Model selection and loss functions for structural time series: networks, spatial models, causality measures, and misspecified or redundant moment conditions

Scidá, Daniela

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Year:: 2016
Contributor:: Scidá, Daniela (creator); Renault, Eric (Director); McCloskey, Adam (Reader); Dungey, Mardi (Reader); Brown University. Economics (sponsor)
Genre:: theses
Subject:: Kullback causality measures; Granger causality; Markov property; non-nested hypotheses; financial networks; SVAR models; spatial models; GMM; misspecified moment conditions; AMSE reduction; optimal weighting matrix; redundancy; Financial institutions--Computer networks; Spatial systems--Mathematical models
Extent:: xiv, 187 p.
DOI: https://doi.org/10.7301/Z0TQ5ZXB

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Abstract:: This dissertation is comprised of the following three chapters: (1) "Causality and Markovianity: Information Theoretic Measures" (joint work with Eric Renault), my job market paper entitled (2) "Structural VAR and Financial Networks: A Minimum Distance Approach to Spatial Modeling," and my third year paper entitled (3) "GMM with Minimum Mean Squared Error." All three chapters are about econometric methodology for time series, with a particular focus on model selection and loss functions. They include both theoretical and empirical developments about Information Theory in Econometrics, Generalized Method of Moments, Networks, and Spatial Modeling. The common feature of all the econometric methodologies developed in this dissertation is the applicability to financial econometrics.
Notes:: Thesis (Ph.D. -- Brown University (2016)

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Rights: In Copyright
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Scidá, Daniela, "Model selection and loss functions for structural time series: networks, spatial models, causality measures, and misspecified or redundant moment conditions" (2016). Economics Theses and Dissertations. Brown Digital Repository. Brown University Library. https://doi.org/10.7301/Z0TQ5ZXB

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Economics Theses and Dissertations

Theses and Dissertations for the Economics department.
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