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III Exploring The Slowdown (Part 2 of 3)

Impediments to Industrial Growth

Capital Formation

3.43 Notwithstanding the view that the extent of capital formation in agriculture, particularly in the public sector is underestimated (ICRA, 2001), the declining capital formation in agriculture has emerged as an issue of paramount concern (Table 3.14). This has been compounded by the decline in the share of public sector investment in agriculture to total public sector investment (Chart III.15). The lack of new capital assets has slowed down the pace and pattern of technological change in agriculture, thus having adverse effect on Total Factor Productivity (TFP). Fixed capital formation in agriculture seems to respond positively to public sector capital formation in canal irrigation. Indian farmers devote a small proportion of both own and borrowed funds for fixed capital formation, as private sector capital formation in agriculture responds positively to technical progress and availability of institutional credit and negatively to rainfall (Dhawan and Yadav, 1995).

Table 3.14 : Gross Capital Formation in Agriculture (1993-94 Prices)


Year

Ratio of Capital Formation

in agriculture to




GCF


Agricultural GDP


1



2


3


1970-71

14.27

7.08

1980-81

15.44

9.92

1981-82

11.19

9.29

1985-86

9.76

8.33

1990-91

9.88

8.03

1991-92

8.66

7.46

1992-93

9.06

7.57

1993-94

8.42

6.87

1994-95

7.30

7.20

1995-96

6.22

7.68

1996-97

7.26

7.22

1997-98

7.00

7.42

1998-99

7.88

7.13

1999-00



7.96


8.02


Source : Ministry of Agriculture, Government of India.

3.44 Unlike the 1970s and the 1980s when the foodgrain-led growth pattern was dependent to a large extent on the public sector capital formation, agricultural growth seems to have been driven more by market considerations and demand in the 1990s (Gulati and Bathla, 2001). The relative decline in the importance of public sector capital formation in the 1990s, however, does not undermine the role of such investments, given their complementarity with private sector capital formation in agriculture, even though by allowing greater role for market forces - as could be evidenced through the evolution of terms-of-trade with declining intervention in the price formation process - the degree of dependence of agricultural growth on public sector investment could be contained without affecting the prospects of growth in agriculture.

Storage, Processing and Marketing

3.45 The lack of proper storage and marketing facilities at the village level results in distress sales, particularly by the small and marginal farmers which adversely affect their incomes. This has a direct bearing on their ability to invest in agriculture. Indian agricultural marketing scenario is characterised by the existence of segmented markets on the one hand and inter-linked markets on the other (Reddy, 2001). There is a geographical market segmentation characterised by lack of market access to farmers, while there are inter-linkages in factor and product markets, which lead to lower and exploitative prices. It has been argued that the interlinked markets result in a suboptimal situation by denying the producer an economic and market determined price for his product (Gangopadhyay, 1994). The inter-linkage between factor and product markets contributes significantly towards limiting the adoption of new technological inputs by way of reducing the farmer's income. Similarly, the inter-linkages in the factor markets (for instance, between credit and labour markets) limits the technology adoption by the small farmers, by way of putting extra-economic demand on farmer's labour at the crucial time, say sowing: thus it contributes to lower production and hence lower income of the small farmers5.

3.46 Other important factors adversely affecting the efficiency of agricultural markets are the lack of proper futures markets, the absence of price discovery and the failure of the market in providing proper price signals. In the absence of proper price signals, the farmers' decision to cultivate any crop may depend on less efficient criteria such as administered prices, rather than demand and supply, leading obviously to inefficient resource allocation. Further, the existence of a large section of unregulated middlemen and traders reduces the market efficiency to a significant level. Bringing these middlemen into the framework of institutional market mechanism with proper regulatory ambit will result in transforming the middlemen into market facilitators, while direct marketing (by producers) provides an opportunity to minimise the role of middlemen (Reddy, 2001).

Agricultural Credit

3.47 Institutional credit to small and marginal farmers plays an important role in replacing informal credit market mechanisms and the inter-linkages arising between informal credit and other factor/product markets. The deceleration in the growth of loans outstanding for the small land holdings during the 1990s as compared with the 1980s is indicative of a combination of better repayment of loans in the 1990s (since most of these loans are of small values and in the nature of crop loans, etc.) as well as low disbursement rate. For small and marginal farmers, the deceleration in the credit disbursal has been the maximum in the 1990s. Small and marginal farmers, thus, continue to be both credit and demand constrained.

3.48 The lack of capital has been a primary factor impeding the adoption of new technological inputs, which are capital intensive. The size and flow of financial resources to agriculture, both in terms of investment and working capital have shrunk significantly. Despite the stipulation of sub-targets for agriculture at 18 per cent under priority sector, credit has not flowed to the desired extent. There exist many escape routes with regard to priority sector lending targets, such as the option to invest in RIDF and place deposits with SIDBI. Direct finance to small and marginal farmers (with land holdings up to two hectares) has been slowing down in recent years (Table 3.15). The average growth in loans outstanding to marginal farmers has decelerated sharply during the 1990s as compared with the growth recorded in the 1980s (Charts III.16 and III.17).

Table 3.15 : Trend Growth Rates of Scheduled Commercial Banks' Direct Finance to Farmers(Short-term and long-term loans)

(Per cent)


Year

Up to 2.5 acres

Above 2.5 acres to

Above 5 acres

Total

(July-June)



5 acres







Accounts


Amount


Accounts


Amount


Accounts


Amount


Accounts


Amount


1


2


3


4


5


6


7


8


9


Loans Outstanding

1980s

8.61

19.33

11.80

21.48

7.41

16.96

9.17

18.39

1990s

-3.69

7.65

-1.58

8.95

-0.92

8.05

-2.27

8.17

Loans Disbursed

1980s

7.51

18.38

11.45

21.55

7.21

17.51

8.51

18.61

1990s


2.16


11.84


5.72


15.88


8.55


16.31


4.95


15.01


Note: Trend Growth Rates are based on semi-logarithmic functions.

Public Distribution System (PDS)

3.49 The PDS has attracted considerable debate in recent years on the ground that the benefits of PDS are not reaching the poor on account of, inter alia, poor targeting and leakages in the system, despite its restructuring in 1997 (Mooij, 1999, GoI 2000b, 2000c and 2000e). It has also been argued that despite the huge food subsidy and the large-scale of intervention, the food security of many households is still marginal or insufficient. In recent years there has been a substantial rise in procurement of foodgrains by the public sector agencies on account of consistent increases in Minimum Support Prices (MSP), despite the recommendations of the Commission for Agricultural Cost and Prices to freeze the same (GoI, 2000d). It is argued that consistent increases in the MSP have distorted relative prices between alternate agricultural activities, land use patterns as well as the consumption of inputs (ICRA, 2001). The stock of 59.14 million tonnes at the end of November 2001 is around two and a half times the norm of 24.30 million tonnes for end-September 2001 (Table 3.16).

3.50 Considerable concern regarding the mounting stocks has been expressed of late, as substantial amount of food credit and food subsidy have been required to finance these operations.

