Introduction Small businesses are owned by and employ a wide variety of entrepreneursâskilled trade technicians, medical professionals, financial consultants, technology innovators, and restaurateurs, among many others. As do large corporations, small businesses rely on loans to purchase inventory, to cover cash flow shortages that may arise from unexpected expenses or periods of inadequate income, or to expand operations. The Federal Reserve has reported that lending to small businesses declined during the Great Recession of 2007-2009. During the recession, many firms scaled down operations in anticipation of fewer sales, and lenders also tightened lending standards. A decade after the recession, evidence on whether lending to small business has increased is arguably inconclusive. Some small firms may be able to access the credit they need; however, others may still face credit constraints, and still others may be discouraged from applying for credit. Furthermore, drawing direct conclusions about small business access to credit can be difficult because available data are limited and fragmented. Congress has demonstrated an ongoing interest in small business loans (SBLs), viewing small businesses as a medium for stimulating the economy and creating jobs. Congress's interest in small business credit access generally focuses on (1) whether small businesses can secure credit from private lenders and (2) whether small businesses can obtain such credit at fair and competitive lending rates. In other words, policymakers are interested in whether market failures exist that impede small business access to credit and, if so, what policy interventions might be warranted to address those failures. Market failures, in economics and specifically in the SBL market context, refer to barriers that impede credit allocation by private lenders. For example, some lenders may be reluctant to lend to businesses with collateral assets (e.g., inventories) that are difficult to liquidate, as may be typical of some small businesses (e.g., restaurants). Under certain financial or regulatory circumstances, small loans may not generate sufficient returns to justify their origination costs, which also may be considered a market failure. In addition, market failures may exist when borrowers pay noncompetitive lending rates in excess of their default risk. Start-ups and some small businesses that provide niche products frequently must rely on mortgage or consumer credit or private equity investors rather than more traditional SBLs because lenders find it challenging to price loans for these firms, which could be another indicator of SBL market failure. Obtaining conclusive evidence on SBL market performance in terms of quantities and pricing is difficult for several reasons. First, there is no consensus definition of a small business across government and industry. Moreover, as the Federal Reserve stated, "fully comprehensive data that directly measure the financing activities of small businesses do not exist." Drawing conclusions about the availability and costs of SBLs is not possible using existing data sources, which lack information such as the size and financial characteristics of the businesses that apply for credit, the types of loan products they seek, the types of lenders to whom they applied for credit, and which credit requests were rejected and which were approved. Second, the risks small business owners take are not standardized and vary extensively across industries and locations. For this reason, determining whether SBL prices (lending rates and fees) are competitive is difficult without standardized benchmark prices that can be used to compare the relative prices of other SBLs. To address SBL market failures, Congress passed legislation to facilitate lending to small businesses that are likely to face hurdles obtaining credit. For example, the Small Business Act of 1953 (P.L. 83-163) established the Small Business Administration (SBA), which administers several types of programs to support capital access for small businesses that can demonstrate the inability to obtain credit at reasonable terms and conditions from private-sector lenders. The Community Reinvestment Act (CRA; P.L. 95-128 ) encouraged banks to address persistent unmet small business credit demands in low- and moderate-income (LMI) communities. The Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank Act; P.L. 111-203 ) required the Bureau of Consumer Financial Protection (CFPB) to collect data from small business lenders to identify the financing needs of small businesses, especially those owned by women and minorities. (The CFPB has not yet implemented this requirement.) In addition, various bills addressing the SBL market have been introduced in the 116 th Congress. For example, H.Res. 370 would express "the sense of the House of Representatives that small business owners seeking financing have fundamental rights, including transparent pricing and terms, competitive products, responsible underwriting, fair treatment from financing providers, brokers, and lead generators, inclusive credit access, and fair collection practices." H.R. 3374 would amend the Equal Credit Opportunity Act to require the collection of small business loan data related to LGBTQ-owned businesses. H.R. 1937 and S. 212 , the Indian Community Economic Enhancement Act of 2019, among other things, would require the Government Accountability Office to assess and quantify the extent to which federal loan guarantees, such as those provided by the SBA, have been used to facilitate credit access in these communities. This report examines th e difficulty of assessing and quantifying market failures in the SBL market, which consists of small business borrowers (demanders) and lenders (suppliers). It begins by reviewing various ways to define a small business, illustrating that there is no consensus definition of the demand side of the SBL market across government or industry. The focus then shifts to describing the supply sideânamely the types of lenders that lend to small businesses, as well as their lending business models and practices. The report subsequently attempts to identify credit shortages in certain SBL market segments (e.g., the market for small loans, loans for businesses with risky or unsuitable collateral, and loans for businesses in underserved communities). It also examines whether market failures associated with SBL pricing can be identified. Finally, the report concludes by briefly discussing the Dodd-Frank Act requirement that the CFPB collect data to facilitate the understanding of SBL market activity. The Demand for SBLs: Multiple Definitions of a Small Business There is no universally accepted definition of a small business. The federal government and industry define small businesses differently in different circumstances. Although factors such as annual earnings, number of employees, type of business, and market share are typically considered, determining the universe of small businesses from which to collect data is difficult without a consensus definition. If a consensus definition existed, then identifying a small business for data-collection purposes would become more feasibleâfor example, a concise question on a loan application might identify whether the business applying for the loan met certain defined factors making it a small business. Below are examples of the ways regulators, researchers, Congress, and industry have defined small businesses: The SBA defines a small business primarily by using a size standards table it compiles and updates periodically. The table lists size thresholds for various industries by either average annual receipts or number of employees. The SBA also defines small businesses differently for different SBA programs. For example, the SBA's 7(a), Certified Development Company/504, and Small Business Investment Company (SBIC) programs have alternative size standards based on tangible net worth and average net income. Academic research frequently uses a firm that has 500 employees or fewer (but does not monopolize an industry) as a proxy measure for a small business. This definition has been adopted by various federal agencies, such as the U.S. Census Bureau, the Bureau of Labor Statistics, and the Federal Reserve. In addition, some research views microbusinesses as a subset of small businesses. A common academic definition of a microbusiness is a firm with only one owner, five employees or fewer, and annual sales and assets under $250,000. Small business definitions in statute also vary. For example, the Internal Revenue Service (IRS) sets different size standards for small businesses under various tax laws. The IRS provides certain tax forms for self-employed taxpayers and small businesses with assets under $10 million. The Patient Protection and Affordable Care Act of 2010 (ACA; P.L. 111-148 ), however, defined a small business in multiple ways (e.g., fewer than 50 full-time employees to avoid ACA's employer shared responsibility provision; fewer than 25 full-time equivalent employees for tax credits, etc.). According to a Federal Deposit Insurance Corporation (FDIC) survey, small and large banks have their own definitions of a small business. Small banks (defined as banks with $10 billion or less in assets) view a small business as one in which the owner "wears many hats," referring to an owner who performs multiple tasks, perhaps because the firm is a start-up or still in its early growth stage. Large banks define small businesses more formally, in terms of annual revenues and sales. The Supply of SBLs: Background on Lenders and Industry Underwriting and Funding Practices This section provides background on small business lenders and underwriting practices. Although small businesses rely on a variety of credit sources that include personal (consumer