
0
4
*
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n
s
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r
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m
p
.
(
2
5
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8
0
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g
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0
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0
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1
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n
s
t
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t
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l
(
1
2
.
5
1
)
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o
n
-
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n
s
t
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t
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t
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s
2
0
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0
0
2
*
(
2
7
.
4
1
)
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n
d
i
v
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d
u
a
l
s
2
0
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0
0
2
*
(
2
8
.
4
5
)
C
o
r
p
o
r
a
t
e
2
7
.
1
£
1
0
2
4
*
*
(
2
1
.
9
6
)
(
c
o
n
t
i
n
u
e
d
)
Table III.
Ownership and allocation
of capital
JFEP
3,2
130
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
4
0
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
R
e
g
r
e
s
s
i
o
n
w
i
t
h
?
x
e
d
i
n
d
u
s
t
r
y
a
n
d
y
e
a
r
e
f
f
e
c
t
s
,
a
n
d
t
i
m
e
a
n
d
i
n
d
u
s
t
r
y
s
p
e
c
i
?
c
e
l
a
s
t
i
c
i
t
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e
s
,
d
e
p
e
n
d
e
n
t
v
a
r
i
a
b
l
e
:
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t
/
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1
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(
6
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8
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)
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6
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9
2
)
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6
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9
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)
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6
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8
8
)
(
6
.
8
5
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6
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)
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6
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4
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6
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0
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6
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2
)
R
2
0
.
2
1
5
0
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2
1
4
0
.
2
1
3
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2
1
5
0
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2
1
6
0
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2
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2
1
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0
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2
2
3
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2
1
3
A
d
j
u
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d
R
2
0
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2
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2
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0
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2
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8
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2
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0
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2
1
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2
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0
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2
1
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0
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2
1
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0
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2
1
1
0
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2
0
7
F
-
v
a
l
u
e
3
2
.
6
6
3
2
.
6
3
3
2
.
4
0
3
2
.
6
6
3
2
.
9
0
3
3
.
6
8
3
2
.
8
1
3
4
.
3
3
3
3
.
0
7
3
3
.
2
8
3
2
.
4
4
N
o
.
o
b
s
e
r
v
a
t
i
o
n
s
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
1
2
,
4
2
3
N
o
t
e
s
:
S
i
g
n
i
?
c
a
n
c
e
a
t
:
*
1
a
n
d
*
*
5
p
e
r
c
e
n
t
l
e
v
e
l
s
,
r
e
s
p
e
c
t
i
v
e
l
y
;
t
-
v
a
l
u
e
s
w
i
t
h
i
n
p
a
r
e
n
t
h
e
s
e
s
;
i
n
c
l
u
d
i
n
g
i
n
d
u
s
t
r
y
e
f
f
e
c
t
s
,
t
i
m
e
e
f
f
e
c
t
s
,
t
i
m
e
d
u
m
m
i
e
s
a
n
d
i
n
d
u
s
t
r
y
d
u
m
m
i
e
s
i
n
t
e
r
a
c
t
e
d
w
i
t
h
g
r
o
w
t
h
i
n
s
a
l
e
s
,
a
n
d
c
o
n
s
t
r
a
i
n
e
d
t
o
z
e
r
o
Table III.
Pro-market
reforms
131
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
4
0
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
we also estimate equation (7) with GI. The results are by andlarge robust, thus not reported
here. Additional robustness checks include multilevel mix effects models where we allow
industry elasticities to vary randomly over time. We ?nd no general trend towards
improved capital allocation over time, nor do we ?nd any improvement in industry
allocation. Industry speci?c elasticities are reported in Table IV.
Most industries report elasticities ranging from 15 to 25 percent, which is low
compared to what might be expected in developed countries. One possible explanation
is that we only look at large incumbent ?rms, whereas most of the growth dynamics
may actually be originating in small-young ?rms. Another explanation for small
industry differences may be geographical differences in regulatory reforms.
Aghion et al. (2006) examines labor policy and ?nd that dismantling the License Raj
proceeded at different speeds across regions in India.
The fact that it is not possible to break down foreign and Indian promoters into
further subcategories is a limitation. It is reasonable to expect different promoters may
have different objectives, resulting in the agency problem; this would be a useful
avenue for further research. This may account for the ?nding that promoters have no
robust signi?cant effect on allocation of capital.
Looking at non-promoters, institutional investors appear to improve allocation of
capital. Breaking down institutional investors into subcategories reveals an interesting
pattern. Mutual funds and foreign institutional investors appear to improve capital
allocation. Banks seem to have a negative impact, but it is not robust. According to the
results, institutional investors increase elasticity of capital by about 2 percentage
points. The positive effect of foreign institutional investors is consistent with the idea
that foreign investment may push openness and accountability. We ?nd few
signi?cant results when studying elasticities of separate industries.
One reason for the low levels of signi?cance is the lack of observations for some
industries (as low as the single digits for some sectors). But perhaps more importantly,
this demonstrates that elasticity of capital is not dependent on industry effects to the
same extent that it is affected by ownership, supporting the importance of ownership
effects on ?rm performance.
Table V contains the elasticity of capital and yearly deviations from the overall
elasticity of capital.
Few of the estimates are signi?cantly different from zero. Those estimates different
from zero display expected signs of the yearly elasticity based on general economic
trends, compared to the overall elasticity of capital during the period. For example, the
elasticity of capital increases during 2005-2006 and decreases during 2001. Overall, the
changes over time are fairly small and seem to follow a general economic trend.
Conclusion
We examined investment behavior and ef?ciency of capital allocation, using the
accelerator principle to derive a measure of capital allocation (elasticity of capital with
respect to output). This reveals how effectively ?rms and industries respond to
changes in the desired capital stock. At one level, this also re?ects investment decisions
possibly driven by reforms.
We ?nd promoters (controlling owners) have no signi?cant impact on allocation of
capital. The reason for this result may be our inability to distinguish various types of
controlling owners, e.g. government promoters and private individuals or families.
