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on Computational Economics |
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Issue of 2017‒09‒24
twelve papers chosen by |
| By: | Davis, John B. (Department of Economics Marquette University) |
| Abstract: | This paper argues that agent-based modeling’s innovations in method developed in terms of simulation techniques also involve an innovation in economic methodology. It shows how Epstein’s generative science conception departs from conventional methodological reasoning, and employs what I term an open rather than closed approach to economic methodology associated with the roles that reflexivity, counterfactual reasoning, and abduction play in ABM. Central to this idea is that improvements in how we know something, a matter of method, determine whether we know something, a matter of methodology. The paper links this alternative view of economics and economic methodology to a social science model of economics and contrasts this with standard economics’ natural science model of economics. The paper discusses what this methodological understanding implies about the concept of emergence. |
| Keywords: | agent-based modeling, simulation, generative science, reflexivity, abduction, social science model of economics, emergence |
| JEL: | A12 B41 C63 |
| Date: | 2017–09 |
| URL: | http://d.repec.org/n?u=RePEc:mrq:wpaper:2017-03&r=cmp |
| By: | Baris Soybilgen (Istanbul Bilgi University) |
| Abstract: | We propose a factor augmented neural network model to obtain short-term predictions of U.S. business cycle regimes. First, dynamic factors are extracted from a large-scale data set consisting of 122 variables. Then, these dynamic factors are fed into neural network models for predicting recession and expansion periods. We show that the neural network model provides good in sample and out of sample fits compared to the popular Markov switching dynamic factor model. We also perform a pseudo real time out of sample forecasting exercise and show that neural network models produce accurate short-term predictions of U.S. business cycle phases. |
| Keywords: | Dynamic Factor Model; Neural Network; Recession |
| JEL: | E37 E31 |
| Date: | 2017–08 |
| URL: | http://d.repec.org/n?u=RePEc:bli:wpaper:1703&r=cmp |
| By: | Li Zheng (LAAS-ISI - Équipe Ingénierie Système et Intégration - LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse] - INP - Institut National Polytechnique [Toulouse] - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UPS - Université Paul Sabatier - Toulouse 3 - CNRS - Centre National de la Recherche Scientifique); Claude Baron (LAAS-ISI - Équipe Ingénierie Système et Intégration - LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse] - INP - Institut National Polytechnique [Toulouse] - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UPS - Université Paul Sabatier - Toulouse 3 - CNRS - Centre National de la Recherche Scientifique); Philippe Esteban (LAAS-ISI - Équipe Ingénierie Système et Intégration - LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse] - INP - Institut National Polytechnique [Toulouse] - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UPS - Université Paul Sabatier - Toulouse 3 - CNRS - Centre National de la Recherche Scientifique); Rui Xue (LAAS-ISI - Équipe Ingénierie Système et Intégration - LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse] - INP - Institut National Polytechnique [Toulouse] - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UPS - Université Paul Sabatier - Toulouse 3 - CNRS - Centre National de la Recherche Scientifique); Qiang Zhang (HFUT - Hefei University of Technology) |
| Abstract: | Performance measurement systems have gotten remarking development since the 1980s. It is also experiencing a step from classical PMSs to a broad diversification of PMSs. However, it seems that the practices in industries are not following the rapid academic rhythm. This paper presents a survey of performance measurement models and frameworks and analyses how these research results are implemented, or not, into software tools available on the market. It thus pointed out the gap between academic research results and supporting tools in the domain of the performance measurement management of engineering projects. |
| Keywords: | Performance Measurement,Project Evaluation,Indicators |
| Date: | 2016–06–28 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-01496409&r=cmp |
