文章基本信息

标题：Influential Commodities Using Hat Values in Stochastic Laspeyres Price Model with AR(1) Errors
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作者：Arfa Maqsood ; S. M. Aqil Burney ; Tahseen Jilani 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2019
卷号：19
期号：4
页码：96-101
出版社：International Journal of Computer Science and Network Security
摘要：This article considers the two structure of stochastic Laspeyres price model. One is the standard regression model of simple Laspeyres price index. While the other is based on an extended approach to the simple version that incorporates a systematic change in relative prices to the simple model. In both versions, the error structure is first order serial correlation. We use the general form of hat matrix to detect the influential commodities in estimating the Laspeyres index number. The results show that the corresponding weights of consumer items have a larger influence on parameter estimates. The extended version of the Laspeyres model investigates the influential commodities more accurately than the simple one as it depends on both the weights and the parameter of AR(1) process.
关键词：Laspeyres index Numbers; Serial Correlation; Autoregressive Process; Hat matrix; Influential Commodities