The impact of climate conditions on economic production. Evidence from a global panel of regions

We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7–14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73–142$/tCO2 in 2020, rising to 92–181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise. © 2020 The Author

Enhanced economic connectivity to foster heat stress-related losses

Assessing global impacts of unexpected meteorological events in an increasingly connected world economy is important for estimating the costs of climate change. We show that since the beginning of the 21st century, the structural evolution of the global supply network has been such as to foster an increase of climate-related production losses. We compute first- and higher-order losses from heat stress–induced reductions in productivity under changing economic and climatic conditions between 1991 and 2011. Since 2001, the economic connectivity has augmented in such a way as to facilitate the cascading of production loss. The influence of this structural change has dominated over the effect of the comparably weak climate warming during this decade. Thus, particularly under future warming, the intensification of international trade has the potential to amplify climate losses if no adaptation measures are taken

Nighttime light data reveal lack of full recovery after hurricanes in Southern US

As the climate warms, many areas of the world are experiencing more frequent and extreme weather events. Hurricanes carry some of the costliest short-term socioeconomic repercussions via economic losses and people displaced. There is, however, little quantitative evidence regarding medium- to long-term effects, nor factors moderating recovery. Here we show that areas affected by hurricanes of category 4 or 5 in the southern US between 2014 and 2020 generally do not demonstrate full recovery in the longer term. Utilizing Visible Infrared Imaging Radiometer Suite nighttime light (NTL) data as a proxy for economic activity and population density, we build a timeline of recovery via NTL radiance levels. We exploit the difference in the eligibility for aid from the Federal Emergency Management Agency (FEMA) to apply a quasi-experimental method to identify changes in NTL radiance attributable to hurricanes. We find that after three years, affected areas demonstrate a reduction in NTL radiance levels of between 2% and 14% compared to the pre-disaster period. Combining these results with machine learning techniques, we are able to investigate those factors that contribute to recovery. We find counties demonstrating smaller reductions in NTL radiance levels in the months following the hurricane are buoyed by the amount of FEMA aid received, but that this aid does not foster a longer-term return to normal radiance levels. Investigating areas receiving FEMA aid at the household and individual level, we find age and employment are more important than other demographic factors in determining hurricane recovery over time. These findings suggest that aid may be more important in motivating short-term recovery for public entities than for individuals but is not sufficient to guarantee complete recovery in the longer term

Corona crisis fuels racially profiled hate in social media networks

[No abstract available

Decay radius of climate decision for solar panels in the city of Fresno, USA

To design incentives towards achieving climate mitigation targets, it is important to understand the mechanisms that affect individual climate decisions such as solar panel installation. It has been shown that peer effects are important in determining the uptake and spread of household photovoltaic installations. Due to coarse geographical data, it remains unclear whether this effect is generated through geographical proximity or within groups exhibiting similar characteristics. Here we show that geographical proximity is the most important predictor of solar panel implementation, and that peer effects diminish with distance. Using satellite imagery, we build a unique geo-located dataset for the city of Fresno to specify the importance of small distances. Employing machine learning techniques, we find the density of solar panels within the shortest measured radius of an address is the most important factor in determining the likelihood of that address having a solar panel. The importance of geographical proximity decreases with distance following an exponential curve with a decay radius of 210 meters. The dependence is slightly more pronounced in low-income groups. These findings support the model of distance-related social diffusion, and suggest priority should be given to seeding panels in areas where few exist

Truncation Error Estimates in Process Life Cycle Assessment Using Input‐Output Analysis

Process life cycle assessment (PLCA) is widely used to quantify environmental flows associated with the manufacturing of products and other processes. As PLCA always depends on defining a system boundary, its application involves truncation errors. Different methods of estimating truncation errors are proposed in the literature; most of these are based on artificially constructed system complete counterfactuals. In this article, we review the literature on truncation errors and their estimates and systematically explore factors that influence truncation error estimates. We classify estimation approaches, together with underlying factors influencing estimation results according to where in the estimation procedure they occur. By contrasting different PLCA truncation/error modeling frameworks using the same underlying input‐output (I‐O) data set and varying cut‐off criteria, we show that modeling choices can significantly influence estimates for PLCA truncation errors. In addition, we find that differences in I‐O and process inventory databases, such as missing service sector activities, can significantly affect estimates of PLCA truncation errors. Our results expose the challenges related to explicit statements on the magnitude of PLCA truncation errors. They also indicate that increasing the strictness of cut‐off criteria in PLCA has only limited influence on the resulting truncation errors. We conclude that applying an additional I‐O life cycle assessment or a path exchange hybrid life cycle assessment to identify where significant contributions are located in upstream layers could significantly reduce PLCA truncation errors.EC/FP7/603864/EU/High-End cLimate Impacts and eXtremes/HELIXDFG, SFB 1026, Sustainable Manufacturing - Globale Wertschöpfung nachhaltig gestalte

