nep-cmp New Economics Papers
on Computational Economics
Issue of 2016‒04‒04
eight papers chosen by

  1. Comparing Genetic Algorithm Crossover and Mutation Operators for the Indexing Problem By Ghosh, Diptesh
  2. Forward or Backward Looking? The Economic Discourse and the Observed Reality By Jochen Lüdering; Peter Winker
  3. Modelling the Electricity and Natural Gas Sectors for the Future Grid: Developing Co-Optimisation Platforms for Market Redesign By Foster, John; Wagner, Liam; Liebman, Ariel
  4. Reducing unwanted consequences of aggregation in large-scale economic models - a systematic empirical evaluation with the GTAP model By Britz, Wolfgang; Drud, Arne; van der Mensbrugghe, Dominique
  5. Parsing the content of bank supervision By Goldsmith-Pinkham, Paul; Hirtle, Beverly; Lucca, David O.
  6. Inequality, Financialisation and Credit Booms - a Model of Two Crises By Cardaci, Alberto; Saraceno, Francesco
  7. Boosting National Infrastructure Investment in West Java: An Analysis Using TERM CGE Model By Viktor Pirmana; Armida Alisjahbana; Irlan Adiyatma Rum
  8. Bank distress in the news: Describing events through deep learning By Samuel R\"onnqvist; Peter Sarlin

