Contribution from neuropsychology to the study of semantic memory

Semantic memory has been studied from various fields. The first models emerged from cognitive psychology from the hand of the division proposed by Tulving between semantic and episodic memory. Over the past thirty years there have been parallel developments in the fields of psycholinguistics, cognitive psychology and cognitive neuropsychology. The present work is to review the contributions that have emerged within the neuropsychology to the study of semantic memory and to present an updated overview of the points of consensus. First, it is defined the term "semantics" conceptually within the field of neuropsychology. Then, there is a dichotomy that passes through both psychological and neuropsychological models on semantic memory: the existence of modals versus amodal representations. Third, there are  developed the main theoretical models in neuropsychology that emerged in an attempt to explain categoryspecific semantic deficits. Finally, more robust contributions and points that still generate some discussion are reviewed.

Labor's shares - aggregate and industry: accounting for both in a model of unbalanced growth with induced innovation

The relative stability of aggregate labor's share constitutes one of the great macroeconomic ratios. However, relative stability at the aggregate level masks the unbalanced nature of industry labor's shares – the Kuznets stylized facts underlie those of Kaldor. We present a two-sector – one labor-only and the other using both capital and labor – model of unbalanced economic development with induced innovation that can rationalize these phenomena as well as several other empirical regularities of actual economies. Specifically, the model features (i) one sector ("goods" production) becoming increasingly capital-intensive over time; (ii) an increasing relative price and share in total output of the labor-only sector ("services"); and (iii) diverging sectoral labor's shares despite (iii) an aggregate labor's share that converges from above to a value between 0 and unity. Furthermore, the model (iv) supports either a neoclassical steadystate or long-run endogenous growth, giving it the potential to account for a wide range of real world development experiences.

A model of school behavior: tuition fees and grading standards

This paper uses a hybrid human capital / signaling model to study grading standards in schools when tuition fees are allowed. The paper analyzes the grading standard set by a profit maximizing school and compares it with the efficient one. The paper also studies grading standards when tuition fees have limits. When fees are regulated a profit maximizing school will set lower grading standards than when they are not regulated. Credit constraints of families also induce schools to lower their standards. Given that in the model presented competition is not feasible, these results show the importance of regulation of grading standards.

A Network model of systemic risk : identifying the sources of dependence across institutions

We design a financial network model that explicitly incorporates linkages across institutions through a direct contagion channel, as well as an indirect common exposure channel. In particular, common exposure is setup so as to link the financial to the real sector. The model is calibrated to balance sheet data on the colombian financial sector. Results indicate that commercial banks are the most systemically important financial institutions in the system. Whereas government owned institutions are the most vulnerable institutions in the system.