This chapter introduces Peru’s approach to collecting, publishing, and using relevant data and indicators at different territorial levels for national and regional policy development, monitoring and performance evaluation. The chapter reviews the quality and coverage of subnational data in Peru and proposes recommendations to improve their availability and international comparability.
Regional Development Policy in Peru
Abstract
The territorial organisation of Peru is based on the political and administrative division of the country, established in the Political Constitution of Peru of 1993, and developed in Law No. 277951, Law of Demarcation and Territorial Organisation of 2012. Based on these norms, Peru is organised into departments (departamentos), provinces (provincias) and districts (distritos) (see Background section), with the National Institute of Statistics and Informatics (Instituto Nacional de Estadística e Informática - INEI) using the same categories for statistical purposes2. In addition, the law categorises population centres into hamlet, town, village, city and metropole.
The law defines districts and provinces according to their compliance with specific requirements based on area and the main population centre (designated as its capital). These include minimum population thresholds, depending on the type of area (coast, highlands, or jungle), with sufficient infrastructure and services in place, such as health, education, sanitation, and other essential facilities, a favourable geographic, environmental, and urban characteristic, as well as economic potential to support its development. Lastly, territorial factors such as location, accessibility, vulnerability, and areas of influence are also considered.
For statistical and comparability purposes, the OECD categorises territorial units within countries into two territorial levels reflecting the administrative organisation of countries: large (TL2) regions and small (TL3) regions. Regional boundaries correspond to administrative divisions defined autonomously by countries using different criteria. The OECD further classifies small regions according to the Access to Functional Urban Areas (FUA) typology and the predominantly urban/intermediate/predominantly rural typology. The OECD Regional Database contains socio-economic and environmental indicators for TL2 and TL3 regions while the OECD Cities Database provides socio-economic and environmental indicators for FUAs with 250 000 inhabitants or more. FUAs are identified according to a common OECD/EU methodology based on population density and commuting-to-work flows
INEI provides geographic vectorial limits in Geo Package format (Gpkg) for the three territorial layers through its Portal de Infraestructura de datos espaciales (last update in 2023).
Following the OECD territorial grid, the 25 regions of Peru (24 departamentos plus the provincia constitucional de Callao) can be classified as TL2 regions (large regions) – as they constitute the primary administrative tier of subnational government – and the 196 provinces as TL3 regions (small regions) as they constitute the second tier of administrative level (Figure 2.1). Both Peruvian regions and provinces are within the range of OECD countries in terms of median population and density. Table 2.2 presents the ranking of Peru’s median region in relation to the median region of OECD countries by TL classification.
Source: Based on Geo Package files https://ide.inei.gob.pe/#capas.
Note: In the above table, the 2-digit codes of Provinces in the map are associated with the code of their related department.
Subnational data producers in Peru
INEI collects data through censuses and surveys3:
National Household Survey (Encuesta Nacional de Hogares, ENAHO): household living conditions, poverty, income, employment, education, and health,
Permanent Employment Survey (Encuesta Permanente de Empleo, EPE): employment and labor market trends in urban areas.
National Business Survey (Encuesta Nacional de Empresas, ENE): business activities, employment, and economic performance across various sectors,
Demographic and Family Health Survey (Encuesta Demográfica y de Salud Familiar, ENDES): demographic and family health data, including fertility, infant mortality, and health care access,
National Victimization Survey (Encuesta Nacional de Victimización, ENV): public safety and crime victimization to inform policy in justice and security sectors.
In addition, INEI co-ordinates the collection of statistical information from other government sectors, including the Ministry of Education (MINEDU), the Ministry of Labor and Employment Promotion (MTPE), the Ministry of Housing, Constructions and Sanitation (MVCS), the Ministry of Economy and Finance (MEF), the Ministry of Agrarian Development and Irrigation (MIDAGRI), the National Registry of Identification and Civil Status (RENIEC), the Ministry of Health (MINSA), the Ministry of Environment (MINAM), and the Household Targeting System (Sistema de Focalización de Hogares SISFOH), consolidated by MIDIS from the information collected by local governments among others.
