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autocorrelation coefficient of the error term in a Cliff and Ord type model. The main finding is that a Wald-test based on GMM …
Persistent link: https://www.econbiz.de/10003202038
theory is kept general to cover a wide range of settings. We note the estimation theory developed by Kelejian and Prucha …
Persistent link: https://www.econbiz.de/10003790570
In this paper we specify a linear Cliff and Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the disturbance process are assumed to be heteroskedastic with an unknown form. We formulate a multi-step...
Persistent link: https://www.econbiz.de/10003792846
This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models. Theoretical results and Monte Carlo simulations suggest that iterated forecasts dominate direct forecasts when estimation error is a...
Persistent link: https://www.econbiz.de/10003807908
This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...
Persistent link: https://www.econbiz.de/10003808637
This paper generalizes the approach to estimating a first-order spatial autoregressive model with spatial autoregressive disturbances (SARAR(1,1)) in a cross-section with heteroskedastic innovations by Kelejian and Prucha (2008) to the case of spatial autoregressive models with spatial...
Persistent link: https://www.econbiz.de/10003748246
Persistent link: https://www.econbiz.de/10003711864
For forecasting and economic analysis many variables are used in logarithms (logs). In time series analysis this transformation is often considered to stabilize the variance of a series. We investigate under which conditions taking logs is beneficial for forecasting. Forecasts based on the...
Persistent link: https://www.econbiz.de/10003820020
We propose a novel dynamic mixture vector autoregressive (VAR) model in which time-varying mixture weights are driven by the predictive likelihood score. Intuitively, the state weight of the k-th component VAR model in the subsequent period is increased if the current observation is more likely...
Persistent link: https://www.econbiz.de/10014251324
Decisions on the presence of seasonal unit roots in economic time series are commonly taken on the basis of statistical hypothesis tests. Some of these tests have absence of unit roots as the null hypothesis, while others use unit roots as their null. Following a suggestion by Hylleberg (1995)...
Persistent link: https://www.econbiz.de/10009781562