996 resultados para Conflict detection
Resumo:
This paper investigates the relationship between linguistic polarization and conflict in the Basque Country. During the 40 years of Franco’s dictatorship the use of the Basque language was banned. Therefore, there may be some linguistic roots underlying the conflict in the Basque Country. We show that at the municipality level, linguistic polarization reduces the level of conflict. This finding is robust to various ways of measuring linguistic and ideological polarization and the inclusion of other covariates. In addition, we find that a high level of the stock of human capital is beneficial for reducing conflict intensity.
Resumo:
This paper reviews the methods for measuring the economic cost of conflict. Estimating the economic costs of conflict requires a counterfactual calculation, which makes this a very difficult task. Social researchers have resorted to different estimation methods depending on the particular effect in question. The method used in each case depends on the units being analyzed (firms, sectors, regions or countries), the outcome variable under study (aggregate output, market valuation of firms, market shares, etc.) and data availability (a single cross-section, time series or panel data). This paper reviews existing methods used in the literature to assess the economic impact of conflict: cost accounting, cross-section methods, time series methods, panel data methods, gravity models, event studies, natural experiments and comparative case studies. The paper ends with a discussion of cost estimates and directions for further research.
Resumo:
In this note we characterize optimal punishments with detection lags when the market consists of n oligopolistic firms. We extend a previous note by Colombo and Labrecciosa (2006) [Colombo, L., and Labrecciosa, P., 2006. Optimal punishments with detection lags. Economic Letters 92, 198-201] to show how in the presence of detection lags optimal punish- ments fail to restore cooperation also in markets with a low number of firms.