Table 3.16 : Procurement, Off-take, Stocks and Food Subsidy


Year

Procurement

Off-Take

Stocks

Food

(Million

(Million

(Million

Subsidy

Tonnes)

Tonnes)

Tonnes)

(Rupees





crore)


1


2


3


4


5


1993-94

26.40

18.61

20.54

5537

1994-95

24.99

19.44

26.80

5100

1995-96

22.24

24.35

20.82

5377

1996-97

20.03

25.63

16.41

6066

1997-98

23.82

18.96

18.12

7500

1998-99

24.22

20.73

21.82

8700

1999-00

31.43

23.05

28.91

9200

2000-01

36.47

17.95

44.98

12042

2001-02

34.83

16.15

59.14

N.A.

(up to

end-November,

2001)






N.A. : Not available

Food subsidy, which amounted to Rs.6,066 crore in 1996-97, has increased to Rs.12,042 crore in 2000-01. During 1997-98 to 2000-01, the outstanding food credit witnessed a rise from Rs.7,597 crore to Rs.39,991 crore, indicating a phenomenal average annual growth of 51.9 per cent (Chart III.18). The share of consumer subsidy in food subsidy has been declining over these years, indicating that much of the increase in food subsidy goes towards carrying costs. Carrying cost of foodgrains increased to Rs.220.35 per quintal in 2000-01 from Rs.158.26 per quintal in 1996-97. Consumer subsidy on rice for below poverty line

(BPL) consumers declined to Rs.565.00 per quintal in July 2000 from Rs.589.33 per quintal in 1997-98. Similarly, the consumer subsidy on wheat for BPL consumers decreased to Rs.415.00 per quintal in July 2000 from Rs.536.35 per quintal in 1997-98. Given the present scenario, the effectiveness of food subsidy in supporting the public distribution programme has been questioned (GoI, 2000e).

3.51 A gradual reduction of the food stock to scale down outstanding food credit and food subsidy needs to be considered. Measures to increase the off-take of foodgrains such as Food for Work Programme and increased open market sales including exports, may help to achieve the objective of gradual scaling down of stocks. There is also a need to streamline the procedure for evaluating the quality of stocks, as this will have an impact on the outstanding advances of commercial banks to the Food Corporation of India.

3.52 Free and fair international trade in agricultural commodities can act as an engine of growth for the economy as a whole. It is interesting to note that agriculture was placed for the first time on the negotiating agenda of the Uruguay Round (1986-1993) (Box III.1).

Determinants of Agricultural Growth

3.53 In view of the many shades in the growing consensus seeking the reform of agriculture, it is useful to undertake an empirical verification of the determinants of agricultural output in the context of the country specific conditions. The determinants considered for this excercise are area under cultivation (chosen over gross sown area so as to take cognisance of the relative importance of various crops through explicit weights in the index), labour and 'technology indicators' such as irrigation intensity (ratio of gross irrigated to net irrigated area), cropping intensity and ratio of area under HYV seeds to gross sown area, rainfall, and time trend.

Box III.1

WTO and Indian Agriculture

The Agreement on Agriculture (AoA), which aimed at the liberalisation of the world trade in agricultural commodities was negotiated and signed by India, along with other countries in April 1994 at Marrakesh, Morocco as a part of the Final Act of the Uruguay Round and was made effective from January 1, 1995. The AoA aims at removing the distortions in world trade in agriculture arising from excessive protection and subsidisation of agriculture. AoA contains provisions with respect to three areas: market access, export subsidies and domestic support. Existing non-tariff barriers in agriculture, which are considered trade-distorting, are to be abolished and converted into tariffs so as to provide the same level of protection and subsequently the tariffs are to be progressively reduced by a simple average of 36 per cent by the developed countries over 6 years (year ending 2000) and by 24 per cent by the developing countries over 10 years (year ending 2004) (Table 3.17). The minimum market access opportunities are to be provided at 3 per cent of the domestic consumption in 1986-88 (to be established by the year 1995) and rising up to 5 per cent by the end of the implementation period.

Table 3.17 : Reduction Commitments Under AoA




Developed

Developing

Countries

Countries


(1995-2000)


(1995-2004)


1


2


3


Tariffs (Base 1986-88) Average

36%

24%

cut for all Agricultural products

Domestic support, Total AMS

20%

13%

(Base 1986-1988):

Export Subsidies(Base1986-1990)

36%

24%

Budgetary outlays for

export subsidies

Volume of subsidised exports


21%


14%


The domestic support to farmers is divided into three categories, viz., Amber Box, Blue Box and Green Box. All domestic support measures considered to distort production and trade (with some exceptions) fall into the category of Amber Box. Subsidies which do not, or at the most cause minimal distortion come under the purview of Green Box. The support under Amber Box directly affects the quantity produced by the producer and the price of the product, whereas the support under the other two heads are neutral in this respect. Subsidies like input subsidies for fertilisers, electricity, support in the form of lower interest rates and market price support fall under the Amber Box category. The Green Box support includes assistance given through environment assistance programmes, services such as research, training and extension, marketing information, certain type of rural infrastructure, etc. Subsidies under Blue Box include direct payment given to farmers in the form of deficiency payment (i.e., the difference in the Government's minimum support price and market price is paid directly to farmers, as practiced in the USA), direct payment to farmers under production limiting programmes, etc.

The support under Green Box is excluded from any reduction commitments and is not subjected to any upper limit. Support under Blue Box is also exempted from any reduction commitments but it has an upper limit. The support under Amber Box is related to the trade distorting support, unlike that under the other two heads. AoA aims at removing this trade-distorting support. The trade distorting support, called as Total Aggregate Measure of Support (AMS) is expressed as a percentage of the total value of the agricultural output. The Agreement stipulates the reduction of total AMS by 20 per cent for the developed countries over a period of six years, while the developing countries are needed to reduce the total AMS by 13 per cent over a period of ten years. Reduction commitments refer to total levels of domestic support and not to individual commodities. Policies which amount to domestic support, both under product specific and non-product specific categories at less than 5 per cent of the value of production for developed countries and less than 10 per cent for developing countries are also excluded from any reduction commitments. Policies which have no, or at the most minimal trade distorting effects on production, are excluded from any reduction commitments.

The developed countries are required to reduce the volume of subsidised exports by 21 per cent over six years and the budgetary outlays for export subsidies by 36 per cent with respect to the base period of 1986-90. Developing countries are required to reduce the volume by 14 per cent and budgetary outlays by 24 per cent over 10 years.

Implications of AoA for India

In India, quantitative restrictions on agricultural imports imposed for balance of payments (BoP) considerations have been removed and these imports are placed in the open general license (OGL) list. In order to provide adequate protection to domestic producers in case of a surge in imports, India can raise the tariffs within the bound ceilings. In case of a few products such as primary products, processed products and edible oils, India had earlier raised the tariffs (during 1999 and 2000) adequately to protect the domestic producers. In case of some other products, India has successfully revised the binding levels through negotiations. However, India can take suitable measures under WTO's Agreement on Safeguards if there is a serious injury to domestic producers due to surge in imports or if there is any such other threat. The Government has already taken a number of measures to safeguard the agriculture sector in the context of the phase-out of quantitative restriction, i.e., import duties on many agro and other items have been substantially increased and import of about 131 products have been subjected to compliance of mandatory Indian quality standards as applicable to domestic goods.

