location and economic efficiency -...
TRANSCRIPT
CHAPTER-V
LOCATION AND ECONOMIC EFFICIENCY
5.1 Productivity in Classical Theory
5.2 Neo-Classical Approach to Productivity
5.3 Partial Productivity
5.3.1 Labour Factor Productivity
5.3.2 Capital Factor Productivity
5.4 Labour Factor Productivity in Sample Units
5.4.1 Labour Factor Productivity m Sample Industrial
Estates
5.4.2 Labour Factor Productivity in Estates m Different
Urban Category-wise
5.4.2.1 lVIetropolitan Industrial Estates
5.4.2.2 City Industrial Estates
5.4.2.3 Town/Rural Industrial Estates
209
5.5 Capital Factor Productivity in Sample Units
5.5.1 Capital Factor Productivity in Sample Industrial Estates
5.5.2 Capital Factor Productivity in Estates in Different Urban
Category-wise
5.5.2.1. Metropolitan Industrial Estates
5.5.2.2. City Industrial Estates
5.5.2.3. Town/Rural lndus,trial Estates
5.6 Rural Economy and Industrial Estates
5.7 Conclusions
210
CHAPTER-V
LOCATION AND ECONOMIC EFICIENCY
Sluggish output growth and low productive efficiency have
received much attention in the studies about the industrialization process in
India. During the decade of eighties the former issue received much
attention. For the successful monitoring of economic progress, whether
at the macro or micro level, it is essential to make scientific appraisal of
the trends in productivity - the efficiency with which resources are
converted into goods and services. The reasons are obvious. Productivity
indices have been accepted not only as a measure of perfonnance but
also as an important indicator of effective improvements in productive
efficiency of the economy as a whole. Their use in forecasting trends and
making policy decisions are widespread.
211
-5.1 Productivity in Classical Theory
In a classical framework, productivity was taken as an important,
often independent source of growth. It is viewed as a relation at a
macro level between commodity inputs and commodity outputs. Adam
Smith 70 in his "Wealth of Nations" refers to progressive, stationary and
declining states based on productivity. He refers to the sources of
productivity improvement such as:
i) improvements in machinery, facilitating and abridging
labour,
ii) altemations in employment in favour of productivity
employment, and
iii) increasing retums due to greater division oflabour.
Smith's contention was that all technical improvements involve a
saving of labour and technically, there is no limit to increase in labour
productivity, given capital expandability. Harrod, 77 in his model of
!:-'Towing economy, followed Adam Smith's reasoning. His opinion was
that due to technical proh'Tess which is labour augmenting in nature, there
will be continuous improvements in productivity even if population
hrrowth rate and net savings are zero. Diminishing retums to factors
was first discovered by West ( 1815), which was followed up by
Ricardo.n In his work, the fundamental proposition is that the ratio of
economic surplus to capital was a natural downward slope at
77
Adam Smith (1937), "An Enquiry into the Nature and Causes ofWealth of Nations", New York, Random House, p. 326
R.F Harrod ( 1940). "The Trade Cycle", as quoted in Collin Clart's 'Constitutions of Economic Progress', London, MacMillan and Co., pp. 470-71. David Ricardo ( 1971 ), "On the Principles of Political Economy and Taxation", ed. by R.M. Hertwell, Penguin Books, Hartmondsworth.
212
successive capital and labour accumulation levels. This falling tendency
can only be checked by technological improvements affecting the·
production of wage goods.
The lapse in Ricardo's analysis was that he did not visualise
diminishing retums to hold even if requirement of subsistence Is
withdrawn. Sir George Ramsa/') in his "Essays on the Distribution of
Wealth" in 1836 excluded wage goods from being a part of capital. He
drew attention to a reduction in capital net output ratio, describing it as a
powerful source of technical prof,rress. Thus, Ramsay was the originator
of the concept of capita] augmenting technical progress. John Staurt
Mi1180 in his famous "Principles of Political Economy" lists, among
causes of superior productivity, superior knowledge and skiJJ of labour
and of those who supervise labour improvements in arts consisting of
inventions and use of machinery; economies of scale; value of spread
of knowledge among common people. Thus, many of the concepts of
factors affecting "residual" can be traced to Mill. The productivity
factpr was considered as central to economics also in the writings of
Francois Quesnay, John Rae and Karl Marx.
The classical approach could hold good when classical conditions
prevailed, namely, labour and capital expanded simultaneously and land
was in elastic supply. There was no technical progress affecting the
quantities of factors and there were no changes in distribution. In the
modem world, capital expands much faster than labour and land IS
inelastic in supply. Here, one has to find out a \vay of grouping together
7')
~II
Sir George Ramsay ( 1836). "Distribution of Wealth" as quoted in P R. Brahmananda's 'Productivity in the Indian Economy- Rising Inputs for Falling Output', Himalay Publishing House, Bombay. J.S. Mill ( 1920), "Principles of Political Economy with some of their Applications to Social Philosophy", ed. by W.J. Ashtey, Longmans Green, London.
213
capital, land and labour to derive a of the aggregate factors. The
classical theory has no answer to this.
5.2 Neo-Classical Approach to Productivity
The marginalist m 1870s postulated that the three factors of
production -- capital, labour and land, will get precise reward rates
depending upon their substitution potential m methods, of production
and consumption pattems. This yielded a determinate theory of
distribution based on marginal productivity. Clark81 showed that given
the variability of factors at the margin, marginal productivity's of
labour, capital and land could be detennined at the aggregate level in the
economy, when any two factors are fixed. Walras82 demonstrated the
theory of general equilibrium of values of goods and services and of
factor reward rates. These developments seemed to provide a way
out for estimating an index number of quantity of each factor and
heralded scope for a method for a combined index of total factor
productivity.
The concept of total factor productivity, defined as the - ratio ,-
between real output and real factor inputs was introduced by Jan
Tinbergen83 in a notable article. This concept was further developed
independent of Tinbergen's work by Stigler. 84 In another branch of
study, the empirical approach of Paul Dc5uglasx5 in the fonn of the
famous Cobb-Douglas production function provided one explanation
~I
,.'"-"
X5
lB. Clark "Conditions of Economic Progress" as quoted in P.R. Brahmananda, op.cit. L Walras ( 1965), "Elements of Pure Economics"- translated by William Jaffe, Allen and Lenwin, London. Jan Tinbergen ( 1959), "On the Theory of Trend Movements", in LH. Klassen eL aL Selected Papers, North Holland_ CJ Stigler "Capital and Rates of Return in Manufacturing Industries" as quoted in P_R Brahmanana. Op_ cit. P_H. Douglas "Real Wages in United States", 1890-1926" as quoted in Clark's Op. cit
215
of invariant relative-factor-shares under conditions of disproportionate
growth of different factor input supplies.
Other important contributions to the measurement of total factor
productivity during the 1950's were made by Fabricant (1951 ),
Schmookler (1952), Abramovitz (1956), Kt;ndrick (1956) and
Solow( 1959). With the spurt of concem and interest m economic
growth since the 1950's, productivity analysis began to receive
considerable focus in growth analysis. The concept of productivity is
seen in tenns of either partial factor productivity or total factor
productivity. In this chapter, we shall discuss the economic perfonnance
of urban industrial estates in the National Capital Region and would
attempt a comparative analysis of those located in semi-urban and
mral locations.
216
5.3 Partial Productivity
It is a concept derived in tenns of a single input, other things
assumed to remain constant. This can be measured either as average or
marginal. 86 Most commonly used partial productivity measures are
labour and capital productivity.
5.3.1 Labour Factor Productivity The computation of labour
productivity is a complex procedure because of the difficulty in
isolating the contribution of labour to a given increase in output.
Generally, the output per unit of labour input is taken as a rough measure
of labour productivity. In the present study the labour productivity has
been calculated with the help of net value added. Net value added87 per
head is a reasonably good indicator of the productivity of labour.
However, net value added per man hour would have been a better
indicator. As it was difficult to get data on man hours worked, net value
added per head was taken to represent labour productivity.
Net Value Added Productivity of Labour=---------
Total Employment
In the denominator both productive and administrative employment
were included. 88 A change in labour productivity can be due to a
combined effect of a change in three factors. (i) The efficiency of factor
N6
X7
The average productivity ratio is output per unit of input. The reciprocal of this gives input requirement per unit of output. Net value Added= Total Sales Value- [Cost of all raw materials+power and fuel + Depreciation ]Here, depreciation is not available as the respondents were asked to give the present sales values of their Plants and Machinery. In small scale industry, there is no strict specifiction of jobs. Even administrative personnel do some manufacturing jobs.
