Abstract

The term productivity was used for the first time over two centuries ago, in the Journal de l’ Agriculture (Tangen, S., 2005). It has been applied in many different circumstances, particularly in relation to economic system, at various levels of aggregation. Productivity is the ratio of what is produced by an operation of process to what is required to produce it, or put simply the ratio of actual output to input over a period of time. Inputs might include transforming and transformed resources (such as materials, equipment, customers and staff) and the outputs are goods and services (Schroeder, R.G., 1985; Slack, N et al, 2001). Measurement of productivity is associated with the extraction of the share of factor input from an increment in output which otherwise cannot be accounted for by mere increase in the quantity of input. Alternatively, productivity means a ratio of actual output to expect resources used. In simpler version, it can be understood as how much and how well one produces from the resources used. If more is produced or better goods are yielded from the same resources, increase in productivity is understood. Productivity varies due to differences in technology, differences in the efficiency in the production process and the differences in the environment in which the production unit operates. The usual method of analysis of productivity is based on the standard definition of production function where it is assumed that maximum output is attended at a given level of input. There are various productivity measures. The choice between them depends on the purpose of productivity measurement and, in many instances, on the availability of the data. Broadly, the measures can be classified as single factor productivity measures (relating to measure of output to a single measure of input) or Multifactor productivity measures (relating a measure of output to a bundle of inputs). Another distinction, of particular relevance at the industry or firm level is between productivity measures that relate some measure of gross output to one or several inputs and those which use a value added concept to capture movement of output. These are measures of labour and capital productivity, and multifactor productivity measures (MFP), in the form of capital- labour MFP, based on a value-added concept of output, or in the form of capital-labor-energy-materials MFP (KLEMS), based on a concept of Gross Output. Among those measures, value added based labour productivity is the single most frequently computed productivity statistics, followed by capital-labour MFP and KLEMS MFP. The Proposed paper is an attempt to measure the Productivity of Indian Cement Industry through the empirical study for a period of 33 Years starting from 1973-74. ASI data is been used with Price correction at WPI (2001-02) and CPI (2002-03) Bases. The productivity indices like Technological change measured through Elasticity of Substitution amongst core factor inputs like labour and capital, Total factor Productivity based on Solow Model on Technological Progress, Capital Intensity and DEA technique to measure Allocative and Technical Efficiencies with 18 decision making units (18 States) and Total Outputs-Net Value Added, Gross Capital Formation & Income are considered for analysis. 2004-05 ASI data is been used.

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