Applied Dynamic Macroeconomics
{'Code': '04050100', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
{'SignBlockName': 'Daniel H. Newlon', 'PO_EMAI': None, 'PO_PHON': None}
This project investigates a variety of topics in dynamic                        macroeconomics.  The topics basically fall into two categories:                 (1) linear time series analyses of rational expectations models                 and (2) the micro foundations of monetary theory.                                                                                                               Anyone who has dealt with aggregate U.S. time series data                       understands the potential for measurement error to bias the                     analysis in quantitatively significant ways.  This is obviously                 true in structural linear rational expectations models where the                sources of error terms in reduced form representations of the                   data are critical to the analysis.  It is also central to                       innovation accounting exercises of the type undertaken by Sims,                 as well as analyses of the Blanchard-Watson type which focus on                 exactly identified VAR systems.  The proposed work on                           interpreting seasonality, alternative models of measurement                     error, and least-squares learning in multi-agent settings is                    motivated by a desire to increase the econometric applicability                 of dynamic economic models and improve their interpretation,                    absent a more fundamental solution which would generate better                  measured data.  The two studies on monetary theory, similarly,                  aim to deepen the understanding of different policy predictions                 given by alternative monetary models.  The particular focus of                  this research is on the impact of timing conventions and                        communications technologies.                                                                                                                                    Although each of the several sub-projects deals with different                  aspects of dynamic macroeconomics and is independent of the                     others, in combination their results should contribute to                       strengthening the general underlying theory.  At the same time,                 the findings on seasonality and measurement error will have                     substantial implications for the way econometricians use                        seasonally adjusted data and interpret empirical results derived                from that data.
{'FirstName': 'Thomas', 'LastName': 'Sargent', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas J Sargent', 'EmailAddress': 'sargent@stanford.edu', 'NSF_ID': '000448754', 'StartDate': '08/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'National Bureau of Economic Research Inc', 'CityName': 'CAMBRIDGE', 'ZipCode': '021385359', 'PhoneNumber': '6178683900', 'StreetAddress': '1050 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MA05', 'ORG_UEI_NUM': 'GT28BRBA2Q49', 'ORG_LGL_BUS_NAME': 'NATIONAL BUREAU OF ECONOMIC RESEARCH INC', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1320', 'Text': 'Economics'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8808121.xml'}