Relevant bibliographies by topics / Computational economics

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Computational economics'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Computational economics"

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Sadiku, Matthew N. O., Mahamadou Tembely, and Sarhan M. Musa. "Computational Economics." International Journal of Engineering Research 6, no. 11 (2017): 464. http://dx.doi.org/10.5958/2319-6890.2017.00065.4.

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Judd, Kenneth, and Scott E. Page. "Computational Public Economics." Journal of Public Economic Theory 6, no. 2 (2004): 195–202. http://dx.doi.org/10.1111/j.1467-9779.2004.00164.x.

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Trisetyarso, Agung. "Quantum Computational Economics." Procedia Computer Science 216 (2023): 3. http://dx.doi.org/10.1016/j.procs.2022.12.103.

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Judd, Kenneth L. "Computational economics and economic theory: Substitutes or complements?" Journal of Economic Dynamics and Control 21, no. 6 (1997): 907–42. http://dx.doi.org/10.1016/s0165-1889(97)00010-9.

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McAdam, Peter. "Handbook of computational economics." Journal of Economic Dynamics and Control 22, no. 3 (1998): 483–87. http://dx.doi.org/10.1016/s0165-1889(97)00094-8.

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Tesfatsion, Leigh. "Agent-based computational economics." Scholarpedia 2, no. 2 (2007): 1970. http://dx.doi.org/10.4249/scholarpedia.1970.

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ORUN, EMRE. "Complexity Economics And Agent- Based Computational Economics." Akademi Sosyal Bilimler Dergisi 7, no. 19 (2020): 48–62. http://dx.doi.org/10.34189/asbd.7.19.004.

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Miranda, Mario J. "Teaching Computational Economics in an Applied Economics Program." Computational Economics 25, no. 3 (2005): 229–54. http://dx.doi.org/10.1007/s10614-005-2207-x.

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Schönbucher, Philipp. "Applied Computational Economics and Finance." Journal of the American Statistical Association 99, no. 466 (2004): 565–66. http://dx.doi.org/10.1198/jasa.2004.s337.

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Amman, Hans M. "The JEDC and computational economics." Journal of Economic Dynamics and Control 21, no. 6 (1997): 905–6. http://dx.doi.org/10.1016/s0165-1889(97)00009-2.

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Dissertations / Theses on the topic "Computational economics"

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Pugh, David. "Essays in computational economics." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9882.

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The focus of my PhD research has been on the acquisition of computational modeling and simulation methods used in both theoretical and applied Economics. My first chapter provides an interactive review of finite-difference methods for solving systems of ordinary differential equations (ODEs) commonly encountered in economic applications using Python. The methods surveyed in this chapter, as well as the accompanying code and IPython lab notebooks should be of interest to any researcher interested in applying finite-difference methods for solving ODEs to economic problems. My second chapter is a
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Jelonek, Piotr Zbigniew. "Essays on computational economics." Thesis, University of Leicester, 2014. http://hdl.handle.net/2381/28644.

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This text consists of two parts. In chapters 2-3 the methods are developed that enable the application of tempered stable distributions to measuring and simulating macroeconomic uncertainties. In contrast to the tools used in finance, these results are applicable to low frequency aggregated data, which typically displays tails of moderate gravity. Thus thay are particularly useful in modelling macroeconomic densities. The new methods may be readily employed in Monte Carlo simulations of possibly skewed, moderately heavy-tailed random variates with arbitrary excess kurtosis. In chapter 4 a comp
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Grinis, Inna. "Essays in applied computational economics." Thesis, London School of Economics and Political Science (University of London), 2017. http://etheses.lse.ac.uk/3580/.

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This thesis presents four distinct essays that lie at the intersection of economics and computation. The first essay constructs an abstract framework for defining skills gaps, mismatches and shortages geometrically and thinking about these phenomena in a unified, formal way. It then develops a job matching model with imperfect information, in which skills mismatches influence the job application decisions of the workers, while skills gaps and shortages shape the competition for workers on the resulting bipartite job applications network. The tools proposed in this chapter could in future work
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Balikcioglu, Metin. "Essays on Environmental and Computational Economics." NCSU, 2008. http://www.lib.ncsu.edu/theses/available/etd-12032008-210449/.

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The study consists of three separate essays. The first essay reassesses and extends the papers by Pindyck (2000, 2002) which analyze the effects of uncertainty and irreversibility on the timing of emissions reduction policy. It is shown that proposed solutions for some of the optimal stopping problems introduced in these papers are incorrect. Correct solutions are provided for both the incorrect special cases and the general model through a numerical method since closed form solutions do not exist for these problems. In the second essay, singular control framework is employed in order to allow
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Schuster, Stephan. "Applications in agent-based computational economics." Thesis, University of Surrey, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556466.

