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REGIONAL ECONOMIST | JANUARY 1999
https://www.stlouisfed.org/publications/regional-economist/january-1999/on-spreads-and-recessions

President's Message: On Spreads and Recessions
William Poole
As borrowers, we know that the interest rates we pay vary with the market's assessment of the risk that we
might default on our obligations. This is why interest rates on U.S. government securities are lower than rates
on private securities of the same maturity: We assume that the government will not renege on its promise.
Likewise, rates on lower-rated private securities, like Baa-rated corporate bonds, are higher than those on
higher-rated Aaa bonds.
The spreads between private and government securities and between Baa- and Aaa-rated bonds typically rise
whenever the economy moves into recession. Why? Because as a firm's earnings decline, so too does its
ability to service its debt. The less creditworthy the borrower and the deeper the recession, the wider the
spreads among interest rates.
A wide range of closely watched rate spreads, including the spreads between Baa- and Aaa-rated securities,
increased dramatically from July to September of last year. These widening spreads led to increased
speculation of economic recession. It is important to note, however, that when the widening of these rate
spreads is due to recession, the recession is already under way. Although I have learned never to say
"impossible," it seems unlikely that a recession is already under way. Moreover, I know of no case where the
period leading to recession was characterized by low-to-declining inflation, declining interest rates and highand-rising money growth—all of which we have now.
A more reasonable explanation for the recent widening of rate spreads is the mid-August announcement that
Russia would default on—technically, restructure—its sovereign debt. Historically, rate spreads have widened
on news that caused investors to reassess risks. Some financial market disturbances affect a narrow range of
rate spreads—for example, the Penn-Central Railroad bankruptcy declaration in 1970 and the near collapse of
Continental Illinois Bank in 1984. Other shocks, like the stock market crash of 1987, affect a broader spectrum
of spreads.
It appears to me that the Russian default led investors to think more carefully about the risks in the
marketplace and to question whether existing spreads were adequate to compensate for those risks. When
rate spreads widen, the danger is that borrowers who previously would have qualified readily for funds will find
it more difficult to obtain them. If spreads remain high for an extended period of time, the effect on the
economy can be substantial. I am inclined to think that this financial market disturbance, like many before it,
will be temporary. Indeed, spreads have narrowed substantially since last October. However, we at the Fed
must continue to watch this situation closely.

REGIONAL ECONOMIST | JANUARY 1999
https://www.stlouisfed.org/publications/regional-economist/january-1999/models-and-monetary-policy-more-science-than-art

Models and Monetary Policy: More Science Than
Art?
Kevin L. Kliesen
According to published minutes of the Federal Open Market Committee meeting held June 30 and July 1,
1998, the FOMC, worried that conditions were ripe for rising inflation, reaffirmed its previous policy position that
a "bias toward restraint"—a tightening of monetary policy—was needed. Just four months later, though,
confronted with the fallout reportedly stemming from the "Asian contagion," the FOMC decided to lower the
federal funds rate—an action the committee repeated in October and November.
Are large-scale macroeconomic forecasting models helpful to the monetary policy process in instances like
this? Or, when expectations of the future change suddenly, does a monetary policy-maker instead feel like the
circus performer who, while tied to a spinning wheel, faces an onslaught of knives thrown by a blindfolded
person?

Policy Challenges
One of the most important challenges confronting U.S. public policy-makers is the design and implementation
of economic policies that best promote rising living standards over time. To most monetary policy practitioners,
price stability—generally defined as an inflation rate low enough not to factor into the planning horizon of
consumers and producers—is the necessary first step to ensuring this outcome. The economy's long-run
growth rate, however, is largely influenced by "real" factors that tend to change rather slowly: population
growth, labor productivity and the rate of technological advancement. The problem facing monetary policymakers is that their actions have little direct influence over these factors.
Over shorter horizons, unforeseen economic disturbances—what economists call shocks—can influence
economic outcomes. These shocks, if allowed to propagate, can affect the economy's health over the long
term. But because these disturbances can't be predicted, gauging their effect is difficult—witness the recent
turmoil in Asia that has spread to other regions and affected financial markets worldwide.
In some instances, however, these disturbances have certain traits in common with previous disturbances. For
example, Federal Reserve Chairman Alan Greenspan has argued that the Asian situation is similar in many
respects to the 1995 Mexican peso crisis. If so, then macroeconomic models may help policy-makers
understand how the economy would respond to such a shock. These models may also help policy-makers
formulate a policy response that minimizes the effects of these shocks.
To do this effectively requires a model that can systematically predict the change of headline variables like
GDP growth, inflation and the unemployment rate. Alas, no model can accomplish all that. To help minimize
the uncertain nature of the forecasting business, economists have developed several types of models to help
them project the path of the economy over time. Whether any of these models can reliably inform policymakers of future outcomes in response to unusual events—and thus effectively add to the process—is open to
debate, however.

Model Types
The types of models used in the policy process can generally be described as either structural models or
forecasting models. Structural models that use a Keynesian systems of equations approach are most prevalent
in the policy arena. These models, which can have several hundred equations and identities, attempt to
forecast such variables as output (real GDP), prices and employment from the ground up—in other words, as
suggested by economic theory.1
In older structural models, such as the Federal Reserve's MPS model, the forward-looking aspect of the
model's structure—which is termed expectations—was usually assumed to be a function of past behavior.2 By
contrast, in newer structural models, such as the Federal Reserve Board's FRB/US Macroeconomic Model and
the International Monetary Fund's MULTIMOD model, the formation of expectations is quite different. These
newer models assume that the economy's producers and consumers are rational in their decision-making
processes—in other words, that they know the structure of the economy (and thus the model).3
In contrast, forecasting models eschew the systems of equations approach, employing just a few equations to
forecast future developments. These models, which are also known as time series models, instead rely on
established statistical correlations between current and previous observations (hence the name time series) of
one or more economic variables.
The most popular of these are plain vector autoregression (VAR) models and VARs that employ an error
correction process.4 An example of the latter is the Vector Error Correction Model (VECM) developed by
researchers associated with the Federal Reserve Bank of St. Louis.5
Unlike structural models, forecasting models like VARs regard all variables as simultaneously determined and,
hence, have an equation for every variable in the model. In other words, they do not assume a unique
behavioral relationship like a consumption, investment or money demand equation, which is assumed by
structural models. In terms of sheer forecasting power, forecasting models generally do better than structural
models. Conversely, forecasting models are not useful for evaluating alternative monetary policies—for
example, looking at what would happen to the growth of real GDP and inflation if the federal funds rate were
raised or lowered 25 basis points.

