The ontological status of shocks and trends in macroeconomics.
Modern empirical macroeconomic models, known as structural autoregressions (SVARs) are dynamic models that typically claim to represent a causal order among contemporaneously valued variables and to merely represent non-structural (reduced-form) co-occurence between lagged variables and contemporane...
| Publicado en: | Synthese Vol. 192; no. 11; pp. 3509 - 3533 |
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| Formato: | Artículo |
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Springer Nature
Nov2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=111504369&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 111504369 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Nov2015 vid: 192 iid: 11 pid: 237 pub: Springer Nature artinfo: ui: 111504369 10.1007/s11229-014-0503-5 ppf: 3509 ppct: 24 formats: fmt: @attributes: type: P size: 655KB tig: atl: The ontological status of shocks and trends in macroeconomics. aug: au: Hoover, Kevin affil: Department of Economics and Department of Philosophy, Duke University, Durham 27708-0097 USA su: Macroeconomics Ontology Economic shock Mathematical variables Econometrics sug: subj: Macroeconomics Ontology Economic shock Mathematical variables Econometrics keyword: Causal Markov condition Causation Counterfactual policy analysis Principle of the common cause Shocks Trends ab: Modern empirical macroeconomic models, known as structural autoregressions (SVARs) are dynamic models that typically claim to represent a causal order among contemporaneously valued variables and to merely represent non-structural (reduced-form) co-occurence between lagged variables and contemporaneous variables. The strategy is held to meet the minimal requirements for identifying the residual errors in particular equations in the model with independent, though otherwise not directly observable, exogenous causes ('shocks') that ultimately account for change in the model. In nonstationary models, such shocks accumulate so that variables have discernible trends. Econometricians have conceived of variables that trend in sympathy with each other (so-called 'cointegrated variables') as sharing one or more of these unobserved trends as a common cause. It is possible for estimates of the values of both the otherwise unobservable individual shocks and the otherwise unobservable common trends to be backed-out of cointegrated systems of equations. The issue addressed in this paper is whether and in what circumstances these values can be regarded as observations of real entities rather than merely artifacts of the representation of variables in the model. The issue is related, on the one hand, to practical methodological problems in the use of SVARs for policy analysis-e.g., does it make sense to estimate of shocks or trends in one model and then use them as measures of variables in a conceptually distinct model? The issue is also related to debates in the philosophical analysis of causation-particularly, whether we are entitled, as assumed by the developers of Bayes-net approaches, to rely on the causal Markov condition (a generalization of Reichenbach's common-cause condition) or whether cointegration generates a practical example of Nancy Cartwright's 'byproducts' objection to the causal Markov condition. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2015. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2015 holdings: @attributes: islocal: N |
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