changing business cycle dynamics v2.1

8/14/2019 Changing Business Cycle Dynamics V2.1

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been challenged as the economy has undergone significant changes. Macroeconomists have

sparred over the theories explaining the reduction in business cycle volatility, but the impacts of

the reduction in output variation are irrefutable and omnipresent. The reduction in U.S. business

cycle volatility since 1980 has been a great boon to households, firms, and policymakers as the

economic environment has become more certain. Reduced volatility seen in output and prices

has several benefits, allowing people to be more consistently employed and reducing resourced

devoted to economic planning and hedging against inflation. This paper will examine the roles

of structural changes in the economy and monetary policymaking with regard to the recent

reduction in business cycle volatility.

For the most part of the 20th century, the U.S. macroeconomy performed extremely well,

with an average growth rate of 3.5% per year.2 This average rate of annual growth, however,

masks the fluctuations around the underlying trend, or natural rate. For much of the 1900s,

steady output growth was punctuated by periods of dramatic contraction and expansion, known

as the business cycle. In the last thirty years, however, these fluctuations in output have been

less pronounced, as contractions and expansions beyond the underlying trend have become more

short-lived and less extreme. As documented by macroeconomists Olivier Blanchard and John

Simon, the standard deviation of output has declined markedly since 1950. Evidence of the

decline in business cycle fluctuation is data on the frequency and length of economic expansions.

Blanchard and Simon note that the average length of an expansion during the 1947 to 1981

period was nineteen quarters, compared to an expansion of thirty six quarters for the 1982 to

2000 period. Also accompanying the significant reduction in output volatility has been a

moderation in both price variability and the unemployment rate. Essentially, the evidence has

2 See Figure 1: Real GDP Yr. chart xls from 1930 to 2006


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shown that gyrations in the price level have become dampened and unemployment has been

more consistently at its long-run natural rate.

The persistent decline in macroeconomic volatility, known as the Great Moderation, is

the result of both structural changes in the economy and better monetary policymaking.

Structural changes contributing to the decline in volatility include the smoothing of the

components of output, innovations in information technology, and the increased sophistication of

financial markets. Related to macroeconomic policymaking, better monetary policy, specifically

an anchoring of inflation expectations, enhanced central bank credibility, and an understanding

of past mistakes, has contributed to the decline in volatility. Together both structural changes

and innovations in policymaking have significantly changed the U.S. economic landscape.

Economists Olivier Blanchard and John Simon note in their 2001 paper, The Long and

Large Decline in U.S. Output Volatility, that the decline in output variation has largely been a

result of the behavior of government spending, consumption, and investment activity. 3 They

attribute volatility in the early period to erratic fiscal policies during both the Korean and

Vietnam wars. Fiscal expansion also affected the volatility of output as spending increased

during Johnsons Great Society program. With respect to consumption and investment activity,

Blanchard and Simon attribute the lower volatility to increased competition and liquidity in

financial markets. Viewed thought the intertemporal lens, with better access to credit and

savings vehicles, firms and consumers face a more linear budget constraint through their initial

endowment point. For the representative household, with imperfect credit markets, the interest

rate charged on borrowing generally exceeds the yield obtainable for savings, resulting in a

kinked budget constraint. Under these conditions, as current income changes, current

consumption will increase proportionally, making consumption more volatile than it would be

3 Blanchard 30


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variation contracted. They find through econometric modeling techniques that the volatility

reduction in the durables sector was large enough to explain 66% of the reduction in aggregate

output volatility.12 Furthermore, this reduction in volatility does not arise from merely a

reduction in final sales volatility, but from production volatility. Kahn estimates that only 15%

of the decline in output volatility in the durables sector can be attributed to a change in sales

volatility.13 Volatility seen in sales figures provides an obvious justification for a decline in

output volatility, as production is performed to fulfill sales orders. With much of the volatility,

however, coming from production, the role of inventory management becomes apparent.

Over the last quarter century, both target inventory to sales ratios and deviations from

target inventory levels have significantly declined. As calculated by the U.S. Department of

Commerce, the inventory to sales ratio for the U.S. economy declined by nearly 16% during the

1992 to 2007 period.14 In his 2002 paper, Kahn decomposes the inventory to sales ratio into

trend and transitory components. The trend components is the target inventory to sales ratio,

which is driven by the advancement of information technologies. The transitory component,

however, is the deviation in the inventory to sales ratio from the desired trend component. He

shows that the target inventory to sales ratio has declined markedly the early 1980s. In addition

to the decline in the target inventory to sales target ratio, deviations of the transitory component

around the target have dampened significantly.15 As the desired amount of inventory held by

firms relative to sales has fallen, businesses have also become more adept at managing the

inventory they hold and targeting their desired levels. The reduction in the target inventory to

sales ratio shows the impact of information technology, specifically powerful computers,

productivity applications, and telecommunications. These innovation have revolutionized how

12 Kahn, McConnell, Perez-Quiros, 185.13 Kahn, McConnell, Perez-Quiros, 186.14 U.S. Department of Commerce, Inventory to Sales Ratio15 Kahn, McConnell, Perez-Quiros, 187.