The Forecasting Process
At each FOMC meeting, committee members are presented with a forecast generated by the Board of
Governors' staff. This forecast, which is the staff's best guess as to the probable direction of the economy over
the next several quarters, is put together in a deliberative fashion. In other words, there is much interaction
between a large number of people responsible for monitoring every major sector of the U.S. economy, as well
as foreign economic developments. What role, if any, do models play in this process? A recently published
article outlines three ways models factor into the forecasting process.6
First, a forecast—termed a baseline projection—is made about how the economy is expected to behave over
the next four to eight quarters. The baseline projection, in which the staff projects the likely direction of real
GDP growth and inflation, takes as its starting point the final forecast generated from the previous FOMC
meeting. The reason for this is that the economic outlook typically does not change dramatically between
FOMC meetings. Nevertheless, between meetings new data become available, and/or previously released
data get revised. In this way, new economic and financial information is used to update the old forecast (from
the previous FOMC meeting), which then becomes the new baseline forecast (for the current FOMC meeting).
At this stage, the staff generally still assumes an unchanged federal funds rate.
Second, assumptions are made about variables that are outside of the process (exogenous variables). These
"conditioning assumptions," as they are called, include judgments about the future stance of monetary and

fiscal policy, foreign economic developments and oil prices. For example, if oil prices are expected to increase,
this may contribute to an increase in inflation. Each participant in this process might then alter his or her view
of the future in response to this anticipated change, making further give and take between the staff—
sometimes involving the use of output generated by model-based forecasts—necessary. Eventually, the
process converges to produce a final forecast that is used as a jumping off point at each FOMC meeting.
The baseline forecast is often termed a "judgmental forecast" because the staff does not rely very heavily on
pure model-based forecasts. During times of high uncertainty, however, there may be more reliance upon the
forecasting model and less reliance upon the judgment of the forecasters. Again, the Asian "crisis" would be a
good example of this.
Finally, a forecast is made showing how, for example, economic growth and inflation will respond to a change
in the federal funds rate target, a significant change in equity prices or major tax legislation. Thus, the policymaker is presented with a baseline forecast (no change in policy) and a forecast contingent on a specific
action. The latter is intended to provide the policy-maker with a framework for thinking about how a policy
action may affect economic growth over the near term.

Policy Hurdles
The deliberative process cannot mask the numerous uncertainties policy-makers face. For example, if there is
no agreement on the type of model to use—and there is not—then all parties will not agree on the strength or
weakness of the economy going forward. Data revisions, which, in some instances, can change the forecast
complexion significantly, further cloud the judgments of policy-makers. Finally—and this ultimately may be the
biggest hurdle of all—there is uncertainty about the policy process itself. For instance, there is no over-arching
consensus about how actions taken by the FOMC will influence the economy in the short run, what the policymaker's main objective should be, or whether a policy rule should be followed.7
For better or worse, monetary policy-making involves a good deal more than simply—and blindly—following a
forecast generated by a complex model. After all, simple forecasting models like VARs and VECMs still do a
good job of forecasting. Although structural models have evolved along with economic theory, policy-makers
will probably remain skeptical of them for evaluating alternative policies. In the end, models, while useful tools,
are not likely to replace the deliberative process currently in use—a process in which forecasts are just one
more piece of information for policy-makers to consider.
Daniel R. Steiner provided research assistance.
Endnotes
1. An identity is an equation that is true by definition. The best known identity is that for GDP: GDP = C + I
+ G + X - M, where C is consumer spending, I is investment, G is government spending, X is exports
and M is imports. Embedded within the model are equations that are used to forecast each component
and all of the major subcomponents. [back to text]
2. See Kmenta (1982). [back to text]
3. This assumption is termed "rational expectations" and can best be explained by President Lincoln's
famous maxim that, "You can fool some of the people all of the time and all of the people some of the
time, but you can't fool all of the people all of the time." [back to text]
4. Simply put, an error correction process enables the model to incorporate long-run statistical
relationships between one or more variables that may help the forecaster do a better job. [back to text]
5. See Anderson et al. (1998). [back to text]
6. See Reifschneider et al. (1997). [back to text]

7. An example of a policy rule is the Taylor Rule, named after Stanford University Professor John B.
Taylor. The Taylor rule is intended to provide the monetary policy-maker with some assessment of an
appropriate level for the federal funds rate target, based on: 1) the strength of the economy relative to
its potential; and 2) the current inflation rate relative to a preferred inflation rate. [back to text]

References
Anderson, Richard G., Dennis Hoffman, and Robert H. Rasche. "A Vector Error Correction Forecasting Model
of the U.S. Economy," Federal Reserve Bank of St. Louis Working Paper No. 98-008A (May 1998).
Blinder, Alan S. Central Banking in Theory and Practice (The MIT Press, 1998).
Brayton, Flint, and Peter Tinsley, eds. "A Guide to FRB/US: A Macro-economic Model of the United States,"
Finance and Discussion Series, Number 42, Federal Reserve Board (October 1996).
Diebold, Francis X. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic
Perspectives (Spring 1998), pp. 175-92.
Kmenta, Jan, ed. Large-Scale Econometric Models (North Holland, 1982).
Reifschneider, David L., David J. Stockton, and David W. Wilcox. "Econometric Models and the Monetary
Policy Process," Carnegie-Rochester Conference Series on Public Policy (December 1997), pp. 1-37.

ABOUT THE AUTHOR
Kevin L. Kliesen
Kevin L. Kliesen is a business economist and research officer at the
Federal Reserve Bank of St. Louis. His research interests include
business economics, and monetary and fiscal policy analysis. He
joined the St. Louis Fed in 1988. Read more about the author and his
research.

REGIONAL ECONOMIST | JANUARY 1999
https://www.stlouisfed.org/publications/regional-economist/january-1999/paper-tigers-how-the-asian-economies-lost-their-bite

Paper Tigers? How the Asian Economies Lost
Their Bite
Michelle Clark Neely
The past year and a half has certainly been an eventful one for international financial markets. Not since the
Latin American debt crisis of the early 1980s has there been so much turmoil in world markets. Like dominoes
tumbling, what started in Thailand in July 1997 soon spread to the other so-called Asian tigers—the fastgrowing countries of East Asia. By mid-1998, the crisis was threatening to envelop countries in Latin America
and Eastern Europe—most notably Brazil and Russia. Although conditions have stabilized somewhat in recent
months, the crisis is far from over, and the effects on the United States and other highly developed countries
have yet to fully play themselves out.
One of the more remarkable aspects of the crisis is the speed with which conditions deteriorated and spillovers
occurred in other countries. Rapid advances in computing and other communications technology have enabled
financial transactions to occur around the globe almost instantaneously. One of the painful lessons of the last
18 months is that capital can flow out of a country as quickly as it comes in—a process that can turn a molehill
into a mountain. The crisis in Asia has raised many questions about the advisability of investing in emerging
market economies and the role of domestic regulators and international organizations like the International
Monetary Fund (IMF) in preventing and stemming the damage once it's under way. But the biggest questions
remain: What happened, why did it happen and what can be done—if anything—to prevent similar crises in the
future?

