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Restoration of Micro Data of John Lossing Buck’s Survey and Analysis of the Inverse Relationship between Yield and Farm Size in Rural China in the 1930’s

Discussion Papers


August 2010


A large scale Chinese agricultural survey was conducted at the direction of John Lossing Buck from 1929 through 1933. At the end of the 1990’s, some parts of the original micro data of Buck’s survey were discovered at Nanjing Agricultural University. An international joint study was begun to restore micro data of Buck’s survey and construct parts of the micro database on both the crop yield survey and special expenditure survey. This paper includes a summary of the characteristics of farmlands and cropping patterns in crop yield micro data that covered 2,102 farmers in 20 counties of 9 provinces.

In order to test the classical hypothesis of whether or not an inverse relationship between land productivity and cultivated area may be observed in developing countries, a Box-Cox transformation test was conducted for functional forms on five main crops of Buck’s crop yield survey. The result of the test shows that the relationship between land productivity and cultivated areas of wheat and barley is linear and somewhat negative; those of rice, rapeseed, and seed cotton appear to be slightly positive. It can be tentatively concluded that the relationship between cultivated area and land productivity are not the same among crops, and the difference of labor intensity and the level of commercialization of each crop may be strongly related to the existence or non-existence of inverse relationships.

Keywords: farm survey, crop yield, farm management
JEL classification: N55, O12, Q12

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Please note that discussion papers are works in various stages of progress and most have not been edited and proofread and may contain errors of fact or judgment. Revised versions of these papers may subsequently appear in more formal publication series. The views expressed in this publication are those of the author(s). The IDE does not guarantee the accuracy of the data included and accepts no responsibility for any consequences arising from its use.