Recent PSC Publication Abstracts
Below are the 10 most recent additions to the PSC publication collection.
Kowalski, Amanda. 2019. "Counting Defiers." PSC Research Report No. 19-893. 3 2019. Abstract.
The LATE monotonicity assumption of Imbens and Angrist (1994) precludes "defiers," individuals whose treatment always runs counter to the instrument, in the terminology of Balke and Pearl (1993) and Angrist et al. (1996). I allow for defiers in a model with a binary instrument and a binary treatment. The model is explicit about the randomization process that gives rise to the instrument. I use the model to develop estimators of the counts of defiers, always takers, compliers, and never takers. I propose separate versions of the estimators for contexts in which the parameter of the randomization process is unspecified, which I intend for use with natural experiments with virtual random assignment. I present an empirical application that revisits Angrist and Evans (1998), which examines the impact of virtual random assignment of the sex of the first two children on subsequent fertility. I find that subsequent fertility is much more responsive to the sex mix of the first two children when defiers are allowed.
Kowalski, Amanda. 2019. "A Model of a Randomized Experiment with an Application to the PROWESS Clinical Trial." PSC Research Report No. 19-894. 3 2019. Abstract.
I develop a model of a randomized experiment with a binary intervention and a binary outcome. Potential outcomes in the intervention and control groups give rise to four types of participants. Fixing ideas such that the outcome is mortality, some participants would live regardless, others would be saved, others would be killed, and others would die regardless. These potential outcome types are not observable. However, I use the model to develop estimators of the number of participants of each type. The model relies on the randomization within the experiment and on deductive reasoning. I apply the model to an important clinical trial, the PROWESS trial, and I perform a Monte Carlo simulation calibrated to estimates from the trial. The reduced form from the trial shows a reduction in mortality, which provided a rationale for FDA approval. However, I find that the intervention killed two participants for every three it saved.
Kowalski, Amanda. 2018. "Biology Meets Behavior in a Clinical Trial: Two Relationships between Mortality and Mammogram Receipt." PSC Research Report No. 18-892. 9 2018. Abstract.
I unite the medical and economics literatures by examining relationships between biology and behavior in a clinical trial. Specifically, I identify relationships between mortality and mammogram receipt using data from the Canadian National Breast Screening Study, an influential clinical trial on mammograms. I find two important relationships. First, I find heterogeneous selection into mammogram receipt: women more likely to receive mammograms are healthier. This relationship follows from a marginal treatment effect (MTE) model that assumes no more than the local average treatment effect (LATE) assumptions. Second, I find treatment effect heterogeneity along the mammogram receipt margin: women more likely to receive mammograms are more likely to be harmed by them. This relationship follows from an ancillary assumption that builds on the first relationship. My findings contribute to the literature concerned about harms from mammography by demonstrating variation across the mammogram receipt margin. This variation poses a challenge for current mammography guidelines for women in their 40s, which unintentionally encourage more
mammograms for healthier women who are more likely to be harmed by them.
Kowalski, Amanda. 2018. "How to Examine External Validity within an Experiment." PSC Research Report No. 18-891. 8 2018. Abstract.
A fundamental concern for researchers who analyze and design experiments is that the experimental result might not be externally valid for all policies. Researchers often attempt to assess external validity by comparing data from an experiment to external data. In this essay, I discuss approaches from the treatment effects literature that researchers can use to begin the examination of external validity internally, within the data from a single experiment. I focus on presenting the approaches simply using figures.
Fisher, Jonathan, David S. Johnson, Timothy S. Smeeding, and Jeffrey Thompson. 2018. "The Demography of Inequality: Income, Wealth and Consumption, 1989-2016." PSC Research Report No. 18-890. 7 2018. Abstract.
Inequality differentially affects demographic groups, and the socioeconomic measure we use matters quite a lot when understanding how inequality differentially affects demographic groups. We examine the demography of inequality using age, race, education, and family type for children, and we show how the demography of inequality depends on the resource measure used: income, consumption, or wealth. Children and the elderly are worse off than non-elderly adults in income terms, but only children and their parents are increasingly and disproportionately found in the lower reaches of the wealth and consumption distributions. For some groups, all lenses show the same picture, as children in single parent households, blacks, and those with less than a high school education are worse off in terms of all resource measures - income, wealth or consumption.
Johnson, David S., Robert F. Schoeni, Laura Tiehen, and Jennifer Cornman. 2018. "Assessing the Effectiveness of SNAP by Examining Extramarginal Participants." PSC Research Report No. 18-889. 4 2018. Abstract.