217
use may have changed, (ii) the amount of capital employed per worker
may have changed, and finally (iii) the quality of labour may l1.ave
changed. Consequently, the observation of movements in these ratios
includes the effects of various types of changes.89 The productivity
of labour has been the subject of study for a long time, both because
of the relative ease of measuring it and because of its welfare aspects.
As the present study is based on cross sectional data, therefore the changes are observed across the individualal industrial estates as well as rural or urban based ndustrial estates.
718
5.3.2 Capital Factor Productivity : Capital productivity een
investigated by several researchers during the last four" decades or so.
It, in semblance to labour productivity, is output per unit of capital
(but in present study, we have taken net value added per unit of capital).
This reflects not only the use of capital efficiency but also the level of
embodied technology in use. In fact, it has been argued that it 1s
impossible to constmct an index of the quantity of capital which 1s
essentially a value concept that is affected by changes90 in the relative
factor prices, the interest and wage rates.
Net Value Added Capital Productivity =
Total Fixed Capital
where total fixed capital includes plant and machinery as well as land
and buildings. It does not include working capital. 91
In recent times, the productivity of various materials and fuels have
also been studied. All these are partial factor productivity's in the sense
that output is related to only one input at a time, without explicit
recob.rnition of the role played by other inputs in the production
process.
')}
Since this study is based on one point of time, i.e.I994, hence price effect is not applicable here.
Although. conceptually, working capital like its fixed counterpart is better considered at a point of time, the required data could not be collected. Data on finances for working capital purposes obtained from non-institutional agencies like friends and relatives, moneylenders, indigenous bankers, personal and private sources and information about self.finance, cash in hand, cash with banks, investment on securities. out-standing, credit and other liquidity, were the most delicate and ditlicult parts of the investigation. The questionnaires did provide for those data but the response was not satisfactory and the data seemed to be inconsistent after applying some cross-checks. These, therefore, could not be used.
"110
Change in partial productivity is able to measure only the saving
achieved in particular cost-elements as a result of changes in productive
efficiency and inter factor substitution. Total factor productivity growth
captures the effects of factor substitutability along with contribution
of its own input. To that extent, partial factor productivity growth might
mislead in understanding the productivity growth. perfonnance. An
appropriate measure to analyse changes in output at different levels of
economic activity, corresponding to the changes m the total inputs, is
the total factor productivity. Estimates of the concept are designed to
provide an indication of the changes in overall efficiency with which
resources are utilised m the production process. Total factor
productivity can be fathomed as the proportion of growth in real output
that cannot be accounted for changes in specifiable inputs. n This is
the reason, why the concept has been tenned as 'measures of our
ignorance'')~ and the residual. 'J-t
Even though, total factor productivity has been analysed as an
altemative to overcome the limitations of partial productivity analysis,
this is also subject to severe objections. In the analysis of total
factor productivity, the total output is the outco}lle of the play of a
weighted composition of all inputs used in the production process so
that one can differentiate the contribution of labour (wages), capital
(profit) and the residual representing technology. The measurement of
total
9.-=-
factor productivity is based on the neo-classical theory of
E.F. Sudit and N. Finger ( 1981 ), "Methodological Issues in Aggregate Productivity Analysis" in Ali Dagramace and Nabil, R. Adam (ed.) Aggregate and Indus- try Level Productivity Analvsis, Martinus NejhoffPublishing, Boston, USA l\1. Abramoitz (1956), "Resources and Output Trend in the United States Since 1870", American Economic Review, May 1956. E. D. Domar ( 1962). "On Total Productivity and All That", Journal of Political Economy, December 1962.
220
production function which rests on certain restrictive asstunptions
about the behaviour of production units and properties. of inputs and
output variables. Errors in estimating the parameters of production
function or errors in measunng variables can bias the estimates of total
factor productivity purely due to erroneous measurement of inputs and
outputs .')5
Another objection against the concept is that it is based on
extreme supply side considerations. In fact in a developing country like
India, the overall productive efficiency is influenced by several other
factors such as demand constraints, market imperfections, institutional
inadequacies, etc.
In the present study, I have worked out partial factor productivity
ratios for two important factors only, namely, labour and capital. Total
factor productivity has not been calculated due to many difficulties.
Moreover, the data supplied by the respondents (entrepreneurs)
during the field survey was not published either by Annual Survey
of Industry (ASI) or National Sample Survey (NSS). Therefore results
of the total factor productivity do not give nom1al total factor
productivity. Moreover, as my purpose was to compare the economic
perfom1ance of the rural and urban industrial estates, I have calculated
pm1ial productivity and not total factor productivity.
95 D.W. Jorgenson and Z. Griliches (1971), Divisia Index Numbers and Productivity Measurement", Review oflncome and Wealth, June 1971.
221
5.4 Labour Productivity in Sample Units
The labour productivity of all the sample llllits has been clubbed
first into six groups and later into three groups for easy
comprehension.The average labour productivity of the 300 sample
industrial tmits in the National Capital Region during 1994 was Rs.
10,755. There were only seventeen units (6 per cent) in which the
average labour productivity was below Rs. 3,000. Large munber of
industrial units fall in the group of Rs.3,000 to Rs. 11,000 ( 194 w1its
i.e. 65 per cent). The highest labour productivity is achieved by 89 units
(30 per cent) where it is more than Rs. 11,000 per worker (Table 5.1 &
5.2 and Figure 5.1 & 5.2).
5.4.1 Labour Factor Productivity in Sample Industrial Estates :
When we consider the trend of labour productivity across the
sample industrial estates of the National Capital Region, we find that
Okhla industrial estate has the highest labour productivity (Rs. 12,678)
which is even more than the average for the total sample size
(Rs.l 0, 755). The second and third place is occupied by the NO IDA and
Alwar industrial estates with Rs.11, 990 and Rs. 10,827 respectively
(Table 5.2 and Figure 5.3 ). These two industrial estates once a gam
exceed the average labour productivity of all sample industrial units.
The least average labour productivity was observed in case of Loni
industrial estate, i.e. Rs. 5, 942 w·hile that of Rozka-Meo industrial estate
was Rs. 8,3 77.
Five industrial units at Rohtak \vere in the group which had an
average labour productivity below Rs.3,000,50 industrial units in Okhla
were in the group where the average labour productivity was
222
J J .)
Table 5.1 Distribution of Industrial Units According to Average Labour Factor Productivity Industrial Estate-wise
INDUS TRIAL ESTA TES
Labour Okhla NO IDA Rohtak AI war Rozka Loni Productivity. Meo (in Rupees)
< 3000 4 2 5 I 1 4
3000-SOfHI 14 8 16 6 10 5
5000-7000 18 18 5 9 4 7
All Estates
17
59
61
7000-9000 9 9 5 10 4 6 43
9000-11000 9 10 5 4 2 I 31
> 11000 25 35 4 20 4 I 89
TOTAL 79 82 40 50 25 24 300
< 3000. 4 2 5 I 1 4 17
3(HI0-11 000 50 45 31 29 20 19 194
> 11000 25 35 4 20 4 1 89
TOTAL 79 82 40 50 25 24 300
Labour Factor Productivity (Number of Industry In Each Group)
35,---------------------------------------------------------------~----.
30 ...................................................................................................................................................... .
:
·:···-!p·········· /
/
............................................. ..,: ... ······r··················· ~ .._ 1S ...................•..•.•...•.... .,J •••• ,.
0 ~' ', ,. ....... I
~ • o .... ····-·····-··-···?·~---- ······; ....... , ..... ::.".~.!-~·-···· ···a·:::..-~·.:.::.·:.:;.·.:..-:1" ·····:::::.-................ : ····--"/~---······················· E ,.."" .•'' .. •· '•,,," ... ;.~-- .......... ~ ~ ," •!~~~---· .. ~-~::.~., .. ~~~·····-·-·lliii•IIIIA ...... ,.. II
5 ······~·.~-_-. .......................... ...,_,-* __________ ~!l..,r------~~--,·•·-.·~·~·~···················· -~.~~,...,." "1111111111111111111111"''""~:-.,..,. ........ :-••• ,.. ...
