Background

Ex-Im operates under the authority of the Export-Import Bank Act of 1945,  as amended. It is an independent agency of the U.S. government. Ex- Im’s mission is to support jobs in the United States by facilitating the  export of U.S. goods and services. In fiscal year 2012, Ex-Im authorized  about $35.8 billion, for 3,796 transactions, to support U.S. exports. Ex-Im  is part of the U.S. Trade Promotion Coordinating Committee, an  interagency committee chaired by Commerce and tasked with  coordinating the export promotion and financing activities of federal  agencies. Ex-Im is also a key participant in the National Export Initiative,  a strategy announced in 2010 to double U.S. exports by 2015 to support  U.S. employment.
Ex-Im provides four types of financing: direct loans, loan guarantees,  working capital guarantees, and export credit insurance.
Direct loans: Medium- and long-term fixed-rate loans Ex-Im provides  directly to foreign buyers of U.S. goods and services.
Loan guarantees: Medium- and long-term loan guarantees to lenders  that Ex-Im will pay the lender if the foreign buyer of U.S. goods and  services, who received the loan, defaults.
Working capital guarantees: Guarantees to lenders for U.S.-based  companies to obtain short-term loans that facilitate the export of  goods and services. Working capital guarantee loans may be  approved for a revolving line of credit that supports multiple export  sales or a single loan that supports a specific export contract.  Insurance: Short- and medium-term insurance Ex-Im provides to U.S.  exporters to protect them against the risk of nonpayment by foreign  buyers for commercial or political reasons.
To balance the interests of multiple stakeholders and Ex-Im’s mission to  support U.S. jobs through export financing, Ex-Im has a domestic content  policy regarding the amount of U.S. content directly associated with the  goods and services exported from the United States. Ex-Im’s short-term  transaction content policy requires at least 50 percent U.S. content. For  medium- and long-term transactions, there is no minimum U.S. content  requirement to receive a portion of financing, but Ex-Im’s support is  limited to the lesser of (1) 85 percent of the total value of all eligible goods  and services in the U.S. export transaction, or (2) 100 percent of the  value of the domestic content in all eligible goods and services in the U.S.  export transaction. To be eligible for support, goods must be shipped  from the United States.
Other industrial countries have their own export credit agencies. For  example, the other Group of Seven (G-7) countries all have at least one  export credit agency. G-7 agencies differ in the magnitude and types of  their activities. All offer medium- and long-term officially supported export  credits. Export credit agencies also can provide other products and  services that can complicate comparisons among institutions. Ex-Im’s  mission emphasizing supporting domestic jobs through exports is unique  among the G-7 agencies. Ex-Im’s charter states that the bank’s objectives  are to contribute to maintaining or increasing the employment of U.S.  workers by financing and facilitating exports through loans, guarantees,  insurance, and credits. This mission underlies certain Ex-Im policies, such  as its economic impact analysis requirement and its domestic content  policy. Other export credit agencies’ missions range from promoting and  supporting domestic exports to securing natural resources.

	Ex-Im Methodology to Estimate the Number of Jobs It Supports Is Based on Export Values and Labor Statistics

To estimate the number of U.S. jobs associated with the exports it helps  finance, Ex-Im uses a methodology based on the input-output approach.  To apply this methodology, Ex-Im uses a BLS data product, known as  employment requirements tables (ERT) which are based on the input- output methodology. It is important to understand the ERT because these  tables play an essential role in Ex-Im’s jobs calculation process. The ERT  provide the total number of jobs (on average) supported by production in  each industry. These BLS data allow Ex-Im to produce a measure that  translates the value of the exports it supports in each industry into an  employment estimate for that industry. In order to use the ERT, Ex-Im  must rely on data from its own system. Ex-Im’s four-step process  estimates the value of all the exports it supports by the industries  associated with those exports. By combining data from the ERT and its  own system and aggregating across industries, Ex-Im produces an  estimate of the total jobs its financing supported.

