Datasets lie at the heart of empirical research as they provide the necessary testing ground to explore new hypotheses and firmly link ideas to reality. This chapter focuses on a specific subset of datasets, namely the historical datasets and details their features. It also characterises the main steps involved in dataset construction including identification, extraction, and synthesis of the information given; it discusses selectivity issues and common biases proper to historical data and introduces the concept of quantity-quality trade-off to dataset construction. Lastly, this chapter concentrates on wage datasets, which have taken centre stage in some of the great debates in economic history and shows how they evolved through time and how their transformation might be explained as a function of technical improvements and proper analysis of the historical context.
Ridolfi, L. (2024). Historical datasets. In C. Diebolt, M. Haupert (a cura di), Handbook of Cliometrics (pp. 2721-2785). Cham : Springer Nature.
Historical datasets
Ridolfi, Leonardo
2024-01-01
Abstract
Datasets lie at the heart of empirical research as they provide the necessary testing ground to explore new hypotheses and firmly link ideas to reality. This chapter focuses on a specific subset of datasets, namely the historical datasets and details their features. It also characterises the main steps involved in dataset construction including identification, extraction, and synthesis of the information given; it discusses selectivity issues and common biases proper to historical data and introduces the concept of quantity-quality trade-off to dataset construction. Lastly, this chapter concentrates on wage datasets, which have taken centre stage in some of the great debates in economic history and shows how they evolved through time and how their transformation might be explained as a function of technical improvements and proper analysis of the historical context.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1233579