Countervailing
Factors in
Business Cycles
Augustyn J. Peretsky, M.A.
Exxeed Econometrics
25 Rollins Place
Laguna Niguel, CA 92677
858-531-5815
760-852-4367
1988, Revised 2010
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 2
The saying “The more things change the more they remain the same” may be
true in economics as well as other fields of endeavor. This paper purports that this
truism is relevant and will examine its consequences. Questions posed may be: To
what extent is the present economic condition unique and to what extent is it
experiencing past patterns and conditions; and how consistent are these patterns?
By examining past business cycles, insight into these questions may be found.
This paper will examine some of the aspects of business cycles, incorporate the
concept of countervailing factors into the cycle model and correlate data with the
hypothesized model:
GNP= Yt ± ∆Yt peak (trough) cos (π/2 l X-Y l) + e
where: Yt-trend line GNP
- ∆Yt trough for 1≤Y≤0, 0≤X≤1
+∆Yt peak for 0≤Y≤1, 1≤X≤0
Figure 1 Business Cycle as represented by model
The purpose, therefore, will be to determine the validity of such a model, its
forecasting ability, that is whether turning points can be estimated, and
inadvertently, discover the dynamics of inverse relationships upon which the model
is based.
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 3
In determining the mechanics of business cycles, countervailing factors have
largely been ignored. Although historically, increasing and decreasing variable
changes can readily be seen in such relationships as money supply and interest
rates, or inflation and unemployment; their incorporation into a complete business
cycle has not been undertaken. As in the case in physical cycles, elements of the
cycle have to exhibit changing antagonistic and synergistic relationships during the
upward and downward swing in order for movement to posses momentum and be
self-perpetuating. The approach in this study is relatively simple: incorporate key
increasing and decreasing variables into the countervailing elements of the cycle,
interchange these variables appropriately into countervailing elements and
construct a model that should be self-sustaining.
The degree to which economic and social phenomenon follow physical
phenomenon may be limiting. Analogies are bound to be imprecise. Unlike
mechanical systems, behavior is far from predictable. Economic activity may differ
from cycle to cycle because of changes in structure, government policy, income
distribution and so on. Variables that are predominate in one cycle may be
insignificant in another.
The concept of countervailing elements is based on inverse relationships in the
cycle. For the sake of simplicity and mathematical conformity, these relationships
are assumed linear. Originally the idea of the model was to average out the various
inverse relationships (variables) into X and Y, creating two averaged opposite
variables in which the maximum point in one would correspond to the minimum in
the other. In order for maximum and minimum to fit the model equation, 0
represents minimum and 1 represents maximum while fractions represent
proportions in-between. (Figure 1) However, as the study progressed it became
evident that such a concise incorporation of the various elements would not be
possible. What did become apparent is that money supply coincides with the model
equation for the most part consistently while its counterpart, interest rates
(inflation) was skewed. The pattern difference is illustrated in figure 2, 3, and 4.
Other variable relationships and patterns in the cycle will be presented and
interpreted, but for the most part this paper will deal with money supply, money
demand, interest rates and inflation in conjunction with the postulated
countervailing model.
The idea of countervailing elements rather than independent and dependent
variable relationships simply introduces the interdirectionality of the relationship
and does not preconceive or preclude cause and effect. Money supply increases
may cause interest rates to decrease but at the same token increases in interest
rates (in an inflationary phase) may cause money supply to decrease through
government policy to stem inflation. Or increases in interest rates (in an
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 4
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
expansionary period) may cause money supply to increase through private
investment.
pg. 5
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 6
Confusion as to cause and effect, and independence of variables is minimized by
viewing these inverse relationships as independent countervailing elements in the
overall cycle subject to the usual independent-dependent relationship of various
degrees at different points or instances in the cycle. Moreover, the inverse
countervailing element will be part of several independent variables determining the
dependent countervailing element (factor), (ex. Y=f(X,z,h…).
