Projected Jobs Supported by Exports, 2009 and 2010 

by Martin Johnson 

Office of Competition and Economics Analysis 

July 2011 

Manufacturing and Services Economics Briefs are produced by the Office of Competition and Economic Analysis of 

the International Trade Administration’s Manufacturing and Services unit. A complete list of reports, along with 

links to other trade data and analysis, is available at www.trade.gov/mas/ian. 
Manufacturing and Services Economics Brief No. 5 

ii Projected Jobs Supported by Exports, 2009 and 2010 – June 2011

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International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 iii 

Contents 

 

Contents ......................................................................................................................................... iii

Executive Summary ........................................................................................................................ v

Projected Jobs Supported by Exports, 2009 and 2010 .................................................................... 1

Appendix A. Description and Evaluation of Estimation Approaches ............................................ 5

Appendix B. Robustness Tests of Projected Value ...................................................................... 11

 
Manufacturing and Services Economics Brief No. 5 

iv Projected Jobs Supported by Exports, 2009 and 2010 – June 2011

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International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 v 

Executive Summary 

The International Trade Administration’s 2010 report “Exports Support American Jobs” 

provided preliminary estimates for jobs supported by exports for 2009 and for the value of 

exports that support one job for 2009 and 2010. The value of exports that support one job has 

been used as a metric to link jobs with export gains under President Barack Obama’s National 

Export Initiative. Given the metric’s prominence, this Economic Brief attempts to improve 

projections and to provide transparency in making the projections. It presents a new and better 

method and provides revised estimates for 2009 and 2010: 

• The revised estimates of jobs supported by exports are 8.7 million in 2009 and 9.2 

million in 2010. The revised number for 2009 increases the preliminary estimate by 

200,000. 

• The value of exports that supports one job was $164,000 in 2009 and $181,000 for 2010. 

That is, the value fell slightly from 2008 to 2009 (from $165,000 to $164,000) because of 

the recession and softness in export prices. In 2010, the value rebounded by $17,000, or 

10 percent, to $181,000 as export prices and productivity strengthened. 

 
Manufacturing and Services Economics Brief No. 5 

vi Projected Jobs Supported by Exports, 2009 and 2010 – June 2011

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International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 1 

Projected Jobs Supported by Exports, 2009 and 2010 

In 2010, the International Trade Administration published a report titled “Exports 

Support American Jobs” by John Tschetter.1 The report provided estimates of jobs supported by 

exports and of the value of exports that support one job from 1993 to 2008. In addition, the 

report provided preliminary estimates of jobs supported by exports for 2009 and preliminary 

estimates of the value of exports to support one job for 2009 and 2010. Since the report’s 

publication, the value of exports that supports one job has frequently been used in government 

press releases and reports to link jobs to exports in support of the National Export Initiative’s 

goal to double exports by the end of 2014. This brief provides revised estimates of these numbers 

for 2009 and 2010. The estimates use additional details that have become available since the 

report was published and an improved method for predicting the information. 

The method in the Tschetter (2010) report used nominal labor productivity to project 

trend increases in the value of exports that support one job. The new method, the 

price/productivity method, relies on predicting year-to-year changes in the value of exports that 

support one job. It uses variables that are more closely related to the value of exports that support 

one job than nominal labor productivity. In addition, two other methods were considered: 

nominal business productivity and jobs to exports. The nominal business productivity method 

uses nominal business labor productivity. The nominal business productivity and 

price/productivity methods start by estimating the value of exports that support one job and then 

calculate jobs supported by exports. The jobs-to-exports method estimates jobs supported by 

exports and then calculates the value of exports to support one job. It uses disaggregated 

information on exports of services and goods, employment by sector, and labor productivity by 

sector. From that information, it constructs jobs supported by sector by type of export. 

Appendix A discusses why a change in model specification is recommended, why 

improved variable choices will better capture changes in the value of exports that support one 

job, and how the price/productivity and the nominal business productivity methods compare with 

the jobs-to-exports method. 

 

1

 Tschetter, John. 2010. “Exports Support American Jobs.” International Trade Research Report No. 1, U.S. 

