Analysis of Influential Factors on Agricultural Surplus Labor Professionalization During China's Economic Downturn

Yang Xiu-li, and Li Lu-tang

College of Economics and Management, Northwest Agriculture & Forestry University, Yangling 712100, Shaanxi, China

Analysis of Influential Factors on Agricultural Surplus Labor Professionalization During China's Economic Downturn

Yang Xiu-li, and Li Lu-tang*

College of Economics and Management, Northwest Agriculture & Forestry University, Yangling 712100, Shaanxi, China

This paper contributed to the pool of studies about agricultural surplus labor in China, also acted as the root to the imminent settlement of the issues concerning agriculture, countryside and farmers. Using data from survey of agricultural surplus labor in 2012, which covered three provinces in northern, midwestern and southern parts of China, this paper analyzed the influential factors on agricultural surplus labor professionalization by adoption of a logistic regression model. It showed that agricultural surplus labor shortage could be explained by low-quality professionalization. It was a feasible and effective way to solve the issue of workforce shortage during economic downturn by improving agricultural surplus labor's professionalization.

agricultural surplus labor, three rural issues, economic downturn, professionalization, logistic regression model

Introduction

Issues concerning agriculture, countryside and farmers have aroused great attention since the beginning of the 21st century. As for the root, surplus rural population and residual labor force have been pushed to the stage, therefore, the proper settlement of surplus rural labor should be the prerequisite for the hot issue. Despite the endowment of large population base, China has still been suffering a significant labor shortage in urban labor market since 2004 (Han, 2010; Li and Wang, 2009). From then on, "laborer barren" has become a nightmare lingering around Perl River Delta region and the Yangtze River Delta region, furthermore, this trend is encroaching into the central and western areas once famous for labor force output (Qu and Mu, 2004; Wang and Meng, 2005). General remarks resort this predicament to the inability of labor force to satisfy the factory expansion in the period of economic booming.

According to the above logic, the year 2012 should have got relief from this scarcity due to the evident economic slump. On the contrary, laborer shortage, especially agricultural surplus labor, still prevailed in the second period while most viewpoints held China would definitely face mass layoffs and unemployment. Scholars provided various explanations to this paradox. Some attributed this phenomenon to lower the birth rate caused by China's birth-control policies (Cai, 2010; Zhai and Yang, 2011). Some perceived that rural emanation in hinterland provinces has become an important factor leading to the labor shortage (Li, 2006; Zhan and Huang, 2013). Others insisted Chinese-style structural rigidity prevented migrant laborers from migration (Kuznets, 1963; Chen, 2000; Huang, 2011). Nevertheless, none of the above interpretation sufficiently accounted for the puzzling agricultural surplus labor shortage. In contrast to the external factors mentioned above, we switched to the internal aspect of this issue, agricultural surpluslabor's willingness for professionalization, which provided survival of income and job opportunities for this special group. Here we defined professionalized agricultural surplus labor as a group of people who have succeeded in urbanization transformation and embodied the following characteristics: firstly, they have completely been involved in the process of industrialization to achieve interests maximization under the guidance of market mechanism; secondly, they possess advanced technology and sound employment ability; thirdly, they enjoy optimal share of compensation and industrial modernization.

Materials and Methods

Data

This paper used data of 2012 Agricultural Surplus Labor Survey questionnaire which were distributed in Hebei, Shaanxi and Zhejiang Provinces, representing the North, Midwest and Southern part of China respectively. Individuals who have been worked out of their hometowns of countrysides for more than one month were defined as agricultural surplus labor.

For the purpose of statistical analysis, we defined an agricultural surplus labor as followings: (i) he was aged between 15 and 64, namely the working-age population; (ii) he possessed valid personal data including age, sex, education and marital status; (iii) he contributed all his abilities to industry instead of agriculture. Through survey, the response rate amounted to 83% and 250 questionnaires were available. Table 1 presents the composition factors categorized by micro-level personal feature, meso-level environment and macro-level policy. As for personal features, age, sex, education level, physical condition and monthly income are composed. Environment factors include labor contract, social contacts, technical level, citizen's attitude, dwelling condition, and community participation. Training, social insurance, attitudes towards household registration system and attitudes towards land policy are involved in the macro factors. From the results, we could infer easily that most agricultural surplus labor possessed comparatively lower educational level and unsatisfying monthly income, wandering around 1 000 Yuan to 2 000 Yuan; the contract signing rate stayed low which reflected the passivity of rural surplus labor's employment and their lack of awareness for reasonable rights.

Explanation of variables in the model

Table 2 shows some descriptive statistics for mean equality through manifestation of a logistic regression model. Besides, means and standard deviations of each variable were also available.

Econometric model and empirical test

Concerning the reality that only two choices were available for the situation of agricultural surplus labor's professionalization, this paper adopted Binary Logistic Regression Model to identify the factors determining professionalization situation.

In the above equation, α is the constant term, m refers to the number of independent variables, βirepresents the coefficient of independent variables and indicates the explanatory degree of independent variables.

Results

The subsection exhibited the empirical results relating to professionalization for agricultural surplus labor, which were achieved through application of logistic regression model. Tables 3 and 4 indicate the coefficient estimates of the independent variables.

