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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.
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