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Sensitivity to missing data assumptions : theory and an evaluation of the U.S. wage structure

Kline, Patrick; Santos, Andres - In: Quantitative economics : QE ; journal of the … 4 (2013) 2, pp. 231-267

This paper develops methods for assessing the sensitivity of empirical conclusions regarding conditional distributions to departures from the missing at random (MAR) assumption. We index the degree of nonignorable selection governing the missing data process by the maximal Kolmogorov–Smirnov...

Persistent link: https://www.econbiz.de/10011757060

Computing sensitivities for distortion risk measures

Glynn, Peter W.; Peng, Yijie; Fu, Michael; Hu, Jian-Qiang - In: INFORMS journal on computing : JOC 33 (2021) 4, pp. 1520-1532

Persistent link: https://www.econbiz.de/10012796944

Nonparametric inference for sensitivity of Haezendonck-Goovaerts risk measure

Wang, Xing; Liu, Qing; Hou, Yanxi; Peng, Liang - In: Scandinavian actuarial journal (2018) 8, pp. 661-680

Persistent link: https://www.econbiz.de/10011939722

Sensitivity to Calibrated Parameters

Jørgensen, Thomas - 2020

Across many fields in economics, a common approach to estimation of economic models is to calibrate a sub-set of model parameters and keep them fixed when estimating the remaining parameters. Calibrated parameters likely affect conclusions based on the model but estimation time often makes a...

Persistent link: https://www.econbiz.de/10012835737

Sensitivity to calibrated parameters

Jørgensen, Thomas H. - 2021

A common approach to estimation of dynamic economic models is to calibrate a sub-set of model parameters and keep them fixed when estimating the remaining parameters. Calibrated parameters likely affect conclusions based on the model but estimation time often makes a systematic investigation of...

Persistent link: https://www.econbiz.de/10012485059

Sensitivity to Calibrated Parameters

Jorgensen, Thomas H. - 2020

Across many ﬁelds in economics, a common approach to estimation of economic models is to calibrate a sub-set of model parameters and keep them ﬁxed when estimating the remaining parameters. Calibrated parameters likely affect conclusions based on the model but estimation time often makes a...

Persistent link: https://www.econbiz.de/10012217015

Scenario Weights for Importance Measurement (SWIM) – an R package for sensitivity analysis

Pesenti, Silvana M.; Bettini, Alberto; Millossovich, Pietro - In: Annals of actuarial science 15 (2021) 2, pp. 458-483

Persistent link: https://www.econbiz.de/10012593589

Scenario Weights for Importance Measurement (SWIM) – An R Package for Sensitivity Analysis

Pesenti, Silvana M. - 2020

The SWIM package implements a flexible sensitivity analysis framework, based primarily on results and tools developed by Pesenti et al. (2019). SWIM provides a stressed version of a stochastic model, subject to model components (random variables) fulfilling given probabilistic constraints...

Persistent link: https://www.econbiz.de/10012844635

Reexamining the evidence on gun ownership and homicide using proxy measures of ownership

Chalak, Karim; Kim, Daniel; Miller, Megan; Pepper, John V. - In: Journal of public economics 208 (2022), pp. 1-9

Persistent link: https://www.econbiz.de/10013347438

Non-Equivalence of Measurement in Latent Variable Modelling of Multigroup Data : A Sensitivity Analysis

Kuha, Jouni; Moustaki, Irini - 2013

consideration is the comparability or equivalence of measurement across the groups. Ideally full equivalence would hold, but very … often it does not. If non-equivalence of measurement is ignored when it is present, substantively interesting comparisons … variable models can be sensitive to assumptions about measurement, in that non-equivalence of measurement does not need to be …

Persistent link: https://www.econbiz.de/10014153331