Productivity in Indian Chemical Sector
An Intra-Sectoral Analysis
The present study attempts to test the assumption of homogeneity of the sub-sectors in an industry with particular reference to the Indian chemical industry. The impact of economic reforms on the productivity levels of an industry at the aggregate and sub-sectors level do vary significantly. While the net impact of the reform process on total factor productivity growth was found to be poor at the aggregate level, the sub-sectors – drugs and pharmaceuticals and paints and varnishes, basic chemicals and dyes and dye stuff industries – greatly benefited from the liberalisation process. Within the sub-sectors, the worst affected was the fertiliser industry as the TFPG declined significantly in the post-reform period. In the same way, the productivity differentials are found at the firm level as well. While small firms experienced a fall in productivity levels during the post-reform period, the large firms could raise productivity. The differences in the productivity levels of small and large firms and among the sub-sectors within an industry reveal the heterogeneity of the industry.
T SAMPATH KUMAR
T
The process of liberalisation can be linked to the manufacturing productivity. The Indian government started to implement a wide range of economic reforms on various fronts to make domestic industries more efficient and internationally competitive. Indian firms were expected to respond positively to these measures. The liberalisation process was to expose firms to international competition and force them to introduce new methods of production, import quality inputs, capital equipment or technology and compel them to improve their efficiency.
Indian firms experienced the reform process since 1991 and we now have enough data to estimate the impact of globalisation and liberalisation policies on Indian industry. There are mixed results revealed by earlier studies. Majumdar (1996) and Sharma (1999) estimated positive impact of liberalisation policies on the factor productivity. But Balakrishnan et al (2000) and Das (2004) found that trade liberalisation did not yield to the productivity growth in the Indian manufacturing sector. The earlier studies were conducted for the aggregates of an industry with an assumption that all the firms in an industry behave alike and therefore industry level characteristics could be attributed to all the firms operating in that industry. But Siddharthan (2004) argues that during the period of liberalisation, new firms with more advanced technologies are likely to enter into industry and the existing firms are expected to develop a strategy to meet the challenges from the new entrants, in particular multinational enterprises (MNEs). Under such a situation, the assumption of homogeneity becomes invalid.
It is found from the earlier studies that all the firms belonging to one industry do not behave in a similar pattern. In an industry consisting of a variety of firms with significant differences in their size, ownership, knowledge and access to technology, the liberalisation process would result in gainers and losers and there will be a productivity gap among firms in an industry. It is in this context that the present study attempts to estimate the trends in the growth of total factor productivity of Indian chemical industries at the sub-sectoral level. The Indian chemical industry consists of five major sectors, namely, (a) fertiliser,
(b) drugs and pharmaceuticals, (c) basic chemicals, (d) paints and varnishes, and (e) dyes and dyestuffs. The study proceeds to estimate the productivity variations in these sub-sectors at the sectoral and firm level caused by the liberalisation process.Thispaper is divided into the following sections: Section I
Economic and Political Weekly September 30, 2006
provides the data and methodology, Section II estimates factor productivity growth at the sectoral level, Section III deals with productivity differentials at firm level and Section IV presents summary and conclusion.
I Data and Methodology
This paper covers a period of 22 years from 1980-81 to 2001-02. The entire period is divided into two phases as prereform period (1980-81 to 1990-91) and post-reform period (1991-92 to 2001-02). Such a classification of the study period is essential to find the impact of economic reforms on the improvements of factor productivity. This paper attempts to estimate the total factor productivity of chemical industries in India at the sub-sectoral level. The estimation of productivity at the aggregate, sub-sectoral and firm level will reveal the performance of this industry and the homogeneity of the subsectors in relation to the liberalisation process.
The total factor productivity growth (TFPG) is estimated using Translog model with three inputs, viz, labour (L), capital (K) and the intermediate inputs (R) (raw materials consumed).
The Translog model of productivity used in the estimation of TFPG is obtained as below; TFPG = ΔP(t)/P(t) – [(½ * (SL (t-1) + SL (t)) * (ΔL(t)/L(t)) + (½ *(SK (t-1) + SK (t)) *(ΔK(t)/K(t)) +
(½ * (SR (t-1) + SR (t)) *(ΔR(t)/R(t)) ] where, ΔP (t)/P (t), ΔL (t)/L (t), ΔK (t)/K (t) and ΔR (t)/R (t) are approximated by corresponding logarithms of ratios of variables over successive year.
