Misallocation Of Labor Research Articles

Does expansion of college education benefit urban entrepreneurship and innovation in China?

It is important to determine whether China's unprecedented expansion of college education (ECE) since 1999 has made a significant impact on the urban entrepreneurship and innovation (E&I). Using the data of 284 cities at the prefecture level and above from 2000 to 2020, this study empirically identifies the average treatment effect (ATE) of China's ECE on the urban E&I with its spatial spillover and explores two mediating channels (i.e., talent accumulation, and labor misallocation) to reveal how China's ECE impacts urban E&I. The results verify that with strong significance and robustness, the ECE for either undergraduates or master's students wholly matter for the E&I of cities, especially cities located in eastern or northeast economic zone，cities with a population less than 5 million or the ones without “Mass Innovation and Entrepreneurship Demonstration Bases”. Meanwhile, both the “Matthew effect” and the spatially “beggar-thy-neighbor” of ATE induced by the ECE are also be confirmed. Arguably, the China's ECE contributes either more talents accumulation or less labor misallocation, thereby furtherly boosting urban E&I. Above results were beneficial, especially at the decision-making for the developing countries to promote urban innovation and entrepreneurship under the scenario of college enrollment expansion.

Research on the income distribution effect of factor allocation efficiency changes among China's three major industries.

This paper aims to study the impact of correcting the factor misallocation among China's three major industries on China's income gap and income distribution pattern. By using the industry Panel data at the provincial level in China, we measure the degree of factor misallocation among the three major industries in China's provinces from 2002 to 2019 by building a factor misallocation measurement model, and then uses reverse thinking to compare the income gap under the condition of no factor misallocation with the actual income gap, and then obtains the impact of factor misallocation on the income gap, And use this method to focus on analyzing the impact of factor allocation efficiency changes among the three industries on income distribution pattern. The research finds that: (1) There is a serious factor misallocation among the three major industries in each province. From the perspective of subdivided factors, the factor misallocation among the three major industries in China's provinces is mainly caused by labor misallocation. Factor misallocation shows a trend of convergence first and then divergence among regions. (2) There is a strong heterogeneity in the explanatory power of different dimensions of the income gap of factor misallocation among the three major industries in China's provinces. Among them, correcting the misallocation of total factors among the three major industries in China's provinces can only narrow the internal income gap of the tertiary sector of the economy, and expand the internal income gap between the primary and secondary industries. (3) The impact of correcting the total misallocation, capital misallocation and labor misallocation among the three industries on the income gap among industries or provinces is narrowing first and then expanding. (4) Further research shows that although the level of factor misallocation among provinces in China is significantly lower than the average level of factor misallocation among the three major industries within each province, it has a stronger explanatory power for the inter-provincial income gap. Correcting the total factor misallocation and labor misallocation among provinces can significantly reduce the inter-provincial income gap in China. Correcting the total factor misallocation and labor misallocation among provinces in 2019 can reduce the inter-provincial income gap by 51.48% and 81.68% respectively. Only correcting the capital misallocation among provinces will expand the inter-provincial income gap, and only correcting the capital misallocation among provinces in 2019 will expand the inter-provincial income gap by 112.21%.

How does broadband internet affect firm-level labor misallocation: The role of information frictions

This study examines an understudied channel through which information and communication technology (ICT) affects labor markets: specifically, its role in enhancing labor allocation efficiency by mitigating information frictions. To investigate this causal relationship, we take advantage of the natural experiment created by the arrival of broadband internet in China in 2000. We employ a difference-in-differences (DiD) estimation strategy, supplemented by instrumental variables (IV) derived from the average incidence rates of lightning and a theoretically optimal backbone network construction plan. Our results show that the arrival of broadband internet markedly alleviates information frictions in labor markets, leading to a significant reduction in firm-level labor misallocation. The effects arising from the decline in information frictions ease the labor shortage problem faced by firms and are more significant in areas with more developed information-sharing networks. Lastly, we estimate the lower bound of the effect of changes in misallocation on treated cities' aggregate productivity, which is 6.3%.

