The estimation of multivariate GARCH models remains a challenging task, even in modern computer environments. This manuscript shows how Independent Component Analysiscan be used to estimate the Generalized Orthogonal GARCH model in a fraction of the time otherwise required. The proposed method...

Inference on the long-run properties of a Vector Autoregression (VAR) consisting wholly of I(1) variables are made using Bayesian methods. In particular, the implications on the forecast and impulse response function distributions of directly estimating and restricting the drift parameters of...

I introduce a technique to estimate parameters in regressions with reduced rank parameters in a general setting. The framework can handle a general class of parameter restrictions and allows for specifications with heteroskedastic and autocorrelated regression errors. Applications of this...

We derive new results on the asymptotic behavior of the estimated parameters of a linear asset pricing model and their associated t-statistics in the presence of a factor that is independent of the returns. The inclusion of this useless factor in the model leads to a violation of the full rank...

In this paper, we extend the results in Hansen (1982) regarding the asymptotic distribution of generalized method of moments (GMM) sample moment conditions. In particular, we show that the part of the scaled sample moment conditions that gives rise to degeneracy in the asymptotic normal...

Similar to Ingram and Whiteman (1994), De Jong et al. (1993) and Del Negro and Schorfheide (2004) this study proposes a methodology of constructing Dynamic Stochastic General Equilibrium (DSGE) consistent prior distributions for Bayesian Vector Autoregressive (BVAR) models. The moments of the...

In this paper, we propose a model based on multivariate decomposition of multiplicative - absolute values and signs - components of several returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional...

Conditional heteroskedasticity can be exploited to identify the structural vector autoregressions (SVAR) but the implications for inference on structural impulse responses have not been investigated in detail yet. We consider the conditionally heteroskedastic SVAR-GARCH model and propose a...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...

Are monetary policy regimes state-dependent? To answer the question this paper estimates New Keynesian general equilibrium models that allow the state of the economy to influence the monetary authority's stance on inflation. I take advantage of recent developments in solving rational...