LONG‐TERM PERSISTENCE

We study whether a positive historical shock can generate long‐term persistence in development. We show that Italian cities that achieved self‐government in the Middle Ages have a higher level of civic capital today than similar cities in the same area that did not. The size of this effect increases with the length of the period of independence and its intensity. This effect persists even after accounting for the fact that cities did not become independent randomly. We conjecture that the Middle‐Age experience of self‐government fostered self‐efficacy beliefs—beliefs in one's own ability to complete tasks and reach goals—and this positive attitude, transmitted across generations, enhances civic capital today. Consistently, we find that fifth‐graders in former free city‐states exhibit stronger self‐efficacy beliefs and that these beliefs are correlated with a higher level of civic capital. (JEL: O43, P16, O10)     

Decomposition of cumulative chi-squared statistics,with some new tools for their interpretation

It is well known that the Pearson statistic \(\chi ^{2}\) can perform poorly in studying the association between ordinal categorical variables. Taguchi’s and Hirotsu’s statistics have been introduced in the literature as simple alternatives to Pearson’s chi-squared test for contingency tables with ordered categorical variables. The aim of this paper is to shed new light on these statistics, stressing their interpretations and characteristics, providing in this way new and different interpretations of these statistics. Moreover, a theoretical scheme is developed showing the links between the different proposals and classes of cumulative chi-squared statistical tests, starting from a unifying index of heterogeneity, unalikeability and variability measures. Users of statistics may find it attractive to understand well the different proposals. Some decompositions of both statistics are also highlighted. This paper presents a case study of optimizing the polysilicon deposition process in a very large-scale integrated circuit, to identify the optimal combination of factor levels. It is obtained by means of the information coming from a correspondence analysis based on Taguchi’s statistic and regression models for binary dependent variables. A new optimal combination of factor levels is obtained, different from many others proposed in the literature for this data.     

Modeling random and non-random decision uncertainty in ratings data: a fuzzy beta model

AStA Advances in Statistical Analysis - Modeling human ratings data subject to raters’ decision uncertainty is an attractive problem in applied statistics. In view of the complex interplay...