Edward Renshaw
Professor of Economics
State University of New York at Albany
The theory of aggregate demand and supply was invented by macro economists to better enable one to understand inflation. This theory is also useful, however, in providing a better fix on the conditions that might lead to an economic recession. Other things being equal, a recession can occur as a result of a downward shift or "slump" in aggregate demand, an upward shift in the supply function or as a result of a combination of these two developments.
In a more dynamic world where inflation has become a chronic problem and population is increasing, Fed policy makers are more inclined to focus their attention on the growth rates for real GDP and its associated price deflator. While the analysis of recessionary shifts in demand and supply growth functions is a bit more complicated than recessionary shifts in ordinary demand and supply schedules, the same basic principles apply. What one wants to avoid is leftward shifts in one or both of these growth functions that are sufficient to produce a negative growth rate for real GDP.
While real GDP and its implicit price deflators are not regarded as being leading economic indicators, shifts in demand and supply growth indicators are of some value in helping to identify years containing a recessionary peak in business activity.
When the policy objective is to control the inflation rate in the short run, the emphasis is likely to be on demand-side variables, in part because of the volatile shifts in aggregate demand, but also because it is not very easy for government or a country's monetary authorities to manipulate supply-side variables, at least in the short run.
Persons responsible for formulating monetary and fiscal policy, however, will always need guide-posts. In searching for inflationary guide- posts one is well advised to not overlook supply-side indicators.
One way to arrive at an aggregate demand curve is to start with IS and LM equations that are expressed in current dollars and combine them so as to eliminate the rate of interest. The resulting equation can be a little cumbersome to interpret, however, even if one uses very simple expressions to represent the IS and LM equations.
A simpler way to assess the effect of changes in different variables on the aggregate demand curve is to start with the accounting identity income equals expenditures or Y = PQ. Converting this expression to logarithms gives one the following log linear expression to represent aggregate demand:
logP = logY - logQ (1)
A change in any variable that is presumed to increase nominal GDP will shift this unit elastic demand curve to the right and any event that lowers nominal GDP will shift the schedule to the left. If you are a Keynesian a simple multiplier model such as equation (3) in Essay 1 can be used to show that an increase in government expenditure, other things equal, will shift the demand curve to the right and that an increase in taxes will shift it to the left.
If you are a monetarist or a Keynesian who believes that money matters, the LM curve can be represented by the equation of exchange which implies that logY will be equal to LogM plus the logarithm of its velocity of circulation, LogV. If the velocity of money is assume to be constant, an increase in the money supply will shift the aggregate demand curve to the right and a decrease will shift it to the left. These effects, however, can be offset or amplified by a change in the velocity of money. The Keynesian demand for money equations assume that the velocity of money will increase in response to an increase in interest rates and decline in response lower interest rates.
Since small changes in logarithms are approximately equal to percentage changes (%), equation (1) can be rewritten as:
%P = %Y - %Q (2)
Any demand side variable, such as the growth of autonomous expenditure or a change in the monetary growth rate, will cause this demand growth equation to shift, if it alters the growth rate for aggregate income.
Nobel Laureate James Tobin (1981) has noted that revolutions in economics are rare. He believes that there have only been three major counter-revolutions in macroeconomics since The General Theory of Employment, Interest and Money was published in 1936. The first was Monetarism, "an ancient doctrine modernized and persuasively propagated by Milton Friedman beginning in the 1950s." A second and closely related counter-revolution was the "so-called New Classical Macroeconomics, based on the elegant and appealing theory of rational expectations." The third is Supply-Side Economics. This counter-revolution is also the most amorphous. Without a Keynes or Friedman or Lucas, it lacks a sacred text expounding its theoretical foundations. It is more spirit, attitude, and ideology than coherent doctrine, and its enthusiasts are of many minds."
