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Các nhân tố ảnh hưởng tới thu nhập của lao động nhập cư khu vực kinh tế phi chính thức tại Hà Nội

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Nghiên cứu này xác định các yếu tố ảnh hưởng đến thu nhập của lao động nhập cư tại Hà Nội. Để đạt được mục tiêu đó, nghiên cứu đã tiến hành khảo sát 425 lao động nhập cư tại 12 quận nội thành. Để hiểu rõ hơn mời các bạn cùng tham khảo nội dung chi tiết của bài viết này.

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Nội dung Text: Các nhân tố ảnh hưởng tới thu nhập của lao động nhập cư khu vực kinh tế phi chính thức tại Hà Nội

  1. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 FACTORS AFFECTING THE INCOME OF MIGRANT WORKERS IN THE INFORMAL ECONOMY IN HANOI CÁC NHÂN TỐ ẢNH HƯỞNG TỚI THU NHẬP CỦA LAO ĐỘNG NHẬP CƯ KHU VỰC KINH TẾ PHI CHÍNH THỨC TẠI HÀ NỘI Dr. Nguyen Minh Thu National Economics University nmthu@neu.edu.vn Abstract The study identified factors affecting the income of migrant workers in Hanoi. To achieve this goal, this study surveyed 425 migrant workers in 12 urban districts. The analysis of quantile regression model has identified three factors that have significant impacts on income at all quan- tile levels, including (i) working experience, (ii) types of job and (iii) gender. In addition, some factors such as age, working hours, qualification also effect income in some percentiles. On this basis, the study offers some meaningful solutions to improve income and ensure the lives of mi- grant workers in Hanoi in the near future. Keywords: income, informal economy, migrant workers Tóm tắt: Nghiên cứu này xác định các yếu tố ảnh hưởng đến thu nhập của lao động nhập cư tại Hà Nội. Để đạt được mục tiêu đó, nghiên cứu đã tiến hành khảo sát 425 lao động nhập cư tại 12 quận nội thành. Phân tích mô hình hồi quy phân vị đã xác định được ba yếu tố có tác động đáng kể đến thu nhập lao động nhập cư ở tất cả các mức phân vị, bao gồm (i) kinh nghiệm làm việc, (ii) loại công việc và (iii) giới tính. Ngoài ra, một số yếu tố như tuổi, số giờ làm việc, trình độ chuyên môn cũng ảnh hưởng đến thu nhập ở một số mức phân vị nhất định. Trên cơ sở đó, nghiên cứu đưa ra một số giải pháp nhằm nâng cao thu nhập và đảm bảo cuộc sống của người lao động nhập cư tại Hà Nội trong thời gian tới. Từ khoá: khu vực kinh tế phi chính thức, lao động di cư, thu nhập 1. Introduction The large discrepancy in incomes between workers in rural and urban areas, especially in big cities and industrial zones like Hanoi, is attracting an influx of workers from other places. On the other hand, the processes of industrialization, modernization, and urbanization are transform- ing massive amounts of agricultural land into industrial land and reducing farmland. Furthermore, climate change is leading to unpredictable and harsher weather, which is resulting in more pre- carious production of agriculture, less productive farming outcomes, increasing the amount of non-working hours. As a result, income of agricultural households are being reduced, making their standards of living drop and leaving their basic needs unmet. These unprecedented phenom- ena form an increasing push for the migrant wave from rural to urban places. 44
  2. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Upon reaching the cities, these people get manual jobs not requiring skills, experience and formal training, but physically demanding and dangerous jobs that urban dwellers do not want to get like cleaners, builders, street vendors, and porters. Their work is mainly in the informal economy, with features being unstable, no contracts or only vocal contracts, long working hours, and no health insurance or government welfare. The average income of informal laborer is 4.4 million VND each month, less than 42% that of formal ones, at around 6.7 million VND/ each month (GSO, 2017). Such low earnings do not guarantee quality of life to their families or them- selves. In the same research, the average number of working hours in the informal economy was 49.2 hours a week, which was 2 more hours than their formal counterparts, at 47.2 hours a week. With long working time and low earnings, they have to struggle with their living in cities, where the living costs are reaching higher and higher. As GSO (2016) reported, 79.1% of internal migrants are from rural to urban, which ac- counts for the largest part in migration. Therefore, the research focuses on analyzing factors af- fecting the income of rural-urban migrants in search for employment. By investigating the laborers in Vietnam’s informal economy, this research aims to: (a) Find out