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Non-published Research Reports

10-11-2009

Efects On he U.S. Economy Of A Serious H1N1

Epidemic: Analysis With he USAGE Model
Peter B. Dixon
Monash University

Maureen T. Rimmer
Monash University

George Verikios
Monash University

Follow this and additional works at: htp://research.create.usc.edu/nonpublished_reports

Recommended Citation
Dixon, Peter B.; Rimmer, Maureen T.; and Verikios, George, "Efects On he U.S. Economy Of A Serious H1N1 Epidemic: Analysis
With he USAGE Model" (2009). Non-published Research Reports. Paper 16.
htp://research.create.usc.edu/nonpublished_reports/16

his Article is brought to you for free and open access by CREATE Research Archive. It has been accepted for inclusion in Non-published Research
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Effects on the U.S. economy of a serious H1N1 epidemic: analysis with the USAGE
model

By Peter B. Dixon, Maureen T. Rimmer and George Verikios

Centre of Policy Studies
Monash University

October 11, 2009

Summary
We analyse the economic effects of an H1N1 influenza epidemic that infects 90
million Americans, requiring 60 million to seek medical attention with 5 million being
hospitalized and 350,000 deaths. We assume that the epidemic is concentrated over a 6
month period in which it causes:
(1) 65 per cent reductions in both inbound and outbound international tourism and
business travel;
(2) an upsurge in sick leave and widespread school closures requiring withdrawal
of parents from the labor force leading to a loss of productivity of 1.05 per
cent;
(3) a 20 per cent surge in demand for hospital and other medical services;
(4) a permanent reduction in the labor force of 0.18 per cent because of H1N1-
related deaths; and
(5) a 0.9 per cent reduction in the average propensity to consume associated with
temporary cessation of large public gatherings, for example sporting events.
Using USAGE, a detailed dynamic CGE model of the U.S., we find that these 5 sets
of shocks would have the effects shown in Table 1. These are quite severe at the height
of the epidemic (peak quarter) and include a 4 per cent reduction in employment.
Averaged over the epidemic year the effects are considerably damped. In the year
following the epidemic, the macroeconomic effects are slightly positive. By reducing
wage rates, the epidemic improves the competitive position of the U.S. economy at the
start of the post-epidemic year.
Table 1. USAGE results for effects of H1N1 epidemic
(Percentage deviations from baseline)
Variable Peak quarter Epidemic year Next year
Employment -4.0 -2.2 0.3
GDP -5.0 -2.8 0.2
Private consumption -5.2 -3.1 0.2
Investment -9.8 -7.4 0.0
Exports -14.9 -9.0 0.2
Imports -12.9 -10.5 -0.6
1. Background on the USAGE model
USAGE 1 is a detailed, dynamic, CGE model of the U.S. It has been developed at
the Centre of Policy Studies, Monash University, in collaboration with the U.S.
International Trade Commission.2 The theoretical structure of USAGE is similar to that
of the MONASH model of Australia (Dixon and Rimmer, 2002). However, in both its
theoretical and empirical detail, USAGE goes beyond MONASH. USAGE can be run
with up to 500 industries, 700 occupations and 51 regions (50 States plus the District of
Columbia). In the application reported in this paper we use a version of the model in
which there are 39 industries.
USAGE includes three types of dynamic mechanisms: capital accumulation;
liability accumulation; and lagged adjustment processes. Capital accumulation is
specified separately for each industry. An industry’s capital stock at the start of year t+1
is its capital at the start of year t plus its investment during year t minus depreciation.
Investment during year t is determined as a positive function of the expected rate of
return on the industry’s capital. 3 Liability accumulation is specified for the public sector
and for the foreign accounts. Public sector liability at the start of year t+1 is public sector
liability at the start of year t plus the public sector deficit incurred during year t. Net
foreign liabilities at the start of year t+1 are specified as net foreign liabilities at the start
of year t plus the current account deficit in year t plus the effects of revaluations of assets
and liabilities caused by changes in price levels and the exchange rate. Lagged
adjustment processes are specified for the response of wage rates to gaps between the
demand for and the supply of labor by occupation.
In a USAGE simulation of the effects of policy and other shocks, we need two
runs of the model: a baseline or business-as-usual run and a policy run. The baseline is
intended to be a plausible forecast while the policy run generates deviations away from
the baseline caused by the shocks under consideration (e.g. an outbreak of H1N1
influenza). The baseline incorporates trends in industry technologies, household
preferences and trade and demographic variables. These trends are estimated largely on
the basis of results from historical runs in which USAGE is forced to track a piece of
history. Most macro variables are exogenous in the baseline so that their paths can be set
in accordance with forecasts made by expert macro forecasting groups such as the
Congressional Budget Office. This requires endogenization of various macro
propensities, e.g. the average propensity to consume. These propensities must be allowed
to adjust in the baseline run to accommodate the exogenous paths for the macro variables.
The policy run in a USAGE study is normally conducted with a different closure
(choice of exogenous variables) from that used in the baseline. In the policy run, macro
variables must be endogenous: we want to know how they are affected by the shocks
under consideration. Correspondingly, macro propensities are exogenized and given the
values they had in the baseline. More generally, all exogenous variables in the policy run
have the values they had in the baseline, either endogenously or exogenously, with the
1
U.S. Applied General Equilibrium.
2
Prominent applications of USAGE by the U.S. International Trade Commission include USITC (2004
and 2007).
3
The investment specification for the MONASH model, adopted in USAGE, is discussed in detail in
Dixon et al. (2005)