Early efforts to derive an aggregate supply curve from the notion of a production function ended in a sea of controversy and an embryonic literature (Wells, 1970) that has been largely forgotten since the invention of the Phillips curve. In the analysis which follows we will emulate Dernburg and McDougall (1976) and assume that it is meaningful to think in terms of an aggregate production function which is approximately log-linear or Cobb-Douglas in form. Where Q is domestic output in constant prices, A is an autonomous shift variable representing technology and other resources that have been left out of the production function, such as energy, K is capital input, and H is the number of hours worked, we have:
1-b b
Q = AK H (3)
If goods and services are supplied by competitive firms or monopolies that are regulated to achieve the same result, the short run supply price will be equal to marginal cost. Assuming that the stock of capital is fixed in the short run and that workers are paid the value of their marginal product, marginal cost, MC, will be equal to the prevailing nominal wage rate, W, divided by the marginal physical product of labor, dQ/dH:
1-b b-1
P = MC = W/(dQ/dH) = W/bAK H (4)
Solving equation (4) for hours worked and substituting the resulting expression back into equation (3) eliminates H and gives us the following short run aggregate marginal cost or supply-side equations:
-1 (1-b)/b -1/b -(1-b)/b
P = b Q A K W (5)
and
logP = -(log)b + [(1-b)/b]logQ - [1/b]logA - [(1-b)/b]logK + logW (6)
Since small changes in logarithmic values are approximately equal to percentage changes (%), if the percentage changes are not very large, these equations can be rewritten in dynamic terms as:
%P = -%b + [(1-b)/b]%Q - [1/b]%A - [(1-b)/b]%K + %W (7)
The pioneering work of Douglas (1976), the share of GDP going to labor, and studies by Solow (1965), Bodkin and Klein (1967) suggest that one might not be very far off the mark to assume that "b" is about equal to 2/3. If this assumption is accepted equation (7) will simplify to:
%P = .5%Q - 1.5%A - .5%K + %W (8)
The slope coefficient of .5 for the percentage change in real GDP implies an elasticity of aggregate supply equal to 2.0. Trying to validate the parameter estimates in equation (8) by regressing real GDP and the other supply-side variables on the inflation rates for the price deflator for real GDP, however, can be a very frustrating and disappointing business.
In a now classic article on "What Do Statistical Demand Curves Show" Working (1927) has shown that it may not be possible to identify the elasticities or slope coefficients for demand and supply curves. To correctly identify these parameters from historical data there must be independent shifts in the two curves. If demand fluctuates a lot more than the supply curve it may be possible to obtain a pretty good estimate of the supply elasticity and vice versa. When these two curves are shifting around simultaneously, however, it is not uncommon to end up with garbage type coefficients that are not a very good reflection of the true price elasticities for either the demand or the supply curves.
When the year to year growth rates for real GDP and its price deflator are plotted on chart paper for the 1960-94 period one observes a negative relationship that is steeper than our unit elastic demand growth equation (2).
The "flattish" nature of the aggregate supply function can be validated to some extent, however, by examining first differences in the year-year growth rates for real GDP and its deflator during years containing recessionary troughs in economic activity.
Since 1929 the first differences in the GDP deflator have been less than half as large, on the average, as the recessionary declines in the growth rate for real GDP. The implication is that recessions have been more successful--at least in the decline phase--at deflating output than the inflation rate.
Supply elasticities which are "impossible" to estimate directly can sometimes be inferred on an indirect basis. Solving the demand growth equation (2) for the %Q and substituting the resulting expression into (8) gives us the following general equilibrium or "reduced form" expression for the inflation rate:
%P = .333%Y - %A - .333%K + .667%W (9)
In Table 8.1 we show some regression coefficients which were obtained by trying to explain year-year growth rates for the GDP price deflator with modified versions of supply growth equation (8) and the general equilibrium solution for the inflation rate implied by equation (9). In these two regressions changes in the autonomous shift variable, %A, and the flow of services from the capital stock, %K, are assumed to be proportional to the year-year growth rate for real gross private domestic investment, %GPDI, and a constant term that is presumed to have a negative coefficient.
