Semiparametric Bayesian Inference in Autoregressive Panel Data Models

By Keisuke Hirano. 2002

141 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0ee2fb318a6420e3fa4d9b49d0899aa57764548a

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Citations in the corpus

Multiple Imputation of Missing or Faulty Values Under Linear Constraints (2014, methodology): “We note that Dirichlet process distributions are widely used for mixture models in economic analyses (e.g., Hirano 2002; Gilbride and Lenk 2010).”
Empirical Likelihood Methods in Econometrics: Theory and Practice (2006, background): “Kester and Kallenberg (1986) show that MLE achieves the lower bound of the above rate if the parametric model belongs to the convex exponential family.”
Bayesian Nonparametric Calibration and Combination of Predictive Distributions (2015, background): “…Papaspiliopoulos and Roberts 2008; © American Statistical Association Taddy 2010), including but not limited to applications in time series analysis (Hirano 2002; Chib and Hamilton 2002; Rodriguez and ter Horst 2008; Jensen and Maheu 2010; Griffin and Steel 2011; Bassetti, Casarin, and Leisen…”
Stick-breaking autoregressive processes (2011, background): “Early applications in economics include autoregressive panel data models (Hirano, 2002), longitudinal data treatment models (Chib and Hamilton, 2002) and stochastic frontiers (Griffin and Steel, 2004).”
Order-Based Dependent Dirichlet Processes (2006, background): “Some recent examples include applications in econometrics (Chib and Hamilton 2002; Hirano 2002), medicine (Kottas, Branco, and Gelfand 2002), health (O’Hagan and Stevens 2003), auditing (Laws and O’Hagan 2002), animal breeding (van der Merwe and Pretorius 2003), survival analysis (Doss and Huffer…”
Nonparametric Applications of Bayesian Inference (2003, unknown): “For more details, see the work of Ferguson (1973, 1974), Rubin (1981), Chamberlain and Imbens (1995), and Hirano (2002).”
Smoothly mixing regressions (2007, unknown): “…independent of x. Geweke and Keane (2000) uses a finite mixture of normals model for transitory shocks to earnings in an otherwise conventional life-cycle model with panel data, and Hirano (2002) does much the same thing beginning with a Dirichlet process prior centered on a normal distribution.”
Bayesian semiparametric modeling of realized covariance matrices (2016, background): “Dependent Dirichlet processes are formalized by MacEachern (2000). Our first extension to incorporate time dependence in the mixture model is based on the infinite hidden Markov model (iHMM).”
Conditional (2019, unknown): “In summary, the main contributions of our work are described as follows: • We propose a Latent Diffusion-based ID Sampler based on DDIM, capable of sampling multidimensional identity embeddings with diversity and realism, which serve as anonymized identity embeddings for subsequent replacement.”
Bayesian semiparametric stochastic volatility modeling (2010, methodology): “, yn) ′ (see Jacquier et al. (1994); Kim et al.”
Program Evaluation as a Decision Problem * (2002, unknown): “It would be an interesting extension to consider more general specifications for earnings processes (see for example Hirano 2000), which might improve predictions to some extent, but for the questions which I examine the current model produces predictions that are robust to generalizations of the…”
Model-Based Clustering of Non-Gaussian Panel Data Based on Skew-t Distributions (2010, methodology): “Hirano (2002) proposed a semiparametric framework, with a nonparametric distribution on the error term, using a Dirichlet prior.”
The Nested Dirichlet Process (2008, background): “Some recent applications of the DP include finance (Kacperczyk, Damien, and Walker 2003), econometrics (Chib and Hamilton 2002; Hirano 2002), epidemiology (Dunson 2005), genetics (Medvedovic and Sivaganesan 2002; Dunson, Herring, and Mulheri-Engel 2007a), medicine (Kottas, Branco, and Gelfand 2002;…”
Forecasting With Dynamic Panel Data Models (2017, unknown): “Fully Bayesian approaches to the analysis of dynamic panel data models have been developed in Chamberlain and Hirano (1999), Hirano (2002), Lancaster (2002).”
Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys (2013, methodology): “We note that Dirichlet process mixture models (Antoniak, 1974) are used in many fields including, for example, econometrics (Chib & Hamilton, 2002; Hirano, 2002), social science (Kyung, Gill, & Casella, 2010), and finance (Rodrı́guez & Dunson, 2011).”
Semiparametric Bayesian Inference of Long‐Memory Stochastic Volatility Models (2004, methodology): “Instead, we adopt the semiparametric Bayesian approach of Tiwari et al. (1988), Chib and Hamilton (2002), and Hirano (2002), where the unknown distribution of the innovations are modelled non-parametrically by a Dirichlet process.”