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Do industrial policy reforms reduceentry barriers? Evidence from Indianmanufacturing industriesM. Suresh Babu aa Department of Humanities , Indian Institute of TechnologyMadras , Chennai, IndiaPublished online: 11 Dec 2008.

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Journal of Economic Policy ReformVol. 11, No. 4, December 2008, 289–300

ISSN 1748-7870 print/ISSN 1748-7889 online© 2008 Taylor & FrancisDOI: 10.1080/17487870802602690http://www.informaworld.com

Do industrial policy reforms reduce entry barriers? Evidence from Indian manufacturing industries

M. Suresh Babu*

Department of Humanities, Indian Institute of Technology Madras, Chennai, IndiaTaylor and FrancisGPRE_A_360437.sgm10.1080/17487870802602690Journal of Policy Reform1384-1289 (print)/1477-2736 (online)Original Article2008Taylor & Francis1140000002008SureshBabusbab77@hotmail.com

Institutional regulations by licensing and capacity restrictions are often considered asbarriers to competition in Indian industry. As most of these regulations have given wayto market mechanisms, an increase in the number of entrants is to be expected. This paperattempts to measure the extent of barriers to entry in Indian manufacturing industries byquantifying the height of barriers for 1991/92 and, a decade after the onset of reforms,2001/02. We find that, contrary to expectations, the height of overall barriers increased.This suggests that dismantling of commands and controls intended to ease entry seemsto have paved the way for the erection and strengthening of market barriers to entry.

Keywords: economic reforms; entry barriers; height of barriers; market barriers

JEL classification: L1, L11, L13

I Introduction

One of the major components of the economic reforms package in India has been the dereg-ulation of and removal of licenses from the manufacturing sector. The rationale providedhas been the argument for inducing competition, with the expectation of an enhancement inefficiency and competitiveness of the manufacturing sector. It is also argued that the lack ofcompetition due to entry restrictions also paved the way for the existence of market power,resulting in welfare loss. Institutional regulations by way of licensing and capacity restric-tions are often considered as barriers to competition in Indian industry. As most of these regu-lations have given way to market signals, an increase in the number of entrants and alterationsin the conditions of entry, mainly the barriers to entry, are expected. This paper attempts tomeasure the extent of barriers to entry in some selected Indian manufacturing industries byempirically quantifying the height of these barriers. The analysis is carried out for two timepoints in accordance with the launching of economic reforms to delineate the possible impactof changes in the policy regime. The paper is confined to some of the measurement issuesof entry barriers. The method followed, on the lines of Geroski (1991), can be described as“consilience of induction”, an attempt to weave together disparate results for different indus-tries, mainly due to the lack of unanimity regarding the measurement of entry and its barriers,as these are the outcome of a complex process of strategic interaction among firms.

II Entry barriers: an informal discussion

Entry is often considered as an “error correction mechanism” to keep markets in (or near)equilibrium and even the threat of entry is considered as an effective source of market

*Email: sureshbabum@iitm.ac.in

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discipline. Entry of new competitors is generally viewed to have beneficial effects. It isconsidered as a source of competitive discipline bidding prices down, thus eliminatingexcess profits. Entry also changes the structure of the market and can upset the traditionalpatterns of market conduct. Quite often new entrants de-throne dominant firms, introducenew technology and fresh approaches to product design and marketing, leading to morecompetitive prices. Viewed from this perspective, entry reduces x-inefficiency and stimu-lates innovation and technical progress (see Geroski 1991). However, evidence points tothe fact that, in reality, the impact of new entrants penetrating into the market seems to below,1 despite the large number of entrants. This points to a close relationship between entryand exit, which means there could be situations in which entry appears to be easy, but post-entry market penetration and survival seems to be difficult.

