Technical change and its measurement is a fascinating subject. The various procedures to measure technical change fall into two categories (i).The parametric approach and (ii). The non-parametric approach. In theformer case, a parametric production function is postulated a priori, using it as basic tool, technical change is estimated. The present book aims at presenting a method to measure technicalprogress relaxing the assumptions of full profit efficiency and constant returns to scale. The method is essentially non-parametric, in which wesolve a number of linear programming problems, first to measure frontier technical change and hence, to estimate average technical change.The rate of shift of frontier production function is attributed to technical progress or innovation and rate of change in profit efficiency is assumed to be due to the CATCHING UP effort of the producer to reach the frontier.

In the present book Chapter - I is an introductory one. It contains the general introduction about the problem of distributed lag models. Chapter - II deals with the specification of the distributed lag models through expectations models.Chapter - III describes the estimation methods for different finite distributed lag models existing in the literature.Chapter - IV gives the details about the various infinite distributed lag models existing in the literature along with the estimation of their parameters.Chapter - V develops a new estimation procedure for a finite distributed lag model by using Bernstein polynomial approximation to a function on which the lag weights are assumed to lie. Chapter - VI depicts the conclusions Several relevant articles regarding the distributed lag models have been presented under the title 'BIBLIOGRAPHY'.

The commercial banking sector in India is constituted by public, private and foreign sector banks. Public sector banks operate at a larger scale than private and foreign sector banks. Before nationalization of Banks they played the role of financial intermediaries whose objectives were deposit collection and lending. Though the Public and Private sector banks are regulated by RBI and Govt. of India, these two sectors are different in their objectives and activities. The public sector banks supply huge credit to priority sectors below the market rate of credit. Therefore, it is desirable to compare the production efficiency of the two sectors of banks. The parameters of comparison are input over all, pure, scale, allocative and cost efficiencies. In several cases actual prices are not known, in some other cases it is required to find potential (minimum) prices and the extent of deviation of actual prices from potential prices. One can also find the prices that can make the producer allocatively efficient. In this book We concentrate on the prices that induce the production unit allocatively efficient and we call them as our shadow prices.

The study estimates efficiency magnitudes by applying LPP technic and compare them with their Stochastic Counterparts. The proposed study combines timeseries, cross section observations on Inputs, Input prices, outputs, derives factor minimal cost functions and formulates the Likelihood functions and maximise them to find MLEs of known parameters. This kind of research study can be further extended to any other functional forms like CES and TRANSLOG production functions etc., with comfortable ease.

Measurement of technical progress dates back to Solow (1957) who expressed technical change as residual, obtained by subtracting weighed input growth from output growth. There were studies of measuring technical change based on factor minimal cost function, assuming technical change is Hicks neutral, producer was at equilibrium. There existed studies which assumed technical change was non-neutral. The present study assumed technical change is Hicks neutral. To measure technical change input-output quantities alone can be used; or input-output quantities and their prices can be utilized; or accounting approach can be used to decompose output growth into their sources; further, production approach can be used; cost function approach can also be used.The various models have been specified in the form of Linear Programming Problems to measure technical changes based on Returns to scale and Input technical efficiencies.