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firms relate to inventory and manage their supply chains. The result of these innovations has

been a reduction in the level of production volatility.

To better understand the exact role inventory and supply chain management play in

affecting output volatility and the impact of information technologies, I have created a model

based on Kahns presentation in On the Causes of the Increased Stability of the U.S. Economy.

In my model of inventory and production decisions, there are three firms, the Low Information

Firm, the High Information Firm, and the Very High Information Firm. Each firm faces the same

amount of final sales for each period, which are determined by a random number generator and

lie between 50 and 150 units of sales.

16

Each firm also must make a production decision at the

start of each period, and is unable to alter its decision after it has dedicated itself to a specific

amount. This production decision is based partly on what each firm believes will be sales next

period and also has an inventory accumulation or exhaustion component. Additionally, all three

firms have a target inventory to sales ratio which is determined exogenously. With respect to

production, the Low Information Firm bases its production decision solely off of last periods

sales, which is based upon the underlying assumption that next periods sales are equal to this

periods sales plus a random error term. The fact that the low information firm bases production

off last periods sales is intuitive assuming the stochastic behavior of sales for each period. The

other two firms, the High Information Firm and the Very High Information Firm are more

advanced in their understanding of next periods sales. They base their production decisions with

perfect information of the next periods final sales. That means they are able to produce exactly

enough to meet sales, but must alter production if they deviate from their target inventory level

given their inventory to sales ratios. Inventory to sales ratios for both the Low Information Firm

and the High Information Firm are fixed at a level of two, while the Very High Information Firm

16 The first four final sales figues are were determined by myself for ease of calculation and grasping the model.


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has a declining inventory to sales ratio to represent the adoption of inventory eliminating

information technologies and better supply chain management. Throughout the model,

production is used to both fill sales projections and to attain the desired inventory to sales ratio.

Inventories are used fulfill sales in the event of a shortfall in production for the Low Information

Firm and can be interpreted as a security buffer in the case of misjudgments in sales projections

by both the High and Very High Information Firms. Data for each of the firms is can be seen in

Figures 1, 2, and 3. The results of a 20 period simulation reveal exactly how new technologies

can smooth production and offer striking implications for the role of inventories and new

technologies.

The results of the simulation show the standard deviations of production for the Low,

High, and Very High firms at 176.13, 94.57, and 36.05 respectively. For the Very High

Information, the volatility of production declined by a staggering 80% relative to the Low

Information Firm. After the adoption of information technology, production volatility declined

as theorized. The new technology impacted the firm in two distinct ways. Contrasting the Low

Information Firm with the High Information Firm, the only change was that the firm equipped

with high information was able to accurately predict future sales, mitigating the need to draw

down on inventories in the event of a large spike in sales. Instead in volatility in production

came from maintaining desired inventory to sales ratios. While the idea that firms can accurately

predict future sales in the next period is a bit extreme, it is not far from reality given econometric

modeling techniques coupled with integrated barcode systems and the emerging radio frequency

identification (RFID) technology found at the retail and manufacturing level. With the wide

availability of accurate data, manufacturers are able to see sales and production needs in real-


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time, enabling more accurate forecasts of future sales.17 Besides the benefit of knowing exactly

what future sales will be, the Very High Information firm had a declining inventory to sales ratio,

reflecting innovation in supply chain management and the use of just-in-time production. Using

information technologies, the representative firm is able to reduce the need to hold costly

inventories, which not only take up physical space but occupy labor in completely unproductive

activities. As telecommunications technologies have improved, coordinating inputs from various

suppliers for production has become easier, eliminating the need for inventories and speeding up

the production process. As inventories are eliminated, the inventory to sales ratio obviously

falls, reducing the need to vary production widely in an effort to obtain target inventory levels.

In addition to the inventory channel, advancements in information technology have

affected the smoothing of output through the production function. The information technology

boom has impacted volatility through the multifactor productivity variable. Consider a simple

model of the production process, Y = ZLK1-, where Y is real output, Z is a measure of total

factor productivity, and L and K are labor and capital respectively. Economists Stephen Oliner

and Daniel Sichel note that during the 1974 to 1999 period, total factor productivity growth made

up more than one-third of the growth in labor productivity.18 Besides the productivity enhancing

characteristics of new technologies, they have likely influenced a moderation in output volatility.

