ScholarLens Back to search
2018•Federal Reserve Bank of Richmond Working PapersOpen access

A Composite Likelihood Approach for Dynamic Structural Models

Fabio Canova, Christian Matthes, Federal Reserve Bank of Richmond

Open full text 7 citations

Abstract

We describe how to use the composite likelihood to ameliorate estimation, computational, and inferential problems in dynamic stochastic general equilibrium models.We present a number of situations where the methodology has the potential to resolve well-known problems.In each case we consider, we provide an example to illustrate how the approach works and its properties in practice.

Open-access reader

About this research paper

What this paper is about

We describe how to use the composite likelihood to ameliorate estimation, computational, and inferential problems in dynamic stochastic general equilibrium models.We present a number of situations where the methodology has the potential to resolve well-known problems.In each case we consider, we provide an example to illustrate how the approach works and its properties in practice.

Why it matters

OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

We describe how to use the composite likelihood to ameliorate estimation, computational, and inferential problems in dynamic stochastic general equilibrium models.We present a number of situations where the methodology has the potential to resolve well-known problems.In each case we consider, we provide an example to illustrate how the approach works and its properties in practice.

Key concepts: Quasi-maximum likelihood, Maximum likelihood, Computer science, Econometrics, Mathematical optimization, Estimation, Composite number, Structural estimation

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
A Composite Likelihood Approach for Dynamic Structural Models — Research Paper | ScholarLens