WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR: THEORY AND EVIDENCE

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1 The Indian Journal of Labour Economics, Vol. 50, No. 1, 2007 WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR: THEORY AND EVIDENCE Ashok Mathur and Sunil Kumar Mishra* This paper is essentially an empirical one but before coming to the Indian context, it presents a broad sweeping view of the place occupied by wage and employment issues in the evolution of economic thought. This paper identifies six types of approaches to wages and employment in the literature. In the background of this theoretical foray, some variables have been identified which may be drawn upon for studying the factors that have influenced the level of wages in relation to the level of employment in India. Before coming to this explanatory empirical exercise, the second part of this paper analyses the all-india trend in wages, employment and some related variables. This has been undertaken, first for the organised industrial sector and then for the unorganised industrial sector, to the extent permitted by the available data. The third part of this paper examines the strength of relationship of the wage rate and its changes with the four identified variables. This exercise has been carried out at three levels. At the first level, regional data have been analysed by examining cross-sectional evidence in respect of the identified variables on the basis of unorganised manufacturing in 17 major states. At the second level, similar analysis is undertaken for organised manufacturing in the cross-section of the same states. Finally, the analysis is conducted at the all-india level by using inter-temporal series for organized manufacturing. The regression results show a strong determinant influence only in case of a limited number of variables. I. THEORETICAL PRELUDE Wages and employment are two variables which vitally affect the economic well-being of a substantial segment of population of any nation. Before coming to the empirical part of this paper, it may be worthwhile to take a look at the place occupied by wages and employment in major schools of economic thought. If one takes a broad sweeping view of economic theory as it has evolved over time, one can discern at least six types of approaches to the issues of wage and employment determination. In an inter-temporal sequence, one can identify them as the Classical School, Marxian version of Classical thought, the Neo-Classical or the so-called Marginalist School, the Keynesian School and its Post-Keynesian empirical extension in the form of the Phillips Curve. Finally, the role of wage negotiations in wage determination is examined. Classifying the approaches into six groups does not imply that there is complete uniformity of approach within each group. There are sub-variants within each group but the hallmark of each school of thought can be represented by certain underlying common features or some dominant variant within each school. An attempt is made to capture these dominant commonalities within each school as also the major differences between the schools, in this paper. However, since there is no universally accepted and standardised representation of * Ashok Mathur, formerly at Jawaharlal Nehru University, is currently a Visiting Professor at the Institute for Human Development. Sunil Kumar Mishra is at the Institute for Human Development. We are very grateful to D.N. Reddy for his comments on an earlier version of this paper and to Balwant Singh Mehta for some of the technical analysis.

2 84 THE INDIAN JOURNAL OF LABOUR ECONOMICS divergent sub-variants within each school, one sometimes finds certain differences among different scholars capturing the essentials of different schools. To that extent, the exposition of different approaches given below may not be found to be in complete conformity with the views of different scholars. Among major contributors to the Classical stream of thought, starting with Adam Smith and Ricardo, some common threads are visibly evident. First, there is an element of long-term wage fixity hovering around the subsistence level, which has been variously referred to as the natural price of labour or minimum subsistence level wages. Subsistence level, however, does not necessarily imply a bare physiological minimum level of consumption essential for human existence. Different interpretations of this level sometimes allow certain basic comforts or certain essential expenditure other than that incurred on food alone. There could be short-term deviations in both directions positive ones during phases of high capital accumulation, or in the negative direction during phases of rapid population growth. Secondly, within the Ricardian framework, which is the most neatly formulated version of the Classical School, wages are viewed as a part of interaction between the long-term dynamics of the growth of an economy and distribution of the total product among labour, capitalist farmers and landowners. Since wages are assumed to be given at a minimum subsistence level, with expansion of the economy, total wages expand in proportion to the growing absorption of labour into the productive process. The rate of profit, which gets equalised through competition among the capitalist farmers as well as among manufacturers, goes on getting reduced as the margin of cultivation shifts to lands of lower fertility with the expansion of population. Since the share of profits in the national product goes on reducing through the competitive process and share of wages increases only in proportion to labour employed, the share of rent to the landowners goes on rising till the attainment a of stationary state, in which the profit rate dwindles to zero. Wages can thus be viewed as being determined essentially by the needs of human existence, with some temporary variations around it. While Classical thought is quite sanguine in its view on the wages front, in respect of the level of employment, it presents a rather rosy picture through the operation of the Say s Law of Markets. As is well known, given the assumptions underlying the Say s Law of Markets, J.B. Say s postulate that supply creates its own demand, would result in automatic achievement of full employment, barring minor deviations on account of aberrations like frictional unemployment. However, Say s formulation does not appear to be in exact conformity with the conclusions which emerge from the Ricardean analytical framework in which the long-term path of employment expansion would be governed by surplus generated in the hands of the capitalists, who are taken to be members of the only class that undertakes capital accumulation. The Marxian School carries over certain features of Classical thought which incorporates the above-mentioned characteristics of the wages paid to labour and profits which arise in the hands of the capitalist class. Labour is considered as the basic source of all value, but it produces more than that needed for its own subsistence. This Surplus Value, which is appropriated by the capitalists, enables capital accumulation. Hence, there is an incentive to generate more surplus value by incorporating capital using technologies which have a higher proportion of constant to variable capital, as also by other means which result in labour exploitation. Since this type of technological change economises on labour, it creates an industrial reserve army of labour. The existence of this reserve army enables wages to be driven down to the minimum subsistence level, as in the Classical thought, but through a very different mechanism. Here, technological change is viewed as forcing wages to be kept low while simultaneously bringing about a decline in the rate of profit through a rise in the organic composition of labour.