Subsidizing startups under imperfect information

How is firm creation affected by imperfect information? Our model of rational inattention generates inefficient entry and labor misallocation, because startups make error-prone decisions. Learning decisions of prospective entrepreneurs alter the effects of lump-sum transfers to startups: the total employment gain is amplified due to an unintended increase in inefficient entry, most entrants hire fewer workers, and misallocation goes up. The transfer changes the learning incentives and makes even productive startups lean towards more conservative hiring. We show that this novel information channel works against well-known mechanisms, and thus can help reconcile recent empirical evidence on startup policies.

Does agricultural factor misallocation hinder agricultural green production efficiency? Evidence from China

The sustainable development of agriculture is challenged by two major issues: increasing resource constraints and environmental pollution. Sustainable agricultural development is achievable by improving green total factor productivity from the perspective of resource allocation. To promote the green development of agriculture, this paper utilizes the SBM super-efficiency mode and thus calculates the agricultural resource misallocation index and agricultural green production efficiency index in China between 2001 and 2019. Furthermore, this paper discusses the temporal and spatial evolution characteristics of agricultural green production efficiency, using a fixed model and spatial econometric models to estimate the influence effect of agricultural resource misallocation on green production efficiency. Below are the results. First, China's agricultural green total factor productivity is growing at an impressive rate, with high efficiency in the northeast, northwest, and southeast coastal areas and low efficiency in the central and inland areas. Second, agricultural capital misallocation, labor misallocation, and land misallocation all negatively impact agricultural green production efficiency. Accordingly, the misallocation of agricultural factors will hamper the growth of agricultural green production efficiency in this region and also in the surrounding areas. Third, the indirect impact on the own agricultural green production efficiency exceeds its direct impact on neighboring regions' efficiency. Fourth, the mechanisms are the upgrading of agricultural industry structure and green technology innovation. According to the findings, reducing resource misallocation can substantially enhance agricultural green productivity, which is an imperative step in addressing agricultural green production. Hence, policies should be formulated that highlight the regional allocation of agricultural production factors and green production-oriented concept of agricultural production. Also, the government should promote the transformation and upgrading of the agricultural industrial structure, as well as the application of green agricultural technologies.

Digital economy and wage gap between high- and low-skilled workers

This paper explores the impact of digital economy development on the wage gap between high- and low-skilled workers based on the China Family Panel Studies (CFPS) database in 2010–2020. The research results suggest that the higher the level of digital economy development, the larger the wage gap between high- and low-skilled workers. Some mediating mechanisms are identified and tested from the perspectives of the reaction of human labor to the development of digital economy: the labor misallocation and the mismatch between technologies and skills of workforce. The latter is represented by the response of workers to the risk of being replaced by machines, implying that high-skilled workers use the Internet to improve their abilities more than their low-skilled counterparts to cope with the substitution effect brought about by digital economic progress. The findings in this paper have important policy implications in the sense that governments at different levels should play an important role in assisting digital economy development in favor of the social disadvantaged groups, particularly the low-skilled workers in the labor market.

Does telecommunications infrastructure promote entrepreneurship in developing countries? Evidence from a quasi-natural experiment in China

As an essential element of the entrepreneurial ecosystem, telecommunications infrastructure could effectively stimulate entrepreneurial activity. Based on prefectural city data from 2003 to 2019, this study constructs a time-varying difference-in-differences model (DID) to identify the impact of telecommunications infrastructure on entrepreneurship by adopting the Broadband China strategy as a quasi-natural experiment. Several heterogeneity analyses are further conducted under different city characteristics. The potential transmission channels from the perspective of resource misallocation are also explored. The results show that telecommunications infrastructure significantly promotes entrepreneurship in China, but there is a time lag effect. The positive impact of telecommunications infrastructure on entrepreneurship is more pronounced in the midwestern regions, small-medium scales, and cities with underdeveloped traditional infrastructure. Alleviating capital and labor misallocation are potential channels for telecommunications infrastructure to promote entrepreneurship. These findings provide evidence for building telecommunications infrastructure rationally to facilitate entrepreneurship and reduce the imbalance of regional entrepreneurship.

