Appendix – XII
Trends in Total Factor Productivity of Manufacturing Sector in West Bengal:
A Sectoral and Temporal Analysis
Sadhan Kumar Chattopadhyay*
This paper seeks to examine the overall industrial scenario of West Bengal for the past three decades. The paper studies
the productivity of capital and labour for the two-digit industry groups and the total factor productivity (TFP) of the
manufacturing sector of West Bengal as a whole vis-à-vis all-India and also for some selected groups of industries for West
Bengal. West Bengal has lost its earlier status of one of the highly industrialised States of the country. Its share to all-India
net value added, share of employment and factories has come down drastically. Profitability of total manufacturing sector
has gone down. Productivity of capital of the manufacturing sector has declined, while labour productivity has increased.
However, the latter has increased mainly due to a few industry groups, which are highly capital intensive and have
contributed around 85 per cent of the profit of the total manufacturing sector. TFP of the West Bengal manufacturing sector
as a whole has been declining, while it has been increasing in case of India. TFP of six industry groups which played a
dominant role during the early 1960s has gone down except Jute industry, which itself is a dying industry. That means no
new industry groups have come up to take up the position of these industries, which have been performing badly. Therefore,
while the State of West Bengal has shown an impressive improvement in case of rural sector, industrial slowdown has not
been arrested as yet in the State.
JEL Classification : D24, O33
Keywords : Production Function, Labour Productivity, Capital productivity, Total Factor Productivity Growth (TFPG)
West Bengal in general and Calcutta in particular was the ‘commercial and industrial hub’ of the whole of Eastern India
before 1947 (Bagchi 1998). The State was a leader in respect of concentration of industrial capital. The State’s share in all-
India stock of capital in the CMI (Census of Manufacturing Industries) sector was 24.6 per
* Research Officer in the Department of Economic Analysis and Policy, Reserve Bank of India. The views expressed in the
paper are personal views of the author and need not represent the views of the institution he is working with.
cent in 1950 (Banerjee 1998). Coal, jute, tea, engineering and iron and steel were the major industries of the State on the
eve of Independence. In 1946 West Bengal had a larger number of factories and factory employees than any other province
in India. However the situation had started changing from the partition of Bengal. Two major industries, viz., jute and tea had
been adversely affected by the partition. Infrastructure sector, particularly loss of Chittagong port, had also got adversely
affected due to this cause. Migration from erstwhile East Pakistan also created large pressure. In the process, the State lost
its industrial base. It not only fell far behind some States like Gujarat, Maharashtra, Karnataka and Andhra Pradesh, but the
State had to suffer a process of deindustrialisation as well1 . Now the State has come a long way since the pre-
Independence period. But the situation does not seem to have changed; rather it appears to have become worse as
discussed in the following sections.
The objective of the paper is to analyse the present condition of the industrial sector of the State. The study tries to examine
the factor productivity growth, especially of capital and labour across industry groups in West Bengal. The most important
aspect of the paper will be estimates of total factor productivity (TFP) growth for West Bengal, supposed to be the first
comprehensive attempt in this area.
The remainder of the paper is structured as follows. Section I discusses the theoretical background and the methodology of
the study. Section II discusses the structure, composition and growth of industrial sector in West Bengal. Section III deals
with capital intensity, and capital and labour productivity. TFP is discussed in Section IV. Concluding observations are
presented in the final Section.
Although technological progress did not get importance in the work of classical economists like Malthus, Ricardo and Mills,
it is considered to be a major determinant of economic growth today. Subsequently, in the works of Marx and Scumpeter it
got some importance with varied degrees. Later on, the concept came to the fore after the works of Tinbergen (1942),
Schmookler (1952), Kendrick (1956), Fabricant (1954), Abramovitz (1956) and Solow (1957).
Any growth in output that is not explained by some index of input growth is attributed to changes in technology or more
broadly productivity. Thus, TFP growth is a catch-all measure that captures changes in efficiency in addition to pure technical
change in the sense of shifts in the production function. As has been aptly pointed out by Goldar (1986) that since there are
constraints to resource expansion in developing countries, a high rate of industrial growth to be achieved and sustained
over a long period requires substantial improvement in total factor productivity.
