Macroeconomic forecasting predicts the economy of a country or the world, using theoretical, empirical, and microfounded models. The purpose is to analyze the entire economy, including factors such as interest rates and taxation.
Macroeconomic forecasting involves making predictions about the entire economy of a country or even the world. Some of these forecasting techniques are described as empirical: they look at the past relationship between different economic data and assume that the same pattern of cause and effect will continue. Other types of macroeconomic forecasting involve working from the assumption that everyone involved in an economy will make rational choices.
The purpose of macroeconomic forecasting is to look at an entire economy. This is in contrast to microeconomics, which looks at a specific market, for example, the way demand and supply affect the sales and price of widgets, or the job market for widget manufacturers. Macroeconomics is more complicated, as it involves not only various individual markets, but also the effects of factors such as interest rates and taxation.
The simplest type of macroeconomic forecasting is theoretical models. They work with ground rules that are held to be true. For example, one such “rule of thumb” could be that if interest rates are halved, people’s disposable income will increase by 20% due to lower mortgage payments and this will lead to 10% greater sales of goods in the economy, with prices rising five percent. The two main disadvantages of such forecasts are that it is difficult to know how accurate the models are and that the complexity of a large economy can greatly exaggerate any inaccuracies in the model.
A more complicated variant of macroeconomic forecasting is known as empirical forecasting. This involves analyzing real data from the past and drawing conclusions. For example, a forecaster might consider changes in income tax and changes in total purchases each year in the past and try to establish a common relationship. This will not necessarily be what would be expected from a purely theoretical perspective. This past relationship can be applied to future predictions. These models vary immensely in complexity, depending on how much data is used and how many factors are considered.
Arguably the most complicated type of macroeconomic forecasting are those classified as microfounded, such as dynamic stochastic general equilibrium models. Microfoundation forecasting involves breaking down the economy into the smallest possible pieces, preferably for each person or organization that makes decisions, such as consumers deciding what to buy, manufacturers deciding where to source supplies, or governments deciding the level of sales tax. The technique, then, involves determining which decisions would best serve self-interest, whether that means consumers are getting value for their money, manufacturers trying to increase profits, or governments trying to maximize tax revenue without hurting the economy. Economists then build this into a complicated model that can predict the effects of a specific change when all parties act in the most rational way.
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