Employment-Productivity Profile and Labour Demand Elasticity: A Preliminary Study of the Organized and Unorganized Indian Textile and Garment Firms

Transcription

1 154 The Journal of Industrial Statistics (2016), 5 (2), Employment-Productivity Profile and Labour Demand Elasticity: A Preliminary Study of the Organized and Unorganized Indian Textile and Garment Firms Sarmishtha Sen 1, Syamsundar College, Burdwan, India Subrata Majumder, Sundarban Mahavidyalaya, South 24 Parganas, India Abstract The present work seeks to trace the pattern of change in labour demand by both organized and unorganized T&G enterprises in India. Changes in average labour demanded across different size-groups of firms classified by firm-specific average labour productivity as well as intermediate input costs have been analysed. The changing share of these groups in estimated aggregate labour demand is also noted and the presence of some kind of stickiness in adjustment of labour demand with respect to productivity performances comes out. Estimation of labour demand elasticity all-india level and for selected textilemajor states suggested the limits of price signals in guiding such optimal adjustments. It is necessary to trace the possible sources of this stickiness in the structural rigidity inherent especially in the vast unorganized segment. Such an analysis has to treat also the endogeneity arising from two-way causality between efficiency-enhancing policy efforts and the two segments existing employment and growth behaviour. 1. Introduction 1.1 Recent interventions in the Indian textile and garment (T&G) industry and especially the National Textile Policy 2000 changed the pre-1985 policy approach radically by gradually removing the major protective measures for the small-scale decentralized section while withdrawing restrictions on their large-scale counterpart (Srinivasulu 1996, Roy 1996, 1998, Niranjana & Vinayan 2001, Galab et al 2009, Kathuria and Mamta 2012). This process signified a shift of two types: first, from a policy era with greater emphasis on employment objective to one explicitly focused on efficiency enhancement based on equalization principle of the market, and secondly from policy-guided inter-firm linkage to market-driven connectivity between organized and unorganized segments. Deregulation of the industry including de-reservation of the garment sector, the latter initiated by the Textile Policy 2000 and mostly completed by 2005, is expected to have removed major blocks to profitable restructuring by the large units - including those with 100% FDI - while allowing them entry practically in every area of T&G production (Singh and Sapra 2007, Chaudhary 2011). With efficiency-enhancing optimal re-allocation of resources by organized units becoming easier and possible now, we can expect a significant change in the employment generating potential of these two constituent segments of the Indian T&G industry especially in the post-mfa period. Increased scope for firm-level optimal adjustment of labour demand suggests that greater part of this employment be concentrated in the relatively high-productivity segments of the industry sarmishtha.sen@gmail.com 2 Assuming a perfectly elastic labour supply, it is plausible to argue that observed changes in employment are guided mainly by the hiring behaviour of the firms.

2 Employment-Productivity Profile and Labour Demand Elasticity Increased trade-liberalization is expected to have offered significant opportunities for expanding production activities especially in the organized segment. There are evidences, on the other side, of unorganized units becoming a part of this technical and structural reorganization through the large-small linkage like subcontracting (Maiti 2008, Sahu 2011). Labour demand in the unorganized segment may fall due to substitution effect arising from use of more sophisticated production techniques associated with such reorganizations. If the organized segment however, contracts out the relatively labour-intensive operations to these enterprises, there is a high possibility of increase in labour demand in the latter due to scale effect. This potential however may not be realized if there is little increase in outsourcing by large units interested in more intense supervision of production and quality control through in-house production. 3 The unorganized units in such a situation may experience very slow expansion of production and labour demand eve in absence of any significant substitution effect. 1.3 Thus, we can trace this process of adjustment at two levels: through following changes in aggregate labour demand at the sectoral level, and by studying the micro-level process of making optimal hiring decisions. Through an exploratory analysis, this paper seeks to examine the pattern of change in aggregate as well as sector-specific demand for labour across the two constituent sections of the Indian T&G firms in the post-2000 years. Further, it attempts to evaluate how individual firms in different locational set-ups adjusted their demand for labour during this period, in response to changes in wage. The estimation of elasticity of labour demand (L D ) for selected Indian states with considerable presence of organized and unorganized T&G units may help us locate the significance among others of various policy parameters in inducing this demand. The broad research questions are the following: How did the distribution of L D in the T&G sector and in its organized and unorganized parts change in the period following Textile Policy 2000? Is there any evidence of direct association between productivity & change in L D in the period following the announcement of National Textile Policy 2000? How does firm-level labour demand adjust with wage & how do relevant locational parameters & policy factors influence labor demand elasticity? Is there any variation across the states? 1.4 The first part of the analysis assumes importance in view of a stagnant productivity performance in the organized T&G segment and an actually falling relative performance of even their bigger unorganized counterparts during the first decade of the present century as noted by Sen and Majumder (2015). In this context, can we expect a direct association between productivity growth and higher employment due to movement of employment from low to relatively high-productivity sub-groups expected in optimal re-allocation of resources made possible by reforms? Here, we treat the observed employment as the amount of L D assuming a perfectly elastic labour supply especially in the vast unorganized segment with approximately fixed wage. More rapid rate of increase in L D among the lowproductivity groups however, would indicate the presence of some kind of stickiness in 3 Reduced traditional marketing support from government is expected to have increased dependence of the unorganized units for access to market on the large and organized ones.