The Drop Heard Round the World
Until the summer of 1997, the world economy looked pretty stable. Although Japan was virtually in recession
and its banking sector was badly damaged, the rest of the industrialized world was growing, and inflation was
low. Mexico was recovering from its 1994-95 financial crisis, and there were no serious, obvious problems in
major emerging market nations. This placid scenario changed dramatically, however, on July 2, 1997, when
Thailand devalued its currency, the baht.1 Within the next several months, the currencies of neighboring
Indonesia, Malaysia and the Philippines came under pressure, too, leading to depreciations against the dollar
ranging from 25 to 33 percent. More modest depreciations then occurred in other parts of Asia, including
Korea, Taiwan and Singapore.
In the fall and winter of '97, pressures on Asian currencies intensified. By January 1998, the currencies hit rock
bottom. The Indonesian rupiah had dropped 81 percent against the dollar since July 1, 1997, the Thai baht, 56
percent, the Malaysian ringgit, 46 percent, and the Philippine peso, 41 percent. Meanwhile, between Oct. 1,
1997, and late December of that year, the Korean won depreciated 55 percent, and the New Taiwan dollar fell
19 percent. Exchange rates in other emerging market countries also came under pressure in the latter half of
1997, but central banks in these nations were generally able to defend their currencies.

The exchange rate crisis in east Asia prompted a pullback in private capital flows to the region (see below),
which prompted further pressure on the region's exchange rates and more capital flight. International investors
—especially banks and portfolio (stock and bond) investors—who had previously been pouring money into the
region became nervous about the ability of Asian firms to pay it back. Much of this capital had been channeled
through the affected countries' domestic banking systems, which had a number of structural problems.
Because so many financial institutions and corporations in the region had borrowed in dollars and were
consequently not protected against foreign exchange risk, the severe currency depreciations seriously
weakened their balance sheets and increased credit risk.
Equity markets in both the affected countries and other emerging market nations—like those in Latin America
—became very volatile. Spreads on emerging market debt, which had been very narrow in the year or so
leading up to the crisis, jumped substantially, especially after problems emerged in Hong Kong in October
1997. International credit agencies began to downgrade emerging market sovereign (government) debt,
dramatically increasing the cost of borrowing. Korea, which had been one of the great success stories in the
developing world, suffered the ignominious distinction of having its debt fall to below investment grade, or "junk
bond" status—one of the largest downgradings in recent history.2

Glossary
Current Account—An account that shows international transactions that involve newly produced
goods and services. For most countries, the merchandise trade balance (exports minus imports) is the
largest component of the current account.
Foreign Direct Investment (FDI)—An international capital flow in which a firm in one country creates
or expands a subsidiary in another. FDI is different from portfolio investment in that it involves the
acquisition of control, as well as a transfer of resources.
Hedge—Protection against risk. An exporter, for example, can hedge against exchange rate risk by
entering into a contract that guarantees a minimum payment, regardless of changes in the importing
country's exchange rate.
Moral Hazard—Occurs when the existence of insurance encourages the insured parties to take risks
since they know they are protected by insurance.

Austerity programs instituted by the IMF as a condition of financial assistance seemingly exacerbated the
crisis. Monetary and fiscal policies were tightened to try to get exchange rate levels under control, causing
domestic interest rates to further rise and growth to slow. Many domestic banks became insolvent in market
value terms as nonperforming loan levels climbed; in some cases, bank runs even occurred. Domestic credit
crunches emerged since banks were too undercapitalized to lend. In countries where sovereign debt was
significantly downgraded, banks could no longer issue internationally recognized letters of credit for domestic
exporters and importers. Since these countries were highly dependent on trade, and were counting on export
revenues to help dig themselves out, this restraint only made matters worse.
In some countries, especially Indonesia, severe political unrest accompanied and exacerbated the economic
turmoil. Further compounding Asia's situation was Japan's continued weakness. By the end of 1997, Japan
had slipped into recession and was not able to help its neighbors with additional investment or increased trade.
Although conditions in the region stabilized somewhat by late 1998, it will be several years before these
formerly fast growing economies get back on track.

What Went Wrong?
The crisis in Asia caught nearly everyone by surprise. After all, this was a region that had accounted for more
than half of the world's economic growth in the 1990s. Inflation was low, and there were no obvious fiscal or
monetary imbalances. Although many of the countries in the region were running high current account deficits
—as they had been for a number of years—the deficits were not generally viewed as a problem since
international investors seemed more than willing to supply the capital to finance them.
If investors and policy-makers had been looking a little more closely, however, they would have seen a number
of similarities between the period preceding the Asian crisis and the periods leading up to the two previous
international financial crises—the 1980s Latin American debt crisis and the 1994-95 Mexican financial crisis.
First, capital inflows to the affected crisis areas were extremely heavy prior to the downturns as international
investors enjoyed easier access to domestic financial markets. In the previous two crises, spreads on
emerging market debt declined substantially as investors downgraded the risk difference between developed
countries' and emerging market countries' debt. Second, the affected regions enjoyed strong ratings from
international credit agencies and widespread investor participation in their markets. In Asia, as in the other two
crisis regions, both of these factors could be viewed as very positive developments—a veritable stamp of
approval from the international financial community.
But, as in the prior two crises, there were warning signs that all of the confidence in Asia may have been
misplaced. Most domestic borrowers, for example, were unhedged against exchange rate risk. This meant that
a large change in a borrowing country's exchange rate could have dramatically increased the cost of paying
back the dollars it borrowed from foreign investors.
Even more ominous were structural problems in the region's financial sectors—especially banking—which left
them ill-equipped to manage the sheer volume of investment flows. A laundry list of some of these problems
includes: extensive government involvement in private-sector investment allocation; underdeveloped and
underregulated equity markets; "crony capitalism" and corruption in banks; overly close linkages between
banks and major industries (called "connected lending"); weak corporate governance; poor supervision and
regulation of financial institutions; and a general lack of transparency in the economy's financial sectors.
Underlying all of these weaknesses, according to many economists, was pervasive moral hazard—a "heads I
win, tails someone else loses" philosophy. Banks, investors and firms assumed that the region's governments
and international organizations would bail them out in the event of financial catastrophe.