JFEP
3,2
132
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
4
0
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Industry
Industry
code
a
Elasticity t-value
No.
observations
Overall elasticity of capital (all industry weighted
average) 0.225
*
4.55 45,443
1. Agriculture, hunting and related service activities 1 20.069 21.28 469
2. Forestry, logging and related services 2 1.958 0.84 2
3. Mining of coal, lignite and extraction of peat 10 0.079 0.70 140
4. Extraction of crude petroleum, natural gas and
incidental activities 11 20.030 20.48 131
5. Mining of uranium and thorium 12 0.264 0.49 11
6. Mining of metal ores 13 20.026 20.40 154
7. Other mining and quarrying 14 20.138
*
22.52 463
8. Manufacturing of food and beverages 15 20.090
* *
21.80 4,060
9. Manufacture of tobacco products 16 0.139 1.52 114
10. Manufacturing of textiles 17 20.053 21.06 3,574
11. Manufacture of wearing, dressing and dyeing of fur 18 20.008 20.15 423
12. Tanning and dressing of leather, saddler, etc. 19 20.060 21.03 305
13. Manufacture of wood, cork, straw and plating
material 20 20.074 21.03 165
14. Manufacture of paper and paper products 21 20.082 21.55 1,057
15. Publish and printing 22 0.077 1.20 293
16. Manufacture of coke, re?ned petroleum and nuclear
fuel 23 20.006 20.11 385
17. Manufacture of chemicals and chemical products 24 20.040 20.81 7,549
18. Manufacture of rubber and plastic products 25 20.044 20.87 2,266
19. Manufacture of non-metallic mineral products 26 20.129
*
22.50 1,631
20. Manufacture of basic metals 27 20.019 20.38 3,027
21. Manufacture of fabricated metal, except machinery
and equipment 28 20.018 20.35 897
22. Manufacture of machinery and equipment NEC 29 20.030 20.59 2,568
23. Manufacturing of of?ce, accounting and computing
machinery 30 0.037 0.65 254
24. Manufacturing of electrical machinery and
apparatus NEC 31 20.007 20.13 1,387
25. Manufacturing of radio, television and
communication apparatus 32 20.047 20.89 901
26. Manufacturing of medical, precision and optical
instruments, clocks and watches 33 0.009 0.17 379
27. Manufacture of motor vehicles, trailers and semi-
trailers 34 0.061 1.19 2,052
28. Manufacture of other transport equipment 35 20.070 21.20 330
29. Manufacture of furniture; manufacturing NEC 36 20.022 20.40 491
30. Electricity, gas, steam and hot water supply 40 20.104
* *
21.88 443
31. Construction 45 20.039 20.76 1,304
32. Sale, maintenance and repair of motor vehicles and
motorcycles 50 20.632 21.14 6
33. Wholesale trade and commission trade except
motor vehicles 51 20.059 21.17 3,176
34. Retail trade and repair of personal and household
goods 52 0.056 0.78 57
35. Hotels and restaurants 55 20.133
*
22.47 793
(continued)
Table IV.
Industry speci?c
elasticities
Pro-market
reforms
133
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
4
0
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Industry
Industry
code
a
Elasticity t-value
No.
observations
36. Land transport; transport via pipelines 60 0.108
*
1.70 263
37. Water transport 61 20.020 20.32 233
38. Air transport 62 0.107 1.02 75
39. Supporting and auxiliary transport activities 63 20.063 21.01 189
40. Post and telecommunication 64 20.016 20.29 246
41. Real estate activities 70 20.031 20.49 150
42. Renting of machinery and equipment without
operator 71 0.139
* *
1.82 48
43. Computer and related activities 72 0.026 0.51 1,460
44. Research and development 73 20.172 21.33 9
45. Other business activities 74 20.082 21.43 255
46. Education 80 20.366
*
22.62 19
47. Health and social work 85 20.076 21.22 229
48. Activities of membership organizations NEC 91 20.062 20.60 21
49. Recreational, cultural and sporting activities 92 20.034 20.63 334
50. Undifferentiated service-producing activities 97 20.104 21.28 40
51. Diversi?ed 98 20.006 20.11 614
Notes: Signi?cance at:
*
5 and
* *
10 percent levels;
a
industry codes follow the national industrial
classi?cation 2004; industry elasticities estimated with industry and year ?xed effect; to obtain the
industry-speci?c elasticities, DS
t
/S
t21
is interacted with industry dummies and constrained to sum to
zero; NEC, not elsewhere classi?ed Table IV.
DSt/St 2 1 0.182
*
(58.84)
1992 0.010 (0.48)
1993 0.006 (0.37)
1994 0.039
*
(2.97)
1995 0.034
*
(3.04)
1996 20.015 (21.61)
1997 20.030
*
(22.99)
1998 20.025
* *
(2.46)
1999 20.013 (21.29)
2000 20.009 (20.99)
2001 20.016
* * *
(21.80)
2002 20.014 (21.51)
2003 20.018
* *
(21.97)
2004 0.013 (1.48)
2005 0.020
* *
(2.28)
2006 0.020
* *
(2.09)
Constant 0.004 (1.13)
R
2
0.22
Adjusted R
2
0.22
F-value 164.7
No. observations 45,443
Notes: Signi?cance at:
*
1,
* *
5 and
* * *
10 percent levels; includes ?xed industry and time effects (not
reported); year dummies interacted with growth in sales; t-values are within parentheses
Table V.
Elasticity of capital and
yearly deviations from
overall elasticity of
capital
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With respect to non-promoter holdings (dispersed ownership), we observe signi?cant
effects of ownership. Institutional investors signi?cantly improve capital allocation.
We observe an interesting pattern in subcategories of institutional owners: mutual
funds and foreign institutional investors improve allocation of capital whereas banks
have no effect or a negative effect. We also ?nd signi?cant variation in capital
allocation across industries, and ownership effects cut across industries.
The overall ?nding is that despite economic reforms, the ef?ciency of capital
allocation remains fairly slow. This indicates signi?cant lag between introduction of
reforms and ?rm responses, and is not entirely surprising given institutional stickiness.
Still, improvements in stock and equity markets, and strong and consistent development
of commercial banks (Aziz et al., 2006) reasonably imply greater ef?ciency. However,
we ?nd overall elasticity of capital is about 26 percent, implying that when sales increase
10 percent, capital stock on average increases by 2.6 percent.
We therefore conclude that while pro-market reforms in India stimulated ef?ciency to
some extent, improvements in capital allocation may come from further deregulation.
Our ?nding that mutual funds and foreign institutional investors signi?cantly improve
allocation of capital provides useful focus for policy makers. Our work contributes to
knowledge on the ef?cient allocation of resources, and in doing so, identi?es several
extensions for research. One important question concerns effects of speci?c institutional
investors. For example, why do banks have a negative or absent effect? This is
important not only because it is surprising, but because many countries actively target
banking reform to create ef?ciencies. Another question is the relatively low capital
allocation in our estimation, versus what has been found for rapidly developing peers,
notably China. Further research can build on Hsieh and Klenow (2007) to better
understand resource allocation in important sectors such as manufacturing. Another
promising direction for future research is to study the institutional lag of reforms across
contents. This can yield implications for practice by helping to differentiate ineffective
policies from those that simply require time to be effective.
Notes
1. See OECD (2007); this estimate is for registered ?rms and likely underestimated due to the
existence of a large unof?cial sector.
2. The original post-independence Industrial Policy Resolution of 1948 emphasized
consistently increasing production. In 1956, a new resolution identi?ed rapid economic
growth as the path to a socialist society, assigning primary responsibility to central
government. Multiple Industrial Policy Statements (1973 and 1977) demonstrated a shift in
treatment of the private sector. In 1980, a new Industrial Policy Statement emphasized
competition and technology in domestic industries in order to encourage exports and foreign
investment.
