Empirical Analysis of Relationship between Farmers’ Income Structure and Consumption in Guizhou Province in the Context of Large-scale Poverty Alleviation

Wuxu TIAN, Jingwei LIU, Zhentao WANG

Moutai Institute, Renhuai 564500, China

Abstract Large-scale poverty alleviation is one of the three major strategic actions of Guizhou Province to plan for leapfrog development.Through building an econometric model, this paper made an empirical analysis of relationship between farmers’ income structure and consumption in Guizhou Province in the context of large-scale poverty alleviation.The results show that the wage income and transfer income of rural residents in Guizhou Province have a significant impact on the promotion of their consumption, and the impact of income from household business operation is also significant, but the impact is relatively weak, while the contribution of farmers’ property income to their consumption is insufficient.Finally, in view of the problems in the relationship between the income structure and consumption of farmers in Guizhou Province, it came up with policy recommendations including broadening the income channels, increasing farmers’ income, improving the income structure, and promoting farmers’ consumption.

Key words Large-scale poverty alleviation, Three rural issues, Income structure, Consumption structure

1 Introduction

Since the "13th Five-Year Plan", in order to implementing the spirit of the 19th National Congress of the Communist Party of China and fully fight the three tough battles of preventing and resolving major risks, targeted poverty alleviation, and pollution prevention, Guizhou Province has proposed to implement three major strategic actions, namely, large-scale poverty alleviation, big data and large ecology.Large-scale poverty alleviation directly involves agriculture, rural areas, and farmers, which are fundamental issues related to China’s national economy and people’s livelihood.The core of the "three rural issues" is to increase farmers’ income.Therefore, the issue of farmers’ income and consumption has always been the concern and attention of both the political and academic circles.The consumption level and consumption structure of farmers are directly related to their income.Related theories and research have shown that the higher the income level of farmers, the faster the income growth level, and the higher their consumption level, andviceversa[1].According to the latest statistical caliber, farmers’ income can be divided into four types: wage income, income from household business operation, property income and transfer income.These four different types of income have their own characteristics and their promotion and influence on farmers’ consumption are also different[2].Through analyzing the impact of farmers’ income structure on their consumption, we are intended to propose practical and effective policy measures to increase farmers’ income, promote farmers’ consumption, and accelerate the establishment of a long-term mechanism for expanding the domestic demand.

2 Analysis of income level and income structure of farmers in Guizhou

Guizhou Province is a large agricultural province in Southwest of China.By the end of 2018, among the province’s 36 million permanent residents, the rural population was 18.898 million, accounting for 52.5% of the province’s total population.In recent years, with the rapid social and economic development and the adjustment and optimization of economic structure in Guizhou Province, the income of farmers in Guizhou Province has increased significantly.By the end of 2018, the total per capita income of rural residents in Guizhou Province was 133.14 million yuan, an increase of 4.76 times since the issue of new statistical data in 2006, with an average annual increase of 13.88%[3](Fig.1).

Fig.1 Annual total per capita income of rural residents in Guizhou Province in 2006-2018

In terms of the income structure, in 2018, the total per capita income of farmers in Guizhou Province was 13 314 yuan, of which the wage income was 4 276 yuan, accounting for 32.12% of total per capita income, the income from household business operation was 6 525 yuan, accounting for 49% of total per capita income, and the property income was 190 yuan, accounting for 1.43% of total per capita income, the transfer income was 2 323 yuan, accounting for 17.45% of total per capita income.These indicate that in the total per capita income of farmers, the main source is the income from household business operation, followed by the wage income, while the property income and transfer income account for a relatively small proportion.From Table 1, it can be seen that although the income from household business operation has always accounted for a relatively large proportion of farmers’ total income, in recent years, the proportion of transfer income starts to increase rapidly, while the changes in proportion of wage income and property income are not enormous.Specifically, the rapid growth of farmers’ transfer income is the highlight of farmers’ income growth in recent years, reflecting China’s efforts to subsidize farmers and transfer payments to increase farmers’ income, narrow the gap between urban and rural areas, and promote rural development.