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A constituent feature of adaptive complex systems are non-linear feedback mechanisms between actors. These mechanisms are often difficult to model and analyse. One pos- sibility of modelling is given by Agent-based Computational Economics (ACE), which uses computer simulation methods to represent such systems and analyse non-linear processes. The aim of this thesis is to explore ways of modelling adaptive agents in ACE models. Its major contribution is of a methodological nature. Artificial intelligence and machine learning methods are used to represent agents and learning processes in economi
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Chong, Shi Kai. "A computational approach to urban economics." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122318.

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Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2018<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 89-92).<br>Cities are home to more than half of the world population today and urbanization is one of this century's biggest drivers of global economic growth. The dynamics of the urban environment is thus an important question to investigate. In this thesis, techniques from statistical modeling, machine learning, data mining and econometrics are utilized to study digital traces of people's everyday liv
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GIRIBONE, PIER GIUSEPPE. "Mathematical modeling in Quantitative Finance and Computational Economics." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1046108.

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The first part of my PhD Thesis deals with different Machine Learning techniques mainly applied to solve financial engineering and risk management issues. After a short literary review, every chapter analyzes a particular topic linked to the implementation of these models, showing the most suitable methodologies able to solve it efficiently. The following topics are therefore covered: *) Data Fitting and Regression *) Forecasting *) Classification *) Outlier Detection and Data Quality *) Pricing Every chapter provides the theoretical explanation of the model, the description of the impl
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Hull, Isaiah. "Essays in Computational Macroeconomics and Finance." Thesis, Boston College, 2013. http://hdl.handle.net/2345/bc-ir:104376.

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Thesis advisor: Peter N. Ireland<br>This dissertation examines three topics in computational macroeconomics and finance. The first two chapters are closely linked; and the third chapter covers a separate topic in finance. Throughout the dissertation, I place a strong emphasis on constructing computational tools and modeling devices; and using them in appropriate applications. The first chapter examines how a central banks choice of interest rate rule impacts the rate of mortgage default and welfare. In this chapter, a quantitative equilibrium (QE) model is constructed that incorporates incompl
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Wong, Yiu Kwong. "Application of computational models and qualitative reasoning to economics." Thesis, Heriot-Watt University, 1996. http://hdl.handle.net/10399/688.

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Lupi, Paolo. "The evolution of collusion : three essays in computational economics." Thesis, University of York, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341598.

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Books on the topic "Computational economics"

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Kendrick, David A. Computational economics. Princeton University Press, 2006.

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Ruben, Mercado P., and Amman Hans M, eds. Computational economics. Princeton University Press, 2006.

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Tesfatsion, Leigh. Handbook of Computational Economics: Agent-Based Computational Economics. Elsevier, 2006.

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1959-, Chen Shu-Heng, Jain L. C, and Tai Chung-Ching, eds. Computational economics: A perspective from computational intelligence. Idea Group Pub., 2006.

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M, Amman Hans, Belsley David A, and Pau L. F. 1948-, eds. Computational economics and econometrics. Kluwer Academic Publishers, 1992.

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Amman, Hans M., David A. Belsley, and Louis F. Pau, eds. Computational Economics and Econometrics. Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-3162-9.

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Varian, Hal R., ed. Computational Economics and Finance. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2340-5.

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M, Amman Hans, Kendrick David A, and Rust John 1955-, eds. Handbook of computational economics. Elsevier, 1996.

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Cooper, W. W., and A. B. Whinston, eds. New Directions in Computational Economics. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0770-9.

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1914-, Cooper William W., and Whinston Andrew B, eds. New directions in computational economics. Kluwer Academic Publishers, 1994.

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Book chapters on the topic "Computational economics"

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Chen, Shu-Heng. "Computational evolutionary economics." In Routledge Handbook of Evolutionary Economics. Routledge, 2023. http://dx.doi.org/10.4324/9780429398971-13.

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Andrášik, Ladislav. "Computational Qualitative Economics." In Computational Intelligence in Engineering. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15220-7_20.

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Marino, Domenico. "Regional Economic Policy and Computational Economics." In Neural Nets WIRN Vietri-99. Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0877-1_43.

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Levy, Moshe. "Agent Based Computational Economics." In Computational Complexity. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-1800-9_2.

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Herbert, Ric D. "Computational Programming Environments." In Advances in Computational Economics. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1049-9_10.