TFP may be defined as the ratio of output to a weighted combination of inputs. “Productivity growth is generally understood
to represent the exogenous shift of a frontier (best practice) production function. The distance from the frontier technology is
X-inefficiency” (Srivastava 1996). Therefore, a precise decomposition of growth of output into the contribution of change in
inputs and that of total productivity is based on the economic theory of production function.
There are two main approaches in estimating the productivity, viz., Production Function Approach (PFA) and Growth
Accounting Approach (GAA)2 . However, as discussed in Trivedi et al. (2000), there are various problems associated with
the production function approach like multicollinearity, autocorrelation and degree of freedom. In order to avoid those
problems we have restricted our analysis of TFP to GAA only.
The key feature of the GAA is separation of change in production on account of changes in the quantities of factors of
production from residual influences, which include technological progress, learning by doing, etc. Multi Factor Productivity
(MFP) actually surrogates these residual influences. The genesis of this approach can be traced back to Tinbergen (1942)
and Solow (1957). Basically there are three main indices used in the GAA. These are (i) Kendrick Index (KI) (ii) Solow Index
(SI) and (iii) Translog Index (TLI). However, KI and SI suffer from some limitations3 . In contrary, TI is superior to both KI and
SI because TI numbers are symmetric in data of different time periods and also satisfy the factor reversal test
approximately4 . It is based on Translog Production Function characterised by constant returns to scale. It allows for
variable elasticity of substitution and does not require the assumption of Hicks-neutrality.
The translog production function of output (Y) emerging from use of labour (L), capital (K) and time (T) is written as
It has been shown by Diewert (1976) that indexes formed in such a fashion are exact for a translog aggregator function and
that they are exact only for a translog aggregator function.
Estimating Translog Production Function
The discrete approximation of the Translog Production Function in the form of Translog Index has been used in most of the
recent studies on the measurement of productivity in the Indian industries5. The Translog Index can be defined as the
Where, V is real value added, w denotes the share of labour in nominal value added, L and K indicate labour and capital,
The equation is based on the general neo-classical production function for which the elasticity of substitution need not be
infinite, equal to unity or even constant. The above equation actually measures the difference between the rate of growth of
real value added and the rate of growth of factor inputs.
Data, Variables and Coverage
This study is based on the Annual Survey Industries (ASI) data. Net value added at constant prices is taken as the measure
of output. Number of employees (including workers and persons other than workers) is taken as the measure of labour
input. However, there is no unique measure of capital. Hence several methods are applied in estimating capital stock. In
this study the perpetual inventory accumulation method (PIAM) has been used for generating the series on capital stock,
which has been used in various studies. The PIAM requires the estimates of capital stock for a benchmark year and
investment in the subsequent years. The time series on capital stock at current prices has been generated by using the
|I is the gross capital formation/investment, B is the book value of fixed capital, D is depreciation, K is the stock of capital at
current prices. Subscript 't' has been used to denote time. Data on all the variables mentioned above are available in ASI.
The study covers the period from 1967-68 to 1999-2000. Data prior to this period is not available in the format required for
calculating the index. Initially the TFPG is calculated for the whole manufacturing sector in West Bengal vis-à-vis all-India
manufacturing as a whole to assess the position of the manufacturing sector in West Bengal as against the all-India
average. Subsequently the TFPG is calculated for six selected industries. Selection has been done on the basis of
contribution to total net value added. These six industry groups have played a pivotal role in the industrial arena of the State.
The intention here is to observe their relative position vis-à-vis other industries in order to investigate whether these
industries are slipping from their strong position. If it is really so, then it is also worth investigating whether any new industry
group is taking up their position.
Structure and Growth of Industry in West Bengal
The sectoral composition of State Domestic Product in West Bengal shows some structural transformation in the State
during the past four decades (viz., 1960-61 to 1999-2000). While the share of primary sector in NSDP has gone down
marginally from 39.2 per cent in 1960-61 to 38.7 per cent in 1999-2000, the share has gone down substantially (by around
10 percentage points) in case of the secondary sector. The decline of share in NSDP is more pronounced in case of the
manufacturing sector. It has gone down from over 25.2 per cent in 1960-61 to mere 10.0 per cent in 1999-2000. However,
the tertiary sector has gained the share at the cost of both manufacturing and agriculture over this period. At the all-India
level also, there has been a change in the structure of the economy. However, in this case the scenario is a bit different from
West Bengal. Unlike West Bengal, the share of secondary sector has gone up from 19.4 per cent to 21.6 per cent during the
same period, notwithstanding the fact that the share of manufacturing sector has slipped downward marginally. However,
like the case of West Bengal, at the all-India level, the shares of the primary sector in general and agriculture in particular
have gone down to a larger extent from 48.2 per cent and 44.4 per cent, respectively, during 1960-61 to 30.5 per cent and
26.3 per cent, respectively, during 1999-2000. Tertiary sector, on the other hand, has increased its share in case of all-India
as is the case with West Bengal from 32.4 per cent in 1960-61 to 48.0 per cent in 1999-2000 (Table 1). Furthermore, the
state’s share in all-India NDP has gone down, albeit marginally, from 7.7 per cent in 1960-61 to 7.6 per cent in 1999-2000.
