Combining survey, census, and administrative data improves the precision of survey estimates of mean agricultural land values. A components-of-variance model is developed and applied to cropland value data for the Corn Belt Performance of the model compared with other procedures is tested using...

Regression models that account for main state effects and nested county effects are considered for the assessment of farmland values. Empirical predictors obtained by replacing the unknown variances in the formula of the optimal predictors by maximum likelihood estimates are presented. The...

This article describes a simple method of estimating the autocorrelations of survey errors for the case of routing-panel sampling designs. Such designs are in routine use, for example, in labor force surveys (LFS). The survey-error autocorrelations induce spurious trends that need to be...

We propose simple parametric and nonparametric bootstrap methods for estimating the prediction mean square error (PMSE) of state vector predictors that use estimated model parameters. As is well known, substituting the model parameters by their estimates in the theoretical PMSE expression that...

We consider a model-dependent approach for multi-level modelling that accounts for informative probability sampling of first- and lower-level population units. The proposed approach consists of first extracting the hierarchical model holding for the sample data given the selected sample, as a...

I consider estimation and seasonal adjustment of population means based on rotating panel surveys carried out at regular time intervals. The analysis uses a dynamic structural model that assumes a decomposition of the mean into a trend-level component and a seasonal component. The model accounts...