Results 281 to 290 of about 5,857,634 (333)
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1985
Recent advances in establishing the nature and scope of estimators in econometrics have shed more light on the importance of instrumental variables. In this book, the authors argue that such methods may be regarded as a strong organizing principle for a wide variety of estimation and hypothesis testing problems in econometrics and statistics.
Roger J. Bowden, Darrell A. Turkington
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Recent advances in establishing the nature and scope of estimators in econometrics have shed more light on the importance of instrumental variables. In this book, the authors argue that such methods may be regarded as a strong organizing principle for a wide variety of estimation and hypothesis testing problems in econometrics and statistics.
Roger J. Bowden, Darrell A. Turkington
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Variable frequency bioimpedance instrumentation
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2005The design of instrumentation used to measure the bioimpedance of skin or tissue is presented. An inexpensive, component level approach, appropriate for use by researchers rather that commercial applications, is emphasized. The design and implementation process is thoroughly explained and design tradeoffs are discussed with relation to various ...
D, Tsunami +4 more
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Instrumental variables estimation: Assumptions, pitfalls, and guidelines
Leadership Quarterly, 2023Nicolas Bastardoz +5 more
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Instrumental and "Quasi-Instrumental" Variables
American Journal of Political Science, 1991The trade-off between the efficiency of an instrumental variable and its exogeneity is widely recognized but little understood. This paper specifies the terms of that trade-off by analyzing the asymptotic mean squared errors associated with the instrumental variables estimator when the instrument may not be perfectly exogenous.
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Statistical Inference in Instrumental Variables Regression with I(1) Processes
, 1990P. Phillips, B. Hansen
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Split Sample Instrumental Variables [PDF]
, 1993 Instrumental Variables (IV) estimates tend to be biased in the same direction as Ordinary Least Squares (OLS) in finite samples if the instruments are weak. To address this problem we propose a new IV estimator which we call Split Sample Instrumental Variables (SSIV).
Joshua Angrist, Alan B. Krueger
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