A regret model applied to the facility location problem with limited capacity facilities

This article addresses issues related to location and allocation problems. Herein, we intend to demonstrate the influence of congestion, through the random number generation, of such systems in final solutions. An algorithm is presented which, in addition to the GRASP, incorporates the Regret with the pminmax method to evaluate the heuristic solution obtained with regard to its robustness for different scenarios. Taking as our point of departure the Facility Location Problem proposed by Balinski [27], an alternative perspective is added associating regret values to particular solutions.N/

How to get what you want when you do not know what you want. A model of incentives, organizational structure and learning

In this paper we present a model of the interplay between learning, incentives and the allocation of decision rights in the context of a generalized agency problem. Within this context, not only actors face conflicting interests but diverging cognitive ?visions? of the right course of action as well. We show that a principal may obtain the implementation of desired organizational policies by means of appropriate incentives or by means of appropriate design of the allocation of decisions, when the latter is cheaper but more complex. We also show that when the principal is uncertain about which course of action is more appropriate and wants to learn it from the environment, organizational structure and incentives interact in non-trivial ways and must be carefully tuned. When learning is not at stake, incentives and organizational structure are substitutes. When instead learning is at stake, organizational structure and incentives may complement each other and have to be fine tuned according to the complexity of the learning process and the competitive pressure which is put on fast or slow learning.Incentives, Organizational Structure, Learning

Combining Outcome-Based and Preference-Based Matching: A Constrained Priority Mechanism

We introduce a constrained priority mechanism that combines outcome-based matching from machine-learning with preference-based allocation schemes common in market design. Using real-world data, we illustrate how our mechanism could be applied to the assignment of refugee families to host country locations, and kindergarteners to schools. Our mechanism allows a planner to first specify a threshold $\bar g$ for the minimum acceptable average outcome score that should be achieved by the assignment. In the refugee matching context, this score corresponds to the predicted probability of employment, while in the student assignment context it corresponds to standardized test scores. The mechanism is a priority mechanism that considers both outcomes and preferences by assigning agents (refugee families, students) based on their preferences, but subject to meeting the planner's specified threshold. The mechanism is both strategy-proof and constrained efficient in that it always generates a matching that is not Pareto dominated by any other matching that respects the planner's threshold.Comment: This manuscript has been accepted for publication by Political Analysis and will appear in a revised form subject to peer review and/or input from the journal's editor. End-users of this manuscript may only make use of it for private research and study and may not distribute it furthe

Measuring Poverty at the State Level

Outlines a model for using the National Academy of Sciences poverty measure, which accounts for all income, non-discretionary work and out-of-pocket health expenses, and geographic cost variations, to estimate the effects of poverty reduction policies

A regret model applied to the maximum coverage location problem with queue discipline

This article discusses issues related to the location and allocation problems where is intended to demonstrate, through the random number generation, the influence of congestion of such systems in the final solutions. It is presented an algorithm that, in addition to the GRASP, incorporates the Regret with the pminmax method to evaluate the heuristic solution obtained in regard to its robustness for different scenarios. To the well know Maximum Coverage Location Problem from Church and Revelle [1] an alternative perspective is added in which the choice behavior of the server does not only depend on the elapsed time from the demand point looking to the center, but also includes the waiting time for service conditioned by a waiting queue.N/

Business fluctuations in a behavioral switching model: Gridlock effects and credit crunch phenomena in financial networks

In this paper we characterize the evolution over time of a credit network in the most general terms as a system of interacting banks and firms operating in a three-sector economy with goods, credit and interbank market. Credit connections change over time via an evolving fitness measure depending from lenders’ supply of liquidity and borrowers’ demand of credit. Moreover, an endogenous learning mechanism allows agents to switch between a loyal or a shopping-around strategy according to their degree of satisfaction. The crucial question we investigate is how financial bubbles and credit-crunch phenomena emerge from the implemented mechanism

Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms

The aim of this note is to identify the factors influencing renewable energy consumption in Madagascar. We tested 12 features covering macroeconomic, financial, social, and environmental aspects, including economic growth, domestic investment, foreign direct investment, financial development, industrial development, inflation, income distribution, trade openness, exchange rate, tourism development, environmental quality, and urbanization. To assess their significance, we assumed a linear relationship between renewable energy consumption and these features over the 1990-2021 period. Next, we applied different machine learning feature selection algorithms classified as filter-based (relative importance for linear regression, correlation method), embedded (LASSO), and wrapper-based (best subset regression, stepwise regression, recursive feature elimination, iterative predictor weighting partial least squares, Boruta, simulated annealing, and genetic algorithms) methods. Our analysis revealed that the five most influential drivers stem from macroeconomic aspects. We found that domestic investment, foreign direct investment, and inflation positively contribute to the adoption of renewable energy sources. On the other hand, industrial development and trade openness negatively affect renewable energy consumption in Madagascar

Simulating interbank payment and securities settlement mechanisms with the BoF-PSS2 simulator

The simulation technique provides a new means for analysing complex interdependencies in payment and securities settlement processing. The Bank of Finland has developed a payment and settlement system simulator (BoF-PSS2) that can be used for constructing simulation models of payment and securities settlement systems. This paper describes the main elements of payment and settlement systems (system structures, interdependencies, processing steps, liquidity consumption, cost and risk dimensions) and how these can be treated in simulation studies. It gives also examples on how these elements have been incorporated in the simulator, as well as an overview of the structure and the features of the BoF-PSS2 simulator.simulations; simulator; payment systems; clearing/settlement; liquidity

On the Impact of Better Targeted Transfers on Poverty in Tunisia

This paper describes the effects of general food subsidies on poverty in Tunisia, as revealed by household survey data for 1990. The analysis indicates that the poorest certainly take advantage of this system, but at the price of considerable leakages to non-poor people and at a sizeable economic efficiency loss resulting from relative price distortions. Further, non-parametric estimations suggest that there are no commodities predominantly consumed by the poor. This implies that targeting by commodities is not an effective way to fight against poverty and so, it is unlikely that restructuring the current scheme would improve significantly the living standards of the less well-off members of society. We then investigate the impact on poverty of a more targeted transfer scheme, based on proxy means-tests, using an appropriate econometric technique to model it. Simulations show that this design would be more effective in reducing poverty than the use of general food subsidies. Finally, dominance tests show that this design would first-order-dominate food subsidies scheme within a range of poverty lines including all those estimated and generally used for Tunisia.Poverty, Targeting, Subsidies, Transfers