Plane Crash-Case Study

Plane Crash-Case Study Plane Crash-Case StudyThree of my closest friends and I take off from San Juan, Puerto Rico, heading for a down island on a flight expected to last 1.5 hours. The commuter plane is propeller powered and seats 8. The pilot keeps us informed during the trip. The pilot tells us that a tropical storm made an unforeseen shift in our direction and may interfere with the flight path. The pilot then decides to adjust for the storm. One hour into the flight a localized storm develops. Lightening hits the plane and partially disables it. The pilot attempts an emergency landing.My friends and I wake up to the following scenario: We were physically okay, and on the beach of a small island. The plane, partially submerged offshore, is incapacitated both mechanically and electrically. The pilot and co-pilot are dead. The small island we are on is about a mile from a larger landmass across the water.San Juan, Puerto RicoThe island we are on contains vegetation.Other than being a bit shaken up, we we re in a panic state of mind. I decided it was time for me to take charge of the situation. I reminded everyone that last we heard a tropical storm was heading in our direction. We all then realized that we needed to come up with a plan of what we needed to do to survive until we can get rescued.We knew that when the lightening had hit the plane the pilot never sent a "mayday". He was too busy trying to control the aircraft and the co-pilot was knocked unconscious from the shock. Right away an idea came to mind while I was brainstorming. I knew one of my friends was very good with electronics so we needed to attempt to get the radio...

How Economists Define and Measure Treatment Effects

How Economists Define and Measure Treatment Effects The term treatment effect  is defined as the average causal effect of a variable on an outcome variable that is of scientific or economic interest. The term first gained traction in the field of medical research where is originated. Since its inception, the term has broadened and has begun to be used more generally as in economic research. Treatment Effects in Economic Research Perhaps one of the most famous examples of treatment effect research in economics is that of a training program or advanced education. At the lowest level, economists have been interested in comparing the earnings or wages of two primary groups: one who participated in the training program and one who did not. An empirical study of treatment effects generally begins with these types of straightforward comparisons. But in practice, such comparisons have the great potential to lead researchers to misleading  conclusions of causal effects, which brings us to the primary problem in treatment effects research. Classic Treatment Effects Problems and Selection Bias In the language of scientific experimentation, a treatment is something done to a person that might have an effect. In the absence of randomized, controlled experiments, discerning the effect of a treatment like a college education or a job training program on income can be clouded by the fact that the person made the choice to be treated. This is known in the scientific research community as selection bias and, it is one of the ​principle  problems in the estimation of treatment effects. The problem of selection bias essentially comes down to the chance that treated individuals may differ from non-treated individuals for reasons other than the treatment itself. As such, the outcomes such treatment would actually a combined result of the persons propensity to choose the treatment and the effects of the treatment itself. Measuring the treatments true effect while screening out the effects of selection bias is the classic treatment effects problem. How Economists Handle Selection Bias In order to measure true treatment effects, economists have certain methods available to them. A standard method is to regress the outcome on other predictors that do not vary with time as well as whether the person took the treatment or not. Using the previous edition treatment example introduced above, an economist may apply a regression of wages not only on years-of-education but also on test scores meant to measure abilities or motivation. The researcher may come to find that both years-of-education and test scores are positively correlated with subsequent wages, so when interpreting the findings the coefficient found on years of education has been partly cleansed of the factors predicting which people would have chosen to have more education. Building upon the use of regressions in treatment effects research, economists may turn to what is known as the potential outcomes framework, which was originally introduced by statisticians. Potential outcomes models use essentially the same methods as switching regression models, but potential outcomes models are not tied to a linear regression framework as are switching regressions.  A more advanced method based upon these modeling techniques is the Heckman two-step.