nep-cmp New Economics Papers
on Computational Economics
Issue of 2017‒01‒08
ten papers chosen by
Stan Miles
Thompson Rivers University

  1. Predicting Economic Recessions Using Machine Learning Algorithms By Rickard Nyman; Paul Ormerod
  2. In-depth analysis of tax reforms using the EUROMOD microsimulation model By Fidel Picos; Marie-Luise Schmitz
  3. Where in cities do "rich" and "poor" people live? The urban economics model revisited By Rémi Lemoy; Charles Raux; Pablo Jensen
  4. The Cost of Climate Stabilization in Southeast Asia, a Joint Assessment with Dynamic Optimization and CGE Models By Bosello, Francesco; Marangoni, Giacomo; Orecchia, Carlo; Raitzer, David A.; Tavoni, Massimo
  5. Decarbonization Pathways in Southeast Asia: New Results for Indonesia, Malaysia, Philippines, Thailand and Viet Nam By Bosello, Francesco; Orecchia, Carlo; Raitzer, David A.
  6. Modification of the GE-IO model of the Russian economy with dynamic optimization of macroeconomic policy By Gilmundinov, Vadim; Bozo, Natalia; Melnikov, Vladimir; Petrov, Sergei
  7. Monte-Carlo Simulation and Stochastic Programming in Real Options Valuation: the Case of Perennial Energy Crop Cultivation By Kostrova, Alisa; Britz, Wolfgang; Djanibekov, Utkur; Finger, Robert
  8. Dynamic scoring of tax reforms in the European Union By Salvador Barrios; Mathias Dolls; Anamaria Maftei; Andreas Peichl; Sara Riscado; Janos Varga; Christian Wittneben
  9. RHOMOLO-v2 Model Description: A spatial computable general equilibrium model for EU regions and sectors By Jean Mercenier; María Teresa à lvarez-Martínez; Andries Brandsma; Francesco Di Comite; Olga Diukanova; d’Artis Kancs; Patrizio Lecca; Montserrat López-Cobo; Philippe Monfort; Damiaan Persyn; Alexandra Rillaers; Mark Thissen; Wouter Torfs
  10. Integer programming methods for special college admissions problems By Kolos Csaba Agoston; Peter Biro; Iain McBride

  1. By: Rickard Nyman; Paul Ormerod
    Abstract: Even at the beginning of 2008, the economic recession of 2008/09 was not being predicted. The failure to predict recessions is a persistent theme in economic forecasting. The Survey of Professional Forecasters (SPF) provides data on predictions made for the growth of total output, GDP, in the United States for one, two, three and four quarters ahead since the end of the 1960s. Over a three quarters ahead horizon, the mean prediction made for GDP growth has never been negative over this period. The correlation between the mean SPF three quarters ahead forecast and the data is very low, and over the most recent 25 years is not significantly different from zero. Here, we show that the machine learning technique of random forests has the potential to give early warning of recessions. We use a small set of explanatory variables from financial markets which would have been available to a forecaster at the time of making the forecast. We train the algorithm over the 1970Q2-1990Q1 period, and make predictions one, three and six quarters ahead. We then re-train over 1970Q2-1990Q2 and make a further set of predictions, and so on. We did not attempt any optimisation of predictions, using only the default input parameters to the algorithm we downloaded in the package R. We compare the predictions made from 1990 to the present with the actual data. One quarter ahead, the algorithm is not able to improve on the SPF predictions. Three and six quarters ahead, the correlations between actual and predicted are low, but they are very significantly different from zero. Although the timing is slightly wrong, a serious downturn in the first half of 2009 could have been predicted six quarters ahead in late 2007. The algorithm never predicts a recession when one did not occur. We obtain even stronger results with random forest machine learning techniques in the case of the United Kingdom.
    Date: 2017–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1701.01428&r=cmp
  2. By: Fidel Picos (European Commission - JRC); Marie-Luise Schmitz (European Commission - JRC)
    Abstract: In the aftermath of the financial and sovereign debt crisis, the need for a better understanding of the fiscal and equity implications of national tax policy reforms is greater than ever. National fiscal policies have a significant share in paving the way for economic recovery, fiscal consolidation and reducing looming inequality problems. The present work sets out a consistent framework for the in-depth country analyses of tax reforms using EUROMOD performed by the European Commission services in the context of the European Semester. Three examples of policy analysis are presented with the focus being on the provision of correct inferences alongside the typically analysed estimates and indicators.