or mortgage) credit, family, friends, and crowd-funding, they also rely on various types of financial institutions (banks and nonbanks). Financial institutions vary in how they are regulated, the business models they adopt, the types of loans they offer, and the growth stages of the small businesses they serve. These differences are all factors involved when evaluating whether shortages exist in the SBL market. Some lenders are increasingly using business credit scores to assess creditworthiness, and they may deny SBLs due to either a lack of or poor business credit history. The SBA since 2014 has also relied upon credit scores to qualify applicants for its 7(a) loan program. In 2016, the Small Business American Dream Gap Report found that many businesses failed to understand their business scores or even know that they had one. The text box below summarizes the information used to compute credit scores specifically for businesses. Types of Small Business Lenders Because banks have historically been the principal sources for commercial business lending, credit availability is frequently evaluated in terms of banking trends; however, nonbank financial institutions also engage in commercial business and industrial (C&I) lending. The Federal Reserve has reported that smaller firms are more likely than large firms to apply to nonbank lenders for credit. Credit unions have become an important source of small business loans in recent years. Likewise, nonbank fintech lenders have become an important source of credit in market segments that banks may have exited (e.g., business loans of $100,000 or less). Bank Lending to Small Businesses Because the types of SBLs made by a bank may be related to its size, this section begins with bank size definitions. Small community banks , which may be defined as having total assets of $1 billion or less, are considered a subset of the larger category of community banks; c ommunity banks may be defined as having total assets up to $10 billion. Large banks have total assets that exceed $10 billion. Community banks hold approximately 50% of outstanding SBLs (defined as the share of loans with principal amounts less than $100,000); however, the number and market share of community banks have been declining for more than a decade. Overall, the number of FDIC-insured institutions fell from a peak of 18,083 in 1986 to 5,477 in 2018. The number of institutions with less than $1 billion in assets fell from 17,514 to 4,704 during that time period, and the share of industry assets held by those banks fell from 37% to 7%. Meanwhile, the number of banks with more than $10 billion in assets rose from 38 to 138, and the share of total banking industry assets held by those banks increased from 28% to 84%. 87 The decline in community banks is meaningful because they have historically been one of the largest sources of funding for small businesses. Furthermore, some academic research suggests that, as banks grow, their enthusiasm for lending to starts-ups and small businesses may diminish. In 2015, the Federal Reserve highlighted a decline in the share of community banks' business loan portfolios with initial principal amounts under $100,000, suggesting that these banks were making fewer loans to small businesses. Credit Union Lending to Small Business Members Although some credit unions make SBLs, their commercial lending activities are limited. The Credit Union Membership Access Act of 1998 (CUMAA; P.L. 105-219 ) codified the definition of a credit union member business loan (MBL) and established a commercial lending cap, among other provisions. An MBL is any loan, line of credit, or letter of credit used for an agricultural purpose or for a commercial, corporate, or other business investment property or venture. The CUMAA limited (for one member or group of associated members) the aggregate amount of outstanding business loans to a maximum of 15% of the credit union's net worth or $100,000, whichever is greater. The CUMAA also limited the aggregate amount of MBLs made by a single credit union to the lesser of 1.75 times the credit union's actual net worth or 1.75 times the minimum net worth required to be well-capitalized. Three exceptions to the credit union aggregate MBL limit were authorized for (1) credit unions that have low-income designations or participate in the Community Development Financial Institutions program; (2) credit unions chartered for making business loans; and (3) credit unions with a history of primarily making such loans. Generally speaking, the volume of credit union MBL lending is minor in comparison to the banking system. As of September 30, 2015, for example, credit unions reportedly accounted for approximately 1.4% of the commercial lending done by the banking system. A large credit unionâone with $10 million or more in assetsâmight adopt a business lending model comparable to a small community bank or perhaps a midsize regional bank in the commercial loan market. Similar to community banks, approximately 85% of MBLs were secured by real estate in 2013, with some credit unions heavily concentrated in agricultural loans. A larger credit union (e.g., $1 billion or more in assets) could originate larger loans relative to most community banks with assets less than $1 billion. Despite competition with some banks in certain localities, the credit union system is significantly smaller than the banking system in terms of overall asset holdings and, correspondingly, has a smaller footprint in the broader commercial lending market. Marketplace (Fintech) Lending The share of SBLs originated by nonbank fintech lenders has expanded. However, whether the increase in originations reflects an increase in small business lending is unclear because not all fintechs retain their loan originations in their asset portfolios. Fintechs may generate revenues by (1) originating loans and collecting underwriting fees; (2) selling the loans to third-party investors (via adoption of a private placement funding model, discussed in the below text box "Funding Options for Lenders"); and (3) collecting loan servicing fees (from either the borrowers or investors). The fintech lending model has attained a competitive edge by streamlining and expediting the more traditional labor- and paper-intensive manual underwriting process by, for example, adopting online application submission and proprietary artificial intelligence for underwriting. For this reason, marketplace lending has been both a substitute (providing credit in some loan markets not served by banks) and a complement (via numerous bank partnerships) to the banking system. If, for example, a fintech partners with a bank and subsequently transfers (sells) its loan originations to a bank's balance sheet, the loan would be reported as a banking asset; such scenarios make it difficult to isolate fintech firms' impact in the broader SBL market. Access to Funding in Different Growth Stages This section explains the relationship between the growth stage of a small business and its access to credit. Start-ups and more established firms are likely to have different experiences obtaining business loans. In addition, underwriting requirements and the degree of loan product customization, which vary among lenders, may also be more suitable for borrowers at different stages. The text box at the end of this section summarizes some funding options for lenders that may also influence their underwriting practices and the types of loans they offer. Funding for Start-ups A firm's growth stage matters for credit access. During the initial start-up stage, small businesses typically have little collateral; their financial statements often lack sufficient histories of earnings and tax returns to meet lender requirements; and they typically do not have a performance track record during an economic downturn. As a result, lenders often find it difficult, time-consuming, and costly to determine whether a start-up is creditworthy. For this reason, start-ups often obtain funds from friends and family and drawdowns of personal savings. In addition, start-ups rely on financing from the owner's personal consumer credit products (e.g., credit cards, home equity loans) rather than a traditional commercial loan made by a financial institution. According to the Federal Reserve Small Business Credit Survey, which defines a small business as having $1 million or less in annual revenue, 42% of the small business owners surveyed used their personal credit scores to secure a loan and 45% used both their business and personal credit scores. Furthermore, having a low business credit score was reported as the number one reason why small businesses were rejected for credit, followed by an insufficient credit history. Because many small businesses rely on personal credit history and consumer credit products (rather than business credit), declines in consumer credit availability during economic downturns are also likely to affect small businesses' access to credit. Home equity credit during the 2007-2009 recession declined along with real estate collateral prices, contributing to tighter lending standards. Likewise, any consumer credit cost increase is likely to affect certain small businesses. For example, given the rise in credit card rates over the recession, small businesses that carried large debt balances over several payment cycles might have paid higher borrowing costs relative to a more conventional business loan. Hence, changes in the availability and pricing of consumer credit are likely to have similar effects on consumers and some small businesses, especially start-ups. Funding for Later-Stage Small Firms Once a firm enters into a more advanced growth stage, it may have one or more of the following attributes: a positive cash flow, more than two years of experience, a high business credit