Department of Commerce, International Trade Administration, Washington, DC. 
Manufacturing and Services Economics Brief No. 5 

2 Projected Jobs Supported by Exports, 2009 and 2010

Appendix B contains a robustness check of how well the models can replicate historical 

values of exports to support one job. The check is especially important for the jobs-to-exports 

method because it has no underlying statistical measure of its ability to predict jobs supported by 

exports. 

The price/productivity method is the best model for two reasons: (a) it controls for the 

effect of independent time trends in the data, and (b) it separates the value of exports that support 

one job into price and real productivity components. 

To illustrate the improvements, this brief compares the historical values of exports to 

support one job (exports per job) to the price/productivity and nominal business productivity 

methods by drawing a simple trend line through the data (see Figure 1). Both the nominal 

business productivity and the price/productivity methods track historical values better than 

would a trend extrapolation, because they account for changes away from the trend. 

Figure 1. Actual and Projected Values of Exports to Support One Job 

Sources: International Trade Administration calculations and Tschetter (2010). 

80

100

120

140

160

180

200

1994 1996 1998 2000 2002 2004 2006 2008 2010

Original

Nominal Business

Productivity

Price/Productivity

Expon.(Original)

Value of Exports per job ($’000’s)

Projected values 

for all 
International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 3 

However, it is not obvious from Figure 1 whether price/productivity or nominal business 

productivity is the better method. Both are close to actual values. To deduce which method is 

better, one must quantify how well the methods match the values of exports that supported one 

job during 1994–2008. For comparison, the jobs-to-exports method is included. 

Three points of comparison are used: accuracy, precision, and risk. Accuracy is how close 

the estimates are to actual values. Ideally, the average error is zero. The price/productivity 

method has the best accuracy (Table 1). Precision is whether the errors of one method are 

systematically closer than those of the others (that is, not only closer on average but closer every 

time). One measure of precision is the standard deviation. The standard deviation of the errors of 

the price/productivity method is less than that of the other methods. Finally, risk is the largest 

absolute error that is observed regardless of whether it is too high or too low. Even if a method is 

closer on average and is systematically closer than other methods, it should not be wildly wrong 

on some occasions. The price/productivity method is best by this measure as well. Because the 

price/productivity method is better at estimating the value of exports to support one job, it also is 

better at estimating jobs supported by exports. 

Table 1. Errors in Predicting the Observed Value of Exports to Support One Job One Year 

Ahead 

 Price/productivity Nominal business 

productivity 

Jobs to exports 

Average error 

(accuracy) 

$70 $160 $3,070 

Standard deviation of 

error (precision) 

$1,030 $1,510 $2,060 

Maximum absolute 

error (risk) 

$2,000 $3,230 $7,230 

Source: International Trade Administration calculations. 

As Table 1 indicates, the jobs-to-exports method was the worst-performing method. 

There are two reasons for its poor performance. First, the value of exports to support one job was 

calculated indirectly from jobs supported by exports. In contrast, the value of exports to support 

one job was the primary consideration of the other two methods. Second, the growth in the value 

of exports to support one job after adjusting for prices was consistently faster than what the 

available data would estimate. The other two methods could implicitly take this change into 

account by estimating an average rate of faster productivity growth. 
Manufacturing and Services Economics Brief No. 5 

4 Projected Jobs Supported by Exports, 2009 and 2010

Given the price/productivity method’s superior performance, its results provide the 

revised estimates. As Table 2 shows, the revised numbers of jobs supported by exports in 2009 

and 2010 using the price/productivity method are greater than the original estimates by about 

200,000 jobs in both years. The increase in jobs supported by exports from 2009 to 2010 is the 

same, 500,000. In contrast, the values of exports to support one job are lower in 2009 and 2010 

than the original estimates by $10,700 (6.1 percent) and $4,300 (2.3 percent), respectively. 

Table 2. Jobs Supported by Exports and the Value of Exports to Support on Job 

 Jobs supported by exports 

(millions) 

Value of Exports to Support 

on Job 

 2009 2010 2009 2010 

Original 8.5 9.0 $175,000 $185,000 

Revised 8.7 9.2 $164,300 $180,700 

Source: Manufacturing and Services/Office of Industry Analysis (MAS/IAN) calculations and Tschetter (2010). 

 
International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 5 

Appendix A. Description and Evaluation of Estimation Approaches 

Tschetter notes in “Exports Support American Jobs” that there is a strong correlation over 

time between nominal labor productivity and the value of exports to support one job (Table A.1). 

