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[{"bbox": "", "centroid": "", "geom": "", "label": {"en": "Peru", "es": "Per\u00fa", "fr": "P\u00e9rou", "pt_BR": "Peru"}, "uri": "https://sws.geonames.org/3932488"}], "groups": [], "relationships_as_subject": [], "relationships_as_object": [], "doi": "10.60966/a79b-xz30", "doi_status": true, "domain": "https://data.iadb.org", "doi_date_published": "2025-03-08", "doi_publisher": "IADB", "data_collection_type": [{"uri": "https://taxonomy.iadb.org/knowledgeProductsTaxonomy/ba70c67d-1a87-46ac-ad2a-479d2c354809", "labels": {"en": "Observational Data", "es": "Datos Observacionales", "fr": "Donn\u00e9es d'observation", "pt_BR": "Dados Observacionais"}}], "keyword": {"en": ["GDP", "Income Distribution", "Inequality", "Mobility"], "es": ["PIB", "Distribuci\u00f3n del ingreso", "Desigualdad", "Movilidad"], "fr": ["PIB", "Distribution du revenu", "In\u00e9galit\u00e9s", "Mobilit\u00e9"], "pt_BR": ["PIB", "Distribui\u00e7\u00e3o de renda", "Desigualdade", "Mobilidade"]}, "contact_point": "opendata@iadb.org", "description": {"en": "### Peru Macroeconomic Data: Historical GDP, Population & Regional Indicators\nThis dataset provides over two centuries of Peru\u2019s macroeconomic history, combining GDP (1990 Geary\u2011Khamis dollars), population counts, regional economic structures, and geospatial indicators across natural regions, ecological floors, and departments. It offers the depth needed to analyze Peru\u2019s long\u2011run economic trajectory from the late colonial era to today.\n### What the Dataset Includes\n#### 1. Historical GDP by Region and Department (1795\u20132017)\n- Annual GDP in 1990 Geary\u2011Khamis dollars  \n- Coverage for Costa, Sierra, and Selva  \n- Detailed ecological floors (Quechua, Suni, Puna, Janca, Selva Alta, Selva Baja, etc.)  \n- Long\u2011run growth, structural change, and regional divergence  \n#### 2. Population Time Series (1795\u20132017)\n- Annual population by natural region and ecological floor  \n- Urbanization via populated vs. unpopulated area  \n- Demographic transitions over 220+ years  \n#### 3. Geospatial & Environmental Indicators\n- Altitude (average, population\u2011weighted, GDP\u2011weighted)  \n- Total vs. populated area  \n- Regional shares of national territory  \n- Ecological classifications shaping economic specialization  \n### Why This Dataset Matters\n#### A 220\u2011Year View of Peru\u2019s Economic History\nUnlike most datasets beginning in the mid\u201120th century, this series reaches back to 1795, enabling:\n- Long\u2011run growth analysis  \n- Regional inequality studies  \n- Reconstruction of Peru\u2019s economic geography  \n- Policy evaluation across historical periods  \n\n#### Rich Regional Detail\nCaptures the geographic forces shaping Peru\u2019s economy:\n- Coastal, Andean, and Amazonian divergence  \n- High\u2011altitude productivity patterns  \n- Shifts in population density  \n- Spatial distribution of economic activity  \n#### Built for Modern Research\nIdeal for:\n- Econometric and spatial modeling  \n- Historical economic analysis  \n- Policy design and evaluation  \n- Cross\u2011country comparison, including Latin America inequality studies  \n### Who Should Use This Dataset\n- Economists and development researchers  \n- Public policy analysts  \n- Historians and economic historians  \n- GIS and spatial\u2011economics