Do lenders favor politically connected firms? Rent provision in an...

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Do lenders favor politically connected firms? Rentprovision in an emerging financial market - by

Asim Ijaz Khwaja and Atif Mian

Zeki Kocaata - Christopher Hols

October 29, 2015

Zeki Kocaata - Christopher Hols Do lenders favor politically connected firms? Rent provision in an emerging financial market - by Asim Ijaz Khwaja and Atif Mian



Research Questions

The paper tries to answer three research questions:

Research Questions1 Do Pakistani lending institutions favor firms that have

political connections?2 How does the political environment affect the rents of

politically connected firms?3 What are the economy-wide costs of these political rents?




Motivation

I Corruption is an economic illness leading to misallocation infunds and therefore to a substantial economic cost

I Important form of corruption: Rent-seeking through politicalcapital, i.e. politicians using their power in order to extractrents for themselves




Contribution

I Filled the gap in the literature, theoretical work on politicalrent seeking and corruption in general is done but theempirical literature on this topic was limited 10 years ago

I First papers to link political environment to rent seeking interms of bank lending




Identification set-up

I Pakistani micro-level loan data from 1996-2002, combine itpolitical election data to estimate the effect of politicalconnectedness on loan characteristics(credit access and priceof loan)

I Several settings of fixed-effectsI Test the effect of political strength on loan characteristicsI Check for alternative explanations (Social Lending and

Efficient Lending)




Results

I Political connected firms borrow 45% more and default 50%more often then regular firms

I This mainly driven by government banksI Political rents increase with the strength of the firm’s

politicianI The economy wide cost are between 0.3% and 1.9%




Evaluation

StrengthsI Huge Data setI Can estimate economic wide cost of this sort of corruption

WeaknessesI Hidden political connectedness is not taken into account (

brother of politician running a firm)I Pitfalls of fixed-effects




Institutional Setting

I Clientelism, rent-seeking, and corruption in PakistanI Ranked 126 out of 176 in the Transparency International

Corruption Perceptions IndexI High level of governmental turnoverI Government banks vulnerable to political influencesI Good candidate to study political connectedness




Data - Loans

I Data from 1996-2002 from the Credit Information Bureau(CIB) at the State Bank of Pakistan (SBP) including

I Credit position by lenders and quartersI Amount of loan outstanding by loan typeI Default amounts, litigations, write-offs and recoveries against

the loanI Geographical and personal information of the borrowers and

lenders




Data - Politicians

I Two relevant elections in 1993 and 1997I Party affiliation including winner and number of votesI Total number of registered voters




Summary Statistics

I 112,685 observations(loans) of 93,316 firmsI Government banks constitute 64% of all lendingI Mean loan size RS. 6.7 millionI Mean default rate 16.9%I Mean net return 93.46% ( loose -6.54% on every Rupee)I 23% of firms are politically connected (have a politician on

board) receiving 37% of overall lending




Methodology I

Two channels of preferential lending1 Access to credit (log. loan size)2 effective price of loan(rate of return...)

Cross-sectionalized specification:

Yij = αj + β1 × Politicali + γ1 × Xi + γ2 × Xij + εij




Methodology I

I Yij is one of the measures of preferential treatmentI Politicali is an indicator variable for whether a firm is

politically connectedI Xi are firm level controlsI Xij are loan type controlsI αj is a bank fixed effect

The coefficient of interest is β1




Methodology I

I Fixed-effects capture unobserved bank specificI Baseline regressionI Measure effect of connectedness to preferential lendingI Problem: omitted-variables biasI Avoid OV by using IV-procedure, for example market power of

firms




Results I




Comments on Specification I

I Omitted variable bias as mentioned beforeI Selection bias possibilityI Are the politicians hired to firms with specific characteristics?I Proposed solution: Use difference-in-differences set-up

exploiting time dimension and Firm fixed-effects ??




Methodology II

I Examine whether the same firm receives greater preferentialtreatment if it is politically connected while borrowing fromthe government compared with a private bank

Yij = αi +αj +β1×Politicali ×GOVj +γ1×Xij +γ2×Xij ×GOVj +εij

I GOVj is an indicator variableI β1 now is the difference-in-differences” estimate of politically

preferences




Methodology II

I Fixed-effects capture unobserved bank specific and unobservedfirm specific

I Government Bank Dummy controls for ownership of the bankand identifies difference




Results II




Comments on Methodology II

I Two possible drawbacks of using fixed effects:I Firstly, big loss of degrees of freedom leading to the possibility

of contaminated t-test inferences




Comments on Methodology II

Secondly, political connectedness variable with measurement error:I The Error-In-the-Variables asymptotic bias minimized by

maximizing total variation.I Fixed effects sucking up big variationI Upon reducing variation in controls, increase in measurement

errorI A barrier to establish causality




Methodology III

I Include the time dimension, test whether preferential lendingincreases after politician wins elections

Yijt = αij + αt + β1 × WINit × GOVj + β2 × WINit + εijt

whereI αij is a loan level fixed effectI WINit is a dummy for whether a politician holds office in tI Later specification looked at the effect when party of

politician won the election and then used WIN − Partyit




Results III




Comments on Methodology III

I No autocorrelation test, autocorrelation could lead to wronginference

I Difference-in-differences strengthens identificationI (Time fixed-effects ?)