To further the discussion a precise definition of barriers is warranted. One of the well-known definitions is that of Bain (1956), who argues that a barrier to entry exists if the newentrant is unable to achieve the profit levels after entry that the incumbent enjoyed prior toits arrival and that the height of these barriers is measured as the level of profits that can besustained against entry in perpetuity. Alternatively, Stigler (1968) is of the view that abarrier to entry would exist if the new firm has to overcome more consumer resistance thandid the established firm and the height of an entry barrier would be the additional cost anentrant would have to bear in order to produce the same revenue as an established firm.While Stigler compares the entrant and incumbent post entry, Bain’s emphasis is on theconditions of entry that permit an established firm to raise prices above the minimumaverage cost of the potential entrants. What is termed a “normative definition” of the barri-ers to entry is provided by von Weizsacker (1980, p. 400), as a “cost of producing (at someor every rate of output) which must be borne by firms which seek to enter an industry butis not borne by firms already in the industry, and which implies a distortion in the use ofeconomic resource from the social point of view”. Demsetz (1982) further extends thisapproach, by supporting an efficient allocation of resources, and argues that in many caseswhat is called an entry barrier is an endogenous response to consumer preferences. Concen-trating solely on the advantages that accrue to an established firm with emphasis on the roleof history and how that affects relative profits, Gilbert (1989) opines that barriers exists if afirm earns rents as a consequence of incumbency. This approach has no relation to theconsequence of entry or exit for economic welfare. The above views on what forms an entrybarrier point to considerable controversy over its definition and how it could be measured.

A skim through the literature on the taxonomy of barriers shows that there is a widerange of factors that can serve as barriers to entry, although the various structural factors donot always necessarily give rise to barriers. However, much depends on the way that thebarriers have been measured in practice. Most of the empirical works have tried to followBain’s painstaking measurement exercise which in practice has often amounted to compar-ing actually observed entrants with incumbents, or has involved simple counter-factualconstructions based on observations of incumbents’ activities. This creates an upward biasin measuring barriers as there is the implicit or explicit use of incumbents’ current activitiesas the “best possible under circumstances”, which ignores the opportunity that entrants mayhave to do better than incumbents. Thus the issue boils down to the interpretation of theevidence. It is ubiquitous that the various structural conditions can give rise to barriers butone always runs the risk of overstating its importance. Apart from the measurementproblems, the extent to which structural factors are strategically exploited by the incumbentsto deter entry is also important (Gorecki 1976). Scale economies per se might not blockentry, unless they are accompanied by the threat of large price cuts attendant upon attemptedentry at the minimum efficient production scale. Similarly, in the case of advertising, the

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issue is the cost of advertising and the calculations based on the advertising response ofincumbents. Thus one ought to explore the incidence of various types of strategic entrybehaviour in evaluating the various structural determinants of entry.

II i Discussions in the Indian context

For many years firms trying to enter an industry had to clear the hurdle of getting permis-sion from the government in the form of licenses. These licensing requirements createdeffective entry barriers in many markets and assured the sheltered life of those firms thatmanaged to enter. However, after the abolition of licensing, except for a few industries, ithas become imperative for firms to formulate entry strategies based on more market-oriented considerations.

There have been a few studies on the barriers to entry in Indian manufacturing. Mani(1992) discusses the issue of barriers to entry in light of the industrial policy statement of1991. According to him, the dismantling of capacity restrictions in many industries intendedto reduce the height of barriers to entry might not work favourably as the earlier policy offixing minimum efficient scales of operation (MES) had erected capital barriers to entry.Siddharthan and Pandit (1992) examine the impact of the policy changes introduced in 1985on the structure, conduct and performance of the manufacturing sector. Using stepwisediscriminant analysis they scanned for the variables that acted as principle discriminants forthe period pre and post 1985. They found labour productivity, size of units, skill and importintensity, rate of entry, rate of investments, growth of output and borrowings as statisticallysignificant, indicating a positive impact of the liberalisation package. However, the studyfails to take into account the further doses of policy changes.

Emphasising more the welfare issues in the event of entry by foreign firms, Jensen andKrishna (1996) examine entry policy in an open economy. They demonstrate that allowingforeign firms in the industry can directly alter the direction of entry bias by shifting profitsaway from the home country. According to them, as the number of firms was kept low inIndia by licensing, liberalising entry was likely to be beneficial to begin with. However,citing the example of Australia which experimented with a liberal entry but restrictivetrade policy prior to the ‘80s, they sound a word of caution that the industry could experi-ence dissipation in profits and high prices due to large fixed costs and small productionruns. Using Centre for Monitoring Indian Economy (CMIE) data for 31 industries for theperiod of 1989–93, Saikia (1997) tries to explain the process of entry in Indian manufactur-ing. Specifying a model of entry on the lines of Orr (1974), he estimates entry as a functionof past industry profit rate, sunk costs measured by machinery intensity, product differenti-ation proxied by intensity of advertising, industry size, concentration, growth and risk. Hefinds that entry is positively associated with market size and growth and deterred in aconcentrated market. After adjusting for simultaneity problems, he finds profits to be oneof the significant determinants of entry. Four types of entry were surveyed in Sen (1997):(1) setting up of a new firm in the industry; (2) buying, i.e., purchasing an existing firm(through mergers, amalgamation or friendly take-over); (3) acquiring control throughhostile take-overs; and (4) entering via a joint venture route. The strategies were identifiedusing the framework of Tirole and Fudenberg (1991). However, he does not present anyempirical evidence from the Indian context.

