nep-cmp New Economics Papers
on Computational Economics
Issue of 2014‒09‒29
twelve papers chosen by
Stan Miles
Thompson Rivers University

  1. Integrated Modeling Frameworks By Randall W. Jackson
  2. A derivative-free approach for a simulation-based optimization problem in healthcare By Stefano Lucidi; Massimo Maurici; Luca Paulon; Francesco Rinaldi; Massimo Roma
  4. Re-weighting EUROMOD for demographic change: an application on Slovenian and Lithuanian data By Kump, Nataša; Navicke, Jekaterina
  5. An iterated local search algorithm for water distribution network design optimisation By DE CORTE, Annelies; SÖRENSEN, Kenneth
  6. Quantifying "Dog Days" By J.A. Giesecke; J.M. Dixon; P.B. Dixon; M.T. Rimmer
  7. Market Design for Rapid Demand Response - The Case of Kenya By Kurt Nielsen; Tseganesh Wubale Tamirat
  8. Climate policy and competitiveness: Policy guidance and quantitative evidence By Jared C. Carbone; Nicholas Rivers
  9. Comparing Solution Methods for DSGE Models with Labor Market Search By Hong Lan; ; ;
  10. How Much Abatement Will Australia's Emissions Reduction Fund Buy? By Harry Clarke; Iain Fraser; Robert Waschik
  11. Interfacing a CGE Labour Market Model with the E3ME Multi-Sector Macroeconomic Model By G.A. Meagher; Felicity Pang; R.A. Wilson
  12. Understanding Exchange Rates Dynamics By Peter Martey Addo; Monica Billio; Dominique Guegan

  1. By: Randall W. Jackson (Regional Research Institute, West Virginia University)
    Abstract: This document is intended to clarify the foundations of the IO and CGE analytical frameworks and procedures that underlie the NSF and USDA/NIFA funded research projects. It covers environmental data, life cycle assessment (LCA), input-output models (IO), structural decomposition analysis (SDA), social accounting matrix models (SAMs), and computable general equilibrium modeling (CGE).
    Keywords: LCA, IO, SDA, SAMs, CGE
    JEL: C67 C68 D58 R13 R15
    Date: 2013–08–09
  2. By: Stefano Lucidi (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza"); Massimo Maurici (Dipartimento di Biomedicina e Prevenzione Laboratorio di Simulazione e Ottimizzazione dei servizi del SSN Universita' di Roma "Tor Vergata"); Luca Paulon (Dipartimento di Biomedicina e Prevenzione Laboratorio di Simulazione e Ottimizzazione dei servizi del SSN Universita' di Roma "Tor Vergata"); Francesco Rinaldi (Dipartimento di Matematica, Universita' di Padova); Massimo Roma (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza")
    Abstract: In this work a simulation-based optimization model is considered in the framework of the management of hospital services. Given specific parameters which describe the hospital setting, the simulation model aims at reproducing the hospital processes and evaluating their efficiency. The use of a simulation-based optimization approach is necessary since the model can not be expressed as closedÐform function. In order to obtain the optimal setting, we combine a derivative-free optimization method with a discrete event simulation model. The resulting framework has been tested on a real healthcare problem. More specifically, we study how to optimize the performance of an obstetric ward of a big Italian hospital, from both an economical and clinical point of view, taking into account some relevant constraints. The resulting optimization problem is a Mixed Integer Nonlinear Programming problem due to the presence of some variables constrained to be integer.
    Keywords: Healthcare problems ; Simulation-based optimization ; Derivative-free methods
    Date: 2014
  3. By: Dudu, Hasan; Cakmak, Erol H
    Abstract: This paper analyses the effects of climate change and trade liberalization on Turkish Economy between 2008 and 2099 by using a recursive dynamic CGE model. Results of a crop-irrigation requirement model are used to generate climate change shocks. The results suggest that the effects of climate change will be effective especially after 2030s with acceleration after 2060s. GDP loss gets as high as 3.5 percent. Main drivers of the loss in GDP are the significant decline in private consumption and up to two percent increase in imports. A trade liberalization scenario where tariffs on imports from EU are eliminated unilaterally by Turkey is also simulated to investigate the interaction between climate change and trade liberalization. Trade policy alleviates the negative effects of climate change only marginally for Turkey, as suggested by the literature for many other regions in the world. Trade liberalization with EU causes a trade diversion effect and decreases imports from other trading regions. The main adjustment mechanism of the economy under trade liberalization works through the substitution of factors for intermediate goods, imported consumption goods and intermediate inputs for domestic goods. Maize, oilseeds, fruits and processed food benefit from trade liberalization while production of other crops generally decline.
    Keywords: Climate Change, Trade Liberalization, Agriculture, Computable General Equilibrium, Turkey, Environmental Economics and Policy, Land Economics/Use, Research Methods/ Statistical Methods, C68, Q54, Q17,
    Date: 2014
  4. By: Kump, Nataša; Navicke, Jekaterina
    Abstract: This paper discusses an application of re-weighting to account for demographic change within a comparative micro-simulation setting. We use the Slovenian and Lithuanian components of the EUROMOD micro-simulation model with data referring to demographic characteristics of the population in 2010 to test the proposed procedures. The data are re-weighted to reflect demographic change up to 2012 and 2020 as indicated in the Eurostat Population Projections (Europop).
