Measuring authoritarianism with different sets of items in a longitudinal study

Item does not contain fulltextAuthoritarianism is a form of social behavior characterized by strict obedience to the authority of a state or organization and adherence to enforcing and maintaining control through the use of oppressive measures. It refers to a complex of nine subsyndromes (Adorno, Frenkel-Brunswik, Levinson, and Sanford, 1950), of which conventionalism (strict adherence to conventional values), aggression and submission are the most important (Meloen, 1991). The subsyndromes explain why authoritarian people tend to look down on (contraidentify) and discriminate social or ethnic groups that are 'different'. Authoritarianism is part of a broader cluster of cultural conservative attitudes, especially vivid within the lower social classes (Meloen and Middendorp, 1985; De Witte, 1990). Scheepers, Felling, and Peters (1992) argue that a sociological explanation for an authoritarian attitude lies within the need for compensation for political powerlessness, caused by unfavorable social circumstances

Application of GSTARI (1,1,1) Model for Forecasting the Consumer Price Index (CPI) in Three Cities in Central Java

Economic development is affected by several factors, one of which is the inflation rate. One indicator used to measure the inflation rate is Consumer Price Index (CPI). The CPI data is recorded simultaneously at several locations over time, produces space-time data. In Central Java Province, CPI is calculated in six regency/cities, so the CPI is affected by the time and other locations named space-time effect. The forecasting methods involve space and time effect simultaneously is GSTAR. This study used the GSTAR model to forecasting the CPI in 3 cities in Central Java, assuming that autoregressive and space-time parameters differ for each location. This study aims to obtain the best GSTAR model to forecast the CPI in three cities in Central Java by using the IDW and NCC weighting. The results indicated that the best GSTAR model for forecast the CPI in three cities (Surakarta, Semarang, and Tegal) was the GSTARI (1,1,1) model. The GSTARI (1,1,1) model fulfils the assumption of homoscedasticity, white noise, and multivariate normal. The MAPE values obtained using the IDW and NCC weighting are 0.2922% and 0.2914%, respectively. From these results, it can be concluded that the best GSTARI (1,1,1) model to forecast the CPI data in three cities in Central Java is NCC weights, as they have a minimum MAPE value . The results of this research can be used as consideration for the government in making economic policies at the present and in the future