;I!~- • .,.,._=~~:~ •.•••••• 0
< 3000 3000-,!iOOO 5000-7000 7000-9000 9000-11000 > 11000 ~roductivity Group Size (in Rupees)
--- Okhlo ··-·· NoidCJ - o- - Alwor ....... Rozko Mao • • • Loni
Fig. 5.1
Table 5.2 Average Labour Factor Productivity :. Industrial Estate-wise
-INDUS TRIAL ESTA TES
Labour Okhla NO IDA Rohtak AI war Rozka Loni All l'roductivity Meo Estates (in Rupees)
< 3tHICI 22lJ3.32 2886.82 2414.36 2852.47 1253.33 2036.11 2309.94
3000-5000 4104.04 4161.94 4000.19 3714.71 3998.36 3997.48 4017.19
5000-7000 5783.90 5719.01 6114.46 5873.90 6264.36 5968.54 5857.81 r-
I \1\.o '10 7953.69 8110.67 7622.73 8014.63 7370.85 8013.74 7916.40
9000-11 otlt. 9971.36 10207.17 4037.03 9676.03 10256.83 9662.94 9939.52 -
> 111100 26778.89 19031.13 40620.24 17225.84 23283.63 14959.74 21917.07
TOTAL 12677.69 11989.86 8860.67 10827.46 8377.02 5942.36 10775.16
< 3000 2293.32 2886.82 2414.36 2852.47 1253.33 2036.11 2309.94
3000-11000 6457.80 . 6917.89 4931.42 6689.79 5751.89 6290.13 6406.55
> 11000 26778.89 19031.13 40620.24 17225.84 23283.63 14959.74 21917.07
TOTAL 12677.69 11989.86 8860.67 10827.46 8377.02 5942.36 10775.16
N N 0\
-(ll Ill Ill 0. ::l
0::
c .:::, _:::..
I ·:;: :n ::l
"tl 0 L
0...
5 0
..0 4[) c
_J
Fig. 5.2
Average Labour Factor Productivity (lndustrlol E:stote-wlse)
< lDDO 31100-6000 !OOD-o70DO 7~000 DIIOO-t tODD > tiOOO
Productivity Group Size (in Rupees)
llllllll!IIOkhlo !mm!Aiwor
~ NOOA ~ Rohtok ~ Rozka IAeo 1·:.:-:::.:] Lori
N N -...)
14
..-.. Ill m m 0. :::l
0:: c v
.::- 1 :~ 0 l :::l "0 0 '-
0..
'-:::l 0
..0 0
_J
Fig. 5.3
Average Labour Factor Productivitv (Industrial Estote-wlse) '
NOIOA Rohlalc Alwar Rozla IA1o0 Lori All £iotot• Sample Industrial E:states
between Rs. 3,000-11,000 and 35 industrial units 'in NOJDA were in the
t:.rroup where the average labour productivity was more .than Rs. II ,000
(Table 5.1 & 5.2 and Figure 5.4 & 5.5).
If we consider the average labour productivity of these three
groups in all the industrial estates then it is observed that in the first
group (below Rs.3,000), the highest average labour productivity was
recorded by NOJDA (Rs. 2,887) in two industrial units and the least was
in Rozka Meo (i.e. Rs.l,253) in one unit. The average labour productivity
of this b'Toup in all industrial estates was Rs.2,3 10.
In the second group ( Rs.3,000-11 ,000) while the average labour
productivity was Rs.6,407, the highest average labour productivity was
scored by NO IDA, having average labour productivity of Rs.6,918 in 45
industrial units and the least was in Rohtak having average labour
productivity of Rs. 4931 in 31 industrial units. In the last t,'TOup with
labour productivity of more than Rs. II ,000, the average was Rs.2, 197 for
89 industrial units. Here. Rohtak replaced NOJDA. Rohtak's average
labour productivity level was Rs.40,620 in four industrial units where as
it was Rs.19,031 in 35 industrial. units. in NOIDA. The least average
labour producti\ ity was observed in Loni (Rs. 14,960) industrial estate
which had only one unit in this group.
If industrial units inside and outside of Okhla industrial estate
are studied separately, it is observed that the outside Okhla, units are
having a higher average labour productivity than the inside Okhla units
(Appendix 5.1 and 5.2). In other words, the average labour
productivity (Rs.16, 709) in units outside Okhla IS more than the
samples' average labour productivity (Rs.l 0, 755). Units inside Okhla
hm·e an a\·erage labour productivity (Rs.10,074) less than that of the
overall average of the sample. The same position was observed in the
case of profitability discussed in the earlier chapter. The profitability of
228
Labour Factor Productivity and Industry (Industrial Estate-wise)
50~---------------------
4!:. Col
=E 40 ;:)
""6 3!\
:£: 30 Col ::J ,
25 £ ..... 20 0
L 15 CD ..0 E 10 ::J z
5
0
Fig. 5.4
L~ss than 3000 3000-11000 lAMe lhal'l 11000 l='roduclivily Group Size (in Rup88s)
llllli!IOkhla HAiwar
~ I'OOA ~ Rohtak rzzzJ Rozka Meo ~ Lori
4S -Ill CD 40 CD 0.. :I 3S ~
c 30 c.. .::=-~ 1? 2S ·s: E1
~ ~ 20 :I "0 e 0 1 s L..
0.. L.. 10 :I 0
..0 s c _. 0
Fig. 5.5
Averoge Lobour Foetor Productivity (Industrial Estate-wise)
Leu !h<:~n 3000 3000-11000 More !han 11000 Productivity Gro~ Size (in Rupees)
l!l!li!DOkhla emmAJwar
E'ZZ3 i'IOOA ~ Rohtok rzzz.l Rozka t.leo 1@ Lori
I .
the industrial units outside Okhla was higher than that of industrial units
falling inside Okhla industrial estate. Thus, here again it is proved that
the outside industrial units are more efficient than those which are
inside.
5.4.2 Labour Factor Productivity in Different Urban Category-
WISe:
In this section; we shalJ discuss the labour productivity with
respect to the industrial estates in metropolitan, city and town or rural
location. From Table 5.3 and Figure 5.6, it is observed that the
industrial estates in the Delhi metropolis have a larger nwnber of units in
the higher groups of average labour productivity. At the same time, Table
5.4 and Figure 5. 7 show that almost in aJJ the six groups the highest . score is attained by the Metropolitan industrial estates except in the
group size of Rs.5,000 - Rs. 7,000 in which Town industrial estates are
occupying the first position.
5.4.2.1 Metropolitan Industrial Estates : In this category, there were I 6 I
sample units (54 per cent) belonging to Okhla industrial estate and
NOlDA industrial estate. Here the average labour productivity was
observed to be Rs.J2,327. There were 60 industrial units (37 per cent)
in which the average labour productivity was more than Rs. 11,000 and
only 6 units (4 per cent) had an average labour productivity of less than
Rs.3,000. The maximum number of units (95 units i.e. 59 per cent) had
an average labour productivity in the group Rs.3,000 to Rs. 11,000.
In the first group, there were six units (4 per cent) where the average
labour productivity was of Rs.2,491 while in the group Rs.3,000 to Rs.
II ,000, there were 95 industrial units (59 per cent of 161) with average
labour productivity of Rs.6,676. The last group had 60 industrial units (37
211
the industrial units outside Okhla was higher than that of industrial tmits
falling inside Okhla industrial estate. rhus, here again 1t is proved that
the outside industrial units are more efficient than those which are
inside.
5.4.2 Labour Factor Productivity in Different Urban Category
wise:
In this section~ we shall discuss the labour productivity with
respect to the industrial estates in metropolitan, city and town or rural
location. From Table 5.3 and Figure 5.6, it is observed that the
industrial estates in the Delhi metropolis have a larger number of tmits in
the higher groups of average labour productivity. At the same time, Table
5.4 and Figure 5.7 show that almost in all the six groups the highest
score is attained by the Metropolitan industrial estates except in the
t,rroup size of Rs.5,000 - Rs. 7,000 in which Town industrial estates are
occupymg the first position.