A Tale of Two Triggers
Since the crisis began, economists have searched for answers as to what triggered the crisis in Asia and its
spread to other emerging markets around the world. Although a number of explanations have been offered, the
vast majority of views fall into one of two camps: the "fundamentalist" view, espoused by Massachusetts
Institute of Technology economist Paul Krugman, among others; and the "panic" view, most closely associated
with Harvard economist Jeffrey Sachs and World Bank chief economist Joseph Stiglitz. The fundamentalist
view focuses on how the borrowing countries' policies and practices fed the crisis, whereas the panic view
focuses on the role lenders played.
The fundamentalist view holds that flawed financial systems were at the root of the crisis and its spread.3
Although there were no obvious macroeconomic forewarning signals, there were changes occurring in these
economies that made them vulnerable to a financial crisis. The seeds for the financial crisis were actually sown
several years before currency pressures began. Because most currencies in the region were in some way
pegged, or tied, to the U.S. dollar, the appreciation of the dollar versus the yen and other major currencies over
the past several years meant that Asian countries were losing competitiveness in export markets. As a result,
export growth—the engine driving these economies—began to slow. Meanwhile, an increasing portion of

foreign capital inflows to the region consisted of liquid portfolio investment, rather than long-term foreign direct
investment (FDI).
The bulk of these liquid capital flows were channeled into domestic investments by local bank and nonbank
financial institutions. Frequently, the same assets—land, real estate and financial assets—were used for
collateral and investment, driving the value of existing collateral up, which, in turn, spurred more lending and
increased asset prices. Risk was further heightened when local banks—in response to low interest rates
overseas and "stable" exchange rates at home—began borrowing foreign exchange abroad. These local
banks then converted the foreign exchange to domestic currency and lent the proceeds domestically,
assuming all the exchange rate risk. These risky practices went unnoticed and/or unchallenged in the weakly
supervised and crony-controlled banking systems in which they occurred.
According to the fundamentalist view, such a bubble was bound to burst in the face of a shock. Some analysts
have argued that the increase in U.S. interest rates in early 1997 provided the pop, while others say it was the
decline in the world prices of exports—computer chips and commodities like rice, wood and rubber—from
these countries. Regardless of the exact cause, asset prices fell, causing nonperforming loans to rise and the
value of collateral to fall; domestic lending then declined and asset prices fell yet again.
Foreign and domestic investors subsequently got spooked, and capital started to flow out of the region. This
put pressure on the exchange rate pegs in the region. Because of the fragile state of the region's domestic
financial systems, the monetary authorities risked further financial turmoil if they attempted to raise interest
rates to defend the pegs. So the pegs were ultimately abandoned. Because so much of the foreign currency
debt was unhedged, the currency depreciations led to widespread bankruptcies and slowing economic growth.
Subscribers to the panic, or "disorderly workout," theory, on the other hand, maintain that the economic
fundamentals in Asia were essentially sound. Rather, a swift change in expectations was the impetus for the
massive capital outflows that triggered and fed the crisis. Economists Steven Radelet and Jeffrey Sachs (1998)
essentially argue that a molehill (problems in Thailand) was turned into a mountain (a regional financial crisis)
because of international investors' irrational behavior and the overly harsh fiscal and monetary medicine
prescribed by the IMF as the crisis broke.
They point to several factors that support the premise that the crisis was panic-induced. First, the crisis was
largely unanticipated. There were no warning signals, such as an increase in interest rates on the region's debt
or downgradings by debt rating agencies. Second, prior to the crisis, there was substantial lending to private
firms and banks that did not have any sort of government guarantee or insurance (a large proportion of which
have gone into or are now facing bankruptcy). This fact contradicts the idea that moral hazard was so
pervasive that investors were knowingly making bad deals, assuming that they would be bailed out. It is
consistent, however, with the notion that international investors panicked in unison and withdrew money from
all investments—good or bad.
Third, once the crisis was under way, the affected countries experienced widespread credit crunches—even
viable domestic exporters that had confirmed sales could not get credit—again suggesting irrationality on the
part of lenders. Fourth, the trigger for the crisis was not the deflation of asset values, as the fundamentalists
argue, but, rather, the sudden withdrawal of funds from the region. Radelet and Sachs argue that some of the
conditions the IMF imposed on these countries for financial assistance "added to, rather than ameliorated, the
panic." 4

Never Again?
Regardless of the cause of the crisis and its consequent spillover to other countries, all analysts agree that the
fallout in Asia and other emerging market nations has been severe. Although initially only financial in nature,

the crisis has led to significant real economic losses in these formerly fast-growing economies. It is clear—
whether one believes the fundamentalist theory or the panic theory—that the region's financial sectors did not
"evolve in parallel with economic performance." 5 Moreover, international investors overinvested in the region
because of a lack of opportunities (low interest rates) in the United States and Japan. This global chase for
short-term profits caused herding, myopic behavior on the part of investors. At the same time, investors were
misled—deliberately, in a few cases—about the ability of Asian economies and financial markets to absorb and
profitably employ the massive inflows of foreign capital. In short, there is plenty of "blame"to go around.
While most analysts agree on the steps—especially reform of the banking sector—these countries must take
to get back on solid economic footing, they acknowledge that Asian governments face a number of enormous
challenges to meet those goals. First, many of the changes that the IMF, the G-7 countries and others offering
help have insisted upon have proved to be extremely difficult to implement politically in several countries.
Leaders like former Indonesian president Suharto—who was eventually forced to resign—and Malaysian
president Mahathir Mohamad were extremely reluctant to enact the needed reforms and clashed with both
their governments and political opponents, creating credibility problems abroad and political unrest at home.
Second, one of the short-term prescriptions for restoring economic health—a large boost in exports—is
running into complications. Japan's continued economic weakness means that one of the region's major export
markets is essentially out of commission. And in other countries, like the United States, protectionist
sentiments have been aroused by the increase in cheaper imports from the region, making it difficult for Asian
exporters to make further inroads in this market. U.S. steel producers, in particular, have been very vocal about
the perceived threat to the U.S. steel industry from the post-crisis drop in world steel prices.6
At this point, most economists expect the Asian countries to return to good health in the next several years.
The outlook for non-Asian countries affected by the contagion—notably Brazil and Russia—is more uncertain,
however. In mid-November 1998, Brazil agreed to a $42 billion IMF-led program to stabilize its economy and
soothe the still jittery international investment community.7 Russia is a tougher case. The first IMF program
there collapsed soon after its enactment, as the Russian government first squandered the initial funds the IMF
provided, then devalued the ruble and defaulted on its sovereign debt, and failed to undertake any of the IMF's
prescriptions for more aid.8
As with previous crises, the next step will be assessing the lessons learned and devising prescriptions for
mitigating similar future crises, wherever they might occur. Clearly, greater transparency in financial
transactions, more stringent regulatory oversight and consistent application of accounting standards would go
a long way toward preventing a collapse the size of Asia's. But no country in the world will ever be immune
from a financial calamity (remember the U.S. savings and loan debacle of the 1980s?). Moreover, the
"regulatory straitjacket" that would be necessary to prevent any type of crisis from occurring would also cut
nations off from the many benefits that come with participating in the international financial community. To
proclaim "never again" is foolhardy; to strive for less fallout and contagion when these crises occur is a goal
worth pursuing.

