Indiana University-Purdue University Indianapolis (IUPUI) / Communities and States are increasingly targeting the consumption of sugar
sweetened beverages (SSBs), especially soda, in their efforts to curb childhood obesity.
However, the empirical evidence based on which policy makers design the relevant policies
is not causally interpretable. In the present study, we suggest a modeling framework that
can be used for making causal estimation and inference in the context of childhood obesity.
This modeling framework is built upon the two-stage residual inclusion (2SRI)
instrumental variables method and have two levels – level one models children’s lifestyle
choices and level two models children’s energy balance which is assumed to be dependent
on their lifestyle behaviors.
We start with a simplified version of the model that includes only one policy, one
lifestyle, one energy balance, and one observable control variable. We then extend this
simple version to be a general one that accommodates multiple policy and lifestyle
variables. The two versions of the model are 1) first estimated via the nonlinear least square
(NLS) method (henceforth NLS-based 2SRI); and 2) then estimated via the maximum
likelihood estimation (MLE) method (henceforth MLE-based 2SRI). Using simulated data,
we show that 1) our proposed 2SRI method outperforms the conventional method that
ignores the inherent nonlinearity [the linear instrumental variables (LIV) method] or the
potential endogeneity [the nonlinear regression (NR) method] in obtaining the relevant
estimators; and 2) the MLE-based 2SRI provides more efficient estimators (also consistent)
compared to the NLS-based one. Real data analysis is conducted to illustrate the implementation of 2SRI method in practice using both NLS and MLE methods. However,
due to data limitation, we are not able to draw any inference regarding the impacts of
lifestyle, specifically SSB consumption, on childhood obesity. We are in the process of
getting better data and, after doing so, we will replicate and extend the analyses conducted
here. These analyses, we believe, will produce causally interpretable evidence of the effects
of SSB consumption and other lifestyle choices on childhood obesity. The empirical
analyses presented in this dissertation should, therefore, be viewed as an illustration of our
newly proposed framework for causal estimation and inference.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/11647 |
| Date | 18 May 2016 |
| Creators | Yang, Yan |
| Contributors | Terza, Joseph V., Courtemanche, Charles, Jung, Haeil, Mak, Henry Y., Wu, Jisong |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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