		Ex-Im Uses BLS Tables to Obtain Jobs Ratios—The Numbers of Jobs Supported by Exports in Particular Industries

The methodology Ex-Im uses relies on a basic input-output approach.  According to Ex-Im and Commerce officials, the basic input-output  approach was designated as the standard for U.S. government agencies  by the Trade Promotion Coordinating Committee and has the advantage  of generating a uniform jobs calculation methodology across the federal  government. The logic underlying the input-output modeling approach  assumes that the production of goods and services in an economy uses  inputs (such as labor) in fixed proportions. Consequently, it is possible to  determine the quantity of labor required for a given level of production. To  apply this methodology, Ex-Im uses the ERT, data tables created by BLS,  to estimate the number of jobs associated with the specific value of  exports Ex-Im supports, rather than the value of total U.S. exports. The  ERT are derived from a set of data showing the relationship between  industries, known as input-output tables. For researchers using an input- output approach, the ERT can be used for analyses that attempt to  estimate the employment effects of exports.
BLS develops the ERT so that users can analyze the job impact of  various types of expenditures, such as exports. The ERT contain, for 195  industries, the number of jobs required to produce one million dollars of  value in each industry (this report refers to this factor as the “jobs ratio”).  Because industries may vary widely in how many jobs they support per  million dollars of expenditure, it is important for Ex-Im to correctly identify  the industry associated with each export transaction it finances. BLS  produces two types of ERT, one that includes the employment effects of  both domestic and imported production and another that removes the  employment effects of imports so that only domestic production is  captured. Ex-Im uses the domestic ERT to estimate the number of U.S.  jobs associated with its exports. While annual versions of the ERT are  produced, the most current year available as of May 2013 is 2010.
Using the ERT, it is possible to obtain either the jobs supported directly in  a particular industry, or in a particular industry plus the industries that  support its production. For example, construction directly supports jobs in  the construction industry but also indirectly supports jobs in industries that  supply the material necessary for construction, such as the steel industry.  Ex-Im uses the value that also includes employment in supporting  industries, which produces a larger jobs ratio. Sometimes this larger  estimate is called the “direct plus indirect effect” or “supply chain.”

		Ex-Im Follows a Four-Step Process to Calculate the Number of Jobs Associated with Its Support

Ex-Im’s process for using the ERT has four steps. First, it determines the  industry associated with each transaction. In some cases, there could be  multiple industries associated with a transaction, if Ex-Im financed  multiple products in the transaction. Second, it determines the total value  of exports Ex-Im supports for each industry. Third, it multiplies these  export values by BLS’s jobs ratio for each industry to obtain the jobs for  that industry. Finally, it aggregates across all industries to produce an  overall estimate. Figure 1 depicts each step of the process.
In step 1, Ex-Im either uses the industry code provided by the applicant  (the exporter or the lender) or relies on its engineers (whom Ex-Im  considers its in-house industry experts) to identify the appropriate North  American Industry Classification System (NAICS) code for the contracts  associated with each transaction Ex-Im finances or supports. Ex-Im  translates its data on transactions into the same industry groups (i.e.,  NAICS-based codes) used by BLS. The method by which Ex-Im obtains  the NAICS code varies by length of repayment term. For short- and  medium-term financing and working capital credit, the applicant (either  the exporter or the lender) provides the NAICS code. For long-term  financing, Ex-Im engineers work with the exporters and project sponsor to  determine the NAICS code. According to Ex-Im officials, to verify and  assign NAICS codes in long-term financing, Ex-Im uses both the  guidance provided by the codebook for assigning NAICS codes and the  experience of the engineer.
In step 2, Ex-Im estimates a dollar value of exports it supports, referred to  as the export value. It does this for each transaction it finances. However,  according to Ex-Im officials, because Ex-Im provides different types of  financial products, it uses two different methods to determine the export  values.  1.  For some financial products, such as direct loans and loan  guarantees, Ex-Im determines the export value after authorization— but before disbursement—by using information provided on the  exporter’s certificate. Specifically, Ex-Im determines the export value  by using the net contract price—the aggregate price of all goods and  services to be exported (i.e., U.S. content plus eligible foreign content  that does not include local costs). Ex-Im includes the value of the  purchase of goods and services that were financed by entities other  than Ex-Im. In other words, the export value is the value of exports in  purchase orders that were at least partially financed by Ex-Im.  According to Ex-Im officials, they generally provided approximately 83  percent of the financing for medium and long-term transactions for  fiscal year 2010 through fiscal year 2012.  2.  For other financial products, such as short-term insurance or working  capital, Ex-Im uses the entire value of the credit or the insurance  policy as the proxy for the export value. Because the export value is  not known at the time of authorization, Ex-Im cannot use the net  contract price to determine the export value. These products include  revolving lines of credit that may be drawn down multiple times during  the available period. Under this type of support, a domestic exporter  can access the credit to make purchases and later repay the debt,  thereby making additional credit available. According to Ex-Im, this  approach may result in an understatement of the total value of the  exports, as multiple purchases can occur without ever reaching the  limit. However, Ex-Im also confirmed that using the entire value of the  credit or insurance policy could result in an overstatement, if all the  credit is not used.
At the end of step 2, Ex-Im creates a summary table, where each row  contains the sum of export value in an industry. In step 3, Ex-Im multiplies  the export values for each industry by the appropriate jobs ratio from the  ERT. Finally, in step 4 it sums across all of the industries to obtain a  single estimate for the number of jobs it supports.
Using this process, Ex-Im estimated 255,000 jobs supported in 2012. To  illustrate, on average, Ex-Im used the following steps:
Ex-Im determined that it supported approximately $40 billion of  exports.
On average, in fiscal year 2012, every million dollars of exports  supported by Ex-Im was associated with 6.5 jobs (based on the  industries that used Ex-Im financing, and the ERT).
Finally, multiplying approximately 40 billion dollars of exports by 6.5  jobs per million results in approximately 255,000 jobs.
In order to verify our understanding of Ex-Im’s jobs calculation process,  we obtained the individual transaction level data from Ex-Im, including the  export values and industry codes for each transaction. We then merged  that data with the most recent ERT from the BLS and summed across all  transactions. Using this data, we were able to obtain close to Ex-Im’s  exact value for the total number of jobs supported, thus confirming the  process that Ex-Im described to us. For more detail about our analysis,  see appendix I.