3. See Bhagwati and Desai (1970) for historic perspective.
4. Similarly, short of privatization, publicly owned companies can be controlled by a
government investment agency rather than ministries subsidizing companies (OECD, 2007).
5. For more on separation of ownership from policy making (OECD, 2007).
6. Often in this type of model, a partial adjustment model is used to allow for lag structure in
the adjustment process. A higher order lag structure simply means higher adjustment costs.
Since we are interested in adjustment cost, we do not investigate lag structure.
Pro-market
reforms
135
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7. The database is provided by the Centre for Monitoring the Indian Economy Pvt. Ltd; usual
accounting caveats apply.
8. As a robustness test we also used gross investments. By and large, the estimates are robust
so we do not report results for gross investments. We measure GI: I
t
¼Profitaftertax2
dividendsþdepreciationþDEquityþDDebt þR&DþAdvertisingand Marketingexpenses:
9. The term promoter is de?ned in regulation 2(h) Securities and Exchange Board of India
(substantial acquisitions of shares and takeovers) regulation 1997.
10. Promoters also include a subcategory for persons acting in concert. However, this category is
not examined further in this paper.
11. A total of 20 percent ownership is enough to have control over a ?rm, consistent with the
corporate governance literature which treats levels below 50 percent suf?cient to maintain
control (Morck et al., 2005).
12. Note that other studies do not use these controls (Wurgler, 2000).
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(The Appendices follow overleaf.)
About the authors
Sameeksha Desai is an Assistant Professor in the School of Public and Environmental Affairs
and Associate Director of the Institute for Development Strategies at Indiana University.
Johan Eklund is an Assistant Professor in Financial Economics at Jo¨nko¨ping International
Business School and a Research Fellow at the Ratio Institute. Johan Eklund is the corresponding
author and can be contacted at: [email protected]
Andreas Ho¨gberg is a PhD Candidate in Economics at Jo¨nko¨ping International Business
School.
Pro-market
reforms
137
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Appendix 1
T
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Table AI.
Summary statistics,
ownership 2002-2006
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6
*
2
0
.
1
1
*
2
0
.
1
6
*
2
0
.
1
3
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2
0
.
0
0
0
.
1
6
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0
.
7
3
*
0
.
2
4
*
1
F
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t
i
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i
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1
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2
0
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1
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2
0
.
0
8
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.
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2
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0
.
1
0
*
0
.
6
1
*
0
.
2
9
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0
.
0
7
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1
N
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i
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i
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p
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1
2
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2
0
.
1
4
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2
0
.
0
3
2
0
.
1
0
*
2
0
.
8
6
*
2
0
.
5
0
*
2
0
.
2
9
*
0
.
8
7
*
2
0
.
3
2
*
2
0
.
2
2
*
2
0
.
2
3
*
2
0
.
2
0
*
1
C
o
r
p
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r
a
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e
b
o
d
i
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s
–
n
o
n
-
p
r
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m
o
t
e
r
s
2
0
.
0
5
*
2
0
.
0
6
*
0
.
0
2
*
0
.
0
1
2
0
.
4
8
*
2
0
.
2
8
*
2
0
.
1
5
*
0
.
4
8
*
2
0
.
1
1
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2
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0
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2
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0
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*
2
0
.
1
5
*
2
0
.
0
3
2
0
.
1
5
*
2
0
,
6
5
*
2
0
.
3
7
*
2
0
.
2
3
*
0
.
6
5
*
2
0
.
3
4
*
2
0
.
2
2
*
2
0
.
2
3
*
2
0
.
2
4
*
0
.
7
9
*
2
0
.
0
3
*
N
o
t
e
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
5
p
e
r
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e
n
t
l
e
v
e
l
Table AII.
Correlations
Pro-market
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139
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doc_138966540.pdf
The purpose of this paper is to study the efficiency of capital allocation, across levels of
ownership, in the aftermath of pro-market reforms in India.
Journal of Financial Economic Policy
Pro-market reforms and allocation of capital in India
Sameeksha Desai J ohan Eklund Andreas Högberg
Article information:
To cite this document:
Sameeksha Desai J ohan Eklund Andreas Högberg, (2011),"Pro-market reforms and allocation of capital in
India", J ournal of Financial Economic Policy, Vol. 3 Iss 2 pp. 123 - 139
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Pro-market reforms and
allocation of capital in India
Sameeksha Desai
Indiana University, Bloomington, Indiana, USA, and
Johan Eklund and Andreas Ho¨gberg
Jo¨ nko¨ ping International Business School, Jo¨ nko¨ ping University,
Jo¨ nko¨ ping, Sweden
Abstract
Purpose – The purpose of this paper is to study the ef?ciency of capital allocation, across levels of
ownership, in the aftermath of pro-market reforms in India.
Design/methodology/approach – The paper measures investment ef?ciency using the accelerator
principle and examines the effect of ownership type on capital allocation.
Findings – No signi?cant improvement in capital allocation during the period studied is found.
The ?ndings suggest ?rms face signi?cant costs in adjusting their capital stock.
Originality/value – The paper uses unique data to estimate the elasticity of capital with respect
to output.
Keywords Capital, Cost allocation, Economic reform, Corporate ownership, India
Paper type Research paper
Introduction
A trend in the economic development of countries is the move towards an open
economy. This is the case for countries that have been self-governing for decades after
colonial rule as well as more recently independent countries. Many respond to strong
external signals that an open economy is both politically and economically desirable.
While timing varies, almost every developing country at some point or another does
pursue pro-market reforms. The goals of reforms are often clear, but their effects on
speci?c institutional arrangements and resource allocation are nuanced.
India is an interesting case because of its economic trajectory since independence
(1947). India immediately embraced state-directed planning and, inspired by Fabian
socialism, established an intricate system of industry licensing and regulations called
the License Raj. For almost three decades, average growth rates of 1.25 percent lagged
behind “less promising” Asian economies. More recent success, marked by high growth
in the mid-2000s, has been attributed to adoption of pro-market reforms. Few would
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
JEL classi?cation – E22, E23, G18, G20, E44, L50
The authors would like to thank Zoltan Acs, A
?
ke E. Andersson, David Audretsch,
Per-Olof Bjuggren, Bo¨rje Johansson, Charlie Karlsson, Prashanth Mahagaonkar, Roger Stough,
Daniel Wiberg, Ryan Woolsey, the Ratio Institute in Stockholm and participants at seminars
held at Jo¨nko¨ping International Business School. Sameeksha Desai thanks the Kauffman
Foundation and Institute for Entrepreneurship and Innovation for research support. Financial
support for Andreas Ho¨gberg’s dissertation from Jan Wallanders and Tom Hedelius Foundation
and Tore Browaldhs Foundation via Handelsbanken is gratefully acknowledged. They also
thank three anonymous reviewers for their comments on the paper.
