nep-cmp New Economics Papers
on Computational Economics
Issue of 2016‒07‒16
twelve papers chosen by
Stan Miles
Thompson Rivers University

  1. CGE model with fiscal sector for Latvia By Konstantins Benkovskis; Eduards Goluzins; Olegs Tkacevs
  2. “Lock-in” Effect of Emission Standard and Its Impact on the Choice of Market Based Instruments By Qian, Haoqi; Wu, Libo; Tang, Weiqi
  3. Boosting National Infrastructure Investment in West Java: An Analysis Using TERM CGE Model By Viktor Pirmana; Armida Alisjahbana; Irlan Adiyatma Rum
  4. MPDATA Meets Black-Scholes: Option Pricing as a Transport Problem By Sylwester Arabas; Ahmad Farhat
  5. Deep Learning for Mortgage Risk By Justin Sirignano; Apaar Sadhwani; Kay Giesecke
  6. Divisive-agglomerative algorithm and complexity of automatic classification problems By Alexander Rubchinsky
  7. The Effects of Labour Market Reforms upon Unemployment and Income Inequalities: an Agent Based Model By Giovanni Dosi; Marcelo C. Pereira; Andrea Roventini; Maria Enrica Virgillito
  8. Effects of a reduction in employers' social security contributions: Evidence from Spain By Campoy-Muñoz, Pilar; Cardenete Flores, Manuel Alejandro; Delgado, M. Carmen; Hewings, Geoffrey
  9. The WITCH 2016 Model - Documentation and Implementation of the Shared Socioeconomic Pathways By Emmerling, Johannes; Drouet, Laurent Drouet; Reis, Lara Aleluia; Bevione, Michela; Berger, Loic; Bosetti, Valentina; Carrara, Samuel; De Cian, Enrica; De Maere D'Aertrycke, Gauthier; Longden, Tom; Malpede, Maurizio; Marangoni, Giacomo; Sferra, Fabio; Tavoni, Massimo; Witajewski-Baltvilks, Jan; Havlik, Petr
  10. Bank capital structure and the credit channel of central bank asset purchases By Darracq Pariès, Matthieu; Hałaj, Grzegorz; Kok, Christoffer
  11. The Market Resources Method for Solving Dynamic Optimization Problems By Ayse Kabukcuoglu; Enrique Martínez-García
  12. Methodological Aspects of Qualitative-Quantitative Analysis of Decision-Making Processes By Gawlik, Remigiusz

  1. By: Konstantins Benkovskis (Bank of Latvia); Eduards Goluzins; Olegs Tkacevs (Bank of Latvia)
    Abstract: This paper describes the first CGE model for Latvia that consists of 32 industries, 55 products and seven categories of final users. To construct the model we use Latvia's National Supply and Use tables for 2011 from the WIOD database. Special attention is devoted to the fiscal block: the model consists of five government expenditure types and five revenue sources, including such four major taxes as the personal income tax (PIT), state social insurance mandatory contributions (SSIMC), value added tax (VAT) and excise tax. We also introduce an endogenous shadow economy, the size of which depends on the level of tax rates and economic activity. These features of the model allow us to obtain rich and detailed conclusions about the effect of several fiscal measures on Latvia's economy, both in aggregate and by sector.
    Keywords: CGE model, Latvia, fiscal policy
    JEL: D58 C68 H2 H6
    Date: 2016–07–04
  2. By: Qian, Haoqi; Wu, Libo; Tang, Weiqi
    Abstract: A country’s existing emission standard policy will lead to a “lock in” effect. When the country plans to adopt new market-based instruments to control greenhouse gas emissions, it must consider this effect as it chooses among instruments to avoid larger efficiency loss. In this paper, we find that the “lock in” effect will cause a kink point to occur on the marginal abatement cost (MAC) curve. This change of shape for the MAC curve reminds us to be cautious in choosing market-based instruments when applying Weitzman’s rule. We also introduce this concept into a dynamic multi-regional computable general equilibrium (CGE) model for China and simulate MAC curves for all regions. After applying Weitzman’s rule, we propose a timeline for introducing price instruments under different marginal benefit (MB) curve scenarios.
