The Systemic Turn in Human and Natural Sciences by Lucia Urbani Ulivi

Author:Lucia Urbani Ulivi
Language: eng
Format: epub
ISBN: 9783030007256
Publisher: Springer International Publishing

3.1 Evaluation of Climate Damages

In most integrated assessment models, climate damages are accounted for by an ad hoc damage function that impacts output (at the sectoral or the macro level) as a function of temperature increases brought about by GHG emissions. This approach ignores the propagation of shocks and the feedbacks that might relate damages to different sectors. Moreover, as most IAMs do not allow for agent heterogeneity, they entirely overlook distributional issues linked to climate damages.

Against this background, one of the characterizing features of complex systems lies in their representation of real phenomena as emerging from the interactions of heterogeneous agents. This approach allows to model the emergence of aggregate damages from micro shocks in production, procurement or finance percolating along network structures where households, firms, banks and the government interact. For instance, Hallegatte (2008) provides a model of shock propagation within Louisiana after the impact of hurricane Katrina. In the model, firms adapt their behaviour in an input-output network. Simulation results show that propagation mechanisms are essential for the assessment of the consequences of disasters, and that taking into account residual production capacities is necessary not to overestimate the positive economic effects of reconstruction. A straightforward consequence is the pivotal role played by the topology of the production network, which determines how firms are connected to each other and how (intermediate) goods flow though these links. Similarly, Henriet et al. (2012) disaggregate industry input-output tables to represent the production structure of regional economies at the firm level. They show that aggregate damages stemming from exogenous disasters are deeply affected by the network structure and the final outcomes depend especially on network concentration and clustering. In particular, concentration (degree of redundancy of suppliers and clients) acts as a risk sharing feature and clustering (degree of geographically dense interactions) allows small groups of interconnected firms to positively react to shocks happening outside the community they belong to.4

Systems’ connectivity increases dramatically the complexity of studying the impact of climate events, and the impossibility to reduce the problem through simple aggregation or to impede failures at all scales calls for a re-design of how to model climate and weather damages (Helbing 2013).

Moving from a relatively restricted geographical focus to a global perspective, Bierkandt et al. (2014) introduce a model (labelled as acclimate) that is designed to evaluate the consequences of extreme climate events through the global supply chain. The model nests AB features (consumption and production sites are treated as agents) in an input-output network employed to track flows of goods in the system (taking also into account transportation). Acclimate is particularly well suited to study the propagation of shocks and it has been extended to better explore the differences between top-down cascades promoted by forwards linkages and demand-induced backward dynamics (Wenz et al. 2014). However, being the time scale of the model’s simulations very short (from days to some weeks), price adjustment mechanisms are nearly absent, and technical change is overlooked. These shortcomings prevent from studying long-run macroeconomic dynamics. Nonetheless, this

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