Exogeneity in Climate Econometrics

Pretis, Felix

doi:10.2139/ssrn.2898203

Cited by 5 publications

(2 citation statements)

References 67 publications

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“…For the present study, we proceed under the assumption of weak exogeneity—studying climate impacts in isolation without explicitly modelling the underlying climate processes—and strong exogeneity—assuming an absence of feedbacks allowing the construction of conditional projections. However, given the strong evidence of economic activity affecting climate, the magnitude of feedbacks in empirical estimates and the potential failure of weak (and strong) exogeneity are open for further research [ 31 ].…”

Section: Methodsmentioning

confidence: 99%

Uncertain impacts on economic growth when stabilizing global temperatures at 1.5°C or 2°C warming

Pretis

Schwarz

Tang

et al. 2018

Phil. Trans. R. Soc. A.

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Empirical evidence suggests that variations in climate affect economic growth across countries over time. However, little is known about the relative impacts of climate change on economic outcomes when global mean surface temperature (GMST) is stabilized at 1.5°C or 2°C warming relative to pre-industrial levels. Here we use a new set of climate simulations under 1.5°C and 2°C warming from the ‘Half a degree Additional warming, Prognosis and Projected Impacts' (HAPPI) project to assess changes in economic growth using empirical estimates of climate impacts in a global panel dataset. Panel estimation results that are robust to outliers and breaks suggest that within-year variability of monthly temperatures and precipitation has little effect on economic growth beyond global nonlinear temperature effects. While expected temperature changes under a GMST increase of 1.5°C lead to proportionally higher warming in the Northern Hemisphere, the projected impact on economic growth is larger in the Tropics and Southern Hemisphere. Accounting for econometric estimation and climate uncertainty, the projected impacts on economic growth of 1.5°C warming are close to indistinguishable from current climate conditions, while 2°C warming suggests statistically lower economic growth for a large set of countries (median projected annual growth up to 2% lower). Level projections of gross domestic product (GDP) per capita exhibit high uncertainties, with median projected global average GDP per capita approximately 5% lower at the end of the century under 2°C warming relative to 1.5°C. The correlation between climate-induced reductions in per capita GDP growth and national income levels is significant at the p < 0.001 level, with lower-income countries experiencing greater losses, which may increase economic inequality between countries and is relevant to discussions of loss and damage under the United Nations Framework Convention on Climate Change.This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

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Section: Methodsmentioning

confidence: 99%

Uncertain impacts on economic growth when stabilizing global temperatures at 1.5°C or 2°C warming

Pretis

Schwarz

Tang

et al. 2018

Phil. Trans. R. Soc. A.

Self Cite

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“…Therefore, in this sense, we could think that global temperature anomalies and CO 2 emissions may also adjust to deviations from the long-run in our estimated climate system. As Pretis (2017) warns, human activity (say, through deforestation) affects local and global climate and climate change, in turn, affects human activity (say, crop yields). Empirically, this implies that if we want to estimate the effect of humanity (in its multiple dimensions) on climate change and vice versa, it is necessary to evaluate the exogeneity of the variables within the economic-climate system to understand these interrelations in the long-run.…”

Section: Long-run Effectsmentioning

confidence: 99%

Are Soybean Yields Getting a Free Ride From Climate Change? Evidence From Argentine Time Series

Ahumada¹,

Cornejo²

2018

Preprint

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Soybean yields are often indicated as an interesting case of climate change mitigation due to the beneficial effects of CO2 fertilization. In this paper we econometrically study this effect using a time series model of yields in a multivariate framework for a main producer and exporter of this commodity, Argentina. We have to deal with the upward behavior of soybean yields trying to identify which variables are the long-run determinants responsible of its observed trend. With this aim we adopt a partial system approach to estimate subsets of long-run relationships due to climate, technological and economic factors. Using an automatic selection algorithm we evaluate encompassing of the different obtained equilibrium correction models. We found that only technological innovations due to new crop practices and the use of modified seeds explain soybean yield in the long run. Regarding short run determinants we found positive effects associated with the use of standard fertilizers and also from changes in atmospheric CO2 concentration which would suggest a mitigation effect from global warming. However, we also found negative climate effects from periods of droughts associated with La Niña episodes, high temperatures and extreme rainfall events during the growing season of the plant.

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How Econometrics Can Help Us Understand the Effects of Climate Change on Crop Yields: The Case of Soybeans

Ahumada

Cornejo

2021

The Latin American Studies Book Series

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Climate econometrics is a new eld which is providing a fruitful approach to give a rigorous basis for many hypotheses related to climate change. With this aim, this chapter illustrates how econometrics can help understand the eects of climate change on the time behavior of crop yields at a country-level scale. We discuss dierent issues which empirical studies should address such as the non-stationarity nature of climate variables, the exogeneity of the variables used for modelling crop yields, the existence of non-linearities, the presence of extreme events, disentangling short and dealing with long-run eects of climate change, and collinearities in a multivariate framework. The incorporation of new lands to production or the rise of crop yields on existing lands to meet increasing demand for food and energy may be threatened by global climate change. However, there are several factors that have reduced the harmful impacts of climate change: adaptation, trade, the declining share over time of agriculture in the economy and carbon fertilization. In particular, the CO 2 fertilization eect should be taken into account for certain crops. As an example, we focus on soybeans in the main producer and exporter countries: Brazil and United States, and particularly in Argentina, as an interesting case of mitigation and adaptation processes due to global and local climate changes.

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Exogeneity in Climate Econometrics

Cited by 5 publications

References 67 publications

Uncertain impacts on economic growth when stabilizing global temperatures at 1.5°C or 2°C warming

Uncertain impacts on economic growth when stabilizing global temperatures at 1.5°C or 2°C warming

Are Soybean Yields Getting a Free Ride From Climate Change? Evidence From Argentine Time Series

How Econometrics Can Help Us Understand the Effects of Climate Change on Crop Yields: The Case of Soybeans

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