The R2, which is the share of the variation in the value of exports to support one job that is 

related to nominal labor productivity, is high. 

Table A.1. Correlation between Nominal Labor Productivity and the Value of Exports 

to Support One Job (R2 = 0.983) 

 Coefficient Standard error t-statistic P-value 

Intercept −0.468 0.118 −3.977 0.001 

Nominal labor 

productivity 1.062 0.024 44.223 0.000 

Sources: MAS/IAN calculations from Tschetter (2010); Bureau of Economic Analysis (BEA) data from 1993 to 

2008. 

Some caution must be taken, however, in interpreting an R2 relationship. If variables 

follow trends over time, regressions between them can have a high R2

 even when no relationship 

exists. As a preliminary step, one should test for a trend in the value of exports to support one 

job. As Table A.2 shows, this exercise finds a 4.6 percent trend increase per year and an equally 

high R2 explained by the trend (0.984). Therefore, a second test is applied to ensure that the 

relationship is real and not just two variables following their trends. 

Table A.2. Strong Trend Increase of 4.6 Percent a Year in the Value of Exports to Support 

One Job (R2

 = 0.984) 

 Coefficient Standard error t-statistic P-value 

Intercept 4.384 0.014 315.250 0.000 

Time 0.046 0.002 29.389 0.000 

Source: MAS/IAN calculations from Tschetter (2010) for 1993–2008. 

The second test checks whether year-to-year changes in the variables are related. If the 

variables’ relationship is not real—that is, if it just reflects two variables following their trends—

then no significant relationship will be found in their year-to-year changes. In addition, the R2

 of 

the year-to-year regression will tell approximately how much of the total R2 is accounted for in 

year-to-year changes and how much is accounted for by trends. As Table A.3 indicates, the yearto-year relationship accounted for about one-third of the total relationship between the value of 
Manufacturing and Services Economics Brief No. 5 

6 Projected Jobs Supported by Exports, 2009 and 2010

exports that support one job and nominal labor productivity (the R2 of 0.324 is about one-third of 

0.983). The remaining two-thirds of their total R2 is due to the individual variables following 

trends. 

Table A.3. Ability of Year-to-Year Changes in Nominal Labor Productivity to Predict 

Year-to-Year Changes in Values of Exports to Support One Job (R2 = 0.324) 

 Coefficient Standard error t-statistic P-value 

Intercept 0.001 0.018 0.080 0.938 

Year-to-year change in 

nominal labor productivity 1.053 0.422 2.496 0.027 

Sources: MAS/IAN calculations from Tschetter (2010); BEA data for 1993–2008. 

Given that nominal labor productivity accounts for only about one-third of the year-toyear change in the value of exports to support one job, one must wonder whether an alternative 

method would better match the value of exports to support one job. The first candidate tested 

was nominal business labor productivity. 

Any labor productivity measure is an average of the labor productivity measures of its 

component labor groups weighted by the component’s share in total employment. Nominal labor 

productivity gives government labor productivity a large weight because government 

employment’s share of total employment is large. In contrast, relatively few government jobs are 

supported by exports, so government labor productivity’s contribution to the value of exports to 

support one job is small. An alternative nominal productivity measure is nominal business labor 

productivity. The contribution of government labor productivity to nominal business 

productivity, by construction, is zero and closer to government labor productivity’s contribution. 

The year-to-year regressions bear this out (Table A.4). The R2

 is larger (0.469 versus 0.324). But 

an R2

 of 0.469 still leaves most of the relationship to trends in the data. 

Table A.4. Ability of Year-to-Year Changes in Nominal Business Productivity to Predict 

Year-to-Year Changes in Value of Exports to Support One Job (R2 = 0.469) 

 Coefficients Standard error t-statistic P-value 

Intercept −0.002 0.014 −0.172 0.866 

Year-to year-change in 

nominal business productivity 1.212 0.358 3.389 0.005 

Sources: MAS/IAN calculations from Tschetter (2010); Bureau Labor Statistics (BLS) data for 1993–2008. 
International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 7 

The price/productivity method recognizes that the value of exports to support one job is a 

measure of nominal labor productivity. Nominal productivity measures implicitly have two parts: 

price and real productivity. For example, the value of exports to support one job can increase 

because export prices increase, but it could also increase because real labor productivity 

increases (fewer jobs are needed to obtain the same quantity of exports). By using export price 

levels and a proxy for real export labor productivity, one can target each part separately and thus 

improve the estimates. Year-to-year changes in the value of exports to support one job are 

regressed on year-to-year changes in export prices and in real business labor productivity. The 

associated R2, 0.717, is higher than the R2 of the other regressions (Table A.5). Most of the 

changes in the value of exports to support one job can be explained by changes in export prices 

and real business productivity and not just by trends. 

