Relevant bibliographies by topics / Computational economics

Contents

  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: 21 February 2023

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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 (May 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 (June 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 (March 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 (January 30, 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 (June 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 (June 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 (June 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 an empirical analysis of the evolution of the distribution of bank size in the U.S. This paper assesses the statistical support for Zipf's Law (i.e., a power law, or Pareto, distribution with a scaling exponent of α = 2) as an appropriate model for the upper tail of the distribution of U.S. banks. Using detailed balance sheet data for all FDIC regulated banks for the years 1992 through 2011, I find significant departures from Zipf's Law for most measures of bank size inmost years. Although Zipf's Law can be statistically rejected, a power law distribution with α of roughly 1.9 statistically outperforms other plausible heavy-tailed alternative distributions. In my final chapter, which is based on joint work with Dr. David Comerford, I apply computational methods to model the relationship between per capita income and city size. A well-known result from the urban economics literature is that a monopolistically competitive market structure combined with internal increasing returns to scale can be used to generate log-linear relations between income and population. I extend this theoretical framework to allow for a variable elasticity of substitution between factors of production in a manner similar to Zhelobodko et al. (2012). Using data on Metropolitan Statistical Areas (MSAs) in the U.S. I find evidence that supports what Zhelobodko et al. (2012) refer to as "increasing relative love for variety (RLV)." Increasing RLV generates procompetitive effects as market size increases which means that IRS, whilst important for small to medium sized cities, are exhausted as cities become large. This has important policy implications as it suggests that focusing intervention on creating scale for small populations is potentially much more valuable than further investments to increase market size in the largest population centers.
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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 computational model of endogenous network formation for the inter-bank overnight lending market is proposed. The structure of this market emerges from interactions of heterogeneous agents who are endowed with assets, liabilities and take into account investment risk. As all the banks are large and their trading affects the prices of risky assets, the costs of price slippage breaks the symmetry of portfolio problem, making inter-bank borrowing and lending more desirable. The model takes into account three channels of contagion - bankruptcy cascades, common component of risky asset returns and erosion of liquidity. The network formation algorithm outputs the ensemble of optimal transactions, the outcome of the corresponding link formation process is pairwise stable. This framework is next employed to investigate the stability of the endogenously generated banking systems.
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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 be employed as the main ingredients of an agent-based model used to investigate how skills gaps, mismatches and shortages affect equilibrium outcomes. The second chapter designs and tests machine learning algorithms to classify 33 million UK online vacancy postings into STEM and non-STEM jobs based on the keywords collected from the vacancy descriptions and job titles. The goal is to investigate whether jobs in “non-STEM” occupations (e.g. Graphic Designers, Economists) also require and value STEM knowledge and skills (e.g. “Microsoft C#”, “Systems Engineering”), thereby contributing to the debate on whether or not the “STEM pipeline leakage” – the fact that less than half of STEM graduates in the UK work in STEM occupations - should be considered as highly problematic. Chapter 3 relates to empirical growth. It proposes a programming algorithm, called “iterative Fit and Filter” (iFF), that extracts trend growth as a sequence of medium/long term average growth rates, and applies it on a sample of over 150 countries. The paper then develops an econometric framework that relates the conditional probabilities of up and down-shifts in trend growth next year to the country's current characteristics, e.g. the growth environment, level of development, demographics, institutions, etc. Finally, Chapter 4 studies credit risk spillovers in financial networks by modelling default as a multi-stage disease with each credit-rating corresponding to a new infection phase. The paper derives analytical and proposes computer simulation-based indicators of systemic importance and vulnerability, then applies them in the context of the Eurozone sovereign debt crisis.
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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 for gradual emission reduction instead of once-for-all type policies. The solution for the model is obtained using the numerical method introduced in the last essay. The effects of uncertainty and irreversibility on optimal emission reduction policy are investigated. The model is illustrated for greenhouse gas mitigation in the context of climate change problem and some of the model parameters are estimated using a state space model. In the third essay, a unified numerical method is introduced for solving multidimensional singular and impulse control models. The link between regime switching and singular/impulse control problems is established. This link results in a convenient representation of optimality conditions for the numerical method. After solving the optimality conditions at a discrete set of points, an approximate solution can be obtained by solving an extended vertical linear complementarity problem using a variety of techniques. The numerical approach is illustrated with four examples from economics and finance literature.
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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 economics domains by means of learning mechanisms. In this work, a general reinforcement learning framework is developed and realised in a simulation system. This system is used to implement three models of increasing complexity in two different economic domains. One of these domains are iterative games in which agents meet repeatedly and interact. In an experimental labour market, it is shown how statistical discrimination can be generated simply by the learning algorithm used. The results resemble actual patterns of observed human behaviour in laboratory settings. The second model treats strategic network formation. The main contribution here is to show how agent-based modelling helps to analyse non-linearity that is introduced when assumptions of perfect information and full rationality are relaxed. The other domain has a Health Economics background. The aim here is to provide insights of how the approach might be useful in real-world applications. For this, a general model of primary care is developed, and the implications of different consumer behaviour patterns (based on the learning features introduced before) analysed.
