Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa July 2015
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Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Stelios Michalopoulos, Louis Putterman and David Weil Brown University, HBS, CEPR and NBER July 2015 University of Warwick Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Research Question I Why Does Stu¤ that Happened in the Past Matter so Much for Current Outcomes? I Old approach: inertia in adjustment of physical/human capital a lá Solow I Sachs et al.: persistent exogenous forces (i.e., geography) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Research Question I Why Does Stu¤ that Happened in the Past Matter so Much for Current Outcomes? I Old approach: inertia in adjustment of physical/human capital a lá Solow I Sachs et al.: persistent exogenous forces (i.e., geography) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation New Literature I New Economics Literature on Persistence (e.g., Spolaore and Wacziarg 2013) I historical events (interacted with geography) =) culture/institutions =) shaping comparative development I persistence of cultural attributes (attitudes towards women - Alesina et al, trust and slave trades - Nunn and Wantchekon, polygyny - Fenske) I persistence of political legacies (Michalopoulos and Papaioannou 2013, 2014, Alsan 2014, Dippel 2014) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Contribution I I Existing literature on persistence looks at I Countries I Country of origin groups (Putterman and Weil, Alesina et al,) I geographic regions, villages I ethnic homelands In this paper we look at individuals belonging to di¤erent ethnic groups within a village Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Contribution I I Existing literature on persistence looks at I Countries I Country of origin groups (Putterman and Weil, Alesina et al,) I geographic regions, villages I ethnic homelands In this paper we look at individuals belonging to di¤erent ethnic groups within a village Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Research Question I How do descendants of pre-colonial agricultural societies perform compared to descendants of "other subsistence" cultures? I agricultural groups versus pastoral ones within the same country I looking at individual-level outcomes I I to isolate the "portable" component of ethnicity we focus on individuals that no longer reside in their ancestral homelands Large literature in the social sciences (e.g., Diamond (1997), Boserup (1965), Richerson et al., 2001) I poses an evolutionary framework where dependence on agriculture provides a comparative advantage in the transition to the modern economy. Existing evidence is mixed. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Research Question I How do descendants of pre-colonial agricultural societies perform compared to descendants of "other subsistence" cultures? I agricultural groups versus pastoral ones within the same country I looking at individual-level outcomes I I to isolate the "portable" component of ethnicity we focus on individuals that no longer reside in their ancestral homelands Large literature in the social sciences (e.g., Diamond (1997), Boserup (1965), Richerson et al., 2001) I poses an evolutionary framework where dependence on agriculture provides a comparative advantage in the transition to the modern economy. Existing evidence is mixed. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Research Question I How do descendants of pre-colonial agricultural societies perform compared to descendants of "other subsistence" cultures? I agricultural groups versus pastoral ones within the same country I looking at individual-level outcomes I I to isolate the "portable" component of ethnicity we focus on individuals that no longer reside in their ancestral homelands Large literature in the social sciences (e.g., Diamond (1997), Boserup (1965), Richerson et al., 2001) I poses an evolutionary framework where dependence on agriculture provides a comparative advantage in the transition to the modern economy. Existing evidence is mixed. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Contribution I Ethnic-speci…c legacies of economic culture have a strong bearing on individual outcomes. I economic culture: the main subsistence activity of your ancestors I Consistent with the idea that intergenerationally vertically transmitted traits in‡uence economic outcomes I Ethnic Inequality I Alesina, Michalopoulos, and Papaioannou (2014) show that ethnic inequality is a strong correlate of underdevelopment I This paper sheds light on the sources of ethnic inequality in Africa Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Contribution I Ethnic-speci…c legacies of economic culture have a strong bearing on individual outcomes. I economic culture: the main subsistence activity of your ancestors I Consistent with the idea that intergenerationally vertically transmitted traits in‡uence economic outcomes I Ethnic Inequality I Alesina, Michalopoulos, and Papaioannou (2014) show that ethnic inequality is a strong correlate of underdevelopment I This paper sheds light on the sources of ethnic inequality in Africa Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Motivation Contribution I Ethnic-speci…c legacies of economic culture have a strong bearing on individual outcomes. I economic culture: the main subsistence activity of your ancestors I Consistent with the idea that intergenerationally vertically transmitted traits in‡uence economic outcomes I Ethnic Inequality I Alesina, Michalopoulos, and Papaioannou (2014) show that ethnic inequality is a strong correlate of underdevelopment I This paper sheds light on the sources of ethnic inequality in Africa Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Pre-colonial Period I Sub-Saharan Africa provides an attractive setting because several hundreds of relatively self-contained ethnic groups pursued di¤erent life-ways as recently as 5 generations ago I Their life-ways were documented by anthropologists in the Ethnographic Atlas, and we can trace contemporary individuals living beyond their ancestors’original ethnic enclaves to their ancestors’ethnic characteristics thanks to self-report of ethnicity in recent surveys. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Pre-colonial Period I Large variation in pre-colonial subsistence patterns I Agricultural Tribes I I Pastoral Tribes I I Tetela in Congo DRC; Bisa in Zambia; Mende in Sierra Leone Samburu, Maasai in Kenya; Sokoto in Nigeria; Afar in Ethiopia Societies dependent on …shing, hunting, gathering I Itsekiri in Nigeria (mostly …shing); Kung in Namibia (mostly gathering); Kindiga in Tanzania (mostly hunting). Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Pre-colonial Period I Large variation in pre-colonial subsistence patterns I Agricultural Tribes I I Pastoral Tribes I I Tetela in Congo DRC; Bisa in Zambia; Mende in Sierra Leone Samburu, Maasai in Kenya; Sokoto in Nigeria; Afar in Ethiopia Societies dependent on …shing, hunting, gathering I Itsekiri in Nigeria (mostly …shing); Kung in Namibia (mostly gathering); Kindiga in Tanzania (mostly hunting). Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Pre-colonial Period I Large variation in pre-colonial subsistence patterns I Agricultural Tribes I I Pastoral Tribes I I Tetela in Congo DRC; Bisa in Zambia; Mende in Sierra Leone Samburu, Maasai in Kenya; Sokoto in Nigeria; Afar in Ethiopia Societies dependent on …shing, hunting, gathering I Itsekiri in Nigeria (mostly …shing); Kung in Namibia (mostly gathering); Kindiga in Tanzania (mostly hunting). Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Pre-Colonial Dependence on Agriculture Pre-Colonial Dependence on Agriculture 86-100% Dependence 76-85% Dependence 66-75% Dependence 56-65% Dependence 46-55% Dependence 36-45% Dependence 26-35% Dependence 16-25% Dependence 6-15% Dependence 0-5% Dependence I . No Information Ü Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Pre-Colonial Dependence on Pastoralism Pre-Colonial Dependence on Pastoralism No Information 0-5% Dependence 16-25% Dependence 26-35% Dependence 36-45% Dependence 46-55% Dependence 56-65% Dependence 6-15% Dependence 66-75% Dependence 76-85% Dependence I . 86-100% Dependence Ü Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns The Argument I Diamond/Esther Boserup’s argument: => early agriculture => fertile ground for the birth of urban industrial societies I Broad patterns consistent with this scheme I Europe, China, India, versus Central Asia, versus Papua New Guinea, Congo DRC I Cross-Country Evidence I Olsson and Hibbs (2004), Putterman (2008), Putterman and Weil (2010) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Main Findings I Individuals tracing ancestry to agricultural groups are better o¤ compared to those of pastoral descent I This is not driven by di¤erences in the location of respondents I we are exploiting within-village variation in the economic outcomes of individuals of di¤erent ethnic backgrounds. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Main Findings I Individuals tracing ancestry to agricultural groups are better o¤ compared to those of pastoral descent I This is not driven by di¤erences in the location of respondents I we are exploiting within-village variation in the economic outcomes of individuals of di¤erent ethnic backgrounds. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns The Argument/Channels I Agricultural groups may have better economic outcomes today because of: I Higher degree of cooperation with Europeans I More concessions from colonizers and post-independence governments I the agricultural mode of production leads to more cooperation and/or increased patience (Galor and Özak) I more patriarchy, and "culture of violence" idea (Nisbett & Cohen, Grosjean) among pastoralists Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns The Argument/Channels I Agricultural groups may have better economic outcomes today because of: I Higher degree of cooperation with Europeans I More concessions from colonizers and post-independence governments I the agricultural mode of production leads to more cooperation and/or increased patience (Galor and Özak) I more patriarchy, and "culture of violence" idea (Nisbett & Cohen, Grosjean) among pastoralists Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Introduction Pre-Colonial Subsistence Patterns Roadmap I Present the Data I Establish the key correlations I Sensitivity Checks and Heterogeneity I Evidence on the possible channels I Investigate the origins of pre-colonial dependence on agriculture and use an IV strategy I Conclude Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Individual-Level Data The Data Sources I Source: Demographic and Health Surveys in Africa I I I 21 Sub-Saharan African countries; 382 groups in the DHS 351,427 respondents between 15 and 64 years old with information on current residence. 2,000 to 34,000 respondents in each country: Out of 351,427 males and females 287,433 were matched to 225 pre-colonial groups on Murdock’s (1959) list. I these 225 ethnic groups map into 187 groups in Murdock’s 1967 Atlas with precolonial traits: I information on the ethnic a¢ liation, current ethnic homeland, religion and occupation of each respondent in the household Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Individual-Level Data The Data Sources I Source: Demographic and Health Surveys in Africa I We focus on education and wealth as indicators of individual economic performance I information on the household wealth: coded on a scale of 1-5 corresponding to the quintiles of wealth distribution for each country. I Education is coded on a scale of 0-5, which are labeled "no education", "incomplete primary", "complete primary", "incomplete secondary", "complete secondary", and "higher". Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Individual-Level Data DHS Location of Respondents ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! !!!! ! ! ! !! ! ! !! !!!!! !!! !! ! ! ! !! ! ! ! ! !! ! ! !! ! ! !!! ! ! !! ! !! ! ! ! ! ! ! !! ! ! ! ! !! ! ! !!! ! ! ! ! ! ! ! !!! ! !!! ! ! !! ! ! ! ! !! !!! ! ! ! ! !!! !! ! ! ! ! ! ! !! ! ! !!!!! !! ! ! ! ! !! ! !! ! !! ! ! ! !! !! ! ! !! !!! !! !!! ! ! ! ! ! ! !! !! ! ! !!! !!! ! ! ! !! ! ! ! ! ! ! ! ! ! !!! ! ! ! ! !! ! ! ! !! !!! ! !!!! ! ! ! ! !! ! ! ! !! !! !!!! !!! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! !!!!! ! !! ! ! ! ! !!! ! ! ! ! !!!! !! ! ! !! !!! ! ! ! !! ! ! ! ! !! !! !! !!! ! ! !! !! ! ! !! !!! ! !! !! ! !! !!!!!!! ! ! !! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! !! !! ! ! ! ! ! ! ! !!! ! ! !!!! ! ! !! ! ! ! ! ! !! !! ! ! ! ! !!! !! ! !!!! !! !! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! !! !! !!! ! !! !! ! !! ! !!!! !!! ! !! ! !! !! !! !! !!! ! ! ! ! ! ! ! ! !!! ! ! ! !!! ! ! !! ! ! 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Location of Respondents in the DHS ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! ! !! ! ! !!! ! ! !! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! !! !!! ! ! !! ! ! !! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! ! ! !! ! ! ! ! ! !! ! ! !! ! !! ! ! ! ! ! ! ! !! ! ! !! !! ! ! ! !! ! ! ! ! ! ! ! !! ! ! !! ! !! ! ! ! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! !! ! !! ! ! ! !!! ! !! ! ! ! !!! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !!! ! ! ! ! ! ! ! ! !! ! ! !!! ! ! !!! !! !! !!! ! !! !!!!!!!! ! !! !! !!! ! ! ! !!! !!! !! ! !! ! !! !! !! !! !! ! !! !! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !!! ! ! ! ! !! !! ! !! ! ! ! !!! !! ! !!!! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! !!! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! !!!! ! !! !!!! !!! !! !! !!! ! !!! ! !! ! ! ! !!! !!! ! !! !! ! ! ! ! ! ! ! ! !! ! ! ! !! !!! !! !! ! !! ! ! !! ! !! ! ! ! ! ! ! ! ! !! !! ! ! ! !!! ! ! ! ! ! ! !! !! !! ! ! ! ! ! ! ! ! !! ! ! ! !! ! ! !!!! !! !!! ! ! !! !! ! ! ! ! !! ! ! !! !!! ! ! ! ! ! ! ! !!!! !! ! ! !! ! ! !! !! !!!! !! ! ! ! ! ! !! !!! ! ! ! !! ! !!! !!! ! ! ! ! !!! ! ! !! ! ! ! ! !! ! ! ! !!! ! ! !! !!!! ! ! ! !! ! ! !! ! ! ! !!!! !! ! ! ! ! ! ! ! !!!! ! ! !! ! ! ! ! ! !! ! !!!! ! ! ! ! !! !! ! ! ! ! ! ! !! ! ! !!!! ! ! !! ! !!! !! ! !!!! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! !!! !! ! ! !! ! ! ! !! ! ! ! ! ! !! ! ! ! !!!! ! ! ! ! !! ! !! ! ! ! ! ! !! ! !! ! !! ! !!! !! ! ! !! ! ! ! !! !! !!! ! ! ! ! ! ! ! !! ! !! !!! !!! ! !! ! ! ! !! !! ! !! !! ! ! ! ! ! !! !! ! !! ! !!! !!! ! ! ! ! ! !! ! ! ! ! ! ! !! !! !! ! ! ! ! ! !! ! ! ! !! ! ! ! !! ! ! !!!! !! ! ! ! ! ! ! ! ! !! ! !! !! ! ! !! ! ! !! ! ! ! !! !!! !!! !! ! ! ! !! !! !! !! ! ! ! ! ! !! !! !! ! ! ! !!! ! ! !! !! ! ! !!! ! !! ! !!! !! ! !! !!! !! ! ! !! ! ! !! ! ! !! ! ! !! !!! ! !!! ! ! ! ! ! !!!!! ! !! ! ! !!!! ! ! ! ! !! ! ! ! ! ! !! ! ! !! ! !! ! ! ! ! ! ! !!! ! ! ! !! ! !! !!! ! ! ! ! !! ! !! ! ! ! ! ! ! ! !! ! !! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! !! !! ! !! ! !! ! !! ! ! !! ! ! ! ! ! ! ! ! !! ! !! !!!! ! ! !!! ! !! !! ! ! ! ! ! ! ! !! ! ! ! ! ! !! !! ! !! ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! !!!! ! ! ! !! ! ! !! ! ! !! ! ! !! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! !!! ! ! !! ! ! ! ! ! ! !!! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !!! !! ! ! ! ! ! ! ! ! ! ! ! !! !! !! !! ! ! ! !! ! ! !! !! !! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! !!! !! ! ! ! ! ! ! ! ! ! ! ! ! !!! ! !! !! ! !! ! ! !! ! !! ! !! ! ! !!! ! ! ! ! ! ! !! !! ! ! ! ! ! ! ! !!! ! ! ! ! ! !! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! !!! ! !! ! !! !! ! ! !! ! ! ! !! ! ! ! ! ! !! ! !! !! ! ! ! ! !!! !! ! ! ! !! !! !! ! ! ! ! ! ! ! ! !!!! ! ! ! ! ! ! ! !! ! !! !! ! ! !! !! !! ! ! ! ! !! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! Ü ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! Boundaries of African Countries I . ! !! ! ! ! ! ! ! ! ! ! Villages in the DHS ! ! ! ! ! ! ! ! !! ! !!! ! ! ! !! !! ! ! ! !! ! ! !! ! !! ! ! ! !! ! ! !!!! !! !! ! ! !! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! !! ! ! ! !! !! !! !! ! ! !!!!! !!!!! !! ! !! ! !! ! !! ! !! ! !! ! ! !!! ! ! ! !!! ! !!! ! !!! ! !! ! ! ! !! !! ! ! ! !! ! !! ! ! ! ! !! ! ! ! !!! !!! ! ! ! ! !! ! ! ! ! ! ! !! !! ! ! ! ! ! !! ! ! ! !!!! !!! ! ! ! ! ! ! !!! !! ! !!! !!!! !! ! ! ! ! !!!! ! ! ! ! !!!!!! !! !!! ! !!!! !! ! !!!! !!! ! ! ! ! !!!! !!!! !! ! ! ! ! ! !!!! ! !! ! ! ! !!! ! !! !!!! ! !! ! !!!!! ! ! !!! !! ! !! ! ! ! ! ! ! ! !!!! ! ! !! ! ! ! !!! !! !!! ! ! ! ! !! ! !!!! !! !! !!! ! !! ! ! !!! !! ! !! ! ! ! !! !!! !! ! ! ! ! !!!!!!! ! ! !! !!! ! ! !! ! ! ! !! ! !! ! ! ! !! ! !!! ! ! ! !! ! ! ! ! ! ! ! !!!!!! ! ! ! ! ! ! ! !!! ! ! ! ! !! !! ! ! !! ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! !!! !! !!! ! !! ! !! ! !! ! ! ! ! !! ! ! ! ! !!! ! !! ! !! !! !! ! !!! !!! ! ! !! ! !!! !! ! ! !! ! !!! !! ! ! !!! ! ! ! !! ! ! ! ! ! ! ! !! !! ! ! ! !! !! ! ! ! ! !! ! ! !!! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! !!! ! ! ! ! !! ! ! ! ! ! ! !!! ! ! !! ! ! !! ! ! !!!! !!!! ! !!!!!! ! !!!!! ! ! !! !! ! ! ! !! ! ! ! ! !!! ! !! ! !! ! ! ! ! ! !! !! !! ! ! ! ! ! ! ! !! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! !! ! ! !! ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! !! ! ! ! ! ! !! ! !! ! ! ! !! ! !!! ! ! ! ! ! ! ! !! ! !! ! ! ! !! !! ! ! ! !!! ! ! !!!! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! !! !! ! ! !!! !! !! ! ! ! !! ! ! ! ! !! ! !!!! !! ! ! ! !! ! !! !! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! !! !! ! !!!!! ! ! ! !! ! ! !! ! !! ! !! ! ! ! ! ! !!! ! ! !! ! !! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! ! !!! !! ! !! ! ! !! !! !!!!! ! ! ! ! ! ! !!! ! ! ! !!!! !! !!! ! ! ! ! ! !! ! !! !!!! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Ethnicity-Level Data Pre-Colonial Ethnic Traits George Peter Murdock’s (1967) Ethnolinguistic Atlas I information on 534 groups in Africa before colonization I variables on the economic structure, ethnic cultural traits (monogamy, polygyny), institutions (political centralization, slavery), societal structure (class strati…cation), etc. I we focus on: I The subsistence type (i.e., dependence on agriculture, pastoralism, hunting/gathering/…shing. etc. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Ethnicity-Level Data Underlying Data on Subsistence Type I Main form of subsistence: I I I I I agriculture (84.1%) pastoralism (7.4%) agriculture and pastoralism equally (7.8%) agriculture and …shing equally (0.9%) Only 17 individuals for whom hunting, …shing, or gathering was the main activity (Mbuti in Congo DRC) I Subsistence shares coded 0-9 correspond to 0-5%, 6-15%, 16-25%, .... 