the level of each factor affecting the income of migrant workers in the informal sector in Vietnam and (b) search for an appropriate policy options for upgrading earnings for migrant workers in the informal sector in Vietnam in a sustainable way. 2. Literature revie There are many factors affecting the income of labor workforce in the informal sector of economy. These factors are classified into two groups including a group of objective factors and a group of subjective factors. The group of subjective factors includes the supply-demand labor market, government policies, law system,...; the group of subjective factors includes personal characteristics and occupational characteristics. Objective factors Government policies Accoding to theo Article 90, The 2012 Labor Code, the minimum salary is the lowest pay- ment paid for the worker doing simplest jobs in normal working conditions and it has to guarantee a basic living for the worker and their family. The resolution of the 15th Party Central Committee, the minimum wage passed the agenda of reforming salary policies, in which salary is considered to be the value of labor power, based on the market regime regulated by the government, with the purpose being guaranteeing that the worker can live off their salary, and the minimum wage meets the basic need. In reality, the incomes of workers in the informal sector of economy are higher than the minimum salary but it does not meet the minimum basic need. Oxfam (2015) shows that the basic salary of almost all migrants does not meet all the needs of living; the min- imum wage only guarantees 60% of the living costs for the laborer (Phạm, 2000). Besides, the policies for poverty alleviation have only focused on the poor living in their registered place, but do not count the people in relative poverty and multidimensional poverty in urban area industrial parks, wherein migrants constitute a tremendous majority. Loan policies 45
  3. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 rely on the household registered book (Oxfam, 2015) require a high degree of transparency in fi- nancial records. Therefore, when they need capital to open or widen their business, invest in equipment, machines, and improve the production, migrants cannot rely on formal financial or- ganizations. As a result, the lack of capital is a barrier against their productivity and the increase of income of migrants. Furthermore, social security and insurance programs do not have any in- centives for migrants in the informal sector of economy to buy them. When they are sick or ill, they are not able to afford health centers for the treatment, which makes their illness worse and prolonged. So their work is discontinued, and their income decreases. Informal costs When doing business, producing products or trading in the informal sector of the economy means many establishment owners, self-account workers, even street vendors have to give some informal payments to law enforcement agents in order to avoid their “regular visit”. Petty cor- ruption is already in the mindset of many authorities and offices, and perhaps bribery is an indis- pensable ritual when someone wants to open their business. Not only do corruption issues deter economic development, discourage widening, extending and upgrading the production, but it also takes part of the income of migrants in the informal sector of economy. As the income of these people is precarious and low, corruption discourages workers from believing in the gov- ernment to open and develop their business. Demand and Supply in the labor market From the perspective of the labor supply, because of the pressure of population growth, the supply of labor workers outweighs the demand. The phenomenon of the low income from farming is the push that farmers have to find other sources of income. When the production level and the productivity is low, laborers move to urban areas and industrial parks. The influx of mi- grants into urban sectors results in an abundance of the laborers, which makes the value of labor, especial manual work, drop. From the perspective of the labor demand, the dramatic growth of industrialization, mod- ernization and urbanization requires the participation of numerous workers in industrial areas, foreign processing zones, etc. Besides this, the demand for goods and services in urban areas is unprecedentedly high. All in all, there are a lot of income opportunities for migrants in urban areas and industrial areas. Thus, the supply-demand relationship of the labor market has an influence on the oppor- tunities of workers, especially workers in the informal economy, partially affects income or ex- penditure paid by them. The determination of the value, salary or remuneration of the labor depends on the labor market (Nguyen, 2017). Subjective factors Personal characteristics of migrants in the informal sector of economy Gender The labor market of Vietnam is still in transformation, except for some positions of man- 46