    Keywords: Fiscal policy analysis, European Semester, survey data, microsimulation, variance estimation
    JEL: H23 H24 H53 C83
    Date: 2016–12
    URL: http://d.repec.org/n?u=RePEc:ipt:taxref:201606&r=cmp
  3. By: Rémi Lemoy; Charles Raux; Pablo Jensen
    Abstract: Reproducing the socio-spatial structure of cities is one of the challenges facing the standard urban economics model of Alonso, Muth, Mills (AMM model). In a widely cited paper, Jan K. Brueckner, Jacques-Fran çois Thisse and Yves Zenou (1999) asked "Why is central Paris rich and downtown Detroit poor?" and proposed a model with a positive central amenity to account for the structure of European cities, where the city center is usually rich, like in Paris. In this work, we exploit the power of the AMM model and show that various utility functions and plausible conditions offer alternative explanations of households' location by income within a city. We first propose to take into account the empirical fact that the share of income spent for housing decreases when income increases. With a Cobb-Douglas utility function and two income groups, this ingredient yields different social structures than the standard one with low income households in the center and rich ones in the periphery. Depending on the relative values of the city radius and a critical radius related to model parameters, different urban forms appear indeed. These include the existence of a "rich" center and more complex socio-spatial urban forms, for instance alternating a rich center, poor suburbs and a rich outer ring, which have not yet been derived from the AMM model to our knowledge. In this work, we combine analytical ideas and illustrations by the means of an agent-based model. Indeed, starting from a random configuration of the city, a system of agents given relevant behaviour rules can find the equilibrium configuration of the AMM model. This modelling approach is inspired from the Monte Carlo method, and from local search optimization algorithms in computer science. Following Brueckner, Thisse and Zenou (1999), we also study the hypothesis of a central amenity. We show that under certain conditions, a central amenity can also yield a rich city center, and even a U-shaped curve of the income as a function of the distance to the city center. This result can be related in particular to empirical findings in some older North American cities, like New York, Chicago or Philadelphia as well as European cities like Paris. We find with agent-based simulations that these outcomes depend strongly on the respective locations of the employment and the amenity centers. Indeed, considering that the CBD and the amenity do not coincide has an important influence on the socio-spatial structure of the city.
    Keywords: urban economics; location; income; amenity; agent-based model
    JEL: D11 R14 C63
    Date: 2016–12
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p524&r=cmp
  4. By: Bosello, Francesco; Marangoni, Giacomo; Orecchia, Carlo; Raitzer, David A.; Tavoni, Massimo
    Abstract: Southeast Asia is at a time one of the most vulnerable region to the impacts of a changing climate, with millions of its inhabitants still trapped in extreme poverty without access to energy and employed in climate-sensitive sectors, and, potentially, one of the world’s biggest contributors to global warming in the future. Fortunately, major Southeast Asian countries are also implementing policies to improve their energy and carbon efficiency and are discussing if and how to extend these further. The present study aims to assess the implications for energy consumption, energy intensity and carbon intensity in the Southeast Asia region of a set of short-term and long-term de-carbonization policies characterized by different degrees of ambition and international cooperation. The analysis applies two energy-climate-economic models. The first, the fully dynamic Integrated Assessment model WITCH, is more aggregated in the sectoral and country representation, but provides a detailed technological description of the energy sector. The second, the ICES Computable General Equilibrium model, offers a richer sectoral breakdown of the economy and of international trade patterns, but is less refined in the representation of technology. The joint application of these two complementary models allows the capture of distinct and key aspects of low- carbon development paths in Southeast Asia.
    Keywords: Climate Change Mitigation, Asian Economies, Computable General Equilibrium Models, Environmental Economics and Policy, Q54, Q58, C68,
