Análise espacial exploratória da relação entre crescimento do PIB e desempenho da agricultura no Rio Grande do Sul
Exploratory spatial analysis of the relationship between GDP growth and agricultural performance in Rio Grande do Sul
Francisco Mazzarolo Seger; Rogério Costa Campos; Mario Duarte Canever; Roberto Mattes Horn
Resumo
Palavras-chave
Abstract
Abstract:: Despite the importance of the Value of Agricultural Production (VAP) for the GDP of Rio Grande do Sul, no quantitative work has been carried out on local scale to assess how this importance may vary over the space. The knowledge about how the VAP is transferred to GDP remains aggregated for the entire state and speculative at local scales. In this study the growth of the GDP (cGDP) and Agricultural Production Value (cVAP) were verified in an Exploratory Spatial Analysis (ESA) to assess the sensitivity of the results to state partitioning and adjacency relationships. Evidences of spatial structuring of the association between cVAP and cGDP were verified in a Monte Carlo test to conclude that the association is non-stationary and heterogeneously defined by the local economy.
Keywords
Referências
Alonso, J. A. F. (2006). A persistência das desigualdades regionais no RS: velhos problemas, soluções convencionais e novas formulações.
Alonso, J. A. F., Benetti, M. D., & Bandeira, P. S. (1994).
Atkinson, R. D. (1998). Technological change and cities.
Audirac, I. (2005). Information technology and urban form: challenges to smart growth.
Bidanset, P. E., & Lombard, J. R. (2014). The effect of kernel and bandwidth specification in geographically weighted regression models on the accuracy and uniformity of mass real estate appraisal.
Chelotti, M. C., & Castanho, R. B. (2006). Territórios da lavoura de arroz e de soja no Rio Grande do Sul: especificidades na produção do espaço agrário regional.
Clark, S. D. (2007). Estimating local car ownership models.
Corrêa, J. C. S., Silveira, R. L. L., & Kist, R. B. B. (2019). Sobre o conceito de desenvolvimento regional: notas para debate.
Du, Q., Wu, C., Ye, X., Ren, F., & Lin, Y. (2018). Evaluating the effects of landscape on housing prices in urban China.
Fochezatto, A., & Ghinis, C. P. (2012). Estrutura produtiva agropecuária e desempenho econômico regional: o caso do Rio Grande do Sul, 1996-2008.
Fochezatto, A., & Grando, M. Z. (2009). Efeitos da estiagem de 2008 na economia do Rio Grande do Sul: uma abordagem multissetorial.
Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002).
Fundação de Economia e Estatística Siegfried Emanuel Heuser – FEE. (2023a).
Fundação de Economia e Estatística Siegfried Emanuel Heuser – FEE. (2023b).
Gibbs, D., & Tanner, K. (1997). Information and communication technologies and local economic development policies: the British case.
Gollini, I., Lu, B., Charlton, M., Brunsdon, C., & Harris, P. (2015). GWmodel: an R package for exploring spatial heterogeneity using geographically weighted models.
Guo, L., Ma, Z., & Zhang, L. (2008). Comparison of bandwidth selection in application of geographically weighted regression: a case study.
Harris, P., & Brunsdon, C. (2010). Exploring spatial variation and spatial relationships in a freshwater acidification critical load data set for Great Britain using geographically weighted summary statistics.
Instituto Brasileiro de Geografia e Estatística – IBGE. (2017).
Instituto Brasileiro de Geografia e Estatística – IBGE. (2019).
Kutay, A. (1986). Effects of telecommunications technology on office location.
Lazzari, M. (2012). Economia gaúcha dependente da agropecuária.
Leamer, E. E., & Storper, M. (2001).
Lewandowska-Gwarda, K. (2018). Geographically weighted regression in the analysis of unemployment in Poland.
Ma, X., Zhang, J., Ding, C., & Wang, Y. (2018). A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership.
Mack, E. A., & Grubesic, T. H. (2009). Broadband provision and firm location in Ohio: an exploratory spatial analysis.
Mirzaei, M.; Bertazzon, S.& Couloigner, I. (2018). OLS and GWR LUR models of wildfire smoke using remote sensing and spatiotemporal data in Alberta.
Moss, M. L. (1998). Technology and cities.
Perroux, F. (1967).
Risco, G. (2016). Distribuição dos setores da economia gaúcha por municípios.
Schuh, A. B., Silva, M. L., Trevisan, L. V., & Coronel, D. A. (2018). Perfil industrial do Rio Grande do Sul e a hipótese de desindustrialização.
Secretaria de Planejamento e Desenvolvimento Regional – SEPLAN-RS. (2015).
Vinayaraj, P., Raghavan, V., & Masumoto, S. (2016). Satellite-derived bathymetry using adaptive geographically weighted regression model.
Zook, M. A. (2005).
Submetido em:
09/03/2022
Aceito em:
27/10/2022