Ph12-Greene-Econmtric7e2
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Ph12-Greene-Econmtric7e2
www.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2. The analysis of individual choice (hat is the focus of this field is fundamentally about modeling discrete outcomes such as purchase decisions, for example whether or not to buy insurance, voting behavior, choice among a set of alternative brands, travel modes or places to live, and responses to s Ph12-Greene-Econmtric7e2urvey questions about the strength of preferences or about self-assessed health or well-being. In these and any number of other cases, the “dependentPh12-Greene-Econmtric7e2
variable" is not a quantitative measure of some economic outcome, but rather an indicator of whether or not some outcome occurred. 11 follows that thewww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2o make probabilistic statements about the occurrence of these events. We will also examine models for counts of occurrences. These are closer to familiar regression models, but are. once again, about discrete outcomes of behavioral choices. As such, in this setting as well, we will be modeling proba Ph12-Greene-Econmtric7e2bilities of events, rather than conditional mean functions.The models that are analyzed in this and the next chapter are built on a platform of preferPh12-Greene-Econmtric7e2
ences of decision makers. We take a random utility view of the choices that arc observed. The decision maker is faced with a situation or set of alterwww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2 influences this is. of course, the ultimate objective of advertising—and by unobservable characteristics of the chooser. Ihe blend of these fundamental bases for individual choice is at the core of the broad range of models that we will examine here.'This chapter and Chapter 18 will describe four b Ph12-Greene-Econmtric7e2road frameworks for analysis:Binary Choice: The individual faces a pair of choices and makes that choice between the two that provides the greater utiPh12-Greene-Econmtric7e2
lity. Many such settings involve the choice between taking an action and not taking that action, for example the decision whether or not to purchase hwww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2rk via public or private transportation. In the binary choice case, the 0/1 outcome is merely a label for “no/yes”—the numerical values are a mere convenience.Multinomial Choice: The individual chooses among more than two choices, once again, making the choice that provides the greatest utility. Tn Ph12-Greene-Econmtric7e2the previous example. private travel might involve a choice of being a driver or passenger while public’See Greene and Hcnshcr (2(110, Chapter 4) forPh12-Greene-Econmtric7e2
an historical perspective on this approach to model specification.681www.downloadslide.com682 PART IV ♦ Cross Sections, Panel Data, and Microeconometrwww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2, a special case of the former. But. more elaborate models of multinomial choice allow a rich specification of consumer preferences. In the multinomial case, the observed response is simply a label for the selected choice: it might be a brand, the name of a place, or the type of travel mode. Numeric Ph12-Greene-Econmtric7e2al assignments are not meaningful in this selling.Ordered Choice: llie individual reveals the strength of his or her preferences with respect to a sinPh12-Greene-Econmtric7e2
gle outcome. Familiar cases involve survey questions about strength of feelings about a particular commodity such as a movie, or self-assessments of swww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2ally 0.1.J for some up-per limit. J. For example, opinions might be labelled 0.1. 2.3.4 to indicate the strength of preferences, for example, for a product, a movie, a candidate or a piece of legislation. But. in this context, the numerical values are only a ranking, not a quantitative measure. Thus Ph12-Greene-Econmtric7e2 a "1” is greater than a “0” in a qualitative sense, but not by one unit, and the difference between a “2” and a “1” is not the same as that between aPh12-Greene-Econmtric7e2
“1” and a “0.”In these three cases, although the numerical outcomes are merely labels of some nonquantitativc outcome, the analysis will nonetheless www.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2 choices. For example, in the binary outcome “did or did not purchase health insurance,” a conditioning model suggests that covariatcs such as age. income, and family situation will help to explain the choice. Ibis chapter will describe a range of models that have been developed around these conside Ph12-Greene-Econmtric7e2rations. We will also be interested in a fourth application of discrete outcome models:Event Counts: The observed outcome is a count of the number ofPh12-Greene-Econmtric7e2
occurrences. In many cases, this is similar to the preceding three sellings in that the “dependent variable" measures an individual choice, such as thwww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2 recreation site. In other cases, the event count might be the outcome of some natural process, such as incidence of a disease in a population or the number of defects per unit of time in a production process. In this setting, we will be doing a more familiar sort of regression modeling. However, th Ph12-Greene-Econmtric7e2e models will still be constructed specifically to accommodate the discrete nature of the observed response variable.We will consider these four casesPh12-Greene-Econmtric7e2
in turn. The four broad areas have many elements in common; however, there are also substantive differences between the particular models and analysiwww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2plications and then present the single basic model that is the centerpiece of the methodology, and. finally, examine some recently developed extensions of the model. This chapter contains a very lengthy discussion of models for binary choices. This analysis is as long as it is because, first, the mo Ph12-Greene-Econmtric7e2dels discussed are used throughout microeconometrics— the central model of binary choice in this area is as ubiquitous as linear regression. Second, aPh12-Greene-Econmtric7e2
ll the econometric issues and features that are encountered in the other areas will appear in the analysis of binary choice, where we can examine themwww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2ls for multinomial and ordered choice considered in Chapter 18 can be built from the two fundamental building blocks, the model of random utility and the translation of that model into a description of binary choices. There are relatively few new econometric issues that arise here. Chapter 18 will b Ph12-Greene-Econmtric7e2e largely devoted to suggesting different approaches to modeling choices among multiple alternatives and models for ordered choices. Once again, modelPh12-Greene-Econmtric7e2
s of preference scales, such as movie or product ratings, or self-assessments of health or wellbeing, can be naturally built up from the fundamental mwww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2 demonstrate some recent applications and innovations.Chapters 17 and 18 are a lengthy but far from complete survey of topics in estimating qualitative response (ỌR) models. None of these models can consistently be estimated with linear regression methods, in most cases, the method of estimation is Ph12-Greene-Econmtric7e2maximum likelihood. Therefore, readers interested in the mechanics of estimation may want to review* the material in Appendices D and E before continuPh12-Greene-Econmtric7e2
ing, rhe various properties of maximum likelihood estimators are discussed in Chapter 14. We shall assume throughout these chapters that the necessarywww.downloadsllde.com17DISCRETE CHOICE^9/9/9J=-17.1 INTRODUCTIONThis is the first of three chapters that will survey models used in microeconometrics. Ph12-Greene-Econmtric7e2 specifically for the OR models. Detailed proofs for most of these models can be found in surveys by Amcmiya (1981). McFadden (1984). Maddala (1983). and Dhrymes (1984). Additional commentary on some of the issues of interest in the contemporary literature is given by Manski and McFadden (1981) and Ph12-Greene-Econmtric7e2Maddala and Florcs-Laguncs (2001). Agresti (2002) and Cameron and Trivcdi (2005) contain numerous theoretical developments and applications. Greene (2Ph12-Greene-Econmtric7e2
008) and Hensher and Greene (2010) provide, among many others, general surveys of discrete choice models and methods.217.2 MODELS FOR BINARY OUTCOMESFGọi ngay
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