title: Determinants of efficiency in the provision of municipal street-cleaning and refuse collection services.
abstract: Effective waste management systems can make critical contributions to public health, environmental sustainability and economic development. The challenge affects every person and institution in society, and measures cannot be undertaken without data collection and a quantitative analysis approach. In this paper, the two-stage double bootstrap procedure of Simar and Wilson (2007) is used to estimate the efficiency determinants of Spanish local entities in the provision of public street-cleaning and refuse collection services. The purpose is to identify factors that influence efficiency. The final sample comprised 1072 municipalities. In the first stage, robust efficiency estimates are obtained with Data Envelopment Analysis (DEA). We apply the second stage, based on a truncated-regression, to estimate the effect of a group of environmental factors on DEA estimates. The results show the existence of a significant relation between efficiency and all the variables analysed (per capita income, urban population density, the comparative index of the importance of tourism and that of the whole economic activity). We have also considered the influence of a dummy categorical variable - the political sign of the governing party - on the efficient provision of the services under study. The results from the methodology proposed show that municipalities governed by progressive parties are more efficient.
authors.affiliation: University of Murcia, Spain. benitobl@um.es
authors.forename: Bernardino
authors.initials: B
authors.lastname: Benito-López
authors.forename: María del Rocio
authors.initials: Mdel R
authors.lastname: Moreno-Enguix
authors.forename: José
authors.initials: J
authors.lastname: Solana-Ibañez
mesh_terms: D002947:Cities; D017598:Efficiency, Organizational; D015233:Models, Statistical; D011057:Politics; D011156:Population Density; D012037:Refuse Disposal / Q000191:economics / Q000379:methods*; D012044:Regression Analysis; D012959:Socioeconomic Factors; D013030:Spain; D018505:Waste Management / Q000379:methods*