The Bank Lending Channel of Monetary Policy Transmission: A Dynamic Bank-level Panel Data Analysis on Tanzania

Transcription

1 Appled Economcs and Fnance Vol., No. ; January 207 ISSN E-ISSN Publshed by Redfame Publshng URL: The Bank Lendng Channel of Monetary Polcy Transmsson: A Dynamc Bank-level Panel Data Analyss on Tanzana Wlfred E. N. Mbowe * Manager, Research Department, Bank of Tanzana, Tanzana Correspondence: Wlfred E. N. Mbowe, Research Department, Bank of Tanzana, Mrambo Street, 88 Dar es Salaam, Tanzana. Receved: September 6, 206 Accepted: December 9, 206 Avalable onlne: December 22, 206 do:/aef.v.2097 URL: Abstract Ths study uses dynamc panel data estmaton models, employng annual bank-level data spannng the perod , to emprcally nvestgate whether or not changes n the monetary polcy n Tanzana nfluence bank lendng behavour,.e., exstence of a bank lendng channel (BLC). It also examnes the dstrbutonal effects of the monetary polcy on banks wth dfferent balance sheet characterstcs and ownershp structures. The fndngs lend support to the hypotheses that, frst: BLC operates n Tanzana, suggestng that bank loans are mportant channel through whch monetary polcy shocks are transmtted to the economy. The fndngs mrror the arguments that the bankng sector stll domnates the fnancal system n the country, whereas money, captal, and real estate markets are stll at ther nfant stages. Banks account for about three-quarters of the fnancal sector s assets, reflectng ther domnance of sources of fundng. Meanwhle, about two-thrds of bank fundng comes from prvate sector deposts, probably constranng banks n offsettng the decrease n funds from deposts by rasng funds from other sources. Second, banks react asymmetrcally to polcy changes nfluenced by sze, captal strength, and ownershp structure. The lendng channel s stronger through domestcally-owned banks and prvately-owned banks than t s wth foregn-owned banks and publc-owned banks. The reason s that, for foregn-owned banks, they could enhance ther captal through rasng of equty abroad and/or beneft from retaned earnngs; whle for publc-owned banks, t could be because they are not under pressure to make proft and, therefore, may opt not to cut-down ther loans followng a monetary polcy shock. The polcy mplcatons are that, n assessng the stance of the monetary polcy, besde short-term nterest rates, t s crtcal for the monetary authorty to trace banks reacton to monetary polcy changes as reflected n loan supply to the prvate sector. Such nvestgaton should also factor n possble asymmetrc responses by banks nfluenced by sze, captalzaton, as well as ownershp structure. Keywords: bank lendng channel, fnancal development, econometrc models, Tanzana. Introducton. Background to the Study Studes, ncludng those by Kng and Levn (993a; 993b), Demrguc and Maksmovc (998), and Levn and Zervos (998), underscore the mportance of well-functonng fnancal markets n an economy. Such markets, not only support economc development, but also enhance the effectveness of monetary polcy because they provde a mechansm for moblzaton and allocaton of fnancal resources. In the 990s, as a follow up to the recommendatons of the Presdental Commsson of Enqury, Tanzana embarked on a seres of fnancal reforms as an effort to promote the development of a market-based fnancal sector. Ths was done as a strategy to turnng around the deteroratng economy and acceleratng economc growth. The strategy was kcked off by the Bankng and Fnancal Insttutons Act of 99, whch paved the way for entrance n the fnancal sector of prvate foregn and domestc nvestors and development of money markets. As a result of ths, Tanzana s fnancal sector wtnessed huge prvate sector nvestment, brngng wth t a new fnancal landscape, as well as a new culture of * Penson funds hold about 2% of total assets, whereas nsurance sector and other remanng fnancal ntermedares hold 2% of the total assets each. 69

2 dong busness (Bank of Tanzana [BoT], 20a). Moreover, the reforms have enhanced the role of banks as a major source of fnance to support economc actvty n the country. These developments have mportant mplcatons on how macroeconomc stablzaton polces, the monetary polcy n partcular, affect economc actvtes. Monetary polcy can nfluence economc actvty n the short to medum term, through a number of channels, ncludng the nterest rate channel, the bank lendng channel (BLC), the balance sheet channel, and the exchange rate channel. Accordng to Montel et al. (202), the ablty of a central bank to nfluence the economc actvty through these transmsson channels depends on the strength and relablty of the lnks between polcy nstruments that t controls and aggregate demand..2 Statement of the Problem and Objectve of the Study Recently, the lterature has stressed the mportance of bank loans n the transmsson mechansm for developng countres, manly because the economes are domnated by many bank-dependent borrowers (Ramlogan, 200). Also, Mshra et al. (200) and Montel et al. (202) provde theoretcal arguments as to why BLC mght be more effectve n less developed countres than other channels. The reasons are related to: frst, undeveloped money markets, so that central banks are unable to conduct monetary polcy through open market transactons n secondary markets. Second, equty and real estate markets tend to be small and llqud, whch weakens the asset prce channel of monetary polcy transmsson. Thrd, nterventons by central banks n the foregn exchange markets weaken the exchange rate channel. Ths may be the case for Tanzana where banks account for about three-quarters of the fnancal sector s assets, and a large part of producton s by small busnesses