The National Centre for Strategic Planning (CEPLAN) prepares reports with “information for planning with a territorial approach” for each department of Peru, with the purpose of presenting a multidimensional diagnosis of the territories. These documents contain updated data and information of different types (bibliographic, statistical and geospatial) and for different territorial dimensions. In addition, CEPLAN generates information and thematic inputs with a territorial and prospective focus that are available in the “Territorial information platform for strategic planning” 4 and the “National Foresight Observatory”5.
The National Environmental Information System (SINIA, governed by the Law No. 28245, regulations approved by Supreme Decree No. 034-2021-MINAM) acts as an environmental data repository. It compiles and disseminates environmental information generated by the administration's entities at the national and subnational levels, based on national and international standards6. It manages a wide range of indicators on environmental health risks, and environmental degradation and protection (e.g. PM2.5 and PM10 concentration, ozone levels; water quality in rivers, lakes, and coastal areas, biological oxygen demand (BOD), and pH levels; biodiversity indicators on species conservation status, deforestation rates, and protected areas; greenhouse gas emissions (GHG), land use and land cover).
Solid waste management data are collected through the Solid Waste Management Information System (Sistema de Información para la Gestión de Residuos Sólidos, SIGERSOL), an official tool that tracks integrated waste management at the national level. Municipalities report data annually and quarterly at both district and provincial levels, which is then used to calculate departmental figures.
Environmental Management Systems (SRGA) measure the effectiveness of regional environmental governance and co-operation in addressing key environmental challenges prioritised by the MINAM. This evaluation is guided by the "Guide for the Operation of the SRGA," (approved by Ministerial Resolution No. 132-2023-MINAM).
Subnational data dissemination
INEI disseminates, and updates, territorial indicators on its website and annual statistical compendiums. The INEI website offers documentation derived from research and surveys conducted by the institution in recent years, which are downloadable in various formats. In many cases, the code and microdata needed to reproduce some indicators is also available:
Based on the National Register of Municipalities (RENAMU) data, INEI produced a PDF document “Perú: Indicadores de Gestión Municipal” that offers detailed statistics related to the management of provincial and district municipalities across Peru (including data on human resources, heavy machinery and vehicles, ICT, municipal planning and finances, social and health services, public cleaning, citizen security, disaster risk management, and environmental protection and conservation). INEI also provides the data at department and district level in formats such as SPSS, CSV, and STATA (https://proyectos.inei.gob.pe/microdatos/).
CEPLAN created the Geo Ceplan platform for accessing georeferenced territorial information to support strategic planning, and the National Foresight Observatory, which compiles data on future trends, risks, and opportunities to inform policy and planning.
The Spatial Data Infrastructure Geoportal (https://visor.geoperu.gob.pe) enables to visualise a wide range of territorial indicators at different geographical scales, from departments and provinces to districts and census blocks. The files and public geographic information to characterise the territory are available on the geographic information platforms of state entities; the main ones are the following:
The INEI Spatial Data Infrastructure portal (Infraestructura de Datos Espaciales, IDE INEI) offers spatial information on various topics such as demographics, housing, economy, and social development (https://ide.inei.gob.pe).
The District Information System for Public Management is an online platform provided by INEI, offering georeferenced statistical data. It presents thematic maps on various topics such as population, health, education, and economic indicators (https://estadist.inei.gob.pe/map).
SIRTOD, the Regional Information System for Decision Making - repository of departmental, provincial and district statistical information related to demographic, social, economic, environmental and natural resources, science and technology, municipal statistics and budgets (https://systems.inei.gob.pe/SIRTOD).
Geoidep: is an online platform managed by INEI. It provides easy access to georeferenced data related to demographic, economic, and social statistics through the R open-source programming language. The platform offers spatial information such as population distribution, poverty levels, and infrastructure (https://geografo.pe/geoidep).
Geo Peru is an initiative of the Presidency of the Council of Ministers (PCM) of Peru, in collaboration with international institutions such as the United Nations Development Program (UNDP) and the Inter-American Development Bank (IDB). GEOPERU is the digital platform of georeferenced data that integrates information from official state sources. It allows identifying social, economic, infrastructure gaps, among others, for decision-making at the territorial level (https://visor.geoperu.gob.pe).
SIGRID (Sistema de Información para la Gestión del Riesgo de Desastres) is an online platform managed by CENEPRED (National Centre for Disaster Risk Estimation, Prevention, and Reduction) that provides georeferenced information on disaster risk scenarios in Peru. It offers maps and data related to natural hazards, vulnerabilities, and risk management (https://sigrid.cenepred.gob.pe).
Geo Servidor is an online platform managed by the Ministry of the Environment (MINAM), providing georeferenced environmental information related to deforestation, land use, biodiversity, and protected areas (https://geoservidor.minam.gob.pe).
National Water Resources Observatory (Observatorio Nacional de Recursos Hídricos): is a tool of the SNIRH (National Water Resources Management System) of the ANA (National Water Authority), developed to disseminate information on water resources (https://snirh.ana.gob.pe/onrh/).
Geo Bosques is an online platform developed by Peru's Ministry of the Environment (MINAM) to provide georeferenced information on forest cover and deforestation. It offers real-time monitoring of forest loss, alerts on deforestation activities, and data on forest conservation areas. (https://geobosques.minam.gob.pe).
INAIGEM Geoportal: managed by the National Reseach Institute for Glaciers and Mountain Ecosystems (Instituto Nacional de Investigación en Glaciares y Ecosistemas de Montaña- INAIGEM) provides information on glacier retreat, mountain ecosystems and other glacier research (https://visor.inaigem.gob.pe).
Geocatmin is an online platform managed by INGEMMET (Geological, Mining, and Metallurgical Institute of Peru) that provides georeferenced information related to mining and geological data. It offers maps and spatial data on mineral resources, mining concessions, geological formations, and hazards (https://geocatmin.ingemmet.gob.pe).
Subnational indicators
INEI publishes all data necessary to analyse, assess and target adequate measures at the different territorial levels. The INEI website offers the general public access to the Microdata system (https://proyectos.inei.gob.pe/microdatos) and to the Regional Microdata system (https://sdmr.inei.gob.pe). From the INEI website, data can be accessed in excel files, as well through R packages from the Spatial Data Infrastructure (SDI) 7. The following indicators are available in excel file at Department level:
Economic indicators (GDP, Gross Value Added by industry8, CPI for Lima Metropolitana) as from 2007 (Base 2007), 1994-2006 (Base 1994).
Population by census year (last census 2017); population estimates at 30th of June by 5-year ranges and sex; births, deaths as from 2015 (total and 0-4); internal mobility over 5-year periods.
Labour force indicators (yearly and quarterly): Encuesta Nacional de Hogares (ENAHO) 2007-2021 and Permanent Survey of National Employment (EPEN) as from 2022 (with the following age ranges: 14-year-old or more, 14 to 24 -year-old, 25 to 44 -year-old, 45 year-old or more); informal labour.
Housing: share of housing ownership; Formalisation of plots of land in human settlements; Granting of title deeds in human settlements.
Social: Poverty and social expenditure: poverty and social expenditure.
Health: number of hospitals, number of hospital beds; number of doctors; and life expectancy at birth.
Education: student enrolment (3-5,6-11,12-16), educational attainment by level of education (15-year-old or more); number of teachers (public, private); Rate of young people (aged 18-24) not in employment nor in formal education and training, by gender (NINI rate ENAHO 2007-2022).
Environment: Environmental Conditions and Quality; Environmental resources and their use; Waste; Natural, Anthropic and Disaster Events; Human Habitat; Environmental Protection, Management and Awareness; and number of vehicles by type of engine.
Innovation and Communication Technologies: Households with access to information and communication technologies; Population with access to Internet; and Information and Communication Technologies in Local Governments.
Crimes: Vehicle theft9.
Degree of urbanisation
In 2020, INEI − within the framework of developing micro-regional data (https://sdmr.inei.gob.pe) in the Apurimac, Ene and Mantaro river valleys (SDRM-VRAEM) in 2020, and in collaboration with UNFPA and CentroGeo of Mexico − applied the definition of Degree of Urbanisation (DEGURBA) and Functional Urban Areas (FUAs). The aim was to contribute to the promotion of public policies and programmes that recognise the territorial diversity of Peru's rural areas, their links with urban areas and access to services based on the results of the 2017 national population and housing census.
In July 2023, the European Commission and the United Nations Human Settlements Programme (UNHABITAT), organised a workshop to apply the Degree of Urbanisation methodology for the production of urban data in Peru using locally produced data. The objective was to present the methodology to different territorial actors and facilitate INEI's use of the methodology to define urban and rural areas for statistical comparisons at the national level.