	Ex-Im Does Not Report Important Details about Its Approach, Including Limitations

The basic methodology used by Ex-Im has recognized limitations, and  Ex-Im also makes certain assumptions about its data. However, in its  reports, Ex-Im does not describe limitations or fully detail assumptions  that are inherent to the methodology. As a result, stakeholders may not  fully understand what the job number represents or how to interpret it in  the proper context.

		Ex-Im Employs a Commonly Used Methodology; However, This Approach Has Limitations

Although the input-output approach on which the ERT are based is a  commonly used methodology, this approach has several limitations.  Some of these limitations are inherent to the ERT. Additional limitations  result from assumptions Ex-Im makes about its data on the industry  codes and export values for the export transactions it finances.
The limitations specific to the ERT are outside of Ex-Im’s direct control.  For example, officials from Commerce and Ex-Im said that the data in the  ERT cannot be used to distinguish between jobs that were newly created  and those that were maintained. The ERT simply show the direct and  indirect (also known as supply chain) employment per $1 million of sales  of goods to final users for each commodity, not whether these are “jobs  created” (employing previously unemployed people or people out of the  labor force, such as students), or “jobs maintained” (continuing pre- existing employment). According to BLS officials, it would be challenging  to find data that can distinguish between newly created and maintained  jobs. Obtaining data detailed enough to allow a researcher to make that  distinction would require many more resources than are currently  available to BLS, according to these officials. They added that this is a  general limitation of the input-output methodology, upon which the ERT  are based, and which is a standard methodology used to calculate  average employment and other inputs needed for a certain level of  production. Because of the lack of specificity and limitations, Ex-Im  officials report that the jobs are “associated with” or “supported by” Ex-Im  financing.
Moreover, the documentation accompanying the ERT also describes  several limitations and assumptions to those data, including the  following:
The employment data are a count of jobs, not of persons employed,  and treat full-time, part-time, and seasonal jobs equally. Persons  who hold multiple jobs show up multiple times in the employment  data.
The age of the data underlying the ERT is a general limitation of  BLS’s employment requirements tables. The ERT incorporate a large  amount of data, which takes time to collect and put in the ERT  framework, according to BLS officials. Ex-Im is using the latest  available ERT, the 2010 ERT; however the industry relationships that  the ERT are based on come from 2002 data from BEA. BLS officials  stated that the current economy may be very different from the  economy in 2002, and the relationships reflected in the latest  available ERT are a decade old. BLS officials acknowledged,  however, these data are the best currently available for Ex-Im to  use.
Furthermore, the ERT data assume average industry relationships;  however Ex-Im’s clients could be different than the typical firm in the  same industry. For example:
The ERT that are adjusted to reflect only domestic employment  assume that each industry’s share of domestic versus international  use of a particular input is constant across industries. For example,  these ERT assume that the automobile industry uses the same  proportion of imported steel as the construction industry. Because of  Ex-Im’s domestic content policy, agency officials said that Ex-Im does  not consider the exports supported by its financing to contain the  same level of imports as the industry averages. Ex-Im officials agreed  that this is a limitation but said that using BLS’s adjusted ERT helps  ensure that imported content is accounted for to some extent. Ex-Im  officials told us they had not assessed the extent to which this  limitation affects the overall jobs estimate.  In addition, officials from Export Development Canada and Ex-Im  and a trade policy researcher said that using input-output  methodology to calculate employment estimates for specific  transactions is also a limitation, since a particular export may be  different than the average for that industry.
The ERT also exclude the impact of spending that results from income  generated by Ex-Im supported jobs, sometimes called the multiplier  effect. For example, an increase in employment in a factory may result in  employment at a nearby restaurant. According to BLS, including these  additional consumer expenditures would result in a larger employment  impact.
Some limitations stem from Ex-Im’s process for determining the industry  and export value. As discussed previously, during step 1 (as shown in fig.  1), Ex-Im determines the industry associated with each transaction.  However, in some cases, Ex-Im has been unable to determine the  industry code. In cases where the NAICS code is missing for  transactions, Ex-Im has used the average across all of its other industries  as the jobs ratio. In almost all of those cases we identified with missing  NAICS codes (that had positive export values), the type of support was  short-term insurance. According to Ex-Im, in short-term insurance, the  lender may not know at the time of authorization which exporter will  benefit from the insurance coverage, and this may explain why the NAICS  code is not identified.
Ex-Im’s jobs calculation methodology is also sensitive to certain  assumptions about how it determines the export value based on its  financing. For example, as discussed previously in step 2, using the  authorized amount as the export value for short-term insurance  transactions could overstate or understate the actual export value. In  addition, according to Ex-Im officials, the export value includes the value  of the purchase of goods and services that were financed by entities other  than Ex-Im.
Finally, according to government officials and trade policy researchers,  the methodology that Ex-Im uses does not answer the question of what  would have happened without Ex-Im financing. A Commerce report and  trade policy researchers we consulted noted that in a high unemployment  economy, additional exports may result in additional jobs. However, in a  low unemployment economy, additional exports may result in jobs shifting  from one firm to another, without an increase in total employment.

		Ex-Im Does Not Describe Limitations or Fully Detail Assumptions in Its Reporting on Employment Effects

