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A Longitudinal Time Series Analysis of the Foreign Affairs Issue: Agendas of the President, the Media, the Public
Unformatted Document Text:  Presidential PR efforts and Foreign Policy 17 The cyclic structure of key issues and events is contrasted with the structure of total public relations activities of the president for the respective stages of the cycle of coverage to determine if and how these key issues and events affected the structure of activity for each stage. Because issues and events are not mutually exclusive, each is compared separately with total foreign policy public relations efforts to determine the impact, if any, on the structure of activity. ARIMA Modeling and Analysis of the Foreign policy Issue Agendas Univariate Analysis of the Series. The first step in the ARIMA analysis is to model each of the series by itself. The first parameter to model is trend (d), which is the systematic change in the level of a time series. The second component to model is the autoregressive parameter (p), which is the correlation in the error structure between observations. As shown in Table 10, the autoregressive parameter p, which is indicated by φ, is simply a correlation coefficient. The final parameter, the moving average process (q), is characterized by a finite persistence in the random shock. In this analysis, a moving average parameter did not have to be modeled because of the nature of each of the series. The ARIMA analysis of each of the univariate series offered interesting insights into the nature of the roller coaster ride through time for each of the measures (see Table 10). The ARIMA model for media indicated a first-order autoressive process and a first-order moving averages process: (1, 0, 1). The ARIMA model for the public opinion series indicated a very strong first-order, autoregressive process: (1, 0, 0). The ARIMA model for the Presidential public relations series indicated a first-order moving averages process: (0, 0, 1). Table 10 Univariate ARIMA Coefficients and Explained Variance_____________________________________________________________

Authors: Mitrook, Michael.
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Presidential PR efforts and Foreign Policy
17
The cyclic structure of key issues and events is contrasted with the structure of
total public relations activities of the president for the respective stages of the cycle of
coverage to determine if and how these key issues and events affected the structure of
activity for each stage. Because issues and events are not mutually exclusive, each is
compared separately with total foreign policy public relations efforts to determine the
impact, if any, on the structure of activity.
ARIMA Modeling and Analysis of the Foreign policy Issue Agendas
Univariate Analysis of the Series. The first step in the ARIMA analysis is to
model each of the series by itself. The first parameter to model is trend (d), which is the
systematic change in the level of a time series. The second component to model is the
autoregressive parameter (p), which is the correlation in the error structure between
observations. As shown in Table 10, the autoregressive parameter p, which is indicated
by
φ,
is simply a correlation coefficient. The final parameter, the moving average process
(q), is characterized by a finite persistence in the random shock. In this analysis, a
moving average parameter did not have to be modeled because of the nature of each of
the series.
The ARIMA analysis of each of the univariate series offered interesting insights
into the nature of the roller coaster ride through time for each of the measures (see Table
10).
The ARIMA model for media indicated a first-order autoressive process and a
first-order moving averages process: (1, 0, 1). The ARIMA model for the public opinion
series indicated a very strong first-order, autoregressive process: (1, 0, 0). The ARIMA
model for the Presidential public relations series indicated a first-order moving averages
process: (0, 0, 1).

Table 10
Univariate ARIMA Coefficients and Explained Variance
_____________________________________________________________


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