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Complex systems' approach and methodologies emphasize interactions, diversity and dynamics. Complex systems perspectives also enable public policies to be considered comprehensively and simulated in all their multiplicity of sectors and scales, of cause and effect. This paper attempts to summarize the content of the book of the project "Modeling Complex Systems for Public Policies". In doing so, it presents the main concepts and methodologies and it associates the characteristics of social, economic, urban and environmental issues of policy with complex systems approaches. The paper makes a brief list of the existing literature in Brazil related to the applications of complex systems and discusses the applications in education, transport, and the legislative process. The paper concludes that public policies may benefit methodologically if studied within this approach, mainly because of the observed heterogeneity of their agents; the connectedness of agents and policies; and the non-linear fashion of interactions among policies. Further, the formal modeling framework, the adequacy of its data treatment and the communication facilitated by modeling together may help the emergence of more sensible, insightful, and full-scope policy-making.

Behavioural economics highlights the role of social preferences in economic decisions. Further, populations are heterogeneous; suggesting that group composition may impact the ability to sustain voluntary public goods contributions. This parallels research in public economics where fractionalization negatively impacts provision. We conduct agent-based simulations of contributions in a public goods game, varying group composition and the weight individuals place on their beliefs versus their underlying social preference type. We then examine the effect of each of these factors on contributions. We find fractionalization in social preference types negatively impacts provision, even controlling for the share of types in a group.

Motivated by the changing nature of the natural gas industry in the European Union driven by the liberalization process, we focus on pricing of gas swing options. These options are embedded in typical gas sales agreements in the form of offtake flexibility concerning volume and time. The gas swing option is actually a set of several American puts on a spread between prices of two or more energy commodities. This fact together with the fact that the energy markets are fundamentally different from traditional financial security markets is important for our choice of valuation technique. Due to the specific features of the energy markets, the existing analytic approximations for spread option pricing are hardly applicable to our framework. That is why we employ Monte Carlo methods to model the spot price dynamics of the underlying commodities. The price of an arbitrarily chosen gas swing option is then computed in accordance with the concept of risk-neutral expectations. Finally, our result is compared with the real payoff from the option realized at time of the option execution and the maximum ex-post payoff the buyer could generate in case he knew the future, discounting to the original time of the option pricing.

This paper examines the structure and direction of developing Asia's trade over the past two decades. The impacts on developing Asia of the economic slowdown in 2009–2010 in high-income countries of the Organization for Economic Cooperation and Development (OECD), which includes the European Union (EU), Japan, and United States (US) are projected through a computable general equilibrium model (CGE) of world trade and production. In addition, the impacts of fiscal stimulus and the rise of protectionist sentiments within developing Asia are examined. The expansion of intraregional trade in Asia reflects the role of the People's Republic of China (PRC) as an assembly point and its reliance on demand from outside the region, the EU and the US in particular. The trade channel is crucial in transmitting economic distress from the OECD countries to developing Asia. The projection shows that developing Asia will continue to suffer from demand decline in OECD countries, with the PRC and India being the most impacted. Though Southeast Asia faces reduced exports to the OECD countries, its exports are reduced significantly to other Asian exporters, demonstrating the indirect trade linkages that now exist in the global economy. Fiscal stimulus from the largest economies (including PRC, EU, Japan, and US) could help boost trade and gross domestic product growth in developing Asia but it is not projected to offset entirely the negative impact from the global economic downturn. Protectionism has a negative impact on the countries and regions that take that course. Southeast Asia would be the most impacted by protectionism. If Southeast Asian countries were to raise their applied tariffs to the maximum most-favored nation bound rates under the World Trade Organization, the impact would be negative on real gross domestic product. Heavy manufactures followed by light manufactures, electronics, and textiles are most impacted.