| By: | Jean-Bernard Chatelain (PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Panthéon-Sorbonne - ENS Paris - École normale supérieure - Paris - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics); Kirsten Ralf (Ecole Supérieure du Commerce Extérieur - ESCE - International business school) |
| Abstract: | This algorithm extends Ljungqvist and Sargent (2012) algorithm of Stackelberg dynamic game to the case of dynamic stochastic general equilibrium models including exogenous forcing variables. It is based on Anderson, Hansen, McGrattan, Sargent (1996) discounted augmented linear quadratic regulator. It adds an intermediate step in solving a Sylvester equation. Forward-looking variables are also optimally anchored on forcing variables. This simple algorithm calls for already programmed routines for Riccati, Sylvester and Inverse matrix in Matlab and Scilab. A Önal step using a change of basis vector computes a vector auto regressive representation including Ramsey optimal policy rule function of laggedobservable variables, when the exogenous forcing variables are not observable. |
| Keywords: | augmented linear quadratic regulator,Ramsey optimal policy, Stackelberg dynamic game, algorithm,forcing variables |
| Date: | 2017–09 |
| URL: | http://d.repec.org/n?u=RePEc:hal:psewpa:halshs-01588188&r=cmp |
| By: | Zura Kakushadze; Willie Yu |
| Abstract: | We give an explicit algorithm and source code for extracting equity risk factors from dead (a.k.a. "flatlined" or "hockey-stick") alphas and using them to improve performance characteristics of good (tradable) alphas. In a nutshell, we use dead alphas to extract directions in the space of stock returns along which there is no money to be made (and/or those bets are too volatile). In practice the number of dead alphas can be large compared with the number of underlying stocks and care is required in identifying the aforesaid directions. |
| Date: | 2017–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1709.06641&r=cmp |
| By: | Zachlod-Jelec, Magdalena (Ministry of Finance); Boratynski, Jakub (Ministry of Finance, University of Łódź) |
| Abstract: | In the paper we address the problem of parameters uncertainty of computable general equilibrium (CGE) simulation results concerning the economic effects of climate policy actions. Large scale CGE models utilize extensive, detailed databases on the structure of the economies (industry-specific technologies, international trade patterns etc.). At the same time, the behaviour of the economic system modelled in the CGE framework is largely driven by assumptions rooted in theory, with relatively little empirical content. It is therefore crucial to understand how assumptions affect outcomes of policy experiments. We employ a static global CGE model PLACE, representing 35 regions and 20 industries, with a focus on representing links between economic activities, energy use and CO2 emissions. Applying systematic sensitivity analysis based on Stroud's (1957) Gaussian quadratures approach we test how variation in elasticity parameters (values of which are subject to substantial uncertainty) affects economic assessment of emission reduction policies. Using as our workhorse simulation scenario the imposition of the European Commission's 40% greenhouse gas (GHG) emission reduction target (with respect to 1990) we find that the uncertainty of model simulation results driven by the uncertainty in assumed elasticities values is quite remarkable indicating that presenting only mean simulation results from CGE models is not sufficient. |
| Keywords: | commputable general equilibrium model; systematic sensitivity analysis; emissions reduction |
| JEL: | C68 D58 |
| Date: | 2016–08–31 |
| URL: | http://d.repec.org/n?u=RePEc:ris:mfplwp:0026&r=cmp |
| By: | Martina Sartori (Department of Economics, University Of Venice Cà Foscari and Bocconi University); Davide Geneletti (University of Trento, Department of Civil, Environmental and Mechanical Engineering); Stefano Schiavo (University of Trento, Department of Economics and Management and School of International Studies); Rocco Scolozzi (University of Trento, Department of Civil, Environmental and Mechanical Engineering) |