The above studies, even though they have discussed the various entry strategies andbarriers, have omitted empirical quantification. The present study, for the first time in theIndian context, addresses this issue in light of the policy changes. I start with the specifica-tion of a model to capture the height of these barriers.

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III Measuring the height of barriers to entry

Firms use a variety of barriers to prevent competition to enhance and sustain their profits.These barriers are used individually or in combination, but in most cases derive strengthfrom interactive effects. To elaborate, even modest advertising can be effective in thepresence of a vigorous after-sales service. This is true for scale economies, as it helps toreap benefits from absolute cost advantages as well, and a combination of advertising andproduct differentiation proves to be more effective than focusing on product differentiationalone. The point to be stressed is that it is misleading to consider the effects of these vari-ous barriers separately, as there exist possibilities of synergies arising out of the jointeffect of all the types of barriers taken together. This prompts an examination of the over-all barriers.

Most of the econometric investigations of entry barriers have been indirect tests. Theyhave regressed profit rates, rather than entry, on those structural characteristics consideredto be barriers to entry. This specification does not permit reliable conclusions regardingthe effectiveness of those variables in deterring entry. There are theoretical reasons forquestioning the often-assumed strong positive relationship between entry barriers and thetrue profit rate. Additionally, of course, there is a gap between true and measured profits.In his pioneering work Orr (1974) put forth a model of entry, which draws parallels fromthe work of Bain and Sylos on limit pricing (Sylos-Labini 1962). According to Orr, theprice-cost margin determined by the limit price implies a certain rate of return on sales,which is directly related to the rate of return on capital for the firms of a particular indus-try where the best practice technology requires a specific capital output ratio. An entrylimit price thus implies an entry limit profit rate on capital and in the absence of barriers,entry will take place until the marginal rates of return on capital across industries becomeequal. Thus entry continues until the industry profit rate reaches a point where theentrant’s expected rate of return on capital is equal to the opportunity cost of capital. Entrythus will be a positive function of the difference between observed and entry limitingprofit rates

Employing Orr’s method provides a reasonably good estimate of the height of the over-all barriers to entry, but it suffers from inaccuracies introduced by the use of variables thatproxy barriers. Thus it can only be considered as a first step in analysing the extent of barri-ers. As entry is discrete and involves a time lag to respond to incentives, which differacross industries, a more suitable method will be to examine a panel of firms across indus-try groups. This also allows for the possibility of inter-industry variations in erecting barri-ers. With these considerations we examine the height of entry barriers at the individualindustry level using a panel of firms for two time points, first at the initial years of theeconomic reforms2 and then a decade after the launching of the reforms. As the analysis isbased on panel data, a more appropriate methodology is that of Geroski (1991), who modi-fies the basic empirical model of Orr. The present investigation has followed this modelclosely.

Consider entry being attracted by excess profits which would occur whenever profitsdiffer from their long-run levels. With the above hypothesis, observations of actual entryrates and current profits can be used to make inferences about the unobservable – the long-run profits. Entry Ejt in an industry j at time t is hypothesised to occur whenever expectedpost-entry profits πe

jt exceed the level of profits protected in the long run by entry barriersbj, that is,

E ( – b )ijte jt

j jt= +γ π µ ( )1

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The level of profits that can be sustained without attracting entry is bj and these “limit prof-its” capture the height of barriers to entry. In other words, γπejt shows entry that would haveoccurred if there were no entry barriers and Ejt is actual entry. The difference between thison average is equal to γbj, which depends on the height of barriers.