India's domestic support to agriculture is well below the limit of 10 per cent of the value of agricultural produce and therefore India is not required to make any reduction in it at present. The subsidies given for PDS are basically the consumer subsidies and are exempt from WTO discipline. India's system of Minimum Support Prices (MSP) as also the provision of input subsidies to agriculture are not constrained by the Agreement. Moreover, the agricultural developmental schemes can also be continued under AoA.

Reference

  1. Government of India, (2001), Focus, Ministry of Commerce.
  2. ________ (2001), Press Releases, Ministry of Commerce.
  3. ________ (2001), WTO and India, various issues, Ministry of Commerce.
  4. WTO (1995), Agreement on Agriculture.

3.54 Elasticities of agricultural output with respect to its various determinants are set out in Table 3.18. Elasticities have been highest, predictably, with respect to area and labour, followed by rain. The elasticity of agricultural production with respect to rain at 0.27 is found to be significant. However, the elasticities with respect to technology variables such as consumption of fertiliser and pesticides, cropping intensity, irrigation intensity and the share of area under HYV seeds to gross cropped area turn out to be very low, often statistically insignificant and hence are not reported. Inclusion of time trend taken as representative of technical progress in the estimation framework reduces the labour co-efficent apart from making it insignificant.

Table 3.18 : Estimated Elasticities of Agricultural Output


Variable


Elasticity


1


2


3


Without Time Trend

Area

0.8243

Labour

0.8618

Rain

0.2667

With Time Trend

Area

0.9096

Labour

0.1844*

Rain

0.2376


Time Trend


0.0174


* : Not significant.

3.55 Indian agriculture calls for reforms encompassing technology upgradation, creation of infrastructure, creation of a better marketing system, revival of the rural credit delivery system, and public sector capital formation in infrastructural facilities, particularly irrigation. In the context of extending reforms to agriculture, multilateral organisation have offered several suggestions drawn from cross-country experience (Box III.2).

Box III.2

International Institutions on Reforming Agriculture

Deceleration in agricultural growth has been a common feature of the growth pattern in the Asia Pacific region in the recent years. Global agricultural growth is also projected to decelerate to 1 per cent in 2000 after exhibiting modest recovery in 1999 (at 2.3 per cent) over 1998 (1.4 per cent). The generally sluggish growth conditions reflect a number of underlying weaknesses which, along with uncertain weather conditions, have stifled the prospects of agricultural growth. The underlying weaknesses continue to persist even after the observed shift in national policies away from public production and state administration in favour of the market.

According to the World Bank, a key aspect in the increasing market orientation of agricultural policies relates to the sequencing of agricultural reforms. Ideally, reforms that increase farmers cost of production by eliminating input subsidies should not precede those that can stimulate growth by raising output prices - such as elimination of regressive price controls and export taxes. Furthermore, supply response in agriculture to reforms may not be symmetrical. An assessment based on 50 agricultural adjustment loans of the World Bank reveals that in countries where agriculture was penalised/taxed, reforms helped in raising farm output. In turn, other countries where agriculture was heavily protected, liberalisation adversely affected agricultural output growth by hastening reallocation of resources away from agriculture. Supply response in agriculture to the overall structural reform measures, however, depends upon the level of agricultural development of a country. An enabling government policy may not prove very effective in the absence of adequate agricultural infrastructure - including roads, irrigation, power, and telecommunications - appropriate technology, credit, farmer education and an assured supply of inputs at right price. Prices for inputs that do not reflect any explicit/implicit subsidy, but which are determined in a competitive market condition and also remove barriers to convergence with international prices could represent good practice in agricultural pricing policy, if not the right price. In revamping the public expenditure programmes for agriculture as part of the overall reform process, however, countries must take adequate precaution to avoid major decline in agricultural growth. Recognising the underlying weaknesses of the agricultural sector in several countries, agricultural adjustment loans generally rely on a two prong approach. The first major aspect of the approach emphasises price reforms and market liberalisation so as to ensure that domestic prices are in line with world market prices, marketing and processing systems are efficient, with better access to efficient technology and public services. The second key aspect emphasises private production in a competitive environment.

The Asian Development Bank points out that in a market-based system for agriculture, the possibility for reaping the potential higher yield would depend on the actual return on agricultural investment and the overall condition for agricultural production (Mingsarn, Santikarn and Benjavan Rerkasem, 2000). In the past years, decline in net returns on food crops has forced farmers to explore alternative farming opportunities with higher returns - including oil crops, fruits and vegetables. The market mechanism, thus, seems to have altered the cropping pattern in favour of more profitable non-food crops. Environmental degradation - the result of faulty application of technology and agricultural policy- has, however, been a subject of concern which could threaten long-run agricultural sustainability. In Asia, water resource management has been fragmented and project based. As a result, both surface water and ground water are used excessively. Crop production in fragile land has also resulted in soil erosion, salinisation, water logging and desertification. Inappropriate technology has often been used to avoid/postpone reforms that may be economically and socially desirable but politically impracticable. While encouraging adoption of any technology for the agricultural sector, therefore, due care must be taken to improve field-level knowledge, better crop management, and proper communication between farmers and research and development (R&D) officials.

The OECD stresses the importance of the response of the labour market in agriculture to the overall process of structural reforms, particularly to sustain the improved labour productivity in agriculture. Surplus labor in agriculture operates as a major impediment to attain the desired labour market adjustment. It also exerts pressures on the government to address their problems through various subsidies. More efficient farm structures under market conditions can therefore emerge only when preconditions to market efficiency could be ensured.

Keeping in view the alternative prescriptions, the future course of reforms in Indian agriculture may have to focus on the following critical areas.

  • Agricultural yield can be increased through creating infrastructural facilities rather than by providing input subsidies. Fertiliser prices need to be streamlined further to reduce the skewed N:P:K ratio in fertiliser consumption.
  • The tools of emerging bio-technology such as genetic engineering seem to offer significant possibilities for increasing yields. Bio-technological inputs such as bio-fertiliser and bio-pesticides are perceived to be scale neutral and can be adopted by even small farmers and provide scope for savings on use of chemical fertilisers and pesticides, apart from being eco-friendly.
  • The practice of increasing the Minimum Support Price (MSP) may have to be re-examined as it has resulted in large procurement of foodgrains by the public sector agencies, leading to an increase in the procurement incidentals. It has also distorted the price formation process in the market.
  • In view of the removal of quantitative restrictions under the WTO agreement, the agricultural prices will have to be aligned with the international prices to be competitive. Appropriate institutional reforms such as setting up of commodity exchanges are necessary to protect domestic producers from greater price volatility that generally characterises the international market for foodgrains and other crops.
  • India is the second largest producer of fruits and vegetables in the world and is perceived to have comparative advantage, which needs to be reaped. Given India's diversified climatic and soil conditions, the growing demand for such items in the affluent parts of the world and the scope for developing the food processing industry explains the need for shifting the pattern of production in favour of fruits and vegetables.

