Bayesian Econometric Methods

By Gary Koop, Dale J. Poirier, J. Tobias. 2007

314 citations recorded by the source corpus.

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Citations in the corpus

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI (2019, neutral): “Bayesian models have been shown to lead to great insights in assorted applications such as cognitive modeling [201, 202], fishery [196, 203], gaming [204], climate [205], econometrics [206] or robotics [207].”
Where Can Tourism-Led Growth and Economy-Driven Tourism Growth Occur? (2019, unknown): “Following the suggestions from Koop, Poirier, and Tobias (2007), a parameter is regarded as “significant” if its associated 95% posterior interval does not include 0.”
How cognitive modeling can benefit from hierarchical Bayesian models. (2011, background): “…concept of exchangeability (e.g., Bernado & Smith, 2000; Schervish, 1995), while others emphasize particularly common and useful hierarchical structures like random-effects and latent mixture models, giving a sort of definition-by-example (e.g., Congdon, 2006; Koop, Poirer, & Tobias, 2007).”
Does Trust Promote Growth (2013, methodology): “The textbook treatment of BMA is available in Koop (2003) and Koop et al. (2007).”
Climate Change and Economic Growth in Africa: An Econometric Analysis (2015, methodology): “7 Detailed description of this model and similar hierarchical models in the Bayesian framework can be found in Koop et al. (2007). 8 We argue that using the average economic growth in the interval in time t –k to t and average weather variables for those periods are similar to the cross-country grow”