some of whch are bank-dependent. Lke n many other developng countres, markets for drect fnancng (e.g., the bond and stock markets) n Tanzana are stll at an nfant stage. However, to the extent that Tanzana undertook consderable fnancal reforms n the 990s, t may have reduced the role of banks n the credt market, and thus, have lmted the potency of BLC (Mshkn, 995). Montel et al (202) argues that the effectveness of BLC n Tanzana may as well be constraned by possble uncompettve bankng system. Knowng how the Bank of Tanzana (BoT) s polcy actons are transmtted to the rest of the economy through ths channel would contrbute to the efforts to enhance the effectveness of the monetary polcy. Ths study seeks to enqure on two related research ssues: role of monetary polcy n nfluencng bank lendng behavour n Tanzana and the extent to whch bank-level characterstcs and ownershp structure affect the effectveness of the monetary polcy. The am s to nvestgate whether the bank lendng channel (BLC) operates n Tanzana, ncludng the dstrbutonal effects of the monetary polcy on banks wth dfferent balance sheet characterstcs and ownershp structures. The hypotheses are that BLC exsts n Tanzana, and that the strength of the channel s nfluenced by bank s sze, balance sheet strength, and ownershp structure. After the ntroducton, secton two presents facts on Tanzana s fnancal system structure, bank credt supply evoluton, as well as challenges to the operaton of the BLC n the country. Whereas secton three surveys the lterature on BLC, secton four detals the conceptual framework and modellng technque. The regresson results and dscusson are n secton fve, whle secton sx wnds up by summarzng the polcy mplcatons of the fndngs, as well as areas for further study. 2. Stylzed Facts on Tanzana s Fnancal System Structure and Bank Credt Supply 2. Polcy Evoluton, Money Market, and Fnancal Structures In Tanzana, bank credt supply has evolved over tme dependng on the socoeconomc polcy of the government. Three broad phases can be dentfed from Tanzana Manland s ndependence n 96. These are the perod before 967; the state control perod from 967 through 99; and the post fnancal lberalzaton perod, 99 to date. Generally, the perod before ndependence through 967 was characterzed by a market-based bank credt supply. Snce Tanzana s ndependence was preceded by massve captal flght and wthdrawals from commercal banks manly drven by uncertanty about the ndependence government that would take over BoT was establshed n 965 to perform all the tradtonal central bankng functons, ncludng overseeng credt allocaton on a compettve envronment. However, BoT could not perform ths functon effectvely followng the proclamaton of the Arusha Declaraton n February 967, whch placed all major means of producton and exchange under the control of the state. Controls were also mposed on bank credt supply. These polcy changes created an nflexble economc system that was characterzed by monopolstc and heavly regulated producton structures. Smlarly, the fnancal system was made up of a few publc nsttutons enjoyng a hgh degree of monopoly n ther areas of specalzaton or functonal desgnaton. Excessve government borrowng and nterference, as well as lack of adequate supervson of fnancal nsttutons resulted n hgh accumulaton of bad debts by banks. Hgh levels of nflaton contrbuted to the declne n real returns on formal fnancal assets and thus fnancal dsntermedaton. These, together wth other macroeconomc nstablty called for the need to undertake comprehensve economc reforms as of 986. These changes were backed by the Internatonal Monetary Fund (IMF) and the World 70

3 Bank (WB) adjustment programmes, whch set targets for varous mportant macroeconomc ndcators. Measures were undertaken n certan crucal areas, ncludng mposton of celng on government fnancng, devaluaton of the Tanzanan shllng to reflect prevalng market condtons, and structural measures to elmnate controls n the foregn exchange market. In 99, the Bankng and Fnancal Insttutons Act (99) was enacted and ts mplementaton paved the way for the entrance n the fnancal sector by prvate foregn and domestc nvestors. Also, t allowed for the elmnaton of remanng fnancal controls, ntroducton of fnancal markets and the use of ndrect nstruments of monetary polcy. Restructurng of nsolvent and neffcent government-owned banks that characterzed the bankng system before 993 enhanced ther effcency and compettveness. These, together wth the enactment of the Foregn Exchange Act n 992 that permtted ndvduals to hold foregn currency and foregn exchange accounts at commercal banks, contrbuted to the ncrease n the customer base as well as quantty and qualty of bankng servces. Moreover, the Bank of Tanzana Act of 995, whch releved the Bank of non-tradtonal central bank functons, gave t ndependence n formulatng and mplementng monetary polcy. The prmary objectve of the monetary authorty remaned mplementng monetary polcy that ensures prce stablty for a balanced and sustanable economc growth. The open market operatons (OMO), ntroduced n 993/9, s the man polcy nstrument, whch provdes mechansm to acheve three man objectves: fnancng of fscal defcts, lqudty management, and anchor of nterest rate determnaton. Banks can access ntraday and Lombard facltes whch were ntroduced n 2003 and Repurchase agreement (REPO) that was ntroduced n 2007 as stand-by credt facltes to accommodate short-term lqudty oblgatons. Meanwhle, the Bank s regulatory and supervsory roles have also been strengthened to complement the monetary polcy. Snce 2007, BoT has adopted a more rsk-focused approach. In efforts to put n place a formal mechansm for sharng of credt