| Abstract: | This paper assesses the structural, joint implications of climate and land-use change on agriculture in the European Union, by means of a computable general equilibrium model of the world economy. The counterfactual simulations are conducted at the year 2050 under the second Shared Socioeconomic Pathway. We find that climate and land-use change are likely to affect agricultural systems very differently across Europe. Northern countries are expected to benefit from climate change impacts, whereas other areas in Europe will suffer negative consequences in terms of reduced agricultural output, real income and welfare. The most vulnerable region is not made of Mediterranean countries, but rather Central Europe. Our results suggest that climate and land-use changes may exacerbate existing disparities within the EU. Therefore, appropriate adaptation strategies and a more flexible land-use are required to limit these negative consequences and possibly exploit the beneficial effects of climate change in some countries. |
| Keywords: | Agricultural productivity, climate change, land-use change, general equilibrium analysis |
| JEL: | C68 Q11 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:ven:wpaper:2017:19&r=cmp |
| By: | Antoszewski, Michal (Ministry of Finance); Boratynski, Jakub (Ministry of Finance); Zachlod-Jelec, Magdalena (Ministry of Finance); Wojtowicz, Krzysztof (Ministry of Economy); Cygler, Maciej (National Centre for Emissions Management); Jeszke, Robert (National Centre for Emissions Management); Pyrka, Maciej (National Centre for Emissions Management); Sikora, Przemyslaw (National Centre for Emissions Management); Bohringer, Christoph (World Bank); Gaska, Jan (World Bank); Jorgenson, Erika (World Bank); Kasek, Leszek (World Bank); Kiuila, Olga (World Bank); Malarski, Ryszard (World Bank); Rabiega, Wojciech (World Bank) |
| Abstract: | PLACE is a static multi-region, multi-sector computable general equilibrium (CGE) model designed to assess the economic impact of energy and climate policies. Policies are typically analyzed using a comparative static approach, in which a situation with policy interference is compared to a situation without policy interference (often termed "baseline" or "business-as-usual"). Based on general equilibrium theory, PLACE incorporates micro-economic mechanisms within a comprehensive macro-economic framework, which distinguishes it from other large-scale economic models such as multivariate econometric models and input output analysis. The particular strengths of the CGE approach is the scope for quantifying distributional impacts of policies and the ability to reflect complex sectoral adjustments. This document constitutes technical documentation of the PLACE model and aims to present the underlying algebra and data sources that were used at different stages during the model's development. |
| Keywords: | computable general equilibrium model; emissions; GTAP; baseline scenario |
| JEL: | C68 D58 |
| Date: | 2015–12–11 |
| URL: | http://d.repec.org/n?u=RePEc:ris:mfplwp:0024&r=cmp |
| By: | Jean-Philippe Bouchaud; Stanislao Gualdi; Marco Tarzia; Francesco Zamponi |
| Abstract: | Which level of inflation should Central Banks be targeting? We investigate this issue in the context of a simplified Agent Based Model of the economy. Depending on the value of the parameters that describe the micro-behaviour of agents (in particular inflation anticipations), we find a surprisingly rich variety of behaviour at the macro-level. Without any monetary policy, our ABM economy can be in a high inflation/high output state, or in a low inflation/low output state. Hyper-inflation, stagflation, deflation and business cycles are also possible. We then introduce a Central Bank with a Taylor-rule-based inflation target, and study the resulting aggregate variables. Our main result is that too low inflation targets are in general detrimental to a CB-controlled economy. One symptom is a persistent under-realisation of inflation, perhaps similar to the current macroeconomic situation. This predicament is alleviated by higher inflation targets that are found to improve both unemployment and negative interest rate episodes, up to the point where erosion of savings becomes unacceptable. Our results are contrasted with the predictions of the standard DSGE model. |
| Date: | 2017–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1709.05117&r=cmp |
| By: | Luciano Pietronero; Matthieu Cristelli; Andrea Gabrielli; Dario Mazzilli; Emanuele Pugliese; Andrea Tacchella; Andrea Zaccaria |