    Keywords: Lock-in Effect; Marginal Abatement Cost Curve; Cap and Trade of Carbon Emissions Rights; Carbon Tax
    JEL: C68 Q58
    Date: 2016–03
  3. By: Viktor Pirmana (Department of Economics, Padjadjaran University); Armida Alisjahbana (Department of Economics, Padjadjaran University); Irlan Adiyatma Rum (Department of Economics, Padjadjaran University)
    Abstract: It is well established that infrastructure investment plays significant role in the acceleration of development through its impact on growth, sector performance and socio-economic indicators. West Java Province is province with the largest population in Indonesia and main contributor to national GDP. In this study, the impact of increased national infrastructure investment in West Java Province is assessed using 2014 data. JaBarTERM5 CGE model is used to simulate two infrastructure investment scenarios, the moderate scenario or increase in government national infrastructure investment only, and the progressive scenario that combines government national infrastructure investment with private investment. The results indicate that under the moderate scenario, West Java GRDP increased by 1.91% (1.91 percentage point compared to baseline, while in the progressive scenario (national plus private infrastructure investment), GRDP increased by up to 3.58% (3.58 percentage point compared to baseline). However, there are differential responses at district level. Districts that experience the highest increase in GRDP are districts close to industrial areas in the vicinity of Jakarta and Bandung. When viewed from its impact on provincial employment, it increases by 2.27% (2.27 percentage point compared to the baseline case) under the progressive scenario. The employment impact is particularly more pronounced in districts that are industrial areas. Sectors that experience increase in their production are Cements, Papers, Textiles, Food Crops, and Transportation Services. Another result is an increase in the prices of Real Estate, and Business and Financial Services, while the price (cost) of trade and transport sector has decreased due to an increase in the access and quality of infrastructure.
    Keywords: National Infrastructure Investment, TERM CGE model, West Java Province
    JEL: H54 H72
    Date: 2016–06
  4. By: Sylwester Arabas; Ahmad Farhat
    Abstract: In this note, we discuss applications of the Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) to numerical solutions of option pricing equations arising in quantitative finance. To demonstrate, we present an application of an unmodified open-source MPDATA solver library, libmpdata++, developed recently in the geoscientific community. We use the library to numerically price a typical example of a financial instrument, an interest rate corridor, assuming the Black-Scholes model. The results obtained with different solver settings are compared with the analytical solution with the aim of depicting the accuracy of the numerical scheme. The goal of this study is to highlight the potential MPDATA has as an accurate finite-difference approach for solving a wide variety of option pricing problems, including problems of current interest.
    Date: 2016–07
  5. By: Justin Sirignano; Apaar Sadhwani; Kay Giesecke
    Abstract: This paper analyzes multi-period mortgage risk at loan and pool levels using an unprecedented dataset of over 120 million prime and subprime mortgages originated across the United States between 1995 and 2014, which includes the individual characteristics of each loan, monthly updates on loan performance over the life of a loan, and a number of time-varying economic variables at the zip code level. We develop, estimate, and test dynamic machine learning models for mortgage prepayment, delinquency, and foreclosure which capture loan-to-loan correlation due to geographic proximity and exposure to common risk factors. The basic building block is a deep neural network which addresses the nonlinear relationship between the explanatory variables and loan performance. Our likelihood estimators, which are based on 3.5 billion borrower-month observations, indicate that mortgage risk is strongly influenced by local economic factors such as zip-code level foreclosure rates. The out-of-sample predictive performance of our deep learning model is a significant improvement over linear models such as logistic regression. Model parameters are estimated using GPU parallel computing due to the computational challenges associated with the large amount of data. The deep learning model's superior accuracy compared to linear models directly translates into improved performance for investors. Portfolios constructed with the deep learning model have lower prepayment and delinquency rates than portfolios chosen with a logistic regression.
    Date: 2016–07
  6. By: Alexander Rubchinsky
    Abstract: An algorithm of solution of the Automatic Classification (AC for brevity) problem is set forth in the paper. In the AC problem, it is required to find one or several artitions, starting with the given pattern matrix or dissimilarity, similarity matrix.
    Date: 2016–07
  7. By: Giovanni Dosi; Marcelo C. Pereira; Andrea Roventini; Maria Enrica Virgillito
    Abstract: This paper is meant to analyse the effects of labour market structural reforms by means of an agent-based model. Building on Dosi et al., (2016b) we introduce a policy regime change characterized by a set of structural reforms on the labour market, keeping constant the structure of the capital- and consumption-good markets. Confirming a recent IMF report (Jaumotte and Buitron, 2015), the model shows how labour market structural reforms reducing workersù bargaining power and compressing wages tend to increase (i) unemployment, (ii) functional income inequality, and (iii) personal income inequality. We further undertake a global sensitivity analysis on key variables and parameters which confirms the robustness of our findings.
    Keywords: Labour Market Structural Reforms, Income Distribution, Inequality, Unemployment, Long-Run Growth
    Date: 2016–05–07
  8. By: Campoy-Muñoz, Pilar; Cardenete Flores, Manuel Alejandro; Delgado, M. Carmen; Hewings, Geoffrey
    Abstract: Programs to reduce employers' social security contributions are being widely discussed in both the political arena and academic forums as tools for promoting economic growth and boosting employment. This paper employs a computable general equilibrium model to assess the economic impact on the national economy of the proposals from the Spanish Confederation of Enterprise Organizations about reducing the social security contributions paid by employers. The results show that the proposals fail to reduce unemployment when they are combined with compensation by revenues from indirect taxes; whereas compensation through increased personal income taxes shows positive results on unemployment in exchange for decreases in private consumption.
