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Please use this identifier to cite or link to this item: http://purl.umn.edu/121872

Title: ARCH, GARCH, and ARMAX Models for Forecasting Pathogen Indicators and Advisories at Marine Recreational Sites
Authors: Ali, Ghulam
Authors (Email): Ali, Ghulam (ali.ghulam@epa.gov)
Keywords: Autoregressive
moving average
ARMAX
ARCH
AR-ARCH
GARCH
pathogens
Huntington Beach
JEL Codes: C22
Q26
Issue Date: 2011-09-24
Series/Report no.: Marine Resource Economics
Volume 26 No. 3
Abstract: Despite the wide ranging applications of time series methodologies for stochastic processes, they have not been used for environmental economics (except climate change). To fill this gap, we introduce time series methodology for the environmental econometrics, presenting autoregressive, moving average, ARCH, GARCH, and ARMAX models. These models are applied to establish a functional relationship between pathogen indicator and meteorological and environmental variables using time series data associated with Huntington Beach, Ohio. According to ARCH, turbidity, dew point, flow, and rainfall are statistically significant variables. Other models produced roughly similar results because of the short lag order. Models confirm the lag order of one using Akaike, Schwartz, and Hannan-Quinn selection criteria, reflecting very short memory of the pathogen indicator series. However, the time series did not support GARCH variance structure. These models not only under forecasted observations at both ends of the distribution of the data, but also simultaneously underforecasted advisories.
URI: http://purl.umn.edu/121872
Identifiers: 0738-1360
Institution/Association: Marine Resource Economics>Volume 26, Number 3, 2011
Total Pages: 14
From Page: 211
To Page: 224
Collections:Volume 26, Number 3, 2011

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