ΔP(t)/P(t) ~ LN [ΔP(t)/P(t-1)] = LN P(t) – LN P(t-1) = ΔLNP(t) ΔL(t)/L(t) ~ LN [ΔL(t)/L(t-1)] = LN L(t) – LN L(t-1) = ΔLNL(t) ΔK(t)/K(t) ~ LN [ΔK(t)/K(t-1)] = LN K(t) – LNK (t-1) = ΔLNK(t) ΔR(t)/R(t) ~ LN [ΔR(t)/R(t-1)] = LN R(t) – LNR (t-1) = ΔLNR(t)
Description of Data and Variables
The present study is based on the unpublished firm level data on the public limited chemical industries obtained from the Company Finances Division of the Reserve Bank of India (RBI). Various studies have used RBI firm level data in their analysis [Srivastava 1996; Feinberg and Majumdar 2001]. The study is made for the five major sub-sectors of the Indian chemical sector, viz, fertiliser, drugs and pharmaceuticals, basic chemicals, paints and varnishes and dyes and dyestuffs. These sub-sectors together constitute nearly 71 per cent of the total chemical sector in India (as per the RBI data in 2001-02). According to the industry codes given by the RBI, the value of each variable was summed up for each sub-sector for the period under consideration. The gross value of production has been taken as a measure of output. Generally, the TFP growth estimates based on value added terms are overestimated as they ignore the contribution of intermediate inputs on productivity growth [Sharma 1999], hence a third variable of intermediate inputs (consumption of raw materials) has been included in the function. Pradhan and Barik (1999) argued that the output, instead of value added, appears to be the appropriate choice of TFPG estimation in India. To offset the influence of price changes, output was deflated by the wholesale price index (1980-81=100) of the corresponding sub-sectors and the raw materials by the WPI of intermediate goods with the same base. The total number of workers and the gross fixed assest are considered measures of labour and capital inputs. Gross fixed capital was deflated by the WPI of machinery and machine products (base 1980-81 =100), thus the real gross fixed capital was included in the function. Since the RBI does not publish the employment details, the average wage rate of the industry was calculated from the Annual Survey of Industries (ASI) data for all the years of the study. The average wage rate was estimated by dividing the total emolument of the industry by the number of workers in that industry [Goldar and others 2004]. This average wage rate obtained from the ASI data was then used to divide the total wages and salary of each sub-sector to estimate the number of workers at the sub-sectoral level. Further the size of the firm is determined on the basis of number of workers. From the data set of RBI, the firms which were present during the entire period of study were separated and grouped as small and large firms. Since there are some differences in size distribution across sectors, the firms are defined “small” (“large”) when the level of employment is less (more) than the geometric mean level of employment of the sector in which the firm operates [Sak and Taymaz 2004].
II Estimates of Factor Productivity Growth
Factor productivity growth rates are computed for the five major sub-sectors of Indian chemical industries. Theoretically there appears to be a relationship between policy measures and productivity growth, although the empirical findings for some developing countries are ambivated. Ahluwalia (1985, 1991) and Parades (1994) found a significant improvement in the productivity growth while Kajiwara (1994) for Philippines and Urata and Yokota for Thailand (1994) estimated a fall in the manufacturing productivity following liberalisation. The estimated annual and mean growth rates of TFP are presented in Tables 1 and 2. Wide variations in the magnitude of TFPG are found in the estimation. The estimated TFPG of the Indian chemical sector at the aggregate and sub-sectoral level reveals contradictory rates of productivity growth. The fertiliser industry recorded positive rates of TFP throughout the study period except during 1991-92 (-1.327) and 1997-98 (-0-022). As against this, the drugs and pharmaceutical industry recorded negative productivity growth rates except in 1999-2000, 2000-01 and 2001-02. During these periods there were positive growth rates of total factor productivity. The basic chemical industry registered positive and negative productivity growth rates both in the pre- and post-reform periods. Paints and varnishes industry have positive TFPG in 1986-87 (1.084), 1997-98 (0.156) and in 2001-02 (0.005). But the dyes and dye stuff industries have experienced positive TFPG mostly in the post-reform period. At the aggregate level also the negative trend in the TFPG is observed during the period of study. Pradhan and Barik (1999) are of the view that the low and negative trend in the TFPG is a common feature in most of the developing countries. They also estimated a negative TFPG for the Indian chemical sector in their study. From this analysis, it could be observed that the impact of the reform process is mixed even within a particular sector.
