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Journal ArticleDOI

Decomposition of Technological Change and Factor Bias in Indian Power Sector: An Unbalanced Panel Data Approach

TL;DR: In this article, the authors analyzed technological change and factor bias in the Indian power sector using a translog cost function and identified the major factors contributing to technological progress, including accumulation of knowledge and increasing scale.
Abstract: Technological change and factor bias in the Indian power sector are analyzed using a translog cost function. Various components of technological progress and factor bias are identified and estimated, using a 21 year unbalanced panel data of Indian states and union territories. Heterogeneity across states is incorporated in the model using a variance component model. Appropriate corrections are made for unbalanced panel data. Empirical results show that the annual average rate of technological progress has been 2.4% for the country as a whole. Accumulation of knowledge and increasing scale are found to be the major factors contributing to technological progress. In contrast, the effects of factor price changes and fixed capital accumulation on technological progress have been unfavorable. Pure factor bias measure indicate saving in the use of fuel and labor, and increased use of materials. Tests are performed to check the curvature properties of the underlying technology.
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Book
25 Jul 1986
TL;DR: In this paper, the authors propose a homogeneity test for linear regression models (analysis of covariance) and show that linear regression with variable intercepts is more consistent than simple regression with simple intercepts.
Abstract: 1. Introduction 2. Homogeneity test for linear regression models (analysis of covariance) 3. Simple regression with variable intercepts 4. Dynamic models with variable intercepts 5. Simultaneous-equations models 6. Variable-coefficient models 7. Discrete data 8. Truncated and censored data 9. Cross-sectional dependent panel data 10. Dynamic system 11. Incomplete panel data 12. Miscellaneous topics 13. A summary view.

6,234 citations

Journal ArticleDOI
TL;DR: The Elements of Econometrics as mentioned in this paper is a textbook for upper-level undergraduate and master's degree courses and may usefully serve as a supplement for traditional Ph.D. courses in economics.
Abstract: This classic text has proven its worth in university classrooms and as a tool kit in research--selling over 40,000 copies in the United States and abroad in its first edition alone. Users have included undergraduate and graduate students of economics and business, and students and researchers in political science, sociology, and other fields where regression models and their extensions are relevant. The book has also served as a handy reference in the "real world" for people who need a clear and accurate explanation of techniques that are used in empirical research.Throughout the book the emphasis is on simplification whenever possible, assuming the readers know college algebra and basic calculus. Jan Kmenta explains all methods within the simplest framework, and generalizations are presented as logical extensions of simple cases. And while a relatively high degree of rigor is preserved, every conflict between rigor and clarity is resolved in favor of the latter. Apart from its clear exposition, the book's strength lies in emphasizing the basic ideas rather than just presenting formulas to learn and rules to apply.The book consists of two parts, which could be considered jointly or separately. Part one covers the basic elements of the theory of statistics and provides readers with a good understanding of the process of scientific generalization from incomplete information. Part two contains a thorough exposition of all basic econometric methods and includes some of the more recent developments in several areas.As a textbook, "Elements of Econometrics" is intended for upper-level undergraduate and master's degree courses and may usefully serve as a supplement for traditional Ph.D. courses in econometrics. Researchers in the social sciences will find it an invaluable reference tool.A solutions manual is also available for teachers who adopt the text for coursework.Jan Kmenta is Professor Emeritus of Economics and Statistics, University of Michigan.

3,838 citations

Journal ArticleDOI
TL;DR: In this paper, a simple test for heteroscedastic disturbances in a linear regression model is developed using the framework of the Lagrangian multiplier test, and the criterion is given as a readily computed function of the OLS residuals.
Abstract: A simple test for heteroscedastic disturbances in a linear regression model is developed using the framework of the Lagrangian multiplier test. For a wide range of heteroscedastic and random coefficient specifications, the criterion is given as a readily computed function of the OLS residuals. Some finite sample evidence is presented to supplement the general asymptotic properties of Lagrangian multiplier tests.

3,629 citations

Book
01 Jun 1985
TL;DR: In this article, the authors proposed a method to improve the quality of the information provided by the user by using the information of the user's interaction with the service provider and the user.
Abstract: Фундаментальный учебник по теории развития сельского хозяйства как отрасли. Рассматривается развитие сектора в историческом масштабе, специфика развития отрасли в развитых и развивающихся странах (с акцентом на развитие в странах с избыточной рабочей силой). В книге представлены следующие темы: аграрная экономика и её роль в общем процессе экономического развития, структурная трансформация, стратегии и модели развития сельского хозяйства и аграрная структура, взаимосвязь сельского хозяйства и промышленности, государственная политика в области сельского хозяйства, макроэкономика и сельское хозяйство, либерализация торговли сельскохозяйственной продукцией.

2,595 citations

Posted Content
TL;DR: In this article, the authors developed two methods for imposing curvature conditions globally in the context of cost function estimation, based on a generalization of a functional form first proposed by McFadden.
Abstract: Empirically estimated flexible functional forms frequently fail to satisfy the appropriate theoretical curvature conditions. Lau and Gallant and Golub have worked out methods for imposing the appropriate curvature conditions locally, but those local techniques frequently fail to yield satisfactory results. We develop two methods for imposing curvature conditions globally in the context of cost function estimation. The first method adopts Lau's technique to a generalization of a functional form first proposed by McFadden. Using this Generalized McFadden functional form, it turns out that imposing the appropriate curvature conditions at one data point imposes the conditions globally. The second method adopts a technique used by McFadden and Barnett, which is based on the fact that a non-negative sum of concave functions will be concave. Our various suggested techniques are illustrated using the U.S. Manufacturing data utilized by Berndt and Khaled

1,014 citations