References

  1. FAO (2001), The State of Food and Agriculture, Rome.
  2. Mingsarn, Santikarn Kaoshard and Benjavan Rerkasem ( 2000), Growth and Sustainability of Agriculture in Asia, Asian Development Bank, Manila.
  3. OECD (1999), Agricultural Policies in Emerging Transition Economies, Vol. 1.
  4. World Bank (1997), 'Reforming Agriculture: The World Bank Goes to Market', A World Bank Operations Evaluation Study.

III. IMPEDIMENTS TO INDUSTRIAL GROWTH

3.56 The deceleration in economic activity in the second half of the 1990s is primarily attributed to industrial slowdown. Cyclical turns in activity have impacted on industrial output, accentuating the demand-supply imbalances. Structural factors have inhibited the growth of capacity creation/expansion in industry, eroded competitiveness and increased the vulnerability of the economy to adverse cyclical or exogenous shocks. Identified structural constraints are lack of adequate infrastructure development, low agricultural buoyancy, large fiscal imbalances and dearth of internal reforms.

3.57 Insufficient demand is regarded as the single most important factor inhibiting growth in manufacturing as well as other segments of the industrial sector. Apart from the global slowdown, the current deceleration in the manufacturing sector is ascribed to slowdown in investments, low business confidence and subdued capital market (NCAER, 2001; Chandrasekhar, 2001; Shetty, 2001; ADB, 2001).

3.58 The growth of value added in the industrial sector in India slowed down in the 1990s after recording significant improvement in the 1980s, with similar trends at the sectoral level. The growth of the industrial sector is affected by intersectoral imbalances in the growth process. The significant deceleration in the growth rate of the mining and quarrying and electricity sectors during the 1990s affected the overall growth of industrial output. The mining and quarrying and the manufacturing sectors have also exhibited higher volatility in the growth rate during the 1990s. These fluctuations in the growth rates and imbalances across the sectors have implications for stabilising output growth at higher levels (Table 3.19, 3.20 and Charts III.19, 20, 21, 22).

Table 3.19 : Trend Growth of Industrial Production in India

(Per cent)


Period

Mining

Manufac-

Electricity

General

and

turing


Quarrying





1


2


3


4


5


1970-1980

4.7

4.1

7.4

4.6

1980-1990

7.7

7.3

8.7

7.5

1990-2000


3.8


6.8


6.6


6.5


Note : The trend growth rates are derived from a semi- logarithimic function.

Table 3.20 : Coefficient of Variation of Industrial Production

(Per cent)


Period

Mining

Manufa-

Electricity

General

And

cturing


Quarrying





1


2


3


4


5


1970-1980

110.1

85.0

67.4

72.9

1980-1990

53.0

32.3

21.2

23.7

1990-2000


125.1


62.2


21.4


55.7


3.59 In the post-liberalisation period, the cyclical fluctuations in industrial activity have been generated by the internal dynamics of the industrial sector apart from supply shocks. Evidence of cyclical behaviour of industrial production has led to the development of leading and coincident indicators of industrial activity (Box III.3).

Box III.3

Leading Indicators of Industrial Activity in India

The approach of leading indicators of economic activity has been widely used to track the phases of business cycles despite the criticism of lack of sound theoretical foundations. The leading indicator analysis of business cycles is woven around the view that economies experience cycles with 'expansions occurring at about the same time in many economic activities, followed similarly by general recessions, contractions and revivals that merge into the expansion phase of the next cycle; this sequence of changes is recurrent but not periodic' (Burns and Mitchell, 1946). The framework of leading indicators provides early signals about turning points in economic activity, which is important for undertaking counter-cyclical policies.

Empirical work on the leading indicator approach originated from the National Bureau of Economic Research (NBER) in the 1930s, and subsequently numerous versions of leading indicators have been developed. The objective of constructing a composite index of leading indicators is to identify the cyclical behaviour of the reference indicator, i.e., the series whose future movements are to be predicted. Reference indicators usually relate to a measure of aggregate real activity, such as aggregate output(GDP), investment and employment, etc. In the absence of high frequency data on aggregate measure of real activity, several studies have used industrial production as the reference series; the OECD indicator system uses the index of total industrial production as the reference series.

The composite index of leading indicators (CILI), being multivariate in nature, has been extensively used as it predicts cyclical turning points more effectively than any single indicator. The CILI is based on the premise that cycle of each component indicator has its unique characteristics as well as features in common with other cycles, but no single cause explains the cyclical fluctuation over a period of time in overall activity. The performance of individual indicators depends on the strength of causal relation with the reference indicator. Accordingly, the multivariate approach, as adopted for composite indicators, is necessary to combine various signals for possible causes of cyclical turning points.

Once the cyclical behaviour of the reference series has been established, the next step is to select an economic time series whose cyclical movements typically predate those of the reference series. The leading component indicators are evaluated on the basis of their relevance, cyclical behaviour and practical considerations relating to timeliness in availability of high frequency information. On statistical consideration, the criterion of being leading indicators utilises the tests of peak-and-trough analysis, cross-correlation analysis, etc. Once a set of leading indicators has been selected, the component indicators are combined into a single composite index to reduce the risk of false signals and to provide a leading indicator with better forecasting and tracking qualities. In the empirical literature, a variety of leading indicators such as average work-week, index of overtime hours, application for unemployment compensation, new companies registered, new orders, vendor performance, construction, stock prices, money supply, change in sensitive material prices, index of consumer expectations, etc. have been used for constructing a multivariate index of business cycles.

In India too, attempts have been made at building leading/coincident indicators of economic/ industrial activity in recent years using the NBER methodology for constructing diffusion and composite indices for identifying growth cycles, the ECRI approach using the Bry Boshan algorithm for coincident economic indicators and a composite leading index for the manufacturing sector as the reference indicator of economic activity.

The construction of an appropriate CILI is constrained by data limitations; many important indicators of business performance of the corporate sector are not available at monthly/quarterly frequency. Despite these data gaps, a CILI has been constructed in terms of the variables that can best explain the turning points of the business cycle. The index of industrial production (IIP) is taken as the reference indicator to represent the industrial activity in the Indian context. The component variables considered were IIP for basic goods, food stocks, deposits of scheduled commercial banks, currency demand, non-food credit, total commercial bank credit, broad money supply, short-term interest rates, stock prices, exports, non-oil imports, WPI of manufacturing, WPI of primary articles, WPI of industrial raw material, WPI of minerals, WPI of fuel, power, light and lubricants, and freight loading of railways, besides the GDP of the United States as an indicator of external economic environment. Seasonally adjusted quarterly series for the period 1988:Q2 to 2001:Q2 are passed through the Hodrick-Prescott Filter to obtain the cyclical component of each series. The lead-lag relationship between the cyclical component of the reference series vis-à-vis other series are identified in terms of cross-correlation matrices at various lags and Granger causality tests with varying lags. Six indicators, viz., non-food credit of commercial banks, currency with the public, prices of fuel group of commodities, freight loading of the railways, exports and non-oil imports emerge as significant.Chart III.23 to Chart III.28 show the cyclical component of the IIP and each of the series. The composite index is compiled for the period using the six variables having a lead of 2-3 quarters. Since the cyclical components of the various series have varying amplitudes, each of the series is standardised taking into account its mean and standard deviation.

