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  <channel rdf:about="https://hdl.handle.net/20.500.12008/10517">
    <title>Colibri Comunidad :</title>
    <link>https://hdl.handle.net/20.500.12008/10517</link>
    <description />
    <items>
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        <rdf:li rdf:resource="https://hdl.handle.net/20.500.12008/53690" />
        <rdf:li rdf:resource="https://hdl.handle.net/20.500.12008/50016" />
        <rdf:li rdf:resource="https://hdl.handle.net/20.500.12008/48543" />
        <rdf:li rdf:resource="https://hdl.handle.net/20.500.12008/48533" />
      </rdf:Seq>
    </items>
    <dc:date>2026-05-14T09:33:03Z</dc:date>
  </channel>
  <item rdf:about="https://hdl.handle.net/20.500.12008/53690">
    <title>Nuevas herramientas para medir la segregación residencial multiescala</title>
    <link>https://hdl.handle.net/20.500.12008/53690</link>
    <description>Título: Nuevas herramientas para medir la segregación residencial multiescala
Autor: Labat, Juan Pablo; Hernández-Banadik, Manuel
Resumen: Este trabajo presenta un instrumento para la medición de la segregación residencial desarrollado en R recogiendo la propuesta metodológica de Reardon y O’Sullivan (2004) e incorporando técnicas para comparar la segregación en su evolución a lo largo del tiempo o entre distintas unidades. Para ello, levanta la restricción de la escala proponiendo un método multiescala flexible que pasa a ser una variable a elegir por el investigador. El instrumento desarrollado en R como el paquete socialseg (Hernández-Banadik y Labat, 2025), permite además la visualización del proceso de medición y una novedosa forma de relacionar la dimensión local y global del fenómeno para macro y micro segregación.; This paper presents an instrument for measuring residential segregation developed in R, based on the methodological proposal of Reardon y O’Sullivan (2004) and incorpo- rating techniques to compare segregation over time or across different units. To achieve this, it lifts the scale restriction by proposing a flexible multiscale method that becomes a variable to be chosen by the researcher. The instrument, developed in R as the socialseg package (Hernández-Banadik y Labat, 2025), also enables the visualization of the measu- rement process and introduces a novel way to relate the local and global dimensions of the phenomenon for macro and micro segregation.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://hdl.handle.net/20.500.12008/50016">
    <title>Política fiscal en América Latina y el Caribe: análisis de las reglas fiscales y el gasto público</title>
    <link>https://hdl.handle.net/20.500.12008/50016</link>
    <description>Título: Política fiscal en América Latina y el Caribe: análisis de las reglas fiscales y el gasto público
Autor: Miranda, Ronald
Resumen: El diseño y la implementación de reglas fiscales han sido ampliamente utilizados como instrumentos para promover la disciplina fiscal y mitigar la prociclicidad del gasto público en distintos países. En América Latina y el Caribe (LAC, por sus siglas en inglés), el gasto público ha mostrado tradicionalmente un comportamiento procíclico, lo que ha limitado su capacidad de desempeñar un rol estabilizador en períodos de recesión o crisis económicas, dando lugar a ajustes fiscales con elevados costos sociales y económicos. La experiencia internacional, tanto en economías desarrolladas como en países en desarrollo, sugiere que las reglas fiscales pueden contribuir significativamente a la sostenibilidad de las finanzas públicas. En este contexto, Uruguay aprobó en 2020 una nueva institucionalidad fiscal a través de la Ley N.º 19.889 (Ley de Urgente Consideración, LUC) y la Ley de Presupuesto Nacional 2020–2024, incorporando reglas sobre el resultado fiscal estructural,&#xD;
topes de gasto y límites de endeudamiento. No obstante, el debate político y académico ha profundizado poco en las implicancias económicas y sociales de estas reformas. Desde una perspectiva comparativa que abarca 167 países, este estudio encuentra que el gasto público tiende a responder de manera procíclica al ciclo macroeconómico. Sin embargo, este efecto se atenúa en contextos donde existen reglas fiscales con mayor solidez institucional. En el caso de los países de LAC, y en particular en Uruguay, si bien el gasto público reacciona positivamente al ciclo económico, no se encuentra evidencia estadísticamente significativa de que las reglas fiscales hayan logrado moderar este patrón en el período analizado.; The design and implementation of fiscal rules have been widely employed as instruments to promote fiscal