2
exception of the variables of interest. Comparison of results from the policy and baseline
runs then gives the effects of moving the variables of interest away from their baseline
values.
For this project, the baseline and policy runs differ with regard to the values given
to exogenous variables representing an outbreak of H1N1 influenza. We interpret the
differences between the results in the baseline and the policy runs as the effects of the
outbreak.
In previous applications, the USAGE model produced annual results. For this
project, the model has been modified so that it produces quarterly results. This
modification is important because it is likely that an epidemic will have sharp effects over
a short period. An annual model tends to smooth out effects leading to potential
underestimation of disruption. For example, if an epidemic caused an 80 per cent loss of
inbound international tourism within a particular quarter, then the adjustment path of the
tourism industry would be quite different from that in a situation in which international
tourism declined by 20 per cent for a year. Similarly, a 20 per cent increase in a single
quarter in demands for medical services related to infectious diseases would place more
stress on the medical system than a 5 per cent increase spread over a year.
2. USAGE simulations: setting the shocks
A major epidemic, e.g. a serious outbreak of H1N1 influenza, could have
significant consequences for the U.S. economy. These could arise from several channels
including:
(1) temporary reductions in inbound and outbound international tourism and
business travel;
(2) a temporary upsurge in sick leave and widespread school closures requiring
withdrawal of parents from the labor force;
(3) a large surge in demand for hospital and other medical services;
(4) some deaths with related permanent reduction in the labor force; and
(5) temporary cessation of large public gatherings, for example sporting events.
Dr Bumsoo Lee (2009) has provided a quantitative scenario covering factors (1)
to (5). In this scenario about 92 million Americans are infected with H1N1 over a period
of 7 quarters. Of these, 59.8 million experience symptoms. Nearly all of the infections
(96.4 per cent) are in the third and fourth quarters. Consequently, in Dr Lee’s scenario
almost all medical expenses, missed days at work, deaths, etc take place in quarters 3 and
4. In our economic modeling we will ignore the parts of Dr Lee’s scenario that are
outside those two quarters.
We assume that the two peak quarters of infection and cost in Dr Lee’s scenario
correspond to Q1 and Q2 in 2010. Following Dr Lee’s estimates we impose 5 sets of
shocks. We asssume:
(S1) that inbound and outbound tourism fall by 65 per cent in 2010.Q1, remain at
this low level in 2010.Q2 and then recover smoothly to their basecase level
over the next four quarters. We assume that Americans who cancel their

