Real Estate

Several parametric and nonparametric methods have been advanced over the years for estimating house price appreciation. This paper compares five of these methods in terms of predictive accuracy, using data from Montgomery County, Pennsylvania. The methods are evaluated on the basis of the mean squared prediction error and the mean absolute prediction error. A statistic developed by Diebold and Mariano is used to determine whether differences in prediction errors are statistically significant. We use the same statistic to determine the effect of sample size on the accuracy of the predictions. In general, parametric methods of estimation produce more accurate estimates of house price appreciation than nonparametric methods. And when the mean absolute prediction error is used as the criterion of accuracy, the repeat sales method produces the most accurate estimate among the parametric methods we tested. Finally, of the five methods we tested, the accuracy of the repeat sales method is least diminished by a reduction in sample size.

In this paper, we develop and estimate a model that decomposes the variance in office vacancy rates into market-specific, time-specific, and random components. The results indicate significant differences in natural vacancy rates across markets. We also find some persistence in deviations from these natural vacancy rates. The analysis is applied to both central business district (CBD) and suburban office markets. We find that natural vacancy rates differ across CBD markets and across suburban markets. Further, the persistence of disequilibrium in one CBD market seems to differ significantly from that in another. This is not shown to be true for suburban markets.

Highlights are presented from an extensive project analyzing the critical factors that accounted for economic growth in American cities in the 1990s. The main findings, organized along five key dimensions, reveal significant changes in the dynamics of urban economies: for the first time, income growth is occurring independently of population growth, and there is evidence of increasing divergence between wealthier and poorer cities. Among the key drivers of urban economic growth, higher education proved to have the greatest positive impact, as knowledge-based activities are increasingly important across all industry sectors. Business diversification appears to favor economic growth, while specialization requires more caution: only certain specializations drive growth, and economic specialization generally may be shifting from industry sectors to business functions and occupations. Income inequality and racial segregation had negative effects on economic growth. Further findings, on s...