5.4.2.1 Metropolitan Industrial ·Estates : In this category, there were 161
sample units (54 per cent) belonging to Okhla indust:ial estate and
NOIDA industnal estate. Here the average labour productivity was
observed to be Rs.12,327. There were 60 industrial units (3 7 per cent)
in which the average labour productivity was more than Rs. II ,000 and
only 6 units ( 4 per cent) had an average labour prodt!ctivity of less than
Rs.3,000. The maximum number of units (95 units i.e. 59 per cent) had
an average labour productivity in the group Rs.3,000 to Rs. 11,000.
In the first group, there were six units ( 4 per cent) where the average
labour productivity was of Rs.2_491 while in the group Rs.3,000 to Rs.
11,000, there were 95 industrial units (59 per cent of 161) with average
labour productivity of Rs.6,676. The last group had 60 industrialtmits (37
231
Table 5.3 Distribution of Industrial Units According to Average Labour Factor Productivity in Different Urban Size Category
Labour Metropolitan City Town All Productivity Estates Estates Estates Estates (in Rupees)
< 3000 6 6 5 17
3000-5000 22 22 15 59
5000-7000 36 14 11 61
7000-9000 IS 15 10 43
9000-11 000 (l) l) 3 31
> 11000 60 24 5 89
TOTAL 161 90 49 300
< 3000 6 6 5 17
3000-11 000 95 60 39 194
> 11000 60 24 5 89
TOTAL 161 90 49 300
10 w '...J
Labour Foetor Productivity end Industry (Urban Category-wise)
-Ill 3l > 0.. :::l
0::
c -:.=.,
. ~ -~ 7000~000 .·.·.·.·.· .. ·.· ·.·.·.·.· . (J1
0.. -li : ; ; :l ---------- : : 0 ,,,_,,, ·~ . ~ W3(VVVVVj
~ 3000~000 ~ttit%:tiitti1x££xhl < 3000 ~
:::J ., 0 ,_
0... 0 10 20 30 40
Number of Industrial Units so
~ ~etro E:stC>tes D City E:stC>tes e Town E:stC>tes
Fig 0 '50 6
110
Table 5.4 Average Labour Factor Productivity in Different Urban Size Categories.
Labour Metropolitan City Town All Productivity Estates Estates Estates Estates (in Rupees)
< 3000 2491.15 2487.38 1879.56 2309.94
3000-5000 4125.09 3922.33 3998.06 4017.19
5000-7000 5751.45 5959.82 6076.07 5857.81
71100-9000 8032.18 7884.00 7756.58 7916.40
9111111·11 000 10095.47 9543.25 10058.87 9939.52
> 1111110 22259.36 21124.91 21618.85 21917.07
TOTAL 12327.00 9953.33 7184.53 10775.16
< 3000 2491.15 2487.38 1879.56 2309.94
3000-11 000 6675.76 6231.30 6014.10 6406.55 -> 11000 22259.36 21124.91 21618.85 21917.07
TOTAL 12327.00 9953.33 7184.53 10775.16
Fig. 5.7
Average Labour Factor Productivity (Urban Cotegory-wlse)
<: 3000 3-DOO ~ 711011ooQDOO 8111111-11DOO > 11000
Productivity Gro~ Size (in R~ees)
I~ ~etro EstatEJB D City EstatBB m Town Estates
per cent) with an average labour productivity of Rs.l2,327 (Table 5.3 &
5.4 and Figure 5.8).
Thus, it may be observed that large town industrial estates had a
higher labour productivity. The average labour productivity of
Metropolitan industrial estate was Rs.l2,327 while in all the town
industrial estates the average labour productivity was Rs.l 0, 795.
5.4.2.2 City Industria! Estates : This category includes the Industrial
Development Colony (IDC) industrial estate of Rohtak district and
Matsya Industrial Area (MIA) industrial estate of Alwar district.
Altogether 90 industrial units were surveyed in this category. The overall
average labour productivity was Rs.9,953. Here too, as was found in
the case of metropolitan industrial estates, there were six industrial units
in the b'TOUp with average labour productivity of less than Rs.3,000 . Each
one, on an average, was having average labour productivity to the tune of
Rs.2,487. Two thirds of the industrial units were in the second h'TOup of
Rs.3,000 to 11,000 having on an average labour productivity of
Rs.6,231. The last h'Toup (more than Rs. II ,000) had 24 industrial
units where the average labour productivity was Rs.21, 125 which was the
highest. In this case, the average labour productivity is not only lower
than Metropolitan industrial estates but also lower than the average of
total sample units. Meaning, thereby, that the industrial estates in
the medium towns were less efficient (Rs.9,953) than those in larger
towns (Rs.12,327), (see Table 5.3 & 5.4 and Figure 5.9).
236
25
20
Average Labour Factor Productivity {Metropolitan Industrial Estates)
················· 40
30
.................. 20
o-b~bdmll~~===::)~o Ldu 11\i:in 3000 3000-11 000 ~61"d 11\i:in 11 000
Productivity Group Size (in Rupaes)
I~ Labour ProducHvity c::J N~..rnbar of I..Hta
Fig. 5.8
.... 6 I.. Q)
..0 E :J z
N w 00
25
Fig. 5.9
Average Labour Factor Productivity (City Industrial Estates)
0
Leu lh<:~n 3000 3000---11000 I.Aore lhcln 11000 Productivity Group Size (in Rupees)
I~ Labour Productivity 9 NI.IT1bar of Urita
0
Ill
~ ::;)
0 ·c ~ ::J
"tl ..&; ..... 0 L. lD
..,:,
10 E ::J z
0
5.4.2.3 Town/Rural Industrial Estates : This category includes the Loni
industrial estate in Ghaziabad district and Rozka Meo industrial estate
of Gurgaon district. A total of 49 industrial units were surveyed in
this category. There were five industrial units in each group with
average labour productivity of less than Rs.3,000 and more than Rs.
11,000. A large number of industrial units (i.e._ 39 w1its) were in the
group with an average labour productivity between Rs.3,000 to 11,000
(Table 5.3 & 5.4 and ·Figure 5.10). The maximwn number of industrial
units (i.e. 15 units) were in the group with average labour productivity
between Rs.3,000 to 5,000. These 15 units were having an average
labour productivity ofRs.3,998. The least number of industrial units were
in the h1foup with average labour productivity between Rs. 9,000-11 ,000,
having three industrial units with average labour productivity of
Rs.l 0,059. If we see the first group (below Rs.3,000), we find that there
were five units with average labour productivity of Rs.l ,880. In the
second group (Rs.3,000-1 0,000), 39 units had an average labour
prodictivity ofRs.6,014 and in the last .61fOllJJ (more than Rs. 11,000)
have an average labour productivity of Rs.21 ,619.
The differences observed in these three types of industrial
estates are significant. As one moves from metropolitan estates to city
estates and town or rural estates, it has been found that the average
labour productivity has continuously declined (Figure 5.11 ).
In the Metropolitan industrial estates, the average labour
productivity was Rs. 12,32 7, while in the City industrial estates and
Town/Rural industrial estates, it was Rs.9,953 and Rs.7,185 respectively.
The difference in per capita average labour productivity between
Metropolitan and City industrial estate is Rs.2,3 74 and bet\veen Ci~y and
Town/Rural industrial estate is Rs.2,768. It may, however, be observed
that the gap between Metropolitan industrial estates and Town/Rural
tv .1:;. 0
2!\
L.
;:5 !\ ..0 ., ....J
Fig. 5.10
Average Labour Factor Productivity (Town Industrial Estotes)
Leu l~<r~ 3000 3000---11000 Lbre """" 11000 Productivity Group Size (in Rupees)
\~Labour FlrocLctivity fZZ'Ll NL.ITlber of IJ-ita
10 L. CD
..0 E ::J z
1-J ~
All Etlalet
<'I G)
·;: T .:>w~ Etlaiet 0 0> G)
0 u c ., City E tlaiet
.J!l L.
:::)
Meir.:> Eilaiet
Fig. 5.11
Average Labour Factor Productivity (Urbot"' Category-wise)
1 077!i.1.S
-71~4.!53
-+ 0 2
~9!53.33
4 s 8 10 Labour F'rodLJCtivily (in Rupees)
(Thous.:l~ds)
12
1 2327 .ao
14
industrial estates ts more than double the difference between
Metropolitan and City industrial estates i.e. Rs. 5,142 ..
