title: Study protocol: combining experimental methods, econometrics and simulation modelling to determine price elasticities for studying food taxes and subsidies (The Price ExaM Study).
abstract: There is a need for accurate and precise food price elasticities (PE, change in consumer demand in response to change in price) to better inform policy on health-related food taxes and subsidies.
  
  
  
  The Price Experiment and Modelling (Price ExaM) study aims to: I) derive accurate and precise food PE values; II) quantify the impact of price changes on quantity and quality of discrete food group purchases and; III) model the potential health and disease impacts of a range of food taxes and subsidies. To achieve this, we will use a novel method that includes a randomised Virtual Supermarket experiment and econometric methods. Findings will be applied in simulation models to estimate population health impact (quality-adjusted life-years [QALYs]) using a multi-state life-table model. The study will consist of four sequential steps: 1. We generate 5000 price sets with random price variation for all 1412 Virtual Supermarket food and beverage products. Then we add systematic price variation for foods to simulate five taxes and subsidies: a fruit and vegetable subsidy and taxes on sugar, saturated fat, salt, and sugar-sweetened beverages. 2. Using an experimental design, 1000 adult New Zealand shoppers complete five household grocery shops in the Virtual Supermarket where they are randomly assigned to one of the 5000 price sets each time. 3. Output data (i.e., multiple observations of price configurations and purchased amounts) are used as inputs to econometric models (using Bayesian methods) to estimate accurate PE values. 4. A disease simulation model will be run with the new PE values as inputs to estimate QALYs gained and health costs saved for the five policy interventions.
  
  
  
  The Price ExaM study has the potential to enhance public health and economic disciplines by introducing internationally novel scientific methods to estimate accurate and precise food PE values. These values will be used to model the potential health and disease impacts of various food pricing policy options. Findings will inform policy on health-related food taxes and subsidies.
  
  
  
  Australian New Zealand Clinical Trials Registry ACTRN12616000122459 (registered 3 February 2016).
authors.affiliation: National Institute for Health Innovation, School of Population Health, University of Auckland, Auckland, New Zealand. w.waterlander@auckland.ac.nz.
authors.forename: Wilma E
authors.initials: WE
authors.lastname: Waterlander
authors.affiliation: Department of Public Health, University of Otago, Wellington, New Zealand.
authors.forename: Tony
authors.initials: T
authors.lastname: Blakely
authors.affiliation: Department of Public Health, University of Otago, Wellington, New Zealand.
authors.forename: Nhung
authors.initials: N
authors.lastname: Nghiem
authors.affiliation: Department of Public Health, University of Otago, Wellington, New Zealand.
authors.forename: Christine L
authors.initials: CL
authors.lastname: Cleghorn
authors.affiliation: National Institute for Health Innovation and Department of Epidemiology and Biostatistics, School of Population Health, University of Auckland, Auckland, New Zealand.
authors.forename: Helen
authors.initials: H
authors.lastname: Eyles
authors.affiliation: Department of Economics, University of Otago, Dunedin, New Zealand.
authors.forename: Murat
authors.initials: M
authors.lastname: Genc
authors.affiliation: Department of Public Health, University of Otago, Wellington, New Zealand.
authors.forename: Nick
authors.initials: N
authors.lastname: Wilson
authors.affiliation: National Institute for Health Innovation, School of Population Health, University of Auckland, Auckland, New Zealand.
authors.forename: Yannan
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: Department of Epidemiology and Biostatistics, School of Population Health, University of Auckland, Auckland, New Zealand.
authors.forename: Boyd
authors.initials: B
authors.lastname: Swinburn
authors.affiliation: Department of Economics, The University of Melbourne, Melbourne, VIC, Australia.
authors.forename: Liana
authors.initials: L
authors.lastname: Jacobi
authors.affiliation: National Institute for Health Innovation, School of Population Health, University of Auckland, Auckland, New Zealand.
authors.forename: Jo
authors.initials: J
authors.lastname: Michie
authors.affiliation: National Institute for Health Innovation, School of Population Health, University of Auckland, Auckland, New Zealand.
authors.forename: Cliona
authors.initials: C
authors.lastname: Ni Mhurchu
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001315:Australia; D001499:Bayes Theorem; D003132:Commerce / Q000191:economics* / Q000706:statistics & numerical data; D005260:Female; D005380:Financing, Government / Q000191:economics* / Q000706:statistics & numerical data*; D005502:Food / Q000191:economics* / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D009520:New Zealand; D013660:Taxes / Q000191:economics* / Q000706:statistics & numerical data*; D055815:Young Adult
keywords: Bayesian; Food policy; Food pricing; Food subsidies; Food taxes; Modelling; Price elasticities; RCT; Virtual supermarket