Pro-market
reforms
123
Journal of Financial Economic Policy
Vol. 3 No. 2, 2011
pp. 123-139
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381111133606
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dispute India’s place among the most important economies in the world today. Yet we
know little about speci?c impacts of reforms on ?rm resources, such as capital.
The purpose of this study is to examine how ef?ciently Indian ?rms allocate capital,
across ownership structures, in the aftermath of pro-market reforms. We use the
accelerator principle to derive a measure of how swiftly ?rms respond to changes in
demand and supply conditions: elasticity of capital with respect to output. This is in fact
a measure of functional ef?ciency of capital markets (Tobin, 1984). We ?nd relatively
low elasticity of capital and no general improvement in capital allocation since the
gradual introduction of reforms in 1991. We ?nd industry variation and ownership
structure matter for capital allocation, but in economic terms, the effects are relatively
small. Our research demonstrates that previous reforms have been inadequate in terms
of resource ef?ciency, and that improvements in capital allocation can come from
further deregulation.
In the next section, we discuss the relevant literature. We discuss our method in the
third section, followed by our data. We present results and conclude in the ?fth section.
Literature review
Reforms are expected to improve the functional ef?ciency of capital markets, a process
which allocates (Tobin, 1984) capital to its most productive, value-creating end.
Resources tied up in ?rms with poor prospects should be able to move to ?rms with
high expected future returns. The speed and ease of this process is an important
contributor to overall economic performance and growth (Levine, 1997).
Ultimately, all ?rms have owners. Dispersed ownership (Berle and Means, 1932)
presents the classic agency problem, where managers and owners may have different
goals. Although concentrated ownership (La Porta et al., 1999) may motivate owners to
be more active in ?rm operations ( Jensen and Meckling, 1976; DeMarzo and Urosevic,
2006), it also enables exploitation of small investors (Stulz, 1988). If small investors have
weaker protection, only large owners can realistically expect returns on investment
(La Porta et al., 1998). Therefore, expectations of poor protection may incentivize
concentrated ownership (Shleifer and Vishny, 1997). Pro-market economic reforms
therefore include measures to protect minority investors and increase the ability of more
people to invest in ?rms. The ability of small investors to con?dently invest is a driver
of economic growth and capital availability.
In India, regulation of capital dramatically affects the private sector because of
historic dominance of small and informal businesses (?rms with more than ten
employees account for only 3.75 percent of total employment[1]). Policies governing
capital evolved as economic priorities changed[2] since independence[3], with clear
pro-market reorientation by 1991. The newindustrial policy of 1991 sought to gradually
reduce the industrial licensing burden on ?rms, and to encourage stronger performance
and competitiveness in public enterprises (Sa´ez and Yang, 2001).
Financial sector deregulation has been an important part of India’s growth strategy
after 1991. For example, legislative requirements for certain levels of investment in
government securities were reduced. Large loans no longer require individual approval
from the Reserve Bank of India; the system for interest rate controls has been
dismantled (Ahluwalia, 2002).
Privatization and foreign investment began at the end of the 1990s, and the ?rst
public company was sold to foreign investors in 1999. Privatization policies focused
JFEP
3,2
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on the sale of minority stakes in ?rms, as opposed to transferring control. Today,
100 percent ownership is allowed in all sectors except banking, insurance,
telecommunications and aviation. State ownership remains in some key sectors.
Ahluwalia (2002: 82) notes:
[. . .] even if the government does not interfere directly in credit decisions, government
ownership means managers of public sector banks are held to standards of accountability
akin to civil servants, which tend to emphasize compliance with rules and procedures and
therefore discourage innovative decision making[4].
This adds another facet to the agency problem[5].
Sa´ez and Yang (2001) examine effects of deregulation in the banking, energy and
telecommunications sectors. They conclude that despite improvement, change was
observed primarily in relatively smaller ?rms. The changes occurred at a sub-national
rather than national level. Also, ?rms in the telecommunications and energy sectors are
still subject to heavy regulations.
Kumbhakar and Sarkar (2003) examine deregulation, ownership and productivity of
?rms in the Indian banking industry between 1985 and 1996. They estimate the growth
of total factor productivity (TFP). The TFP is divided into sub-components: technical
change, scale and miscellaneous. Using data for public and private banks, and for
periods before and after deregulation, they do not ?nd an increase in the growth of
TFP. This is interpreted as lack of change on the part of short- and medium-term
bank-level policies despite deregulation. However, they ?nd improved performance in
private banks while public banks did not respond strongly to deregulation.
Banking reforms have strengthened performance but may still be necessary to
achieve further gains (Aziz et al., 2006). Speci?c dynamics of capital allocation remain
largely unclear, but given the extent of policy reforms, it is reasonable to expect ?rms
to have become gradually more responsive to shifts in supply and demand conditions.
Method
Our method is based on the accelerator principle, which holds that investments are
determined by changes in output. If output grows, this is taken to re?ect growing need
for capital. The simple accelerator model assumes output is proportional to capital. By
the same token, any level of output will also be associated with the stock of capital.
This method is a way to measure what Tobin (1984) called the functional ef?ciency of
capital markets. The accelerator model is also closely associated with Samuelson’s
(1939) accelerator-multiplicator model of business cycles. Our method is similar to
Wurgler (2000) and Desai and Eklund (2008) though modi?ed to be consistent with
investment theory. Given our data (accounting data), this is preferable over other
methods, such as data envelopment analysis.
The accelerator model with a desired level of capital denoted K
*
t
is determined by
the output Y
t
:
K
*
t
¼ kY
t
ð1Þ
In equation (1), k, is the capital coef?cient. Assuming desired level of capital is equal to
actual capital, denoted K
t
, changes in desired stock of capital are proportional to net
investments, I
t
and ðK
t
2K
t21
Þ. Net investments I
t
can be denoted as:
I
t
¼ K
t
2K
t21
¼ lðY
t
2Y
t21
Þ ð2Þ
Pro-market
reforms
125
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Given the formulation of net investments in equation (2), these are proportional to
change in output over time and an accelerator l. Since we assumed desired capital
equals actual capital, then l ¼ k. However, this assumption is not normally ful?lled.
The following equation is obtained by dividing both sides of the equation with
K
t21
:
I
t
K
t21
¼ l
DY
t
K
t21
ð3Þ
Since K
t
¼ kY
t21
we can substitute K
t21
with kY
t21
in equation (4), giving the
following:
I
t
K
t21
¼ l
* DY
t
Y
t21
ð4Þ
Now l
*
represents l=k, or elasticity of capital with respect to output (re?ected by
sales). The normalization allows us to make empirical estimations of equation (4).
By assuming that K
*
t
¼ K
t
, over time we will get l ¼ k, resulting in l
*
¼ 1. If the
adjustment is incomplete and partial, then K
*
t
– K
t
and elasticity of capital with respect
to output, l
*
, will be , 1. This means l
*
re?ects the cost ?rms face in adjusting their
capital stock: costlier adjustment will be re?ected by lower elasticity, all else equal[6].
