A Fistful of Dollars: Lobbying and the Financial Crisis1

Using detailed information on lobbying and mortgage lending activities, we find that lenders lobbying more on issues related to mortgage lending (i) had higher loan-to-income ratios, (ii) securitized more intensively, and (iii) had faster growing portfolios. Ex-post, delinquency rates are higher in areas where lobbyist' lending grew faster and they experienced negative abnormal stock returns during key crisis events. The findings are robust to (i) falsification tests using lobbying on issues unrelated to mortgage lending, (ii) a difference-in-difference approach based on state-level laws, and (iii) instrumental variables strategies. These results show that lobbying lenders engage in riskier lending.

Abstract

Using detailed information on lobbying and mortgage lending activities, we find that lenders lobbying more on issues related to mortgage lending (i) had higher loan-to-income ratios, (ii) securitized more intensively, and (iii) had faster growing portfolios. Ex-post, delinquency rates are higher in areas where lobbyist' lending grew faster and they experienced negative abnormal stock returns during key crisis events. The findings are robust to (i) falsification tests using lobbying on issues unrelated to mortgage lending, (ii) a difference-in-difference approach based on state-level laws, and (iii) instrumental variables strategies. These results show that lobbying lenders engage in riskier lending.

I. Introduction

On December 31, 2007, the Wall Street Journal reported that Ameriquest Mortgage and Countrywide Financial, two of the largest mortgage lenders in the nation, spent respectively $20.5 million and $8.7 million in political donations, campaign contributions, and lobbying activities from 2002 through 20062 The sought outcome, according to the article, was the defeat of anti-predatory lending legislation. In other words, timely regulatory response that could have mitigated reckless lending practices and the consequent rise in delinquencies and foreclosures was shut down by some mortgage lenders. Such anecdotal evidence suggests that the political influence of the financial industry contributed to the 2007 mortgage crisis, which, in the fall of 2008, generalized in the worst bout of financial instability since the Great Depression.3 However, formal analysis of these assertions has so far remained scant.4

To the best of our knowledge, this is the first study to examine empirically the relationship between lobbying by financial institutions and mortgage lending in the run-up to the financial crisis. We construct a unique dataset combining information on mortgage lending activities and lobbying at the federal level by the financial industry. By going through individual lobbying reports, we identify lobbying activities on issues specifically related to rules and regulations of consumer protection in mortgage lending, underwriting standards, and securities laws (henceforth, the “specific issues”).5

The paper focuses on the mortgage lending behavior and performance of financial institutions. First, we analyze the relationship between lobbying and ex-ante characteristics of loans originated. We focus on three measures of mortgage lending: loan-to-income ratio (which we consider as a proxy for lending standards), proportion of loans sold (measuring recourse to securitization), and mortgage loan growth rates (positively correlated with risk-taking6). Next, we analyze measures of ex-post performance of lobbying lenders. In particular, we explore whether, at the Metropolitan Statistical Area (MSA) level, delinquency rates – an indicator of loan quality - are associated with the expansion of lobbying lenders’ mortgage lending. We also carry out an event study during key episodes of the financial crisis to assess whether the stocks of lobbying lenders performed differently from those of other financial institutions.

Our analysis establishes that financial intermediaries’ lobbying activities on specific issues are significantly related to both their mortgage lending behavior and their ex-post performance. Controlling for unobserved lender and area characteristics as well as changes over time in the macroeconomic and local conditions, lenders that lobby more intensively (i) originate mortgages with higher loan-to-income ratios, (ii) securitize a faster growing proportion of loans originated; and (iii) have faster growing mortgage loan portfolios. Our analysis of ex-post performance comprises two pieces of evidence: (i) faster relative growth of mortgage loans by lobbying lenders is associated with higher ex-post default rates at the MSA level in 2008; and (ii) lobbying lenders experienced negative abnormal stock returns during the main events of the financial crisis in 2007 and 2008.

We perform a number of tests to mitigate omitted variables and reverse causality concerns. First, we conduct falsification tests by exploiting information about lobbying on financial issues that are unrelated to mortgage lending and securitization. Next, we adopt a difference-in-difference strategy to test whether the characteristics of mortgage loans originated by lobbying lenders respond differently to the introduction of anti-predatory lending laws at the state level, than those originated by other lenders. Finally, we adopt instrumental variable strategies using as instruments the lags of explanatory variables, and the distance between the headquarters of the financial institution and Washington, D.C., which is exogenous and proxies for the cost of lobbying. The main findings are robust to these alternative identification strategies.

Our findings indicate that lobbying is associated ex-ante with more risk-taking and ex-post with worse performance. This is consistent with several explanations, including a moral hazard interpretation whereby lenders take up risky lending strategies because they engage in specialized rent-seeking and expect preferential treatment associated with lobbying.7 Such preferential treatment could be a higher probability of being bailed out, potentially under less stringent conditions, in the event of a financial crisis.8 Another source of moral hazard could be “short-termism”, whereby lenders lobby to create a regulatory environment that allows them exploit short-term gains.9 Such distortions have been claimed to be related to risk-shifting in financial markets. Under the moral hazard interpretation, misallocation of resources can occur and it might be socially optimal to curtail lobbying or use public oversight to realign incentives.

Yet, other explanations are also consistent with our results and they might entail radically different policy conclusions. First, “bad” lenders could lobby more to mimic “good” lenders and choose riskier lending strategies ex ante resulting in worse outcomes ex post. Second, lobbying lenders may specialize in catering to borrowers with lower income levels and originate mortgages that appear riskier ex ante, with a higher incidence of default in a downturn. In this case, our findings would not necessarily indicate lower credit standards but capture the specialization of the lender. Third, overoptimistic lenders may lobby more intensively against a tightening of lending laws to exploit expected profit opportunities because they underestimate the likelihood of adverse events.10 As opposed to the moral hazard interpretation, under these explanations, it is possible that financial institutions lobby to reveal information or promote innovation rather than engage in rent-seeking.

While these explanations cannot be definitely ruled out, various tests suggest that they may be less likely to be valid. These tests consist of the inclusion of lender and time-varying area fixed effects; explicit controls for specialization (e.g. whether the lender is subprime, or is regulated by HUD); falsification tests based on lobbying for financial issues unrelated to mortgage lending and securitization; regressions uncovering a differential effect of lobbying on ex-ante lending standards after 2004, when important regulatory changes affecting securitization and loan standards took place; and regressions showing a differential effect of lobbying on ex-ante lending characteristics and ex-post performance for larger lenders, in line with “too-big-to-fail” arguments.

The results imply that lending behavior is to some extent affected by politics of special interest groups. They provide suggestive evidence that the political influence of the financial industry might have the potential to have an impact on financial stability.11 However, it should be recognized that it is hard to distinguish whether it is rent-seeking or information-revealing that drives lobbying by the financial industry, hence policy implications should be taken cautiously.

The rest of the paper is organized as follows. Section II discusses the related literature. Section III outlines the empirical strategy. Section IV describes the dataset. Section V presents the results and Section VI concludes.