Thus, the industrial estates of the Metropolitan areas are more
efficient than those in either City or Town/Rural areas. The earlier
studies on efficiency of industrial estates in different cJass size of Towns
and in Rural areas have also arrived at the same concJusions. These are
given below.
Sanghvi96, in hi,s study, found that "value added by manufacture
labour and value added by manufacture-emolwnent ratios are better
indicators of labour productivity. On an average, one employee of the
sample units contributed value added to the extent of Rs.5, 151 during the
year 1972, while one rupee spent by sample units on wages and salaries
added Rs.2.25 to the output in tenns of value added by manufacture.
Productivity of labour estimated by these tvvo ratios was highest in the
case of the Udhna (Urban) industrial units and lowest in case of the
Umborgaon (Rural) industrial units. Though the perfonnance of labour
m) in tenns that of
of Umbergaon (Rural)
:trial units located at
ustrial units and those
re efficient than those
ge labour productivity
~1igher than in the rural
so, all the urban estates
rural estates.
)eveloping Economy",
242
5.5 Capital Factor Productivity
In this section we will discuss the economic efficiency of sample
units on the basis of capital productivity assessed in (a) each individual
industrial estate, and (b) in industrial estates grouped in terms of different
urban size categories i.e. Metropolitan, City and Town and Rural estates.
Capital productivity of all the sample units has been clubbed first into six
categories and later into three categories for easy comprehension.
We find a large number of units in the lower group of capital
productivity. In the lowest group of less than Rs.I lakh there were 171
units (57 per cent) and in the group ofRs.1 to 2 lakhs there were 78 units
(26 per cent). Together these two lowest groups contain 249 units (83 per
cent) of the total sample units (Table 5.5 and 5.6 and Figure 5.12 and
5.13 ). So far as industrial estates are concemed, in the two highest groups,
there is not a single unit from Alwar, Rozka Meo and Loni (Rs. 4 to 5
lakhs and more than Rs.5 lakhs). In the lowest two groups, the maximum
average capital productivity was attained by Rohtak and Rozka Meo (Rs.
0.8 lakh and Rs. 1.44 lakhs respectively). In the two highest groups
Okhla's capital productivity is Rs. 4.3 lakhs and NOIDA's Rs. 12.33
lakhs.
5.5.1 Capital Factor Productivity m Sample Industrial Estates :
It can be observed from Table 5.5 and 5.6 that the average capital
productivity in all the sample industrial units was Rs. 1.41 lakhs. More
than 50 per cent industrial units· ( 171 units) had an average capital
productivity of less than Rs. one lakh i.e. Rs. 0.6 lakh (Figure 5.14 and
5. 15 ). There were 121 industrial units ( 40 per cent ) in which the average
capital productivity was in the group of Rs. 1 to 5 lakhs i.e. each unit had
243
Table 5.5 Distribution of Industrial Units According to Average Capital Factor Productivity (Industrial Estates-wise)
IND UST TRIAL EST ATES
Capital < Okhla NO IDA Rohtak AI war Rozka Loni Productivity. Meo (Lakhs Rs.)
< 1 41 25 37 34 16 18
1-2 22 35 0 11 6 4
2-3 5 12 I 3 1 1
3-4 4 6 0 2 2 1
4-5 4 I 0 0 0 0
>5 3 3 2 0 0 0
TOTAL 79 82 40 50 25 24
< 1 41 25 37 34 16 18
1-5 35 54 I 16 9 6
>5 3 3 2 0 0 0
TOTAL 79 82 I
40 50 25 24
All Estates
171
78
23
15
5
8
300
171
121
8
300
lBO
180 ~ ·c: 140 :::l
l5 120 ·;:: iii 100 ::J "0 _.!;
BO ._ 0
'- 80 Q)
..Ll E 4.0 ::J
z 20
0
Fig. 5.12
< I
Capital Productivity and industry (lndustrlol Estate-wise)
I~ 2~ 3~ '~ F'roductivity Group Size (in Lokhs Rs.)
lrzza ~Ho !EmBAJwor
l7lll i'mA ~ Rohtok IZZZ.l Rozko ·Mao g;gza Lori
> 5
Table 5.6 Average Capital Productivity : Industrial Estates-wise
INDU STR IAL ESTA TES
Capital Okhla NO IDA Rohtak AI war Rozka Loni All P•·nductivity. Meo Estates (Lakhs Rs.)
< 1 0.61 0.74 0.80 0.63 0.63 0.65 0.60
1-2 1.36 1.37 0.00 1.37 1.44 1.32 1.37
2-3 2.41 2.42 2.2Y 2.43 2.98 2.29 2.43
3-4 3.53 3.23 0.00 3.46 3.34 3.46 3.37
4-5 4.30 4.23 0.00 0.00 0.00 0.00 4.25
>5 10.22 5.45 12.33 0.00 0.00 0.00 7.83
TOTAL 1.63 1.65 1.41 1.02 1.14 0.95 1.41
< I 0.61 0.74 0.80 0.63 0.63 0.65 0.60
1-5 2.10 1.86 2.29 1.83 2.03 1.84 1.93
>5 10.22 5.45 12.33 0.00 0.00 0.00 7.83
TOTAL 1.63 1.65 1.41 1.02 1.14 0.95 1.41
.-.. 30 IIi
0::
~ 25 ..Y. c ._J
6 20
~ 15 :~ 0 :J ~ 10 L.
0..
] 5 '(i c u
Fig. 5.13
< 1
Average Capital Factor Productivity (Industrial Estote-wlse)
1-2 2-3 3-4 4~
Productivity Group Size (in Lckhs !=Is.)
rz:z.2j NXlA ~ ~ohtak
rzzzJ ~ozka t.J.eo gm Lori
> 5
.._ 0 L. 20 ..,
..0
§ 10 z
Fig. 5.14
Capital Factor Productivity & Industry (Industrial t:state-wlse)
<1 1-!!i >S F'roductivity Group Size (in Lckhs Rs.)
1::::::1 Okhla
I!IIIBAiwar B i'OOA ~ Rohtak
IZZZJ Rozka l.1eo ~ Lori
-14 ...; ~
"' 12 L. .:X 0
10 _J
c: .:=,
~ 8
:?: s 0 :J
"0 0 4
d:: ] 2 ·o.. 0
(.) 0
Average Capital Factor Productivity (Industrial Estote-wlse)
' " ' " ' " .. ' " ' " ' ,, ' •• /I
' " ' ,, . . ' •••••••••••·•••••••••••••••••••···•·•••••••••••••••••••••·••••••••••••••••••••••••••••••••••· ,, II
::·::: · 1r:: -:-[~;:;
<1 1-!!i >!!i Productivity GroL.Jp Size (in Lakhs Rs.)
CJOkhiCl
UAiwClr
E.£.:1 NOOA ~ RohtClk
rzz.zJ RozkCl llleo 1@1 Lori
Fig. 5.15
an average capital productivity of Rs. 1 . 93 lakhs. The maximum average
capital productivity was attained by only six industrial units falling in the
group of more than Rs. 5 lakhs.
Among the different industrial estates, NOIDA industrial estate had
achieved the highest average capital productivity of Rs. 1.65 lakhs and the
least was attained by Loni industrial estate with an average capital
productivity ofRs. 0.95lakh (Table 5.6 and Figure 5.16). It inay however,
be recalled that labour productivity in Okhla industrial estate97 was the
highest but in tenns of capital productivity, NOIDA had a highest lead
over Okhla industrial estate.
In the first group of average capital productivity (i.e. below Rs.
lakh), Okhla (Gombined) had 41 industrial units with an average capital
productivity which was the lowest (i.e. Rs. 0.611akh) and Rohtak had 3 7
units which had the highest average capital productivity (i.e. Rs. 0.80
lakh).
In the second group (Rs. 1 to 5 lakhs) Rohtak had again the highest
average capital productivity of Rs. 2.29 lakhs in one unit. The lowest
average capital productivity of Rs.1.83 Jakhs was found in Alwar estate
with 16 units.
In the last group with a capital productivity of more than Rs. 5
lakhs, Rohtak once again had the highest average, with two units of the
value of Rs. 12.33 lakhs. The lowest average capital productivity was of
NO IDA with three units of the value of Rs.5.45 lakhs. Here we observe
that although Rohtak had the lead over all the estates in all the three ~-
groups of average capital productivity, its total average capital productivity
G.S. Bhati (1976),Industrial Estates- An Evaluation" University ofBombay, Bombay, p. I 93.