Table 1 Income structure of rural residents in Guizhou Province in 2006-2018 %

3 Analysis of the consumption level and consumption structure of farmers in Guizhou

As the total income of farmers in Guizhou Province continues to increase, the absolute amount of farmers’ per capita consumption expenditure is also rising.From Fig.2, it can be seen that the per capita consumption expenditure increased from 1 627 yuan in 2006 to 9 170 yuan in 2018, an increase of 5.64 times and an average annual increase of 15.5%.Internationally, Engel’s Coefficient is usually used to measure the living standards of people in a country or region.The Engel’s Coefficient uses the proportion of food expenditure to total consumption expenditure to illustrate the degree of influence of economic development and income increase on living consumption.In general, when other conditions are the same, the larger the Engel’s Coefficient, the poorer the people of a country or region; conversely, the smaller the Engel’s coefficient, the richer the people of a country or region.According to the standards of Food and Agriculture Organization of the United Nations, an Engel’s Coefficient above 59% means poverty, 50%-59% means adequate food and clothing, 40%-50% means well-off, 30%-40% means rich, and below 30% means the richest[4].From Fig.3, it can be seen that since 2011, the Engel’s Coefficient of rural households in Guizhou Province has continued to decline, indicating that in recent years, with the continuous increase of rural residents’ income level, their consumption behavior has also undergone tremendous changes, and the wealth of rural residents in Guizhou Province is increasing year by year.

Fig.3 Engel’s Coefficient of rural households in Guizhou Province in 2006-2018

Fig.2 Annual per capita living consumption expenditure of rural residents in Guizhou Province in 2006-2018

From Table 2, it can be seen that while the proportion of food expenditure(Engel’s Coefficient)declines, the proportion of people’s expenditure on transportation and communication increases significantly, and the expenditure on education, culture and entertainment also increases.With the continuous improvement of the consumption level of rural residents in Guizhou Province, the consumption structure has improved, and it has changed from subsistence consumption to development consumption, but enjoyment consumption is still slightly insufficient.Such changing trend of consumption structure reflects the historical development trend and era leaping of Guizhou Province and even China’s rural residents from poverty to adequate food and clothing, and then to well-off.

Table 2 Consumption expenditure structure of rural residents in Guizhou Province in 2006-2018 %

4 Impact of income structure on consumption expenditure

4.1 Variables and modelWe selected four income sources of per capita total income as the influencing factors of per capita living consumption expenditure, namely, wage income(X1), income from household business operation(X2), property income(X3), and transfer income(X4)as independent variables, and per capita consumption expenditure(Y)as the dependent variable.The data were selected from the data of theStatisticalYearbookofGuizhouProvince(2006-2018).On the basis of this, we established a multiple linear regression model, and made an econometric of the impact of farmers’ income structure on their consumption[5].The model was set as:

y=β0+β1x1+β2x2+β3x3+β4x4+ε

whereβi(i=1, 2, 3, 4)is the parameter to be estimated, andεis the stochastic error term.

4.2 Regression and test

4.2.1Model regression.With the aid of Eviews software, we made the OLS regression analysis on the above model, and the result output is shown in Table 3.

Table 3 Eviews output results(1)

From Table 3, we obtained the following regression equation(keep two digits after the decimal point):

From the regression results, it can be seen thatR2is large and close to 1, andF=8 434.75>F0.05(4, 8)=3.84, so the overall linear relationship between per capita consumption expenditure and the above explanatory variables is considered to be significant.However, because the coefficient ofX3 did not pass thettest, there may be multicollinearity among the explanatory variables.The correlation coefficient matrix between the explanatory variablesX1,X2,X3, andX4 is shown in Table 4.It can be found that the variables are highly correlated, thus it proved that there is serious multicollinearity in the model.In order to solve this problem, we adopted the stepwise regression method to correct it.

Table 4 Correlation coefficient matrix between explanatory variables

First, we separately made regression ofYtoX1,X2, andX3, and found thatR2=0.978 3 ofYtoX1 is the largest.This means that the per capita living consumption expenditure is most affected by wage income, so we took this unary regression model as the initial regression model, namely:

Secondly, we imported other explanatory variablesX2,X3,X4 into the above-mentioned initial regression model to find the optimal regression equation.We determined whether the newly imported variables are independent based on the change in the goodness of fit.If the goodness of fit changes significantly, it means that the newly imported variable is an independent explanatory variable; if the change in the goodness of fit is not significant, it means that the newly imported variable is not an independent explanatory variable, it can be replaced by a linear combination of other variables, indicating that there is a collinearity relationship between it and other explanatory variables[6].The stepwise regression results are shown in Table 5.

