The present configuration of Brazil’s economic space is heavily rooted in the development path followed by the country since colonial times. The uneven distribution of wealth in the Brazilian territory is characterized by a high concentration of resources in the Center-South portion of the country. In the classification adopted in B-MARIA, in which the regional setting consists of three different regions – North, Northeast, and Center-South (Rest of Brazil), the latter comprises the more dynamic regions of the Southeast and South, as well as the Center-West (Map 1.1). This classification, heavily constrained by data availability, considers the Southeast, South and Center-West regions as a single region, precluding the analysis of each of these regions individually. However, the regional delimitation still offers a great range of analytical possibilities focusing on the less developed regions of the North and Northeast Brazil. The degree of regional inequality in Brazil can be gauged from Table 1.1 below, which shows the proportion of the average per capita output of each region to the national average per capita output. While the Northeast presented, in 1994, an average per capita output 50% below of the national average, and the North reached only 68.0% of the national average, the other regions, especially the Southeast, showed indicators substantially above the national average. These differences in regional wealth are accompanied by impressive differences in regional social indicators as well, which can be summarized by the poverty incidence indicator estimated by IPEA: in 1990, 40.9% of the population in the Northeast were considered to be indigent, in contrast to 13.9% in the North, 12.4% in the Southeast, 18.1% in the South, and 16.1% in the Center-West (Guimarães Neto, 1995).
巴西目前的经济空间格局在很大程度上植根于该国自殖民时代以来所走的发展道路。巴西领土上财富分配不均的特点是资源高度集中在该国中南部地区。在B-MARIA采用的分类中，区域环境包括三个不同的区域——北部、东北部和中南部(巴西其他地区)，后者包括东南部和南部更有活力的地区，以及中西部(图1.1)。这种分类受到数据可用性的严重限制，将东南、南部和中西部地区视为一个单一区域，无法对每个区域进行单独分析。但是，区域划分仍然提供了很大范围的分析可能性，重点放在巴西北部和东北部较不发达的区域。区域不平等的程度在巴西可以从下面的表1.1,测量显示的平均人均产出的比例每个地区是全国平均水平的人均产出。1994年，东北地区的人均产出比全国平均水平低50%，北方仅达到全国平均水平的68.0%，而其他地区，特别是东南地区的指标则大大高于全国平均水平。这些地区财富的差异也伴随着地区社会指标的显著差异，这可以用IPEA估计的贫困发生率指标来概括:1990年，东北地区40.9%的人口被认为是贫困的，而北部为13.9%，东南部为12.4%，南部为18.1%，中西部为16.1% (guimar es Neto, 1995)。
{"title":"Regional Development and Regional Inequality: An Overview of the Brazilian Economy","authors":"E. Haddad","doi":"10.1201/9780429449406-1","DOIUrl":"https://doi.org/10.1201/9780429449406-1","url":null,"abstract":"The present configuration of Brazil’s economic space is heavily rooted in the development path followed by the country since colonial times. The uneven distribution of wealth in the Brazilian territory is characterized by a high concentration of resources in the Center-South portion of the country. In the classification adopted in B-MARIA, in which the regional setting consists of three different regions – North, Northeast, and Center-South (Rest of Brazil), the latter comprises the more dynamic regions of the Southeast and South, as well as the Center-West (Map 1.1). This classification, heavily constrained by data availability, considers the Southeast, South and Center-West regions as a single region, precluding the analysis of each of these regions individually. However, the regional delimitation still offers a great range of analytical possibilities focusing on the less developed regions of the North and Northeast Brazil. The degree of regional inequality in Brazil can be gauged from Table 1.1 below, which shows the proportion of the average per capita output of each region to the national average per capita output. While the Northeast presented, in 1994, an average per capita output 50% below of the national average, and the North reached only 68.0% of the national average, the other regions, especially the Southeast, showed indicators substantially above the national average. These differences in regional wealth are accompanied by impressive differences in regional social indicators as well, which can be summarized by the poverty incidence indicator estimated by IPEA: in 1990, 40.9% of the population in the Northeast were considered to be indigent, in contrast to 13.9% in the North, 12.4% in the Southeast, 18.1% in the South, and 16.1% in the Center-West (Guimarães Neto, 1995).","PeriodicalId":106051,"journal":{"name":"Regional Inequality and Structural Changes","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121815295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Linkage and Interdependence in the Brazilian Economy: The B-MARIA Data Input Files","authors":"E. Haddad","doi":"10.1201/9780429449406-4","DOIUrl":"https://doi.org/10.1201/9780429449406-4","url":null,"abstract":"","PeriodicalId":106051,"journal":{"name":"Regional Inequality and Structural Changes","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124352060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Conclusion","authors":"E. A. Haddad","doi":"10.1201/9780429449406-6","DOIUrl":"https://doi.org/10.1201/9780429449406-6","url":null,"abstract":"","PeriodicalId":106051,"journal":{"name":"Regional Inequality and Structural Changes","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123681331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interregional Computable General Equilibrium Models: A Survey on Specification and Implementation Issues","authors":"E. Haddad","doi":"10.1201/9780429449406-2","DOIUrl":"https://doi.org/10.1201/9780429449406-2","url":null,"abstract":"","PeriodicalId":106051,"journal":{"name":"Regional Inequality and Structural Changes","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124787022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Regional Impacts of Macroeconomic, Structural and Sectoral Policies in the Brazilian Economy","authors":"E. Haddad","doi":"10.1201/9780429449406-5","DOIUrl":"https://doi.org/10.1201/9780429449406-5","url":null,"abstract":"","PeriodicalId":106051,"journal":{"name":"Regional Inequality and Structural Changes","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120923914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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