Population, territory and sustainable development

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29 Box IV.1 GRADIENT-BASED DEFINITIONS AND ESTIMATES OF THE RURAL POPULATION Population censuses are one of the chief sources of information used in demographic studies and, as here, in the study of the rural population. The definitions of “urban” and “rural” used in censuses vary a great deal, however, at times even from one census to another in the same country. As a result, the question of the international comparability of census figures used in cross-country analyses and in population estimates and projections is sometimes a controversial one. The criteria used in censuses to classify population groups as urban or rural include numerical parameters according to which a settlement is defined as urban if it has a given number of inhabitants (e.g. 1,000, 1,500, 2,000, 2,500), a specified number of contiguous dwellings or a given population density within a defined area, with the zones that do not meet those requirements being defined as rural on a residual basis. There are also administrative parameters, whereby the capital or seat of government of a local administrative district (e.g. parish, municipality, canton) is defined as urban and everything else as rural. In some cases, a combination of criteria is used. For example, some countries use a mixture of administrative and locational parameters and determine which areas are to be categorized as urban based on a combination of political/administrative factors (capital or seat of the municipal government, for example) and the presence of certain types of basic infrastructure, blocks and some public utilities, with everything else being defined as rural. Others combine numeric and functional criteria, with urban areas being defined on the basis of a minimum number of inhabitants and the availability of basic infrastructure for the delivery of public services; here again, rural areas are defined residually. Still others combine numeric criteria with parameters relating to the sectoral composition of the economically active population (see table 1). As can be seen from the following table, over the past 50 years many of the countries have changed the criteria they use for this purpose, while others have maintained the same criterion. For example, Argentina, the Bolivarian Republic of Venezuela, Mexico and the Plurinational State of Bolivia have all used a numeric criterion, although the numeric threshold that they use differs and, in some cases, has also differed from one census to the next within the same country. Brazil, the Dominican Republic, Ecuador, Haiti and Uruguay, on the other hand, define their urban populations on the basis of a political/administrative criterion. Others have used a mixture of criteria, as in the cases of Costa Rica, which combines a political/administrative criterion with an infrastructure-based standard, and Chile, which has used numeric and functional (production activity) criteria in its last two censuses. Secondary/primary criteria Size of population Table 1 LATIN AMERICA: CENSUS DEFINITIONS OF URBAN AND RURAL POPULATION GROUPS, BY PRIMARY AND SECONDARY CRITERIA, 1950-2000 Size of population Infrastructure/services Production activity Political/administrative status Argentina Bolivia (Plurinational State of) Mexico Puerto Rico Venezuela (Bolivarian Republic of) Chile (1970) Cuba (1970, 1981, 2002) Guatemala (1950) Honduras (1961, 1974, 1988, 2001) Nicaragua (1963, 1971, 1995, 2005) Panama Chile (1992, 2002) Nicaragua (1963, 1971) Colombia (1964, 1973) Nicaragua (1995 y 2005) Peru (1972, 1981, 1993, 2007) Guatemala (2002) Infrastructure/services Cuba (1953) El Salvador (2007) Locational criteria Chile (1982) Chile (1960) Political/administrative Peru (1940) Chile (1952) status Costa Rica Paraguay (1962) Peru (1961) Brazil Colombia (1951, 1985, 1993) Dominican Republic Ecuador El Salvador (1950, 1961, 1971, 1992) Guatemala (1964, 1973, 1981, 1994) Haiti Honduras (1950) Jamaica Nicaragua (1950) Paraguay (1950, 1972, 1982, 1992, 2002) Uruguay Source: Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC, on the basis of Jorge Rodríguez, “Distribución espacial de la población de Latin America and the Caribbean: tendencias, interpretaciones y desafíos para las políticas públicas”, Población y desarrollo series, No. 32 (LC/L.1831–P), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), 2002. United Nations publication, Sales No. S.02.II.G.137. The countries of the region thus use differing criteria for estimating the size of the rural population, and membership in that population is a residual demographic category, since the countries start by determining which areas are urban and estimating the size of the urban population on that basis, with everyone that is left over being classified as rural.