nformaton and reduce nformaton asymmetry on borrowers, a databank and prvate credt reference bureaus were establshed snce October 202. There s huge evdence to show that the comprehensve fnancal reforms mplemented n the 990s greatly contrbuted to the fnancal development observed n Tanzana today (Nord et al., 2009; Mbowe, 200; and BoT, 20a). Nonetheless, such fnancal development followed fnancal reforms wth a consderable lag, mplyng a delayed structural shft. For example, whle nterest rates were lberalzed n 99 and entry of prvate banks was permtted n 992, none began operatons untl 99, and the bankng system began to expand dramatcally only after 998. In 998, Tanzana had 8 commercal banks wth 78 branches, but by 2009 the number of commercal banks had ncreased to 3 wth 07 branches. At the end of December 200, the bankng sector was composed of 2 bankng nsttutons consstng of 28 fully-fledged commercal banks and fnancal nsttutons wth 73 branches country-wde (BoT, 200). As the number of bankng nsttutons ncreased to 8 at the end of 20, the number of branches rose to 503 (BoT, 20b). As t was the case before fnancal reforms, the bankng sector domnates the fnancal system although now wth more banks compared wth only three banks before the reforms. As at the end of 20, the bankng nsttutons accounted for about 75% of the total fnancal assets (BoT, 20b). Ths stuaton ponts to a possblty of banks domnance n sources of fundng, lkely strengthenng BLC. In terms of market share, 50.5% (or an average of 5% durng the perod ) of banks assets were foregn-owned. In 20, the ownershp structure of the bankng sector was such that fve nsttutons were majorty state-owned and 3 were majorty prvately-owned. Twenty-fve bankng nsttutons were locally-owned and 23 were foregn-owned. Despte the ncrease n the number of banks, the bankng sector has persstently been domnated by the same fve largest banks. Meanwhle, the stock market s stll undeveloped. 2 The polcy and structural changes, as well as dynamcs n the money markets and bank ownershp structures may have mportant mplcatons on the effcacy of BLC n the country. 3. Lterature Survey 3. Theoretcal Lterature BLC s based on the vew that banks play an mportant role n the fnancal system as an external source of fnancng for frms. Because of banks specal role, certan borrowers wll hghly depend on bank loans, and wll not have access to credt markets unless they borrow from banks. Bernanke and Blnder (988) propose a framework through whch monetary polcy can affect banks portfolo behavour. The framework presupposes that a monetary contracton rases the nterest rates even for government bonds, whch may be consdered to be rsk-free. Banks cannot ncrease the Penson funds hold about 2% of total assets, whereas nsurance sector and other remanng fnancal ntermedares hold 2% of the total assets each. 2 For example, Montel et al. (202) ndcate that Tanzana s stock market captalzaton as a rato of GDP s very low, at around compared to 0.27 and 0.90 for low-ncome and advanced economes, respectvely. 7

4 deposts rate by as much snce they have to buld requred reserves; banks suffer a deposts dran as nvestors reshuffle ther portfolos towards hgher nterest bearng assets. As a result of the deposts dran, banks have to adjust ther portfolos. If banks dfferentate between makng loans and holdng government bonds, they wll be unwllng to deplete ther holdngs of government bonds below a certan level. The bank wll restrct the supply of loans nstead, leadng to a declne n nvestment spendng, and a fall n economc actvty. Below s a schematc representaton of BLC n whch the vertcal lne ndcates the drecton of change. The horzontal lne ndcates the channel through whch the effect of a monetary polcy change s transmtted to an economc actvty. In ths, a contractonary monetary polcy (MP) reflected by an ncrease n the polcy rate leads to a fall n bank reserves and bank deposts, subsequently leadng to a declne n the bank loans to the prvate sector. In turn, t leads to contractng nvestment spendng and then fallng economc actvty (output, Y). MP bank deposts bank loans Investment Y () Bernanke and Blnder (988) ndcate three condtons for the exstence of BLC. Frst, frms should not be perfectly ndfferent to dfferent types of fnance. They should be dependent on bank loans and cannot replace losses of bank loans emanatng from the ncrease n the polcy rate wth other types of fnance. If frms were ndfferent between the two types of fnancng, then the decrease n supply of loans would not affect the frms at all. Ths condton s assumed to hold n Tanzana because banks are the major source of fnance for economc actvtes. Second, the central bank should be able to affect supply of loans through changes t mposes on the volume of reserves. Ths s the focus of nvestgaton by the current study. The assumpton s that, for example, n a contractonary monetary polcy, banks wll not be able to offset the decrease n funds from deposts by rasng funds from other sources. The thrd condton for a bank lendng channel to hold, whch we assume holds for the Tanzana s that, there are some mperfectons n the adjustment of the aggregate prce level. The mperfect prce adjustment s necessary because monetary polcy would have no mpact f prces adjusted by the same percentage every tme money supply was changed. 