score, or achieves $1 million or more in annual revenues. Lenders can subsequently provide more mature businesses with one or more loans secured by their assets, supported by their credit and earnings histories. Accordingly, firms in later growth stages tend to have greater access to SBLs. Nevertheless, small firms still are more likely to obtain credit via relationship lending . Two prevailing commercial lending underwriting models are relationship and transactional lending . Small and community banks typically engage in relationship lending (or relationship banking), meaning that they develop close familiarity with their customers (i.e., soft information) and provide financial services within a circumscribed geographical area. Relationship lending provides a comparative advantage for pricing lending risks that are unique, infrequent, and localized. A relationship lender may also prefer being in close geographical proximity to the collateral (e.g., local real estate) borrowers used to secure their loans. The nature of the risks requires the loan underwriting process to be more labor-intensive. By contrast, large institutions typically engage in transactional lending that frequently relies on automated, statistical underwriting methodologies and large volumes. Transactional lending provides a comparative advantage for loan pricing when the borrowers face more conventional business risks (i.e., hard information, such as sales fluctuations, costs of inputs, specific industry factors, and other relevant metrics) rather than idiosyncratic risks that are difficult for an automated underwriting model to quantify. By relying on conventional financial metrics and documentation, transactional lenders do not need to be located near their borrowers to monitor their financial health. Moreover, because underwriting is more automated for these institutions, credit requests are most frequently denied because of (1) weak business performance, (2) insufficient loan collateral, and (3) having too much existing debt outstanding. A lender's underwriting model influences the way it defines a small business. As previously mentioned, community banks tend to describe small businesses as those whose owners multitask, meaning that they perform multiple large-scale tasks rather than relying on designated, full-time employees. Small businesses who face these types of challenges are unlikely to provide (in a timely manner) the metrics necessary for automated underwriting and, therefore, tend to be underwritten manually when requesting credit. For manual underwriting, small firms' credit scores are often not essential to evaluate creditworthiness and determine loan terms. Instead, relationship lending allows for more tailoring of loans (e.g., customized lending terms or repayment schedules) to small firms' idiosyncratic needs. Hence, lenders with relationship lending models are likely more well-adapted to underwrite businesses with risks that are unusual and oftentimes difficult to quantify. By contrast, large banks use metrics such as the dollar amount of annual sales revenues to categorize a small business. Automated underwriting becomes more amenable for businesses with business credit scores and the ability to provide financial documentation in a timely manner. A bank may offer an unsecured credit card loan to a firm with reliable financial performance records, thus reducing the monitoring costs associated with collateralized lending. Furthermore, firms with standardized financials can obtain more standardized (noncustomized) and competitively priced loans, which can be delivered faster. In general, the average costs to originate (and fund) loans decrease as the volume of loans or loan amounts increase. Lenders with transactional lending models can benefit more (relative to manual underwriters) from such economies of scale because their customer bases include more borrowers with standardized and quantifiable risks. Although they tend to rely on different types of credit, both start-ups and well-established firms may be highly dependent on certain lenders that specialize in underwriting loans for certain industries (e.g., maritime, breweries and distilleries, or moving). In addition, some lenders primarily engaged in transactional underwriting may still rely on relationship lending under some limited circumstances. For example, a larger firm may be willing to relax supplementary financial requirements (known as covenants) designed to reduce credit risk for borrowers with whom the firm has an ongoing relationship. This type of action may be considered a form of manual underwriting. Attempting to Identify SBL Market Failures This section attempts to find evidence of market failures that may be addressed by policy interventions. The specific areas of potential concern are (1) whether the lending industry is providing enough small loans for small businesses; (2) whether certain small businesses lack the type of collateral that lenders require to secure the loans; (3) whether the amount of credit provided in low- and moderate-income (LMI) communities is insufficient; and (4) whether the price of credit is too expensive for small businesses. Shortage of Small Loans Reviewing the number of small-sized loans may help determine if a SBL market shortage exists, assuming that (1) lenders make small-sized loans to small businesses and (2) an ideal size definition exists. The FDIC provides multiple size definitions of SBLs: loans with origination amounts less than or equal to $100,000; loans with origination amounts less than or equal to $250,000; loans to firms with gross annual revenues less than or equal to $1 million; and loans with origination amounts greater than $250,000 to firms satisfying any amenable small business definition. The FDIC's 2018 Small Business Lending Survey of 1,200 banks uses a C&I loan size limit of $1 million as a proxy for small business lending. In 2015, the Federal Reserve specifically highlighted the decline of community banks' business loans with initial principal amounts under $100,000. The current interest-rate environment, which has been at a historic low since the recent recession, may influence this outcome. In a low-interest-rate environment, even relationship lenders may have a greater incentive to increase loan sizes to generate sufficient interest income to cover the costs of providing them. Assuming that the underwriting, servicing, and compliance costs do not vary with loan size, then incurring those fixed costs for larger-sized loans, which may be more likely to generate more interest revenue, may be more economical for lenders. The retreat from the $100,000 loan market might be temporary if interest rates rise in the future. Nonetheless, denials of SBL requests because of a shift in lenders' preferences toward originating larger loans may indicate a market failure. Attempting to find a proxy for market failure by examining the availability of SBLs of $100,000 or any size threshold is challenging for the following reasons: According to the Federal Reserve's Survey of Lending Terms , at the beginning of 2017, the average C&I loan size for all domestic commercial banks (excluding U.S. branches and agencies of foreign banks) was approximately $575,000; the average business loan size at small domestic banks was approximately $123,000; and the average loan size at large domestic banks was approximately $729,000. By contrast, at the beginning of 2007 (prior to the 2007-2009 recession), the average C&I loan size for all domestic commercial banks was approximately $379,000; the average business loan size at small domestic banks was approximately $117,000; and the average loan size at large domestic banks was approximately $578,000. Despite the 51.7% increase in average C&I loan size for all domestic commercial banks, the average C&I loan size for small commercial banksâwhich hold approximately 50% of outstanding SBLsâincreased by a relatively modest 5.13%. Thus, it is not apparent that the smaller-size SBL market segment has been displaced. If lenders increase the total amount of SBLs made at $250,000 or $1 million, for example, while simultaneously making fewer loans of $100,000, then whether that outcome represents an increase or decrease in overall small business lending is subject to debate. Similarly, the FDIC noted that even the $1 million loan size limit may underestimate the amount of loans made to small firms. Some small firms (with annual revenues under $1 million) may get loans that exceed $1 million. Some SBLs may be secured by residential real estate and counted as mortgages. Conversely, the data collected may overstate SBLs to small businesses. The financial data on bank C&I loans do not report on loans made to a well-defined group of small firms. Instead, the data only report on small loans to all businesses (regardless of size), thus overstating the amount of SBLs, given that large businesses also receive loans of these sizes. The demand for $100,000 SBLs (from community banks) may have decreased. For example, technology firms, which represent many start-ups since the 2007-2009 recession, frequently do not purchase large amounts of inventory. Such firms that are able to operate out of the owners' homes may finance operations with personal savings and credit cards. Conversely, the demand for large loans may have increased . For example, some firms may determine that obtaining larger-size loans during the current low-interest-rate environment is more economical than having to reborrow at some point in the future at higher lending rates. In addition to the abovementioned issues, drawing conclusions about SBL shortages based primarily on the lending practices of community banks is premature in the absence of a comprehensive dataset that includes loans made by nonbank lenders. Fintech lenders may be filling the