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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
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 89-92).
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 lives. In particular, we investigated how people influence the economic growth of cities, as well as how the urban environment affect the decisions made by people. Focusing on the role of cities as centers of consumption, we found that a gravity model based on the availability of a large and diverse pool of amenities accurately explained human flows observed from credit card records. Investigation of the consumption patterns of individuals in Istanbul, Beijing and various metropolitan areas in the United States revealed a positive relationship between the diversity of urban amenities consumed and the city's economic growth. Taking the perspective of cities as hubs for information exchange, we modeled the interactions between individuals in the cities of Beijing and Istanbul using records of their home and work locations and demonstrated how cities which facilitate the mixing of diverse human capital are crucial to the flow of new ideas across communities and their productivity. This contributes to the body of evidence which supports the notion that efficient information exchange is the key factor that drives innovation. To investigate how urban environments shape people's decisions, we study the social influence city dwellers have on each other and showed how face-to-face interaction and information exchange across different residential communities can shape their behavior and increase the similarity of their financial habits and political views in Istanbul.
by Shi Kai Chong.
S.M.
S.M. Massachusetts Institute of Technology, Computation for Design and Optimization Program
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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
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 incomplete markets, aggregate uncertainty, overlapping generations, and realistic mortgage structure. Through a series of counterfactual simulations, five things are demonstrated: 1) nominal interest rate rules that exhibit cyclical behavior increase the average default rate and lower average welfare; 2) welfare can be substantially improved by adopting a modified Taylor rule that stabilizes house prices; 3) a decrease in the length of the interest rate cycle will tend to increase the average default rate; 4) if the business and housing cycles are not aligned, then aggressive inflation targeting will tend to increase the mortgage default rate; and 5) placing a legal cap on loan-to-value ratios will lower the average default rate and lessen the intensity of extreme events. In addition to these findings, this paper also incorporates an important mechanism for default, which had not pre- viously been included in the QE literature: default spikes happen when income falls and home equity is degraded at the same time. The paper concludes with a policy recommendation for central banks: if they wish to crises where many households default simultaneously, they should either adopt a rule that generates interest rates with slow-moving cycles or use a modified Taylor rule that also targets house price growth. The second chapter generalizes the solution method used in the first and compares it to more common techniques used in the computational macroeconomics literature, including the parameterized expectations approach (PEA), projection methods, and value function iteration. In particular, this chapter compares the speed and accuracy of the aforementioned modifications to an alternative method that was introduced separately by Judd (1998), Sutton and Barto (1998), and Van Roy et al. (1997), but was not developed into a general solution method until Powell (2007) introduced it to the Operations Research literature. This approach involves rewriting the Bellman equation in terms of the post-decision state variables, rather than the pre-decision state variables, as is done in standard dynamic programming applications in economics. I show that this approach yields considerable performance benefits over common global solution methods when the state space is large; and has the added benefit of not forcing modelers to assume a data generating process for shocks. In addition to this, I construct two new algorithms that take advantage of this approach to solve heterogenous agent models. Finally, the third chapter imports the SIR model from mathematical epidemiol- ogy; and uses it to construct a model of financial epidemics. In particular, the paper demonstrates how the SIR model can be microfounded in an economic context to make predictions about financial epidemics, such as the spread of asset-backed securities (ABS) and exchange-traded funds (ETFs), the proliferation of zombie financial institutions, and the expansion of financial bubbles and mean-reverting fads. The paper proceeds by developing the 1-host SIR model for economic and financial contexts; and then moves on to demonstrate how to work with the multi-host version of the model. In addition to showing how the SIR framework can be used to model economic interactions, it will also: 1) show how it can be simulated; 2) use it to develop and estimate a sufficient statistic for the spread of a financial epidemic; and 3) show how policymakers can impose the financial analog of herd immunity-that is, prevent the spread of a financial epidemic without completely banning the asset or behavior associated with the epidemic. Importantly, the paper will focus on developing a neutral framework to describe financial epidemics that can be either bad or good. That is, the general framework can be applied to epidemics that constitute a mean-reverting fad or an informational bubble, but ultimately yield little value and shrink in importance; or epidemics that are long-lasting and yield a new financial in- strument that generates permanent efficiency gains or previously unrealized hedging opportunities
Thesis (PhD) — Boston College, 2013
Submitted to: Boston College. Graduate School of Arts and Sciences
Discipline: Economics
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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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Gao, Lili. "Applications of MachLearning and Computational Linguistics in Financial Economics." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/815.