The decline in West Bengal’s stronghold position in respect of industrial status can be gauged from the declining share of
secondary sector, in general, and manufacturing sector, in particular, in all-India NDP. It implies that the other States have
come forward gradually in respect of industrial development and surpassed the leading position of West Bengal. It can be
observed from Table 2 that the relative share of secondary sector has gone down from 10.9 per cent in 1960-61 to 6.4 per
cent in 1999-2000. Furthermore, the share of the State’s total manufacturing sector in all-India NDP has also gone down
from 13.1 per cent in 1960-61 to a mere 6.6 per cent in 1999-2000 entirely due to the registered manufacturing sector.
Structural change can also be noticed from the contribution of different industries in net value added. The contribution of
major industries of the manufacturing sector at the 2-digit level (2-3) was more than 90 per cent of the total manufacturing
sector during 1979-80.
Table 1: Composition of NSDP of West Bengal vis-à-vis All-India NDP
1960-61 1970-71 1980-81 1990-91 1999-2000
West All West All West All West All West All
Bengal India Bengal India Bengal India Bengal India Bengal India
1 2 3 4 5 6 7 8 9 10 11
1. Primary 39.2 48.2 45.1 48.0 38.7 41.3 33.6 34.7 38.7 30.5
Agriculture 34.7 44.4 41.5 44.2 34.6 36.3 28.6 29.9 33.7 26.3
2. Secondary 27.6 19.4 22.7 19.9 24.7 23.0 26.2 25.5 18.1 21.6
Manufacturing 19.8 7.3 12.9 7.6 14.0 9.1 9.7 11.0 4.5 8.5
Manufacturing 5.4 7.5 4.7 6.6 4.7 7.8 7.8 7.1 5.5 5.2
Manufacturing 25.2 14.8 17.5 14.2 18.7 16.9 17.5 18.1 10.0 13.6
3. Tertiary 33.3 32.4 32.2 32.2 36.6 35.7 40.2 39.8 43.2 48.0
Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Almost two decades later, the contribution had come down to 59 per cent. That means more than 40 per cent of net value
added is contributed by those industries, which are outside the domain of the manufacturing sector. However, within the
manufacturing sector there has not been any significant change in the contribution to net value added with a few exceptions.
The significant change has occurred only in case of the jute industry and manufacture of transport equipment and parts
whose contributions have come down to 10.8 per cent and 1.0 per cent, respectively, in 1997-98 from 23.3 per cent and 10.5
per cent, respectively, in 1979-80. On the other hand, the share went up marginally in case of leather and leather products
and rubber, plastic, petroleum and coal products.
In brief, although there has been a structural change in the State, the industry, as a whole, could not gain much during the
last 26 years. This is evident from both the share of the State in all-India NSDP
Table 2: Share of Manufacturing Sector of West Bengal in All-India NDP
1960-61 1970-71 1980-81 1990-91 1999-2000
1 2 3 4 5 6
1. Manufacturing - Registered 21.0 14.7 12.4 6.5 4.4
2. Manufacturing - Unregistered 5.5 6.1 4.8 8.2 10.4
3. Manufacturing - Total 13.1 10.7 8.2 7.2 6.6
4. Secondary 10.9 9.9 10.4 7.7 6.4
Source: National Accounts Statistics, Government of India, various issues.