Because the value of the data is increasing in some instances (GNP, money
supply…) maximum and minimum points were determined by calculating a trend
line ( a regression line was determined by computer; midpoints, maximum,
minimum were assigned from the observed cycle) through the variable’s data
(Figure 1).
Methodology
Computer regression analysis was used to establish a trend line and measure
points along the cycle. Time was the independent variable and data as supplied by
Citidat computer records was the dependent variable. Both quarterly and monthly
data was used. Peak, trough and midpoints of GNP were marked out on the
regressed results. Patterns were established corresponding to GNP’s peak, trough,
and midpoints. Conversely, from the variable-GNP pattern cycle, patterns were
established for the relationships:
Inflation-GNP
Interest Rates-Money Supply
Interest Rates-Debt
Debt-GNP
Savings-Debt (Interest Rates, Inflation)
Savings-GNP
Savings-Investment
Investment-GNP
Investment-Interest Rates (Inflation)
Investment-Debt
Net Exports-GNP
Measurement for consistency (inconsistency) was determined by counting the
number of quarters the cycle was off the pattern mark at midpoint, trough or peak.
In this way, the error was analyzed by using the regression equation (y=a + bx +e)
(Figure 4-a). The independent variable, x, becomes the cycle number and y, errornumber of quarters the cycle was off the pattern mark either at midpoint, trough or
peak becomes the dependent variable. A zero error indicates perfect consistency
while deviation from zero shows the extent of inconsistency. Soritec computer
program was used for the computer regression analysis. The results gave: R2
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 7
(coefficient of determination), u (mean of dependent variable), Durbin Watson,
coefficients a, b, t ratio, and standard deviation. A 95% confidence interval was,
also, determined. Since industrial capacity closely coincided with GNP on a quarterly
basis also since it is a percentage statistic more amenable to regression analysis
and fits the model’s minimum and maximum requirements it was used as a proxy
for GNP. As long as the mean (error) is within the standard deviation interval and
close to y=o (zero error) of the proposed model there is a high probability of
consistency and the model’s validity.
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 8
The interpretation of the 95% confidence level and the standard
deviation is a bit tricky. Since these parameters are reflective of the
normal bell shaped curve, the correlation-hypothesized model is
dependent on the rejection of the alternative hypothesis, that is, the
invalidity of the model’s correlation of the inflection point (midpoint,
trough or peak) GNP and the inflection point of the proposed parameter
such as money supply (Figures 17 & 18).Because computer regression
analysis would only compute mean(z=0), standard deviation (z=1) of the
data, and so on, the position of perfect zero is critical in determining
consistency(Figure 4b). For instance, if the zero is outside the 95%
confidence interval then we reject the correlation -hypothesized model
(null hypothesis) and conclude that there is a 95% probabili ty that the
hypothesis is invalid. If the zero is within the 95% confidence interval
then a 95% probability of rejection can not be made.
Similarly, the standard deviation (z score=1) of a normal bell shaped
curve has a confidence level of 68%, an d the placement of y=zero at or
just outside of the standard deviation has a 68% confidence of rejecting
the correlation-hypothesized model (null hypothesis) if it is used as a
rejection criterion. Conversely, there is a 32% confidence of accepting
the null hypothesis if it is not used as the rejection point .
In essence, as the difference between y=0 and the mean, u
diminishes, this lowers the chance of rejecting the null hypothesis and
heightens the probability of validating the model and its conclusions.
Data and Statistical Results
After examining data from 1945 to 1986 a pattern between GNP
(capacity) and the various variables can be established. Figure 5
illustrates the direct and inverse changes in the relationship between
money supply and inflation rate as the cycle changes. Figure 6 depicts a
similar relationship between net export and exchange rate. In figure 7
thru 14, the relationship between phase changes for the various
relationships is analyzed. The phase changes of the cycles are numbered
1,2,3,4.
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 9
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 10
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 11
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 12
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 13
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 14
From the computer data, the patter ns repeat themselves consistently.
Statistically, change in inflection point consistency was measured for
money supply and GNP (capacity); and net export and GNP (capacity).
For net exports two measurements were made, one at the capacity t rough
point where net export reaches its maximum proportional level and the
other measurement was made at the midpoint where net export attains
its lowest level. The error of inconsistency was determined by counting
the number of quarters the cycles were off their mark. A regression
analysis was then made on these errors, using the number of the cycle as
the independent variable and the error as the dependent variable. The
data (figures 15 & 16) clearly shows that the relationships fit within a
95% confidence interval. For the mid-capacity net export (minimum)
mean was 0.714286 with a standa rd deviation ± 3.87575 quarters.The
calculated z score for y=0 was determined to be -0.18425
(z=0-0.714284/3.87575) The 95% confidence interval was determined to
be 3.2142≤.714≤4.3904. The trough net export (maximum) point
measured a mean -0.8333 with a standard deviation ±3.50985. The
calculated z score for y=0 was determined to be +0.23741
(z=0—0.8333/3,50985). The 95% confidence interval was determined to
be -5.7028≤-0.8333≤4.0365.
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 15
For money supply, two measurements were also made, one at the capacity
midpoint (expansion cycle) where money supply reaches the maximum
proportional level and the other measurement was made at peak capacity (GNP)
where money supply attains its mid-level. The data (Figure 17 and 18) clearly
shows that the relationships fit within the 95% confidence level. For mid-capacity
money supply (maximum) the mean was 1.0 with a standard deviation ±2.190989
quarters.The calculated z score for y=0 was determined to be -0.4564
(z=0-1/2.190989) The 95% confidence interval was determined to be 1.097≤i.0≤3.907. The peak capacity money supply (midpoint) measured a mean 0.20 with a standard deviation ±0.316228 quarters. The calculated z score for y=0
was determined to be -0.63247 (z=0-0.2/0.316228). The 95% confidence interval
was determined to be -1.4395≤-0.2≤1.0365.
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 16
Interpretation of Data
Theoretical reasons for these results are complex, controversial, abstract and
speculative. From interpreting the data, the proposed model equation does not
work well. The only variable that fits the equation in the majority of cycles is money
supply. Assigning X to money supply and leaving the other variable, Y, as a blank
corresponding countervailing factor works well for fitting the data and for
forecasting purposes.
The inconsistency of the predicted pattern of money supply and its
countervailing element, interest rate (inflation rate or price level), and actual data
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 17
is a key question posed in this study. Coupling this with the observation that
interest rate (inflation rate) decreases (increases) precede money supply increases
(decreases) in reaching a maximum or minimum, an abstract theoretical model of 2
major countervailing elements can be established.
The model’s two proposed elements: income (income efficiency) and price level
(inflation rate) have in essence been observed or mentioned by both the Monetarist
and Keynesian economists. Keynes establishes his General Theory on the concept
of money demand as determined by income, price level and interest rates (MD=kPY
+ L(i)). Monetarists, on the other hand, base their theory on price level and income
eliminating interest rates (MD=kPY) in accordance with Classical (Cambridge)
interpretation.
According to Milton Friedman:
The next effect is the income and price level effect. As cash balances are built
up, people’s attempts to acquire other assets raise the prices of assets and drive
down the interest rate. That will tend to produce an increase in spending. Along
standard income and expenditure lines, it will tend to increase business
investment. Alternatively, to look at it more broadly, the price of sources of
services will be raised relative to the prices of the service flows themselves. This
leads to an increase in spending on the service flows and, therefore, to an
increase in current income. In addition, it leads to an increase in spending on
producing sources of services in response to the higher price which can now be
obtained for them.
