Academic-quality transformation tools for ungrouped numeric data in econometrics & statistics
Macroeconomics studies how an entire economy behaves — how total output, the general price level, employment, and interest rates are determined. To understand these outcomes, economists typically divide the economy into three interconnected markets: the goods market, the money market, and the labour market. The famous IS-LM model, which we
Why does an economy sometimes get stuck producing less than it could, with willing workers and idle machines sitting unused? Classical economists assumed markets would sort this out through prices and wages. Keynes argued something more powerful: output is driven by aggregate demand, and the economy can settle into equilibrium
Introduction: Multiple Linear Regression Using Matrix The matrix approach to regression becomes especially powerful once we move beyond a single explanatory variable. It gives us numerical estimates of our multiple linear regression parameters more efficiently. In this post, we estimate a demand function using matrix algebra, where quantity demanded ()
Data transformations are one of the most important steps in applied economics. Before any economic variable, say GDP, inflation, wages, or trade, can be used in a model, it usually needs to be changed in some way. Raw data is rarely ready to use as it comes. This article explains
Economic forecasting has always been one of the toughest jobs in economics — predicting inflation, growth, or job trends often felt like reading tea leaves. But today, artificial intelligence and machine learning are changing the game, helping economists see patterns in data that human eyes and old statistical models often
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