We propose a state-dependent Phillips curve (PC) where the regime has changed endogenously. Using this framework, a free-standing PC is constructed. This study tests the robustness of the model, various types of inflation, slack measures, and various expectation measures. The PC is found to work...

I use Bayesian VARs with stochastic volatility to forecast global temperatures and sea level and ice cover in the Northerin emisphere until 2010, by exploiting (i) their long-run equilibrium relationship with climate change drivers (CCDs) and (ii) the relationship between world GDP and...

I use Bayesian VARs with stochastic volatility to forecast global temperatures and sea level and ice cover in the Northerin emisphere until 2010, by exploiting (i) their long-run equilibrium relationship with climate change drivers (CCDs) and (ii) the relationship between world GDP and...

This paper introduces a novel approach to simulation smoothing for nonlinear and non-Gaussian state space models. It allows for computing smoothed estimates of the states and nonlinear functions of the states, as well as visualizing the joint smoothing distribution. The approach combines...

We propose a factor correlated unobserved components (FCUC) model to analyze the sticky and flexible components of U.S. inflation. The proposed FCUC framework estimates trend inflation and component cycles in a flexible stochastic environment with time-varying volatility, factor loadings, and...

This paper introduces a novel approach to simulation smoothing for nonlinear and non-Gaussian state space models. It allows for computing smoothed estimates of the states and nonlinear functions of the states, as well as visualizing the joint smoothing distribution. The approach combines...

We consider structural vector autoregressions identified through stochastic volatility. Our focus is on whether a particular structural shock is identified by heteroskedasticity without the need to impose any sign or exclusion restrictions. Three contributions emerge from our exercise: (i) a set...

In this paper, we assess whether key relations between US interest rates have been stable over time. This is done by estimating trivariate hybrid time-varying parameter Bayesian VAR models with stochastic volatility for the three-month Treasury bill rate, the slope of the Treasury yield curve...

We study the time-varying effects of Tobin's q and cash flow on investment dynamics in the USA using a vector autoregression model with drifting parameters and stochastic volatilities estimated via Bayesian methods. We find significant variation over time of the response of investment to shocks...

In this paper, we extend the standard Gaussian stochastic-volatility Bayesian VAR by employing the generalized hyperbolic skew Student's t distribution for the innovations. Allowing the skewness parameter to vary over time, our specification permits flexible modelling of innovations in terms of...

In this paper, we assess whether key relations between US interest rates have been stable over time. This is done by estimating trivariate hybrid time-varying parameter Bayesian VAR models with stochastic volatility for the three-month Treasury bill rate, the slope of the Treasury yield curve...

Modeling, Analysis, and Optimization for Mathematical Finance, Economics, and Risks is a critical domain that integrates mathematical theory with practical applications to address the complexities of modern financial and economic systems. This special issue focuses on recent studies that are...

The effects of stochastic volatility, jump clustering, and regime switching are considered when pricing variance swaps. This study established a two-stage procedure that simplifies the derivation by first isolating the regime switching from other stochastic sources. Based on this, a novel...

We consider structural vector autoregressions identified through stochastic volatility. Our focus is on whether a particular structural shock is identified by heteroskedasticity without the need to impose any sign or exclusion restrictions. Three contributions emerge from our exercise: (i) a set...

In this paper, we extend the standard Gaussian stochastic-volatility Bayesian VAR by employing the generalized hyperbolic skew Student's t distribution for the innovations. Allowing the skewness parameter to vary over time, our specification permits flexible modelling of innovations in terms of...

In this paper, we investigate non-linear linkages between Bitcoin and the unconventional monetary policies of the European Central Bank (ECB). In particular, we examine whether a low-interest rate environment resulting from QE indirectly encourages investors to move towards Bitcoin. Using a...

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis...

This work provides a new method for pricing options under the generalized stochastic volatility models with Jacobi stochastic correlation. Our method is based on the observation that the generalized models belong to the class of polynomial diffusions and therefore the option prices can be...

We study the time-varying effects of Tobin's q and cash flow on investment dynamics in the USA using a vector autoregression model with drifting parameters and stochastic volatilities estimated via Bayesian methods. We find significant variation over time of the response of investment to shocks...

The return of high inflation in Latin America (and worldwide) since 2021 has renewed concerns about the persistence of above-target inflation and a potential de-anchoring of inflation expectations. This paper shows that trend inflation estimation using forward-looking information can offer...

This paper provides insights into the time-varying dynamics of the German business cycle over the last five decades. To do so, I employ an open-economy time-varying parameter VAR with stochastic volatility, which I estimate by quasi-Bayesian techniques. The reduced-form analysis reveals...

We calculate the social cost of carbon (SCC) under stochastic climate volatility resulting from uncertainty about future climate risk regimes where weather extremes are becoming more frequent and intense. Using a stochastic dynamic integrated climate-economy model where representative agents are...