Intermediate service input distortions and total factor productivity: Evidence from China

PLOS ONE RESEARCH ARTICLE Intermediate service input distortions and total factor productivity: Evidence from China Meng Shen☯, Tian Liu ID☯* Economic Department, Capital University of Economics and Business, Beijing, China ☯ These authors contributed equally to this work. * Abstract a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Shen M, Liu T (2024) Intermediate service input distortions and total factor productivity: Evidence from China. PLoS ONE 19(1): e0296429. https://doi.org/10.1371/journal. pone.0296429 China has the most minimal proportion of intermediate service inputs among the input-output datasets encompassing 43 countries and regions within the WIOD database. This study employs a non-parametric estimation methodology to compute the appropriate input levels for two distinct categories of intermediate goods. Furthermore, it evaluates the decline in total factor productivity resulting from distortions in intermediate input. The research findings are as follows: 1) China’s producer services exhibit an output elasticity approximately twice that of industrial intermediate goods. However, the input for producer services is only about half of that for the latter. This points to a notable deviation of China’s input for producer services from the optimal level. 2) Upon achieving an optimal level of input allocation for intermediates, the entire industry could experience an 11.48% boost in total factor productivity. In particular, the manufacturing sector could witness an impressive surge of 33.91%. 3) A positive correlation is discerned between intermediate input distortions and the import of intermediate products. Editor: Gianni Onesti, Gabriele d’Annunzio University of Chieti and Pescara: Universita degli Studi Gabriele d’Annunzio Chieti Pescara, ITALY Received: August 17, 2023 Introduction Accepted: December 11, 2023 Intermediate services, encompassing domains like design, research and development, finance, and logistics, play a pivotal role as intermediary inputs. These services predominantly find their place in the upstream sectors of industries, dictating the trajectory of China’s economic restructuring and the metamorphosis of its economic growth model. Based on data from the World Input-Output Database (WIOD), it’s evident that China’s average utilization of intermediate services as inputs across industries accounted for 37.48% during the period spanning from 2000 to 2014. This proportion not only falls below the 56.70% average observed in developed nations like those within the OECD but also notably deviates from the global average of 54.88% (Fig 1). Consequently, China stands at the bottom among the 43 countries and regions covered in the database. The glaring disparity in the utilization of intermediate service inputs in China starkly contrasts with its remarkable economic progress, marking a significant deviation from global trends. This inconsistency underscores the urgent need for a more in-depth investigation into this matter. The term ’de-industrialization’ is intricately linked to this phenomenon, portraying a process where the relative importance of manufacturing declines while the share of Published: January 2, 2024 Copyright: © 2024 Shen, Liu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All files are available from the figshare database (DOI:10.6084/m9. figshare.24647844). Funding: The authors received no specific funding for this work. Competing interests: The authors have declared that no competing interests exist. PLOS ONE | https://doi.org/10.1371/journal.pone.0296429 January 2, 2024 1 / 23 PLOS ONE Intermediate service input distortions and total factor productivity Fig 1. Intermediate service inputs as a share of total intermediate inputs. (A) Fig 1 shows the annual average of intermediate service inputs for the 43 countries in the WIOD database, China ranks lowest in 43 countries for intermediate service inputs. (B) The dotted line is the average share of world inputs in intermediate services, the blue line is the United States, the solid black line is China, and the gray line is for the other 41 countries. https://doi.org/10.1371/journal.pone.0296429.g001 services increases [1]. A substantial body of literature has sought to elucidate this phenomenon by focusing on the growing fragmentation of national manufacturing value chains and the gradual outsourcing of service activities from the manufacturing core [2–7]. This paper diverges from previous approaches that analyze restructuring and structural change within the manufacturing sector, as we provide insights into the relationship between intermediate inputs and total factor productivity. Assessing whether the presence of intermediate service inputs leads to losses in total factor productivity confronts intricate challenges, primarily rooted in endogeneity concerns. According to conventional economic theory, in the absence of market barriers, the cost-return ratios of diverse input factors are expected to converge. When the marginal rate of return on intermediate service inputs exceeds that of other input factors, it becomes logical to escalate the usage of intermediate services to amplify the overall output. However, it’s crucial to note that conventional measures may introduce estimation biases [8]. For instance, augmenting industrial intermediate inputs might yield more pronounced benefits for technological advancement, potentially leading to an underestimation of the advantages conferred by industrial intermediate inputs, especially when total factor productivity isn’t directly observable. Building upon insights from De Loecker and Warzynski [8], this paper commences by meticulously computing unbiased output elasticities for two distinct types of intermediate goods: industrial intermediates and intermediate services. Subsequently, employing the costbenefit maximization principle, it calculates the ratio of output elasticities to expenditure shares for each type of intermediate, wherein the disjunction between the two ratios signifies the extent of distortion in intermediate service inputs. This culminates in the quantification of total factor productivity losses attributable to distortions in intermediate service inputs. This paper introduces an innovative non-parametric estimation methodology situated within the framework of monopolistic competition. The aim is to estimate the marginal rate of return for factors while sidestepping potential endogeneity issues that could arise. This approach provides a more comprehensive and accurate assessment of the role played by intermediate inputs, addressing the intricacies introduced by factors such as technological progress. PLOS ONE | https://doi.org/10.1371/journal.pone.0 (...truncated)