by Robert Stephen DiMatteo.; Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and, (S.M.)--Massachusetts Institute of Technology, Technology and Policy Program, 1996.; Includes bibliographical references (p. 159-168).

What are the underlying rationales for industrial policy? Does empirical evidence support the use of industrial policy for correcting market failures that plague the process of industrialization? This article addresses these questions through a critical survey of the analytical literature on industrial policy. It also reviews some recent industry successes and argues that public interventions have played only a limited role. Moreover, the recent ascendance and dominance of international production networks in the sectors in which developing countries once had considerable success implies a further limitation on the potential role of industrial policies as traditionally understood. Overall, there appears to be little empirical support for an activist government policy even though market failures exist that can, in principle, justify the use of industrial policy.

This paper evaluates a youth internship program in the Republic of Yemen that provided firms with a 50 percent subsidy to hire recent graduates of universities and vocational schools. The first round of the program took place in 2014 and required both firms and youth to apply for the program. The paper examines the demand for such a program, and finds that in the context of an economy facing substantial political and economic uncertainty, it appears there is an oversupply of graduates in science, technology, engineering, and mathematics, and a relative undersupply of graduates in marketing and business. Conditional on the types of graduates firms were looking to hire as interns, applicants were then randomly chosen for the program. Receiving an internship resulted in an almost doubling of work experience in 2014, and a 73 percent increase in income during this period compared with the control group. A short-term follow-up survey conducted just as civil conflict was breaking out shows that internship recipients had better employment outcomes than the control group in the first five months after the program ended.

Many complex decision making problems like scheduling in manufacturing systems, portfolio management in finance, admission control in communication networks etc., with clear and precise objectives, can be formulated as stochastic dynamic programming problems in which the objective of decision making is to maximize a single "overall" reward. In these formulations, finding an optimal decision policy involves computing a certain "value function" which assigns to each state the optimal reward one would obtain if the system was started from that state. This function then naturally prescribes the optimal policy, which is to take decisions that drive the system to states with maximum value. For many practical problems, the computation of the exact value function is intractable, analytically and numerically, due to the enormous size of the state space. Therefore one has to resort to one of the following approximation methods to find a good sub-optimal policy: (1) Approximate the value function. (2) Restrict the search for a good policy to a smaller family of policies. In this thesis, we propose and study actor-critic algorithms which combine the above two approaches with simulation to find the best policy among a parameterized class of policies. Actor-critic algorithms have two learning units: an actor and a critic. An actor is a decision maker with a tunable parameter. A critic is a function approximator. The critic tries to approximate the value function of the policy used by the actor...

Since genetic algorithm was proposed by John Holland (Holland J. H., 1975) in the early 1970s, the study of evolutionary algorithm has emerged as a popular research field (Civicioglu & Besdok, 2013). Researchers from various scientific and engineering disciplines have been digging into this field, exploring the unique power of evolutionary algorithms (Hadka & Reed, 2013). Many applications have been successfully proposed in the past twenty years. For example, mechanical design (Lampinen & Zelinka, 1999), electromagnetic optimization (Rahmat-Samii & Michielssen, 1999), environmental protection (Bertini, Felice, Moretti, & Pizzuti, 2010), finance (Larkin & Ryan, 2010), musical orchestration (Esling, Carpentier, & Agon, 2010), pipe routing (Furuholmen, Glette, Hovin, & Torresen, 2010), and nuclear reactor core design (Sacco, Henderson, Rios-Coelho, Ali, & Pereira, 2009). In particular, its function optimization capability was highlighted (Goldberg & Richardson, 1987) because of its high adaptability to different function landscapes, to which we cannot apply traditional optimization techniques (Wong, Leung, & Wong, 2009). Here we review the applications of evolutionary algorithms in bioinformatics.