3.2 Emprcal Lterature The lterature s rch n studes whch have tested the exstence of BLC n dfferent economes or n a group of countres. Most of these studes are based on developed economes. When estmatng a bank loan supply functon, the challenge s whether to use bank aggregate data or bank-level (panel) data. Ths s because the observed changes n the quantty of loans after a monetary polcy movement may not entrely be attrbuted to a loan supply shfts. A monetary contracton could as well depress aggregate demand through the nterest rate channel, thereby decreasng the demand for bank loans. Studes that focus on bank aggregate data usually examne the response of aggregate loans, deposts and bond holdngs to monetary polcy shocks usng the vector-autoregresson (VAR) framework. Ths set up, however, does not allow the dentfcaton of supply and demand effects on credt growth. For example, Benanke and Blnder (992) used nnovatons n 3-month Treasury blls rate (T-bll) to capture exogenous shfts n monetary polcy. They found an nverse relatonshp between bank loans and tght monetary polcy, and therefore supported the credt channel vew n the US economy. As t wll be shown later, by usng bank-level data, mxed conclusons arse wth respect to the strength of BLC n the US. Due to dffcultes n dstngushng shfts n loan demand from shfts n loan supply, studes focus on cross-secton (bank-level) data and try to capture asymmetres n loan supply behavour by examnng reduced-form equatons n bank loans to monetary polcy measures. Implct n ths approach whch the current study adopts s the assumpton that, when asymmetres are present, loan supply shfts may be dentfed. Dfferent studes have used dsaggregated bank data n nvestgatng the exstence of BLC, partcularly n developed economes. The studes nclude those on the US economy (such as Kashyap and Sten, 995; Kashyap and Sten, 2000; Kshan and Opela, 2000; and Ashcraft, 2006), n the UK (Huang, 2003; and Gambacorta, 2005), and n the Euro zone, (Altunvas et al., 2002; and Angelon et al., 2003). Generally, most of these studes conclude that, a tght monetary polcy leads to a declne n bank loans, whch n turn has a negatve mpact on the economy. Also, emprcal evdence supports the dea that well-captalzed and lqud banks are less affected by a monetary polcy change than those wth low captal and lqudty. Bank sze seems to be rrelevant n some of the studes. Specfcally, Kashyap and Sten (995) found that, growth n bank loans n the sub-segment of small commercal banks s most responsve to monetary polcy. In another study, Kashyap and Sten (2000) dvded banks n two categores: asset and lqudty sze, and found that the smallest most llqud banks were most responsve to monetary polcy shocks. These fndngs were supported by Kshan and Opela (2000) who dvded banks wth respect to sze and captal strength. Ashcraft (2006), however, questons the exstence of BLC n the US when usng bank-level data. Ashcraft dentfed a dfferental response of loan supply to changes n the Federal Fund Rate across banks. When Ashcraft aggregated the bank data up to the state level, the loan market share of afflated banks tended to mtgate the negatve response of loan 72

5 supply to changes n monetary polcy. In addton, the aggregate elastcty of output to bank lendng was very small. Cetorell and Goldberg (2008) developed on the work of Kashyap et al. (993), Kashyap and Sten (995), and Kashyap and Sten (2000) for the US bankng sector by brngng n an element of globalzaton. Cetorell and Goldberg concluded that BLC exsted n the US, and that, large globally-orented banks extensvely reled on nternal captal markets to smoothen domestc lqudty shocks. Lkewse, Ehermann et al. (200) used a panel of bank balance sheet data and tested for BLC n the Euro zone, and concluded that monetary polcy dd alter bank loan supply, and the effect was hghly dependent on ndvdual bank s lqudty level. Workng on smlar lne, Westerlund (2003) used an ARDL panel data modellng approach and the results supported the exstence of BLC n Sweden for the perod Studes have also found evdence of BLC operaton n Afrca. Sche (2005) nvestgated the exstence of BLC n South Afrca by usng a specfcaton as n Kashyap et al. (993). Sche regressed the total stock of gross loans on ther lag, real GDP, and ndcator of monetary polcy, a vector of bank characterstcs (sze and captalzaton) and the nteracton of monetary polcy and the bank characterstcs. The fndngs supported that the jont effect of monetary polcy and bank characterstcs were statstcally sgnfcantly and postve, mplyng banks wth stronger balance sheets could cushon the effects of a tght monetary polcy on ther loan portfolo. Moreover, Sche and Njenga (200) nvestgated exstence of BLC n Kenya by usng data from banks annual audted balance sheets. They employed an IS/LM model wth bank credt, n lne wth Bernanke and Blnder (988). As a measure of captalzaton, they used the rato of excess captal to total rsk-weghted assets; and for lqudty, they used the rato of excess lqud assets to total labltes. Sche and Njenga found that, monetary polcy had a more pronounced effect on banks wth less lqud balance sheets and on those less captalzed. By usng a modellng approach as n Ehrmann et al. (200), Chbundu (2009) examned exstence of BLC n Ngera by regressng total loans on ts own lag, a measure of polcy rate, GDP, nflaton and bank characterstcs, namely, sze, lqudty and captalzaton. The results were consstent wth a weak BLC. The sze and lqudty postons of banks were found to act as a source of nformaton asymmetry that nfluenced banks behavour on loan supply followng changes n monetary polcy. On Tanzana, Montel et al. (202) assessed the effect of monetary polcy on aggregate demand by usng VAR and aggregate data. Although the study s not comparable to the current study, Montel et al. found no evdence of effectve monetary transmsson n Tanzana. Monetary polcy transmsson to loan rate was found to be weak. The authors concluded that, n order to complement the aggregate estmates, a more mcro-based evdence of