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Humans have been trying to predict the future since the beginning of time. From the ancient Greeks consulting the Oracle of Delphi to kings from the Shang Dynasty turning to oracle bones, people have tried to predict everything from the weather to success on the battlefield.
In these initial forecasts people used their judgement and previous experiences to observe trends and patterns, which made their reliability difficult to assess and reproduce.
In the late 19th to early 20th century, the introduction of statistical tools allowed people to analyze data over time, marking the start of the modern era of quantitative forecasting, By the 1930s, economists were beginning to systematically model entire economies. At the end of World War II, using these models, many predicted a post-war return to economic depression.
Lawrence Klein, however, predicted the opposite. One of the pioneers in building macroeconomic models, Klein predicted that the economy would expand—fueled by an unsatisfied demand for consumer goods during the war combined with the purchasing power of returning soldiers. He was right.
His research led to a series of increasingly sophisticated models that captured the complex dynamics of economies. Klein joined the Department of Economics in the School of Arts & Sciences in 1958 and went on to construct the Wharton Econometric Forecasting Model, which was used to forecast fluctuations in national products, exports, investments, and consumption and to study their effect on areas such as taxation, public expenditure, and rising oil prices—a legacy that continues today in tools like the Penn Wharton Budget Model.
Today, mathematical modeling continues to forecast economic trends and is widely used to predict everything from weather and climate change to public health outcomes and the impacts of policies, energy systems, and financial markets.
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