  4. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 agement or female-dominated employment, the payment for women is still low compared to men in all types of occupations or positions. The average income of men is 1 million VND higher than their female counterparts in the informal sector of economy in Hanoi (Nguyen, 2017). In other economies, Bhatti (2013) suggests that men get a 10.44% higher amount in their income in comparison with women in the labor market of Pakistan, while Lee and Lee (2006) point out that Korea has a much bigger gap, with men getting 36.69% more in their earnings compared to fe- males. In the area of Southeast Asian Nations, females in Manila, Philippines get 516 pesos less than their male counterparts, while in smaller cities of the Philippines, the gap is much severer, at 775 pesos (Hagen Koo & Peter, 2005). Therefore, gender is one of the main factors influencing labor market as a whole, and workers in the informal sector of economy. Age Previous research often points out that young workers get higher income than their older counterparts, because the youths have health on their side. Besides this, workers age 25-45 are usually the head of the family, thereby the financial pressure for them is higher than others. It is both the motive and the push to make them earn more money. Sukti and his partners (2015) con- cluded age was one of three prime factors affecting the income gap between the informal sector and the formal sector in Thailand. When also using age to analyze the income gap between the informal and formal sectors, the result showed that 50% of the income disparity stemmed from individual characteristics, including age of the laborer. In Vietnam, Nguyen (2017) suggested that workers under 35 years old in the informal sector get higher income than those who are above 35 years old, but this discrepancy is not big. Highest level of education In almost all research, education is considered to be one of the main factors affecting the income of workers. When holding other factors affecting income constant, one rural-urban mi- grant in the Red River delta with a university earns 39% more than their counterparts who just finished primary school, and the figure for urban-urban migrants is higher, at 71% (Jean-Diere et al., 2012). In other economies, Lee and Lee (2006) show that the number of years going to school has a positive effect on income, with a one-year increase resulting a 4% increase in the income. Pakistan’s labor market saw the 4.8% increase (Bhatti, 2013), and the variable affected most on the income of migrant laborers of Philippines (Hagen & Peter, 2005); and the increase in income was 6.32% in the model for worker in service sector of Vietnam (Tong, 2015). Experience The number of years of working experience has a positive effect on income: an one-year increase of working experience results in a 3.02% increase in the income in the Korean Labor market (Lee and Lee, 2006). The figure for Pakistan is 3.05% (Bhatti, 2013) and the proportion of the increase is 6.43% within the service sector in Vietnam (Tong, 2015). To resume, the re- search above assumed that working experience has a positive effect on income. In addition, when conducting research on workers in the informal sector of the Red River delta, Jean-Diere (2012) saw that the working experience before migration does not influence the income of workers from 47
  5. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 the rural areas, while it has a statistically significant positive effect on the income of migrant workers from urban areas. This result shows the disadvantage of migrants from the rural areas when the joined the labor market in the urban areas. Occupational characteristics Working time The income of Pakistanis rises by 0.19% when they work one more hour (Bhati, 2013). Similarly, in the service sector of Vietnam the figure is 0.36% (Tong, 2015). The hired workers in Hanoi who work above 8 hours earn 4.56 million per month, and make 4.09 million VND with 8 hours working per day on average, and those who work under 8 hours earn 3.47 million VND each month (Nguyen, 2017). This research all shows that working time influences income with a positive effect. Working conditions and environment Working conditions and environments