Digitalization, resource misallocation and low-carbon agricultural production: evidence from China

With the rapid development of digital technologies such as artificial intelligence, big data and cloud computing, China’s agricultural production is entering a new era characterized by digitalization. Based on provincial panel data of China from 2013 to 2020, this paper adopts the system GMM and mediating effects model to systematically examine the impact of digitalization on low-carbon agricultural production from the perspective of resource misallocation. The results indicate that digitalization can significantly curb agricultural carbon emissions and thus promote low-carbon agricultural production, and this finding still holds after the robustness test. The heterogeneity analysis indicates that the inhibiting effect of digitalization on agricultural carbon emissions is most pronounced in the eastern region relative to the central and western regions (the regression coefficients are −0.400 and −0.126 respectively). Further mechanism analysis suggests that digitalization can reduce agricultural carbon emissions by correcting the widespread capital and labor misallocation in agricultural factor markets. The findings of this study provide significant policy implications for low-carbon agricultural production in China.

Revisiting the real exchange rate misalignment‐economic growth nexus via the across‐sector misallocation channel

AbstractThis study assesses whether the component of across‐sector labor and capital misallocation induced by real effective exchange rate (REER) misalignments in turn significantly affects economic development. REER imbalances are derived from a Behavioral Equilibrium Exchange Rate model; labor and capital misallocation is measured according to indicators in Ando and Nassar (IMF Working Papers, 2017, 17, 1) and Aoki (Journal of the Japanese and International Economies, 2012, 26, pp. 473–494), on a unique cross‐country cross‐sector national account dataset of 54 countries and 12 sectors over 1980–2015. Both REER over‐ and undervaluations are found to lead to rising across‐sector labor (but not capital) misallocation and, uniquely via this channel, significantly hamper real growth.

Will the COVID-19 Pandemic Outbreak Intensify the Resource Misallocation in China’s Food Production?

Resource misallocation is one of the important manifestations of agricultural supply-side distortion and an important causal factor that hinders food production increase and affects food security. Did the COVID-19 pandemic intensify China’s food production misallocation? The extent and consequences require quantitative assessment and scenario analysis. In this paper, we use a combination of input-output model and computable general equilibrium (CGE) model, and further incorporate the most important input factor in agriculture—intermediate inputs—into the model. At the same time, simulation of the pandemic impact from the demand and supply sides, respectively, and scenario analysis of the impact of the COVID-19 pandemic on China’s food production. The results of the study show that: first, compared with the baseline level before the epidemic, the overall TFP growth of China’s food industry chain decreased, and the TFP growth rate of the food distribution sector decreased most significantly. Second, there are significant factor misallocation distortions of capital, labor, and intermediate inputs. Third, in the short term, the period of the COVID-19 pandemic led to a decline in the vitality of the national labor market, but the return of non-farm employed labor in rural areas instead reduced the degree of labor misallocation in the food sector. Fourth, the demand side has a greater impact on China’s food production, among which the consumer demand has a particularly strong impact on the resource allocation of food production, and the short-term shock will mainly have a more obvious impact on the allocation of labor factors and the allocation of intermediate input factors in the food industry chain. Accordingly, this paper proposes that in order to guarantee China’s food security and adapt to the short-term characteristics of the era when the COVID-19 pandemic is rampant, China should make efforts in four areas: rational allocation of food production resources and factors, solid construction of the whole food industry chain, stable guarantee of the food market system and transfer to enhance social expectations.

The Opening of High-Speed Railways, the Improvement of Factor Allocation Efficiency between Regions, and the City's Environmental Quality Improvement.

Based on the panel data of prefecture-level cities in China from 2006 to 2019, this paper uses the PSM-DID method to empirically test the internal impact mechanism among high-speed railway opening, inter-regional factor allocation efficiency, and urban environmental governance. The research results show that: (1) There is a serious factor-misallocation problem among prefecture-level cities in China. From 2006 to 2019, the factor misallocation between prefecture-level cities led to an average annual loss of total factor productivity in China's economy of 52.5%, an average labor misallocation of 23.16%, and an average capital misallocation of 18.69%. Since 2013, capital misallocation has exceeded labor misallocation as the main reason for factor misallocation among prefecture-level cities in China. (2) The opening of high-speed railways can promote the efficiency of urban factor allocation through the technological innovation effect, the foreign investment attraction effect, and the population agglomeration effect. The improvement of urban factor allocation efficiency can promote the improvement of urban environmental quality through the effects of industrial structure optimization, income enhancement, and human capital agglomeration. Therefore, the opening of a high-speed railway can improve urban environmental quality through the intermediary effect of improving the efficiency of urban factor allocation; that is, the opening of a high-speed railway has a dual positive effect of economic efficiency and environmental quality improvement. (3) The optimization effect of factor allocation and the environmental governance effect of the opening of high-speed railways have strong urban scale heterogeneity, urban characteristic heterogeneity, and regional heterogeneity. The research content of this paper has important guiding significance for the construction of China's new development paradigm, accelerating the construction of "a unified national market," and green and low-carbon development.