With the risk of being repetitive, we discuss the micro economic foundations ofEquation (1) more explicitly as provided in Geroski (1991). Suppose that a firm i choosesoutput xi and that industry output is x ≡ Σxi. Assume that the output is homogenous and thedemand is p = p(x) and the marginal costs are constant at a level of ci per unit. The currentperiod profits net of fixed cost are

The choice of xi by firm i in period t is affected by two constraints. First, rivals are likelyto respond to any attempt by i to expand and this response is likely to occur over time. Usingconjectural variations we suppose that firm i expects an initial aggregate response, dxI/ dxit

≡ θ0 by all rivals and a subsequent response dxt+1/dxit ≡ θ1 to any output change that it makesin period t. As dx / dxi = (1 + Σdxj/ dxi), j ≠ i then θ0 = θ1 = 0 describes a situation in whichprice is expected to remain constant when xi changes. Larger θ0 and θ1 indicate that therivals are less accommodating and hence a larger price decline consequent on increasing xi.Second, if xit ≠ xit–1, the choice of xi in t may involve firm i in substantial short-run adjust-ment costs. These adjustment costs Ajt = A(xit,xit–1) are assumed to be proportional to theincrease in market share implied by the choice of xit given xit–1. That is, if Sit ≡ xit/xt thenmarginal costs are assumed to be dAit/dxit ≡ dt(Sit – Sit–1). Also assume that dt/pt ≡ δ whichis constant over time.

With these assumptions, choice in t by firm i has future effect and a rational decision-maker will maximise the expected present discount value of profits.

Where p is the discount factor, Et(.) denotes the expectation at time t of the quantity inparentheses. To simplify the notation, subscript i is suppressed.

The sequence of xit which maximises Equation (3) (see Sargent 1979 for details)satisfies

Rearranging and simplifying Equation (4) gives

where Et(St+1) ≡ Se(t+1), λ ≡ ρPt/P(t+1) and is assumed to be constant and η is the elasticity of

demand (η < 0). Collecting terms and suppressing τ, we obtain

πi i ix [P(X) – c ]= ( )2

V E ( (x [ (x ) – C]) – A )t t t t t+0

= + +=∑ρ ρτ

τ τ ττ

α

( )3

P C x P' (x + ) – (S )

+ E [ (X ) – (S )] = 0t+ it t 0 t it it 1

t 1 t+ +1 1 t+1 it+1 it

τ τ

τ τ

τ θ δρ θ δ

– –

' – ( )–+ +

+ +

S

X P Sit 4

m ( ) – (S )

+ ( ) – (S )= 0

t+0

t+ 1

et+ +1

1 et+ +1

τ τ τ τ

τ τ τ

θη

δ

λθη

λδ

+ + +

+

S S

S S

t t

t

–

– ( )

–

5

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294 M.S. Babu

where mt ≡ (pt − c)/pt, i’s price - cost margin,

With restrictions on the parameters the solution to Equation (6) is

where η1 and η2 are such that 0 < η1<1/γ1<η2.Defining

we can write Equation (7) as

If θ1 = δ = 0, then the current choice of xit has no effect on πi(t+1) and Equation (5)simplifies to

which is the Cowling-Waterson model of market structure and price-cost margins.For an entrant in its year of entry St–1 = 0, then Equation (9) simplifies to

Et = entrant’s market penetration.From equation (11) it is clear that entry will occur if the appropriately discounted present

value of the stream of expected post-entry margins is positive and that entrants will respondmore quickly to given S*t. But this is an incomplete model of entry due to two problems.Firstly, entrants may have to pay a fixed entry cost (F) to enter, and secondly the level ofcost ci that the entrant i incurs in producing output xi is not observable. The observablevariable is the price-cost margin of the incumbents. When entry costs exist, then marginalcost does not equal average cost. Thus if (p–ai)/p is the price-average cost margin of theincumbents, then that of entrants is

γ γ γ0 1 1 2 1 0m S S Ste

t t t+ + + =+ – ( )6

γ δγ λ θ η ρδ γ

γ θ η δ λδ γ

0–1

1 1 0

2 0 0

= ,

= [( / ) – ] ,

= [( / ) – + ]