An unweighted index of these six series is compiled to forecast the turning points of industrial activity in India with implicit assumption that industrial sector is undergoing rapid changes and the production cycles may change over time. The CILI for the industrial activity leads the actual IIP by two quarters. The CILI, particularly since the early 1990s is able to capture the turning points of the IIP about two quarters in advance (Chart III.29).

References

  1. Burns, A.F. and W.C.Mitchell (1946), 'Measuring Business Cycles', National Bureau of Economic Research, New York.
  2. Chitre, V.S. (1982), 'Growth Cycles in Indian Economy', Artha Vijnana, Vol. 24.
  3. Dua, P. and A. Banerji (1999), 'An Index of Coincident Economic Indicators for the Indian Economy', Journal of Quantitative Economics, Vol.15,No.2.
  4. Koopmans, T.C. (1947), 'Measurement without Theory', The Review of Economics and Statistics, Vol. 29.
  5. Mall, O.P.(1999), 'Composite Index of Leading Indicators for Business Cycles in India', RBI Occasional Papers, Vol.20, No.3.

Demand Constraints in the Industrial Sector

3.60 It is essential to identify the role of the demand side factors in contributing to the declining industrial output. Of the important components of the demand for industrial goods, government consumption demand has been used in India as a counter-cyclical measure during the downturn in industrial activities, as the private consumption tends to be pro-cyclical.

3.61 A clear pattern emerges between the real private consumption expenditure and the industrial output during the 1980s and the 1990s. During the 1980s and the early 1990s, high growth in industrial output was associated with sustained growth in real private consumption demand. In contrast, during the downturn the latter half of the 1990s, real private consumption demand has decelerated. While the cyclical component of the private final consumption expenditure generally exhibits pro-cyclical movements with the industrial production, government final consumption expenditure exhibited counter-cyclical movements (Chart III.30).

3.62 An important factor explaining the fluctuations in economic activity and industrial output during the phases of business cycle is the changes in inventory holdings. The credit view on the role of inventories in explaining industrial output postulates that the impulses of a restrictive monetary policy are transmitted immediately through higher carrying cost on inventory investment, which in turn would affect the level of output through backward linkages with the industrial sector (Gertler and Gilchrist, 1994; Bernanke and Gertler, 1995). Although inventory investment may constitute a small part of the total value of output in the industrial sector, it may significantly explain the output changes. Changes in inventory holdings are found to be closely associated with cyclical turning points in economic activity in India (Darbha, 1999). On the basis of the observed trends in the inventory holdings and growth in industrial output, changes in inventory show generally pro-cyclical movement, implying that adjustment in the inventories leads the variations in industrial output (Chart III.31).

3.63 The sectoral inter-linkages between agriculture and industry provide the basis for analysing the industrial slowdown. An analysis of the inter-linkages shows that the significant improvement in industrial output in the 1980s was accompanied by an improvement in the growth rate of per capita real income in agriculture. In the 1990s, with decline in the per capita real GDP growth in agriculture to 1.3 per cent, the average industrial output growth declined to 6.0 per cent (Table 3.21).

3.64 Slow growth in agricultural output adversely impacts on the industrial production by affecting the surplus of wage goods, supply of inputs, and demand for industrial goods. On the demand side, the hypothesis of 'agricultural drag' inhibiting growth of industrial output has been a subject of considerable empirical research. It is observed that while the growth of wage goods has not been a factor constraining industrial output, the slow growth of agricultural income impacts on consumer demand for industrial goods (Ahluwalia, 1991).

Table 3.21: Per Capita Real GDP in Agriculture and Real GDP Growth in Industry

(Per cent)


Period

Per Capita Real GDP

Real GDP growth


Growth in Agriculture


in Industry


1


2


3


1970-80

-0.9

4.4

1980-90

2.5

7.4

1990-2000


1.3


6.0


Private consumption demand is, to a large extent, determined by the levels of farm incomes. Analysis covering the post-Green Revolution period yields two agricultural factors that limited the forward thrust to industrial growth in India, viz., volatility in the growth of agriculture output and low growth in the per capita agricultural income.

Capacity Utilisation and Output Growth

3.65 Industrial output is significantly influenced by the rate of capacity utilisation in industry. The low rate of capacity utilisation in Indian industry indicates underutilisation of factor inputs which can impose an enormous growth constraint on the economy. The declining rate of capacity utilisation also indicates the sluggish growth in demand during the downturn in economic activity, and the adjustment of supply to underlying demand conditions. The direct measurement of capacity utilisation is often constrained by the availability of information on the installed capacity in industry. The literature on capacity utilisation suggests various measures, such as, the Wharton Index of Capacity Utilisation and the Minimum Capital-Output Ratio Method (Klein and Summers, 1966). These measures and their variants have been widely used to analyse capacity utilisation in industry. In the absence of direct measures, the common traits in the behaviour of these indirect measures can provide some insights into capacity utilisation.

Wharton Index

3.66 In the Wharton Index, the capacity of a firm/industry in the short run is represented by the maximum sustainable level of production under normal working conditions when the firm is operating its existing capital stock at its customary level of intensity. However, it is argued that the peaks so identified may not truly reflect the capacity output of the industry (Paul, 1974) and that the capacity expansion takes place in a smooth and gradual manner which may not be true (Phillips, 1963). Despite some limitations, the method has been widely used to assess the capacity utilisation in industrial sector. Under this method, seasonally adjusted monthly values of indices of output are averaged into quarterly data which are used for identifying peaks as indicators of capacity output. The estimates based on the Wharton Index for the Indian manufacturing sector for the period 1971 to 2001 indicate that there has been an improvement in capacity utilisation in the manufacturing industries as a group during the 1980s. Capacity utilisation, however, showed deterioration in the 1990s, except for some brief spells. The electricity sector, unlike the manufacturing sector, witnessed an improvement during the 1990s over the 1980s and 1970s, mainly attributed to rising demand. The capacity utilisation in the mining and quarrying sector, however, witnessed deterioration over the decades with rising gaps in the 1990s. The impact of slackening demand in the recent years resulted in lower capacity utilisation (Chart III.32 to III.34).

Minimum Capital-Output Ratio Measure

3.67 As per this method, developed by the National Industrial Conference Board of the USA, a benchmark year is selected on the basis of lowest capital-output ratio (in real terms). The output corresponding to the lowest capital-output ratio is taken as the capacity output. The measure of capacity utilisation is obtained by deflating real fixed capital stock by the minimum capital-output ratio.