Lognormal random variables appear naturally in many engineering disciplines, including wireless communications, reliability theory, and finance. So, too, does the sum of (correlated) lognormal random variables. Unfortunately, no closed form probability distribution exists for such a sum, and it requires approximation. Some approximation methods date back over 80 years and most take one of two approaches, either: 1) an approximate probability distribution is derived mathematically, or 2) the sum is approximated by a single lognormal random variable. In this research, we take the latter approach and review a fairly recent approximation procedure proposed by Mehta, Wu, Molisch, and Zhang (2007), then implement it using C++. The result is applied to a discrete time model commonly encountered within the field of financial economics.; Comment: Fully documented source code is included

This paper describes the rationale, curriculum and subject matter of a new MSc module being taught on an MSc Finance and Information Management course at the University of Wales Institute in Cardiff. Academic research on spreadsheet risks now has some penetration in academic literature and there is a growing body of knowledge on the subjects of spreadsheet error, human factors, spreadsheet engineering, "best practice", spreadsheet risk management and various techniques used to mitigate spreadsheet errors. This new MSc module in End User Computing Risk Management is an attempt to pull all of this research and practitioner experience together to arm the next generation of finance spreadsheet champions with the relevant knowledge, techniques and critical perspective on an emerging discipline.; Comment: 9 Pages, 1 Table

Spreadsheets are ubiquitous, heavily relied on throughout vast swathes of finance, commerce, industry, academia and Government. They are also acknowledged to be extraordinarily and unacceptably prone to error. If these two points are accepted, it has to follow that their uncontrolled use has the potential to inflict considerable damage. One approach to controlling such error should be to define as "good practice" a set of characteristics that a spreadsheet must possess and as "bad practice" another set that it must avoid. Defining such characteristics should, in principle, perfectly do-able. However, being able to say with authority at a definite moment that any particular spreadsheet complies with these characteristics is very much more difficult. The author asserts that the use of automated spreadsheet development could markedly help in ensuring and demonstrating such compliance.; Comment: 8 Pages

Recognizing that the use of spreadsheets within finance will likely not subside in the near future, this paper discusses a major barrier that is preventing more organizations from adopting enterprise spreadsheet management programs. But even without a corporate mandated effort to improve spreadsheet controls, finance functions can still take simple yet effective steps to start managing the risk of errors in key spreadsheets by strategically selecting controls that complement existing user practice; Comment: 8 Pages, 4 Tables; Proc. European Spreadsheet Risks Int. Grp. (EuSpRIG) 2011 ISBN 978-0-9566256-9-4

The use of spreadsheets is widespread. Be it in business, finance, engineering or other areas, spreadsheets are created for their flexibility and ease to quickly model a problem. Very often they evolve from simple prototypes to implementations of crucial business logic. Spreadsheets that play a crucial role in an organization will naturally have a long lifespan and will be maintained and evolved by several people. Therefore, it is important not only to look at their reliability, i.e., how well is the intended functionality implemented, but also at their maintainability, i.e., how easy it is to diagnose a spreadsheet for deficiencies and modify it without degrading its quality. In this position paper we argue for the need to create a model to estimate the maintainability of a spreadsheet based on (automated) measurement. We propose to do so by applying a structured methodology that has already shown its value in the estimation of maintainability of software products. We also argue for the creation of a curated, community-contributed repository of spreadsheets.; Comment: 7 Pages, 1 Figure; Proc. European Spreadsheet Risks Int. Grp. (EuSpRIG) 2011 ISBN 978-0-9566256-9-4

We consider the challenge of creating guidelines to evaluate the quality of a spreadsheet model. We suggest four principles. First, state the domain-the spreadsheets to which the guidelines apply. Second, distinguish between the process by which a spreadsheet is constructed from the resulting spreadsheet artifact. Third, guidelines should be written in terms of the artifact, independent of the process. Fourth, the meaning of "quality" must be defined. We illustrate these principles with an example. We define the domain of "analytical spreadsheet models", which are used in business, finance, engineering, and science. We propose for discussion a framework and terminology for evaluating the quality of analytical spreadsheet models. This framework categorizes and generalizes the findings of previous work on the more narrow domain of financial spreadsheet models. We suggest that the ultimate goal is a set of guidelines for an evaluator, and a checklist for a developer.; Comment: Proc. European Spreadsheet Risks Int. Grp. (EuSpRIG) 2011 ISBN 978-0-9566256-9-4