    Keywords: computable general equilibrium models,social security contributions,tax reforms,fiscal consolidation
    JEL: C68 H20 H32
    Date: 2016
  9. By: Emmerling, Johannes; Drouet, Laurent Drouet; Reis, Lara Aleluia; Bevione, Michela; Berger, Loic; Bosetti, Valentina; Carrara, Samuel; De Cian, Enrica; De Maere D'Aertrycke, Gauthier; Longden, Tom; Malpede, Maurizio; Marangoni, Giacomo; Sferra, Fabio; Tavoni, Massimo; Witajewski-Baltvilks, Jan; Havlik, Petr
    Abstract: This paper describes the WITCH - World Induced Technical Change Hybrid - model in its structure, calibration, and the implementation of the SSP/RCP scenario implementation. The WITCH model is a regionally disaggregated hard-linked model based on a Ramsey type optimal growth model and a detailed bottom-up energy sector model. A particular focus of the model is the modeling or technical change and RnD investments and the analysis of cooperative and non-cooperative climate policies. Moreover, the WITCH 2016 version now includes land-use change modeling based on the GLOBIOM model, and air pollutants, as well as detailed modeling of the transport sector and the possibility for stochastic modeling. This version has been also used to implement the Shared Socioeconomic Pathways (SSPs) set of scenarios and RCP based climate policies to provide a new set of climate scenarios. In this paper, we describe in detail the mathematical formulation of the WITCH model, the solution method and calibration, as well as the implementation of the five SSP scenarios. This report therefore provides detailed information for interested users of the model, and for understanding the implementation of the different “worlds" of the SSP.
    Keywords: Integrated Assessment Model, SSPs, Climate Change, Scenarios, Research and Development/Tech Change/Emerging Technologies, Q54, C63,
    Date: 2016–07–04
  10. By: Darracq Pariès, Matthieu; Hałaj, Grzegorz; Kok, Christoffer
    Abstract: With the aim of reigniting inflation in the euro area, in early 2015 the ECB embarked on a large-scale asset purchase programme. We analyse the macroeconomic effects of the Asset Purchase Programme via the banking system, exploiting the cross-section of individual bank portfolio decisions. For this purpose, an augmented version of the DSGE model of Gertler and Karadi (2013), featuring a segmented banking sector, is estimated for the euro area and combined with a bank portfolio optimisation approach using granular bank level data. An important feature of our modelling approach is that it captures the heterogeneity of banks’ responses to yield curve shocks, due to individual banks’ balance sheet structure, different capital and liquidity constraints as well as different credit and market risk characteristics. The deep parameters of the DSGE model which control the transmission channel of central bank asset purchases are then adjusted to reproduce the easing of lending conditions consistent with the bank-level portfolio optimisation. Our macroeconomic simulations suggest that such unconventional policies have the potential to strongly support the growth momentum in the euro area and significantly lift inflation prospects. The paper also illustrates that the benefits of the measure crucially hinge on banks’ ability and incentives to ease their lending conditions, which can vary significantly across jurisdictions and segments of the banking system. JEL Classification: C61, E52, G11
    Keywords: banking, DSGE, portfolio optimisation, quantitative easing
    Date: 2016–06
  11. By: Ayse Kabukcuoglu (Koc University); Enrique Martínez-García (Federal Reserve Bank of Dallas, Southern Methodist University)
    Abstract: We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll’s (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides advantages in terms of speed and accuracy over Howard’s policy improvement algorithm. Codes are available.
    Keywords: DSGE models; Computational methods; Policy function iteration; Endogenous grid.
    JEL: C6 C61 C63 C68
    Date: 2016–07
  12. By: Gawlik, Remigiusz
    Abstract: The paper aims at recognizing the possibilities and perspectives of application of qualitative-quantitative research methodology in the field of economics, with a special focus on production engineering management processes. The main goal of the research is to define the methods that would extend the research apparatus of economists and managers by tools that allow the inclusion of qualitative determinants into quantitative analysis. Such approach is justified by qualitative character of many determinants of economic occurrences. At the same time quantitative approach seems to be predominant in production engineering management, although methods of transposition of qualitative decision criteria can be found in literature. Nevertheless, international economics and management could profit from a mixed methodology, incorporating both types of determinants into joint decision-making models. The research methodology consists of literature review and own analysis of applicability of mixed qualitative-quantitative methods for managerial decision-making. The expected outcome of the research is to find which methods should be applied to include qualitative-quantitative analysis into multicriteria decision-making models in the fields of economics, with a special regard to production engineering management.
    Keywords: qualitative-quantitative analysis; hierarchical decision-making; neural-network models; management; manufacturing processes
    JEL: C45 C65 D79 D81
    Date: 2016–06

This nep-cmp issue is ©2016 by Stan Miles. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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