st: zero-inflation and bounds on ARIMA predictions

["Winston, Carla A." <Carla.Winston@va.gov>]

Dear friends, I am using Stata 12.1 for a regression model of healthcare telephone calls predicting hospital admissions.  Admissions and calls can never be non-negative.  The admissions are zero-inflated and stationary; calls are stationary.  The data are in weeks, are second-order autoregressive, and show annual seasonality (i.e., at 52 weeks).

arima admissions calls, sarima(2,0,0,52) vce(robust) diffuse

I have been working to create a seasonally adjusted model and am generally happy with the above, but predictions include negative numbers for some of the weeks when observed admissions are zero.  Would it be better to use a negative binomial or zero-inflated Poisson model rather than ARIMA?  Or is there another way to bound the ARIMA?  I like the ease of the ARIMA seasonal coding, but want to ensure that model predictions are never < 0.  I have also examined -prais- and -vecm- but did not settle on a satisfactory way to account for the seasonality.  


Thanks for your suggestions.

Carla

Carla.winston@va.gov


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