30 Box IV.1 (concluded) In addition, since the cut-off levels are low and since density or remoteness are not used as criteria, many population groups that live in what are essentially rural areas (with a scattered population) are classified as residing in urban areas. None of the countries uses population density or the distance from towns as explicit criteria either, even though they are often associated with the economic and geographical dividing lines between urban and rural areas (Rodríguez and Meneses, 2011). This classification of the ways in which urban and rural areas are defined therefore fails to settle the controversy, since, once a country has chosen one or more parameters, it must then make other decisions about the specification of its indicators and cut-off points which will have very important operational implications (Rodríguez, 2002). When numerical or political/administrative criteria are used, the corresponding indicators are obvious, but in other cases, such as when, for example, criteria based on locational factors and production activity are used, then the selection may become a subject of heated debate. Thus, no matter what definition is used, difficult decisions have to be made about where to set the cut-off points (Rodríguez, 2002). Reservations about the accuracy of measurements of rural areas have led to the proposal of some alternative methods. More recent approaches focus on setting aside this kind of demographic definition of rurality and replacing it with one in which rural areas are viewed as territories, as a spatial category that is chiefly defined on the basis of population density, remoteness and economic activity (Dirven, 2011). Rural territories are then seen as being characterized by low population density, remoteness and a predominance of primary economic activities. This territorial approach also focuses on discerning the heterogeneity of rural areas, of the interactions among them and between them and urban areas, and the way that these relationships evolve. In order to achieve this, it becomes necessary to make the shift from dichotomic measurements to gradient-based measurements or rurality indices, such as the following: (i) A combined density/economic-activity gradient: A different approach to estimating “rurality” is to use a combination of population density and the share of agricultural employment. Density is determined by measuring the population in the next-smallest administrative division after municipal districts (minor administrative divisions) --referred to as “areas of analysis”-- using census microdata and digital census maps. Economic activity is incorporated at the lower level, which is generally the level of the units used to collect census data. This is the level at which small areas in which at least 35% of the economically active population (EAP) is employed in agriculture are identified. These areas are then aggregated at the level of areas of analysis. This makes it possible to determine, for each area of analysis, what percentage of all small areas have at least 35% of their EAP employed in the agricultural sector. Candia (2011) takes a somewhat different approach by combining information on population density and agricultural employment with the level of unmet basic needs (UBN) in the different categories of areas of analysis. This yields two important findings: (a) the extent of unmet basic needs increases as population density decreases; and (b) the extent of unmet basic needs increases as the percentage of the EAP employed in agriculture rises. (ii) A multi-variable rural-urban gradient: Saborío and Rodríguez (2008) use geographic information systems (GIS) and satellite imagery restitution tools developed by Arce and Samudio (2008) to construct a rurality gradient that merges environmental information, information on land use, geographical data (distance to roads and towns) and economic information (the share of employment accounted for by agriculture). They first develop a rurality index that combines information on land use and remoteness. This information is then synthesized into a rural-urban gradient which is then supplemented with information on the employment status of the economically active population. This gradient-based approach marks a departure from the idea that rurality is something that transitions linearly into urbanity. Furthermore, since poverty is not a variable that is included in any of the original indices, it also leaves behind the idea that “rural” can be equated with “poverty” or “backwardness”. Nonetheless, as will become evident in the discussions presented in this chapter, the persistence of social inequalities associated with the urban-rural dichotomy used in censuses and surveys is a powerful argument for its validity, and it will therefore be used in this study as well. Source: Latin American and Caribbean Demographic Centre (CELADE) - Population Division of ECLAC, on the basis of Jorge Rodríguez, “Distribución espacial de la población de Latin America and the Caribbean: Tendencias, interpretaciones y desafíos para las políticas públicas”, Población y desarrollo series, No. 32 (LC/L.1831–P), Santiago, Chile, Economic Commission for Latin America and the Caribbean (ECLAC), 2002. United Nations publication, Sales No. S.02.II.G.137; Economic Commission for Latin America and the Caribbean (ECLAC), “Urbanization prospects”, Demographic Observatory, No. 8 (LC/G.2422-P), Santiago, Chile, 2009. United Nations publication, Sales No. E/S.10.II.G.57; A. Rodríguez and J. Meneses, “Transformaciones rurales en Latin America y sus relaciones con la rural population”, paper presented at the Expert Meeting on Population, Territory and Sustainable Development, Santiago, Chile, 16-17 August 2011; M. Dirven, “El empleo rural no agrícola: tendencias, interpretaciones y políticas”, paper presented at the Expert Meeting on Population, Territory and Sustainable Development, Santiago, Chile, 16-17 August 2011.