Sidebar 1

International Capital: Easy In, Easy Out
The five Asian economies hit hardest by the crisis—Indonesia, Korea, Malaysia, the Philippines and
Thailand—have been on a tremendous roller-coaster ride in international financial markets. For several
years before the outbreak of the crisis, these five countries enjoyed an enormous inflow of foreign
capital (Line 2 of the table), mostly from private creditors (Line 3). This foreign capital inflow enabled
these countries to finance their current account deficits (Line 1), invest overseas (Line 13) and add to

their reserves (Line 14). In 1995, for example, $86.3 billion flowed into these five countries from
international sources; $41 billion (47.5 percent) financed the current account deficit and $31.3 billion
(36.3 percent) was reinvested in nonequity assets overseas. The remaining $14 billion (16.2 percent)
went into the countries' international reserves.
In 1995 and 1996, the bulk of these inflows were from private sources, such as loans from commercial
banks (Line 8); investments like bond issues and private placements by nonbank private creditors (Line
9); equity investment (Line 6); and foreign direct investment (Line 5). In 1996, official inflows (Line 10)—
loans and other financing from international organizations like the World Bank and the IMF (Line 11), as
well as assistance from other nations (bilateral creditors, Line 12)—were negligible, and even negative
(that is, the countries were paying back international official creditors).
The picture completely turned around in 1997, however. External financing to the five countries dropped
from $91.2 billion to $25 billion—an amount insufficient to cover the countries' collective current account
deficits at the time. A net outflow of portfolio equity, as well as commercial bank funding, occurred.
Reserves fell by nearly $31 billion as the countries attempted to defend their currencies and bolster
their economies.9 Official flows, meanwhile, jumped significantly to help cover the short-fall and
moderate the crisis.
Forecasts for 1998 and 1999 show a slightly improved picture. Private capital is still expected to flow
out of the region, but a turnaround in the countries' current account balances and the continuation of
official assistance will enable the countries to collectively replenish their reserves. Most of the
improvement in their current accounts is likely to come from a reduction in imports (as these countries
struggle to resume economic growth) and a rebound in exports. Foreign direct investment (Line 5) in
the countries is expected to increase modestly—a vote of confidence from investors taking the long
view.

Five Asian Economies: External Financing1
(billions of U.S. dollars)
Line

1995 1996

1997 1998 1999
e

f

f

1. Current
account balance

–
41.0

–
54.5

–
26.3

59.9

58.6

2. External
financing, net

86.3

91.2

25.0

3.7

–
10.0

3. Private flows,
net

83.8

93.8

–6.0

–
24.6

–
15.1

15.9

17.4

–0.2

8.0

6.5

5. Direct
equity, net

4.9

5.8

6.5

6.9

7.4

6. Portfolio
equity, net

11.0

11.6

–6.8

1.1

–0.9

67.9

76.4

–5.7

–
32.6

–
21.6

8.
Commercial 58.0
banks, net

58.3

–
29.0

–
30.5

–
17.8

9.
Nonbanks,
net

9.9

18.1

23.3

–2.1

–3.8

10. Official flows,
net

2.5

–2.6

30.9

28.3

5.0

11.
International
financial
institutions

–0.3

–2.0

22.6

22.4

2.5

12. Bilateral
creditors

2.9

–0.6

8.4

5.9

2.6

13. Resident
lending/other, net2

–
31.3

–
17.4

–
29.4

–
23.2

–
18.7

14. Reserves
excluding gold (–
= increase)

–
14.0

–
19.3

30.7

–
40.4

–
29.9

4. Equity
investment, net

7. Private
creditors, net

Key:
1 – Indonesia, Malaysia, South Korea, Thailand, Philippines
2 – Including resident net lending, monetary gold and errors and omissions
e – estimate
f – IIF forecast
SOURCE: Institute of International Finance
[back to text]

Thomas A. Pollmann provided research assistance.
Endnotes
1. For detailed overviews of the events leading up to and including the crisis, see International Monetary
Fund (1998) and Corsetti, Pesenti and Roubini (1998). An excellent web site containing hundreds of
articles on the Asian crisis is maintained by Nouriel Roubini of New York University. The web address is:
www.stern.nyu.edu/~nroubini/asia/AsiaHomepage.html#intro1 [back to text]
2. Indonesia's and Thailand's sovereign debt was similarly downgraded. [back to text]
3. See Krugman (1998), Noland et al. (1998) and Corsetti, Pesenti and Roubini (1998) for a detailed
explanation of the fundamentalist view. [back to text]
4. Radelet and Sachs (1998), p. 44. [back to text]
5. Noland et al. (1998), p. 3. [back to text]
6. See Wayne (1998). [back to text]
7. See Blustein (1998). [back to text]
8. See Sanger (1998). [back to text]
9. Part of the outflow of reserves was due to the inability of Korean banks to roll over their international
bank loans, which forced the Bank of Korea to stop in and assist the banks, providing dollars to pay off
the bank loans. The central bank was also providing dollars to domestic firms that could no longer get
them from domestic banks. [back to text]

References
Blustein, Paul. "U.S., IMF Announce Plan to Avert Brazilian Crisis," Washington Post (November 14, 1998).
Corsetti, Giancarlo, Paolo Pesenti, and Nouriel Roubini. "What Caused the Asian Currency and Financial
Crisis?" Mimeo, New York University (September 1998).
International Monetary Fund. International Capital Markets: Developments, Prospects, and Key Policy Issues,
Washington, D.C. (September 1998).
Krugman, Paul. "Asia: What Went Wrong," Fortune (March 2, 1998), p. 32.
Noland, Marcus et al. "Global Economic Effects of the Asian Currency Devaluations," Policy Analyses in
International Economics, Institute for International Economics (July 1998).
Radelet, Steven, and Jeffrey Sachs. "The Onset of the East Asian Financial Crisis," NBER Working Paper No.
6680 (August 1998).
Sanger, David E. "As Economies Fail, the IMF is Rife with Recriminations," New York Times (October 2, 1998).
Wayne, Leslie. "American Steel at the Barricades," New York Times (December 10, 1998).

REGIONAL ECONOMIST | JANUARY 1999
https://www.stlouisfed.org/publications/regional-economist/january-1999/the-national-and-district-economiesare-they-marchingin-step

The National and District Economies—Are They
Marching in Step?
Adam M. Zaretsky
The U.S. economy could not decide at what pace it wanted to produce output last year. In the first quarter of
1998, real GDP posted an unexpectedly high 5.5 percent annual growth rate. This was followed by a slower
1.8 percent annual growth rate in the second quarter. Many analysts, who at this point had already begun to
acknowledge the effects that both the Asian crisis and jittery financial markets were having on the national
economy, were then surprised by the early number for third-quarter real growth—a startling jump to 3.9
percent. Fast, slow, fast—just what has been happening in the U.S. economy? And has the economy of the
Eighth Federal Reserve District been following suit or marching to the beat of a different drummer?

