Coming home from a MOOC

My ten-week Massive Open Online Course "Statistical Mechanics: Algorithms and Computations", in early 2014, focused on subjects such as Monte Carlo sampling, molecular dynamics, transition phases in hard-sphere liquids, simulated annealing, classical spin models, quantum Monte Carlo algorithms, and Bose-Einstein condensation, etc. It familiarized a huge international crowd of students with cutting-edge subjects in computational physics. Here, I present the topics of the course, its basic design ideas, its scope and challenges, and compare it with earlier attempts in online teaching.Comment: 4 page editorial, based on a talk at the XXVIth IUPAP Conference on Computational Physics, CCP2014 (August 11-14, 2014, Boston, Massachusetts, USA

First Records of \u3ci\u3eCecidomyia Candidipes\u3c/i\u3e (Diptera: Cecidomyiidae) in Wisconsin

First report of Cecidomyia candidipes from five Wisconsin counties

Peer and selection effects on youth smoking in California

A number of studies have indicated that peer smoking is a highly influential factor in a young person's decision to smoke. However, these results are suspect because the studies often fail to account for selection and simultaneity bias. This paper develops an econometric model of youth smoking which incorporates both peer effects and selection effects, and estimates its parameters using data on California youth. Identification is achieved by using the degree of selection on observables as a proxy for the degree of selection on unobservables. The results indicate that the influence of peers on a young person's decision to smoke is much weaker than is suggested by reduced form models.social interactions, peer effects, smoking, substance use

New Records of Rhopalosomatidae (Hymenoptera: Vespoidea) From Wisconsin

The rhopalosomatid Olixon banksii is recorded from Wisconsin for the first time

Peer effects and selection effects in youth smoking

social interactions, peer effects

Simulation-based estimation of peer effects

The influence of peer behavior on an individual's choices has received renewed interest in recent years. However, accurate measures of this influence are difficult to obtain. Standard reduced-form methods lead to upwardly biased estimates due to simultaneity, common shocks, and nonrandom peer group selection. This paper describes a structural econometric model of peer effects in binary choice, as well as a simulated maximum likelihood estimator for its parameters. The model is nonparametrically identified under plausible restrictions, and can place informative bounds on parameter values under much weaker restrictions. Monte Carlo results indicate that this estimator performs better than a reduced form approach in a wide variety of settings. A brief application to youth smoking demonstrates the method and suggests that previous studies dramatically overstate peer influence.social interactions, peer effects, neighborhood effects