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The error structure of time series cross-section hedonic models with sporadic event timing and serial correlation

✍ Scribed by Gregory S. Amacher; Daniel Hellerstein


Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
217 KB
Volume
14
Category
Article
ISSN
0883-7252

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✦ Synopsis


When estimating hedonic models of housing prices, the use of time series cross-section repeat sales data can provide improvements in estimator eciency and correct for unobserved characteristics. However, in cases where serial correlation is present, the irregular timing of sales should also be considered. In this paper we develop a model that uses information on the timing of events to account for the sporadic occurrence of events. The model presumes that the serial correlation process can be decomposed into a time-independent (event-wise) component and a time-dependent (time-wise) component. Empirical tests cannot reject the presence of sporadic correlation patterns, while simulations show that the failure to account for sporadic correlation leads to signi®cant losses in eciency, and that the losses from ignoring sporadic correlation when it exists are larger than losses when sporadic correlation is falsely assumed.