The first regression in Table 8.1, which represents supply growth equation (8), is dominated by the growth rate for wages and salaries per full time equivalent employee in domestic industries. The coefficients for the growth rates for real GDP and GPDI are not very significant from a statistical point of view and have signs that are opposite to what one would expect on a theoretical basis.
The coefficients for the second regression in Table 8.1 representing a general equilibrium solution to our demand and supply growth equations all have the right sign and are statistically significant. When the slope coefficient for the percentage change in real GDP in supply growth equation (8) is equal to .5 one would expect, on the basis of equation (9), to obtain a coefficient equal to about .333 for the growth rate for nominal GDP, %Y.
The actual coefficient of .297 for the percentage change in nominal GDP in the second regression in Table 8.1 is a little less than one might have hoped for but not widely out of sync with the derived value of .333 for equation (9). By working backwards one can determine that the implied slope coefficient for the growth rate for real GDP is equal to about .45.
One of the nice things about a log linear supply function is its flexibility. If one assumes that the flow of services from the capital stock will increase at about the same rate as the growth of output equation (8) will simplify to:
%P = - 1.5%A + %W (10)
Inflation, in that event, will be solely a supply-side phenomenon dependent on wage inflation and autonomous shifts in the production function. If one adopts a longer run horizon and assumes on the basis of rational expectations theory that the percentage change in wages will be about equal to the inflation rate, equation (8) will simplify to:
%Q = 3%A + %K (11)
Solving our demand growth equation (2) for the percentage change in output and substituting the resulting expression into this vertical supply growth equation gives us:
%P = %Y - 3%A - %K (12)
This result, in conjunction with the quantity theory of money which makes %Y equal to the growth rate for the money supply, is more in line with Milton Friedman's assertion that "inflation is always and everywhere a monetary phenomenon in the sense that it is and can be produced only by a more rapid increase in the quantity of money than in output." There is an old saying, however, which was popularized by John Maynard Keynes, that in the long run we are all dead. Friedman, moreover, is also noted for the contention that an economic model should be evaluated not so much on the basis of its assumptions but whether it yields useful predictions.
When first differences in the Dec.-Dec. inflation rate for the consumer price index are rank ordered in terms of the first differences in the Dec.-Dec. growth rate for M2 one observes an inverse, policy reaction type of relationship between these two variables, rather than the positive relationship which one would have expected on the basis of equations (8), (9) and (12), when the %Y is replaced with %M. See columns (1) and (2) of Table 8.2. The inverse relationship is a beautiful illustration of the Fed's tendency to "lean against the inflationary wind".
One of the more interesting points to note in connection with Table 8.2 is that the US economy has usually performed very well after any year when the Dec.-Dec. growth rate for M2 was allowed to increase. Most of the really poor growth years for the US economy have followed substantial declines in the M2 growth rate. The most notable exceptions to this conclusion since 1961 occurred after 1979 when the Fed, in an effort to quickly end the specter of double digit inflation for the consumer price index, allowed short term interest rates to fluctuate widely enough to tip the US economy into two recessions over a three year period.
In 1995 the M2 growth rate increased 4.2 percent after five years of very sluggish growth. In 1996 it accelerated to 4.6 percent. To the extent that consumers were saving for a near term purpose, such as being able to finance the down payment on a new car or house, these increases in liquid saving may have helped to revive the economy to the point where the Board of Governors of the Federal Reserve felt it was desirable to again raise the Federal Funds rate in March 1997.
In his midyear review of monetary policy objectives for 1993 Federal Reserve Chairman Alan Greenspan noted that, "The historical relationships between money and income, and between money and the price level have largely broken down, depriving the aggregates of much of their usefulness as guides to policy. At least for the time being, M2 has been downgraded as a reliable indicator of financial conditions in the economy, and no single variable has yet been identified to take its place. . .In these circumstances, it is especially prudent to focus on longer-term policy guides. One important guide-post is real interest rates, which have a key bearing on longer-run spending decisions and inflation prospects."