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Levy, Moshe. "Agent Based Computational Economics." In Complex Systems in Finance and Econometrics. Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-7701-4_1.

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Levy, Moshe. "Agent-Based Computational Economics." In Encyclopedia of Complexity and Systems Science. Springer New York, 2014. http://dx.doi.org/10.1007/978-3-642-27737-5_6-7.

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Levy, Moshe. "Agent Based Computational Economics." In Encyclopedia of Complexity and Systems Science. Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-30440-3_6.

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Levy, Moshe. "Agent-Based Computational Economics." In Complex Social and Behavioral Systems. Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0368-0_6.

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Chen, Shu-Heng. "Computational Intelligence in Agent-Based Computational Economics." In Studies in Computational Intelligence. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78293-3_13.

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Conference papers on the topic "Computational economics"

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Zhang, Haobo. "Research on Regional Economic Development and Application of Computational Economics Method." In 2024 4th International Conference on Mobile Networks and Wireless Communications (ICMNWC). IEEE, 2024. https://doi.org/10.1109/icmnwc63764.2024.10872237.

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Guo, Yue, and Yi Yang. "EconNLI: Evaluating Large Language Models on Economics Reasoning." In Findings of the Association for Computational Linguistics ACL 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-acl.58.

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Halpern, Joseph Y., Rafael Pass, and Lior Seeman. "Computational Extensive-Form Games." In EC '16: ACM Conference on Economics and Computation. ACM, 2016. http://dx.doi.org/10.1145/2940716.2940733.

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Yang, Jianhong. "Parametricization of Language Economics in Computational Advertising." In ICEIT 2019: 2019 8th International Conference on Educational and Information Technology. ACM, 2019. http://dx.doi.org/10.1145/3318396.3318397.

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Criner, O. "Control systems identification in finance and economics." In COMPUTATIONAL FINANCE 2008. WIT Press, 2008. http://dx.doi.org/10.2495/cf080011.

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Hansen, Kristoffer Arnsfelt, and Troels Bjerre Lund. "Computational Complexity of Proper Equilibrium." In EC '18: ACM Conference on Economics and Computation. ACM, 2018. http://dx.doi.org/10.1145/3219166.3219199.

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Cai, Yang, and Christos Papadimitriou. "Simultaneous bayesian auctions and computational complexity." In EC '14: ACM Conference on Economics and Computation. ACM, 2014. http://dx.doi.org/10.1145/2600057.2602877.

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Echenique, Federico, Daniel Golovin, and Adam Wierman. "A revealed preference approach to computational complexity in economics." In the 12th ACM conference. ACM Press, 2011. http://dx.doi.org/10.1145/1993574.1993591.

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Hu, Chenrui, and Ming Zhang. "Fractional High Frequency Cosine and Sine Higher Order Neural Network for Economics." In 2019 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2019. http://dx.doi.org/10.1109/csci49370.2019.00102.

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Zhang, Hanrui. "Clock Auctions: Allocation-Based Characterization, Computational Complexity, and Economic Efficiency." In EC '25: 26th ACM Conference on Economics and Computation. ACM, 2025. https://doi.org/10.1145/3736252.3742493.

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Reports on the topic "Computational economics"

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Judd, Kenneth. Computational Economics and Economic Theory: Substitutes or Complements. National Bureau of Economic Research, 1997. http://dx.doi.org/10.3386/t0208.

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Hayashi, Tadateru, Sanchita Basu Das, Manbar Singh Khadka, et al. Economic Impact Analysis of Improved Connectivity in Nepal. Asian Development Bank, 2020. http://dx.doi.org/10.22617/wps200312-2.

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This study estimates and analyzes the economic impact of ongoing and future infrastructure development projects in Nepal by using the geographical simulation model developed by the Institute of Developing Economies (IDE-GSM). The IDE-GSM is a computational general equilibrium model based on spatial economics. The simulation analysis reveals that ongoing infrastructure development projects in Nepal benefit the country’s economy, and that the planned connectivity improvement with India will have positive impact with anticipated major shift in mode of transport for trade. The study takes into con
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Alhaji, Mohammed M., Nyaga Robert, and Patrick Forscher. All responses are local. How behavioral systems can enhance global management of the Mpox outbreak. Busara, 2024. http://dx.doi.org/10.62372/yeup3422.