3
 outbound tourism save their holiday money. This imparts a small reduction
(0.91 per cent) to the average propensity to consume in 2010.Q1 which we
assume is reversed gradually over the period 2010.Q3 to 2011.Q2.
(S2) that workers miss a total of 84.5 million days of work over the two quarters
2010.Q1 and 2010.Q2 on account of their own sickness and a further 48.1
million days while caring for children who are either sick or kept home by
school closures. We assume that aversion behavior (fear) keeps a further 5
per cent of the workforce at home for 1.5 weeks during 2010.Q1 and 2010.Q2,
giving a loss of 56.3 million work days (=150m workers multiplied by 5 per
cent multiplied by 7.5 days). In total there is a loss of 188.9 million
workdays. This translates to a reduction in labor productivity of 1.05 per cent
[= 188.9 million days out of the 18,000 million days available from 150
million workers supplying 120 days each]. We assume that labor productivity
returns to normal in 2010.Q3.
(S3) that out of the 59.8 million people who experience symptoms: 15 million seek
no medical attention but spend $3 (2003 dollars) on pharmaceuticals; 39.7
million seek medical attention but are not hospitalized, incurring expenses of
$293 (2003 dollars); 4.7 million are hospitalized and survive, incurring
expenses of $18,298 (2003 dollars); and 0.35 million are hospitalized but die,
incurring expenses of $46,120 (2003 dollars). Altogether medical expenses
are $114,014million (2003 dollars) incurred over a six month period. This
amounts to a 19.45 per cent increase in demand for medical services over
2010.Q1 and 2010.Q2. We assume that demand for medical services returns
to normal in 2010.Q3.
(S4) that out of the 0.35 million who die, 0.27 million are workers. This translates
into a permanent reduction in the labor force of 0.18 per cent, phased in as a
reduction of 0.09 per cent in 2010.Q1 and a further 0.09 per cent in 2010.Q2
[0.09 = 0.5*100*0.27/150].
(S5) that in 2010.Q1 and 2010.Q2 Americans reduce their attendance at sporting
events and other entertainments involving large gatherings by 75 per cent.
This is equivalent to a 7.0 per cent reduction in demand for the USAGE
product Miscellaneous services which represents 13 per cent of household
expenditures. We assume that Americans save their attendance money and
thus their average propensity to consume falls by 0.90 per cent in 2010.Q1.
We assume that attendance at mass entertainments returns to normal in
2010.Q3 and the associated reduction in the average propensity to consume is
eliminated.
3. Results
This section reports USAGE results for the effects of the shocks described in
section 2. We start with the employment and GDP effects of the 5 sets of shocks in total.
Then we analyse the employment results in more detail by describing the effects of each
set of shocks individually. Next we look at investment and the other expenditure
components of GDP. Following this we present results for industries.

4
Employment and GDP
Chart 1 shows the combined effects of the shocks on aggregate employment and
GDP. The main effect occurs in 2010.Q2 when employment falls 4.0 per cent below the
baseline. The reduction in GDP is even larger, 5.0 per cent in 2010.Q2. The decline in
GDP relative to employment mainly reflects the loss in productivity imposed in (S2). On
average through 2010, the epidemic reduces aggregate employment by 2.2 per cent and
GDP by 2.8 per cent. Both aggregate employment and GDP are a little higher in 2011
with the 2010 epidemic than they would have been without it. Through 2011, Chart 1
shows average positive deviations for employment and GDP of 0.3 per cent and 0.2 per
cent. As indicated in Chart 2, the epidemic-related reduction in employment in 2010
causes real wage rates to be lower than they otherwise would have been. This allows the
U.S. to arrive in 2011 with enhanced international competitiveness so that when tourism
recovers and the other epidemic-related shocks disappear, employment and output move
above their baseline values.
Charts 3 to 6 indicate the relative importance of the different shocks in
determining the overall employment effects. We introduce the shocks sequentially with
the effect of each set of shocks being revealed by comparison of results in successive
simulations. The order in which the shocks are introduced is arbitrary. Fortunately the
ordering is not important in the calculation of the effects of each set of shocks.
The solid line in Chart 3 shows the effects of the collapse of international tourism
(S1) alone while the dotted line shows the combined effects of the tourism and
productivity shocks, (S1) and (S2). The chart shows that the tourism shocks are the
major contributor to the short-run employment effects of the hypothetical epidemic. Out
of the 4.0 per cent reduction in 2010.Q2, 2.4 percentage points are contributed by these
shocks. Comparison of the dotted line in Chart 3 with the solid line shows that the
productivity shocks (S2) are a relatively minor contributor to aggregate employment. In
2010.Q2 the productivity shocks move employment down by an extra 0.5 percentage
points, from -2.4 per cent to -2.9 per cent.
Comparison of the dotted and solid lines in Chart 4 shows that the aggregate
employment effects of diverting expenditures towards medical services and away from
other categories of household expenditure (S3) is positive in the short run. The main
reason is that the production of medical services (e.g. hospital care) is considerably more
labor intensive than production of most other items of household expenditure. The
employment effect of the diversion of expenditures is damped in our simulations because
we assume that half of the extra labor requirements in medical industries is provided by
longer hours rather than extra jobs. Nevertheless, the short-run aggregate employment
effect in 2010 of the diversion remains positive. Extra medical expenditures in 2010
have a small negative effect on aggregate employment in 2011: the dotted line in Chart 4
lies below the solid line for most of 2011. This is a reflection of the wage mechanism
mentioned earlier: extra employment in 2010 associated with medical expenditures
weakens the competitive advantage that the U.S. experiences in 2011.
Chart 5 indicates that H1N1 deaths (S4) have almost no effect on employment in
the short run but have a small negative effect in the long run. Short-run results in
USAGE are mainly demand driven and the deaths have little effect on aggregate demand.

