Misallocation Of Labor Research Articles

Market distortion, factor misallocation, and efficiency loss in manufacturing enterprises

Market distortion hinders the free flow of production factors and ultimately reduces the manufacturing industry’s output level. Optimal factor allocation improves the overall output level by adjusting the allocation of factors among enterprises without increasing the input of additional factors. We applied the heterogeneous firm model to examine market distortion and factor misallocation among manufacturing firms based on China’s micro enterprise data. Our empirical findings indicate that manufacturing enterprises in China engage in a serious misallocation of capital and labor, and the degree of capital misallocation is much greater than that of labor; and the total factor productivity (TFP) of China's manufacturing industry has great potential to increase. In addition, this study introduces a time-varying elasticity production function model suitable for China's national conditions. The model more accurately explains China’s current factor misallocation situation and introduces a new method for measuring mismatch in other developing countries.

Can low‐carbon development force enterprises to make digital transformation?

AbstractEnterprises need to innovate business strategies to deal with the negative effects of low‐carbon development, among which digital transformation is an important breakthrough technology. This paper discusses the impact of low‐carbon development on enterprises' digital transformation. Theoretical analysis shows that environmental regulations driven by low‐carbon development have the compensatory effect of stimulating enterprise digital transformation to mitigate misallocation of capital and labor, especially for enterprises with higher productivity. In addition, both the construction of network infrastructure and the development of digital finance can strengthen the incentives for enterprises' digital transformation. The empirical tests based on Chinese A‐share listed enterprises show that the degree of enterprises' digital transformation increases by 0.0122 standard deviation for every one standard deviation reduction in regional carbon emission intensity. These results deepen the understanding of the relationship between green development and microenterprise digitalization.

Labor market rigidities and misallocation: Evidence from a natural experiment

This paper estimates the impact of labor market rigidities on labor misallocation. To this end, we use a recent policy change in Belgium, leading to an increase in employment protection for blue-collar workers and a decrease in employment protection for white-collar workers. The wedge between marginal product and marginal cost - the gap - is used as a measure for misallocation. Using a rich data set of the universe of Belgian firms, evidence shows that a firm with 90% blue-collar workers experienced after the policy change an increase in the gap of 3300 euro relative to a firm with 10% of blue-collar workers.

Digital Economy, Intelligent Manufacturing, and Labor Mismatch

Factor mismatch is considered to be an important restriction on the growth of total factor productivity. Based on the panel data of 30 Chinese provinces from 2013 to 2019, this work first measures the digital economy development index of each Chinese province by using a particle swarm optimization projection pursuit model, followed by a panel econometric model, to verify the effect of the digital economy and artificial intelligence manufacturing on the labor-resource mismatch. The results show that, from 2013 to 2019, China’s digital economy generally showed a trend of steady progress, with an average annual growth rate of 12.10%. The mismatch index of the labor force dropped by 1.46% every year, and the situation of insufficient or surplus allocation of labor force resources in China was alleviated. The fitting results of the spatial econometric model show that the digital economy can reduce the labor mismatch index, and this conclusion has remained valid after a series of robustness tests. The intermediary mechanism shows that intelligent manufacturing plays a masking role in the process of alleviating labor misallocation in the digital economy. Artificial intelligence cannot alleviate labor mismatches, but it strengthens the corrective function of the digital economy.

Towards sustainable development in China: How do green technology innovation and resource misallocation affect carbon emission performance?

Green technology innovation is an effective way through which to achieve carbon neutrality and sustainable development. Based on provincial panel data of 30 provinces in China from 2005 to 2018, this work examines the tripartite relationship among green technology innovation, resource misallocation, and carbon emission performance by constructing panel regression models and a dynamic threshold panel model. The research results show that green technology innovation significantly improves carbon emission performance. Further analysis shows that both capital and labour misallocation have a negative impact on carbon emission performance and hinder the contribution of green technology innovation to the improvement of carbon emission performance. The regression results show that there is a threshold effect of green technology innovation on carbon emission performance: as the degree of resource misallocation increases, the positive impact of green technology innovation on carbon emission performance gradually decreases. This study provides an important reference for policy-makers in implementing policies to improve carbon emission performance. Policy-makers should continue to promote the level of green technology innovation and improve the efficiency of labour and capital allocation.

