规划进展:将创新和结构变革纳入经济规划模式

Nils Rochowicz
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摘要

本文探讨了将创新和结构变革纳入经济规划模型的挑战。以往的经济规划方法大多考虑的是商品和服务分配的静态问题,而将创新和变革的动态问题置于次要地位(如果有的话)。然而,莫罗佐夫(2021 年)认为,包括计划经济在内的任何替代性经济体系所面临的主要挑战是,如何纳入一种可与资本主义的创新和动态性质相媲美的进步模式。本文认为计划经济中以往的变革方法不足以作为规划技术进步的核心要素,因此引入了两种新的互补方法来规划创新:民主加速任务以及筛选和扩展技术。民主加速任务针对创新的需求方,将民主制定的新能力需求转化为研发项目,以满足这些需求。筛选和推广技术则在供应方面发挥作用,根据民主决定的优先事项选择有前途的新技术,并将其发展为成品。这两种方法都广泛借鉴了有关创新的不同文献中的定量和定性证据,以建立一个以经验为基础的模型,尤其侧重于:(1) 规划创新时的民主决策;(2) 结合技术预测和创新经济学的见解来引导技术进步。所提出的模型证明了规划和引导技术进步的可行性,也是为此设计制度和算法结构的第一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Planning progress: Incorporating innovation and structural change into models of economic planning
This paper addresses the challenge of incorporating innovation and structural change in models of economic planning. Previous approaches to economic planning have mostly considered the static problem of the allocation of goods and services, leaving a secondary role (if at all) for the dynamic problem of innovation and change. However, Morozov (2021) argues that the key challenge for any alternative economic system, including planning, is to incorporate a model for progress that can rival the perceived innovative and dynamic nature of capitalism. Finding previous approaches to change in planned economies to be insufficient as central elements of planning technological progress, this paper introduces two new and complementary approaches to planning innovation: Democratic accelerated missions and screening and scaling technologies. Democratic accelerated missions act on the demand side of innovation, translating democratically formulated needs for new capabilities into research and development projects to fulfill these needs. Screening and scaling technologies act on the supply side, selecting promising new technologies based on democratically decided priorities and developing them towards finished products. Both approaches draw extensively on quantitative and qualitative evidence from different strands of literature on innovation to build an empirically grounded model, with a particular focus on (1) democratic decision-making in planning innovation, and (2) incorporating insights from technology prediction and the economics of innovation to steer technological progress. The proposed model demonstrates the feasibility of planning and directing technological progress, and is a first step towards designing institutional and algorithmic structures to this end.
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