On the measurement of diffuse support: Some evidence from MexicoSeligson, Mitchell A.
doi: 10.1007/BF00428858pmid: N/A
Abstract A large body of theoretical research suggests a strong association between diffuse support for the political system and political stability. Yet, empirical research has paid little attention to the measurement of diffuse support, preferring instead to rely uncritically upon the Trust in Government index devised many years ago. This paper seeks to test a new measure, Political Support-Alienation with data from Mexico. The alternative measure is shown to have greater reliability and validity than the standard measure. Important implications for the interpretation of levels of diffuse support in Mexico emerge from the analysis. Data from the United states and Costa Rica are introduced to provide comparative perspective.
Objective and subjective income adequacy: Their relationship to perceived life quality measuresAckerman, Norleen;Paolucci, Beatrice
doi: 10.1007/BF00428859pmid: N/A
Abstract The study investigated the extent to which income adequacy was related to satisfaction with perceived overall life quality and two of the more economically based domains of life quality: satisfaction with family income and satisfaction with level of consumption. A representative national sample of 1046 adults was interviewed. Findings indicated that as income adequacy increased, whether objectively or subjectively measured, satisfaction with each of the three life quality measures also increased. Income adequacy explained more of the variance in the two economically based domains than in the more global area of overal life quality. Thus income adequacy was a contributor to life quality, but other domains of life experience were also important. Subjective adequacy explained more of the variation in each of the three life quality measures than did objective adequacy. While respondents differed significantly in the congruency in their subjective and objective adequacy levels, that difference explained very little of the variation in satisfaction with the three life quality measures.
The growing impact of marriageVeenhoven, Ruut
doi: 10.1007/BF00428860pmid: N/A
Abstract In present day Western society the institution of marriage appears to be of great significance for the well-being of the individual. Compared with married persons, the unmarried are generally less happy, less healthy, more disturbed and more prone to premature death. Among the married, happiness and health are highly dependent on marital success. The idea has been floated that the importance of marriage is now gradually declining. It is believed that single life is becoming more satisfying and that married persons are gradually becoming less dependent on their spouses. Empirical data do not substantiate that belief. Firstly, the differences in well-being between unmarried and married persons are becoming greater rather than smaller. In the Netherlands — between 1950 and 1980 — suicide rates have risen far more among the unmarried than among the married. Furthermore the differences in happiness between unmarried and married persons appear greatest in the most modern European countries, whereas almost no differences exist in the most traditional ones. Secondly, married persons appear to have become more dependent on the relationship with their spouse rather than less. During the last few decades in the Netherlands the overall happiness of married people has become more closely associated with their satisfaction with marriage. These trends can be interpreted as suggesting that marriage is becoming an increasingly indispensable ‘haven’ in an increasingly ‘privatizing’ world.
Community-level determinants of infant and child mortality in peruYoung, Frank W.;Edmonston, Barry;Andes, Nancy
doi: 10.1007/BF00428861pmid: N/A
Abstract A technique is proposed for calculating community-level sex-specific infant and child mortality on the basis of the household data collected by the World Fertiligy Survey. These estimates then serve as dependent variables for a multivariate analysis of 84 Peruvian communities of less than 25 000 population. This analysis is guided by a quasi-theoretical strategy that puts three classes of variables in competition: physical ecology, program interventions, and social structure. The representative of the first category, altitude, was significantly associated with male and female child mortality when the other independent variables were controlled. However this result is probably better interpreted as an indirect effect of social organization in the mountainous areas. The representative variable of the second category, number of local medical institutions, was unrelated to any of the four dependent variables. All three of the indicators of the social organization-community population size, proportion of educated women, and proportion speaking Spanish-were negatively correlated with the dependent variables as expected, but in the multivariate analysis only female education continued to be a consistent negative predictor. However, there is reason to believe that population size and capacity to speak the national language would be predictors with a larger sample. The paper concludes with a preliminary analysis of those communities having significantly higher or lower mortality rates than would have been expected on the basis of a knowledge of Spanish, education, community size and local medical facilities. Such deviant case analysis may pinpoint “problem communities” or, alternatively, communities with special advantages.
A comparison of regression and ARIMA models for assessing program effects: An application to the mandated highway speed limit reduction of 1974Veney, James E.;Luckey, James W.
doi: 10.1007/BF00428862pmid: N/A
Abstract Time series analysis is a technique which has been utilized by econometricians and others for examining the relationship between events and time, particularly for forecasting purposes. More recent work has focused on time series analysis as a method to evaluate the effects of an exogenous event on a series. The major advantage of the interrupted time series design over a simple pre-post comparison is that the form of the change is taken into account. This paper will examine two alternative models for analyzing such data: regression and ARIMA. An example of the application of the two models will be demonstrated using data on highway deaths in North Carolina occurring before and after the national reduction in speed limits instituted in 1974. Conclusions are drawn about the comparative usefulness of these two techniques for program evaluation.