Impact of environmental variables on the efficiency of water companies in England and Wales: a double-bootstrap approach

Assesing the influence of environmental variables on the performance of water companies: An efficiency analysis tree approach

“…The efficiency of the English and Welsh water industry improved considerably during the 2006-2010 period. Regulatory incentives might positively impact efficiency, such as sharing any outperformance in expenditure with customers and financial rewards and penalties when network quality improves (Villegas et al, 2019). The efficiency of WaSCs substantially improved (from 0.439 to 0.517, on average), whereas the mean efficiency of WoCs increased slightly (from 0.508 to 0.537).…”

“…order-m (Simar and Wilson, 2007;Ferreira and Marques, 2017). However, it is challenging to select the number of bootstrap replications and optimal number of m (Villegas et al, 2019). Consequently, Esteve et al (2020Esteve et al ( , 2021a developed a new technique, called Efficiency Analysis Trees (EAT).…”

Comparing Operational, Environmental and Eco-Efficiency of Water Companies in England and Wales

“…Consequently, we selected the following variables which were based on topography, water treatment complexity and density [41,[66][67][68]. The variables used to capture topography included: (i) the water taken from boreholes measured in percentage [10,60,69]; (ii) the water taken from rivers measured in percentage [10,41,70], (iii) average pumping head as a proxy for the energy requirements to supply water to end-users [10,41,60]. We included two variables to capture treatment complexity: (iv) the water that gets advanced treatment measured in percentage (for more details please see [66][67][68]71] and (v) the number of treatment works required to treat water that comes from surface [41,71,72].…”

“…We included two variables to capture treatment complexity: (iv) the water that gets advanced treatment measured in percentage (for more details please see [66][67][68]71] and (v) the number of treatment works required to treat water that comes from surface [41,71,72]. Finally, we included population density which was calculated as a ratio of water population and area [69][70][71][72][73]. Table 1 summarizes the descriptive statistics for the variables employed in the empirical application.…”

Diversification and efficiency of life insurers in China and India

“…For its consistent and specific inference on two-stage analysis with DEA estimation in stage 1, bootstrap truncated regression is often utilised to identify relevant variables of efficiency, e.g. for Mozambican banks (Wanke et al 2016), European life insurance companies (Eling and Schaper 2017), water companies in England and Wales (Villegas et al 2019) and hotels in Sri Lanka (Kularatne et al 2019).…”