Table A.5. Strong Correlation of Yearly Changes in the Value of Exports to Support One 

Job with Yearly Changes in Export Price and Labor Productivity (R2 = 0.717) 

 Coefficients Standard error t-stat P-value 

Intercept 0.010 0.007 1.453 0.172 

Year-to-year change in export price 0.699 0.140 4.982 0.000 

Year-to-year change in business 

labor productivity 1.217 0.264 4.611 0.001 

Sources: MAS/IAN calculations from Tschetter (2010); BEA and BLS data for 1993–2010. 

The jobs-to-exports method does not directly estimate the value of exports to support one 

job. Rather, it estimates export-supported jobs by type of export and by sector of employment. 

The total number of jobs supported by exports and the total value of exports then implies the 

value of exports that supports one job. This disaggregated approach recognizes that exports can 

be goods or services, changes in export prices and export quantities may differ by type of export, 

goods and services exports use labor in different proportions, and labor productivity will differ 

by sector. 

For example, both prices and quantities of goods exports were hit hard in 2009, but they 

rebounded strongly in 2010 (Table A.6). In contrast, prices and quantities of services exports 

were about one-third less than prices and quantities of goods exports in 2009 and, consequently, 

rebounded by less in 2010. 
Manufacturing and Services Economics Brief No. 5 

8 Projected Jobs Supported by Exports, 2009 and 2010

Table A.6. Changes in Export Price and Quantity from 2008 

 Price change from 2008 (%) Quantity change from 2008 (%) 

2009 2010 2009 2010 

Exports −5.4 −1.4 −9.5 0.3 

Goods −6.8 −2.3 −12.0 1.3 

Services −2.2 0.6 −3.9 −1.8 

Sources: Price change, BEA; quantity change, MAS/IAN calculations based on Census Bureau values net of 

reexports deflated by BEA price changes. 

In addition, as Table A.7 indicates, the types of jobs supported by services exports are 

heavily tilted to jobs in the services sector. In contrast, the types of jobs supported by goods 

exports are tilted toward goods jobs but to a much smaller degree. Finally, labor productivity 

growth was much stronger in the goods sector than in the services sector. The jobs-to-exports 

approach accounts for differences in export prices, export quantities, job composition, and labor 

productivity. 

Table A.7. Composition of Export-Supported Jobs (2008) and Labor Productivity by 

Goods and Services 

 Job share (%) Change in labor productivity from 2008 

(%) 

Sector Goods exports Services exports 2009 2010 

Goods 57.9 42.1 5.0 10.0 

Services 14.3 85.7 1.7 5.0 

Sources: Job share, calculated from Tschetter (2010) using figures 12 and 14; labor productivity, calculated from 

BEA and BLS. 

The number of jobs supported by exports is calculated in four steps. The first step starts 

with the Census Bureau’s reported values of exports of goods and of reexports. Reexports are 

imports of goods that are subsequently exported without being transformed (for example, cars 

off-loaded in the United States and exported to Canada). The value of reexports is subtracted 

from the value of goods exports because reexports likely support few, if any, U.S. jobs. The 

second step takes this adjusted value of goods exports and the Census Bureau’s value of services 

exports and adjusts them by their respective changes in export prices to obtain real exports. For 

example, if the value of goods exports increased 20 percent but the price of such exports 

increased 10 percent, then the increase in real goods exports would be 10 percent. The third step 

applies the changes in real exports to the table of export-supported jobs by sector and by type of 

export to estimate the number of jobs supported by exports if there were no changes in labor 

productivity. To continue with the example, one would find that if there were no changes in labor 
International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 9 

productivity, the 10 percent increase in real goods exports would lead to a 10 percent increase in 

the number of jobs in both sectors supported by goods exports. The fourth step is to apply the 

change in labor productivity by sector to the number of jobs by sector supported by each type of 

export. This step obtains an estimate of the number of jobs by sector supported by type of export. 