5
In the longer run, employment is determined mainly by labor supply: demand for labor
adjusts to changes in supply via wage movements. Beyond 2010, H1N1-related deaths in
2010 reduce employment by reducing labor supply.
Consistent with the idea that the short-run results are demand driven, Chart 6
indicates that diversion of entertainment expenditures into savings (S5) has a significant
negative effect on employment in the first half of 2010: for 2010.Q2 the dotted line in
Chart 6 lies 1.4 percentage points below the solid line. Again, the wage mechanism
means that employment-reducing shocks in 2010 have a small positive effect on
employment in 2011.
Investment and capital
Chart 7 shows that the epidemic reduces investment: by 1.5 per cent in 2010.Q1;
by 9.8 per cent in 2010.Q2; and by 12.6 per cent in 2010.Q3. In 2010.Q1, investment
falls below the baseline because demand-contracting [(S1) and (S5)] and cost-increasing
[(S2)] shocks reduce the rental value of capital. This damps expected rates of return and
thereby reduces investment. It is also true that in 2010.Q1 the epidemic causes excess
capacity to appear in some industries, particularly those related to tourism and
construction. Excess capacity in 2010.Q1 has a strongly negative effect on in investment
in 2010.Q2. Weak investment in 2010.Q2 causes further excess capacity to appear,
explaining weak investment in 2010.Q3. In 2010.Q3, much of the pick up in demand for
capital associated with the recovery in the demand for entertainment and the start of the
recovery in tourism is satisfied by working down the excess capacity that appeared in
2010.Q1 and 2010.Q2. By 2010.Q4 investment starts to move back towards the baseline.
This is because excess capacity in 2010.Q3 is declining as capital in existence adjusts
down and capital in use adjusts up, Chart 8. By 2011.Q1, excess capacity is eliminated
(that is, capacity utilization is at normal levels).
Expenditure components of GDP
Chart 9 shows epidemic-induced movements in the real expenditure components
of GDP. Exports decline sharply in 2010.Q1 reflecting the 65 per cent reduction in
inbound tourism (S1). Although inbound tourism does not fully recover until 2011.Q2,
aggregate exports move back close to their baseline path by 2010.Q3. The recovery of
exports is assisted by real devaluation (Chart 10, to be discussed shortly) associated with
weak investment (already discussed). Imports decline sharply in 2010.Q1 and 2010.Q2.
This reflects three factors: the reduction in outbound tourism; real devaluation (in
2010.Q2); and the decline in GDP. Private consumption closely follows the path of real
GDP. Public consumption is treated exogenously and assumed not to be affected by the
epidemic.
As shown in Chart 10, the initial movement in the real exchange rate is positive.
Then there is significant real devaluation. Eventually the real exchange rate returns close
to its baseline. These movements can be understood through the GDP identity:
Y − (C + I + G) = X − M . (1)
Initially, 2010.Q1, Y, and C fall by about 3.5 per cent, G doesn’t move and I falls by
about 1.5 per cent. This means that X-M must fall. The fall in X-M is facilitated by real
appreciation. In 2010.Q2, the deviation in the left hand side of (1) is close to zero: the

