Innovative analytic methodologies for collecting and analyzing biomarkers and genetic materials

Data and methods are closely interlinked in demography and economics and give rise to our last theme, Innovative methods and materials. Some methodologies improve inferences given data imperfections, but other approaches assume the availability of specific data, such as date of entry and exit in survival models (Allison). Many PARC Associates have either developed new methods or collected innovative data or both. Recent innovations in methods include the development of new procedures for tackling traditional data problems such as cohort differences in mortality (Preston and Wang), missing data (Allison), and the tempo of fertility change (H‐P Kohler). Other innovations include the development of methods for attributing causality, such as investigating the behaviors of individuals in the presence of heterogeneity (Behrman), counterfactual policy evaluation (Wolpin, Todd), including feedbacks in general equilibrium processes (Fernández‐ Villaverde, Smetters, Wolpin), and program evaluation such as propensity matching (Rosenbaum, Smith, Todd). Other Associates have made contributions by collecting innovative data. Recent examples include field studies on twins for control of genetic and other endowments (Behrman, H‐P Kohler) and on HIV/AIDS and risk behaviors, integrating biodemographic and sociodemographic measures (Aiken, Behrman, Bravo, Chao, H‐P Kohler, Mitchell, Polsky, Sochalski, Soldo, Todd, Watkins). Soldo used unfolding brackets in MHAS to minimize non‐response to survey questions soliciting point estimates and developed a cognitive battery that assumed neither literacy while (Elo, I Kohler, Preston) linked census records and death certificates, and Mitchell has expertise in linking survey data with SSA records.