Functional urban areas
For statistical purposes, INEI defines an urban area as "the part of the territory of a district occupied by one or more urban population centres.10” Likewise, an urban population centre is defined as "a place with at least 100 dwellings grouped contiguously to form blocks and streets. All district capitals are considered urban population centres even if they do not meet the aforementioned condition".
In the case of metropolitan areas and intermediate cities, the Ministry of Housing, Construction and Sanitation (MVCS), within the framework of its functions and through the Supreme Decree No. 022-2016/MVCS "Regulation of Land Development and Sustainable Urban Development", have classified cities in hierarchical population ranges.
National Metropolis (1st rank): Continuous urban town that includes the metropolitan area of Lima‑Callao, which – as the main urban centre of the country –, presents an area of influence of national scope and is related to other cities on a global scale. It concentrates a large part of the country's financial, commercial, and administrative activity.
Regional Metropolis (2nd rank): Continuous urban town that maintains links with the National Metropolis. This continuum includes departmental capitals and may be the product of a process of conurbation of two or more cities and population centres, transcending political-administrative boundaries. Its geoeconomic space is functionally defined from a main centre or metropolitan centre that – due to its large population, dynamism (social, economic, political, administrative, and cultural), as well as its levels of infrastructure, services and markets – exerts a strong influence on cities and population centres with which they intensely exchange population flows, goods and services.
City (3rd to 5th rank): Continuous urban settlement with a population greater than 5 000 inhabitants. This continuum includes departmental, provincial and district capitals. It fulfils an urban function in the organisation of the territory and has essential public services, urban infrastructure for education, health, recreation, as well as spaces for housing, commercial, industrial, and service activities. They are classified into: (Mayor City (3rd rank), from 100 001 to 500 000 inhabitants; Intermediate City (4th rank), from 20 001 to 100 000 inhabitants; and Minor City (5th rank), from 5 001 to 20 000 inhabitants).
For the National Economic Census (CENEC) and the Permanent National Employment Survey (EPEN), INEI focuses on urban areas as its primary units of evaluation and analysis. However, certain national censuses and surveys also cover both urban and rural areas. Some of the key indicators produced by INEI include:
Employment indicators, for metropolitan Lima and urban areas, specifically those related to the Economically Active Population and Minimum Living Wage.
Population and housing indicators, such as Population Magnitude and Growth.
Social indicators, such as those related to students enrolled in the national education system in urban areas.
Environmental indicators, such as those related to human habitat, the proportion of the urban population living in slums, informal settlements, or inadequate housing.
Gender indicators, such as those related to salaried employment for men and women in urban areas, by economic status, economic activity and age, and the unemployment rate for men and women in urban areas.
Income-stratified maps at the block level of large cities.
Typologies of urban and rural areas
The definitions of urban and rural areas applied at the district level by INEI follow specific criteria based on housing clusters11:
Urban areas are defined as population centres with 2 000 or more inhabitants, where the houses are grouped closely together, forming blocks and streets. Urban centres include cities and their subdivisions, such as urbanisations, housing complexes, and emerging towns. For census purposes, areas with at least 100 contiguous houses (about 500 inhabitants) are also considered urban, including district capitals, even if they do not meet the minimum population threshold.
Rural areas are defined as population centres with fewer than 2 000 inhabitants. This classification applies in contrast to urban areas. There are 2 types of rural population centres: a) the rural population centre, with 500 to less than 2 000 inhabitants, with dwellings generally grouped together to form blocks and streets; and b) the rural population centre, village, camp, agricultural unit, etc., with less than 500 inhabitants and with dispersed dwellings. The categories of rural population centre are villages, annex, hamlet, community.
Overall, the Peru’s system of territorial statistics is of good quality and compiles a large amount of data and indicators related to regional development. Key demographic, socio-economic, and environmental indicators are generally available and easily accessible at the TL2 level, and some also available at the TL3 level. Peru has also begun implementing the degree of urbanisation and functional urban area methodologies to allow for more international comparison of its geographical units. Investments have also been made to facilitate data accessibility and disseminations, including through open data and digital technologies such as the Spatial Data Infrastructure Geoportal. Nevertheless, the government of Peru could consider taking additional steps to promote the use of territorial indicators throughout the policymaking process, including enhancing capacity at the regional and local levels to effectively utilise these indicators.
