## Friday, August 29, 2014

## Thursday, August 28, 2014

### Price Elasticity in B2B

Interesting article on price elasticity when firms sell to other firms. If changes in prices do not affect demand, then price elasticity is not helpful in setting the profit maximizing price.

Labels:
MBA8160,
Price Elasticity

## Wednesday, August 27, 2014

### Demand and Changes in Preferences

The Wall Street Journal reports that demand for frozen food is declining in part due to changing preferences by customers. In economics one way we represent consumer market behavior is using by using a demand curve. As consumers behavior changes such as due to outside factors (such as tastes for a type of food) so will the demand curve representing that behavior. Thus a decrease in the tastes or preferences for a product or service leads to a leftward shift in the demand curve for that product or service.

Labels:
Demand,
ECON 1100,
Preferences

## Tuesday, August 26, 2014

### Economics and Statistical Analysis

I have been teaching a course called Sports Economics for over 15 years, meaning that I am old. In the teaching of this course, I require the students to read a plethora of peer-reviewed economic research that employs statistical analysis. Each semester I take a full class period to review a topic called linear multivariate regression and then build on that as the semester moves forward, with the realization that my Sports Economics course is NOT a course on statistics but uses and analyzes a plethora of statistical concepts. As a help, I have decided to include some links on statistics that occur in Sports Economics.

First, the course is based on regression analysis using the subject called econometrics. Here is a great piece by Thoma on in how economists use econometrics and why. Once a statistical analysis has been performed, Stevenson and Wolfers explain what should you be looking for in terms of the big picture as to whether this is important or even interesting.

In terms of tying some of this statistical terminology to everyday thinking, here are some helps:

The difference between Type I errors (false positive) and Type II errors (false negative).

Examples of spurious correlations (i.e. variables that are correlated, but have nothing to do with each other).

A nice critique of only using p values in statistical analysis.

How some state insignificant (p-value) results.

Using dance to explain some statistical concepts.

First, the course is based on regression analysis using the subject called econometrics. Here is a great piece by Thoma on in how economists use econometrics and why. Once a statistical analysis has been performed, Stevenson and Wolfers explain what should you be looking for in terms of the big picture as to whether this is important or even interesting.

In terms of tying some of this statistical terminology to everyday thinking, here are some helps:

The difference between Type I errors (false positive) and Type II errors (false negative).

Examples of spurious correlations (i.e. variables that are correlated, but have nothing to do with each other).

A nice critique of only using p values in statistical analysis.

How some state insignificant (p-value) results.

Using dance to explain some statistical concepts.

Labels:
ECON 3390

## Monday, August 25, 2014

## Tuesday, August 19, 2014

## Tuesday, July 29, 2014

Subscribe to:
Posts (Atom)