Climate Change
David has had a long-standing interest in the natural sciences, including palaeontology and geology. From his readings on these topics and from discussions with experts, David became concerned about anthropogenic influences in climate change and the economic consequences thereof.
At the time, much climate science was nonstochastic and scenario-driven, so David saw a role for econometrics in advancing understanding and driving policy.Hendry (2011)—David's initial foray into climate econometrics—exam- ines geologic evidence on climate change and its role in great extinctions. Relatedly, Castle and Hendry (2020) derive the causal role of atmospheric CO2 levels in past Ice Ages. Hendry and Pretis (2013) turn to relatively recent evidence from the Mauna Loa Observatory, using IIS and automatic model selection across a wide range of climatic and economic variables to determine the extent to which anthropogenic sources increase atmospheric CO2. Their model controls for a number of natural carbon sources and sinks—such as vegetation, temperature, weather, and dynamic transport—and determines the additional anthropogenic contributions from industrial production, business cycles, and shocks. The anthropogenic sources are significant contributors to changes in atmospheric CO2. Pretis and Hendry (2013) illustrate how advances in econometric methodology can improve existing studies of global warming. Pretis, Schneider, Smerdon and Hendry (2016) develop saturation procedures using “designer breaks” to detect and identify volcanic eruptions, some of which created strong albeit temporary climatic changes.
In 2015, David and Felix Pretis received a £660,000 grant from the Robertson Foundation to support their research programme Climate Econometrics, ably managed by Angela Wenham. The programme serves as a key catalyst for wide-ranging econometric advances in climate change, with several recent developments.
Pretis (2020) shows the equivalence of energy balance models and cointegrated vector autoregressions. David's former DPhil student Andrew Martinez (2020a) uses a multidisciplinary approach with automated model selection to show that larger errors in a hurricane's predicted landfall increase the hurricane's damages; see also Martinez (2020b). Hendry (2020) and Castle and Hendry (2020) model CO2 emissions in the UK over the last century and a half using saturation techniques and automatic model selection. Over the last several decades, UK emissions have dropped dramatically to pre-1900 levels, even while real income increased manyfold, with legislation and technological improvements being key factors in the reduction. To paraphrase the title of David's 2020 paper (“First In, First Out”), Britain was the first country into the Industrial Revolution—then producing a large share of global anthropogenic CO2 emissions—and Britain is now becoming one of the first countries out. On 22 April 2017, Britain had its first full day in over a century with no electricity being produced by coal- fired plants. In April 2020, electricity production in Britain went for 18 consecutive days coal-free. While climate change remains a major global challenge, progress can be made. Modern dynamic econometric analysis can shed light on climate change and help guide policy.6