gap in small business lending left by a decline in community banks. Because fintech lenders generally are not required to hold capital against their portfolio loans or can fund via private placement, they may be able to take advantage of opportunities to lend to small businesses that would not generate sufficient profit margins for community banks. Loans retained in fintech lenders' portfolios or funded via private placement, however, are currently not reported to the federal banking regulators. Furthermore, businesses may have multiple loans and often seek credit from multiple lenders. In some cases, small businesses may be able to obtain credit from some lenders and not others, particularly in cases when borrowers inadvertently seek credit from lenders using incompatible underwriting models. In short, the focus on a particular loan size or particular lender type is arguably too narrow for evaluating performance in the SBL market. Collateral Eligibility for Secured Lending A market failure may exist if lenders are unwilling to provide loans backed by illiquid collateral (i.e., collateral that cannot be easily liquidated if the borrower fails to repay the loan)âan issue that may disproportionately affect certain small businesses. Banks and credit unions provide business loans via asset-based lending (ABL) guidelines that require firms to pledge assets (e.g., cash, receivables from inventory sales, inventory) as collateral for loans. For ABL purposes, federal banking regulators define a SBL as any loan to a small business (as defined by Section 3(a) of the Small Business Act of 1953 [P.L. 83-163 as amended] and implemented by the SBA) or a loan that does not exceed $2 million for commercial, corporate, business, or agricultural purposes. A bank typically provides fully collateralized short-term loans (under five years) to firms based upon their performance records (e.g., sufficient credit and earnings histories and assets), and it monitors the risks to the collateral that would need to be liquidated (sold) if the small business experienced financial distress. Similarly, credit unions can provide MBLs that comply with NCUA's ABL guidelines. Some firms' inventory, however, may not be ideal for ABL guidelines. Collateral that would be difficult to liquidate without losing too much value may not be acceptable. For example, restaurants (a common type of small business) have leases, cooking equipment (likely to resell for less than its initial sale price), and inventories of food that would not generate the income necessary to recoup losses from a loan default. Restaurants also have difficulty demonstrating the ability to repay a loan over a period of years. For this reason, lenders may not accept a restaurant's collateral as security for a loan. In response to this market failure, the SBA administers various programs to facilitate small business credit access (typically loans for up to $5 million and for 5-25 years) for financially healthy firms with collateral or inventory less likely to satisfy ABL requirements. Some borrowers that can demonstrate the ability to repay (e.g., minimum business credit score, management experience, minimum levels of cash flow, some collateral, and personal guarantees by the business owners) still may not be able to obtain affordable credit elsewhere (i.e., from other lenders), which might seem paradoxical. This may be because the firm's inventory does not turn over at a steady pace (e.g., seasonal merchandise), and a lender would face difficulty quickly liquidating the collateral if the firm became financially distressed. For a fee, the SBA may retain the credit risk of a small business loan up to a certain percentage, and the lender assumes the remaining share of credit risk to ensure incentive alignment during underwriting. SBA-guaranteed loans frequently have higher lending rates relative to ABL loans, taking into account the guarantee (and loan servicing) fees charged to borrowers to compensate the federal agency for retaining a majority of the default risk and the additional risk correlated with illiquid collateral. Following the recent recession, the SBA has reported an increase in the dollar amount of guaranteed lending over 2013-2018, which might indicate the ability to mitigate more market failures. If, however, borrowers fail to repay their loans and it is not possible to recover sufficient fees and proceeds from asset liquidations to cover the losses, then the SBA may need additional appropriations from Congress to account for the shortfall. The utility of government intervention in the form of SBA-guaranteed lending, therefore, is debatable. When borrowers are unable to obtain private-sector credit but subsequently repay their SBA loans, that outcome may suggest that a government guarantee helped correct a failure and improve SBL market performance. Conversely, when borrowers are unable to obtain private-sector credit and subsequently default on their SBA loans, that outcome suggests no market failure initially existed in the private SBL market. Monitoring loan performance is useful in distinguishing between a legitimate credit market barrier and an excessive lending risk, but such monitoring can only occur after loans have been originated and guaranteed, which underscores the difficulty of correctly identifying and effectively mitigating market failures. SBLs and the Community Reinvestment Act A market failure may exist if lenders make fewer SBLs in low- and moderate-income (LMI) areas than in higher-income areas. The Community Reinvestment Act of 1977 (CRA; P.L. 95-128 ) was designed to encourage banking institutions to meet the credit needs of their entire communities. The federal banking regulatory agenciesâthe Board of Governors of the Federal Reserve System, the Federal Deposit Insurance Corporation, and the Office of the Comptroller of the Currencyâcurrently implement the CRA. The regulators issue CRA credits, or points, when banks engage in qualifying activitiesâsuch as mortgage, consumer, and business lending; community investments; and low-cost services that would benefit LMI areas and entitiesâthat occur within a designated assessment area. These credits are then used to issue each bank a performance rating. The CRA requires these ratings be considered when banks apply for charters, branches, mergers, and acquisitions, among other things. Under the CRA, the banking regulators award CRA credit to certain SBLs (including small farm loans), provided these loans meet both (1) a size test and (2) a purpose test. Small businesses that receive an SBL must either (1) meet the size eligibility standards for the SBA's Certified Development Company/504 or SBIC programs or (2) have gross annual revenues of $1 million or less to qualify for CRA credit. The loans must also promote community and economic development, as explained in the federal bank regulators' guidelines, to qualify for CRA credit. Figure 1 shows the distribution of SBLs for $1 million or less that were eligible for CRA credit over the 2009-2017 period across census tracts grouped into four relative income categories as measured against median family income (MFI). For comparison, the last column shows the median percentages of total SBLs over the entire period. The median figures are as follows: 5.2% in the low-income tracts (< 50% of MFI), 16.7% in the moderate-income tracts (50% â¥ MFI < 80%), 40% in the middle-income tracts (80% â¥ MFI <120%), and 37.9% in the upper-income tracts (120% â¥ of MFI). This figure does not capture all CRA business lending because SBLs exceeding $1 million may also receive CRA credit. (In addition, the data in this figure represent a subset of lending activity that occurs in LMI tracts because large C&I loans, as well as consumer loans, may qualify for CRA credit.) Furthermore, changes in the number of SBL or CRA loans could indicate a change in the percentage of CRA credit awarded to SBLs, a change in total SBL originations, or both. Despite data limitations, the trends suggest that the share of SBLs in LMI areas has remained steady at approximately 20% for almost a decade. Whether that share can increase furtherâwhich would suggest that credit may not be accessible for small businesses located in LMI areasâis difficult to determine. For example, the demand for small business credit in LMI areas may be lower relative to higher-income areas. The number of potential businesses and lending opportunities in LMI areas may be comparatively lower if a greater percentage of small businesses locate in areas where their prospective customers would have sufficient incomes to sustain demand for the products or services they offer. In short, the data on SBLs awarded CRA credit do not provide a way to measure the demand for SBLs. There is no information on the number of businesses located in LMI areas that applied for loans and were subsequently rejected, making it difficult to conclude that a failure exists in the SBL market in LMI areas. Accordingly, Congress has called for the collection of data from small business lenders, discussed in more detail in the section entitled " CFPB Collection of Small Business Data ." Small Business Loan Pricing The pricing of SBLsâspecifically interest rates and feesâis another consideration for evaluating the small business credit market's overall performance. A small business might not seek credit if it is too expensive. A small business might determine that it cannot afford an offer for credit if more of its financial resources (e.g., net income) must be devoted to paying interest than reinvesting in operations. When loan prices are set substantially higher than the risks posed by borrowers and the costs to acquire the funds used to make the loans, the pricing is not considered competitive. In economics, a competitive price is one that multiple suppliers would offer