Comparability
In Peru, several challenges affect the collection and comparability of territorial statistics, which can be categorised as follows:
Geographical: Peru’s diverse geography, with its mix of urban and remote rural areas, poses logistical difficulties for collecting accurate and timely data from all regions.
Typologies:
The DEGURBA and FUA definitions are currently only applied to the VRAEM region (Valle de los Ríos Apurímac, Ene y Mantaro), which is a region in Peru encompassing parts of the departments of Ayacucho, Cusco, Huancavelica, and Junín. This limit domestic and international comparison.
The definitions for urban and rural areas do not specify (i) regions with strong urban-rural interactions, (ii) varying types of rural areas, or (iii) functional rural regions. Instead, they focus solely on population size and housing density, without addressing the complexities of urban-rural dynamics or the functional roles different rural areas may play,
Socio-economic: High rates of informality in both urban and rural areas hinder consistent data collection, as information may be incomplete or unreliable. This affects the accuracy of a wide range of indicators.
Institutional: The lack of standardised definitions (e.g., urban and rural areas or population centres) across institutions results in non-comparable data, highlighting the need for continuous updates and the strengthening of territorial statistical systems at regional and local levels. In addition, geographical definitions are not harmonised in a way that allow for international comparability, particularly for cities, and urban and rural areas. Peru could consider applying the OECD typology based on access to cities to provinces. By adopting this framework, Peru can ensure that its data on population distribution, urbanisation, and rural development are consistent with international standards.
Technological: Limited technological tools and high implementation costs lead to inconsistent, outdated, or missing data. Additionally, insufficient IT infrastructure, like internet access and geographic information systems (GIS), particularly in rural areas, complicates data collection and processing.
Data coverage
Overall, Peru benefits from a good coverage of territorial data and statistics to measure regional disparities and performances, which are accessible to the large public, especially at level of regiones. The statistical system of Peru is of quality and compiles a large amount of data and indicators related to regional development. Few indicators are missing to complete the OECD data request at subnational level:
Economic: Households disposable income; International trade in goods.
Demographic: Birth by age of the mother to calculate total fertility rates; Deaths by 5-year ranges; international migration flows and presence of migrants.
Labour: labour indicators for 15 to 64-year-old
Education: student enrolment (for the age ranges 6-14,15-19, 20-29, 30-39, 40-64); education attainment of the 25 to 64-year-old population by level of education (groups of ISCED 2011 levels 0-2, 3-4, 5-8, and disaggregated tertiary education 5,6,7,8.); early leavers rate.
Innovation: R&D expenses and personnel.
Social: Number of homicides; Voter turnout; Housing (number of rooms per capita, cost of housing as a share of household disposable income).
Subnational government finance data that are consistent with the international SNA.
Data dissemination
The subnational data coverage and completeness in Peru sufficiently meet the current statistical requirements for populating the OECD Regional database at the TL2 level, with the exception of indicators such as disposable income, international trade in goods, total fertility rates, deaths by age, international migration, labour indicators for the 15-64 age group, student enrolment, R&D, homicides, voting data, and housing. Further improvements at the TL3 level would help fill data gaps and enhance the international comparability of Peru at this level. The accessibility of subnational data can be enhanced by providing a dedicated data browser or APIs (Application Programming Interface) that allows users to easily fetch the indicators. Additionally, implementing systematic codification linked to regions and cities will further streamline data access.
Continue progressing in the use of harmonised geographical definitions that ensure international comparability. Peru has launched several projects to apply the degree of urbanisation and functional urban areas methodologies within specific parts of its territory. However, to ensure consistent definitions of functional urban areas (FUAs), cities, as well as urban and rural areas − including urban-rural linkages − that are comparable across countries. This work needs to be consolidated nationwide. This is essential not only for effectively monitoring global agendas, such as the Sustainable Development Goals (SDGs), but also for improving metropolitan governance and understanding urban-rural linkages within the country.
Strengthen data production, dissemination, and visualisation on indicators at the small region level (TL3). Beyond the use of census and survey data, this could be done by expanding data integration from administrative registers and by leveraging on new and innovative sources of data. Measuring economic, social, and environmental outcomes at the level of provinces can provide valuable insights on geographical disparities, including by meaningful and comparable classifications of small regions such as the access-to-city typology, as promoted by the OECD (OECD, 2022[6]).