II. Related Literature

Since the pioneering work by Krueger (1974), rent seeking has been identified as a key activity of economic agents in market economies. Lobbying – broadly defined as a legal activity aiming at changing existing rules or policies or procuring individual benefits – is a common form of rent-seeking activity in developed countries.12 Building upon the private-interest theories of regulation (Stigler, 1971, and Becker, 1983), research on lobbying has developed into two broad strands: studies that focus on the relationship between lobbying activities and specific policies (see, for instance, Grossman and Helpman, 1994, Goldberg and Maggi, 1999, and Ludema, Mayda, and Mishra, 2009, for the case of trade policy, Facchini, Mayda and Mishra, 2008, for the case of immigration policy, and Kroszner and Stratmann, 1998, for financial services) and those that aim to explore the consequences of rent-seeking activity by special interest groups for firm-specific economic outcomes (see, for example, Bertrand et al., 2004, and Claessens et al., 2008). Issues specific to banking and finance have been studied by, among others, Kroszner and Strahan (1999), who show that special interest theory can explain the design and timing of bank regulation in the U.S.; and Kwahja and Mian (2005), who find that in Pakistan politically-connected firms obtain exclusive loans from public banks and have much higher default rates. Our study, focusing on lobbying and lending behavior, fits more closely in the second strand.

Our paper is also related to the emerging literature on the current crisis. This literature has characterized the evolution of lending standards and the potential contribution of distorted incentives in affecting the supply of credit, but has so far ignored the role of political economy factors. Mayer, Pence and Sherlund (2009) show that subprime lending grew extremely fast between 2001 and 2006, and that no-documentation, no down-payment loans represented a large share of these loans. Mian and Sufi (2008) analyze the contribution of subprime lending to the expansion of mortgage credit and its impact on default rates, and show that the expansion in mortgage credit to subprime zip codes is closely correlated with the increase in securitization, a finding consistent with distorted incentives in mortgage lending. Keys et al. (2009) provide microeconomic evidence of moral hazard associated with securitization of high-cost mortgages. Dell’Ariccia, Igan, and Laeven (2008) provide evidence that areas in which lenders relaxed lending standards more also experienced larger increases in subprime delinquency rates, and that the relaxation of lending standards was associated with the recent entry of large lenders. Regarding the role of short-termism, there is, so far, no consensus on whether distortions in compensation contracts contributed to excessive risk-taking, with some positive evidence (Agarwal and Wang, 2009; Cheng, Hong, and Scheinkman, 2009) being matched by negative evidence (Fahlenbrach and Stulz, 2009).

Overall, there remains scarce evidence in the literature on the political economy of the current financial crisis. Igan and Landoni (2008) study the relationship between anti-predatory lending laws and campaign contributions and show that contributions increase after a law comes into effect. Mian, Sufi and Trebbi (forthcoming) focus on the consequences of financial crisis and show that constituent and special interests theories explain voting on key bills in 2008. In contrast to these papers, we study the role of political economy factors in shaping lending standards during the credit boom and their impact on loan outcomes during the crisis.

III. Empirical Approach

In this section, we first lay out some basic relationships between lenders’ lobbying and lending to motivate the empirical specification. Next, we describe the empirical strategies employed in the paper.

A. Lobbying and Loan Characteristics

Framework

We consider a simple framework relating lobbying to loan characteristics. A lender i among a set of n lenders can lobby to influence the policymaker or to credibly signal information on the mortgage loan market.13 A given contribution level lobbyingi (pol) is chosen by lobbyist i to maximize his welfare, taking the contribution schedules of other lobbyists as given, and anticipating that the policymaker chooses the policy pol:

lobbyingi(pol)=λBi+νCi+ϑlobbyingi(pol)+γpol+ηi(1)

where lobbyingi is either a dummy variable equal to 1 or the lobbying expenditures if a firm lobbies and equal to zero otherwise; the contribution schedules of other lobbyists are summarized in the vector lobbying−i (pol); Bi is a vector of lender-specific benefits of lobbying; Ci is the cost associated with lobbying which we assume to be exogenous and ηi is an error term. 14

In response to lobbying activities of lenders, the policymaker chooses a policy level that maximizes his welfare.15 In equilibrium, policy depends on lobbying activities of all agents:

pol=αlobbyingi+βlobbyingi(2)

We assume that characteristics of mortgage loans originated by lender i - including ex-ante characteristics, such as the loan-to-income ratio and the probability of securitization, as well as ex-post characteristics, such as delinquency rates – are related to (i) a set of average borrower characteristics Zi, (ii) lender characteristics Xi, (iii) policies, and (iv) lobbying expenditures:

loani=ϕZi+φXi+μpol +δlobbyingi+νi(3)

where loani is a vector of average loan characteristics of lender i, and νi is a residual. Combining with equation (2) leads to the following equation in which lobbying is associated with loani both directly (δ) and indirectly through changes in policies (μα):

loani=ϕZi+φXi+(μα+δ)lobbyingi+εi(4)

where εi is an error term capturing unobserved factors influencing loan characteristics.16

Possible interpretations

Lobbying could be associated with loan characteristics for several reasons. First, lobbying could affect loan characteristics directly if lenders lobby the policymaker because they expect preferential treatment – for example, a higher probability of being bailed out in the event of a financial crisis, or a lower probability of scrutiny by bank supervisors (coefficient δ in equations (3) and (4)). This in turn could lead to moral hazard and induce lenders to originate loans that would appear riskier ex ante.17 Moreover, assuming all else equal, these loans would have a higher probability of default ex post.

In another form of preferential treatment, lobbying buys access to policymakers. Such access could increase lender’s franchise value by enhancing its reputation and providing publicity. In that case, however, there is little reason to expect lobbying lenders to make riskier loans and have higher default rates especially if enhancing franchise value is linked to long-term value maximization.

Lobbying could also be indirectly associated with loan characteristics through its potential effect on the regulatory environment (coefficient μα in equation (4)). Various interpretations, with different implications for the sign of the relationship between lobbying and lending, can be captured through this channel.

  • Lenders lobby to prevent a tightening of lending laws that may reduce the benefits associated with short-termist strategies emphasizing short-term gains over long-term profit maximization. Such a moral hazard motivation for lobbying would result in more risk-taking ex ante and worse performance ex post.

  • Owing to a genuine and systematic underestimation of default probabilities, overoptimistic lenders could lobby to prevent a tightening of lending laws, and, would take more risks ex ante and experience higher default rates ex post, holding everything else equal.

  • Lenders specializing in risky market segments may lobby to signal their superior information on lending opportunities, thereby preventing tighter regulation that would limit growth in these segments. Then, lobbying lenders would originate loans that appear to carry more risk, but, holding other factors constant, these loans would not be expected to underperform other lenders’ loans ex-post. However, if one assumes that the risky segments are disproportionately hit harder by shocks, one could expect to observe worse performance of specialized lender loans.

  • Lenders that are able to benefit from lax regulations of mortgage lending – possibly because they are better at screening borrowers – would simultaneously lobby against bills aiming at tightening lending laws and choose seemingly more lax lending standards than other lenders. In that case, they may appear to originate riskier loans but ex-post outcomes would not necessarily be worse if these “good” lenders account for the risks properly.