Table 3: Index of Industrial Production -Compound Growth Rate for West Bengal vis-à-vis All-India
Period Mining & Manufacturing Electricity General
1 2 3 4 5
1970-71 to 1980-81 (at 1970=100)
West Bengal 0.01 1.82 1.43 1.62
All-India 4.26 4.05 7.33 4.42
1980-81 to 1992-93 (at1980-81=100)
West Bengal 0.10 1.84 8.80 2.23
All-India 6.94 6.41 8.63 6.75
1993-94 to 2000-01 (at 1993-94=100)
West Bengal 0.78 3.37 6.59 3.62
All-India 3.98 7.63 6.40 7.20
Sources : 1. Economic Review, Government of West Bengal, various issues.
2. Handbook of Statistics of Indian Economy, RBI, various Issues.
and share in all-India net value added in total manufacturing sector. A similar picture emerges from an analysis of the
trends in the IIP of the State (Table 3).
Concomitantly, the share of the State in the country’s total number of factories, employment and value added has witnessed
a gradual decline. The share of factories has gone down from 15.8 per cent in 1960-61 to 4.8 per cent in 1999-2000 (Chart
1). Similarly, the share
in net value added has gone down from 23.2 per cent over the decade of 1960s to 5.4 per cent during the decade of 1990s,
while that of employment has gone down from 23.1 per cent to 8.4 per cent over the same period (Charts 2 and 3 and Table
During the period 1973-74 to 1999-2000, the net value added (NVA) of the total manufacturing sector grew at an annual
compound rate of 1.8 per cent, while employment had grown at an annual compound rate of (-)1.3 per cent. However, fixed
capital had grown at a relatively high annual compound rate of 5.2 per cent. Industry-wise performance is presented in
Table 4: Percentage Share of West Bengal in All-India
Period NVA Employment
1 2 3
1959-60 23.2 23.1
1960-61 to 1969-70 20.1 21.3
1970-71 to 1979-80 12.8 14.9
1980-81 to 1989-90 8.5 10.8
1990-91 to 1999-2000 5.4 8.4
The industries which played a vital role in West Bengal during the period of 1960s were food products (20-21), textiles (23-
25), rubber plastic and petroleum products (30), basic chemical and chemical products (31), basic metal and alloy (33), and
manufacture of machinery and equipment (including electrical machinery) (35-36). All these industries contributed
significantly to all India net value added in respective industries during 1960. However, over the next four decades, the share
of these industries in net value added to all-India level fell sharply. The share of textiles went down to 12.3 per
Table 5: Industry-wise Performance of Major Indicator (1973-74 to 1999-2000)
Negative Below Between Above 4 per cent Above
2 per cent 2 and 4 and below 7per cent
per cent 7 per cent
1 2 3 4 5 6
NVA 31,37 23-25,34,35- 28,29,33 20-21, 26, 30, 22
36,38 27, 32
VO 37 23-25 28,35-36 20-21, 29, 30, 22, 26, 27
31, 32, 33, 34, 38
EMO 28, 31, 35-36, 23-25, 29, 34, 20-21, 22, 26,
37 38 27, 30, 32, 33
TE 23-25, 28, 29, 20-21, 26, 30 27, 22
31, 32, 33, 34,
FC 37 31 23-25, 30, 32, 33, 20-21, 22, 26,
34, 35-36,38 27, 28, 29
Note :1. NVA : Net Value Added; VO: Value of Output; EMO: Emoluments;
TE : Total Employment; FC: Fixed Capital
2. Explanations of industrial codes are given in Annex 2.
cent in 1999 from 16.2 per cent in 1960 while that of chemical products went down to merely 0.7 per cent from 16.4 per cent
over the same period of time (Table 6). Further, the share of food products fell to 2.8 per cent in 1999 from 13.5 per cent in
1960. While machinery and equipment including electricity contributed 33.9 per cent during 1960, the joint contribution of
these two industry groups to value added came down to only 3.8 per cent in 1999. Rubber, plastic and petroleum products
showed an even more dismal picture as their contribution came down from 43.2 per cent in 1960 to a mere 1.7 per cent in
1999. On the other hand, the contribution to all-India net value added increased for some industries such as food products;
rubber, plastic, petroleum; and basic metal and alloys.
