![]() One of the four factors behind the Kaya Identity equation is affluence: GDP, or the average income per person. If improvements in energy or carbon intensity were slow (or in some cases non-existent), then CO 2 emissions grew rapidly. What differentiates whether CO 2 emissions have greatly increased, stabilized, or fallen was whether countries could reduce their energy and carbon intensity fast enough to offset this large increase in GDP (and increases in population). This has been a major driver of emissions – a stronger driver than the increase in population. ![]() What’s common between countries is that most have seen a large increase in GDP over this period. In the box below we explain how to interpret this chart. Also shown is total annual CO 2 emissions – the final result. ![]() ![]() This interactive chart shows the relative change in the four factors: population, GDP per capita, energy intensity (energy per unit of GDP), and carbon intensity (CO 2 per unit of energy) over time. An even less ethical practice is denoted by the expression “cherry-picking,” usually referring to biased selection of patients, analysis of subsets of data, or reporting of results favorable to the interests of a researcher, organization, or sponsor.With data we can look more closely at how the four factors in the Kaya Identity are driving emissions across different countries, and over time. The scientific validity of data dredging is dubious, usually unacceptable. Such analyses are sometimes done when data have been collected on a large number of variables and unanticipated hypotheses are suggested by hypothesis-free analyses. Under the terms of the licence agreement, an individual user may print out a PDF of a single entry from a reference work in OR for personal use (for details see Privacy Policy and Legal Notice).ĭate: 02 August 2023 Data Dredging Source: A Dictionary of Epidemiology Author(s): Miquel PortaĪ jargon term meaning analyses done on a post hoc basis without benefit of prestated hypotheses. PRINTED FROM OXFORD REFERENCE ((c) Copyright Oxford University Press, 2023.
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