Business reform outcomes: Why so different?

Post-crisis policy making increasingly focuses on doing business reforms. We argue that the effects of those reforms will be different across countries. To understand the reasons for the reform outcome divergence, we advance a novel firm-size distribution (FSDs) argument. At the center of the argument is the fact that FSDs are different across countries and stable over time. Then, if a given doing business reform induces firms of different size to grow differently, this will produce a variety of reform outcomes across countries. To advance the argument, we set up a tractable general equilibrium (GE) model and study how firms of different size grow after a doing business reform. The model predicts that larger firms will grow faster than smaller firms after the reform. The model predictions are tested on the Enterprise Surveys (ES) data, merged with the Doing Business indicators. We confirm that firms of different size grow differently after a Doing Business reform. Thus, based on the notable differences of firm size distributions across countries, identical reforms to start, operate and close a business will produce a variety of reform outcomes across countries.     

Sociopolitical control among parents of school-age children in a post-socialist city

This study explored sociopolitical control among parents of school-age children in a suburban municipality of a large post-socialist city. The participants completed a questionnaire that asked them about their sense of sociopolitical control in terms of leadership competence and policy control, as well as about other aspects of their lives, including mental health. The findings show that the participants have a greater sense of sociopolitical control in terms of leadership competence than in terms of policy control. Moreover, the findings show that voting in the last presidential election and degree of depression influenced negatively the sense of leadership competence among parti-cipants. Within the context of empowerment, the findings have implications for practice which focuses on consumer-based activities that allow citizens more leadership opportunities and control at the local level. Future research is needed that replicates this study, taking into account its limitations. In order for citizens in post-socialist countries to create civil societies at the same time that they implement market economies, they must be empowered. Some evidence suggests that several factors, including mental health problems, may influence the sense of empowerment among citizens in post-socialist coun-tries. Within the context of empowerment, this study examines sociopolitical control among citizens in a suburb of a large post-socialist city. The findings in the study have implications for social welfare practice in this city and for future research.     

On Large Deviations of Sums of Independent Random Variables

Extensions of some limit theorems are proved for tail probabilities of sums of independent identically distributed random variables satisfying the one-sided or two-sided Cramér's condition. The large deviation x-region under consideration is broader than in the classical Cramér's theorem, and the estimate of the remainder is uniform with respect to x. The corresponding asymptotic expansion with arbitrarily many summands is also obtained.     

Anti‐foreigner Sentiment: State of the Art

This review presents the contributions of anti‐foreigner sentiment research, its theoretical and methodological limitations, and potential solutions for its further development. Six different explanations are proposed to account for the distribution of anti‐foreigner sentiment within and across countries: economic competition, human capital, cultural affinity, social capital, political values, and the institutional environment. In this review, we argue that much of the extant literature heavily emphasizes variables, rather than causal mechanisms, and exhibits three main methodological limitations: (a) variable selection bias; (b) determining causality; and (c) endogeneity. We propose synthesizing prevailing theoretical perspectives around causal mechanisms and reformulating predictive models to strengthen a promising research program.     

On lower bounds for tail probabilities

Chebyshev's inequality and its generalizations make it possible to give upper bounds for the tail probabilities in the distribution of a random variable. We present a method of finding lower bounds for these probabilities . The method is based on improvements of the Lyapunov inequality for moments of a random variable.     

Revising the Harris-Todaro framework to model labour migration from the Canadian Northern frontier

The Harris-Todaro model of labour migration was developed almost four decades ago, and since has become a classic method of migration analysis in less developed countries. This paper explores the applicability of the Harris-Todaro (HT) framework outside its traditional use, by modelling frontier-metropolis migration in Canada. If appropriate, the framework can potentially be used in other countries with similar regional dichotomies, such as Russia and Australia. The paper argues that the HT model is generally applicable in the context of migration from the resource frontier to large metropolitan areas of the Canadian south, although it requires several modifications. The classic HT model is extended to account for northern labour-force heterogeneity (Aboriginal and Non-Aboriginal), the possibility of having or losing jobs in the declining and undiversified frontier economy, and living cost differentials. Further analysis is focused on Aboriginal migration from isolated northern communities. The plausibility of the modified HT model is demonstrated using an empirical test, in which the model is used to assess migration probabilities of Aboriginal labour migrants. These new insights into the mechanisms of frontier-metropolis migration could provide a better basis for developing planning strategies, aimed to sustain human capital in the Canadian North, and for optimizing welfare policies both in the North and in the South.     

Asteroid Risk Assessment: A Probabilistic Approach

Following the 2013 Chelyabinsk event, the risks posed by asteroids attracted renewed interest, from both the scientific and policy‐making communities. It reminded the world that impacts from near‐Earth objects (NEOs), while rare, have the potential to cause great damage to cities and populations. Point estimates of the risk (such as mean numbers of casualties) have been proposed, but because of the low‐probability, high‐consequence nature of asteroid impacts, these averages provide limited actionable information. While more work is needed to further refine its input distributions (e.g., NEO diameters), the probabilistic model presented in this article allows a more complete evaluation of the risk of NEO impacts because the results are distributions that cover the range of potential casualties. This model is based on a modularized simulation that uses probabilistic inputs to estimate probabilistic risk metrics, including those of rare asteroid impacts. Illustrative results of this analysis are presented for a period of 100 years. As part of this demonstration, we assess the effectiveness of civil defense measures in mitigating the risk of human casualties. We find that they are likely to be beneficial but not a panacea. We also compute the probability—but not the consequences—of an impact with global effects (“cataclysm”). We conclude that there is a continued need for NEO observation, and for analyses of the feasibility and risk‐reduction effectiveness of space missions designed to deflect or destroy asteroids that threaten the Earth.     

Large Deviations for Sums of Independent Non Identically Distributed Random Variables

This article considers large deviation results for sums of independent non identically distributed random variables, generalizing the result of Petrov (1968 Petrov , V. V. ( 1968 ). Asymptotic behavior of probabilities of large deviations . Theor. Probab. Appl. 13 : 408 – 420 . [Google Scholar]) by using a weaker and more natural condition on bounds of the cumulant generating functions of the sequence of random variables.     

On the convergence of two sequential Monte Carlo methods for maximum a posteriori sequence estimation and stochastic global optimization

This paper addresses the problem of maximum a posteriori (MAP) sequence estimation in general state-space models. We consider two algorithms based on the sequential Monte Carlo (SMC) methodology (also known as particle filtering). We prove that they produce approximations of the MAP estimator and that they converge almost surely. We also derive a lower bound for the number of particles that are needed to achieve a given approximation accuracy. In the last part of the paper, we investigate the application of particle filtering and MAP estimation to the global optimization of a class of (possibly non-convex and possibly non-differentiable) cost functions. In particular, we show how to convert the cost-minimization problem into one of MAP sequence estimation for a state-space model that is “matched” to the cost of interest. We provide examples that illustrate the application of the methodology as well as numerical results.