The existence and character of this effect does not depend on any doctrinal
position about the way in which monetary forces affect the economy. Whether
monetary forces are considered as affecting the economy through the interest
rate and thence through investment spending or whether, as I believe, reported
interest rates are only a few of a large set of rates of interest and effect of
monetary change is exerted much more broadly, in either case the effect of the
more rapid rate of monetary growth will tend to be a rise in nominal income.1
From the point of view of countervailing factors and this study, Friedman’s
interpretation coincides with phase 4 and 1 of the business cycle. Cash balances
(savings through less spending and T-bill purchases by government) from the
empirical evidence do increase in phase 4 reaching a maximum at the trough level
or inflection point between 4 and 1 (Figure 10 and 11). Government policy of
increasing money supply to spur economic activity in a recession has a lag effect
1
Havrilevsky and Boorman, Issues, Friedman, Milton, “Factors Affecting the Level of Interest
Rates”, P.368
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 18
between policies such as buying T-bills, lowering prime rates and other measures;
and its effect on the economy.
The multiplier effect from increased cash balances has a lag effect during phase
1 in which bank loans increase, business and private investment increase, and debt
decrease produce an increase in spending as shown in Figures 8-13 culminating in
the maximization of money supply some point past the trend line or inflection point
between phase 1 and phase 2. At the trend line besides debt, interest rates and
inflation rate are at their lowest level, this coincides with Friedman’s observation
that “the more rapid rate of monetary growth will tend to be a rise in nominal
income”.
A closer examination of savings and GNP (spending) in Figure 10 does
corroborate Friedman’s assertions. Savings going into “peoples attempts to acquire
other assets” in phase 1 depletes savings while increases spending (GNP), increases
current income and increases business investment thereby increasing employment
and other resources of production.
Another Friedman assertion, the prices of services (labor, etc.) relative to
service flows increase, implies a rise in income (income efficiency), that is, inflation
and interest costs are at their lowest level while increased demand for services has
a positive effect on employment.
At equilibrium economist’s assume that money demand equals money supply
(MD=MS) at points in time thereby determining interest rates. However, the
dynamic state of the economy leads us to conclude that as price level (P) and
income (Y) change throughout the cycle, money supply and money demand are
also constantly changing their equilibrium point therefore establishing the prevailing
interest rate.
It is, therefore, easy to deduce from observations that income becomes directly
correlated to money demand and money supply (with a lag effect) while interest
rates and price level are inversely related. Increased income as mentioned in
Friedman’s interpretation means increase demand for money (increase demand for
durable goods and shifts in liquidity preference). Also in the Keynesian
interpretation the relationship is apparent.
The proposed model is very much mathematically idealized. Its value is in both
adapting mathematically a real empirical cycle’s behavior and comparing it to the
idealized model. In this idealized interpretation, income is a much more abstract
variable than a real concrete measurable quantity. Income takes on the
characteristic of efficiency. The precise definition and determination of income is
difficult to ascertain. Intuitively, income in this context can be thought of as the
attainment of goods and services by consumers at different levels of productivity,
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 19
price level, income distribution (nominal wages), employment, industrial capacity,
savings, debt (satiety). That is:
Income=f (productivity, price level, nominal wages, employment, industrial
capacity, satiety…)
Price level, also reflects measurable and immeasurable variables: inventory,
interest rates, capacity, taste, demand, technology, (productivity) etc., its
measurement is partially made and provided by government econometricians. That
is:
Price level=f (inventory, interest rates, capacity, taste demand, technology…)
Figure 1 illustrates the countervailing idea of having income (Y) reach its
maximum and price level its minimum at the trend line prior to GNP peaking ¼
cycle thereafter. Here income and price level represent the most efficient point in
the cycle. Microeconomically, this may represent the lowest aggregate average total
cost of production and least cost capacity. Conversely, ¼ cycle after GNP peaks
represents the least efficient point in the cycle. Here price level change (inflation
rate) is at its maximum and income-efficiency at its lowest. The best example of
such an idealized cycle is found in the stagflation period of 1971-1979. Price level
and interest rates reached their peak between phase 3 and 4 (Figure 5-1974) while
money supply reached its lowest point toward the end of phase 4, reflecting a lag
effect and confirming the precedence behavior of money demand (income) over
money supply.
