Estimating Price Elasticities of Demand for Alcohol and Tobacco In The uk james Collis Magdalena Czubek Surjinder Johal



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Estimating Price Elasticities of Demand for Alcohol and Tobacco In The UK

James Collis

Magdalena Czubek

Surjinder Johal

27 May 2010

Abstract

UK duties on alcohol and tobacco generated almost £18 billion in exchequer revenues in 2009-10. HM Revenue & Customs use own-price and cross-price elasticities to analyse the effect of duty rate changes upon exchequer revenues. A duty rate increase will have two opposing effects on tax revenues: increase revenues by levying more duty per unit sold, but also reducing consumption through the resulting higher prices as consumers substitute away to other products, and sometimes towards the significant non-duty paid sector. The interplay between these effects is very important for predicting exchequer revenues and informing policy debate.



Contact Details:

James.Collis@hmrc.gsi.gov.uk; Magdalena.Czubek@hmrc.gsi.gov.uk; Surjinder.Johal@hmrc.gsi.gov.uk.


1 Introduction


Duty on alcohol and tobacco generated £9.0 billion and £8.9 billion respectively in exchequer revenues in 2009-10. This is around 3%-4% of the total raised by HM Revenue & Customs (HMRC).

HMRC uses own-price and cross-price elasticities to analyse the effect of duty rate changes upon exchequer revenues. A duty rate increase will have two opposing effects on tax revenues: increase revenues by levying more duty per unit sold, but also reducing consumption through the resulting higher prices as consumers substitute away to other products. There is also the possibility that consumers may opt to switch to the non-duty paid sector both through legal (cross border shopping) and illegal (smuggling and counterfeit) means. The size of the non-duty paid sector can be significant. The latest estimates for cigarettes, for example, suggest the market share is around 12%. The interplay between these different effects is very important for predicting exchequer revenues and informing policy debate.

HMRC are primarily concerned with the elasticity of duty paid alcohol and tobacco rather than consumption as a whole. This distinction is important because whilst the consumption of these products is typically thought of as inelastic, particularly with regard to their social habit or addiction properties, consumption from the duty paid sector will be more elastic.

As well as overall revenue, HMRC are also interested in the substitutability across different products and what that implies for duty rates. For example, for a number of years in the 1990s, spirits duty was frozen whilst duty rates on beer and wine increased; cider has typically been taxed less heavily than beer. When considering the revenue effects of such policies, it is important to understand in what way changes in the relative prices of different alcohols will affect sales and therefore tax revenues from each type of alcohol.

One of the main objectives in re–estimating the models are to ensure that our elasticity estimates accurately reflect current market conditions. The evidence is that estimated demand elasticities can be relatively unstable and can vary considerably across studies. This variability may reflect actual changes in tastes but probably also includes a stochastic element, particularly with regard to different data sets and non-linearity and so on.

We are estimating elasticities separately for the alcohol and tobacco markets. This paper outlines the different methodologies pursued to estimate demand for alcohol and tobacco. Section 2 summarises some previous studies. Section 3 discusses a cointegration technique using time series data. Sections 4 and 5 are based on the same cross-section household expenditure dataset. The first uses a QUAIDS model whilst the second employs a Tobit estimation.


2 Previous Studies


Alcohol

The last time that HMRC modelled alcohol demand was in the paper by Huang (2003). That used a single equation dynamic error-correction model and applied it to data from the Office for National Statistics (ONS). Four different equations were estimated: beer in the off trade, beer in the on trade, spirits and wine.

Although the model has performed well it is clearly time that the estimations were updated. In particular, there are a number of areas that we think need to be re-considered. Firstly, the current model only considers the distinction between the on and off trade for beer. Whilst it is arguable that the beer market is the one where the distinction is most important, we would ideally like to make the separation for all products. Secondly, there have been some significant changes in drinking habits, in particular the growth of the markets for cider and the ready-to-drink category. Neither of these was modelled in the previous study.

Tobacco

The previous tobacco modelling exercise was carried out by Cullum and Pissarides (2004). They used an Almost Ideal Demand System (AIDS) to look at the markets for cigarettes and hand rolled tobacco (HRT). They also explicitly estimated the demand for the duty-paid domestic market, the cross-border market and the illicit market. They used data from ONS, HMRC and tobacco manufacturers.

At the time of this research there was considerable concern that prior models had not captured the rapid rise in the growth of the non duty-paid sector. During the 1990s the size of this sector grew from virtually zero to over 20% of the cigarettes market and over 60% of the HRT market.

Arguably, this model has performed less well than the alcohol estimation. One of the main reasons for this is that the size of the non duty-paid sector has declined in the ensuing years. In 2000 HMRC introduced a new tobacco strategy to counter the growth in the non duty-paid sector and it would appear that this has had a good degree of success, though other factors (exchange rates, inflation only duty rises amongst others) have also likely played a role. The elasticities estimated in the Cullum and Pissarides study are probably on the high side in the current climate, where receipts from tobacco have risen sharply in recent years.



Meta-Analysis

There are a large number of studies looking at alcohol and tobacco but, fortunately, Gallet (2007) and Gallet and List (2003) have conducted extensive meta-analysis to examine the differences across the literature. Gallet (2007) considers results from 132 international studies on alcohol from 1942 to 2002 to see how the price elasticity varies across a range of different factors, including beverage type, functional form, data type and estimation method. Each was compared to a simple baseline regression. He found that:



  • Beer was consistently more inelastic than other beverages (wine and spirits).

  • Non-linear functional forms (AIDS, Rotterdam, semi-log) tended to produce more inelastic elasticities than linear models.

  • However, addiction models were not significantly different.

  • There was no significant difference between time series data and panel data.

  • Compared to OLS, other estimation methods - two stage least squares (2SLS) and three stage least squares (3SLS) produce more elastic price elasticities.

  • However, a single equation maximum likelihood estimation (MLE) tends to result in more inelastic elasticities than OLS.

  • Full information maximum likelihood (FIML), generalised least squares (GLS) and generalised method of moments (GMM) were not significantly different to OLS.

  • The short run elasticity is more inelastic than the long run.

Gallet and List (2003) looks at tobacco research in a similar way, comparing different studies to a baseline estimation, in this case a single equation, OLS, semi-log regression with smoking consumption as the dependent variable. They look at 86 studies from 1933 to 2001. Again, their selection is not limited to the UK. The main findings were:

  • Estimations based on AIDS specifications tend to produce more inelastic elasticities than the baseline.

  • The rational addition model tends to generate more inelastic elasticities than the baseline; estimates from the myopic model are not significantly different.

  • The linear and double-log specifications are not significantly different to the baseline.

  • There is no significant difference between using time series and cross section data.

  • Neither 2SLS, 3SLS, FIML were significantly different to the OLS baseline. GLS and MLE studies tended to produce more inelastic elasticities, though the latter result is of marginal significance. GMM estimations tend to result in more elastic elasticities.

  • The short run elasticity is more inelastic than the long run.

The results from these two meta-analyses are useful benchmarks when modelling alcohol and tobacco. In particular, they are of value when we compare results across the different approaches we have been exploring.


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