    Date: 2016–12–23
    URL: http://d.repec.org/n?u=RePEc:ags:feemmi:251810&r=cmp
  5. By: Bosello, Francesco; Orecchia, Carlo; Raitzer, David A.
    Abstract: Southeast Asia is one of the most vulnerable regions of the world to the impacts of climate change. At the same time, the region is also following a trajectory that could make it a major contributor to greenhouse gas emissions in the future. Understanding the economic implications of policy options for low carbon growth is essential to formulate instruments that achieve the greatest emissions reductions at lowest cost. This study focuses on five developing countries of Southeast Asia that collectively account for 90% of regional emissions in recent years—Indonesia, Malaysia, the Philippines, Thailand, and Viet Nam. The analyses are based on the CGE economy-energy-environment model ICES under an array of scenarios reflecting business as usual, fragmented climate policies, an approximately 2.4°C post 2020 global climate stabilization target, termed 650 parts per million (ppm) carbon dioxide (CO2) equivalent (eq), and an approximately 2°C global target (termed 500 ppm CO2 eq). Averted deforestation through reducing emissions from forest degradation and deforestation (REDD) is included in some scenarios. The study shows that global and coordinated action is found to be critical to the cost effectiveness of emissions stabilization policies. A 650ppm stabilization scenario (below 3°C in 2100) has a similar cost to the region to current fragmented targets, but achieves much higher levels of emissions reductions. However, only some of the countries have short-term emissions targets that are consistent with a stabilization scenario at 650ppm: these are Indonesia, Philippines and Viet Nam. None of the countries’ mid-term targets are coherent with more ambitious stabilization scenario at 500ppm.
    Keywords: Climate Change Mitigation, Asian Economies, Computable General Equilibrium Models, Environmental Economics and Policy, Q54, Q58, C68,
    Date: 2016–12–15
    URL: http://d.repec.org/n?u=RePEc:ags:feemmi:250260&r=cmp
  6. By: Gilmundinov, Vadim; Bozo, Natalia; Melnikov, Vladimir; Petrov, Sergei
    Abstract: The paper describes recent results connected with extension of the general equilibrium input-output model of Russia with aggregated markets (Gilmundinov et al, 2015). Consideration of economic policy’s influence on a variety of macroeconomic and structural policy goals is an aim of this extension. For this purpose we add into GE-IO model sectoral fixed capital investment’s sub-models and sub-model of dynamic optimization of economic policy. Sectoral sub-models of fixed capital investments are based on the assessments of sectoral production functions with variable degree of capacity use. Sub-model of dynamic optimization of economic policy is based on extension of basic approaches suggested by H. Theil (1954, 1964), J. Tinbergen (1952) and R. Mundell (1962) with dynamic social losses function and accounting of influence of economic policy on sectoral structure of national economy. The suggested modification allows to simulate impact of different variants of economic policy on national economy, aggregated markets and main sectors. That is very helpful for estimation of consequences of various internal and external shocks and development of optimal economic policy and gives more advantages in comparison with standard DSGE or CGE models. The preliminary results of simulations based on suggested model for the Russian economy show considerable dependence of the Russian economy dynamic and structure on economic policy. Optimal economic policy should be hybrid with combining structural policy with sectoral credit policy of Central Bank. According to the basic scenario of simulation with neutral economic policy the Russian GDP in constant prices will decline at 1.8% in 2016 in comparison to 2015 and almost have no changes in 2017 in comparison to 2016. Stimulating economic policy allows to raise growth rates of the Russian economy at 2-3%.
    Keywords: Economic Policy, Optimization, Input-Output, Economy of Russia, Forecasting, General Equilibrium
    JEL: C61 C63 C67 E52
    Date: 2016–05–15
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:75597&r=cmp
  7. By: Kostrova, Alisa; Britz, Wolfgang; Djanibekov, Utkur; Finger, Robert
    Keywords: Scenario Tree Reduction, Compound Option, American Option, Farming Investment Decision, Bioenergy, Agribusiness, Agricultural Finance, Crop Production/Industries, Farm Management, Financial Economics, Land Economics/Use, Production Economics, Resource /Energy Economics and Policy, Risk and Uncertainty, C61, C63, G32, Q12, Q42,
    Date: 2016–12–15
    URL: http://d.repec.org/n?u=RePEc:ags:ubfred:250253&r=cmp
  8. By: Salvador Barrios (European Commission - JRC); Mathias Dolls (ZEW); Anamaria Maftei (European Commission - JRC); Andreas Peichl (ZEW); Sara Riscado (European Commission - JRC); Janos Varga (European Commission – DG ECFIN); Christian Wittneben (ZEW)
    Abstract: In this paper, we present a dynamic scoring analysis of tax reforms for European countries. In this analysis we account for the feedback effects resulting from the adjustment in the labour market and for the economy-wide reaction to tax policy changes. We combine the microsimulation model EUROMOD, extended to incorporate an estimated labour supply model, with the new Keynesian DSGE model QUEST, used by the European Commission for analysing fiscal and structural reform in EU member states. These two models are connected in two ways: by introducing tax policy shocks in QUEST, derived from computing changes in implicit tax rates using EUROMOD; and by calibrating the elasticity of labour supply and the non-participation rates, by skill categories, in QUEST from values calculated using EUROMOD and the estimated labour supply function. Moreover, we discuss aggregation issues and the consistency between the micro and macro modelling of labour supply and interpret the model interaction in terms of tax incidence analysis. We illustrate the methodological approach with the results obtained when scoring specific reforms in three EU Member States, namely, Italy, Belgium and Poland. We compare two different scenarios – one in which the behavioural response to tax changes over the medium term is ignored and another scenario where this behavioural/micro-dimension is embedded into the microsimulation model. In this particular set-up, we do not find evidence of strong second-round effects, and the fiscal and distributional effects of the reforms tend to overlap in both scenarios. We attribute these results to existing rigidities in labour and product markets, which have shrunk further the small tax policy shocks introduced into the macroeconomic model.
