Introduction to Econometrics

Introduction & Historical Context

Econometrics has its formal origin nearly a century ago, with Ragnar Frisch being credited with inventing econometrics in the 1930s. Frisch was the first editor for Econometrica, one of the top economics journals, and won the 1969 Nobel Prize for Economics along with Jan Tinbergen. Quantitative methods to analyze economics, however, were used earlier. Now, quantitative methods are used by governments, businesses, and banks to analyze data and make economic decisions.

Branches of Econometrics: Theoretical & Applied

Econometrics contains two main branches: theoretical and applied. Theoretical econometrics focuses on creating statistical methods and utilizing statistical models. Applied econometrics, on the other hand, combines economic models, mathematical procedures, and statistical methods to analyze data and find trends about economic issues.

The Role of Algebra & Calculus in Economic Analysis

Many disciplines are used in econometrics, primarily algebra, calculus, and statistics. Algebra helps model functions like Cost 𝐶(𝑥), Revenue 𝑅(𝑥), and Profit 𝑃(𝑥), where 𝑃(𝑥) = 𝑅(𝑥) − 𝐶(𝑥). These functions are then analyzed further using integral and differential calculus. Differentiation is used for marginal analysis, maximization, and minimization of functions, with some practical uses including minimizing cost and maximizing utility and profit. Integration, the reverse of differentiation, is also valuable in economics. Integration of marginal values helps us find aggregate values, such as integrating the marginal profit function to get total profit. Integrating the difference between the line of perfect equality and the Lorenz curve will help us find the Gini Coefficient, an inequality indicator.

Statistical Methods in Econometrics

Statistics is also prevalent in economics for trend analysis using inference, regression, and experimentation. Statistical inference is used to derive conclusions about a population from a sample. Causal inference is a method of inference where causality between variables is established. Regression analysis determines the relationship between variables to forecast economic outcomes. Future outcomes can be predicted based on past data. Some regression applications include relating income and education to predicting whether the minimum wage affects unemployment. Experimentation methods are used in economics to establish a valid relationship between variables. For example, a difference-in-difference regression method was used to determine the relationship between minimum wage and unemployment in the Nobel-prize winning study, “Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania.” To utilize the diff-in-diff regression method, Card and Krueger used quasi-experimental methods, comparing the unemployment rate of New Jersey, which implemented minimum wages, versus that of Pennsylvania, which had no minimum wage.

Quantitative Methods or Economic Reasoning?

Although econometrics remains widespread, balancing mathematical rigor versus intuitive economic reasoning is an important debate. Keynes and Tinbergen, prominent economists of their time, disagreed on whether economics should be quantitative. While Keynes believed economic reasoning should guide decision making, Tinbergen believed that quantitative approaches are the most powerful in making economic decisions. 

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Bibliography

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