Page 3 and 4: Alicia Bárcena Executive Secretary
Page 5 and 6: 4 Chapter VII Regional inequalities
Page 7 and 8: 6 Table V.3 Latin America (9 countr
Page 9 and 10: 8 Figure IV.10 Latin America (selec
Page 11 and 12: 10 Map VII.5 Plurinational State of
Page 13 and 14: 12 This document is therefore divid
Page 16 and 17: 15 Chapter II CONCEPTS, DEFINITIONS
Page 18 and 19: 17 which guarantee comparability. C
Page 20 and 21: 19 social inclusion, with improveme
Page 22: 21 The above description is clearly
Page 25 and 26: 24 Table III.1 LATIN AMERICA AND TH
Page 27 and 28: 26 Table III.3 LATIN AMERICA (19 CO
Page 29: 28 While the rural population of La
Page 33 and 34: 32 As a result of the absolute and
Page 35 and 36: 34 The sustained decline in the rur
Page 37 and 38: 36 Country Table IV.2 LATIN AMERICA
Page 39 and 40: 38 Country Table IV.5 LATIN AMERICA
Page 41 and 42: 40 Box IV.3 THE AGEING OF THE RURAL
Page 43 and 44: 42 Rodríguez and Meneses (2011) co
Page 45 and 46: 44 The classification outlined in t
Page 47 and 48: 46 An analysis of the results obtai
Page 49 and 50: 48 Although the inhabitants of some
Page 51 and 52: 50 Non-agricultural employment has
Page 53 and 54: 52 C. PRODUCTION PATTERNS AND THE R
Page 55 and 56: 54 Box IV.5 IMPACTS OF SOYBEAN PROD
Page 57 and 58: 56 A recent study entitled Inserci
Page 59 and 60: 58 Table IV.11 LATIN AMERICA: POOR
Page 61 and 62: 60 Figure IV.7 POVERTY IN RURAL HOU
Page 63 and 64: 62 Box IV.6 (concluded) These and o
Page 65 and 66: 64 combine a number of factors of w
Page 67 and 68: 66 Figure IV.10 LATIN AMERICA (SELE
Page 69 and 70: 68 The data in figure IV.11 also sh
Page 71 and 72: 70 Figure IV.12 LATIN AMERICA: AVER
Page 73 and 74: 72 Box IV.8 ADOLESCENT FERTILITY IN
Page 75 and 76: 74 Map V.1 SOUTH AMERICA: POPULATIO
Page 77 and 78: 76 Prime examples of this include t
Page 79 and 80: 78 Table V.2 LATIN AMERICA (9 COUNT
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80 creation of tax-free zones, the
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82 Box V.2 (concluded) State polici
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84 In any case, only once the infor
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86 It is not possible to draw direc
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88 studies was conducted recently b
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90 C. THE POLITICAL CONTEXT AND MOB
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93 Chapter VII REGIONAL INEQUALITIE
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95 Map VII.2 LATIN AMERICA AND THE
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97 Some of these programmes were su
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99 D. TERRITORIAL EQUITY, REGIONAL
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101 Map VII.3 CHILE: CLASSIFICATION
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103 In Mexico, most of the chronica
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105 Figure VII.3 ECUADOR: POVERTY R
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107 However, internal migration can
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109 Table VII.5 LATIN AMERICA (SELE
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111 Table VII.7 PERU (SIERRA DEPART
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113 Lastly, in the case of Ecuador,
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115 Chapter VIII SUSTAINED URBANIZA
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117 This chapter presents the most
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119 Busso, 2009; and ECLAC-UN-HABIT
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121 estimate of the urban populatio
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123 Figure VIII.2 LATIN AMERICA AND
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125 First, the region’s economy i
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127 urbanized; the rural population
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129 rural areas. According to the s
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131 the absence of a strategic visi
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133 The need to design ad hoc inter
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135 settlements with low-income pop
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137 Figure VIII.4 LATIN AMERICA AND
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139 At the same time, decentralizat
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142 The rest of the system of citie
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144 Table IX.1 LATIN AMERICA: NUMBE
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146 First is the demographic scope
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148 Basing the same series on towns
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150 Table IX.2 LATIN AMERICA: PROSP
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152 The data emerging from 2010 cen
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154 City size Table IX.6 LATIN AMER
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156 Figure IX.5 LATIN AMERICA (1,73
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158 For unemployment, the picture i
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160 rate differential among the dif
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162 individuals valued cultural fac
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164 that draw migrants, due precise
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166 Table IX.10 LATIN AMERICA AND T
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169 Chapter X TRENDS, MUTATIONS AND
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171 Table X.2 LATIN AMERICA: EVOLUT
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173 1. Demographic evolution of lar
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175 As table X.4 shows, during the
Page 178 and 179:
177 comparison. But the most convin
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179 in recent years, which are desc
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181 Map X.2 MEXICO: INTERCENSAL GRO
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183 irregular settlements known as
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185 The third argument is based on
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187 Map X.4 MEXICO CITY: EXTENDED M
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189 more general social inequalitie
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191 5. Concluding remarks: the grea
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194 In view of lower internal migra
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196 familiarity with surroundings a
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198 connections; (ii) identify the
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200 The report casts light on an is
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202 Box XI.3 PROTECTING THE ECOSYST
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204 In view of the above, the prima
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206 overlap of functions and alloca
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208 Many of the programmes develope
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210 A breakdown of net migration by
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212 Box XI.8 (concluded) Case studi
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215 Bibliography Abba, Artemio Pedr
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217 Cecchini, S. and A. Madariaga (
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219 (2010a), Time for equality: clo
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221 Hiebert, Daniel and David Ley (
Page 224 and 225:
223 Pendall, R., R. Puentes and J.
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225 Rodríguez, J. and M. Villa (19
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