Price-setting for Residential Water: Estimation of Water Demand in Lahore

The Water and Sewerage Agency (WASA) of Lahore is facing soaring demand and rising costs. But while massive investments are made to augment supply, tariffs remain low and are not adjusted in line with growing expenses. This has resulted not only in heavy and increasingly unsustainable reliance on loans and subsidies, but also in consumers undervaluing the resource, resulting in its inefficient utilisation. In this scenario, water tariffs badly need to be reformed. This study explores the potential of a pricing policy to regulate residential water demand in order to achieve the objectives of cost recovery, efficient water use, and equitable allocation of water resources. To this end, a demand function is estimated using household level data about water consumption and socio-economic characteristics of 156 households supplied by WASA, Lahore, for the period 2004-2006. Under block-rate tariffs the price variable is endogenously determined and a system of simultaneous equations emerges, solved here using two-stage least squares method. The estimated model explains 57 percent variation in water demand. The study finds water demand to be inelastic to price and, considering WASA’s exceedingly low tariffs, recommends up to 50 percent increase in the current tariff structure. Further computations show that a 50 percent increase will not endanger lifeline water supply. However, tariff increases may not be felt uniformly across all income groups, and absence of income data remains a limitation of this study. The study also recommends linking the non-volumetric part of tariffs to wealth-determined variables, such as property value and income.Water Demand; Price-setting

Price-setting for Residential Water: Estimation of Water Demand in Lahore

The population of Lahore has roughly doubled over the past twenty years, and an increase of two million is expected by the year 2020 [UN (2005)]. This has important implications for city planning as demand for housing, electricity, water, sanitation, public health, education, and infrastructure grows accordingly. Water and Sanitation Agency (WASA), the city’s official water supplier, has often responded to the growing demand by offering the supply-side solution: augmenting supply capacity by exploiting new water resources.1 Such investments are costly, but in view of the public good nature of water, WASA has kept tariffs well below the costrecovery level, relying on heavy loans and subsidies. While this arrangement may have worked in the past, it is now becoming increasingly unsustainable, because (1) WASA is facing severe financial constraints and which has led to poor service and underinvestment, and (2) the environmental cost of extracting water is increasing. With its low tariff rates and continually increasing costs, the WASA Lahore is unable to meet even its operation and management (O&M) costs [WASA (2007)]. WASA has been receiving financial assistance from the provincial and Lahore district governments as well as international donors in the form of grants and loans with the grant element gradually diminishing over the passage of time. In 2007, WASA currently owed Rs 5.6 billion to these agencies [WASA (2007)]. Deteriorating financial situation has also led to short-term planning, reactive operational strategy, and underinvestment in asset maintenance, future capacity, IT equipment, management and accounting information system, and training [IFC (2005)]. Consequently, WASA has shown suboptimal performance: low pressure and irregular supply, leakages, poor customer service, etc

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences

Differential Sensitivity to Adversity by Income: Evidence from a Study of Bereavement [Replication package]

Replication packag

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences