TO TAX OR NOT TO TAX? THE CASE OF ELECTRONIC COMMERCE

Despite the intensifying debate over the taxation of Internet commerce, the relevant issues have not been given a systematic treatment in the context of the literature on optimal taxation. This article presents such an analysis and investigates separately the taxation of business purchases of intermediate goods, the taxation of consumer purchases of final goods and services, and the various issues of administration and compliance costs as they apply to the development of E-commerce. The authors conclude that generally the optimal tax literature cannot be used in support of a blanket tax exemption for Internet purchases. Certain conditions could lead to the optimality of an exemption, but those conditions are not likely to be met in practice.     

Combinations of technology in US patents, 1926–2009: a weakening base for future innovation?

In combinatorial models of innovations, new technologies are built from combinations of pre-existing technological components. Researchers learn which components work well together by observing previously successful combinations and the pool of ideas can be ‘fished out’, i.e. exhausted, if it is not ‘restocked’ by the discovery of novel connections. We first show US patents have made increasingly less novel connections among technological constituents since the 1950s, and that the number of technological fields to which these connections are applicable has stopped growing since the 1980s. We then estimate the parameters of an ideas production function, and find parameter estimates consistent with technology fields being fished out if not continually restocked by the discovery of novel connections between technological components. We use the ideas production function to estimate the number of new patent applications induced by each patent granted between 1926 and 2001, and show this number has trended downward since the 1940s.     

When does incentive compensation motivate managerial behaviors? An experimental investigation of the fit between incentive compensation,executive core self-evaluation,and firm performance

We develop and test an integrative model that examines the fit between compensation schemes, executives' characteristics, and situational factors. We propose that a fit among all three factors is crucial to motivate desirable managerial behaviors. Using a specially designed management simulation, our study demonstrates that the effectiveness of incentive compensation to motivate managerial behaviors depends on executives' core self-evaluation and firm performance. Our results show that, relative to fixed salary compensation, executives with higher core self-evaluation respond to incentive compensation with greater perseverance, competitive strategy focus, ethical behavior, and strategic risk taking during organizational decline. However, these interaction effects are not present during organizational growth. Our theory and empirical evidence provide significant insights into the complex relationships among compensation schemes, executives' characteristics, firm performance, and managerial behaviors. Copyright © 2012 John Wiley & Sons, Ltd.     

THE IMPACT OF BODY WEIGHT ON OCCUPATIONAL MOBILITY AND CAREER DEVELOPMENT

This article examines the relationship between individuals' weight and employment decisions over the life cycle. I estimate a dynamic stochastic model of individuals' annual choices of occupation, hours worked, and schooling. Evidence suggests that heavier individuals face higher switching costs when transitioning into white‐collar occupations, earn lower returns to experience in white‐collar occupations, and earn lower wages in socially intensive jobs. I simulate a hypothetical antidiscrimination policy treating obese workers as a protected class. Although such a policy would reduce gaps in occupational attainment, it would have little effect on the observed divergence in wages between obese and nonobese workers.     

A review and validation of overall survival extrapolation in health technology assessments of cancer immunotherapy by the National Institute for Health and Care Excellence: how did the initial best estimate compare to trial data subsequently made available?

Background: Validation of overall survival (OS) extrapolations of immune-checkpoint inhibitors (ICIs) during the National Institute for Health and Care Excellence (NICE) Single Technology Assessment (STA) process is limited due to data still maturing at the time of submission. Inaccurate extrapolation may lead to inappropriate decision-making. The availability of more mature trial data facilitates a retrospective analysis of the plausibility and validity of initial extrapolations. This study compares these extrapolations to subsequently available longer-term data.

Methods: A systematic search of completed NICE appraisals of ICIs from March 2000 to December 2017 was performed. A targeted search was also undertaken to procure published OS data from the pivotal clinical trials for each identified STA made available post-submission to NICE. Initial Kaplan-Meier curves and associated extrapolations from NICE documentation were extracted to compare the accuracy of OS projections versus the most mature data.

Results: The review identified 11 STAs, of which 10 provided OS data upon submission to NICE. The extrapolations undertaken considered parametric or piecewise survival models. Additional data cut-offs provided a mean of 18 months of OS beyond the end of the original data. Initial extrapolations typically under-estimated OS from the most mature data cut-off by 0.4–2.7%, depending on the choice of assessment method and use of the manufacturer- or ERG-preferred extrapolation.

Conclusion: Long-term extrapolation of OS is required for NICE STAs based on initial immature OS data. The results of this study demonstrate that the initial OS extrapolations employed by manufacturers and ERGs generally predicted OS reasonably well when compared to more mature data (when available), although on average they appeared to underestimate OS. This review and validation shows that, while the choice of OS extrapolation is uncertain, the methods adopted are generally aligned with later-published follow-up data and appear appropriate for informing HTA decisions.     

Equilibrium Effects of Superstition in the Housing Market

We investigate the interaction of product quality differentiation and consumer preference heterogeneity in durable goods markets, focusing on the effects of secondary market liquidity and consumer heterogeneity on equilibrium prices. We build an infinite‐horizon dynamic model of the apartments housing market that captures the above features. Some apartments are considered lucky, and some consumers are superstitious. Lucky apartments are valued more highly than non‐lucky ones only by superstitious consumers. Results show that the difference between the lucky apartment price and the non‐lucky apartment price becomes smaller when the secondary market becomes less liquid and when consumers’ preference heterogeneity becomes more persistent as opposed to time‐varying.     

A quantile regression approach for estimating panel data models using instrumental variables

We introduce a quantile regression approach to panel data models with endogenous variables and individual effects correlated with the independent variables. We find newly developed quantile regression methods can be easily adapted to estimate this class of models efficiently.     

DISCRETE CHOICE AND RATIONAL INATTENTION: A GENERAL EQUIVALENCE RESULT

This article establishes a general equivalence between discrete choice and rational inattention models. Matějka and McKay (2015) showed that when information costs are modeled using the Shannon entropy, the choice probabilities in the rational inattention (RI) model take the multinomial logit form. We show that, for one given prior over states, RI choice probabilities may take the form of any additive random utility discrete choice model (ARUM) when the information cost is a Bregman information, a class defined in this article. The prior information of the rationally inattentive agent is summarized in a constant vector of utilities in the corresponding ARUM.     

A Poisson mixture model of discrete choice

In this paper, we introduce a new Poisson mixture model for count panel data where the underlying Poisson process intensity is determined endogenously by consumer latent utility maximization over a set of choice alternatives. This formulation accommodates the choice and count in a single random utility framework with desirable theoretical properties. Individual heterogeneity is introduced through a random coefficient scheme with a flexible semiparametric distribution. We deal with the analytical intractability of the resulting mixture by recasting the model as an embedding of infinite sequences of scaled moments of the mixing distribution, and newly derive their cumulant representations along with bounds on their rate of numerical convergence. We further develop an efficient recursive algorithm for fast evaluation of the model likelihood within a Bayesian Gibbs sampling scheme. We apply our model to a recent household panel of supermarket visit counts. We estimate the nonparametric density of three key variables of interest-price, driving distance, and their interaction-while controlling for a range of consumer demographic characteristics. We use this econometric framework to assess the opportunity cost of time and analyze the interaction between store choice, trip frequency, search intensity, and household and store characteristics. We also conduct a counterfactual welfare experiment and compute the compensating variation for a 10%-30% increase in Walmart prices.