What is Economic Forecasting?
Economic forecasting is the process of attempting to predict the future condition of the economy using a combination of important and widely followed indicators.
Economic forecasting involves the building of statistical models with inputs of several key variables, or indicators, typically in an attempt to come up with a future gross domestic product (GDP) growth rate. Primary economic indicators include inflation, interest rates, industrial production, consumer confidence, worker productivity, retail sales, and unemployment rates.
How businesses use economic forecasting
Many businesses forecast the economy to make important decisions that may impact their future processes or policies. For example, decisions about hiring, spending, and investments can be much more informed using forecasting methods. If an economist tells the business that unemployment is high, the business may be more likely to hold a hiring event to attract unemployed members of the population. Large businesses tend to have their own in-house economist so they can focus on assessing forecasts that are relevant to the business.
Government officials also use forecasting methods to make informed decisions. As they make decisions that can affect the economy, government officials rely on the results to create and implement successful fiscal and monetary policies.
Limitations of Economic Forecasting
Economic forecasting is often described as a flawed science. Many suspect that economists who work for the White House are forced to toe the line, producing unrealistic scenarios in an attempt to justify legislation. Will the inherently flawed self-serving economic forecasts by the Federal government be accurate? As with any forecast, time will tell.
The challenges and subjective human behavioral aspects of economic forecasting are not limited to the government. Private-sector economists, academics, and even the Federal Reserve Board (FSB) have issued economic forecasts that were wildly off the mark. Ask Alan Greenspan, Ben Bernanke or a highly compensated Wall Street or ivory tower economist what GDP forecasts they produced in 2006 for 2007-2009—the period of the Great Recession.
Economic forecasters have a history of neglecting to foresee crises. According to Prakash Loungani, assistant director and senior personnel and budget manager at the International Monetary Fund (IMF), economists failed to predict 148 of the past 150 recessions.
Loungani said this inability to spot imminent downturns is reflective of the pressures on forecasters to play it safe. Many, he added, prefer not to stray away from the consensus, mindful that bold projections could damage their reputation and potentially lead them to lose their jobs.
Models of Economic Forecasting
There are several methods of economic forecasting available. They include causal, qualitative methods, and the examination of time series methods, among others.
Causal models often use regression analysis, from simpler models to multiple regression. They determine the future by establishing a relationship between sets of data collected from the near past. On the other hand, qualitative methods may include surveys, cross-referencing macroeconomic data, etc.
The methods based on time series try to determine growth by picking up on trends and determining moving averages.
Economic forecasting models include the Grinold and Kroner Model, the input-output model, calculating demand forecast accuracy, etc.
One can also combine different types of forecasts to get a consensus forecast. First, several specialists study the subject. And then, someone gathers all the data and uses a large volume of studies to determine the consensus in the scientific community.
It’s also essential to note the subjectiveness of economic forecasting. For example, different individuals may follow distinct economic theories and diverge on whether government spending is bad or good for the economy. It means that one may interpret the same data differently.