Estimating Price Elasticities When there is Smuggling: The Sensitivity of Smoking to Price in Canada

A central parameter for evaluating tax policies is the price elasticity of demand for cigarettes. But in many countries this parameter is difficult to estimate reliably due to widespread smuggling, which significantly biases estimates using legal sales data. An excellent example is Canada, where widespread smuggling in the early 1990s, in response to large tax increases, biases upwards the response of legal cigarette sales to price. We surmount this problem through two approaches: excluding the provinces and years where smuggling was greatest; and using household level expenditure data on smoking, where there is a downward bias to estimated elasticities from smuggling. These two approaches yield a tightly estimated elasticity in the range of -0.45 to -0.47. We also show that the sensitivity of smoking to price is much larger among lower income Canadians. In the context of recent behavioral models of smoking, whereby higher taxes reduce unwanted smoking among price sensitive populations, this finding suggests that cigarette taxes may not be as regressive as previously suggested. Finally, we show that price increases on cigarettes do not increase, and may actually decrease, consumption of alcohol; as a result, smuggling of cigarettes may have raised consumption of alcohol as well.

Collaborative Targeted Maximum Likelihood Estimation

Collaborative double robust targeted maximum likelihood estimators represent a fundamental further advance over standard targeted maximum likelihood estimators of causal inference and variable importance parameters. The targeted maximum likelihood approach involves fluctuating an initial density estimate, (Q), in order to make a bias/variance tradeoff targeted towards a specific parameter in a semi-parametric model. The fluctuation involves estimation of a nuisance parameter portion of the likelihood, g. TMLE and other double robust estimators have been shown to be consistent and asymptotically normally distributed (CAN) under regularity conditions, when either one of these two factors of the likelihood of the data is correctly specified. In this article we provide a template for applying collaborative targeted maximum likelihood estimation (C-TMLE) to the estimation of pathwise differentiable parameters in semi-parametric models. The procedure creates a sequence of candidate targeted maximum likelihood estimators based on an initial estimate for Q coupled with a succession of increasingly non-parametric estimates for g. In a departure from current state of the art nuisance parameter estimation, C-TMLE estimates of g are constructed based on a loss function for the relevant factor Q_0, instead of a loss function for the nuisance parameter itself. Likelihood-based cross-validation is used to select the best estimator among all candidate TMLE estimators in this sequence. A penalized-likelihood loss function for Q_0 is suggested when the parameter of interest is borderline-identifiable. We present theoretical results for collaborative double robustness, demonstrating that the collaborative targeted maximum likelihood estimator is CAN when Q and g are both mis-specified, providing that g solves a specified score equation implied by the difference between the Q and the true Q_0. This marks an improvement over the current definition of double robustness in the estimating equation literature. We also establish an asymptotic linearity theorem for the C-DR-TMLE of the target parameter, showing that the C-DR-TMLE is more adaptive to the truth, and, as a consequence, can even be super efficient if the first stage density estimator does an excellent job itself with respect to the target parameter. This research provides a template for targeted efficient and robust loss-based learning of a particular target feature of the probability distribution of the data within large (infinite dimensional) semi-parametric models, while still providing statistical inference in terms of confidence intervals and p-values. This research also breaks with a taboo (e.g., in the propensity score literature in the field of causal inference) on using the relevant part of likelihood to fine-tune the fitting of the nuisance parameter/censoring mechanism/treatment mechanism

tmle: An R Package for Targeted Maximum Likelihood Estimation

Targeted maximum likelihood estimation (TMLE) presents an approach for construction of an efficient double-robust semi-parametric substitution estimator of a target feature of the data generating distribution, such as a statistical association measure or a causal effect parameter. tmle is a recently developed R package that implements TMLE for estimation of the effect of a binary treatment at a single point in time on an outcome of interest, controlling for user supplied covariates: the additive treatment effect, the relative risk, the odds ratio. The package allows outcome data with missingness, and experimental units that contribute repeated records of the point-treatment data structure, thereby allowing this package to analyze longitudinal data structures. The TMLE of the direct effect of the binary treatment, controlling for a binary intermediate variable on the pathway from treatment to the outcome, is also implemented. Estimation of the parameters of a marginal structural model for binary treatments is also provided. Relevant factors of the likelihood may be modeled or fit by user-specified commands, or fit data-adaptively internally. Effect estimates, variances, p-values, and 95% confidence intervals are provided by the software

Optimal Composite Material for Low Cost Fabrication of Large Composite Aerospace Structures using NASA Resins or POSS Nanoparticle Modifications

Thermoplastic laminates in situ consolidated via tape or tow placement require full mechanical properties. Realizing full properties requires resin crystallinity to be controlled - partial crystallinity leads to unacceptably low laminate compression properties. There are two approaches: utilize an amorphous matrix resin; or place material made from a semi-crystalline resin featuring kinetics faster than the process. In this paper, a matrix resin evaluation and trade study was completed with commercial and NASA amorphous polyimides on the one hand, and with PEKK mixed with POSS nanoparticles for accelerated crystallinity growth on the other. A new thermoplastic impregnated material, 6 mm wide (0.25-in) AS-4 carbon/LaRC(TradeMark)8515 dry polyimide tow, was fabricated. Since LaRC(TradeMark)8515 is fully amorphous, it attains full properties following in situ consolidation, with no post processing required to build crystallinity. The tow in situ processing was demonstrated via in situ thermoplastic filament winding it into rings

HIFIRE Flight 2 Overview and Status Update 2011

A collaborative international effort, the Hypersonic International Flight Research Experimentation (HIFiRE) Program aims to study basic hypersonic phenomena through flight experimentation. HIFiRE Flight 2 teams the United States Air Force Research Lab (AFRL), NASA, and the Australian Defence Science and Technology Organisation (DSTO). Flight 2 will develop an alternative test technique for acquiring high enthalpy scramjet flight test data, allowing exploration of accelerating hydrocarbon-fueled scramjet performance and dual-to-scram mode transition up to and beyond Mach 8 flight. The generic scramjet flowpath is research quality and the test fuel is a simple surrogate for an endothermically cracked liquid hydrocarbon fuel. HIFiRE Flight 2 will be a first of its kind in contribution to scramjets. The HIFiRE program builds upon the HyShot and HYCAUSE programs and aims to leverage the low-cost flight test technique developed in those programs. It will explore suppressed trajectories of a sounding rocket propelled test article and their utility in studying ramjet-scramjet mode transition and flame extinction limits research. This paper describes the overall scramjet flight test experiment mission goals and objectives, flight test approach and strategy, ground test and analysis summary, development status and project schedule. A successful launch and operation will present to the scramjet community valuable flight test data in addition to a new tool, and vehicle, with which to explore high enthalpy scramjet technologies

Moral Hazard and Claims Deterrence in Private Disability Insurance

Exploiting within-firm, over-time variation in plan parameters for nearly 10,000 Long Term Disability (LTD) policies held by US employers, we present the first empirical analysis of the determinants of private LTD spells. We find that a shorter waiting period and a higher replacement rate increase the incidence of LTD spells. Sixty percent of the latter effect is due to the mechanical censoring of shorter spells, with the remainder due to the deterrence of spells that would have continued beyond the waiting period. Deterrence is driven primarily by a reduction in the incidence of shorter duration spells and less severe disabilities