250
LB
...-.. 1.8 IIi ~
... 1.4 ..r::; .::.t
_'3u c ~1 ·;;; 'fl O.B
-e e o.a 0..
0 ~ 0.4
c <..:J 0.2
Fig. 5.16
Ow-ia
Average Capital Factor Productivity (Industrial Estate-wise)
1.85
NelDA Roltlalc Alwor Rozlm t.4a:> AI ulal•
Sampls Industrial Estates
was only Rs.1.4 f lakhs which is less than that in the NO IDA industrial
estate (Rs.l.65 lakhs).
It is pertinent to ask here why Rohtak has a lead in a11 the three
groups of average capital productivity. This is because Rohtak has 37
units (out of 40 units) in the lower group of average capital productivity,
while NOIDA has only 25 units (Out of 82 units). In other words in
Rohtak only three units .are in the two higher groups of average capital
productivity, while in NOIDA there are 57 units. Therefore, in spite of
Rohtak' s lead over NO IDA in all the three !:,TfOups, the overa11 position of
NOIDA is better.
Now if we take the case of Okhla separately i.e. Okhla Industrial
estate (outside) and Okhla industrial estate (inside) then we find that Okhla
(inside) has a better position than Okhla (outside) which is unlike the case
in average labour productivity. That is, the industrial units within the
Okhla estate have an average capital productivity of Rs. 1 .68 lakhs, while
that of outside units is Rs.l.55 lakhs, i.e., a differences of Rs. 0.13 lakhs.
(Appendix 5.4 ).
5.5.2 Capital Factor Productivity m Estates in Different Urban
Categories : Here we will analyse the average capital factor
productivity in tenns of Metropolitan, City and Town industrial estates.
Like in labour productivity there are a large number of units (249 i.e., 83
per cent) in the lowest two f,Tfoups (less than Rs. 1 lakh and 1 to 2 lakhs) of
capital productivity. In the two highest groups (Rs.4 to 5 lakhs and more
than Rs. 5 lakhs) of average capital productivity, there are only 4 per cent
units ( 13 units). Not a single unit of Town industrial estate has such a high
capital productivity. The highest average capital productivity is attained by
II Metro units and 2 City tmits (Table 5. 7 and 5.8 and Figure 5 .I7 and
5.18).
5.5.2.1 Metropolitan Industrial Estates: The Metropolitan industrial estates
which include the Okhla and NOIDA industrial estates has I6I industiial
units where the average capital productivity is Rs.I.64 lakhs. There are
41 per cent units ( 66 units) where the average capital productivity is less
than Rs.l lakh (i.e.0.66 lakh) and 51 per cent units (89 units) with an
average capital productivity of Rs.1.95 lakhs. Only 4 per cent tmits (6
units) have the highest average capital productivity of Rs. 7.83 lakhs in the
group of more than Rs.5 lakhs (Figure 5.19).
It may be observed here that while the total average productivity of
the sample's capital is Rs.1.41 lakhs, the average capital productivity in
Metropolitan industrial estate units (161 units) is Rs.1.64 lakhs. It means
that in the Metropolitan industrial estates, average capital productivity is
higher than the total sample's average capital productivity by Rs.23000.
Thus it could be easily conjectured that the average capital productivity in
Metropolitan industrial estates, must be greater than the other two types of
towns which we discuss below.
5.5.2.2 City Industrial Estates : Rohtak and Alwar City industrial estates
have 90 units. The total average capital productivity of this category is
Rs.1.19 lakhs. Here in 79 per cent industrial units (7 I units), the average
capital productivity is Rs.O. 71 lakh and in 19 per cent (17 units), it is
Rs.l.86 lakhs. Only hvo per cent industrial units have an average capital
productivity of Rs.l2.33 lakhs which is aJso the highest average capital
253
Table 5.7 Distribution of Industrial Units According to Average Capital Factor Productivity in Different Urban Size Categories
URBAN CATEGORY WISE
Capital Metropolitan City Town All t>roductivity Estates Estates Estates Estates (Lakhs Rs.)
< I 66 71 34 171 ..
1-2 57 11 10 78
2--' 17 4 2 23
J-4 10 2 3 15
4-5 5 0 0 5
>5 6 2 0 8
TOTAL 161 90 49 300
< I 66 71 34 171
1-5 89 17 15 121
>5 6 2 0 8
TOTAL 161 90 49 300
Note: Industrial units in numhcrs
BO
70
~ ·c: so =:l
c ·c so 1'i :J
"tl ~0 ..!; ..... 0 30 L (I)
.J:J 20 E
:J z 10
Fig. 5.17
<I
Capital Factor Productivity & Industry (Urban CoteQory-wlse)
1-2 2-<1 3-4 ~-5 > 5 F'roductivity Croup Size (in Lokhs 1=1s.)
9 ~atrD Estates ~ City Estates f-:.:-:.:-:·1 TDwn Estates
Table 5.8 Average Capital Factor Productivity in Different Urban Size Categories
URBAN CATEGORY WISE
Capital Metropolitan City Town All Productivity Estates Estates Estates Estates (Lakhs Rs.)
< I 0.66 0.71 0.64 0.60
1-2 1.36 1.37 1.39 1.37
2-3 2.42 2.40 2.64 2.43
3-4 3.35 3.46 3.38 3.37
4-5 4.29 0.00 0.00 4.29
> 5 7.83 12.33 0.00 7.83
TOTAL 1.64 1.19 1.04 1.41
< 1 0.66 0.71 0.64 0.60
1-5 l.lJ5 1.86 1.95 1.93
>5 7.83 12.33 0.00 7.83
TOTAL 1.64 1.19 1.04 1.41
' Average Capital Factor Productivity
(Urban Category-wise) ·
u -..; cr. 12 Ill
_c ..::1. c 10 _J
c c.
< 1 1-2 2-3 3-4 4~ > 5
F'roductivily Gro~ Siza (in Lckhs Rs.)
8 ~etro E:states E'Zl..il City E:states [Z] Town E:atates
Fig. 5.18
8 .-.. v) cc 7 (/)
..c: ~ 6 ...J
. .§. 5
~ ·:; 4
~ .g 3 0 ... c.. 2 :§ ·c. 1· <tl (.)
Fig. 5.19
Average Capital Factor Productivity (~etropolitan Industrial Estates)
<1 1·5 >5
Productivity Group Size (in Lakhs Rs.)
I~ C~itc) ProdJCtivit EJ ~mber of Unit5
90
ab
70
60
50
40
30
20
10
0
.l!3 ·c: ::J c;,; ·;:: -(/)
::I '0 .s -0 ... Q)
.0 E ::I 2
productivity. Here it is observed that the average capital productivity
(Rs.l.l9 lakhs )of all 90 units is less than that in the Metropolitan
industrial estate's (Rs.1.64 lakhs), (Figure 5.20}.
5.5.2.3 Town/Rural Industrial Estates : It includes Loni (24 units) and
Rozka Meo (25 units) which altogether consist of 79 industrial units. It
has an average capital productivity of Rs.l.04 lakhs (49 units). More than
50 per cent units (34 units) are having on an average capital productivity
of Rs.0.64 lakhs and rest of the 31 per cent units (15 units) of Rs.1.95
lakhs. There is not a single unit in this urban category which has an
average capital productivity of more than Rs.5 lakhs (Figure 5.21 ).
If we consider all three types of industrial units together then it is
found that the Metropolitan industrial estate has a lead not only over the
other two types of urban estates but also on the total sample's average
capital productivity. Metropolitan industrial estate, had a lead of Rs.0.23
lakh on the total sample units (300 units), in tenns of average capital
productivity. It also had a lead of Rs. 0.45 lakh and Rs.0.60 lakh over the.
City estate and Town/Rural estates respectively. The City estates, had a
lead of Rs.0.15 lakh over the Town/Rural industrial estates in tenns of
average capital productivity (Figure 5.22).
Here once again we obse1ve that the average capital productivity of
the metropolitan estate is h1Teater than that of City estate or Town/Rural
· estates.
14 ~
vi c:c V'l .c .;,:: ~ -l c::: :.::.
z:. ·:; u
::::l '0 0 .... 0...
IS 'E. ~
(.)
Fig. 5.20
Average Capital Factor Productivity (City Industrial Estates)
71 12.33
................