So, if labor productivity in the goods sector increases by 5 percent, then the goods sector would 

not need 10 percent more jobs to support a 10 percent increase in real goods exports—it would 

need only 9.5 percent more jobs to produce a 10 percent increase in goods exports. 

The jobs-to-exports method leads to substantially more jobs supported by exports in 2009 

and 2010 than was estimated in Tschetter (2010) (Table A.8). One factor contributing to this 

difference is that export prices were hard hit in 2009, so the nominal decrease in exports 

overestimated the decrease in the actual quantity of exports. 

Table A.8. Jobs Supported by Exports Under the Jobs-to-Exports Method (millions) 

Jobs-to-exports method 

2009 estimate 2010 estimate 

Original 

method

Jobs-to-exports method Original 

method

Jobs-to-exports method

Total Goods Services Total Goods Services

Exports 8.5 8.99 3.64 5.35 9.1a 9.66 3.95 5.71 

Goods 6.0 6.45 3.46 3.00 n.a. 7.08 3.77 3.31 

Services 2.5 2.54 0.18 2.36 n.a. 2.58 0.18 2.40 

Sources: Tschetter (2010), MAS/IAN calculation from Tschetter (2010), BEA data, and BLS data. Numbers may not 

add because of rounding. 

a. Estimated from Census Bureau data for 2010 divided by $185,000, the value of exports to support one job in 

Tschetter (2010).

 The 2009 estimates for jobs supported by exports using the jobs-to-exports method are 

bigger than the original estimate and those obtained by and nominal business productivity and 

price/productivity methods. Therefore, the implied value of exports to support one job is less 

than original estimate, and the estimates of the nominal business productivity method and 

price/productivity method. Tschetter (2010). 

Table A.9. Substantial Reduction of the Value of Exports to Support one job in the Jobs-to 

Exports Method 

 2009 2010 

Original Jobs-to-Exports Tschetter Jobs-to- Exports 

Exports 175,000 161,300 185,000 173,600 

Goods n.a. 146,900 n.a. 160,200 

Services n.a. 197,900 n.a. 210,400 

Source: MAS/IAN calculations from Tschetter (2010), BEA, and BLS data. 
Manufacturing and Services Economics Brief No. 5 

10 Projected Jobs Supported by Exports, 2009 and 2010

Comparing the original estimate of the value of exports to support one job to those from 

the three methods that allow for changes off trend, one finds that the recession took those values 

significantly below the trend estimates in 2009. However, in 2010, the values began returning to 

trend. If one compares the increase in jobs from 2009 to 2010, the three methods and the original 

estimate arrive at similar magnitudes of changes in jobs supported by exports—an increase of 

between 500,000 and 700,000 in jobs supported by exports (Table A.10). 

 

Table A.10. Value of Exports to Support One Job and Jobs-Supported by Exports 

Method Value of Exports to Support One Job Jobs supported by exports 

2009 2010 Change 

(%) 

2009 

(millions) 

2010 

(millions) 

Change 

(%) 

Original $175,000 $185,000 5.7 8.5 9.0 0.6 

Nominal business 

productivity 

$169,600 $181,000 6.7 8.6 9.3 0.7 

Price/productivity $164,300 $180,700 10.0 8.8 9.3 0.5 

Jobs-to-exports $161,300 $173,600 7.6 9.0 9.7 0.7 

Source: MAS/IAN calculations and Tschetter (2010). 

Although the revised methods provide similar results, the jobs-to-exports method 

approach has two potential advantages over the nominal business productivity and 

price/productivity methods. First, it provides disaggregated estimates of jobs supported by 

exports and values of exports to support one job by separating (a) goods and services exports and 

(b) goods and services sectors. Second, similar to the historical estimates from 1993 to 2008, it 

explicitly accounts for changes in the composition of exports and differences in export sectors 

that the other three, as models of total exports, cannot. 