6
fall in Y and the fixity of G are sufficient to offset the strong negative deviation in I.
Consequently, the exchange rate deviation in 2010.Q2 is small. In 2010.Q3 to 2011.Q1
the deviation path for investment is well below those for Y, C and G. Thus, the deviation
in X-M is positive requiring real devaluation. Beyond 2011.Q1, the macro expenditure
aggregates, and correspondingly the real exchange rate, return close to their basecase
paths.
Industry outputs
USAGE results for the effects of the hypothetical epidemic on industry outputs
are given in Charts 11 to 16. Chart 11 covers industries that are directly impacted by the
epidemic. Output of Medical services is stimulated in the first half of 2010 by about 20
per cent through (S3). Inbound and Outbound tourism contract in the first half of 2010
by about 65 percent through (S1). Miscellaneous services contracts by about 10 per cent
through the direct shock applied in (S5) and through the general contraction in economic
activity. The Domestic vacation industry is slightly stimulated via favourable
substitution against Outbound tourism.
Chart 12 shows sharp short-run contractionary effects for industries supplying
inputs to investment. In 2010.Q3, output of construction is about 12.5 per cent below its
baseline and remains below baseline until 2011.Q2. Other investment-supplying
industries benefit from their trade exposure. For example, the outputs of Machinery,
Electrical machinery and Transport equipment are above their baselines by 2010.Q4,
even though aggregate investment is still well below its baseline (Chart 7). This reflects
a low real exchange rate (Chart 10) which facilitates exports of the products of these
industries and inhibits imports.
Charts 13 and 14 show that import-competing industries are adversely affected by
the hypothetical epidemic in the short run. This is mainly through the contraction of
economic activity. By 2010.Q3, output of most of these industries is above baseline: real
devaluation improves their competitive position against imports. Exceptions are Mining
(mainly crude oil) and petroleum products which do not return to baseline until 2011.Q1.
Output of these products is related mainly to economic activity, with import shares in the
domestic market responding only sluggishly to changes in the real exchange rate.
Charts 15 and 16 show results for service industries. With two exceptions, output
of these industries dips well below baseline in 2010.Q1 and 2010.Q2, recovers in the
second half of 2010 and moves slightly above baseline in 2011. The first exception is
Government services (defense, public administration, etc). This industry shows zero
output deviations because its entire sales are to government consumption which we
assume is unaffected by the epidemic. The second exception is Ownership of dwellings.
The output of this industry is the shelter provide by the housing stock. The epidemic-
related investment slump in 2010 leaves the housing stock, and therefore the output of
this industry, below baseline in 2011.
Concluding remarks
In this paper we used a quarterly CGE model to simulate the effects of a
hypothetical H1N1 epidemic infecting about 90 million Americans and causing
symptoms of various levels of severity in about 60 million. The use of a model with

7
quarterly periodicity rather than the usual annual periodicity allowed us to capture the
short-run nature of an epidemic. Such an event would have its economic effects
concentrated over no more than one or two quarters.
Our analysis demonstrates that an H1N1 epidemic could have significant
macroeconomic effects. It is likely that it would reduce household demands for
entertainment services and demands by international tourists for hotels, travel and other
services within the U.S. It is also likely that industries would face increased costs via
absenteeism. Both the demand decreases and cost increases associated with an epidemic
of the size assumed in this paper could be expected to cause a sharp reduction in
investment with resulting adverse effects on employment and GDP. In our simulations
the reductions in employment and GDP in the peak quarter of the assumed epidemic were
4 and 5 per cent respectively.
The CGE model showed substantial epidemic-related effects on several
industries: positive for medical services; positive for domestic vacations; negative for
inbound and outbound tourism; and negative for miscellaneous services which includes
mass-attendance entertainment. For other industries, the results were fairly uniform with
variations reflecting macroeconomic effects. Construction was particularly adversely
affected in the short run by weakness in investment. Trade-exposed industries showed
rapid recovery facilitated by real devaluation. For nearly all industries, the epidemic
produced a sharp but short-lived downturn.
References
Dixon, P.B. and M.T. Rimmer (2002), Dynamic General Equilibrium Modelling for
Forecasting and Policy: a Practical Guide and Documentation of MONASH,
Contributions to Economic Analysis 256, North-Holland Publishing Company,
pp.xiv+338.
Dixon, P.B., K.R. Pearson, M.R. Picton and M.T. Rimmer (2005), “Rational expectations
for large CGE models: a practical algorithm and a policy application”, Economic
Modelling, Vol. 22(6), December, pp.1001-1019.
Lee, Bumsoo (2009), “H1N1 epidemic: Data for economic modeling”, note, September
19, pp. 8.
United States International Trade Commission (2004), The Economic Effects of
Significant U.S. Import Restraints: Fourth Update 2004, Investigation No. 332-
325, Publication 3701, June.
United States International Trade Commission (2007), The Economic Effects of
Significant U.S. Import Restraints: Fifth Update 2007, Investigation No. 332-325,
Publication 3906, February.

