Replication Data for: Farmer Differentiation, Inter-Generational Differences and Chemical Fertilizer Reduction Behavior of Farmers in Rural China

Description

This dataset originates from a large-scale field survey of rice-farming households conducted in Jiangxi Province, China, from November 2022 to August 2023. To ensure scientific rigor, a multi-stage stratified random sampling strategy (based on per capita GDP) was employed across 30 counties, yielding 1,345 valid household observations through face-to-face structured interviews. Given Jiangxi's prominent role as a major rice-producing region and its recent policy focus on agricultural green development, this dataset provides a highly representative micro-level foundation. It is primarily used to analyze farmers' green production behaviors, specifically focusing on the reduction of chemical inputs and their environmental and economic effects in agriculture.

Steps to reproduce

Regional Stratification: Classify all counties (including cities and districts) in Jiangxi Province into three tiers (high, medium, and low) based on their per capita GDP. County Sampling: Randomly select 10 counties from each of the three GDP tiers, yielding a total of 30 sample counties. Township and Village Sampling: Within each selected county, randomly sample 2 townships. Subsequently, randomly select 2 villages from each of those townships. Household Sampling: Randomly select 5 to 15 rice-farming households from each sampled village to serve as the target respondents. Field Survey Execution: Conduct face-to-face interviews using a structured questionnaire. (Note: The original survey was conducted between November 2022 and August 2023, distributing 1,500 questionnaires with a 94% collection rate). Data Cleaning and Validation: Screen the collected questionnaires (1,410 total). Exclude any observations with missing or inconsistent key variables to arrive at the final valid sample size (1,345 observations) for empirical analysis.

Institutions

• Zhejiang A & F University

  Zhejiang, Lin’an Shi

Categories

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