Keep leveraging the use of administrative registers, and innovative data sources and technologies. The use of administrative registers, and unconventional data sources – such as satellite imagery, geospatial data, and big data – could be tested and eventually integrated to fill important data gaps and to improve the accuracy of certain territorial indicators. Leveraging these new data sources would provide better insights into territorial dynamics, speed up real-time information collection, and allow for better anticipation and preparation to socio-economic and environmental shocks.
Enhance the systematic integration and use of indicators into territorial planning and performance monitoring. While Peru has significantly advanced on the production of territorial indicators, more efforts are needed to increase the use of those indicators in the different stages of policymaking. Indeed, multidimensional territorial indicators should be systematically integrated into the design and monitoring of public policies in Peru, particularly in the priority areas identified in this report. It is essential to establish evaluation mechanisms that rely on these indicators to track progress and continuously adjust public strategies based on the results achieved.
Improve management of subnational data dissemination and visualisation tools. Peru has advanced on subnational and georeferenced data dissemination. However, the proliferation of platforms can make it challenging for users to locate the necessary data. The country could streamline this by consolidating data into fewer platforms and reducing the duplication of indicators across existing web tools. This could simplify data maintenance and enhance the user experience. Also, the interoperability of subnational data across the national statistical system could be improved by keep investing in formats and standards, making it easier to exchange and integrate data with other systems.
References
[3] Dijkstra, L., H. Poelman and P. Veneri (2019), “The EU-OECD definition of a functional urban area”, OECD Regional Development Working Papers, No. 2019/11, OECD Publishing, Paris, https://doi.org/10.1787/d58cb34d-en.
[2] Fadic, M. et al. (2019), “Classifying small (TL3) regions based on metropolitan population, low density and remoteness”, OECD Regional Development Working Papers, No. 2019/06, OECD Publishing, Paris, https://doi.org/10.1787/b902cc00-en.
[5] OECD (2024), Regions,cities and loval areas statistics (databases), https://data-explorer.oecd.org/?lc=en&fs[0]=Topic%2C0%7CRegions%2C%20cities%20and%20local%20areas%23GEO%23&pg=0&fc=Topic&bp=true&snb=58.
[6] OECD (2022), OECD Regions and Cities at a Glance 2022, OECD Publishing, Paris, https://doi.org/10.1787/14108660-en.
[1] OECD (2022), OECD Territorial grid, https://www.oecd.org/regional/regional-statistics/territorial-grid.pdf.
[4] OECD (2018), Extended regional typology, https://www.oecd-ilibrary.org/sites/reg_cit_glance-2018-50-en/index.html?itemId=/content/component/reg_cit_glance-2018-50-en&mimeType=text/html.
← 1. For further information see: Reglamento de la Ley Nº 27795, Ley de Demarcación y Organización Territorial, D.S N° 019-2003-PCM, https://www.minam.gob.pe/wp-content/uploads/2017/04/Ley-N%C2%B0-27795.pdf
← 2. For further information see: https://ide.inei.gob.pe/
← 3. For further information see: https://www.inei.gob.pe/biblioteca-virtual/investigaciones.
← 4. CEPLAN Territorial information platform: https://geo.ceplan.gob.pe.
← 5. CEPLAN National Foresight Observatory: https://observatorio.ceplan.gob.pe/inicio.
← 6. List of International Conventions on the Environment signed by Peru, SINIA website: https://sinia.minam.gob.pe/documentos/relacion-convenios-internacionales-medio-ambiente-suscritos-peru.
← 7. INEI: download R package Peruvian data managed by the Spatial Data Infrastructure (SDI) https://geografo.pe/geoidep.
← 8. For further information see: https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib0883/Libro.pdf
← 9. INEI Public safety https://www.inei.gob.pe/estadisticas/indice-tematico/seguridad-ciudadana.
← 10. INEI definition of urban centres in Census: https://proyectos.inei.gob.pe/web/biblioineipub/bancopub/Est/Lib0862/anexo04.pdf
← 11. For further information see: INEI https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1539/cap01.pdf and https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1383/anexo02.pdf.