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Purpose: Using survey data from Shandong, Henan and Guizhou provinces of China, the purpose of this paper is to accurately measure the impact of rural residents' financial education on financial literacy. Design/methodology/approach: This paper chooses one province from the Eastern, Central and Western Regions of China, namely, Shandong, Henan and Guizhou, respectively, and 1,565 samples are obtained through a questionnaire survey. First, the paper constructs a financial literacy assessment framework and, then, scores the financial literacy of the respondents. Second, using ordinary least squares, feasible generalized least squares method and forward search method, the paper estimates the impact factors of financial literacy level. To avoid sample selection errors and endogeneity problems, the authors divide the respondents into treatment group (participated in financial education) and control group (non-participating in financial education) and, then, adopt propensity score matching (PSM) to analyze the impact of rural residents' financial education on financial literacy. Findings: The results show that education level and risk level have significant impact on rural residents' participation in financial education, and some unobservable abilities and qualities also affect their participation. Therefore, the process of rural residents' participation in financial education exists, which gives rise to self-selection and endogeneity problems; financial education is promoting rural residents' financial literacy, but the effect of promotion becomes smaller after taking into account sample self-selection and endogenous problems. Rural residents of female, higher age, single, higher education level, higher parental education level, agricultural type, higher family annual per capita income and lower risk level show stronger effects on their financial literacy level, if they participate in financial education. Research limitations/implications: The survey sample was drawn from three provinces randomly but the site selection was not random. The implication is in rural China, financial education has positive effect on residents' financial literacy level but considering the sample self- selection and endogenous nature, its impact becomes smaller. Practical implications: The government should encourage rural residents to participate fully in financial education activities, especially those with a low educational level, low risk preference and mainly engaged in agricultural production. Originality/value: The effect of financial education on financial literacy has not reached a consistent conclusion, and there is fewer quantitative discussion about this issue. The originality of this paper is based on the Organization for Economic Co-operation and Development evaluation index system; this paper constructs the evaluation index system of rural residents' financial literacy in China and uses the PSM method to accurately measure the effect of financial education on financial literacy. [ABSTRACT FROM AUTHOR]

The area of karst terrain in China covers 3.63×106 km2, with more than 40% in the southwestern region over the Guizhou Plateau. Karst comprises exposed carbonate bedrock over approximately 1.30×106 km2 of this area, which suffers from soil degradation and poor crop yield. This paper aims to gain a better understanding of the environmental controls on crop yield in order to enable more sustainable use of natural resources for food production and development. More precisely, four kinds of artificial neural network were used to analyse and simulate the spatial patterns of crop yield for seven crop species grown in Guizhou Province, exploring the relationships with meteorological, soil, irrigation and fertilization factors. The results of spatial classification showed that most regions of high-level crop yield per area and total crop yield are located in the central-north area of Guizhou. Moreover, the three artificial neural networks used to simulate the spatial patterns of crop yield all demonstrated a good correlation coefficient between simulated and true yield. However, the Back Propagation network had the best performance based on both accuracy and runtime. Among the 13 influencing factors investigated, temperature (16.4%), radiation (15.3%), soil moisture (13.5%), fertilization of N (13.5%) and P (12.4%) had the largest contribution to crop yield spatial distribution. These results suggest that neural networks have potential application in identifying environmental controls on crop yield and in modelling spatial patterns of crop yield, which could enable local stakeholders to realize sustainable development and crop production goals. [ABSTRACT FROM AUTHOR]

[Objective] The objective of the paper is to provide the scientific basis for rational fertilization in Jianhe County of Guizhou Province and similar areas. [Method] The effects of soil nutrient indexes(total N .organic matter, available N .available K, available P, total P and total K)on soil fertility are explored by using variation coefficient method, correlation coefficient method and weighted mean method, and then the soil fertility in paddy field and dry' land is evaluated by using improved Nemerow comprehensive evaluation method combined with the weight coefficient mean value of the three methods. [Result] The soil available k in paddy field and total P in dry land were at a lower level, while other nutrient indexes were at a medium-high, high and higher level. The soil available N content in six dry' land sampling sites with different plants was high. Soil total P and available k fluctuate greatly among sampling sites, while organic matter content fluctuates less. The soil available P in fertility factor weighted coefficient of paddy field and dry land was the highest, respectively 0. 2710 and 0. 2358 comparing the mean value of the three weighted method weighted coefficient. The available P is the main factor influencing soil fertility in paddy field and dry' land and soil fertility indexes is 1.52 and 1.63 separately. The soil comprehensive fertility was at a fertile level. [Conclusion] The soil fertility of paddy field and dry land in Jianhe County is at a fertile level, and available P is the main factor influencing soil fertility in paddy field and dry land. The soil N content in paddy field and dry land is high, which can meet the demand of crop production. Therefore, N fertilization should be reduced in production. The soil K content in paddy field is low, and the corresponding fertilization measures should be taken to improve K supply level in paddy field. [ABSTRACT FROM AUTHOR]