Spatial Determinants of Urban Residential Water Demand in Fortaleza, Brazil

被引:0
|
作者
Diego de Maria André
José Raimundo Carvalho
机构
[1] CAEN/UFC and LECO/UFC (Laboratório de Econometria e Otimização),
来源
Water Resources Management | 2014年 / 28卷
关键词
Spatial effects; Spatial regression; Water demand; C21; Q21; Q25;
D O I
暂无
中图分类号
学科分类号
摘要
This paper aims at estimating the residential water demand function for the city of Fortaleza, Brazil, considering the potential impact of including spatial effects in the model. The empirical evidence is a unique micro-data set obtained through a household water consumption survey carried out in 2007. We estimated three econometric models, which have as explanatory variables the average/marginal price, the difference, income, number of male and female residents and the number of bathrooms, under different spatial specifications: the Spatial Error Model (SEM), the Spatial Autoregressive model (SAR), and finally, the Spatial Autoregressive Moving Average model (SARMA). Results suggest that the SARMA model is the “best” as shown by a series of tests. Such results contradict conclusions drawn by Chang et al. (Urban Geogr 31(7):953–972, 2010), House-Peters et al. (JAWRA J Am Water Resour Assoc 46(3), 2010), and Ramachandran and Johnston (2011). This means, among other things, that not controlling spatial effects is a key specification error, underestimating the effect of almost all variables in the model. Sometimes, these differences can be as high as 24.66 % and 13.32 % for price elasticity in the Average Price and the McFadden models, respectively.
引用
收藏
页码:2401 / 2414
页数:13
相关论文
共 50 条
  • [1] Spatial Determinants of Urban Residential Water Demand in Fortaleza, Brazil
    Andre, Diego de Maria
    Carvalho, Jose Raimundo
    WATER RESOURCES MANAGEMENT, 2014, 28 (09) : 2401 - 2414
  • [2] Determinants of urban residential water demand in Libya
    Daw, Mabroka Mohamed
    Ali, Elhadi Ramadan
    Toriman, Mohd Ekhwan
    INTERNATIONAL JOURNAL OF INNOVATION AND SUSTAINABLE DEVELOPMENT, 2021, 15 (03) : 261 - 279
  • [3] Urban Water Demand Modeling Using Machine Learning Techniques: Case Study of Fortaleza, Brazil
    Nunes Carvalho, Tais Maria
    de Souza Filho, Francisco de Assis
    Porto, Victor Costa
    JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 2021, 147 (01)
  • [4] Determinants of residential water demand in Germany
    Schleich, Joachim
    Hillenbrand, Thomas
    ECOLOGICAL ECONOMICS, 2009, 68 (06) : 1756 - 1769
  • [5] Estimating the Determinants of Residential Water Demand in Italy
    Romano, Giulia
    Salvati, Nicola
    Guerrini, Andrea
    WATER, 2014, 6 (10) : 2929 - 2945
  • [6] Determinants of tuberculosis transmission and treatment abandonment in Fortaleza, Brazil
    Harling, Guy
    Lima Neto, Antonio S.
    Sousa, Geziel S.
    Machado, Marcia M. T.
    Castro, Marcia C.
    BMC PUBLIC HEALTH, 2017, 17
  • [7] URBAN RESIDENTIAL DEMAND FOR WATER IN THE UNITED-STATES
    FOSTER, HS
    BEATTIE, BR
    LAND ECONOMICS, 1979, 55 (01) : 43 - 58
  • [8] Future implications of urban intensification on residential water demand
    Ghavidelfar, Saeed
    Shamseldin, Asaad Y.
    Melville, Bruce W.
    JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT, 2017, 60 (10) : 1809 - 1824
  • [9] POLICY RELEVANCE IN STUDIES OF URBAN RESIDENTIAL WATER DEMAND
    MARTIN, WE
    THOMAS, JF
    WATER RESOURCES RESEARCH, 1986, 22 (13) : 1735 - 1741
  • [10] Temporal and spatial aggregation in modeling residential water demand
    Guercio, R
    Magini, R
    Pallavicini, I
    WATER RESOURCES MANAGEMENT II, 2003, 8 : 151 - 160