THE USE OF MATRIX METHODS AND DUMMY VARIABLES FOR FORECASTING IN ECONOMETRIC MODELS

The article considers the classical linear regression model and methods for constructing forecasts based on it. Using the example of oil production data in the Republic of Kazakhstan for 2005–2023, the technology of matrix estimation of the parameters of the paired regression equation is demonstrated. Special attention is paid to the method of constructing forecast values and their confidence intervals using a dummy variable for one observation (the Salkever method). The forecast values are compared with the actual data of 2024, confirming the adequacy of the constructed model. The article is of interest to specialists in the field of applied econometrics and forecasting.