3 WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR 85 Thus, the nature of technological change under capitalism, according to Marxian thought, hastens the decay of capitalism through a declining rate of profit, on the one hand, while on the other hand, it keeps in abeyance the achievement of full employment through the emergence of a reserve army of labour. This, in turn, keeps wages pegged to the subsistence level. In terms of its mechanics, the Marxian system results in bringing about subsistence or near subsistence level wages, as in the Classical theory, but in terms of the level of employment, the two deviate from each other. While Classical economics subscribed to the notion of automatic full employment, the Marxian dynamics keeps full employment permanently in abeyance. Moreover, in respect of technological change, while in Classical thought, the absence of technological change results in the operation of the law of diminishing marginal returns and brings about a movement of the capitalist system towards the stationary state, in Marxian thought, technological change itself sows the seeds of the breakdown of capitalism by bringing about a decline in the rate of profit. The Neo-Classical approach to wages is very different from that underlying the Classical Theory, though the term Neo-Classical gives the impression that it is a modified version of Classical economics. In the Classical School s approach, wages tend to get anchored to a given level determined by exogenous forces related to the sustenance of labour and certain prevailing norms or conventions. But within the Neo-Classical framework, wages are considered to be akin to the price of any other factor of production or commodity in the product market, which is determined by the demand for and supply of a factor or a commodity. The supply of labour is considered to be dependent upon the disutility of labour which needs to be overcome by the payment of wage as an incentive. The demand for labour, on the other hand, is dependent upon the marginal productivity of labour, which declines with the application of every successive unit of labour. The wage rate prevailing in the market is thus the outcome of interaction of the falling demand curve and the rising supply schedule of labour. The interaction of demand and supply schedules of labour takes place at the micro- level but the Neo-Classical framework generalises it to the economy-wide macro- level. Thus, interaction of the market demand schedule, based on diminishing marginal productivity, and the supply schedule of labour simultaneously determine the wage rate as the price of labour and the aggregate level of employment in an economy. Since, at the equilibrium wage rate, the aggregate supply of labour is supposed to get fully absorbed, the equilibrium level of aggregate employment is taken to be the point at which there is automatic achievement of full employment. The equilibrium level of employment at the macro-level via the wage rate adjustment is thus implicitly taken to be the definition of full employment. In a similar fashion, equilibrium is supposed to be brought about for capital and other factors of production at the aggregate level. However, the Cambridge School has major objection to it in case of capital goods, which are of a completely heterogeneous character. The objection of the Cambridge School to the Marginal Productivity Theory, specifically in its application to capital, is that it involves the pricing of heterogeneous capital goods without which aggregation of capital goods and hence marginal productivity of capital cannot be determined. The pricing of capital goods, in turn, depends upon the wages paid to labour for their role in the production of capital goods. The marginal productivity of different factors, which is supposed to determine the distribution of income in the Neo-Classical School, cannot be independently determined unless the distribution of income among labour and other factors are known in advance. The major deviation of Keynesian economics from the Classical and Neo-Classical Schools, both of which are based on the principle of automatic adjustment to full employment, provided

