Can Nutritional Label Use Influence Body Weight Outcomes?

被引:33
作者
Drichoutis, Andreas C. [1 ]
Nayga, Rodolfo M., Jr. [2 ]
Lazaridis, Panagiotis [3 ]
机构
[1] Univ Ioannina, Dept Econ, GR-45110 Ioannina, Greece
[2] Univ Arkansas, Dept Agr Econ & Agribusiness, Fayetteville, AR 72701 USA
[3] Agr Univ Athens, Dept Agr Econ & Rural Dev, Athens 11855, Greece
关键词
PROPENSITY SCORE; INSTRUMENTAL VARIABLES; MATCHING ESTIMATORS; OBESITY;
D O I
10.1111/j.1467-6435.2009.00448.x
中图分类号
F [经济];
学科分类号
020101 [政治经济学];
摘要
P>Many countries around the world have already mandated, or plan to mandate, the presence of nutrition related information on most pre-packaged food products. Health advocates and lobbyists would like to see similar laws mandating nutrition information in the restaurant and fast-food market as well. In fact, New York City has already taken a step forward and now requires all chain restaurants with 15 or more establishments anywhere in US to show calorie information on their menus and menu board. The benefits were estimated to be as much as 150,000 fewer obese New Yorkers over the next five years. The implied benefits of the presence of nutrition information are that consumers will be able to observe such information and then make informed (and hopefully healthier) food choices. In this study, we use the latest available dataset from the US National Health and Nutrition Examination Survey (2005-2006) to explore whether reading such nutrition information really has an effect on body weight outcomes. In order to deal with the inherent problem of cross-sectional datasets, namely self-selection, and the possible occurrence of reverse causality we use a propensity score matching approach to estimate causal treatment effects. We conducted a series of tests related to variable choice of the propensity score specification, quality of matching indicators, robustness checks, and sensitivity to unobserved heterogeneity, using Rosenbaum bounds to validate our propensity score exercise. Our results generally suggest that reading nutrition information does not affect body mass index. The implications of our findings are also discussed.
引用
收藏
页码:500 / 525
页数:26
相关论文
共 36 条
[1]
Large sample properties of matching estimators for average treatment effects [J].
Abadie, A ;
Imbens, GW .
ECONOMETRICA, 2006, 74 (01) :235-267
[2]
Obesity as Market Failure: Could a 'Deliberative Economy' Overcome the Problems of Paternalism? [J].
Anand, Paul ;
Gray, Alastair .
KYKLOS, 2009, 62 (02) :182-190
[3]
Estimation of average treatment effects based on propensity scores [J].
Becker, Sascha O. ;
Ichino, Andrea .
STATA JOURNAL, 2002, 2 (04) :358-377
[4]
How robust is the evidence on the effects of college quality? Evidence from matching [J].
Black, DA ;
Smith, JA .
JOURNAL OF ECONOMETRICS, 2004, 121 (1-2) :99-124
[5]
Does marketing products as remedies create "Get out of jail free cards"? [J].
Bolton, LE ;
Cohen, JB ;
Bloom, PN .
JOURNAL OF CONSUMER RESEARCH, 2006, 33 (01) :71-81
[6]
Some practical guidance for the implementation of propensity score matching [J].
Caliendo, Marco ;
Kopeinig, Sabine .
JOURNAL OF ECONOMIC SURVEYS, 2008, 22 (01) :31-72
[7]
Coulson N. S., 2000, British Food Journal, V102, P661, DOI 10.1108/00070700010362031
[8]
Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments [J].
DiPrete, TA ;
Gangl, M .
SOCIOLOGICAL METHODOLOGY, 2004, VOL 34, 2004, 34 :271-310
[9]
*EUR ADV SERV, 2004, INTR MAND NUTR LAB E
[10]
GANGL M, 2004, STATA MODULE PERFORM