We find the asymptotic distribution of the OLS estimator of the parameters $% \beta$ and $\rho$ in the mixed spatial model with exogenous regressors $% Y_n=X_n\beta+\rho W_nY_n+V_n$. The exogenous regressors may be bounded or growing, like polynomial trends. The assumption about the spatial matrix $W_n $ is appropriate for the situation when each economic agent is influenced by many others. The error term is a short-memory linear process. The key finding is that in general the asymptotic distribution contains both linear and quadratic forms in standard normal variables and is not normal
We consider a mixed vector autoregressive model with deterministic exogenous regressors and an autor...
We investigate the asymptotic bias of the ordinary least squares estimator for spatial autoregressiv...
Least squares estimation has casually been dismissed as an inconsistent estimation method for mixed ...
AbstractWe find the asymptotic distribution of the OLS estimator of the parameters β and ρ in the mi...
We find the asymptotics of the OLS estimator of the parameters $\beta$ and $\rho$ in the spatial aut...
AbstractWe derive the asymptotics of the OLS estimator for a purely autoregressive spatial model. On...
We derive the asymptotics of the OLS estimator for a purely autoregressive spatial model. Only low-l...
Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, ...
This paper presents a fundamentally improved statement on asymptotic behaviour of the well-known Gau...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
This paper considers a flexible semiparametric spatial autoregressive (mixed-regressive) model in wh...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
AbstractThis paper develops consistency and asymptotic normality of parameter estimates for a higher...
We consider a mixed vector autoregressive model with deterministic exogenous regressors and an autor...
We investigate the asymptotic bias of the ordinary least squares estimator for spatial autoregressiv...
Least squares estimation has casually been dismissed as an inconsistent estimation method for mixed ...
AbstractWe find the asymptotic distribution of the OLS estimator of the parameters β and ρ in the mi...
We find the asymptotics of the OLS estimator of the parameters $\beta$ and $\rho$ in the spatial aut...
AbstractWe derive the asymptotics of the OLS estimator for a purely autoregressive spatial model. On...
We derive the asymptotics of the OLS estimator for a purely autoregressive spatial model. Only low-l...
Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, ...
This paper presents a fundamentally improved statement on asymptotic behaviour of the well-known Gau...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
This paper considers a flexible semiparametric spatial autoregressive (mixed-regressive) model in wh...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
AbstractThis paper develops consistency and asymptotic normality of parameter estimates for a higher...
We consider a mixed vector autoregressive model with deterministic exogenous regressors and an autor...
We investigate the asymptotic bias of the ordinary least squares estimator for spatial autoregressiv...
Least squares estimation has casually been dismissed as an inconsistent estimation method for mixed ...