3 156 The Journal of Industrial Statistics, Vol. 5, No. 2 adjustment of labour demand despite poor productivity performances. Next, we examine the firm-specific adjustment of labour demand by Indian T&G units - both organized and unorganized - in response to wage while controlling other factors potentially influencing labour demand in thirteen textile-major states. 1.5 Rest of the paper is organized as follows: Section 2 delineates, based on the available empirical findings, the possible link between employment, labour productivity and labour demand elasticity in the organized and unorganized T&G segments. The next section entitled Methodology and the Database first discusses the methodological requirements of this kind of an issue. Variables and the source of data used for this purpose are described in two following subsections in it. Section 4 presents the findings of both the exploratory analysis and the regression exercise respectively in two subsections while section 5 contains the concluding observations. 2. Links between Employment and Productivity: An Outline 2.1 Using the Flow Chart 1, we attempt to explain the possible channels through which segment-specific labour demand and its average labour productivity may be related in the context of heightened market-based competition in the domestic economy along with increased integration with the global economy. Trade liberalization and complete abolition of MFA require that the T&G units, both organized and unorganized, enhance productivity and competitiveness. Indian textile production base is known to have suffered from accumulated structural weaknesses resulting from fragmentation of productive capacity, lack of technological upgrading especially modernization, and absence of advantages in terms of scale economies. Restrictive textile policies of the pre-1985 era did not allow capacity expansion or changing input-mix in the organized segment according to the requirements of production efficiency. Thus such a policy strategy was viewed as an obstacle to the achievement of export-competitiveness. The restrictions on the large organized units for optimal restructuring - through capacity expansion or capital imports and subsequent capital deepening process - were lowered in the post-1985 years especially after the National Textile Policy 2000 had allowed entry of large units in garment production including 100% automatic approval of FDI. Organized sector in most of the Indian manufacturing industries have resorted to increased use of labour-displacing technologies despite the remaining labour laws as has been noted by a number of empirical studies in the recent years (Nagaraj 2004, Rani and Unni 2004, Banga 2005, Sen and Dasgupta 2006, Das and Kalita 2009, among others). This may have exerted a negative pressure on employment through substitution effect Trade liberalization on the other hand, especially in the post-mfa years, offer greater scope for venturing in markets hitherto restricted by MFA quota. Traditional trade theories would suggest an expansion of the labour-intensive exporting segment. In fact, Indian T&G exports are known to have created a niche market of their own while producing innovation- or design-intensive high value-adding customized items. It has achieved export success particularly in the high-end fashion segment on the basis of economies of scope. The T&G enterprises are also catering to the expanding domestic, especially urban market 4 Increased use of capital may have been prompted by absence of skilled labour while increased capital intensity may also be a reflection of increased labour productivity.

4 Employment-Productivity Profile and Labour Demand Elasticity of consumers with rising purchasing power and demand for tailor-made and highly differentiated T&G products (Roy 1998, Teewari 2005, Singh and Sapra op cit. for example). The expanding market base presents opportunities for greater specialization, efficiencyenhancing restructuring and improvement in labour productivity at least in certain segments of the organized T&G units Organized segment however subcontract a part of its operations, especially the labour-intensive ones, to the unorganized segment as a means to achieve costcompetitiveness. There are empirical evidences indicating use of increased share of lowcost labour in the Indian T&G sector as a cost-cutting and efficiency-enhancing strategy especially in the years after the implementation of Agreement on Textiles and Clothing (Abraham & Sasikumar 2010, for instance). Maiti and Marjit (2008) on the other hand argued that with increased international price of T&G product, it becomes profitable for the organized section of the T&G industry to outsource increasing proportion of production activities to the unorganized units while retaining and specializing in the marketing-related activities. Ability to serve the increasingly globalized domestic and international markets - of such a linkage between organized and unorganized firms however hinges on developing technical and organizational capability of the latter under the supervision of the parent firms. In such a scenario it is plausible to argue that export success of the organized parent unit may be accompanied by an improvement of productivity performance of the unorganized subcontracting firm. Downward pressure on employment arising from any possible increase in capital intensity may be outweighed by expansionary tendency of employment in the segment via scale-effect. Flow Chart 1 Productivity-Employment Link in Organized T&G and Induced Effect in the Unorganized T&G Segments Search for Increased Competitiveness Relaxed Optimal Restructuring by ORGANIZED ORGANIZED ORGANIZED T&G EMPLOYMENT T&G (-) (+) Use of Labor -saving Technique Organized Specializing in Marketing & Monitoring Increased Scale of Operation Labor-intensive Operations Outsourced UNORGANIZED T&G EMPLOYMENT Greater Trade openness Expanding Domestic Market Source: Authors Understanding Survivalist UNORGANIZED: Productivity-Employment Disconnect & Modern UNORGANIZED: Relatively Rapid Employment Increase in High-Productivity Deciles 5 Organized firms are expected to respond more effectively than their unorganized counterpart to these opportunities.the phenomenon of relatively high increase of employment in labour-intensive exporting industries has found support in empirical studies (Kakarlapudi 2010, for instance).