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Mpox represents a dire threat to public health. We believe that behavioral science can play a crucial role in understanding and managing the Mpox threat as effective management of public health requires understanding and managing human behavior. However, behavioral science alone may not be enough: pandemics spread through complex networks of human behavior that we call behavioral systems (Diaz del Valle, Wendel, &amp; Jang, 2023); responding effectively to Mpox may therefore require an interdisciplinary toolkit that integrates qualitative and quantitative methods from across psychology, behavi
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Diakonova, Marina, Corinna Ghirelli, and Juan Quiñónez. Economic Policy Uncertainty in Central America and the Dominican Republic. Banco de España, 2024. http://dx.doi.org/10.53479/37524.

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The advent of Big Data and computational tools has transformed macroeconomic analysis, introducing real-time, high-frequency text-based indicators such as the economic policy uncertainty (EPU) index pioneered by Baker et al. (2016). However, constructing the EPU index for developing economies remains a challenge, mostly due to limited press coverage. Our study focuses on the Central American region, comprising Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama and the Dominican Republic (CAPADR). We construct country-specific EPU indices using a combination of local and regional s
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Mermelstein, Ben, Volker Nocke, Mark Satterthwaite, and Michael Whinston. Internal versus External Growth in Industries with Scale Economies: A Computational Model of Optimal Merger Policy. National Bureau of Economic Research, 2014. http://dx.doi.org/10.3386/w20051.

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Debuque-Gonzales, Margarita, Charlotte Justine Diokno-Sicat, John Paul Corpus, Robert Hector Palomar, Mark Gerald Ruiz, and Ramona Maria Miral. Fiscal Effects of the COVID-19 Pandemic: Assessing Public Debt Sustainability in the Philippines. Philippine Institute for Development Studies, 2022. https://doi.org/10.62986/dp2022.17.

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This paper examines whether the current level of debt in the country, given the national government’s fiscal policy and plans, remains on a sustainable path. By end-2021, a year after the peak of the public health and economic crisis brought about by the COVID-19 pandemic, the country’s debt-to-GDP ratio had already climbed to 60.5 percent, over 20 percentage points above pre-pandemic levels and slightly above the government’s indicative cap. Several empirical exercises were performed in this paper to investigate the country’s fiscal solvency, namely by (1) providing a historical decomposition
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Pearson, Ken, and Channing Arndt. Implementing Systematic Sensitivity Analysis Using GEMPACK. GTAP Technical Paper, 2000. http://dx.doi.org/10.21642/gtap.tp03.

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In economic simulation, results often hinge crucially on values of key exogenous inputs (the values of the parameters of the model and the shocks applied). Computational burden has, in the past, hindered systematic investigation of the impacts of variations in these key exogenous inputs. In this document, practical methods for conducting systematic sensitivity analysis for any model implemented using the GEMPACK suite of software are documented. The procedures described here are based on GTAP Technical Paper number 2 which sets out the theory behind the Gaussian quadrature methods on which the
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Francois, Joseph, and Neil Foster-McGregor. Modeling the Impact of Carbon Border Policies on Emissions, Global Value Chains, and Welfare. Asian Development Bank, 2025. https://doi.org/10.22617/wps250274-2.

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This paper employs a computational general equilibrium model to estimate the impact of border carbon adjustment (BCA) policies on emissions and economic performance. Results suggest that while an expanded scheme of carbon prices and BCAs can reduce emissions, underlying growth trends quickly undo the highest emissions reductions modeled. Results also suggest that in some cases the potential impacts of mitigation actions through domestic and trade-related carbon taxes may fall disproportionately on poorer regions.
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Danylchuk, Hanna B., and Serhiy O. Semerikov. Advances in machine learning for the innovation economy: in the shadow of war. Криворізький державний педагогічний університет, 2023. http://dx.doi.org/10.31812/123456789/7732.

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This preface introduces the selected and revised papers presented at the 10th International Conference on Monitoring, Modeling &amp; Management of Emergent Economy (M3E2 2022), held online in Ukraine, on November 17-18, 2022. The conference aimed to bring together researchers, practitioners, and students from various fields to exchange ideas, share experiences, and discuss challenges and opportunities in applying computational intelligence and data science for the innovation economy. The innovation economy is a term that describes the emerging paradigm of economic development that is driven by
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Korinek, Anton, and Jai Vipra. Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence. Institute for New Economic Thinking Working Paper Series, 2024. http://dx.doi.org/10.36687/inetwp228.

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This paper examines the evolving structure and competition dynamics of the rapidly growing market for foundation models, focusing on large language models (LLMs). We describe the technological characteristics that shape the industry and have given rise to fierce competition among the leading players. The paper analyzes the cost structure of foundation models, emphasizing the importance of key inputs such as computational resources, data, and talent, and identifies significant economies of scale and scope that may create a tendency towards greater market concentration in the future. We explore
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