85-100% I Unweighted means: agriculture 5.9, pastoralism 2.3, gathering 0.32, hunting 0.70, …shing 0.76. I I I Among "mostly agriculture" mean agriculture is 6.27 (S.D. 1.03) Among "mostly pastoralism" mean pastoral is 6.32 (S.D. 1.55) We collapse hunting/…shing/gathering to a single category Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Ethnicity-Level Data How Was the Matching Done? Method same name Afrobarometer Ethnologue / Joshua Project Other Not Matched I Percent 48.4 4.4 19.1 9.4 18.7 We also match individuals’current residence to the traditional tribal homelands of Murdock’s Map in 1959 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Analysis What do we Look at? I Agricultural groups reside in regions that are more conducive to agriculture (more on this below). I I So, exploiting across-individuals across-ethnicity variation picks up both location-speci…c di¤erences as well as portable ethnic-speci…c traits. To uncover the importance of portable ethnic-speci…c traits we exploit within-village across-ethnicity variation in pre-colonial economic traits. I Leveraging the presence of respondents outside their ancestral ethnic homelands. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Analysis What do we Look at? I Agricultural groups reside in regions that are more conducive to agriculture (more on this below). I I So, exploiting across-individuals across-ethnicity variation picks up both location-speci…c di¤erences as well as portable ethnic-speci…c traits. To uncover the importance of portable ethnic-speci…c traits we exploit within-village across-ethnicity variation in pre-colonial economic traits. I Leveraging the presence of respondents outside their ancestral ethnic homelands. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Analysis Within-Current Ethnic Homeland Variation ! !! !! ! ! ! DZING MBALA !! BUNDA LELE ! ! ! ! ! ! PENDE LUWA ! TETELA !KUBA !! ! !! YAKA ! !! ! ! NYAMWEZI SONGE ! !! ! LULUA ! ! ! !! ! ! ! ! ! ! ! !! !MBAGANI ! ! ! ! ! ! ! ! ! PIMBWE LUBA LUNDA ! ! BENDE KONONGO HOLOHOLO ! ! !! ! ! ! ! TURU ! BUYE !! CHOKWE IRAMBA HA !! ! ! ! ! ! !! SONGOLA ! ! SAGARA HEHE SANGU MBUNGA TABWA ! ! SAFWA NDAMBA ! !!!! POGORO ! ! ! LUNGU ! NYAKYUSA ! BENA ! ! !!! IWA ! SHILA!! ! !! !!! !!! NGINDO KINGA !! ! !! ! ! ! !! ! LAMBYA ! ! !! ! ! ! ! ! ! KISI !! LUAPULA ! ! ! !!! ! ! FIPA ! ! ! !! ! !! ! ! ! ! ! ! ! ! ! MAGWANGARA ! ! ! ! BEMBA ! ! ! ! TUMBUKA !!! !! !!! ! ! !! ! ! ! ! ! ! ! ! !! ! !! ! MATENGO !!! ! ! ! !! ! SENGA ! ! ! ! ! !!! ! ! !! ! ! ! !! ! ! AUSHI !UNGA ! ! ! ! ! ! !! ! ! ! ! !! ! ! !!!!! ! !! ! MOMBERA !!! ! !! ! LUIMBE ! !! NYASA ! !! !!! LUVALE !! ! ! !! ! ! ! ! ! ! ! !! ! ! ! !!! ! !!! ! YAO! ! ! ! LAMBA ! !!!! ! !! BISA ! ! ! ! ! ! !! ! ! ! !!!!!! ! ! !! ! !! ! ! ! ! ! ! ! ! !KAONDE ! ! ! ! ! ! ! ! ! ! ! LUCHAZI ! ! !! ! !! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !!! ! ! ! !! ! !! !! ! ! ! !! !! ! !! ! ! ! ! ! ! ! ! !! ! !!! ! ! ! ! ! ! !! !! ! !! MPEZENI ! ! ! ! ! ! LALA ! ! !! ! !! !! !! ! ! !! !! ! ! ! LUKOKWE ! ! !! !!! ! ! ! ! !! ! ! !! ! !! MAKUA ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! NGONYELU !!! !! !!!!! ! ! ! ! ! ! !!! ! !! !!! ! ! ! ! !! ! !! !! ! ! !!! ! ! !! ! ! CHEWA !!!!!!!!! ! !! ! ! GOMANI !! ! !! ! ! ! !! ! ! !! ! ! !!! ! !! !! !! ! MBUNDA ! !! ! !!!! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !!!!! !!! !!! ! ! ! ! !! !! ! NKOYA ! !! !LENJE! ! ! !! ! ! ! ! ! ! ! ! ! !! ! !! !!! !! ! ! ! ! ! !! NSENGA !! ! ! ! ! ! !!! !! !! !! !! ! !! ! ! !! ! ! ! !! ! ! ! ! !! !! ! ! !! ! ! ! LOZI ! ! !! ! ! ! ! ! ! ! !! ! ! !! ! !! ! MBWELA ! ! ! ! !! ! ! ! ! !! !! ! ! ! ! !!!! ! ! ! ! !! MASHASHA ! ! !! KUNDA ! ! ! ! ! ! ! ! ! ! ! ! !!! ! !!! ! !! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ILA ! ! ! ! ! !! ! ! !! ! ! ! ! ! ! ! ! ! ! ! NYANJA ! ! ! ! !! ! ! ! ! !! ! LOMWE ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !!! !! ! ! !! ! ! ! ! ! ! ! ! !!! !! ! ! ! ! ! ! !! ! ! ! ! ! !! !!! !! !! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! !! ! MASHI ! ! !! !! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! TOTELA ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! !! ! ! TONGA ! ZIMBA ! ! !! ! ! ! ! ! ! ! ! ! KOREKORE ! ! ! ! !! ! ! TAWARA ! !CHUABO ! KWANGARE MBUKUSHU ! !!! ! ! !!!! ! !! ! !! !! ! !! NUKWE! ! !! !! ! SUBIA ! ! !! !! ! !!! ! !! ! ! ! ZEZURU ! !! !! ! ! SENA! !! !! ! ! ! !! ! ! ! !!! MANYIKA ! HIECHWARE NDEBELE ! KOBA ! KUNG !! !! ! !! ! ! !! !! !! !! ! !! !! ! ! ! NDEMBU ! !! ! ! Current Location of Respondents Boundaries of African Countries I . GOGO KIMBU YEKE ! ! SONGO ! RANGI MASAI SANDAWE ! Villages in the DHS Ü Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Analysis How Many Are Outside their Homelands I 40% of respondents live within their ancestral homelands. I 7% live within 10 kilometers of their respective ethnic border. I I Given the inherent error in the pre-colonial mapping of ethnicities’ boundaries (as well as the fact that DHS perturbs the village coordinates by 5-10 kilometers) we consider these guys as "non-movers" I 79% of the remaining 61% resides between 10 and 500 kilometers away from the border of their homeland. We use the term "mover" to denote those individuals currently residing out of their ancestral homelands Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Analysis Mover and Urban/Rural Residence Rural Urban Total Non-Mover 71,323 Row Pct. 0.72 Col Pct. 0.43 27,393 0.28 0.31 98,716 1.00 0.38 Mover Row Pct. Col Pct. 95,650 0.61 0.57 62,203 0.39 0.69 157,853 1.00 0.62 Total Row Pct. Col Pct. 166,973 0.65 1.00 89,596 0.35 1.00 256,569 1.00 1.00 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Analysis Within-Current Ethnic Homeland Variation I I How much of the individual variation in education and wealth may be explained by: I living in a given country I residing in a given ethnic homeland I identifying with a given ethnic group (country FE regression) (Map FE regression) (Murdock Atlas FE regression) We are interested in the variation explained by belonging to a given ethnicity over and above the role of the ethnic location (country or ethnic homeland). Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Analysis Within-Current Ethnic Homeland Variation I I How much of the individual variation in education and wealth may be explained by: I living in a given country I residing in a given ethnic homeland I identifying with a given ethnic group (country FE regression) (Map FE regression) (Murdock Atlas FE regression) We are interested in the variation explained by belonging to a given ethnicity over and above the role of the ethnic location (country or ethnic homeland). Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Analysis What do Fixed E¤ects Only Regressions Tell Us? R^2 from FE Regressions All Education All Wealth Movers Education Movers Wealth Country FE 0.163 0.013 0.149 0.035 Homeland FE 0.306 0.249 0.308 0.32 Ethnicity FE 0.268 0.152 0.261 0.204 Country-Ethnicity FE 0.286 0.165 0.286 0.219 Country-Homeland FE 0.306 0.249 0.308 0.32 Country-Homeland FE & Country-Ethnicity FE 0.331 0.285 0.343 0.364 Observations 285,218 269,992 154,694 146,158 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Baseline Estimating Equation Empirical Speci…cation yi ;e;h;c = a + Age + hgfe + ah;c + "i ;e;h;c I yi ;e;h;c : economic outcomes of individual i belonging to ethnicity e living in homeland h in country c. I Age : pre-colonial dependence on agriculture of ethnicity e. I hgf : pre-colonial dependence on hunting/gathering/…shing of ethnicity e. I ah;c : vector of country-ethnic homeland FE. I Cluster at the ethnicity dimension Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Baseline Estimating Equation Within-Current Ethnic Homeland Variation ! !! !! ! ! ! DZING MBALA !! BUNDA LELE ! ! ! ! ! ! PENDE LUWA ! TETELA !KUBA !! ! !! YAKA ! !! ! ! NYAMWEZI SONGE ! !! ! LULUA ! ! ! !! ! ! ! ! ! ! ! !! !MBAGANI ! ! ! ! ! ! ! ! ! PIMBWE LUBA LUNDA ! ! BENDE KONONGO HOLOHOLO ! ! !! ! ! ! ! TURU ! BUYE !! CHOKWE IRAMBA HA !! ! ! ! ! ! !! SONGOLA ! ! SAGARA HEHE SANGU MBUNGA TABWA ! ! SAFWA NDAMBA ! !!!! POGORO ! ! ! LUNGU ! NYAKYUSA ! BENA ! ! !!! IWA ! SHILA!! ! !! !!! !!! NGINDO KINGA !! ! !! ! ! ! !! ! LAMBYA ! ! !! ! ! ! ! ! ! KISI !! LUAPULA ! ! ! !!! ! ! FIPA ! ! ! !! ! !! ! ! ! ! ! ! ! ! ! MAGWANGARA ! ! ! ! BEMBA ! ! ! ! TUMBUKA !!! !! !!! ! ! !! ! ! ! ! ! ! ! ! !! ! !! ! MATENGO !!! ! ! ! !! ! SENGA ! ! ! ! ! !!! ! ! !! ! ! ! !! ! ! AUSHI !UNGA ! ! ! ! ! ! !! ! ! ! ! !! ! ! !!!!! ! !! ! MOMBERA !!! ! !! ! LUIMBE ! !! NYASA ! !! !!! LUVALE !! ! ! !! ! ! ! ! ! ! ! !! ! ! ! !!! ! !!! ! YAO! ! ! ! LAMBA ! !!!! ! !! BISA ! ! ! ! ! ! !! ! ! ! !!!!!! ! ! !! ! !! ! ! ! ! ! ! ! ! !KAONDE ! ! ! ! ! ! ! ! ! ! ! LUCHAZI ! ! !! ! !! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !!! ! ! ! !! ! !! !! ! ! ! !! !! ! !! ! ! ! ! ! ! ! ! !! ! !!! ! ! ! ! ! ! !! !! ! !! MPEZENI ! ! ! ! ! ! LALA ! ! !! ! !! !! !! ! ! !! !! ! ! ! LUKOKWE ! ! !! !!! ! ! ! ! !! ! ! !! ! !! MAKUA ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! NGONYELU !!! !! !!!!! ! ! ! ! ! ! !!! ! !! !!! ! ! ! ! !! ! !! !! ! ! !!! ! ! !! ! ! CHEWA !!!!!!!!! ! !! ! ! GOMANI !! ! !! ! ! ! !! ! ! !! ! ! !!! ! !! !! !! ! MBUNDA ! !! ! !!!! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !!!!! !!! !!! ! ! ! ! !! !! ! NKOYA ! !! !LENJE! ! ! !! ! ! ! ! ! ! ! ! ! !! ! !! !!! !! ! ! ! ! ! !! NSENGA !! ! ! ! ! ! !!! !! !! !! !! ! !! ! ! !! ! ! ! !! ! ! ! ! !! !! ! ! !! ! ! ! LOZI ! ! !! ! ! ! ! ! ! ! !! ! ! !! ! !! ! MBWELA ! ! ! ! !! ! ! ! ! !! !! ! ! ! ! !!!! ! ! ! ! !! MASHASHA ! ! !! KUNDA ! ! ! ! ! ! ! ! ! ! ! ! !!! ! !!! ! !! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ILA ! ! ! ! ! !! ! ! !! ! ! ! ! ! ! ! ! ! ! ! NYANJA ! ! ! ! !! ! ! ! ! !! ! LOMWE ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !!! !! ! ! !! ! ! ! ! ! ! ! ! !!! !! ! ! ! ! ! ! !! ! ! ! ! ! !! !!! !! !! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! !! ! MASHI ! ! !! !! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! TOTELA ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! !! ! ! TONGA ! ZIMBA ! ! !! ! ! ! ! ! ! ! ! ! KOREKORE ! ! ! ! !! ! ! TAWARA ! !CHUABO ! KWANGARE MBUKUSHU ! !!! ! ! !!!! ! !! ! !! !! ! !! NUKWE! ! !! !! ! SUBIA ! ! !! !! ! !!! ! !! ! ! ! ZEZURU ! !! !! ! ! SENA! !! !! ! ! ! !! ! ! ! !!! MANYIKA ! HIECHWARE NDEBELE ! KOBA ! KUNG !! !! ! !! ! ! !! !! !! !! ! !! !! ! ! ! NDEMBU ! !! ! ! Current Location of Respondents Boundaries of African Countries I . GOGO KIMBU YEKE ! ! SONGO ! RANGI MASAI SANDAWE ! Villages in the DHS Ü Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Benchmark Results Table 2. Benchmark - DHS Regressions within Ethnic Homelands (All Individuals) VARIABLES agriculture gather/hunt/fish 1 2 3 4 Education Education Education Education Simple Controls Country FE Ethnic HomelandCountry FE Occupation FE 6 Wealth 7 Wealth 8 Wealth 0.2271*** (0.0459) 0.1585*** (0.0495) 0.1808*** (0.0338) 0.0655*** (0.0250) Yes Yes Yes No 0.0980*** (0.0230) 0.0470*** (0.0159) 1.6290*** (0.0474) Yes No 0.0984*** (0.0228) 0.0512*** (0.0156) 1.4284*** (0.0486) Yes No 0.2337*** (0.0432) 0.2095*** (0.0547) 0.1498*** (0.0259) 0.1026*** (0.0214) Yes Yes Yes No 0.1034*** (0.0212) 0.0918*** (0.0200) 0.9199*** (0.0357) Yes No No Yes Yes Yes No Yes Yes Yes No No No Yes No No No Yes urban 0.1011*** (0.0191) 0.0911*** (0.0185) 0.7079*** (0.0292) Yes No 5 Wealth Observations 285,155 285,155 285,155 285,155 269,929 269,929 269,929 269,929 R-squared 0.239 0.350 0.418 0.493 0.056 0.266 0.488 0.515 Standard errors in parentheses are clustered at the ethnicity level; simple controls include age, age squared, a female dummy, and a mover dummy; *** p<0.01, ** p<0.05, * p<0.1 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Within-Village Variation I So far, looking within ethnic homelands we exploit both within-village/town/city as well as cross-village variation. I Is the pattern similar if we exploit within-village across-individuals variation? yi ;e;v ;c = a + Age + hgfe + av ;c + "i ;v ;c I av ;c : vector of 8,236 village FE. I Caveat: the more one zooms in the more pressing become issues of sorting and segregation by income/education Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Within-Village Variation I So far, looking within ethnic homelands we exploit both within-village/town/city as well as cross-village variation. I Is the pattern similar if we exploit within-village across-individuals variation? yi ;e;v ;c = a + Age + hgfe + av ;c + "i ;v ;c I av ;c : vector of 8,236 village FE. I Caveat: the more one zooms in the more pressing become issues of sorting and segregation by income/education Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Let’s Zoom in on a Vilage in the Tabwa Homeland-Zambia Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Who Lives in this Village? Ethnicities of Respondents bemba: 70% of ancestral agriculture kaonde: 50% of ancestral agriculture I luba: 40% of ancestral agriculture Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence What is the Education of the Individuals? ( ! luba bemba ( ! bemba bemba ( ! ! ( luba ( ! bemba ( ! ( ! bemba bemba ( ! Education of Each Respondent ( ! I No Education ( ! Incomplete Primary ( ! Complete Primary ( ! Incomplete Secondary kaonde ( ! ( ! luba Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Benchmark Speci…cations with Village FE Table3. Benchmark: DHS Regressions within Villages/Towns (All Individuals) 1 2 3 4 5 6 VARIABLES Education Education Education Wealth Wealth Wealth agriculture gather/hunt/fish urban Simple Controls Ethnic HomelandCountry FE Coordinates FE Occupation FE 0.1034*** (0.0212) 0.0918*** (0.0200) 0.9199*** (0.0357) 0.0731*** (0.0147) 0.0708*** (0.0155) 0.0694*** (0.0128) 0.0681*** (0.0140) 0.0980*** (0.0230) 0.0470*** (0.0159) 1.6290*** (0.0474) 0.0394*** (0.0073) 0.0179** (0.0073) 0.0384*** (0.0071) 0.0193*** (0.0070) Yes Yes Yes Yes Yes Yes Yes No No Yes No No No Yes Yes No Yes Yes No No Yes No No Yes Observations 285,155 285,155 285,155 269,929 269,929 269,929 R-squared 0.418 0.506 0.559 0.488 0.676 0.681 Standard errors in parentheses are clustered at the ethnicity level; simple controls include age, age squared, a female dummy, and a mover dummy; Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Breaking the Components of HGF Table3. Benchmark: DHS Regressions within Villages/Towns (All Individuals) 1 2 3 4 5 6 VARIABLES Education Education Education Wealth Wealth Wealth agriculture gathering 0.1036*** 0.0763*** 0.0725*** (0.0216) (0.0157) (0.0140) 0.0526* 0.0166 0.0167 (0.0311) (0.0227) (0.0197) 0.0983*** (0.0236) -0.0143 (0.0284) 0.0406*** (0.0079) -0.0071 (0.0107) 0.0397*** (0.0078) -0.0042 (0.0102) 0.0268* (0.0152) 0.0294** (0.0149) hunting 0.1058*** 0.0953*** 0.0922*** 0.0683** (0.0326) (0.0263) (0.0243) (0.0320) fishing 0.1041*** 0.0889*** 0.0846*** 0.0666*** 0.0276*** 0.0275*** urban 0.9201*** (0.0260) (0.0215) (0.0193) (0.0358) Simple Controls Ethnic HomelandCountry FE Coordinates FE Occupation FE Yes (0.0220) (0.0088) (0.0083) Yes Yes 1.6292*** (0.0474) Yes Yes Yes Yes No No Yes No No No Yes Yes No Yes Yes No No Yes No No Yes Observations 285,155 285,155 285,155 269,929 269,929 269,929 R-squared 0.418 0.507 0.559 0.489 0.676 0.681 Standard errors in parentheses are clustered at the ethnicity level, simple controls include age, Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Using the Mostly Categories Benchmark: DHS Regressions within Villages/Towns with Mostly Categories 3 4 5 6 VARIABLES Education Wealth Wealth Wealth Mostly Agriculture 0.1518*** (0.0567) -0.0191 (0.0592) 0.3144*** (0.1170) 0.0852 (0.1214) -1.7948*** (0.1166) 1.6337*** (0.0472) 0.1208*** (0.0389) 0.0294 (0.0421) 0.1150*** (0.0362) 0.0211 (0.0399) Simple Controls Yes Yes Yes Yes Ethnic HomelandCountry FE Coordinates FE No Yes No No Yes No Yes Yes Occupation FE Yes No No Yes Mixed Dependence Mostly Hunting urban Observations 285,155 269,929 269,929 269,929 R-squared 0.559 0.488 0.676 0.681 Standard errors in parentheses are clustered at the ethnicity level, simple controls include age, age squared, a female dummy, and a mover dummy. Omitted category Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Preliminary Evidence Using the Afrobarometer Surveys Table 14: Ancestral Lifeways and Education in Afrobarometer 1 VARIABLES Education agriculture gather/hunt/fish 0.0471** (0.0184) 0.0227 (0.0180) Yes Yes Simple Controls Coordinates FE 0.535 R-squared 21578 Observations Standard errors in parentheses are clustered at the Atlas level; Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Heterogeneity In‡uence of Ancestral Traits By Occupation-Location I Are descendants of pre-colonial farmers better o¤ because of being more productive in farming-related occupations? I Is the di¤erence between descendants of pre-colonial farmers and other a re‡ection of di¤erential productivity of farmers in rural versus urban places? I Is the pattern driven by a speci…c country? I Is the pattern driven by individuals that recently migrated? Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Heterogeneity In‡uence of Ancestral Traits By Occupation-Location I Are descendants of pre-colonial farmers better o¤ because of being more productive in farming-related occupations? I Is the di¤erence between descendants of pre-colonial farmers and other a re‡ection of di¤erential productivity of farmers in rural versus urban places? I Is the pattern driven by a speci…c country? I Is the pattern driven by individuals that recently migrated? Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Heterogeneity Results Table 4: Heterogeneity by Occupation and Location 1 2 Education Education VARIABLES agriculture gather/hunt/fish Simple Controls Coordinates FE Farming-Related Non-Farming Related 0.0515*** (0.0106) 0.0416*** (0.0113) Yes Yes 0.0727*** (0.0233) 0.0791*** (0.0224) Yes Yes 3 Education 4 Education Urban Rural 0.0764*** (0.0196) 0.0849*** (0.0208) Yes Yes 0.0703*** (0.0114) 0.0550*** (0.0116) Yes Yes 5 Wealth 6 Wealth Farming-Related Non-Farming Related 0.0431*** (0.0098) 0.0219** (0.0101) Yes Yes 0.0390*** (0.0077) 0.0222*** (0.0074) Yes Yes 7 Wealth 8 Wealth Urban Rural 0.0206*** (0.0055) 0.0095 (0.0066) Yes Yes 0.0645*** (0.0109) 0.0278*** (0.0096) Yes Yes Observations 97,599 101,565 97,702 187,453 92,156 94,685 92,726 177,203 R-squared 0.497 0.504 0.390 0.500 0.483 0.718 0.613 0.476 Standard errors in parentheses, clustered at the ethnicity level. Simple controls include age, age squared, a female dummy, and a mover dummy; Farming-related industries include self-employed agriculture, agricultural employee, forest, breeding, hunting and fishing. Non-farming related industries include professional, technical, managerial positions, clerical positions, sales, household and domestic, services, skilled manual, and unskilled manual. Not working individuals are excluded. *** p<0.01, ** p<0.05, * p<0.1 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Heterogeneity In‡uence of Ancestral Agriculture by Country I For 10-14 out of the 20 countries (depending on the speci…cation) the in‡uence of ancestral dependence on agriculture is positive and signi…cant (for only one country it is negative and insigni…cant). Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Heterogeneity Recent Migration I Who is more likely to have moved in life? I one may worry that the pattern is driven by those of pastoral background having recently left their homelands. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Heterogeneity Who is more likely to have moved in life? Table 5. Determinants of Migration VARIABLES agriculture gather/hunt/fish Simple Controls Coorrdinates FE Occupation FE Observations R-squared 1 mover 2 mover 3 moved_in_life 4 moved_in_life -0.0465** -0.0464** 0.0052 0.0049 (0.0212) (0.0211) (0.0052) (0.0050) -0.1179*** -0.1177*** -0.0062 -0.0061 (0.0254) (0.0253) (0.0053) (0.0051) Yes Yes Yes Yes Yes Yes Yes Yes No Yes No Yes 285,163 0.768 285,163 0.768 188,268 0.229 188,268 0.233 Standard errors in parentheses are clustered at the ethnicity level; Simple controls include age, age squared, a female dummy, and a mover dummy; Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Heterogeneity Individuals that Did not Move in Life I Are di¤erences in economic performance driven by di¤erences in the number of years since people have left their original site of residence? I Partial Solution I Flexibly Account for when Each Individual Moved in Her Current Residence Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Heterogeneity Accoounting for When one Moved DHS Regressions within Villages/Towns (All Individuals) Controlling for How Long Each Individual Resides in her Current Location VARIABLES agriculture gather/hunt/fish urban Simple Controls Ethnic HomelandCountry FE Coordinates FE Occupation FE Observations R-squared 1 2 3 Education Education Education 4 Wealth 5 Wealth 6 Wealth 0.1307*** (0.0199) 0.1138*** (0.0212) 0.8363*** (0.0322) 0.0899*** (0.0158) 0.0781*** (0.0196) 0.0889*** (0.0145) 0.0786*** (0.0185) Yes Yes Yes Yes Yes Yes Yes No No Yes No No No Yes Yes No Yes Yes No No Yes No No Yes 192,367 0.441 192,367 0.525 192,367 0.568 0.0771*** 0.0211*** 0.0204*** (0.0164) (0.0080) (0.0077) 0.0490*** 0.0059 0.0071 (0.0156) (0.0093) (0.0086) 1.5770*** (0.0629) 177,176 0.482 177,176 0.665 177,176 0.670 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Selection into Migration Are Non-Autochthonous Di¤erent? I By exploiting within-ethnic-homeland variation we leverage the presence of movers. I Of course, movers are a selected sample. I Does being a mover co-vary with the ancestral subsistence type? I remember is mover is someone that resides outside his ancestral ethnic homeland Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Selection into Migration Who is More Likely to Live Outside her Homeland? Table 5. Determinants of Migration VARIABLES agriculture gather/hunt/fish Simple Controls Coorrdinates FE Occupation FE Observations R-squared 1 mover 2 mover 3 moved_in_life 4 moved_in_life -0.0465** -0.0464** 0.0052 0.0049 (0.0212) (0.0211) (0.0052) (0.0050) -0.1179*** -0.1177*** -0.0062 -0.0061 (0.0254) (0.0253) (0.0053) (0.0051) Yes Yes Yes Yes Yes Yes Yes Yes No Yes No Yes 285,163 0.768 285,163 0.768 188,268 0.229 188,268 0.233 Standard errors in parentheses are clustered at the ethnicity level; Simple controls include age, age squared, a female dummy, and a mover dummy; Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Selection into Migration Who is More Likely to Live Outside his Ancestral Homeland? I Concern: Individuals of agricultural ethnic background are more positively selected than individuals of pastoral background. I Finding that economic performance of movers changes by the ancestral subsistence economy has a dual interpretation I Di¤erential Selection into migration I Di¤erential portability of ethnic-speci…c skills outside the ancestral homeland ethnic homeland. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Selection into Migration Who is More Likely to Live Outside his Ancestral Homeland? I Concern: Individuals of agricultural ethnic background are more positively selected than individuals of pastoral background. I Finding that economic performance of movers changes by the ancestral subsistence economy has a dual interpretation I Di¤erential Selection into migration I Di¤erential portability of ethnic-speci…c skills outside the ancestral homeland ethnic homeland. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Selection into Migration Results Table 6. Effect of Differential Selection into Migration VARIABLES agriculture gather/hunt/fish mover mover X agric mover X ghf Simple Controls Country FE Occupation FE (1) Education (2) Education (3) Wealth (4) Wealth 0.2808*** -0.0607 0.2817*** -0.0683 0.7465** -0.3505 -0.0571 -0.0515 -0.1087** -0.0482 0.2711*** -0.0543 0.2748*** -0.0638 0.7812** -0.3282 -0.0731 -0.0482 -0.1156*** -0.0442 0.2408*** -0.057 0.1723*** -0.0586 0.4978 -0.3454 -0.0184 -0.0445 -0.0202 -0.0553 0.2351*** -0.0494 0.1793*** -0.05 0.5583* -0.3087 -0.04 -0.0398 -0.037 -0.0473 Yes Yes No Yes Yes Yes Yes Yes No Yes Yes Yes Observations 285,155 285,155 269,929 269,929 R-squared 0.241 0.38 0.056 0.219 Standard errors in parentheses are clustered at the ethnicity level; Simple controls include age, age squared and a female dummy. Mover is a dummy variable that equals one if an individual is at least 10 kilometers away from her ancestral Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Type of Subsistence or Other Ethnic Traits What Other Ancestral Ethnic Traits are Portable? I I using data from Murdock’s Ethnolinguistic Atlas explore whether I other (than type of subsistence) ethnic-speci…c traits correlate with individual economic performance I pre-colonial dependence on agriculture continues to correlate signi…cantly with development, conditional on other ethnic traits Ethnic traits I degree of political complexity I occupational specialization I early development (size and complexity of early settlements) I cultural traits (polygyny; class strati…cation; clans) I local features (elections for local headman; indigenous slavery; inheritance rule for property) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Type of Subsistence or Other Ethnic Traits What Other Ancestral Ethnic Traits are Portable? I I using data from Murdock’s Ethnolinguistic Atlas explore whether I other (than type of subsistence) ethnic-speci…c traits correlate with individual economic performance I pre-colonial dependence on agriculture continues to correlate signi…cantly with development, conditional on other ethnic traits Ethnic traits I degree of political complexity I occupational specialization I early development (size and complexity of early settlements) I cultural traits (polygyny; class strati…cation; clans) I local features (elections for local headman; indigenous slavery; inheritance rule for property) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Type of Subsistence or Other Ethnic Traits Pre-Colonial Agriculture or Other Ethnic Traits? Education Panel A. Education (All Individuals) 1 2 VARIABLES Education Education agriculture agriculture gather_hunt_fish Polygyny Clans 0.0733*** 0.0870*** (0.0147) (0.0165) 0.0821*** 0.0862*** (0.0171) (0.0165) 0.0784*** 0.0607*** (0.0163) (0.0160) 0.0537* (0.0322) -0.0415 (0.0445) Settlement Pattern 3 Education 4 Education 5 Education 6 Education 0.0741*** (0.0155) 0.0782*** (0.0146) 0.0672*** (0.0174) 0.0746*** 0.0746*** 0.0760*** 0.0666*** (0.0155) (0.0155) (0.0143) (0.0234) 0.0760*** 0.0743*** 0.0760*** 0.0622*** (0.0156) (0.0154) (0.0143) (0.0226) 0.0781*** 0.0717*** 0.0651*** 0.0639** (0.0170) (0.0163) (0.0161) (0.0296) -0.0182* (0.0108) 0.0514* (0.0274) Local Jurisdictional Hierarchy Political Centralization 0.0109 (0.0204) Class Stratification 0.0120 (0.0394) Elections Slavery Property Simple Controls Coordinates FE Observations R-squared Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 281,005 0.508 260,798 0.514 270,786 0.524 269,443 0.511 269,443 0.511 258,246 0.513 7 8 9 10 Education Education Education Education 0.0748*** 0.0710***0.0889** (0.0135) (0.0158) (0.0385) 0.0674*** 0.0735***0.0846*** (0.0126) (0.0161) (0.0287) 0.0643*** 0.0607*** 0.0487* (0.0143) (0.0157) (0.0275) 0.1058 (0.0749) -0.0469 (0.0621) -0.0158 (0.0177) 0.1039** (0.0497) -0.0248 (0.0359) 0.0420 (0.0656) -0.1021 -0.1424 (0.0884) (0.1022) -0.1885*** -0.1254** (0.0363) (0.0547) -0.1633**-0.1913** (0.0699) (0.0922) Yes Yes Yes Yes Yes Yes Yes Yes 217,898 0.516 269,953 0.512 256,542 175,604 0.508 0.529 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Type of Subsistence or Other Ethnic Traits Pre-Colonial Agriculture or Other Ethnic Traits? Wealth Panel B. Wealth (All Individuals) 1 VARIABLES Wealth agriculture agriculture gather_hunt_fish Polygyny Clans 2 Wealth 0.0395*** 0.0410*** (0.0074) (0.0077) 0.0391*** 0.0405*** (0.0085) (0.0079) 0.0177** 0.0151* (0.0086) (0.0085) -0.0026 (0.0178) -0.0217 (0.0264) Settlement Pattern 3 Wealth 0.0407*** (0.0078) 0.0419*** (0.0074) 0.0157** (0.0076) -0.0052 (0.0051) Local Jurisdictional Hierarchy Political Centralization Class Stratification Elections Slavery Property Simple Controls Coordinates FE Observations R-squared Yes Yes Yes Yes Yes Yes 265,779 0.672 245,572 0.675 253,423 0.678 4 Wealth 5 Wealth 6 Wealth 