R&D Policy in Economies with Endogenous Growth and Non-Renewable Resources

The aim of this paper is to analyze how active R&D policies affect the growth rate of an economy with endogenous growth and non-renewable resources. We know from Scholz and Ziemens (1999) and Groth (2006) that in infinitely lived agents (ILA) economies, any active R&D policy increases the growth rate of the economy. To see if this result also appears in economies with finite lifetime agents, we developed an endogenous growth overlapping generations (OLG) economy à la Diamond which uses non-renewable resources as essential inputs in final good’s production. We show analytically that any R&D policy that reduces the use of natural resources implies a raise in the growth rate of the economy. Numerically we show that in economies with low intertemporal elasticity of substitution (IES), active R&D policies lead the economy to increase the depletion of non-renewable resources. Nevertheless, we find that active R&D policies always imply increases in the endogenous growth rate, in both scenarios. Furthermore, when the IES coefficient is lower (greater) than one, active R&D policies affect the growth rate of the economy in the ILA more (less) than in OLG economies.

Growth in Overlapping Generation Economies with Non-Renewable Resources

Published as an article in: Journal of Environmental Economics and Management, 2005, vol. 50, issue 2, pages 387-407.

Web resources to disseminate methodology in heritage documentation

Impreso por la Diputación Foral de Álava, D.L. VI-430/99.

Does training policy help to attract, retain and develop valuable human resources? Analysis from the Mondragon case

This is an electronic version of the accepted paper in the journal:Advances in the Economic Analysis of Participatory and Labor-Managed Firms. Volumen. 12

Discounting the value of natural resources in costbenefit analysis: a case study for policy making

4 p.

Implementing Integrated Water Resources Management in the Ebro River Basin: From Theory to Facts

JA-925

NEW METHODOLOGY FOR FEEDER RECONFIGURATION IN DISTRIBUTION NETWORKS WITH DISTRIBUTED ENERGY RESOURCES

This doctoral Thesis defines and develops a new methodology for feeder reconfiguration in distribution networks with Distributed Energy Resources (DER). The proposed methodology is based on metaheuristic Ant Colony Optimization (ACO) algorithms. The methodology is called Item Oriented Ant System (IOAS) and the doctoral Thesis also defines three variations of the original methodology, Item Oriented Ant Colony System (IOACS), Item Oriented Max-min Ant System (IOMMAS) y Item Oriented Max-min Ant Colony System (IOACS). All methodologies pursue a twofold objective, to minimize the power losses and maximize DER penetration in distribution networks. The aim of the variations is to find the algorithm that adapts better to the present optimization problem, solving it most efficiently. The main feature of the methodology lies in the fact that the heuristic information and the exploitation information (pheromone) are attached to the item not to the path. Besides, the doctoral Thesis proposes to use feeder reconfiguration in order to increase the distribution network capacity of accepting a major degree of DER. The proposed methodology and its three variations have been tested and verified in two distribution networks well documented in the existing bibliography. These networks have been modeled and used to test all proposed methodologies for different scenarios with various DER penetration degrees.

Distribution of Healthcare resources II.Study and Comparison of a Linear Programming Problem and its Dual. Resolution and Evaluation of a Practical Case and its Programming using Excel and Win QSB.

[EN]This research had as primary objective to model different types of problems using linear programming and apply different methods so as to find an adequate solution to them. To achieve this objective, a linear programming problem and its dual were studied and compared. For that, linear programming techniques were provided and an introduction of the duality theory was given, analyzing the dual problem and the duality theorems. Then, a general economic interpretation was given and different optimal dual variables like shadow prices were studied through the next practical case: An aesthetic surgery hospital wanted to organize its monthly waiting list of four types of surgeries to maximize its daily income. To solve this practical case, we modelled the linear programming problem following the relationships between the primal problem and its dual. Additionally, we solved the dual problem graphically, and then we found the optimal solution of the practical case posed through its dual, following the different theorems of the duality theory. Moreover, how Complementary Slackness can help to solve linear programming problems was studied. To facilitate the solution Solver application of Excel and Win QSB programme were used.