how ndvdual banks bascally respond to monetary polcy shocks would be partcularly mportant. The current study attempts to fll ths gap.. Methodology. Conceptual Framework BLC n Tanzana s analysed by usng a proft-maxmzaton framework developed by Sten (998) and Ehrmann et al. (200). By gnorng the tme subscrpt (t) n the specfcaton, the balance sheet of bank s defned as: L S DBC, (2) where, L s the volume of bank loans, S s the securtes, D s the volume of the demand deposts from household, B s the level of non-secured fundng, and C s the captal of the bank. The bank s assumed to act n a market characterzed by monopolstc competton. The demand for bank loan L can be wrtten as: d L d y2p3rl. (3) Loan demand s assumed to be postvely related to economc actvty (y), and negatvely wth loan nomnal nterest rate ( r L ), so that: 0 and 3 0. In contrast, the coeffcent of nflaton ( p ) 2 can be ether postve or negatve dependng on the nature of the economy s steady-state equlbrum. The bank captal s lnked to the level of the loans, whereas the bank s holdng of securtes s lnked to the level of the deposts as follows: C kl, and () S cd (5) 73

6 The demand deposts (D) are secured and they are demanded because of ther role as a means of payment. Therefore, the demand deposts are negatvely related to the nterest rate of an alternatve rsk-free asset ( r s ) and ths s taken as the monetary polcy rate. Ths s wrtten as: D r 0 s, where 0 (6) Deposts are assumed to be exogenous to the bank, and they wll drop after the monetary tghtenng (that s, after an ncrease n r s ). However, the bank has access to alternatve sources of funds (e.g., nterbank loan and debt securtes), whch are unsecured but attract nterest. Snce banks are perceved to be rsky, the supplers of unsecured fnance ask for an external fnance premum, the level of whch depends on the bank s balance sheet health ( x ) that s easly observed by all market partcpants. The hgher s the x, the lower the external premum. So that, the nterest rate of the unsecured fnancng (B) s: 0 r B r c x ), where c x for (7) s( 0 0 Bank cannot rase unsecured funds f t s offered at less than r B, and t can rase any amount of funds f t pad at B B least r. Snce r s a cost factor, the bank wll not be ready to pay more than r B. Assumng B 0, the proft of the bank ) can be wrtten as: ( L s B r L r, S r B, (8) Where, captures bank-specfc admnstratve costs and remuneraton costs for the requred captal holdngs. By nsertng (2) to (6) nto (8), and assumng equlbrum n the loan market, yelds: L 2 L y p sdrs k L s D r [( ) ( ) ] B (9) By settng the frst-order condton to zero, and nsertng (7) n (9), the loan supply functon can be wrtten as: L 2 ( k) c ( k) y p rs xrs (0) L Equaton 0 s the standard loan equaton n macro modellng. An mplct dentfyng assumpton s that the nterest rate loan demand elastcty does not depend on the bank characterstcs ( x ). In other words, the coeffcent 3 s the same for all banks. The assumpton of homogenous reacton of the loan demand s crucal for the dentfcaton of monetary polcy effects on loan supply because t rules out the case where, for example, small or large bank customers are more senstve to nterest rate changes. Such assumpton seems qute reasonable for Tanzana n vew of the fact that bank loans are the major source of external fnance for frms. Drect estmaton of the bank loan supply functon s favoured because f fnancal markets are characterzed by asymmetrc nformaton, the effect of monetary polcy through the nterest rate channel could be amplfed by changes n the avalablty of nternal cash flow or of external fnance (Brssms and Dels, 2007). When banks are the man provders of funds for households or frms, monetary polcy could affect the latter s spendng va shfts n loan supply. Another reason relates to the fact that, estmaton of reduced-form equatons lnkng bank loans to monetary polcy varables does not allow dentfcaton of the parameters of the structural model. Snce due to data lmtatons, the observed asymmetres cannot be explctly attrbuted to the output responses of frms that borrow from a partcular sze category of banks, and ther mplcatons for aggregate economc actvty and transmsson mechansm are not clearly vsble (Kashyap and Sten, 2000). A monetary polcy tghtenng through an ncrease n the polcy rate ( r s ) leads to a reducton n deposts n Equaton 6. However, banks can keep the asset sde of ther balance sheets unchanged only f they ncrease other sources of fundng B accordngly. But, the nterest rate whch banks have to pay for the funds was ncreased by the monetary polcy tghtenng accordng to the Equaton 7. Banks pass at least part of ths hgher cost to ther loan rate r ), whch n turn 7 ( L,

7 reduces the loan demand. Therefore, n Equaton 0 t s expected that the monetary polcy rate, to the supply of bank loans. Equaton s a modfed verson of equaton 0, and s used for emprcal nvestgaton: rs has a negatve effect J J ln Lt j ln Lt j j rpt j jxt j ( rpt * xt j j0 ( ) j j ( ) J j ln yt j j ( ) J j ln pt j j ( ) J ln HHIt j j ( ) ) J ln NIIt j NPLt LLPt j ( ) ( ) ( ) t () In Equaton, Δ and ln ndcate frst dfference and natural logarthm of the varables, respectvely. The stochastc error term s expressed as. The varable L s the real growth rate of bank loan for bank at tme t. The varable rp denotes the approprate nterest rate measurng the monetary polcy stance, here captured by the weghted average Treasury bll rate (manly due to absence of actve central bank polcy rate). Hgher values of r p correspond to a tghter monetary polcy stance. The use of weghted average Treasury bll rate should be approprate for Tanzana because the monetary authorty targets monetary aggregates, and through open market operatons, the resultant nterest rate serves as an anchor of nterest rates determnaton by banks. Commercal banks are expected to adjust ther lendng and deposts nterest rates basng on the changes n the Treasury bll rates. 