Point vS Probabilistic forecastS?

Prediction intervals are the most valuable statistical tools available to hotel investment decision-makers. However, they are not used as frequently as they should be. Lodging analysts traditionally use point estimates – that is, single-parameter estimates of occupancy, ADR, and RevPAR, etc.

As single numbers, point estimates are almost always above or below the parameters they are supposed to estimate. Without additional information, point estimates are less than optimal for making hotel investment decisions! Prediction interval estimates are very likely to be true, and the prediction level specifies and controls the probability that the interval estimates are true.

A prediction interval is a standard way of describing the precision of a measurement of some parameter, such as a RevPAR forecast. There are two common ways of stating prediction intervals both of which provide exactly the same information, for example, 1) Total U.S. RevPAR is forecast to grow by 5% plus or minus 2% with 90% confidence. 2) Total U.S. RevPAR is forecast to grow by between 3% and 7%, with 90% confidence.

The prediction level provides information about how sure you are that the true value of the parameter you have an interest in lies between the upper and lower bounds. This is not a subjective indication of confidence: one doesn’t merely substitute the number 90% for the phrase “I’m quite sure.” Instead, the prediction interval is calculated using statistical techniques that ensure that the confidence level is objective.

Recognizing and dealing with possible numbers around the most probable number is a major function of hotel investment risk analysis and is the reason we believe that no major investment decision should be made without the benefit of prediction intervals!

Call us today for a free phone consultation to see if your business can benefit from our forecasting services.