A statistical analysis of the energy effectiveness of building refurbishment

Owing to the rapid urban growth of past decades, the refurbishment of buildings has become a central topic ofcity development. A key aspect of building renovations deals with energy saving, both for economic and en-vironmental concerns. The present literature mainly focuses on technological solutions for buildings, and therelateddataarestudiedwithdescriptivestatistics.Instead,thispaperaimstoevaluatetheenergyeffectivenessofrefurbishment interventions from a global sector viewpoint. This implies building representative datasets, de-veloping asyntheticcostindicator,estimatingaproperregression model, evaluatingthe meaningof resultsandoutline proper support policies. Two relevant case-studies are considered: the first is a published dataset ofEuropean service buildings, which contains detailed information on the undertaken interventions. The cost in-dicator is builtby averaging standard costs per square meter; next, a Beta regression model is fitted to the data.Thisbelongstotheclassof generalizedlinearmodels(GLM)anditis suitablewhenthedependentvariable(thesaving rate) has an asymmetrical distribution on the interval [0,1]. The second case study is a survey on theretrofitting decisions of households in an urban area of Venice; the related dataset includes information on thecost of investment, the energy saving, and the comfort improvement. Comfort may be a subjective perception,including physical, psychological and economic wellness;however, it is alsoa drive for housing renovation andfor energy saving itself. Statistical analyses show a significant positive dependence between all variables, con-firming the energy saving effectiveness of refurbishment interventions. On the base of these results, properrefurbishment policies, both for public and private actors, are finally proposed.