1
$\begingroup$

Whilst this may be a fundamental and basic question, I need to pin down a solid understanding of exactly what in-sample forecasting is and entails. I understand out-of-sample as taking a period of training data and forecasting future values based on the regression of data from that period. However, in-sample seems to be seldom defined without reference to not being out-of-sample.

Take the example of a time series from 1900-2000 for which I have a regression specification. I want to make in-sample forecasts for 1990-2000. What does this entail?

$\endgroup$
1
$\begingroup$

It entails using all the data available at your disposal, 100 years in this case, and fitting a model. Then you take the last year, say 1999, and make predictions for it using your model (which was fitted using all the data, including those of year 1999).

Basically, I don't know if anyone uses the name "in-sample prediction", but it corresponds to the bad practice of training a model with your data, and then "predicting" for a portion of that data.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.