Ex-Im reports the number of jobs its financing supports and the  methodology it uses but does not describe the limitations or fully detail the  assumptions related to its data or methodology. Ex-Im first reported the  total number of jobs it supports in its 2010 annual report and started  providing an overview of its methodology in its 2011 report. The 2012  report states that the Trade Promotion Coordinating Committee identified  this basic methodology as the official U.S. government calculation of jobs  supported through exports. The report further states that Ex-Im uses the  latest available domestic ERT from BLS (which is based on input-output  tables from BEA), National Income and Product Accounts data (also from  BEA), and BLS industry employment data to calculate the number of jobs  associated with Ex-Im supported exports of goods and services.
Ex-Im has also reported the number of jobs it supports in various other  documents, including reporting to comply with the Government  Performance and Results Act, the Chairman’s statements to Congress, its  website, and press releases. Some press releases that announce new  transactions also state the number of jobs associated with a specific  transaction. Most of the press releases we reviewed provide only a brief  statement about how Ex-Im calculates its job estimate. For example, an  October 2, 2012, press release announcing $105 million in financing for  an aquarium in Brazil states: “The transaction will support approximately  700 American jobs, according to bank estimates derived from  Departments of Commerce and Labor data and methodology.”
Ex-Im officials told us they use the results of its jobs calculations for  reporting purposes only. According to Ex-Im officials, Ex-Im calculates the  number of jobs supported for the transactions reviewed by Ex-Im’s Board  of Directors, at the request of one of its board members. Ex-Im board  members stated that the purpose of reporting these numbers is to give  Congress a sense of the employment effects of Ex-Im activities; they do  not use them for decision making. Board members also told us that the  chief consideration when making a financing decision is the credit  worthiness of the firm. Officials stated that they do not make decisions  based on how many jobs would be supported by a particular transaction.
However, none of Ex-Im’s reporting discusses limitations or fully details  the assumptions in its data or in the methodology it uses. Most of the  limitations and assumptions are not specific to Ex-Im, but are common to  the methodology. For example, Ex-Im’s brief discussion of the  methodology in its 2012 annual report does not explain that the  methodology does not allow it to differentiate between the number of new  jobs that were created and the number of jobs maintained as a result of  its financing. In addition, Ex-Im does not specify that jobs associated with  the multiplier effect are not captured in its jobs estimates. Further, the  report does not state that the employment estimate is an overall count of  jobs, not full-time equivalents. Thus, the number of jobs that Ex-Im says it  supports can include part-time and seasonal jobs. Similarly, its press  releases that include the number of jobs associated with a specific  transaction also do not state the limitations and assumptions associated  with the methodology. Officials said that, in reporting the number of jobs  associated with Ex-Im financing, they clearly state that it is an estimate.
Because it is a nonfinancial and unaudited number, the caveat of  “estimate” seemed sufficient, according to Ex-Im officials. According to  GAO’s Standards for Internal Control in the Federal Government,  effective communications should occur in a broad sense with information  flowing down, across, and up the organization. Management should  ensure there are adequate means of communicating with, and obtaining  information from, external stakeholders that may have a significant impact  on the agency achieving its goals. By not including more information in its  report, Ex-Im does not allow readers, including Congressional and public  stakeholders, to fully understand what the jobs number represents or how  to interpret it in the proper context.

	Alternative Methodologies Address Some Limitations but Have Other Drawbacks

Although alternative methodologies may address some of the limitations  in Ex-Im’s jobs calculation methodology, these alternatives have their own  limitations. Trade policy researchers we spoke to suggested alternative  methodologies that Ex-Im could potentially use to calculate the effects of  its financing on employment. However, these methodologies have their  own limitations, such as not including the effects of Ex-Im financing on  indirect jobs (the supply chain) and would require a significant amount of  data collection by Ex-Im that would be time consuming, require more  technical expertise, and cost more.
