Results 31 to 40 of about 30,695 (301)
EconometricaEmpirical research typically involves a robustness‐efficiency tradeoff. A researcher seeking to estimate a scalar parameter can invoke strong assumptions to motivate a restricted estimator that is precise but may be heavily biased, or they can relax some of these assumptions to motivate a more robust, but variable, unrestricted estimator.
Armstrong, Timothy B. +2 more
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Acknowledging Misspecification in Macroeconomic Theory
, 2002 We explore methods for confronting model misspecification in macroeconomics. We construct dynamic equilibria in which private agents and policy makers recognize that models are approximations.
Thomas J. Sargent, Lars Peter Hansen
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Confronting model misspecification in macroeconomics [PDF]
Journal of Econometrics, 2012 We estimate a Markov-switching mixture of two familiar macroeconomic models: a richly parameterized dynamic stochastic general equilibrium (DSGE) model and a corresponding Bayesian vector autoregression (BVAR) model. We show that the Markov-switching mixture model dominates both individual models and improves the fit considerably.
Daniel F. Waggoner, Tao Zha
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Making Decisions under Model Misspecification [PDF]
SSRN Electronic Journal, 2020 Abstract We use decision theory to confront uncertainty that is sufficiently broad to incorporate “models as approximations.” We presume the existence of a featured collection of what we call “structured models” that have explicit substantive motivations.
Cerreia–Vioglio, Simone +3 more
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Experiment 2: Misspecification and censoring.
, 2023 Relative bias of the MHRATT estimation methods for varying censoring rates and different DGPs. Sample size is n = 1500, true MHRATT = 0.8 and good overlap (k = 1). In Scenario (A) there is no model misspecification. (TIF)
Guilherme W. F. Barros (17598966) +2 more
core +1 more source
Structured Ambiguity and Model Misspecification
Journal of Economic Theory, 2018 A decision maker is averse to not knowing a prior over a set of restricted structured models (ambiguity) and suspects that each structured model is misspecified. The decision maker evaluates intertemporal plans under all of the structured models and, to recognize possible misspecifications, under unstructured alternatives that are statistically close ...
Lars Peter Hansen, Thomas J. Sargent
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Agribusiness, EarlyView.ABSTRACT In the agricultural landscape of most developing countries, the last decade has witnessed the expansion of outsourced agricultural extension services. Private firms and nongovernmental organizations focused on delivering agricultural extension and advisory services to farmers have emerged.
Boris D. Soh Wenda +3 more
wiley +1 more source
Modeling Model Misspecification in Structural Equation Models
Stats, 2023 Structural equation models constrain mean vectors and covariance matrices and are frequently applied in the social sciences. Frequently, the structural equation model is misspecified to some extent.
Alexander Robitzsch
doaj +1 more source
Informational herding with model misspecification [PDF]
Journal of Economic Theory, 2014 This paper demonstrates that a misspecified model of information processing interferes with long-run learning and offers an explanation for why individuals may continue to choose an inefficient action, despite sufficient public information to learn the true state. I consider a social learning environment where agents draw inference from private signals,
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Agribusiness, EarlyView.ABSTRACT Using survey and discrete choice experiment data, we examined US specialty crop growers' preferences for marketing contract attributes in the context of emerging blockchain‐based technologies and expanding traceability initiatives. Results show that farmers preferred traditional written contracts but might be willing to accept digital ...
Elizabeth Canales +3 more
wiley +1 more source