Economic forecast is the prediction of future trends in a country’s economy. It is an important tool for business and government, helping them to plan investment and policy decisions. It can also be used to identify and assess risks. However, since the forecasting process is subjective and political, many rational people view economic forecasts produced by governments with a healthy dose of skepticism.
The forecasting process starts with collecting relevant historical data, and it ends with analyzing the information. This step includes data cleansing, identification of patterns and trends in the data, seasonal adjustment, and time series analysis. In the case of time series analysis, there are different methods to choose from including regression models (linear and non-linear), exponential smoothing, and ARIMA models.
Other factors may be taken into account when constructing an economic forecast, such as demographics, changes in the global energy market, technological innovations, and external shocks. Often, a forecasting model takes these factors into account, and it is often based on econometric methods.
There are many different types of economic forecasts, and they can vary greatly in accuracy. For example, a non-linear model might perform well during rapid expansion periods, but it might fail to capture cyclical swings. Some models, like the Malthus theory of bare subsistence population growth based on arithmetic food supply increases and exponential population growth rates, might be flawed by unrealistic assumptions.