The Ups and Downs of the National Economy...
To answer the first question, the national economy has slowed since 1997, despite the appearance of a
rebound in the third quarter. As always, the announced third-quarter GDP growth rate is only a preliminary
number, subject to revision. In the first and second quarters of 1998, for example, the preliminary numbers
showed real growth of 4.8 percent and 1.6 percent, respectively. After revision, the final numbers revealed that
real growth was actually 5.5 percent in the first quarter and 1.8 percent in the second.
On top of this, the initial data show that much of the increase in the third-quarter GDP growth rate came from
an unexpected rise in inventory accumulation, due to a rebound at the end of the General Motors shutdown
and a stronger U.S. dollar. Although the end of the GM shutdown in late July led to a rebuilding of dealer
inventories, the actual change in total automotive inventories was still negative. The rate of decline of these
inventories, however, slowed substantially. Add to this the many businesses—particularly retailers—that sought
to take advantage of the relatively low prices of Asian goods resulting from weak Asian economies and an
appreciating dollar, and the jump in inventory investment is accounted for.
The Bureau of Economic Analysis—the government agency responsible for GDP data—stated in its thirdquarter GDP report that inventory investment accounted for almost a full percentage point of the 3.9 percent
growth rate. Actually, this percentage point represents almost all of investment's contribution to real output. In
the second quarter of 1998, in contrast, inventory (dis)investment reduced real GDP growth by almost 2.7
percentage points, making total investment's contribution to real output negative.
At the same time inventories were increasing, consumer spending was moderating. In particular, spending on
durable goods—like cars and household appliances—and spending on nondurable goods—like food and
clothing—increased slightly, but substantially less than in the second quarter. Meanwhile, spending on services
—like entertainment, health and financial—maintained its brisk second-quarter pace. Thus, third-quarter
growth in spending on services essentially drove growth in consumption. Earlier, growth in spending on
durables had played a much more important role.

Along with the recently erratic GDP numbers has been a slowing in payroll employment growth. Between June
and October of 1998, employment growth has averaged about 189,000 jobs a month. During the first five
months of the year, however, employment growth averaged 255,000 jobs a month.1 Actually, as the
accompanying table shows, U.S. payroll employment grew at a 2 percent annual rate in the third quarter of
1998, almost a percentage point less than the first quarter. In the second quarter, jobs grew at a 2.3 percent
annual rate. Thus, job growth has been steadily slowing all year. These employment data do not necessarily
contradict the output data, though, because third-quarter GDP growth would have been roughly 2.9 percent
(about the long-run average growth rate) without inventory investment. The continued slowing in employment
growth, coupled with the recent inventory accumulation, could therefore signal a further slackening of output
growth in the coming quarter—most likely, a return to a more average growth rate.

Table 1

Slowing the Step: Payroll Employment Growth Rates
Total
Quarter

Manufacturing

III/98 II/98 I/98 III/98 II/98 I/98

Nonmanufacturing
III/98

II/98

I/98

United States

2.0

2.3

2.8

–3.0 –0.5 1.5

2.9

2.8

3.1

Eighth District

0.3

1.9

1.4

–2.5 –0.5 1.0

0.9

2.4

1.4

NOTE: All data are seasonally adjusted annual rates of quarterly growth. See Endnote 2 for a definition of the Eighth District
SOURCE: U.S. Bureau of Labor Statistics

The picture isn't all glum, though. Tight labor markets across the nation have made it tough for employers to fill
vacancies. Without new workers, there can be no job growth. Nonetheless, the nation's nonmanufacturing
sector, which employs about 85 percent of all workers, continues to show strong employment growth. The third
quarter's 2.9 percent annual growth rate in nonmanufacturing employment is comparable to the 2.8 percent
rate posted in the second quarter and the 3 percent rate in the first.
The U.S. manufacturing sector, however, is bearing the brunt of the employment decline. In the third quarter,
employment in this sector fell at a 3 percent annual rate, much sharper than the 0.5 percent decline posted in
the second quarter. Employment declines at manufacturing firms, however, are not that unusual since these
firms tend to be affected by the business cycle more. But manufacturing employment declines are not
necessarily the norm, either. Manufacturing employment grew at a 1.5 percent annual rate in the first quarter of
1998, marking the end of a two-year positive growth trend. Taken together, then, the currently available data
seem to suggest that the slowing in national output growth that began in the second quarter of 1998 is
probably still with us and will likely stick around into next quarter.

...and of the District Economy
Whether the District economy has been following suit or marching to the beat of a different drummer is a more
difficult question to answer. The principal reason for the difficulty is that state-level output data are not as timely
as GDP. In fact, the latest gross state product data (the state-level equivalent of GDP) are from 1996—almost
three years old! Thus, much more reliance must be placed on employment data.
Payroll employment growth in the District has actually been following a different beat since 1997.2 For
example, payroll employment grew at a 0.3 percent annual rate in the third quarter of 1998, after rising at a 1.9

percent rate a quarter earlier. And that rate was up from the 1.4 percent gain in the first quarter. Thus, in the
third quarter of this year, District employment growth was more than 1.5 percentage points less than the nation
as a whole. Like their national counterparts, however, District labor markets are extremely tight.
Unlike the rest of the nation, though, employment growth in the District's nonmanufacturing sector, which
employs about 85 percent of all District workers, has been slowing. In the third quarter of 1998, new jobs in this
sector were created at only a 0.9 percent annual rate, after rising at a 2.4 percent rate in the second quarter.
That's a 1.5 percentage point swing in one quarter—the biggest monthly drop in this growth rate since the
second quarter of 1995. That said, it is only one quarter, and the decline came on the heels of a 1 percentage
point gain between the first and second quarters of 1998.
At the same time, the District's manufacturing sector has followed a pattern of steady decline, like its national
counterpart. District manufacturing employment fell at a 2.5 percent annual rate in the third quarter of this year,
after a drop of 0.5 percent in the second quarter. As with the national numbers, though, it's not unusual to see
manufacturing employment decline from time to time. Still, coupled with the severe turnaround in
nonmanufacturing employment, the trend becomes more troubling. With both major employment sectors in
decline, therefore, the outlook for District output growth is probably a bit weaker than it is for the rest of the
country.
What is the answer to the question, then? The District economy has been marching to the beat of a different
drummer, but it's not completely out of step. While District manufacturing employment seems to be mimicking
the nation rather well, District nonmanufacturing employment appears to be doing its own thing. Furthermore, if
the swings in District employment growth rates are a reliable indicator of expected movements in District
output growth rates, output growth is probably going to remain slower than it was six months or a year ago.
Unfortunately, the output data to confirm this won't be available for two more years.
AUTHOR'S NOTE: Since this article was written, the final GDP growth number for the third quarter was
released. It was 3.7 percent.
Gilberto Espinoza provided research assistance.
Endnotes
1. These figures have been adjusted for the effects of the GM strike. [back to text]
2. The "District" composite contains data for the whole states of Arkansas, Illinois, Indiana, Kentucky,
Mississippi, Missouri and Tennessee. For information on how the individual states compare with the
nation and this "District" composite, see the tables and charts on pages 18 and 19 of this publication. All
data have been seasonally adjusted. [back to text]

REGIONAL ECONOMIST | JANUARY 1999
https://www.stlouisfed.org/publications/regional-economist/january-1999/news-bulletins-from-the-eighth-federal-reserve-district