One trade policy researcher we spoke to suggested that Ex-Im could  conduct an assessment of firms that received Ex-Im financing in  comparison to firms that did not receive Ex-Im financing. This approach,  using firm-specific data, could potentially estimate whether the jobs would  have existed without Ex-Im financing. For example, the German Ministry  of Economics and Technology commissioned a study by the University of  Munich on the employment effects of the export credit guarantees  provided by the German export credit agency. This 6-month study used  econometric analysis to examine firm-level data while taking into account  other potential causes of export success and found that the German  export credit agency’s guarantees had increased exports and created  jobs. According to their report, their estimate of jobs created using this  approach was comparable to estimates derived from an input-output  approach. However, Ex-Im officials noted that the type of data used in the  German study may not be readily available in the United States to Ex-Im.
Another trade policy researcher suggested a different approach using  firm-level data from Census or BLS to examine job creation and  destruction over time. This approach could be potentially informative of  changes in the labor market not captured by a total jobs number, such as  whether these are new jobs, or whether firms supported by Ex-Im are less  likely to reduce employment. In contrast, the current input-output method  used by Ex-Im provides a static look at the number of jobs supported by  Ex-Im financing and does not show how the economy has gained or lost  jobs over time. While the approach of using firm-level data may yield  information about the creation and destruction of jobs, it may not yield a  static estimate of the number of jobs supported. In addition, BLS officials  stated that such an analysis would only identify whether a firm’s total  employment increased or decreased over time, but would not identify a  new set of jobs in the firm and would not control for factors other than Ex- Im financing that could cause a change in employment. An Export  Development Canada official also stated that such a methodology  introduces the potential for selection bias. Furthermore, Commerce  officials stated that such an analysis would be too time consuming to  conduct every year.
Two trade policy researchers and Ex-Im and Export Development  Canada officials we spoke with said that these alternative approaches  that rely on firm-level data would require more resources for data  collection and analysis than does Ex-Im’s current input-output based  methodology. In particular, a methodology using firm-level data would  require a significant amount of data collection by Ex-Im that would be time  consuming, require more technical expertise, and have a monetary cost.  Moreover, these alternatives may not capture the indirect (the supply  chain) effect of Ex-Im financing. These trade policy researchers said that  the input-output approach is appropriate given Ex-Im’s limited resources  and how the agency uses the number of jobs supported.
Export Development Canada officials said they use an input-output based  approach, which also captures the indirect (the supply chain) effect,  similar to the methodology used by Ex-Im to calculate the number of jobs  supported by its financing. However, for insurance products, Export  Development Canada uses the contracts for the exports it is supporting to  calculate the export value. This approach allows this agency to capture  export values that differ from authorized amounts since the authorized  amount could overstate or understate the actual export value. Ex-Im  officials said they lack the staff and resources to adopt Export  Development Canada’s method and that Ex-Im faced some limitations  with its data systems. Additionally, using the authorized value for the  short-term insurance products, Ex-Im officials said, ensures that the value  is only counted once in the fiscal year it was authorized and is not  counted again in subsequent fiscal years.
Prior to the use of the input-output based approach, Ex-Im, as well as  Export Development Canada, tried to collect information on the number of  jobs associated with their financing directly from the companies that  received the financing. Officials from both agencies said that they had  problems with the data they received from the companies. An official from  Export Development Canada also said that smaller companies found this  process burdensome. According to Ex-Im, surveyed firms responded in  inconsistent ways, such as claiming all employed workers at a firm were  supported by the exports. They also reported that since financial  intermediaries or foreign buyers often submit the applications for Ex-Im  financing, they do not know the jobs impact for the U.S. exporter or  service provider. Moreover, any jobs-impact information from applicants  does not account for indirect jobs created in the supply chain, which the  input-output approach does include.

