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The costs of production

Mathematical economics relies on statistical observations to prove, disprove and predict economic behavior. Although the discipline is heavily influenced by the bias of the researcher, mathematics allows economists to explain observable phenomenon and provides the backbone for theoretical interpretation.

Economists often wrestle with competing models capable of explaining the same recurring relationship called an empirical regularity, but few models provide definitive clues to the size of the association between central economic variables. From Main Street to Wall Street to Washington, this is what matters most to policymakers. When setting monetary policy, for example, central bankers want to know the likely impact of changes in official interest rates on inflation and the growth rate of the economy. It is in cases like this that economists turn to econometrics.

Using Econometrics

By turning to econometrics, the mixture of economic theory, mathematics and statistical inference can quantify valuable economic phenomena. In other words, it turns theoretical economic models into useful tools for everyday economic policymaking. The objective of econometrics is to convert qualitative statements (such as “the relationship between two or more variables is positive”) into quantitative statements (such as “consumption expenditure increases by 95 cents for every one dollar increase in disposable income”).

As we’re flooded with ever more information, it’s something of an understatement to say the blending of qualitative and quantitative methods are a substantial improvement on traditional economic techniques. As Stock and Watson (2007) put it, “econometric methods are used in many branches of economics, including finance, labor economics, macroeconomics, microeconomics and economic policy.” Economic policy decisions are rarely made without econometric analysis to assess their impact.