to buyers for the same good or service. A competitive price is often the best or lowest that a buyer can find for a good or service and, therefore, can be used as a benchmark price when comparison shopping to evaluate other offers. Determining whether SBLs are competitively priced is challenging. A common market failure is imperfect information, or information asymmetry âwhen one party in a transaction has more accurate or more detailed information than the other party. This imbalance can result in inefficient outcomes. In the case of the small business credit market, the risks taken by small business owners are not standardized and vary extensively across industries and geographical locations. It is difficult for lenders to determine competitive loan pricing without sufficient comparable businesses from which to obtain reasonable estimates of expected losses and predict cash flows. Similarly, it may be difficult for small businesses to determine whether a loan offer is competitive without sufficient comparable business loans. Relationship lending, as previously discussed, can alleviate an SBL market failure that arises from the inability to price credit risks. Relationship lending allows a lender to collect more information about a borrower's financial behaviors, which may result in less stringent collateral requirements and greater access to credit at a lower price over time. Disclosure laws are another way to potentially resolve this type of market failure. In consumer credit markets, the Truth-In-Lending Act of 1968 (TILA; P.L. 90-301) requires lenders to disclose the total cost of credit to consumers in the form of an annual percentage rate (APR). TILA is designed to ensure borrowers are aware of their loan costs. For some consumer products, regulators require lenders to provide greater disclosures about product features that could result in borrowers paying excessive rates and fees, especially in cases where they are unaware of assessed penalty fees and interest-rate increases. Effective disclosures arguably mitigate the incentive for lenders to charge substantial markups above funding costs and borrowers' risks, thus resulting in lower loan prices. Although TILA applies to mortgage and consumer loans, it does not apply to business loans. For this reason, legislative proposals have been introduced in Congress to extend TILA disclosures to small firms. For example, H.R. 5660 , the Small Business Credit Card Act of 2018, would extend TILA disclosures to firms with 50 or fewer employees. Whether TILA protections for business credit would result in more competitive business loan terms is unclear. First, evidence suggests that TILA protections do not necessarily encourage consumers to shop for lower borrowing rates despite having more standardized (e.g., collateral) lending risks relative to businesses, suggesting it is unlikely TILA protections for small business would encourage them to shop around for credit. Second, some small businesses may already rely on certain types of credit to which TILA does apply. For example, some businesses obtain credit via personal credit cards and home equity loans, to which TILA disclosure requirements already apply. In addition, many lenders already disclose APRs on their business credit cards. CFPB Collection of Small Business Data The Dodd-Frank Act requires financial institutions to compile, maintain, and report information concerning credit applications made by women-owned, minority-owned, and small businesses. This data collection is intended to "facilitate enforcement of fair lending laws" and to "enable communities, governmental entities, and creditors to identify business and community development needs and opportunities of women-owned, minority-owned, and small businesses." The Dodd-Frank Act authorizes the CFPB to collect various data from financial institutions about the credit applications they receive from small businesses, including the number of the application and date it was received; the type and purpose of loan or credit applied for; the amount of credit applied for and approved; the type of action taken with regard to each application and the date of such action; the census tract of the principal place of business; the business's gross annual revenue; and the race, sex, and ethnicity of the business's principal owners. On May 10, 2017, the CFPB announced that it was seeking public comment about the small business financing market, including relevant business lending data used and maintained by financial institutions and the costs associated with the collection and reporting of data. Specifically, the CFPB requested information on five categories: "(1) small business definition, (2) data points, (3) financial institutions engaged in business lending, (4) access to credit and financial products offered to businesses, and (5) privacy." With respect to definition, the CFPB sought comment on the best definition of a small business and the burden of collecting data under that definition. In addition, the CFPB requested information on what data financial institutions should be required to collect and report, and which institutions should be exempted. The CFPB also requested feedback on product types offered to small businesses because the variety of terms and loan covenants that can be used to tailor loans, in addition to the interest rate, are part of the overall cost (price) of credit. The comment period closed on September 14, 2017. The CFPB has not yet issued a proposed rule, but it recently announced that such a rule was part of its spring 2019 regulatory agenda. Evaluating the small business lending market's overall performance (in terms of market failures) would be easier with less fragmented, more complete data. Collecting data, however, poses challenges for the CFPB and industry lenders. First, the Equal Credit Opportunity Act prohibits the collection of race and gender information, thus increasing the difficulty for the CFPB to implement a rule that would require such reporting. In addition, the collection and reporting of SBL data would likely need to be converted to a digital format. The fixed costs to implement digital reporting systems could be relatively larger for small financial institutions than for large institutions. Large institutions have more customers (to justify the initial expense) and offer a more limited range of standardized products. Depending upon the collection requirements eventually implemented, some institutions might decide to offer more standardized, less tailored financial products to reduce reporting costs. It is possible that more financial institutions may require minimum loan amounts (e.g., exit the loan market delineated as $100,000 and below) to ensure that the loans generate enough revenue to cover the costs to fund and report data. Conclusion From an economics viewpoint, the ability to evaluate the performance of various SBL market segmentsâspecifically whether (1) a small business credit shortage exists or (2) pricing for loans to small businesses is significantly above the lending risks and funding costsâis extremely challenging. Policymakers have been interested in whether market failures that impede small business access to capital exist and, if so, what policy interventions might address those market failures. However, it is difficult to discern which policy interventions would be most well-suited to addressing potential small business credit market failures without better data about the market itself. Arriving at more definitive conclusions about the availability and costs of SBLs might be possible with information such as the size and financial characteristics of the businesses that apply for loans, the types of loan products they request, the type of lenders to whom they applied, and which applications were approved and rejected. Collecting the necessary data, however, presents both legal and cost challenges.


Introduction Social Security provides insured workers and their eligible family members with a measure of protection against the loss of income due to the worker's retirement, disability, or death. The amount of the monthly benefit payable to workers and their family members is based on the worker's career-average earnings from jobs covered by Social Security (i.e., jobs in which the worker's earnings were subject to the Social Security payroll tax). Although participation in Social Security is compulsory for most workers, about 6% of all workers in paid employment or self-employment are not covered by Social Security. Most noncovered workers are state and local government employees who are covered by alternative staff-retirement systems or permanent civilian federal employees hired before January 1, 1984, most of whom are covered by the Civil Service Retirement System (CSRS) or other alternative retirement plans. Social Security benefits are designed to replace a certain percentage of a worker's career-average earnings (referred to as the replacement rate ) for those who remain in covered employment throughout their careers. The benefit formula is weighted to replace a greater share of career-average earnings (i.e., provide a higher replacement rate) for low-paid workers than for high-paid workers. However, providing an appropriate replacement rate for beneficiaries whose careers are split between covered and noncovered employment (referred to hereinafter as split-career beneficiaries ) is challenging because years of noncovered earnings are marked as zeros in Social Security earnings records, so split-career beneficiaries appear to have low career-average earnings. Therefore, without adjusting for noncovered earnings, split-career beneficiaries would receive a higher replacement rate than beneficiaries with the same earnings who spent their entire careers in Social Security-covered employment. The windfall