Migrant-native socioeconomic differentials in Thailand

Recent research has suggested that the position of many urban migrants compares favorably with that of urban natives. This generalization is refined by referring to three key distinctions: migrants from rural versus urban origins, recent versus more experienced cityward migrants, and type of urban destination. In Thailand in the early 1970s, migrants to smaller urban centers, especially the more experienced migrants, are economically more successful than migrants to the large metropolitan centers and in some cases are more successful than urban natives. Reasons for this pattern are discussed.     

Improving Voting Systems through Service‐Operations Management

We apply service‐operations‐management concepts to improve the efficiency and equity of voting systems. Recent elections in the United States and elsewhere have been plagued by long lines, excessive waiting times, and perceptions of unfairness. We build models for the waiting lines at voting precincts using both traditional steady‐state queueing methods and simulation models. We develop solution methods to allocate voting machines optimally to precincts. Our objective functions consider both the efficiency and the equity of the voting system. We compare our allocation algorithm to several competing methods, including those used in practice. We examine several different strategies for improving voting operations on both the demand and the capacity side of voting systems, and we present a complete case study of applying our method to data from the 2008 election for Franklin County, Ohio. We conclude that our method is superior to existing polices in terms of efficiency and equity and that it is robust in terms of uncertainties regarding turnout rates on Election Day. We also suggest several operational improvements to the voting process drawn from the service‐operations literature.     

Gender Differences in Criminal Sentencing: Do Effects Vary Across Violent,Property, and Drug Offenses?*

Objective. Many studies find that females benefit from their gender in sentencing decisions. Few researchers, however, address whether the gender‐sentencing association might be stronger for some crimes, such as minor nonviolent offending, and weaker for other offenses, such as serious violent crime. Method. Using a large random sample of convicted offenders in Texas drawn from a statewide project on sentencing practices mandated by the 73rd Texas Legislature, logistic regression and OLS regression analyses of likelihood of imprisonment and prison length illustrate the importance of looking at sentencing outcomes not only in terms of gender but also in terms of crime type. Results. Specifically, we find that the effect of gender on sentencing does vary by crime type, but not in a consistent or predicted fashion. For both property and drug offending, females are less likely to be sentenced to prison and also receive shorter sentences if they are sentenced to prison. For violent offending, however, females are no less likely than males to receive prison time, but for those who do, females receive substantially shorter sentences than males. Conclusions. We conclude that such variation in the gender‐sentencing association across crime type is largely due to features of Texas' legal code that channel the level of discretion available to judges depending on crime type and whether incarceration likelihood or sentence length is examined.     

The Distribution of the Record Position and its Applications

This is mainly an expository article on the positions of records in sequences of ordered elements. Such sequences are obtained, for example, when observing and ordering continuous iid random variables. In practice, records are of interest, for example, in meteorology and sports. A k-record is obtained when a new element is placed at position k counted from the top. The sequences of time points, when new k-records occur, are studied by elementary random walk methods. In the last section, it is shown that the time scale can be changed so that the time points of the k-records follow, approximately, a Poisson process.     

Interest groups and strategic constructivism: business actors and border security policies in the European Union

Evidence suggests that business lobbying shapes European Union (EU) border security policies, but there has been no detailed empirical and theoretical work detailing how interest groups exert influence in this domain. Building on strategic constructivist accounts of policy-making, the article argues that EU border security policies have been tailored to the preferences, identities, and frames of business actors through three key processes. Policy preferences are co-constituted by business actors through strategic communication, identities are constructed to gain political legitimacy through strategic legitimation, and social contexts are framed to fit business interests through practices of strategic contextualisation. I use evidence from in-depth interviews with key actors in the field of EU border security policy-making, participant observation at key border security events, and analysis of key policy documents to build the argument.     

A Review of Some Modern Approaches to the Problem of Trend Extraction

This article presents a review of some modern approaches to trend extraction for one-dimensional time series, which is one of the major tasks of time series analysis. The trend of a time series is usually defined as a smooth additive component which contains information about the time series global change, and we discuss this and other definitions of the trend. We do not aim to review all the novel approaches, but rather to observe the problem from different viewpoints and from different areas of expertise. The article contributes to understanding the concept of a trend and the problem of its extraction. We present an overview of advantages and disadvantages of the approaches under consideration, which are: the model-based approach (MBA), nonparametric linear filtering, singular spectrum analysis (SSA), and wavelets. The MBA assumes the specification of a stochastic time series model, which is usually either an autoregressive integrated moving average (ARIMA) model or a state space model. The nonparametric filtering methods do not require specification of model and are popular because of their simplicity in application. We discuss the Henderson, LOESS, and Hodrick–Prescott filters and their versions derived by exploiting the Reproducing Kernel Hilbert Space methodology. In addition to these prominent approaches, we consider SSA and wavelet methods. SSA is widespread in the geosciences; its algorithm is similar to that of principal components analysis, but SSA is applied to time series. Wavelet methods are the de facto standard for denoising in signal procession, and recent works revealed their potential in trend analysis.