Improving Surveying Accuracy and Efficiency in Connecticut: An Accuracy Assessment of GEOID03 and GEOID09

Comparing published NAVD 88 Helmert orthometric heights of First-Order bench marks against GPS-determined orthometric heights showed that GEOID03 and GEOID09 perform at their reported accuracy in Connecticut. GPS-determined orthometric heights were determined by subtracting geoid undulations from ellipsoid heights obtained from a network least-squares adjustment of GPS occupations in 2007 and 2008. A total of 73 markers were occupied in these stability classes: 25 class A, 11 class B, 12 class C, 2 class D bench marks, and 23 temporary marks with transferred elevations. Adjusted ellipsoid heights were compared against OPUS as a check. We found that: the GPS-determined orthometric heights of stability class A markers and the transfers are statistically lower than their published values but just barely; stability class B, C and D markers are also statistically lower in a manner consistent with subsidence or settling; GEOID09 does not exhibit a statistically significant residual trend across Connecticut; and GEOID09 out-performed GEOID03. A "correction surface" is not recommended in spite of the geoid models being statistically different than the NAVD 88 heights because the uncertainties involved dominate the discrepancies. Instead, it is recommended that the vertical control network be re-observed.

Using Leading Indicators to Forecast US Home Sales in a Bayesian VAR Framework

This paper uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting US home sales. The benchmark Bayesian model includes home sales, the price of homes, the mortgage rate, real personal disposable income, and the unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.