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| ==Building the Product Space== | | ==Building the Product Space== |
| + | 构建产品空间 |
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| There exists a number of factors that can describe the relatedness between a pair of products: the amount of [[capital (economics)|capital]] required for production, technological sophistication, or inputs and outputs in a product's value chain, for examples. Choosing to study one of these notions assume the others are relatively unimportant; instead, the Product Space considers an outcome-based measure built on the idea that if a pair of products are related because they require similar institutions, capital, infrastructure, technology, etc., they are likely to be produced in tandem. Dissimilar goods, on the other hand, are less likely to be co-produced. This [[a posteriori]] test of similarity is called “proximity.” | | There exists a number of factors that can describe the relatedness between a pair of products: the amount of [[capital (economics)|capital]] required for production, technological sophistication, or inputs and outputs in a product's value chain, for examples. Choosing to study one of these notions assume the others are relatively unimportant; instead, the Product Space considers an outcome-based measure built on the idea that if a pair of products are related because they require similar institutions, capital, infrastructure, technology, etc., they are likely to be produced in tandem. Dissimilar goods, on the other hand, are less likely to be co-produced. This [[a posteriori]] test of similarity is called “proximity.” |
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| There exists a number of factors that can describe the relatedness between a pair of products: the amount of capital required for production, technological sophistication, or inputs and outputs in a product's value chain, for examples. Choosing to study one of these notions assume the others are relatively unimportant; instead, the Product Space considers an outcome-based measure built on the idea that if a pair of products are related because they require similar institutions, capital, infrastructure, technology, etc., they are likely to be produced in tandem. Dissimilar goods, on the other hand, are less likely to be co-produced. This a posteriori test of similarity is called “proximity.” | | There exists a number of factors that can describe the relatedness between a pair of products: the amount of capital required for production, technological sophistication, or inputs and outputs in a product's value chain, for examples. Choosing to study one of these notions assume the others are relatively unimportant; instead, the Product Space considers an outcome-based measure built on the idea that if a pair of products are related because they require similar institutions, capital, infrastructure, technology, etc., they are likely to be produced in tandem. Dissimilar goods, on the other hand, are less likely to be co-produced. This a posteriori test of similarity is called “proximity.” |
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− | 有许多因素可以描述一对产品之间的关系: 例如,生产所需的资本数量,技术复杂程度,或者产品价值链中的投入和产出。选择研究其中一个概念,假定其他概念相对不重要; 相反,产品空间考虑一种基于结果的衡量方法,这种方法的基础是,如果一对产品因为需要相似的机构、资金、基础设施、技术等而相互关联,那么它们很可能是一起生产的。另一方面,不同种类的产品则不太可能共同生产。这种相似性的后验测试被称为“接近性”
| + | 有许多要素可以描述一对产品之间的关系: 例如,生产所需的'''<font color="#ff8000">资本 capital</font>'''数量,技术复杂程度,或者产品价值链中的投入和产出。选择研究其中一个概念,假定其他概念相对不重要; 相对的,产品空间考虑一种基于结果的衡量方法,这种方法的基础是,如果一对产品因为需要相似的机构、资金、基础设施、技术等而相互关联,那么它们很可能是一起生产的。另一方面,不同种类的产品则不太可能共同生产。这种相似性的后验测试被称为“接近性” |
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| 这个矩阵的每一行和每一列都代表一个特定的商品,这个矩阵中的非对角线项反映了一对产品之间的接近程度。邻近矩阵的可视化表示显示了高度模块化: 一些商品高度连接,而其他商品是不连接的。此外,矩阵是稀疏的。5% 的元素等于0,32% 小于0.1,65% 的条目小于0.2。由于数据集的稀疏性,网络可视化是一种比较合适的数据集表示方法。 | | 这个矩阵的每一行和每一列都代表一个特定的商品,这个矩阵中的非对角线项反映了一对产品之间的接近程度。邻近矩阵的可视化表示显示了高度模块化: 一些商品高度连接,而其他商品是不连接的。此外,矩阵是稀疏的。5% 的元素等于0,32% 小于0.1,65% 的条目小于0.2。由于数据集的稀疏性,网络可视化是一种比较合适的数据集表示方法。 |
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| ==The Product Space network== | | ==The Product Space network== |