The December T-bill yield minus the 12 month percentage change in the all urban consumer price index is of some value in helping to explain changes in the inflation rate for the CPI from 1949-95. There has been a marked propensity for the CPI inflation rate to have declined or remained fairly stable when the real year-end return on T-bills was greater than 1.8 percent. Lower inflation adjusted rates of return on T-bills have a much higher propensity to be associated with accelerating inflation. See Table 8.3.
Inflationary shocks, however, are often very difficult to predict in advance of their occurrence. A relatively high inflation adjusted return on T-bills at the end of the year, in any event, has not provided investors with much assurance that the CPI inflation rate wouldn't accelerate in the following year.
Many of the theories that have been developed by economists to explain the business cycle are basically concerned with shifts in demand and/or supply. See Sherman (1991) for a more extensive survey of theories pertaining to the business cycle.
In column (4) of Table 8.4 first differences in the fourth-quarter to fourth-quarter growth rate for nominal GDP are used to represent shifts in the demand growth intercept. In the post 1968 period declines in this intercept in conjunction with a five percent or more decline in the four quarter growth rate for the real value of residential construction in column (6) have always signified that the US economy either was in a recession or was on the verge of entering a recession.
A zero growth marginal cost intercept value can be calculated each year for our supply growth equation (8) by subtracting one-half of the actual growth rate for real GDP in column (3) of Table 8.4 from the inflation rate for its implicit price deflator in column (2). First differences in these intercept values are shown in column (5).
There has only been one year in the post 1968 period when there was no increase in the marginal cost or supply growth intercept during a year containing a recessionary peak in business activity. That year was 1981, when the short lived business recovery from July 1980 to July 1981 was terminated by a more than doubling of the Federal funds rate from 9.03 percent to 19.04 percent.
All of the business expansions from 1961-1990, which lasted more than one year, have been plagued by at least one supply shock amounting to 2.0 percentage points or more.
Once the supply growth curve has begun to shift upward at a rapid rate the Fed should probably pay as much attention to recession indicators as to inflation indicators.
Short business expansions are usually terminated as a result of very tight monetary policies initiated by the Fed to prevent an acceleration of the inflation rate. In commenting on the 24 month business expansion from April 1958 to April 1960 Stephen McNees, a Vice President at the Federal Reserve Bank of Boston, (1992) noted that "an acceleration in the inflation in the mid '50s may have been the source of two recessions, the 1957-58 recession born out of the necessity to roll back an actual acceleration in inflation, and the 1960-61 recession born out of fear of having to repeat that experience." As was previously noted, the termination of the 12 month business expansion from July 1980 to July 1981, was even more clearly the result of very tight monetary policy.
While it is theoretically possible for a supply shock to produce a recession without a slump in the growth rate for nominal GDP, I don't believe that has ever happened in the United States. Since the stock market crash of 1929 there has always been a decline in the growth rate for nominal GDP in Table 8.4 just before or during a year containing a peak in business activity.
The economics profession has developed a fairly elaborate theory of aggregate demand. This theory suggests that the growth of demand can be controlled to some extent by employing appropriate monetary and fiscal policies. Our ability to manage and control aggregate supply, on the other hand, is in a more embryonic state of development.
While economic recessions have always helped to moderate wage and price inflation, the decline in the marginal cost growth intercepts has sometimes occurred only after a considerable lag. The first year following the recessionary trough years of (1949, 1954, 1958, 1961, 1970, 1975, 1980, 1982 and 1991), when labor productivity was rebounding at a rapid rate, is the only phase of the business cycle that has consistently exhibited a downward shift in the marginal cost intercepts in the post 1947 period.
The favorable shifts in our supply growth equation at that point in the business cycle are probably related to the "adjustment costs" associated with any attempt to minimize labor input during short lived recessions. Unused capacity and the existence of an employed labor force that is not fully utilized makes it possible for business enterprises to rapidly expand their output after a recessionary trough in economic activity without hiring many new employees.
