The Trial Compilation of Agriculture Purchasing Managers’ Index for Taiwan: The case of Taiwanese Hog industry.

• Main Authors: Tzu-Ling Tien, 田子玲
• Other Authors: 李宗儒
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/8ku92u

碩士 === 國立中興大學 === 全球事務研究跨洲碩士學位學程 === 106 === Most of the agricultural researches and forecasting in Taiwan are focusing on individual agriculture industry or product. Hence, there is an absence of agricultural index to describe the economic status in the market. Agricultural companies and government departments haven’t had information except agricultural Gross Domestic Profit (GDP) to measure the development of the current industry. To solve the problem, we search for index who shares the features mentioned above in non-agriculture industry, and thus, we found Purchasing Managers’ Index (PMI) and Non-Manufacturing Index (NMI). In this thesis, we consider that PMI and NMI share the features, which we are looking for in agriculture index, are able to predict GDP variability also represent economic status of the industry. Therefore, we will conduct a trial agricultural PMI as aim of the research. Including twelves variables monthly data for five years, we will adapt correlation coefficient to determine if the variables are strongly correlated to macro-economic indexes. After correlation coefficient, Principle components analysis will be applied to decide the best weight for each variables in APPMI (Agricultural Pig Purchasing Managers’ Index) formula. With all diffusion indexes multiply the optimal weight for each variable and adding them up, we have APPMI as time series for five years. In twelves different combinations of data set, which had been conducted principle component analysis, we had found one of the PCA4 data set is able to interpret 70 percent of variability of total revenue in hog industry. In PCA4, variables, traded amount、price per kilogram、total weight、farms amount are included. After refining and seasonal adjusting, also combining with other agriculture industries, APMI will be able to represent as agriculture economic status, which could be a solid reference for agricultures companies and government while making decision or evaluation for investing in the industry. In the thesis, assumptions and limits also are illustrated for further researches and refine.