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In the world of the financial economics, we have abundant text data. Articles in the Wall Street Journal and on Bloomberg Terminals, corporate SEC filings, earnings-call transcripts, social media messages, etc. all contain ample information about financial markets and investor behaviors. Extracting meaningful signals from unstructured and high dimensional text data is not an easy task. However, with the development of machine learning and computational linguistic techniques, processing and statistically analyzing textual documents tasks can be accomplished, and many applications of statistical text analysis in social sciences have proven to be successful.
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Books on the topic "Computational economics"

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

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Kendrick, David A. Computational economics. Princeton, N.J: Princeton University Press, 2006.

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Tesfatsion, Leigh. Handbook of Computational Economics: Agent-Based Computational Economics. Burlington: 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. Hershey PA: Idea Group Pub., 2006.

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

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Amman, Hans M., David A. Belsley, and Louis F. Pau, eds. Computational Economics and Econometrics. Dordrecht: 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. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2340-5.

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

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Dadkhah, Kamran. Foundations of mathematical & computational economics. Mason, OH: Thomson South-Western, 2007.

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

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Book chapters on the topic "Computational economics"

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Andrášik, Ladislav. "Computational Qualitative Economics." In Computational Intelligence in Engineering, 247–61. Berlin, Heidelberg: 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, 376–90. London: 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, 18–38. New York, NY: 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, 271–96. Boston, MA: 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, 1–21. New York, NY: 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, 1–30. New York, NY: 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, 92–112. New York, NY: 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, 825–49. New York, NY: 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, 517–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78293-3_13.

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Dudek, Gregor. "Computational Evaluation." In Lecture Notes in Economics and Mathematical Systems, 165–213. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-05443-7_7.

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Conference papers on the topic "Computational economics"

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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. New York, NY, USA: 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. New York, NY, USA: 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. Southampton, UK: 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. New York, NY, USA: 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. New York, NY, USA: 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. New York, New York, USA: 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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SANDHOLM, THOMAS, and KEVIN LAI. "EVALUATING DEMAND PREDICTION TECHNIQUES FOR COMPUTATIONAL MARKETS." In Proceedings of the 3rd International Workshop on Grid Economics and Business Models. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812773470_0001.

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Carroll, Christopher, Alexander Kaufman, Jacqueline Kazil, Nathan Palmer, and Matthew White. "The Econ-ARK and HARK: Open Source Tools for Computational Economics." In Python in Science Conference. SciPy, 2018. http://dx.doi.org/10.25080/majora-4af1f417-004.

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Cai, Rangjia, and Haiying Ma. "Thoughts on the Teaching and Methods of Agent-based Computational Economics." In CIPAE 2021: 2021 2nd International Conference on Computers, Information Processing and Advanced Education. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3456887.3456907.

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Reports on the topic "Computational economics"

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

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Hayashi, Tadateru, Sanchita Basu Das, Manbar Singh Khadka, Ikumo Isono, Souknilanh Keola, Kenmei Tsubota, and Kazunobu Hayakawa. Economic Impact Analysis of Improved Connectivity in Nepal. Asian Development Bank, November 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 consideration efforts by the Government of Nepal to promote and strengthen international connectivity under the South Asia Subregional Economic Cooperation framework.
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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. Cambridge, MA: National Bureau of Economic Research, April 2014. http://dx.doi.org/10.3386/w20051.

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Moreno Pérez, Carlos, and Marco Minozzo. “Making Text Talk”: The Minutes of the Central Bank of Brazil and the Real Economy. Madrid: Banco de España, November 2022. http://dx.doi.org/10.53479/23646.