From a public policy point of view, however, the more important conclusion to be derived from Table 8.4 is that shifts in aggregate demand and supply are not very well coordinated. What one would like to observe is shifts which preserve a stable price level (or inflation rate) and keep aggregate output growing at a rate which is at or very near its potential. But that has seldom happened.
Former CEA Chairman Beryl Sprinkel (1964) was among the first economists to publicize a positive relationship between changes in the money supply and changes in stock prices. If one could have accurately predicted what would happen during the year to the real value of the conventional money supply that information would have sometimes been of considerable value in helping to identify good years to have been in the stock market. Since the beginning of World War II there have been 26 years when the December-December growth rate for M1 was at least 1.6 percentage points higher than the growth rate for the all item CPI and in each of these years the financial return for the S&P index was positive. (See those cases marked with a double asterisk in column 5 of Table 8.5)
When the first differences in this method of adjusting the M1 growth rate for inflation have been equal to four percentage points or more the following year financial returns for the S&P index have also been positive. (See the eleven returns in column 5 of Table 8.5 which are identified with a hatch mark.)
Using the data in the first and last columns of this table one can verify the conclusion that the financial returns have also been positive after those years when the M1 growth rate has increased by three percentage points or more. The presumption is that the Fed would not let the money supply accelerate this much if it believed that inflation was a serious problem that might get out of hand.
There is another type of monetary acceleration that should be checked when investing in the stock market. The six years when the monetary growth rate in the first column of Table 13.6 increased and residential building permits in the second column declined have been followed by positive returns for the S&P index. When cash and checkable deposits are increasing at an accelerated rate and the demand for mortgages is expected to decline, it is reasonable to suppose that more savings will be available to prop up the stock market.
Bodkin, R. G. and L. R. Klein (1967). "Nonlinear Estimation of Aggregate Production Functions," Review of Economics and Statistics.
Dernburg, Thomas and Duncan McDougall (1976). Macroeconomics(New York: McGraw Hill, Fifth edition), 436-38.
Douglas, Paul (1976). "The Cobb-Douglas Production Function Once Again," Journal of Political Economy, (October), 903-17.
McNees, Stephen (1992). "The 1990-91 Recession in Historical Perspective," CITE>New England Economic Review, Jan./Feb., 9.
Sherman, Howard (1991). The Business Cycle(Princeton, New Jersey: Princeton University Press).
Solow, Robert (1957). "Technical Change and the Aggregate Production Function," The Review of Economic Statistics, 39(August), 312- 20.
-----, (1965). Capital Theory and the Rate of Return(Chicago: Rand McNally), 81-85.
Sprinkel, B. (1964). Money and Stock Prices(Richard Irwin).
Tobin, James (1981). "Supply-Side Economics: What Is It? Will It Work?" Economic Outlook USA, Summer.
Wells, P. (1970). "Keynes' Aggregate Supply Function," Economic Journal, September, 536-38.
Working, E. J. (1927). "What Do Statistical Demand Curves Show?" Quarterly Journal of Economics, 212-235.
Independent Variables Regression Coefficients
(1) (2)
Constant term. -1.257 -2.529
(-1.629) (-4.311)
Percentage change in chain weighted real GDP -.207
expressed in 1992 dollars. (-1.530)
Percentage change in nominal GDP. .297
(2.700)
Percentage change in chain weighted real GPDI .007 -.076
expressed in 1992 dollars. (.248) (-3.172)
Percentage change in wages and salaries per full-time 1.151 .894
equivalent employee in domestic industries. This (11.205) (6.223)
data was obtained from The Survey of Current Business,
Table 6.6C.
Summary Statistics
Adjusted R-squared .826 .849
Standard Error of the Regression 1.032 .961
Durbin Watson Statistic 1.280 1.442
The parentheses contain t-statistics for the hypothesis that the coefficient's true value is zero.
