Cliometrics

Cliometrics

Cliometrics is a method of applying formal economic models and econometric analysis to historical trends and events. In order to test economic hypotheses, econometricians adapt formal economic models to incorporate measurable economic data and investigate whether the observable statistical relationships among these data sets agree with the implications of the theoretical models. Cliometrics stands on four pillars: mathematical modeling of economic theory, econometrics, large economic historical data sets, and computing technology to handle the many necessary calculations. Prior approaches to economic history tended to rely on the qualitative and narrative methods familiar to historians and interpret the economic aspects of historical investigation as contingent on the particular or unique historical conditions of a given time period or setting. Cliometrics revolutionized the study of economic history and stands in contrast to prior methods of economic history, which tend to rely on qualitative, interpretive, and narrative methods.

Cliometrics is the application of mathematical economics and econometrics to the study of economic history.

What Is Cliometrics?

Cliometrics is a method of applying formal economic models and econometric analysis to historical trends and events. Cliometrics revolutionized the study of economic history and stands in contrast to prior methods of economic history, which tend to rely on qualitative, interpretive, and narrative methods. Cliometrics began to develop in the 1950s and 60s and the Cliometric Society was founded in 1983. In 1993, Douglass North and Robert Fogel shared the Nobel Prize in Economics for their pioneering work in cliometrics. 

Cliometrics is also called econometric history and new economic history.

Cliometrics is the application of mathematical economics and econometrics to the study of economic history.
Cliometrics developed in the mid-20th century and revolutionized the study of economic history, which had previously been dominated by more qualitative methods.
Prior approaches to economic history tended to rely on the qualitative and narrative methods familiar to historians.
Cliometrics stands on four pillars: mathematical modeling of economic theory, econometrics, large economic historical data sets, and computing technology to handle the many necessary calculations.

Understanding Cliometrics

Cliometrics is an area of economic study that attempts to use historical data to model economic principles. Cliometrics uses economic theory and econometrics to gain insight into the past with modeling and statistics. The data used in the analysis include large pools of macro-level data regarding population and behavior trends, such as census data. Cliometrics is related to cliodynamics, which is the general application of modern mathematical and statistical models to historical data sets in other areas beyond economics. 

Academic journals that deal with cliometrics are the Economic History Review, Cliometrica, and Explorations in Economic History. Examples of article topics include nineteenth-century labor productivity in the United States and the United Kingdom, credit rationing and crowding out during the Industrial Revolution, and the relationship between population and real wages in Italian history.

Prior approaches to economic history tended to rely on the qualitative and narrative methods familiar to historians and interpret the economic aspects of historical investigation as contingent on the particular or unique historical conditions of a given time period or setting. However, over the course of the first half of the 20th century, the practice of economics was largely transformed by the development and widespread adoption of neoclassical mathematical models, econometric statistical analysis, the collection and use of large economic datasets such as national accounts, and computing technology to realize practical application of these tools. Cliometrics is simply the logical extension of this transformation into the field of economic history based on these four pillars. 

Neoclassical Modeling

Economic models developed during the 20th century typically seek to describe universal laws of economic behavior based on certain assumptions about rational people can be expected to act given the conditions of scarcity and limited choices presented to them. Unless human rationality is only a recent development, early cliometricians argued, then the economic theories based on it should apply not just to current economic events, but also to economic phenomena 100 or 1,000 years ago.   

Econometrics

In order to test economic hypotheses, econometricians adapt formal economic models to incorporate measurable economic data and investigate whether the observable statistical relationships among these data sets agree with the implications of the theoretical models. For economic history, cliometricians argue, this means that competing explanations of historical events such as the Industrial Revolution no longer need to be simply considered differences of opinion regarding how one historian or another chooses to interpret the historical record, but they can instead be rigorously tested and compared to eliminate erroneous historical theories.

Historical Data

Cliometricians emphasize the use of large data sets of historical information regarding prices, quantities of goods, incomes, and other relevant economic variables. Vast collections of these data sets were already available in the form of mercantile records and published financial reports dating back years, decades, or in some cases centuries, but they were largely ignored by previous economic historians or only selectively used to support their narratives. At least in part, this was simply due to the unavailability of the proper mathematical and physical tools to handle and make meaningful use of large quantitative data sets. 

Computer Technology

For cliometrics, the final piece of the puzzle was modern computing technology. Computers make possible the processing of large numbers of mathematical operations on large data sets. Without them, calculating the statistics and relationships between them that are required for the testing of hypotheses derived from economic theory regarding economic history would be impossible.

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