The Effect of a Nutrient Tax Kathy Baylis, Tirtha Dhar, and Sohini Paul (with thanks to CSPI) Ottawa Oct. 22, 2008.

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Presentation transcript:

The Effect of a Nutrient Tax Kathy Baylis, Tirtha Dhar, and Sohini Paul (with thanks to CSPI) Ottawa Oct. 22, 2008

Baylis, Dhar and Paul Oct. 22, 2008 Background –fish at $18.82 per 1000 cal (Edmonton grocery store) –Apples at $6.00 per 1000 cal (Vancouver grocery store) –Wendy’s value meal at $3.45 per 1000 cal –7-11 double big gulp at $2.10 per 1000 cal WHO, CMA and various public health groups argue for financial incentives around food consumption Energy-dense, nutrient poor (ENDP) foods tend to be cheaper (Drewnowski and Specter 2004).

Baylis, Dhar and Paul Oct. 22, 2008 Some past studies A number find an effect –French et al (2001) experiment with vending machines and saw 10% price decrease in low-fat snacks increased sales. –Schroeter, Lusk and Tyner (2007) and Tefft (2006) show a tax on high-cal soft drinks would decrease weight. –Mytton, Gray, Rayner and Rutter (2007) Targeted tax in the UK Others less optimistic –Kuchler Tegene and Harris (2004, 2005) show consumers not very responsive to (very small) price of salty snacks – Smed, Jensen and Denver (2005) find that a fat tax might increase sugar consumption and vice versa. –Oaks (2005) looks at snack tax in Maine and finds no effect on consumption. –Chouinard et al (2007) look at dairy foods, and although they argue they find effect (low elasticity of demand for fat), show 10% tax on dairy fat does lead to 1% reduction in fat consumption

Baylis, Dhar and Paul Oct. 22, 2008 Past studies cont’d Evidence in favour of subsidies –Cash et al. (2005) on fruit and vegetable subsidies –Jeffery et al. (1994, 1997) cafeteria experiment on fruit and vegetable prices and selection. –Asfaw (2007) show subsidies of fruit, milk and eggs are associated with lower BMI in Egypt, and higher prices on energy-dense foods lead to a higher BMI –Clark and Levedahl (2006) argue that increasing income would have a larger effect than a tax

Baylis, Dhar and Paul Oct. 22, 2008 Arguments against Is the externality real? –Yes. Even in US with private healthcare, extra costs to medicare and medicaid are substantial. –US costs in 1998 estimated to be at least $92.6B, ½ from Medicare/Medicaid –Canada cost estimates range from $1.6 B to $6 B The externality will change per person –True, but can target foods that most overconsume, and/or are more addictive –Debate around whether there are ‘bad’ foods. –Richards, Patterson and Tegene (2004) use scanner data and find that carbohydrates, fat, protein and sodium may be addictive.

Baylis, Dhar and Paul Oct. 22, 2008 Arguments Against Regressive –Poor are more likely to consume EDNP foods, and –Poor spend higher % of income on food –But, we have GST rebate, and –Might be able to subsidize some foods Complicated –Current tax code?

Baylis, Dhar and Paul Oct. 22, 2008 GST/PST rules Which is taxed? Breakfast bars (e.g. pop tarts) versus granola bars Bagged salad, including dressing versus pre- made salad Ready-to-heat soup versus hot soup. Milk at a restaurant versus no-fruit ‘juice drink’ at a convenience store Varies by province Food tax amount and type varies by US state

Baylis, Dhar and Paul Oct. 22, 2008 Arguments in favour Can change consumer behaviour (elastic response is good) May encourage reformulation (as with transfats and ad. rules) Raises revenue (inelastic response is good) Information/stigma (Cash et al, 2008)

Baylis, Dhar and Paul Oct. 22, 2008 What we are doing Using 2001 Household food expenditure survey in Canada, estimated demand elasticities. Use nutrient information from Health Canada to predict the distribution and effect of taxes.

Baylis, Dhar and Paul Oct. 22, 2008 Own-price elasticity estimates CommodityPrice-elasticity Beef-0.56 Pork-1.35 Chicken-0.85 Lamb and other meat-1.16 Meat preparations (e.g. bacon)-0.95

Baylis, Dhar and Paul Oct. 22, 2008 What we find so far Using meat consumption, a tax on fat decreases beef and bacon and sausage expenditure and increases pork and chicken expenditure. Thus, even for relatively broad categories, consumers are price sensitive.

Baylis, Dhar and Paul Oct. 22, 2008 Next steps Complete current demand system estimation and nutrient model Consider income distribution –poor people have different substitution patterns than rich Use scanner data to look at specific food categories (frozen foods)

Baylis, Dhar and Paul Oct. 22, 2008 Take-home message We already have a tax that makes value judgements – “Eating out is bad. Eating ready-made food is bad. Eating 6 doughnuts is OK tho…” This tax could be targeted more directly at nutrients Very initial evidence that consumers will respond to price incentives Regressivity needs to be addressed, through GST rebate and/or food subsidies