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This paper investigates the relationship between the views expressed in the minutes of the meetings of the Central Bank of Brazil’s Monetary Policy Committee (COPOM) and the real economy. It applies various computational linguistic machine learning algorithms to construct measures of the minutes of the COPOM. First, we create measures of the content of the paragraphs of the minutes using Latent Dirichlet Allocation (LDA). Second, we build an uncertainty index for the minutes using Word Embedding and K-Means. Then, we combine these indices to create two topic-uncertainty indices. The first one is constructed from paragraphs with a higher probability of topics related to “general economic conditions”. The second topic-uncertainty index is constructed from paragraphs that have a higher probability of topics related to “inflation” and the “monetary policy discussion”. Finally, we employ a structural VAR model to explore the lasting effects of these uncertainty indices on certain Brazilian macroeconomic variables. Our results show that greater uncertainty leads to a decline in inflation, the exchange rate, industrial production and retail trade in the period from January 2000 to July 2019.
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Mehmood, Hamid, Surya Karthik Mukkavilli, Ingmar Weber, Atsushi Koshio, Chinaporn Meechaiya, Thanapon Piman, Kenneth Mubea, Cecilia Tortajada, Kimberly Mahadeo, and Danielle Liao. Strategic Foresight to Applications of Artificial Intelligence to Achieve Water-related Sustainable Development Goals. United Nations University Institute for Water, Environment and Health, April 2020. http://dx.doi.org/10.53328/lotc2968.

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The report recommends that: 1) Policymakers should conduct holistic assessments of social, economic, and cultural factors before AI adoption in the water sector, as prospective applications of AI are case- specific. It is also important to conduct baseline studies to measure the implementation capacity, return on investment, and impact of intervention. 2) To ensure positive development outcomes, policies regarding the use of AI for water-related challenges should be coupled with capacity and infrastructure development policies. Capacity development policies need to address the AI and Information and Communications Technology (ICT) needs for the AI-related skill development of all water-related stakeholders. Infrastructure development policies should address the underlying requirements of computation, energy, data generation, and storage. The sequencing of these policies is critical. 3) To mitigate the predicted job displacement that will accompany AI-led innovation in the water sector, policies should direct investments towards enabling a skilled workforce by developing water sector-related education at all levels. This skilled workforce should be strategically placed to offset dependency on the private sector. 4) Water-related challenges are cross-cutting running from grassroots to the global level and require an understanding of the water ecosystem. It is important for countries connected by major rivers and watersheds to collaborate in developing policies that advance the use of AI to address common water-related challenges. 5) A council or agency with representation from all stakeholders should be constituted at the national level, to allow for the successful adoption of AI by water agencies. This council or agency should be tasked with the development of policies, guidelines, and codes of conduct for the adoption of AI in the water-sector. These key policy recommendations can be used as primary guidelines for the development of strategies and plans to use AI to help achieve water-related SDGs.
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Wu, Yingjie, Selim Gunay, and Khalid Mosalam. Hybrid Simulations for the Seismic Evaluation of Resilient Highway Bridge Systems. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, November 2020. http://dx.doi.org/10.55461/ytgv8834.