Table 3.22 : Capacity Utilisation (CU) in Industry : Minimum Capital-Output Measure (C/O)


Period

Manufacturing


Mining and Quarrying


Electricity



C/O


CU (Per cent)


C/O


CU (Per cent)


C/O


CU (Per cent)


1


2


3


4


5


6


7


1970-71 to 1974-75

2.8

98.6

1.4

95.0

11.8

80.7

1975-76 to 1979-80

2.9

94.8

1.9

69.9

11.5

82.5

1980-81 to 1984-85

3.2

84.8

2.6

50.6

12.3

77.3

1985-86 to 1989-90

3.1

88.1

3.4

38.0

11.6

81.9

1990-91 to 1994-95

3.0

90.6

3.3

38.7

10.7

88.6

1995-96 to 1999-2000


3.7


75.7


3.2


41.0


9.9


96.6


The estimates of capacity utilisation in the manufacturing sector in India for the period 1970-71 to 1999- 2000 indicate that some improvement in the capacity utilisation occurred towards the late 1980s and the first half of 1990s, i.e., during the period associated with acceleration in the industrial growth rate. The mining and quarrying sector recorded significant decline in capacity utilisation. In the electricity sector, capacity utilisation rose steadily up to the 1990s. These sectoral imbalances in the capacity utilisation have implications for the overall industrial growth (Table 3.22).

3.68 In the context of developing economies, capacity utilisation is determined by both demand as well as supply side factors. Among the demand side factors, inventories in relation to sales of the firm is important. Among the supply side factors, raw material, energy, transport, credit, etc. are recognised (Sastry, 1980; Rangarajan, 1990; Ajit, 1993).

3.69 An empirical exercise is conducted in order to identify the proximate determinants of capacity utilisation in the manufacturing sector within a behavioural approach. Demand factors embodied in real private final consumption have a strong positive impact on capacity utilisation6. On the supply side, energy prices, which affect the cost of production of the industry, have a dampening effect. The dummy variable for the liberalisation period of the 1990s indicates that capacity utilisation could have declined in the post-liberalisation period, indicative of a cyclical catch-up (IMF, 2000). The actual level of capacity utilisation adjusts to the desired level fairly quickly, i.e. within a year(Table 3.23).

Table 3.23 : Elasticities of Capacity Utilisation in Manufacturing in India

Elasticities



LPFCE


LWPIFUEL


1


2


3


Short-run

0.583

-0.288

Long-run


1.123


-0.555


LPFCE

=log of real private final consumption expenditure

LWPIFUEL


= log of WPI of fuel, power, light and lubricants


Infrastructural Constraint on Growth

3.70 Among the institutional and other structural factors underlying industrial growth, infrastructure is recognised as the most important source of output growth because of its simultaneous impact on capacity creation and improvement in productivity of capital. The infrastructural sectors such as transport, power and telecommunications provide critical inputs for the manufacturing sector of the economy. The capital-intensive nature of such services requiring lumpy investment and long gestation periods, characteristics of pure public goods, underscores the role of Government in provision and management of infrastructure. As infrastructure services constitute direct inputs to production, a reduction in cost of such inputs improves the profitability of producing enterprises. Increasing availability of infrastructure facilitates the efficient use of other factors of production like labour and capital. It is argued that though higher output growth leads to higher investment in infrastructure, certain minimum investment in infrastructure is required to achieve a sustainable level of growth. Various studies have estimated the impact of infrastructure on economic growth (Aschauer, 1989; Munnel 1990a, 1990b). In the Indian context, elasticities of output with respect to various stocks of infrastructure indicate that transport and communication sectors play a dominant role in explaining the variations in gross domestic product and in other sectors (Sahoo and Saxena, 1999).

3.71 Industrial output growth in India has closely tracked the movements in the composite index of infrastructure industries during the 1980s and 1990s. This observed relationship between infrastructure growth and industrial performance in India has implications for sustaining the higher output growth and narrowing the output gap over the medium term (Chart III.35).

3.72 Empirical evidence points to a robust relationship between infrastructure investment and productivity growth in the manufacturing sector (Ahluwalia, 1991). The high growth performance of infrastructure sector during the 1980s can be attributed to a strong resurgence in the growth of infrastructure investment during the Sixth and the Seventh Plans. The public sector dominates in the power sector, water supply, railways and roads, etc., while the private sector is predominantly in the transport sector, mainly road cargo transport. The India Infrastructure Report (1996) projected infrastructure investment requirement at 8.0 per cent of GDP over a medium term (Table 3.24). The requirements of funds for infrastructure are estimated to rise and an increasing proportion of gross domestic investment would have to be earmarked for financing the infrastructure.

Table 3.24 : Projected Investment Requirements for Infrastructure (Macro Estimates)

(Rupees billion)


Year

Gross

GDI in

GDI in

GDI in

Domestic

Infrast-

Infrastr-

Infrastr-

Investment

ructure

ucture

ucture

(GDI)

as %

as % of -





of GDP


total GDI


1



2


3


4


5


1990-91

1448.5

287.4

5.4

19.8

1995-96

2825.5

598.6

5.5

21.2

2000-01

4512.0

1076.0

7.0

23.8

2003-04

5938.8

1472.3

7.6

24.8

2004-05

6523.4

1639.0

7.8

25.1

2005-06


7179.5


1826.1


8.0


25.4


Note

: The data for GDP, Projected GDI and GDI in infrastructure from 1995-96 onwards are at1995-96 prices.

Source: The India Infrastructure Report (1996)

Sectoral Imbalances and Gaps in Infrastructure

3.73 Sectoral imbalances in infrastructure impose constraints on the growth of industrial output. Juxtaposed with the slowdown in the growth of the infrastructure sector between the 1980s and 1990s, the persistence of sectoral imbalances in the infrastructure sub-sectors has simultaneously posed challenges for capacity expansion as well as utilisation of the existing capacity. The sectoral performance during the 1990s reveals that the average growth of all infrastructure industries, except for the steel sector, has remained significantly lower than in the 1980s. The decline in the overall growth of infrastructure sector in the 1990s in relation to the 1980s emanated mainly from a decline in growth of electricity, coal and petroleum. The stylised facts highlight the importance of the energy sector in sustaining higher growth of industrial output (Chart III.36, 37, 38, 39, 40).

3.74 Identification of sectoral infrastructure gaps assumes critical importance. The deficit in the existing availability of various infrastructure services vis-a-vis the potential demand provides a measure of the infrastructure gap. Among the important sub-sectors, the power sector has grown at a rate of 6.6 per cent during the 1990s as against 9.2 per cent in the 1980s. Simultaneously, the gap between demand and supply has remained significant, notwithstanding the fact that several reforms, including private participation, have been undertaken to boost growth of the power sector to fill the gap. The demand-supply gap in power widened to 11.5 per cent by 1996-97 from 7.9 per cent in 1990-91, although there was some decline thereafter. Poor performance of State Electricity Boards (SEBs), with increasing financial strain emanating from low average tariffs and high cross subsidies to agriculture and household sectors has stunted the growth of the power sector (Table 3.25).