The statistic results in Table 3 showed the likelihood ratio chi-square of 171.881 which indicated no significant difference between predicted values and observed ones. With degree of freedom at 15 and correspondingly p-value of 0.000, the model demonstrated significance at the level of 0.05. Meanwhile, the statistic of -2Loglikehood was two times as much as the logarithmic likelihood function, which sounded preferred when the figure was pretty small accordingto experience in econometrics. Therefore, the value 35.517 could suggest an ideal value. Furthermore, the statistics of Cox&SnellR2 and NagelkerkeR2 were 0.645 and 0.906, respectively, which could successfully explain the change of independent variables and verify a expectant model as a whole.

Table 1 Basic information for surveyed sample

Table 2 Definitions and summary of statistics

Table 3 Significance of the model

Table 4 Professionalization of migrant workers

Table 3 showed that at the significance level of 10%, variables such as age, education and monthly income, labor contract, social contacts, technical level, citizen's attitude, dwelling condition and community participation, job training and household regression system had succeeded in passing the test of significance; sex, physical condition and social insurance were rejected. Among those significant variables, education and community participation presented especially striking influence on the agricultural surplus labor's professionalization. The concrete analysis is illustrated by Table 4.

Discussion

Factors at micro-level

Among considered factors affecting agricultural surplus labor's professionalization, three were significant, namely education level, monthly income and age. Education level and monthly income exerted potentially positive impact on professionalization. Monthly income was approximated by the value of portfolio volume ordered in four categories, which ranged from less than 1 000 RMB to above 3 000 RMB. High income contributed abundant capital to professionalization and low income deteriorated burden on agricultural households. However, the expectation of age was negative, indicating older labors were likely to induce less confidence in professionalization, while younger ones possessed more enthusiasm on integration into city; consequently more remunerative employment opportunities were available to young people. Therefore, education and monthly income seemed to affect professionalization positively, whereas age for agricultural surplus labor indicated negative influence. Although age was a good proxy for experience, our results rejected this intuition.

Factors at meso-level

At meso-level, six variables performed significant, including community participation, technical level, labor contract, social contact, citizen's attitude and dwelling condition. It took on a remarkable correlation between higher community participation and professionalization, which sounded reasonable because professionalized agricultural surplus labor were inclined to experience an intimate relation with urban life, and to involve in community activities to a certain degree. Recent years have witnessed popularity of public linedancing in communities, accelerating city integration on the premise of professionalization invisibly. The variables of technical level, labor contract, social contact, dwelling condition and citizen's attitude presented low correlations with professionalization although figures seemed significant. Labor embodying higher technical level and better dwelling condition tended to become professionalized easily and efficiently, and vice verse. In addition, diversity between labor contract, social contact and citizen's attitude manifested significant connection with professionalization. As the link for bilateral economic relation between employer and employee, labor contract guaranteed an expected transaction, but asymmetric engagement contract reduced agricultural surplus labor to absolute inferiority.

Factors at macro-level

In addition to individual and environment factors considered so far, household registration policy and experience of job training were also included. Job training was a principle pathway to accumulate labor's professional quality, skill level and employment competency. As can be seen from the results, more job training provided agricultural surplus labor more confidence for professionalization. If migrant workers could accept job training from the channel of companies, society or the government, they were able to perceive higher degree of civil rights and more bargaining power, and accordingly boost their confidence to professionalize and settlement in the cities. Reinforced in the regression analyses, the household registration system showed negative effect on professionalization, which inferred an impediment to the professionalization and exerted unwise affection onChina's current stage of development and long-term division of the urban and rural policy.

Conclusions

The calculations presented in the paper showed that the labor force shortage was caused by the absolute quantity rather than comparative quantity of agricultural surplus labor. The sustainability of labor force could depend on the professionalization of agricultural surplus labor in China's economic development program. Furthermore, we could not regard the labor shortage as a supply constrain in labor market, but a superexcellent catalyst for urbanization fulfillment by improvement of population quality.

While the past advantage of labor abundance came to an end with ongoing economic restructuring and adjustment, China had to consider new workforce policy to promote productivity enhancement (Peng, 2008; Wang and Zhou, 2013). In our opinion, the lowquality of agricultural surplus labor was an important reason to explain labor force shortage; hence the quantity of workforce could be substituted by improved workforce quality in the form of professionalization in order to maintain China's workforce competitiveness. We concluded that cultivation of high-quality professionalization for agricultural surplus labor could not entirely depend on individuals themselves, but a comprehensive endeavor for every aspect.

In view of the above considerations, we were inclined to suggest a sound solution to the labor force shortage from a professionalization perspective. It would be bound to provide strong supports for comprehensive and sustainable implementation of the high-quality professionalization achievement of rural surplus labor, and to promote healthy and sustainable economic development as well.

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1006-8104(2014)-01-0064-06

Received 6 May 2013

Yang Xiu-li (1979-), female, Ph. D, engaged in the research of agricultural economics management. E-mail: xlyang1012@163.com

* Corresponding author. Li Lu-tang, professor, supervisor of Ph. D student, engaged in the research of agricultural economics management. E-mail: lilut@nwsuaf.edu.cn