Data-Driven Approaches to Measuring the E�ects of

Water Quality Policies

David A. Keiser

Iowa State Economics and CARD

October 2015

OutlineEconomic Studies

Distinguishing Features

I Few key parametersI Research designs control for processesI Point and nonpoint source behaviorI Contrast with mechanistic models

General Approaches

I End of Pipe or Edge of FieldI Ambient MeasurementsI Use and Damages

End of PipePoint Sources

Theory

I Municipal, Industrial BehaviorI Government Interventions, E�uent Limits, Overlapping Regulations

Data

I Monthly plant-level discharge data from US EPA

Empirics

I Panel Data and Di�erences-in-Di�erences

Examples

I Earnhart (2004a, 2004b, 2007, 2014); Shimshack and Ward (2008);Cohen and Keiser (2015)

Edge of FieldNonpoint Sources

Land use and conservation practices

Very little data-driven approaches in economics

IA State STRIPS Project

Surface Water Quality

Limited Number of Economic Studies

I Conservation Reserve Program (Sprague and Gronberg 2012)I Environmental Regulations (Smith and Wolloh 2012; Greenstone andHanna 2014; Keiser and Shapiro 2015)

I Fracking (Olmstead et al. 2013)I Transboundary Pollution (Sigman 2002, 2005; Limpscomb andMobarak 2014)

Common in Hydrology Literature

I Trend StudiesI USGS SPARROW Models

Key Components

Data and Routing

I US rivers, streams, lakes (US EPA, USGS)I Global rivers and streams (UN)I Focus on BOD, DO, Fecal Coliform, Nutrients

Research Designs

I OLS with many controlsI Watershed or station �xed e�ectsI Di�erences-in-Di�erences with upstream vs. downstream

DataUS EPA (STORET) and USGS (NWIS)

Keiser and Shapiro (2015)

DataUN Global Environment Monitoring System

Sigman (2002)

DataIndia (National Water Monitoring Programme)

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Figure 3. Water Qual ity Monitors on India’s Major Rivers

Notes: Dots denote cities with monitoring stations under India’s National Water Monitoring Programme (NWMP). Only cities with monitors on major rivers are included, as geospacial data for smaller rivers is unavailable. Geographical data are drawn from MIT’s Geodata Repository. Monitoring locations are determined from CPCB and SPCB online sources and Google Maps.

Greenstone and Hanna (2014)

Research DesignsCross-sectional Variation (OLS)

Yi = βXi +αZi + εi

Water quality (Yi )

Policy or action (Xi )

Other factors (Zi )

Research DesignsYi = βXi +αZi + εi

Fig. 1. Export (normalized to site drainage area) of (a) total nitrogen (N) and (b) total phosphorus (P) from agricultural watersheds in the United States.

Fig. 2. Percentage of agricultural area in (a) the Conservation Reserve Program and (b) conservation tillage in the United States in 2002.

Sprague and Gronberg (2012)

Research DesignsVariation over Time and Space (Panel Data Methods)

Yit = βXit +αZit +δi +δt + εit

Water quality (Yit)

Policy or action (Xit)

Other factors (Zit)

County, watershed, or monitor �xed-e�ect (δi)

Year �xed-e�ect (δt)

Research DesignsYit = βXit +αZit +δi +δt + εit

Fig. 1. Surface water quality monitors, shale gaswells, and wastewater treatment facilities in Pennsylvania watersheds (2000–2011).

Olmstead et al. (2013)

Research DesignsDi�erences-in-Di�erences

Yidt = βXit ·d +αZidt +δid +δit + εidt

Water quality up or downstream of location i (Yidt)

Policy or action at location i and time t (Xit)

Downstream indicator (d)

Other factors (Zidt)

Location-downstream �xed-e�ect (δid)

Location-year �xed-e�ect (δit)

Research DesignsYidt = βXit ·d+αZidt +δid +δit + εidt

Keiser and Shapiro (2015)

Research Needs for FEWWhere do we go from here?

Focus

I Food and energy sectors

Data Needs

I In�uent and e�uent at point sourcesI Long-term ambient monitoring (US and global)I Upstream/downstream routing capabilities

Linking with Mechanistic Approaches

I E�uent processesI Removal processesI Dynamics and feedbacks