    Date: 2014–06–25
  5. By: DE CORTE, Annelies; SÖRENSEN, Kenneth
    Abstract: Using a structured design methodology, we develop an eXcient iterated local search metaheuristic for the water distribution network design optimisation problem. The algorithm outperforms existing algorithms in the literature while being considerably less complex. Our approach is — contrary to algorithms in the literature — also shown to perform well on large, realistic instances.
    Keywords: Water distribution network design, Iterated local search, Mixed-integer non-linear optimisation, Pipe sizing
    Date: 2014–08
  6. By: J.A. Giesecke; J.M. Dixon; P.B. Dixon; M.T. Rimmer
    Abstract: In his recent book "Dog Days", Garnaut (2013) argues that the Australian economy faces significant economic challenges, with a risk that just as the investment phase of the mining boom ends, Australia will be entering an economic environment characterised by declining terms of trade, a rising dependency ratio and rising world interest rates. In this paper, we evaluate the consequences of these challenges for key macroeconomic variables and per-capita measures of economic wellbeing using an economy-wide model. With plausible assumptions on key inputs to our model, we produce a scenario that is broadly consistent with the pessimistic picture for the immediate future of the Australian economy as portrayed in Dog Days. We forecast real per-capita incomes to fall at a rate of 0.3% p.a., so that by 2019/20 they have returned to the level of 2010/11. To maintain an unchanged unemployment rate over the forecast period, the average real wage must fall by 0.89% p.a., returning to its 2007/08 level by 2019/20. Fiscal consolidation sees damped growth in consumption. With real aggregate per-capita consumption falling at -079% p.a., it returns to its 2008/09 level by 2019/20. These are our forecast outcomes under an orderly adjustment scenario. However as Garnaut notes, there is a risk of mismanagement of the policy adjustments that will be required in the face of Australia's new economic realities. We simulate this through a scenario in which public and private consumption per capita, and real wages, initially remain at their 2013/14 levels, despite a decline in real per capita national income. The macroeconomic adjustments that this scenario entails ultimately generate significant economic volatility, with the unemployment rate rising to 6.6 per cent by 2015/16, before a 2.8% real wage fall in 2016/17 commences the process of returning the unemployment rate to its current level by 2019/20. Maintenance of our recent experience of rapid growth in per-capita income will require a substantial increase in multifactor productivity growth. In our third simulation, we model the size of the increase in multifactor productivity necessary to offset the forecast declining terms of trade, rising dependency ratio, and other forecast economic challenges. We find that the required rate of productivity growth, at 1.96% p.a., is of a level not seen in Australia since the last program of major structural reform in the 1990s. It seems unlikely that we can count on the tailwinds of any recent programs of micro reform to generate the levels of multifactor productivity growth that will be needed to maintain recent growth rates in real income. In our fourth simulation, we set a more modest goal, uncovering the productivity growth required to maintain, not increase, real per capita incomes. At 0.49% p.a., this rate is higher than the average productivity performance of the last decade, suggesting Australia faces a significant reform challenge in maintaining, let alone growing, real per capita incomes in the post-boom environment.
    Keywords: CGE modelling, dynamics, mining boom, productivity, economic growth, living standards
    JEL: C68 D58 F43 F16 O40
    Date: 2014–07
  7. By: Kurt Nielsen (Department of Food and Resource Economics, University of Copenhagen); Tseganesh Wubale Tamirat (Department of Food and Resource Economics, University of Copenhagen)
    Abstract: We suggest a market design for rapid demand response in electricity markets. The solution consists of remotely controlled switches, meters, forecasting models as well as a flexible auction market to set prices and select endusers job by job. The auction market motivates truth-telling and makes it simple to involve the endusers in advance and to activate demand response immediately. The collective solution is analyzed and economic simulations are conducted for the case of Kenya. Kenya has been suering from unreliable electricity supply for many years and companies and households have learned to adjust by investments in backup generators. We focus on turning the many private backup generators into a demand response system. The economic simulation focuses on possible distortion introduced by various ways of splitting the generated surplus from the demand response system. An auction run instantly as the Transmission System Operator (TSO) requests demand response and the winning endusers are disconnected immediately if the TSO accepts the result of the auction. The endusers are compensated with a uniform auction price job by job and the Aggregator receives part of the surplus. The simulation captures the nature of the demand response system and reveals that a simple markup contract between the Aggregator and the TSO is sufficiently flexible and little distorting. The simulation also provide a the less intuitive result, that the auction motivates the TSO to oer a high markup contract to the Aggregator to motivate a large pool of demand response. We discuss how this may motivate the alternative owner structure where the Aggregator is a cooperative owned by the endusers themselves.