| Abstract: | This note is a contribution to the debate about the optimal algorithm for Economic Complexity that recently appeared on ArXiv [1, 2] . The authors of [2] eventually agree that the ECI+ algorithm [1] consists just in a renaming of the Fitness algorithm we introduced in 2012, as we explicitly showed in [3]. However, they omit any comment on the fact that their extensive numerical tests claimed to demonstrate that the same algorithm works well if they name it ECI+, but not if its name is Fitness. They should realize that this eliminates any credibility to their numerical methods and therefore also to their new analysis, in which they consider many algorithms [2]. Since by their own admission the best algorithm is the Fitness one, their new claim became that the search for the best algorithm is pointless and all algorithms are alike. This is exactly the opposite of what they claimed a few days ago and it does not deserve much comments. After these clarifications we also present a constructive analysis of the status of Economic Complexity, its algorithms, its successes and its perspectives. For us the discussion closes here, we will not reply to further comments. |
| Date: | 2017–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1709.05272&r=cmp |
| By: | Thorir Bjarnason (School of Science and Engineering, Reykjavik University, Iceland); Einar Jón Erlingsson (School of Science and Engineering, Reykjavik University, Iceland); Bulent Ozel (LEE and Department of Economics, Universitat Jaume I, Castellón, Spain); Hlynur Stefánsson (School of Science and Engineering, Reykjavik University, Iceland); Jón Thor Sturluson (School of Science and Engineering, Reykjavik University, Iceland); Marco Raberto (DIME-University of Genoa, Italy) |
| Abstract: | Mortgage instruments differ in many respects. Their microeconomic effects might be easily calculated but their effects on a macroeconomic level are not always easily understood. Agent-based models can be used to study the macroeconomic effects that emerge from the microeconomic behavior of multiple interacting agents. Using a macroeconomic model of a credit network economy we have found that inflation-indexed mortgages can mislead households’ expectations of risk, encouraging them to buy more housing due to their low initial amortizations which, in turn, stimulates housing prices. The results further hint that in long-run inflation-indexed mortgages create relatively more uneven housing wealth distribution in between households. We also find that the effectiveness of standard monetary policy tools is diminished when inflation-indexed mortgages are used. Banks partake in the interest rate risk with fixed rate mortgages but bear little or no risk with adjustable rate or inflation-indexed mortgages. We have seen in this study that mortgage types, macroprudential tools and other policy tools can be experimented on, give insights into the interplay between agents and insight into the effects that certain policy settings may have on a macroeconomic level. |
| Keywords: | Credit cycles, mortgage, housing market, agent-based model, inflation-indexation |
| JEL: | C63 E25 G21 R31 R38 |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:jau:wpaper:2017/10&r=cmp |
| By: | Charles Sims (Howard H. Baker Jr. Center for Public Policy and Department of Economics, University of Tennessee); Betsy Heines (Mathematics Department, University of Tennessee); Suzanne Lenhart (Mathematics Department, University of Tennessee) |
| Abstract: | The number of large-scale, high-severity forest fires occurring in the United States is increasing, as is the cost to suppress these fires. One of the key challenges in studying the costs and benefits of forest are prevention management is the incorporation of risk and uncertainty surrounding management decisions. We use a technique developed by William Reed to incorporate the stochasticity of the time of a forest fire into our optimal control problem. Using this optimal control problem we explore the potential trade-offs between prevention management spending and suppression spending, along with the overall economic viability of prevention management spending. Our goal is to determine the optimal fire prevention management spending rate and the optimal re suppression spending which maximizes the expected value of a forest. We develop a parameter set re ecting the 2011 Las Conchas Fire in New Mexico and numerically solve our optimal control problem. Furthermore, we adapt this problem to simulate a sequence of fires and corresponding controls. We perform a simulation study to determine how, on average, prevention management spending a ects the value of a forest given an unknown number of fires over a fixed management horizon. Overall, our results support the conclusion that the prevention management e orts offset rising suppression costs and increase the value of a forest overall. |
| Keywords: | forest fire; optimal control; stochasticity |
| JEL: | Q2 C6 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:ten:wpaper:2017-05&r=cmp |