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Price Nudge for Obesity
(with Romana Khan & Kanishka Misra)
Why Intervene?
• Dire consequences of obesity to Individual
– Increased risks of type 2 diabetes, hypertension,
cardiovascular diseases, cancer, gallbladder disease,
osteoarthritis, disabilities, psychosocial problems
...Estimated 112,000 deaths every year
Externalities: Significant economic
implications costing $150 billion p.a.
– Medical costs: half on Medicare and Medicaid
– Additional productivity loss
Vishal Singh, Stern School of Business, NYU 2
How to Intervene?
 Disclosure & Education
 Limiting choices (zoning and prohibition)
 Marketing regulation (Limiting messages)
 Surveillance (data provision)
 Taxation
– “Fat Taxes” or “Junk Food Tax”
– Already in place in many states
– Soda tax (mean rate 5.2%) in 33 US states
– A sugar based tax has been proposed
o Bans/Regulations
Vishal Singh, Stern School of Business, NYU 3
Problems with “Twinkie” Tax
o Ideological
Highly Regressive
Will it Work?
o Will it get Implemented?
o Strong Industry Opposition
Previous Evidence
o Field Work
Econometric/data problems
Focus on Sales Tax
Industry Funded
Experimental Work 
Lab/Cafeteria/Vending Machines
Small non-representative samples
This Paper: Quasi Natural Experiment
$2.91 $2.91 $2.91 $2.90
$2.87
$2.73
$2.71
$2.60
$2.40
$2.45
$2.50
$2.55
$2.60
$2.65
$2.70
$2.75
$2.80
$2.85
$2.90
$2.95
Whole milk 2% milk 1% milk Skim milk
Uniform Price Non-Uniform Price
Depending on where you live and what supermarket chain you patronize, you see one of these patterns.
Milk Pricing in the US
Milk Pricing in the US
Vishal Singh, Stern School of Business, NYU 7
Non Flat Pricing
Primarily Non-Flat
Mixed
Primarily Flat
Flat Pricing
No Data Available
Southeast FMMO
Pennsylvania: Large milk
producer. State
regulations.
Uniform/Non-Uniform price
structure is consistent across
stores within a chain, even in
mixed states.
Upper Midwest FMMO: Wisconsin is
2nd largest producer
Central FMMO
Northeast FMMO
MidEast
FMMO
DATA
 1800 + supermarkets
 6 Years weekly data
 UPC level sales,
price, promotion etc.
 Counties represent
approximately 50% of
the population
a) Comparison of Demographic Profile between Flat and NonFlat Stores
Flat stores Non-Flat stores
Mean
Std
Dev Mean
Std
Dev p-value
Low income 18% 38% 21% 41% 0.08
High income 19% 39% 20% 40% 0.60
% Poverty 2% 1% 2% 1% 0.22
% Children 4% 1% 4% 1% 0.62
% College 39% 49% 41% 49% 0.58
% White 78% 19% 77% 19% 0.49
% Elderly 12% 4% 12% 5% 0.32
Population density 0.12 0.31 0.13 0.18 0.52
(b) (1) Regression of (Price Whole/ Price 2%) milk and (2) Variance Decomposition
(1) (2)
Estimate Std Error
% of explained variation
accounted for by:
Intercept 1.0393 (0.006)
Median Income -0.0017 (0.002) 0.06%
% HH Kids -0.0003 (0.001) 0.00%
% College -0.0005 (0.002) 0.01%
% White -0.0014 (0.001) 0.09%
Population Density -0.0003 (0.001) 0.00%
Wage 0.0028 (0.002) 0.14%
All retailers within 5 miles -0.0002 (0.001) 0.00%
Discount retailers within 10 miles -0.0021 (0.001) 0.18%
Marketing Order Fixed Effects Included 15.44%
Chain Fixed Effects Included 84.07%
R square 0.658
Is Pricing Structure Exogenous?
Does it Change Behavior?