3.75 In the telecommunications sector, the demand-supply gap has significantly narrowed from 27.9 per cent in 1991-92 to 12.2 per cent in 2000-01, reflecting the impact of reorientation of policies followed in the sector (Chart III.41). A sharp narrowing in the demand-supply imbalances in this sector notwithstanding, the extent of gap remains higher than the power sector.

Table 3.25 : Demand-Supply Gap in the Power Sector in India

(Million units)


Year

Requirement

Availability

Deficit

Deficit

as % of





Requirement


1


2


3


4


5


1990-91

2,67,632

2,46,560

21,072

7.9

1991-92

2,88,974

2,66,432

22,542

7.8

1992-93

3,05,266

2,79,824

25,442

8.3

1993-94

3,23,252

2,99,494

23,758

7.3

1994-95

3,52,260

3,27,281

24,979

7.1

1995-96

3,89,721

3,54,045

35,676

9.2

1996-97

4,13,490

3,65,900

47,590

11.5

1997-98

4,24,505

3,90,330

34,175

8.1

1998-99

4,46,584

4,20,235

26,349

5.9

1999-2000

4,80,430

4,50,594

29,836

6.2

2000-01


5,07,213


4,67,401


39,812


7.8


Source: Annual Reports, Ministry of Power, Government

of India, various issues.

Although entry of the private sector has led to some increase in service expansion, the rollout of services has not begun as quickly as expected. The existing gaps in the telecom sector have implications for the technical efficiency and productivity growth in the industrial sector.

3.76 The role of public capital in infrastructure in explaining the growth in productivity and output is well recognised. Keeping in view the stylised facts on the performance of infrastructure and demand-supply mismatches, the role of public capital in mitigating these gaps needs some assessment. With a view to exploring the role of public capital in infrastructure in explaining the output growth, a logarithmic form of the Cobb-Douglas production function for the manufacturing sector is estimated with public capital stock as an additional argument (Chart III.42). The public capital in infrastructure emerges as the most dominant factor in explaining output growth in the manufacturing sector with a positive elasticity of 0.76. These estimates highlight the role of public infrastructure investment in sustaining higher output growth in the long term.

The Sources of Industrial Growth

3.77 The growth process of the industrial sector during the decade of the 1990s has underscored the need for identifying the sources of growth for achieving higher output growth over the medium term. The classical growth theories recognised the role of physical capital accumulation as a determinant of growth. The Harrod-Domar model of growth emphasised the influences of physical capital and savings in creating effective demand as well as productive capacity in explaining the growth process. The role of productivity in the growth process was recognised by Solow (1957) in a growth accounting framework. Evolution of the endogenous growth theory towards the end of the 1980s drew attention to the role of continuous advances in human skills and technology along with factor accumulation to off-set the dampening effect of diminishing returns in sustaining the growth process.

3.78 Factor productivity as a source of industrial growth and trade competitiveness of nations has been well recognised. The total factor productivity (TFP) growth, on an average, accounted for nearly 50 per cent of the output growth for a group of developed countries, whereas the contribution of the same in the case of developing countries was only 31 per cent (Chenery, Robinson and Syrquin, 1986). This was, to a large extent, on account of a much faster growth of factor inputs in developing economies than in the developed economies (Pack, 1988). More recent empirical studies on sources of output growth in developing countries suggest that about 60-70 per cent of per capita growth is explained by capital accumulation, while human capital accounts for 10-20 per cent and the remaining on account of improvement in the total factor productivity (IMF, 2000). Notwithstanding varying evidence, some empirical work on the contribution of factor productivity to output growth in the East Asian economies reveals that the TFP accounted for about 50-55 per cent of the output growth. These diverse findings lead to a broad inference that the growth experience is country specific. It emerges, however, that while capital accumulation is a critical factor for achieving rapid growth, other factors are also important.

3.79 In the Indian manufacturing sector, the analysis of the sources of growth between 1959-60 to 1985-86 indicates that overall long-term annual growth of 5.3 per cent in value added in the manufacturing sector was associated with rapid growth of capital (8 per cent), moderate growth of employment (3 per cent) and negative growth in TFP at 0.4 per cent (Ahluwalia, 1991). These findings suggest that till the mid-1980s, the entire growth was led mainly by the capital accumulation and the contribution of productivity growth was negligible, reflecting the low efficiency of factor use. A synoptic view of the studies conducted on the Indian manufacturing sector indicates that even though an increasing trend in labour productivity has been witnessed in case of most of the industry groups, the level of labour productivity in India is abysmally low and its convergence to international standards seems to be a difficult proposition in the near future (Table 3.26).

3.80 In these studies, factor productivity growth obtained through the single deflation approach is lower than the double deflation approach, implying that the relative prices of inputs and output have increased over time7. Firm level panel evidence, however, indicates a strong evidence of a decline in productivity growth rates in the 1990s as compared with the 1980s. Productivity growth of firms in the manufacturing sector could have been adversely affected by the poor performance of the efficiency component in productivity (NCAER, 2001). For small-scale industries, there is a decline in labour productivity growth during the1990s (1990-96) to 3.7 per cent from 6.2 per cent in the 1980s and a decline in capital productivity growth to -1.6 per cent from 2.6 per cent during the same period (SIDBI, 2000).

Table 3.26 : Trends in Factor Productivity in the Manufacturing Sector in India- Alternative Estimates

(Per cent per annum)


Study

Period Covered

TFPG (Single

TFPG(Double




Deflation Method)


Deflation Method)



1


2


3


4


Brahmananda (1982)

1950-51 to 1980-81

-0.2

Ahluwalia (1985)

1959-60 to 1979-80

-0.6

Ahluwalia (1991)

1959-60 to 1985-86

-0.4

Balakrishnan and Pushpangadan (1994)

1970-71 to 1988-89

0.5

3.1

Majumdar (1996)

1950-51 to 1992-93

1.7*

Rao, M.J. (1996)

1973-74 to 1992-93

1.3@

2.2

Pradhan and Barik (1998)

1963-64 to 1992-93

0.6

Trivedi et al (2000)

1973-74 to 1997-98

1.95

3.7


NCAER (2001)


1980-81 to 1996-97


-0.05 to 0.04#



*

The estimates are reported only for the sub-period 1973-74 to 1992-93, out of the total period of the study

spanning 1950-51 to 1992-93.

@ Growth rate of TFP is obtained indirectly from the estimates of TPG.

#

Represent different econometric estimates of TFPG based on the firm level panel data set.

3.81 In the context of the growing degree of openness of the economy, the level and growth rates of productivity of labour and capital have to be compared with some benchmark levels. Comparative levels of value added per person in manufacturing in 1987 revealed that for India, the ratio was only 7.2 per cent of that of the United States and 10.3 per cent of that of the West Germany (Ark, 1996). This indicates that the level of productivity in India is relatively low and would require considerable improvement to achieve convergence to the international levels.