This article belongs to the Special Issue On-Surface Synthesis of Low-Dimensional Organic Nanostructures. ; Chiral graphene nanoribbons are extremely interesting structures due to their narrow band gaps and potential development of spin-polarized edge states. Here, we study their band structure on low work function silver surfaces. The use of a curved Ag single crystal provides, within the same sample, regions of disparate step structure and step density. Whereas the former leads to distinct azimuthal growth orientations of the graphene nanoribbons atop, the latter modulates the substrate's work function and thereby the interface energy level alignment. In turn, we disclose the associated charge transfer from the substrate to the ribbon and assess its effect on the nanoribbon's properties and the edge state magnetization. ; We acknowledge financial support from MCIN/AEI/10.13039/501100011033 (grant nos. PID2019-107338RB-C62, PID2019-107338RB-C63, PID2019-107338RB-C66, and PCI2019-111933-2 and MAT-2017-88374-P), the European Union's Horizon 2020 research and innovation program (FET Open project SPRING, grant no. 863098), the Xunta de Galicia (Centro Singular de Investigación de Galicia, 2019–2022, grant no. ED431G2019/03), the European Regional Development Fund, the Basque Government (Grant IT-1255-19), Gobierno Vasco-UPV/EHU (Project No. IT1246-19) and the Dpto. Educación Gobierno Vasco (Grant No. PIBA-2020-1-0014). ; Peer reviewed

1 archivo PDF (16 páginas). efrsfriiiuno ; El diseño de zonas electorales es un problema difícil de resolver que ha sido estudiado tanto por su complejidad computacional como por los riesgos asociados a su manipulación, que puede incidir de forma directa en el triunfo de un partido político, y tener consecuencias graves como la marginación de diferentes sectores sociales. Para promover procesos democráticos se han establecido diferentes criterios que deben satisfacerse como son el equilibrio poblacional, la conexidad y la compacidad geométrica. En este artículo se propone un algoritmo, basado en técnicas heurísticas, capaz de generar zonas electorales que cumplen con estos criterios. Esta propuesta fue aplicada en el Estado de México, y los resultados obtenidos muestran que el algoritmo favorece la creación de zonas de alta calidad. ABSTRACT: Redistricting is a complex problem in which democracy of the electoral processes is promoted by some constraints such as population balance, contiguity and compactness. In this paper we solve the problem by means of a novel hybrid algorithm based in two heuristics techniques. This algorithm was applied in a real example in the Estado de Mexico. The results show that the new algorithm favors the creation of high quality districts. Clasificación JEL (JEL Classification): C15, C44, C63. PALABRAS CLAVE (Keywords): Regionalización, Redistritación Electoral, Representación Ciudadana, Geografía Electoral, Elecciones, Gerrymandering, Multiple Criteria Districting Problems y Simulated Annealing.

This article contributes to the field of evolutionary macroeconomics by highlighting the dynamic interlinkages between micro-meso-macro with a Veblenian meso foundation in an agent-based macroeconomic model. Consumption is dependent on endogenously changing social class and signaling, such as bandwagon, Veblen and snob effects. In particular, we test the macroeconomic effects of this meso foundation in a generic agent-based model of a closed artificial economy. The model is stock-flow consistent and builds upon local decision heuristics of heterogeneous agents characterized by bounded rationality and satisficing behavior. These agents include a multitude of households (workers and capitalists), firms, banks as well as a capital goods firm, a government and a central bank. Simulation experiments indicate coevolutionary dynamics between signaling-by-consuming and firm specialization that eventually effect employment and consumer prices, as well as other macroeconomic aggregates.

This paper describes a structural dynamic microsimulation model of the household that has been developed to explore behavioural responses to pensions policy counterfactuals in Ireland. The model is based upon the life-cycle theory of behaviour, which assumes that individuals make their decisions to maximise expected lifetime utility, subject to expectations that are consistent with the prevailing decision making environment. The model is calibrated to match Irish survey data.

We obtain a recursive formulation for a general class of contracting problems involving incentive constraints. These constraints make the corresponding maximization sup problems non-recursive. Our approach consists of studying a recursive Lagrangian. Under standard general conditions, there is a recursive saddle-point (infsup) functional equation (analogous to a Bellman equation) that characterizes the recursive solution to the planner's problem and forward-looking constraints. Our approach has been applied to a large class of dynamic contractual problems, such as contracts with limited enforcement, optimal policy design with implementability constraints, and dynamic political economy models.