Exploring the role of co-agglomeration of manufacturing and producer services on carbon productivity: An empirical study of 282 cities in China

Carbon productivity is a better measure of a region's sustainable economic growth since it considers economic development and carbon emissions at the same time. It is crucial to improve carbon productivity through the co-agglomeration of manufacturing and producer services for China. To better understand the effect and mechanism of co-agglomeration, this study uses panel data of 282 Chinese cities from 2003 to 2017 to examine the effect of manufacturing and producer services co-agglomeration on carbon productivity. Further, moderating effects models and panel threshold models are used to investigate the mechanisms of co-agglomeration effect on carbon productivity. The results suggest that the influence of co-agglomeration on carbon productivity is U-shaped with an inflection point of 3.63, indicating that a high level of co-agglomeration is required for carbon productivity to increase. Compared with other cities, cities in the eastern region or with a large scale have lower inflection points. The upgrading of industrial structure, production efficiency, and the production chain has a positive moderating effect on the influence of co-agglomeration on carbon productivity, while upgrading of non-production chains does not. When the levels of capital misallocation and labor misallocation reach the threshold of 1.115 and 1.557 respectively, industrial co-agglomeration has a promoting effect on carbon productivity. This research offers valuable insights for optimizing the urban industrial layout to improve carbon productivity.

Digital Economy, Factor Allocation, and Sustainable Agricultural Development: The Perspective of Labor and Capital Misallocation

As an emerging economy, the combination of the digital economy and industrial development can lead to a variety of new industries and new formats and form new momentum. This paper aims to analyze how the digital economy affects sustainable agricultural development, through what path, and what role the factor allocation plays in this process. Based on the analysis of the impact mechanism of the digital economy on sustainable agricultural development, this paper takes 30 provinces in China from 2013 to 2020 as the research object, builds a panel data model and mediation effect model, empirical analyses on the impact of the digital economy on sustainable agricultural development, and verifies the mediation effect of factor allocation in this process. This study found that the digital economy significantly promoted sustainable agricultural development. At the national level, this obvious promotion effect was achieved by reducing the misallocation of labor and capital. At the regional level, sustainable agricultural development in the eastern region of China depended on the optimization effect of the digital economy on the allocation of labor and capital, but the situation was slightly different in the central and western regions of China. The digital economy in the central and western regions of China significantly improved sustainable agricultural development by allocation effect of labor factors. Although the allocation effect of capital factors had a positive effect on sustainable agricultural development, it was not significant. In order to promote sustainable agricultural development, the digital industry development should be accelerated, the allocation effect of the factor market should be brought into play, and the digital economy should be better integrated with sustainable agricultural development so as to realize the modernization of agricultural development.

Business Environment and Resource Allocation Based on the Perspective of the National Value Chain.