S mte

t= +

∞

∑η η γη

ττ

τ1 t –1 1 0

2=0

S + (1

) ( )7

S mtet

* ( )≡ +

∞

∑γ ηη η

ττ

τ

0 1

1 2=01 –(

1) 8

∆S St = (1 – )(S – )1*

t t –1η ( )9

m St =–

( )θη

0t 10

Et t= (1 – )S1*η ( )11

p a a aE– –( )1 1

p p+ 12

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We can write Equation (10) in terms of observable as

where πe is the discounted expected present value of π.Equation (1) is the basic empirical model of entry. Equations (2) to (12) provide inter-

pretations of γ, πe and b. To translate equation (1) into a regression equation to measure theheight of entry barriers, we need to express it in terms of observables, but neither πe

jt nor bj

is directly observable. One is expectational variable and the other unobserved outcomes.Following Orr (1974) we assume that entrants use lagged actual profits πjt-1 to proxyexpected post-entry profits and to model bj as being determined by a series of observablefeatures of current market structure.

where we have assumed that only one observable measure of entry barriers Xj is used. NowEquation (1) could be transformed into a regression model

Ignoring purely random transitory factors, Ejt=0 in the long run and using this condition tosolve Equation (15) for the level of limit profits πj*j,

If the entrants expect no higher profits than π*j, then they will not be able to cover theirentry costs, so will not enjoy a positive return post entry.

One conceptual problem which makes Equations (15) a little tentative is that the use ofobserved profits prior to entry πjt–1 to predict expected post-entry profits πe

jt presumes thatentrants have naive expectations. πe

jt, the level of profit expected by the entrant post entry,is not observable prior to entry. However, an entrant who forms rational expectations willmake use of all the information available to it at the time it makes the decisions. This infor-mation comes in two forms: (1) observed data reflecting past market outcomes and (2) aprior knowledge of how market processes operate. The two types of information comple-ment each other because knowledge of market operations enables the entrant to establish acausal link between the different observables in its information set. So we combine the twotypes of information in a simple econometric model which enables the entrant to predictprofits.

With the observed data on profits πjt–1 and other variables Zj we can model the interac-tion between entry and profitability by expressing each as a distributed lag function of theother plus exogenous variables. Solving the model by eliminating the entry variables yieldsan auto regression in profits

Writing (p – a ) / p, b ( a – a ) / p, (1 – )1 E 1 1π γ η≡ ≡ ≡

E ( – b )iteit i= γ π ( )13

b Xj j= +β β0 141 ( )

jt 0 1 jt –1 2 j ij

0 0 1 2 1

E = + + X +

where = , = , =

α α π α µ

α γβ α γ α γβ ( )15

j* 0 1 j

1

Xπ

α αα

= +

( )16

jt jt –1 jt jtZπ λ π ε= (L) + +Φ ( )17

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296 M.S. Babu

where λ(L) is a polynomial in the lag operator L. The assumption of rational expecta-tions implies that expectations are unbiased and will differ from realised values onlyrandomly.

We can use the predictions from Equation (17) in place of unobservable latent variableπe

jt if entrants’ expectations are rational. Doing this ensures that the information availableto entrants in t-1 will be used to make predictions of πjt and this in turn implies that Ejt willbe a regression error with classical properties. We assume that entrants make their decisionsrationally, using the predicted value of πjt to proxy the latent variable πe

jt to model the signalthat attracts entry.3 Assuming that the height of barriers to entry ought to be fixed in theshort to medium run in most of the industries, and that they take specific value in eachindustry, we can measure the height of barriers to entry as

where the fixed effects ßj are objects of estimation along with ß1 and Xj is an observabledeterminant of barriers. Substituting Equation (18) in Equation (1) generates an equationlike (15), the difference being that α0 takes a different value for each industry. Theamended model becomes an equation with fixed effects and can only be estimated usingpanel data.

We propose estimation of Equation (15) using a rational expectations estimator for πejt.

As the model includes fixed effect to capture unobserved entry barriers we work with twoyears of data. Two separate panels are estimated to compare barriers over time. The firstpanel uses data for 1991 and 1992 and the second one for 2001 and 2002. The observablevariables are industry size and industry growth. All observables are assumed exogenous.These decisions leave us with an entry equation

The first step in the estimation of Equation (19) is to generate proxy values for πejt. The

reduced form estimates of Equation (17) used to generate the proxy values are given below.4