It is also interesting to note that the share of manufacturing sector in total net value added has gone down from 90.0 per
cent in 1970 to 59.2 per cent in 1997-98, while in case of India, the fall has been relatively moderate (from 88 per cent to
81.2 per cent during the same period). The industries which have taken up the share from core manufacturing sector are
electricity, gas, water supply, non-conventional energy, storage & warehousing services, sanitation, etc. As we have seen in
Table 3, the IIP growth in electricity has gradually
Table 6: Share of Net Value Added of Select Industries in West Bengal to All-India
Year Food Textiles Rubber Basic Basic Manufacture of All
Products (23+24+25) Plastic, Chemical and Metal machinery
(20-21) Petroleum Chemical and Alloy including elec-
etc. Products (33) trical machinery
(30) (31) (35-36)
(1) (2) (3) (4) (5) (6) (7) (9)
1960 13.5 16.2 43.2 16.4 10.6 33.9 22.3
1965 10.8 19.7 48.1 12.5 8.5 29.3 21.6
1970 8.5 16.5 30.2 8.6 6.7 16.1 14.0
1974* 8.6 15.2 15.1 7.6 16.6 14.8 12.9
1980 3.9 16.7 7.2 5.7 16.5 10.7 11.3
1985 6.5 11.2 5.2 3.9 17.0 6.3 8.6
1990 4.6 9.4 4.5 6.5 8.5 6.4 6.2
1995 2.4 9.8 2.3 4.0 8.3 6.1 4.7
1999 2.8 12.3 1.7 0.7 6.2 3.8 3.7
* Data for 1975 is not available.
Source :Annual Survey of Industries, Government of India, various issues.
increased from 1970-71 to 1999-2000. That means contribution of electricity in overall industrial sector has been high in
West Bengal. But it is also true that the growth of electricity is not high enough to generate high industrial growth. This is
evident from the low industrial growth depicted in Table 3.
Capital Intensity, Productivity of Labour and Capital
Factor intensity can be discussed with the help of fixed capital per employee and value added per employee. However,
there is no unique measurement of capital intensity or labour intensity. Industries can be grouped into labour-intensive or
capital-intensive on the basis of average capital-labour ratio (K/L). If the capital-labour ratio of a particular industry is above
the average then the industry may be considered as a capital-intensive one. However, this methodology is admittedly
arbitrary in nature since there is no specific capital-labour ratio for the industries.
The average capital per employee for the entire manufacturing sector was Rs.190.1 in 1973-74, Rs.184.4 in 1980-81, Rs.
251 in 1990-91 and Rs.1070.2 in 1999-2000 at constant prices (1981-82 = 100). As per the norms discussed above, the
industries with capital per employee above these respective averages may be regarded as capital-intensive and those with
capital per employee below them as labour-intensive. The industries coming under each of these categories in 1973-74
and 1999-2000 are listed below:
i) Capital-intensive industries
1973-74 28, 30, 31, 33, 35-36, 37
1999-2000 28, 30, 31, 33, 35-36
ii) Labour-intensive industries
1973-74 20-21, 22, 23-24-25, 26, 27, 29, 32, 34, 38
1999-2000 20-21, 22, 23-24-25, 26, 27, 29, 32, 34, 37, 38
It may be observed from the above list that there has not been any significant change in the structure of industries by factor
intensity over the period. However, there is only one exception. Manufacture of transport equipment and parts (37), which
was in the capital-intensive category during 1973-74 shifted to the labour-intensive category in 1999-2000.
The share of capital-intensive industries in the manufacturing sector also declined over the three-decade period. During the
year 1973-74, the capital intensive industries contributed 58.1 per cent to both total value added and output and 45.5 per
cent to employment. In 1999-2000 the share of value added had gone down to 41.9 per cent, output to 53.7 per cent and
employment to 35.9 per cent. That means labour-intensive industries provided employment to more than 64 per cent of total
employment in the manufacturing sector by using lesser quantity (around 30 per cent) of the capital asset. However, it is
interesting to note that the share of profit of the capital intensive industries increased from 61.8 per cent in 1973-74 to 85.5
per cent in 1999-2000. The share of profit of the labour intensive industries concomitantly fell from 38.2 per cent to 14.5 per
cent. It is worth mentioning that out of 17 two-digit industry groups only five were capital intensive in 1999-2000. Therefore,
only five industry groups are contributing over 85 per cent of total profit in the manufacturing sector in West Bengal, whereas
the rest 12 industry groups are contributing below 15 per cent.
Productivity of Labour
Labour productivity is considered to be one of the oldest and widely used measures of productivity (Trivedi, et al. 2000).