<1 1·5 >5
Productivty Group Size (in Lakhs Rs.)
I kZ] C~itc:J Prodx:tivit S3 ~mber of Lklih;
80
70 (J) -·c: :::l (il
E (J) ::::1
"C .E
30 -0 .... Q)
20 .a E ::::1
10 z
2
~ ·~ ::l 0.8 "0 0 ....
0..
ca ..... ·~ (.)
Fig. 5.21
Average Capital Factor Productivity (Town Industrial Estates)
··················'································
<1 1-5 >5
Productivity Group Size (in Lakhs Rs.)
I• Ctl)ita Prodx:tivit ~ ~mber of Units
IV :;]'\ IV
/
All Estates
Average Capital Factor Productivity (Urban Category-wise)
~ ~ ·~ TownEstates ~ 1il 0 c:: ell
-e :::J
City Estates--!
MetroEstates-1.64
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
Capital Productivity (in Lakhs Rs.)
Fig. 5.22
5.6 Rural Economy and Industrial Estates
One of the most important objectives of the industrial estates policy
is to help in the industrialization of economically backward and nrral areas
. Even before independence, mral development had been one of the planks
of material movement and the slogan .of industrialization was very popular
in the country. But the thinking had been more on the lines of developing
mral areas through cottage and tiny industries. With the development of
modem small scale industries, the demand for their extension to ntral areas
became strong and the scheme of industrial estate was considered to be the
most effective way of achieving this objective.
The economy of rural area is predominantly agricultural, where
agriculture is supporting and supported by industry. There are artisans and.
craftsmen , household and cottage industries and sometimes small and
medium size industries. They take their inputs from quarrying and fisheries
and generally sell the processed and semi-processed outputs to the local
market. They use mainly locally available materials, manpower, skills
talents, capital and other resources, produce goods and services to meet
local needs and demands and export surplus to outside regions. Next to
agriculture, therefore, industry can be considered as the most important
economic activity to be planned for rural development.
At the time of fonnation of the Second Five Year Plan, much
attention was given to the goal of rural industralisation through industrial
estates.
263
5.6.1 Philosophy of Rural Industrialisation : The philosophy of rural
industrialization through industrial estates has been that if would generate
employment at the local level, would use local resources and labour
intensive technology, would produce goods to satisfy changing local
demand, would ii1crease incomes at the village level, would serve as ·a
nucleus of industrial activity in the surrow1ding areas and their by stimulate
entrepreneurship among the local people and would be responsible for
social upliftment and ·economic development of rural India The rural
economy would , hence, become more diversified and strengthened .and
would be better able to absorb the ladles and the poor, thereby stemming
or reducing migration to the cities.
In addition to this industrial estates, where facilities such as
transport communication, power, watrer, sewerage and fire protection are
provided, would generate some secondary brrowth. Related industries may
spring up to take advantage of highway facilities or railway stations, or
newly laid utility lines or other new facilities introduced on the industrial
estate. Grovvth may also result from attempts to fill the gaps in facilities
offered by the industrial estate. In this sense an industrial estate serves as a
magnet for finns providing services. for industry; these may include
services relating to equipment, repair, wholesale and storage facilities. All
these will stimulate employment opportunities on the fringes.
In order to analyse the local impact of industrial estates we have
tested the following hypothesis in this study:
" Industrial estates generate employment opportunities for the local
population rather than attract migrant workers"
In the sample industrial estates, only 38 per cent workers are of
local origin (local here means that the workers employed belong to the
same district in which that industrial estate is located and stayed there for
more than 5 years) and the remaining 62 per cent have come from outside
(Table 5.9 and Figure 5.23). None of the industrial estate, the local
workers is more than 50 per cent, while all the industrial estates are
employing more than 50 per cent of their workers from outside. The lowest
percentage shares of workers of local origin are in ·okhla industrial estate
(33 per cent). This low share is, because a large section of the workers
consists of daily commuters.
The largest share of workers of local origin are found in Rozka Meo
and Loni rural industrial estates. They account for 4.7 per cent and 44 per
cent of the total workers respectively. Rohtak and NOIDA occupy the
second and· third place by employing 63 per cent and 61 per cent local
workers respectively.
If we see Table 5.10 and Figure 5.24 then we find that Mineral
industry employs more than 50 per cent workers of local origin (i.e. 51.42
per cent). The Packing and Cement industry has the highest percentage
share of workers of outsider origin (66.93 and 65.75) respectively).At the
sametime these two are also the smallest employers of workers of local
origin(33 .07 and 34.25 per cent respectively).
From Table 5.11 and Figure 5.25 it is clear that in the Metropolitan
industrial estate the percentage share of the local workers is the least and
that of Town/Rural industrial estates (36 per cent and 46 per cent
respectively) the highest. In case of non-local workers , the Metropolitan
industrial estates have the highest position with a share of 64 per cent. The
second place is attained, once again by Town/Rural industrial estates. City
industrial estates have the middle position in between these two extreme
urban categories (Metropolitan and Town estates).
Here the general trend that is· noticed is that as one moves away
from Delhi the percentage shares of local workers in the industrial estates
increases and that of non-local workers decreases. In other words, it can
be said that percentage shares of local workers in the metropolitan town is
Table 5.9 Place of Origin of Workers in the Sample Industrial Estates
GEOGRA PHI CAL LOCA TION
Industrial Local Outsider Total % of %of Total Estates (1) (2) (3) (1) (2)
Okhla 718 1448 2166 33.14 66.86 100
NO IDA 692 1008 1700 40.71 59.29 100
Rohtak 226 383 609 37.11 62.89 100
AI war 413 617 1030 40.09 59.91 100
Rozka Meo 277 315 592 46.79 53.21 100
Loni 197 243 440 44.77 55.23 100
All Estates 2523 4014 6537 38.60 61.40 100
..
1.1) ....
70 Uf
60 ............. ·.
~ 50 .... 0
3: 40 -0 Ol n:! 30 .... c: Ill ~ 20 Ill
Cl...
10
Place of Origin of Workers (Estafe-wise)
61 ........ 63 . 62
... ········~·························sfi··········· 53 ~
·······4· 4
41 ....... Jt
Okhla NOIDA Rohtak Alwar Rozka Mea Loni AU Estates
Sample Industrial Estates
I ~ Local D Outsider
Fig. 5.23
tv 0\ 00
Table 5.10 Place of Origin of Workers in Different Industrial Categories
GEOGRA PHI CAL LOCA I
Industrial Local Outsider Total % of Categories (1) (2) (3) (1)
Chemical 374 637 lOll 36.99
Electrical 220 WJ 579 38.00
<:arment I'JX 336 534 37.08
Mechanical 4~1 821 1312 37.42
Pat:king 42 85 127 33.07
Electroni<· 126 225 351 35.90
l'rinting 56 103 15~ 35.22
l'lastic 148 224 372 39.7&
Food 166 228 394 42.13
(:lass & Cer. Ill 199 310 35.81
Mineral 145 137 282 51.42
Textile 70 !OJ 171 40.94
Cement 125 240 365 34.25
M..tallurgy 140 213 353 39.66
Miscc. 92 125 217 42.40
All Industry 2504 4033 6537 38.31
Nok: < ·~r.=Ceramic Mi.<t:~.=Miscdkncou.<
TION
% of Total (2)
63.01 100
62.00 100
62.92 100
62.58 !00
66.93 !00
64.10 !00
64.78 100
60.22 100
57.87 !00
64.19 100
48.58 !00
59.06 100
65.75 !00
60.34 100
57.60 100
61.69 !00
70
55
(/) 50 ..... Q) ~ ..... 0
?:: ~5
-0 ~0
0)
"' .... c:: 45 Q) <'.) ..... Q)
0.. 40
35
Place of Origin of Workers (lndustr ial Category-wise)
~~ . ·······························;""·······"'~·~---~-····················*····················-,.l>o: .. :························
...... ._ ~ ....... ~ '- I ' I '-
.. - ················ . .... '.'....-,-~-::i./ \ .. f( ... . " .... ,<.;/~-,. • •
. .. .' .... . 1. ...... . ' . I I
.................................................................................. :tf········································· ' ' ' ' I \ ······················································ ........................... , ....... , ...................................... .