Further evidence of the two countervailing elements in the 1971-1979 period
can be seen by noting that in the 1973-79 cycle employment reached its highest
level in phase 3 close to phase 4. This illustrates the inefficiency of income during
this period. Although employment and capacity remained high, the price level rose
reflecting high demand for an economy experiencing diminished goods and services
(GNP decline).
Many of the variables determining the two countervailing elements are
intangible and difficult to measure. Satiety, for example is one such variable. One
way of examining satiety is to determine maximum level consumer debt and
savings. If the idea of a satiety point is valid them major variables reflecting
satiety; savings and debt should reach peak levels together with GNP. Indeed, the
pattern formed (figure 10) shows that savings is maximized both at the trough and
peak. Debt, on the other hand, reaches its maximum at peak GNP and its minimum
at the midpoint phase 1 and 2. Therefore, their use as a satiety indicator and
income-efficiency determiners coincides with the theoretical placement of maximum
income-efficiency at the midpoint (between phase 1 and phase 2), the point of least
debt. And the skewed characteristic of income-efficiency at the peak where debt
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 20
also peaks in the majority of cycles other than the 1971-1979 period further
substantiates the theoretical inferences.
However, even with the use of these variables the intangibility of a satiety
measurement for goods and services and other variables makes the task of a
concrete measurement of income efficiency most difficult if not impossible to attain.
One means of circumscribing such a task and determining the purported incomeefficiency variable as countervailing to price-level is a comparative study of the
amount of goods and services affordable and the percentage of income spent on
each by a median-wage earner working a standard 40 hour week throughout the
cycle. As the median wage changes in the cycles at 40 hours/week, the percentage
of income needed to purchase basic median items such as housing, transportation,
food, etc. (coupled with debt capacity and savings) may be a relevant barometer of
the income-efficiency concept.
In a recent Time magazine article2 a comparison of purchasing power (incomeefficiency) between generations was made. The article compared the percentage of
income needed for the purchase of goods and services by the father in the late 50’s
and now by his offspring. A similar but more empirical study of purchasing power
within a cycle may prove well worthwhile.
The examination of cycles other than the 1973-79 cycle have a skewed
relationship between money supply and price level change. By conjecture, they may
reveal an economic paradox. It may be paradoxical that at peak GNP, interest rates
and inflation peak correspondingly close afterwards thereby inversely producing the
lowest income-efficiency point.
The distinction between income-efficiency and real or nominal income is
paramount in this analysis. While real (nominal) income may be rising for our
hypothetical median 40 hour per week wage earner as business activity increases
and demand for his services in turn increases his wage and output (number of
hours worked), his income-efficiency for the standard 40 hours will be declining.
That is, his overall (phase 2) spending will be increasing and contributing to
increases in price level and business activity as purchasing power viewed from the
income-efficiency concept will be losing ground.
In essence, the increase in higher GNP during phase 1 will concomitantly be
raising income-efficiency, while increase of GNP in phase 2 will be countered by
decreases in income-efficiency.
The decline of GNP in phase 3 of the cycle will in part be spurred by the decline
in income-efficiency. As GNP reaches its midpoint on the downward slide, price level
2
Gwynne S.C, Time, How One California Family Has Been Caught in the Middle, Oct. 10, 1988 Vol. 132 No. 15
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 21
and income-efficiency change magnitude. Price level is at its maximum while
income-efficiency is at its minimum. Thus, in phase 4 as income-efficiency improves
and price level change (inflation) decreases, GNP will decelerate to the trough
because of the pull effect upward by increasing income-efficiency and declining pull
downward by price level. In effect, in accordance with the model’s equation (Figure
1) at both the trough and peak the magnitude of both elements is at their half way
point (X=1/2, Y=1/2). Thereby, peak and trough being created at the point where
income-efficiency equals price level. Since both factors change in opposite
magnitude, one increasing and the other decreasing the midpoint represents the
point where one is at its maximum and the other at its minimum (either X=1, Y=0
or X=0, Y=1). In this fashion, the cycle goes full-circle propagating itself in a selfperpetuating manner.