are diverse in the informal sector of economy. Peo- ple working indoors are production workers, salespeople, domestic servants, etc. They are often hired by other people or sometimes self-employed, and many of them get fixed payment. Others work outdoors, or their workplace is mobile like builders, motorbike taxi drivers, or street ven- dors, thereby their productivity somehow depends on weather conditions. The harsh environment affects the working production and thereby affects the remuneration of the laborer (Nguyen, 2017). Therefore, when analyzing factors affecting the income of workers in the informal sector of economy, we cannot ignore the condition of working place. Thus, studies related to the income of rural-to-urban migrant workers have shown objective and subjective factors affecting labor income in the informal economy. However, these studies only conduct descriptive statistics or simple analytical methods such as simple or multiple re- gression, have not done in-depth quantitative analysis. This is the gap for the research to propose a model and method to study factors affecting the income of migrant workers in the informal economy. 3. Methodology Proposed model The study was conducted in Hanoi with the same legal environment, so it limited the scope of assessing the impact of subjective factors on income. Based on previous studies, the proposed model includes 2 main factor groups affecting the income of migrant workers in the informal economy in Hanoi as following: 48
  6. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Figure 1: Proposed research model Data collection method The topic uses two methods of collecting primary and secondary data, specifically as follows: First, overview documents from a number of sources such as public books, international and national magazines (e.g. journal of economics and development), newspapers, previous re- search, essays, posts on reliable websites (WIEGO, ILO, GSO, etc.) to get hold of information about living conditions, income of non-informal migrant workers, factors affecting income and the level of their influence on income. Second, conduct a sample survey in the form of direct interviews based on prepared ques- tionnaires. In addition, conducting in-depth interviews to find out more about the needs and issues that have not been mentioned in the questionnaire. This also helps to check the data collected from the questionnaires. The questionnaire includes three main section. Section A collects personal information, having 6 questions about gender, year of birth, marital status, highest level of schooling (calcu- lated until high school), and professional qualifications. Section B gathers information about em- ployment, including 17 questions regarding to the employment of the migrant worker in the informal economy before and after migration, and also the occupational characteristics of the main jobs the worker was holding (status of employment, working experience, working time, etc.). Section C includes some questions on income of workers in the informal sector. Hanoi now totally has 30 administrative units as districts, including 12 urban districts, 17 rural districts, 1 town. The influx of working migrants flows mainly into urban districts in search 49
  7. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 for job opportunities and better earnings. Therefore, the study focused on surveying in 12 urban districts of Hanoi: Ba Dinh, Bac Tu Liem, Cau Giay, Dong Da, Ha Dong, Hai Ba Trung, Hoan Kiem, Hoang Mai, Long Bien, Nam Tu Liem, Tay Ho and Thanh Xuan. Because of limitations of time and finance, in each district we selected one ward to do interviews. The surveyed ward was the area wherein informal migrant workers crowded. Migrant workers often looked for jobs around markets, wholesales markets, bus stations, construction sites, food streets, etc. (Hoang Thien Trang, 2017). Besides, in order to get reliable results, the sample size needs to be larger than, or at least equal to, the minimum level permitted. In our survey, the size of sampling is determined by Iarossi formula (2006): Nz2 σ2 n= Nε2 + z2 σ2 In which: N - The size of population z - Standardized score σ2 - Population Variance ε - Sampling error size In Hanoi, there are 1 million migrant workers working in the informal sector (Vietnam women’s union, 2016), and the growth of this city population is above 200,000 people per year, in which 70% are driven by migration, equivalent to 140,000 people each year. Because of the data limitation about the size of migrant workers in the informal economy for the surveyed period, we estimate based on data from 2016 the