In this paper we analyze the predictive power of the yield curve on output growth using a vector autoregressive model with multiple structural breaks in the intercept term and the volatility. To estimate the model and to detect the number of breaks, we apply a Bayesian approach with Markov chain Monte Carlo algorithm. We find strong evidence of three structural breaks using the US data
We consider how to estimate the trend and cycle of a time series, such as real gross domestic produc...
We use Bayesian time-varying parameters VARs with stochastic volatility to investigate changes in th...
We propose a new approach to forecasting the term structure of interest rates, which allows to effic...
This paper proposes a new structural-break vector autoregressive (VAR) model for predicting real out...
This paper considers a vector autoregressive model or a vector error correction model with multiple ...
This paper proposes a new structural-break vector autoregressive (VAR) model for predicting real out...
This thesis consists of three essays in empirical finance and macroeconomics. The first essay propos...
This paper develops a new Bayesian approach to structural break modeling. The focuses of the approac...
This paper develops a Bayesian approach for analyzing a vector autoregressive model with multiple st...
This paper provides a feasible approach to estimation and forecasting of multiple structural breaks ...
Abstract In this paper, we consider a Bayesian analysis of the unbalanced (general) growth curve mod...
US yield curve dynamics are subject to time-variation, but there is ambiguity about its precise form...
We use machine learning, applied mathematics and techniques from modern statistics to refine Dynamic...
We present an algorithm, based on a differential evolution MCMC method, for Bayesian inference in AR...
Financial data generally span a long time period and are well known to be subject to structural chan...
We consider how to estimate the trend and cycle of a time series, such as real gross domestic produc...
We use Bayesian time-varying parameters VARs with stochastic volatility to investigate changes in th...
We propose a new approach to forecasting the term structure of interest rates, which allows to effic...
This paper proposes a new structural-break vector autoregressive (VAR) model for predicting real out...
This paper considers a vector autoregressive model or a vector error correction model with multiple ...
This paper proposes a new structural-break vector autoregressive (VAR) model for predicting real out...
This thesis consists of three essays in empirical finance and macroeconomics. The first essay propos...
This paper develops a new Bayesian approach to structural break modeling. The focuses of the approac...
This paper develops a Bayesian approach for analyzing a vector autoregressive model with multiple st...
This paper provides a feasible approach to estimation and forecasting of multiple structural breaks ...
Abstract In this paper, we consider a Bayesian analysis of the unbalanced (general) growth curve mod...
US yield curve dynamics are subject to time-variation, but there is ambiguity about its precise form...
We use machine learning, applied mathematics and techniques from modern statistics to refine Dynamic...
We present an algorithm, based on a differential evolution MCMC method, for Bayesian inference in AR...
Financial data generally span a long time period and are well known to be subject to structural chan...
We consider how to estimate the trend and cycle of a time series, such as real gross domestic produc...
We use Bayesian time-varying parameters VARs with stochastic volatility to investigate changes in th...
We propose a new approach to forecasting the term structure of interest rates, which allows to effic...