Who performs a stronger response to whom? Detecting individual competitive actions and reactions

This study analyzes the degree of competition through individual actions and reactions. Empirical support for this analysis has derived mainly from structural econometric models describing the nature of competition. This analysis extends the existing literature by empirically considering a direct measurement of competition through the analysis of the competitive actions and responses, and describing how firms compete within and between strategic groups. We estimate the firms’ conduct in the Spanish deposits market with 146 firms and 18,888 observations. This is a specially compelling context for the banking industry, in which a deregulation process gives rise to the adoption of aggressive strategies seeking to increase the market shares of deposit accounts; thus, producing a turbulent situation of increasing rivalry. Our results offer a deeper understanding of the firms’ competitive behavior, since we identify different patterns of actions and reactions depending upon the strategic group the firm belongs to.     

An algorithm to compute the cdf of the product of two normal random variables

This paper provides a fortran algorithm that can be used to compute the cdf of the product of two normal distribution random variables. We also give references that provide mathematical properties, tables, and applications of this distribution     

Open Borders to a Revolution: Culture,Politics and Migration

Susan Migden Socolow, The Bureaucrats of Buenos Aires, 1769–1810: Amor al Real Servicio (1987), xxi + 356 (Duke University Press, Durham, N.C., $45.00).

W. Hamish Fraser, Conflict and Class. Scottish Workers 1700–1838 (1988), 202 (John Donald, £20.00).

Margaret Ripley Wolfe, Kingsport, Tennessee: A Planned American City (1987), xii + 259 (The University Press of Kentucky, Lexington, £24.00).

Carl Chinn, They Worked All Their Lives. Women of the Urban Poor in England, 1880–1939 (1988), xii + 187 (Manchester University Press, Manchester, £22.50).

Linda Bryder, Below the Magic Mountain: A Social History of Tuberculosis in Twentieth‐Century Britain (1988), xv + 298 (Oxford University Press, Oxford, £30.00).

F. B. Smith, The Retreat of Tuberculosis 1850–1950 (1988), 271 (Croom Helm, £25.00).     

Risk Perception in a Developing Country: The Case of Chile

In this work we characterize risk perception in Chile, based on the psychometric paradigm, exploring the difference between perceived social and personal risk. For this purpose, we conducted a survey including 54 hazards, 16 risk attributes, and 3 risk constructs. The survey, divided into four parts, was administered to 508 residents of Santiago, Chile. Using factor analysis, three main factors, which accounted for 80% of the sample's variance, were identified: factor 1, commonly called "Dread Risk" in the literature, explained 37% of variance; factor 2, "Unknown Risk," explained 28%; and factor 3, which we called "Personal Effect," explained 15% of the variance. On average, individuals perceived themselves as less exposed to risk and with more control and knowledge about them than the general population. OLS regression models were used to test the association of perceived risk with the three main factors. For social risk, factor 1 had the greatest explanatory power, while factor 2 had a negative sign. For personal risk, only factors 2 and 3 were significant, with factor 3 having the greatest explanatory power. Risk denial (defined as the difference between perceived personal and social risk) was associated with factors 1 and 2 only, with factor 2 having a negative sign. The difference between desired and actual regulation levels proved positive for all hazards, thus indicating that Chileans are dissatisfied with the current regulation level for all the hazards analyzed. The comparison of data at the aggregate and at the individual subject's level suggests that while the aggregate analysis overestimates the magnitude of the correlations it still reflects the tendency of the individual responses.     

Population and Deforestation in Costa Rica

This paper addresses a central debate in research and policy on population and environment, namely the extent to which rapid population growth is associated with the massive deforestation currently underway in the tropics. We utilize the experience of Costa Rica during the last forty years to illustrate what the main issues are, discuss the history of deforestation in that country, and present results from conventional regression methods and from the application of spatial analyses. These analyses enable us to estimate the magnitude of the relation between population and deforestation and to identify the factors that are responsible for the linkage between them.     

Life Domain Satisfactions as Predictors of Overall Life Satisfaction Among Workers: Evidence from Chile

This article examines the subjective antecedents of life satisfaction of workers. Adopting a ‘bottom-up’ perspective, we assessed the unique influence that satisfaction with multiple life domains have on evaluative judgments of overall life satisfaction. Based on a nationwide sample of 530 Chilean workers, we simultaneously tested the effects of seven life domain satisfactions that have been consistently included in extant models of life satisfaction and subjective well-being. These were satisfaction with health, financial situation, social relationships, one’s self-worth, leisure-time, family, and work. Having controlled for age and gender, results showed that satisfaction with one’s financial situation was the dominant predictor of overall life satisfaction of workers, with a weight of .36. Satisfaction with family, work, and health had effects of .25, .14, and .14, respectively. Interestingly, satisfaction with one’s self-worth, leisure-time, and social relationships did not have statistically significant effects on life satisfaction, although the first two showed t values near the critical value.     

Are Poor Neighborhoods Resource Deprived? A Case Study of Childcare Centers in New York*

Objective. Many social scientists believe poor mothers are better off in middle‐class than in poor neighborhoods, partly because the latter are deprived of important institutional resources. We test whether poor neighborhoods are more likely to lack one critical institutional resource, the childcare center. Methods. We use geocoded data on all licensed centers in the City of New York, address matched to Census tracts. We estimate logit models of presence of center in tract, testing for the linear and nonlinear effects of tract poverty level after controlling for residential instability, joblessness, ethnic makeup, and other demographic factors. We complement the analysis with documentary, interview, and ethnographic data on centers in one poor and one nonpoor neighborhood in the city. Results. We find (1) that the probability of presence of a childcare center does not decrease as poverty level increases; (2) the relationship depends strongly on funding source, with privately funded centers being less likely and publicly funded ones more likely to be present in poor neighborhoods; and (3) at least two factors affect why poor neighborhoods are more likely to have certain centers, the local state and the (often neglected) nonprofit infrastructure. Conclusions. The findings suggest that poor mothers are not necessarily better off in middle‐class neighborhoods in this respect. The market assumptions underlying the initial hypothesis should be modified. More empirical research on the effect of the nonprofit sector on the prevalence of neighborhood institutions is needed.     

Diagnostic tools in generalized Weibull linear regression models

We propose some statistical tools for diagnosing the class of generalized Weibull linear regression models [A.A. Prudente and G.M. Cordeiro, Generalized Weibull linear models, Comm. Statist. Theory Methods 39 (2010), pp. 3739–3755]. This class of models is an alternative means of analysing positive, continuous and skewed data and, due to its statistical properties, is very competitive with gamma regression models. First, we show that the Weibull model induces ma-ximum likelihood estimators asymptotically more efficient than the gamma model. Standardized residuals are defined, and their statistical properties are examined empirically. Some measures are derived based on the case-deletion model, including the generalized Cook's distance and measures for identifying influential observations on partial F-tests. The results of a simulation study conducted to assess behaviour of the global influence approach are also presented. Further, we perform a local influence analysis under the case-weights, response and explanatory variables perturbation schemes. The Weibull, gamma and other Weibull-type regression models are fitted into three data sets to illustrate the proposed diagnostic tools. Statistical analyses indicate that the Weibull model fitted into these data yields better fits than other common alternative models.