  • It is also possible that lenders lobby to tighten regulations, rather than to relax them, in order to restrict entry by others, that is, to prevent competition. Then, one would observe lobbying lenders adopting safer lending strategies, not riskier ones. Hence, there would be little reason to expect these loans to be of lower quality ex post.

  • “Bad” lenders may mimic the lobbying behavior of good lenders to fool the policymaker or because they have a higher probability of being in need of preferential treatment owing to lower capacity to manage and absorb risk when hit by a shock. In this case, intensive lobbying activity would be associated with riskier loans ex ante and worse outcomes ex post.

In sum, an association between lobbying behavior and loan characteristics could arise for a variety of reasons (see text table for a summary). The sign of the estimated coefficient between lobbying and loan characteristics could, however, help discriminate between some of these possible interpretations.

Expected Signs of the Relationship between Lobbying and Lending

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Notes: Ex ante, + (-) denotes lobbying being associated with higher (lower) risk taking. Ex post, + (-) denotes lobbying being associated with worse (better) outcomes.

B. Empirical Specifications

Our empirical strategy consists of alternative specifications based on equation (4). First, we analyze the relationship between lobbying and the ex-ante characteristics of loans originated (the loan-to-income ratio; the proportion of loans sold; the growth rate of loans originated). Second, we explore the relationship between lobbying and ex-post loan outcomes (delinquency rates; stock returns during the crisis). Endogeneity concerns are addressed through falsification tests, instrumental variables, and difference-in-difference strategies.

Ex-ante loan characteristics

First, we estimate the following panel equation:

yimt=α+βli+λZimt+vm+πt+vm*πt+εimt(5)

where yimt is a measure of loan characteristics for lender i, in MSA m during year t. li is a dummy for lenders that lobby the federal government for specific issues related to consumer protection in mortgage lending and securitization.18 Zimt denotes a set of control variables at the lender-MSA level. vm and πt denote a set of MSA and year fixed effects respectively. vm * πt captures the effect of all MSA-time varying factors, which are constant across lenders. The parameter of interest is β, which captures time-invariant differences in mortgage loan characteristics between lenders that lobby and lenders that do not lobby. Second, we estimate the following panel equation:

yimt=α+δ(lnLOBAM)it1+si+vm+πt+vm*πt+λZimt+εimt(6)

where outcome variables are the same as in equation (4), (ln LOBAM)it−1 is the logarithm of the amount of lobbying expenditures by lender i during year t − 1.19 si denotes a set of lender fixed effects which capture the effect of all lender-specific time-invariant loan characteristics. The preferred specification includes lender, MSA, year effects and MSA*year interactions; lobbying expenses only change at the lender-year level and there is little reason to expect a lender’s lobbying at the national level to impact its lending behavior differently from one MSA to the other, hence lender*year and lender*MSA interactions are not included. The effect of lobbying on lending behavior is identified based on the within-lender correlation over time between lobbying expenditures and loan characteristics.

Our main variable capturing ex-ante characteristics is the loan-to-income ratio (LIR) averaged at the lender-MSA level. This measure is a simplified version of a commonly used indicator, debt-to-income ratio, to determine whether a borrower can afford a mortgage loan. Lenders usually require that mortgage payments cannot exceed a certain proportion of the applicant’s income.20 As the maximum proportion allowed increases, the burden of servicing the loan becomes harder and the default probability potentially increases. We compute the LIR as a proxy for such limits required by the lender and interpret increases in this ratio that are not explained by lender and location characteristics or time fixed effects as a loosening in lending standards.

In addition, we use as alternative dependent variables (i) the proportion of mortgages securitized and (ii) annual growth rate in the amount of loans originated. Recourse to securitization is considered to weaken monitoring incentives; hence, a higher proportion of securitized loans can be associated with lower credit standards (see Keys et al, 2009, for evidence that securitization leads to less monitoring and worse loan performance). Next, fast expansion of credit could be associated with lower lending standards for several reasons. For example, if there are constraints on training and employing loan officers, increased number of applications will lead to less time and expertise allocated to each application to assess their quality (see Berger and Udell, 2004). Or, in a booming economy, increasing collateral values will increase creditworthiness of intrinsically bad borrowers and, when collateral values drop during the bust, these borrowers are more likely to default (see Kiyotaki and Moore, 1997). Alternatively, competitive pressures might force lenders to loosen lending standards in order to preserve their market shares.

Ex-post performance

To evaluate ex-post loan performance, we analyze delinquency rates in 2008 and abnormal stock returns during key events of the financial crisis.

Delinquency rates

Our data on delinquency rates are at the MSA level (see Section IV); so we relate this variable to the growth of lobbying lenders’ market share in the MSA during 2000-06. This variable measures the expansion of mortgage loans by lobbying lenders relative to the expansion of such loans by all lenders during the period of interest.21 Specifically, we estimate the following cross-sectional empirical model:

drm,2008=α+θgmsh¯m+μXm+ηZm+εm(7)

where drm, 2008 is the MSA level delinquency rate as of 2008, gmsh¯m is the average annual growth rate of the total market share of lobbying lenders in the MSA over 2000-06, Xm is a set of MSA characteristics and Zm is a set of mortgage loan characteristics and lender characteristics averaged at the MSA level. The coefficient of interest θ captures the partial correlation between delinquency rates and the growth rate of mortgage lending by lobbying lenders relative to non-lobbying competitors.

Event study

We conduct an event study analysis on stock returns of lobbying lenders following key dates of the financial crisis. We follow the methodology developed in recent studies assessing the value of political connections (Fisman, 2001; Faccio, 2005; and Fisman et al., 2006). Specifically, we perform an event study around dates of major events of the financial crisis and ask whether lenders who lobbied on the specific issues related to mortgage lending and securitization experienced abnormal stock market returns during the month the event took place. 22

We consider the following empirical specification:

Rie=α+βli+γXi+εi(8)

where Rie is the ex-dividend monthly return on firm i’s stock over the event period e, li is a dummy for financial institutions that lobby on the specific issues, Xi is a set of control variables, and εi is a residual.23 In addition to the simple stock return, we consider two measures of abnormal returns: (i) the mean-adjusted return, defined as the stock return of firm i adjusted for its mean over 2007-08; (2) the market- and risk-adjusted return defined as the stock return adjusted for the predicted return based on the CAPM.24

We consider major events of the crisis related to the pressure in short-term funding markets in 2007 and the collapse of major investment banks exposed to subprime products in 2008. The event dates are: (i) August 1-17, 2007 (ECB injection of overnight liquidity in response to problems in French and German banks); (ii) December 12, 2007 (coordinated injection of liquidity by major central banks to address short-term funding market pressures); (iii) March 11-16, 2008 (JP Morgan acquires Bear Stearns after Fed provides $30 billion in non-recourse funding; Fed expands liquidity provision); and (iv) September 15-16, 2008 (Lehman Brothers files for bankruptcy while AIG is bailed out).