As new information technologies, specifically productivity applications, data management

software, and telecommunications devices, have become more widespread, shocks to total factor

productivity, the Z variable, have become smaller. With better data and communications devices,

management techniques and the best practices within firms have become more consistent and

17 Erik Brynjolfsson and Lorin Hitt discuss the impacts of computers and productivity applications at great length

and specificity in their 2000 paperBeyond Computation: Information Technology, Organizational Transformation,

and Business Performance. Their granular, but highly enlightening, analysis, however, is beyond the scope of this

paper.18 Stephen Oliner and Daniel Sichel. The Resurgence of Growth in the Late 1990s: Is Information Technology the

Story? 2000, JEP


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widely shared throughout firms and industries. Interactions between capital and labor have not

only become more efficient, but have become more reliably efficient as management technique

and know how abounds in the modern information-laden firm. Total factor productivity has also

been affected by the decline in inventories relative to sales. With no inventories to manage, labor

and capital resources are not distracted from productive activities to manage inventory

accumulation and exhaustion. With the inventory shock to total factor productivity lessened or

eliminated, output is able to grow at a smoother rate without period interruption.

Besides the impact of structural factors which have contributed to the decline in

macroeconomic volatility, much research has focused on how monetary policymaking has

impacted the recent stability of macroeconomic variables. In contrast to the Great Inflation

period of the 1970s, the subsequent Volcker-Greenspan era has been characterized by a marked

stabilization in both inflation and output. During much of the 1970s, the U.S. economy was

characterized by high inflation and deep recessions. The blame for the increase in inflation

during this period falls squarely on the shoulders of an accommodative Fed. The Volcker-

Greenspan era of policymaking, however, has brought about a distinct smoothing of

macroeconomic variables through an enhanced understanding of inflation expectations,

implementation of the Taylor principle, and flattening of the Phillips curve.

The recent decline in price volatility relative to the pre-Volcker era can be characterized

as a decrease in both inflation persistence and an anchoring of inflation expectations. Frederic

Mishkin, member of Board of Governors, notes that since the early 1970s, the persistence of

inflation has declined markedly. Given an inflationary shock, inflation reverts more quickly to

its long run level than it has in the past.19 By regressing inflation on twelve lags of itself,

Mishkin notes that the coefficients sum to approximately 0.6 and has declined significantly since

19 Mishkin inflation expectations 2


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the 1970s.20 A decline in the sum of lagged coefficients signifies that the impact in inflation only

produces a small amount of additional pressure in the future, a boon to policymakers. James

Stock and Mark Watson explain a similar phenomenon in their 2007 paper with regard to

inflation persistence. They decompose inflation into trend and transitory components, and note

that trend inflation has fallen significantly while the transitory component has become less

important in determining inflation.21 The anchoring of trend inflation signifies a reduction in

inflation expectations. The decline in inflation expectations and actual inflation are mutually

reinforcing. As expectations remain anchored actual inflation remains low, fulfilling the low

expectations and offering additional credibility to the central bank. Credibility is important

because even with a temporary rise in inflation, long-run expectations will be anchored based on

the idea that the Fed is competent. While the decline in the variability of prices has been less

pronounced than the moderation of output, it is a significant change to the macroeconomic

environment that can be attributed to better monetary policymaking.

In addition to the taming of inflation expectations, better monetary policy has affected the

variability of inflation through an adherence to the Taylor principle. While the principles of

sound money were certainly well known during much of the 20th century, data shows that only

over the last 25 years have monetary policymakers demonstrated a competence in reducing

inflation and its volatility. Specifically, under the chairmanship of Paul Volcker, the Federal

Reserve began to tame inflation with an adherence to the Taylor principle. Upon arriving at the

Federal Reserve, Chairman Volcker faced double-digit rates of inflation, but his hawkish stance

and use of the Taylor principle quickly reduced both actual inflation and inflation expectations.

The Taylor principle is that idea that given an increase in the rate of inflation, the nominal Fed

20 Mishkin inflation expectations 221 James Stock and Mark Watson. Why Has U.S. Inflation Become Harder to Forecast?


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Funds rate must increase by more than the rate of inflation for the interest rate increase to have a

real effect. This simple principle, while well know during the Great Inflation, was not adhered to

by the Federal Reserve. Economist Richard Clarida explains that the Feds response to inflation

had changed significantly since the 1970s. In his 2000 study of the behavior of the Federal

Reserve, he finds that the Feds response to inflationary pressure changed dramatically from the

pre-Volcker period to the Volcker-Greenspan period. Using John Taylors specification of the

Taylor Curve, Clarida constructs a model of the nominal Fed Funds rate using the equilibrium

real rate of interest, the deviation of inflation from the implicit target rate, and a measure of the

output gap. Clarida finds that the coefficient on the inflation term increased noticeably across

the pre-Volcker and Volcker-Greenspan periods. Clarida finds that the coefficient increased from

0.83 to 2.15, both statistically significant.22 Additionally, for the output gap term, Clarida shows

that the coefficient changed from 0.27 to 0.93, with the Volcker-Greenspan coefficient

marginally significant.23 The increase in the Feds responsiveness shows their adherence to the

Taylor rule, as increases in inflation are met with increases in the real Fed Funds rate.