I ' I \ ~
. ........................................................... ,.~:..~\,:····-r ........... i\-J, ............• :::. ..... ':-., ..... . - / \1 ' I )I
.. -- ------- ' ' I \ ' .............................. :>: ......... _...~.:-.c ......................... Ji!i ..................... \."~---······················ 'w' -
CHE ELE GAR ~C PAC Elf Pill PL~ FOO OLC ~ rEX CEW ~r t.t> foiO
Industrial Categories
j-•-· Local •+-· Outsider
Fig. 5.24
Table 5.11 Place of Origin of Workers in· Industrial Estates in Different Urban Categories
GEOGRA PHI CAL LOCA TION
Unban Local Outsider Total % of %of Total . Categories* (t) (2) (3) (1) (2)
Metro. 1410 2456 3866 36.47 63.53 100
City 639 1000 1639 38.99 61.01 100
Town/Rural 474 558 1032 45.93 54.(>7 100
All 2523 4014 6537 38.60 61.40 100 Categories
Note: a. * Indicates Industrial Estates, a.Metro.=Metropolitan
N -...I
Fig. 5.25"
Place of Origin of Workers (Urban Calegory-wlse)
Metro Cly· Towrv'Rural All Categories
Urban Categories .
I ~ Local ~ Outsider
least, while in the Town/Rural industrial estates, the most . The opposite
position is observed in case of shares of workers employed from outside. It
means the Metropolitan industrial estates had the largest percentage shares
of non-local workers and the Town/Rural industrial estates had a
significant share of workers of local origin.
So far as workers level of skill is concerned, NIODA and Okhla
industrial estates had the largest share of skilled workers . It was 42.82 per
cent and 36.61 per cent at NOIDA and Okhla respectively. Rohtak had
largest share of skilled workers (23.97). Rohtak and Loni industrial estate
had employed more than 60 per cent unskilled workers (Table 5.12 and
Figure 5.26). One can , therefore, infer that Okhla and NOIDA have
capital intensive industry while Rohtak and Loni have labour intensive
industry.
Thus from the above evidence the third and last hypothesis ts
proved with the following qualifications:
The industrial estates in the Small Town/Rural areas generate more
employment opportunities for the local population than the Metropolitan
and City industrial estates. and work as a catalyst in checking emigration
of workers in the already densely populated Metropolitan and City
industrial estates.
272
Table 5.12 Distribution of Workers in Industrial Estates According to Level of Skill
Industrial Skid. Unskld. Admi. Total % of % of %of Total Estates (1) (2) (3) (1) (2) (3)
Okhla 793 991 382 2166 36.61 45.75 17.64. 100
NO IDA 728 713 259 1700 42.82 41.94 15.24 100 '
Rohtak 146 385 78 609 23.97 63.22 12.81 100
AI war 320 598 112 1030 31.06 58.06 10.88 100
Rozka Meo 178 319 95 592 30.07 53.89 16.05 100 -
Loni 128 268 44 440 29.09 60.91 10.00 100
All Estates 2293 3274 970 6537 35.08 50.08 14.84 100
Note: Skld.=Skilled, Unskld.=Unskilled, Admi.=Administrative
Fig. 5.26
Level of Skill (Estate-wise)
NOIDA Rohtak Atwr:. Mea Lori
Samle Industrial Estates
~~Skilled ~ Unskiled ~ Actninistrative
5. 7 Conclusions
(I) The efficiency of those industrial estates which are located near
the Metropolis is greater than that of the industrial estates, which are
located either near the City or Town/Rural areas. This was observed both
in tenns of labour productivity as well as capital productivity.
Some earlier studies have also come to the same conclusion.
Sanghvi9s in his study of Udlma estate near a large town concludes, 'lliat
when we make inter-estate comparison, the Udhna estate (Large Town)
excels all other estates. It had relatively higher output-capital ratios (2. I 0)
than any other ratios. That is the ratios of output-capital is greater than
those of Medium Town (Nevasari i.e.1.52) and Small Town or Rural
industrial estate Bulsar/Vapi i.e. 0.92". Bhati in his study has also come to
the conclusion that, "In respect of both labour and capital productivities,
Urban estates have proved, on an average ,to be more efficient than mral
estates".
(2) A significant proportion of the industrial units i.e., 65 per cent
of the total sample units fall in the group with an average labour
productivity ofless than Rs.3000~ In the highest labour productivity group
(i.e. more than Rs. 11 ,000) 30 per cent units occur and the rest 5 per cent
are in the group which ranges between Rs. 3000 to Rs.ll ,000.
'JX Sanghvi's conclusive table is given belo\v. Capital Productivity
Industrial estates. (average) Urban 0.963 Rur~ 0.806 R.L. Sanghvi ( 1979), op.cit., p.I70.
Labour Productivity (average) Rs.5934 Rs.3368
275
In tenns of labour productivity the top rank was attained by Okhla
Industrial estate (with Rs.12,6 78) and the NO IDA industrial estate
occupied the second place (with Rs.l I ,000). These two Metropolitan
industrial estates along with one City industrial estate (Alwar, where
labour productivity was Rs.l 0,827), had more than the average labour
productivity of the sample i.e. Rs.l 0, 77 5." Okhla industrial estate had an
edge over NOIDA industrial estate which shows that the workers in the
Okhla industrial estate were more productive than· NOIDA industrial
estate in I 994. 99 It leads us to conjecture that the units in Okhla industrial
estate were inore labour intensive than those in NOIDA industrial estate.
(3) In tenns of average labour productivity, only 5.67 per cent
units were in the lowest group (less than Rs.3000) and 29.67 per cent units
in the highest group (more than Rs.ll ,000). As opposed to the labour
productivity, the capital productivity had a different position. A large
number of industrial units i.e. 57 per cent units were in the lower group
(less than Rs.l lakh) and only 2.67 per cent units were in the highest group
(more than Rs.5 lakhs) of capital productivity.
In terms of industrial estates NOIDA industrial estate occupied the first
place with an average capital productivity of Rs.1.68 lakhs and Okhla
industrial estate occupied the second place (with Rs.1.63 lakhs). These
are the only two industrial estates which have an average capital
productivity which is more than that of the total sample. NOIDA industrial
estate was replaced by the Okhla industrial estate which occupies the first
place in tenns of capital productivity. The average capital productivity of
NOIDA industrial estate indicates that the industrial units are more capital
intensive than those of Okhla industrial estate.
99 The values is derived from the graph given in support of the text by the author. G.S. Bhati ( 1976), op.cit., p.193, (Bhati's abstract Table).
276
(4) It was observed that labour productivity was the highest in case
of Metropolitan industrial estates (Rs.12,327) and lowest in the City
industrial estate (Rs. 7185). It means there was a decline in the labour
productivity from Metropolitan industrial estate to City industrial estate
and Town industrial estate.
This was llOt only observed in the labour productivity but in capital
productivity as well. In case of the Metropolitan industrial estates, the
average capital productivity was Rs.l .64 lakhs, while the City industrial
estate and tl}e Town industrial estate had an average capital productivity of
Rs.l.19 lakhs and Rs.1.04 lakhs respectively.
The Metropolitan industrial estates have perfonned better than
either City industrial estates or Town industrial estates in tenns of labour
productivity as well as capital productivity 100 . The better perfonnance of
Metropolitan industrial estates is due to extemal economies which provide
a viable environment to grow and prosper in. Not only do they have basic
industrial necessities such as water, energy or a transport network, but also
a trained labour pool and market. On the other hand City industrial estates
and Town industrial estates have relatively poor infrastmctural facilities
and most of the material required and product sold by the industrial
enterprises are located in remote urban centres. Transport bottle-necks
and relatively high transpm1ation costs plague the units and non
availability of skilled labour compel the entrepreneurs to pay relatively
higher wages to attract skilled workers from urban centers.
1(1(1 R.L. Sanghvi (1979), o~. p.181. R.L Sanghvi, On the basis of Surplus Capital Ratios has also drawn the same conclusion that Well organised urban estate units seemed to be more efficient than semi-urban or rural ones and the semi-urban industrial units to be superior to mral industrial units in economic efficiency."
277
The analysis of labour productivity and capital productivity for
industrial estates (Urban and Rural category-wise), show~ that in general
Metropolitan industrial estates have utilised labour and capital potential
more efficiently than the City industrial estates or Town/Rural industrial
estates.
278