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521.
Jean-François Fagnart Marc Germain Bruno Van der Linden 《The Scandinavian journal of economics》2023,125(1):170-207
We study the consequences of a working time reduction (WTR) in a growth model with efficiency wages and an essential natural resource (natural capital), and in which technical progress cannot reduce the resource content of final production to zero. We show that if natural capital is scarce enough, a WTR increases the long-term levels of the hourly wage and employment. A numerical analysis of the transitory impacts of a WTR confirms that when natural capital is scarcer, a WTR increases employment more and the hourly wage less, with a less negative initial impact on output. 相似文献
522.
523.
Dupire Marion Haddad Christian Slagmulder Regine 《Journal of Financial Services Research》2022,61(3):319-365
Journal of Financial Services Research - This study investigates the relationship between board risk oversight practices at financial institutions in the EU and systemic risk during the sovereign... 相似文献
524.
Luis Raúl Pericchi Guerra was born in Caracas, Venezuela, on 11 March 1952. He completed a B.S. in Mathematics in 1975 at the Universidad Simón Bolívar in Caracas, an M.S. in Statistics at the University of California Berkeley in 1978 and a Ph.D. in Statistics at Imperial College London in 1981. After graduating from Imperial College, Luis Raúl went back to Universidad Simón Bolívar. There, he played a key role in the developing of graduate programmes in Statistics and single handedly built an internationally recognised group focused on Bayesian statistics. In 2001, he moved to the Universidad de Puerto Rico in Rio Piedras to become the Chair of the Mathematics Department. At Universidad de Puerto Rico, he was instrumental in the establishment of a Ph.D. track in Computational Mathematics and Statistics. Luis Raúl has published over 120 papers in statistical and domain-specific journals, making significant contributions to several areas of Bayesian statistics (especially in the areas of model selection and Bayesian robustness) and their application (especially in hydrology). He is a Fellow of the American Statistical Association, the International Society for Bayesian Analysis, the John Simon Guggenheim Memorial Foundation and an Elected Member of the International Statistical Institute. This conversation took place over multiple sessions during the 2022 O'Bayes meeting in Santa Cruz, California, and the months that followed. 相似文献
525.
Deschamps Bruno Fei Tianlun Jiang Ying Liu Xiaoquan 《Review of Quantitative Finance and Accounting》2022,58(3):1117-1144
Review of Quantitative Finance and Accounting - We investigate the macroeconomic determinants of stock market volatility in China using the two-component GARCH-MIDAS model of Engle et al.... 相似文献
526.
Luiz Brotherhood Bruno R. Delalibera Luciene Torres de Mello Pereira 《Bulletin of economic research》2023,75(3):588-608
We study the trade-off between governmental investments in pretertiary and tertiary education from an efficiency point of view. We develop a model comprising agents with different incomes and abilities, public and private schools, and public universities that select applicants based on an admission exam. Reallocating governmental resources from tertiary to pretertiary education may positively affect aggregate production and human capital if some conditions are satisfied. For instance, in an economy with a high proportion of credit-constrained students, a reallocation of expenditure toward public schools benefits many students, compensating for the negative effect of a decrease in public university investments. We also quantitatively investigate the optimal allocation of public investment between pretertiary and tertiary education, and we find that a 10% increase in productivity of public investments in pretertiary education could increase the optimal GDP between 2.1% and 3%. 相似文献
527.
Bruno Ferman 《Journal of Applied Econometrics》2023,38(3):358-369
We analyze the challenges for inference in difference-in-differences (DID) when there is spatial correlation. We present novel theoretical insights and empirical evidence on the settings in which ignoring spatial correlation should lead to more or less distortions in DID applications. We show that details, such as the time frame used in the estimation, the choice of the treated and control groups, and the choice of the estimator, are key determinants of distortions due to spatial correlation. We also analyze the feasibility and trade-offs involved in a series of alternatives to take spatial correlation into account. Given that, we provide relevant recommendations for applied researchers on how to mitigate and assess the possibility of inference distortions due to spatial correlation. 相似文献