Mu‐Chun Wang
Biographic Data
| ID | 9107506 |
|---|---|
| NAME | Mu‐Chun Wang |
| GIVEN NAMES | Mu‐Chun |
| FAMILY NAME | Wang |
| SIGNATURE | WANG M C |
| AFFILIATIONS | Universität Hamburg |
| ORCID | 0000-0002-4605-0658 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
High‐Frequency Instruments With Time‐Varying Reliability
The effects of monetary policy shocks are regularly estimated using high‐frequency surprises in asset prices around central bank meetings as an instrument. These studies, insofar as they explicitly model the relationship between instrument and structural shock, assume a constant relationship between the instrument and the monetary policy shock. By allowing for time variation in this relationship, we show that only a few distinct periods are infor…
Estimation of Heterogeneous Agent Models
Using a Bewley‐Hugget‐Aiyagari model we show how to use the Fokker‐Planck equation for likelihood inference in heterogeneous agent (HA) models. We study the finite sample properties of the maximum likelihood estimator (MLE) in Monte Carlo experiments using cross‐sectional data on wealth and income. We use the Kullback–Leibler divergence to investigate identification problems that may affect inference. Unrestricted MLE leads to considerable biases…
Choosing Prior Hyperparameters
Time-varying parameter models with stochastic volatility are widely used to study macroeconomic and financial data. These models are almost exclusively estimated using Bayesian methods. A common practice is to focus on prior distributions that themselves depend on relatively few hyperparameters such as the scaling factor for the prior covariance matrix of the residuals governing time variation in the parameters. The choice of these hyperparameter…
No prominent works on this page.
Choosing Prior Hyperparameters
Time-varying parameter models with stochastic volatility are widely used to study macroeconomic and financial data. These models are almost exclusively estimated using Bayesian methods. A common practice is to focus on prior distributions that themselves depend on relatively few hyperparameters such as the scaling factor for the prior covariance matrix of the residuals governing time variation in the parameters. The choice of these hyperparameter…
Estimation of Heterogeneous Agent Models
Using a Bewley‐Hugget‐Aiyagari model we show how to use the Fokker‐Planck equation for likelihood inference in heterogeneous agent (HA) models. We study the finite sample properties of the maximum likelihood estimator (MLE) in Monte Carlo experiments using cross‐sectional data on wealth and income. We use the Kullback–Leibler divergence to investigate identification problems that may affect inference. Unrestricted MLE leads to considerable biases…
High‐Frequency Instruments With Time‐Varying Reliability
The effects of monetary policy shocks are regularly estimated using high‐frequency surprises in asset prices around central bank meetings as an instrument. These studies, insofar as they explicitly model the relationship between instrument and structural shock, assume a constant relationship between the instrument and the monetary policy shock. By allowing for time variation in this relationship, we show that only a few distinct periods are infor…
Monetary Policy and Economic Impact (3 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Econometrics (2 works) · Mathematics (2 works) · Monte Carlo method (2 works) · Statistics (2 works) · Applied Mathematics (1 work) · Bayesian inference (1 work) · Bayesian probability (1 work)