|
on Computational Economics |
|
Issue of 2012‒07‒01
five papers chosen by |
| By: | Stephan Schaeffler (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen) |
| Abstract: | The purpose of this paper is the comparative analysis of four natural gas storage valuation approaches. In competitive natural gas markets the optimal valuation and operation of natural gas storages is a key task for natural gas companies operating storages. Within this paper, four spot based valuation approaches are analyzed regarding computational time and accuracy. In particular, explicit and implicit finite differences, multinomial recombining trees, and Least Squares Monte Carlo Simulation are compared. These approaches are applied to the valuation of a gas storage facility considering three different underlying price processes. Major characteristics of historical natural gas prices are: seasonality, mean reversion and jumps. Therefore, we consider a mean reversion process as underlying price process. In a first step, we extend this mean reversion process to a mean reversion jump diffusion process, to account for jumps, occurring in historical gas spot price time series. Moreover, we consider a more general price process accounting for mean reversion as well as seasonal patterns as observed in the historical time series. Besides the analysis of the numerical results, the benefits and drawbacks of the methodologies are discussed. |
| Keywords: | natural gas valuation, limited liquidity |
| JEL: | C61 L95 Q40 |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:dui:wpaper:1201&r=cmp |
| By: | Victor Aguirregabiria; Gustavo Vicentini |
| Abstract: | We propose a dynamic model of an oligopoly industry characterized by spatial competition between multi-store retailers. Firms compete in prices and decide where to open or close stores depending on demand conditions and the number of competitors at different locations, and on location-specific private-information shocks. We develop an algorithm to approximate a Markov Perfect Equilibrium in our model, and propose a procedure for the estimation of the parameters of the model using panel data on number of stores, prices, and quantities at multiple geographic locations within a city. We also present numerical examples to illustrate the model and algorithm. |
| Keywords: | Spatial competition; Store location; Industry dynamics; Sunk costs. |
| JEL: | C73 L13 L81 R10 R30 |
| Date: | 2012–06–14 |
| URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-457&r=cmp |
| By: | Tiago Colliri |
| Abstract: | The importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this area, particularly in this field, we still cannot find a unified model that includes volume and price variations for stock assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. Besides the model can be considered mathematically very simple, it was able to improve significantly the performance of agents operating with real financial data, as will be showed in this paper. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market. |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1206.5224&r=cmp |
| By: | Emin Dinlersoz; Jeremy Greenwood |
| Abstract: | Union membership displayed an inverted U-shaped pattern over the 20th century, while the distribution of income sketched a U. A model of unions is developed to analyze these phenomena. There is a distribution of firms in the economy. Firms hire capital, plus skilled and unskilled labor. Unionization is a costly process. A union decides how many firms to organize and its members’ wage rate. Simulation of the developed model establishes that skilled-biased technological change, which affects the productivity of skilled labor relative to unskilled labor, can potentially explain the above facts. Statistical analysis suggests that skill-biased technological change is an important factor in de-unionization. |
| Keywords: | CES,economic,research,micro,data,microdata, Computers, Distribution of Income, Flexible Manufacturing, Mass Production, Numerically Controlled Machines, Panel-Data Regression Analysis, Relative Price of New Equipment, Skill-Biased Technological Change, Simulation Analysis, Union Coverage, Union Membership, Deunionization |
| JEL: | J51 J24 L23 L11 L16 O14 O33 |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:cen:wpaper:12-12&r=cmp |
| By: | Pussep, Anton; Schief, Markus; Widjaja, Thomas |
| Abstract: | The value chain is a widely used framework for industry and firm analysis. To our knowledge, the conceptualisation of value chains is so far guided by “soft” criteria like intuition of experts rather than clearly stated methods with regard to the value chain boundaries and the granularity as well as the separation of activities. Therefore, we propose a combination of well-known methods – such as the Delphi study approach and clustering algorithms – to (1) ensure a holistic view of the industry at hand by covering all underlying economic concepts, (2) ensure the uniqueness of activities, and (3) provide a hierarchy of activities that allows deriving value chains at different levels of granularity. Since software is a good with specific economic properties, practitioners and researchers require a value chain framework reflecting the industry specifics. This paper contributes by proposing methods for value chain construction and applying these methods to the software industry. The resulting universal and hierarchical software value chain can serve as a sound foundation for further studies of the software industry. Furthermore, practitioners can tailor the proposed methods to their needs and apply the software value chain to their firms. |
| Keywords: | value chain, granularity, software industry |
| Date: | 2012–06–10 |
| URL: | http://d.repec.org/n?u=RePEc:dar:wpaper:57077&r=cmp |