Exploring the Impact of the Digital Economy on Carbon Emission Efficiency Under Factor Misallocation Constraints: New Insights From China

The digital economy has introduced far-reaching innovations in the fields of government governance, enterprise production, and social operation. How to motivate the economic development mode towards a low-carbon and greenway transformation through the digital economy is a major issue concerning the Chinese government. However, there is scarce evidence to interpret the role mechanism of the digital economy on carbon emission efficiency from the factor misallocation scenario. Taking a database from 30 provincial-level administrative regions for the period from 2011 to 2019 in China as an example, the paper examines the effect of the digital economy on carbon emission efficiency, as well as explores its role mechanism deeply in terms of factor misallocation (capital misallocation and labor misallocation). The results suggest that there is a significant potential for the digital economy to contribute to carbon emission efficiency, as well as this finding, is valid when considering both the endogeneity issue and a series of robustness checks. Also, the digital economy can significantly contribute to carbon efficiency in both southern and northern regions, but more strongly in the northern region. Besides, the digital economy can inhibit the factor misallocation (labor misallocation and capital misallocation) level which ultimately improves carbon emission efficiency. Finally, as a digital economy, it can positively impact carbon efficiency in the long run by mitigating factor misallocation (labor misallocation and capital misallocation).

Habit Formation and the Misallocation of Labor: Evidence from Forced Migrations

Abstract We use a research design created by forced migrations to examine the costs and benefits of leaving agriculture in mid-20th century Finland. After World War II, 11% of the Finnish population was resettled from areas ceded to the Soviet Union. Entire rural communities were moved to locations that resembled the origin areas, and displaced farmers were given land and assistance to establish new farms. Despite this policy of reconstructing the pre-war situation, forced migration increased the likelihood of switching to non-agricultural jobs and moving to urban areas. Consequently, forced migration also increased the long-term income of the displaced rural population. By contrast, forced migration decreased the income of the resettled urban population. We examine the extent to which these effects can be explained by the quality of the new farms, human capital investments, networks, and discrimination, but do not find evidence supporting these mechanisms. Instead, we argue that habit formation toward residential locations provides the most compelling rationalization for our results.

Does industrial intelligence improve resource misallocation? An empirical test based on China.

Resource misallocation has become a new threat to China's high-quality economic development, and industrial intelligence may play an important role in optimizing resource allocation. Using panel data of 30 Chinese provinces from 2010 to 2020, the relationship between industrial intelligence and resource misallocation is studied using the spatial Durbin (SDM) model. To further explore the indirect effect of environmental pollution on resource misallocation, the interaction term between industrial intelligence and environmental pollution is added to test how environmental pollution affects the relationship between industrial intelligence and resource. The research results show that industrial intelligence in China has significant spatial correlation. Local industrial intelligence can improve the local resource allocation, but the intelligence of neighboring industries will intensify the resource misallocation in the region. The interaction between environmental pollution and industrial intelligence also further affects resource allocation, and the interaction term can intensify local capital allocation to improve local labor allocation, and the interaction term in the surrounding area will also improve capital and labor misallocation in the region. Heterogeneous results find that industrial intelligence exacerbates resource misallocation in regions with insufficient capital allocation, and the mediating effect of environmental pollution is not significant. However, in places with excess capital allocation, the development of industrial intelligence helps improve resource misallocation, while the mediating effect of environmental pollution is also present, and industrial intelligence can improve resource misallocation through the indirect effect of improving environmental pollution. Therefore, the policies of local industrial development policies need to fully consider the resource allocation situation in the region. At the same time, it needs to smooth the capital circulation mechanism, reduce the cost of capital allocation, establish a sound employment mechanism, and improve labor misallocation.

Revisiting the optimal inflation rate with downward nominal wage rigidity: The role of heterogeneity

In this paper, I study the optimal inflation rate in a sticky price economy where workers are heterogeneous in labor productivity and wage changes are subject to asymmetric adjustment costs. The model calibrated to U.S. micro wage data implies downward nominal wage rigidity (DNWR). The optimal inflation rate is substantially higher than stated in the literature in the presence of worker heterogeneity. A key to understanding the result is that DNWR causes a cross-sectional misallocation of labor as well as inefficient aggregate dynamics, enlarging the “grease the wheels” effect of inflation.

