41 datasets found

This dataset contains results from Grand Canonical Monte Carlo (GCMC) Simulation (data/isotherms_sim/) and experiment (data/isotherms/exp). All Data is presented in a jupyter...

The aim of this paper is to develop a spatial group-wise heteroskedasticity test based on the scan approach, specifically developed for spatial autocorrelation regression models...

We propose a scan test for the presence of spatial groupwise heteroskedasticity in cross-sectional data. The scan approach has been used in different fields before, including...

This dataset contains results from Grand Canonical Monte Carlo (GCMC) Simulation (data/isotherms_sim/) and experiment (data/isotherms/exp). All Data is presented in a jupyter...

In this paper we investigate the multi-period forecast performance of a number of empirical self-exciting threshold autoregressive (SETAR) models that have been proposed in the...

This paper develops a new model for the analysis of stochastic volatility (SV) models. Since volatility is a latent variable in SV models, it is difficult to evaluate the exact...

This paper compares two methods for undertaking likelihood-based inference in dynamic equilibrium economies: a sequential Monte Carlo filter and the Kalman filter. The...

We perform an extensive series of Monte Carlo experiments to compare the performance of two variants of the jackknife instrumental variables estimator, or JIVE, with that of the...

This paper analyzes patterns in the earnings development of young labor market entrants over their life cycle. We identify four distinctly different types of transition patterns...

In this paper we modify the expectation maximization algorithm in order to estimate the parameters of the dynamic factor model on a dataset with an arbitrary pattern of missing...

This paper considers a panel data stochastic frontier model that disentangles unobserved firm effects (firm heterogeneity) from persistent (time-invariant/long-term) and...

We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models; wherein a particle approximation to the...

When dealing with the estimation of Engel curves, measurement errors in expenditure data and simultaneity are likely sources of endogeneity. In this paper we study...

Motivated by the need for a positive-semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra-high-frequency asset prices in a...

We bring together some recent advances in the literature on vector autoregressive moving-average models, creating a simple specification and estimation strategy for the...

Two-step nonparametric estimators have become standard in empirical auctions. A drawback concerns boundary effects which cause inconsistencies near the endpoints of the support...

This paper presents an empirical study of endogenous treatment effects in the presence of heterogeneous responses. We estimate the incentive and selection effects of having...

This paper studies panel data models with unobserved group factor structures. The group membership of each unit and the number of groups are left unspecified. We estimate the...

We propose a novel methodology for dynamic econometric modelling of large financial networks subject to persistence, structural changes and sparsity. We estimate bivariate...

This paper considers identification of spatial Durbin dynamic panel models under 2SLS and ML estimations. We show that the parameters are generally identified via 2SLS moment...