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on Computational Economics |
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Issue of 2015‒01‒03
seven papers chosen by |
| By: | Arndt, Channing; Davies, Rob; Gabriel, Sherwin; Makrelov, Konstantin; Merven, Bruno |
| Abstract: | We link a bottom-up energy sector model to a recursive dynamic computable general equilibrium model of South Africa in order to examine two of the country.s main energy policy considerations: (i) the introduction of a carbon tax and (ii) liberalization of |
| Keywords: | integrated bottom-up model, the integrated MARKAL-EFOM system, computable general equilibrium, carbon tax, South Africa |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:unu:wpaper:wp2014-135&r=cmp |
| By: | Wei Ma (Department of Economics, University of Pretoria) |
| Abstract: | The problem of computing equilibria for general equilibrium models with incomplete real asset markets, or GEI models for the sake of brevity, is reconsidered. It is shown here that the rank-dropping behavior of the asset return matrix could be dealt with in rather a simple fashion: We first compute its singular value decomposition, and then, through this decomposition, construct, by the introduction of a homotopy parameter, a new matrix such that it has constant rank before a desired equilibrium is reached. By adjunction of this idea to the homotopy method, a simpler constructive proof is obtained for the generic existence of GEI equilibria. For the purpose of computing these equilibria, from this constructive proof is then derived a path-following algorithm whose performance is finally demonstrated by means of two numerical examples. |
| Keywords: | Incomplete asset markets, General equilibrium theory, Homotopy method |
| JEL: | C68 C63 |
| Date: | 2014–12 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:201478&r=cmp |
| By: | Vatsa, Amit Kumar; Ghosh, Diptesh |
| Abstract: | This paper supersedes the work presented in WP.No.2014-02-06. We study the problem of allocating doctors to primary health centers (PHC). We model the problem as a multi-period uncapacitated facility location problem under uncertainty. The problem is unconventional in that the uncertainty is in the number and period of availability of doctors. This work aims to determine the sequence of opening facil- ities (assigning doctors to the PHC) over multiple periods so as to cover the maximum demand. We use a minmax regret approach to solve the problem under uncertainty. We present solution techniques using tabu search and compare our solutions with optimal solutions obtained using commercial solvers. We see that one of our tabu search algorithms is faster and yields optimal solutions in the problems we tested on. |
| URL: | http://d.repec.org/n?u=RePEc:iim:iimawp:12923&r=cmp |
| By: | Postek, K.S. (Tilburg University, Center For Economic Research); den Hertog, D. (Tilburg University, Center For Economic Research) |
| Abstract: | In this paper we propose a methodology for constructing decision rules for in- teger and continuous decision variables in multiperiod robust linear optimization problems. This type of problems finds application in, for example, inventory management, lot sizing, and manpower management. We show that by iteratively splitting the uncertainty set into subsets one can differentiate the later-period decisions based on the revealed uncertain parameters. At the same time, the problem’s computational complexity stays at the same level as for the static robust problem. This holds also in the non-fixed recourse situation. In the fixed recourse situation our approach can be combined with linear decision rules for the continuous decision variables. We provide theoretical results how to split the uncertainty set by identifying sets of uncertain parameter scenarios to be divided for an improvement in the worst-case objective value. Based on this theory, we propose several splitting heuristics. Numerical examples entailing a capital budgeting and a lot sizing problem illustrate the advantages of the proposed approach. |
| Keywords: | adjustable; decision rules; integer; multi-stage; robust optimization |
| JEL: | C61 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:tiu:tiucen:8649012b-1bb0-4d34-83f1-792d61863249&r=cmp |
| By: | Jérôme Danguy; Bruno van Pottelsberghe |
| Abstract: | This paper provides new evidence about the budgetary consequences â?? for patent offices â?? of the coexistence of the forthcoming Unitary Patent (UP) with the current European Patent (EP). Simulation results illustrate a dilemma between (1) high UP renewal fees to ensure enough financial income for all national patent offices (NPOs) and (2) low UP renewal fees to make the UP system affordable, with very few NPOs losing on financial revenues. The simulations help to understand the positions of several patent offices, and underline an alternative way to proceed with the negotiations while reducing financial risks for the whole system. |
| Date: | 2014–11 |
| URL: | http://d.repec.org/n?u=RePEc:bre:wpaper:858&r=cmp |
| By: | Faraglia, Elisa; Marcet, Albert; Oikonomou, Rigas; Scott, Andrew |
| Abstract: | Our aim is to provide insights into some basic facts of US government debt management by introducing simple financial frictions in a Ramsey model of fiscal policy. We find that the share of short bonds in total U.S. debt is large, persistent, and highly correlated with total debt. A well known literature argues that optimal debt management should behave very differently: long term debt provides fiscal insurance, hence short bonds should not be issued and the position on short debt is volatile and negatively correlated with total debt. We show that this result hinges on the assumption that governments buy back the entire stock of previously issued long bonds each year, which is very far from observed debt management. We document how the U.S. Treasury rarely has repurchased bonds before 10 years after issuance. When we impose in the model that the government does not buy back old bonds the puzzle disappears and the optimal bond portfolio matches the facts mentioned above. The reason is that issuing only long term debt under no buyback would lead to a lumpiness in debt service payments, short bonds help offset this by smoothing out interest payments and tax rates. The same reasoning helps explain why governments issue coupon-paying bonds. Solving dynamic stochastic models of optimal policy with a portfolio choice is computationally challenging. A separate contribution of this paper is to propose computational tools that enable this broad class of models to be solved. In particular we propose two significant extensions to the PEA class of computational methods which overcome problems due to the size of the model. These methods should be useful to many applications with portfolio problems and large state spaces. |
| Keywords: | Computational methods; Debt Management; Fiscal Policy; Incomplete Markets; Maturity Structure; Tax Smoothing |
| JEL: | C63 E43 E62 H63 |
| Date: | 2014–12 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:10281&r=cmp |
| By: | Cavarretta, Fabrice (ESSEC Business School); Furr , Nathan (BYU (Brigham Young University) Marriott School of Management) |
| Abstract: | Boundedly rational managerial actors struggling to process information often use a limited set of “theories of action,” or simple rules. However, simple rules may have a hierarchical structure, with some simple rules guiding others. Assuming the existence of such “keystone rules,” we establish the complexity of determining an efficient set, and therefore the necessity of using meta-heuristic approaches. We explore the development of “keystone rules” among entrepreneurs as a genetic algorithm, where the computationally hard problem of picking rules is solved by social calculation. We find that the emergent keystone rules among the observed entrepreneurs do not match existing “scientific” theories but have particular epistemic properties. The identification of keystone rules could fill a theoretical gap between the rational decision and the social construction perspectives. |
| Keywords: | entrepreneurship; simple rules; theory; cognition; evolution |
| JEL: | L26 |
| Date: | 2014–11 |
| URL: | http://d.repec.org/n?u=RePEc:ebg:essewp:dr-14015&r=cmp |