3.82 Sources of productivity growth in India could broadly comprise infrastructure, reorientation in the trade and industrial policies, foreign direct investment along with technology transfers, reforms in the labour market to impart necessary flexibility and supply response, changes in exit procedures through appropriate legislation on industrial sickness, the Companies Act and industrial disputes and bankruptcy laws. The supply side response would depend upon raising investment in infrastructure, hastening of disinvestment process and restructuring of public enterprises.

Technological Progress and Industrial Growth

3.83 Productivity growth is the combined effect of pure technical progress as well as the improvement in the overall efficiency of factor use. Technological change involves an improvement in technology, knowledge and work efficiency. Technological progress is recognised as the key to maintaining productivity growth, and the driving force behind economic growth (Solow, 1957).

3.84 Attempts have been made in recent years to examine the role of technology expenditure on growth of productivity and output. Empirical findings support the view that science and technology play a critical role in the growth process of major industrialised countries (Sveikauskas, 1983). The hypothesis that research and development (R&D) fosters productivity growth through advances in technology has also gained support at the empirical level (Scherer, 1983). While explaining the differences in growth rates of labour productivity in the industrialised countries, it is found that technological development in the form of the growth of R&D expenditures and technology gap explain the growth rate of labour productivity in the industrial countries (Rensman and Kuper, 2000). In the case of newly industrialised countries, rapid growth in productivity and output is found to be the outcome of the ability to acquire advanced technology (Rothwell and Zegveld, 1985). These findings have important implications for the developing countries aiming for higher productivity growth since technological progress is based mainly on the import of technology.

3.85 Given that the Indian firms do not spend much on R&D, import of capital goods and machinery has had a significant impact on corporate performance. Capital deepening (i.e., rise in capital-output ratio) was not found to be favouring the performance of larger firms, implying that up to a certain point, capital deepening might help growth and profits, beyond that further increases in the capital-sales ratio prove counterproductive to growth and profits (Siddharthan, 1992). These empirical findings, though relate to the pre-liberalisation period, lend support to the role of technological progress in enhancing productivity and growth. In the context of the technology gap in Indian industry during the 1980s, the per firm expenditure on technology imports revealed a steady rise, while the R&D expenditure continued to remain meagre (Swaminathan, 1993).

3.86 The impact of the reform process on technological improvement can be evaluated by comparing these indicators to the outcome of the 1990s. In the case of public limited companies in India, the ratio of R&D expenditure to their total output was as low as 0.08 per cent in 1985-86, increasing to 0.31 per cent in 1990-91 and remaining almost at that level in 1999-2000. This reflects considerably low level of R&D expenditure in the production process as compared with industrialised countries. One of the factors for inadequate growth in R&D expenditure during the post-liberalisation period is the liberalisation of technology import and foreign investment policy (Table 3.27).

3.87 The sectoral break up of R&D expenditure suggests that the maximum investments are recorded in chemical and pharmaceutical groups, followed by engineering, motor vechicles, transport and information technology. The R&D expenditure on electricity generation and supply witnessed sharp decline during the 1990s. The low level of R&D expenditure in the Indian industry may have implications for productivity growth, competitiveness and export performance; however, the unfavourable impact can be, to a certain extent, mitigated through technology imports and foreign collaboration.

Table 3.27 : Research and Development Expenditure in Public Limited Companies

(Per cent of total output)



Industry


1985-86


1990-91


1995-96


1999-2000



1


2


3


4


5


Aggregate

0.08

0.31

0.28

0.29

1.

Tea,Sugar, Jute

0.02

0.09

0.1

0.04

2.

Cotton Textile & Rayon

0.01

0.05

0.13

0.08

3.

Engineering, Motor vehicles, Transport etc.

0.11

0.38

0.31

0.31

4.

Chemicals & Pharmaceuticals etc.

0.08

0.33

0.39

0.39

5.

Cement

0.04

0.16

0.11

0.12

6.

Rubber and Paper Products

0.05

0.2

0.2

0.23

7.

Electricity Generation and Supply

-

0.53

0.07

0.01

8.


Information & Technology


-


-


-


0.28


Source: Selected Financial Statistics of Public Limited Companies, RBI

3.88 An important feature of technological progress in India since 1991 has been the growth in foreign collaborations. The Indian experience shows that FDI has increasingly moved into priority areas such as power generation, oil refining, telecommunications, electronics and food processing, i.e., the sectors where domestic investment is inadequate. The trends in FDI inflow reflect an increasing trend in the 1990s; however, FDI inflows to India continue to remain marginal when compared with the aggregate flow to the emerging economies and the gap between FDI approvals and actual inflows continues to remain wide (Table 3.28).

Table 3.28 : Number of Foreign Collaboration Approvals and FDI


Year

No. of

FDI in India

FDI to All

FDI to India as

Foreign

(US $ Million)

Developing

% of FDI to all

Collaboration

Countries

Developing


approvals



(US $ Million)


Countries


1


2


3


4


5


1981

389

92

12293

0.7

1986

957

118

9482

1.2

1991

950

74

35494

0.2

1992

1520

277

47130

0.6

1993

1476

550

66574

0.8

1994

1854

973

90036

1.1

1995

2337

2144

106990

2.0

1996

-

2426

131451

1.8

1997

-

3577

172571

2.1

1998

-

2635

176764

1.5

1999

-

2169

185408

1.2

2000


-


-


178004


-


Source : Reserve Bank of India and Global Development Finance, World Bank.

3.89 There is no empirical evidence of complementarity between technology import and domestic technological efforts and export performance of FDI firms (Subrahmanian, et al,1996). Accordingly, strategic interventions by using the country's comparative advantage in R&D and other inputs are considered necessary to strengthen linkages between multi-national corporations and Indian firms for domestic technological progress, and non-equity forms of tie-ups can be used for acquiring advanced technologies with greater scope for local adaptations, improvements and innovations.

3.90 Apart from the state of technology, efficiency improvements, which are endogenous to the firm, are critical in achieving outward shifts of the production frontier. The mean technical efficiency of Indian firms taken together seems to have declined in the 1990s as compared with the pre-reform period, particularly in the manufacturing sector (NCAER, 2001).

3.91 Cyclical variations in activity superimposed upon a persistent slowdown, underutilisation of capacity in various industries and the tightening of structural impediments have combined to produce a drag on industrial growth. A higher level of output growth can be sustained only by considerable improvements in the existing levels of infrastructure, particularly telecommunication and power. FDI can be an important conduit for technology transfer in India, although it currently operates only at the margin. In the case of public enterprises, productivity improvement would essentially require setting a clear path for restructuring and privatisation. The institutional environment in which the public sector operates would require significant reforms. A conducive environment for industrial growth hinges upon the rationalisation of labour legislations, changes in exit procedures through appropriate legislation relating to industrial sickness, and modifications in the Companies Act and industrial disputes and bankruptcy laws to impart necessary flexibility and supply response in the labour market. These measures would reduce the implicit cost of labour in production process.

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