1,721,106 research outputs found
Comparison of machine learning predictions of subjective poverty in rural China
No full textPurpose
Despite rising incomes and reduction of extreme poverty, the feeling of being poor remains widespread. Support programs can improve well-being, but they first require identifying who are the households that judge their income is insufficient to meet their basic needs, and what factors are associated with subjective poverty.
Design/methodology/approach
Households report the income level they judge is sufficient to make ends meet. Then, they are classified as being subjectively poor if their own monetary income is inferior to the level they indicated. Second, the study compares the performance of three machine learning algorithms, the random forest, support vector machines and least absolute shrinkage and selection operator (LASSO) regression, applied to a set of socioeconomic variables to predict subjective poverty status.
Findings
The random forest generates 85.29% of correct predictions using a range of income and non-income predictors, closely followed by the other two techniques. For the middle-income group, the LASSO regression outperforms random forest. Subjective poverty is mostly associated with monetary income for low-income households. However, a combination of low income, low endowment (land, consumption assets) and unusual large expenditure (medical, gifts) constitutes the key predictors of feeling poor for the middle-income households.
Practical implications
To reduce the feeling of poverty, policy intervention should continue to focus on increasing incomes. However, improvements in nonincome domains such as health expenditure, education and family demographics can also relieve the feeling of income inadequacy. Methodologically, better performance of either algorithm depends on the data at hand.
Originality/value
For the first time, the authors show that prediction techniques are reliable to identify subjective poverty prevalence, with example from rural China. The analysis offers specific attention to the modest-income households, who may feel poor but not be identified as such by objective poverty lines, and is relevant when policy-makers seek to address the “next step” after ending extreme poverty. Prediction performance and mechanisms for three machine learning algorithms are compared
The attraction effect of cleaning air on migrants in China: A comparative analysis with the contribution of wage and house prices
No full texthttp://dx.doi.org/10.13039/501100001809 National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100004147 Tsinghua Universit
Village Inequality in Western China
Full text linkIncreased regional inequality has been a major concern in many emerging economies like China, India, Vietnam and Thailand. However, even a large inequality is observed within the lagging regions. The objective of this paper is to look into what are the sources of within region inequality using the community surveys and a census type of households in Western China. This snapshot view of inequality within and between rural villages in western China is based on a census-type household survey in three administrative villages and a sampling survey of 286 natural villages in the poor province of Guizhou in 2004. In contrast to coastal regions, nonfarm income is distributed unevenly in this inland western region. This acco unts for the largest share of overall income inequality. But agriculture is still the rural peoples major source of livelihood in this particular location. On the expenditure side, health care is one of the most important sources of inequality. Because rural income is strongly related to human capital, the uneven access to health care will translate into a larger income gap in the long run. The analysis based on the natural village survey indicates that income varies widely across villages. Access to infrastructure and markets, education, and political participation explain most of this variation. These findings have important implications on the future development strategy in promoting lagging regions development and poverty reduction. While the overall economic development will be the main instrument to bring the majority poor out of poverty, a targeted approach has become increasingly crucial in helping the poor villages and households. It is critical to understand why these villages and households can not particulate in the growth process and how development programs and various transfer programs help them to overcome the constraints they face.Rural Development, Poverty, Inequality, Public investment, H54, O47, O53, R11, Community/Rural/Urban Development,
Local Public Goods Provision in the Post-Agricultural Tax Era in Rural China
Full text linkThis paper investigates regional differences in local public goods provision in rural area in the 2000s, using large village sample surveys (CHIP 2002 and 2007 surveys, a survey in Ningxia). Focuses are on changes in the coverage of public investment projects, regional differences in the determinants of public investment projects, and changes in the coverage of public services provided by village collectives. The main findings are as follows. First, we confirmed that coverage of public investment projects had increased in the 2000s. Second, in spite of concentration of fiscal administration into county level as one of the pillars of the reform of taxation and local fiscal system, administrative villages still played indispensable roles in local public goods provision. Third, we found that incentive of peasants, financial ability of villages, and incentive of local government affect location decision and budget structure of public investment projects and that direction and strength of such factors were different by regions.Local Public goods, Village, Local Government, Rural China
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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