Endogeneity

A potential problem is that the decision to lobby may be endogenous, in particular, as a result of omitted variables that are correlated with both loan characteristics and performance and the decision to lobby. For instance, lobbying lenders may have expanded credit faster in areas that experienced higher delinquency rates as a result of unobserved characteristics of their pool of borrowers during the boom period. In addition, there might be reverse causality, for example, lenders lobby because they originate risky loans under lax regulations and want to prevent tightening of laws.25

To address these concerns, and help interpret our results, we implement several empirical strategies, in addition to including fixed effects. First, we use falsification tests based on lenders’ lobbying on financial sector issues unrelated to those we identified as being crucial for the mortgage market (see Data Description). These tests provide evidence that lobbying in general is not a proxy for unobserved lender characteristics.

Second, we make use of difference-in-difference estimations exploiting state-level variation in lending laws to uncover whether the existence of anti-predatory lending laws at the state level have differential effects on the mortgage lending behavior of financial intermediaries that lobby relative to those that do not lobby.26, 27 The hypothesis is that lobbying lenders were originating riskier loans than other lenders in the absence of anti-predatory lending laws. Therefore, when a law comes into effect at the state level they will tighten their loan terms more than other lenders to meet the minimum legal requirements. We estimate the following difference-in-difference panel equation:

yimt=α+βAPLst+δ(ln LOBAM)it1+ϕ(ln LOBAM)it1 APLst+γXmt+λZimt+si+vm+πt+εimt(10)

APLst is a dummy equal to one if there exists an anti-predatory lending law in state s, where MSA m is located, at time t.28 Xmt denotes a set of MSA-year varying controls. In regressions without lender fixed effects, the treatment group includes all lenders located in states without anti-predatory lending laws. In regressions with lender fixed effects, the control group includes the branches and subsidiaries of the same lender located in states that have not yet implemented anti-predatory lending laws and the treatment group comprises those that are located in states that have already implemented such laws. Hence, the control and treated groups are a priori very similar among many dimensions, including organizational and technological efficiency.

Third, we adopt an instrumental-variables strategy based on components of the cost of lobbying that do not directly affect loan characteristics and outcomes. Our instrument is the distance between a lender’s headquarters and Washington, D.C. combined with other variables described in Section V. Finally, we apply Generalized Method of Moments (GMM) using lags of explanatory variables as internal instruments in addition to the external instrument.

IV. Data Description

A. Mortgage Lending

Mortgage lenders are required to provide detailed information on the applications they receive and the loans they originate under the Home Mortgage Disclosure Act (HMDA). Enacted by Congress in 1975, HMDA data covers a broad set of depository and no depository financial institutions. Comparisons of the total amount of loan originations in the HMDA and industry sources indicate that around 90 percent of the mortgage lending activity is covered by the loan application registry. Our coverage of HMDA data is from 1999 to 2007 to match the lobbying database.

We collapse the data to MSA-lender level with 378 MSAs and almost 9000 lenders. Then, we construct our variables of interest: loan-to-income ratio at origination, loan securitization rates, mortgage loan growth rate, and the extent of lending activity by lobbying lenders at the MSA level.

B. Lobbying

Lobbyists in the U.S. - often organized in special interest groups - can legally influence the policy formation process through two main channels. First, they can offer campaign finance contributions, in particular through political action committees (PACs). These activities have received a fair amount of attention in the literature. 29 Second, they are allowed to carry out lobbying activities in the executive and legislative branches of the federal government. These lobbying activities, albeit accounting for about 90 percent of lobbyists’ expenditures (Table 1a), have in contrast received scant attention in the literature. Individual companies and organizations have been required to provide a substantial amount of information on their lobbying activities starting with the introduction of the Lobbying Disclosure Act of 1995. Since 1996, all lobbyists (intermediaries who lobby on behalf of companies and organizations) have to file semi-annual reports to the Secretary of the Senate’s Office of Public Records (SOPR), listing the name of each client (firm), the total income they have received from each of them, and specific lobbying issues. In parallel, all firms with in-house lobbying departments are required to file similar reports stating the total dollar amount they have spent (either in-house or in payments to external lobbyists). Legislation requires the disclosure not only of the dollar amounts actually received/spent, but also of the issues for which lobbying is carried out. Thus, unlike PAC contributions, lobbying expenditures of companies can be associated with very specific targeted policy areas. Finally, the reports must also state which chamber of Congress and which executive departments or agencies were contacted. Such detailed information is reported by roughly 9000 companies, around 600 of which are in the finance, insurance and real estate (FIRE) industry.

Table 1a.

Targeted Political Activity Campaign Contributions and Lobbying Expenditures

(millions of dollars)

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Source: Center for Responsive Politics.

C. Other Data

We supplement the information from the lobbying and HMDA databases with MSA-level and state-level data on economic and social indicators such as income, unemployment, population, and house price appreciation.30 We also obtain data on delinquent loans from Loan Performance, a private data company. The stock price return is computed using data from Compustat. Finally, information on the enactment of anti-predatory lending laws is from Bostic et al (2008).31

D. Construction of the Regressions Dataset

Matching Lobbying Firms to Lenders

The matching of the lobbying and HMDA databases is a tedious task that was performed in several steps (see Appendix). We use an algorithm that finds potential matches in HMDA of lenders in the lobbying database by searching for common words in the name strings. After the algorithm narrows down the potential matches of lobbying firms among the HMDA lenders, we go through the list one by one to determine the right match. Finally, we examine meticulously the corporate structure of the firms that appear in the lobbying database and that might be matched to particular HMDA lenders based on our algorithm. We create four lobbying identifiers reflecting several types of matches: (i) exact matches; (ii) matches to parent firm; (iii) matches to affiliated firms; and (iv) matches to subsidiaries. The lobbying variables used in the regressions combine these four variables.32

Identifying Lobbying Activity Targeted to the Mortgage Market

For identification purposes, it is important to distinguish between lobbying activities that are related to mortgage-market-specific issues from other lobbying activities. We first concentrate only on issues related to the five general issues of interest (accounting, banking, bankruptcy, housing, and financial institutions) and then gather information on the specific issues, which are typically acts proposed at the House or the Senate, that were listed by the lobbyists as the main issue for the lobbying activity.33 Then, we go through these specific issues one by one and determine whether an issue can be directly linked to restrictions on mortgage market lending. For example, H.R. 1163 of 2003 (Predatory Mortgage Lending Practices Reduction Act) and H.R. 4471 of 2005 (Fair and Responsible Lending Act), regulating high cost mortgages, are bills that we deem to be relevant to mortgage market lending. On the other hand, H.R. 2201 of 2005 (Consumer Debt Prevention and Education Act) and the Sarbanes-Oxley Act of 2002, although in general related to financial services, do not include any provisions directly related to mortgage lending and are not classified as mortgage-market-specific issues. After classifying all listed issues, we split the total lobbying expenditure by a lender into lobbying expenditure on specific and non-specific issues. In order to estimate lobbying expenditures associated with specific issues, we split lobbying expenditures evenly across issues. To be more specific, we first divide the total lobbying expenditure by the number of all general issues and multiply by the number of general issues selected. Then, we divide this by the total number of specific issues listed under the five general issues and multiply by the number of specific issues of interest.34

E. Summary Statistics

As shown in Table 1a, between 1999 and 2006, interest groups have spent on average about $4.2 billion per political cycle on targeted political activity, which includes PAC campaign contributions and lobbying expenditures. Lobbying expenditures represent by far the bulk of all interest groups’ money spent on targeted political activity (close to 90 percent). Expenditures by FIRE companies constitute roughly 15 percent of overall lobbying expenditures in any election cycle. Approximately 10 percent of all firms that lobbied during this time period were associated with FIRE.