The paper describes a spatial economic agent-based model (ABM), consistent with the principles of new economic geography (NEG), which allows the discrete-time evolutionary simulation of complex interactions of household and firm location choices. In contrast with the current ABM approaches, it considers a multi-regional (multi-urban) setting to enable a more realistic representation of decisions related to commuting, migration and household and employment location. The model allows simulating spatially differentiated, multi-commodity markets for land and labor in a system of cities and the behavior of profit-maximizing firms with multi-regional asset investment decisions, incorporating endogenous intra- and inter-urban transport costs with congestion effects. It also accounts for the impact of industrial and urban agglomeration forces on location choices and the formation of urban development patterns. Other features include the representation of the actions of central and local government agents to address issues of territorial development, efficiency and equity. The simulation set-up and evolutionary analysis of the spatial ABM are presented and several implications are discussed with regard to the possible outcomes of a set of policy interventions.

Existence of outliers and structural breaks having mutually unknown nature, in time series data, offer challenges to data analysts in model identification, estimation and validation. Detection of these outliers has been an important area of research in time series since long. To analyze the impact of these structural breaks and outliers on model identification, estimation and their inferential analysis, we use two data generating processes: MA(1) and ARMA(1,1). The performance of the test statistics for detecting additive outlier(AO), innovative outlier(IO), level shift(LS) and transient change(TC) is investigated using simulation strategy through power of a test, empirical level of significance, empirical critical values, misspecification frequencies and sampling distribution of estimators for the two models. The empirical critical values are found higher than the theoretical cut-off points, empirical power of the test statistics is not satisfactory for small sample size, large cut-off points and large model coefficient. We have explored confusion between LS, AO, TC and IO at different critical values(c) by varying sample size. We have also collected empirical evidence from time series data for Pakistan using 3-stage iterative procedure to detect multiple outliers and structural breaks. We find that neglecting shocks lead to wrong identification, biased estimation and excess kurtosis.
JEL Classification Codes: C15, C18, C63, C32, C87, C51, C52, C82
AMS Classification Codes: 62, 65, 91, DI, 62-08, 62J20, 00A72, 91-08, 91-10, 91-11 62P20, 91B82, 91B84, 62M07, 62M09, 62M10, 62M15, 62M20

Much research has been devoted to examination of the financial easing policy of the European Central Bank (ECB). However, this study is one of the first to use a dynamic micro-founded model to investigate empirically the impact of the ECB's Quantitative Easing (QE) policy on consumption and investment by economic agents in Italy (households, government, firms, and the rest of the world). For this purpose, we constructed a Financial Social Accounting Matrix (FSAM) for the Italian economy for the year 2009 to calibrate a dynamic computable general equilibrium model (DCGE). This model allowed us to evaluate the direct and indirect impact of money flow on the behavior of consumption and investment. The findings of the study confirmed the positive impact of the ECB's monetary policy on the level of investment and consumption.

Climate policy has been mainly studied with economic models that assume representative, rational agents. However, it aims at changing behavior associated with carbon-intensive goods that are often subject to bounded rationality and social preferences, such as status and imitation. Here we use a macroeconomic multi-agent model with such features to test the effect of various policies on both environmental and economic performance. The model is particularly suitable to address distributional impacts of climate policies, not only because populations of many agents are included, but also as these are composed of different classes of households driven by specific motivations. We simulate various policy scenarios, combining in different ways a carbon tax, a reduction of labor taxes, subsidies for green innovation, a price subsidy to consumers for less carbon-intensive products, and green government procurement. The results show pronounced differences with those obtained by rational-agent model studies. It turns out that demand-oriented subsidies lead to lower unemployment and higher output, but perform less well in terms of carbon emissions. The supply-oriented subsidy for green innovation results in a significant reduction of carbon emissions with a slight reduction of unemployment. ; Series: WWWforEurope

This paper is concerned with the apparent change in the U.S. oil price-macroeconomy relationship. It is investigated to what extent this change can be accounted for by the large oil price surges witnessed in the 1970s. The innovative approach of rolling impulse responses is applied and both the aggregate and the industry-level is considered. It is found that the first oil crisis has an persistent" effect in the sense that this incident still dominates long-run results and superimposes both subsample and industry-specifics. The results, furthermore, suggest that the Great Moderation can essentially be explained by the non-occurrence of large oil shocks after the mid 1980s and that oil is less important for the economy than many researchers still believe.