Economic and Political Weekly September 30, 2006
In order to understand the influence of economic reforms on TFPG, the mean growth rates of TFP were estimated for the pre- and post-reform period and are presented in Tables 1 and 2. The estimated mean TFPG for the aggregate and the sub-sectors of the Indian chemical industry reveal a contradictory picture with the positive and negative rates. For the period 1980-81 to 2001-02, the mean TFPG was positive for fertilisers (0.847) and dyes and dye stuff (0.016) while it was negative for drugs and pharmaceuticals (-0.175), basic chemicals (-0.126) and for paints and varnishes, it was -0.490. At the aggregate level, the TFPG was also negative at -0.199 during this period.
During the pre-reform period (1980-81 to 1990-91), as shown in Table 1, invariably all the major sub-sectors have recorded negative TFPG except the fertiliser industry with a positive productivity rate of 0.903. The negative rates varied among the other sectors, viz, drugs and pharmaceuticals (-0.234), basic chemicals (-0.132), paints and varnishes (-0.819) and dyes and dye stuff industry (-0.111).
It could be noticed from the mean TFPG estimated during the post-reform period that the reform process yielded mixed results on the productivity levels of the sub-sectors of Indian chemical sector. The economic reforms started to yield positive results in drugs and pharmaceuticals, basic chemicals and paints and varnishes industries. It is visible from the estimated mean TFPG that there is a significant drop in the extent of negative TFPG when compared to that in the pre-reform period. In the case of dyes and dye stuff industries, the negative productivity growth estimated in the pre-reform period (-0.111) has even turned out to be positive (0.144) in the post-reform period. As against this, the impact of economic reforms was found to be negative in the case of the fertiliser industries. The mean growth rate of TFP of this sector, though positive, declined to 0.791, when compared to the pre-reform period (0.903). But at the aggregate level, the negative rate further worsened to -0.227 from -0.171 estimated in the pre-reform period. From the mean growth rates of TFP, it can be stated that the net impact of economic reforms was quite conducive to the sub-sectors of the Indian chemical industries except for the fertiliser industry. But the impact varied in its magnitude depending on the nature of the industry.
III Firm Size and Productivity Differentials
The differences in productivity growth at the firm level will reveal the homogeneity/heterogeneity of a sector in an industry. Industry becomes more productive when the firms operating in the industry adopt new and better methods of production. The assumption of homogeneity of an industry holds good when all the firms in an industry tend to have a similar pattern of productivity changes. But due to the differences in its size, particularly in the changing market environment, the productivity changes tend to vary. In an open market, some firms thrive while others disappear. There are, within the industry, winners and losers. The notion is that the inefficient firms can perhaps survive in a protected economy but will perish in a more competitive environment [Levinsohn and Amil 1999]. Therefore, when the economy becomes more competitive, the productivity differentials widen depending on the size of the firms operating in the industry. Indeed, there appears to be a fact that there exist productivity differentials between small and large scale enterprises independent of the sector and economy. Gulbiten and Taymaz (2000) in their study found that there are substantial productivity differentials between small-sized enterprises and large corporations independent of sector and economy, and the productivity differentials decrease by economic development but do not vanish even in the developed countries.
Earlier studies have concluded that small firms are less productive than the large ones. The productivity differentials between small and large firms seem to originate from number of sources. You (1995) and Taymaz (2004) found that technological factors (economies of scale) are the principal determinants of such differences. Gulbiten and Taymaz (2000) explain that the small firms may be as efficient as large firms but operate less productively than the larger firms since they may not be exploiting economies of scale. Secondly, small firms may be maximising profits with existing capital, labour and technology, yet they may be operating less productively than the larger firms because they utilise older technologies and low quality inputs. Further, the existence of wage differences may also result in productivity differentials between small and large firms. For example, small firms tend to pay lower wages than their counterparts. Although, small firms seem to be advantageous in terms of labour cost they face, lower wages are usually accompanied by less skilled labourers and the disadvantage of utilising cheap unskilled
