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ON THE ROBUSTNESS OF MIXTURE MODELS IN THE PRESENCE OF HIDDEN MARKOV REGIMES WITH COVARIATE-DEPENDENT TRANSITION PROBABILITIES

协变量依赖转移概率的隐马尔可夫状态下,混合模型的稳健性

This article studies the robustness of quasi-maximum-likelihood estimation in hidden Markov models when the regime-switching structure is misspecified. Specifically, we examine the case where the data-generating process features a hidden Markov regime sequence with covariate-dependent transition probabilities, but estimation proceeds under a simplified mixture model that assumes regimes are independent and identically distributed. We show that the parameters governing the…

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Maximum Likelihood Estimation in Markov Regime‐Switching Models With Covariate‐Dependent Transition Probabilities

协变量依赖转移概率的马尔可夫状态转换模型最大似然估计

This paper considers maximum likelihood (ML) estimation in a large class of models with hidden Markov regimes. We investigate consistency of the ML estimator and local asymptotic normality for the models under general conditions, which allow for autoregressive dynamics in the observable process, Markov regime sequences with covariate‐dependent transition matrices, and possible model misspecification. A Monte Carlo study examines the finite‐sample properties of the ML…

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Estimating and Forecasting the Yield Curve Using A Markov Switching Dynamic Nelson and Siegel Model

Summary We estimate versions of the Nelson–Siegel model of the yield curve of US government bonds using a Markov switching latent variable model that allows for discrete changes in the stochastic process followed by the interest rates. Our modeling approach is motivated by evidence suggesting the existence of breaks in the behavior of the US yield curve that depend, for example, on whether the economy is in a recession or a boom, or on the stance of monetary policy. Our…

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Multivariate contemporaneous-threshold autoregressive models

多元当期阈值自回归模型

This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex-ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific noise covariance matrix, the model can…

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Contemporaneous threshold autoregressive models: Estimation, testing and forecasting

同期门限自回归模型:估计、检验与预测

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta (1998), in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well-suited to rational expectations applications (and pricing exercises), in that it allows the…

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Markov switching causality and the money–output relationship

马尔可夫切换因果性与货币—产出关系

Abstract The causal link between monetary variables and output is one of the most studied issues in macroeconomics. One puzzle from this literature is that the results of causality tests appear to be sensitive with respect to the sample period that one considers. As a way of overcoming this difficulty, we propose a method for analysing Granger causality which is based on a vector autoregressive model with time‐varying parameters. We model parameter time‐variation so as to…

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Testing the unbiased forward exchange rate hypothesis using a Markov switching model and instrumental variables

用马尔可夫转换模型与工具变量检验远期汇率无偏假说

Abstract This paper develops a model for the forward and spot exchange rate which allows for the presence of a Markov switching risk premium in the forward market and considers the issue of testing the unbiased forward exchange rate (UFER) hypothesis. Using US/UK data, it is shown that the UFER hypothesis cannot be rejected, provided that instrumental variables are used to account for within‐regime correlation between explanatory variables and disturbances in the Markov…

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On Markov error‐correction models, with an application to stock prices and dividends

马尔可夫误差修正模型:股票价格与股息应用

Abstract This paper considers Markov error‐correction (MEC) models in which deviations from the long‐run equilibrium are characterized by different rates of adjustment. To motivate our analysis and illustrate the various issues involved, our discussion is structured around the analysis of the long‐run properties of US stock prices and dividends. It is shown that the MEC model is flexible enough to account for situations where deviations from the long‐run equilibrium are…

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Detecting periodically collapsing bubbles: a Markov-switching unit root test

识别周期性崩溃的泡沫:马尔可夫切换单位根检验

This paper addresses the problem of testing for the presence of a stochastic bubble in a time series in the case that the bubble is periodically collapsing so that the asset price keeps returning to the level implied by the market fundamentals. As this is essentially a problem of identifying the collapsing periods from the expanding ones, we propose using a generalization of the Dickey-Fuller test procedure which makes use of the class of Markov regime-switching models. The…

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COINTEGRATION AND CHANGES IN REGIME: THE JAPANESE CONSUMPTION FUNCTION

协整与体制变化:日本消费函数

In this paper we examine a model of cointegration where long-run parameters are subject to switching between several different cointegrating regimes. These shifts are allowed to be governed by the outcome of an unobserved Markov chain with unknown transition probabilities. We illustrate this approach using Japanese data on consumption and disposable income, and find that the data favor a Markov-switching long-run relationship over a standard temporally stable formulation.

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COINTEGRATION AND CHANGES IN REGIME: THE JAPANESE CONSUMPTION FUNCTION

协整与状态变化:日本消费函数

In this paper we examine a model of cointegration where long-run parameters are subject to switching between several different cointegrating regimes. These shifts are allowed to be governed by the outcome of an unobserved Markov chain with unknown transition probabilities. We illustrate this approach using Japanese data on consumption and disposable income, and find that the data favor a Markov-switching long-run relationship over a standard temporally stable formulation.

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