number of informal migrant workers in the year 2019, and it is 1.5 million. A bit of research to determine impacts of resources on incomes in rural areas in Thanh Hoa has the size of sampling error ε of 2.5%, standardized score z with 95% confidence level being 1.96, and a population standard deviation of 0.0144-0.0255% (Chu Thi Kim Loan & Nguyen Kim Huong, 2015). Therefore, the minimum sample size of the survey is 138 observa- tions. Data analysis method Descriptive statistics is used to describe basic characteristics and features of data gathered. The main purpose of descriptive statistics is to provide a brief summary of the samples, often represented through tables, diagrams, charts, histograms, etc. which illustrate general results of the survey with parameters about mode, mean, median, etc. This method allows the user to show, capture basic features, characteristics of the researched object at scientific, clear, logical, eye- catching, and convenient ways that facilitate understanding, observation, and comparison. Multiple regression was employed to provide estimates of the conditional mean of the re- sponse variable given certain values of the predictor variables and to determine the overall fit (variance explained) of the model and the relative contribution of each of the predictors to the total variance being examined. In this research, the dependent variable is income; the independent ones are gender, schooling, age, etc. In addition, quantile regression, an extension of linear regression, is also used. It was first 50
  8. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 introduced by Koenker & Bassett in the year 1978 (Koenker & Bassett, 1978). Instead of esti- mating the model with average effects using the OLS linear model, the quantile regression pro- duces different effects along the distribution (quantiles) of the dependent variable. Median regression is more robust to outliers than the OLS regression. 4. results and discussion Sample description statistics To achieve the study purpose, the minimum sample size of this survey is 138 observations. In reality, the bigger the sample size is, the more significant and reliable the statistical testing and estimation are. Thus, the study was carried out with a larger extent corresponding to a sample size of 425 observations. Some information about respondents as following. Table 1. Generalinformation about the respondents Number of respondents Percentage (%) Gender 425 100.00 Male 249 58.59 Female 176 41.41 Age 425 100.00 15 to 24 102 24.00 25 to 34 127 29.88 35 to 44 79 18.59 45 to 54 77 18.12 55+ 40 9.41 Level of schooling 425 100.00 Primary school graduate or below 47 11.06 Secondary school graduate or below 213 50.12 High school graduate or below 165 38.82 Working hours 425 100.00 8 hours or below 98 23.06 8 to 12 hours 236 55.53 Above 12 hours 91 21.41 Source: Synthesized from the result of the survey Regresion analysis Based on the proposed model, perform regression analysis with the dependent variable is monthly income of migrant workers in the informal economy (million VND/month). There are 15 independent variables, including: AGE: age of the migrant workers (years) EXP: years of experience in the current job (years) 51
  9. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 HOURS: number of working hours per month (hours) SEX: dummy variable representing gender (1: male, 0: female) MAR1: dummy variable representing married workers (Yes = 1, No = 0) MAR2: dummy variable representing separated/divorced/widowed workers (Yes = 1, No = 0) SCHOOL: years of schooling (years) QUALIFI1: dummy variable representing people who attending technical training or vo- cational centers (Yes = 1, No = 0) QUALIFI2: dummy variable representing people who holding primary/intermediate cer- tificate (Yes = 1, No = 0) QUALIFI3: dummy variable representing people who holding college or university degree (Yes = 1, No = 0) JOB1: dummy variable representing wage worker (Yes = 1, No = 0) JOB2: dummy variable representing street trade (Yes = 1, No = 0) JOB3: dummy variable representing freelance worker (Yes = 1, No = 0) EAT_STAY: dummy variable representing wage worker who got support for meals (Yes= 1, No = 0) The existence of heteroscedasticity is a major concern in the application of regression analy- sis, including the analysis of variance, as it can invalidate statistical tests of significance tests of significance that assume the modelling errors are uncorrelated and uniform-hence that their vari- ances do not vary with the effects being modeled. So, the study test the heteroscedasticity before conducting the regression analysis. To test heteroscedasticity, the research used the White test, the null and alternative hypothe- ses are: H0: The variances of the errors are equal H1: The variances of the errors are not equal Table 2: The result of testing heteroscedasticity Source chi2 df P-value Heteroskedasticity 198.26 108 0.0000 Skewness 30.29 15 0.0109 Kurtosis 1.71 1 0.1911 Total 230.25 124 0.0000 Source: Synthesized from the results of the model, using STATA 13 The table 3 showed that total P-value < 0,05, so we rejected H0 and accepted H1 hypothesis, thereby the model had the phenomenon heteroscedasticity. To fix the phenomenon heteroscedas- ticity, we used the robust standard error method. 52