specialists  \n- Students, educators, think tanks, and multilaterals", "es": "### Datos macroecon\u00f3micos del Per\u00fa: PIB hist\u00f3rico, poblaci\u00f3n e indicadores regionales\nEste conjunto de datos re\u00fane m\u00e1s de dos siglos de la historia macroecon\u00f3mica peruana e integra el producto interno bruto (PIB) en d\u00f3lares Geary\u2011Khamis de 1990, los conteos de poblaci\u00f3n, las estructuras econ\u00f3micas regionales y los indicadores geoespaciales correspondientes a las regiones naturales, los pisos ecol\u00f3gicos y los departamentos. Brinda la profundidad necesaria para examinar la trayectoria econ\u00f3mica de largo plazo del Per\u00fa, desde el ocaso de la era colonial hasta nuestros d\u00edas.\n### Qu\u00e9 contiene el conjunto de datos\n#### 1. PIB hist\u00f3rico por regi\u00f3n y departamento (1795\u20132017)\n- PIB anual expresado en d\u00f3lares Geary\u2011Khamis de 1990  \n- Cobertura de la Costa, la Sierra y la Selva  \n- Pisos ecol\u00f3gicos al detalle (Quechua, Suni, Puna, Janca, Selva Alta, Selva Baja, etc.)  \n- Crecimiento de largo plazo, transformaci\u00f3n estructural y divergencia entre regiones  \n#### 2. Series temporales de poblaci\u00f3n (1795\u20132017)\n- Poblaci\u00f3n anual desagregada por regi\u00f3n natural y piso ecol\u00f3gico  \n- Urbanizaci\u00f3n a partir del contraste entre \u00e1rea poblada y no poblada  \n- Transiciones demogr\u00e1ficas registradas a lo largo de m\u00e1s de 220 a\u00f1os  \n#### 3. Indicadores geoespaciales y ambientales\n- Altitud (promedio, ponderada por poblaci\u00f3n y ponderada por PIB)  \n- \u00c1rea total frente al \u00e1rea efectivamente poblada  \n- Participaci\u00f3n de cada regi\u00f3n en el territorio nacional  \n- Clasificaciones ecol\u00f3gicas que moldean la especializaci\u00f3n productiva  \n### Por qu\u00e9 resulta relevante este conjunto de datos\n#### Una mirada de 220 a\u00f1os a la historia econ\u00f3mica peruana\nA diferencia de la mayor\u00eda de las bases que arrancan a mediados del siglo XX, esta serie llega hasta 1795, lo que habilita:\n- El an\u00e1lisis del crecimiento de largo plazo  \n- Los estudios sobre desigualdad regional  \n- La reconstrucci\u00f3n de la geograf\u00eda econ\u00f3mica del Per\u00fa  \n- La evaluaci\u00f3n de pol\u00edticas en distintos per\u00edodos hist\u00f3ricos  \n\n#### Una rica granularidad regional\nRecoge las fuerzas geogr\u00e1ficas que dan forma a la econom\u00eda peruana:\n- La divergencia entre la costa, los Andes y la Amazon\u00eda  \n- Los patrones de productividad en zonas de gran altitud  \n- Las variaciones en la densidad poblacional  \n- La distribuci\u00f3n espacial de la actividad econ\u00f3mica  \n#### Pensado para la investigaci\u00f3n actual\nResulta id\u00f3neo para:\n- El modelado econom\u00e9trico y espacial  \n- El an\u00e1lisis de historia econ\u00f3mica  \n- El dise\u00f1o y la evaluaci\u00f3n de pol\u00edticas  \n- La comparaci\u00f3n entre pa\u00edses, incluidos los estudios de desigualdad en Am\u00e9rica Latina  \n### A qui\u00e9n est\u00e1 dirigido este conjunto de datos\n- Economistas e investigadores del desarrollo  \n- Analistas de pol\u00edticas p\u00fablicas  \n- Historiadores e historiadores econ\u00f3micos  \n- Especialistas en SIG y econom\u00eda espacial  \n- Estudiantes, docentes, centros de pensamiento y organismos multilaterales", "fr": "### Donn\u00e9es