Ironically, this behavior is best illustrated in the 1971-1979 period,
appropriately named the stagflation period. The inflection point for price level in this
period lies at both midpoints of GNP. Most significantly, the length of time phase 3
lasts is dependent on the inflection of both income-efficiency and price level.
Exogenous variables such as net exports propelled by exchange rates affect the
two countervailing factors simultaneously. In phase 1, the exchange rate reflects an
increase of the U.S. dollar compared to other currencies. During this period as the
inflation rate and interest rate declines, the value of the dollar increases and
imports increase coincidently.
The depreciation of the dollar in the “ideal” business cycle model begins slightly
before the midpoint of the expansionary cycle (phases 1and 2), thereby taking the
cycle into phase 2, the inflationary phase. Here interest rate and inflation rate tend
to increase reaching a maximum at the end of phase 3 (the GNP trend line). This
causes increased export for the U.S., while imports decrease. Ironically, the net
effect is increased U.S. income, contributing to decreasing income-efficiency.
However, as exports increase in phase 4 the net effect is positive contributing to
increasing income-efficiency as other factors contribute to decreased incomeefficiency such as lower demand for durable goods and higher unemployment
(decrease in GNP).
The scarcity of dollars in the world economy depleted during phase 2.3.4 and
world demand for U.S. goods will have a high impact on the demand for dollars,
therefore raising the exchange rate. In this fashion the cycle goes full-circle, ending
up again in phase 1 with a high exchange rate and a propensity to consume imports
at increasing income-efficiency and decreasing price level.
As a final note, as the cycle precedes from phase to phase income and price
level change relative to each other. Changes of magnitude may vary from cycle to
cycle, peak inflation may reach 20% in one cycle while peak inflation may only
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 22
reach 5% in another. Income-efficiency, likewise, may change in magnitude from
cycle to cycle. The period (1945-1988) of this study encompassed relatively mild
and short recessions primarily caused by inflation increases and income-efficiency
decreases. More protracted and severe recessions such as the Great Depression
may still fit the model although income-efficiency defined by 25% unemployment,
and price level defined by a deflation of prices below the cost of production; create
greater weight on certain components such as government policy that as
independent variables delineate price level and income-efficiency.
Conclusion
The preparation of this paper has been an evolutionary process. The initial ideas
of aggregated averaged countervailing factors proved to be unsustainable. This
gave rise to the observation that money supply and a blank countervailing variable
are consistent with the proposed model and can be used for forecasting purposes.
The final idealized model of countervailing factors: income-efficiency and price
level change as determined by the various variables is not a new revelation. It is
merely a perspective utilizing the model’s equation for cycle behavior given changes
in GNP through these two factors. Also, viewed in this manner it is hoped that the
model has presented a more structured analysis of the business cycle.
Countervailing Factors in Business Cycles; by Augustyn J. Peretsky, M.A.
pg. 23
Bibliography
1. Havrilevsky and Boorman, Issues,
Friedman, Milton, “Factors Affecting the Level of Interest Rates” p.378-394
2. Gwynne S.C., Time, How One California Family Has Been Caught in the
Middle, Oct. 10, 1988 Vol. 132 No. 15
3. Blinder, Alan S. , Fischer, Stanley, 1981, “Inventories, Rational Expectations,
and the Business Cycle”, Journal of Monetary Economics 8 p.277-304
(Northland-Holland Publishing Company)
4. Havrilevsky and Boorman, Issues, Jordan, Elements of Money Stock
Determination, p.268-287
5. Woodland, A.D., International Trade and Resource Allocation, North Holland
Publishing Company, 1982
6. Hazary, B.R., The Pure Theory of International Trade and Distortions, Wiley
1978
7. Hall, R.E., Taylor, J.E., Macroeconomics, Theory, Performance, and Policy,
(W.W. Norton & Company) 1986