10.3886/ICPSR27063.v7 Lee, James Z. Campbell, Cameron D. Inter-university Consortium for Political and Social Research 2010 agricultural production agriculture demographic characteristics disabilities disasters eighteenth century exports family history family structure generations historical data households immigrants imports military rank municipalities nineteenth century occupational status rural population 2010-06-22 2012-11-27 1749 1909 administrative records data; census/enumeration data 27063 7 The China Multi-Generational Panel Dataset - Liaoning (CMGPD-LN) is drawn from the population registers compiled by the Imperial Household Agency (neiwufu) in Shengjing, currently the northeast Chinese province of Liaoning, between 1749 and 1909. It provides 1.5 million triennial observations of more than 260,000 residents from 698 communities. The population mainly consists of immigrants from North China who settled in rural Liaoning during the early eighteenth century, and their descendants. The data provide socioeconomic, demographic, and other characteristics for individuals, households, and communities, and record demographic outcomes such as marriage, fertility, and mortality. The data also record specific disabilities for a subset of adult males. Additionally, the collection includes monthly and annual grain price data, custom records for the city of Yingkou, as well as information regarding natural disasters, such as floods, droughts, and earthquakes. This dataset is unique among publicly available population databases because of its time span, volume, detail, and completeness of recording, and because it provides longitudinal data not just on individuals, but on their households, descent groups, and communities. Further information about this dataset can be found on the <a href="http://www.icpsr.umich.edu/icpsrweb/CMGPD/">CMGPD-LN</a> Web site. Possible applications of the dataset include the study of relationships between demographic behavior, family organization, and socioeconomic status across the life course and across generations, the influence of region and community on demographic outcomes, and development and assessment of quantitative methods for the analysis of complex longitudinal datasets.