PAD 520 WEEK 6 Discussion 2


In Case Study 1.1, one of the issues is going to be the time constraints of policy making with the analysts. Due to the time constraints policy analyses do not absorb the collection and analysis of new data, which can be fundamental in any policy making decision (Dunn, 2012).  Another concern would have to be the large number of various impacts is difficult to value in dollar terms, which makes a benefit-cost analysis unfeasible and even impossible in a lot of cases (Dunn, 2012).  In Case Study 5.1, the issues are going to be a matter of identifying and challenging, the assumptions on which benefit-cost analysis is based. When one is trying to conduct the benefit-cost they can be sensitive to the assumptions that are in place. An important drawback with benefit cost analysis is that while most benefits and costs that arise in the present are known, many that arise in the future are unknown. A benefit cost analysis must be conducted using information that is available. This information will be limited by our current knowledge of benefits and costs. Some future benefits and costs cannot conceive, much less measured. However, the role of uncertainty plagues not only benefit cost analysis but also most other decision-making methods.

The speed at which drivers operate their vehicles frankly affects two piece measures of the highway system; mobility and safety. Higher speeds provide for lower travel times, a measure of good mobility. However, the relationship of speed to safety is not as clear cut. It is difficult to separate speed from other distinctiveness including the type of highway facility. Still, it is generally agreed that the risk of injuries and fatalities increases with speed. Designers of highways use a designated design speed to establish design features; operators set speed limits deemed safe for the particular type of road; but drivers select their speed based on their individual perception of safety. Quite frequently, these speed measures are not compatible and their values relative to each other can vary. A clear understanding of how speed affects safety has also been obscured by the use of different speed-related indicators and a wide range of study methods. Different studies have evaluated the safety effects of speed limits, operating speeds and design speed, with some studies making the unsubstantiated assumption that these characteristics are related to each other. Many of the speed related studies are based on data from high-speed highways. Too often, the results and conclusions of these studies are inappropriately applied to all roads and streets. Despite the complexity and challenge of understanding speed-safety relationships, useful research conclusions have been reached (Speed Concepts, 2014).

From the case studies, Case 1.1 and Case 5.1, recommend the best ways to estimate the value of time and the cost of a gallon of gasoline. Support your position with at least two reasons and one example.

Value of Time (VOT) is a key factor in economics and policy. The answer is based on the economics of supply and demand and how products are manufactured and sold – along with what the government takes in taxes.  In order to test whether drivers seek to conserve energy by reducing speeds, our main task is to estimate the direct causal effect of the price of gasoline on speeding behavior. This direct effect has to be estimated in the absence of congestion because otherwise observed speeds are merely a reaction of changes in travel demand affecting congestion.  First start by estimating the relationship between speed and gasoline using the same method as in Burger and Kaffine (2009). Using the night hours of 2am to 4am as the time of the uncongested condition, the average speed in week t and highway i is estimated by

Speedit = α + β*pricet + Xit + Fi + Yt + εit : where pricet is the weekly average gas price, Fi are freeway site fixed effects, Yt are year fixed effects and Xit are precipitation, holiday and summer dummies as well as income and unemployment. To explore the causes that drive this result, we analyze the potential effect of road conditions that could confound this estimate. Seasonality turns out to be important because of its correlation with the cyclicality of gas prices. In the summer, speeds may be higher because of better visibility—extended daylight and less rain—and no freezing temperatures (Wolff, 2010).


Dunn, W. (2012). Public policy analysis: An introduction (5th ed.). Boston: Pearson.

Speed Concepts: Informational Guide – Safety | Federal Highway Administration. (2014, October 15). Retrieved November 13, 2014, from

Wolff, H. (2010). Value of Time: Speeding Behavior and Gasoline Prices. Retrieved November 13, 2014, from