The
purpose of this article is to present an alternative method for intervention
analysis of time series data that is simpler to use than the traditional method of fitting an explanatory Autoregressive
Integrated Moving Average (ARIMA) model. Time
series regression analysis is commonly used to test the effect of an
event on a time series. An econometric modeling method, which uses a
heteroskedasticity and autocorrelation consistent (HAC) estimator of the
covariance matrix instead of fitting an ARIMA model, is proposed as an
alternative. The method of parametric bootstrap is used to compare the two
approaches for intervention analysis. The results of this study suggest that
the time series regression method and the HAC method give very similar results
for intervention analysis, and hence the proposed HAC method should be used for
intervention analysis, instead of the more complicated method of ARIMA
modeling. The alternative method presented here is expected to be very helpful
in gaming and hospitality research.
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