3 It s assumed that, tghter monetary polcy stance should result n slower credt growth. Because there wll usually be a lag for monetary polcy to take effect, and there may also be reverse causalty problem, lagged weghted average Treasury bll rate was used nstead. The ( r * t) nteracton varable pt x was ncluded to measure the nteracton of the monetary polcy rate wth the bank characterstcs. The parameters of nterest n Equaton are the ' s, and the ' s, whch are assumed to be the same across banks. A monetary tghtenng s expected to reduce lendng, hence j are expected to be negatve. As for the nteracton j terms, ' s measure the effects of monetary polcy whch s expected to be weaker among larger, more lqud and better captalzed banks. Large, more lqud and well captalzed banks are expected to be able to better sheld ther loans from monetary shocks by usng ther buffer of lqud assets and/or attractng funds from non-depost sources, thus, ' s are assumed to be postve for asset sze, lqudty and captalzaton. As mentoned earler, bank characterstcs may be a source of banks asymmetrc reacton to monetary polcy changes. Ths vew s n lne wth the lterature n ths area (see, for example, Kashyap and Sten, 995 and 2000; and Peek and Rosengren, 995). Therefore, captured n the model are vectors of bank-specfc characterstcs: asset sze; lqudty; and captalzaton, as specfed by varable x n equatons 0 and. For the asset sze, logarthm of total assets was used; whle lqudty and bank captalzaton were captured as the rato of lqud assets (cash, nterbank lendng and securtes) to total assets and the rato of bank equty captal plus reserves to total assets, respectvely. As shown below, bank characterstcs varables are defned as devatons from the cross-sectonal mean at each tme perod n the case of the sze varable, so as to remove ts trend, or the overall mean n the case of the bank strength varables (lqudty and captalzaton) whch do not have trend. All three crtera are normalzed wth respect to ther average across all the banks n the sample n order to get ndcators that sum to zero over the observatons. Ths means that, for the regresson model n equatons 0 and, the average of the nteracton terms ( rs * x ) s zero and the respectve coeffcent can be nterpretable as the overall monetary polcy effects on loans. For bank at tme t, the sze (S), lqudty (LQ) and captalzaton (CA) ndcators are therefore computed as: St log At N N log A t (2) 3 Interbank nterest rate could be an alternatve proxy for a polcy rate, but snce t was hghly correlated wth the Treasury bll rate durng the study perod, only the latter was thus used n the estmaton. 75

8 LQ t LA A T T N N t t LA A t t, (3) Ct CAt At T T N N t C t. () At In order to solate changes n total loans caused by movements n loan demand, a vector of control varables, Z, was captured. In the lterature, varables such as Gross Domestc Product (GDP), Consumer Prce Index (CPI) and Real Exchange Rate (RER) have been used. Added to the model to control for demand effects s real GDP growth. Ths should be approprate for Tanzana where an average of 7.% real GDP growth was observed for the perod Hgher GDP growth s assumed to translate nto hgher credt growth. In lne wth Guo and Stepanyan (20), GDP growth entered the model n ts lags n order to avod the problem of reverse causalty, that s, hgh credt growth leads to hgher GDP growth. Consderable stablty was observed n exchange rate durng the study perod; therefore, nflaton captures the effects of expected nflaton on real credt growth. Tanzana experenced consderable nflatonary pressure n the onset of the fnancal crss emanatng from the rse n food and energy prces n the world market, partcularly from Ghosh and Gosh (999) argue that the stock market ndex may also reflect the avalablty and attractveness of alternatves to bank credt equty fnance n partcular from the demand sde, but ths s assumed away n ths study because the stock market n Tanzana s stll underdeveloped. Innovaton n ths modellng s four-fold. Non-nterest ncome for banks was added to the model to capture the effect of ( HHI ) other servces demanded by customers; banks ownershp structure; the Herfndahl ndex t to take care of the degree of competton n the bankng sector; and bank s rsk poston. The bank s rsk poston s captured by two rsk ( NPL ) measures: the rato of nonperformng loans to total loans t and the rato of loan-loss provsons to ( ) nonperformng loans LLP t. The former varable reflects past credt rsk and may sgnal fnancal dffcultes n the bankng system, whereas the latter varable measures the severty of regulatons on rsk-takng n lendng actvtes, respectvely. If banks are reasonably well-behaved, they should tend to lower ther credt supply n response to mountng credt rsk and/or ncreasng loan-loss provsons beng mposed upon them. Meanwhle, the Herfndahl ndex 5 ranges from a low of 0, ndcatng perfect competton, to a hgh of 0,000, ndcatng complete monopoly. Greater values mean greater concentraton and less competton, thus beng negatvely related to loan supply. Herfndahl ndex s computed from banks market shares of deposts. Also analysed s the dstrbutonal effect of monetary polcy shocks along ownershp structure of banks. The exstence of BLC s assessed through the sgns and sgnfcance of the nteracton coeffcents ( ' s coeffcents) whch measure the dfferental mpact of monetary polcy on bank lendng dependng on the bank s balance sheet strength, sze and