Capital and labor misallocation in the Netherlands

Capital and labor misallocation in the Netherlands

Labor Misallocation Across Firms and Regions

Labor Misallocation Across Firms and Regions

Impact of regulatory policies on job creation in developing countries

The objective of this paper is to study the effects of labor market regulation policies on the allocation of labor. Specifically, it aims to highlight the effects of regulatory policies on the choice of kind of job, taking into account market segmentation and barriers to entry into the formal sector. To do so, we used the fourth Cameroon Household Survey (ECAM 4) and a self-selection model. The results show that individual and institutional factors are responsible for the misallocation of labor between the formal and informal sectors. Thus, we find that women and youth preference for informal jobs is involuntary because it is constrained by the existence of barriers to entry to the labor market. These results suggest that there is a certain amount of regulatory flexibility to increase the level of formal employment, even to transform informal jobs into formal jobs.

High-technology zones, misallocation of resources among cities and aggregate productivity: evidence from China

ABSTRACT Recent literature has been debating the performance of high-technology zones (HTZs) in developing countries. This paper contributes to this debate by examining how national HTZs in China affect allocative efficiency of resources among Chinese cities as well as China’s total factor productivity (TFP) growth. This paper finds that resource misallocation among cities reduces China’s TFP growth by 4.5% of which capital misallocation accounts for 2.4% and labour misallocation accounts for 2.1%. Moreover, we find that the establishment of national HTZs in China increases aggregate TFP by improving the allocative efficiency of capital among cities: that is, redistributing more capital from lower to higher productivity cities. In contrast, we find little evidence of TFP gain driven by technical efficiency following the establishment of HTZs. This paper thus reveals a potential positive effect of establishing HTZs in developing countries: although establishing HTZs may not improve the technical efficiency of these countries, it may nevertheless mitigate these countries’ resource misallocation and enhance their aggregate TFP.

Market Distortion, Inter-Provincial Factor Misallocation, and Total Factor Productivity

As an emerging economy, market distortions exist in China’s institutional adjustment during its economy transformation. However, the price distortion of capital and labor factors will lead to factor misallocation among provinces. This will eventually reduce the total factor productivity (TFP) at the national level. Based on Hsieh and Klenow’s [1] model framework, this paper aims to measure the degree of misallocation of capital and labor factors among provinces, and estimates the growth potential of China’s TFP by using input-output data from 1993 to 2017. The findings show that: First, the degree of inter-provincial labor misallocation is greater than that of capital. For example, in 2017, the degree of capital (labor) misallocation was 5.77% (10.25%), resulting in China’s TFP loss of 17.23%. Second, due to the factor marketization reforms, the degree of labor misallocation has declined while the degree of capital misallocation has intensified in recent years. Lastly, this paper introduces the time-varying elasticity production function model, finding that using the Cobb-Douglas production function will cause the factor misallocation to be underestimated by 5.91% due to the assumption of constant output elasticity.

The effect of government intervention on the resource misallocation in innovation: ownership differences

ABSTRACT In the present study, the misallocation of resources in innovation in the China’s high-tech industry sector was analysed. A model was constructed to measure the misallocation of resources at the level of the department. Based on the model, there is an estimated misallocation of total resources, capital, and labour, respectively. The empirical findings show that there is a misallocation of innovation resources in the high-tech industry sector, with a general trend of fluctuation from 45.73% in 2009 to 7.85% in 2016. The misallocation of resources caused by labour is greater than capital. Government intervention has a significant negative impact on the misallocation of resources in innovation. An increase in the share of SOEs in an industry will deepen the misallocation.

Wage Determination Across Firms

Some firms pay higher wages than others for identical workers. To unpack the firm wage premium distribution, I develop and implement a new structural decomposition using datasets that cover the universe of employers and employees in France. Existing research shows that firm wage premia depend on firms' labor productivity and wage-setting power. This paper shows that they also depend on firms' product market power and labor share of production. I find these firm characteristics to be correlated with each other, implying that: (i) without taking the latter set of characteristics into account, workhorse models that generate firm wage premia overestimate the contributions of firms' labor productivity and wage-setting power; (ii) conventional measures of input misallocation overestimate the degree of labor misallocation; (iii) high productivity firms have low labor shares of revenue not only because of greater product market power, but also greater labor market power and low labor shares of production.

