『RC』inventory-smoothing 已確認

ethen0403

我只隐约记得一道阅读短文章，是我做的最后一篇：开篇给出一个概念叫做production-smoothing model, 应该叫生产平滑模型？ 然后列举了这种Model或者说策略的诸多好处，比如在订单很多需求变大的时候不用扩大生产规模增加Output。使用这种策略得到的收益超过了存储存货所要的成本。作者还在这一段提到销售量和存货理论上应该是逆相关关系。但是实际的Empirical Test并不是。

很多人检验这个模型。有人用aggregation data来检测这个模型。但是发现对公司们并不适用，有人说是因为aggregation data累积了太多公司，无法看出这个模型在Individual Firm身上的适用性。但是又有人检验Individual的公司发现也不适用。到此戛然而止。

http://forum.chasedream.com/GMAT_Math/thread-751428-1-1.html?extparms=ThreadCatalogID%3d47%26page%3d1


考古




第一段：inventory-smoothing理论/model的思想是，用库存(inventory)作为buffer,应付可能出现的产品需求的突然增长。这样公司就不用改变当前的生产，production level就会保持稳定 (这里有题)
第二段：根据这个理论，production的variance会下降。而且如果需求增加，sales的variance会增加。但是经过科学家调查，发现production比sales的variance要高，而且他们（或者是sales和inventory，不影响整体阅读）的variance是correlated.这说明要么这个理论有问题，要么还有其他因素影响了调查结果。
第三段：第一句话是，科学家所做的调查是基于aggregate level的（后面有问这句话的作用，我选：提供了possibility that masks对单个企业的应用）。这样一些seasonality的数据可能被忽略。但是有科学家对单个企业做调查，有科学家专门对individual firm做调查，但也与inventory-smoothing理论不符


Q1：主旨：讨论一个模型并研究其问题
Q2：Inventory smoothing 的作用，选保证生产稳定
Q3：最后一段提到aggregate data说明什么：选大概说“暗示aggregate data使得smoothing 理论不适用于individual company”那个选项。
Q3，V2：有一题问“文中提到aggregate data"说明什么：有两个选项有点迷惑，1个说“suggest the possibility that aggregate data masked the applicability of the model to individual company"，还有一个选项说"provide the reason why the model doesn't match real life situation"，具体用词上可能有出入，我想了很久选了前者。现在想想觉得前者应该是对的。

Q4：Inventory-smoothing里面问inventory  primarily concerned with？JJ里那道类似的选的是使生产保持恒定，但是我考的时候感觉peaks and valleys of sales 那个选项好像更好，意思大概就是消除销售峰谷的影响，因为有另外两个选项都是说恒速生产这同一个意思。答案2：那个peaks and valleys 不是说的sales而是说的，demand，看到demand，狗主就把这项排了，选了保持生产稳定。

Q5：第二段：学者通过aggregate data研究发现根据生产平滑模型推算的结果和现实不符合，问为什么
Q6：1匿名主旨题：讨论一个模型并研究其不可靠性


背景資訊：
To understand the inventory behaviors of manufacturers, production smoothing is one of the most discussed theoretical models from the perspective of macroeconomics or an individual firm. The basic motive of production smoothing is that companies can increase or decrease their finished goods inventories to allow production that is smoother than sales [1]. Hence, the production-smoothing model (PSM) of inventories depends on a convex short-run cost function and adjustment costs that induce firms to maintain inventories for dampening the effects of demand fluctuations [2]. In other words, production has to be less volatile than sales in PSM. The above hypothesis is reasonable because it’s a common scene in manufacturing. Meanwhile, inventories will most usually serve as production smoother if adjusting production is costly in comparison with the costs of keeping inventories [3]. Based on the above framework, researchers have developed various formulations of PSM, which have been empirically implemented to different manufacturing sectors. However, the applications of PSM remain debatable despite the intuitive appeal of PSM. Previous empirical studies have shown mixed results regarding the validation of PSM, and Ghali [4] has shown that we should expect to see production smoothing for only a subset of manufacturing industries. He also claims that unless one confines the analysis solely to data on industries for which the PSM should a priori be applicable, the percentage of cases where smoothing is observed is irrelevant. Hence, it is important to verify different formations of PSM and to extend the empirical study of PSM to other key industries.