WAGE GAPS AND MIGRANTION COSTS: AN ANALYSIS FROM SIMULATION DATA

Borjas (1987, 1991 and 1994) developed the self-selection theory, applying Roy’s model (1951) to migration studies. He establishes that the characteristics of migrants in terms of skills and abilities are driven by wage distribution differences between the host country and home. In this regard, when the country of origin has higher relative returns for skills and more disperse income distribution, a negative selection of migrants is generated, and vice versa. A great deal of literature has studied Self-selection model to analyse how wage distribution influences migrants’ decisions, leading to consistent and inconsistent results. Given the conflicting results in the literature, this paper examines how migration costs and wage differences influence self-selection patterns –i.e. skills in terms of schooling levels. Taking into account that self-selection can not be studied systematically by means of standard data sources because of the lack of data, we propose an analytical model based on the individual investment decision theory (Human Capital theory), applying simulated data by Monte-Carlo method. The theory of individual investment decisions allows us to analyze self-selection patterns across differences in wages and economic conditions at home and in host countries and to introduce uncertainty using a stochastic framework. An empirical application for long-distant migrations –from Ecuador to Spain– is implemented. Our findings show that migrants are positively selected on observable skills between Spain and Ecuador, considering both constant direct migration costs and constant direct migration costs-plus-variable opportunity migration costs. Secondary data from official sources confirm this tendency.

WAGE GAPS AND MIGRANTION COSTS: AN ANALYSIS FROM SIMULATION DATA

Borjas (1987, 1991 and 1994) developed the self-selection theory, applying Roy's model (1951) to migration studies. He establishes that the characteristics of migrants in terms of skills and abilities are driven by wage distribution differences between the host country and home. In this regard, when the country of origin has higher relative returns for skills and more disperse income distribution, a negative selection of migrants is generated, and vice versa. A great deal of literature has studied Self-selection model to analyse how wage distribution influences migrants' decisions, leading to consistent and inconsistent results. Given the conflicting results in the literature, this paper examines how migration costs and wage differences influence self-selection patterns -i.e. skills in terms of schooling levels. Taking into account that self-selection can not be studied systematically by means of standard data sources because of the lack of data, we propose an analytical model based on the individual investment decision theory (Human Capital theory), applying simulated data by Monte-Carlo method. The theory of individual investment decisions allows us to analyze self-selection patterns across differences in wages and economic conditions at home and in host countries and to introduce uncertainty using a stochastic framework. An empirical application for long-distant migrations -from Ecuador to Spain- is implemented. Our findings show that migrants are positively selected on observable skills between Spain and Ecuador, considering both constant direct migration costs and constant direct migration costs-plus-variable opportunity migration costs. Secondary data from official sources confirm this tendency

Re-thinking the Etiological Framework of Neurodegeneration

Neurodegenerative diseases are among the leading causes of disability and death worldwide. The disease-related socioeconomic burden is expected to increase with the steadily increasing life expectancy. In spite of decades of clinical and basic research, most strategies designed to manage degenerative brain diseases are palliative. This is not surprising as neurodegeneration progresses "silently" for decades before symptoms are noticed. Importantly, conceptual models with heuristic value used to study neurodegeneration have been constructed retrospectively, based on signs and symptoms already present in affected patients;a circumstance that may confound causes and consequences. Hence, innovative, paradigm-shifting views of the etiology of these diseases are necessary to enable their timely prevention and treatment. Here, we outline four alternative views, not mutually exclusive, on different etiological paths toward neurodegeneration. First, we propose neurodegeneration as being a secondary outcome of a primary cardiovascular cause with vascular pathology disrupting the vital homeostatic interactions between the vasculature and the brain, resulting in cognitive impairment, dementia, and cerebrovascular events such as stroke. Second, we suggest that the persistence of senescent cells in neuronal circuits may favor, together with systemic metabolic diseases, neurodegeneration to occur. Third, we argue that neurodegeneration may start in response to altered body and brain trophic interactions established via the hardwire that connects peripheral targets with central neuronal structures or by means of extracellular vesicle (E\-mediated communication. Lastly, we elaborate on how lifespan body dysbiosis may be linked to the origin of neurodegeneration. We highlight the existence of bacterial products that modulate the gut-brain axis causing neuroinflammation and neuronal dysfunction. As a concluding section, we end by recommending research avenues to investigate these etiological paths in the future. We think that this requires an integrated, interdisciplinary conceptual research approach based on the investigation of the multimodal aspects of physiology and pathophysiology. It involves utilizing proper conceptual models, experimental animal units, and identifying currently unused opportunities derived from human data. Overall, the proposed etiological paths and experimental recommendations will be important guidelines for future cross-discipline research to overcome the translational roadblock and to develop causative treatments for neurodegenerative diseases