4 86 THE INDIAN JOURNAL OF LABOUR ECONOMICS there are no impediments on account of frictions within the economy, occurs in respect of employment determination at the macro-level. The Keynesian analytical framework parts company with the Say s Law that Supply Creates Its Own Demand, since the latter is valid only if the marginal propensity to consume is taken to be one and whatever is saved is automatically invested. Both these implicit assumptions are invalid. Within the Keynesian framework, the level of employment is dependent upon aggregate demand, which can generate full employment only if the gap between the full employment level of income and consumption is filled up by an equivalent level of investment. Similarly, in terms of the Keynesian view of Neo-Classical formulation, the automatic achievement of full employment through a wage adjustment mechanism is possible only if the demand for the labour schedule is taken as given. While this may be possible at the micro-level, when one is dealing with the macro-economic level, the demand for the labour schedule cannot assume the level of income as a ceteris paribus condition. When the decline in wage rate gets generalised to the whole economy, the aggregate level of income and hence, the declining demand schedule for labour in the economy would shift downwards. This would bring down in its wake the equilibrium level of wages as also the equilibrium level of employment, which cannot, in any meaningful sense, be considered as the level of full employment. Wage determination was not as basic a concern of Keynes as his concern for employment. But wage level does occupy an important part in his formulation. Money wages are, by and large, considered to stay constant up to the vicinity of the full employment zone. They are not taken to be given as being governed by the subsistence level fixity of the type associated with the Classical School, but are taken to be given at a reasonable level consistent with a decent level of living. It is only after the achievement of full employment that money wages and prices are supposed to rise when the labour market becomes more tight. It may be pointed out here that though Keynes does not take wages to be determined by the marginal productivity of labour, he does not dissociate himself from the marginal productivity of labour which is taken to get equated to the existing wage level. After the full employment level has been attained and there is a tendency for money wages to rise, the real wage level is supposed to be brought back into equality with marginal productivity through a rise in the price level generated by the pressure of rise in wages. The behaviour of wages and prices in the near full employment zone led to the development of one of the post-keynesian formulations which attracted considerable attention, particularly in the 1950s and 1960s, namely that of A.W. Phillips (1958), which has come to be known as the Phillips Curve formulation. The main contribution of Phillips was to establish empirically, on the basis of nearly a century of data pertaining to the British economy, that the nominal wage rate started rising as the level of employment increased to reach a high level. Expressed in terms of the unemployment rate as a measure of its counterpart, viz. the level of employment, Phillips observed an inverse relationship between the level of unemployment and the rate of increase of the wage level. The negative relationship of the pace of wage rate change to the unemployment rate is supposed to emanate from a rise in the strength of trade unions near the full employment zone wherein their bargaining power increases as compared to situations in which there exist hordes of unemployed workers at the factory gates. Lipsey (1960) observed further that in addition to the level of unemployment affecting the rate of change of wages, the rate of change of wages was influenced negatively by the pace of change of unemployment, implying thereby that the higher the pace at which unemployment decreased, the higher would be the pace of wage increase. It was also estimated by Phillips that in case of U.K., the rate of

5 WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR 87 wage increase dwindled to zero and that wages and prices would stabilise if the unemployment rate were around 5 ½ per cent or so. Finally, in decisions about wage changes, it is also argued that wages depend upon or rather should depend upon the capacity of an industry to pay, which could be variously interpreted as the rate of profit earned in an industry or productivity per worker in it. There is also the counter-argument that the capacity of an industry also represents the contribution of capital and technology in an industry. Notwithstanding these arguments and counter-arguments, it is difficult to deny that the productivity per worker plays a role in determining the wages paid (also see Stiglitz, 1974). II. QUANTITATIVE DIMENSIONS OF WAGES AND EMPLOYMENT IN INDIA 1. All-India Organised Industrial Sector Having taken a fleeting view of the major cross-currents of theoretical developments in the area of wages and employment over the past two and a half centuries or so, we shall now move on to the empirical analysis of some of the variables related to wages and employment in the industrial sector in India. We pick out certain variables of relevance emerging from the preceding theoretical part with a view to examining their trends and inter-relationships in the Indian context. For this purpose, the analysis is conducted at three levels. We look separately at the organised industrial sector, based on the Annual Survey of Industries (ASI) data, and then at unorganised manufacturing, based on NSS data. First, the empirical scenario is analysed separately in the all-india context and then in the regional context, based on data for seventeen major states. The time periods covered for this analysis vary from six to thirty years, depending upon the availability of data. First, we may take an overall view of the national economy for the organised industrial sector on the basis of the following variables of major importance: (i) Number of factories; (ii) Number of workers; (iii) Total number of employees, including executives and middle level staff in addition to the blue- collared workers; (iv) Total wages to workers; (v) Total emoluments which include wages and payments other than wages like salaries, etc.; (vi) Value added; (vii) Real wage per worker at prices; (viii) Total emoluments per employee, i.e. earnings per wage and non-wage employee; (ix) Real emoluments per non-wage employee; (x) Real Productivity per worker (at prices); and (xi) Productivity per employee (Value Added per wage and non-wage employee at prices). The last four variables are not published but have been derived from published data, using price indices. These variables have been examined for a period of three decades, broken up into three sub-periods, viz.; (a) , which is the pre-reform era; (b) , representing, by and large, the creeping liberalisation phase, though strictly speaking, 1991 is the end of this phase; and (c) , which is the period of full-fledged liberalisation.