	Conclusions

Ex-Im’s primary mission is to support U.S. jobs through the exports that it  finances, and it estimates the number of jobs supported by its financing in  order to provide Congress and the public with a broad sense of its impact  on U.S. employment. The jobs number reported by Ex-Im is an estimate,  used by Ex-Im as an indicator of how the agency is fulfilling its mission to  support U.S. employment. Although the methodology Ex-Im uses does  not distinguish between jobs that were newly created or jobs that were  maintained, its current methodology has certain advantages. For  example, it is based on the input-output approach commonly used in  economic analysis; it includes indirect jobs in the supply chain; and it can  be performed using limited resources. Providing a precise accounting of  the jobs supported by Ex-Im’s financing may not be feasible because of  the complexity and cost of doing so. While trade policy researchers we  consulted identified other methodologies, they also identified limitations of  those methodologies. For example, these methodologies would require  more resources to conduct, would be difficult to perform on a regular  basis, and would not include indirect jobs in the supply chain.  Nonetheless there are important limitations and assumptions that affect  Ex-Im’s estimate of the number of jobs supported by its financing. While  Ex-Im’s reporting includes a brief overview of its methodology, it has not  included a discussion of the limitations or fully detailed the assumptions of  the methodology and data. The lack of detailed reporting reduces the  ability of congressional and public stakeholders to fully understand what  the jobs number represents and the extent to which Ex-Im’s financing  may have affected U.S. employment.

	Recommendation for Executive Action

To ensure better understanding of its jobs calculation methodology, the  Chairman of Ex-Im Bank should increase transparency by improving  reporting on the assumptions and limitations in the methodology and data  used to calculate the number of jobs Ex-Im supports through its financing.