    Keywords: : Demand response, auction market, contracts, simulation
    Date: 2014–08
  8. By: Jared C. Carbone (Division of Economics and Business, Colorado School of Mines); Nicholas Rivers (University of Ottawa)
    Abstract: When considering adoption of a domestic climate change policy, politicians and the public frequently refer to concerns about competitiveness. Competitiveness in this context does not have a precise economic definition. In this article, we discuss possible ways to anchor the concept of competitiveness in economic analysis. This framework then serves as the basis of a systematic survey the literature on the quantitative impacts of unilateral climate change policy derived from the results of computable general equilibrium (or CGE) models. We provide empirical estimates of the magnitude of competitiveness effects that might be associated with the adoption of unilateral climate change policies and a meta-analysis of the key sensitivities displayed by the models as a guide to future research.
    Keywords: competitiveness, leakage, policy, carbon tax, climate change, computable general equilibrium
    JEL: C68 Q52 Q54
    Date: 2014–08
  9. By: Hong Lan; ; ;
    Abstract: I compare the performance of solution methods in solving a standard real business cycle model with labor market search frictions. Under the conventional calibration, the model is solved by the projection method using the Chebyshev polynomials as its basis, and the perturbation methods up to third order in both levels and logs. Evaluated by two accuracy tests, the projection approximation achieves the highest degree of accuracy, closely followed by the third order perturbation in levels. Although different in accuracy, all the approximated solutions produce simulated moments similar in value.
    Keywords: Computational methods; DSGE; Business cycles; Search and matching; Accuracy test
    JEL: C63 C68 E32
    Date: 2014–09
  10. By: Harry Clarke (School of Economics, La Trobe University); Iain Fraser (School of Economics, La Trobe University; University of Kent); Robert Waschik (School of Economics, La Trobe University)
    Abstract: The economic implications for Australia of replacing its carbon tax policy with an Emissions Reduction Fund (ERF) scheme are examined. A computable general equilibrium model is used to show that the budget allocated for the ERF is about 50 per cent of that required to meet Australia's greenhouse gas abatement commitments.
    Keywords: carbon tax, emissions reduction fund, computable general equilibrium model
    JEL: C68 Q48 Q52
    Date: 2014–08
  11. By: G.A. Meagher; Felicity Pang; R.A. Wilson
    Abstract: In recent years, a series of European labour market forecasts have been produced on behalf of, and have been published by, the European Centre for the Development of Vocational Training (CEDEFOP). These forecasts were generated using a modular modelling approach containing two major components: * a multi-sector macroeconomic model (E3ME) for 29 European countries, primarily developed and operated by Cambridge Econometrics, and * a labour market extension (WLME), primarily developed and operated by the Institute for Employment Research at the University of Warwick. The countries are treated as an integrated system in E3ME but the extension is applied to each country separately. Forecasts of employment by industry are determined by E3ME; forecasts of employment by occupation and qualification are determined by the extension. The two components rely mainly on time series econometric techniques to generate their forecasts. This paper describes how WLME can be replaced with an alternative extension (MLME) which incorporates a computable general equilibrium model. The CGE model has been developed primarily at the Centre of Policy Studies at Monash University. Compared to WLME, MLME relies less on time series extrapolation and more on explicitly modelled economic behaviour. This approach introduces a range of behavioural and technical parameters which offer more scope for modelling developments in the labour market which impact on occupations and skills rather industries. Forecasts produced using the new E3ME-MLME system are reported for the United Kingdom, Greece and the Netherlands, and compared with the corresponding forecasts produced using the existing E3ME-WLME system. The focus of the comparison is on qualitative differences in the way the two sets of forecasts are to be interpreted. In particular, the sense in which explicit specification of technical change and economic behaviour (in the new system) can be substituted for time series extrapolation techniques (in the existing system) is carefully considered. The primary objective of the paper, therefore, is to demonstrate the empirical feasibility of the alternative methodology rather than to produce robust alternative forecasts.
    Keywords: Forecasting, CGE models, hybrid models, labour markets
    JEL: C53 C58 D58 E27 J23 O41
    Date: 2014–09
  12. By: Peter Martey Addo (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, Università Ca' Foscari of Venice - Department of Economics, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Monica Billio (Università Ca' Foscari of Venice - Department of Economics); Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)
    Abstract: With the emergence of the chaos theory and the method of surrogates data, nonlinear approaches employed in analysing time series typically suffer from high computational complexity and lack of straightforward explanation. Therefore, the need for methods capable of characterizing time series in terms of their linear, nonlinear, deterministic and stochastic nature are preferable. In this paper, we provide a signal modality analysis on a variety of exchange rates. The analysis is achieved by using the recently proposed "delay vector variance" (DVV) method, which examines local predictability of a signal in the phase space to detect the presence of determinism and nonlinearity in a time series. Optimal embedding parameters used in the DVV analysis are obtain via differential entropy based method using wavelet-based surrogates. A comprehensive analysis of the feasibility of this approach is provided. The empirical results show that the DVV method can be opted as an alternative way to understanding exchange rates dynamics.
    Keywords: Nonlinearity analysis; exchange rates; surrogates; Delay vector variance (DVV) method; wavelets
    Date: 2013–02

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