Pieces of Eight: News Bulletins from the Eighth
Federal Reserve District
Jeryldine Tully

Regional Economist Takes Its Show on the Road
Starting next issue, you'll see all-new content in the Pieces of Eight section. The usual Pieces of Eight content
will be replaced by an economic profile on a town or city somewhere in the Eighth Federal Reserve District
(see map). We'll discover—in-person—the economic aftereffects in areas that have undergone major recent
changes, whether they be positive or negative, man-made or acts of God.
We're making the change for two reasons. First, we learned in last year's readership survey that the Pieces of
Eight section was the only one in The Regional Economist that went largely unread (so if you're reading this
now, you're the exception!). Secondly, we wanted to look for a way to impart more regional information into the
publication to balance the increasingly global nature of the economic topics covered in the three main articles.
We're looking forward to learning more about our region and sharing that information with you. If you have
ideas about which areas would be interesting for us to visit, send them to Jeryldine Tully at
Jeryldine.Tully@stls.frb.org.

Data Page Changes on the Way
Starting with the April issue of The Regional Economist, the data pages will have a new look. We're revamping
the content, in addition to freshening up the design. To make way for the community profile that will replace the
content that usually appears on this page (see related story above), the number of data pages will be reduced
to three from five. We're also introducing a national and regional economic briefing essay for those who would
like a text synopsis of current data trends.
The new data pages will cover banking, as well as regional business, national economic and agricultural
indicators.
The District banking data will look familiar; the only thing missing will be the breakouts of performance
ratios by bank size.
The regional business indicators will be condensed to one page, instead of two, with the data
reformatted to highlight growth rates, rather than levels. Some new data series also will be added; for
example, year-to-date housing permits for each of the seven District states will be reported. In addition,
charts highlighting District economic data that come out less frequently will be rotated among the four
yearly issues.
A third page will contain national economic indicators, like GDP growth and inflation, as well as
agricultural data.

We realize that some of you will still want to have access to the data we're eliminating. Not to worry: Starting in
April, all of the data series you're used to seeing in printed form in The Regional Economist will be available on
FRED®, the Bank's economic data base.

District
Data

The Regional Economist • January 1999

Selected economic indicators of banking,
agricultural and business conditions in
the Eighth Federal Reserve District

Commercial Bank Performance Ratios
U.S., District and State
All
U.S.

U.S.
District
<$15B ]

IL

AR

IN

KY

MS

MO

TN

Return on Average
Assets (Annualized)
3rd quarter 1998

1.49%

1.36%

1.37%

1.20%

1.34%

1.34%

1.32%

1.21%

1.63%

2nd quarter 1998

1.46

1.36

1.39

1.46

1.33

1.32

1.31

1.05

1.62

3rd quarter 1997

1.37

1.34

1.32

1.14

1.35

1.29

1.46

1.28

1.59

Return on Average
Equity (Annualized)
3rd quarter 1998

15.35%

15.39% 14.11% 11.69% 14.96% 16.18%

13.42% 14.15%

19.68%

2nd quarter 1998

15.09

15.51

14.44

16.20

14.76

16.00

13.39

11.92

19.80

3rd quarter 1997

14.78

15.10

13.98

12.89

15.16

14.85

15.26

15.42

17.83

Net Interest Margin
(Annualized)
3rd quarter 1998

4.80%

4.30%

4.29%

4.44%

4.29%

4.21%

4.63%

3.88%

4.81%

2nd quarter 1998

4.71

4.25

4.33

3.63

4.23

4.24

4.62

4.13

4.75

4.89

4.46

AAA

4.35

4.34

4.39

5.00

4.48

4.46

3rd quarter 1998

1.02%

0.90%

1.02%

0.96%

0.60%

0.69%

0.59%

0.88%

1.18%

2nd quarter 1998

0.95

0.93

1.00

0.99

0.55

0.74

0.67

0.86

1.28

3rd quarter 1997

1.05

1.00

0.94

1.04

0.60

0.70

0.59

0.83

1.96

3rd quarter 1998

0.80%

0.33%

0.22%

0.29%

0.21%

0.37%

0.28%

0.22%

0.55%

2nd quarter 1998

0.72

0.31

0.22

0.17

0.20

0.34

0.26

0.26

0.51

3rd quarter 1997

0.80

0.37

0.20

0.54

0.15

0.33

0.28

0.31

0.63

3rd quarter 1998

1.85%

1.40%

1.29%

1.36%

1.26%

1.37%

1.42%

1.42%

1.51%

2nd quarter 1998

1.83

1.41

1.35

1.29

1.23

1.42

1.44

1.46

1.52

3rd quarter 1997

1.89

1.42

1.35

1.43

1.30

1.51

1.47

1.38

1.43

3rd quarter 1997
Nonperforming Loans
•f Total Loans

2

Net Loan Losses 4Average Total Loans
(Annualized)

Loan Loss Reserve -f
Total Loans

1

2

U.S. banks with average assets of less than $15 billion are shown
separately to make comparisons with District banks more meaningful, as there are no District banks with average assets
greater than $15 billion.
Includes loans 90 days or more past due and nonaccrual loans

NOTE: Data include only that portion of the state within Eighth
District boundaries.
SOURCE: FFIEC Reports of Condition and Income for all Insured
U.S. Commercial Banks

Commercial Bank Performance Ratios
by Asset Size

3rd Quarter 1998
Asset Quality

Earnings

Net Loan Loss Ratio

Return on Average Assets
Annualized

Return on Average Equity

Nonperforming Loan Ratio2

Net Interest Margin"

Loan Loss Reserve Ratio

D = District

< $100 Million

$300 Million - $1 Billion

US = United States

$100 Million-$300 Million

$1 Billion-$15 Billion

1

Loan losses are adjusted for recoveries.

NOTE: Asset quality ratios are calculated as a percent of total loans.

2

Includes loans 90 days or more past due and nonaccrual loans

SOURCE: FFIEC Reports of Condition and Income for all Insured

3

Interest income less interest expense as a percent of average
earning assets

U.S. Commercial Banks

16

The Regional Economist • January 1999

Agricultural Bank Performance Ratios
U.S.