“The wide usage of labour productivity is due to the fact that it can be used as proxy for the amount of goods available for
consumption per labourer. Hence increase in labour productivity is very often regarded as an end in itself and in such a
situation the role of capital gets reduced merely to that of enabling labour productivity to rise.” Moreover, in comparison to
per capita real GDP, labour productivity is viewed as a superior indicator since the former ignores importance of working
hours per person/employment rates in the growth process (Maddison, 1987). In many industrialised countries labour
productivity is calculated as the real value added per man-hour. However, most of the studies in India are based on data on
number of employees or workers for estimation of labour productivity. Following this convention, we have also used the data
on number of employees in calculating labour productivity.
The growth rate of labour productivity in the manufacturing sector as a whole increased from 1.6 per cent in 1970s to 2.6 per
cent in the 1980s and further to 5.7 per cent in 1990s. During 1970-71 to 1999-2000, it increased at an annual compound
growth rate of 2.5 per cent. Out of 15 two-digit industry groups only 4 groups (viz., manufacture of beverages, tobacco and
related products; manufacture of wood and wood products; manufacture of basic chemical and chemical products; and
manufacture of transport equipment and parts) recorded negative annual compound growth in labour productivity (Table 7).
Productivity of Capital
Generally there is an inverse relationship between capital intensity and output to capital ratio (Srivastava, 1996). However, it
is found that all the industries, both labour and capital intensive, have shown declining capital productivity. The fastest
decline in the output to capital ratio is in manufacture of chemical and chemical products (except products of petroleum and
coal) (31), manufacture of leather, leather and fur products (29) and manufacture of paper and paper
Table 7: Growth Rate of Labour Productivity of the Manufacturing Sector (Industry-wise) in West Bengal
Period/Industry Groups 20-21 22 23-25 26 27 28
1970-71 to 1999-2000 2.3 -0.3 2.1 3.9 -3.2 3.8
Period/Industry Groups 29 30 31 32 33 34
1970-71 to 1999-2000 2.5 5.5 -0.2 3.2 4.7 1.8
Period/Industry Groups 35-36 37 38 Manufacturing
1970-71 to 1999-2000 3.2 -0.2 2.5 2.5
Note: Descriptions of industrial codes given in Annex 2.
products, printing and publishing and allied products (28). The slowest decline is observed in manufacture of beverages,
tobacco and tobacco products (22), manufacture of textile products (26) and manufacture of rubber, plastic, petroleum and
coal products (30).
Profitability of Industrial Sector
The industrial sector has suffered low profitability since 1979-80 and in fact, negative profitability during 1983-84 to 1990-91
(excepting 1987-88), whereas at the all-India level the scenario is entirely opposite (Table 8). It has been hypothesized by
Ray (1996) that loss-making units in the public sector (assuming that private sector firms cannot continue to exist as loss
making ones in the long run) perhaps dominated profit making firms in West Bengal leading to this perverse phenomenon
of persistent negative profitability of the overall industrial sector. However, this hypothesis appears to be only partly true. This
is because, as has been observed in the early part of discussion, there has been a gradual decline in number of factories
in West Bengal. As a result, the share of factories in total has gone down drastically. That means, the industrial units
Table 8: Profitability: Profits/Output in terms of ASI Aggregate Data
Year West Bengal India Year West Bengal India
1 2 3 4 5 6
1973-74 6.6 11.5 1987-88 2.1 2.1
1974-75 5.9 8.3 1988-89 -4.0 4.0
1975-76 4.0 17.2 1989-90 -3.9 3.9
1976-77 3.7 17.2 1990-91 -0.8 4.2
1977-78 3.3 16.5 1991-92 -1.3 3.2
1978-79 3.5 6.7 1992-93 -1.5 4.0
1979-80 3.5 5.9 1993-94 2.1 6.7
1980-81 1.1 3.4 1994-95 0.6 7.2
1981-82 -0.2 4.6 1995-96 -0.4 6.6
1982-83 0.4 4.1 1996-97 2.2 7.7
1983-84 -1.5 4.9 1997-98 5.7 5.1
1984-85 -1.6 3.1 1998-99 0.2 6.7
1985-86 -0.4 2.9 1999-2000 -6.7 5.3
1986-87 -1.8 3.1
Source : Estimated from time series data on ASI (Various Issues).