The proliferation of social media such as real time microblogging and online reputation systems facilitate real time sensing of social patterns and behavior. In the last decade, sensing and decision making in social networks have witnessed significant progress in the electrical engineering, computer science, economics, finance, and sociology research communities. Research in this area involves the interaction of dynamic random graphs, socio-economic analysis, and statistical inference algorithms. This monograph provides a survey, tutorial development, and discussion of four highly stylized examples: social learning for interactive sensing; tracking the degree distribution of social networks; sensing and information diffusion; and coordination of decision making via game-theoretic learning. Each of the four examples is motivated by practical examples, and comprises of a literature survey together with careful problem formulation and mathematical analysis. Despite being highly stylized, these examples provide a rich variety of models, algorithms and analysis tools that are readily accessible to a signal processing, control/systems theory, and applied mathematics audience.; Comment: Foundations and Trends in Signal Processing, Now Publishers...

Business specifications are essential to describe and understand businesses (and, in particular, business rules) independently of any computing systems used for their possible automation. They have to express this understanding in a clear, precise, and explicit way, in order to act as a common ground between business domain experts and software developers. They also provide the basis for reuse of concepts and constructs ("patterns") common to all - from finance to telecommunications -, or a large number of, businesses, and in doing so save intellectual effort, time and money. Moreover, these patterns substantially ease the elicitation and validation of business specifications during walkthroughs with business customers, and support separation of concerns using viewpoints.; Comment: 21 pages, 0 figures

Financial statements contain quantitative information and manager's subjective evaluation of firm's financial status. Using information released in U.S. 10-K filings. Both qualitative and quantitative appraisals are crucial for quality financial decisions. To extract such opinioned statements from the reports, we built tagging models based on the conditional random field (CRF) techniques, considering a variety of combinations of linguistic factors including morphology, orthography, predicate-argument structure, syntax, and simple semantics. Our results show that the CRF models are reasonably effective to find opinion holders in experiments when we adopted the popular MPQA corpus for training and testing. The contribution of our paper is to identify opinion patterns in multiword expressions (MWEs) forms rather than in single word forms. We find that the managers of corporations attempt to use more optimistic words to obfuscate negative financial performance and to accentuate the positive financial performance. Our results also show that decreasing earnings were often accompanied by ambiguous and mild statements in the reporting year and that increasing earnings were stated in assertive and positive way.; Comment: 24 pages, 3 figures...

This paper proposes a general adaptive procedure for budget-limited predictor design in high dimensions called two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS). SPARCS can be applied to high dimensional prediction problems in experimental science, medicine, finance, and engineering, as illustrated by the following. Suppose one wishes to run a sequence of experiments to learn a sparse multivariate predictor of a dependent variable $Y$ (disease prognosis for instance) based on a $p$ dimensional set of independent variables $\mathbf X=[X_1,\ldots, X_p]^T$ (assayed biomarkers). Assume that the cost of acquiring the full set of variables $\mathbf X$ increases linearly in its dimension. SPARCS breaks the data collection into two stages in order to achieve an optimal tradeoff between sampling cost and predictor performance. In the first stage we collect a few ($n$) expensive samples $\{y_i,\mathbf x_i\}_{i=1}^n$, at the full dimension $p\gg n$ of $\mathbf X$, winnowing the number of variables down to a smaller dimension $l < p$ using a type of cross-correlation or regression coefficient screening. In the second stage we collect a larger number $(t-n)$ of cheaper samples of the $l$ variables that passed the screening of the first stage. At the second stage...

