RG

IN CONTEXT

FOCUS

Economic methods

KEY THINKER

Ragnar Frisch (1895–1973)

BEFORE

1696 English economist Gregory King publishes Natural and Political Observations, containing the first quantitative (measurable) analysis of economics.

1914 US economist Henry Moore publishes Economic Cycles: Their Law and Cause, laying the foundations for statistical economics, the forerunner of econometrics.

AFTER

1940 Austrian economist Ludwig von Mises argues that empirical methods cannot be applied to social sciences.

2003 British economist Clive Granger wins the Nobel Prize for his analyses of the relationship between economic variables over time.

In the 1930s Norwegian economist Ragnar Frisch developed a new discipline that he called “econometrics.” His aim was to develop methods to explain and predict the movements of the economy. Econometrics is the application of mathematical testing methods to economic theories, providing a statistical basis on which to prove or disprove a theory. Economic beliefs, such as “a better education leads to a higher salary,” may be correct, but can only be proven through an equation that takes data on educational attainment levels and compares it with salary levels. Econometrics also enables economists to analyze past market trends and predict future performance by extracting patterns from economic data.

"Intermediate between mathematics, statistics, and economics we find a new discipline which… may be called econometrics."

Ragnar Frisch

Statistical pitfalls

Although econometrics is an important tool of empirical explanation, there are pitfalls. For instance, past market trends are no real guarantee of future market performance. It is also difficult to take all variables into account. In the education example educational attainment is not the only factor that affects the wage—other, unmeasurable skills might also play a role. These kinds of problems can weaken the validity of the results of economic models. It is also important not to confuse statistical significance with economic significance.

See also: Measuring wealthInflation and unemploymentFinancial engineeringComplexity and chaos