discipline and mitigate the procyclical nature of public expenditure across countries. In Latin America and the Caribbean (LAC), public spending has traditionally exhibited a procyclical pattern, thereby limiting its capacity to serve a stabilising function during periods of recession or economic crisis. This dynamic has often led to fiscal adjustments with substantial social and economic costs. International experience, spanning both advanced and developing economies, suggests that well-designed fiscal rules can significantly enhance the sustainability of public finances. In this context, Uruguay introduced a new fiscal framework in 2020 through Law No. 19,889 (Ley de Urgente Consideración, LUC) and the 2020–2024 National Budget Law, incorporating provisions related to the&#xD;
structural fiscal balance, expenditure ceilings, and borrowing limits. However, the economic and social implications of these reforms have received limited attention in political and academic debates. Drawing on a comparative analysis of 167 countries, this study finds that public expenditure tends to behave procyclically in response to the macroeconomic cycle. Nevertheless, this effect is mitigated in institutional environments characterized by stronger fiscal rules. In the case of LAC countries—and Uruguay in particular—although&#xD;
public expenditure continues to respond positively to economic fluctuations, there is no statistically significant evidence that fiscal rules have succeeded in moderating this pattern during the period under review.</description>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://hdl.handle.net/20.500.12008/48543">
    <title>On standardness and the non-estimability of certain functionals of a set</title>
    <link>https://hdl.handle.net/20.500.12008/48543</link>
    <description>Título: On standardness and the non-estimability of certain functionals of a set
Autor: Cholaquidis, Alejandro; Moreno, Leonardo; Pateiro-López, Beatriz
Resumen: Standardness is a popular assumption in the literature on set estimation. It also appears in statistical approaches to topological data analysis, where it is common to assume that the data were sampled from a probability measure that satisfies the standard assumption. Relevant results in this field, such as rates of convergence and confidence sets, depend on the standardness parameter, which in practice may be unknown. In this paper, we review the notion of standardness and its connection to other geometrical restrictions. We prove the almost sure consistency of a plug-in type estimator for the so-called standardness constant, already studied in the literature. We propose a method to correct the bias of the plug-in estimator and corroborate our theoretical&#xD;
findings through a small simulation study. We also show that it is not possible to determine, based on a finite sample, whether a probability measure satisfies the standard assumption.</description>
    <dc:date>2023-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://hdl.handle.net/20.500.12008/48533">
    <title>Conformal inference for regression on Riemannian Manifolds</title>
    <link>https://hdl.handle.net/20.500.12008/48533</link>
    <description>Título: Conformal inference for regression on Riemannian Manifolds
Autor: Cholaquidis, Alejandro; Gamboa, Fabrice; Moreno, Leonardo
Resumen: Regression on manifolds, and, more broadly, statistics on manifolds, has garnered significant importance in recent years due to the vast number of applications for this type of data. Circular data is a classic example, but so is data in the space of covariance matrices, data on the Grassmannian manifold obtained as a result of principal component analysis, among many others. In this work we investigate prediction sets for regression scenarios when the response variable, denoted by Y, resides in a manifold, and the covariable, denoted by X, lies in Euclidean space. This extends the concepts delineated in [Lei and Wasserman, 2014] to this novel context. Aligning with traditional principles in conformal inference, these prediction sets are distribution-free, indicating that no specific assumptions are imposed on the joint distribution of (X, Y ), and they maintain a non-parametric character. We prove the asymptotic almost sure convergence of the empirical version of these regions on the manifold to their population counterparts. The efficiency of this method is shown through a comprehensive simulation study and an analysis involving real-world data.</description>
    <dc:date>2023-01-01T00:00:00Z</dc:date>
  </item>
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