Source of basic data: Survey of Current Business and Economic Report of the President, February 1996.
Year Change in First Differences CPI Inflation Rate Following Year
M2 Growth Current Following Growth Rate
Rate Year Year Real GDP
(1) (2) (3) (4)
1975T 7.2 -5.4 -2.0 5.6
1971 6.8 -2.3 .1 5.4
1967 4.7 - .5 1.7 4.7
1995 3.8 - .2 .8 2.5
1970T 2.9 - .6 -2.3 3.3
1983 2.6 .0 .1 6.8
1961T 2.5 - .7 .6 6.0
1988 2.2 .0 .2 3.4
1986 1.5 -2.7 3.3 2.9
1981 1.2 -3.6 -5.1 -2.1
1962 .7 .6 .3 4.3
1976 .6 -2.0 1.8 4.9
1980T .6 - .8 -3.6 2.5
1996-------- .4---------- .8--------- ?------------- ?
1963 .3 .3 - .6 5.8
1979 .3 4.3 - .8 - .3
1965 .1 .9 1.6 6.4
1993 .0 - .2 .0 3.5
1989 - .3 .2 1.5 1.3
1964 - .4 - .6 .9 6.4
1972 - .4 .1 5.3 5.7
1991T - .6 -3.0 - .2 2.7
1985 - .7 - .1 -2.7 3.0
1982T - .9 -5.1 .0 4.0
1974 -1.1 3.6 -5.4 - .6
1994 -1.2 .0 - .2 2.0
1968 -1.3 1.7 1.5 3.0
1992 -1.5 - .2 - .2 2.3
1990 -1.8 1.5 -3.0 -1.0
1978 -2.7 2.3 4.3 2.9
1984 -2.7 .1 - .1 3.7
1977 -3.0 1.8 2.3 5.0
1966 -3.5 1.6 - .5 2.6
1969 -4.3 1.5 - .6 .0
1987 -5.9 3.3 .0 3.8
1973 -6.4 5.3 3.6 - .4
T identifies a year containing a recessionary trough in economic activity.
Source of basic data: Economic Report of the President.
Year Real CPI First Differences CPI Inflation Rate
T-bill Inflation Current Following
Rate Rate Year Year
1983 5.2 3.8 .0 .1
1986 4.4 1.1 -2.7 3.3
1984 4.3 3.9 .1 - .1
1982 4.2 3.8 -5.1 .0
1988 3.7 4.4 .0 .2
1985 3.3 3.8 - .1 -2.7
1949 3.2 -2.1 -5.1 8.0
1980 3.2 12.5 - .8 -3.6
1989 3.0 4.6 .2 1.5
1959 2.9 1.7 - .1 - .3
1964 2.9 1.0 - .6 .9
1994 2.9 2.7 .0 - .2
1995 2.7 2.5 - .2 .8
1965 2.5 1.9 .9 1.6
1955 2.2 .4 1.1 2.6
1967 2.0 3.0 - .5 1.7
1981 2.0 8.9 -3.6 -5.1
1954 1.9 - .7 -1.4 1.1
1961 1.9 .7 - .7 .6
1963 1.9 1.6 .3 - .6
1972 1.7 3.4 .1 5.3
1962 1.6 1.3 .6 .3
1996------ 1.6-------- 3.3----------- .8--------- ?