8
 Chart 1. Effects of the hypothetical epidemic on aggregate employment and GDP
(percentage deviations from baseline)
1

0
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

-1

-2

Employment
-3

-4

GDP

-5

-6

Chart 2. Effects of the hypothetical epidemic on aggregate employment and the real
wage rate (percentage deviations from baseline)
1

0.5
Employment

0
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

-0.5

-1
Real wage rate

-1.5

-2

-2.5

-3

-3.5

-4

-4.5

9
 Chart 3. Effects of tourism (S1) and productivity (S2) shocks on aggregate
employment (percentage deviations from baseline)
1

0.5

0
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

-0.5

-1

-1.5

-2
(S1)

-2.5

(S1)+(S2)

-3

-3.5

Chart 4. Revealing the effects of medical expenses (S3) on aggregate employment

(percentage deviations from baseline)
1

0.5

0
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

-0.5

-1

-1.5

(S1)+(S2)+(S3)

-2

-2.5
(S1)+(S2)

-3

-3.5

10
Chart 5. Revealing the effects of H1N1-related deaths (S4) on aggregate employment
(percentage deviations from baseline)
1

0.5

(S1)+(S2)+(S3)

0
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

(S1)+(S2)+(S3)+(S4)
-0.5

-1

-1.5

-2

-2.5

-3

Chart 6. Revealing the effects of entertainment cancellations (S5) on aggregate

employment (percentage deviations from baseline)
1

0.5

0
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

-0.5

-1

(S1)+(S2)+(S3)+(S4)
-1.5

-2

-2.5

-3

-3.5
(S1)+(S2)+(S3)+(S4)+(S5)

-4

-4.5

11
 Chart 7. Effects of the hypothetical epidemic on aggregate investment
(percentage deviations from baseline)

0
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

-2

-4

-6

-8

-10

-12

-14

Chart 8. Effects of the hypothetical epidemic on aggregate investment and capital

(percentage deviations from baseline)
2

Capital in existence
0

-2
excess capacity

-4

-6
Capital in use

Investment
-8

-10

-12

-14
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

12
 Chart 9. Effects of the hypothetical epidemic on expenditure components of GDP
(percentage deviations from baseline)
5

Public cons.
0

GDP
Private cons.
-5

Investment

-10

Imports

-15

Exports

-20

-25
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

Chart 10. Effects of the hypothetical epidemic on the real exchange rate
(percentage deviations from baseline)
4

The real exchange rate is measured by movements in the U.S. price level
compared with prices levels in trading partners expressed in a common currency.

2 Negative movements in the real exchange rate indicate improvements in

the international competitiveness of the U.S.

0
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

-2

-4

-6

-8

13
Chart 11. Effects of the hypothetical epidemic on output of directly impacted industries
(percentage deviations from baseline)
30

20 Medical services

10
Domestic vacation

-10
Misc. services

-20

-30

-40 Inbound tourism

Outbound tourism
-50

-60

-70

-80
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

Chart 12. Effects of the hypothetical epidemic on output of investment-related

industries (percentage deviations from baseline)
8

6
Machinery

4
Elect. Mach.

0
Transport equip.
-2

-4

Computers
-6

-8 Wood furn.

-10

-12 Construction

-14
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

14
Chart 13. Effects of the hypothetical epidemic on output of highly protected import-
competing industries (percentage deviations from baseline)
8

6 Footwear

2
Agriculture

-2

Textiles
-4

-6
Apparel

-8
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

Chart 14. Effects of the hypothetical epidemic on output of other import-competing

industries (percentage deviations from baseline)
4

3 Metal prods.

2
Chemicals

1 Manu. nec Motor vehicles

Mining
0

-1

Petroleum prods.
-2

-3

-4

-5

-6

-7
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

15
Chart 15. Effects of the hypothetical epidemic on output of government-related service
industries (percentage deviations from baseline)
2

1
Social services

Govt. services
0

-1

-2
Utilities
-3

-4 Govt. enterprises

-5

-6

-7

-8 Education
Communications

-9
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

Chart 16. Effects of the hypothetical epidemic on output of private-sector service

industries (percentage deviations from baseline)
2

0
Business services

Ownership of Dwellings

-2

Auto rental
-4 Trade margins

-6

-8

Transport services

-10
2009.Q4 2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 2012.Q1 2012.Q2 2012.Q3