The first set of estimates corresponds to the panel for 1991 and 1992 and the second set ofestimates for 2001 and 2002. EXP denotes export intensity and t statistics are denoted inparentheses. The high explanatory power of the models is due to the inclusion of thelagged profits as explanatory variables. This points to the fact that current profits areaffected to a great extent by the past profits, while export intensity does not seem to affectthe observed current profits. Another notable feature is that there exist significant fixed

b = ß + ß Xj j 1 j ( )18

jtd d

jte

0d

jt–1

1d

jt–1 jd

jtd

E = + SIZE

+ GROW + f +

γ π α

α µ ( )19

π π π π

π π π π

t

2

t

= – 0.31 – 0.12 – 0.002 – 0.04 + 0.01 – 0.002

(–3.21) (–2.34) (–1.03) (–2.84) (2.11) (–1.24)

R = 0.92

= – 0.28 – 0.14 – 0.003 – 0.02 + 0.01 – 0.001

(–3.37) (–3.11) (–.96) (–2.41) (2.02)

t t t t t t

t t t t t t

SIZE GROW EXP

SIZE GROW EXP

– – – – – –

– – – – – –

1 2 3 1 1 1

1 2 3 1 1 1

(–0.87) (–0.87)

R = 0.892

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Journal of Economic Policy Reform 297

effects and that the between variations in the data dominate the within variations. This alsoimplies that the differences in profit margins between industries are larger than the marginswithin an industrial group.

Having generated the proxy values for expected profits, we estimate Equation (19) alongwith the fixed effects and results are reported in Table 1.

From the table it follows that a 10% rise in expected profits increases entry by around1.5% during 1991 and 1992 while the increase in entry falls below 1% for 2001 and 2002.It can also be observed that entry exhibits variations with excess profits and variations inindustry size and growth rate appears to have little effect on the barriers and thus on theentry flows. Using the estimated parameters and Equation (16) we solve for the level ofprofits which can be sustained without attracting entry, that is the limit profits, which are ameasure of the height of barriers to entry. As the fixed effects could not be reduced to asample-wide constant, there exist substantial inter-industry variations in the height ofbarriers. On average, the height of barriers in 1991 was around 24% and this increased toaround 30% by 2001. This means that firms could maintain prices above 24% of costs with-out attracting entry in 1991, and in 2001 they could maintain above 30%. This points to anincrease in the barriers over time.

Figure 1 makes this point more explicit. It can be noticed that in all the industries consid-ered, there has been an increase in the height of overall barriers. Barriers are the highest incapital-intensive industries like chemicals, machinery and metal products for both the timepoints considered. The synergy between barriers arising out of investments and scale couldbe a plausible explanation for the high barriers in these industries. In terms of the rate ofchange of barriers between 1991 and 2001, we find that on the whole there has been anincrease in barriers of about 25%. Chemicals witnessed the maximum of a 31% increasefollowed by non-metallic mineral products and food products. Metal products whichalready had high entry barriers in 1991 registered the lowest increase in 2001 followed bytextiles. Interestingly we find both barriers and the rate of entry increasing in the case offood products, an industry which has registered very high output growth as well. Thisconsiderable inter-industry variation in the height of barriers and its changes over timewarrants detailed explanations, which lies beyond the purview of this paper. However, it isinteresting to note that industries responded differently to the dismantling of the umbrellaof protection offered to them earlier. These differences might be due to the difference inmarket structure, inter-industry variations in growth and profitability, threat of entry byforeign firms and the extent of corporate restructuring taking place in the industry. This,however, demands detailed industry studies.Figure 1. Height of barriers by industry

Table 1. Regressions explaining entry.

Panel I Panel II

πejt 1.42

(3.11)0.81

(2.27)Sizet−1 0.02

(1.01)0.02

(0.78)GROWt−1 −0.13

(−1.36)−0.19

(−1.07)R2 0.46 0.41

Note: Panel I refers to 1991, 1992 and panel II refers to 2001, 2002. t statistics are given in parentheses. πejt

expected profits measured as the predicted value from πjt from equation (17). Sizet-1 is the lagged log of totaloutput and GROW t-1 is the lagged rate of growth of output. The dependent variable Ejt is the gross entry.

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IV To sum up

In this paper an analysis of the extent of barriers for new entrants in the manufacturing sectorhas been attempted. As the thrust of the industrial policy reforms has focused on the easingand removal of restrictions in the industrial sector, the analysis has been for the period sincethe onset of these changes in the policy realm. As a prelude to the analysis, the extent ofentry is traced. The number of new entrants measured as the gross entry declines over time,pointing to the existence of hindrances even after the removal of institutionalised barrierslike licenses. These hindrances are the non-institutionalised market barriers, the extent ofwhich has been captured by examining the height of these barriers.

