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New data, new results? How data sources and vintages affect the replicability of research

  • Colorado State University

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

Macroeconomic variables like unemployment, inflation, trade, or GDP are not set in stone: they are preliminary estimates that are constantly revised by statistical agencies. These data revisions, or data vintages, often provide conflicting information about the size of a country’s economy or its level of development, reducing our confidence in established findings. Would researchers come to different conclusions if they used different vintages? To answer this question, I survey all articles published in a top political science journal between 2005 and 2020. I replicate three prominent articles and find that the use of different vintages can lead to different statistical results, calling into question the robustness of otherwise rigorous empirical research. These findings have two practical implications. First, researchers should always be transparent about their data sources and vintages. Second, researchers should be more modest about the precision and accuracy of their point estimates, since these estimates can mask large measurement errors.

Original languageEnglish
Number of pages13
JournalResearch and Politics
Volume10
Issue number2
DOIs
StatePublished - Apr 2023
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Keywords

  • data quality
  • development indicators
  • replication
  • statistical capacity

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