	Agency Comments and Our Evaluation

We provided a draft of this report to Ex-Im, Commerce, and Labor for  comment. We also provided relevant sections to Export Development  Canada for technical comment.
In its written comments, which are reproduced in appendix II, Ex-Im  stated that it agrees with GAO’s recommendation and will provide greater  detail on the assumptions and limitations associated with its jobs  calculation methodology. Ex-Im further stated that it will begin  implementation of the recommendation this fiscal year with its 2013  annual report, which will include greater information on the assumptions  and limitations of its methodology. Ex-Im will provide this information in  annual reports and on its website.
Commerce stated that it agrees with GAO’s recommendation for  improved reporting on how Ex-Im calculates the number of jobs that are  supported by exports for which it provides financing. Commerce also  recommended that Ex-Im make it clear that its jobs estimate is indicative  of jobs supported by Ex-Im financing and is different than the estimate of  jobs supported by total U.S. exports that Commerce publishes as the  official estimate of the U.S. government. Commerce’s comments are  reproduced in appendix III.
Export Development Canada stated that it recognizes the deficiencies in  the input-output approach, but that it believes that compared with other  potential methodologies, this approach provides the best solution.  According to Export Development Canada, the input-output approach  uses a simple method to capture the indirect impact of the supply chain  on domestic employment. In addition, Export Development Canada said  that while using firm-level data to estimate the effect of financing might  offer other insights, it would also be complex to analyze, and could  introduce another bias. Further, Export Development Canada said that in  its experience, surveying firms directly may not lead to reliable  information, and also could be burdensome to smaller firms.
Ex-Im, Commerce, and Export Development Canada also provided  technical comments that were incorporated, as appropriate. We received  no comments from Labor.
We are sending copies of this report to interested congressional  committees, the Chairman of the Export-Import Bank of the United States,  and the Secretaries of Commerce and Labor. In addition, the report is  available at no charge on the GAO website at http://www.gao.gov.

Appendix I: Objectives, Scope, and Methodology

The objectives of this report were to (1) describe the methodology and  processes the Export-Import Bank of the United States (Ex-Im) uses to  calculate the effects of its financing on employment in the United States,  (2) examine the limitations of Ex-Im’s approach and how Ex-Im reports on  its methodology, and (3) describe alternative methodologies and their  limitations.
To describe the methodology and processes Ex-Im uses to calculate the  effects of its financing on employment in the United States, we  interviewed Ex-Im staff involved with producing the estimate and  reviewed descriptions of the estimate in the most recent annual reports  and other documentation provided by Ex-Im. Because Ex-Im’s method  uses the Bureau of Labor Statistics’ (BLS) employment requirements  tables (ERT), we interviewed BLS staff and reviewed technical  documentation on the ERT. In addition, we reviewed the Microsoft Excel  spreadsheet Ex-Im uses to perform the estimate, by examining formulas  in the sheet used to produce the estimate. Because Ex-Im provided the  underlying raw data used by the spreadsheet, we were able to combine  its data with the ERT data and replicate Ex-Im’s jobs estimate by the  following steps. First, we downloaded the ERT directly from the BLS  website. Then, we merged the ERT with the raw data provided by Ex-Im,  by industry. Finally, we multiplied the jobs ratio by Ex-Im data’s export  value (for the appropriate industry), and aggregated across transactions.  Following this procedure, we obtained a value close to Ex-Im’s exact  value for a jobs estimate. Replicating Ex-Im’s estimate helped to verify  that Ex-Im followed the process and used the specific ERT that it stated it  did, and that all of the raw data were reflected in its jobs estimate. We  performed our replication using SAS, a computer program distinct from  Excel. Based on our interviews with knowledgeable agency officials,  review of relevant documentation, and replication of Ex-Im’s calculation,  we determined the data were sufficiently reliable for the purposes of our  report.
To examine the limitations of Ex-Im’s approach, how Ex-Im reports on its  methodology, and alternative methodologies, we reviewed relevant  documentation related to Ex-Im, including recent annual reports,  descriptions of Ex-Im’s jobs calculation methodology, and press releases  that included information on jobs supported by Ex-Im financing. We also  reviewed recent GAO reports on Ex-Im and export credit agencies, and  literature related to input-output methodology. In addition, we interviewed  Ex-Im officials from various divisions of the organization about how they  calculate the number of jobs supported by Ex-Im’s financing, how they  obtain data about Ex-Im’s transactions, and how the jobs number is used.  We also interviewed officials from the BLS at the Department of Labor to  discuss the employment requirements tables (ERT). In addition, we  interviewed officials from the Department of Commerce, specifically from  the Bureau of Economic Analysis—which develops the data in the input- output tables that BLS uses in its ERT—and from the International Trade  Administration—which also calculates the number of jobs supported by  U.S. exports overall. We reviewed relevant documentation from these  agencies such as technical documentation on the ERT. We also spoke  with officials from four other countries’ export credit agencies to obtain  information on their efforts to determine the number of jobs associated  with their financing, including the export credit agencies of Canada,  Japan, France, and the United Kingdom. We selected these countries’  export credit agencies because GAO had consulted with them on prior  engagements based on their similarities to Ex-Im. We obtained  information on a study that analyzed the employment effects of  Germany’s export credit agency as an example of an alternative  methodology. We met with three selected trade policy researchers to  obtain their perspectives on Ex-Im’s methodology and discuss potential  alternative methodologies to calculate the effect of Ex-Im’s financing on  employment. We selected these researchers because GAO had  consulted with them on prior engagements related to export credit  agencies based on their knowledge of the issues, or they had been  recommended to us through interviews with knowledgeable government  officials due to their expertise in the area. In addition, we reviewed GAO’s  Standards for Internal Control in the Federal Government to assess Ex- Im’s communication regarding its jobs calculation methodology.
We conducted this performance audit from August 2012 to May 2013 in  accordance with generally accepted government auditing standards.  Those standards require that we plan and perform the audit to obtain  sufficient, appropriate evidence to provide a reasonable basis for our  findings and conclusions based on our audit objectives. We believe that  the evidence obtained provides a reasonable basis for our findings and  conclusions based on our audit objectives.

