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马克思对李嘉图经济学研究方法的批判及其启示

Marx's Critique of Ricardo's Economics Research Method and Its Enlightenment
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摘要 李嘉图摒弃了斯密的现象描述决,运用抽象法来研究经济范畴的内在联系,在三大阶级的对立中揭示资本主义社会的经济发展规律,在马克思看来,李嘉图之所以是英国古典经济学的完成者,正是因为他在立足于劳动价值论分析了阶级对立关系。马克思集中分析了李嘉图经济理论所引发的主要争论,并提出了自己解决这些争论的计划,在此基础上,马克思指出李嘉图崇尚生产力法则并承认资本主义社会阶级对立的存在足正确的,但其经济学研究方法既是非历史的抽象。又缺乏一定的抽象力。马克思认为李嘉图力图赋予资本主义社会以天然合理性的做法是错误的,他未能把利润、工资和地租等范畴放在历史性社会生产关系层面进行考察。马克思对李嘉图经济学研究方法的批判有助于我们立足于以人民为本的价值旨趣和历史唯物主义的研究方法,形成科学的中国特色社会主义政治经济学理论体系,促进新时代中国特色社会主义经济建设的进一步发展。 Ricardo abandoned Smith's phenomenon description method and used the abstract method to study the internal relation of economic categories,and to reveal the economic development law of capitalist societyamid the opposition of the three major classes.In the opinion of Marx the reason why Ricardo was called the completer of British classical economicswas exactly because he analyzed class antagonism based on the labor theory of value.Marx carried out centralized analysis ofmajor debates arising from Ricardo's economic theory and proposed his own plan to resolve the debates On this basis,Marx pointed outthat Ricardo was correct in advocating the law of productive forces and acknowledging the existence of class antagonism in capitalist society,but Ricardo's economies research method was non-historical abstraction and lacked certain abstract power Marx believed that Ricardo's attempt to endow capitalist society with natural rationality was wrongaand Ricardo failed to examine the categories such as profitswagesand land rent from the perspective ofhistorical social production relations Marx's critique ofRicardo's economics research methods can help us form a scientific theoretical system of socialist political economics with Chinese characteristics based on the people-oriented value objective and research method of historical materialism,and promote further development of socialist economic construction with Chinese characteristics in the new era.
作者 胡莹 高路 Hu Ying;Gao Lu
出处 《当代经济研究》 CSSCI 北大核心 2022年第3期18-26,F0003,共10页 Contemporary Economic Research
基金 国家社会科学基金重大项目(20&7D056)。
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