6 88 THE INDIAN JOURNAL OF LABOUR ECONOMICS Table 1(a) All-India Values and Trend of Basic Variables (Organised Manufacturing) Values at point of time Growth rate per annum S. no. Variable Number of factories 64,133 96,503 1,21,594 1,29, (units) 2. Number of workers (in thousand) 3. Number of employees (in thousand) 4. Total wages to workers (Rs. crore) at prices 5. Total emoluments ,101 11, (Rs. crore) at prices 6. Value added (Rs. crore) 27,044 37,249 1,04,889 1,52, at Prices 7. Real wage per worker ,284 10, (worker only) at prices 8. Total emoluments per ,748 14, employee (workers+ non- wage employees) at prices 9. Emolument per employee 14,479 14,510 20,618 31, (excluding workers) 10. Productivity per worker 58,034 61,600 1,58,156 2,51, at prices 11. Productivity per employee 46,467 48,282 1,20,451 1,94, (Value added per worker + non-wage employee) at prices Source: Various volumes of Annual Survey of Industries (ASI). Wherever value variables are involved, as in case of variables (7)-(10), they have been converted into a constant price base, depending upon the most suitable base year in terms of data availability. For wage per worker as well as for productivity per worker, the base year used is The absolute value of these variables at each of the four points of time and growth rates for the above three variables are given in Table 1a. A glance at Table 1(b) brings out some points of considerable importance. For six out of the 11 variables viz., for variables (1), (2), (3), (4) and (5), there is a successive decline of growth rates from the 1970s to the 1980s and from the 1990s to the early part of the current millennium. Moreover, there is a substantial decline in growth rates, so much so that for the number of workers, the number of employees, the total wage bill as well as the wages per worker, there was a negative growth rate during the period Thus for both variables of basic interest to us, i.e., wages and employment, there was a substantial dip in their pace of expansion. In contrast, for value added in organised manufacturing (6), emolument per employee (8), productivity per worker (10) and productivity per employee (11), there was a substantial step-up in the growth rates of these variables from the 1970s to the creeping liberalisation phase of the 1980s. But in the era of full-throttle reforms, i.e. during the period , these growth rates also nose-dived.

7 WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR 89 Table 1b Ratios of Key Basic Variables (Organised Manufacturing) Ratio at point of time Sl. no. Ratio description (%) Ratio of emolument per non-wage employee to wage per worker 2. Percentage of wage per worker to productivity per worker 3. Percentage of emolument per employee to productivity per employee 4. Percentage of wage per worker to earnings per employee to wage per worker Note: Wage per worker and emolument per employee given in rows 7 and 8 of Table 1a have been multiplied by the Consumer Price Index of Industrial Workers in , i.e. a ratio of 2.58, in order to derive wage per worker and emolument per employee at prices. Before dividing these by productivity per worker, this step was necessary since productivity figures in Table 1a are at prices, while wages and emoluments in Table 1a were at prices. Source: Same as Table 1a. A few other points need to be observed. Firstly, the fact that the employment growth plummeted downwards in the 1980s, while value added growth shot up from 4.08 per cent to 7.68 per cent, is just a reinforcement of the jobless growth phenomenon in the organised industrial sector, which is widely known. The same story was repeated during the 1990s and the current decade (also see Goldar, 2000; Nagraj, 1994). Secondly, it may be noticed that while during the 1970s, the growth rate of wage per worker was higher than that of emolument per employee, the situation during the 1980s and during the post-reform period was quite the reverse, particularly during the post-reform phase when the wage growth rate was negative (-0.27 per cent) while that of emolument per employee was very high at per cent per annum. In fact, during the 1980s, while the growth rate of emolument per employee (2.81 per cent) had gone up as compared to the 1970s (1.98 per cent), in case of wages per worker, the growth rate during the 1980s (2.59 per cent) had come down from that of 2.75 per cent during the 1970s. The significance of this comparison lies in the fact that it shows that emoluments, which include return to high-level manpower, i.e. the non-wage component, has been doing much better than the earnings of workers in general. Thirdly, while percentage of wage to productivity per worker (Table 1b) increased during the 1970s from per cent to per cent, subsequently it declined continuously, becoming a mere per cent during the year A similar trend emerges in the case of percentage of emolument to productivity per employee ratio. Finally, while during the 1970s, the wage in relation to emolument per employee improved from 78.4 per cent to 82.6 per cent during the 1970s and subsequently this proportion started declining, dipping to 67.5 per cent during This is a consequence of the fact already pointed out that while the emolument rate has been maintaining its upward direction during the post-reform era, the real wage rate growth became negative. This has widened the disparity between the wages paid to workers and the emoluments of non-wage employees. In order to bring out this disparity in a clearly visible form, the emoluments of non-wage employees, i.e., white-collared workers, have been estimated from the available data. The average emolument per non-wage employee has been estimated from the data on total emoluments and total employees. By subtracting the number of workers from the number of employees and the