Alternative explanation

I Two alternative explanations for their finding

1 Social Lending2 Efficient Lending

I Both unlikely




Alternative explanation

I Social lending: Test for politicians owning firms in a differentstate then where they go elected and find that it doesn’tchange the result

I Efficient lending: government banks are loosing money withevery politically loan, there should be similar differencesbetween private banks and if lending would be efficientpolitically firms would get less loan not more




Costs of Rents

I Measure the cost of rents for the whole economy by

1 Deadweight Loss of Taxation2 Cost of Investment Distortion




Deadweight Loss of Taxation

I Defaulted loans can be seen as transfers made by the taxpayers to the rent seekers

I Estimate a DWL of 0.16-0.3% of GDP




Cost of Investment Distortion

I Captures the loss of what could have been if this loans wouldhave gone to productive firms

I Market-to-book ratio in Pakistan is 2.96 so loss is in betweeen0.8-1.6% of GDP




Conclusion - Summary

I Three questions: 1. Are politically firms favored?, 2. How theenvironment affects the rents? and 3. What the costs are?

I Politically connected firms getting more loans and defaultingmore often

I Correlated with the strength of the politician on boardI Economy wide costs: 0.3%-1.9% of GDP per year




Conclusion - Evaluation

I Huge and reliable date set, population of the loansI Can’t deal with hidden political connection, don’t check for

relatives, school friends or similar relationsI Concerns about excessive use of fixed-effectsI Loan makers could be corrupt themselves




Conclusion - Lessons

I Corruption is a huge problem and brings enormous economiccosts

I Future research:1 Are Banking systems with a large share of government banks

usually more corrupt?2 Are banks corrupt themselves?3 Does the same applies to private loans?




Politically Connected Firms by Mara Faccio

I Research Questions: What common characteristics docountries with widespread political connections share? Dopolitical connections add to company value?

I Faccio develops the following measure of politicalconnectedness:

1 A top officers (CEO, President,...)2 A large shareholder (at least 10 %)

I Is a member of the parliament, a minister or closely related toa top politician or party

I Data from 47 countries





I First question: Uses two-boundary Tobit model, significanceof relation between connection variables and independentvariables

I Second question: use event study around the announcementof business man entering politics and politicians entering acompany





I Connected firms represent 8% of the world’s stock marketcapitalization

I More likely in countries considered highly corrupt, restrictforeign investment for their citizen, more transparent systems

I No significant effect of appointing politicians to boardI Increasing stock prices when a business man enters politicsI Value increases more if elected Prime Minister then being

elected to the Parliament




Betting on Hitler - The value of political connection in NaziGermany by Thomas Ferguson and Hans-Joachim Voth

I Research Question: Measure whether being affiliated with theNazi regime made a difference for the market value of the firm

I Look at the market value of the firms at the Berlin Stockexchange before and after the Nazis came to power

1 Business leaders or firms contributors financially contributed tothe party or Hitler or Goring

2 Business man provided support to the Nazi party at crucialmoments, serving on (or helping to finance) various groupsthat advised the Party or Hitler on economic policy





I Use OLS regression, Nazi Dummy(only significant in twomonths) and splitting up the sample by size, industry andbeing a weapon supplier

I Probit regression on Nazi DummyI Matching estimator(treated and untreated groups)I IV-estimator (Electoral Preferences in Region of Origin)





I Companies affiliated with the regime outperform the marketby 5% to 8%. account for a large part of the rise prices

I Connections surprisingly largeI That large connections are just found in third world

countries(compared with the measures Faccio finds)I Example I.G. Farben made a 400,000 RM contribution, share

price increased by 12% to 1,190 mio. RM




Estimating the Value of Political Connections by RaymondFisman

I Research Question: Effect of political change on market valueof political connected firms

I Political connected firms in Indonesia in 1997I Dictator Suharto sick, bad news about his health affected

stock market




Estimating the Value of Political Connections by RaymondFisman

I Event study for the time period 1995-1997I Political connection measured by Suharto Dependency IndexI Indonesia good candidate for event study due to centralized

and stable structureI The event used is the health news of SuhartoI Political connected firms reacted to the bad newsI political rents included in stock prices




Political Firms, Public Procurement and DemocratizationProcess by Stephane Straub

I Research Question: Effect of government change on politicalconnected firms?

I Paraguay in government change in 2008I Ruling Paraguayan Colorado Party lost the electionI Established a system of political connectedness in government

firms beforeI Data on all public procurement transactions from 2004-2011I Use fixed-effects and Dummies and for efficiency gains and

IV-approach(Using Government Change and institutionsDummy as IV)




Political Firms, Public Procurement and DemocratizationProcess by Stephane Straub

I Government change reduced contracts awarded to firmsconnected to the former government

I Politically non connected firms and to a lesser extend firmsconnected to former opposition benefited from Depolitizationprocess

I Evidence of binding constraints, in particular time needed foran efficient class of entrepreneurs to emerge

I Some efficiency gains




Summary

I Political connectedness increases company valueI Rent extractionI Strong politicians gain more rentI Weak systems are more vulnerable


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