Also contributing to the moderation in inflationary volatility has been a changing

relationship between inflation and changes in output. This relationship is typically expressed

through the Phillips curve, which relates inflation to unemployment. The Phillips curve can be

expressed as, = e (U-Un) + , in which represents the rate of inflation, e is expected

inflation, (U-Un) is the deviation of unemployment from its natural rate, is the responsiveness

of inflation to capacity utilization, and is a supply shock. Recent evidence has shown that the

coefficient on the unemployment term has declined since the 1980s.24 The finding that inflation

is less responsive to changes in capacity utilization has two striking macroeconomic

22 Richard Clarida. Monetary Policy Rules.23 Richard Clarida. Monetary Policy Rules.24 Mishkin Inflation Dynamics Page 5


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implications. First, if the coefficient on the unemployment gap has declined, that means the

Phillips curve has flattened, suggesting that changes in resource utilization do not have such a

great impact on inflation. The Feds hawkish stance on inflation has likely influenced a

flattening of the Phillips curve, as price increases have become less frequent and the Feds ability

to manage demand shocks has been more credible. The result is that people expect inflation to

remain contained and deviations in resource utilization do not cause large changes in inflation.

As discussed at great length before, output has moderated significantly since the 1980s, but there

are still fluctuations in the business cycle. The flattening in the Phillips curve explains also why

inflation has moderated over the same time period of output. Not only has the variability of

output decreased which would suggest that inflation should have moderated, but inflations

response to the business cycle has also dampened. Secondly, the decline in inflationary

expectations has reduced the e term, shifting the Phillips curve closer to the origin. The fact

that inflation expectations can shift a flatter Phillips curve also indicates a potential danger to

policymakers and the economy. If inflation expectations were to increase suddenly,

policymakers would be forced to sacrifice a large amount of output to bring price pressures back

to an acceptable level.

Bringing together the two chief macroeconomic variables, output and inflation, is the

Taylor curve, which represents the volatility tradeoff between the two variables. The downward

sloping Taylor curve shows the different combinations of output and inflation volatility available

to policymakers. Given an exogenous supply shock, the Taylor curve is a convenient way of

describing the optimal choices policymakers face, as they must choose between keeping prices

stable or output at its natural rate. Recent volatility in both prices and output can be explained by

an inward shift of the Taylor curve. In his 2004 speech, Ben Bernanke explain, If monetary


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policies during the late 1960s and he 170s were sufficiently far from optimal, the result could be

a combination of output volatility and inflation volatility lying well above the efficient frontier

define by the Taylor curve.25 For example, during the 1970s, policymakers had an overly

optimistic view of the economys potential, and sought to exploit a long-run version of the

Phillips curve to attain higher output. The result was elevated prices and more volatile output as

money growth created Using better data, having a informed idea of where potential output is,

and competent policymaking can achieve a lower inflation and output volatility.

The recent decline in macroeconomic variability, known as the Great Moderation, has its

roots in both structural changes and innovations in monetary policymaking. The components of

output have moderated significantly through the development of deeper financial markets,

technology, and inventory management. On the monetary side, the use the anchoring of inflation

expectations coupled with better policymaking has reduced the volatility of output and kept

prices consistently low. The result of the decrease in macroeconomic volatility has been a great

boon for society. The moderation in macroeconomic variables has not only affected an

understanding of macroeconomics, but has improved the quality of life and business for all

people. More consistent incomes, sales, employment, and prices lessened the need for economic

planning and the amount of resources required to hedging fluctuations in the business cycle and

the impacts of inflation.

25 Bernanke great moderation speech 3.


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Correlation Between Inflation and Unemployment

Correlation

1960-1970 -0.7868

1970-1980 0.3401

1980-1990 0.0829

1990-2007 0.2115


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Std. of Prices Std. of Output

1960 1.54% 2.13%

1970 2.90% 2.73%

1980 3.88% 2.67%

1990-Present 1.11% 1.41%


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Figure 1

Natural Log of RGDP

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Natural Log of RGDP

Figure 2

dFIgue

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StandardDeviationofOutput

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eriod)

Very High Information Firm

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Figure 3

Low Information Firm

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Figure 4

changing business cycle dynamics v2.1

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