China is actively upgrading its industrial structure through industries transferring between developed and undeveloped areas; however, the overall level of the national value chain is still not high, and the asymmetric competition pattern between the upstream and the downstream has not been broken. Therefore, this paper establishes a competitive equilibrium model for the production of manufacturing enterprises, with factor price distortion, under the condition of constant returns to scale. The authors derive the relative distortion coefficients of each factor price, calculate the misallocation indices of capital and labor, and construct an industry resource misallocation measure. Furthermore, this paper applies the regional value-added decomposition model to calculate the national value chain index and matches the market index of the China Market Index Database with the Chinese Industrial Enterprises Database and the Inter-Regional Input-Output Tables through quantitative analysis. From the perspective of the national value chain, the authors study the improvement effect and mechanism of the business environment on the resource allocation in industry. The study shows that industry resource allocation will be improved by 17.89% if the business environment level is improved by one standard deviation. This effect is most prevalent in the eastern and central regions, not so much in the west; the effect of downstream industries in the national value chain is higher than that of upstream industries; the improvement effect on capital allocation is higher in downstream industries than in the upstream industries; and the improvement effect on labor misallocation is basically the same in both the upstream and the downstream. Compared with labor intensive industries, capital intensive industries are more influenced by the national value chain, while the effect of upstream industries is weaker. At the same time, it is well documented that participation in the global value chain can improve the efficiency of regional resource allocation, and the construction of high-tech zones can improve resource allocation for both upstream and downstream industries. Based on the results of study, the authors propose suggestions for optimizing business environments, suiting the national value chain construction, and improving resource allocation in the future.

Impact of Structural Distortions on Resource Allocation in China: Evidence from an Innovative Empirical Model

This paper examines the impact of structural distortions on resource allocation among industries, regions (provinces), and ownerships in China, using data from 2003 to 2019. This paper innovatively develops an empirical model to measure multi-dimensional structural distortions and assesses the resource misallocation degrees regarding industries, regions, and ownerships. The results indicate that China’s most serious resource misallocation is related to industries, followed by regions and ownerships, and the most severe capital misallocation is associated with ownership, and labor misallocation exists in industries. The present study contributes to the literature by creating an innovative two-layer empirical model to address the limitations of Hsieh and Klenow’s model. The findings have identified which group (industry, region, and ownership) is excessive or insufficient in resource usage, and the results have profound policy and practical implications.

Pathways to carbon neutrality: how do government corruption and resource misallocation affect carbon emissions?

The government corruption and resource misallocation are important factors that inhibit economic transformation and environmental governance. Using a study sample of 30 provinces in China, this study employs the spatial econometric methods and threshold model to investigate the relationship between regional corruption, resource misallocation, and CO2 emission. The results show that there is a clear spatial dependence and correlation of CO2 emissions. Government corruption is a neglected contributor to carbon emissions, and this promotion effects are attributed to a promotion in resource misallocation. Moreover, the CO2 emissions are significantly promoted by local labor misallocation and capital misallocation, and the increasing effect is more pronounced in areas with high corruption. For spatial spillover effects, there is also no evidence that local CO2 emissions are significantly promoted by capital misallocation of surrounding areas. Additionally, the promoting effect of corruption on CO2 emissions is more pronounced in regions with weak environmental regulation, low marketization process, and the central and western of China. This work elucidates the mechanism of the impact of corruption on environmental pollution from the perspective of resource allocation, and provides an important reference for the effective management of environmental pollution.

Quantitative Evaluation and Characteristic Analysis of Resource Allocation Efficiency of the Energy Industry in the Yangtze River Economic Belt

The resource allocation efficiency of the energy industry in the Yangtze River economic belt is related to the green and high-quality development of the region. This study constructed a quantitative model which modified from the traditional HK model to evaluate the efficiency of energy industry resource allocation. This paper makes a quantitative evaluation of the efficiency of inter-industrial and inter-regional resource allocation of the energy industry in the Yangtze River economic belt from 2000 to 2019. The results show that: the average annual loss of total factor productivity of the energy industry in the Yangtze River economic belt is as high as 25.11% due to the misallocation of resources among the energy industries, capital misallocation, labor misallocation, and intermediate input misallocation were 12.32%, 7.08%, and 5.08%, respectively. The misallocation of resources among the energy industries of the provinces in upper, middle, and lower reaches is gradually increasing in turn. The average annual loss of total factor productivity (TFP) in the energy industry of the Yangtze River economic belt is 6.5% due to the misallocation of resources between regions. Capital misallocation, labor misallocation, and intermediate input misallocation were 2.48%, 3.40%, and 0.63%, respectively. In the upper, middle, and lower reaches of the Yangtze River, the labor force, capital, and intermediate input of each province’s energy industry were misallocated to a different extent. According to the trend of resource input in the energy industry of various provinces and cities, the middle and lower reaches of the Yangtze River also show different characteristics.

