Introduction: 

I am looking at the relationship between the trends in different age ranges and see if there is a correlation between those figures and total computer sales.  GDP has been steadily climbing over time, as well as the prices of computers have been steadily falling.  Starting in 1980 and ending in 2000, based on the various declines in the birth rate, we are able to see how depressions in certain age brackets can affect the total sales of computers.

Model:

            The graphs that have been generated to show the total sales of computers and price enable us to see an interesting relationship between the prices of technology (computers) vs. the necessity of the consumer to have it.  1993 is an interesting year in this model because it is the year in which the price of this new technology because feasible for the consumer to afford.  After that year, prices continued to keep falling, and the quantity of computers sky rocketed.

            Certain age brackets have a stronger impact on the total sales, some of while have been eliminated from the equation, and some of which stayed because they have a large impact.  The basic microeconomic supply and demand principal that relates to the economic question that we are looking at, and can be seen in the graph below:

  As demand rises, there is a shift in the demand curve, bring it from “Demand” to “Demand’”, which drives up prices.  However, due to this large increase in demand, as we will see in later graphs, the supply curve has to shift as well to meet the newly increased demand.  So this shift, from “Supply” to “Supply’”, causes prices to fall and increases the equilibrium which results in a further increase in the quantity.  Over time, in the computer market, one would predict that this huge increase in demand would cause prices to fall as quantity increased so much.   It would also be expected that as the number of people at certain ages increases, like an increased trend in the 20 – 25 age category, would result in increased sales. 

 
Data:

            The data was obtained off of the Bureau of Economic Analysis,  www.bea.gov, which provided the data for the quantity and price of computers from 1980 – 2000.  The population figures were found using EViews, and the DRI Database.  There were a few variables that were deleted because their T-Stat was not big enough;  those include PAN6, COMPCurrDoll, and IMPDef.

Results:

            The final regression that we got was based on the following:

QUANTITY =  B0 + B1 (PRICE) + B2 (GDP) + B3 (PAN3) + B4 (PAN4) +B5 (PAN5) + B7 (PAN7) + B8 (PAN8) + B9 (PAN9)

After deleting the variables that were not significant enough, this is the final regression that was obtained before the addition of AR(1).

            Based on certain age brackets that have suffered declines in recent years, there are a few in particular that really have an impact on QUANTITY.  PAN3, PAN5, PAN9, GDP, and PRICE, all have significant T-Statistics after AR(1) was included in the equation.  Here is the final regression from EViews:

Conclusion:

When there are many people in a certain age bracket, we can see how much weight they really have when comparing that with computer sales.  This relationship is not as strong from 1980 – 1990 as it was from 1990 – 2000, seeing as there was a technological boom in the 90’s when computer sales were at an all time high, and as a result the price was driven down to increase sales even more.  However this leaves us with many questions about what the graphs will look like in the future; will the graphs for quantity and price being to level out as they have in the past?  Was this short term economic stimulus good for the economy, or would a more gradual trend be more healthy?  This relationship between quantity of computers purchased and the birthrates & costs is something that plays a vital part to the way that the US economy is shaped today, and plays an integral part in the economic boom in the 90’s and has shaped the way in which society functions today.