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Macroeconomic models of consumer demand for consumer packaged goods in Asia

机译:消费者对亚洲消费品包装需求的宏观经济模型

摘要

CPGCo, a global manufacturer of consumer packaged goods, has had tremendous difficulty in producing accurate forecasts for its products in developing markets. The problem was especially apparent during the global economic crisis in 2008, which caused demand for its products to become highly volatile. Its troubles have been aggravated by its long forecasting horizon, as it has not been able to adjust quickly enough to rapid market shifts due to fluctuations in various macroeconomic indicators. As a result, CPGCo faces heavy stockouts and excess inventories. This thesis explores the suitability of using macroeconomic indicators to forecast consumer demand for three developing countries in Asia as well as three separate product segments. A total of 27 macroeconomic models are constructed using stepwise multiple linear regression analysis employing three separate dependent variables: the firm's monthly wholesale shipment volume, retail market share by volume, and retail sales. The world oil price and country-specific exchange rates, stock indexes, interest rates, consumer price indexes, and consumer confidence indicators are used as independent variables. With our models, we are capable of producing extremely accurate forecasts for a small sample set with errors at or below 7.2%. Our findings also indicate that the consumer price index has the most influence on consumer demand, appearing in 81% of our models; thus, we recommend that CPGCo tracks the consumer price index of each country to complement its current forecasting processes.
机译:CPGCo是一家消费包装产品的全球制造商,在为其发展中市场的产品提供准确的预测方面遇到了巨大的困难。该问题在2008年的全球经济危机期间尤为明显,这导致对其产品的需求变得高度不稳定。由于长期的预测前景,它的麻烦更加严重,因为由于各种宏观经济指标的波动,它无法迅速适应迅速的市场变化。结果,CPGCo面临大量缺货和过多库存。本文探讨了使用宏观经济指标预测亚洲三个发展中国家以及三个不同产品领域的消费者需求的适用性。使用逐步多元线性回归分析,使用三个独立的因变量,建立了总共27个宏观经济模型:企业的每月批发出货量,按体积计算的零售市场份额和零售额。世界油价和特定国家/地区的汇率,股票指数,利率,消费者价格指数和消费者信心指标被用作自变量。使用我们的模型,我们能够为误差不超过7.2%的小样本集提供极其准确的预测。我们的发现还表明,消费者价格指数对消费者需求的影响最大,在我们的模型中占81%。因此,我们建议CPGCo跟踪每个国家的消费者物价指数,以补充其当前的预测过程。

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