Econometrics uses statistical analysis to predict economic trends through econometric models, which establish and test relationships between economic factors. Developed by Norwegian economist Ragnar Frisch in the 1930s, econometric modeling is an uncertain science that incorporates probability due to human behavior. Governments and central banks use econometric data to guide fiscal management strategies, but critics accuse officials of using data that supports their pre-existing views.
Economists often rely on econometrics to predict future trends, which in a very broad sense is the application of statistical analysis to economic data. One of the main tools of this discipline is the econometric model. In a basic sense, econometric modeling is used to establish and test a predictable relationship between two economic factors, such as how income affects spending.
Econometrics first emerged in the 1930s as the brainchild of Norwegian economist Ragnar Frisch. Frisch was the first to bring elements of statistical analysis into economic study, and he believed that they could help lend a greater degree of confidence to economic forecasts. Among his particular contributions to the field was the introduction of linear regression modeling, which has become a classic econometric model.
At its core, an econometric model offers empirical analysis to a field of study that has traditionally withstood such scrutiny. A variety of different econometric methods have been developed to help analysts provide statistically meaningful guidance on economic phenomena. One of the central concepts of econometric modeling is that it is an uncertain science, because it depends so much on human behavior. Every econometric model, therefore, incorporates some degree of probability into its formulation.
When creating a typical econometric model, an economist must first be clear about what he wants the model to show. It is usually the impact of one factor on another. The next step is to record data and measurements on a given set of variables to generate what is known as a dataset. This data could be a worker’s earnings over a period of time, the Gross Domestic Product (GDP) of a country, the interest rates offered by a central bank, or any other information of interest based on the model’s target.
Once an economist is satisfied with the data that has been collected, he can begin to manipulate it and leverage the model to produce usable results. These results are subjected to scrutiny and judged by peers. Good models emerge as those that stand up to scrutiny and are shown to reproduce reliable and realistic data over and over again.
Increasingly, the use of econometric models has been adopted by policy makers to help guide fiscal management strategies. Governments and central banks use and pay handsomely for econometric data. As with many policy endeavors, it is not uncommon for observers and economists to accuse government officials of using data that support their pre-existing views, rather than allowing the data to guide them to a new conclusion.
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