  10. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Table 3: Robust multiple regression result Overall assessment about the model R2 R2-adjusted F statistic P-value N 0.5381 0.5058 9.31 0.000 425 The value of each variable Variable name Coefficient Standardized deviation t-statistic P-value CONSTANT 7.134 1.360 5.25 0.000 AGE -0.022 0.018 -1.22 0.223 EXP 0.087 0.029 3.04 0.003*** HOURS 0.008 0.003 2.46 0.014** SEX 2.399 0.377 6.37 0.000*** MAR1 0.588 0.362 1.62 0.105 MAR2 0.081 0.720 0.11 0.911 SCHOOL 0.515 0.398 1.29 0.197 QUALIFI1 0.592 0.426 1.39 0.165 QUALIFI2 0.613 0.575 1.07 0.287 QUALIFI3 1.082 0.704 1.54 0.125 JOB1 -3.485 1.047 -3.33 0.001*** JOB2 -4.997 0.901 -5.55 0.000*** JOB3 -4.554 1.018 -4.47 0.000*** EAT_STAY -1.888 0.558 -3.38 0.001 ****, **, *** significance at 10%, 5%, 1% Synthesized from the results of the model using STATA 13 Quantile regression analysis The result of the multiple regression with the OLS method showed that the model had the phenomenon heteroscedasticity, proving that the level of effect on the income of independent variables was different on each segment of the income. Therefore, quantile regression would show this difference clearly. In order to assess how the effect of independent variables changed at quantiles of the income, the research conducted quantile regression analysis at percentiles 10%, 25%, 50%, 75% và 90%. Table 3 was the result of quantile regression, distributed on the two sides of the percentile 50%. 53
  11. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Table 4: Quantile regression coefficients at different quantiles Coefficients of the quantile regression INCOME 10% 25% 50% 75% 90% AGE -0,024 -0,030* -0,036** -0,031 -0,018 EXP 0,069*** 0,052** 0,061** 0,102*** 0,126*** HOURS 0,005** 0,002 0,003* 0,006** 0,006 MAR1 0,372 0,297 0,708 0,732 0,330 MAR2 0,700 0,396 1,029 0,178 -0,921 SCHOOL 0,652 0,537 0,517 0,434 0,603 QUALIFI1 0,239 0,319 0,152 0,066 0,481 QUALIFI2 0,873 0,784 0,709 1,010 1,072 QUALIFI3 1,667*** 0,855* 0,769 0,518 0,143 JOB1 -0,712 -2,100** -2,615*** -5,491*** -7,420** JOB2 -1,542* -2,861*** -3,852*** -6,608*** -8,643*** JOB3 -1,350 -2,642** -2,636** -5,195*** -8,101*** SEX 1,660*** 1,413*** 1,693*** 2,202*** 2,773*** EAT_STAY -1,498** -1,429** -1,288** -0,736 -1,366* *, **, *** significant at 10%, 5%, 1% Compared with multiple regression, the regression results at different quantiles are different. The results show that there are only 3 factors that affect income of the informal sector workers at all quantile levels, including EXP, JOB2 and SEX. 54
  12. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Figure 2: Regression coefficients of years of working experience and gender of migrant workers Source: Synthesized from the result of the quantile regression using Stata 13 At all the percentiles, years of experience has a positive effect on income. Especially, the higher the income is, the more experience impacts on income, and vice versa. In the high-income group, years of working experience made the higher increase in income than the low-income group. The increase was huge at the 65th percentile and 85th percentile. In addition, it is clear that gender disparities occur at all income percentiles. From the 35th percentile, the income of males outweighed the income of females with the gap widening at higher percentile levels. There is real gender income inequality and it gets more severe in the high-income group. In contrast, some factors such as MAR1, MAR2, SCHOOL, QUALIFI1 and QUALIFI2 were not statistically significant at all quantile levels. This is also the same results as the conven- tional multiple regression model. For the remaining factors, the influence of factors on income is different at different quan- tile. For example, the age of the migrant did not have effect on income at 10th, 75th and 90th per- centiles. But in the range from the 25th percentile to the 50th percentile, i.e. income of the migrants is in the lower middle group, age really has a negative effect on their income. 55