5 158 The Journal of Industrial Statistics, Vol. 5, No To accommodate the phenomenon of intrinsically heterogeneity and diversity of the unorganized T&G segment in our analysis, we have divided it in two distinct groups: one mostly survivalist 6 and the other dynamic 7 section (following Sen 2016). Enhanced market-based competition of the recent years and changing policy regime are expected to influence these two parts differentially. For instance, market incentives are expected to work better with the latter group, which is better-placed to reap benefits from policy support too. We can expect a direct association here between productivity improvement and employment generation through competition as well as collaboration with the organized segment. The traditional group, on the contrary, is not supposed to display any such definite pattern as the urge to survive, and not production efficiency, is the driving force behind its operations. 2.5 Trade liberalization has been found to be associated with increasing labour demand elasticity in the organized manufacturing industry. Unorganized segment however falls outside the scope of labour legislation, wage variation may be low and competitive labour supply does not allow effective assessment of the effect of wage-variation on demand for labour Methodology and the Database 3.1 Methodology: In the first exercise, we examine the change in segment-specific labour demanded (L D ) across size-groups based on level of unit-specific average labour productivity as well as on the firm-level expenses on intermediate inputs. We undertake further an exploratory analysis of the inter-relationship of change in average labour demand with change in productivity and changing share of different size-groups in estimated aggregate labour demand. This part of the analysis makes use mainly of summary statistics on average labour productivity (AP L ) and L D to demonstrate whether or not any increase in L D is located in the relatively growing section of T&G firms during the post-2000 years The issues involved in the estimation of labour demand elasticity are mainly twofold: specification of demand function and choosing the proper estimator, and selecting 6 This group refers to typically low-productivity units either operating independently in the local market or is connected with distant markets through traditional and often exploitative chain of intermediaries. These firms generally lack the preparedness to adapt with efficiency-improving market signals or to respond to policy support. 7 This group consists of units, generally mechanized and modern, linked with globalized market through collaborations with large-scale sector resulting in technological spillover, increased capital intensity and enhanced production performance. 8 If increased wage is a reflection of use of labour with higher productivity (evident from fall in the share of low-productivity self-employment, (Goldar and Sadhukhan 2015)) in the unorganized section and scale effect dominates substitution effect we may not observe the effect of wage rise as expected on labour demand. Increased exposure to trade may give rise to asset-specificity and the export obligations may call for long term relationship with the skilled-worker. In this case considerations other than wage may dominate employment decisions of the unit concerned). In fact, elasticity of wages with respect to productivity was higher than unity in most of the organized manufacturing industries including textiles between 1990 and 2006 (Mitra 2013). Nagaraj (2004) observed that relative cost of labour did not seem to have any influence on employment decisions even in organized manufacturing at the turn of the present century.

6 Employment-Productivity Profile and Labour Demand Elasticity the variables for estimation and consideration of their characteristics. Assuming an unlimited labour supply and identical technology with varying factor price ratio (assuming comparable unit cost of capital and different labour remuneration rates) across the organized and unorganized segments we attempt to estimate segment-specific labour demand elasticity from the following labour demand function (following Hasan et al 2007 and Goldar 2009):... (1) where, (with competitive labour market), (total emoluments per laborday), is the logarithmic value of the wage series; (-), =organized segment dummy (+), = proportion of subcontracting big establishments in unorganized T&G segment in a state (+), G=garment-dummy ( 0 if textile) (-), =effort toward productivity improvement through capital structure (simple mean of unit s ranks in terms of log Capitallabor ratio, capital in land & non-land capital-intensity) (+), =effort on productivity improvement through input structure (simple mean of the units ranks by & log material costs) (-), = simple mean of % spending on electricity in total output (exceeding 1%) and state-level proportion of such power-driven establishments in the unorganized &G segment, Y=output value-added of a firm (+); =random error As individual firm s labour demand and its output (a specific measure for T&G value-added of a firm) are simultaneously determined within the model, both are likely to be correlated with the random error term 9. This may result in biased and inconsistent estimates. Use of instrumental variable (IV) regression method can give us consistent estimators by reducing unobserved or hidden bias especially in the observational studies like this. An instrumental variable has to satisfy two criteria: it has to be highly correlated with the problematic endogenous explanatory variable but should not affect the outcome independently We use instrumental variable regression method with the help of two-stage least squares (2SLS) estimator where the estimation is done at two stages. Suppose, the population regression relating the dependent variable and the output-regressor is as follows: (2) Where represents other covariates, and is the error term representing omitted factors that determine. A non-zero correlation between and, due to endogeneity for example, will yield inconsistent estimates. At the first stage, the variable under consideration, firm s output is decomposed into two parts: a part that is not correlated with the random error and therefore is non-problematic, and the other that is correlated with the error term. Here individual firm s output is regressed on the chosen instrument, which is correlated with 9 This happens due to possible reverse causation of labour demand to output giving rise to the problem of endogeneity. Endogeneity of labour price or wage is taken care of by the assumption of perfectly elastic labour supply typical of a developing economy.

