Policy incentives, ownership effects, and firm productivity—Evidence from China’s Agricultural Leading Firms Program

Gan, Lin; Takahashi, Yoshifumi; Nomura, Hisako; Yabe, Mitsuyasu

doi:10.1016/j.eap.2022.01.001

Cited by 8 publications

(2 citation statements)

References 35 publications

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“…Therefore, filling them does not severely impact the data structure. Third, we refer to Cai and Liu (2009), Chen et al (2019), and Lin et al (2022) to clean up the data, including missing value deletion, outlier cleaning, and nominal variable deflating. After processing, we obtain data from 1,198,018 observations containing 213,228 firms.…”

Section: Data and Descriptive Statisticsmentioning

confidence: 99%

The short‐ and long‐term impacts of overinvestments on the profitability of agri‐food processing firms in China

et al. 2023

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This study examines the short‐ and long‐term impacts of overinvestments on the profitability of Chinese agri‐food processing firms. We construct an overinvestment age variable measured as the number of years since the most recent overinvestment and use a two‐way fixed effects model based on firm‐level data for the Chinese agri‐food‐processing industry from 1998 to 2013 to conduct the research. We find that the profitability of firms improves during the first and second years following the most recent overinvestment. However, from the third year onward, profitability declines, and the restraining effect increases year by year. In addition, we find that regional differences and differences in financing constraints can explain the heterogeneity of the overinvestment age affecting firm profitability. [EconLit Citations: D22, L25, L66].

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Section: Data and Descriptive Statisticsmentioning

confidence: 99%

The short‐ and long‐term impacts of overinvestments on the profitability of agri‐food processing firms in China

et al. 2023

Self Cite

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“…Although there have been abundant achievements on agricultural enterprises in various aspects, such as the planting industry [6], animal husbandry [7], fishery [8], and the agricultural product processing industry [9], studies on ALEs are relatively scarce. Research on ALEs has focused on topics such as operational models [10], development characteristics [11], production efficiency [12], social effects [13], and competitive advantages [14] and has paid less attention to spatial patterns and influencing factors.…”

Section: Introductionmentioning

confidence: 99%

Spatial Pattern and Influencing Factors of Agricultural Leading Enterprises in Heilongjiang Province, China

Wang,

Ma,

Luo

2023

Agriculture

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As one of the major new agricultural business entities, agricultural leading enterprises (ALEs) are responsible for ensuring national food security, leading agricultural and rural modernization, and increasing farmers’ employment prospects and incomes. From the perspective of headquarters and branches, this study used a point pattern analysis, the local Moran’s index, the rank-size rule, and the geographical detector to depict the spatial pattern of ALEs in Heilongjiang Province, detect influencing factors, and reveal the spatial layout mechanism. The main conclusions are as follows. (1) ALE headquarters and branches in Heilongjiang Province had different location requirements, and their layout orientation, clustering areas, and influencing factors were different. (2) The headquarters displayed a pronounced urban and agglomeration orientation, while branches exhibited a significant farm dependence and raw material orientation. (3) Both the headquarters and the branches showed a significant trend towards spatial clustering. The headquarters were mainly in the Harbin municipal district and surrounding counties, including Wuchang, Zhaodong, and Beilin, which showed a high–high cluster pattern. The branches were mainly in the Sanjiang Plain. Tongjiang, Fujin, Hulin, Mishan, Raohe, Baoqing, and Suibin showed a high–high cluster pattern, while the Harbin municipal district and Bei’an showed a high–low outlier pattern. (4) The ALEs’ regional connection network in Heilongjiang Province was radially distributed with the Harbin municipal district as the centre. The agricultural reclamation system deeply influenced it. (5) The number of supporting enterprises, number of permanent residents, gross domestic product, railway mileage, number of people with Bachelor’s degrees or above, and distance from the provincial capital were the main influencing factors of the headquarters spatial pattern in Heilongjiang Province. The number of state farms in Heilongjiang Province, the per capita grain yield, highway mileage, and distance from the provincial capital were the main influencing factors of the branch spatial patterns in Heilongjiang Province. The interaction results indicated that the explanatory power of two-factor interaction was stronger than that of a single factor regardless of headquarters or branches, and most interaction types were bilinear enhancements. This study aims to provide a decision-making reference for the long-term development of ALEs in Heilongjiang Province at the present stage and accelerate the development of agricultural industrialization in major grain-producing areas.

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Carbon regulation and enterprise investment: Evidence from China

Yang,

Zhao,

Shao

et al. 2023

Energy Economics

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Policy incentives, ownership effects, and firm productivity—Evidence from China’s Agricultural Leading Firms Program

Cited by 8 publications

References 35 publications

The short‐ and long‐term impacts of overinvestments on the profitability of agri‐food processing firms in China

The short‐ and long‐term impacts of overinvestments on the profitability of agri‐food processing firms in China

Spatial Pattern and Influencing Factors of Agricultural Leading Enterprises in Heilongjiang Province, China

Carbon regulation and enterprise investment: Evidence from China

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