8 90 THE INDIAN JOURNAL OF LABOUR ECONOMICS wage bill from total emoluments to all employees, the number of non-worker employees and emoluments of non-workers have been estimated. Based on these, Table 1b gives estimates of the non-wage employees and their emoluments, which have been used for deriving the average emolument of non-wage employees and the ratio of emoluments per non-wage employee to wage per worker. As can be observed from Table 1(b), the ratio of the emolument rate to wage rate has shot up from 1.98 in to 3.12 in , whereas it was 2.39 in All-India Unorganised Manufacturing Sector Information about the basic variables we have been discussing above is not available on a comparable basis for unorganised manufacturing. In some directions, the NSS data are much more intensive than the ASI data, for example, in terms of Own Account Manufacturing Enterprise (OAME), Non-directory Manufacturing Enterprise (NDME) and Directory Manufacturing Enterprise (DME) classification, which is relevant only for unorganised manufacturing, whereas in terms of classification into workers and employees, the data availability as also their relevance exists only in case of the organised industrial sector ASI data. Table 2a, therefore, portrays trends in terms of the number of enterprises, employment, output (GVA) and labour productivity (Gross Value Added per worker at constant price base) in unorganised manufacturing. These figures from to are taken entirely from Sheila Bhalla s work (2003) whose Tables were derived from NSS data. Estimates for subsequent points of time were prepared by authors on the basis of NSS data for and , though for some variables for data were also taken from Sheila Bhalla s work. As may be observed, in relation to the organised sector, total unorganised manufacturing employment (Table 2a) is much higher. Unorganised employment was 2.3 times of that in organised manufacturing in , but it increased to 4.54 times by This reflects meagre growth of organised manufacturing employment while employment in unorganised Table 2a Absolute Values and Ratios of Unorganised to Organised Manufacturing Variables: to Variable Unorganised (Absolute values) Number of enterprises Number of workers Total GVA per worker Wage per worker Organised (Absolute values) Number of enterprises Number of workers ( 000) Total GVA per worker Wage per worker Ratio of unorganised to organised Ratio of unorganised units* to organised units Ratio of unorganised employment to organised employment Ratio of GVA unorganised to GVA organised Ratio of GVA PW unorganised to GVA PW organised Note:* These include DME, NDME as also OAME. Source: Bhalla (2003).

9 WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR 91 manufacturing went on mounting at a rapid pace. In case of OAME employment, employment in the rural unorganised sector employment predominates, whereas for NDME and DME, urban employment predominates. The picture in terms of the number of enterprises is, by and large, similar to this but here unorganised manufacturing units predominate by a far higher ratio of 85 to 183 times, as is evident from Table 2a. This ratio declined continuously from till , from a level of 183 to 103, but rose again to 12.9 in This indicates a faster growth of unorganised units than the organised ones during the reform period, after As regards the Gross Value Added (GVA) and productivity per worker, the relative position of the unorganised and organised segments is quite the opposite. The aggregate GVA in organised manufacturing predominates despite a larger volume of employment and number of enterprises in unorganised manufacturing. While the number of enterprises and employment in the unorganised sector exceeds that in the organised sector, unorganised manufacturing GVA has been only 0.28 (i.e. 28 per cent) to 0.49 (i.e. 49 per cent) of organised manufacturing GVA. As regards the productivity per worker, the unorganised manufacturing productivity per worker is far lower at 0.07 (=7 per cent) to 0.12 (=12 per cent) of that in organised manufacturing. After assessing the relative importance of organised and unorganised manufacturing employment, their wages and productivity, we now turn to their pace of expansion over time (see Table 2b). It is not easy to compare growth rates pertaining to organised (Table 1a) and unorganised manufacturing (Table 2a) since the delineation of quinquennial time periods of NSS rounds does not match the three time periods selected for organised manufacturing. Still, some broad conclusions can be drawn. From the 1970s up to the mid-1990s, the trend of employment expansion is broadly parallel in unorganised manufacturing to that in the organised segment. As evident from Table 2b, while during the period, 1970s to the early 1980s, the pace of Table 2b Growth Rates per annum (Unorganised Manufacturing: Rural+Urban) Variable/Period OAME NDME DME All No. of enterprises to * to to to Employment to * to to to GVA to * to to to GVA (Productivity per worker) to * to to to Note: *For both OAME and NDME.

