The Past in the Present. Lessons on Semiotics of History from George H. Mead and Boris A. Uspensky

This article examines the parallels between George H. Mead's theory of time and Boris A. Uspensky's semiotics of history, looking for implications relevant to the symbolic interactionist theory of historical processes. It suggests that Mead's theory of time and theory of communication hold important implications for semiotic analysis of the historical dimension of sociocultural phenomena. A further aim is to link the symbolic interactionist tradition of the Chicago school with the Tartu school and its semiotics of history. This would fuel the further development of both theoretical orientations.     

Do people think about absolute or relative price differences when choosing between substitute goods?

The article presents experimental evidence that shows that people often consider relative price differences in addition to absolute differences when choosing between substitute goods. Because the choice between substitute goods is a very common one, this is an important finding. The experiment uses scenarios in various consumption categories: hotel rooms, flights, and books. Subjects were either students or participants in an economics conference. The data allow to reject the hypothesis that people think only about relative price differences in favor of the hypothesis that people think about both relative and absolute price differences. Whether the price given to the subjects is that of the high-quality good or of the low-quality good makes a large difference, a result that is related to the endowment effect and the status quo bias. Implications of the results for business strategy and other areas are also discussed.     

First‐order bias correction for fractionally integrated time series

Most of the long memory estimators for stationary fractionally integrated time series models are known to experience non‐negligible bias in small and finite samples. Simple moment estimators are also vulnerable to such bias, but can easily be corrected. In this article, the authors propose bias reduction methods for a lag‐one sample autocorrelation‐based moment estimator. In order to reduce the bias of the moment estimator, the authors explicitly obtain the exact bias of lag‐one sample autocorrelation up to the order n⁻¹. An example where the exact first‐order bias can be noticeably more accurate than its asymptotic counterpart, even for large samples, is presented. The authors show via a simulation study that the proposed methods are promising and effective in reducing the bias of the moment estimator with minimal variance inflation. The proposed methods are applied to the northern hemisphere data. The Canadian Journal of Statistics 37: 476–493; 2009 © 2009 Statistical Society of Canada     

《长恨歌》主题辨析

《长恨歌》主题历来颇多争议，在教学过程中亦常有“主题之辩”等疑窦。不管是暴露说、讽喻规正说还是爱情说，总觉得有失偏颇；双重或多重主题，尽管中庸，但又太过笼统。不妨在双重或多重主题的前提下，偏重情爱，偏重伤感，采用“讽婉”或“讽劝”等概念，就可较为准确地揭示《长恨歌》动之以情、婉转以劝并以帝王切身之痛而达到的基本价值取向，这将会更加切合诗的原意，而且还可以弥补或者中和学术界在定性李隆基和杨玉环关系方面存在的分歧进而达成共识。     

The debt trap: A two-compartment train wreck… and how to avoid it

We explore sustainable paths out of a debt trap with a highly stylized two-sector differential equations model for the stocks of money in Government and Society. The model fits the data for the U.S. between 1981 and 2012 with a coefficient of correlation of 0.996. The solutions provide detailed “escape conditions” from the debt trap. A primary surplus is required. Then a government can escape its debt trap either through sustained annual monetary outflows from society to the government (taxation) but with a low initial growth rate, or through annual monetary inflows into both sectors (stimulus) with higher initial growth rate. We illustrate the use of our model with simulations which show how five indebted countries can escape their debt trap in 30 (or 70) years.     

LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

ABSTRACT

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

Decomposing primary and secondary effects: A new decomposition method

One strand of educational inequality research aims at decomposing the effect of social class origin on educational choices into primary and secondary effects. We formalize this distinction and present a new and simple method that allows empirical assessment of the relative magnitudes of primary and secondary effects. Contrary to other decomposition methods, this new method is unbiased, is more intuitive, and decomposes effects of both discrete and continuous measures of social origin. The method also provides analytically derived statistical tests and is easily calculated with standard statistical software. We give examples using the Danish Longitudinal Survey of Youth.