Lobbying in the FIRE industry seems to be more prominent than it is in other industries. Figure 1 shows data on lobbying intensity (defined as lobbying expenditures per firm) by sector. Firms lobbying in the FIRE industry spent approximately $479,500 per firm in 2006 compared to $300,273 per firm in defense or $200,187 per firm in construction. Moreover, as shown in Figure 2, the lobbying intensity for FIRE increased at a much faster pace relative to the average lobbying intensity over 1999–2006. Finally, Table 1b shows that lobbying by financial intermediaries on issues related to mortgage lending and securitization totaled $475 million during 1999-2006 ($161 million was spent in 2005 and 2006 alone). Lobbying expenditures by lenders’ associations remained comparatively small ($76 million during 1999-2006).

Figure 1.
Figure 1.

Lobbying exp/firm, by sector, 2006

Citation: IMF Working Papers 2009, 287; 10.5089/9781451874327.001.A001

Figure 2.
Figure 2.

Evolution of lobbying lntensity (expenditures per firm) over time

Citation: IMF Working Papers 2009, 287; 10.5089/9781451874327.001.A001

Table 1b.

Lobbying by Financial Institutions and Lenders’ Associations

(millions of dollars)

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Similar inspection of the HMDA database reveals time trends indicating higher LIR and increased recourse to securitization (Figures 3 and 4). Our matching process ends up matching around 250 firms in the lobbying database to one or more lenders in the HMDA database, corresponding to roughly 40 percent of FIRE firms that lobby and 3 percent of HMDA lenders. In the final MSA-lender level dataset we use in the empirical analysis, the lenders that lobby comprise around 13 percent of the observations, reflecting the fact that lobbying lenders tend to be larger and/or more geographically diverse than those that do not lobby. In 2006, roughly 13 percent of lender-MSA pairs lobbied; and about 9 percent lobbied on regulations related to mortgage lending and securitization. Summary statistics on the variables used in the empirical analysis and the match rates are shown in Table 2. As a first impression, the only significant difference between lobbying lenders and the other lenders is that the former are typically much larger (in terms of assets) than the latter.

Figure 3.
Figure 3.

Lending Standards

Citation: IMF Working Papers 2009, 287; 10.5089/9781451874327.001.A001

Figure 4.
Figure 4.

Securitization

Citation: IMF Working Papers 2009, 287; 10.5089/9781451874327.001.A001

Table 2.

Summary Statistics

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V. Results

A. Empirical Analysis of Loan-to-Income Ratio

Table 3 presents the fixed-effects regression results based on equation (5) of the LIR of originated loans on a dummy variable for lenders lobbying on specific issues. The coefficient on this dummy variable is positive and statistically significant at the 1 percent level in all regressions. Loans originated by lenders lobbying on specific issues have higher LIR on average. This finding remains unaffected when controlling for observable MSA (column (2)) and lender-MSA characteristics (column (3)). Lender-MSA level control variables ensure that the estimated coefficient on the dummy for lobbying lenders does not reflect characteristics such as the size of the lender (proxied by log of assets), the market power of the lender in a particular MSA (proxied by its market share), or other factors proxying for observable and unobservable characteristics of a lender’s pool of applicants such as (i) whether the lender focuses on community development mortgages or has a brokerage-type business model (proxied by a dummy for HUD-regulated lenders), (ii) whether the lender specializes in subprime lending, and (iii) the average income of applicants of loans originated by the lender in a particular MSA. Moreover, the size of the coefficient increases as control variables are added to the regression suggesting that omitted variables at the MSA level and at the lender-MSA level may have resulted in attenuation bias.35 Adding MSA, year, and cross MSA-year fixed effects does not affect the magnitude or the significance of the estimated coefficients (columns (4) to (7)). This set of fixed effects confirm that our results do not reflect unobserved, either time-invariant or time-varying MSA characteristics, or time effects common to all MSAs. Importantly, MSA-year interactions in column (6) guarantee that the estimated effect is not biased due to, for example, the average quality of the pool of applicants at the MSA level.

Table 3.

Effect of Lobbying on Loan-to-Income Ratio

Dependent variable: Loan-to-income ratio at (lender, MSA, year) level

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Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. See text for details. Standard errors denoted in parentheses are clustered at the lender-MSA level. ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively.

The magnitude of the effect is not trivial. The estimated coefficient of 0.14 implies that the average LIR of mortgages originated is about 0.14 points higher for lobbying lenders than for other lenders. This is about 7 percent of the average LIR of 1.97 in the complete sample.

Table 4 reports regressions of LIR on lobbying expenditures. The coefficient on the lobbying amount is positive and significant at a 1 percent level for various sets of fixed effects and control variables. The advantage of using the level of lobbying expenditures relative to the dummy in Table 3 is that the time variation in lobbying amounts allows us to introduce lender fixed effects, and therefore to identify the coefficient of interest on the within dimension, in contrast to the results of Table 3 in which the coefficient of interest reflects systematic differences between firms. In specifications including lender fixed effects (columns (3) to (5)), the coefficient of interest therefore reflects a correlation over time between the LIR and the lobbying amounts for lobbying lenders only. Hence, any time-invariant lender-specific factors – such as a superior screening technology -affecting both the decision to lobby and lending standards are absorbed by the lender fixed effects. Another source of concern is that there may be shocks common to all lenders and we address this concern by introducing time dummies. Columns (2) to (5) show that the coefficient remains significant. Furthermore, columns (4) and (5) include MSA*year interactions controlling for time-varying local conditions faced by lenders.36

Table 4.

Effect of Lobbying Expenditures on Loan-to-Income Ratio

Dependent variable: Loan-to-income ratio at (lender, MSA, year) level

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Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. See text for details. Standard errors denoted in parentheses are clustered at the lender-MSA level.***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively.

The range of estimated coefficient suggests that a one standard deviation rise in lobbying expenditures is associated with a 0.02-0.11 points rise in LIR. This constitutes 1-5 percent of the average LIR of 1.97 in the complete sample.37

B. Falsification Tests

The estimated relationship between LIR and the lobbying decision may capture omitted factors that affect both the decision to lobby and the characteristics of loans originated. If the results are driven by omitted factors affecting the decision to lobby on financial sector issues in general, we would expect to obtain a similar result for lenders that lobby on financial sector issues that are unrelated to mortgage lending. To carry out the falsification exercise, we create a dummy variable for lenders lobbying on issues that are not related to mortgage lending and securitization, e.g., consumer credit and security of personal information, financial services other than mortgage lending, deposit insurance, anti-money laundering, etc. We repeat the regressions presented in Table 3 by adding the new dummy. Table 5 displays the results. We find that the dummy for lobbying on specific issues has a positive and significant coefficient while the dummy for lobbying on other issues has a negative and significant sign. These falsification tests further support the interpretation that the relationship between lobbying and mortgage lending behavior is not coincidental and is unlikely to be driven by omitted characteristics.

