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Issues in the Estimation of Causal Effects in Population Research, with an Application to the Effects of Teenage Childbearing

The estimation of causal effects has become an important subject of study in Population Research. This essay surveys the recent literature in economics on this issue, with a focus on the method of instrumental variables. Conditions for the validity of instrumental variable methods are discussed along with the proper interpretation of the resulting estimates. Several difficult issues with the method are outlined, including the problem of external validity, reconciling the differences in estimates when different instruments are used, and detecting instrument validity. Population Research has a distinguished history of empirical work on a wide variety of important topics related to Population growth, the components of demographic trends, estimation of vital rates, life table construction, investigation into causes of historical Population developments, and many others. However, one branch of Population Research that has seen increasing interest has been in the area of social demography, where the determinants of individual behavior regarding fertility, marriage, and related areas has been studied. It is in that branch that issues of causal inference have arisen, and with which this essay is concerned. This development in Population Research coincides with a more general interest in causal inference in statistics and in other social sciences such as economics. In statistics, the development of the Rubin Causal Model (Rubin, 1974) as a framework for studying causal questions has become a dominant paradigm even though, at the same time, there is considerable work by other statisticians using somewhat different frames. The development in statistics, while having many historical antecedents in the field, by and large occurred only in the 1970s and 1980s. Prior to that time, randomized experiments were regarded as the only method for true causal inference. However, randomized experiments are generally not possible in many fields, including Population Research, and hence methods for the analysis of causation using observational data are needed. In economics, while causality has a much longer history dating to the development of the simultaneous equations model, which saw its fullest development in the Cowles Commission work in the 1950s, renewed interest in the issue has arisen since the 1980s and 1990s as more 2 subtle issues have been addressed. Other social science disciplines such as sociology and political science are following the developments in statistics and in economics, with new developments adapted to their unique sets of questions and issues. This essay will review the issues in causal modeling using primarily the framework adapted in economics, and will apply those modeling issues to the study of Population questions. The economics framework is, when boiled down to essentials, observationally equivalent to the Rubin Causal model in statistics, although the interpretation and language used to describe the two are quite different. In addition, their practical empirical implementation is often quite different, with economists leaning toward modeling by the use of regression equations with explicitly represented error terms, an approach different from that in statistics. While the causal modeling developments in economics have taken many directions, the vast majority of applications in the field use the method of instrumental variables (IV) to estimate causal effects. Therefore, this essay will also concentrate on that method, outlining both its rationale and advantages and the pitfalls and weaknesses associated with its use. Brief mention will be made of other methods such as panel data fixed effects methods and matching. The running example in the essay is the question of whether teenage childbearing has a deleterious effect on female economic outcomes such as income and earnings. The increase in rates of teen childbearing in the U.S. has been a source of public concern not only because much of that childbearing is nonmarital but also because of the widespread perception that women who begin their childbearing at a very young age run the risk of harming their educational progress and their later economic and social success. There has been a great deal of Research on this issue with, surprisingly, much less support for this conventional view as might be expected. But the See Moffitt (2003,2005) for earlier reviews. 1 3 literature has also generated much discussion of the method of causal effects and of the effects of using different instruments for estimation. Thus, this particular literature can be used to illustrate a number of the issues in causal modeling in Population Research in general. The first section below lays out the general causal model in economics and discusses a number of the main issues. The method of instrumental variables is then outlined, followed by a categorization of the types of instruments most often used. Additional issues in the use of instrumental variables are then reviewed, followed by a set of conclusions. Some of the points made in the essay are (i) a tradeoff between internal validity and external validity is often faced by analysts using the method; (ii) multiple instruments or instruments with multiple values can be used to learn more about effects in heterogeneous Populations than binary instruments; and (iii) use of theory is important to determine mechanisms by which treatments affect outcomes and how differing instruments interact with those mechanisms. The Basic Causal Model The basic causal model in economics dates to the Cowles Commission work on simultaneous equations in economics and, later, its adaptation to individual actions represented in the switching regression model (Heckman, 1978; Lee, 1979). Heckman and Robb (1985) and Bjorklund and Moffitt (1987) made the connection between that model and newer thinking in causal modeling as well as introducing the notion of heterogeneity to be discussed momentarily. Heckman et al. (2006) provide a recent overview of the model. The prototype linear regression model used in this literature is

Remarks on the analysis of causal relationships in Population Research.

The problem of determining cause and effect is one of the oldest in the social sciences, where laboratory experimentation is generally not possible. This article provides a perspective on the analysis of causal relationships in Population Research that draws upon recent discussions of this issue in the field of economics. Within economics, thinking about causal estimation has shifted dramatically in the past decade toward a more pessimistic reading of what is possible and a retreat in the ambitiousness of claims of causal determination. In this article, the framework that underlies this conclusion is presented, the central identification problem is discussed in detail, and examples from the field of Population Research are given. Some of the more important aspects of this framework are related to the problem of the variability of causal effects for different individuals; the relationships among structural forms, reduced forms, and knowledge of mechanisms; the problem of internal versus external validity and the related issue of extrapolation; and the importance of theory and outside evidence.

Causal Analysis in Population Research: An Economist's Perspective

The problem of determining cause and effect is one of the oldest questions in the social sciences. This note provides a perspective on the analysis of causal relationships in Population Research, drawing upon recent discussions in the field of economics. Within economics, thinking about causal estimation has shifted markedly in the last decade toward a more pessimistic reading of what is possible and a retreat in the ambitiousness of claims of causal determination. The framework that underlies this conclusion is presented, methods for isolating causal effects are discussed, and an example from the field of Population Research is given.

Bibliography of Finnish Population Research 1999

Bibliography of Finnish Population Research 1995-1998

Bibliography of Finnish Population Research 1994

The bibliography covers mainly the literature on Population Research published in Finland during 1994. Included are independent publications articles in periodicals and mainly nationwide statistics published in Finland as well as studies by Finnish authors published abroad. (EXCERPT)

Bibliography of Finnish Population Research 1992-1993

Bibliography of Finnish Population Research 1991

Developing and Maintaining a Population Research Registry to Support Primary Healthcare Research

Population Research registries provide necessary foundational information for primary healthcare (PHC) Research and, more generally, for health services Research. Data on Population socio-demographic, morbidity, mortality, geographic, service registration and other characteristics provide critical information to describe and study need, demand for and use of services by the Population overall and by Population subgroups. Research registries using linked health data have been established in a number of jurisdictions to support Population-based Research initiatives (Roos and Nicol 1999; Roos et al. 2003). Data from these registries enable policy analyses, planning and management of healthcare resources (Roos et al. 2004) and information to support system-level performance measurement and evaluation of services. This special issue of Healthcare Policy documents the development of an information system for PHC Research in British Columbia. In this paper, we describe the development of a Population Research registry as part of this PHC information system. The Population Research registry includes almost all individuals living in British Columbia, together with anonymized core data for each individual. Strict protocols have been established to ensure security and to protect privacy and confidentiality of personal health information. The BC Population Research registry can be used to identify and study groups in the province and to support analysis of treatment prevalence and other Population-based rates. Not only does the registry provide data on the Population, but these can be combined with data from other sources to analyze service utilization, some qualities of PHC and selected outcomes for the Population. The Population Research registry, along with a physician information system (see Watson et al. 2009, page 77 of this special issue of Healthcare Policy), forms the foundation for a PHC information system to support Research on Population, providers and utilization of healthcare services.

Developing and maintaining a Population Research registry to support primary healthcare Research.

WHAT DID WE DO?: This paper describes the creation of a Population Research registry as part of an information system to support primary healthcare (PHC) Research in British Columbia. The Population registry includes all residents of the province who were either eligible to use or actually used healthcare services, together with demographic, geographic, health status, registration and service use data. The PHC Population Research registry is built using administrative data inputs, and data are anonymized to comply with privacy and confidentiality standards. WHAT DID WE LEARN?: The registry provides data to undertake Research into PHC needs and service utilization. It facilitates both Population-based Research as well as Research on Population subgroups. Combined with anonymous physician and utilization data, the information system can be used to study service utilization rates for Population-based analyses. Over the longer term, the information will contribute to our understanding of PHC qualities and outcomes. WHAT ARE THE IMPLICATIONS?: Continued completeness of the Population Research registry depends upon full administrative source data. Planning to ensure complete data capture is critical both for the Research registry and our ability to undertake Population-based PHC Research.

Using administrative health care system records to recruit a community-based sample for Population Research.

Abstract Purpose Epidemiologists often seek a representative sample of particular persons from geographically bounded areas. However, it has become increasingly difficult to identify a sample frame that truly represents the underlying target Population. We assessed the degree to which a clinic-based sample represents a target community. Methods Our sample frame is from a large health care provider from the Minneapolis-Saint Paul, Minnesota, metropolitan area. We used U.S. Census data to examine the sociodemographic and geospatial distribution of the sampling frame and among those who did and did not respond. Results Our study's overall response rate was 57%. The most impoverished areas of the target Population were under-represented in our sample frame, but this under-representation was similar for both respondents and nonrespondents. In addition, our sampled Population was slightly older compared to the target Population. Using ecological-level census-derived markers of sociodemographic characteristics, members of the sample frame were similar to that of the target Population except for being somewhat more highly educated. However, the distributions of available individual-level data such as race and education were different between respondents and the target Population. Conclusions Although the use of health care administrative records for identifying a sampling frame that represents a target Population has limitations, our findings suggest that this method had strengths. More comparisons of methods for identifying and recruiting target Populations are needed.

The Family Planning Services and Population Research Act of 1970 — Public Law 91-572

In recent years, there has been a heightened public concern over the increasing Population of the nation and the improved medical ability to control conception. In 1970, the Congress and the President took action on both subjects in the form of the Family Planning Services and Population Research Act. It is the purpose of this paper to examine the legislative history of the Act beginning in 1965.1 Consideration will be limited to those aspects of the history that relate to the domestic popu lation and family planning concerns. It is not the purpose of this paper to consider either the international Population question or the actions of foreign or international bodies, nor is it the purpose of this paper to attempt to ascertain whether in fact there is or will be a national Population crisis. Rather, this paper is directed toward examining the testimony of public and pri vate witnesses, public documents which relate to the various legislative proposals, some of the policy questions that were dealt with, as well as toward the consideration of commentary on the factors that combined to produce the 1970 legislation.