An alternative to using net investments is gross investments (GI), obtained by
adding replacement investments (depreciation of assets). Assuming proportionality to
the old capital stock, we can denote this as dK
t21
. GI are thus de?ned as: equation (2)
plus dK
t21
, GI
t
¼ dK
t21
þlDY
t
. Mutatis mutandis, the corresponding equation for
GI is GI
t
=K
t21
¼ d þl
*
DY
t
=Y
t21
. In empirical applications, this means the only
difference between net and GI will be captured by the intercept.
We estimate the following:
I
i;t
K
i;t21
¼ a þ h
i
þ u
t
þl
*
DS
i;t
S
i;t21
þ 1
i;t
ð5Þ
In equation (5), elasticity of capital with respect to sales is represented by l
*
, where I
represents investments made by the ?rmi in time period t. Capital stock in period t 2 1
is denoted as Kand S denotes sales in period t. To control for unobserved heterogeneity,
we include a ?xed effect h
j
where j represents industry or ?rm effects. We include u
t
to
control for business cycle ?xed year effects.
Using panel data with ?xed effects, we add interaction variables (dummies) to
capture different types of ?rm owners. We also use time dummies for time-speci?c
effects. Using interaction terms, the empirical equation will have following functional
form:
I
i;t
K
i;t21
¼ a þ h
i
þ u
t
þb
1
DS
i;t
S
i;t21
þ b
2
DS
i;t
S
i;t21
£ X
1;i;t
þ · · ·
þb
n
DS
i;t
S
i;t21
£ X
n21;i;t
þ1
i;t
ð6Þ
where the X’s denote explanatory variables. Thus, the elasticity of capital, l*,
corresponds to the marginal effect in equation (6):
l
*
¼ b
1
þ b
2
£ X
1
þ · · · þ b
n
£ X
n21
ð7Þ
JFEP
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We use interaction explanatory variables with sales growth in order to determine how
these variables affect elasticity of capital.
Data
We collect ?rm-level accounting data on investments, capital stock and sales from the
Prowess India database[7]. Total assets are used as a measure of capital stock, K
t
, and
sales are used as our measure of output. We use net investments (DK
t
), measured as
change in total assets[8]. De?nitions and sources of variables are listed in Table I.
We exclude the ?nancial sector since investments made by ?nancial ?rms are of a
different nature than in other sectors. All accounting ?gures have been adjusted for
in?ation with consumer price index (CPI) from IMF.
Ownership data available from the Prowess database is subdivided into broad
categories. There are two main ownership categories: promoters and non-promoters.
Promoters are de?nedbyIndianlegislation[9] andis basicallysynonymous to controlling
owner. Apromoter is legallyde?ned as a personwho is in control of the company andhas
the right to appoint directors or control management. Non-promoters refers to a dispersed
ownership stake, i.e. no controlling owner. Apart from distinguishing between Indian
Component De?nition
Sales Sum of industrial sales and income from non-?nancial
services
a
Capital Total assets
a
In?ation Measured with average CPI
b
Capital intensity Capital divided by sales
Ownership categories
Promoters holding (%) The dominant/controlling owner. Indian law de?nes
promoters as the person in control of the company. All
ownership categories are measured as percentage share of
equity capital
Indian promoters (%) Domestic controlling owners
a
Foreign promoters (%) Foreign controlling owner
a
Persons acting in concert (%) –
promoters
Persons/owners acting in concert as controlling owners
a
Non-promoters holding (%) Non-promoters are the shares held by non controlling
owners, i.e. dispersed ownership
a
Institutions – non-promoters (%) Institutional non-promoters are the sum of the shares held by
mutual funds, banks and foreign institutional investors
a
Mutual funds/UTI (%) – non-
promoters
Includes non-promoting mutual funds
a
Banks, FI’s, insurance companies (%)
– non-promoters
Includes non-promoting banks, ?nancial institutions and
insurance companies
a
Foreign institutional
investors (%) – non-promoters
Includes non-promoting foreign institutional investors
a
Non-institutions (%) – non-promoters Includes non-promoter non-institutional investors
a
Corporate bodies (%) – non-promoters Includes non-promoter corporate bodies
a
Individuals (%) – non-promoters Includes non-promoting individual investors
a
Other non-institutions (%) –
non-promoters
Non-promoters not elsewhere de?ned
a
Sources:
a
Prowess;
b
IMF, World Economic Outlook Database 2007
Table I.
Variables
Pro-market
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promoters and foreign promoters, it is not possible to further subdivide the promoter
category[10]. Thus, the following are included within the promoter category and cannot
be extricated: individual/family promoters, state and government promoters, corporate
promoters and institutional promoters. It is possible, however, to subdivide
non-promoters into subcategories. This is meaningful as non-promoters represent the
mirror image of promoters (promoters being a measure of ownership concentration).
Few ?rms in India are characterized by dispersed ownership. In 2006, only 126 of
2,050 ?rms had dispersed ownership, where no owner controlled 20 percent or more of
the shares. Table II presents data on promoter and non-promoter holdings.
95 percent of the ?rms had an Indian promoter (controlling owner) and 86 percent
had an Indian promoter owning more than 20 percent of shares[11]. Some 10 percent of
?rms had some degree of state or government ownership, and about 4 percent had a
state or government promoter. On average, Indian promoters own about 46 percent of
shares, whereas average ownership of foreign promoters is about 28 percent. However,
the overall average promoter holding is just above 50 percent. Total promoter holding
is larger than Indian and foreign promoters separately because, in a number of cases,
foreign and domestic promoters act in concert and are thus jointly de?ned as
promoters. Since it is not possible to distinguish various promoter categories, the data
are problematic and do not add up precisely.
In contrast to data on promoters, data on various categories of non-promoters are
available. Non-promoters are divided into institutional non-promoters and
non-institutional promoters. The institutional non-promoter group is further split into:
.
mutual funds;
.
banks, ?nancial institutions and insurance companies; and
.
foreign institutional investors.
It is not possible to identify the extent to which banks, ?nancial institutions and
insurance companies are state or governmental controlled. Summary statistics of the
ownership data and correlations are presented in Appendices 1 and 2.
We construct an unbalanced panel of more than 7,000 companies for 1991-2006.