AR

IL

IN

KY

MS

MO

TN

Return on average assets (annualized)
3rd quarter 1998

1.30%

1.38%

1.25%

1.17%

1.40%

1.45%

1.22%

1.23%

2nd quarter 1998

1.30

1.28

1.30

1.21

1.40

1.38

1.20

1.24

3rd quarter 1997

1.33

1.42

1.31

1.26

1.46

1.55

1.31

1.36

3rd quarter 1998

12.35%

12.76%

11.25%

11.53%

13.05%

15.17%

11.82%

11.07%

2nd quarter 1998

12.43

12.06

11.56

11.94

13.28

14.37

11.62

11.30

3rd quarter 1997

12.69

13.15

11.83

12.57

13.62

16.53

12.36

13.58

Return on average equity (annualized)

Net interest margin (annualized)
3rd quarter 1998

4.47%

4.28%

4.35%

4.82%

4.47%

5.07%

4.29%

2nd quarter 1998

4.45

4.30

4.10

4.98

4.43

4.99

4.24

4.21

3rd quarter 1997

4.62

4.46

4.16

4.56

4.60

5.08

4.48

4.43

0.13%

4.19%

Ag loan losses •=- average ag loans (annualized)
3rd quarter 1998

0.16%

0.16%

-0.04%

0.07%

0.23%

0.15%

0.09%

2nd quarter 1998

0.14

0.13

-0.14

-0.05

0.03

0.19

0.17

0.01

3rd quarter 1997

0.14

0.08

-0.05

-0.61

0.15

0.24

0.11

0.02

3rd quarter 1998

1.44%

0.91%

0.84%

2.66%

1.68%

1.50%

1.16%

0.94%

2nd quarter 1998

1.51

0.79

0.81

3.50

2.24

1.72

1.26

0.88

3rd quarter 1997

1.32

0.68

0.71

3.43

1.70

0.89

1.65

0.34

Ag nonperforming loans 1 •=• total ag loans

1

Includes loans 90 days or more past due and nonaccrual loans

NOTE: Agricultural banks are defined as those banks with a greater-than-average share of agricultural loans to total loans.
Data include only that portion of the state within Eighth District boundaries.
SOURCE: FFIEC Reports of Condition and Income for all Insured U.S. Commercial Banks

U.S. Agricultural Exports*
Monthly Data

U.S. Agricultural Exports by Commodity
Commodity

Jul

Aug

Sep

Dollar a m o u n t s in billions
Year-to-date

Change from year ago

Livestock & products

.88

.83

.75

10.67

Corn

.35

.35

.30

4.26

-30.0

Cotton

.20

.14

.10

2.54

-7.0

Rice

.07

.07

.07

1.13

16.0

Soybeans

.20

.17

.17

6.12

-12.0

Tobacco

.06

.10

.08

1.45

-10.0

Wheat

.31

.34

.30

3.76

-9.0

3.88

3.70

3.49

53.73

-4.0

1

TOTAL

-2.0%

Includes commodities not listed here

U.S. Crop and Livestock
Prices

Indexes of Food and Agricultural Prices
Growth 1

Level
111/98

11/98

111/97

II/98-III/98

III/97-III/98

101

103

107

-8.8%

-6.2%

134

131

140

9.5

-4.1

82

91

113

-36.1

-27.7

Indiana

87

98

112

-37.9

-22.3

Missouri

90

98

107

-29.0

-16.2

N.A.

N.A.

N.A.

Prices received by U.S. farmers

2

Prices received by District farmers3
Arkansas
Illinois

Tennessee

N.A.

N.A.

Prices paid by U.S. farmers
Production items

Ill

114

117

-9.1

-5.1

Other items

114

116

117

-5.6

-2.6

Consumer food prices

161

160

158

2.8

2.1

Consumer nonfood prices

164

163

161

1.6

1.5

1

Compounded annual rates of change are computed from unrounded data.
2
Index of prices received for all farm products and prices paid (1990-92=100)
3
Indexes for Kentucky and Mississippi are unavailable.
N.A. = Not Available
NOTE: Data not seasonally adjusted except for consumer food prices and nonfood prices

17

Selected U.S. and State Business Indicators
Compounded Annual Rates of Change in
Nonagricultural Employment

United States
IH/1998 11/1998 III/1997
Labor force
(in thousands)
137,595 137,351 136,379
Total nonagricultural
employment
(in thousands)
126,141 125,516 122,995
Unemployment rate
4.5%
4.4% 4.9%
II/1998

1/1998 11/1997

Real personal income*
(in billions)
$4,351.0 $4,324.3 $4,210.4

Arkansas
III/1998 11/1998 HI/1997
Labor force
(in thousands)
1,241.2
Total nonagricultural
employment
(in thousands)
1,127.1
Unemployment rate
4.7%
II/1998
Real personal income*
(in billions)
$31.4

1,246.6 1,209.5
1,125.1 1,105.4
5.1% 5.3%
1/1998 11/1997
$31.4

$30.8

Illinois
HI/1998 11/1998 HI/1997
Labor force
(in thousands)
6,159.5
Total nonagricultural
employment
(in thousands)
5,881.3
Unemployment rate
4.4%

5,864.7 5,787.8
4.2% 4.6%

11/1998

1/1998 II/1997

Real personal income*
(in billions)
$213.0

6,143.4

$211.3

6,133.5

$206.5

Indiana
HI/1998 11/1998 III/1997
Labor force
(in thousands)
3,088.3
Total nonagricultural
employment
(in thousands)
2,875.3
Unemployment rate
2.8%

2,892.0 2,863.5
2.8% 3.6%

H/1998

1/1998 11/1997

Real personal income*
(in billions)
$87.1

3,097.2

$86.7

3,102.2

$84.5

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Kentucky
HI/1998 11/1998 III/1997
Labor force
(in thousands)
Total nonagricultural
employment
(in thousands)
Unemployment rate

1,943.8

1,940.8 1,935.4

1,754.2
4.2%

1,748.8 1,719.4
4.2%
5.3%

H/1998

1/1998 11/1997

Real personal income*
(in billions)
$51.4

$51.1

$50.0

Mississippi
HI/1998 11/1998 III/1997
Labor force
(in thousands)
Total nonagricultural
employment
(in thousands)
Unemployment rate

1,281.3

1,279.8 1,268.8

1,123.6
5.1%

1,121.7 1,110.3
5.0%
5.8%

11/1998

1/1998 11/1997

Real personal income*
(in billions)
$31.6

$31.4

$30.7

Missouri
HI/1998 11/1998 III/1997
Labor force
(in thousands)
2,908.0
Total nonagricultural
employment
(in thousands)
2,676.5
Unemployment rate
4.0%
11/1998
Real personal income*
(in billions)
$81.9

2,911.9

2,878.9

2,672.1
4.4%

2,642.0
4.1%

1/1998 11/1997
$81.3

$79.5

Tennessee
HI/1998 11/1998 III/1997
Labor force
(in thousands)
2,776.6
Total nonagricultural
employment
(in thousands)
2,621.0
Unemployment rate
4.0%
11/1998
Real personal income*
(in billions)
$77.5
Total
Manufacturing

2,778.7

2,704.3

2,622.8
4.3%

2,589.0
5.5%

1/1998 11/1997
$77.3

$75.7

Construction

Government
General Services

Finance, Insurance
and Real Estate

Transportation, Communication
and Public Utilities
I Wholesale/Retail Trade

NOTE: All data are seasonally adjusted. The nonagricultural employment data reflect the most current benchmark revision.
* Annual rate. Data deflated by CPI, 1982-84=100.

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