On Variational Bayes Estimation and Variational Information Criteria for Linear Regression Models

Variational Bayes (VB) estimation is a fast alternative to Markov Chain Monte Carlo for performing approximate Baesian inference. This procedure can be an efficient and effective means of analyzing large datasets. However, VB estimation is often criticised, typically on empirical grounds, for being unable to produce valid statistical inferences. In this article we refute this criticism for one of the simplest models where Bayesian inference is not analytically tractable, that is, the Bayesian linear model (for a particular choice of priors). We prove that under mild regularity conditions, VB based estimators enjoy some desirable frequentist properties such as consistency and can be used to obtain asymptotically valid standard errors. In addition to these results we introduce two VB information criteria: the variational Akaike information criterion and the variational Bayesian information criterion. We show that variational Akaike information criterion is asymptotically equivalent to the frequentist Akaike information criterion and that the variational Bayesian information criterion is first order equivalent to the Bayesian information criterion in linear regression. These results motivate the potential use of the variational information criteria for more complex models. We support our theoretical results with numerical examples.     

Covariate Decomposition Methods for Longitudinal Missing‐at‐Random Data and Predictors Associated with Subject‐Specific Effects

Investigators often gather longitudinal data to assess changes in responses over time within subjects and to relate these changes to within‐subject changes in predictors. Missing data are common in such studies and predictors can be correlated with subject‐specific effects. Maximum likelihood methods for generalized linear mixed models provide consistent estimates when the data are ‘missing at random’ (MAR) but can produce inconsistent estimates in settings where the random effects are correlated with one of the predictors. On the other hand, conditional maximum likelihood methods (and closely related maximum likelihood methods that partition covariates into between‐ and within‐cluster components) provide consistent estimation when random effects are correlated with predictors but can produce inconsistent covariate effect estimates when data are MAR. Using theory, simulation studies, and fits to example data this paper shows that decomposition methods using complete covariate information produce consistent estimates. In some practical cases these methods, that ostensibly require complete covariate information, actually only involve the observed covariates. These results offer an easy‐to‐use approach to simultaneously protect against bias from both cluster‐level confounding and MAR missingness in assessments of change.     

Sense of belonging in secondary schools: a survey of LGB and heterosexual students in Flanders

This study focuses on differences in sense of belonging between lesbian, gay, and bisexual (LGB) and heterosexual students. Data from 1,745 secondary school students were collected with an online survey. Step-wise multiple regression analyses was used to investigate the relationship between sexual orientation and sense of school belonging. The results show that sexual orientation has an impact on sense of belonging for girls, but not for boys. Perceived discrimination and LGB friendliness of the school appeared to be important indicators of sense of belonging for all the respondents, irrespective of their sexual orientation.     

Piece rates and workplace injury: Does survey evidence support Adam Smith?

While piece rates are routinely associated with higher productivity and wages, they can also generate unanticipated effects. Using cross-country European data, we provide among the first general survey evidence of a strong link between piece rates and workplace injury. Despite controls for workplace hazards, job characteristics and worker effort, piece rates workers suffer a 5 percentage point greater likelihood of injury. This remains despite attempts to control for endogeneity and heterogeneity. As piece rate wage premium estimates rarely control for injury likelihood, this raises the specter that part of that premium reflects a compensating wage differential for risk of injury.     

A location analysis approach for military maintenance scheduling with geographically dispersed service areas

This research uses a two-stage maximal covering location problem (MCLP) model to develop Inter continental ballistic missile (ICBM) maintenance schedules for the US Air Force. Solutions are compared to actual missile maintenance activities accomplished at F. E. Warren Air Force Base (AFB), Wyoming in May 2005. Sensitivity analysis is performed to determine the impact of altering security response times and the number of security patrol areas on the quality of daily maintenance schedules and personnel usage. Results indicate marked improvement over traditional Air Force scheduling methods. In addition sensitivity analysis identifies the levels at which the quality and quantity of maintenance performance is impacted.     

Calibration of FISK, an Invasiveness Screening Tool for Nonnative Freshwater Fishes

Adapted from the weed risk assessment (WRA) of Pheloung, Williams, and Halloy, the fish invasiveness scoring kit (FISK) was proposed as a screening tool for freshwater fishes. This article describes improvements to FISK, in particular the incorporation of confidence (certainty/uncertainty) ranking of the assessors' responses, and reports on the calibration of the score system, specifically: determination of most appropriate score thresholds for classifying nonnative species into low-, medium-, and high-risk categories, assessment of the patterns of assessors' confidences in their responses in the FISK assessments. Using receiver operating characteristic (ROC) curves, FISK was demonstrated to distinguish accurately (and with statistical confidence) between potentially invasive and noninvasive species of nonnative fishes, with the statistically appropriate threshold score for high-risk species scores being ≥19. Within the group of species classed as high risk using this new threshold, a "higher risk" category could be visually identified, at present consisting of two species (topmouth gudgeon Pseudorasbora parva and gibel carp Carassius gibelio ). FISK represents a useful and viable tool to aid decision- and policymakers in assessing and classifying freshwater fishes according to their potential invasiveness.     

The Effect of Expected Income on Individual Migration Decisions

This paper develops a tractable econometric model of optimal migration, focusing on expected income as the main economic influence on migration. The model improves on previous work in two respects: it covers optimal sequences of location decisions (rather than a single once‐for‐all choice) and it allows for many alternative location choices. The model is estimated using panel data from the National Longitudinal Survey of Youth on white males with a high‐school education. Our main conclusion is that interstate migration decisions are influenced to a substantial extent by income prospects. The results suggest that the link between income and migration decisions is driven both by geographic differences in mean wages and by a tendency to move in search of a better locational match when the income realization in the current location is unfavorable.     

Qipao： Traditional Elegance Reinvents Itself In Modern Chinese Fashion

It was with some trepidation that I first went to teach in China, in 2004.All my information about China had come from old newsreel films. Basically,I was expecting a drab, black and white place where people queued to use the local telephone.     

Modeling the Niger Delta Insurgency

Nigeria's oil guarantees its role in the global economy; however, the state's overwhelming weaknesses perpetuate a high level of volatility vis-à-vis the potential for an immediate disruption of the national, regional, and global environment. This study presents a current qualitative analysis of Nigeria to produce a model that characterizes current conditions in the state and the state response to the nefarious acts in the delta region. This model will serve as a baseline for a significant iteration of the model that reflects the delta region counter-insurgency at various levels of strength: a what-if scenario of the region with an increase of state security over southern separatists, insurgents seeking to gain control of the oil assets. The conjectured model serves to inform/educate decision and policy makers in developing proactive, effective strategies to counter existent and potential threats in the Niger Delta.