Table 5.

Effect of Lobbying on Loan-to-Income Ratio: Falsification Tests

Dependent variable: Loan-to-income ratio at (lender, MSA, year) level

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Lobbying on specific issues refers to laws and regulations related to financial and banking sector policies. See text for details. Lobbying on other issues is measured by total lobbying expenditures if the lender lobbies only for other issues, and zero otherwise. Standard errors denoted in parentheses are clustered at the lender-MSA level. ***, ** and * represent significance at 1, 5 and 10 percent, respectively.

C. Difference-in-Difference Estimations

We exploit the state-level and time-level variation in the existence of anti-predatory lending laws to uncover whether laws being in place have a differential effect on the mortgage lending behavior of lobbying lenders relative to those that do not lobby. As shown in Table 6, the coefficient on the interaction term between the dummy for an anti-predatory lending law and lobbying intensity is negative and significant at the 1 percent level in columns (2)-(4). This result is consistent with the hypothesis that lobbying lenders, at the margin, raise their lending standards more than other lenders, when anti-predatory lending laws are in place, according to the general formulation of equation (7). The result is robust to including lender, MSA and year fixed effects, and when we control for MSA-time, lender-time or lender-MSA-time level observable characteristics. In addition, the overall effect of an anti-predatory lending law being in place, evaluated at the average lobbying expenditures in the sample, is β+ϕ(ln LOBAM)¯<0. This suggests that LIR is lower in MSAs that belong to states with anti-predatory lending laws in place.

Table 6.

Effect of Specific Issues Lobbying Expenditures: Difference-in-Difference Strategy

Dependent variable: Loan-to-income ratio at (lender, MSA, year) level

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Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. Standard errors denoted in parentheses are clustered at the lender-MSA level. ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively.

D. Instrumental Variable Regressions and GMM

To further address endogeneity concerns, we develop an instrumental variable strategy. As discussed earlier, the concern is that lobbying on issues specific to mortgage lending may be correlated with unobserved lender-time or lender-MSA-time varying loan characteristics, which could bias our estimates. The within lender estimations reported in Table 4 partially address endogeneity bias, but only if the unobserved lender characteristics do not vary over time.

To address the identification issue in the regressions with lender fixed effects, we need an instrument that is both lender-specific and time-varying. The instrument we consider is a proxy for the cost of lobbying, which is likely to be correlated with lobbying and can arguably be assumed not to affect lending other than through lobbying. First, we construct the lender-specific component. A number of papers have shown that distance affects financial decisions both within countries (Petersen and Rajan, 1995), and across countries (Mian, 2006). Following this literature, we hypothesize that the cost of lobbying is an increasing function of the distance between the headquarters of a financial institution and Washington, D.C., and consider this distance as the first exogenous component of the cost of lobbying. Second, a time-varying component of the cost of lobbying is given by the rest of the world purchases of U.S. Treasury securities from the Flow of Funds Accounts published by the Federal Reserve. The idea underlying the instrument is that when capital inflows are high, the cost of capital (and the return on capital) is low, and therefore the opportunity cost of lobbying is low. Importantly, we expect neither the lender-specific nor the time-varying component of the instrument to be correlated with the unobservable determinants of lending.38 We multiply these two variables to obtain an instrument that is both lender-specific and time-varying.

Table 7 shows that the coefficient on lobbying expenditures remains highly significant in the second stage of the 2SLS when it is instrumented. However, the size of the coefficient increases dramatically which suggests that, indeed, the OLS estimate is biased downward. Table 7 also reports the first stage and suggests that the instrument is strong. The first-stage F-statistic is very high, with the p-value for the test of significance of excluded instruments equal to 0. The correlation between the instrument and the endogenous variable reflects the positive time-series relationship between lobbying expenditures and capital inflows.

Table 7.

Effect of Lobbying Expenditures on Loan-to-Income Ratio: Instrumental Variables

Dependent variable: Loan-to-income ratio at (lender, MSA, year) level

article image
Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. Lender lobbying expenditures on specific issues is instrumented by the interaction of distance of the lender’s headquarters to Washington, DC (lender-varying) and rest of the world’s purchases of US treasuries (time-varying). See text for details. Standard errors denoted in parentheses are clustered at the MSA level. ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively.

Table 8 reports the results from system GMM estimations. Lagged levels of lobbying expenditures (in addition to the external instrument in Table 7) are used as instruments in the difference equation whereas lagged differences are used in the level equations. Columns (1)-(5) implement the system GMM using alternative number of lags as instruments. The results support the finding that increase in lobbying expenses is associated with higher LIR. The estimated coefficient is statistically significant at the one percent level in all the specifications. The magnitude of the coefficient is higher than in Table 4, suggesting a negative correlation between the unobserved component of LIR and lobbying expenses in the OLS. Importantly, in all specifications, the Hansen’s test for overidentifying restrictions passes at the one percent significance level and the null hypothesis of no two-period serial correlation in the residuals cannot be rejected.

Table 8.

Effect of Lobbying Expenditures on Loan-to-Income Ratios – System GMM

Dependent variable: Loan-to-income ratio at (lender, year) level

article image
The data are collapsed at the lender-year level. Market share at the lender-year level is a weighted average of market shares at the lender-MSA-year level, with weights being the share of loans originated by a lender during a particular year in a given MSA. Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. See text for details. All specifications are estimated by system GMM. Lagged log lender lobbying expenditures on specific issues is treated as endogenous. Lagged levels (in the first difference equation) and lagged differences (in the levels equation) of this variable are used as internal instruments, whereas the external instrument is the same as in Table 5, i.e., the interaction of distance of the lender’s headquarter to Washington, DC (lender-varying) and rest of the world’s purchases of US treasuries (time-varying). Standard errors denoted in parentheses are clustered at the lender level ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively.

E. Evidence on Lobbying and Securitization and Mortgage Credit Growth

As discussed in Section III, the proportion of mortgage loans that are securitized is another potentially important indicator of the quality of mortgages originated by financial institutions. Table 9 shows that the proportion of mortgage loans securitized is positively correlated with lobbying expenditures within lenders. The result is robust to the inclusion of lender, MSA and year fixed effects and MSA*year interactions. In columns (4)-(6), we also show that the results are robust to instrumenting the lobbying variable.

Table 9.

Effect of Lobbying Expenditures on Proportion of Loans Sold

Dependent variable: Proportion of loans sold at (lender, MSA, year) level

article image
Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. In Columns (4)-(6), lender lobbying expenditures on specific issues is instrumented by the interaction of distance of the lender’s headquarters to Washington, DC (lender-varying) and rest of the world’s purchases of US treasuries (time-varying). See text for details. Standard errors denoted in parentheses are clustered at the lender-MSA level ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively.

