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Subject: heterogeneity × WGL Institute: PIK ×

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    Fiscal Consolidation Programs and Income Inequality
    (Malden, Mass. [u.a.] : Wiley-Blackwell, 2020) Brinca, Pedro; Ferreira, Miguel H.; Franco, Francesco; Holter, Hans A.; Malafry, Laurence
    We document a strong empirical relationship between higher income inequality and stronger recessive impacts of fiscal consolidation episodes across time and space. To explain this finding, we develop a life-cycle economy with uninsurable income risk. We calibrate our model to match key characteristics of several European economies, including inequality and fiscal structures, and study the effects of fiscal consolidation programs. In our model, higher income risk induces precautionary savings behavior, which decreases the proportion of credit-constrained agents in the economy. These agents have less elastic labor supply responses to fiscal consolidations, which explain the correlation with inequality in the data.
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    Key determinants of global land-use projections
    ([London] : Nature Publishing Group UK, 2019) Stehfest, Elke; van Zeist, Willem-Jan; Valin, Hugo; Havlik, Petr; Popp, Alexander; Kyle, Page; Tabeau, Andrzej; Mason-D’Croz, Daniel; Hasegawa, Tomoko; Bodirsky, Benjamin L.; Calvin, Katherine; Doelman, Jonathan C.; Fujimori, Shinichiro; Humpenöder, Florian; Lotze-Campen, Hermann; van Meijl, Hans; Wiebe, Keith
    Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies.
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    Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks
    (London : Nature Publishing Group, 2017) Zemp, D.C.; Schleussner, C.-F.; Barbosa, H.M.J.; Hirota, M.; Montade, V.; Sampaio, G.; Staal, A.; Wang-Erlandsson, L.; Rammig, A.
    Reduced rainfall increases the risk of forest dieback, while in return forest loss might intensify regional droughts. The consequences of this vegetation-atmosphere feedback for the stability of the Amazon forest are still unclear. Here we show that the risk of self-amplified Amazon forest loss increases nonlinearly with dry-season intensification. We apply a novel complex-network approach, in which Amazon forest patches are linked by observation-based atmospheric water fluxes. Our results suggest that the risk of self-amplified forest loss is reduced with increasing heterogeneity in the response of forest patches to reduced rainfall. Under dry-season Amazonian rainfall reductions, comparable to Last Glacial Maximum conditions, additional forest loss due to self-amplified effects occurs in 10-13% of the Amazon basin. Although our findings do not indicate that the projected rainfall changes for the end of the twenty-first century will lead to complete Amazon dieback, they suggest that frequent extreme drought events have the potential to destabilize large parts of the Amazon forest.
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    Historic and future increase in the global land area affected by monthly heat extremes
    (Bristol : IOP Publishing, 2013) Coumou, Dim; Robinson, Alexander
    Climatic warming of about 0.5 ° C in the global mean since the 1970s has strongly increased the occurrence-probability of heat extremes on monthly to seasonal time scales. For the 21st century, climate models predict more substantial warming. Here we show that the multi-model mean of the CMIP5 (Coupled Model Intercomparison Project) climate models accurately reproduces the evolution over time and spatial patterns of the historically observed increase in monthly heat extremes. For the near-term (i.e., by 2040), the models predict a robust, several-fold increase in the frequency of such heat extremes, irrespective of the emission scenario. However, mitigation can strongly reduce the number of heat extremes by the second half of the 21st century. Unmitigated climate change causes most (>50%) continental regions to move to a new climatic regime with the coldest summer months by the end of the century substantially hotter than the hottest experienced today. We show that the land fraction experiencing extreme heat as a function of global mean temperature follows a simple cumulative distribution function, which depends only on natural variability and the level of spatial heterogeneity in the warming.