Road to glory or highway to hell? Global road access and climate change mitigation

Transportation infrastructure is considered a key factor for economic development and poverty alleviation. The United Nations have explicitly included the provision of transport infrastructure access, e.g. through all-season road access, in their Sustainable Development Goal agenda (SDGs, target 9.1). Yet, little is known about the number of people lacking access to roads worldwide, the costs of closing existing access gaps and the implications of additional roads for other sustainability concerns such as climate change mitigation (SDG-13). Here we quantify, for 250 countries and territories, the percentage of population without road access in 2 km. We find that infrastructure investments required to provide quasi-universal road access are about USD 3 trillion. We estimate that the associated cumulative CO2 emissions from construction work and additional traffic until the end of the century amount to roughly 16 Gt. Our geographically explicit global analysis provides a starting point for refined regional studies and for the quantification of further environmental and social implications of SDG-9.1

Post-Brexit no-trade-deal scenario: Short-term consumer benefit at the expense of long-term economic development

After the United Kingdom has left the European Union it remains unclear whether the two parties can successfully negotiate and sign a trade agreement within the transition period. Ongoing negotiations, practical obstacles and resulting uncertainties make it highly unlikely that economic actors would be fully prepared to a “no-trade-deal” situation. Here we provide an economic shock simulation of the immediate aftermath of such a post-Brexit no-trade-deal scenario by computing the time evolution of more than 1.8 million interactions between more than 6,600 economic actors in the global trade network. We find an abrupt decline in the number of goods produced in the UK and the EU. This sudden output reduction is caused by drops in demand as customers on the respective other side of the Channel incorporate the new trade restriction into their decision-making. As a response, producers reduce prices in order to stimulate demand elsewhere. In the short term consumers benefit from lower prices but production value decreases with potentially severe socio-economic consequences in the longer term

Future heat stress to reduce people’s purchasing power

With increasing carbon emissions rising temperatures are likely to impact our economies and societies profoundly. In particular, it has been shown that heat stress can strongly reduce labor productivity. The resulting economic perturbations can propagate along the global supply network. Here we show, using numerical simulations, that output losses due to heat stress alone are expected to increase by about 24% within the next 20 years, if no additional adaptation measures are taken. The subsequent market response with rising prices and supply shortages strongly reduces the consumers’ purchasing power in almost all countries including the US and Europe with particularly strong effects in India, Brazil, and Indonesia. As a consequence, the producing sectors in many regions temporarily benefit from higher selling prices while decreasing their production in quantity, whereas other countries suffer losses within their entire national economy. Our results stress that, even though climate shocks may stimulate economic activity in some regions and some sectors, their unpredictability exerts increasing pressure on people’s livelihood

Teleconnected food supply shocks

The 2008–2010 food crisis might have been a harbinger of fundamental climate-induced food crises with geopolitical implications. Heat-wave-induced yield losses in Russia and resulting export restrictions led to increases in market prices for wheat across the Middle East, likely contributing to the Arab Spring. With ongoing climate change, temperatures and temperature variability will rise, leading to higher uncertainty in yields for major nutritional crops. Here we investigate which countries are most vulnerable to teleconnected supply-shocks, i.e. where diets strongly rely on the import of wheat, maize, or rice, and where a large share of the population is living in poverty. We find that the Middle East is most sensitive to teleconnected supply shocks in wheat, Central America to supply shocks in maize, and Western Africa to supply shocks in rice. Weighing with poverty levels, Sub-Saharan Africa is most affected. Altogether, a simultaneous 10% reduction in exports of wheat, rice, and maize would reduce caloric intake of 55 million people living in poverty by about 5%. Export bans in major producing regions would put up to 200 million people below the poverty line at risk, 90% of which live in Sub-Saharan Africa. Our results suggest that a region-specific combination of national increases in agricultural productivity and diversification of trade partners and diets can effectively decrease future food security risks