ownershp structure. Also, accordng to the theory of the bank lendng channel, the coeffcent of the polcy rate must be negatve n order to mply that loans fall after a monetary polcy tghtenng. All bank-specfc varables enter the equaton wth a lag. Equaton was estmated for banks real loans to the prvate sector as a dependent varable and ths served as a benchmark equaton. Separate estmatons were made for the fve largest banks (whch are also most lqud and captalzed banks) and other (small) banks n the sample to capture asymmetrc reactons to monetary polcy. Also separate estmatons were done for domestcally- and foregn-owned banks, as well as prvately- and publc-owned banks. The study used commercal banks annual audted balance sheet data for the perod A total of 2 commercal banks (out of 8 banks) were used n estmatons; these are the banks whch were n operaton throughout the study perod. All data was obtaned from BoT except the real GDP and CPI whch were sourced from the Tanzana Natonal Bureau of Statstcs. The span of study perod and data frequency was determned by data avalablty. The chosen perod enabled the use of revsed GDP, nflaton and nterest rates data. Also, the perod was characterzed by consderable fnancal development, and a relatvely hgh relance on market forces n determnng nterest rates. 6 Only loan-loss provson varable was used n ths study due to unavalablty of enough data on nonperformng loans. 5 Herfndahl ndex measures concentraton of the loans n the bankng sector calculated as the sum of the squares of market shares for each frm. Ths s one method of summarzng the degree to whch an ndustry s olgopolstc and the concentraton of market control held by the largest frms n the ndustry. 6 Montel et al. (202) suggest that nvestgaton of the monetary transmsson n Tanzana should be based on post-2000 data followng a delayed fnancal development to fnancal reforms started n the 990s. 76

9 .2 Descrptve Statstcs of the Varables The appended tables I-A and I-B summarze descrptve statstcs of the varables n a sample of 2 banks, whereas the correlaton coeffcents of the same are detaled n appendx Table I-C. Appendx Table I-A shows that the mean and standard devatons of the logarthm of real credt to the prvate sector are 6.25 and.66, respectvely. The Jarque-Bera test statstc suggests non-normalty n the data. Meanwhle, the share of the top fve banks assets to total assets declned from 83.% n to 58.8% n n favour of the medum sze banks (appendx Table I-B). Ths s an ndcaton of ncreased competton n the sector. The medum sze banks and the bottom fve banks were more captalzed than the top fve5 banks, probably ndcatng dffcultes to smaller banks n accessng other sources of funds. In lne wth ths, smaller banks also hold szeable amount of ther total assets n lqud assets. Meanwhle, foregn-owned banks, whch accounted for about 5.8% of the total assets n the perod , were relatvely more captalzed, wth the rato of ther captal to total assets standng at.% compared to 3.0% of domestcally-owned banks, suggestng that foregn-owned banks could be n a better poston to cushon negatve effects on ther balance sheets. For domestcally-owned banks, they hold a sgnfcant share of ther assets n lqud assets for that effect. Durng the perod , domestcally-owned banks held an average of 2.9% of ther assets n lqud assets compared to.6% held by foregn-owned banks. Meanwhle, the growth n real bank credt to the prvate sector s postvely related to real GDP growth, competton and captalzaton measures, and negatvely correlated wth the T-bll rate (polcy rate), perceved rsk, and lqudty and sze measures (appendx Table I-C). Hgh correlaton between the exogenous varables cannot be dened ether, partcularly between real GDP and nflaton; real GDP and competton measure; competton measure and nflaton; and bank sze measure and non-nterest ncome. Appended fgures I-A to I-D depct the trends of the seres n whch banks are numbered from to 2. It s evdent from the plots that real credt to the prvate sector by most of the banks ncreased durng the study perod. Ths s consstent wth the ncrease n the sze of banks and ncreasng competton n the bankng sector. The central bank seems to have followed a restrctve monetary polcy stance reflected by the rse n Treasury bll rate durng the perods and Generally, the seres seem to be non-statonary, save for banks balance sheet strength ndcators (.e., lqudty and captalzaton). Statonarty of the seres was further tested by usng Im, Pesaran and Shn W-stat and Augmented Dckey-Fuller methods for the panel and tme seres data, respectvely. The results are summarzed n Table. The unt root results suggest that the null hypothess of non-statonarty of the seres n levels cannot be rejected for most of the seres. 7 When dfferenced once, all the seres are accepted to be statonary wth very hgh probablty. Table. Unt root tests for the varables Varable Indvdual ntercept Level Indvdual trend and ntercept st dfference Indvdua l ntercept Indvdual trend and ntercept Lags for each estmato n Log real credt to prvate sector* Log real GDP** Log CPI** Log non-nterest ncome** Loan-loss provson** Herfndahl ndex* T-bll rate** Sze* Lqudty* Captalzaton* Note: * and ** mply tests usng Im, Pesaran and Shn W-stat and Augmented Dckey-Fuller Tests, respectvely. +(++)+++ mply statstcally sgnfcant at 0%(5%)% levels. Source: Author's computatons. On account of the descrptve statstcs, and gven a narrow panel of only 2 banks, t was reasonable to proceed usng 7 Unt root results for the tme seres should be nterpreted wth cauton because of the shortness of the sample perod ( years). 77

