4.5 Article

Empirical analysis of the main factors influencing rice harvest losses based on sampling survey data of ten provinces in China

Journal

CHINA AGRICULTURAL ECONOMIC REVIEW
Volume 9, Issue 2, Pages 287-302

Publisher

EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/CAER-03-2016-0036

Keywords

Rice; Food losses; Harvest losses; Marginal effect; Ordered multinomial logistic model

Funding

  1. Fundamental Research Funds for the Central Universities [201513004-6, 2017JDZD01, 2015JDZD01]

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Purpose - In China, a major grain producer, rice losses during harvest cannot be ignored. The purpose of this paper is to assess the extent of rice harvest losses in major grain-producing areas in China by a sampling survey, and to further analyze the main factors influencing rice harvest losses using an ordered multinomial logistic model. Design/methodology/approach - In this study, data were collected using a multi-stage sampling method from ten major rice-producing provinces/regions in China. On this basis, five counties were selected from each of these provinces/regions. In the actual survey, house numbers were randomly selected, and then corresponding farmer households were visited by trained investigators. Findings - The survey found that 56.22 percent of respondents believed that rice harvest losses were 4 percent or lower in China, though there were differences among the provinces. The proportion of family business income, planting scale, mechanization level, timely harvest, and operational meticulousness had negative effects on rice harvest losses. On the other hand, farmers' experience of employment as migrant workers had a positive effect on rice harvest losses. In addition, bad weather and short handedness during harvest significantly increased rice harvest losses. Originality/value - The meaning of rice harvest losses was defined based on previous research findings on the definition of grain harvest losses and the realities in China. The current rice harvest losses in different areas in China were analyzed based on sampling survey data from 957 farmers in ten provinces in China.

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