Wednesday, June 13, 2012

Measuring Inflation

Measuring the change of prices is a difficult task.  There is no way to obtain a completely objective overall change in prices.  Every measure will have some kind of bias, and can be argued to be over or underestimated. 

Over the decades there have been changes in the way the government measures the consumer price index (CPI).  One change was to incorporate substitution effects.  This means that if the price of steak increases, and people consumer more beef, then beef is now a larger part of the economy and should have a bigger weighting in the CPI.  A second change is to incorporate qualitative changes into the CPI.  Thus, if the computer speed doubles in 2 years, but the average computer price remains the same, then the CPI will record a reduction in price for computers.

I wanted to take my own measurement of inflation using items that would not be affected by either of these 2 changes.  I wanted to see how much smaller the government inflation number is compared to the modified CPI number.  I also wanted to see if there was a change from decade to decade from the 60s to the 2000s, to see if there is an increase in the difference between the two numbers over the decades as the government implemented more changes.

Saturday, April 28, 2012

Measuring the Effectiveness of Political Parties at the State Level in the U.S. (Part 2)

I wanted to revisit the topic of comparing the dominance of a political party in charge of the state house and senate and looking at the pattern of internal migration. I will do two regressions. The first looks at the average exact percentage of the number of Democrats in both chambers and then takes the average of those percentages. So if the Democrats control 60% of the house and 70% of the senate in State A, then State A will have the number 65 assigned to it for the PolAvg variable. I look at two time periods. I take the average political dominance for the 1990s and the 2000s. I then run a pooled regression, using Is2000s as a dummy variable. The data shows coefficient, then p-value. The results are:

PopChange %




Adjusted R-squared: 0.068

 The results show that on average the population of each state is increasing by 7.127% when the state legislature is controlled by all Republicans.  If the state legislature turns from entirely Republican to entirely Democrat, the state's population increase will fall by 10.04 percentage points so that the state will over the decade be losing population at a rate of -2.913.  The result is statistically significant with a two sided T-Test with a P-Value of .0129.  The R-Squared is low at .068 which suggests that there are many other reasons for leaving a state besides the ruling political party.  The low R-Squared is a weakness in this regression.