1966 1.5 3.5 1.6 - .5
1969 1.5 6.2 1.5 - .6
1987 1.4 4.4 3.3 .0
1952 1.3 .8 -5.2 - .1
1968 1.2 4.7 1.7 1.5
1958 1.0 1.8 -1.1 - .1
1991 1.0 3.1 -3.0 - .2
1953 .9 .7 - .1 -1.4
1960 .9 1.4 - .3 - .7
1971 .7 3.3 -2.3 .1
1990 .7 6.1 1.5 -3.0
1993 .4 2.7 - .2 .0
1992 .3 2.9 - .2 - .2
1956 .2 3.0 2.6 - .1
1957 .2 2.9 - .1 -1.1
1978 .1 9.0 2.3 4.3
1976 - .5 4.9 -2.0 1.8
1977 - .6 6.7 1.8 2.3
1970 - .7 5.6 - .6 -2.3
1979 -1.2 13.3 4.3 - .8
1973 -1.3 8.7 5.3 3.6
1975 -1.4 6.9 -5.4 -2.0
1951 -4.3 6.0 .1 -5.2
1950 -4.5 5.9 8.0 .1
1974 -5.1 12.3 3.6 -5.4
Year 4th Qtr.-4th Qtr. Growth Rates --% Point Changes-- Growth Real
Nominal Implicit Real Demand MC Residential
GDP Price GDP Intercept Intercept Construction
Deflator
(1) (2) (3) (4)n (5)n (6)
1968 9.5 4.4 4.9 3.5 -.1 6.3
1969P 6.9 5.0 1.8 -2.6 2.1P -5.8
1970T 5.0 5.1 -.2 -1.9 1.1 8.9
1971 9.4 5.1 4.3 4.4 -2.3 26.4
1972 11.9 4.3 7.2 2.5 -2.2 13.0
1973P 11.4 7.0 4.2 -.5 4.2P -10.5
1974 8.0 10.1 -2.2 -3.4 6.3 -25.6
1975T 10.3 7.7 2.4 2.3 -4.7 7.0
1976 10.0 5.3 4.7 -.3 -3.6 25.8
1977 11.7 6.4 4.9 1.7 1.1 12.8
1978 14.8 8.2 6.0 3.1 1.2 6.6
1979 9.9 8.6 1.3 -4.9 2.8 -9.1
1980P,T 9.9 9.8 .0 .0 1.8P -15.5
1981P 9.4 8.3 1.0 -.5 -2.0P -21.8
1982T 3.5 5.2 -1.6 -5.9 -1.8 -1.2
1983 11.2 3.9 6.9 7.7 -4.5 46.3
1984 9.0 3.6 5.2 -2.2 .5 4.3
1985 7.3 3.4 3.8 -1.7 .5 4.3
1986 5.0 2.5 2.4 -2.3 -.2 11.1
1987 7.4 3.3 4.0 2.4 .0 -2.5
1988 7.6 4.0 3.5 .2 .9 -.4
1989 6.4 3.9 2.4 -1.2 .5 -7.0
1990P 4.4 4.6 -.2 -2.0 2.0P -15.1
1991T 3.8 3.4 .4 -.6 -1.5 1.0
1992 6.3 2.6 3.7 2.5 -2.4 16.9
1993 4.8 2.5 2.2 -1.5 .6 8.1
1994 5.9 2.3 3.5 1.1 -.9 5.7
1995 3.8 2.5 1.3 -2.1 1.4 -1.5
1996 5.2 1.8 3.2 1.4 -1.7 4.2
Footnotes for Table 8.4
(4)n. First differences in the growth of nominal GDP in column (1).
(5)n. First differences in the growth of the implicit price deflator in column (2) minus one-half of the growth rate for real GDP in column (3).
P identifies a year containing a recessionary peak in business activity.
T identifies a year containing a recessionary trough in business activity.
Source of basic data: Survey of Current Business.
