We estimate location values for single family houses using a standard house price and characteristics dataset and local polynomial regressions (LPR), a procedure that allows for complex interactions between the values of structural characteristics and the value of land. We also compare LPR to...

As an alternative to ordinary least squares (OLS), we estimate location values for single family houses using a standard housing price and characteristics dataset by local polynomial regressions (LPR), a semi-parametric procedure. We also compare the LPR and OLS models in the Denver metropolitan...

Broadband availability data collected by the Federal Communications Commission (“FCC”) using its Form 477 are heavily criticized as inaccurate. These data certainly overstate availability since a census block is indicated as having broadband throughout the block even if only a single home in...

Using a panel data set for OECD countries we replicate the typical features of the New Keynesian Phillips curve models (NPCs) that have been estimated on country data. While this corroborates the NPC also on the macro panel data set, a different conclusion is reached when we test whether the NPC...

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)...

This paper re-examines inference for cluster samples. Sensitivity analysis is proposed as a new method to perform inference when the number of groups is small. Based on estimations using disaggregated data, the sensitivity of the standard errors with respect to the variance of the cluster...

This paper develops a simulation estimation algorithm that is particularly useful for estimating dynamic panel data models with unobserved endogenous state variables. The new approach can easily deal with the commonly encountered and widely discussed "initial conditions problem," as well as the...

Recently some new techniques have been proposed for the estimation of the slope coefficients in presence of unobserved components. Though, the presence of common observed and unobserved factors is neither considered or the estimation of their impacts is not taken into account. In this work a...

Panel data, whose series length T is large but whose cross-section size N need not be, are assumed to have a common time trend. The time trend is of unknown form, the model includes additive, unknown, individual-specific components, and we allow for spatial or other cross-sectional dependence...

Non-spherical errors, namely heteroscedasticity, serial correlation and cross-sectional correlation are commonly present within panel data sets. These can cause significant problems for econometric analyses. The FGLS(Parks) estimator has been demonstrated to produce considerable efficiency gains...