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Bridges often serve as key links in local and national transportation networks. Bridge closures can result in severe costs, not only in the form of repair or replacement, but also in the form of economic losses related to medium- and long-term interruption of businesses and disruption to surrounding communities. In addition, continuous functionality of bridges is very important after any seismic event for emergency response and recovery purposes. Considering the importance of these structures, the associated structural design philosophy is shifting from collapse prevention to maintaining functionality in the aftermath of moderate to strong earthquakes, referred to as “resiliency” in earthquake engineering research. Moreover, the associated construction philosophy is being modernized with the utilization of accelerated bridge construction (ABC) techniques, which strive to reduce the impact of construction on traffic, society, economy and on-site safety. This report presents two bridge systems that target the aforementioned issues. A study that combined numerical and experimental research was undertaken to characterize the seismic performance of these bridge systems. The first part of the study focuses on the structural system-level response of highway bridges that incorporate a class of innovative connecting devices called the “V-connector,”, which can be used to connect two components in a structural system, e.g., the column and the bridge deck, or the column and its foundation. This device, designed by ACII, Inc., results in an isolation surface at the connection plane via a connector rod placed in a V-shaped tube that is embedded into the concrete. Energy dissipation is provided by friction between a special washer located around the V-shaped tube and a top plate. Because of the period elongation due to the isolation layer and the limited amount of force transferred by the relatively flexible connector rod, bridge columns are protected from experiencing damage, thus leading to improved seismic behavior. The V-connector system also facilitates the ABC by allowing on-site assembly of prefabricated structural parts including those of the V-connector. A single-column, two-span highway bridge located in Northern California was used for the proof-of-concept of the proposed V-connector protective system. The V-connector was designed to result in an elastic bridge response based on nonlinear dynamic analyses of the bridge model with the V-connector. Accordingly, a one-third scale V-connector was fabricated based on a set of selected design parameters. A quasi-static cyclic test was first conducted to characterize the force-displacement relationship of the V-connector, followed by a hybrid simulation (HS) test in the longitudinal direction of the bridge to verify the intended linear elastic response of the bridge system. In the HS test, all bridge components were analytically modeled except for the V-connector, which was simulated as the experimental substructure in a specially designed and constructed test setup. Linear elastic bridge response was confirmed according to the HS results. The response of the bridge with the V-connector was compared against that of the as-built bridge without the V-connector, which experienced significant column damage. These results justified the effectiveness of this innovative device. The second part of the study presents the HS test conducted on a one-third scale two-column bridge bent with self-centering columns (broadly defined as “resilient columns” in this study) to reduce (or ultimately eliminate) any residual drifts. The comparison of the HS test with a previously conducted shaking table test on an identical bridge bent is one of the highlights of this study. The concept of resiliency was incorporated in the design of the bridge bent columns characterized by a well-balanced combination of self-centering, rocking, and energy-dissipating mechanisms. This combination is expected to lead to minimum damage and low levels of residual drifts. The ABC is achieved by utilizing precast columns and end members (cap beam and foundation) through an innovative socket connection. In order to conduct the HS test, a new hybrid simulation system (HSS) was developed, utilizing commonly available software and hardware components in most structural laboratories including: a computational platform using Matlab/Simulink [MathWorks 2015], an interface hardware/software platform dSPACE [2017], and MTS controllers and data acquisition (DAQ) system for the utilized actuators and sensors. Proper operation of the HSS was verified using a trial run without the test specimen before the actual HS test. In the conducted HS test, the two-column bridge bent was simulated as the experimental substructure while modeling the horizontal and vertical inertia masses and corresponding mass proportional damping in the computer. The same ground motions from the shaking table test, consisting of one horizontal component and the vertical component, were applied as input excitations to the equations of motion in the HS. Good matching was obtained between the shaking table and the HS test results, demonstrating the appropriateness of the defined governing equations of motion and the employed damping model, in addition to the reliability of the developed HSS with minimum simulation errors. The small residual drifts and the minimum level of structural damage at large peak drift levels demonstrated the superior seismic response of the innovative design of the bridge bent with self-centering columns. The reliability of the developed HS approach motivated performing a follow-up HS study focusing on the transverse direction of the bridge, where the entire two-span bridge deck and its abutments represented the computational substructure, while the two-column bridge bent was the physical substructure. This investigation was effective in shedding light on the system-level performance of the entire bridge system that incorporated innovative bridge bent design beyond what can be achieved via shaking table tests, which are usually limited by large-scale bridge system testing capacities.
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Or, Etti, David Galbraith, and Anne Fennell. Exploring mechanisms involved in grape bud dormancy: Large-scale analysis of expression reprogramming following controlled dormancy induction and dormancy release. United States Department of Agriculture, December 2002. http://dx.doi.org/10.32747/2002.7587232.bard.

