We suggest a new class of cross-sectional space-time models based on local AR models and nearest neighbors using distances between observations. For the estimation we use a tightness prior for prediction of regional GDP forecasts. We extend the model to the model with exogenous variable model...

We suggest a new class of cross-sectional space-time models based on local AR models and nearest neighbors using distances between observations. For the estimation we use a tightness prior for prediction of regional GDP forecasts. We extend the model to the model with exogenous variable model...

In this paper, we estimate the CO2 emission function based on the production function, taking into account the interregional spillover effect in Japan. Using the estimated result, we propose suitable means of simulation using spatial econometrics and simulate which prefecture can reduce the CO2...

This paper considers the distance functional weight matrix in spatial autoregressive and spatial error models from a Bayesian point of view. We considered the Markov chain Monte Carlo methods to estimate the parameters of the models. Our approach is illustrated with simulated data set.

In this paper, we estimate the CO2 emission function based on the production function, taking into account the interregional spillover effect in Japan. Using the estimated result, we propose suitable means of simulation using spatial econometrics and simulate which prefecture can reduce the CO2...

This paper considers the distance functional weight matrix in spatial autoregressive and spatial error models from a Bayesian point of view. We considered the Markov chain Monte Carlo methods to estimate the parameters of the models. Our approach is illustrated with simulated data set.

We estimate inequality including Gini coefficients using a lognormal parametric model for an investigation of persistent inequality. The asymptotic theory of selected order statistics enables us to construct a linear model based on grouped data. We extend the linear model to a dynamic model in...

We suggest a new class of cross-sectional space-time models based on local AR models and nearest neighbors using distances between observations. For the estimation we use a tightness prior for prediction of regional GDP forecasts. We extend the model to the model with exogenous variable model...