Tackling model selection and validation : an information theoretic criterion

Simulated economies suffer intrinsically from validation and comparison problems. The choice of a suitable indicator quantifying the distance between the model and the data is pivotal to model selection. However, how to validate and discriminate between models are still open problems calling for further investigation, especially in light of the increasing use of simulations in social sciences. In this paper I present a new information theoretic criterion to measure how close models' synthetic output replicates the properties of observable time series without the need to resort to any likelihood function or to impose stationarity requirements. This indicator is sufficiently general to be applied to any kind of model able to simulate or predict time series data, from simple univariate models such as Auto Regressive Moving Average (ARMA) and Markov processes to more complex objects including agent-based or dynamic stochastic general equilibrium models. More specifically, I use a simple function of the L-divergence computed at different block lengths in order to select the model that is better able to reproduce the distributions of time changes in the data. To evaluate the L-divergence, probabilities are estimated across frequencies including a correction for the systematic bias. Finally, using a known data generating process, I show how this indicator can be used to validate and discriminate between different univariate models providing a precise measure of the distance of each model from the data

Believe me when I say green! Heterogeneous expectations and climate policy uncertainty

We develop a dynamic model where heterogeneous firms take investment decisions depending on their beliefs on future carbon prices. A policy-maker announces a forward-looking carbon price schedule but can decide to default on its plans if perceived transition risks are high. We show that weak policy commitment, especially when combined with ambitious mitigation announcements, can trap the economy into a vicious circle of credibility loss, carbon-intensive investments and increasing risk perceptions, ultimately leading to a failure of the transition. The presence of behavioural frictions and heterogeneity - both in capital investment choices and in the assessment of the policy-maker’s credibility - has strong non-linear effects on the transition dynamics and the emergence of ‘high-carbon traps’. We identify analytical conditions leading to a successful transition and provide a numerical application for the EU economy

Believe me when I say green! Heterogeneous expectations and climate policy uncertainty

We develop a dynamic model where heterogeneous firms take investment decisions depending on their beliefs on future carbon prices. A policy-maker announces a forward-looking carbon price schedule but can decide to default on its plans if perceived transition risks are high. We show that weak policy commitment, especially when combined with ambitious mitigation announcements, can trap the economy into a vicious circle of credibility loss, carbon-intensive investments and increasing risk perceptions, ultimately leading to a failure of the transition. The presence of behavioural frictions and heterogeneity - both in capital investment choices and in the assessment of the policy-maker’s credibility - has strong non-linear effects on the transition dynamics and the emergence of ‘high-carbon traps’. We identify analytical conditions leading to a successful transition and provide a numerical application for the EU economy

Faraway, so Close: Coupled Climate and Economic Dynamics in an Agent-Based Integrated Assessment Model

In this work we develop an agent-based model that offers an alternative to standard, computable general equilibrium integrated assessment models (IAMs). The Dystopian Schumpeter meeting Keynes (DSK) model is composed of heterogeneous firms belonging to capital-good, consumption-good and energy sectors. Production and energy generation lead to greenhouse gas emissions, which affect temperature dynamics. Climate damages are modelled at the individual level as stochastic shocks hitting workers' labour productivity, energy efficiency, capital stock and inventories of firms. In that, aggregate damages emerge from the aggregation of losses suffered by heterogeneous, interacting and boundedly rational agents. The model is run focusing on a business-as-usual carbon-intensive scenario consistent with a Representative Concentration Pathway 8.5. We find that the DSK model is able to account for a wide ensemble of micro- and macro-empirical regularities concerning both economic and climate dynamics. Simulation experiments show a substantial lack of isomorphism between the effects of micro- and macro-level shocks, as it is typical in complex system models. In particular, different types of shocks have heterogeneous impact on output growth, unemployment rate, and the likelihood of economic crises, pointing to the importance of the different economic channel affected by the shock. Overall, we report much larger climate damages than those projected by standard IAMs under comparable scenarios, suggesting possible shifts in the growth dynamics, from a self-sustained pattern to stagnation and high volatility, and the need of urgent policy interventions