losses over time and as a process became sick and finally had to close down the unit. Hence the obvious economic
consequence has been exit of all inefficient industrial units. Since the exit process occurred in a phased manner it perhaps
led to a gradual and systematic decline of aggregate industrial output and employment - a process termed de-
Section IV Total Factor Productivity
The total factor productivity of West Bengal decreased gradually during the period 1966 to 1999 in contrast to the rising trend
for India as a whole. As stated earlier, we have tried to examine the total factor productivity of six industry groups, which
played dominant role during the early 1960s. It can be seen that except jute all the remaining five industry groups have
shown declining TFP growth. Machinery and machine tools initially showed rising trend, but after 1970s it remained
stagnant (Charts 4a-4f). The TFP growth contribution to output is negative for two out of six industry groups (Table 9). For the
remaining four groups, however, the TFP growth
Table 9: Trend Growth Rates of Productivity of Various industries 1966-1999 (Per cent per annum)
Industry Group Trend Growth Trend Rates of TFP contribution
Rate of Real Growth of to Output
Value Added TFP growth
1 2 3 4
Manufacture of Food products 2.0 -1.4 -70.0
Manufacture of jute, hemp etc. 13.1 12.0 91.6
Manufacture of Rubber, Plastic, 0.4 -0.8 -200.0
Manufacture of Chemical and 7.9 10.6 134.2
Basic Metal and Alloys 3.3 1.6 48.5
Manufacture of Machinery, Machine 3.2 2.9 90.6
Tools (including electrical machinery)
Manufacturing Sector 2.1 -1.2 -57.1
Manufacturing Sector (All India) 6.3 4.6 73.0
Source : Estimated from time series data on ASI (Various Issues).
contribution to output growth is substantial. Manufacture of chemical and chemical products recorded more than 100 per
cent contribution from TFP growth. For the period 1966-1999, TFP contribution to output growth is negative for the whole
manufacturing sector, whereas at the all-India level TFP contribution to manufacturing sector output is positive and
|The study shows that West Bengal has gradually lost its stronghold position once enjoyed during the early 1960s. The
State's shares in net value added, employment and number of factories have gone down drastically over the years. Looking
at the 2-digit level industry group, it is observed that only one industry (viz., manufacture of beverages, tobacco and related
products) has registered annual compound growth rate of above 7 per cent in net value added, while 5 industry groups have
recorded annual compound growth rate of between 4 and 7 per cent. So far as employment is concerned, majority of the
industry groups has witnessed negative growth rate. It is interesting to note that only 5 industry groups, which are highly
capital intensive, contributed over 85 per cent of total profit in the manufacturing sector. It has also been found that growth of
labour productivity in the manufacturing sector as a whole increased from 1.6 per cent in 1970s to 2.6 per cent in the 1980s
and further to 5.7 per cent in 1990s. The share of net value added of six important industry groups in West Bengal to all India
NVA has declined over the past 30 years. Because of deceleration in growth rate of these industries, the overall industrial
scenario of the State was adversely affected. Moreover, the total factor productivity of the manufacturing sector of the State
declined during the period, whereas it has gone up at the all-India level. The six most important industries which were the
main contributor to industrial growth of the State have lost their position and their TFP growth rates have gone down
drastically except Jute which itself is a dying industry. The TFP growth contribution to output is found to be negative for two
out of the six industry groups. However, as a whole, the industrial sector does not seem to have come out from decelerating
condition. Technological obsolescence of these six important industry groups may be one of the major reasons of industrial
deceleration in the State. Furthermore, although some industries have lost their base, no new industry has come up to take
over that position. It cannot be denied that the rural Bengal has changed a lot. In the rural sector the State has set an
example for other States in regard to implementation of land reform, and institution of panchayati raj well in advance of the
73rd and 74th constitutional amendment which could enable the State to regain its pre-eminent position, by taking
advantage of a boost from domestic farm sector. In contrast, as the analysis in this paper suggests, the situation is entirely
different in the arena of industrial development of the State.
1 See Bagchi (1998)
2 For details see Trivedi et al (2000).
3 Properties of these indices and their limitations have been discussed by Goldar (1986) and Trivedi et al (2000).
4 Divisia Index or Translog Index is discussed in Annex 3.
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Annex - 1
The Concordance Table
NIC 1987 code NIC 1998 code
Source :National Industrial Classification, Central Statistical
Organisation, Ministry of Planning and Programme Implementation,
Government of India, New Delhi 1998.