Since we use growth in sales and capital stock from previous periods, we have data
Average ownership per year
Type of owner 2002 2003 2004 2005 2006
Promoters holding (%) 50.62 51.80 51.23 50.32 50.40
Indian promoters (%) 39.37 40.29 39.28 38.71 43.87
Foreign promoters (%) 5.93 6.08 5.86 5.95 6.53
Persons acting in concert (%) – promoters 5.32 5.44 6.09 5.66 0
Non-promoters holding (%) 49.38 48.16 48.77 49.59 49.23
Institutions (%) – non-promoters 6.85 6.44 6.22 6.85 7.14
Mutual funds/UTI (%) – non-promoters 1.81 1.54 1.45 1.63 1.74
Banks, FI’s, insurance companies (%) – non-promoters 4.34 3.77 3.37 2.94 2.80
Foreign institutional investors (%) – non-promoters 0.70 1.14 1.38 2.27 2.65
Non-institutions (%) – non-promoters 42.53 41.71 42.57 42.79 41.82
Corporate bodies (%) – non-promoters 9.99 10.15 10.92 11.22 9.03
Individuals (%) – non-promoters 31.42 30.31 30.28 30.11 30.41
Other non-institutions (%) – non-promoters 1.12 1.24 1.36 1.45 2.38
Table II.
Mean share of
ownership per type of
owner and per year
JFEP
3,2
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A
t
2
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:
4
0
2
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a
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a
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y
2
0
1
6
(
P
T
)
for 15 years. In total, the panel includes 48,623 observations. Unfortunately, the data do
not follow a normal distribution: the skewness and kurtosis test for normality clearly
indicates non-normality, mainly due to extreme outliers. A less skewed distribution is
achieved by removing the 2.5th and 97.5th percentiles of our dependent and independent
variables. After this, 6,457 companies and 45,443 observations remain. Ownership data
are only available from 2001 until 2006, corresponding to 12,423 observations.
We use industry effects in all regressions to control for unobserved heterogeneity
across ?rms. This is theoretically appropriate because much unobserved heterogeneity
across ?rms can be attributed to industry differences and regulatory differences across
industries. However, the empirical results are unaffected by the choice between ?xed
industry and ?xed ?rm effects. To further control for ?rm speci?c effects, we include
controls for ?rm size and capital intensity. Both size and capital intensity can be
expected to impact the adjustment of the capital stock, and thus, elasticity of the
capital stock. In particular, we expect capital intensity to be important for the speed
of adjustment. Consequently, we also include our measure of capital intensity
as an interaction term with sales growth. Our results are robust with inclusion or
omission of these controls[12].
In addition to the sales accelerator, overall elasticity of capital has been estimated
using a pro?t accelerator and value-added accelerator. The value-added accelerator was
insigni?cant. The pro?t accelerator was signi?cant but economically negligible.
A possible explanation is the quality of accounting data, rendering pro?ts and value
added incomparable across ?rms. Using ?xed effects estimation, the overall R
2
for the
pro?t accelerator was less than 1 percent. An interpretation is relative reliability of sales
(fairly consistent reporting across ?rms) versus likely variation (e.g. underreporting) in
reporting of pro?ts and value added. The measure of investment used solves some of
these problems by including depreciation and all items in the income statement and
balance sheet that can be counted as investment.
Results
We estimate overall elasticity of capital for India as approximately 0.20, lower than
could be expected. This suggests it takes at least ?ve years for the average ?rmto adjust
to changes in demand and supply. From investment theory, one would expect elasticity
of capital to equal one. Lower elasticity indicates ?rms only partially adjusting capital
stock to changes in output, implying that investments are not expanded to the point
where marginal return on capital equals its opportunity cost.
Table III reports results for ownership categories and contains regular ?xed effects
results.
The estimates show signi?cant, minor, positive effects on allocation of capital for
promotors and negative effects from non-promotors. However, breaking down
ownership into sub-levels shows only Indian promoters having a positive signi?cant
effect on allocation of capital. The picture is mixed for non-promotors. All effects on
allocation of capital are signi?cantly different from zero, but only institutions overall,
mutual funds and foreign institutions have a positive effect. The controls for size and
capital intensity all show high signi?cance levels and expected signs.
Industry dummies were interacted with DS
t
/S
t21
and the coef?cients constrained to
sumto zero, suchthat industryspeci?c elasticities are obtained. This means anysigni?cant
effect of ownership on elasticity of capital cuts across industries. As a robustness check,
Pro-market
reforms
129
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)
Table III.
Ownership and allocation
of capital
JFEP
3,2
130
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Table III.
Pro-market
reforms
131
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d
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P
O
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D
I
C
H
E
R
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U
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2
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:
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a
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(
P
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)
we also estimate equation (7) with GI. The results are by andlarge robust, thus not reported
here. Additional robustness checks include multilevel mix effects models where we allow
industry elasticities to vary randomly over time. We ?nd no general trend towards
improved capital allocation over time, nor do we ?nd any improvement in industry
allocation. Industry speci?c elasticities are reported in Table IV.
Most industries report elasticities ranging from 15 to 25 percent, which is low
compared to what might be expected in developed countries. One possible explanation
is that we only look at large incumbent ?rms, whereas most of the growth dynamics
may actually be originating in small-young ?rms. Another explanation for small
industry differences may be geographical differences in regulatory reforms.
Aghion et al. (2006) examines labor policy and ?nd that dismantling the License Raj
proceeded at different speeds across regions in India.
The fact that it is not possible to break down foreign and Indian promoters into
further subcategories is a limitation. It is reasonable to expect different promoters may
have different objectives, resulting in the agency problem; this would be a useful
avenue for further research. This may account for the ?nding that promoters have no
robust signi?cant effect on allocation of capital.
Looking at non-promoters, institutional investors appear to improve allocation of
capital. Breaking down institutional investors into subcategories reveals an interesting
pattern. Mutual funds and foreign institutional investors appear to improve capital
allocation. Banks seem to have a negative impact, but it is not robust. According to the
results, institutional investors increase elasticity of capital by about 2 percentage
points. The positive effect of foreign institutional investors is consistent with the idea
that foreign investment may push openness and accountability. We ?nd few
signi?cant results when studying elasticities of separate industries.
One reason for the low levels of signi?cance is the lack of observations for some
industries (as low as the single digits for some sectors). But perhaps more importantly,
this demonstrates that elasticity of capital is not dependent on industry effects to the
same extent that it is affected by ownership, supporting the importance of ownership
effects on ?rm performance.
Table V contains the elasticity of capital and yearly deviations from the overall
elasticity of capital.
Few of the estimates are signi?cantly different from zero. Those estimates different
from zero display expected signs of the yearly elasticity based on general economic
trends, compared to the overall elasticity of capital during the period. For example, the
elasticity of capital increases during 2005-2006 and decreases during 2001. Overall, the
changes over time are fairly small and seem to follow a general economic trend.
Conclusion
We examined investment behavior and ef?ciency of capital allocation, using the
accelerator principle to derive a measure of capital allocation (elasticity of capital with
respect to output). This reveals how effectively ?rms and industries respond to
changes in the desired capital stock. At one level, this also re?ects investment decisions
possibly driven by reforms.
We ?nd promoters (controlling owners) have no signi?cant impact on allocation of
capital. The reason for this result may be our inability to distinguish various types of
controlling owners, e.g. government promoters and private individuals or families.