7 160 The Journal of Industrial Statistics, Vol. 5, No. 2 but not with. The second stage estimates the concerned regression coefficient with the help of this exogenous variation component i.e. the problem-free part of variation in firm s output. Thus, the first stage of the regression links firm s output with the chosen instrument, (3) Here, is the intercept, the slope and the error term. From the regression, we have the predicted variation in firm s output, as - the part uncorrelated with the error term in the original regression. In the absence of actual regression coefficients and the second stage regresses on this predicted variation in i.e.. As is not correlated with a simple OLS will give us consistent estimate of i s In this research exercise, we attempt to estimate the labour demand function by the 2SLS IV estimator. At the all-india level we tried two alternative instruments: Y 1 _ins=per capita Net State Domestic Product at constant prices 10 as has been used in similar studies of labour demand estimation & Y 2 _ins=each firm s share of NSDP apportioned according to its share in total GVA of these establishments for each state). 11 As we are working on two repeated cross-section database we estimate the elasticity with the instrumental variable estimator separately for the years 2001 and We carried out this regression analysis for sample units in India as a whole and separately for thirteen selected states with major presence of T&G establishments in both organized and the unorganized segments (details given in Table 11) to examine state-specific variations. Variables e.g. LINKAGE (proportion of unorganized units linked with bigger firms through subcontracting), TECH (the average degree of mechanization of unorganized establishments in a state), and per capita NSDP have single values for each state. So these cannot be used in the state-level regression exercise. 3.2 Choice of Variables: Studies explaining the pattern of Indian manufacturing employment growth and those estimating labour demand have concentrated on the following factors: the indicators marking labour market rigidity, increased trade-openness encouraging adoption of capitalintensive and often imported production techniques as well as cheaper inputs, presence of major supply-side bottlenecks in different states (Nagaraj 2004, Das and Kalita 2009, ICRIER 2008, Kannan & Raveendran 2009, Nataraj 2010, Goldar 2011, Mitra op. cit.). Unlike these works (generally dealing with the organized manufacturing sector, Nataraj 2010 being an exception), any analysis of changing labour demand condition of one particular industry has to take in explicit consideration the specific interaction of that industry s structure with 10 This measure, representing the state s level of prosperity, influences the overall T&G production of the state but is expected to be minimally affected by the T&G industry-specific developments, which are likely to influence the sector s labour demand also. 11 Pairwise correlation between firms output measure and the proposed second instrument was quite high at least at 5% level of significance.

