Econometric models and methods
Christ, Carl F
Econometric models and methods - New Delhi Wiley Eastern 1970 - 705 p.
Why should the tools of inductive inference differ from one empirical discipline to another? In a deeper sense, the tools do not differ. Econo metrics shares its logical foundations with psychometrics and biometrics and, for that matter, with meteorology and even with experimental physics. Two or more sets of jointly asserted propositions about observable facts (not about mathematics or logic or ethics) are compared to determine which set is, in some sense, in better correspondence with facts. In Harold Hotelling's terminology each set of propositions, or hypotheses, contains a subset which is "considered" (tested) and its complement which is "maintained" (assumed) for the purposes of an individual piece of empirical inquiry. Econometric usage (perhaps since Mann and Wald [1943]) attaches the name "prior" to the maintained propositions, thus extending that old philosophical term to propositions which, although not subjected to test in the particular research piece in question, may well have been derived from previous observations. The "prior" propositions give "specification" (R. A. Fisher's term) of a part, not all, of the properties of the studied phenomena-for example, the form of some functions and possibly the sign, the range, or even the exact numerical value of some of their parameters. To take a crude example, proportionality between two observable variables may be asserted a priori, but the choice between rival candidates for the proportionality constant (e.g., between the various estimates of the economists' "velocity of circulation of money") will depend on facts. To be sure, nothing can prevent the facts from discrediting the prior assumption itself.One of the merits of the book is its patient use of examples, introduc ing difficulties step by step. Some methodological problems arise when the simplest economic theory of the freshman classroom (nonstochastic statics) is confronted with available, though generously simplified, facts. New problems of method are added as we ascend to more complex and realistic theories (stochastic dynamics). The reader is then introduced to methods of classical statistical inference. These were developed for the most part in sampling studies outside of economics, and the nature of economic data and tasks creates additional problems (identification, structural estimation, predictive tests) which may not have been noted yet may well arise, and in fact have arisen, in other disciplines. The book should be of great interest to economists. It should also interest students of scientific method applied to nonexperimental data for practical decision purposes, a problem that arises especially, but not exclusively, in social sciences.
Economics
330.1543 CHR
Econometric models and methods - New Delhi Wiley Eastern 1970 - 705 p.
Why should the tools of inductive inference differ from one empirical discipline to another? In a deeper sense, the tools do not differ. Econo metrics shares its logical foundations with psychometrics and biometrics and, for that matter, with meteorology and even with experimental physics. Two or more sets of jointly asserted propositions about observable facts (not about mathematics or logic or ethics) are compared to determine which set is, in some sense, in better correspondence with facts. In Harold Hotelling's terminology each set of propositions, or hypotheses, contains a subset which is "considered" (tested) and its complement which is "maintained" (assumed) for the purposes of an individual piece of empirical inquiry. Econometric usage (perhaps since Mann and Wald [1943]) attaches the name "prior" to the maintained propositions, thus extending that old philosophical term to propositions which, although not subjected to test in the particular research piece in question, may well have been derived from previous observations. The "prior" propositions give "specification" (R. A. Fisher's term) of a part, not all, of the properties of the studied phenomena-for example, the form of some functions and possibly the sign, the range, or even the exact numerical value of some of their parameters. To take a crude example, proportionality between two observable variables may be asserted a priori, but the choice between rival candidates for the proportionality constant (e.g., between the various estimates of the economists' "velocity of circulation of money") will depend on facts. To be sure, nothing can prevent the facts from discrediting the prior assumption itself.One of the merits of the book is its patient use of examples, introduc ing difficulties step by step. Some methodological problems arise when the simplest economic theory of the freshman classroom (nonstochastic statics) is confronted with available, though generously simplified, facts. New problems of method are added as we ascend to more complex and realistic theories (stochastic dynamics). The reader is then introduced to methods of classical statistical inference. These were developed for the most part in sampling studies outside of economics, and the nature of economic data and tasks creates additional problems (identification, structural estimation, predictive tests) which may not have been noted yet may well arise, and in fact have arisen, in other disciplines. The book should be of great interest to economists. It should also interest students of scientific method applied to nonexperimental data for practical decision purposes, a problem that arises especially, but not exclusively, in social sciences.
Economics
330.1543 CHR