  13. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Figure 2: The regression coefficients of the age of the migrant and the average number of working hours per month Source: Synthesized from the result of the quantile regression using Stata 13 The coefficient regression of working hours in the low income group (10th percentile) and the upper middle income group (50th and 70th percentiles) are statistically significant. However, because these coefficients are quite small, the change in working time have a negligible effect on income. In addition, the study found significant differences in income among different types of job (wage worker, freelance worker, street trader) and between workers holding university degree or above and those not holding any technical/professional qualification in most of the percentiles. Conclusion and Policy Implications The results show two main factors affecting the income of migrant workers at all per- centiles, including years of experience and gender. It is consistent with previous studies, which show the main factors in the research model. However, this study focuses on different percentiles which tend to be more severe in the high-income group. In addition, age is also one of the factors to be considered in the research models. It is sim- ilar to the work of Nguyen (2017) and Skuti et al. (2015). Compared to previous studies, thanks to the percentile regression method, the paper clearly shows the impact of working time on em- ployee’s income and its significance for different group of migrant workers. Combining with the open-ended question about difficulties of workers in the process of working and earning money, the study has made some conclusions about the income of migran workers: (1) the average income of migrant is quite low in comparison with ones in formal econ- omy; (2) there is an imbalance in income distribution and it gets more severe in the high-income group; (3) the influence of some factors such as marital status, years of schooling and intermediate 56
  14. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 or lower qualifications on the research sample is not significant; (4) their jobs are not stable and precarious. Moreover, they met barriers in approaching loan programs in both migrant-sending communities and migrant-receiving communities, because they do not meet the conditions. In conclusion, workers in the informal sector of the economy suffered tremendous setbacks while making earnings. Support from external parties is essential as workers themselves are not aware of their right to benefits and the situation in the demand-supply labor market. On that basis, the study proposed some recommendations in order to raise incomes and en- sure the lives of migrant workers in urban districts as follows: (i) encourage and improve the ed- ucation and qualification for migrant workers to equip more knowledge and skills; (ii) support and subsidize workers who need loans which encourage them to promote production or doing business; (iii) Provide information on workers’ rights, promote health insurance and social in- surance programs to ensure social security for them. REFERENCES 1. Chu Thi Kim Loan, Nguyen Van Huong (2015), The impact of resources on farm house- hold income in Thanh Hoa province: A case study in Tho Xuan and Ha Trung, Journal of Science and Development 2. General Statistics Office (2017), The 2016 informal employment in Vietnam. 3. General Statistics Office & United Nations Population Fund (2016), The 2015 national internal migrant survey. 4. Hagen Koo & Peter C. Smith (2005), Migration, the urban informal sector, and earnings in the Philippines, The Sociological Quarterly, Vol.24, No.2, pp.219-232. 5. Oxfam Vietnam (2015), Brief report: Legal and practical barriers for migrant workers in the access to social protection, Labor Rights Program of Oxfam in Vietnam. 6. Pham Quy Tho (2000), Effects of rural-urban migration and employment of migration in the period of industrialization and modernization. 7. Purwaka Hari Prihanto & Adi Bhakti (2017). Profile of informal sector workers and fac- tors affecting informal sector employment, Vol.5, No.2. 8. R.Koenker, G.Bassett (1978), Regression quantiles, Journal of the Econometric Society, 46 (1978) 9. Sukti Dasguta, Ruttiya Bhula-or and Tiraphap Fakthong (2015), Earnings differentials between formal and informal employment in Thailand. 10. Tong Quoc Bao (2015), Analysis of factors affecting income in the service sector in Vietnam, Journal of Science. 57
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