7 Wealth 8 Wealth 9 Wealth 10 Wealth 0.0408*** 0.0408*** 0.0422*** 0.0218*** 0.0386*** 0.0340*** 0.0134 (0.0078) (0.0078) (0.0075) (0.0083) (0.0074) (0.0073) (0.0145) 0.0406*** 0.0400*** 0.0424*** 0.0232*** 0.0378*** 0.0344*** -0.0187 (0.0078) (0.0077) (0.0072) (0.0084) (0.0072) (0.0073) (0.0173) 0.0158** 0.0186** 0.0216*** 0.0028 0.0195** 0.0147* -0.0547 (0.0077) (0.0076) (0.0078) (0.0119) (0.0077) (0.0082) (0.0424) -0.0460 (0.0443) 0.0029 (0.0077) 0.0110 (0.0251) -0.0085 0.0146 (0.0127) (0.0182) 0.0280** 0.0666* (0.0113) (0.0375) 0.0597*** -0.0402 (0.0201) (0.0482) 0.0278 0.0154 (0.0310) (0.0313) -0.0202 -0.0315 (0.0211) (0.0713) -0.0267 -0.00933 (0.0381) (0.0721) Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 254,217 0.677 254,217 0.677 244,512 0.669 207,903 0.675 254,727 0.669 243,557 167,621 0.672 0.678 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Type of Subsistence or Other Ethnic Traits Results I pre-colonial dependence on agriculture => robust correlate of individual-level economic performance I I reassures that the estimates are not picking up the e¤ect of other ethnic features some evidence that pre-colonial indigenous slavery negatively impacts education Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Type of Subsistence or Other Ethnic Traits Results I pre-colonial dependence on agriculture => robust correlate of individual-level economic performance I I reassures that the estimates are not picking up the e¤ect of other ethnic features some evidence that pre-colonial indigenous slavery negatively impacts education Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Pre-Colonial Subsistence and the Colonial In‡uence Colonization and the Subsistence Pattern I Is the channel via which pre-colonial subsistence pattern shapes individual economic performance the colonial experience? I Account for the number of slaves extracted during the slave raids I Account for the number of missions established I Account for religious denomination (partially driven by the advent of Europeans) I Account for distance to the capital (partially decided by the colonizers) I note that all these traits are at the level of your ancestral ethnic group (not current ethnic homeland) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Pre-Colonial Subsistence and the Colonial In‡uence Colonization and the Subsistence Pattern I Is the channel via which pre-colonial subsistence pattern shapes individual economic performance the colonial experience? I Account for the number of slaves extracted during the slave raids I Account for the number of missions established I Account for religious denomination (partially driven by the advent of Europeans) I Account for distance to the capital (partially decided by the colonizers) I note that all these traits are at the level of your ancestral ethnic group (not current ethnic homeland) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Pre-Colonial Subsistence and the Colonial In‡uence Pre-Colonial Agriculture or Other Ethnic Traits? Education Table 8. Colonial Roots VARIABLES (1) Education (2) Education (3) Education agriculture (4) Education (5) Education (6) Wealth (7) Wealth (8) Wealth (9) Wealth (10) Wealth 0.0731*** 0.0745*** 0.0738*** (0.0147) (0.0152) (0.0148) 0.0708*** 0.0711*** 0.0676*** (0.0155) (0.0156) (0.0151) ln(1+slaves per km2) -0.0026 -0.0043 (0.0051) (0.0052) 0.2115** ln(1+ Christian missions (0.1025) per km2) 0.0575*** 0.0565*** 0.0394*** 0.0362*** 0.0359*** 0.0364*** 0.0363*** (0.0127) (0.0118) (0.0073) (0.0081) (0.0080) (0.0082) (0.0081) 0.0493*** 0.0482*** 0.0179** 0.0166** 0.0152** 0.0163** 0.0143* (0.0122) (0.0119) (0.0073) (0.0075) (0.0076) (0.0076) (0.0073) -0.0009 -0.0032 0.0051 0.0045 0.0047 0.0036 (0.0040) (0.0038) (0.0038) (0.0038) (0.0038) (0.0038) 0.1451 0.0903 0.0845** 0.0817** 0.0570* (0.0896) (0.0910) (0.0341) (0.0345) (0.0340) Muslim -0.4179*** -0.4105*** (0.0278) (0.0279) -0.4162*** -0.4134*** (0.0388) (0.0391) -0.0963* (0.0577) -0.0002** (0.0001) Yes Yes gather/hunt/fish Other Religions Distance to the Capital City Distance to the Coast 0.0050 0.0078 (0.0238) (0.0236) -0.1679***-0.1680*** (0.0184) (0.0188) -0.1010*** (0.0310) -2.91E-05 (3.84E-05) Yes Yes Simple Controls Yes Yes Yes Yes Yes Yes Coordinates FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes 285,155 0.506 284,654 0.507 284,654 0.507 284,208 0.513 283,264 0.514 269,929 0.676 269,428 0.676 269,428 0.676 268,987 0.676 268,043 0.676 Observations R-squared Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Channels - The Narrative I Physical environments a¤ect ways of wresting a living from nature (lifeway). (E.g.: land suitable for agriculture settled by Bantu-speaking farmers, areas better for herding settled by Nilo-Saharan-speaking herders I Lifeway plausibly a¤ected attitudes, norms, (psycho-social-cultural adaptations). Examples: I I I I farmers acclimate to more sustained repetitive labor than do herders; farmers adapt to living in proximity to neighbors / less mobile; herders acclimate to projecting readiness to defend their movable property from threat of theft. Di¤erential inclinations become cultural inheritances that are partly maintained after relocation and engagement in new economic activities. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Channels - The Narrative I Physical environments a¤ect ways of wresting a living from nature (lifeway). (E.g.: land suitable for agriculture settled by Bantu-speaking farmers, areas better for herding settled by Nilo-Saharan-speaking herders I Lifeway plausibly a¤ected attitudes, norms, (psycho-social-cultural adaptations). Examples: I I I I farmers acclimate to more sustained repetitive labor than do herders; farmers adapt to living in proximity to neighbors / less mobile; herders acclimate to projecting readiness to defend their movable property from threat of theft. Di¤erential inclinations become cultural inheritances that are partly maintained after relocation and engagement in new economic activities. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Channels - The Narrative I Physical environments a¤ect ways of wresting a living from nature (lifeway). (E.g.: land suitable for agriculture settled by Bantu-speaking farmers, areas better for herding settled by Nilo-Saharan-speaking herders I Lifeway plausibly a¤ected attitudes, norms, (psycho-social-cultural adaptations). Examples: I I I I farmers acclimate to more sustained repetitive labor than do herders; farmers adapt to living in proximity to neighbors / less mobile; herders acclimate to projecting readiness to defend their movable property from threat of theft. Di¤erential inclinations become cultural inheritances that are partly maintained after relocation and engagement in new economic activities. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Channels - Attitudes and Beliefs I A natural theory explaining persistent e¤ect of ancestral lifeways on modern outcomes is the cultural transmission of attitudes that impact behavior today. I The range of potentially relevant traits is enormous, and measurement of any particular one is di¢ cult. I Candidates include proclivity towards violence, non-cooperativeness, impatience, etc. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Attitudes Towards Women I Is there evidence of proclivity to violence in the DHS? I DHS o¤ers a set of consistently measured traits regarding the conditions under which it would be acceptable for a man to beat his wife. I I These are: (i) wife goes out without telling him; (ii) wife neglects the children; (iii) wife argues with him; (iv) wife refuses to have sex with him; (v) wife burns the food. As our dependent variable, we use the …rst principal component of these …ve measures. I The …rst pca explains on average 60% of the variation of each variable. Standard Deviation of dep. var is 1.73. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Attitudes Towards Women by Males Table 9. Violence Toward Women 3 VARIABLES agriculture gather/hunt/fish 4 5 First Principal Component of Whether it is Justified to Beat One's Wife -0.0339** (0.0159) -0.0190 (0.0148) -0.0316** (0.0147) -0.0161 (0.0144) -0.0273** (0.0137) -0.0104 (0.0141) 0.1312*** (0.0255) 0.1657*** (0.0419) Yes Yes Yes Yes Yes Yes Muslim Other Religions education wealth Simple Controls Coordinates FE Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Proclivity towards Violence I The question on violence against women captures both proclivity to violence and attitudes towards women. I Which of these two components is more likely to be re‡ected in the answers? I I First, we looked at other questions capturing the women bargaining power in the household. Second, we focused on households that had both sons and daughters and looked at whether daughters have less education than sons within the same household. There is no evidence that agricultural households allow for more bargaining power/education to women in the household. I Hence, the violence against women more likely re‡ects an increased proclivity to violence among those of pastoral descent. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Proclivity towards Violence I The question on violence against women captures both proclivity to violence and attitudes towards women. I Which of these two components is more likely to be re‡ected in the answers? I I First, we looked at other questions capturing the women bargaining power in the household. Second, we focused on households that had both sons and daughters and looked at whether daughters have less education than sons within the same household. There is no evidence that agricultural households allow for more bargaining power/education to women in the household. I Hence, the violence against women more likely re‡ects an increased proclivity to violence among those of pastoral descent. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Proclivity towards Violence I The question on violence against women captures both proclivity to violence and attitudes towards women. I Which of these two components is more likely to be re‡ected in the answers? I I First, we looked at other questions capturing the women bargaining power in the household. Second, we focused on households that had both sons and daughters and looked at whether daughters have less education than sons within the same household. There is no evidence that agricultural households allow for more bargaining power/education to women in the household. I Hence, the violence against women more likely re‡ects an increased proclivity to violence among those of pastoral descent. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Attitudes and Beliefs - Afrobarometer I Do descendants from agricultural groups display di¤erent attitudes and beliefs compared to pastoral ones? I Using survey data from the Afrobarometer Surveys we …nd that: I Members of agricultural groups feel their group has more political in‡uence I Respondents of pastoral ancestry are perceived by the interviewer to have "worse" interpersonal attitudes Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Attitudes and Beliefs - Afrobarometer I Do descendants from agricultural groups display di¤erent attitudes and beliefs compared to pastoral ones? I Using survey data from the Afrobarometer Surveys we …nd that: I Members of agricultural groups feel their group has more political in‡uence I Respondents of pastoral ancestry are perceived by the interviewer to have "worse" interpersonal attitudes Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Pre-Colonial Agriculture and Attitudes I Table 13. Political Perceptions and Attitudes 1 2 3 -0.0678*** (0.0239) -0.0007 (0.0271) -0.0061 (0.0040) -0.0026 (0.0036) -0.0183*** (0.0060) -0.0109* (0.0056) -0.0134* (0.0071) -0.003 (0.0052) -0.0216*** (0.0079) -0.0176** (0.0072) -0.0121* (0.0065) 0.0019 (0.0058) -0.0153*** (0.0053) -0.0021 (0.0040) Simple Controls Yes Yes Yes Yes Yes Yes Yes Coordinates FE Yes Yes Yes Yes Yes Yes Yes Interviewer FE R-squared Observations Yes Yes Yes Yes Yes Yes Yes 0.343 20139 0.369 21570 0.361 21582 0.346 21586 0.351 21582 0.393 21588 0.427 21584 VARIABLES agriculture gather/hunt/fish 4 5 6 7 Respondent is Group's Political Respondent is Respondent is Respondent is Respondent is Respondent NonInfluence Hostile Bored Impatient Suspicious is Dishonest Cooperative Standard errors in parentheses are clustered at the Atlas level; Simple controls include age, age squared and a female dummy; Group's political influence variable captures the respondents perception whether his/her own group has more influence politically compared to otehr groups. Higher values indicate lesser influence. *** p<0.01, ** p<0.05, * p<0.1 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Pre-Colonial Agriculture and Attitudes I Do di¤erences in political perceptions and attitudes account for some of the in‡uence of ancestral lifeways on economic performance? Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Data Channels of In‡uence of Pre-Colonial Subsistence Pre-Colonial Agriculture and Attitudes Table 14: Ancestral Lifeways Education, Political Representation and Attitudes No Controls Accounting for Political Influence Accounting for Political Influence & Attitudes VARIABLES Education Education Education agriculture 0.0437** (0.0186) 0.0262 (0.0178) Yes Yes 0.0402** (0.0183) 0.0264 (0.0173) Yes Yes 0.0355* (0.0181) 0.0251 (0.0172) Yes Yes gather/hunt/fish Simple Controls Coordinates FE 0.538 0.539 0.545 R-squared 20077 20077 20077 Observations Standard errors in parentheses are clustered at the Atlas level; Simple controls include age, age squared and a female dummy; In Column 3 we control for the respondent's perception of own ethnic influence in politics. In Column 4 we control for the respondent's perception of own ethnic influence in politics as well as the attitudes of each respondent as recorded by the interviewer regarding whether the respondent is bored, non-cooperative, suspicious, impatient and dishonest. The education variable takes 6 distinct values indicating no formal education, incomplete Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Approach I Agriculture is more likely among groups that reside historically on more fertile regions Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Pre-Colonial Dependence on Agriculture I Pre-Colonial Dependence on Agriculture 0.001 - 0.067 86-100% Dependence 0.068 - 0.179 76-85% Dependence 0.180 - 0.280 66-75% Dependence 56-65% Dependence 46-55% Dependence 36-45% Dependence 26-35% Dependence 16-25% Dependence 6-15% Dependence 0-5% Dependence . Suitability for Agriculture No Information Ü 0.281 - 0.355 0.356 - 0.431 0.432 - 0.514 0.515 - 0.597 0.598 - 0.695 0.696 - 0.816 0.817 - 0.979 Ü Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Farming Suitability and Agricultural Dependence Table 10: Log of Average Land Subsistence and Modes of Pre-Colonial Subsistence VARIABLES (1) agriculture (2) pastoralism (3) gather/hunt/fish Ln (Land Suitablity for Agriculture) 0.6566*** (0.1579) -0.7053*** (0.1726) 0.0428 (0.1009) 187 0.137 187 0.141 187 -0.005 Observations R-squared Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence IV Results I May use ancestral homeland suitability for agriculture to instrument for pre-colonial dependence on farming I What does this approach buy us? I To the extent that "better" cultures adopt more productive technologies more intensively than others then dependence on agriculture may be a manifestation of these primordial di¤erences. I Instrumenting for ancestral land suitability for agriculture deals with this issue. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence IV Results I May use ancestral homeland suitability for agriculture to instrument for pre-colonial dependence on farming I What does this approach buy us? I To the extent that "better" cultures adopt more productive technologies more intensively than others then dependence on agriculture may be a manifestation of these primordial di¤erences. I Instrumenting for ancestral land suitability for agriculture deals with this issue. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence IV Results: All Individuals Table 11. IV for Full Sample (1) VARIABLES Education agriculture gather/hunt/fish 0.1215** (0.0551) 0.0883** (0.0349) (2) Education (3) Education 0.0567* 0.0513* (0.0335) (0.0297) 0.0629*** 0.0593*** (0.0209) (0.0185) (4) Wealth (5) Wealth (6) Wealth 0.1191** (0.0599) 0.0327 (0.0353) 0.0267** (0.0118) 0.0114 (0.0079) 0.0233** (0.0115) 0.0115 (0.0073) Simple Controls Yes Yes Yes Yes Yes Yes Country-Ethnic Homeland FE Yes No No Yes No No Coordinates FE No Yes Yes No Yes Yes Occupation FE No No Yes No No Yes First Stage FStatistic 52.34 22.27 25.14 52.34 22.27 25.14 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Endogeneity of Historical Locations of Groups I The Argument I Ethnic homelands may be an outcome of stronger more violent groups taking over the relatively more fertile areas pushing "weaker" groups into marginal zones. I Should this be true then the observed correlations are not driven by agricultural dependence conferring developmental advantages to agricultural societies but it is deeply-rooted primordial traits that are driving both a higher dependence on agriculture and improved economic outcomes today. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Endogeneity of Historical Locations of Groups I The Argument I Ethnic homelands may be an outcome of stronger more violent groups taking over the relatively more fertile areas pushing "weaker" groups into marginal zones. I Should this be true then the observed correlations are not driven by agricultural dependence conferring developmental advantages to agricultural societies but it is deeply-rooted primordial traits that are driving both a higher dependence on agriculture and improved economic outcomes today. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Endogeneity of Historical Locations of Groups I Counterargument(s): I Culture of violence is a common theme among pastoral societies rather than farming ones. I Historical migrations in Africa and beyond seem to be driven by groups selecting into territories that are similar to their ancestral homelands (Michalopoulos, 2012): I Bantu expansion (farmers spreading into areas suitable for farming) I expansion of Semitic Languages (pastoralists spreading into lands suitable for herding) I In the speci…c case of Africa the presence of Tse-Tse ‡y precluded cultures dependent on camels/horses to conquer such territories. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Endogeneity of Historical Locations of Groups I Counterargument(s): I Culture of violence is a common theme among pastoral societies rather than farming ones. I Historical migrations in Africa and beyond seem to be driven by groups selecting into territories that are similar to their ancestral homelands (Michalopoulos, 2012): I Bantu expansion (farmers spreading into areas suitable for farming) I expansion of Semitic Languages (pastoralists spreading into lands suitable for herding) I In the speci…c case of Africa the presence of Tse-Tse ‡y precluded cultures dependent on camels/horses to conquer such territories. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Endogeneity of Historical Locations of Groups I Counterargument(s): I Culture of violence is a common theme among pastoral societies rather than farming ones. I Historical migrations in Africa and beyond seem to be driven by groups selecting into territories that are similar to their ancestral homelands (Michalopoulos, 2012): I Bantu expansion (farmers spreading into areas suitable for farming) I expansion of Semitic Languages (pastoralists spreading into lands suitable for herding) I In the speci…c case of Africa the presence of Tse-Tse ‡y precluded cultures dependent on camels/horses to conquer such territories. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities I An alternative way to partially address this concern is to compare groups that belong to common cultural macro entities. I Note that cultural a¢ nities are often an outcome of similarities in the production among these groups so the …ner the distinction of groupings the more similar are the groups with respect to their subsistence practises. I To assess the robustness of our results we employ 3 di¤erent levels of cultural aggregation starting from: I linguistic families moving to I linguistic sub-families and ending with I ethnic clusters. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities I An alternative way to partially address this concern is to compare groups that belong to common cultural macro entities. I Note that cultural a¢ nities are often an outcome of similarities in the production among these groups so the …ner the distinction of groupings the more similar are the groups with respect to their subsistence practises. I To assess the robustness of our results we employ 3 di¤erent levels of cultural aggregation starting from: I linguistic families moving to I linguistic sub-families and ending with I ethnic clusters. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities I An alternative way to partially address this concern is to compare groups that belong to common cultural macro entities. I Note that cultural a¢ nities are often an outcome of similarities in the production among these groups so the …ner the distinction of groupings the more similar are the groups with respect to their subsistence practises. I To assess the robustness of our results we employ 3 di¤erent levels of cultural aggregation starting from: I linguistic families moving to I linguistic sub-families and ending with I ethnic clusters. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities: Language Families I The 187 Murdock groups in our dataset belong to 6 Language Families, 13 Language Sub-Families, and 36 ethnic clusters I Examples of Language families I Khoisan or click I Niger-Congo (Nc) I Chari-Nile or Macro-Sudanic (Cn) I Kanuric or Central Saharan etc I Koman (Km) I Afro-Asiatic or Hamito-Semitic (Aa) Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities: Language Families Table 12A. Exploiting Within Linguistic Family Variation 1 2 3 VARIABLES Education Education Education agriculture 4 Wealth 5 Wealth 6 Wealth 0.0735*** (0.0148) 0.0712*** (0.0156) 0.0768*** (0.0164) 0.0683*** (0.0148) 0.0734*** (0.0147) 0.0658*** (0.0135) 0.0393*** (0.0074) 0.0178** (0.0073) 0.0381*** (0.0076) 0.0182** (0.0070) 0.0373*** (0.0074) 0.0195*** (0.0067) Simple Controls Yes Yes Yes Yes Yes Yes Coordinates FE Yes Yes Yes Yes Yes Yes Linguistic Family(v98) FE No Yes Yes No Yes Yes Occupation FE No No Yes No No Yes gather/hunt/fish Observations 280,557 280,557 280,557 265,331 265,331 265,331 R-squared 0.508 0.509 0.561 0.671 0.671 0.677 Standard errors in parentheses are clustered at the ethnicity level; Simple controls include age, age squared, a female dummy, and a mover dummy; *** p<0.01, ** p<0.05, * p<0.1 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities: Linguistic Sub-Families I Examples of Sub-families for Niger-Congo (Nc): I I I I I I I I Atlantic or West Atlantic (NcA) Bantoid or Central (NcB) Eastern or Adamawa-Eastern (NcE) Gur or Voltaic (NcG) Ijo or Ijaw (NcI) Kwa (NcK) Mande (NcM) Language Sub-family FE explain roughly 20% of the variation in agricultural dependence across groups Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities: Linguistic Sub-Families I Examples of Sub-families for Niger-Congo (Nc): I I I I I I I I Atlantic or West Atlantic (NcA) Bantoid or Central (NcB) Eastern or Adamawa-Eastern (NcE) Gur or Voltaic (NcG) Ijo or Ijaw (NcI) Kwa (NcK) Mande (NcM) Language Sub-family FE explain roughly 20% of the variation in agricultural dependence across groups Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities: Linguistic Sub-Families Table 12B. Exploiting Within Linguistic Sub-Family Variation 1 2 3 VARIABLES Education Education Education agriculture 4 Wealth 5 Wealth 6 Wealth 0.0731*** (0.0147) 0.0708*** (0.0155) 0.0414** (0.0203) 0.0295 (0.0220) 0.0406** (0.0174) 0.0277 (0.0193) 0.0398*** (0.0077) 0.0177** (0.0076) 0.0341*** (0.0095) 0.0239*** (0.0077) 0.0326*** (0.0087) 0.0233*** (0.0071) Simple Controls Yes Yes Yes Yes Yes Yes Coordinates FE Yes Yes Yes Yes Yes Yes Linguistic Subfamily(v99) FE Occupation FE No Yes Yes No Yes Yes No No Yes No No Yes gather/hunt/fish Observations 285,155 271,781 271,781 256,555 256,555 256,555 R-squared 0.506 0.511 0.563 0.669 0.670 0.675 Standard errors in parentheses are clustered at the ethnicity level; Simple controls include age, age squared, a female dummy, and a mover dummy; *** p<0.01, ** p<0.05, * p<0.1 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities: Ethnic Clusters I Examples of Ethnic Clusters (come from Murdock’s 1959 book and correspond to the chapters’headings) I I I I I I I I Southwestern Bantu Central Bantu Northwestern Bantu Northeast Coastal Bantu Kenya Highland Bantu Interlacustrine Bantu Fulani Ethnic Cluster FE explain roughly 60% of the variation in agricultural dependence across groups Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities: Ethnic Clusters I Examples of Ethnic Clusters (come from Murdock’s 1959 book and correspond to the chapters’headings) I I I I I I I I Southwestern Bantu Central Bantu Northwestern Bantu Northeast Coastal Bantu Kenya Highland Bantu Interlacustrine Bantu Fulani Ethnic Cluster FE explain roughly 60% of the variation in agricultural dependence across groups Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Origins of Agricultural Dependence Accounting for Cultural Similarities: Ethnic Clusters Table 12C. Exploiting Within Ethnic-Cluster Variation 1 2 3 VARIABLES Education Education Education agriculture 4 Wealth 5 Wealth 6 Wealth 0.0731*** (0.0147) 0.0708*** (0.0155) 0.0711*** (0.0146) 0.0732*** (0.0147) 0.0645*** (0.0125) 0.0670*** (0.0131) 0.0394*** (0.0073) 0.0179** (0.0073) 0.0367** (0.0154) 0.0257* (0.0145) 0.0372** (0.0167) 0.0281* (0.0160) Simple Controls Yes Yes Yes Yes Yes Yes Coordinates FE Yes Yes Yes Yes Yes Yes Ethnic Cluster FE No Yes Yes No Yes Yes Occupation FE No No Yes No No Yes gather/hunt/fish Observations 285,155 285,155 285,155 269,929 269,929 269,929 R-squared 0.506 0.509 0.561 0.676 0.676 0.682 Standard errors in parentheses are clustered at the ethnicity level; Simple controls include age, age squared, a female dummy, and a mover dummy; *** p<0.01, ** p<0.05, * p<0.1 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Conclusion Main Contribution I There is a long-standing hypothesis in the social sciences that dependence on agriculture o¤ered early farmers a developmental head start compared to other modes of production. Existing evidence is mixed. I O¤er individual-level evidence that descendants of agriculturalists have better economic outcomes compared to descendants of pastoralists. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Conclusion Results Summary I Tracing ancestry to a given ethnic group (and less so to a given country) has important implications for individual economic performance I In particular, ancestral dependence on agriculture versus pastoralism systematically confers economic bene…ts to descendants from such groups I within countries. I within ethnic homelands I within villages I within occupational groups, within urban and rural places. I result does not re‡ect observable di¤erences in other ethnic speci…c traits. Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Conclusion Implications - Future Research I Future work I more work on channels I study how national policies mitigate or exacerbate these ethnic-speci…c legacies Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Appendix Moved in Life and Autochthonous Mover and Whether Moved in Life (unweighted) Moved in life Haven't moved in life Total Mover Row Pct. Col. Pct. 16,510 51.87 59.79 15,319 48.13 49.21 31,829 100 54.19 Non-Mover Row Pct. Col. Pct. 11,103 41.26 40.21 15,809 58.74 50.79 26,912 100 45.81 Total Row Pct. Col. Pct. 27,613 47.01 100 31,128 52.99 100 58,741 100 100 Ancestral Lifeways and Individual Economic Outcomes: Evidence from Africa Appendix Moved in Life and Autochthonous
