Random-Time Aggregation in Partial Adjustment Models
How is econometric analysis (of partial adjustment models) affected by the fact that, although data collection is done at regular, fixed intervals of time, economic decisions are made at random intervals of time? This article addresses this question by modeling the economic decision-making process as a general point process. Under random-time aggregation, (1) inference on the speed of adjustment is biased-adjustments are a function of the intensity of the point process and the proportion of adjustment; 2) inference on the correlation with exogenous variables is generally downward biased; and (3) a nonconstant intensity of the point process gives rise to a general class of regime-dependent time series models. An empirical application to test the production-smoothing-buffer-stock model of inventory behavior illustrates, in practice, the effects of random-time aggregation.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Volume (Year): 17 (1999)
Issue (Month): 3 (July)
|Contact details of provider:|| Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main|
|Order Information:||Web: http://www.amstat.org/publications/index.html|