There are weaknesses in the jobs-to-export method, however. It uses more detail and, 

therefore, has more opportunities for errors. In addition, the jobs-to-export method is not 

statistically tested. Appendix B tests those weaknesses by checking how well the three methods 

can “project” the values of exports to support one job observed from 1993 to 2008 in the same 

way that they would project future values of exports to support one job. 
International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 11 

Appendix B. Robustness Tests of Projected Value 

The robustness tests discussed in this appendix aim to measure how well the three 

methods “predict,” one and two years out, the historical values of exports to support one job 

given the information that would have been available in each year. These tests are necessary 

because there is a two-year delay in the release of BLS’ input-output databases from which a 

historical calculation can be made and because there is a desire for more timely information on 

jobs supported by exports and the value of exports to support one job to measure the progress of 

the National Export Initiative. 

For the price/productivity and nominal business productivity models, predicting historical 

values proceeds as follows. Observed values of nominal and real productivity and export prices 

are known in the year for which a prediction is made. Using those values in the regression 

equations, one can predict the percentage change in the value of exports to support one job. In 

the one-year-ahead projection, the predicted percentage change in the value of exports to support 

one job is applied to the previous year’s observed value to project the current year’s value. In the 

two-years-ahead projection, observed values of nominal and real productivity and export prices 

are known to obtain a predicted change in the value of exports to support one job. The predicted 

change is applied to the one-year-ahead projected value to estimate a two-years-ahead value. 

Given that the price/productivity method is better than the nominal business productivity 

model in predicting the yearly change in the value of exports to support one job, one would 

expect that the one-year-ahead and two-years-ahead projected values would also be better. For 

example, the average errors for one and two years out are less. Also, with respect to precision, 

standard deviation is less (Table B.1). None of the statistical differences are significant, which is 

not surprising given the few observations, but the results reinforce the presumption that 

price/productivity is a better method. 
Manufacturing and Services Economics Brief No. 5 

12 Projected Jobs Supported by Exports, 2009 and 2010

Table B.1. Estimation of Historical Value of Exports to Support One Job Using the 

Nominal Business Productivity and Price/Productivity Methods 

Nominal business productivity Price/productivity 

1 year ahead 2 years ahead 1 year ahead 2 years ahead 

Average error $160 $210 $70 $160 

Standard 

deviation of error 

$1,510 $2,350 $1,030 $1,580 

Maximum 

absolute value of 

error 

$3,230 $4,050 $2,000 $3,010 

Source: International Trade Administration calculations. 

The jobs-to-exports method relies on the value of exports net of reexports, price changes 

in exports to estimate real exports, and productivity changes to adjust the quantities of labor 

supported by exports. The robustness test for the jobs-to-exports method begins by checking 

whether, given Tschetter’s (2010) export values for the year, an adjustment of export values for 

price and labor productivity changes, as discussed in Appendix A, would lead to projections that 

were better than either statistical method (that is, the nominal business productivity method and 

the price/productivity method). If the projections are worse, then adding another source of error 

from using the Census Bureau’s export values would not improve the projections. Applying the 

robustness test, one sees that the jobs-to-exports method overestimates the number of jobs 

supported by exports in every year (Figure B.1). 

The systematic errors undermine the robustness of the jobs-to-export method. In addition, 

it is unlikely that errors can be improved upon. Export price indexes (the first step) are not likely 

to be significantly biased by whether prices of reexports are included in the export price index. 

Consequently, the estimated change in real exports is not a likely source for the observed error. 

Observed productivity changes are available only at the higher levels of aggregations. 

Because the jobs-to-exports consistently overestimates the number of jobs supported by 

exports, it consistently underestimates the value of exports to support one job. The resulting 

errors are quite large even at just one year ahead (Table B.2). Because the errors at one year 

ahead are so large, no attempt is made to calculate estimates for two years ahead. The 

price/productivity method, by implication, clearly outperforms the original method and the two 

alternative methods. 
International Trade Administration 

Projected Jobs Supported by Exports, 2009 and 2010 13 

Figure B.1. The Jobs-to-Exports Method overestimates the Number of Jobs Supported by 

Exports (millions) 

Source: IAN Estimates and Tschetter (2010). 

Table B.2. Errors under the Jobs-to-Exports Method 

 Jobs-to-Export Method 

Average error $3,070 

Standard deviation of error $2,060 

Maximum absolute error $7,230 

Source: International Trade Administration calculations. 

 

0

2

4

6

8

10

12

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Actual

Jobs to Exports Method
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