Estimating nonlinear additive models with nonstationarities and correlated errors

In this paper, we study a nonparametric additive regression model suitable for a wide range of time series applications. Our model includes a periodic component, a deterministic time trend, various component functions of stochastic explanatory variables, and an AR(p) error process that accounts for serial correlation in the regression error. We propose an estimation procedure for the nonparametric component functions and the parameters of the error process based on smooth backfitting and quasimaximum likelihood methods. Our theory establishes convergence rates and the asymptotic normality of our estimators. Moreover, we are able to derive an oracle‐type result for the estimators of the AR parameters: Under fairly mild conditions, the limiting distribution of our parameter estimators is the same as when the nonparametric component functions are known. Finally, we illustrate our estimation procedure by applying it to a sample of climate and ozone data collected on the Antarctic Peninsula.     

Long-Term Earnings Differentials Between African American and White Men by Educational Level

This paper investigates long-term earnings differentials between African American and white men using data that match respondents in the Survey of Income and Program Participation to 30 years of their longitudinal earnings as recorded by the Social Security Administration. Given changing labor market conditions over three decades, we focus on how racial differentials vary by educational level because the latter has important and persistent effects on labor market outcomes over the course of an entire work career. The results show that the long-term earnings of African American men are more disadvantaged at lower levels of educational attainment. Controlling for demographic characteristics, work disability, and various indicators of educational achievement does not explain the lower long-term earnings of less-educated black men in comparison to less-educated white men. The interaction arises because black men without a high school degree have a larger number of years of zero earnings during their work careers. Other results show that this racial interaction by educational level is not apparent in cross-sectional data which do not provide information on the accumulation of zero earnings over the course of 30 years. We interpret these findings as indicating that compared to either less-educated white men or highly educated black men, the long-term earnings of less-educated African American men are likely to be more negatively affected by the consequences of residential and economic segregation, unemployment, being out of the labor force, activities in the informal economy, incarceration, and poorer health.     

Cyclical Evolution of the Global Right

An understanding of the current right‐wing national and transnational social movements can benefit from comparing them to the global and national conditions operating during their last appearance in the first half of the twentieth century and by carefully comparing twentieth‐century fascism with the neofascist and right‐wing populist movements that have been emerging in the twenty‐first century. This allows us to assess the similarities and differences, and to gain insights about what could be the consequences of the reemergence of populist nationalism and fascist movements. Our study uses the comparative evolutionary world‐systems perspective to study the Global Right from 1800 to the present. We see fascism as a form of capitalism that emerges when the capitalist project is in crisis. World historical waves of right‐wing populism and fascism are caused by the cycles of globalization and deglobalization, the rise and fall of hegemonic core powers, long business cycles (the Kondratieff wave), and interactions with both Centrist Liberalism and the Global Left. We consider how crises of the global capitalist system have produced right‐wing backlashes in the past, and how a future terminal crisis of capitalism could lead to a reemergence of a new form of authoritarian global governance or a reorganized global democracy in the future.     

Women’s mobility and ‘transport-related social exclusion’ in Bishkek

This paper analyses gendered mobilities in Bishkek in the space of the most popular form of public transport: the minibus, or ‘marshrutka’. As the means by which women often access various important sites of daily life, the marshrutka itself is a site of negotiation and interaction. Utilizing theories of mobility and empirical data, we argue that marshrutkas are spaces that can give rise to two dichotomous conditions: positive marshrutka experiences may increase the social mobility of female passengers and subsequently increase social empowerment and influence, while negative ones can provide the grounds for social exclusion and gender inequality.     

“It Is What It Is”: Masculinity,Homosexuality, and Inclusive Discourse in Mixed Martial Arts

In this article we make use of inclusive masculinity theory to explore online media representations of male homosexuality and masculinity within the increasingly popular combat sport of mixed martial arts (MMA). Adopting a case-study approach, we discuss narratives constructed around one aspirational male MMA fighter, Dakota Cochrane, whose history of having participated in gay pornography became a major talking point on a number of MMA discussion/community Web sites during early 2012. While these narratives attempted to discursively rescue Cochrane’s supposedly threatened masculinity, highlighting both his “true” heterosexuality and his prodigious fighting abilities, they also simultaneously celebrated the acceptance of homosexual men within the sport that Cochrane’s case implied. Thus, we suggest that these media representations of homosexuality and masculinity within MMA are indicative of declining cultural homophobia and homohysteria and an inclusive vision of masculinity, as previously described by proponents of inclusive masculinity theory.     

Statistical Inference Enables Bad Science; Statistical Thinking Enables Good Science

ABSTRACT

Scientific research of all kinds should be guided by statistical thinking: in the design and conduct of the study, in the disciplined exploration and enlightened display of the data, and to avoid statistical pitfalls in the interpretation of the results. However, formal, probability-based statistical inference should play no role in most scientific research, which is inherently exploratory, requiring flexible methods of analysis that inherently risk overfitting. The nature of exploratory work is that data are used to help guide model choice, and under these circumstances, uncertainty cannot be precisely quantified, because of the inevitable model selection bias that results. To be valid, statistical inference should be restricted to situations where the study design and analysis plan are specified prior to data collection. Exploratory data analysis provides the flexibility needed for most other situations, including statistical methods that are regularized, robust, or nonparametric. Of course, no individual statistical analysis should be considered sufficient to establish scientific validity: research requires many sets of data along many lines of evidence, with a watchfulness for systematic error. Replicating and predicting findings in new data and new settings is a stronger way of validating claims than blessing results from an isolated study with statistical inferences.     

Evaluating social investment in disability policy

Disability policy in European countries is displaying a shift towards social investment: increasing human capital and access to the labour market. The reasoning that underlies this transition is that disabled persons would benefit from mainstream employment, but are impeded in traditional policy by deficiencies in labour supply and demand. However, the shift towards more activating policies in many countries is accompanied by a decline in social protection. It is unclear whether social investment may effectively promote the employment chances of disabled persons within this context. The present research examines this question through a quantitative, cross-sectional, multilevel analysis on microdata from 22 EU countries. Our findings suggest greater activation to predict lower employment chances, while reducing passive support shows mixed effects. Conversely, measures for facilitation in daily life predict greater employment chances, as do measures for sheltered work. These findings raise questions over the value of social investment for disabled persons—and underline the need to overcome broader barriers in the labour market and in society.