For Adam Smith, wealth was related to the division of labor. As people and firms specialize in different activities, economic efficiency increases, suggesting that development is associated with an increase in the number of individual activities and with the complexity that emerges from the interactions between them. Here we develop a view of economic growth and development that gives a central role to the complexity of a country's economy by interpreting trade data as a bipartite network in which countries are connected to the products they export, and show that it is possible to quantify the complexity of a country's economy by characterizing the structure of this network. Furthermore, we show that the measures of complexity we derive are correlated with a country's level of income, and that deviations from this relationship are predictive of future growth. This suggests that countries tend to converge to the level of income dictated by the complexity of their productive structures, indicating that development efforts should focus on generating the conditions that would allow complexity to emerge to generate sustained growth and prosperity.

中国正处于产业结构升级转型的节点上,探究中国出口经济复杂度的影响因素对制定下一阶段的产业政策有深刻影响。利用中国海关数据库,在三种主流复杂度指标计算基础上,深入分析中国城市产业地理集聚与出口经济复杂度发展演化,并运用计量模型对两者之间的关系进行实证检验。研究得到以下主要结论：① 全国城市产业地理集聚程度基本呈现东部高、中西部点状起伏的空间格局,且城市间产业集聚水平差异逐渐缩小。② 城市出口经济复杂度空间分布格局与产业地理集聚分布具有一致性,高复杂度地区主要为环渤海、长三角、珠三角地区以及中西部中心城市,城市间发展差距随时间缩小。③ 主流经济复杂度测算方法中的经济复杂度指数并不适用于中国城市尺度,而适应性复杂度和新经济复杂度的测算效果更好。④ 模型研究结果显示,产业地理集聚通过知识溢出和生产要素共享产生的积极影响超过了竞争拥挤带来的负面影响,促进了出口经济复杂度提升;且通过促进高复杂度产业进入与低复杂度产业退出有效推动了城市产业升级。

It is widely understood that innovations tend to be concentrated in cities, which is evidenced by innovative output increasing disproportionately with city size. Yet, given the heterogeneity of countries and technologies, few studies explore the relationship between population and innovation numbers. For instance, in the USA, innovative output scaling is substantial and is particularly pronounced for complex technologies. Whether this is a universal pattern of complex technologies and a potential facilitator of scaling, is unknown. Our analysis compared urban scaling in urban areas across 33 countries and 569 technologies. Considerable variation was identified between countries, which is rooted in two fundamental mechanisms (sorting and boosting). The sorting of innovation-intensive technologies is found to drive larger innovation counts among cities. Among most countries, this mechanism contributes to scaling more than city size boosting innovation within specific technologies. While complex technologies are concentrated in large cities and benefit from the advantages of urbanization, their contribution to the urban scaling of innovations is limited.

Summarising the complexity of a country's economy in a single number is the holy grail for scholars engaging in data-based economics. In a field where the Gross Domestic Product remains the preferred indicator for many, economic complexity measures, aiming at uncovering the productive knowledge of countries, have been stirring the pot in the past few years. The commonly used methodologies to measure economic complexity produce contrasting results, undermining their acceptance and applications. Here we show that these methodologies - apparently conflicting on fundamental aspects - can be reconciled by adopting a neat mathematical perspective based on linear-algebra tools within a bipartite-networks framework. The obtained results shed new light on the potential of economic complexity to trace and forecast countries' innovation potential and to interpret the temporal dynamics of economic growth, possibly paving the way to a micro-foundation of the field.

The capabilities of a firm, or any organization, lie primarily in the organizing principles by which individual and functional expertise is structured, coordinated, and communicated. Firms are social communities which use their relational structure and shared coding schemes to enhance the transfer and communication of new skills and capabilities. To replicate new knowledge in the absence of a social community is difficult. A classic demonstration is the well-studied problem of the transfer across country borders of manufacturing capabilities that support production of new product innovations. We show in this article that the degree of codification and how easily capabilities are taught has a significant influence on the speed of transfer. What makes the question of knowledge codification particularly interesting is that firms compete not only through the creation, replication, and transfer of their own knowledge, but also through their ability to imitate the product innovations of competitors. The capacity to speed the internal transfer of a production capability to new markets (e.g., those in other countries) is, consequently, of fundamental significance in a competitive environment. In the attempt to speed the internal transfer of knowledge, the dilemma arises that capabilities which can be easily communicated within the firm are more likely to be easily imitated by competitors. This relationship is tested by analyzing the effects of the ease of codifying and communicating a manufacturing capability not only on the time to its transfer, but also on the time to imitation of the new product. ’The determinants of the time to imitation are found to be the extent to which knowledge of the manufacturing processes is “common” among competitors, and the degree of continuous recombination of capabilities leading to improvement of the product or the manufacturing process. We support this interpretation by a discussion of the results from field research. A wider implication of these findings is the proposition that the transfer and recombination of organizational capabilities are the foundation of an evolutionary theory of the firm. A critical element limiting the expansion of a firm is that the competitive value of codifying knowledge leads to the selection of organizing principles that are not functional in all competitive environments. The pressure of speed is of critical importance to understand the evolutionary advantage of nonoptimal rules of coordinated action within a social community.