Appendix II: Comments from the Export- Import Bank of the United States

Appendix III: Comments from the Department of Commerce

Appendix IV: GAO Contact and Staff Acknowledgements

	Contact

	Staff Acknowledgments

In addition to the person named above, Jose Alfredo Gomez (Director),  Juan Gobel (Assistant Director), Christina Werth, Rachel Girshick, and  Benjamin Bolitzer made key contributions to this report. Also contributing  to this report were Karen Deans, Susan Offutt, Martin de Alteriis, Etana  Finkler, Robert Alarapon, and Ernie Jackson.

Summary:
Why GAO Did This Study

Ex-Im provides loans, guarantees, and insurance to U.S. exporters. One of Ex-Im's primary missions is to support U.S. jobs through exports. In its 2012 annual report, Ex-Im stated that its financing helped support an estimated 255,000 export-related U.S. jobs.
In 2012, Congress passed the Export-Import Bank Reauthorization Act of 2012. The act required GAO to report on the process and methodology used by Ex-Im to calculate the effects of export financing on U.S. employment. This report (1) describes the methodology and processes Ex-Im uses to calculate the effects of its financing on U.S. employment and (2) examines the limitations of Ex-Im's approach and how Ex-Im reports on its methodology, and provides additional related information.
To address these objectives, GAO reviewed relevant Ex-Im documents, obtained and reviewed the data Ex-Im uses for its calculations, and interviewed agency officials and trade policy researchers.

What GAO Found

The U.S. Export-Import Bank's (Ex-Im) methodology to calculate the number of U.S. jobs associated with the exports it helps finance has four key steps. First, Ex-Im determines the industry associated with each transaction it finances. Second, Ex-Im calculates the total value of exports it supports for each industry. Ex-Im implements these first two steps using its own data. Third, Ex-Im multiplies the export value for each industry by the Bureau of Labor Statistics (BLS) ratio of jobs needed to support $1 million in exports in that industry--a figure known as the "jobs ratio." Finally, Ex-Im aggregates across all industries to produce an overall estimate.
Ex-Im reports the number of jobs its financing supports and the methodology it uses but does not describe limitations of the methodology or fully detail its assumptions. Although the BLS data tables that Ex-Im relies on are based on a commonly used methodology, this methodology has limitations. For example, the employment data are a count of jobs that treats full-time, part-time, and seasonal jobs equally. In addition, the data assume average industry relationships, but Ex-Im's clients could be different from the typical firm in the same industry. Further, the underlying approach cannot answer the question of what would have happened without Ex-Im financing. Ex-Im does not report these limitations or fully detail the assumptions related to its data or methodology. GAO's Standards for Internal Controls in the Federal Government states that, in addition to internal communication, management should ensure adequate communication with external stakeholders, which could include Congress and the public. Because of a lack of reporting on the assumptions and limitations of its methodology and data, Congressional and public stakeholders may not fully understand what the jobs number that Ex-Im reports represents and the extent to which Ex-Im's financing may have affected U.S. employment.

What GAO Recommends

To ensure better understanding of its jobs calculation methodology, GAO recommends that Ex-Im improve reporting on the assumptions and limitations in the methodology and data used to calculate the number of jobs Ex-Im supports through its financing. Ex-Im agreed with the recommendation and stated that it would begin reporting more detailed information in its fiscal year 2013 annual report.