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The timing of dormancy induction and release is very important to the economic production of table grape. Advances in manipulation of dormancy induction and dormancy release are dependent on the establishment of a comprehensive understanding of biological mechanisms involved in bud dormancy. To gain insight into these mechanisms we initiated the research that had two main objectives: A. Analyzing the expression profiles of large subsets of genes, following controlled dormancy induction and dormancy release, and assessing the role of known metabolic pathways, known regulatory genes and novel sequences involved in these processes B. Comparing expression profiles following the perception of various artificial as well as natural signals known to induce dormancy release, and searching for gene showing similar expression patterns, as candidates for further study of pathways having potential to play a central role in dormancy release. We first created targeted EST collections from V. vinifera and V. riparia mature buds. Clones were randomly selected from cDNA libraries prepared following controlled dormancy release and controlled dormancy induction and from respective controls. The entire collection (7920 vinifera and 1194 riparia clones) was sequenced and subjected to bioinformatics analysis, including clustering, annotations and GO classifications. PCR products from the entire collection were used for printing of cDNA microarrays. Bud tissue in general, and the dormant bud in particular, are under-represented within the grape EST database. Accordingly, 59% of the our vinifera EST collection, composed of 5516 unigenes, are not included within the current Vitis TIGR collection and about 22% of these transcripts bear no resemblance to any known plant transcript, corroborating the current need for our targeted EST collection and the bud specific cDNA array. Analysis of the V. riparia sequences yielded 814 unigenes, of which 140 are unique (keilin et al., manuscript, Appendix B). Results from computational expression profiling of the vinifera collection suggest that oxidative stress, calcium signaling, intracellular vesicle trafficking and anaerobic mode of carbohydrate metabolism play a role in the regulation and execution of grape-bud dormancy release. A comprehensive analysis confirmed the induction of transcription from several calcium–signaling related genes following HC treatment, and detected an inhibiting effect of calcium channel blocker and calcium chelator on HC-induced and chilling-induced bud break. It also detected the existence of HC-induced and calcium dependent protein phosphorylation activity. These data suggest, for the first time, that calcium signaling is involved in the mechanism of dormancy release (Pang et al., in preparation). We compared the effects of heat shock (HS) to those detected in buds following HC application and found that HS lead to earlier and higher bud break. We also demonstrated similar temporary reduction in catalase expression and temporary induction of ascorbate peroxidase, glutathione reductase, thioredoxin and glutathione S transferase expression following both treatments. These findings further support the assumption that temporary oxidative stress is part of the mechanism leading to bud break. The temporary induction of sucrose syntase, pyruvate decarboxylase and alcohol dehydrogenase indicate that temporary respiratory stress is developed and suggest that mitochondrial function may be of central importance for that mechanism. These finding, suggesting triggering of identical mechanisms by HS and HC, justified the comparison of expression profiles of HC and HS treated buds, as a tool for the identification of pathways with a central role in dormancy release (Halaly et al., in preparation). RNA samples from buds treated with HS, HC and water were hybridized with the cDNA arrays in an interconnected loop design. Differentially expressed genes from the were selected using R-language package from Bioconductor project called LIMMA and clones showing a significant change following both HS and HC treatments, compared to control, were selected for further analysis. A total of 1541 clones show significant induction, of which 37% have no hit or unknown function and the rest represent 661 genes with identified function. Similarly, out of 1452 clones showing significant reduction, only 53% of the clones have identified function and they represent 573 genes. The 661 induced genes are involved in 445 different molecular functions. About 90% of those functions were classified to 20 categories based on careful survey of the literature. Among other things, it appears that carbohydrate metabolism and mitochondrial function may be of central importance in the mechanism of dormancy release and studies in this direction are ongoing. Analysis of the reduced function is ongoing (Appendix A). A second set of hybridizations was carried out with RNA samples from buds exposed to short photoperiod, leading to induction of bud dormancy, and long photoperiod treatment, as control. Analysis indicated that 42 genes were significant difference between LD and SD and 11 of these were unique.
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COMPLETE SET ROTATION-LIFTING CONSTRUCTION TECHNOLOGY FOR FREE-FORM SURFACE ROOF STRUCTURES WITH LARGE ELEVATION DIFFERENCE. The Hong Kong Institute of Steel Construction, August 2022. http://dx.doi.org/10.18057/icass2020.p.618.

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A complete set rotation-lifting construction technology for free-form surface roof structures with large elevation difference is in this paper. Six principles for this construction technology are proposed. Based on optimization theory, a digital analysis method is developed for calculating the exact solution of lying posture and rotation axis. Theoretical algorithm of multi-lifting point synchronous lifting control technology with different lifting speed and the same lifting ratio is proposed, and a control program is developed. Structural configuration of key construction stage is inspected and monitored by applying the digital system. The system compares computational analysis results with the real-time structure configuration, and the result is provided for construction control. The construction technology has been successfully applied in the Hangzhou West Railway Station project, which has good economic and social benefits.
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SECOND-ORDER DIRECT ANALYSIS FOR STEEL H-PILES ACCOUNTING FOR POST-DRIVING RESIDUAL STRESSES. The Hong Kong Institute of Steel Construction, August 2022. http://dx.doi.org/10.18057/icass2020.p.349.

