Local Bank Financial Constraints and Firm Access to External Finance

More documents

Recommendations

Info

The variable of interest on the right hand side of the equation, F it , represents all the sourcesof capital net of regulatory reserve requirements of bank i at month t (from now on, sources ofcapital). 7 The test for financial constraints consists in estimating the sensitivity of bank lendingto changes in sources of capital holding other determinants of the demand and supply of creditconstant. The test is implemented by estimating β 0 through 2SLS using an exogenous source ofvariation in sources of capital. A positive estimate of this sensitivity, β 0 , will contradict the nullhypothesis of no financial constraints.The fundamental identification assumption of this test is that the source of variation insources of capital is not correlated with changes in the marginal cost of capital or investmentopportunities of the bank. There are several reasons why the actual amounts of finance receivedfrom the MYPES program may not constitute an exogenous source of variation in sources ofcapital in this setting. I discuss in turn each of these reasons and the potential biases they mayintroduce, and then describe the empirical strategy used to address them.The Targeting RuleExternal financing received by banks was conditional on banks expanding lending to thetarget group of borrowers. This raises the concern that unconstrained banks may haveexpanded lending in order to comply with the allocation rule and retain access to a subsidizedsource of finance in the future. I will provide arguments and show evidence contrary to thisinterpretation. Enforcement of targeting rules in directed lending programs is not attempted orineffective in general. It is not attempted because the monitoring of directed lending programshas been shaped by the typical failure of these programs to spend the allocated budgets. Thecommon practice is to set up administrative monitoring systems aimed at measuring budgetexecution performance (Barger (1998)). And it is ineffective because banks can exploit resource13
fungibility. In a recent study of an on-lending program targeted to the export sector credit inPakistan, Zia (2006) shows that 50% of the on-lending resources allocated to exporting firmsare misallocated, in the sense that crowd out existing finance of the export sector and have noeffect on output or productivity of the target sector.The MYPES program was not an exception to these general features of on-lendingprograms. The government agency that was the sole responsible of monitoring the MYPESprogram execution monitored target firms’ debt only after these received program financing.This means banks could re-label debt of existing eligible clients as ‘program loans’ to complywith the targeting rule and at the same time retain freedom to allocate resources to theirpreferred use. Figure 1 shows preliminary evidence that suggests such re-labeling took place inthe case at hand. The figure shows the monthly evolution of total bank debt of a sample offirms that received credit labeled as ‘program loans’. The horizontal axis measures the timerelative to the date each firm received a program loan. The graph shows how receiving aprogram loan had no effect on the amount of debt a firm had from the program bank. Instead,program loans substituted dollar for dollar other preexisting debt of existing bank clients.Section IV provides additional and systematic evidence that the lending expansion was directedto firms that did not meet the targeting criteria.Endogenous timing and Size of Program WavesThe second concern is that the government may have timed the program to coincide withperiods when the banking sector was in need of additional liquidity, e.g. due to depositshortages. In this case the estimate of β 0 will be biased downwards: the true effect of anadditional dollar of external financing provided by the program on bank lending is attenuatedby the concurrent effect of the drop in deposits. The pattern of yearly flows of program14
Page 1: Local Bank Financial Constraintsand
Page 7 and 8: anked second among emerging market
Page 9 and 10: capital net of reserve requirements
Page 11 and 12: of the world “when the level of f
Page 13: higher proportion of loans in poor
Page 18 and 19: ―15.4% versus 6.3%, and has an av
Page 20 and 21: The second step is to calculate the
Page 22 and 23: The CDSF data is used to construct
Page 24 and 25: I estimate a regression of bank sou
Page 26 and 27: and strong influence on the financi
Page 28 and 29: interaction term, β C 0 , represen
Page 30 and 31: C. Underinvestment or Free Cash Flo
Page 32 and 33: A potential concern with the previo
Page 34 and 35: ln(Debt ikt ) - ln(Debt ikt-1 ) =
Page 36 and 37: program finance are negative, which
Page 38 and 39: orrower bank debt comes solely from
Page 40 and 41: Appendix: A Model of Program Partic
Page 42 and 43: higher region and size point scores
Page 44 and 45: Bharath, Sreedhar, Sandeep Dahiya,
Page 46 and 47: Jensen, Michael, 1986, Agency Costs
Page 48 and 49: Peek, Joe, and Eric Rosengren, 1997
Page 50 and 51: Figure 1Evidence on Loan Re-Labelin
Page 52 and 53: Figure 3Kernel Estimation of the Mo
Page 54 and 55: Table IILoan and Loan Recipient Sum
Page 56 and 57: Table IVOLS/2SLS Estimates of the E
Page 58 and 59: Table VIConstraints or Free Cash Fl
Page 60 and 61: Table VIIITesting for Changes in Ba
Page 62 and 63: 1 For examples of the first line of
Page 64 and 65:
12 The 2SLS estimates of the sensit
show all

Local Bank Financial Constraints and Firm Access to External Finance

Create successful ePaper yourself

Delete template?

Save as template?