elimination provision (WEP) is a modified benefit formula that reduces Social Security benefits for certain retired or disabled workers who have earnings not covered by Social Security and are entitled to pension benefits based on those noncovered earnings (including certain foreign pensions). Its purpose is to remove an unintended advantage or windfall that these workers would otherwise receive as a result of the interaction between the regular Social Security benefit formula and the workers' relatively short careers in Social Security-covered employment. In December 2018, nearly 1.9 million people (or about 3% of all Social Security beneficiaries) were affected by the WEP. Some argue that the current-law WEP formula generally fails to provide the correct benefit adjustment (reduction) to affected beneficiaries. It overadjusts the benefit for some affected workers by producing a relatively large benefit reduction that gives them a lower replacement rate than similar workers whose entire careers were covered by Social Security; in contrast, it underadjusts the benefit for some other affected beneficiaries by producing a relatively small benefit reduction, giving them a higher replacement rate than similar workers whose entire careers were covered by Social Security. Legislative proposals have been introduced to substitute the current WEP with a proportional formula that would provide the same replacement rate to split-career beneficiaries and beneficiaries whose entire careers are covered. This report explains how the proportional formula would work and how it differs from the current-law WEP formula. It also discusses how Social Security benefits would change under the proportional formula for workers with different levels of earnings, years of noncovered earnings, and timing of those noncovered earnings (i.e., early career, midcareer, or late career). Lastly, this report concludes with historical and recent legislative proposals that are based on the proportional formula. The Current-Law WEP How Does the Current-Law WEP Work? Among other requirements, a worker generally needs 40 earnings credits (10 years of Social Security-covered employment) to be eligible for a Social Security retired-worker benefit. The Social Security regular benefit formula applies three replacement factorsâ90%, 32%, and 15%âto three different brackets of a worker's average indexed monthly earnings (AIME), which is the monthly average of the 35 highest years of indexed covered earnings. The result is the primary insurance amount (PIA), which is the worker's basic benefit before any adjustments are made for factors such as cost-of-living adjustments (COLAs), early retirement, delayed retirement, or noncovered earnings. For workers who become eligible for benefits in 2020, the PIA is based on the formula in Table 1 . The dollar amounts in the table, known as bend points , are adjusted annually for average earnings growth. Under current law, the WEP reduction is based on years of coverage (YOCs)âthe larger the number of YOCs, the lower the WEP reduction. For people with 20 or fewer YOCs who become eligible for benefits in 2020, the WEP reduces the first replacement factor from 90% to 40% (referred to as the WEP replacement factor in this report), resulting in a maximum benefit reduction of $480 (90% of $960 minus 40% of $960). A worker with an AIME of $1,500 who becomes eligible for Social Security benefits in 2020 would receive an unadjusted monthly benefit of $1,036.80 if all earnings are covered by Social Security, compared to a WEP-reduced monthly benefit of $556.80 if he or she has 20 or fewer YOCs (see Table 1 ). For each YOC in excess of 20, the WEP replacement factor increases by 5%. For example, the WEP factor is 45% for those with 21 YOCs and 50% for those with 22 YOCs. The WEP factor reaches 90% for those with 30 or more YOCs, and at that point it is phased out (see Figure 1 ). The amount of substantial covered earnings needed for a YOC is $25,575 in 2020; the amount is adjusted annually by average wage growth. Workers with annual covered earnings below the level of substantial earnings do not receive a YOC. For example, a worker who earns $5,640 in 2020 (covered earnings) will receive four earnings credits for the purpose of Social Security eligibility, but will not qualify for a YOC for the WEP purpose. In December 2018, of the nearly 1.9 million beneficiaries affected by the WEP, nearly 1.6 million (84%) had 20 YOCs or fewer, and the remaining 0.3 million (16%) had 21-29 YOCs (see Figure 1 ). Two groups of beneficiaries with noncovered employment are exempt from the WEP: (1) those with 30 or more YOCs; and (2) those not receiving a pension based on those noncovered earnings. SSA's Office of the Chief Actuary estimated that roughly 18 million Social Security worker beneficiaries with some noncovered earnings were exempt from the current WEP in 2018. Among them, about 9.4 million (52%) had 30 or more YOCs. Additionally, a guarantee provision in the WEP ensures that the WEP reduction cannot exceed one-half of the pension based on the worker's noncovered employment. Benefit Adjustments Under the Current-Law WEP The regular Social Security benefit formula is progressive, replacing a greater share of career-average earnings for low-paid workers than for high-paid workers. For example, Table 2 displays five types of scaled workers with hypothetical lifetime earnings from low to high, whose earnings patterns are based on actual Social Security-insured workers' career earnings. The replacement rateâthe percentage of AIME replaced by the PIAâranges from 83.3% for a very low-earning worker whose entire career is covered to 60.5% for a low-earning worker, 44.8% for a medium-earning working, 37.2% for a high-earning worker, and 29.4% for a worker who earns the taxable maximum every year. If a person has earnings not covered by Social Security, those noncovered earnings are shown as zeros in their Social Security earnings records, thus resulting in relatively lower career-average earnings. The regular formula cannot distinguish between workers who have low career-average earnings because they worked for many years at low earnings in covered employment and workers who appear to have low career-average earnings because they worked for many years in jobs not covered by Social Security. Therefore, without a PIA reduction for noncovered earnings, a worker who split his or her career between covered and noncovered employment might receive a higher replacement rate than a worker with the same level of earnings who spent an entire career in covered employment. For example, a low-scaled worker is estimated to have annual career-average earnings of $22,588. If all career earnings were covered, the worker would receive a 60.5% replacement rate in Social Security benefits. However, if the second half of the low-scaled worker's career was in noncovered employment, the worker would receive a replacement rate of 90.0% based on the regular benefit formula before adjusting for noncovered earnings (see Table 2 ). The WEP PIA addresses this problem by reducing the replacement rate for certain workers who have noncovered earnings. For example, the replacement rate would be adjusted from 90.0% to 40.0% for a low-scaled worker if the second half of his career was not covered by Social Security. The WEP's original intent was to ensure that Social Security beneficiaries with some earnings from noncovered employment received the same replacement rate as workers who spent their entire careers in covered employment. However, the current-law WEP formula can only approximately achieve that goal. The current-law WEP formula over adjust s benefits for certain affected beneficiaries by producing a relatively large benefit reduction, resulting in a lower replacement rate than a similar worker whose entire career was covered by Social Security would receive. For example, a very low-scaled worker who spent the second half of his or her career in noncovered employment would receive a replacement rate of 40.0% using the WEP formula, which is substantially lower than the replacement rate a very low-scaled worker whose entire career was covered by Social Security (83.3%) would receive. The magnitude of such benefit overadjustment is smaller for affected beneficiaries with relatively higher lifetime earnings. For example, if the second half of a high-scaled worker's career was not covered by Social Security, the worker would receive a WEP benefit replacing 34.4% of covered AIME, which is slightly lower than the replacement rate for high-scaled workers whose entire careers are covered by Social Security (37.2%). In addition, the current-law WEP formula under adjust s Social Security benefits for some other beneficiaries by producing a relatively small benefit reduction, resulting in a higher replacement rate than a similar worker whose entire career is covered would receive. Such underadjustment usually applies to workers with significantly high lifetime earnings and some earnings not covered by Social Security. For example, a taxable-maximum worker who earned the taxable-maximum amount each year of work history is estimated to have career-average earnings of $123,232. If the second half of the taxable-maximum worker's career was not covered by Social Security, the worker would receive a 33.2% replacement rate in Social Security benefits under the WEP, compared to 29.4% if the entire career had been covered by Social Security (see Table 2 ). The Proportional Formula for the WEP How Would the Proportional Formula Work? The proportional formula for the WEP would apply the regular Social Security benefit formula to all past earnings up to the taxable maximum from both covered and noncovered employment. The resulting benefit would then be multiplied by the ratio of career-average earnings (AIME) from