Administrative Structure of the Sovereign State of Boyacá (1857-1886)

The present article has as objectives to show the organization and the functioning of the central administration of the state of Boyacá, as manifested through the President of the state and the secretaries of dispatch, to examine how they operated and which functions were assigned to them during the period of 1857 to 1886. These will be examined through the lenses of the 1857, 1863 and 1869 constitutions and their subsequent normative development as well as through the roles given them by the Legislative Assembly and the State President. Likewise, it will study the progress of the state as seen through the reports presented by the president and the secretaries of dispatch. It must be kept in mind that until now nothing has been written on this topic; the text is innovative in that it allows us to reconstruct a part of our national documentary heritage.

Preliminary factorial structure of the O’Kelly Women’s Belief Scales in Mexican population

A Back-translated Mexican version of the Austra- lian o’Kelly Women’s Belief scales was given to a sample of 363 women born and living in Mexico. A factor analysis with a varimax rotation with cu- toff eigenvalues of 3 showed that 36 out of the 92 items originally developed in the Australian study accounted for 40.138% of the variance, and could be ultimately grouped into two factors: one “ra- tionality” factor, with a total of 14 items, and one “Irrationality” factor with a total of 22 items, and with a very low Pearson’s rs (.119) between them. these results support the equivalency of the Mexi- can version to the original instrument used to iden- tify the presence of the reBt’s absolutistic, rigid beliefs about traditional feminine roles in women.

Estimating and Forecasting the Term Structure of Interest Rates:US and Colombia Analysis

In this paper we use the most representative models that exist in the literature on term structure of interest rates. In particular, we explore affine one factor models and polynomial-type approximations such as Nelson and Siegel. Our empirical application considers monthly data of USA and Colombia for estimation and forecasting. We find that affine models do not provide adequate performance either in-sample or out-of-sample. On the contrary, parsimonious models such as Nelson and Siegel have adequate results in-sample, however out-of-sample they are not able to systematically improve upon random walk base forecast.