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Business Productivity Growth Hypothesis
In this assignment, we will attempt to study the effects that difference in Income Ratio
(henceforth known as I.R.) between the years 1980 and 1990 have on the Productivity
Growth (P.G.) during the same period of time.
The Income Ratio of one specific year can be found if we take the average income of the
richest faction of a country (the richest 20% of the population) and divide it by that of
the poorest faction (the poorest 20%). In this assignment, the Income Ratios that were
used were those of 13 different countries. The I.R.'s on both 1980 and 1990 were taken
for all these countries and, to find the difference between them, the I.R. for 1990 was
divided by the I.R. for 1980, for each country. These new numbers illustrate the change
of I.R. between the two years so that we can compare how the P.G. changes in relation to
the changes in the I.R..
On this assignment, we use inductive reasoning to examine the data and find a theory (a
hypothesis) that would combine the data given in a way that would make sense, based
solely on our data. How do we know if the theory that we formulate makes sense? In this
case we will plot the points (derived from the column I.R. 1990/1980, going on the
x-axis, and the column Productivity Growth 79-90, on the y-axis). According to how the
points are on the graph in relation to the Average Point (0.94,1.45) (point that is an
average of all values and which divides the graph into four Quadrants), if 80% of these
points are where they would be expected to be to conform to the hypothesis, then there is
no reason to reject this hypothesis. If, on the other hand, the majority of the points
does not conform to our hypothesis (are not where they were predicted to be), then it is
rejected.
Another method of reasoning frequently used by Mainstream economists is deductive
knowledge, as opposed to inductive, described above. Their theory is formulated and only
then it is applied to the data. Their theory on this subject suggests that productivity
within a country grows when the population has incentives to work harder (or to work
more). When the gap between rich and poor increases (an increase in I.R. form 1980-90,
resulting in a larger ratio on the column I.R. 1990/1980), so does the population's
eagerness to work, therefore increasing the Productivity Growth. Since when one variable
goes up the other also goes up, there is a positive (or direct) correlation between the
two. Mainstream economists use deductive reasoning to deduce that there exists a positive
correlation between the two factors. In short, their hypothesis is that when the Income
Ratio increases, the Productivity Growth also increases, since people are more motivated.
For this to be true, we would expect a line going up and to the right on the graph,
passing by Quadrants II and IV. Most points (80% or more) would have to be on these two
Quadrants. This, however, is not the case (see graph), since only about 30.77% of the
points plotted satisfy these conditions.
Since the original hypothesis was rejected, we might want to see if there is a negative
correlation between the two variables (that is, as one goes up, the other goes down). Our
new hypothesis would then be as the Income Ratio increases, the Productivity Growth
decreases. Then, in the case of a high I.R., people in lower classes would rationally
start to feel insecure and that their work is not being recognized by society, therefore
losing motivation and producing less. In this case, since there's a negative correlation,
one would expect the line on the graph to go downwards, from left to right, passing on
Quadrants I and III. If this hypothesis were valid, 80%+ of the points would have to be
on these Quadrants. This is also not the case, for only 69.32% of the points are on the
appropriate Quadrants. Like the first, this second hypothesis also has to be rejected.
After analyzing these two relationships and seeing that neither is valid, we conclude
that there is no direct relationship between the two variables tested. That does not mean
that one has no effect on the other (it probably does), only that there may be other
factors and influences involved that have not been accounted for in this assignment and
that one is not the only factor responsible for the changes in the other.