covered employment only to career-average earnings (AIME) from both covered and noncovered employment. By concept, the PIA under the proportional formula (i.e., proportional PIA) would be as follows: Proportional PIA=PIA for all EarningsÃAIME for Covered EarningsAIME for all Earnings In other words, a Social Security benefit would be calculated based on a worker's combined covered and noncovered earnings, but only the portion based on covered earnings would be payable as a Social Security benefit. Benefit Adjustments Under the Proportional Formula Under the proportional formula, Social Security beneficiaries with some earnings from noncovered employment would receive the same replacement rate (ratio of PIA to AIME) for covered earnings as similarly situated workers who spent their entire careers in covered employment, regardless of earnings levels, years of covered earnings, or the timing of those covered earnings. Figure 3 illustrates this, showing that a medium-scaled worker would receive a 44.8% replacement rate under the proportional formula whether the worker's entire career or only half of the worker's career was covered by Social Security. This 44.8% replacement rate for the split-career worker would be lower than the windfall replacement rate under the regular PIA without any adjustment for noncovered earnings (60.2%), but higher than the rate under the current WEP PIA (35.9%), which overadjusts the benefit reduction for noncovered earnings. The proportional formula would provide a higher benefit than the WEP for workers whose Social Security benefits are currently overadjusted, such as the very low-, low-, medium-, and high-scaled workers shown in Table 3 . Because scaled workers with relatively lower lifetime earnings receive a larger overadjustment under the current WEP, those workers would receive a larger monthly benefit increase under the proportional formula. For example, the monthly benefit increase under the proportional formula relative to the current WEP would be $213.90 for very low-scaled workers if their careers' second halves were not covered by Social Security, compared to $182.20 for low-scaled workers, $176.50 for medium-scaled workers, and $87.10 for high-scaled workers. In contrast, workers whose Social Security benefits are underadjusted by the current WEP, such as taxable-maximum workers, would receive a lower benefit under the proportional formula. Comparing the Proportional Formula with Current Law The proportional formula discussed above would differ from the current-law WEP formula in terms of monthly benefit amounts, improper payments, and notification to beneficiaries. Differences in Monthly Benefits Given the current-law WEP formula's design, the proportional formula would increase Social Security benefits for some beneficiaries with noncovered employment and decrease benefits for others. Beneficiaries who would receive a lower benefit under the proportional formula than under current law include beneficiaries with noncovered earnings who are exempt from the current-law WEP, such as those with 30 or more YOCs or those not receiving a noncovered pension; and beneficiaries whose benefits are underadjusted using the current WEP PIA, such as those who have relatively high lifetime earnings, are close to 30 YOCs, or are affected by the current-law guarantee provision. If the proportional formula had applied to current beneficiaries in 2018, SSA's Office of the Chief Actuary (OCACT) estimates that about 1.1 million beneficiaries affected by the current WEP (or 69%) would have received a higher benefit and about 0.5 million beneficiaries affected by the current WEP (or 31%) would have received a lower benefit. In addition, 13.5 million beneficiaries with some noncovered earnings who were exempted from the current WEP in 2018 would have received a lower benefit under the proportional formula. Exemptions and the Guarantee Provision Under Current Law Beneficiaries who are eligible for either of the two exemptions to the current-law WEP would receive a lower benefit under the proportional formula. Beneficiaries with 30 or more YOCs are exempted from the current WEP, but under the proportional formula, workers with 30 or more YOCs and very few years of noncovered employment (even less than a year) would probably receive proportional reductions in their Social Security benefits. For example, a medium scaled-worker who earned 30 YOCs in his earlier career would not be affected by the current WEP even if he took a noncovered position afterward and was entitled to a noncovered pension (see case [1] in Table 4 ). In this case, the worker would receive an unreduced Social Security benefit of $1,707.30, which would be higher than the proportional PIA ($1,612.00) based on earnings from noncovered employment. SSA's OCACT estimates that, in 2018, roughly 9.4 million Social Security retired-worker and disabled-worker beneficiaries with some noncovered earnings were exempt from the current WEP because they had 30 or more YOCs. Because those beneficiaries have relatively few years of noncovered earnings, their benefit reductions under the proportional formula would be relatively small. The other exemption applies to beneficiaries with noncovered earnings who do not receive a pension based on those noncovered earnings. Those beneficiaries could receive a lower benefit under the proportional formula because their earnings from noncovered employment could reduce the proportion of overall career-average earnings from covered jobs. For example, under current law, a medium-scaled worker who worked in a noncovered position from age 55 to age 61 but received no noncovered pension benefits would be exempt from the WEP and receive a Social Security benefit equal to $1,551.10 (see case [2] in Table 4 ). This amount would be higher than the benefit computed by the proportional formula ($1,432.80) because those seven years of noncovered employment would proportionally reduce the Social Security benefit. Estimates from OCACT find that about 8.6 million Social Security retired-worker and disabled-worker beneficiaries with some noncovered earnings and less than 30 YOCs were exempt from the current WEP in 2018 because they had no pension based on those noncovered earnings. In addition, the guarantee provision under current law limits benefit reductions by ensuring that the WEP reduction cannot exceed one-half of the noncovered pension benefit. This provision typically leads to small benefit reductions for beneficiaries who receive small pension benefits based on relatively short careers in noncovered employment. The proportional formula would not limit reductions in this way, so those workers' benefits would be lower under the proportional formula than under the WEP. For example, a low-scaled worker who worked in a noncovered position from age 52 to age 61 and received a monthly benefit from a noncovered pension equal to $100 would receive a WEP reduction of no more than $50 under current law (see case [3] in Table 4 ). Therefore, this worker would receive $896.10 under the current WEP, but $770.90 under the proportional formula with no guarantee provision. Years of Coverage In addition to the exemptions and the guarantee provision, whether a worker with noncovered earnings would receive a lower Social Security benefit under the proportional formula relative to current law also depends on YOCs based on substantial earnings. The number of YOCs determines the WEP replacement factor under current law (see Figure 1 ). In general, the larger the number of YOCs, the higher the WEP replacement factor. Workers who have employment not covered by Social Security also need to earn the substantial covered amount ($25,575 in 2020) to receive one YOC, which is much higher than the earnings required for Social Security eligibility ($5,640 in 2020). Because of the WEP's higher YOC earnings threshold, workers with relatively lower covered earnings who are affected by the WEP may be entitled to Social Security benefits based on earnings credits but not qualify for a YOC for WEP purposes. Although YOCs are a critical factor for determining the PIA under the current-law WEP, they are not relevant for the proportional formula. To compare monthly benefits based on the two formulas by YOCs, Figure 4 shows a medium-scaled worker's monthly benefit amounts under the current WEP PIA and the proportional PIA. If the medium-scaled worker took a job covered by Social Security in the earlier part of her career and the number of YOCs was relatively small (less than 27 for a medium-scaled worker), the proportional formula would provide a higher benefit than the current WEP. However, if the number of YOCs were relatively large (more than 27 for a medium-scaled worker), the proportional formula would provide a lower benefit than the currentâlaw WEP. Two reasons may explain why the proportional formula would provide a lower benefit than the current-law WEP at the higher level of YOCs. First, current law exempts beneficiaries from the WEP if they have 30 or more YOCs, resulting in a higher benefit amount than under the proportional formula. Second, when YOCs are close to 30, the current-law WEP replacement factor is relatively large, such as 85% for 29 YOCs (see Figure 1 ), so the current-law WEP PIA underadjusts and produces a higher benefit than the proportional formula. The monthly benefit difference between the proportional formula and the current-law WEP formula also depends on earning levels. For example, the very low- and low-scaled workers in Figure 5 had fewer than 20 YOCs because their annual earnings were typically less than the substantial earnings required for a YOC. They would receive a current-law WEP PIA based on the lowest WEP replacement factor (40%). Therefore, the proportional PIA for these workers would generally be higher than the WEP PIA, because the 40% WEP replacement factor overreduces their Social Security benefits for noncovered earnings. The proportional PIA would also be higher than the WEP PIA for medium- and high-scaled workers with relatively fewer YOCs, such as Figure 5 's medium-scaled workers with fewer than 29 years of covered earnings and high-scaled workers with YOCs between 11 and 22. However, as YOCs increase, the WEP replacement factor goes up, so the WEP PIA is higher than the proportional PIA for medium- and high-scaled workers with more YOCs. For workers with substantially high earnings, such as taxable maximum workers, the proportional PIA would generally be lower than the WEP PIA. Timing of Noncovered Employment The size of the monthly benefit difference between the proportional PIA and the WEP PIA also depends on the timing of covered and noncovered employment. Figure 6 compares three medium-scaled workers with 20 years of covered employment in early career, midcareer, and late career, respectively. Because early-career earnings are relatively lower than earnings in later years, a medium-scaled worker whose early career is covered by Social Security would tend to have a lower WEP PIA, a lower proportional PIA, and a lower monthly benefit difference between the two formulas than a medium-scaled worker with covered earnings at midcareer or late career. This example indicates that the WEP PIA and proportional PIA amounts depend on the timing of noncovered employment, as well as earning levels from both covered and noncovered employment. Administration and Improper Payments The current-law WEP and the proportional formula differ not only in benefit calculation, but also in administration and associated costs. SSA's ability to administer the current WEP depends in large part on the type of noncovered employment on which a beneficiary's pension is based. For most federal retirees and survivors, SSA relies primarily on noncovered pension data matched from the Office of Personnel Management (OPM). However, for state or local retirees and certain retirees with foreign pensions, SSA relies primarily on beneficiaries to self-report noncovered pension amounts. Based on the information matched and provided, SSA determines whether and to what extent to apply the WEP. Unreported state and local government pensions lead to improper payments. According to SSA, WEP has been a leading cause of computational errors related to overpayments. For FY2013 through FY2017, WEP accounted for 63% of reported computation overpayment errors, and average overpayments related to WEP totaled approximately $520 million annually. In contrast, the proportional formula is applied based on covered and noncovered earnings records, which are reported to SSA on Internal Revenue Service (IRS) Form W-2. Without other provisions, benefits based solely on the proportional formula would likely have fewer errors compared to benefits computed with the current-law WEP formula. Notification to Beneficiaries The annual Social Security statements that SSA makes available to all eligible workers provide benefit estimates based only on covered employment, with no estimates of the WEP adjustment because SSA is not provided with information on receipt of noncovered pensions until an individual self-reports this benefit when applying for Social Security. Because of this limitation, beneficiaries have argued that they were not given sufficient notice of how much their benefits would be reduced due to the WEP. To address this issue, the Social Security Protection Act of 2004 ( P.L. 108-203 ) requires state and local government employers to disclose the WEP's effect to affected employees hired on or after January 1, 2005. SSA also responded to those communication issues by inserting a description of the WEP into the statement beginning in 2007. However, communication challenges remain. The statement provides no estimates of the current WEP adjustment. The WEP adjustment is difficult to estimate without information on noncovered pensions, which is generally not available until the worker is entitled to such pension at a later date. Compared to the current WEP, the estimate of noncovered earnings used in the proportional formula and the corresponding proportional PIA would be relatively easier to include in the statement. The proportional PIA estimate would have to be based on certain assumptions regarding future employment type, but it would not require noncovered pension information. Legislative Proposals Based on the Proportional Formula Proposals in the 1980s 1981 In 1981, proposals to address Social Security benefits for individuals receiving pensions from noncovered employment were discussed as part of broad reform efforts to address Social Security's financing issues, which were a major concern at the time. Some of the proposals called for worker PIA computations to use both covered and noncovered earnings, and for the PIA based on combined earnings to then be reduced by the ratio of noncovered earnings to combined earnings. This method is commonly referred to as the proportional formula , as discussed earlier in this report. This proposal was recommended by the National Commission on Social Security and included in Section 301 of H.R. 3207 , the Social Security Amendments of 1981 as introduced in the 97 th Congress. Other proposals called for a modified benefit formula that would change the first replacement factor in the regular benefit formula for workers with pensions based on noncovered work, which is similar to current law. For example, a May 1981 Reagan Administration proposal would have substituted the 90% replacement factor in the regular benefit formula with a 32% replacement factor for affected beneficiaries. The proposal would have guaranteed that the Social Security benefit reduction could not exceed one-half of the noncovered pension. 1983 In January 1983, the National Commission on Social Security Reform (NCSSR, better known as the Greenspan Commission) recommended eliminating the windfall portion of benefits for individuals who received a pension based on noncovered employment. The two methods discussed above were suggested: (1) the proportional formula based on covered and noncovered earnings, and (2) the modified benefit formula, substituting the 90% replacement factor with 32%. In the same year, SSA offered comments on the two methods. The agency indicated that the proportional formula would be the most conceptually appropriate, but would require SSA to maintain detailed records on workers' noncovered earnings in a manner comparable to the current covered earnings record operations, which would have required extensive data reporting, maintenance, and correction processes, and could likely not have been done with limited cost at that time. In contrast, SSA indicated the modified benefit formula based on the replacement factor would achieve the proportional formula's approximate results and be vastly easier to administer. SSA also recommended lowering the 90% replacement factor to 61% (the midpoint between the 90% factor and the 32% factor), as the 32% replacement factor would overadjust for the windfall. In March 1983, Congress incorporated the NCSSR's recommendations (with some modifications), along with additional provisions to resolve the remaining long-range deficit, into the Social Security Amendments of 1983 ( P.L. 98-21 ). The conference agreed that the 90% replacement factor in the regular benefit formula would be substituted with a 40% replacement factor (phased in over five years), as in current law. Proposals from 2004 to Present Since 2004, various bills have been introduced to replace the current WEP formula with the proportional formula based on both covered and noncovered earnings. Partly because all covered and noncovered earnings have been reported to SSA on Form W-2 since 1978, sufficient earnings records are now available to apply the proportional formula. Thus, a previous major area of concern for administering a proportional formula has been alleviated. Legislative proposals based on the proportional formula usually address two essential questions: (1) whether the proportional formula would be applied to beneficiaries affected by the current WEP; and (2) how to treat beneficiaries who would receive a lower benefit under the proportional formula compared to current law. For the first question, proposals either apply the proportional formula to all current and future affected beneficiaries, or apply the proportional formula only to certain future beneficiaries and provide an additional monthly benefit (usually referred to as a rebate ) to those affected by the current WEP. For the second question, some proposals include a no-benefit-cut provision such that the beneficiary would receive a benefit based on the higher of the current WEP formula and the proportional formula. For example, S. 113 and H.R. 2797 in the 112 th Congress would have applied the proportional formula to all beneficiaries (both current and future beneficiaries) after 1985 and provided a no-benefit-cut or hold harmless provision to beneficiaries who had worked in noncovered positions prior to one year after the bill's enactment. In a somewhat different approach, H.R. 3934 and H.R. 4540 in the 116 th Congress would apply the proportional formula to beneficiaries becoming eligible after a certain date, such as December 31, 2021; provide a rebate to beneficiaries affected by the current-law WEP; and mandate a no-benefit-cut provision for some or all future beneficiaries. The above two bills introduced in the 116 th Congress also include provisions to require SSA to show noncovered as well as covered earnings records on Social Security statements and to require studies on ways to facilitate data exchanges between SSA and state and local governments to improve current-law WEP administration.