The traditional approach to estimate spatial models bases on a preconceived spatial weights matrix to measure spatial interaction among locations. The a priori assumptions used to define this matrix are supposed to be in line with the "true" spatial relationships among the locations of the...

In this paper, we evaluate the spatial location patterns of Spanish manufacturing firms and we assess the different tendencies to cluster in each industry relative to the whole of manufacturing. To do this, we use a distance-based method (Marcon and Puech, 2003; Duranton and Overman, 2005), more...

This study develops an easy forecasting model using prefectural data in Japan. The Markov chain known as a stochastic model corresponds to the vector auto-regressive (VAR) model of the first order. If the transition probability matrix can be appropriately estimated, the forecasting model using...

We generalize the basic Wishart multivariate stochastic volatility model of Philipov and Glickmann (2006) to encompass regime switching behavior. The latent state variable is driven by a first-order Markov process. In order to estimate the proposed model we use Bayesian Markov Chain Monte Carlo...

The superiority of full information approaches when estimating a system of equation is well known for large samples. However, less is known about the small sample properties of these estimators relative to limited information approachs. This is especially true for the context of Panel data...

In this paper, we build a Computable General Equilibrium (CGE)-microsimulation model for the economy of Nicaragua following the Top-Down approach (see Bourguignon et al., 2003), that is, the reform is simulated first at the macro level with the CGE model, and then it is passed onto the...

This paper considers estimation methods and inference for linear dynamic panel data models with unit-specific heterogeneity and a short time dimension. In particular, we focus on the identification of the coefficients of time-invariant variables in a dynamic version of the Hausman and Taylor...

Providing a decent living standard and preventing old-age poverty are the two major challenges of pension insurance schemes. Replacement rates below the poverty line despite many years of contribution represent a major challenge for public pension schemes with respect to the systems "raison...

In this paper we analyze the performance of supremum augmented Dickey-Fuller (SADF), generalized SADF (GSADF), and backward SADF (BSADF) tests, as introduced by Phillips et al. (International Economic Review 56:1043-1078, 2015) for detecting and date-stamping financial bubbles. In Monte Carlo...

We revisit the question whether U.S. fiscal policy in the pre-Volcker period was active or passive. To determine the policy stance, we estimate a DSGE model with monetary and fiscal policy interactions employing a sequential Monte Carlo algorithm (SMC) for posterior evaluation. In contrast to...