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"Driven steel H-piles are extensively adopted in engineering practice due to their convenience and efficiency in both economic and construction. The post-driving residual stress, a compressive axial stress distributed along the pile induced by the pile installation, might significantly deteriorate the pile bearing capacity. Thus, a large enough factor of safety is adopted in the traditional analysis to cover the influence caused by the post-driving residual stress. However, it sometimes leads to a large waste in costs and materials. Thus, the present study adopted the second-order analysis, a modern simulationbased design method, for the design of the driven steel H-pile. A robust and efficient finite element formula is necessary to conduct the second-order design method in practice. Hence, a new Line-Finite Element (LFE) formula is proposed in this paper. The developed LFE directly captures all the crucial factors in the analysis of the driven steel H pile, including the nonlinear Soil-Structure Interaction (SSI) and the post-driving residual stress. A validation example is presented at the end of this paper, which illustrates the accuracy and the computational efficiency of the proposed LFE formula."
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10

African Open Science Platform Part 1: Landscape Study. Academy of Science of South Africa (ASSAf), 2019. http://dx.doi.org/10.17159/assaf.2019/0047.

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This report maps the African landscape of Open Science – with a focus on Open Data as a sub-set of Open Science. Data to inform the landscape study were collected through a variety of methods, including surveys, desk research, engagement with a community of practice, networking with stakeholders, participation in conferences, case study presentations, and workshops hosted. Although the majority of African countries (35 of 54) demonstrates commitment to science through its investment in research and development (R&D), academies of science, ministries of science and technology, policies, recognition of research, and participation in the Science Granting Councils Initiative (SGCI), the following countries demonstrate the highest commitment and political willingness to invest in science: Botswana, Ethiopia, Kenya, Senegal, South Africa, Tanzania, and Uganda. In addition to existing policies in Science, Technology and Innovation (STI), the following countries have made progress towards Open Data policies: Botswana, Kenya, Madagascar, Mauritius, South Africa and Uganda. Only two African countries (Kenya and South Africa) at this stage contribute 0.8% of its GDP (Gross Domestic Product) to R&D (Research and Development), which is the closest to the AU’s (African Union’s) suggested 1%. Countries such as Lesotho and Madagascar ranked as 0%, while the R&D expenditure for 24 African countries is unknown. In addition to this, science globally has become fully dependent on stable ICT (Information and Communication Technologies) infrastructure, which includes connectivity/bandwidth, high performance computing facilities and data services. This is especially applicable since countries globally are finding themselves in the midst of the 4th Industrial Revolution (4IR), which is not only “about” data, but which “is” data. According to an article1 by Alan Marcus (2015) (Senior Director, Head of Information Technology and Telecommunications Industries, World Economic Forum), “At its core, data represents a post-industrial opportunity. Its uses have unprecedented complexity, velocity and global reach. As digital communications become ubiquitous, data will rule in a world where nearly everyone and everything is connected in real time. That will require a highly reliable, secure and available infrastructure at its core, and innovation at the edge.” Every industry is affected as part of this revolution – also science. An important component of the digital transformation is “trust” – people must be able to trust that governments and all other industries (including the science sector), adequately handle and protect their data. This requires accountability on a global level, and digital industries must embrace the change and go for a higher standard of protection. “This will reassure consumers and citizens, benefitting the whole digital economy”, says Marcus. A stable and secure information and communication technologies (ICT) infrastructure – currently provided by the National Research and Education Networks (NRENs) – is key to advance collaboration in science. The AfricaConnect2 project (AfricaConnect (2012–2014) and AfricaConnect2 (2016–2018)) through establishing connectivity between National Research and Education Networks (NRENs), is planning to roll out AfricaConnect3 by the end of 2019. The concern however is that selected African governments (with the exception of a few countries such as South Africa, Mozambique, Ethiopia and others) have low awareness of the impact the Internet has today on all societal levels, how much ICT (and the 4th Industrial Revolution) have affected research, and the added value an NREN can bring to higher education and research in addressing the respective needs, which is far more complex than simply providing connectivity. Apart from more commitment and investment in R&D, African governments – to become and remain part of the 4th Industrial Revolution – have no option other than to acknowledge and commit to the role NRENs play in advancing science towards addressing the SDG (Sustainable Development Goals). For successful collaboration