macro\u00e9conomiques du P\u00e9rou : PIB historique, population et indicateurs r\u00e9gionaux\nCe jeu de donn\u00e9es rassemble plus de deux si\u00e8cles d'histoire macro\u00e9conomique p\u00e9ruvienne en croisant le produit int\u00e9rieur brut (PIB) en dollars Geary\u2011Khamis de 1990, les effectifs de population, les structures \u00e9conomiques r\u00e9gionales et des indicateurs g\u00e9ospatiaux par r\u00e9gions naturelles, \u00e9tages \u00e9cologiques et d\u00e9partements. Il procure la profondeur requise pour retracer la trajectoire \u00e9conomique de long terme du P\u00e9rou, de la fin de l'\u00e9poque coloniale \u00e0 aujourd'hui.\n### Contenu du jeu de donn\u00e9es\n#### 1. PIB historique par r\u00e9gion et par d\u00e9partement (1795\u20132017)\n- PIB annuel libell\u00e9 en dollars Geary\u2011Khamis de 1990  \n- Couverture de la Costa, de la Sierra et de la Selva  \n- \u00c9tages \u00e9cologiques d\u00e9crits en d\u00e9tail (Quechua, Suni, Puna, Janca, Selva Alta, Selva Baja, etc.)  \n- Croissance de long terme, mutation structurelle et divergence entre r\u00e9gions  \n#### 2. S\u00e9ries temporelles de population (1795\u20132017)\n- Population annuelle ventil\u00e9e par r\u00e9gion naturelle et par \u00e9tage \u00e9cologique  \n- Urbanisation appr\u00e9hend\u00e9e par l'opposition entre zone peupl\u00e9e et zone non peupl\u00e9e  \n- Transitions d\u00e9mographiques observ\u00e9es sur plus de 220 ans  \n#### 3. Indicateurs g\u00e9ospatiaux et environnementaux\n- Altitude (moyenne, pond\u00e9r\u00e9e par la population et pond\u00e9r\u00e9e par le PIB)  \n- Superficie totale compar\u00e9e \u00e0 la superficie effectivement peupl\u00e9e  \n- Poids de chaque r\u00e9gion dans le territoire national  \n- Classifications \u00e9cologiques qui mod\u00e8lent la sp\u00e9cialisation productive  \n### Pourquoi ce jeu de donn\u00e9es compte\n#### Un regard de 220 ans sur l'histoire \u00e9conomique p\u00e9ruvienne\nContrairement \u00e0 la plupart des bases qui d\u00e9butent au milieu du XXe si\u00e8cle, cette s\u00e9rie remonte jusqu'en 1795, rendant possibles :\n- L'analyse de la croissance de long terme  \n- Les \u00e9tudes sur les in\u00e9galit\u00e9s r\u00e9gionales  \n- La reconstitution de la g\u00e9ographie \u00e9conomique du P\u00e9rou  \n- L'\u00e9valuation des politiques au fil des p\u00e9riodes historiques  \n\n#### Une fine granularit\u00e9 r\u00e9gionale\nLe jeu de donn\u00e9es saisit les forces g\u00e9ographiques qui fa\u00e7onnent l'\u00e9conomie p\u00e9ruvienne :\n- La divergence entre le littoral, les Andes et l'Amazonie  \n- Les profils de productivit\u00e9 en haute altitude  \n- Les inflexions de la densit\u00e9 de population  \n- La r\u00e9partition spatiale de l'activit\u00e9 \u00e9conomique  \n#### Con\u00e7u pour la recherche d'aujourd'hui\nIl convient parfaitement \u00e0 :\n- La mod\u00e9lisation \u00e9conom\u00e9trique et spatiale  \n- L'analyse d'histoire \u00e9conomique  \n- La conception et l'\u00e9valuation des politiques  \n- La comparaison entre pays, y compris les \u00e9tudes sur les in\u00e9galit\u00e9s en Am\u00e9rique latine  \n### \u00c0 qui s'adresse ce jeu de donn\u00e9es\n- \u00c9conomistes et chercheurs en d\u00e9veloppement  \n- Analystes des politiques publiques  \n- Historiens et historiens de l'\u00e9conomie  \n- Sp\u00e9cialistes des SIG et de l'\u00e9conomie spatiale  \n- \u00c9tudiants, enseignants, groupes de r\u00e9flexion et organismes multilat\u00e9raux", "pt_BR": "### Dados macroecon\u00f4micos do Peru: PIB hist\u00f3rico, popula\u00e7\u00e3o e indicadores regionais\nEste conjunto de dados re\u00fane mais de dois s\u00e9culos da hist\u00f3ria macroecon\u00f4mica peruana, articulando o produto interno bruto (PIB) em d\u00f3lares Geary\u2011Khamis de 1990, as contagens populacionais, as estruturas econ\u00f4micas regionais e os indicadores geoespaciais referentes \u00e0s regi\u00f5es naturais, aos andares ecol\u00f3gicos e aos departamentos. Entrega a profundidade necess\u00e1ria para acompanhar a trajet\u00f3ria econ\u00f4mica de longo prazo do Peru, do entardecer da era colonial at\u00e9 os dias atuais.\n### O que o conjunto de dados traz\n#### 1. PIB hist\u00f3rico por regi\u00e3o e departamento (1795\u20132017)\n- PIB anual expresso em d\u00f3lares Geary\u2011Khamis de 1990  \n- Cobertura de Costa, Sierra e Selva  \n- Andares ecol\u00f3gicos descritos em detalhe (Quechua, Suni, Puna, Janca, Selva Alta, Selva Baja, etc.)  \n- Crescimento de longo prazo, transforma\u00e7\u00e3o estrutural e diverg\u00eancia entre regi\u00f5es  \n#### 2. S\u00e9ries temporais de popula\u00e7\u00e3o (1795\u20132017)\n- Popula\u00e7\u00e3o anual discriminada por regi\u00e3o natural e andar ecol\u00f3gico  \n- Urbaniza\u00e7\u00e3o captada pelo contraste entre \u00e1rea povoada e n\u00e3o povoada  \n- Transi\u00e7\u00f5es demogr\u00e1ficas acompanhadas ao longo de mais de 220 anos  \n#### 3. Indicadores geoespaciais e ambientais\n- Altitude (m\u00e9dia, ponderada pela popula\u00e7\u00e3o e ponderada pelo PIB)  \n- \u00c1rea total em contraste com a \u00e1rea efetivamente povoada  \n- Peso de cada regi\u00e3o no territ\u00f3rio nacional  \n- Classifica\u00e7\u00f5es ecol\u00f3gicas que moldam a especializa\u00e7\u00e3o produtiva  \n### Por que este conjunto de dados \u00e9 relevante\n#### Um panorama de 220 anos da hist\u00f3ria econ\u00f4mica peruana\nDiferentemente da maioria das bases que come\u00e7am em meados do s\u00e9culo XX, esta s\u00e9rie recua at\u00e9 1795, o que viabiliza:\n- A an\u00e1lise do crescimento de longo prazo  \n- Os estudos sobre desigualdade regional  \n- A reconstru\u00e7\u00e3o da geografia econ\u00f4mica do Peru  \n- A avalia\u00e7\u00e3o de pol\u00edticas em diferentes per\u00edodos hist\u00f3ricos  \n\n#### Um rico detalhamento regional\nCapta as for\u00e7as geogr\u00e1ficas que d\u00e3o forma \u00e0 economia peruana:\n- A diverg\u00eancia entre o litoral, os Andes e a Amaz\u00f4nia  \n- Os padr\u00f5es de produtividade em grande altitude  \n- As oscila\u00e7\u00f5es na densidade populacional  \n- A distribui\u00e7\u00e3o espacial da atividade econ\u00f4mica  \n#### Feito para a pesquisa contempor\u00e2nea\nIdeal para:\n- A modelagem econom\u00e9trica e espacial  \n- A an\u00e1lise de hist\u00f3ria econ\u00f4mica  \n- A concep\u00e7\u00e3o e a avalia\u00e7\u00e3o de pol\u00edticas  \n- A compara\u00e7\u00e3o entre pa\u00edses, incluindo estudos de desigualdade na Am\u00e9rica Latina  \n### Para quem \u00e9 este conjunto de dados\n- Economistas e pesquisadores de desenvolvimento  \n- Analistas de pol\u00edticas p\u00fablicas  \n- Historiadores e historiadores econ\u00f4micos  \n- Especialistas em SIG e economia espacial  \n- Estudantes, educadores, centros de estudos e organismos multilaterais"}}}