RENT SEEKING IN ELITE NETWORKS

Transcription

1 RENT SEEKING IN ELITE NETWORKS HASELMANN, R., SCHOENHERR, D. & VIG, V. (2018) Réka Blazsek 20 November 2018

2 RESEARCH FOCUS: EFFECTS OF SOCIAL CAPITAL Bright side: mitigates informational frictions reduces adverse selection & moral hazard social learning Dark side: distorts markets self-serving interest groups, extractive institutions This papers studies the role of elite social networks in credit allocation in Germany Evidence for preferential treatment by connected bankers Inefficient allocation: lower returns on loans, extra funds paid out to CEOs Rent-seeking is universal but methods vary

3 SETUP: BUSINESS NETWORKS IN GERMANY Service club organization across Germany with local branches Objective: to maintain its reputation as an elite network Membership: invitation only; high professional qualification and social standing are required, e.g. local business, professional and political leaders, incl. bankers One member per industry Weekly social gatherings

4 EMPIRICAL STRATEGY: DATA Time period: Network data: Membership info on corporate and bank CEOs from the German credit register 841 enter an existing club during the sample period or participate in one of 91 new club formations 573 club bankers (241 private; 268 state; 64 cooperative) Loan and balance sheet data: from the Deutsche Bundesbank that records loans of at least 1 million; quarterly loan observations Matched dataset: Loan-level data with accounting information for 741 firms; firm-year observations

5 Lending volume: EMPIRICAL STRATEGY: REGRESSION SPECIFICATION I!"#(!"%&') )*+ = - *+ + - )* + / 1&#2"34 )* %5672 *+ + 8 )*+!"#(!"%&') )*+ : changes in total financing received by firm j from bank i at time t - *+ : time-series variation in firm j s demand for credit - )* : average level of lending between bank i and firm j 1&#2"34 )* : 1 if firm j and bank i belong to the same club %5672 *+ : 1 from the year when firm j enters a club A quarter-by-quarter comparison of the volume of loans granted by ingroup and out-group banks to the same firm

6 EMPIRICAL STRATEGY: REGRESSION SPECIFICATION II Changes in the share of in-group lending volume: "#$%&'( )&*#+ ( ),&,*) )&*#+.,= 0, , + 9 "., May eliminate an upward bias estimating 2 if firms substitute borrowing

7 EMPIRICAL STRATEGY: REGRESSION SPECIFICATION III Loan performance:!"# $% = ' $ + ' % + ) +,-./01 $% + 2 $%!"# $% : realized return on loans after interest payments, defaults and recovery rates +,-./01 $% : 1 if loan from an in-group bank ' % : firm fixed effects ' $ : bank fixed effects

8 RESULTS I: BANK LENDING AND FIRM BORROWING CHANNEL Significant increase in in-group lending, while no increase in outgroup lending Firm-after fixed effects: the same firm with both in-group and out-group borrowing experiences higher increase in in-group lending!

9 RESULTS II: SHARE OF IN-GROUP LENDING pp increase in the share of in-group lending after joining a club Rise in in-group lending following entry from 13 to 22%

10 RESULTS III: RETURN ON LOANS (1/2) Value-weighted portfolio: the same bank s in-group portfolio generates a return 3.49 pp lower than its out-group portfolio No significant differences in observable loan characteristics! Comparing returns of in-group and out-group banks from lending to the same firm, in-group firms generate 2.37 pp lower ROL on average

11 Differences in recovery rates conditional on default: The share of in-group lending is 28.82% higher when the firm defaults compared to non-default states, while lending to nonmember firms close to default decreases by 16.61%! Evidence for preferential treatment: excess continuation RESULTS III: RETURN ON LOANS (2/2)

12 ADDITIONAL TESTS Bank ownership: do the inherent differences in the governance of state-owned and private banks create different incentives for bank CEOs? Does increased competition discourage cronyism? Career concerns of older vs younger bankers Deployment of funds: how do firms use the extra financing? Investment to asset ratio falls after entry to a club The extra financing is likely to be used to increase liquidity position & to pay out funds to the owners! Though unobserved in the data, this may partly uncover bankers incentives in prefential lending.

13 CONCLUSION Evidence for the distortive effects of elite networks in the form of misallocation of credit Prefential treatment of connected bankers: excess continuation of financing Significantly lower return on loans; no new investments Welfare implications, adverse effects on economy hard to estimate Rent-seeking and cronyism are universal phenomena Subtler in well-developed countries with stronger institutions Policy implications? Increase reputation costs; strengthen checks and balances within banks