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Rather than calculate point estimates of the response of a time\u2010series to an aggregate shock, we calculate the whole probability density function of the response and use Monte\u2010Carlo or Gibbs sampling techniques to evaluate its properties. The proposed techniques impose identification restrictions in a way that includes the uncertainty in these restrictions, and thus are an improvement over traditional approaches that typically use least\u2010squares techniques supplemented by bootstrapping. We apply these techniques in the context of two different models. A key finding is that measures of uncertainty, such as posterior standard deviations, are much larger than are their classical counterparts.<\/jats:p>","DOI":"10.1002\/jae.3950070406","type":"journal-article","created":{"date-parts":[[2007,7,12]],"date-time":"2007-07-12T16:49:26Z","timestamp":1184258966000},"page":"395-411","source":"Crossref","is-referenced-by-count":24,"title":["Aggregate shocks and macroeconomic fluctuations: A bayesian approach"],"prefix":"10.1002","volume":"7","author":[{"given":"G.","family":"Koop","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2006,11,7]]},"reference":[{"key":"e_1_2_1_2_1","first-page":"655","article-title":"The dynamic effects of aggregate demand and supply disturbances","volume":"79","author":"Blanchard O.","year":"1989","journal-title":"American Economic Review"},{"key":"e_1_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Casella G. andE.George (1992) \u2018Explaining the Gibbs sampler\u2019 American Statistician(forthcoming).","DOI":"10.2307\/2685208"},{"key":"e_1_2_1_4_1","unstructured":"Doan T. 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