10 92 THE INDIAN JOURNAL OF LABOUR ECONOMICS employment expansion (12.74 per cent per annum) was substantially above that in the organised segment (5.24 per cent per annum), in the 1980s and up to 1994, the pace of employment expansion was not only lower but even negative. However, after 1994, the pace of employment expansion in the unorganised segment deviated radically from that in the organised segment. While during the post 1995-reform phase the pace of employment expansion dipped to negative level in the organised segment (-0.78 per cent per annum), in unorganised manufacturing, there was a substantial rise from 1.72 per cent per annum during to per cent per annum during This tendency on the part of employers to shift from the organised to the unorganised segment fits in with the tendency of employers to contract out work to enterprises in the informal unorganised segment. It is also reflected in the rising proportion of casual workers vis-à-vis the declining proportion of regular workers, since the former are not bound by any employment protection legislation which is applicable only to regular employees in the organised segment and not to any workers in unorganised manufacturing. The rise in employment expansion during was much more evident in the urban segment (7.08 per cent per annum) as compared to that in the rural unorganised segment (2.88 per cent per annum). It may also be pointed out that employment expansion was much more evident among the urban OAME (8.97 per cent) than among urban NDME (8.38 per cent) or DME (3.27 per cent per annum). By and large, a similar picture emerges in case of growth in the number of unorganised manufacturing enterprises. Similar is the case with GVA and productivity per worker growth. But two deviations from the above pattern may be noted. The GVA growth rate declined progressively during , but to a much lower extent than in case of employment. Although the same was true in case of productivity per worker, but the dip was much less, being roughly near about 2.0 per cent per annum. Secondly, during , the increase in the growth rate of GVA was much higher, reaching a level of per cent vis-à-vis 4.25 per cent in the case of employment. The productivity per worker also increased at a higher rate of 5.85 per cent during Thus in respect of employment growth as well as its productivity, unorganised manufacturing appears to have fared better as compared to its organised counterpart. When we consider the wage per worker, the ratio of unorganised to organised was also not only low, but declined substantially from 0.35 to 0.15 during the period 1994 to This decline has to be seen against the absence of any decline in the ratio of unorganised to organised productivity per worker (0.07) during the same period (see Table 2a; also see Unni, 2006, and Narain, 2006). 3. Strength of Trade Unionism Finally, one of the variables which stands on a somewhat different footing from those discussed earlier but which is of importance in the context of Keynesian and post-keynesian theories of wages and unemployment, is the extent of unionisation of the labour force (Phillips, 1958; Hines, 1964). It is fairly widely recognised these days that trade unions have been losing power (Saini, 2006; Shyam Sundar, 2006). The total number of workers enrolled as members of Registered Trade Unions at the all-india level are given in Appendix Table 1 from to 2002, which is the latest year for which data are available. While the absolute number of members has been fluctuating and there has been an increase during some periods, the strength of the trade union body, as a whole, depends, among other factors, upon the number of trade union members in relation to the size of the total workforce, referred to as the Degree of Unionisation. This is very small when one views it in relation to the total workforce in the non-agricultural sector, or even as a proportion of the organised sector workforce. Lately, however, a drive to enroll members

11 WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR 93 Table 2c Degree of Unionisation Year t % of trade union registered workers to Total workers (Ta) Non-agricultural workers (Tb) Note: Trend lines: T a = t (1.64) T b = **t (2.74) where Ta is a percentage of union membership to the total workforce. Tb is a percentage of union membership to the non-agricultural workforce. t is the time (in terms of number of years from ). ** represents statistical significance at 0.05 levels Figure 1 Degree of Unionisation Ta (obs.) Ta and Tb 6.00 y = x Tb (obs.) Linear (Tb (obs.)) Linear (Ta (obs.)) 4.00 y = x Time (t) Note: Ta (obs) is the observed percentage of membership of registered unions to the total workforce. Ta (est) is the estimated percentage of membership of registered union to the total workforce. Tb (obs) is the observed percentage of membership of registered union to the non-agricultural workforce. Tb (est) is the estimated percentage of membership of registered union to the non-agricultural workforce.