This paper presents a development paradigm for Ethiopia, based on appropriate services and innovative use of mobile communications technologies via applications tailored for sectors like business, finance, healthcare, governance, education and infotainment. The experience of other developing countries like India and Kenya is cited so as to adapt those to the Ethiopian context. Notable application areas in the aforementioned sectors have been outlined. The ETC 'next generation network' is taken into consideration, with an emphasis on mobile service offering by the Telco itself and/or third party service providers. In addition, enabling technologies like mobile internet, location-based systems, open interfaces to large telecom networks, specifically service-oriented architecture (SOA), Parlay/JAIN and the like are discussed. The paper points out possible endeavors by such stakeholders like: telecom agencies and network operators; businesses, government and NGOs; entrepreneurs and innovators; technology companies and professionals; as well as researchers and academic institutions. ICT4D through mobile services and their role in bridging the digital divide by building a virtual 'network economy' is presented.; Comment: 3rd Scientific Conference on Electrical Engineering...

Using virtual stock markets with artificial interacting software investors, aka agent-based models (ABMs), we present a method to reverse engineer real-world financial time series. We model financial markets as made of a large number of interacting boundedly rational agents. By optimizing the similarity between the actual data and that generated by the reconstructed virtual stock market, we obtain parameters and strategies, which reveal some of the inner workings of the target stock market. We validate our approach by out-of-sample predictions of directional moves of the Nasdaq Composite Index.; Comment: 14 pages, 2 figures

The discovery of new and interesting patterns in large datasets, known as data mining, draws more and more interest as the quantities of available data are exploding. Data mining techniques may be applied to different domains and fields such as computer science, health sector, insurances, homeland security, banking and finance, etc. In this paper we are interested by the discovery of a specific category of patterns, known as rare and non-present patterns. We present a novel approach towards the discovery of non-present patterns using rare item-set mining.; Comment: 17 pages, 5 figures, International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), Vol.1, No.1, August 2012

Spreadsheets often need changing in ways made tedious and risky by Excel. For example: simultaneously altering many tables' size, orientation, and position; inserting cross-tabulations; moving data between sheets; splitting and merging sheets. A safer, faster restructuring tool is, we claim, Excelsior. The result of a research project into reducing spreadsheet risk, Excelsior is the first ever tool for modularising spreadsheets; i.e. for building them from components which can be independently created, tested, debugged, and updated. It represents spreadsheets in a way that makes these components explicit, separates them from layout, and allows both components and layout to be changed without breaking dependent formulae. Here, we report experiments to test that this does indeed make such changes easier. In one, we automatically generated a cross-tabulation and added it to a spreadsheet. In the other, we generated new versions of a 10,000-cell housing-finance spreadsheet containing many interconnected 20*40 tables. We varied table sizes from 5*10 to 200*2,000; moved tables between sheets; and flipped table orientations. Each change generated a spreadsheet with different structure but identical outputs; each change took just a few minutes.; Comment: 18 Pages...

Enterprise Resource Planning ERP systems integrate information across an entire organization that automate core activities such as finance accounting, human resources, manufacturing, production and supply chain management etc. to facilitate an integrated centralized system and rapid decision making resulting in cost reduction, greater planning, and increased control. Many organizations are updating their current management information systems with ERP systems. This is not a trivial task. They have to identify the organizations objectives and satisfy a myriad of stakeholders. They have to understand what business processes they have, how they can be improved, and what particular systems would best suit their needs. They have to understand how an ERP system is built, it involves the modification of an existing system with its own set of business rules. Deciding what to ask for and how to select the best option is a very complex operation and there is limited experience with this type of contracting in organizations. In this paper we discuss a particular experience with contracting out an ERP system, provide some lessons learned, and offer suggestions in how the RFP and bid selection processes could have been improved.; Comment: 14 pages...