13,864 research outputs found
Symmetry-Aware Marginal Density Estimation
The Rao-Blackwell theorem is utilized to analyze and improve the scalability
of inference in large probabilistic models that exhibit symmetries. A novel
marginal density estimator is introduced and shown both analytically and
empirically to outperform standard estimators by several orders of magnitude.
The developed theory and algorithms apply to a broad class of probabilistic
models including statistical relational models considered not susceptible to
lifted probabilistic inference.Comment: To appear in proceedings of AAAI 201
SEMIPARAMETRIC BAYESIAN ANALYSIS OF SIMULTANEOUS SYSTEMS WITH AN APPLICATION TO JAPANESE MEAT DEMAND
This paper motivates and applies a variant of the Bayesian Bootstrap Multivariate Regression by Heckelei and Mittelhammer (2003) to a Japanese meat demand specification with endogenous regressors. The methodology is first given an alternative and more elegants motivation and then extended to incorporate microtheoretic restrictions and to apply in the context of a simultaneous equation models. The results of the application are compared to results based on an earlier approach used by Heckelei, Mittelhammer, and Wahl (1996).Demand and Price Analysis,
Equation of state for Universe from similarity symmetries
In this paper we proposed to use the group of analysis of symmetries of the
dynamical system to describe the evolution of the Universe. This methods is
used in searching for the unknown equation of state. It is shown that group of
symmetries enforce the form of the equation of state for noninteracting scaling
multifluids. We showed that symmetries give rise the equation of state in the
form and energy density
, which
is commonly used in cosmology. The FRW model filled with scaling fluid (called
homological) is confronted with the observations of distant type Ia supernovae.
We found the class of model parameters admissible by the statistical analysis
of SNIa data. We showed that the model with scaling fluid fits well to
supernovae data. We found that and (), which can correspond to (hyper) phantom fluid, and to a
high density universe. However if we assume prior that
then the favoured model is close to concordance
CDM model. Our results predict that in the considered model with
scaling fluids distant type Ia supernovae should be brighter than in
CDM model, while intermediate distant SNIa should be fainter than in
CDM model. We also investigate whether the model with scaling fluid is
actually preferred by data over CDM model. As a result we find from
the Akaike model selection criterion prefers the model with noninteracting
scaling fluid.Comment: accepted for publication versio
Post-selection point and interval estimation of signal sizes in Gaussian samples
We tackle the problem of the estimation of a vector of means from a single
vector-valued observation . Whereas previous work reduces the size of the
estimates for the largest (absolute) sample elements via shrinkage (like
James-Stein) or biases estimated via empirical Bayes methodology, we take a
novel approach. We adapt recent developments by Lee et al (2013) in post
selection inference for the Lasso to the orthogonal setting, where sample
elements have different underlying signal sizes. This is exactly the setup
encountered when estimating many means. It is shown that other selection
procedures, like selecting the largest (absolute) sample elements and the
Benjamini-Hochberg procedure, can be cast into their framework, allowing us to
leverage their results. Point and interval estimates for signal sizes are
proposed. These seem to perform quite well against competitors, both recent and
more tenured.
Furthermore, we prove an upper bound to the worst case risk of our estimator,
when combined with the Benjamini-Hochberg procedure, and show that it is within
a constant multiple of the minimax risk over a rich set of parameter spaces
meant to evoke sparsity.Comment: 27 pages, 13 figure
Endogenous Persistence in an Estimated DSGE Model under Imperfect Information
We provide a tool for estimating DSGE models by BayesianMaximum-likelihood methods under very general information assumptions. This framework is applied to a New Keynesian model where we compare the standard approach, that assumes an informational asymmetry between private agents and the econometrician, with an assumption of informational symmetry. For the former, private agents observe all state variables including shocks, whereas the econometrician uses only data for output, inflation and interest rates. For the latter both agents have the same imperfect information set and this corresponds to what we term the 'informational consistency principle'. We first assume rational expectations and then generalize the model to allow some households and firms to form expectations adaptively. We find that in terms of model posterior probabilities, impulse responses, second moments and autocorrelations, the assumption of informational symmetry by rational agents significantly improves the model fit. We also find qualified empirical support for the heterogenous expectations model. JEL Classification: C11, C52, E12, E32.Imperfect Information, DSGE Model, Rational versus Adaptive Expectations, Bayesian Estimation
Endogenous Persistence in an Estimated DSGE Model under Imperfect Information
We provide a tool for estimating DSGE models by Bayesian Maximum-likelihood meth?ods under very general information assumptions. This framework is applied to a New Keynesian model where we compare the standard approach, that assumes an informa?tional asymmetry between private agents and the econometrician, with an assumption of informational symmetry. For the former, private agents observe all state variables including shocks, whereas the econometrician uses only data for output, inflation and interest rates. For the latter both agents have the same imperfect information set and this corresponds to what we term the ĆĀ”ĆĀ®informational consistency principleĆĀ”ĆĀÆ. We first assume rational expectations and then generalize the model to allow some households and firms to form expectations adaptively. We find that in terms of model posterior probabilities, impulse responses, second moments and autocorrelations, the assumption of informational symmetry by rational agents significantly improves the model fit. We also find qualified empirical support for the heterogenous expectations model.Imperfect Information, DSGE Model, Rational versus Adaptive Expectations, Bayesian Estimation.
"Substituability between Mobile and Fixed Telephones: Evidence and Implications for India"
Substitutability between mobile and fixed phones is an important consequence of India's telecom sector's deregulation since 1991. This paper tests for substitutability between mobile and fixed phones, based on a binary logit model and using the household sample survey data from the Karnataka State in South India. Estimated cross price elasticity offers empirical evidence for substitutability rather than complementarity between fixed and mobile phone services. This evidence is symmetric in mobile and fixed phone models. The empirical results have implications for on-going policy discussion on subsidization by the Access Deficit Charge and for changing the bases for Universal Service Obligation.
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