Measuring the welfare costs of racial discrimination in the labor market

AbstractWe find that the conditional wage‐gap for non‐whites is negatively related to gross domestic product per worker across the US. To explain this, we develop a model linking unequal access to employment with the wage gap, labor misallocation, and income loss. The presence of underprivileged workers allows inefficient firms to co‐exist with efficient ones and leads to skill misallocation, higher unemployment and lower output. Calibrating the model to match the US, we find a fall in market‐based racial discrimination renders inefficient firms non‐profitable, causing reallocation of labor and a positive effect on income as high as 4 percent when discrimination is eliminated.

Labor misallocation and productivity growth in Vietnamese manufacturing firms

PurposeThis research identifies the level of labor misallocation in Vietnamese manufacturing sector for the period 2005–2019. The paper also examines the effects of labor misallocation on productivity in Vietnamese manufacturing firms controlled by industry- and firm-level factors.Design/methodology/approachThe level of labor misallocation and efficiency gains in total factor productivity (TFP) are assessed using Vietnam's annual enterprise survey data for the period 2005–2019 and Hsieh and Klenow (2009) productivity decomposition framework.FindingsThe results indicate four main points. Firstly, labor misallocation tends to increase from 2005 to 2019. Secondly, labor misallocation by firm ownership and technology level is found to be highest in state-owned enterprise and low-tech industries, whereas foreign direct investment and high-tech firms have lowest labor misallocation. Labor misallocation in small- and medium-sized enterprises is higher than in large-sized enterprises and is equivalent to overall sample. Thirdly, labor misallocation decreases productivity in manufacturing firms. The firm-level factors such as bigger technology gap, external capital, firm scale and poor liquidity ratio decrease productivity in manufacturing firms. Whereas firm-level factors such as Vietnam's accession to the WTO, reasonable corporate tax structure, capital intensity, human capital and firm age increase productivity of manufacturing firms. The industry-level factors such as FDI horizontal, forward and supply backward spillovers promote productivity from foreign firms to domestic ones. Meanwhile, only backward linkages reduce productivity of firms. Finally, by difference-in-differences (DID) method, the result indicates foreign firms have higher average labor productivity than domestic firms before or after Vietnam's accession to the WTO. After joining WTO, the average labor productivity of foreign firms is increased by 854 million VND while the average labor productivity of domestic firms is increased by 895 million VND. The DID between the two groups (domestic firms and foreign firms) before and after Vietnam's accession to WTO is 41 million dong.Research limitations/implicationsThe main limitation of the study is that the market is assumed perfectly competitive. The model focuses on selective factors affecting labor productivity.Originality/valueThe focus of many previous international research papers was generally to look at the level of labor misallocation in developed countries. However, knowledge about labor misallocation is limited, particularly in the context of developing countries. This paper examines the level of labor misallocation by region, ownership, level of technology and firm size on productivity and the effect of misallocation on productivity in Vietnamese manufacturing firms.Peer reviewThe peer-review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2021-0552.

The impact of high-speed railway on labor spatial misallocation—Based on spatial difference-in-differences analysis

Existing studies neglected to assess the resource allocation effect of high-speed railway (HSR). This paper examines the impact of HSR on labor spatial misallocation in China by applying a modified spatial difference-in-differences approach, which identify local treatment effect, spillover effect on treated and untreated regions. The study finds: (1) Opening HSR alleviates not only the local labor misallocation but also the misallocation in surrounding areas to a greater extent, including cities with HSR (treatment group) and without HSR (control group), which contributes to the overall productivity increase. The spillover effect of HSR is larger than the direct effect. (2) The largest spillover effect occurs in adjacent areas near 350 km apart, while the spillover effect disappears beyond 500 km. (3) The direction and magnitude of HSR effect depend on the urban scale. For large-scale cities, the impact of opening HSR is greater versus small-scale ones. • A spatial DID model is applied to identify the impact of HSR on labor misallocation. • HSR mitigates the misallocation for both treated and non-treated regions nearby. • The spillover effect of HSR reaches the maximum at the distance of 350 kilometers. • The impact of HSR on misallocation varies by city scale.