Doctorat en sciences sociales, politiques et économiques / info:eu-repo/semantics/nonPublished

Doctorat en sciences sociales, politiques et économiques / info:eu-repo/semantics/nonPublished

Doctorat en sciences sociales, politiques et économiques / info:eu-repo/semantics/nonPublished

M.Ing. ( Electrical & Electronic Engineering Science) / Economic modelling tools have gained popularity in recent years due to the increasing need for greater knowledge to assist policy makers and economists. A number of computational intelligence approaches have been proposed for economic modelling. Most of these approaches focus on the accuracy of prediction and not much research has been allocated to investigate the interpretability of the decisions derived from these systems. This work proposes the use of computational intelligence techniques (Rough set theory (RST) and the Multi-layer perceptron (MLP) model) to model the South African economy. RST is a rule-based technique suitable for analysing vague, uncertain and imprecise data. RST extracts rules from the data to model the system. These rules are used for prediction and interpreting the decision process. The lesser the number of rules, the easier it is to interpret the model. The performance of the RST is dependent on the discretization technique employed. An equal frequency bin (EFB), Boolean reasoning (BR), entropy partition (EP) and the Naïve algorithm (NA) are used to develop an RST model. The model trained using EFB data performs better than the models trained using BR and EP. RST was used to model South Africa’s financial sector. Here, accuracy of 86.8%, 57.7%, 64.5% and 43% were achieved for EFB, BR, EP and NA respectively. This work also proposes an ensemble of rough set theory and the multi-layer perceptron model to model the South African economy wherein, a prediction of the direction of the gross domestic product is presented. This work also proposes the use of an auto-associative Neural Network to impute missing economic data. The auto-associative neural network imputed the ten variables or attributes that were used in the prediction model. These variables were: Construction contractors rating lack of skilled labour as constraint, Tertiary economic sector contribution to GDP, Income velocity of circulation of money, Total manufacturing production volume, Manufacturing firms rating lack of skilled labour as constraint, Total asset value of banking industry, Nominal unit labour cost, Total mass of Platinum Group Metals (PGMs) mined, Total revenue from sale of PGMs and the Gross Domestic Expenditure (GDE). The level of imputation accuracy achieved varied with the attribute. The accuracy ranged from 85.9% to 98.7%.

This dissertation describes two theories of risky choice based on a normatively axiomatized partial order. The first theory is an atemporal alternative to von Neumann and Morgenstern's Expected Utility Theory that accommodates the status quo bias, violations of Independence and preference reversals. The second theory is an extension of the Inter-temporal von Neumann-Morgenstern theory of Kreps and Porteus (1978) that features a normatively deduced preference for flexibility. A substantial part of the thesis is devoted to examining equilibrium implications of the inter-temporal theory. In particular, a multi-agent multi-period Bayesian rational expectations equilibrium is shown to exist under certain conditions. Implications to asset pricing are then investigated with an explicit parameterization of the model. / Business, Sauder School of / Finance, Division of / Graduate

We aim to investigate the stability of various stock-flow consistent economic models, and the potential causes for economic collapse therein. Through parameter sensitivity analysis, we study models that feature a public sector, an active central bank, and a household sector with independent consumption. Our final, most comprehensive economic system combines all of the intricacies of each model, prominently featuring a demand-driven economy that is stabilized by an expansionary monetary policy. In addition, we incorporate a climate module for each economic system, and analyze public sector intervention through carbon taxes and abatement subsidies. We find that the most common feature of economic instability is a lack of demand, driven by decreases in capital investment from firms, as well as a decline in household consumption. In order to maintain a stable growth path and prevent a permanent economic contraction, we propose the implementations of an expansionary monetary policy, increased public sector subsidies of abatement costs, and stricter carbon taxes. / Thesis / Master of Science (MSc)