Complexity and the Economics of Climate Change: a Survey and a Look Forward

URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/cesdp2016.htmlDocuments de travail du Centre d'Economie de la Sorbonne 2016.58 - ISSN : 1955-611XWe provide a survey of the micro and macro economics of climate change from a complexity science perspective and we discuss the challenges ahead for this line of research. We identify four areas of the literature where complex system models have already produced valuable insights: (i) coalition formation and climate negotiations, (ii) macroeconomic impacts of climate-related events, (iii) energy markets and (iv) diffusion of climate-friendly technologies. On each of these issues, accounting for heterogeneity, interactions and disequilibrium dynamics provides a complementary and novel perspective to the one of standard equilibrium models. Furthermore, it highlights the potential economic benefits of mitigation and adaptation policies and the risk of under-estimating systemic climate change-related risks

Looking for Criminal Intents in JavaScript Obfuscated Code

The majority of websites incorporate JavaScript for client-side execution in a supposedly protected environment. Unfortunately, JavaScript has also proven to be a critical attack vector for both independent and state-sponsored groups of hackers. On the one hand, defenders need to analyze scripts to ensure that no threat is delivered and to respond to potential security incidents. On the other, attackers aim to obfuscate the source code in order to disorient the defenders or even to make code analysis practically impossible. Since code obfuscation may also be adopted by companies for legitimate intellectual-property protection, a dilemma remains on whether a script is harmless or malignant, if not criminal. To help analysts deal with such a dilemma, a methodology is proposed, called JACOB, which is based on five steps, namely: (1) source code parsing, (2) control flow graph recovery, (3) region identification, (4) code structuring, and (5) partial evaluation. These steps implement a sort of decompilation for control flow flattened code, which is progressively transformed into something that is close to the original JavaScript source, thereby making eventual code analysis possible. Most relevantly, JACOB has been successfully applied to uncover unwanted user tracking and fingerprinting in e-commerce websites operated by a well-known Chinese company

Complexity and the Economics of Climate Change: A Survey and a Look Forward

Climate change is one of the most daunting challenges human kind has ever faced. In the paper, we provide a survey of the micro and macro economics of climate change from a complexity science perspective and we discuss the challenges ahead for this line of research. We identify four areas of the literature where complex system models have already produced valuable insights: (i) coalition formation and climate negotiations, (ii) macroeconomic impacts of climate-related events, (iii) energy markets and (iv) diffusion of climatefriendly technologies. On each of these issues, accounting for heterogeneity, interactions and disequilibrium dynamics provides a complementary and novel perspective to the one of standard equilibrium models. Furthermore, it highlights the potential economic benefits of mitigation and adaptation policies and the risk of under-estimating systemic climate change-related risks

Green transitions and the prevention of environmental disasters : market based vs command-and-control policies

The paper compares the effects of market-based (M-B) and command-and-control (C&C) climate policies on the direction of technical change and the prevention of environmental disasters. Drawing on a model of endogenous growth and directed technical change, we show that M-B policies (carbon taxes and subsidies toward clean sectors) suffer from path dependence and exhibit bounded window of opportunities: delays in their implementation make them ineffective both in redirecting technical change, (i.e. triggering a transition toward clean energy) and in avoiding environmental catastrophes. On the contrary, we find that C&C interventions are favored by path dependence and guarantee policy effectiveness irrespectively of the timing of their introduction. As the hypothesis of path dependence in technological change has received vast empirical support and it is a key feature of many models of growth, we argue that C&C policies should be seen as a valuable and non-equivalent alternative to M-B interventions

Broadband and Tunable Light Harvesting in Nanorippled MoS2 Ultrathin Films

Nanofabrication of flat optic silica gratings conformally layered with two-dimensional (2D) MoS2 is demonstrated over large area (cm2), achieving a strong amplification of the photon absorption in the active 2D layer. The anisotropic subwavelength silica gratings induce a highly ordered periodic modulation of the MoS2 layer, promoting the excitation of Guided Mode Anomalies (GMA) at the interfaces of the 2D layer. We show the capability to achieve a broadband tuning of these lattice modes from the visible (VIS) to the near-infrared (NIR) by simply tailoring the illumination conditions and/or the period of the lattice. Remarkably, we demonstrate the possibility to strongly confine resonant and nonresonant light into the 2D MoS2 layers via GMA excitation, leading to a strong absorption enhancement as high as 240% relative to a flat continuous MoS2 film. Due to their broadband and tunable photon harvesting capabilities, these large area 2D MoS2 metastructures represent an ideal scalable platform for new generation devices in nanophotonics, photo- detection and -conversion, and quantum technologies