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Industry
Industry
code
a
Elasticity t-value
No.
observations
Overall elasticity of capital (all industry weighted
average) 0.225
*
4.55 45,443
1. Agriculture, hunting and related service activities 1 20.069 21.28 469
2. Forestry, logging and related services 2 1.958 0.84 2
3. Mining of coal, lignite and extraction of peat 10 0.079 0.70 140
4. Extraction of crude petroleum, natural gas and
incidental activities 11 20.030 20.48 131
5. Mining of uranium and thorium 12 0.264 0.49 11
6. Mining of metal ores 13 20.026 20.40 154
7. Other mining and quarrying 14 20.138
*
22.52 463
8. Manufacturing of food and beverages 15 20.090
* *
21.80 4,060
9. Manufacture of tobacco products 16 0.139 1.52 114
10. Manufacturing of textiles 17 20.053 21.06 3,574
11. Manufacture of wearing, dressing and dyeing of fur 18 20.008 20.15 423
12. Tanning and dressing of leather, saddler, etc. 19 20.060 21.03 305
13. Manufacture of wood, cork, straw and plating
material 20 20.074 21.03 165
14. Manufacture of paper and paper products 21 20.082 21.55 1,057
15. Publish and printing 22 0.077 1.20 293
16. Manufacture of coke, re?ned petroleum and nuclear
fuel 23 20.006 20.11 385
17. Manufacture of chemicals and chemical products 24 20.040 20.81 7,549
18. Manufacture of rubber and plastic products 25 20.044 20.87 2,266
19. Manufacture of non-metallic mineral products 26 20.129
*
22.50 1,631
20. Manufacture of basic metals 27 20.019 20.38 3,027
21. Manufacture of fabricated metal, except machinery
and equipment 28 20.018 20.35 897
22. Manufacture of machinery and equipment NEC 29 20.030 20.59 2,568
23. Manufacturing of of?ce, accounting and computing
machinery 30 0.037 0.65 254
24. Manufacturing of electrical machinery and
apparatus NEC 31 20.007 20.13 1,387
25. Manufacturing of radio, television and
communication apparatus 32 20.047 20.89 901
26. Manufacturing of medical, precision and optical
instruments, clocks and watches 33 0.009 0.17 379
27. Manufacture of motor vehicles, trailers and semi-
trailers 34 0.061 1.19 2,052
28. Manufacture of other transport equipment 35 20.070 21.20 330
29. Manufacture of furniture; manufacturing NEC 36 20.022 20.40 491
30. Electricity, gas, steam and hot water supply 40 20.104
* *
21.88 443
31. Construction 45 20.039 20.76 1,304
32. Sale, maintenance and repair of motor vehicles and
motorcycles 50 20.632 21.14 6
33. Wholesale trade and commission trade except
motor vehicles 51 20.059 21.17 3,176
34. Retail trade and repair of personal and household
goods 52 0.056 0.78 57
35. Hotels and restaurants 55 20.133
*
22.47 793
(continued)
Table IV.
Industry speci?c
elasticities
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a
Elasticity t-value
No.
observations
36. Land transport; transport via pipelines 60 0.108
*
1.70 263
37. Water transport 61 20.020 20.32 233
38. Air transport 62 0.107 1.02 75
39. Supporting and auxiliary transport activities 63 20.063 21.01 189
40. Post and telecommunication 64 20.016 20.29 246
41. Real estate activities 70 20.031 20.49 150
42. Renting of machinery and equipment without
operator 71 0.139
* *
1.82 48
43. Computer and related activities 72 0.026 0.51 1,460
44. Research and development 73 20.172 21.33 9
45. Other business activities 74 20.082 21.43 255
46. Education 80 20.366
*
22.62 19
47. Health and social work 85 20.076 21.22 229
48. Activities of membership organizations NEC 91 20.062 20.60 21
49. Recreational, cultural and sporting activities 92 20.034 20.63 334
50. Undifferentiated service-producing activities 97 20.104 21.28 40
51. Diversi?ed 98 20.006 20.11 614
Notes: Signi?cance at:
*
5 and
* *
10 percent levels;
a
industry codes follow the national industrial
classi?cation 2004; industry elasticities estimated with industry and year ?xed effect; to obtain the
industry-speci?c elasticities, DS
t
/S
t21
is interacted with industry dummies and constrained to sum to
zero; NEC, not elsewhere classi?ed Table IV.
DSt/St 2 1 0.182
*
(58.84)
1992 0.010 (0.48)
1993 0.006 (0.37)
1994 0.039
*
(2.97)
1995 0.034
*
(3.04)
1996 20.015 (21.61)
1997 20.030
*
(22.99)
1998 20.025
* *
(2.46)
1999 20.013 (21.29)
2000 20.009 (20.99)
2001 20.016
* * *
(21.80)
2002 20.014 (21.51)
2003 20.018
* *
(21.97)
2004 0.013 (1.48)
2005 0.020
* *
(2.28)
2006 0.020
* *
(2.09)
Constant 0.004 (1.13)
R
2
0.22
Adjusted R
2
0.22
F-value 164.7
No. observations 45,443
Notes: Signi?cance at:
*
1,
* *
5 and
* * *
10 percent levels; includes ?xed industry and time effects (not
reported); year dummies interacted with growth in sales; t-values are within parentheses
Table V.
Elasticity of capital and
yearly deviations from
overall elasticity of
capital
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With respect to non-promoter holdings (dispersed ownership), we observe signi?cant
effects of ownership. Institutional investors signi?cantly improve capital allocation.
We observe an interesting pattern in subcategories of institutional owners: mutual
funds and foreign institutional investors improve allocation of capital whereas banks
have no effect or a negative effect. We also ?nd signi?cant variation in capital
allocation across industries, and ownership effects cut across industries.
The overall ?nding is that despite economic reforms, the ef?ciency of capital
allocation remains fairly slow. This indicates signi?cant lag between introduction of
reforms and ?rm responses, and is not entirely surprising given institutional stickiness.
Still, improvements in stock and equity markets, and strong and consistent development
of commercial banks (Aziz et al., 2006) reasonably imply greater ef?ciency. However,
we ?nd overall elasticity of capital is about 26 percent, implying that when sales increase
10 percent, capital stock on average increases by 2.6 percent.
We therefore conclude that while pro-market reforms in India stimulated ef?ciency to
some extent, improvements in capital allocation may come from further deregulation.
Our ?nding that mutual funds and foreign institutional investors signi?cantly improve
allocation of capital provides useful focus for policy makers. Our work contributes to
knowledge on the ef?cient allocation of resources, and in doing so, identi?es several
extensions for research. One important question concerns effects of speci?c institutional
investors. For example, why do banks have a negative or absent effect? This is
important not only because it is surprising, but because many countries actively target
banking reform to create ef?ciencies. Another question is the relatively low capital
allocation in our estimation, versus what has been found for rapidly developing peers,
notably China. Further research can build on Hsieh and Klenow (2007) to better
understand resource allocation in important sectors such as manufacturing. Another
promising direction for future research is to study the institutional lag of reforms across
contents. This can yield implications for practice by helping to differentiate ineffective
policies from those that simply require time to be effective.