A fast expansion of mortgage credit could also be associated with lower lending standards for reasons discussed in Section III. Table 10 shows that lobbying is positively correlated with the growth of mortgage loans. This result is significant at the 1 percent level in both the fixed effects and IV specifications, suggesting that lobbying lenders, through faster expansion of their mortgage loan portfolios, tend to lend more aggressively and potentially take bigger risks.

Table 10.

Effect of Lobbying Expenditures on Credit Growth

Dependent variable: Growth in amount of originated loans at (lender, MSA, year) level

article image
Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. In Columns (4)-(6), lender lobbying expenditures on specific issues is instrumented by the interaction of distance of the lender’s headquarters to Washington, DC (lender-varying) and rest of the world’s purchases of US treasuries (time-varying). See text for details. Standard errors denoted in parentheses are clustered at the lender-MSA level. ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively.

F. Lobbying and Delinquency Rates

So far, the evidence suggests that there exists a strong link between lobbying on issues related to mortgage lending and the characteristics of loans originated. In this section, we analyze the relationship between the relative growth of mortgage loans of lenders who lobby on the specific issues we identified and the ex-post average delinquency rate at the MSA level as of 2008, based on specification (7).39 We follow a conservative approach by clustering the error terms at the state level.

Regression results reported in Tables 11a and 11b show that delinquency rates in 2008 are significantly higher in MSAs in which mortgage lending by lobbying lenders has expanded relatively faster than mortgage lending by other lenders. This result is robust to (i) the inclusion of various MSA-level characteristics, including characteristics of the mortgage lending market such as the share of subprime loans and the number of lenders, (ii) the inclusion of state fixed effects to control for state-specific unobserved factors, and (iii) the exclusion of states in which the housing boom-bust cycle was more severe (California, Florida, and Nevada) to ensure that mortgage market outcomes of these three states are not driving the results. The estimated effect is economically significant: a one standard deviation increase in the relative growth of mortgage loans of lobbying lenders is associated with almost a 1 percentage point increase in the delinquency rate.

Table 11a.

Effect of Lobbying on Loan Delinquency Rates

Dependent variable: Delinquency rate in 2008 at (MSA, year) level

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Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. Large lenders are the top quartile of lobbying lenders (in terms of assets). ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively. Robust standard errors are in brackets.
Table 11b.

Effect of Lobbying on Loan Delinquency Rates: Instrumental Variables

Dependent variable: Delinquency rate in 2008 at (MSA, year) level

article image
Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively. Robust standard errors are in brackets.

To address endogeneity concerns, we perform two tests. First, as in the analysis of loan characteristics, we make use of a falsification test to show that expansion of mortgage lending by lobbying firms does not merely reflect unobserved lender characteristics correlated with lobbying activities in general. We find no statistically significant relationship between delinquency rates and the relative expansion of mortgage lending by lenders that lobbied on financial issues unrelated to securitization or consumer protection in mortgage lending. This suggests that lobbying by financial institutions is unlikely to be a general proxy for specific unobserved lenders’ characteristics that could be systematically correlated with delinquency rates (columns (4) and (5) in Table 11a).

Second, we develop an instrumental variable strategy to further address such omitted factors bias. As a first instrument, we consider the sum of the 1998 market share in the MSA of lenders who lobbied on specific issues, in which each lender’s initial market share is weighted by the distance between each lender’s headquarters and Washington, D.C. This instrument is valid if (i) the initial presence of a lender in a MSA is predetermined and is not correlated with the lending conditions that prevailed in this MSA in the following years; (ii) the distance between a lender’s headquarters and Washington, D.C. – a proxy for certain costs of lobbying – is uncorrelated with lending conditions in any specific MSA. The correlation between this instrument and the endogenous variable is negative potentially reflecting that a smaller initial market share coupled with low cost of lobbying results in faster subsequent growth of lobbying lenders in that area. We consider a second instrument defined in a similar way (initial market share weighted by the distance variable), but using instead the initial market share of lenders lobbying on financial sector issues that are not related to securitization and mortgage lending. The sign of the correlation between the instrument and the endogenous variable is positive probably because, in MSAs in which these other lenders have a larger initial presence, lenders lobbying on our issues of interest may intensify their lending activities and gain market share even more when these other lenders have a higher cost of lobbying.

Regression results are reported in Table 11b, and confirm the conclusions of our OLS estimations. When instrumenting the variable of interest, the coefficient increases significantly, suggesting that there might be an attenuation bias in the OLS estimates. In regressions combining the two instruments, the Hansen J tests accept the validity of the instruments. Furthermore, to allay concerns of weak instrument bias, we also make use of LIML estimator known to be more robust to weak instrument bias and confirm the 2SLS results.

G. Stock Price Returns during the Crisis

We conduct an analysis of financial institutions’ stock returns during major market events of the financial crisis to investigate the relationship between lobbying activities and ex-post lender stock price performance during the financial crisis. This analysis provides suggestive evidence on the perceived ex-post value of lobbying lenders portfolios during the financial panics of 2007 and 2008. In particular, we would not expect to find any significant abnormal returns if lobbying was not systematically related to the quality of mortgage loans originated by the lenders. Regression results are reported in Table 12. Our analysis indicates that financial institutions that lobbied on specific issues experienced negative abnormal returns during the major events of the financial crisis suggesting that these financial institutions were significantly more exposed, directly or indirectly, to bad mortgage loans.

Table 12.

Lobbying and Abnormal Stock Returns

article image
Mean-adjusted stock price return is the stock price return over the month of the event, adjusted for its mean over 2007-08.Market- and risk-adjusted return is the stock price return over the month of the event, adjusted for the predicted return based on a CAPM where the market portfolio is proxied by the stock price index of financial institutions in the S&P500.Market events: (1) August 1-17, 2007: suspension of redemptions on funds with subprime exposures; (2) Dec 12, 2007: Fed, ECB, SNB and Bank of Canada jointly announce measures to address short-term funding market pressures; Fed establishes Term Auction Facility (TAF); (3) March 11-16, 2008: JP Morgan acquires Bear Stearns after Fed provides $30 billion in non-recourse funding; Fed creates Term Securities Lending Facility (TSLF) and Primary Dealer Credit Facility (PDCF) to expand liquidity provision to wider group of counterparties; (4) September 15-16, 2008: U.S. Investment bank Lehman Brothers files for bankruptcy; U.S. authorities step in to rescue AIG.Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively. Robust standard errors are in brackets.

The coefficient of interest is statistically significant at conventional levels in all the specifications. Moreover, the estimated effect is very large. Using the estimated coefficient for the market and risk adjusted returns, lobbying financial institutions lost on average 6.7 percent more in value during the 2007 events than other financial institutions; and 16.6 percent more in value during the 2008 events. The differential loss of value is even more impressive during the Lehman failure: a 27 percent additional loss of value when returns are adjusted for the market correlation. The results suggest that these financial institutions were significantly more exposed to bad mortgage loans than other financial institutions.