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Appendix. USAGE results: numbers underlying charts

Chart 1 Effects of the hypothetical epidemic on aggregate employment and GDP (% deviation from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
emp_person -2.334 -4.029 -2.108 -0.474 0.232 0.504 0.386 0.268 -2.236 0.348 -0.944
GDP -3.268 -4.975 -2.267 -0.644 0.092 0.335 0.274 0.203 -2.789 0.226 -1.281

Chart 2. Effects of the hypothetical epidemic on aggregate employment and the real wage rate (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
real_wage -0.373 -1.009 -1.483 -1.601 -1.482 -1.244 -1.06 -0.927 -1.117 -1.178 -1.147
emp_person -2.334 -4.029 -2.108 -0.474 0.232 0.504 0.386 0.268 -2.236 0.348 -0.944

Chart 3 Effects of tourism (S1) and productivity (S2) shocks on aggregate employment (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
S1 -1.694 -2.448 -2.065 -1.102 -0.046 0.486 0.617 0.565 -1.827 0.406 -0.711
S1+S2 -1.94 -2.909 -2.366 -1.159 -0.055 0.504 0.629 0.572 -2.094 0.413 -0.841

Chart 4 Revealing the effects of medical expenses (S3) on aggregate employment (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
S1+S2 -1.94 -2.909 -2.366 -1.159 -0.055 0.504 0.629 0.572 -2.094 0.413 -0.841
S1+S2+S3 -1.263 -2.589 -1.669 -0.464 0.163 0.424 0.32 0.216 -1.496 0.281 -0.608

Chart 5 Revealing the effects of H1N1-related deaths (S4) on aggregate employment (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
S1+S2+S3 -1.263 -2.589 -1.669 -0.464 0.163 0.424 0.32 0.216 -1.496 0.281 -0.608
S1+S2+S3+S4 -1.275 -2.641 -1.745 -0.549 0.08 0.334 0.221 0.108 -1.553 0.186 -0.683

Chart 6 Revealing the effects of entertainment cancellations (S5) on aggregate employment (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
S1+S2+S3+S4 -1.275 -2.641 -1.745 -0.549 0.08 0.334 0.221 0.108 -1.553 0.186 -0.683
S1+S2+S3+S4+S5 -2.334 -4.029 -2.108 -0.474 0.232 0.504 0.386 0.268 -2.236 0.348 -0.944
Chart 7 Effects of the hypothetical epidemic on aggregate investment (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
Aggregate
investment -1.549 -9.769 -12.577 -5.838 -1.77 0.822 0.669 0.427 -7.433 0.037 -3.698

Chart 8
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
Aggregate
investment -1.549 -9.769 -12.577 -5.838 -1.77 0.822 0.669 0.427 -7.433 0.037 -3.698
Capital in use -4.19 -5.936 -2.926 -1.424 -0.59 -0.592 -0.565 -0.541 -3.619 -0.572 -2.096
Capital in existence 0 -0.03 -0.221 -0.464 -0.569 -0.592 -0.565 -0.541 -0.179 -0.567 -0.373

Chart 9 Effects of the hypothetical epidemic on expenditure components of GDP (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
Aggregate
investment -1.549 -9.769 -12.577 -5.838 -1.77 0.822 0.669 0.427 -7.433 0.037 -3.698
Imports -9.54 -12.911 -11.778 -7.643 -3.711 0.389 0.466 0.328 -10.468 -0.632 -5.550
GDP -3.268 -4.975 -2.267 -0.644 0.092 0.335 0.274 0.203 -2.789 0.226 -1.281
Private
consumption -3.554 -5.217 -2.49 -1.224 -0.311 0.338 0.381 0.266 -3.121 0.169 -1.476
Exports -19.155 -14.89 -1.573 -0.243 -0.002 0.365 -0.009 0.262 -8.965 0.154 -4.406
Public
consumption 0 0 0 0 0 0 0 0 0.000 0.000 0.000

Chart 10 Effects of the hypothetical epidemic on the real exchange rate (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
Real exchange rate 1.945 -0.275 -7.505 -6.286 -3.675 -0.174 0.195 0.124 -3.030 -0.883 -1.956