Table 1: Trends in the TFPG of Indian Chemical Sector (Pre-Reform Period)
Year Fertiliser Drugs and Basic Paints Dyes and Chemical Pharma-Chemicals and Dye Stuffs Sector ceuticals Varnishes
1980-81 0.903 -0.070 -0.237 -0.665 -0.107 -0.219 1981-82 0.391 -0.337 -0.332 -1.074 -0.057 -0.764 1982-83 0.667 -0.293 -0.253 -1.237 -0.064 -0.257 1983-84 1.987 -0.517 -0.402 -0.792 0.447 0.140 1984-85 0.257 -0.156 -0.123 -0.844 -0.477 -0.174 1985-86 0.176 -0.200 0.446 -1.098 -0.030 0.076 1986-87 1.289 -0.209 0.014 1.084 0.074 0.070 1987-88 1.976 -0.119 0.014 -3.342 -0.203 0.092 1988-89 0.112 -0.159 -0.217 -0.767 -0.126 -0.532 1989-90 1.222 -0.102 -0.142 -0.056 -0.515 -0.181 1990-91 0.951 -0.408 -0.218 -0.216 -0.163 -0.137 Mean 0.903 -0.234 -0.132 -0.819 -0.111 -0.171
Table 2: Trends in the TFPG of Indian Chemical Sector (Post-Reform Period)
Year | Fertiliser | Drugs and | Basic | Paints | Dyes and | Chemical |
---|---|---|---|---|---|---|
Pharma- | Chemicals | a nd | Dye Stuffs | Sector | ||
ceuticals | Varnishes | |||||
1991-92 | -1.327 | -0.217 | -0.743 | -0.437 | -0.787 | -1.741 |
1992-93 | 0.986 | -0.178 | -0.295 | -0.261 | -0.153 | -0.313 |
1993-94 | 1.037 | -0.045 | -0.335 | -0.405 | 0.302 | 0.222 |
1994-95 | 0.526 | -0.365 | -0.361 | -0.142 | -0.112 | -0.411 |
1995-96 | 0.987 | -0.143 | 0.194 | -0.292 | 0.231 | -0.143 |
1996-97 | 1.109 | -0.043 | -0.046 | -0.110 | 0.204 | -0.113 |
1997-98 | -0.022 | -0.111 | 0.055 | 0.156 | 0.363 | 0.355 |
1998-99 | 0.658 | -0.234 | 0.262 | -0.183 | 0.103 | -0.818 |
1999-2000 1.815 | 0.008 | -0.190 | -0.032 | 0.244 | 0.189 | |
2000-01 | 1.177 | 0.022 | -0.008 | -0.078 | 0.156 | -0.129 |
2001-02 | 1.755 | 0.034 | 0.156 | 0.005 | 1.029 | 0.404 |
Mean | 0.791 | -0.116 | -0.119 | -0.162 | 0.144 | -0.227 |
Overall | ||||||
m e a n | 0.847 | -0.175 | -0.126 | -0.490 | 0.019 | -0.199 |
Economic and Political Weekly September 30, 2006
labourers might outstrip its cost advantage, reducing the small firms’ productiveness.
The underlying facts of the extent of productivity differentials of small and large firms in an industry have become a measure of homogeneity of the industry concerned. Within this purview, the study has made an attempt to estimate the TFP growth of the different sub-sectors of the Indian chemical industry at the firm level during the period of study.
Table 3 presents the estimated mean TFP growth rates of small and large firms in each sub-sector of the Indian chemical industry. The obtained mean TFPG estimates show that the small firms have lower productivity growth than the large firms. Further, small firms in all the sub-sectors are found to have a lower productivity level than their sectoral mean levels of productivity estimated for the entire period of study (shown in Table 2) except the paints and varnishes sector in which the TFPG of small firms is marginally higher at -0.111 than its sectoral mean rate of -0.490. On the contrary, the large firms in each sub-sector have higher rates of TFP except in the fertiliser sector where there is a marginal fall in the mean rate of TFPG of large firms at 0.775, when compared to the sectoral mean rate of 0.847.
From Tables 1 and 2, it can be noticed that when the chemical sector as a whole witnessed a decline in the productivity level during the post-reform period, the sub-sectors, other than fertilisers, marked an improvement. But the picture was different at the firm level. Invariably, the small firms in all the sub-sectors experienced a significant decline in productivity growth rates during the post-reform period except in the drugs and pharmaceutical sector in which they recorded a marginal improvement to -0.399 from -0.432 estimated for the pre-reform period. Urata and Kawai (2001) found that larger firms normally have higher total factor productivity levels and growth than smaller firms. There are, however, some exceptions to this pattern where small firms tend to have an edge due to two distinctive features of small firms, viz, the practice of sub-contracting and the use of external patents. Whereas in the case of large firms, there was a significant improvement in the TFPG of all the sub-sectors except fertilisers in which both small and large firms experienced a decline in the productivity growth during the post-reform period. It is perhaps due to the increase in the factor inputs. Schumachar and Jayant (1999) noted that following liberalisation, output declined considerably and thereby decreased the productivity of the fertiliser industry in the country. They also found that increase in the material input was the driving factor for productivity losses in the Indian fertiliser sector.
