Spatial econometrics addresses the challenges posed by spatially correlated data, enabling researchers to understand and quantify how economic phenomena in one location can influence those in ...

This paper considers semiparametric inference for longitudinal data collected at irregular and possibly subject-specific times. We propose an irregular time ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 79, No. 2 (MARCH 2017), pp. 507-524 (18 pages) Most time series that are encountered in practice contain non-zero ...

The regression model with autocorrelated disturbances is as follows: In these equations, y t are the dependent values, x t is a column vector of regressor variables, is a column vector of structural ...

The model assumed is first-order autoregressive with contemporaneous correlation between cross sections. In this model, the covariance matrix for the vector of random errors u can be expressed as A ...

This paper proposes an extended conditional autoregressive range (EXCARR) model to describe the range-based volatility dynamics of financial assets. Our EXCARR model not only takes the conditional ...

The vector autoregressive model has long been used for portfolio analysis, while a recent extension (VARX) incorporates exogenous factors. Despite its increased forecasting precision, the ...