    Keywords: Dynamic scoring, tax reforms, first and second round effects, labour market behaviour
    Date: 2016–12
    URL: http://d.repec.org/n?u=RePEc:ipt:taxref:201603&r=cmp
  9. By: Jean Mercenier (European Commission – JRC); María Teresa à lvarez-Martínez (European Commission – JRC); Andries Brandsma (European Commission – JRC); Francesco Di Comite (European Commission – JRC); Olga Diukanova (European Commission – JRC); d’Artis Kancs (European Commission – JRC); Patrizio Lecca (European Commission – JRC); Montserrat López-Cobo (European Commission – JRC); Philippe Monfort (European Commission – DG REGIO); Damiaan Persyn (European Commission – JRC); Alexandra Rillaers (European Commission – DG REGIO); Mark Thissen; Wouter Torfs
    Abstract: This report presents the current version of the European Commission's spatial computable general equilibrium model RHOMOLO, developed by the Directorate-General Joint Research Centre (DG JRC) in collaboration with the Directorate-General for Regional and Urban Policy (DG REGIO) to undertake the ex-ante impact assessment of EU policies and structural reforms. The RHOMOLO model has been used with DG REGIO for the impact assessment of Cohesion Policy, and with the European Investment Bank for impact assessment of EU investment support policies. The structure of the model departs from standard computable general equilibrium models in several dimensions. First, it generalises the modelling of market interactions by introducing imperfect competition in products and labour markets. Second, it exploits the advantages of a full asymmetric bilateral trade cost matrix for all EU regions to capture a rich set of spatial market interactions and regional features. Third, it acknowledges the importance of space also for non-market interactions through an inter-regional knowledge spill-over mechanism originating from research and development activities within a country. This report describes the theoretical foundation of RHOMOLO-v2 (v2 = version 2), its mathematical structure, dynamics, data sources and calibration to allow the reader to approach the model and its outputs with a higher degree of awareness of its strength and limitations. Indeed, as for any general equilibrium model with a reasonable level of complexity, in RHOMOLO it is often challenging to track the mechanisms at work after a policy shock and clearly disentangle causes and effects because of the high number of channels of adjustment and the presence of many feedback effects. The purpose of this documentation is thus to provide a compass to the reader to sail safely through its many equations, assumptions and connections.
    Keywords: Spatial computable general equilibrium, economic modelling, spatial anamysis, policy impact assessment, economic geography, regional economics.
    JEL: C68 D58 F12 R13 R30
    Date: 2016–12
    URL: http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc100011&r=cmp
  10. By: Kolos Csaba Agoston (Department of Operations Research and Actuarial Sciences, Corvinus University of Budapest); Peter Biro (Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences and Department of Operations Research and Actuarial Sciences, Corvinus University of Budapest); Iain McBride (School of Computing Science, University of Glasgow)
    Abstract: We develop Integer Programming (IP) solutions for some special college admission problems arising from the Hungarian higher education admission scheme. We focus on four special features, namely the solution concept of stable score-limits, the presence of lower and common quotas, and paired applications. We note that each of the latter three special feature makes the college admissions problem NP-hard to solve. Currently, a heuristic based on the Gale-Shapley algorithm is being used in the Hungarian application. The IP methods that we propose are not only interesting theoretically, but may also serve as an alternative solution concept for this practical application, and other similar applications. We finish the paper by presenting a simulation using the 2008 data of the Hungarian higher education admission scheme.
    Keywords: College admissions problem, integer programming, stable score-limits, lower quotas, common quotas, paired applications, simulations
    JEL: C61 C63 C78
    Date: 2016–10
    URL: http://d.repec.org/n?u=RePEc:has:discpr:1632&r=cmp

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