Table 5 Stepwise regression

Through stepwise regression, it can be found thatY= f(X1,X2,X4)is the optimal model, and the model has high explanatory power.The Eviews output results of this model are shown in Table 6.Therefore, the regression equation after eliminating multiple collinearities is(keeping two digits after the decimal point):

The results of this model show that in 2006-2018, for every 1 yuan increase in wage income of farmers in Guizhou Province, the per capita living expenditure will increase by 1.13 yuan; for every 1 yuan increase in the income from household business operation, the per capita living expenditure will increase by 0.21 yuan; for every 1 yuan increase in the transfer income, the per capita living expenditure will increase by 1.20 yuan.

4.2.2Model test.(i)Economic significance test: according to Table 6, the size and sign of the coefficients of the regression equation are consistent with economic significance.(ii)Statistical significance test: according to Table 6, thettest of each coefficient is statistically significant, and theFtest shows that the regression equation is also significant on the whole.(iii)Heteroskedasticity test: the results of White heteroscedasticity test show that the model does not have heteroscedasticity, as shown in Table 7.(iv)Autocorrelation test: According to the results of Table 6, D.W.=2.47, and whenn=13,k=4(including constant terms), dL=0.574, dU=2.094, then: 4-dU=1.906

Table 6 Eviews output results(2)

Table 7 White heteroskedasticity test

Table 8 Lagrangian multiplier(LM)series(first order)autocorrelation test

4 Conclusions and recommendations

From the above analysis, it can be known that the wage income, the income from household business operation and transfer income of farmers have a significant impact on their living consumption level, while the contribution of farmers’ property income to their consumption is insufficient.The influence of wage income on the living consumption level reflects that both the number and income of migrant workers of Guizhou Province has increased, while the impact of the transfer income on the living consumption reflects that Guizhou Province has made certain achievements in the large-scale poverty alleviation strategy, and the transfer payment of both central and local government for farmers has increased.However, compared with other provinces[7], the impact of the income from household business operation on the consumption level is not high, while the influence of property income on the consumption level is not significant.These reveal the structural problem in the income of farmers in Guizhou Province.The income of farmers depends mainly on the income from migrant work and transfer payment of government, while the growth of the income from household business operation is inadequate, thus it is necessary to further improve related policies and systems, develop characteristic agriculture, better improve farmers’ income structure, and promote the development of farmers’ consumption, agriculture, and rural areas.

(i)Making effort to increase farmers’ income and narrow the gap between urban and rural areas.The income level and structure of farmers not only exert an important impact on their consumption level, but also have a decisive effect on their consumption structure[8].Although to a certain extent the income of farmers in Guizhou Province has increased significantly, compared with the income of urban residents, its growth rate is relatively slow, and the gap between urban and rural areas has widened.According to statistics, the total per capita income of farmers in Guizhou Province in 2018 was 13 314 yuan, while the per capita disposable income of urban residents in the same period was 31 592 yuan, 2.37 times the former.Therefore, the government should continue to increase investment in "agriculture, rural areas and farmers", strengthen agricultural infrastructure construction, promote and popularize advanced agricultural technology, promote and develop agricultural modernization, and fundamentally increase the income level of rural residents.

(ii)Widening the channels for increasing farmers’ income and improving the income structure.It is recommended to effectively solve the job problem of migrant workers in cities, improve the vocational skills of migrant workers through vocational training, and effectively protect the legal rights and interests of migrant workers, so as to promote the continuous and stable growth of migrant workers’ wage income.Besides, it is recommended to consolidate and improve the basic rural management system, establish an agricultural product reserve system and price adjustment mechanism, encourage and promote farmers to plant cash crops and special agricultural products, so as to ensure the continuous growth of farmers’ income from household business operation.Also, it is recommended to improve the rural financial market and products, enhance the financial awareness of rural residents, and increase farmers’ consumption power through increasing their property income[9].Furthermore, it is recommended to continue to increase the transfer payment to agricultural and rural farmers, reduce the burden on farmers, and stimulate their consumption power with transfer income[10].

(iii)The issue concerning agriculture, rural areas and farmers is a fundamental issue related to the national economy and people’s livelihood.It is required to always take this issue as the top priority of the governments at all levels work.The 19th National Congress of CPC proposed the implementation of rural revitalization strategy.Therefore, governments at all levels should solidly set up the strategic concept of top priority, continue to increase policy support to strengthen agriculture, benefit farmers, and enrich rural areas, actively promote the construction of a new socialist countryside and a well-off society to promote coordinated economic and social development.