Econometric estimation of the height of the barriers for 1991/92 and 2001/02 yields thatthe height of barriers has increased in 2001/02 in all the industries examined from a sampleof firms drawn from the CMIE. Ever since the doing away of the “license raj”,5 firms havebeen able to indulge in entry blocking strategies fuelled by the working of market forces. Thedilution and dismantling of commands and controls intended to ease entry have thus pavedthe way for the erection and strengthening of market barriers which have grown over time.

AcknowledgementsI thank Stephen Martin and David Audretsch for discussions and Pulapre Balakrishnan, K. Pushpan-gadan, K.L. Krishna and N.S. Sidharthan for their comments and suggestions. An earlier version waspresented at JEI2005, Bilbao, Spain, Centre for Development Studies, Trivandrum, India and IndianInstitute of Technology Madras, participants of which I thank for valuable suggestions. Errors, if any,are solely my responsibility.

Notes1. For a discussion of the market penetration of new entrants see Masson and Shaanan (1986), Yip

(1982), Hause and Du Reitz (1984).

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

Textiles Wood pdts. Chemicals Machinery Metals products

1991

2001

Food pdts. Non-metallicmineral pdts

Figure 1. Height of barriers by industry.

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2. A discussion of the various components of economic reforms in India and their possible reper-cussions on the industrial sector is avoided here as a plethora of studies already exists on theissue.

3. See Wallis (1980) and Wickens (1982) for the standard procedure to estimate rational expectationmodels and Pagan (1984, 1986) on the properties of two-stage estimators.

4. See Appendix for details on data.5. The earlier “command and control” regime in India is often referred to as the “license permit raj”.

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Appendix

1. Selection of the time points for analysis: The years 1991/92 and 2001/02 were selected consid-ering the timing of the liberalization policy. As is well known by now, 1991 forms a rupture ineconomic policy-making in India. The scope, coverage and extent of reforms introduced in1991 have been much more than the earlier four decades. 2001/02 was considered to be adecade after the significant reforms.

2. Sample of industries: Ideally one could have considered the entire two-digit disaggregation ofthe manufacturing sector. But paucity of data on entry, and certain industries having very fewentrants, limited the analysis to the seven industries listed in the table below. These seven two-digit industries of National Industrial Classification of 1987 accounted for nearly 53% of fixedcapital, 64% of employment, 62% of gross output and 64% of the net value added of the entiremanufacturing sector in 1991 and maintained more or less the same shares in 2001.

3. Measuring entry: The daunting task here is the issue of tracing entry. Entry can generally bemeasured in four different ways: (a) by counting the number of new firms, which, expressed asthe percentage of the existing stock of incumbents, gives the measure of incidence of entry; (b)by weighing each entrant by its size relative to the market, which gives a measure of marketpenetration when summed over all entrants; (c) net entry rates which are adjusted to exit; andfinally (d) by considering only those firms which survive the initial period. I consider the firstmeasure, that is, counting the number of new firms, for want of reliable information on marketpenetration, exit and survival. One way to infer the magnitude of entry at the aggregate levelin India is by examining the Letters of Intent (LOIs) and Industrial Entrepreneurs Memoran-dum (IEMs). These point to the potential entry rather than actual. In order to get a magnitudeof the actual entry we examine a sample of firms from the CMIE’s electronic database PROW-ESS. CMIE provides information on the background of firms in which both the year of incor-poration of the firm as well as the year of commencement of production is given for nearly7000 firms listed in the Bombay Stock Exchange. We consider the year of commencement ofproduction as the year of entry, as the firm actually enters the market from that year onwards.Thus from the sample of firms, by examining the year of commencement of production of eachfirm, we trace the number of entrants in each industrial group, which is provided in the tablebelow. For this reason the number of entrants might look small for a large economy like India.

Number of entrants according to the industrial groups considered.

Industrial group 1991/92 2001/02

Food products 42 50Non-metallic mineral products 25 15Textiles 23 21Wood products 9 9Chemicals 36 33Machinery 36 35Metal products 21 16Total 192 179

Source: CMIE, Prowess.

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