Earlier this year, the Handbook of Historical Economics, edited by Alberto Bisin and Giovanni Federico was published. The handbook covers a lot of ground, including chapters on resources for work in economic history (historical data and where to find them by Giuliano and Matranga; the use of archeological data in economics by Matranga and Pascali; econometrics in historical work by Valencia Caicedo; and history as evolution by Nunn) as well as topics in historical economics (such as a review of research on religion in economic history by Becker, Rubin and Woessmann). I think the handbook is an incredible resource for students and researchers in this area, and I recommend checking it out if you have the chance!
The chapter I contributed discusses the use of ethnographic and field data in historical economics. I review some of the more common sources of ethnographic data used in work in historical economics, particularly work that is examining the causes or consequences of various cultural practices or traits. I also compile a list of papers that have used these various data sources in economics. The goal is to highlight the benefits of using ethnographic data, particularly in contexts where other historical data are limited and to draw attention to some databases compiled in other disciplines that may be of interest to economists.
Some of the most commonly used ethnographic data sources are the Ethnographic Atlas (Murdock, 1957, 1967) and the related Standard Cross Cultural Survey (Murdock and White, 1969). The Ethnographic Atlas (EA) is an ethnicity level database with pre-industrial cultural characteristics on 1,265 ethnic groups from around the world. It was compiled by Murdock (1967), based on his own reading and coding of available ethnographies. The primary data sources are from various time periods, depending on when reliable data is available. The data set includes variables such as location, major subsistence activities, forms of political organization, and cultural practices.
The Standard Cross Cultural Survey (SCCS) is a sample of 186 ethnic groups, chosen from cultural groupings in the EA (Murdock and White, 1969). While there are fewer groups represented in the SCCS, there are over 2000 variables in the data set.
For work in Africa, the EA is often paired with the Murdock ethnic group boundary map (Murdock, 1959). In the map, Murdock outlines approximations of historical boundaries of ethnic groups as of the nineteenth century. While there are 835 ethnic group boundaries in the Murdock map, there are only 527 ethnic groups represented in the EA for Africa. Thus, matching between the data sets requires making decisions about the correct way to build a concordance, e.g. based on cultural or geographic proximity. One publicly available concordance is from Fenske (2013).
These data sets have been widely used in economics. See for example Gennaioli and Rainer (2007), Nunn and Wantchekon (2011), Alesina, Giuliano and Nunn (2013), Michalopoulos and Papaioannou (2013, 2014), Fenske (2014), Alsan (2015), Fenske (2015), Michalopoulos and Papaioannou (2016), Enke (2019). Bahrami-Rad, Becker and Henrich (2018) includes information on papers published in anthropology using these data sources. See Lowes (2021) for a more complete listing of papers in economics using these data sources.
Despite the wide use of the EA and SCCS, there are of course some potential short-comings of this data. For example, the data are not time varying, so it only represents a description of an ethnic group at a particular point in time. Relatedly, the timing at which ethnic groups were observed varies. Additionally, for some places fewer ethnic groups are represented. A recent validation effort by Bahrami-Rad et al. (2018) suggests that the EA data is indeed correlated with contemporary representative data from the Demographic and Health Surveys. For example, they show a positive correlation between historical characteristics such as breastfeeding duration or patrilocality and present-day outcomes.
Giuliano and Nunn (2018) construct the Ancestral Characteristics Database by augmenting the data in the Ethnographic Atlas with several additional data sources. They add data for groups from Europe and Siberia. They also combine the EA with data from the Ethnologue, on the geographic distribution of languages (Gordon, 2009). Finally, they also include geographic variables. These data are available here.
Although the databases described above are the most commonly used in work in economics regarding historical cultural practices, there are other cultural and ethnographic data sets that may of interest and use to those working in historical economics. I describe some of them briefly below and include links to where you can find more information on them.
Human Relations Area Files (HRAF): HRAF is a collection of ethnographies that has been subject coded at the paragraph level. Approximately 300 cultures are covered in HRAF, and it is searchable by subject (Ember, 2012).
Seshat: Global Hisotory Databank: Seshat is a database of human polities over time (Turchin et al., forthcoming). The idea is to systematically code social and political organization of societies and how they change. It covers 4000 BCE to 1900 CE.
Pulotu: Database of Pacific Religious Beliefs and Practices: Pulotu is a database of Austronesian supernatural beliefs and practices (Watts et al., 2015).
Database of Places, language, culture and environment (D-Place): D-Place is a database with information on geography, language, culture and environment for over 1400 human societies (Kirby et al., 2016). It combines the EA, the Binford Hunter Gatherer data set (Binford, 2001; Binford and Johnson, 2006), the SCCS, and the Western North American Indians data set (Jorgensen, 1980, 1999b,a).