12 94 THE INDIAN JOURNAL OF LABOUR ECONOMICS from the non-agricultural unorganised sector, and even among agricultural labour, has paid some dividends and trade unionism has spread to these in some states. But in overall terms, the proportion of union membership is quite limited. The above-mentioned declining trend in the strength of trade unionism is evident from the proportion of trade union members to the total workforce as also in relation to the non-agricultural workforce given in Table 2c at seven points of time for which the NSS data on workforce are available. Data on trade union membership for , which is the latest year covered in this paper, are not yet available. As may be observed from Table 2c, while the trade union membership as a proportion of the total workforce has been only 1-3 per cent, even membership as a proportion of the non-agricultural workforce has been very low, lying between 2.5 per cent and 10 per cent. Moreover, the secular trend of this proportion has been that of decline, as evident from linear trend lines given below Table 2c and in Figure 1, thus confirming the view about the declining strength of trade unions. III. INTER-RELATIONSHIP OF WAGES, EMPLOYMENT AND PRODUCTIVITY: THE REGIONAL CONTEXT Until now, after discussing various theoretical approaches to the issue of wages and employment, we have examined trends in major variables of interest to us. But all the discussion was focused on assessment of the concerned variables, independently of one another. We shall now analyse the relationships among them with the objective of examining some of the factors which influence the level of wages. As already pointed out, we shall pick up the variables, taking a cue from various theoretical approaches delineated earlier, and examine their relationship in the Indian context. For the purpose of examining the relevant relationships, two approaches are possible, of which the first entails the use of time series data. But one is likely to encounter the problem of auto-correlation in this context. Therefore, for the present purpose, though we shall examine the relationship with the help of time series approach at the all-india level, we start off with relationships in the regional context, first for the unorganised NSS-based industrial sector and then for the organised sector on the basis of analysis of ASI data. As regards the variables chosen, at the outset, it may be pointed out that for the empirical purpose of this paper, it is not easy to draw upon all the theoretical formulations outlined above, particularly the Classical and the Marxian ones. Among the rest, firstly, on the basis of the Neo- Classical model as interpreted in Section I of this paper, there is expected to be a negative relationship between wage rate and the level of employment. But this relationship is, strictly speaking, a micro- level relationship though it has been generalised to the macro- level. Moreover, Mukherjee (2006), using the Neo-Classical tools of analysis, has pointed out that a decline in wages need not always result in an increase in employment, which is implicit in the Neo-Classical theory. Our data are also macro- level data. The nearest possible way in which macro- level data could be converted to test a micro- level relationship, in our view, was to regress the average wage per worker on average employment per enterprise, in each state, considering a state as a unit of observation, as if it were a firm. There are, no doubt, flaws in this process. The first one is obviously the fact that it is not very appropriate to use state level data as a proxy for firm level micro- data. Secondly, the relationship of wage rate to employment per enterprise could also be interpreted as reflecting the effect of economies or diseconomies of scale. Notwithstanding these problems, regional data have been used to yield regression results postulating dependence of the wage rate on the size of employment per enterprise. In terms of the Keynesian formulation (1936), though money wages are taken to be exogenously determined at a fixed rate, which covers the means of decent living, they are

13 WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR 95 Table 3 Emolument per Worker (Unorganised Manufacturing) State Emolument per worker, 2000 Growth ( ) Value Rank % Rank Andhra Pradesh 12, Assam 13, Bihar 16, Gujarat 23, Haryana 21, Himachal Pradesh 26, Jammu & Kashmir 21, Karnataka 12, Kerala 17, Madhya Pradesh 13, Maharashtra Orissa Punjab Rajasthan Tamil Nadu Uttar Pradesh West Bengal All-India CV supposed to rise towards the full employment level. According to the Keynesian theory, therefore, one would expect that the level of employment would exhibit a positive relationship between the wage per worker and the level of employment, or instead, a negative relationship between the wage per worker and the rate of unemployment. Thus, the second determinant of the wage rate in the subsequent analysis is taken to be the unemployment rate, expressed in terms of the Current Daily Status (CDS) unemployment rate. The post-keynesian extension in the form of the Phillips Curve, as outlined in the earlier theoretical section, differs slightly from the functional relationship postulated in the above paragraph. In the Phillips Curve, it is the rate of change of the wage rate which is supposed to be determined by the unemployment rate in a negative direction and not the wage rate. As pointed out in Section I, the positive impact of the level of employment on the wage rate reflects the expected growth in the strength of trade unions towards a full employment situation. Further, Lipsey s (1960) extension makes the rate of change of wage a function of change in the unemployment rate in addition to the unemployment rate. Thus we also estimate the regression function, which postulates a change in the wage rate to be dependent upon the unemployment rate and a change in the unemployment rate in addition to making it a function of the degree of unionisation. Finally, on the basis of the role of wage negotiations and decisions of management in the organised segment, the wage rate is expressed as a function of productivity per worker at a point of time, as well as the pace of change of the wage rate as a function of the pace of change of productivity per worker. 1. Unorganised Manufacturing Results We have estimated the above relationships on the basis of the NSS Rounds for and as well as for a change over this period. Before analysing regression relationships,

