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Erscheinungsjahr: 
2023
Quellenangabe: 
[Journal:] Economics: The Open-Access, Open-Assessment Journal [ISSN:] 1864-6042 [Volume:] 17 [Issue:] 1 [Article No.:] 20220039 [Year:] 2023 [Pages:] 1-14
Verlag: 
De Gruyter, Berlin
Zusammenfassung: 
This article proposes a methodology to identify technological transitions (TTs) by systematically using the total variation distance (TVD) metric. We use a database of renewable energy generation (REG) patents to exemplify the usefulness of TVD to uncover moments where a "big change" in REG technology happened. To do this, we compare the observed frequency distribution of technology codes of REG patents filed between 1973 and 2015 in the US, spread across seven categories (e.g., wind and tidal). We identify two crucial TTs, one at the beginning of the 1980s and another in the late 1990s and early 2000s. In this manner, we reconcile qualitative evidence that registers major REG changes with a quantitative measure that reflects them. Policy evaluations or causality analyses often rely on identifying TTs accurately; therefore, this approach is not constrained to the REG technology or TTs but helps reveal such transition moments in a database whose characteristics are suitable for the use of TVD.
Schlagwörter: 
patent classification
renewable energy generation
technological transitions
total variation distance
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