Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

/pdf/the-theory-of-industrial-organization-19bejph0ej.pdf

The Theory of Industrial Organization

The theory of precautionary saving is shown in this paper to be isomorphic to the Arrow-Pratt theory of risk aversion, making possible the application of a large body of knowledge about risk aversion to precautionary saving, and more generally, to the theory of optimal choice under risk In particular, a measure of the strength of precautionary saving motive analogous to the Arrow-Pratt measure of risk aversion is used to establish a number of new propositions about precautionary saving, and to give a new interpretation of the Oreze-Modigliani substitution effect

Precautionary Saving in the Small and in the Large

A critical question facing experimental economists is whether behavior inside the laboratory is a good indicator of behavior outside the laboratory. To address that question, we build a model in which the choices that individuals make depend not just on financial implications, but also on the nature and extent of scrutiny by others, the particular context in which a decision is embedded, and the manner in which participants and tasks are selected. We present empirical evidence demonstrating the importance of these various factors. To the extent that lab and naturally occurring environments systematically differ on any of these dimensions, the results obtained inside and outside the lab need not correspond. Focusing on experiments designed to measure social preferences, we discuss the extent to which the existing laboratory results generalize to naturally-occurring markets. We summarize cases where the lab may understate the importance of social preferences as well as instances in which the lab might exaggerate their importance. We conclude by emphasizing the importance of interpreting laboratory and field data through the lens of theory.

/pdf/what-do-laboratory-experiments-measuring-social-preferences-178u4j8nii.pdf

What Do Laboratory Experiments Measuring Social Preferences Reveal About the Real World

Proponents of the Bayh-Dole Act argue that industrial use of federally funded research would be reduced without university patent licensing. Our survey of U.S. universities supports this view, emphasizing the embryonic state of most technologies licensed and the need for inventor cooperation in commercialization. Thus, for most university inventions, there is a moral-hazard problem with inventor effort. For such inventions, development does not occur unless the inventor's income is tied to the licensee's output by payments such as royalties or equity. Sponsored research from the licensee cannot by itself solve this problem.

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Proofs and Prototypes for Sale: The Licensing of University Inventions

The Stone index typically used in estimating linear almost ideal demand systems is not invariant to changes in units of measurement, which may seriously affect the approximation properties of the model. A modification to the Stone index, or use of a regular price index instead, are both desirable practices in estimating linear AI models.

/pdf/units-of-measurement-and-the-stone-index-in-demand-system-1k3i13sibd.pdf

Units of Measurement and the Stone Index in Demand System Estimation

Uncertainty and risk are quintessential features of agricultural production. After a brief overview of the main sources of agricultural risk, we provide an exposition of expected utility theory and of the notion of risk aversion. This is followed by a basic analysis of agricultural production decisions under risk, including some comparative statics results from stylized models. Selected empirical topics are surveyed, with emphasis on risk analyses as they pertain to production decisions at the farm level. Risk management is then discussed, and a synthesis of hedging models is presented. We conclude with a detailed review of agricultural insurance, with emphasis on the moral hazard and adverse selection problems that arise in the context of crop insurance.

Chapter 2 Uncertainty, risk aversion, and risk management for agricultural producers

The profound changes that have affected agriculture in modern times are perhaps best illustrated by the evolution of production techniques due to mechanization, new chemical inputs such as herbicides, pesticides and fertilizers, genetic selection of crops and animals, new crop varieties, and countless other technical and organizational improvements. These innovations have allowed a generalized increase in physical output while, at the same time, agriculture has suffered a massive exodus of labor forces towards the non-farm sectors. Indeed, a stylized fact of developed countries’ post-war growth is that productivity in agriculture has grown faster than in other sectors (Jorgenson and Gollop, 1992). This remarkable record naturally begs the question of what is at its root, and a view that commands considerable consensus is that agricultural productivity growth is due to (past) investments in scientific research and development (R&D).

https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1286&context=econ_las_staffpapers

Intellectual Property Rights and the Welfare Effects of Agricultural R&D

Uncertainty, Risk Aversion, and Risk Management for Agricultural Producers

A three-region world model for the soybean complex is developed to evaluate the welfare effects of Roundup Ready (RR) soybean adoption. The structural modeling of the innovation accounts for farmers’ adoption incentives and for the observed pricing of RR soybean seeds as a proprietary technology. The calibrated model is solved for various scenarios to evaluate the production, price, and welfare impacts of RR soybean adoption. The United States gains substantially from the innovation, with the innovator capturing the larger share of the welfare gains. US farmers benefit in the base scenario, but would be adversely affected if the RR innovation were to increase yields. Spillover of the new technology to foreign competitors erodes the competitive position of domestic soybean producers, and export of the technology per se may not improve the welfare position of the innovating country. Consumers in every region gain from the adoption of RR soybeans. [ JEL Classification: F14, O33, Q16]. © 2000 John Wiley & Sons, Inc.

https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1325&context=econ_las_staffpapers

GianCarlo Moschini

Papers

Units of Measurement and the Stone Index in Demand System Estimation

Chapter 2 Uncertainty, risk aversion, and risk management for agricultural producers

Intellectual Property Rights and the Welfare Effects of Agricultural R&D

Uncertainty, Risk Aversion, and Risk Management for Agricultural Producers

Roundup Ready Soybeans and Welfare Effects in the Soybean Complex