Anthropogenic influences on atmospheric CO2

Abstract

We identify anthropogenic contributions to atmospheric CO 2 measured at Mauna Loa using a statistical automatic model selection algorithm (Autometrics). We find that vegetation, temperature and other natural factors alone cannot explain the trend or the variation in CO 2 growth. Industrial production components, driven by business cycles and economic shocks, are highly significant contributors.

Comment on "Polynomial cointegration tests of anthropogenic impact on global warming" by Beenstock et al. (2012) – some hazards in econometric modelling of climate change

“…Fourth, one can account for the changes in measurement (the most basic approach being indicator variables for the time periods before or after the break) while potentially also accounting for other unknown unmodelled breaks (see e.g. Hendry and Pretis, 2013). As emphasized in Hendry (2009), to draw substantive conclusions from a statistical or econometric analysis requires a complete, comprehensive and constant model; and to draw causal conclusions further requires that such a model is invariant to changes in all other variables.…”

Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis

“…Hendry (1999) proposes IIS as a procedure for testing parameter constancy. Further discussion, recent developments, and applications appear in Hendry, Johansen, and Santos (2008), Doornik (2009), Johansen and Nielsen (2009, 2013, Hendry and Santos (2010), Ericsson (2011aEricsson ( , 2011bEricsson ( , 2012, Ericsson and Reisman (2012), Bergamelli and Urga (2013), Hendry and Pretis (2013), Hendry and Doornik (2014), Pretis, Mann, and Kaufmann (2015), and Castle, Doornik, Hendry, and Pretis (2015). proposes a new application for IIS-as a generic test for time-varying forecast bias.…”

Detecting Location Shifts during Model Selection by Step-Indicator Saturation

“…Hendry et al [3] derive the null distribution of IIS for independent, identically distributed (IID) data, and [4] generalize that analysis to dynamic regression models (possibly with unit roots). Hendry and Santos [5] propose an IIS-based test of super exogeneity, building on [6]; and [7][8][9][10][11][12] provide empirical applications of IIS.…”