14 96 THE INDIAN JOURNAL OF LABOUR ECONOMICS let us take a fleeting look at the state-wise position in terms of some of the key variables (see Tables 3 and 4). The DME/NDME as well as the rural urban break-up are largely being skipped over for this purpose. But it may be pointed out that the data exclude OAME enterprises since they are supposed to be household units that do not employ any hired labour. As may be observed, in terms of the emoluments per hired worker (Table 3), the top ranking states were Himachal Pradesh, Gujarat, Maharashtra, Punjab, Rajasthan and Haryana, in that order, in , whereas in terms of the growth of emoluments over the period , the top ranking states were Himachal Pradesh, Bihar, Karnataka, Jammu & Kashmir, and Rajasthan. The fact that, in terms of the growth rate of emoluments, some of the less developed states emerge at the top could be a reflection of the low wage base effect. In terms of the productivity per worker, the five states that emerge at the top are Himachal Pradesh, Punjab, Maharashtra, Gujarat and Haryana (see Appendix Table 2). On the other hand, when we examine the urban unemployment rates in (see Table 4), the five highest rates are to be found in the case of Kerala, Assam, West Bengal, Orissa and Bihar. These states are subject to either the high pressure of population or under-development. The change in unemployment rates ( ) and the state-wise ranks are given in Appendix Table 3. As regards the variables which exercise a visibly positive influence on the level of emoluments per hired worker, regression results showing the relationship between the employment per enterprise and the unemployment rate in are given in Table 5. It may be observed that the results reveal a significant positive value of r (=+0.56;t=2.64) only in the case of the urban segment. As already pointed out, this relationship can be interpreted ambivalently, either as the effect of economies of scale or a negation of the Neo-Classical type negative relationship between wages and employment. The latter result is not borne out in terms of unorganised manufacturing data for since the relationship is a positive one. Even stronger results emerge for (see Table 5), since the value of the correlation co-efficient is again a strong positive figure of (t=+4.52) in case of the urban segment, (t=+2.62) in the rural segment and (t=3.57) for the overall economy. Table 4 Unemployment per Thousand Persons ( and ) State Rank Rural Urban Rural Urban Rural Urban Andhra Pradesh Assam Bihar Gujarat Haryana Himachal Pradesh Jammu & Kashmir Karnataka Kerala Madhya Pradesh Maharashtra Orissa Punjab Rajasthan Tamil Nadu Uttar Pradesh West Bengal All-India CV

15 WAGES AND EMPLOYMENT IN THE INDIAN INDUSTRIAL SECTOR 97 Table 5 Relationship between Employment per Hired Worker and Employment per Enterprise Year Area Category b value t value r value Rural NDME DME All Urban NDME DME All Total NDME DME All Rural NDME DME All Urban NDME DME All Total NDME DME All Next we examine the regression postulating wage per worker as a function of the unemployment rate. The results for the years and are given in Table 6. Both the regression equations show a negative relationship in the urban segment which is in conformity with the Keynesian postulate as interpreted by us. But the value of the correlation coefficients is rather weak, yielding t-values of 1.08 in , and 1.69 in On the other hand, in case of the rural segment, the correlation coefficients are even more feeble with a t value of less than one. Thirdly, we may now look at the regression results in terms of the wage rate as a function of the productivity per worker. The results for the years and are given in Table 7. As may be observed, this gives the strongest relationship of the wage per worker among the three determinants considered. The correlation coefficients of wages and productivity in different segments are all above , significant at high levels with the t values ranging Table 6 Relationship between Unemployment and Wage per Worker Year Area Category b value t value r value Rural NDME DME All Urban NDME DME All Rural NDME DME All Urban NDME DME All

16 98 THE INDIAN JOURNAL OF LABOUR ECONOMICS Table 7 Relationship between Productivity per Worker and Wage per Worker Year Area Category b value t value r value Rural NDME DME All Urban NDME DME All Total NDME DME All Rural NDME DME All Urban NDME DME All Total NDME DME All generally above the 3.0 level. This is true of rural as well as urban segments, and of NDME as well as DME, both for and Thus, it appears that in actual practice, a powerful influence on wages paid is that of productivity per worker, irrespective of the formulations of formal theories. In order to assess the composite effect of all the preceding three variables on wages, the results of multiple regression, based on these variables, are presented in Tables 8(a) and 8(b), for and , respectively. As may be observed, the multiple correlation is quite high for both the rural as well as urban segments; but the t values of the b coefficients are not very high in case of the two variables, i.e. employment per enterprise, and the unemployment rate. The high multiple correlation coefficient is essentially on account of the highly significant b coefficient of the productivity per worker (GVA per worker). This is in conformity with the single variable relationships derived earlier. We now analyse some of the variables based on the pace of change over time. First, flowing from the Phillips Curve formulation, the rate of change of wage rate over the period was regressed on the unemployment rate prevailing in The regression results are presented in Table 9. As may be observed, though most of the correlations and b-coefficients, are negative, these are highly insignificant. Similarly, a change in the wage rates as a function of a change in the unemployment rates, suggested by the Lipsey (1960) type formulation, yielded quite insignificant results, though these regressions are not being given in the text of this paper. The same emerged to be the case in the subsequent time series analysis. It would thus appear that the Phillips Curve formulation, which was developed in the context of developed economies, does not emerge to be important in the case of India s industrial sector. Lastly, a change in wage rate over was regressed on the growth of productivity per worker over the same period to see if positive wage productivity growth holds its place in the dynamic context as well. As may be observed from Table 10, this relationship is almost as strong as that at the two points of time ( and ) in case of the rural sector. But

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