and direction, it is fundamental that policies within one country are aligned with one another. Alignment on continental level is crucial for the future Pan-African African Open Science Platform to be successful. Both the HIPSSA ((Harmonization of ICT Policies in Sub-Saharan Africa)3 project and WATRA (the West Africa Telecommunications Regulators Assembly)4, have made progress towards the regulation of the telecom sector, and in particular of bottlenecks which curb the development of competition among ISPs. A study under HIPSSA identified potential bottlenecks in access at an affordable price to the international capacity of submarine cables and suggested means and tools used by regulators to remedy them. Work on the recommended measures and making them operational continues in collaboration with WATRA. In addition to sufficient bandwidth and connectivity, high-performance computing facilities and services in support of data sharing are also required. The South African National Integrated Cyberinfrastructure System5 (NICIS) has made great progress in planning and setting up a cyberinfrastructure ecosystem in support of collaborative science and data sharing. The regional Southern African Development Community6 (SADC) Cyber-infrastructure Framework provides a valuable roadmap towards high-speed Internet, developing human capacity and skills in ICT technologies, high- performance computing and more. The following countries have been identified as having high-performance computing facilities, some as a result of the Square Kilometre Array7 (SKA) partnership: Botswana, Ghana, Kenya, Madagascar, Mozambique, Mauritius, Namibia, South Africa, Tunisia, and Zambia. More and more NRENs – especially the Level 6 NRENs 8 (Algeria, Egypt, Kenya, South Africa, and recently Zambia) – are exploring offering additional services; also in support of data sharing and transfer. The following NRENs already allow for running data-intensive applications and sharing of high-end computing assets, bio-modelling and computation on high-performance/ supercomputers: KENET (Kenya), TENET (South Africa), RENU (Uganda), ZAMREN (Zambia), EUN (Egypt) and ARN (Algeria). Fifteen higher education training institutions from eight African countries (Botswana, Benin, Kenya, Nigeria, Rwanda, South Africa, Sudan, and Tanzania) have been identified as offering formal courses on data science. In addition to formal degrees, a number of international short courses have been developed and free international online courses are also available as an option to build capacity and integrate as part of curricula. The small number of higher education or research intensive institutions offering data science is however insufficient, and there is a desperate need for more training in data science. The CODATA-RDA Schools of Research Data Science aim at addressing the continental need for foundational data skills across all disciplines, along with training conducted by The Carpentries 9 programme (specifically Data Carpentry 10 ). Thus far, CODATA-RDA schools in collaboration with AOSP, integrating content from Data Carpentry, were presented in Rwanda (in 2018), and during17-29 June 2019, in Ethiopia. Awareness regarding Open Science (including Open Data) is evident through the 12 Open Science-related Open Access/Open Data/Open Science declarations and agreements endorsed or signed by African governments; 200 Open Access journals from Africa registered on the Directory of Open Access Journals (DOAJ); 174 Open Access institutional research repositories registered on openDOAR (Directory of Open Access Repositories); 33 Open Access/Open Science policies registered on ROARMAP (Registry of Open Access Repository Mandates and Policies); 24 data repositories registered with the Registry of Data Repositories (re3data.org) (although the pilot project identified 66 research data repositories); and one data repository assigned the CoreTrustSeal. Although this is a start, far more needs to be done to align African data curation and research practices with global standards. Funding to conduct research remains a challenge. African researchers mostly fund their own research, and there are little incentives for them to make their research and accompanying data sets openly accessible. Funding and peer recognition, along with an enabling research environment conducive for research, are regarded as major incentives. The landscape report concludes with a number of concerns towards sharing research data openly, as well as challenges in terms of Open Data policy, ICT infrastructure supportive of data sharing, capacity building, lack of skills, and the need for incentives. Although great progress has been made in terms of Open Science and Open Data practices, more awareness needs to be created and further advocacy efforts are required for buy-in from African governments. A federated African Open Science Platform (AOSP) will not only encourage more collaboration among researchers in addressing the SDGs, but it will also benefit the many stakeholders identified as part of the pilot phase. The time is now, for governments in Africa, to acknowledge the important role of science in general, but specifically Open Science and Open Data, through developing and aligning the relevant policies, investing in an ICT infrastructure conducive for data sharing through committing funding to making NRENs financially sustainable, incentivising open research practices by scientists, and creating opportunities for more scientists and stakeholders across all disciplines to be trained in data management.
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