8 Employment-Productivity Profile and Labour Demand Elasticity changes in market conditions on the one hand, and the same with relevant policy parameters there 12 on the other The analysis has to be sensitive to potential variation in effect of same structural or policy-level change in an estimation that covers both the organized and unorganized segments. Change in policies instilling greater flexibility in the labour market may have differential impact on the two segments. Similarly, increased trade-openness is also expected to influence the two segments response in terms of production and employment differentially, especially depending on the concerned unit s structural location with respect to new market opportunities. The impacts may vary less if production in the organized and unorganized sections is linked through subcontracting These interventions - through influencing productivity - may affect the labour demand of the organized and unorganized sections of the industry. As noted in the introductory section, recent policy efforts targeting the Indian T&G sector have attempted to establish a strong connectivity of large and small firms through subcontracting. Thus, the extent of variation in subcontracting percentage would indicate the extent of organizedunorganized linkage as well as the pro-competitive stance of the policy regime. The process of mechanization (alongwith other infrastructural factors) adds to the speed of production and increases the scope of these linkages by ensuring adhering to the delivery schedule as well as the quality-specifications of crucial and big national/global buyers. Indicator of mechanization - a proxy of productivity enhancing technology-centered effort of the firm, based on the proportion of electricity consumption in T&G units especially in the unorganized segment will be an important factor to be controlled. Individual firm s organizational location as well as the product-group catered by it (textile or garment, for instance) serves to incorporate segment-specific variation in the Indian T&G industry at the unit level and across states. Following Biswas et al (2014), we have controlled various aspects of firm s productivity-enhancing effort through the channel of capital (by constructing a composite index of different measures of capital i.e., different sub-categories of capital) and channel of other non-capital inputs in the L D elasticity estimation Due to non-accessibility of systematic and direct information on many such factors over time, we have tried to control or reduce the extent of heterogeneity by controlling various structural and location parameters of the sample units. 13 Thus, we incorporate structural location of the firm: the segment it operates in (ORG), the product-group it 12 We have not included policy variables, such as amendments to the Industrial Disputes Act, the reforms introduced to scale up the social security contribution by the firms or to dilute them effectively as a direct measure of rigidity in the structure of the labour market due to our limited access to such data. These changes, labour being a state subject also, can vary across the states considered here. Neither had we had access to data required for constructing measures e.g. index of state-business relation or investment climate (as in Caliet al 2009, for example). We could only devise indirect measures against those potential influences. Similarly, information on industry-specific and productivity-enhancing interventions (such as Textile Upgradation Funds Scheme) targeting conduct of the firm operating in the market and marketing helps to aid optimal response to market-driven forces in presence of pre-market constraints, might be relevant. Firm-level data used here however do not provide such information. 13 Use of direct information is also constrained by availability of comparable statistics on the same variable at the two ends of the study period. For example, we could not construct any such comprehensive index of state-specific policy efforts and structural features using indiastats.com.

9 162 The Journal of Industrial Statistics, Vol. 5, No. 2 produces and markets (G), degree of labour-market rigidity (RGDT) 14, extent of connectivity between unorganized units with bigger concerns (LINKAGE). 15 The last two factors also reflect the current policy inclination in respective state s textile and garment sector. On the other side, we have controlled firm s efficiency-enhancing effort in the production sphere like KP 16, INP and extent of mechanization. By concentrating only on the relatively big T&G establishments and excluding unorganized T&G firms with no hired worker from this estimation exercise, we can somewhat reasonably treat the effect of trade-liberalization policies symmetrical across the two segments. 17 This exclusion allows us to focus on changes in domestic structure of the industry especially in terms of variation in the effect of policy on the labour demand at the state level where the relevant policies include existing labour laws and pro-competitive interventions meant for the T&G sector. 3.3 Database: Unit level data on the organized factories from the Annual Survey of Industries (ASI) database were pulled together with the information on unorganized manufacturing units provided by the successive rounds of NSSO (using the framework of Sen and Majumder 2015, summed up in Table A1). The exact choice of time points was guided by our access and availability of unit level data and the comparability of the two sets of industrial statistics. The data are in the form of repeated cross-sections and our study period refers to the years between 2001 and Each observation in our data set collates information on a number of variables including those on input and output bundles for different individual industrial enterprises. Necessary adjustments were made to ensure comparability of categories representing the same variables. We have considered only the perennial enterprises in the unorganized sector, which operate regularly throughout the year to make the comparison more compatible. For the same reason, we have only included unorganized firms hiring worker on a regular basis. Two full-time hired workers were taken as the relevant cut-off to get the final set of observations as in Sen and Majumder Similarly, both the data sets were converted at prices - for the exploratory part - by deflating with the help of wholesale price index (WPI) for Manufacturing Products 18. The pre-reform analysis has been carried out on the 14 Scope of profitable adjustment in labour demand in response to changing wages is expected to be limited by the extent of rigidity prevailing in the state s labour market thereby putting a downward pressure on labour elasticity of demand 15 LINKAGE acts here roughly as a proxy of state-specific textile policy effort and labour market flexibility (i.e., indicator of the general state of development in the T&G industry in each state - as that would indicate the scope for restructuring the entire value chain spanning both the segments); 16 KP - (capital pillar) indicates the nature of technology development through capital structure. The interactive terms of wage with capital-based effort and other inputs-based effort are likely to capture the effect of these channels generally on employment generation and specifically on labour demand elasticity 17 The one- or two-worker units (known as own account manufacturing enterprises, the OAMEs) were found to face significant participation constraints leading to lower incidence of large-small linkage there (Sen and Majumder 2014).Estimation of labour demand elasticity also loses relevance somewhat in units with preponderance of unpaid worker and with difficulty in distinguishing between the worker s and entrepreneurial roles. 18 To simplify we have not resorted to use of multiple indices although use of WPI for textile products and WPI for textiles machinery or that for general machinery to deflate output and fixed capital stock respectively would be more appropriate. However, this is a limitation of the measures used in this work.

