nep-cmp New Economics Papers
on Computational Economics
Issue of 2005‒10‒04
five papers chosen by
Stan Miles
York University

  1. SIGMA: a new open economy model for policy analysis By Christopher J. Erceg; Luca Guerrieri; Christopher Gust
  2. Exact Properties of Measures of Optimal Investment for Institutional Investors By John Knight; Stephen Satchell
  3. Measurement of contagion in banks’ equity prices By Reint Gropp; Gerard Moerman
  4. Seasonal adjustment and the detection of business cycle phases By Antonio Matas Mir; Denise R Osborn
  5. Computing second-order-accurate solutions for rational expectation models using linear solution methods By Giovanni Lombardo; Alan Sutherland

  1. By: Christopher J. Erceg; Luca Guerrieri; Christopher Gust
    Abstract: In this paper, we describe a new multi-country open economy SDGE model named "SIGMA" that we have developed as a quantitative tool for policy analysis. We compare SIGMA's implications to those of an estimated large-scale econometric policy model (the FRB/Global model) for an array of shocks that are often examined in open-economy policy simulations. We show that SIGMA's implications for the near-term (2-3 year) responses of key variables are generally similar to those of FRB/Global. Two features of our modeling framework, including rational expectations with learning, and the inclusion of some non-Ricardian agents, play an important role in giving SIGMA more flexibility to generate responses akin to the econometric policy model; nevertheless, some quantitative disparities between the two models remain due to certain restrictive aspects of SIGMA's optimization-based framework. We conclude by using long-term simulations to illustrate some areas of comparative advantage of our SDGE modeling framework. These include linking model responses to underlying structural features of the economy, and fully articulating the endogenous channels through which "imbalances" arising from various shocks are alleviated.
    Keywords: Macroeconomics - Econometric models ; Business cycles - Econometric models
    Date: 2005
  2. By: John Knight; Stephen Satchell
    Abstract: We revisit the problem of calculating the exact distribution of optimal investments in a mean variance world under multivariate normality. The context we consider is where problems in optimisation are addressed through the use of Monte-Carlo simulation. Our findings give clear insight as to when Monte-Carlo simulation will, and will not work. Whilst a number of authors have considered aspects of this exact problem before, we extend the problem by considering the problem of an investor who wishes to maximise quadratic utility defined in terms of alpha and tracking errors. The results derived allow some exact and numerical analysis. Furthermore, they allow us to also derive results for the more traditional nonbenchmarked portfolio problem.
    Keywords: alpha, tracking error, mean-variance, Monte-Carlo
    JEL: G11
    Date: 2005–09
  3. By: Reint Gropp (European Central Bank, Kaiserstrasse 28, 60311 Frankfurt am Main, Germany.); Gerard Moerman (Erasmus University Rotterdam, The Netherlands)
    Abstract: This paper uses the co-incidence of extreme shocks to banks’ risk to examine within country and across country contagion among large EU banks. Banks’ risk is measured by the first difference of weekly distances to default and abnormal returns. Using Monte Carlo simulations, the paper examines whether the observed frequency of large shocks experienced by two or more banks simultaneously is consistent with the assumption of a multivariate normal or a student t distribution. Further, the paper proposes a simple metric, which is used to identify contagion from one bank to another and identify “systemically important” banks in the EU.
    Keywords: Banking; Contagion; Monte Carlo Simulations.
    JEL: G21 F36 G15
    Date: 2003–12
  4. By: Antonio Matas Mir (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.); Denise R Osborn (Centre for Growth and Business Cycle Research, School of Economic Studies, University of Manchester, UK)
    Abstract: To date, there has been little investigation of the impact of seasonal adjustment on the detection of business cycle expansion and recession regimes. We study this question both analytically and through Monte Carlo simulations. Analytically, we view the occurrence of a single business cycle regime as a structural break that is later reversed, showing that the effect of the linear symmetric X-11 filter differs with the duration of the regime. Through the use of Markov switching models for regime identification, the simulation analysis shows that seasonal adjustment has desirable properties in clarifying the true regime when this is well underway, but it distorts regime inference around turning points, with this being especially marked after the end of recessions and when the one-sided X-11 filter is employed.
    Keywords: Seasonal adjustment; business cycles; Markov switching models.
    JEL: E32 C22 C80
    Date: 2004–05
  5. By: Giovanni Lombardo (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany); Alan Sutherland (School of Economics and Finance, University of St Andrews, St Andrews, KY16 9AL, United Kingdom)
    Abstract: This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. The result is a state-space representation for the realized values of the variables of the model. This state-space representation can easily be used to compute impulse responses as well as conditional and unconditional forecasts.
    Keywords: Second order approximation; Solution method for rational expectation models.
    JEL: C63 E0
    Date: 2005–05

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