  1. By: Ghosh, Diptesh
    Abstract: The tool indexing problem is one of allocating tools to slots in a tool magazine so as to minimize the tool change time in automated machining. Genetic algorithms have been suggested in the literature to solve this problem, but the reasons behind the choice of operators for those algorithms are unclear. In this paper we compare the performances of four common crossover operators and four common mutation operators to find the one most suited for the problem. Our experiments show that the choice of operators for the genetic algorithms presented in the literature is suboptimal.
  2. By: Jochen Lüdering (University of Giessen); Peter Winker (University of Giessen)
    Abstract: Is academic research anticipating economic shake-ups or merely reflecting the past? Exploiting the corpus of articles published in the Journal of Economics and Statistics (Jahrbücher für Nationalökonomie und Statistik) for the years 1949 to 2010, this pilot study proposes a quantitative framework for addressing these questions. The framework comprises two steps. First, methods from computational linguistics are used to identify relevant topics and their relative importance over time. In particular, Latent Dirichlet Analysis is applied to the corpus after some preparatory work. Second, for some of the topics which are closely related to specific economic indicators, the developments of topic weights and indicator values are confronted in dynamic regression and VAR models. The results indicate that for some topics of interest, the discourse in the journal leads developments in the real economy, while for other topics it is the other way round.
    Date: 2016
  3. By: Foster, John; Wagner, Liam; Liebman, Ariel
    Abstract: This report provides detail on the modelling and scenario frameworks for the economic analysis of the Future Grid. These frameworks and modelling platforms have been constructed to support the Future Grid Cluster in examining policy and market issues which will affect the electricity and natural gas markets in Australia. Initially we provide an overview of the co-optimisation and expansion of transmission networks and electricity generation for the future grid. In this section we outline not only the key mechanisms and analyses required, but also how we have and will continue to collaborate with the other projects within the Future Grid Cluster. In section 3 we provide an extensive analysis of the electricity market modelling platform PLEXOS. This section will outline, not only the mechanistic components of modelling electricity markets, but also some of the assumptions which are required to examine issues such as generation investment under uncertainty. The following section is a discussion of the natural gas modelling platform ATESHGAH. This model has been in construction for several years prior to the commencement of the Future Grid Cluster and represents a significant shift in gas market modelling methodology for Australia, compared to previous approaches. This model is capable of examining multiple issues associated with policy, market, economic, and physical aspects of gas production, transmission, sale and liquefied natural gas (LNG) export simultaneously. We have used this model to examine how Australia’s eastern gas market could be affected by the commencement of LNG exports from Curtis Island in 2015/16. In the remaining section, we present the scenario modelling framework as an overview and present some initial results for Scenario 1: Set and Forget. These results represent the first set of simulations and should thus be viewed as an initial attempt to undertake the large search space that the four scenarios evaluated in the Future Grid Forum encompass.
    Keywords: Energy Economics, Electricity Markets
    JEL: Q41 Q47 Q48
    Date: 2015–12–01
  4. By: Britz, Wolfgang; Drud, Arne; van der Mensbrugghe, Dominique
    Abstract: We discuss how to avoid aggregation bias in large-scale global Computable General Equilibrium (CGE) models by reducing the need of pre-model aggregation, based on the combination of algorithmic improvements and a filtering approach which removes small transactions. Using large-scale sensitivity analysis, we show the impact of pre-aggregation and filtering on model size, model solution time and simulated welfare impacts, using a multi-lateral partial trade liberalization simulated with the standard GTAP model as the test case. We conclude that pre-model aggregation should be avoided as far as possible, and that our filtering approach and algorithmic improvements allow global CGE analysis even with highly disaggregated data sets at moderate solution times.
    Keywords: Computable General Equilibrium analysis, aggregation bias, International Relations/Trade, Research Methods/ Statistical Methods, C68, C63,
    Date: 2015–12–10
  5. By: Goldsmith-Pinkham, Paul (Federal Reserve Bank of New York); Hirtle, Beverly (Federal Reserve Bank of New York); Lucca, David O. (Federal Reserve Bank of New York)
    Abstract: We measure bank supervision using the database of supervisory issues, known as matters requiring attention or immediate attention, raised by Federal Reserve examiners to banking organizations. The volume of supervisory issues increases with banks’ asset size, especially for the largest and most complex banks, and decreases with profitability and the quality of the loan portfolio. Stressed banks are faster at resolving issues, but all else equal, resolving new issues takes longer the more issues a bank faces, which may suggest capacity constraints in addressing multiple supervisory issues. Using computational linguistic methods on the text of the issue description, we define five categorical issue topics. The subset of issues related to capital levels and loan portfolio are the most consequential in terms of regulatory rating downgrades and are directly related to changes in banks’ balance sheet characteristics and profitability. Other issues appear to reflect soft information and are less correlated with bank observables. By categorizing questions asked by analysts at banks’ quarterly earnings calls using the same linguistic approach, we find that market monitors raise issues similar to those of supervisors when the issues are related to hard information (such as loan quality or capital) and public supervisory assessment programs.
    Keywords: bank supervision; bank regulation; market monitoring; text classification; Latent Dirichlet Allocation
    JEL: G21 G28
    Date: 2016–03–01
  6. By: Cardaci, Alberto (Lombardy Advanced School of Economic Research, Milan); Saraceno, Francesco (LUISS School of European Political Economy)
    Abstract: We develop a macroeconomic model with an agent-based household sector and a stock-flow consistent structure, in order to analyse the impact of rising income inequality on the likelihood of a debt crisis for diff erent institutional settings. In particular, we study how economic crises emerge in the presence of di fferent credit conditions and policy reactions to rising income disparities. Our simulations show the relevance of the degree of financialisation of an economy. In fact, when inequality grows, a Scylla and Charybdis kind of dilemma seems to arise: on the one hand, low credit availability implies a drop in aggregate demand and output; on the other hand, a higher willingness to lend and lower perceptions of system risk result in greater instability and a debt-driven boom and bust cycle. The model allows us to replicate the credit-led consumption booms that paved the way for both the crisis of 1929 and the recent financial crisis. In addition, our paper yields a new insight on the appropriate policy reaction: tackling inequality by means of a more progressive tax system compensates for the rise in income disparities thereby stabilising the economy. This is a better solution compared to a more proactive fiscal policy which, instead, only leads to a larger duration of the boom and bust cycle.
    Keywords: Inequality; Household Debt; Credit Markets; Agent-Based Models; StockFlow Consistency
    JEL: C63 D31 E21 E62 G01
    Date: 2016–02–19
  7. 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: 2015–12
  8. By: Samuel R\"onnqvist; Peter Sarlin
    Abstract: While many models are purposed for detecting the occurrence of events in complex systems, the task of providing qualitative detail on the developments is not usually as well automated. We present a deep learning approach for detecting relevant discussion in text and extracting natural language descriptions of events. Supervised by only a small set of event information, the model is leveraged by unsupervised learning of semantic vector representations on extensive text data. We demonstrate applicability to the study of financial risk based on news (6.6M articles), particularly bank distress and government interventions (243 events), where indices can signal the level of bank-stress-related reporting at the entity level, or aggregated at country or European level, while being coupled with explanations. Thus, we exemplify how text, as timely and widely available data, can serve as a useful complementary source of information for financial risk analytics.
    Date: 2016–03

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.