Environmental Regulation, Resource Misallocation and Industrial Total Factor Productivity: A Spatial Empirical Study Based on China’s Provincial Panel Data

A vast theoretical and empirical literature has been devoted to exploring the relationship between environmental regulation and total factor productivity (TFP), but no consensus has been reached and the reason may be attributed to the fact that the resource reallocation effect of environmental regulation is ignored. In this paper, we introduce resource misallocation in the process of discussing the impact of environmental regulation on TFP, taking China’s provincial industrial panel data from 1997 to 2017 as a sample, and the spatial econometric method is employed to investigate whether environmental regulation has a resource reallocation effect and affects TFP. The results indicate that there is a U-shaped relationship between environmental regulation and industrial TFP and a negative spatial spillover effect of environmental regulation on industrial TFP at the provincial level in China. Both capital misallocation and labor misallocation will lead to the loss of industrial TFP. Capital misallocation has a negative spatial spillover effect on industrial TFP, while labor misallocation is just the opposite. Environmental regulation can produce a positive resource reallocation effect, which in turn promotes the industrial TFP in the range of 28% to 33%, while capital misallocation and labor misallocation are only partial mediator.

Firing restrictions and economic resilience: Protect and survive?

Firing restrictions are in use throughout the developed world but their role in the transmission of macroeconomic shocks into the real economy is mostly unstudied. We illustrate the theoretical role of these policies as amplifiers of macroeconomic shocks via labor-misallocation-induced output losses following an adverse shock. We use our model to derive an aggregation result which features a labor misallocation term and conduct a simulation exercise which demonstrates how misallocation can drive total factor productivity (TFP) down during recessions. We then perform a quasi-natural experiment which utilizes global credit supply shocks to study this amplifying role using a panel of 21 OECD economies. We show that strict firing restrictions are associated with a weaker initial response of the labor market, which is followed by a stronger and more persistent decline in real output as well as a slower return of real activity to pre-shock levels. The stronger output decline can be mostly explained by a stronger fall in aggregate TFP, which supports our theoretical predictions.

Barriers to Growth-Enhancing Structural Transformation: The Role of Subnational Differences in Intersectoral Productivity Gaps

The movement of workers from the farm sector to a more productive nonfarm sector has failed to generate significant gains in labor productivity in recent decades in many developing countries. This paper offers a new perspective into the barriers to growth-enhancing structural transformation, combining structural modeling with enterprise census data from Ghana. We argue that subnational differences in the intersectoral productivity gap between the nonfarm informal and formal sectors constrain the productivity gain from structural transformation. In Ghana, intersectoral productivity gaps among the richer regions are on average three times larger than among the poorer regions. We model the disparity in regional intersectoral productivity gaps as reflecting the disparity in the regional misallocation of labor between the informal and formal sectors and identify misallocation as the output wedge between the informal and formal sectors. Simulations suggest that a more productive nonfarm informal sector reduces the disparity in regional intersectoral productivity gaps and, in turn, increases national productivity and the contribution of structural transformation to national productivity. For example, a 90-percent reduction in the disparity in regional intersectoral productivity gaps raises Ghana's national aggregate productivity by 11.9 percent and the contribution of structural transformation to productivity by 19.7 percent.

Property rights, land circulation and off-farm labor supply: evidence from a land tenure reform in China

Weak property rights over land prevent efficient allocation of production factors in the developing world. Farmers who lack title secure access to the land they work by providing evidence of productive use. The ``use it or lose it'' principle leads to a thin land rental market and a misallocation of labor between economic sectors. Leverage a land tenure reform in China starting in the late 1990s, I investigate the extent to which secure property rights increase allocative efficiency of land and labor. I exploit implementation of land policies with staggered timing to show that secure property rights led to 1) more land rental participants and a higher share of rented farmland and 2) a reallocation of rural labor towards the non-farm sector. To examine if there is a redistribution of farmland to productive farmers, I estimate a discrete choice model in which leases are categorized based on the relationships between landlords and tenants. The estimation shows that secure property rights lead to landlord-tenant matches that are less driven by relationship and location, indicating a more efficient allocation of land. I further apply the model to labor allocation and find that off-farm workers are more likely to migrate out of their hometowns than to work locally. I finally estimate the welfare impact of the land reform and find that a one standard deviation increase in land right intensity leads to 25\% increase in durable goods consumption.