10 Employment-Productivity Profile and Labour Demand Elasticity basis of 9056 unit level observations and the analysis of the later period uses 6522 observations 19. Composition of the firms however changed in the estimation of L D elasticity as the latter required fulfilling different criteria of analysis. Per capita NSDP value was downloaded from the RBI Handbook of Statistics. 4. Findings: 4.1. Change in L D across Productivity-groups and Firm-size: An Exploration: In this section, we attempt to examine whether or not any increase registered in labour demand is concentrated in the relatively high productivity firms or in the higher sizegroups (based on firm-level expenses on intermediate inputs) in the industry. We start with checking if average labour demand - measured in labour-days generated - has increased in the relatively high productivity sectors or in the low-productivity ones. For this, we have classified the sample units in different size groups based on the values of average labour productivity (AP L ). In Table 2, we have divided all the T&G firms into four quartile groups of AP L distribution. Summary statistics of L D - obtained after applying population weights - shows that greater mean L D values were recorded in the upper two productivity quartiles by T&G units of these two sections taken together in both the years. Just the opposite was true for the unorganized segment at both time-points while organized section displayed the same pattern in the last year. Median L D values followed the same pattern of recording greater values in the lowemost quartiles both for all the T&G units of the industry and for its unorganized part (the same table). For the organized segment, median value was relatively high in the top quartiles, particularly in the second and third quartiles Table 3 shows that increase in mean L D over time seems to have been concentrated in the rather higher productivity groups. Disaggregation into the organized and unorganized segments however indicates that the increase was greater in the lower productivity segments of the organized part of the industry 20. On the other hand, firms at both the lower and higher productivity ends of the unorganized segment seem to have experienced this rise 21. Reliability of these findings however seems to be compromised as the coefficient of variation of the extreme two productivity quartiles is quite high (see Table 4, for the selected summary statistics) i.e., the firms in those quartiles are not homogenous in terms of the criterion of grouping viz. average labour productivity Thus, we disaggregated the units further into productivity-deciles and tried to examine the pattern of change in L D across these deciles. It is clear from the Table 5 that the firms constituting different deciles (except the topmost one 22 ) of the T&G enterprises and their organized and unorganized sectors are relatively homogenous groups in terms of their respective productivity performances. 19 The final data set was obtained after excluding firms with non-positive values of output (the relevant measures-gross output or GVA) and/or inputs (capital, labour and material-fuel) to make it more reliable. 20 This was also true when we considered the rise in median L D values across the productivity quartiles of the organized segment (as Table A1 in the appendix shows). 21 Median L D also followed a similar pattern for the unorganized units and for all the sample units taken together. 22 The concerned CV has however decreased significantly at the last time-point.

11 164 The Journal of Industrial Statistics, Vol. 5, No Table 6 presents the change in mean values of estimated L D (obtained again by applying population weights) across productivity deciles at the two time-points concerned. It does not throw any clearly discernible pattern of relationship between the productivity performances of the firm and change in estimated labour demanded by it. There was rise in mean estimated L D in almost all the productivity deciles (except the third decile in the entire set of T&G firms as well as fourth and eighth productivity deciles of sample organized units) during the study period. The increase of the mean value for all the T&G units was concentrated towards the medium deciles especially sixth through ninth deciles. Estimated mean L D for the unorganized establishments increased more at both lower and upper ends than around the middle of the productivity distribution, as is expected from our conceptualization of the segment in Section 2. The pattern remains the same even if we consider the median L D (see Table 7 presenting selected descriptive statistics for the distribution of estimated L D ). 23 The pattern is not so clear for organized segment: the rise was greater in lowest three deciles, generally low in the topmost three deciles and fluctuated around the medium deciles. Thus, changes in both mean and median L D values do not indicate any definite relation between size-groups of productivity and change in average level of L D for the organized units during the study period The other possible way to get an idea of the distribution of L D across productivity deciles is to check if greater part of labour demand generated now is concentrated in the higher or lower productivity deciles than before. Thus, we proceed to examine whether firm-level change in L D has translated in any improvement in the share of higher productivity deciles in total labour demand. Table 8 presents the changing share of productivity deciles in total L D over time, taking all T&G units together and the organized and unorganized segments separately. The sample units in the sector as a whole definitely show an increased concentration of share in total L D around the middle section of the productivity distribution. Once we locate the changes in the two constituent segments, we find a clear deterioration in the distribution of estimated L D as the share has increased mainly in the lower productivity deciles of organized (except for the 7 th decile) and especially unorganized T&G firms. The striking observation here is that of a significantly high increase in share of the topmost two productivity deciles in the unorganized part indicating the possibility of a sustainable growth of firm in these productivity size-groups Next, we carry out a similar exercise by examining distribution of estimated L D in both the years across size-groups of firms classified in terms of firm-level expenses on intermediate inputs. 25 Firms were grouped initially in quartiles as well as deciles based on this criterion. However, the coefficient of variation in intermediate input costs is very high across both the quartiles and the decile-groups. To make the comparative analysis more meaningful we have resorted to a classification by trial whereby all the sample units were categorized in 17 clusters. Our aim in this categorization was to retain as many observations as possible in the analysis for both the time-points without allowing a very high coefficient of variation of intermediate input costs in individual clusters. Table 9 presents the details of this classification and the selected summary statistics for expenses on intermediate inputs 23 This was true also for all the sample units. 25 This seems better than the possible alternative schemes of size-classifications - based on size of employment or by stock of fixed capital. This is so because size-classification based on intermediate input costs is expected to minimize the problem of slack or underutilization.

