Econometric Modeling of Processes with Varying Structural   Parameters
{'Code': '04050100', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
{'SignBlockName': 'Robin A. Cantor', 'PO_EMAI': None, 'PO_PHON': None}
This project continues a successful line of econometric research on a           type of model especially suited for time series analysis, in                    particular for examining financial sector price movements.                      Traditional statistical methods for time series analysis assume that            the variances of forecast errors remain constant from one observation           to the next.  Professor Engle and his colleagues have developed a               class of models know as Autoregressive Conditional Heteroskedasticity           (ARCH) models which relax this restrictive assumption.  In the ARCH             model the variances of a variable are themselves stochastic and                 conditioned on the information contained in the entire variable set.            These models have been used very successfully in analyzing asset price          movements, volatility in the stock market, in forecasting inflation,            and in measuring risk.                                                                                                                                          In this project Professor Engle extends his past work to include                multivariate time series models.  He allows the variances to change             over time in a manner that does not decrease the generality of the              model, but results in a parsimonious specification.  Also included in           this work is the concept of co-integration, which is a statistical              characterization of several series of data which might reasonably               contain common trends or growth tendencies.  This is an important               extension in that such models have a straightforward economic                   interpretation.  Professor Engle also empirically validates his                 theoretical work by applying the ARCH specification to data on asset            prices in foreign exchange markets, interest rates, options contracts,          and equity prices.
{'FirstName': 'Robert', 'LastName': 'Engle', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert F Engle', 'EmailAddress': 'rengle@ucfd.edu', 'NSF_ID': '000205718', 'StartDate': '08/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1320', 'Text': 'Economics'}
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