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Quasi-Experiments in Empirical Economics: An Application to Extreme Levels of Lake Michigan Michael R. Moore School of Natural Resources and Environment University of Michigan
Outline Quasi-experiments in empirical economics Application to extremely low levels of Lake Michigan  Research question: did the extremely low levels  of Lake Michigan in 2000-07 cause economic  impacts in Lake Michigan coastal counties?
Quasi-experiment Experiment Scientific method of control group, treatment group, and experimental treatment What is the effect of the treatment on the treatment group? Quasi-experiment Research design of groups and a treatment not arranged in advance A by-product of public policy, public program, or nature Desirable feature: establishes causal evidence, not simply association evidence
Average Treatment Effect (ATE): what is the effect of the treatment on an outcome variable in the treated counties? ATE = [(Average 4 – Average 3) – (Average 2 – Average 1)]            (approximated ATE)
Low lake levels(Michigan Sea Grant Archives)
Policy dialogues on lake levels (IJC) Lake Ontario – St. Lawrence River Study (2006) Lake Ontario is a regulated lake “Lake levels are too even; not enough fluctuation” Upper Great Lakes Study (2012) Lake Superior is regulated; Lakes Michigan-Huron and Erie are unregulated Joint management of these lake levels “levels of Lake Michigan-Huron are too extreme”
Great Lakes lake levels, 1960-2007 Michigan-Huron Erie Superior Ontario
Extremely low lake levels as a quasi experiment Control group: Counties adjacent to  Lakes Ontario and Erie  Treatment group: 	Counties adjacent to Lake Michigan-Huron Treatment:  	2000-07 episode of extremely low levels
Data: NAICS Sector 72, Accommodation and Food Services County-level data for 1990-2007 Outcome variables: establishments, employment, and wage rate in Sector 72 We expect the Average Treatment Effects to be negative
Results Approximated Average Treatment Effects: Establishments (number of establishments) 		ATE:  [(239 - 213) – (590 - 567)] = 3 Employment (number of employees) 		ATE: [(4240 - 3704) – (10481 - 9554)] = -391 Wage Rate (cents per hour) 		ATE: [(873 - 648) – (860 - 661)] = 26
Summary and Conclusions
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Economic Impact Studies: Practical Tips & Examples - Michael Moore

  • 1. Quasi-Experiments in Empirical Economics: An Application to Extreme Levels of Lake Michigan Michael R. Moore School of Natural Resources and Environment University of Michigan
  • 2. Outline Quasi-experiments in empirical economics Application to extremely low levels of Lake Michigan Research question: did the extremely low levels of Lake Michigan in 2000-07 cause economic impacts in Lake Michigan coastal counties?
  • 3. Quasi-experiment Experiment Scientific method of control group, treatment group, and experimental treatment What is the effect of the treatment on the treatment group? Quasi-experiment Research design of groups and a treatment not arranged in advance A by-product of public policy, public program, or nature Desirable feature: establishes causal evidence, not simply association evidence
  • 4. Average Treatment Effect (ATE): what is the effect of the treatment on an outcome variable in the treated counties? ATE = [(Average 4 – Average 3) – (Average 2 – Average 1)] (approximated ATE)
  • 5. Low lake levels(Michigan Sea Grant Archives)
  • 6. Policy dialogues on lake levels (IJC) Lake Ontario – St. Lawrence River Study (2006) Lake Ontario is a regulated lake “Lake levels are too even; not enough fluctuation” Upper Great Lakes Study (2012) Lake Superior is regulated; Lakes Michigan-Huron and Erie are unregulated Joint management of these lake levels “levels of Lake Michigan-Huron are too extreme”
  • 7. Great Lakes lake levels, 1960-2007 Michigan-Huron Erie Superior Ontario
  • 8. Extremely low lake levels as a quasi experiment Control group: Counties adjacent to Lakes Ontario and Erie Treatment group: Counties adjacent to Lake Michigan-Huron Treatment: 2000-07 episode of extremely low levels
  • 9. Data: NAICS Sector 72, Accommodation and Food Services County-level data for 1990-2007 Outcome variables: establishments, employment, and wage rate in Sector 72 We expect the Average Treatment Effects to be negative
  • 10. Results Approximated Average Treatment Effects: Establishments (number of establishments) ATE: [(239 - 213) – (590 - 567)] = 3 Employment (number of employees) ATE: [(4240 - 3704) – (10481 - 9554)] = -391 Wage Rate (cents per hour) ATE: [(873 - 648) – (860 - 661)] = 26