12 Employment-Productivity Profile and Labour Demand Elasticity in these groups. Findings from the exploratory analysis of change in estimated mean L D and share of the groups so obtained in total L D are presented in Table Almost all the size groups experienced fall in mean AP L but quite a few of them registered positive change in mean L D. Considering all the T&G firms in the sample together we find clearly that the increase in mean L D is higher around the middle-sized firms. In fact the medium-sized firms had recorded higher share of L D in the aggregate demand for labour in both the years. Notwithstanding the declining productivity performance in most of the size-groups, a few also exhibited increase in their respective shares in total labour demand. It is clear, however from the above discussion that there is no definite and positive correspondence between the change in L D and level as well as over time growth in productivity in organized sphere of the industry. Employment growth in the unorganized part however seemed to be concentrated towards the two ends of productivity distribution. This probably indicates at some kind of stickiness in optimal adjustment of L D according to productivity performances in different segments of T&G firms. 4.2 Estimation of Labour Demand Elasticity: With the help of two-stage least square estimator we have carried out an instrumental variable regression analysis for estimating the labour demand elasticity. We could incorporate all the variables enlisted in the section 3.1 only in the L D estimation at the all-india level. Here we have reported only the results of the second stage of instrumental variable regression (presented in Table 12) 27. As mentioned earlier, we tried two possible instruments against firm output for the all-india regression: one used in similar studies on estimating labour demand elasticity (Y 1 _ins), the per capita net state domestic product (PCNSDP); and the alternative instrument devised in our study (Y 2 _ins). 28 What we find here is that the labour demand elasticity had the expected negative sign at the first time point while it was statistically insignificant at the end of the study period. The responsiveness of L D with respect to wage increases significantly if the concerned firm was in the organized sector while it decreased when the firm belonged to a state with greater degree of connectivity between organized and unorganized segments. The direction of influence on the same responsiveness of L D however changed during the study period for factors such as labour market rigidity, individual firm s effort in terms of improving inputs, degree of mechanization of the state in which the firm was located. Firms had responded more through adjusting L D to wage changes at the first time-point while it responded less at the end of the study period in states with higher labour market rigidity or in states with greater extent of mechanization in the unorganized segment Labour demand elasticity became significantly lower with firm s effort toward improvement in the basic non-capital inputs it used but did not differ significantly with its effort in terms of improvement in the capital stock and capital intensity in the first period. It 26 Similar results for the mentioned quartiles and deciles are not reported due to the reason specified here. 27 Results significant at least at 5% level are discussed only. 28 It was explained earlier in section 4.1. The first instrument however, never proved to be statistically significant with alternative measures of labour market rigidity or even after excluding the regressors with t-values less than one. Thus, we had reported only the results of the regression using the second instrument. 29 Labour market rigidity does not allow optimal adjustment in labour demand despite wage rise. Higher extent of mechanization in the unorganized segment probably facilitates greater subcontracting by organized units.

13 166 The Journal of Industrial Statistics, Vol. 5, No. 2 is noteworthy however that the elasticity increased significantly at the last time-point with enhanced effort toward improvement on both input and capital fronts. This seems encouraging as very little lowering of wage can bring about a substantially high and statistically significant increase in labour demand through complementary efforts in terms of physical capital and other inputs e.g. raw materials. Individual firm s location in the garment sector lowered the effect of one percent change in wage on the L D adjustment in the first year possibly indicating the relatively greater dominance of non-wage factors (especially stronger scale effect) in such adjustments compared to that among the textileproducing firms. The product-segment wise location of the firm however had no statistically significant effect on the labour demand elasticity at the latest year under consideration Results of estimation of labour demand through the 2SLS-IV regression for the selected thirteen states with major presence of both organized and unorganized T&G units are reported in Table 13 (second state dealing with the instrumented variable). Only the second instrument Y 2 _ins is used in this regression exercise. Like in the all India-level regression the instrument concerned was found to be positively significant in all states and at both the time-points Adjustment of labour demand with changing wage was of varied degree and in different directions in the selected states. Estimated labour demand elasticity had the expected negative sign in seven out of the 13 states in 2001(Andhra Pradesh, Gujarat, Karnataka, Kerala, Maharashtra, Uttar Pradesh and West Bengal). But in no state it was negative significant in The value was positive and statistically significant only in Tamil Nadu in the first year, while it became positive significant also in Delhi, Karnataka, Maharashtra, Rajasthan and West Bengal at the end of the study period. Among the latter set of states, Delhi and Rajasthan displayed statistically insignificant elasticity value in The estimated elasticity was insignificant at both time-points in Haryana, Madhya Pradesh and Punjab. In the states viz., Andhra Pradesh, Gujarat, Kerala and Uttar Pradesh, labour demand elasticity was negative significant in 2001 and it became statistically insignificant in the latter year. This indicates again the possibility of non-wage factors dominating individual firm s optimal adjustment of L D There was a few uniform patterns also, similar to the one exhibited in the estimation for all-india T&G labour demand function. For example, labour demand elasticity always increased when the firm in question operated in the organized segment rather than in the unorganized part of the industry. 31 This increase was statistically significant in all the states at both ends of the study period. Labour market rigidity generally exerted an expected negative significant effect on the elasticity values (except registering a positive significant effect in Punjab, Rajasthan and West Bengal and without any significant effect Gujarat and Kerala in 2001). It was negative and statistically significant at least at 5% level in all the states in the last year Similarly the responsiveness of L D to changing wages was lowered by the efforts toward improvement of non-capital inputs (except an insignificant effect in Andhra Pradesh 30 The coefficient value increased for Karnataka, Rajasthan and Tamil Nadu, remained almost the same in Andhra Pradesh, Delhi,Gujarat, and Kerala, and declined somewhat in the others. 31 As is expected from our discussion in Section 2, labour demand elasticity has actually increased at the end of the study period for a typical organized unit in all the states and at the all-india level.

14 Employment-Productivity Profile and Labour Demand Elasticity in 2011). 32 This might indicate that further possibility of enhancing labour demand by reducing wages may be limited if the effort in terms of improving non-capital inputs is already at a higher level. Operating in the garment sector also seems to have exerted a statistically significant negative influence on estimated labour demand elasticity. The effect was negative significant at both the time points in the states of Maharashtra, Rajasthan, Uttar Pradesh and West Bengal. It was negative significant in Andhra Pradesh, Gujarat and Kerala in 2001 but later became statistically insignificant. On the contrary, it was insignificant in the first year and became statistically significant (-) at the end of the study period in Madhya Pradesh and Tamil Nadu. The elasticity value did not differ significantly depending on the product-markets catered by the firms in both the years in the remaining states. Why labour demand adjusted in particular ways with changing wages and why the estimated labour demand elasticity was influenced by relevant locational and other factors in the above-discussed manner in the selected states however, needs a thorough mapping of more concrete state-specific characteristics and their effects on the labour demand condition in a comparative framework. This however lies beyond the scope of this preliminary analysis. 5. Conclusion 5.1 Indian textile policies in the recent years have gradually removed most important protective measures for decentralized and significant restrictions on the organized sectors giving way to the free interplay of market forces. In the near absence of growth-restricting regulations, optimal re-allocation of productive resources including labour through greater connectivity between the organized and unorganized segments seems to be an ongoing process. It is then logical to expect that the segments with lower-productivity and efficiency will be outcompeted and labour demand will mainly concentrate in the relatively growing section of T&G firms. On this backdrop, the present paper seeks to trace the pattern of change in employment in both the organized and unorganized firms in the Indian T&G industry. For this, we attempted to examine the inter-relationship between change in labour demand and the same in average labour productivity. Steeper rise in mean L D as well as share in aggregate L D was concentrated in groups of all T&G units, classified by intermediate input costs, which also registered substantial fall in AP L. Disaggregated exploration for the organized and unorganized segments indicated no definite pattern in the organized part while both mean L D and share in aggregate rose in the extreme size-groups of the unorganized T&G establishments. Thus the exploratory analysis pointed at the presence of some sort of stickiness in the behaviour of certain segments e.g. the survivalist unorganized set, with respect to productivity performances necessitating the study of firm-specific employment behaviour. 5.2 This prompted us to inquire the nature of L D adjustment with respect to changes in market structure and in policy shifts influencing the structure or having a direct bearing on the firm s conduct. The particular approach of estimating labour demand function and of deriving estimate of L D elasticity with respect to wage was adopted while controlling certain structural parameters. We sought to carry out the estimation using the two-stage least squares IV estimator at the all India level as well as for selected states with major presence 32 Like in the regression for all India units, we used the effort in terms of only non-labour inputs among the non-capital components such as raw-materials and fuels as a measure of input-based improvement effort and found similar results.