Dec.-Dec. Growth Rates
Year ---------------------- Real First Financial Return
M1 CPI M1 Diff. S&P Composite
(1) (2) (3)n (4)n (5)
1942 29.3 9.0 20.3 15.9 19.2**
1943 27.0 3.0* 24.0 3.7 25.7**#
1944 13.4 2.3* 11.1 -12.9 19.3**
1945 12.9 2.2 10.7 - .4 35.7**
1946 5.2 18.1 -12.9 -23.6 - 7.8
1947 4.4 8.8* - 4.4 8.5 5.5
1948 - 1.4 3.0* - 4.4 .0 5.4#
1949 - .3 - 2.1* 1.8 6.2 17.8**
1950 4.5 5.9 - 1.4 - 3.2 30.5#
1951 5.6 6.0 - .4 1.0 23.4
1952 3.8 .8* 3.0 3.4 17.7**
1953 1.1 .7 .4 - 2.6 - 1.2
1954 2.7 - .7* 3.4 3.0 51.2**
1955 2.2 .4 1.8 - 1.6 31.0**
1956 1.3 3.0 - 1.7 - 3.5 6.4
1957 - .7 2.9 - 3.6 - 1.9 -10.4
1958 3.8 1.8* 2.0 5.6 42.4**
1959 .6 1.7 - 1.1 - 3.1 11.8#
1960 .5 1.4* - .9 .2 .3
1961 3.2 .7* 2.5 3.4 26.6**
1962 1.8 1.3 .5 - 2.0 - 8.8
1963 3.7 1.6 2.1 1.6 22.5**
1964 4.6 1.0* 3.6 1.5 16.3**
1965 4.7 1.9 2.8 - .8 12.3**
1966 2.4 3.5 - 1.1 - 3.9 -10.0
1967 6.6 3.0* 3.6 4.7 23.7**
1968 7.7 4.7 3.0 - .6 10.8**#
1969 3.3 6.2 - 2.9 - 5.9 - 8.3
1970 5.1 5.6* - .5 2.4 3.5
1971 6.5 3.3* 3.2 3.7 14.1**
1972 9.2 3.4 5.8 2.6 18.7**
1973 5.5 8.7 - 3.2 - 9.0 -14.5
1974 4.4 12.3 - 7.9 - 4.7 -26.0
1975 4.8 6.9* - 2.1 5.8 36.9
1976 6.5 4.9* 1.6 3.7 23.6**#
1977 8.2 6.7 1.5 - .1 - 7.2
1978 8.2 9.0 - .8 - 2.3 6.4
1979 6.8 13.3 - 6.5 - 5.7 18.4
Dec.-Dec. Growth Rates
Year ---------------------- Real First Financial Return
M1 CPI M1 Diff. S&P Composite
(1) (2) (3)n (4)n (5)
1980 6.8 12.5* - 5.7 .8 31.5
1981 6.8 8.9* - 2.1 3.6 - 4.8
1982 8.7 3.8* 4.9 7.0 20.4**
1983 9.8 3.8 6.0 1.1 22.3**#
1984 5.9 3.9 2.0 - 4.0 6.0**
1985 12.3 3.8 8.5 6.5 31.1**
1986 16.9 1.1* 15.8 7.3 18.5**#
1987 3.5 4.4 - .9 -16.7 5.7#
1988 4.9 4.4 .5 1.4 16.3
1989 .9 4.6 - 3.7 - 4.2 31.2
1990 4.0 6.1 - 2.1 1.6 - 3.1
1991 8.6 3.1* 5.5 7.6 30.0**
1992 14.2 2.9* 11.3 5.8 7.4**#
1993 10.2 2.7* 7.5 - 3.8 9.4**#
1994 1.8 2.7 - .9 - 8.4 1.3
1995 - 2.1 2.5* - 4.6 - 3.7 37.1
1996 - 4.3 3.3 - 7.6 - 3.0 22.3
(3)n. Column (1) minus column (2).
(4)n. First differences in column (3).
*Identifies years when the December-December growth rate for the CPI declined by .2 percentage points or more. Except for 1981, when the Fed allowed short term interest rates to rise enough to tip the US economy into a recession, the financial returns for these years have all been positive.
**Identifies cases where the inflation adjusted growth rate for M1 in column (3) was equal to 1.7 percentage points or more. All of the financial returns in these years have been positive.
#Identifies years when the first differences in the inflation adjusted growth rate for M1 in column (4) in the preceding year were equal to 4.0 percentage points or more. All of the financial returns in these years have been positive.
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