No Unobserved Differences in Taste
Correlation of Shares & SEC
Large Response to Small Price Changes
Recommendations
• Small price gaps that are reflected at the
point of purchase
– Mitigates the regressive nature of taxes
$1.05
$.95
$2.05
$1.95
NOTE: Approximately half of the total grocery sales are on promotion
Altering the Food Subsidies

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Fat Tax Slideshow

  • 1. Price Nudge for Obesity (with Romana Khan & Kanishka Misra)
  • 2. Why Intervene? • Dire consequences of obesity to Individual – Increased risks of type 2 diabetes, hypertension, cardiovascular diseases, cancer, gallbladder disease, osteoarthritis, disabilities, psychosocial problems ...Estimated 112,000 deaths every year Externalities: Significant economic implications costing $150 billion p.a. – Medical costs: half on Medicare and Medicaid – Additional productivity loss Vishal Singh, Stern School of Business, NYU 2
  • 3. How to Intervene?  Disclosure & Education  Limiting choices (zoning and prohibition)  Marketing regulation (Limiting messages)  Surveillance (data provision)  Taxation – “Fat Taxes” or “Junk Food Tax” – Already in place in many states – Soda tax (mean rate 5.2%) in 33 US states – A sugar based tax has been proposed o Bans/Regulations Vishal Singh, Stern School of Business, NYU 3
  • 4. Problems with “Twinkie” Tax o Ideological Highly Regressive Will it Work? o Will it get Implemented? o Strong Industry Opposition
  • 5. Previous Evidence o Field Work Econometric/data problems Focus on Sales Tax Industry Funded Experimental Work  Lab/Cafeteria/Vending Machines Small non-representative samples
  • 6. This Paper: Quasi Natural Experiment $2.91 $2.91 $2.91 $2.90 $2.87 $2.73 $2.71 $2.60 $2.40 $2.45 $2.50 $2.55 $2.60 $2.65 $2.70 $2.75 $2.80 $2.85 $2.90 $2.95 Whole milk 2% milk 1% milk Skim milk Uniform Price Non-Uniform Price Depending on where you live and what supermarket chain you patronize, you see one of these patterns. Milk Pricing in the US
  • 7. Milk Pricing in the US Vishal Singh, Stern School of Business, NYU 7 Non Flat Pricing Primarily Non-Flat Mixed Primarily Flat Flat Pricing No Data Available Southeast FMMO Pennsylvania: Large milk producer. State regulations. Uniform/Non-Uniform price structure is consistent across stores within a chain, even in mixed states. Upper Midwest FMMO: Wisconsin is 2nd largest producer Central FMMO Northeast FMMO MidEast FMMO DATA  1800 + supermarkets  6 Years weekly data  UPC level sales, price, promotion etc.  Counties represent approximately 50% of the population
  • 8.
  • 9. a) Comparison of Demographic Profile between Flat and NonFlat Stores Flat stores Non-Flat stores Mean Std Dev Mean Std Dev p-value Low income 18% 38% 21% 41% 0.08 High income 19% 39% 20% 40% 0.60 % Poverty 2% 1% 2% 1% 0.22 % Children 4% 1% 4% 1% 0.62 % College 39% 49% 41% 49% 0.58 % White 78% 19% 77% 19% 0.49 % Elderly 12% 4% 12% 5% 0.32 Population density 0.12 0.31 0.13 0.18 0.52 (b) (1) Regression of (Price Whole/ Price 2%) milk and (2) Variance Decomposition (1) (2) Estimate Std Error % of explained variation accounted for by: Intercept 1.0393 (0.006) Median Income -0.0017 (0.002) 0.06% % HH Kids -0.0003 (0.001) 0.00% % College -0.0005 (0.002) 0.01% % White -0.0014 (0.001) 0.09% Population Density -0.0003 (0.001) 0.00% Wage 0.0028 (0.002) 0.14% All retailers within 5 miles -0.0002 (0.001) 0.00% Discount retailers within 10 miles -0.0021 (0.001) 0.18% Marketing Order Fixed Effects Included 15.44% Chain Fixed Effects Included 84.07% R square 0.658 Is Pricing Structure Exogenous?
  • 10.
  • 11. Does it Change Behavior?
  • 14. Large Response to Small Price Changes
  • 15. Recommendations • Small price gaps that are reflected at the point of purchase – Mitigates the regressive nature of taxes $1.05 $.95 $2.05 $1.95 NOTE: Approximately half of the total grocery sales are on promotion
  • 16.
  • 17. Altering the Food Subsidies