Interestingly, the coefficient on the subprime lender dummy is insignificant in most regressions - and even positive in one specification – suggesting that the estimated coefficient does not merely reflect the effect of a specialization of the lender considered. Another proxy for specialization – the log of mortgage loans originated in proportion to total assets – does not alter our coefficient of interest, even though it has the expected negative sign.40 We also control for the log of assets of the lender as a proxy for size, but find no significant effect on abnormal stock returns.

H. Discussion of Results

To summarize, lobbying is associated ex ante with more risk-taking as measured by higher LIR, higher securitization and faster credit expansion. In addition, there is evidence that delinquency rates are higher in areas in which lobbying lenders expanded their mortgage lending more aggressively, and that these lenders had more negative abnormal returns during the key events of the financial crisis.

Taken together, these results are consistent with several of the explanations discussed in Section III. These include expectations of preferential treatment (e.g. a higher probability of being bailed out in the event of a financial crisis) or the desire to exploit high short-term gains associated with riskier lending strategies. Both bail-out and short-termism stories involve moral hazard elements. One piece of evidence supporting this story is that we find a stronger correlation between lobbying and ex-ante loan characteristics as well as ex-post performance for the largest lobbying lenders. Table 13, columns (1) and (2) show that the correlation between lobbying and LIR and between lobbying and proportion of loans sold is indeed stronger for lenders in the top quartile in terms of assets. Column (3) confirms that a similar result obtains for the relationship between the growth of the market share of lobbying lenders and ex-post delinquency rates. When the growth of market share for the subset of large lobbying lenders is introduced as an additional variable, the estimated relationship is even stronger.

Table 13.

Evidence Inconsistent with Alternative Explanations

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Lobbying on specific issues refers to lobbying on bills and regulations related to mortgage lending (such as consumer protection laws) and securitization. In columns (1) to (3), large lenders are the top quartile of lobbying lenders (in terms of assets). Standard errors denoted in parentheses are clustered at the lender-MSA level in columns (1), (2), (4), and (5) and at the state level in column (3). ***, ** and * represent statistical significance at 1, 5 and 10 percent, respectively.

Although other explanations without such elements cannot be ruled out, they tend to be somewhat less consistent with our analysis. We consider three alternative stories that could potentially explain the results: (i) bad lenders lobbying more, (ii) specialization, and (iii) overoptimism.

First, suppose that bad lenders, who make bad loans, lobby more. The objective of bad lenders, in other words, is to mimic the lobbying behavior of good lenders (who lobby to signal their superior information and to ensure that the regulations allow them to fully exploit such relative advantages or simply to shut down competition). Yet, bad lenders do not have the precise information on what issues the good lenders lobby for. So, they would lobby more in general and not particularly on issues related to mortgage lending. However, falsification tests discussed above (Table 5) suggest otherwise as we do not find lobbying on unrelated issues to be associated with more risk.

Second, lobbying lenders may be specialized in catering to riskier borrowers, e.g. borrowers with lower income levels or operate in areas with higher average property prices. In this case, we would expect lobbying to be associated with higher LIR, not necessarily indicating lower credit standards but signaling the specialization of the lender. This is also consistent with higher delinquency rates since riskier borrowers are more likely to default during a downturn. However, we include explicit controls, e.g., whether the lender is subprime or is regulated by HUD, as well as area and lender characteristics to capture such specialization effects. Moreover, inclusion of variables that could explain defaults at the MSA level, e.g., house price changes, and the instrumental variable strategy in the delinquency rate analysis suggest that the estimated effect does not capture unobserved shocks that may affect the probability of default in areas in which lobbying lenders expanded their activity more than others.

Third, and perhaps the most likely, alternative interpretation is that overoptimistic lenders may have underestimated the likelihood of an adverse event affecting the mortgage market more than other financial intermediaries did.41 Under this interpretation, these lenders would have lobbied to prevent a tightening of lending standards to exploit their better information on the market or to fully use their capacity at increasing the supply of mortgage loans. Such an interpretation based on overoptimism would also be consistent with lax lending and higher ex-post exposure of lobbying lenders to poorly performing pools of mortgage loans. However, our analysis shows that the relaxation of lending standards of lobbying lenders was even stronger in 2005 and 2006. In particular, we test whether the average LIR of loans originated by lobbying lenders significantly changed after 2004 (Table 13, columns (4) and (5)). We find that LIR for lobbying lenders increased significantly relative to their own sample average (column (4)), as well as relative to all lenders when year dummies are included in the specification (column (5)).42 This result implies that lobbying lenders relaxed their lending standards more than other lenders. It is not clear why lenders would have become even more overoptimistic during the years when signs of stress in the housing market were becoming visible.43

More generally, it is empirically extremely difficult to distinguish alternative stories of moral hazard and lobbying as an information dissemination mechanism. Ultimately, we do not know the exact activities on which lobbying expenditures are spent. While these alternative interpretations could produce observationally equivalent empirical evidence, policy implications are vastly different. Specialized rent-seeking for preferential treatment such as bail-outs could suggest curtailment of lobbying as a socially optimal outcome. Distorted incentives due to short-termism linking risky lending and lobbying could evoke public intervention in the design of executive compensation. If, however, lenders lobby to inform the policymaker and promote innovation, lobbying should be recognized as a socially beneficial channel to facilitate informed decision making.

VI. Conclusion

This paper studies the relationship between lobbying by financial institutions and mortgage lending. To the best of our knowledge, this is the first study documenting how lobbying may have contributed to the accumulation of risks leading the way to the current financial crisis. We carefully construct a database at the lender level combining information on loan characteristics and lobbying expenditures on laws and regulations related to mortgage lending (such as consumer protection laws) and securitization. We show that lenders that lobby more intensively on these specific issues have (i) more lax lending standards measured by loan-to-income ratio, (ii) greater tendency to securitize, and (iii) faster growing mortgage loan portfolios. Ex post, delinquency rates are higher in areas in which lobbying lenders’ mortgage lending grew faster, and, during key events of the crisis, these lenders experienced negative abnormal stock returns. These findings seem to be consistent with a moral hazard interpretation whereby financial intermediaries lobby to obtain private benefits, making loans under less stringent terms. Moral hazard could emerge because they expect to be bailed out when losses amount during a financial crisis or because they privilege short-term gains over long-term profits. Under such an interpretation, specialized rent-seeking and short-termism might justify reining in lobbying activities or public oversight of optimal contracts in the financial industry. Yet, it cannot be ruled out that lenders lobby to inform the policymaker and shocks out of their control lead to riskier lending and undesirable outcomes. Under this interpretation, lobbying by the financial industry can be an integral part of informed policymaking. With the caveat that empirical evidence cannot single out one interpretation as the true explanation, our analysis suggests that the political influence of the financial industry can be a source of systemic risk. Therefore, it provides some support to the view that the prevention of future crises might require weakening political influence of the financial industry or closer monitoring of lobbying activities to understand the incentives behind better.

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