The 'fat tax': economic incentives to reduce obesity

This Briefing Note looks at the potential for the introduction of a "fat tax" into the UK in an effort to reduce the growing prevalence of obesity in Britain. There are different forms such a tax could take. One possibility is to tax the nutrient contents of foods such that those containing more fat or salt, for example, are taxed more heavily. Alternatively, particular types of foods, such as snacks or soft drinks, could be subject to a tax, or VAT could be extended to foods that are currently zero-rated but have a high fat content. Revenue from a "fat tax" could be used in various ways, such as financing subsidies for healthy foods or exercise equipment, funding advertising campaigns for healthy eating or in schools. Alternatively, it could form part of general government receipts. This Briefing Note will look at trends in UK obesity (Section 2) and examine evidence on eating habits and exercise in order to see whether trends here can account for what we see happening to obesity (Section 3). We will then go on, in Section 4, to review some of the key economic reasons behind why we might be concerned about obesity and why we might consider there to be a case for government intervention. Moving on, we discuss how food is currently taxed (Section 5) and the various ways in which a "fat tax" might be introduced (Section 6), looking at particular issues the government might need to address should it wish to introduce one. We will finish in Section 7 by presenting some simple analysis of a hypothetical "fat tax" in terms of how it might impact differently on the rich and the poor. Section 8 concludes

Individual effects and dynamics in count data models

In this paper we examine the panel data estimation of dynamic models for count data that include correlated fixed effects and predetermined variables. Use of a linear feedback model ls proposed. The standard Poisson conditional maximum llkelihood estimator for non-dynamic models, which ls shown to be the same as the Poisson maximum llkelihood estimator in a model with individual specific constants, ls inconsistent when regressors are predetermined. A quasi-differenced GMM estimator ls consistent for the parameters in the dynamic model, but when series are highly persistent, there ls a problem of weak instrument bias. An estimator ls proposed that utilises pre-sample information of the dependent count variable, which is shown in Monte Carlo simulations to possess desirable small sample properties. The models and estimators are applied to data on US patents and R&D expenditure

Waiting lists, waiting times and admissions: an empirical analysis at hospital and general practice level

We report an empirical analysis of the responses of the supply and demand for secondary care to waiting list size and waiting times. Whereas previous empirical analyses have used data aggregated to area level, our analysis is novel in that it focuses on the supply responses of a single hospital and the demand responses of the GP practices it serves, and distinguishes between outpatient visits, inpatient admissions, daycase treatment and emergency admissions. The results are plausible and in line with the theoretical model. For example: the demand from practices for outpatient visits is negatively affected by waiting times and distance to the hospital. Increases in waiting times and waiting lists lead to increases in supply; the supply of elective inpatient admissions is affected negatively by current emergency admissions and positively by lagged waiting list and waiting time. We use the empirical results to investigate the dynamic responses to one off policy measures to reduce waiting times and lists by increasing supply

Parental income and children’s smoking behaviour: evidence from the british household panel survey

Does money matter? When investigating health behaviour, research often finds a strong positive association between income and healthy behaviour. This could however be due to individual characteristics that determine both income and health investment and is not necessarily due to the role of money per se. In this study we look at this relationship over the generations by studying the association between parental income and children’s prevalence to smoke in Britain using data from the British Household Panel Survey and British Youth Survey. We find an inverse relation between parental income and children’s smoking prevalence, but when looking at within household changes by comparing sibling’s smoking status differences at the same age, we find instead a positive effect. This indicates that within household increases in income lead to an increased probability of smoking of a younger child

Pharmaceutical promotion and GP prescription behaviour

The aim of this paper is to empirically analyse the responses by general practitioners to promotional activities for pharmaceuticals by pharmaceutical companies. Promotion can be beneficial for society as a means of providing information, but it can also be harmful in the sense that it lowers price sensitivity of doctors and it merely is a means of establishing market share, even when cheaper, therapeutically equivalent drugs are available. A model is estimated that includes interactions of promotion expenditures and prices and that explicitly exploits the panel structure of the data, allowing for drug specific effects and dynamic adjustments, or habit persistence. The data used are aggregate monthly GP prescriptions per drug together with monthly outlays on drug promotion for the period 1994-1999 for 11 therapeutic markets, covering more than half of the total prescription drug market in the Netherlands. Identification of price effects is obtained by the introduction of the Pharmaceutical Prices Act, which established that Dutch drugs prices became a weighted average of the prices in surrounding countries after June 1996. We conclude that, on average, GP drug price sensitivity is small, but adversely affected by promotion.

Estimation of count data models with endogenous regressors; an application to demand for health care

The generalized method of moments (GMM) estimation technique is discussed for count data models with endogenous regressors. Count data models can be specified with additive or multiplicative errors. It is shown that, in general, a set of instruments is not orthogonal to both error types. Simultaneous equations with a dependent count variable often do not have a reduced form which is a simple function of the instruments. However, a simultaneous model with a count and a binary variable can only be logically consistent when the system is recursive. The GMM estimator is used in the estimation of a model explaining the number of visits to doctors, with as a possible endogenous regressor a self-reported binary health index. Further, a model is estimated, in stages, that includes latent health instead of the binary health index

Identification of causal effects on binary outcomes using structural mean models

Structural mean models (SMMs) were originally formulated to estimate causal effects among those selecting treatment in randomized controlled trials affected by nonignorable noncompliance. It has already been established that SMMs can identify these causal effects in randomized placebo-controlled trials under fairly weak assumptions. SMMs are now being used to analyze other types of study where identification depends on a no effect modification assumption. We highlight how this assumption depends crucially on the unknown causal model that generated the data, and so is difficult to justify. However, we also highlight that, if treatment selection is monotonic, additive and multiplicative SMMs do identify local (or complier) causal effects, but that the double-logistic SMM estimator does not without further assumptions. We clarify the proper interpretation of inferences from SMMs by means of an application and a simulation study. © 2010 The Author