A primary objective of in-kind transfer programs is to promote the consumption of specific goods. Standard economic theory implies that the program's ability to achieve this objective depends critically on the proportion of recipients whose spending on the good is limited to the amount of the in-kind transfer, i.e., they are extramarginal. For these families, an increase in benefits will translate into an equal sized increase in consumption of the good. We find that roughly 30% of participants in SNAP are extramarginal, which is larger than previous estimates and implies in-kind benefits provided through SNAP promote food consumption. Furthermore, very low income SNAP families are much more likely to be extramarginal, and extramarginal families have extremely low income and are nearly five times more likely to be food insecure than families not on SNAP, implying that families are extramarginal not because their food needs are fully met by SNAP, but because their income is so low.
Mehta, Neil, and Hui Zheng. 2018. "Do the effects of major risk factors for mortality rise or fall with age?" PSC Research Report No. 18-888. 2 2018. Abstract.
Researchers are often interested in how a risk factor's effect on mortality changes with age because the pattern has direct relevancies to life-course theories, public health practice, and demographic modeling. Here we highlight the importance of mathematical scale to interpreting risk factor by age interactions, describing how the choice of scale has critical implications for theory development and arguing that many life-course studies have not recognized the importance of scale to conclusions drawn from their findings. We also provide an empirical analysis of risk factor by age interactions drawing from a set of major risk factors for mortality often studied in demography and epidemiology. We show that these risk factors conform to a general pattern-the strength of their association with mortality tends to increase with age. This prevailing pattern of increasing risks by age across multiple major risk factors for mortality has not been identified previously. We go on to argue that the pattern has critical underpinnings for life-course theory, public health allocation, and clinical practice.
Axinn, William G., James Wagner, Mick P. Couper, and Scott Crawford. 2018. "Campus Climate Surveys of Sexual Misconduct: Limiting the Risk of Nonresponse Bias." PSC Research Report No. 18-887. 2 2018. Abstract.
High attention to campus surveys of sexual misconduct has raised concerns about the potential of nonresponse bias in data from these surveys. Best practices in survey methodology offer many options to limit nonresponse. Here we examine two of the most potent options: individual incentives for participation and two-phase survey designs that alter the method of contact. Analyzing data from the University of Michigan's 2015 campus climate survey we demonstrate that a two-phase design introducing telephone and face-to-face reminders to complete the survey can produce stronger change in response rates, characteristics of those who respond, and statistical estimates than higher incentive levels. Cost comparison also reveals use of trained interviewers to contact students can be more efficient than higher incentive levels.
Zhou, Xiang, and Yu Xie. 2018. "Heterogeneous Treatment Effects in the Presence of Self-Selection: A Propensity Score Perspective." PSC Research Report No. 18-886. 1 2018. Abstract.
An essential feature common to all empirical social research is variability across units of analysis. Individuals differ not only in background characteristics, but also in how they respond to a particular treatment, intervention, or stimulation. Moreover, individuals may self-select into treatment on the basis of their anticipated treatment effects. To study heterogeneous treatment effects in the presence of self-selection, Heckman and Vytlacil (1999, 2001a, 2005, 2007b) have developed a structural approach that builds on the marginal treatment effect (MTE). In this paper, we extend the MTE-based approach through a redefinition of MTE. Specifically, we redefine MTE as the expected treatment effect conditional on the propensity score (instead of all observed covariates) as well as a latent variable representing unobserved resistance to treatment. The redefined MTE improves upon the original MTE in a number of aspects. First, while it is conditional on a unidimensional summary of covariates, it is sufficient to capture all of the treatment effect heterogeneity that is consequential for selection bias. Second, the new MTE is a bivariate function, and thus is easier to visualize than the original MTE. Third, as with the original MTE, the new MTE can also be used as a building block for evaluating standard causal estimands such as ATE and TT. However, the weights associated with the new MTE are simpler, more intuitive, and easier to compute. Finally, the redefined MTE immediately reveals treatment effect heterogeneity among individuals who are at the margin of treatment. As a result, it can be used to evaluate a wide range of policy changes with little analytical twist, and to design policy interventions that optimize the marginal benefits of treatment.
Teerawichitchainan, Bussarawan, and John E. Knodel. 2017. "Impacts of Migration on Households in the Dry Zone, Myanmar." PSC Research Report No. 17-882. 10 2017. Abstract.
In 2014 an estimated 12% of all Myanmar households had internal migrants and 8% had international migrants - proportions projected to grow significantly within the next decade. This study analyzes data from Myanmar's 2017 Dry Zone Migration Impact Survey to assess the impacts of migration on households in migration-source areas. It examines characteristics and patterns of migration in the Dry Zone, distinguishing between economic and non-economic migration, and the extent to which migration affects material wellbeing and livelihoods experienced by migrant-sending versus non-migrant households. It also examines the economic and social implications of migration for household members remaining in the Dry Zone. Specifically, it evaluates the wellbeing and unmet needs of potentially vulnerable segments of the population left behind in migrant-sending households, including dependent children and other family members in need of personal care (e.g., the elderly and disabled). Based on the empirical findings, the authors discuss how policy and support can be enhanced to increase the positive impacts of migration on migrant-sending households and to address its negative consequences.