Instrumental Variables Approach to Rural Water Service Demand

Deller, Steven C.; Chicoine, David; Ramamurthy, Ganapathi S.

doi:10.2307/1059417

Cited by 40 publications

(36 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We discuss this further in Section 2.3. 6 Prior to Hewitt and Hanemann (1995), only three published studies had estimated price elasticities in the elastic range [17], [18], [19].…”

Section: Consumer Responses To Water Prices and Price Structurementioning

confidence: 99%

“…Thus, OLS estimates of the demand parameters will be biased and inconsistent. In the literature, this problem has been addressed with instrumental variables (IV) models, such as two-stage least squares, for labor supply and water and energy demand [29], [30], [19], [31], [32]. While such models can estimate downward-sloping demand curves, they exhibit two key limitations.…”

Section: Demand Modelsmentioning

confidence: 99%

“…18 Finally, the models include a set of dummy variables that represent the 11 urban areas included in the study: Denver, Eugene, Seattle, San Diego, Tampa, Phoenix, Tempe/Scottsdale, Waterloo/Cambridge (Ontario), Walnut Valley, Las Virgenes, and Lompoc, accounting for variations in geography and other factors not addressed by the other covariates. 19 For the non-parametric simulations, we draw 100 random samples of size N, with replacement, from the data; take the expectation of conditional demand in exponential form; simulate a one percent change in price or income; calculate the resulting percent change in expected demand; and report the mean of bootstrapped estimates. For the parametric simulations, we generate 100 random draws from each error distribution and estimate elasticities for each pair of error draws, using the original data and parameter estimates and taking expectations of conditional demand.…”

Section: The Datamentioning

confidence: 99%

See 2 more Smart Citations

Water Demand Under Alternative Price Structures

Olmstead¹,

Hanemann²,

Stavins³

2007

View full text Add to dashboard Cite

“…We discuss this further in Section 2.3. 6 Prior to Hewitt and Hanemann (1995), only three published studies had estimated price elasticities in the elastic range [17], [18], [19].…”

Section: Consumer Responses To Water Prices and Price Structurementioning

confidence: 99%

Section: Demand Modelsmentioning

confidence: 99%

Section: The Datamentioning

confidence: 99%

See 1 more Smart Citation

Water Demand Under Alternative Price Structures

Olmstead¹,

Hanemann²,

Stavins³

2007

View full text Add to dashboard Cite

“…A larger value of the error term will increase the likelihood that water consumption will be observed in a higher block (at a higher marginal price), and the opposite will be true for a small value of the error term. This problem was Þrst treated by estimating simultaneous equations models, such as two-stage least squares (2SLS) and other instrumental variables models, an idea borrowed from the labor supply and energy demand literatures [1] [24][63] [62].…”

Section: Block Pricing and Econometricsmentioning

confidence: 99%

“…Most importantly, economic theory predicts downward-sloping demand curves, requiring a negative relationship between price (p) and quantity (w). 24 In addition, income ( e Y ) and quantity should be positively correlated.…”

Section: Econometric Model Of Water Demandmentioning

confidence: 99%

Muffled Price Signals: Household Water Demand under Increasing-Block Prices

2002

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract In many areas of the world, including large parts of the United States, scarce water supplies are a serious resource and environmental concern. The possibility exists that water is being used at rates that exceed what would be dictated by efficiency criteria, particularly when externaltities are taken into account. Because of this, much attention has been paid by policy makers and others to the use of demand management techniques, including requirements for the adoption of speciÞc technologies and restrictions on particular uses. A natural question for economists to ask is whether price would be a more cost-effective instrument to facilitate water demand management. Terms of use: Documents inAs a Þrst step in such an investigation, this paper draws upon a newly-available set of detailed data to estimate econometrically the demand function for household use of urban water supplies. We analyze cross-sectional time-series data that track 1,082 single-family households served by 16 water utilities in 11 urban areas in the United States and Canada. Because of the diverse multiple-block pricing structures that abound, estimating the effects of price and price structure on residential water demand poses some challenging and interesting problems.We Þnd that the sensitivity of residential water demand to price is quite low, and that the effect of price structure may be more inßuential than the magnitude of marginal price itself. The household-level data we use allow us to assess the inßuences on residential water demand of climate, sociodemographic factors, and characteristics of housing stock, including home vintage. Our results indicate substantial heterogeneity in likely household responses to utility demand-management policies.

show abstract