Sample data alone never suffice to draw conclusions about populations. Inference always requires assumptions about the population and sampling process. Statistical theory has revealed much about how strength of assumptions affects the precision of point estimates, but has had much less to say about how it affects the identification of population parameters. Indeed, it has been commonplace to think of identification as a binary event - a parameter is either identified or not - and to view point identification as a pre-condition for inference. Yet there is enormous scope for fruitful inference...
Sample data alone never suffice to draw conclusions about populations. Inference always requires assumptions about the population and sampling process...
This book is a full-scale exposition of Charles Manski's new methodology for analyzing empirical questions in the social sciences. He recommends that researchers first ask what can be learned from data alone, and then ask what can be learned when data are combined with credible weak assumptions. Inferences predicated on weak assumptions, he argues, can achieve wide consensus, while ones that require strong assumptions almost inevitably are subject to sharp disagreements.
Building on the foundation laid in the author's Identification Problems in the Social Sciences (Harvard,...
This book is a full-scale exposition of Charles Manski's new methodology for analyzing empirical questions in the social sciences. He recommends th...
This book provides a language and a set of tools for finding bounds on the predictions that social and behavioral scientists can logically make from nonexperimental and experimental data. The economist Charles Manski draws on examples from criminology, demography, epidemiology, social psychology, and sociology as well as economics to illustrate this language and to demonstrate the broad usefulness of the tools.
There are many traditional ways to present identification problems in econometrics, sociology, and psychometrics. Some of these are primarily statistical in nature, using...
This book provides a language and a set of tools for finding bounds on the predictions that social and behavioral scientists can logically make fro...
Economists have long sought to learn the effect of a "treatment" on some outcome of interest, just as doctors do with their patients. A central practical objective of research on treatment response is to provide decision makers with information useful in choosing treatments. Often the decision maker is a social planner who must choose treatments for a heterogeneous population--for example, a physician choosing medical treatments for diverse patients or a judge choosing sentences for convicted offenders. But research on treatment response rarely provides all the information that planners...
Economists have long sought to learn the effect of a "treatment" on some outcome of interest, just as doctors do with their patients. A central pra...
Economists and psychologists have, on the whole, exhibited sharply different perspectives on the elicitation of preferences. Economists, who have made preference the central primitive in their thinking about human behavior, have for the most part rejected elicitation and have instead sought to infer preferences from observations of choice behavior. Psychologists, who have tended to think of preference as a context-determined subjective construct, have embraced elicitation as their dominant approach to measurement. This volume, based on a symposium organized by Daniel McFadden at the...
Economists and psychologists have, on the whole, exhibited sharply different perspectives on the elicitation of preferences. Economists, who have made...
Covers the development of discrete choice analysis, of related structural models for analysis of choice behavior, and of the statistical theory used in inference on these models.
Covers the development of discrete choice analysis, of related structural models for analysis of choice behavior, and of the statistical theory used i...
Sample data alone never suffice to draw conclusions about populations. Inference always requires assumptions about the population and sampling process. Statistical theory has revealed much about how strength of assumptions affects the precision of point estimates, but has had much less to say about how it affects the identification of population parameters. Indeed, it has been commonplace to think of identification as a binary event - a parameter is either identified or not - and to view point identification as a pre-condition for inference. Yet there is enormous scope for fruitful inference...
Sample data alone never suffice to draw conclusions about populations. Inference always requires assumptions about the population and sampling process...
Economists and psychologists have, on the whole, exhibited sharply different perspectives on the elicitation of preferences. Economists, who have made preference the central primitive in their thinking about human behavior, have for the most part rejected elicitation and have instead sought to infer preferences from observations of choice behavior. Psychologists, who have tended to think of preference as a context-determined subjective construct, have embraced elicitation as their dominant approach to measurement. This volume, based on a symposium organized by Daniel McFadden at the...
Economists and psychologists have, on the whole, exhibited sharply different perspectives on the elicitation of preferences. Economists, who have made...