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Charts 11-16 Effects of the hypothetical epidemic on output of industries (percentage deviations from baseline)
2010.Q1 2010.Q2 2010.Q3 2010.Q4 2011.Q1 2011.Q2 2011.Q3 2011.Q4 ave 2010 ave 2011 ave 10-11
FgnHol -65 -65 -54.496 -40.839 -23.084 0 0 0 -56.334 -5.771 -31.052
ExpTour -66.701 -65.264 -48.624 -34.308 -18.871 -1.257 -1.562 -1.211 -53.724 -5.725 -29.725
Holiday 4.623 1.934 7.054 5.958 3.413 -0.068 0.164 0.08 4.892 0.897 2.895
MedicServ 17.623 17.538 -0.561 -0.382 -0.212 -0.02 -0.515 -1.035 8.555 -0.446 4.055
MiscServ -7.791 -9.042 -1.93 -0.487 0.002 0.206 0.192 0.153 -4.813 0.138 -2.337

Construct -2.056 -10.148 -12.531 -6.366 -2.404 0.235 0.211 0.09 -7.775 -0.467 -4.121
Machinery -3.827 -3.929 4.287 5.438 3.928 1.244 0.851 0.822 0.492 1.711 1.102
WoodFurn -3.678 -8.143 -4.883 -0.739 0.534 0.613 0.457 0.387 -4.361 0.498 -1.932
ElectMach -4.285 -4.889 2.184 3.231 2.586 0.925 0.655 0.622 -0.940 1.197 0.129
Computers -4.031 -6.543 -2.228 0.763 1.388 0.981 0.76 0.59 -3.010 0.930 -1.040
TransEquip -2.087 -2.721 1.578 2.315 2.086 1.225 0.978 0.919 -0.229 1.302 0.537

Footwear -5.684 -4.143 5.762 5.38 3.355 0.573 0.328 0.403 0.406 0.397 0.387
Apparel -6.005 -5.615 3.263 3.47 2.266 0.492 0.357 0.398 0.405 0.404 0.4
Textiles -5.185 -4.686 3.099 3.466 2.413 0.581 0.376 0.396 0.383 0.364 0.345
Agric -5.292 -4.984 1.014 1.1 0.81 0.185 0.111 0.116 0.112 0.106 0.102

Mining -4.272 -5.08 -0.142 -0.059 0.028 -0.103 -0.131 -0.131 -2.388 -0.084 -1.236
MotorVeh -5.083 -5.974 1.545 2.523 2.248 1.213 0.987 0.904 -1.747 1.338 -0.205
Petrolprods -4.613 -6.046 -1.626 -0.333 -0.021 -0.01 0.007 -0.007 -3.155 -0.008 -1.581
Chemicals -3.453 -2.061 1.857 2.06 1.578 0.614 0.488 0.475 -0.399 0.789 0.195
ManuNEC -2.582 -3.312 0.141 1.243 1.036 0.159 -0.033 -0.069 -1.128 0.273 -0.427
MetalProds -4.229 -5.202 1.884 2.997 2.395 0.8 0.532 0.513 -1.138 1.060 -0.039

Education -7.222 -8.126 -3.706 -2.025 -0.739 0.215 0.193 0.158 -5.270 -0.043 -2.657
SocialServ -5.786 -7.216 -1.704 -0.487 0.178 0.567 0.58 0.497 -3.798 0.456 -1.671
Enterprise -4.483 -5.919 -1.736 -0.589 -0.042 0.218 0.221 0.155 -3.182 0.138 -1.522
Communicat -5.001 -6.563 -2.195 -0.729 -0.123 -0.008 0.005 -0.015 -3.622 -0.035 -1.829
Utilities -4.66 -6.168 -2.314 -1.215 -0.351 -0.018 0.027 0.013 -3.589 -0.082 -1.836

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GovtServ 0 0 0 0 0 0 0 0 0.000 0.000 0.000

TradMarg -5.081 -7.174 -2.79 -0.887 0.016 0.467 0.46 0.371 -3.983 0.329 -1.827
OwnoccDwell -5.347 -8.048 -4.554 -2.214 -0.686 -0.701 -0.688 -0.682 -5.041 -0.689 -2.865
BusFinServ -4.731 -6.039 -0.932 0.325 0.6 0.461 0.395 0.338 -2.844 0.449 -1.198
TransMarg -7.885 -8.933 -3.531 -1.403 -0.427 0.097 0.04 0.051 -5.438 -0.060 -2.749
AutoRent -4.216 -5.863 -2.386 -0.739 -0.039 0.14 0.097 0.032 -3.301 0.058 -1.622

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