Fisher market models and market equilibrium computation algorithms have long been central research topics in economics, operations research, and theoretical computer science. Recently, they have found diverse applications in the design of Internet marketplaces. In this thesis, we develop tractable optimization models and algorithms for computing market equilibria under various practically relevant settings. In Chapter 1, we study first-order methods for computing market equilibria under a finite number of buyers with linear, quasilinear or Leontief utilities. For linear and Leontief utilities, we show that their corresponding convex programs---whose solutions are market equilibria and vice versa---exhibits strong-convexity-like structures after simple reformulations. This allows us to design the first gradient-based algorithms that achieve a linear rate of convergence for computing market equilibria. For buyers with quasilinear utility functions, we propose a new convex program capturing market equilibria, which is analogous to the Shmyrev convex program for linear utilities. Applying the mirror descent algorithm to this convex program leads to a distributed and interpretable Proportional Response (PR) dynamics that converges to equilibrium prices and utilities. This generalizes the classical PR dynamics and its convergence guarantees, previously known for linear utilities, to the case of quasilinear utilities. In Chapter 2, we consider a generalization of a linear Fisher market where there is a finite set of buyers and a measurable item space. We introduce generalizations of the Eisenberg-Gale convex program and its dual to this setting, which leads to infinite-dimensional Banach-space optimization problems. We show that these convex programs always have optimal solutions and these optimal solutions correspond to market equilibria. In particular, a market equilibrium always exists. We also show that KKT-type optimality conditions for these convex programs imply the defining properties of market equilibria and are necessary and sufficient for a solution pair to be optimal. Then, we show that, similar to the classical finite-dimensional case, a market equilibrium is Pareto optimal, envy-free and proportional. Moreover, when the item space measure is atomless, we show that there always exists a pure equilibrium allocation, which can be viewed as a generalized fair division, that is, a Pareto optimal, envy-free, and proportional partition of the item space. This leads to generalizations of classical results on the existence and characterizations of fair divisions of a measurable set. When the item space is a closed interval and buyers have piecewise linear valuations, we show that the infinite-dimensional Eisenberg-Gale-type convex program can be reformulated as a finite-dimensional convex conic program, which can be solved efficiently using off-the-shelf optimization software. Based on the convex conic reformulation, we also develop the first polynomial-time algorithm for finding a fair division of an interval under piecewise linear valuations. For general buyer valuations or a very large number of buyers, we propose computing market equilibria using stochastic optimization and give high-probability convergence guarantees. Finally, we show that most of the above results easily extend to the case of quasilinear utilities. In Chapter 3, we consider an online market setting where items arrive sequentially and must be allocated to buyers irrevocably. We define the notion of an online market equilibrium as time-indexed allocations and prices which guarantee buyer optimality and market clearance in hindsight. We propose simple, scalable and interpretable allocation and pricing dynamics termed as PACE (Pacing ACcording to Estimated utilities). When items are drawn independently from an unknown distribution with a possibly continuous support, we show that PACE leads to an online market equilibrium asymptotically. In particular, PACE ensures that buyers' time-averaged utilities converge to the equilibrium utilities of a static market with item supplies being the unknown distribution and that buyers' time-averaged expenditures converge to their per-period budget. Hence, many desirable properties of market equilibrium-based fair division such as envy-freeness, Pareto optimality, and the proportional-share guarantee are also attained asymptotically in the online setting. Next, we extend the dynamics to handle quasilinear buyer utilities, which gives the first online algorithm for computing pacing equilibria in first-price auctions. Finally, numerical experiments show that the dynamics converges quickly under various metrics.

The major objectives of this study are to: (i) improve the understanding of what is meant by economic diversification and economic diversity, (ii) provide a comprehensive conceptual framework for region-specific analysis of the relationship between changing economic structure and economic performance measured in terms of the growth, stability, and distribution of income and employment, and (iii) construct an operational model of a regional economy that can be used to assess the impacts of alternative development strategies. This study attempts to sort out the overlaps, contradictions, and gaps among the different economic and finance theories, and the different definitions and measures of economic diversification and diversity. The subject of economic diversification or diversity is addressed in the context of the question: "What is the relationship between a region’s changing economic structure and performance?" A structural model of a regional economy, an extended input-output model based on a social accounting matrix (SAM), serves as the foundation of the conceptual framework and operational model. The SAM-based input- output model explicitly depicts the functional relationship between economic structure and performance. The region’s demand, production technologies, and trade flows are included as part of economic structure. Economic performance is measured as the growth, stability, and distribution of regional income and employment, by occupation group. The structural model is used to analyze the relationship between economic structure and performance for a given time period, and to analyze changes over time. Growth, stability, and distributional impacts are considered simultaneously. By doing this, potential tradeoffs can be explicitly addressed. To identify the structural sources of growth and stability, the SAM-based input-output model is decomposed at different points in time. By decomposing a SAM-based model it is possible to analyze structural sources of growth and stability in terms of both supply and demand factors. Alternative development strategies can be modelled using this conceptual framework. The operational model quantifies the relationship between: (i) the anticipated growth and stability of exogenous final demands, and (ii) the anticipated growth, stability, and distribution of endogenous income and employment, by occupation group. The operational model focuses attention on the distributional impacts of changing economic structure and performance. The relationship between a region’s social welfare, and the aggregation scheme and accounting stance used in the analysis of economic impacts are explicitly addressed. As such, there are explicit social welfare criteria for comparing and ranking alternative development strategies. The operational model presented in this study is well-suited to many popular input-output application packages. / Ph. D.

Business Management / (M.Sc.(Operation Research))

We generalize the theory of stochastic impulse control of jump diffusions introduced by Oksendal and Sulem (2004) with milder assumptions. In particular, we assume that the original process is affected by the interventions. We also generalize the optimal central bank intervention problem including market reaction introduced by Moreno (2007), allowing the exchange rate dynamic to follow a jump diffusion process. We furthermore generalize the approximation theory of stochastic impulse control problems by a sequence of iterated optimal stopping problems which is also introduced in Oksendal and Sulem (2004). We develop new results which allow us to reduce a given impulse control problem to a sequence of iterated optimal stopping problems even though the original process is affected by interventions. / by Sandun C. Perera. / Thesis (Ph.D.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.