Database of Religious History (DRH): The DRH compiles information on religious traditions (Slingerland and Sullivan, 2017). Data is at the religious group level (rather than the cultural group level).
Alesina, A., Giuliano, P., Nunn, N., 2013. On the origins of gender roles: women and the plough. The Quarterly Journal of Economics 128 (2), 469–530.
Binford, L.R., Johnson, A., 2006. Documentation for Program for Calculating Environmental and Hunter-Gatherer Frames of Reference (ENVCALC2).
Bahrami-Rad, D., Becker, A., Henrich, J., 2018. Tabulated Nonsense? Testing the Validity of the Ethnographic Atlas and the Persistence of Culture. Working Paper. Harvard University.
Ember, C.R., 2012. Leadership in Science and Technology: A Reference Handbook, Vol. 2. Sage, Los Angeles
Enke, B., 2019. Kinship, cooperation, and the evolution of moral systems. The Quarterly Journal of Economics 134 (2), 953–1019.
Fenske, J., 2013. Does land abundance explain African institutions? The Economic Journal 123 (573), 1363–1390.
Fenske, J., 2015. African polygamy: past and present. Journal of Development Economics 117, 58–73.
Giuliano, P., Nunn, N., 2018. Ancestral characteristics of modern populations. Economic History of Developing Regions 33 (1), 1–17.
Handbook of Historical Economics. Edited by Alberton Bisin and Giovanni Federico. Elsevier/Academic Press, April 1st, 2021.
Kirby, K.R., Gray, R.D., Greenhill, S.J., Jordan, F.M., Gomes-Ng, S., Bibiko, H.-J., Blasi, D.E., Botero, C.A., Bowern, C., Ember, C.R., Leehr, D., Low, B.S., McCarter, J., Divale, W., Gavin, M.C., 2016. D-PLACE: a global database of cultural, linguistic and environmental diversity. PLoS ONE 11 (7), e0158391.
Murdock, G.P., 1957. World ethnographic sample. Ethnology 59 (4), 664–687.
Murdock, G.P., 1967. Ethnographic Atlas. University of Pittsburgh Press, Pittsburgh.
Murdock, G.P., White, D.R., 1969. Standard cross-cultural sample. Ethnology 8 (4), 329–369.
Gennaioli, N., Rainer, I., 2007. The modern impact of precolonial centralization in Africa. Journal of Economic Growth 12 (3), 185–234.
Jorgensen, J.G., 1999a. Codebook for western Indians data. World Cultures 19 (2), 144–293.
Jorgensen, J.G., 1999b. An empirical procedure for defining and sampling culture bearing units in continuous geographic areas. World Cultures 10 (2), 139–143.
Nunn, N., Wantchekon, L., 2011. The slave trade and the origins of mistrust in Africa. The American Economic Review 101 (7), 3221–3252.
Michalopoulos, S., Papaioannou, E., 2013. Precolonial ethnic institutions and contemporary African development. Econometrica 81 (1), 113–152.
Michalopoulos, S., Papaioannou, E., 2014. National institutions and subnational development in Africa. The Quarterly Journal of Economics 129 (1), 151–213.
Michalopoulos, S., Papaioannou, E., 2016. The long-run effects of the scramble in Africa. The American Economic Review 106 (7), 1802–1848.
Slingerland, E., Sullivan, B., 2017. Durkheim with data: the database of religious history. Journal of the American Academy of Religion 85 (2), 312–347.
Turchin, P., Whitehouse, H., Francois, P., Hoyer, D., Alves, A., Baines, J., Baker, D., Bartkowiak, M., Bates, J., Bennett, J., Bidmead, J., Bol, P., Ceccarelli, A., Christakis, K., Christian, D., Covey, A., De Angelis, F., Earle, T.K., Edwards, N.R., Feinman, G., Grohmann, S., Holden, P.B., Juliusson, A., Korotayev, A., Kradin, N., Kristinsson, A., Larson, J., Litwin, O., Mair, V., Manning, J.G., Manning, P., Marciniak, A., McMahon, G., Miksic, J., Garcia, J.C.M., Morris, I., Mostern, R., Mullins, D., Oyebamiji, O., Peregrine, P., Petrie, C., Preiser-Kapeller, J., Rudiak-Gould, P., Sabloff, P., Savage, P., Spencer, C., Stark, M., ter Haar, B., Thurner, S., Wallace, V., Witoszek, N., Xie, L., forthcoming. An introduction to seshat: global history databank. Journal of Cognitive Historiography.
Watts, J., Sheehan, O., Greenhil, S.J., Gomes-Ng, S., Atkinson, Q.D., Bulbulia, J., Gray, R.D., 2015. Pulotu: database of Austronesian supernatural beliefs and practices. PLoS ONE 10 (9), e0136783.