Notes
1. See OECD (2007); this estimate is for registered ?rms and likely underestimated due to the
existence of a large unof?cial sector.
2. The original post-independence Industrial Policy Resolution of 1948 emphasized
consistently increasing production. In 1956, a new resolution identi?ed rapid economic
growth as the path to a socialist society, assigning primary responsibility to central
government. Multiple Industrial Policy Statements (1973 and 1977) demonstrated a shift in
treatment of the private sector. In 1980, a new Industrial Policy Statement emphasized
competition and technology in domestic industries in order to encourage exports and foreign
investment.
3. See Bhagwati and Desai (1970) for historic perspective.
4. Similarly, short of privatization, publicly owned companies can be controlled by a
government investment agency rather than ministries subsidizing companies (OECD, 2007).
5. For more on separation of ownership from policy making (OECD, 2007).
6. Often in this type of model, a partial adjustment model is used to allow for lag structure in
the adjustment process. A higher order lag structure simply means higher adjustment costs.
Since we are interested in adjustment cost, we do not investigate lag structure.
Pro-market
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7. The database is provided by the Centre for Monitoring the Indian Economy Pvt. Ltd; usual
accounting caveats apply.
8. As a robustness test we also used gross investments. By and large, the estimates are robust
so we do not report results for gross investments. We measure GI: I
t
¼Profitaftertax2
dividendsþdepreciationþDEquityþDDebt þR&DþAdvertisingand Marketingexpenses:
9. The term promoter is de?ned in regulation 2(h) Securities and Exchange Board of India
(substantial acquisitions of shares and takeovers) regulation 1997.
10. Promoters also include a subcategory for persons acting in concert. However, this category is
not examined further in this paper.
11. A total of 20 percent ownership is enough to have control over a ?rm, consistent with the
corporate governance literature which treats levels below 50 percent suf?cient to maintain
control (Morck et al., 2005).
12. Note that other studies do not use these controls (Wurgler, 2000).
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(The Appendices follow overleaf.)
About the authors
Sameeksha Desai is an Assistant Professor in the School of Public and Environmental Affairs
and Associate Director of the Institute for Development Strategies at Indiana University.
Johan Eklund is an Assistant Professor in Financial Economics at Jo¨nko¨ping International
Business School and a Research Fellow at the Ratio Institute. Johan Eklund is the corresponding
author and can be contacted at: [email protected]
Andreas Ho¨gberg is a PhD Candidate in Economics at Jo¨nko¨ping International Business
School.
Pro-market
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137
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Appendix 1
T
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Table AI.
Summary statistics,
ownership 2002-2006
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B
a
n
k
s
,
F
I
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s
,
i
n
s
u
r
a
n
c
e
F
o
r
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i
g
n
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n
s
t
i
t
u
t
i
o
n
a
l
i
n
v
e
s
t
o
r
s
N
o
n
-
i
n
s
t
i
t
u
t
i
o
n
s
C
o
r
p
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r
a
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e
b
o
d
i
e
s
S
a
l
e
1
T
o
t
a
l
a
s
s
e
t
s
0
.
7
1
*
1
G
r
o
w
t
h
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n
s
a
l
e
s
(
D
S
t
/
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t
2
1
)
0
.
0
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0
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1
I
n
v
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s
t
m
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(
I
t
/
K
t
2
1
)
0
.
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1
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0
.
4
0
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1
P
r
o
m
o
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r
s
h
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l
d
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g
0
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5
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1
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.
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7
*
1
I
n
d
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a
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p
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0
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1
F
o
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2
0
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0
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0
1
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2
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0
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2
8
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2
0
.
4
3
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1
N
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n
-
p
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m
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r
s
h
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l
d
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2
0
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2
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2
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1
2
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7
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2
0
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6
0
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2
0
.
2
8
*
1
I
n
s
t
i
t
u
t
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o
n
s
–
n
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n
-
p
r
o
m
o
t
e
r
0
.
1
5
*
0
.
1
8
*
0
.
0
3
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0
.
0
5
*
2
0
.
1
9
*
2
0
.
1
6
*
0
.
0
3
*
0
.
1
9
*
1
M
u
t
u
a
l
f
u
n
d
s
/
U
T
I
n
o
n
-
p
r
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m
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t
e
r
s
0
.
0
7
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0
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0
8
*
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.
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3
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0
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0
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2
0
.
1
1
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2
0
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1
1
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0
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0
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.
1
1
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0
.
6
3
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1
B
a
n
k
s
,
F
I
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s
,
i
n
s
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r
a
n
c
e
c
o
m
p
a
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s
n
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-
p
r
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m
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t
e
r
s
0
.
0
7
*
0
.
0
8
2
0
.
0
6
*
2
0
.
1
1
*
2
0
.
1
6
*
2
0
.
1
3
*
2
0
.
0
0
0
.
1
6
*
0
.
7
3
*
0
.
2
4
*
1
F
o
r
e
i
g
n
i
n
s
t
i
t
u
t
i
o
n
a
l
i
n
v
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s
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s
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-
p
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s
0
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7
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2
1
0
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1
1
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2
1
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0
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1
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0
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0
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1
0
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6
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2
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0
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0
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1
N
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-
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n
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t
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t
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t
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-
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s
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*
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0
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1
4
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0
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0
3
2
0
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1
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2
0
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8
6
*
2
0
.
5
0
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2
0
.
2
9
*
0
.
8
7
*
2
0
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3
2
*
2
0
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2
2
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2
0
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2
3
*
2
0
.
2
0
*
1
C
o
r
p
o
r
a
t
e
b
o
d
i
e
s
–
n
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n
-
p
r
o
m
o
t
e
r
s
2
0
.
0
5
*
2
0
.
0
6
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0
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.
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1
2
0
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4
8
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2
0
.
2
8
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2
0
.
1
5
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0
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4
8
*
2
0
.
1
1
*
2
0
.
0
8
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2
0
.
0
8
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2
0
.
0
6
*
0
.
5
2
*
1
I
n
d
i
v
i
d
u
a
l
s
n
o
n
-
p
r
o
m
o
t
e
r
s
2
0
.
1
2
*
2
0
.
1
5
*
2
0
.
0
3
2
0
.
1
5
*
2
0
,
6
5
*
2
0
.
3
7
*
2
0
.
2
3
*
0
.
6
5
*
2
0
.
3
4
*
2
0
.
2
2
*
2
0
.
2
3
*
2
0
.
2
4
*
0
.
7
9
*
2
0
.
0
3
*
N
o
t
e
:
S
i
g
n
i
?
c
a
n
t
a
t
:
*
5
p
e
r
c
e
n
t
l
e
v
e
l
Table AII.
Correlations
Pro-market
reforms
139
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
4
0
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
doc_138966540.pdf