A simple comparison of the productivity differentials between small and large firms at the sub-sectoral level reveals that both in the pre- and post-reform period, the small firms are found to have lower productivity levels than the larger ones. The higher productivity levels of large firms compared to the small firms may be due to the better exploitation of economies of scale by them. Further, the large firms are able to use high quality inputs, better technologies and make huge investment on R&D activities. As a result, they could get greater returns from their increased innovative measures. Similarly, one more argument can be put forth for the comparatively better productivity performance of large firms. The liberalisation measures have made the market environment more competitive. Under highly competitive market conditions, the small firms failed to compete while large firms could manage with the adoption of advanced technologies of production. Tybout (2000) points out a fact that there exists a discrimination of small and large firms in the financial market also. Especially in a country where private sector credit is scarce and rationed, financial institutions discriminate against small and large firms thereby increasing the cost conditions of small firms and thus decreased their productivity levels.
IV Findings and Conclusion
The simple analysis made to estimate the intra-industry productivity variations in the Indian chemical sector during the period 1980-81 to 2001-02 reveals contradictory results at the aggregate, sectoral and firm level. On the whole the impact of economic reforms on total factor productivity at the aggregate level was poor as the negative mean rate of TFPG estimated in the pre-reform period further increased in the post-reform period. But this declining trend is not applicable to all the sub-sectors. The estimated measures of TFPG at the sectoral level show that the TFPG of drugs and pharmaceuticals, paints and varnishes, basic chemical and dyes and dye stuff industries are better in the post-reform period as there is a change in the sign or a decline in the extent of negative productivity growth. But in the case of the fertiliser industry, the liberalisation process is found to have its adverse impact as there is a fall in the total factor productivity growth during the post-reform period. At the firm level, though the small firms are less productive than the large firms, the small firms in the drugs and pharmaceutical and paints and varnishes sector experienced a marginal increase in the productivity growth while large firms in the fertiliser sector marked a decline during the post-reform period.
Thus, the pattern of total productivity growth showed mixed trends in the Indian chemical sector at the intra-sectoral level. To sum up, TFPG itself witnessed a better performance in the post-reform period at the sub-sectoral level which is different from the industry average. When firm size is considered, in both the periods, the small firms have lower levels of productivity growth than the larger firms. Irrespective of the sectors, the large firms, due to the better exploitation of economies of scale and the ability to adopt new methods of production, are more productive than the small ones. Tybout (2000) suggested that small firms should adopt more innovative measures to make them more efficient and productive. That is, the innovation initiated either to survive or to create their own market niches appears to be effective in increasing efficiency. With the present economic environment, these results cannot be finalised. There
Table 3: Firm Size and Productivity Differentialsin the Indian Chemical Sector
Firms Period Fertiliser Drugs and Basic Paints Dyes and Pharma-Chemicals and Dye Stuffs ceuticals Varnishes
Small Pre-reform 0.340 -0.432 -0.168 -0.286 -0.058 firms Post-reform 0.266 -0.399 -0.204 0.065 -0.112 Overall 0.303 -0.416 -0.186 -0.111 -0.085 Large Pre-reform 0.986 0.133 0.29 -0.102 0.093 firms Post-reform 0.563 0.545 0.486 0.39 0.645 Overall 0.775 0.339 0.388 0.144 0.369
Economic and Political Weekly September 30, 2006 are time lags in the realisation of the final result of the reform measures like foreign capital inflows, R&D, technology transfers and the other spillover effects exerted by the foreign entrants. One important conclusion that can be drawn from this analysis is that this study confirms the results of Liu (1993), Liu and Tybout (1996) and Bartelsman and Doms (2000) that the assumption of homogeneity, that is all the firms in an industry are alike, might not be valid. The variations in the growth rates and the signs prove that the heterogeneity conditions prevail in the industry and under such conditions, liberalisation would result in gainers and losers in an industry. It is suggested that while making policy decisions on the basis of aggregates, the consideration of intra-sectoral variations will provide more valuable decisions.

Email: tsampath_136@yahoo.com
[I am grateful to my guide S Jayaraj, who proffered me with valuable suggestions and corrections for the improvement of this work. I sincerely also acknowledge the assistance rendered by K Pushpangadan, who cleared my doubts in the estimation of productivity. I am also grateful to the anonymous referee for his comments and suggestions on an earlier version of this paper.]
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RESERVATIONS IN HIGHER EDUCATION
June 17, 2006
Redesigning Affirmative Action: Castes and Benefits in Higher Education – Satish Deshpande, Yogendra Yadav
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Assumptions and Arithmetic of Caste-Based Reservations – Rohini Somanathan
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Merit of Reservations – Kancha Ilaiah
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