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Econophysics of Labor Migration

May 16, 2019.

 

     

 

Figure 1. The heavy congestion in Bangkok's bus terminals just before the start of Songkran festival (the traditional Thai New Year around mid-April which serves as a time for family and friends’ reunions). This indicates that the large number of rural people has left their hometown to find works in large cities. (Source : https://www.108news.net/news/63096 and http://www.chaoprayanews.com/2011/11/04/บขส-มั่นใจย้ายรถจากหมอชิต/ )

 

        From the world’s rapid urbanization, people tend to migrate from rural areas (focusing on agricultural economy) to the urban areas (emphasizing on industrial economy) over the last few decades (e.g. see Figures 1 and 2). According to statistical data, the population of large cities around the world has increased considerably. In 2018, the UN stated that 55% of the world's population lives in various metropolitan areas, and this figure will increase to 68% within the next 30 years [1]. Typically, the highly populated urban area often encounters various economic and social problems. This includes traffic congestion, slum communities with high unemployment rate and poverty problems, homeless invading public space problems, crime and drug problems, etc. These problems may result in urban residents to lack of safety in life and properties as well as personal welfare. In addition, congestion in urban areas also causes health problems resulting from activities within the city, e.g. polluted air, noises and wastewater, etc. These toxic environments affect urban people health very much and may reduce the quality of life and working efficiency in urban areas. Therefore, in order to prevent or alleviate such problems, the government should be engaged with detailed/comprehensive information on the migration between rural and urban areas as well as a model that can conform to such the move. This information can be used as a guideline for establishing a management policy corresponding to the population level in the areas.

 

 

 

Figure 2. Rural people from the agricultural sector come to sell their labor-power in industrial plants. (Source: https://www.prachachat.net/local-economy/news-106393 and  http://www.acnews.net/detailcsr.php?news_id=N255603373)

 

        The Thailand Center of Excellence in Physics (ThEP Center) has recognized the importance of such problems, and therefore begun to investigate the characteristic of Thai society in transit (which in the past focuses on agriculture) to a society that emphasizes on using technology to enable mass production. The investigation has been done through the migration of workers from agriculture sector (in rural area) to industrial sectors (in urban area) using the Cobb-Douglas migration theory [2]. It was found that the difference in wages between those in agricultural and industrial sectors (after normalizing with that of the industrial sector) strongly depends on the unemployment rate in urban areas and the number of workers Na in the agricultural sector in the form [3] . In this equation,  Nm  is the number of jobs available in the industrial sector,  Na is the total number of workers in the agricultural sector and  is the overall coefficients that depends on the amount of agricultural production ,  the average price of agricultural product (compared with that of the industrial product) , and the industrial production capacity . This wage difference is one of the main motivations that drive workers to the sector with more income. However, Thai society since the past is a society where parents, children, brothers and sisters live together in a household. Even being at the transition to urban society, a survey conducted by the National Statistical Office (Thailand) in 2010 found that the average number of members in the household is 3.8 people [4]. This confirms that we are still away from a family of one. Also, family members tend to work in the same area (sector). Therefore, by combining the effects of interpersonal interaction and motivation from the wage difference, it is possible to create a utility function in the form . In this utility equation, the first term on the right is the result of social interaction, whereas the second term comes from the income difference between the urban and rural areas. J  is the constant referring to the level of interpersonal relationships, si = ±1 is the states of workers being in rural areas (emphasized on agricultural economy) (-1) or urban areas (emphasized on industrial economics) (+1) and  is a migration-driven force due to the wage difference between agriculture and the industrial sectors. In addition, the k variable relates to the workers’ opinion on how important the income difference in their judgment is. As one may see, the model processed under this utility function will migrate workers to sector that yield lower utility function. In addition, it can be noticed that this model is comparable to the ferromagnetic Ising model in statistical mechanics, which demonstrates the ability in applying Physics knowledge to the real situation. Note that, the initial urban population may be set to 20 percent of the total population, which is the default initial value for the transition to industrial societies in many developing countries [5].

 

 

Figure 3. Normalized agriculture workers ma  as a function of coefficients associated to agricultural prices and production ratio . [3]

 

        Based on the investigation, it can be concluded and shown in Figure 3 [3], which presents the number of workers in the agricultural sector (normalized with the total number of population from both sectors) ma as functions of the agricultural product price coefficient and the production coefficients of both sectors. As can be seen, when the workers feel that the income difference is not important ( is small, which reflects conditions that workers are happy with the status quo), most workers will reside in the agricultural sector (rural area) according to being agricultural based Thai society. However, when workers become aware of the difference in income ( is higher), most workers will relocate to stay in the industrial sector (urban area) when the agricultural product price index is low (low  or less income in the agricultural sector). However, when the agricultural products increase in price, the worker’s migration turns back to the agricultural sector (rural area), resulting in the phase-transition like behavior of residence in both sectors.  Note that this phase changing also bases on the realization of the income difference factor (), unless the phase-transition may never occur. As can be seen, the results from Figure 3 may benefit the government in making important economic policies relating to the price of agricultural products (compared with other general consumer goods on the average) and the distribution of workers in both agricultural and industrial production sectors. However, the results shown are rather initial as the model considered only one farm/firm in each agricultural/industrial sector, whereas there could be many and each may provide different scales in salary. In addition, it may be necessary to adjust the coefficients of agricultural products to be in units comparable with real living costs or include the government intervention (such as agricultural product pledge or agricultural product price assurance). Such issues will be the ThEP Center’s next research plan steps.

 

References

 

  1. United Nation, 2018, “68% of the world population projected to live in urban areas by 2050” , Website: https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html, Retrieved on 29 April 2019.
  2. C.W. Cobb and P.H. Douglass, 1928, “A Theory of Production”,  American Economic Review 18, 139-165.
  3. A.P. Jaroenjittichai and Y. Laosiritaworn, “Benefits driven migration between agricultural and manufacturing sectors: Econophysics modelling via Monte Carlo simulation on Ising spin model”, Journal of Physics: Conference Series 1144, 012182.
  4. National Statistical Office Thailand, 2010, “The 2010 Population and Housing Census”, Website: http://popcensus.nso.go.th/upload/census-report-6-4-54-en.pdf, Retrieved on 29 April 2019.
  5. J. J. Silveira, A. L. Espindola and T. J. Penna, 2006, “An Agent Based Model to Rural-Urban Migration Analysis”, Physica A: Statistical Mechanics and Its Applications 364, 445-456.

 

Reported by

 

Associated Professor Dr. Yongyut Laosiritaworn

Department of Physics and Materials Science, Chiang Mai University, Chiang Mai-50200, Thailand

E-mail: yongyut.laosiri@cmu.ac.th