A financial macro-network approach to climate policy evaluation

Existing approaches to assess the economic impact of climate policies tend to overlook the financial sector and to focus only on direct effects of policies on the specific institutional sector they target, neglecting possible feedbacks between sectors, thus, underestimating the overall policy effect. To fill in this gap, we develop a methodology based on financial networks, which allows for analyzing the transmission throughout the economy of positive or negative shocks induced by the introduction of specific climate policies. We apply the methodology to empirical data of the Euro Area to identify the feedback loops between the financial sector and the real economy both through direct and indirect chains of financial exposures across multiple financial instruments. By focusing on climate policy-induced shocks that affect directly either the banking sector or non-financial firms, we analyze the reinforcing feedback loops that could amplify the effects of shocks on the financial sector and then cascade on the real economy. Our analysis helps to understand the conditions for virtuous or vicious cycles to arise in the climate-finance nexus and to provide a comprehensive assessment of the economic impact of climate policies

Tipping elements of the Indian monsoon : Prediction of onset and withdrawal

Funded by LINC project. Grant Number: 289447 EC's Marie Curie ITN program. Grant Number: FP7-PEOPLE-2011-ITN RFBR. Grant Number: 16-07-01186 Government of Russian Federation. Grant Number: 14.Z50.31.0033Peer reviewedPublisher PD

Financialization in the EU and its consequences

Building on ISIGrowth research, in this policy brief we present empirical evidence on the patterns of increasing financialization in the EU in the last two decades, an analysis of its possible adverse effects on several objectives of the EU 2030 agenda, including inclusive growth, innovation, inequality and financial stability. We conclude by providing some policy insights and recommendations. The notion of financialization reflects, on the one hand, the engagement of non-financial firms into financial activities not directly related to production, and, on the other hand, the relative size of the financial sector with respect to the overall economy. Several empirical indicators show that financialization has been increasing in the Euro Area in the last two decades. This finding is important because while financialization has been so far mostly considered to be a driver for growth and innovation, there is today a wealth of theoretical arguments and empirical evidence pointing to the detrimental effects of excessive financialization for growth, innovation, inequality and financial stability. First, excessive financialization depresses economic growth because it implies that a larger fraction of credit is directed toward unfruitful investment projects, possibly generating economic crises (e.g. via housing price bubbles). Second, financialization has negative impact on innovation because the separation between actors taking risks from innovation and actors extracting rents from innovation implies lower share of reinvested profits (e.g. via short-termism and share buy-backs). Third, financialization contributes to inequality by strengthening top earners’ bargaining power in terms of higher wages and lower taxation, as well as by burdening public budgets with fiscal assistance to financial institutions in time of crisis. Fourth, financialization may lead to financial instability by increasing both the leverage of interconnected financial institutions and the risk of mispricing of large asset classes (e.g. the dynamics of leverage and mispricing of mortgage backed securities in the run of the 2008 financial crisis). We suggest some countermeasures that could help containing excessive financialization, including: (i) fostering the demand in the real sector; (ii) establishing mission-oriented programs by going beyond the traditional conceptual framework to fix market failures and aim to create markets where they may not exist at all; (iii) encouraging the alignment of top managers’ compensation schemes with long-term profit and corporate social responsible goals; (iv) studying the possibility of setting a minimal ratio on banks for lending to the real economy (to non-real estate sectors); (v) studying the possibility of setting a maximal level of intra-financial leverage for financial institutions

Temporal organization of magnetospheric fluctuations unveiled by recurrence patterns in the Dst index

This work has been financially supported by the joint Greek-German project “Transdisciplinary assessment of dynamical complexity in magnetosphere and climate: A unified description of the nonlinear dynamics across extreme events” funded by IKY and DAAD. Individual financial support of the authors has been granted by the LINC (Learning about Interacting Networks in Climate) project (project no. 289447) funded by the Marie Curie Initial Training Network (ITN) program (FP7-PEOPLE2011-ITN), the German Federal Ministry for Science and Education (BMBF) via the Young Investigator’s Group CoSy-CC2 (grant no. 01LN1306A) and the project GLUES, the Stordalen Foundation (Planetary Boundary Research Network PB.net), and the International Research Training Group IRTG 1740/TRP 2014/50151-0, jointly funded by the German Research Foundation (DFG, Deutsche Forschungsgemeinschaft) and the S˜ao Paulo Research Foundation (FAPESP, Funda¸c˜ao de Amparo `a Pesquisa do Estado de S˜ao Paulo). Numerical codes used for estimating RQA and RNA properties can be found in the software package pyunicorn70, which is available at https://github.com/pik-copan/pyunicorn. The Dst data have been obtained from the World Data Center for Geomagnetism, Kyoto (http://wdc.kugi.kyoto-u.ac.jp/index.html). We are grateful to three reviewers of an earlier version of this manuscript for their detailed comments.Peer reviewedPublisher PD

