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Noel D. Uri

Researcher at Federal Trade Commission

Publications -  90
Citations -  572

Noel D. Uri is an academic researcher from Federal Trade Commission. The author has contributed to research in topics: Load duration curve & Price elasticity of demand. The author has an hindex of 13, co-authored 90 publications receiving 559 citations. Previous affiliations of Noel D. Uri include The Catholic University of America.

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A note on spatial and temporal price and allocation modeling: Quadratic programming or linear complementary programming?

TL;DR: In this paper, a clarification of the specific conditions under which the linear complementary programming (LCP) formulation is applicable in such areas as spatial and temporal price and allocation modeling is presented.
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Geographic Markets, Causality and Railroad Deregulation

TL;DR: In this article, an approach to define a market using the notion of instantaneous causality is presented, and the market for which the approach is empirically implemented is the flour market in the United States over the period January 1979 through October 1982.
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Conservation tillage and the use of energy and other inputs in US agriculture

Noel D. Uri
- 01 Sep 1998 - 
TL;DR: The effectiveness of conservation tillage practices in reducing the impact of agricultural production on the environment is dependent on what happens to energy, pesticide and fertilizer use as these practices are more extensively adopted as mentioned in this paper.
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The demand for beverages and interbeverage substitution in the united states

TL;DR: In this article, the authors measured the substitution between seven beverages consumed in the United States with the objective of shedding some light on just what is the relevant market for antitrust purposes with regard to the overall beverage market.
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A re-examination of the relationship between industry structure and economic performance

Noel D. Uri
- 01 Oct 1988 - 
TL;DR: In this paper, the authors developed a simultaneous equations model of profitability, concentration, advertising expenditures and research and development outlays to determine the importance to the estimation results of a subset of the data that can have a disproportionate influence.