Annex - 2
The Concordance Table
NIC Code Description of Industry
220-21 Manufacture of Food Products
22 Manufacture of Beverages, Tobacco and Related Products
23 Manufacture of Cotton Textiles
24 Manufacture of Wool, Silk and Man-made Fibre Textiles
25 Manufacture of Jute and Other Vegetable Fibre textiles (Excl.
26 Manufacture of Textile Products (Including Wearing Apparel)
27 Manufacture of Wood and Wood Products, Furniture and
28 Manufacture of Paper and Paper Products and Printing,
Publishing & Allied Industries
29 Manufacture of Leather & Leather Products, Fur & Leather
30 Manufacture of Basic Chemicals and Chemical Products
(Except Products of Petroleum and Coal)
31 Manufacture of Rubber, Plastic, Petroleum and Coal Products;
Processing of Nuclear Fuels.
32 Manufacture of Non-metallic Mineral Products
33 Basic Metal and Alloys Industries
34 Manufacture of Metal Products and Parts, except Machinery
35 Manufacture of Machinery and Equipment, Electrical (other
than Transport equipment (and excl. Manufacture of Scientific
Equipment, Photographic/Cinematic Equ. and Watches &
36 Manufacture of Machinery and Equipment, Non-electrical
(other than Transport, Scientific, Photographic/Cinematic
Equ. Watches & Clocks)
37 Manufacture of Transport Equipment and Parts
38 Other Manufacturing Industries (Including Manufacture of
Scientific, Photographic/Cinematic Equipment, Watches &
39 Repairs of Capital Goods
Annex - 3
Divisia Index – Translog Index
The need for Divisia index has been noted by Solow (1957) and Jorgenson and Griliches (1967). Subsequently Christensen
and Jorgenson (1969,1970), Jorgenson and Griliches 1972), Gallop and Jorgenson (1980) have used approximations to
the Divisia index known as translog index in their studies.
The properties of the Divisia index, which make its application highly desirable, have been discussed in the seminal paper
of Christensen and Jorgenson (1970). It has been pointed out that the rates of growth of the Divisia indexes of prices and
quantities add up to the rate of growth of the value (factor reversal test) and that such indexes are symmetric in different
directions of time (time reversal test). Divisia indexes also have the reproductive property that “a Divisia index of Divisia
indexes is a Divisia index of the components.” For application to data at discrete points of time an approximation to the
continuous Divisia index is required. The translog index is a discrete version (developed by Tornquist) of the continuous
Divisia index. Translog index numbers are symmetric in data of different time periods and also satisfy the factor reversal test
approximately. But they do not have the reproductive property. The translog index of technological change is based on a
translog production function, characterised by constant returns to scale. It allows for variable elasticity of substitution and as
pointed out above it does not require the assumption of Hicks-neutrality.
To describe the Divisia index we may consider a somewhat general model. Let’s consider an aggregate production function
with two factors of production:
Y = F(K, L,T) (1)
Where Y denotes aggregate output, K aggregate capital, L aggregate labour and T time. It is assumed that F is continuous,
twice differentiable and characterized by constant returns to scale. These aggregates are taken as functions of their
Similar assumptions about continuity, differentiability and homogeneity are made for these functions. Corresponding to
them there are m output prices, n capital prices and q labour prices, denoted respectively by
|Correspondingly, aggregate prices are denoted by p, r and w. Under the assumption of perfect competition and profit
maximization, the conditions of producer's equilibrium require that the shares of the factor prices be equal to their
elasticities, so that
SYi is the share of the i'th output component in aggregate output. Similarly SKj and SLu are the shares of the j'th capital
input and the u'th labour input in aggregate capital and aggregate labour respectively. Linear homogeneity requires
|Differentiating equation (1) totally with respect to time and rearranging terms, we obtain
|Thus, a weighted average of growth rates of individual components gives the growth rate for the aggregate. These are
respectively called the Divisia quantity Indexes of output, capital and labour.
On the price side, it is seen that the assumptions of constant returns to scale, perfect competition and profit maximization
require that the prices of output, capital and labour be consistent with the following equation
|This form gives us the Divisia price index of technological change.
For application to data at discrete points of time, an approximation to the continuous Divisia index, known as translog index,
may be used. This assumes that translog function describes the relationships between Y, K, L and T (production function)
and also the relationships between the aggregates and components. Constant returns to scale is assumed for all these
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