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

We introduce the \texttt{pyunicorn} (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. \texttt{pyunicorn} is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, \texttt{pyunicorn} provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis (RQA), recurrence networks, visibility graphs and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.Comment: 28 pages, 17 figure

Indian Summer Monsoon

Das Ziel dieser Arbeit ist es Geheimnisse des Indischen Monsuns aufzudecken-ein groß-skaliges Klimaphänomen,das mehr als 1,7 Milliarden Menschen stark beeinflußt.Folglich ist das Verständnis der Mechanismen des Indischen Monsuns und seine erfolgreiche Prognose nicht nur eine Frage von größtem Interesse,sondern auch eine bedeutende wissenschaftliche Herausforderung.Der erste Teil dieser Arbeit ist den extremen Niederschlagsereignissen über dem Indischen Subkontinent gewidmet.In dieser Arbeit wurde gezeigt,dass eine Synchronizität zwischen extremen Niederschlagsereignissen in den Eastern Ghats und Nord Pakistan Regionen durch das Zusammenspiel zwischen dem indischen Monsun und einem nicht-Monsun-Niederschlagsmuster verursacht wird.Dieses Ergebnis unterstreicht die Bedeutung der Region Nord-Pakistan zur Ableitung der Wechselwirkung zwischen dem indischen Monsun-System und den West-Störungen,und verbessert daher das Verständnis der Kopplung des indischen Monsuns mit den Extratropen.Der zweite Teil der Arbeit befasst sich mit dem Problem der räumlichen und zeitlichen Organisation des abrupten Übergangs auf den indischen Monsun.Hier wird ein neuartiger Mechanismus des räumlich-zeitlichen Übergangs zur Regenperiode vorgeschlagen.Er hat mehrere Vorteile gegenüber bestehenden Erklärungen der Natur des indischen Monsuns:Es beschreibt den abrupten Übergang in einer gewählten Region des indischen Subkontinents sowie die räumliche Ausbreitung und Variabilität des indischen Monsuns beim Einsetzen entlang der Achse des Monsuns.Der dritte Teil dieser Arbeit konzentriert sich auf das Problem der Vorhersagbarkeit des indischen Monsuns.Das vorgeschlagene Verfahren ermöglicht die Vorhersage des Einsetzens und Endens über einen mehr als zwei Wochen bzw.einen Monat früheren Zeitraum im Vergleich zu bisher bekannten Methoden.Schließlich kann die vorgeschlagene Instrumentarium direkt in das bestehende lang-reichweitige Vorhersagesystem für den Monsuns implementiert werden.The aim of this thesis is to uncover some of the mysteries surrounding the Indian Monsoon - a large-scale climatic phenomenon affecting more than 1.7 billion people. Consequently, understanding the mechanisms of the Indian monsoon and its successful forecasting is not only a question of great interest, but also a significant scientific challenge. The first part of this thesis is devoted to extreme rainfall events over the Indian subcontinent. In this thesis, I have shown that a synchronicity between extreme rainfall events in the Eastern Ghats and North Pakistan regions is caused by the interplay between the Indian Monsoon and a non-monsoonal precipitation pattern driven by the Westerlies - Western Disturbances. This result highlights the importance of the North Pakistan region for inferring the interaction between the Indian Monsoon system and Western Disturbances, and, therefore, improves the understanding of the Indian Monsoon coupling with the extratropics. The second part of this dissertation is concerned with the problem of the spatial and temporal organization of the abrupt transition to the Indian monsoon. Here, I have proposed a novel mechanism of a spatio-temporal transition to monsoon. It has several advantages in comparison to existing explanations of the Indian Monsoon nature: it describes the abrupt transition to monsoon in a chosen region of the Indian subcontinent, as well as the spatial propagation and variability of the Indian Monsoon onset along the axis of advance of monsoon. The third part of this thesis focuses on the problem of predictability of the Indian Monsoon. I have developed a novel method that predicts the onset and withdrawal dates more than two weeks and a month earlier than existing methods, respectively. Finally, the proposed scheme can be directly implemented into the existing long-range forecasting system of the monsoon''s timing

Network-based forecasting of climate phenomena

Network theory, as emerging from complex systems science, can provide critical predictive power for mitigating the global warming crisis and other societal challenges. Here we discuss the main differences of this approach to classical numerical modeling and highlight several cases where the network approach substantially improved the prediction of high-impact phenomena: 1) El Niño events, 2) droughts in the central Amazon, 3) extreme rainfall in the eastern Central Andes, 4) the Indian summer monsoon, and 5) extreme stratospheric polar vortex states that influence the occurrence of wintertime cold spells in northern Eurasia. In this perspective, we argue that network-based approaches can gainfully complement numerical modeling