Optimal Taxation and Food Policy: Impacts of Food Taxes
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 Optimal Taxation and Food Policy: Impacts of Food Taxes on Nutrient Intakes. New Directions in Welfare – OECD, Paris – July 2011. Thomas Allen (University of Perpignan, CIHEAM/IAMM-MOISA and INRA-ALISS) Olivier Allais (INRA-ALISS) Véronique Nichèle (INRA-ALISS)

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 Optimal Taxation and Food Policy: Impacts of Food Taxes on Nutrient Intakes

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 Optimal Taxation and Food Policy: Impacts of Food Taxes

on Nutrient Intakes

New Directions in Welfare – OECD, Paris – July 2011

Thomas Allen (University of Perpignan, CIHEAM/IAMM-MOISA and INRA-ALISS)

Olivier Allais (INRA-ALISS)

Véronique Nichèle (INRA-ALISS)

Martine Padilla (CIHEAM/IAMM-MOISA)


Outline of the presentation

  • Background

  • Research objectives

  • Methodology

  • Results

  • Discussion


Background

Increase in the prevalence of obesity and overweight in France since 1990 (Obépi, 2009);

Higher risk of illnesses for which nutrition is an essential determinant, among the low-income groups (InVS, 2006)

Nutrient-rich food are associated with higher diet costs and energy-dense food with lower costs (Darmon et al., 2007);

Public Health authorities’ questioning and academic discussion on the prospect of potential « fat taxes ».


Research Question

How best to design a fiscal policy improving households’ allocation of goods in terms of nutrient adequacy to recommendations?


Objective

Identify the optimal price conditions improving households’ diet quality.


Review of the Litterature

  • Food consumption economics : Estimation of a food demand system to capture price elasticities (Deaton et al.)

  • Health studies : Definition of the public health question and tools of analysis (Drewnowski et al.)

  • Public economics: Modelisation of the optimal taxation conditions (Ramsey,Murty et al.)


Optimal taxation modelRamsey's model (1927)

  • Taxes' objective: Raise funds.

  • Planner's ojective: Maximise social welfare under the constraint that tax revenue covers a given level of public expenditure.

s.c.


Optimal taxation modelInverse elasticity rule

Ramsey rule: The reduction in demand for each good, caused by the tax system, should be proportional for each good.

Inverse elasticity rule: Optimal tax rates on each good should be inversely proportional to the good’s own–price elasticity of demand.


Optimal taxation modelApplication to a nutritional policy objective

Taxes' objective:Transforming consumption behaviours.

Planner's objectif: Maximise social welfare under the constraint that the overall diet quality of consumers' food basket reach a minimum level in terms of nutrient adequacy to recommendations.

s.c.


Optimal taxation modelA nutritional quality/price ratio

Optimal financing criteria : The optimal tax rates, for each good, are decreasing functions of their own-price elasticity of demand.

Optimal adequation criteria: The optimal tax rates, for each good, are decreasing functions of their « nutritional quality/ price » ratio.


Optimal taxation modelSystem of simultaneous equations

  • The maximization program results in a system of equations where each optimal price variation, tk, :

Where quali, p and x are vectors of the diet quality indicators, initial prices and quantities associated with each good and e the own and cross price elasticities.

  • Solving this sytem requires to estimate a complete food demand system.


Methodology – Demand modelA conditionally linear system

Selection of the Almost Ideal Demand System model (Deaton and Muellbauer, 1980):

Iterated Least Square Estimator (Blundell and Robin, 1999).


Methodology – Pseudo-Panel Data

  • A panel of scanner data:

    - 156 periods: 1996-2007

    - 8 cohorts: Date of birth/Social status

    - 27 food groups

  • Group agregation:

    Homogenous categories in terms of nutritional content (fruits/vegetables fresh/processed, snacks/already prepared meals, vegetable/animal fat, salty/sugary fat).

  • Price construction:

    24 clusters of price according to Localisation/Social status.


Methodology - Nutrient adequacy indicators

  • MAR:

  • LIM:

  • SAIN:


Nutrient adequacy indicatorsMAR - Mean adequacy ratio

The MAR for a 100g of food i:

The MAR for a food basket:


Nutrient adequacy indicatorsLIM – Score des composés à limiter

The LIM for a 100g o food i:

The LIM for a food basket:


Nutrient adequacy indicatorsSAIN – Score d’adéquation individuel aux recommandations nutritionnelles

The SAIN for a 100g of food i:

The SAIN for a food basket:


Results – Price elasticty of demand

Uncompensated own-price elasticities

  • Statistically significant.

  • Negatives.

  • Low and inelastic.

  • Within usual range.


Simulations – Optimal taxation MAR

  • Goods to tax:Fish, meat, poultry, deli meat, snacks, sugar, animal fat, beverages

  • Goods to subsidize: Fruits and vegetables, yoghurt, milk, cereals and starches, potatoes, vegetable fat and salty snacks


Simulations – Optimal taxation LIM

  • Goods to tax:Fruits and soft drinks, deli meat, snacks, mixed dishes, dairy products, cereals and starches, vegetable and animal fat, sweets and salty snacks.

  • Goods to subsidize: Fish, meat, poultry, vegetables, potatoes, water coffee and tea and alcoholic beverages.


Simulations – Optimal taxation SAIN

  • Improvements once calorie intakes are taken into consideration:

  • Mixed dishes are to be taxed; water to be subsidized.

  • Meat are more heavily taxed; fruits and vegetables more heavily subsidized.


Fiscal incidence

Welfare losses homogeneously spread over all income groups.


ConclusionResults and policy implications

Theoretical result: A « diet quality/price » ratio and an augmented inverse elasticity rule;

Empirical results: Mixed evidence supporting food taxation:

- Low price elasticities and high tax rates;

- Weak convergence on food groups to tax/ subsidize accross nutrient adequacy indicators.


Appendices


Methodology – Optimal taxation (2)

Use of the Lagragian Method to obtain a system of n+2 linear and non-linear equations and n+2 unknowns.

with


Methodology – Optimal taxation (3)

  • Using the Lagrangian method:

with

  • And assuming a differentiable demand function:


Methodology – Optimal taxation (4)

  • Increasing the MAR objective until the other constraints collapse is equivalent to:

  • Maximisation Program:

s.c.


Methodology – Optimal taxation (5)

  • Maximisation Program:

s.c.


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