@inproceedings{d505bd4db226481cb7f02ebf7fee94b9,

title = "Prediction of Malaysian Monthly GDP",

abstract = "The paper attempts to use a method based on multivariate power-normal distribution to predict the Malaysian Gross Domestic Product next month. Letting r(t) be the vector consisting of the month-t values on m selected macroeconomic variables, and GDP, we model the month-(t+1) GDP to be dependent on the present and l-1 past values r(t), r(t−1),…,r(t−l+1) via a conditional distribution which is derived from a [(m+1)l+1]-dimensional power-normal distribution. The 100(α/2)% and 100(1-α/2)% points of the conditional distribution may be used to form an out-of sample prediction interval. This interval together with the mean of the conditional distribution may be used to predict the month-(t+1) GDP. The mean absolute percentage error (MAPE), estimated coverage probability and average length of the prediction interval are used as the criterions for selecting the suitable lag value l−1 and the subset from a pool of 17 macroeconomic variables. It is found that the relatively better models would be those of which 2 ≤ l ≤ 3, and involving one or two of the macroeconomic variables given by Market Indicative Yield, Oil Prices, Exchange Rate and Import Trade.",

keywords = "EURO AREA",

author = "Hin, {Pooi Ah} and Soo, {Huei Ching} and Yeing, {Pan Wei}",

year = "2015",

doi = "10.1063/1.4937102",

language = "English",

isbn = "978-0-7354-1338-2",

series = "AIP Conference Proceedings",

publisher = "AIP Publishing",

editor = "Adyda Ibrahim and Jafri Zulkepli and Nazrina Aziz and Nazihah Ahmad and Syariza Abdul-Rahman",

booktitle = "INNOVATION AND ANALYTICS CONFERENCE AND EXHIBITION (IACE 2015)",

address = "United States",

note = "2nd Innovation and Analytics Conference and Exhibition 2015, IACE 2015 ; Conference date: 29-09-2015 Through 01-10-2015",

}