Quantile Methods for Stochastic Frontier Analysis (Foundations and Trends(r) in Econometrics)
Language: English
Published by Now Publishers, 2022
- Softcover
- Used
Seller: Blue Vase Books, Interlochen, MI, U.S.A.Blue Vase Books
AbeBooks seller since May 22, 2017
Condition: Used - Good
£ 386.18
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The item shows wear from consistent use, but it remains in good condition and works perfectly. All pages and cover are intact including the dust cover, if applicable . Spine may show signs of wear. Pages may include limited notes and highlighting. May NOT include discs, access code or other supplemental materials.
Seller Inventory # BVV.1638280940.G
- Title
- Quantile Methods for Stochastic Frontier Analysis (Foundations and Trends(r) in Econometrics)
- Author
- Papadopoulos, Alecos; Parmeter, Christopher F
- Publisher
- Now Publishers
- Publication year
- 2022
- Condition
- good
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1638280940
- ISBN 13
- 9781638280941
Sections 1 to 5 present the current state of affairs. Section 1 details the very close link between the regression function and the conditional quantile function, in order to show that the quantile relation is not some disconnected statistical aspect that lives independently of our regression specification. This section also shows what the quantile approach and the Q-estimator actually do, and we contrast this with what SFA models want to do, using also a simulated example. Section 2 presents the main characteristics and properties of the linear Q-estimator when the error term is independent of the regressors, as a necessary preparation to move to Section 3, where the authors show how some of these properties are fundamentally incompatible with the goals and purposes of SFA. Section 4 discusses recent advances that properly construct the deterministic frontier. Section 5 moves away from quantile regression and presents likelihood-based approaches that use density functions that include as one of their parameters the probability of the zero-quantile of their distributions. Sections 6 to 9 present a new estimator, but also metrics and insights that allow to fruitfully use the quantile approach in SFA. Section 6 shows how one can use the Qestimator together with additional assumptions in order to provide conceptually valid and useful estimation and inference results in SFMs. Section 7 presents quantile-dependent measures of efficiency both at the sample level, and at the individual level, but also how the conditional quantiles of the distribution of inefficiency can be used to offer a picture of how individual efficiency scores are distributed around a chosen quantile of the efficiency distribution. Section 8 proves a fundamental result: that positive and high values of the composite error term of production SFA models, are expected to co-exist with low inefficiency, in a concrete probabilistic sense. Section 9 examines the case of dependence between the error term and the regressors or other covariates. Section 10 provides an empirical illustration that showcases the approach of the four previous Sections, and functions as a guide for detailed applied studies. Section 11 includes a list of the various open issues as well as ideas and directions for future research, while Section 12 offers a short summary and conclusions.
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Blue Vase Books
Interlochen, MI, U.S.A.
AbeBooks seller since May 22, 2017
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