10 frst dfference dynamc GMM as per Arellano and Bond (99). However, n order to control for weaknesses assocated wth the use of fxed effect and frst dfference GMM estmators, a system GMM approach, whch combnes both regresson n dfferences and n levels as suggested by Blundell and Bond (998) 8, was employed. A dynamc panel data analyss s justfed on two reasons. Frst, there s a close banker-customer relatonshp that develops and may create lock-n effects, thus makng t costly for the borrower to change bank (Morgan, 998). Thus, lagged values of loans affect current loan postons. In other words, under these crcumstances, the bank acqures nformatonal monopoly over a clent and hence t s extremely costly for a customer to change a bank, because the servces of the new bank wll be more expensve, snce t needs to collect nformaton about the new customer. Second, monetary polcy only mpacts lendng behavour wth a lag due to long-term contractual commtments, hence lagged values of the explanatory varables also affect current loan postons (Sche, 2005). Thrd, the presence of sgnfcant autocorrelaton n panel regresson suggests that a dynamc panel s more approprate. Wth ths, testng for I() could be seen as complementary to the decson because t s unlkely to get spurous regresson n panels because, as the number of N goes to nfnty, t would domnate the tme T gong to nfnty. The use of ths approach notwthstandng, the results obtaned after controllng for fxed and random effects, as well as dynamc panel data effects as suggested by Arellano-Bond are also reported for robustness check purposes. 5. Regresson Results and Dscusson The emprcal results are summarzed n tables 2-5. The general model results are reported n Table 2. The results are obtaned from system dynamc panel data estmatons, where the real credt to the prvate sector was used as a dependent varable. The ndependent varables are the real GDP, CPI, bank characterstcs, weghted average Treasury bll rate, and nteracton terms between the polcy rate and bank characterstcs. Banks non-nterest ncome, a measure of competton n the bankng sector and banks rsk percepton were dropped from the model because ther coeffcents were found to be statstcally nsgnfcant. 9 In all estmatons robust standard errors were used. The null hypothess that coeffcents of the ndependent varables are jontly non-zero was rejected wth very hgh probablty, and that of no autocorrelaton n the frst dfferenced errors could not be rejected n most of estmatons, ndcatng well-specfed models. Here, dscusson s made to the fndngs basng on the models n whch the nteracton terms have two lags. Ths should be approprate for Tanzana, where there are consderable long-term contractual arrangements between lenders and borrowers so much as to attract prme rates on loans. 5. The Exstence of BLC n Tanzana As depcted n Table 2, the coeffcent of the polcy rate s negatve and statstcally sgnfcant at the conventonal % and 5% levels, mplyng that bank loans fall after a monetary polcy tghtenng. In model 3, an ncrease n the polcy rate by one percentage pont would reduce the rato of bank credt to GDP, whch was 20% n 202, by 0.57 percentage ponts n the short run and.39 percentage ponts n the long run. 0 Furthermore, all coeffcents of the nteracton terms are postve (as expected), and those of bank sze and captalzaton are statstcally sgnfcant at % level. 8 Incluson of lagged dependent varables as regressors renders OLS estmator n a fxed effect model based and nconsstent resultng n neffcent estmates. Lkewse, f the lagged dependent and explanatory varables are persstent over tme or nearly a random work, then lagged levels of these varables are weak nstruments for the regresson equaton n dfferences. 9 Results of the model wth all varables are appended as Table II-A. 0 Long-run coeffcents were computed as: ( ), where and are the coeffcents of the polcy rate and the lag of real credt, respectvely. 78

11 Table 2. The effect of monetary polcy on bank loan supply to the prvate sector Dependant varable: Real bank credt to the prvate sector Model : No Lag Model 2: Lag Model 3: Lag Varable Coeffcent P-value Coeffcent P-value Coeffcent P-value lnrlp(-) *** 00 lnrgdp 5.979*** 00.93*** 00.75** 0 lncp *** *** ** 3 tbl -25** 8 -*** ** 3 S 0.608*** *** 09 LQ CA -.529** ** 35 S*tbl ** 55 25*** 07 2*** 00 LQ*tbl * CA*tbl *** 00 Constant *** *** ** Note: lnrlp s log real bank credt to the prvate sector, lnrgdp, log real GDP; lcp, log consumer prce ndex; S, LQ, and CA are bank sze, lqudty and captalzaton levels respectvely; and * s a multplcaton sgn. 2 Lags on the nteracton terms; System dynamc panel-data estmaton; Sample: 200- Number of obs Lags on Instruments Wald ch *** *** *** H0: No autocorrelaton n frstdfferenced errors (AR())--p value for lag H0: No autocorrelaton n frstdfferenced errors (AR())--p value for lag *(**)*** mply statstcally sgnfcant at 0%(5%)% levels. Source: Author s computatons. In order to test the robustness of the results, estmatons were also made controllng for fxed and random effects, as well as dynamc panel data effects as suggested by Arellano-Bond. The fndngs are appended as Table II-B, and they support the null hypothess of exstence of BLC n Tanzana. In partcular, the coeffcent of the polcy rate s negatve and statstcally sgnfcant. Its magntude, at 26, compares well wth 283 obtaned n the parsmonous system dynamc panel data model. Lkewse, coeffcents of the nteracton terms on bank captalzaton and sze are postve and statstcally sgnfcant, supportng that the two bank characterstcs could be mportant sources of nformaton asymmetry n the bankng system. 5.2 Role of Bank sze n Explanng BLC To avod over-parameterzaton, the data set was splt nto two: small banks and large banks, and the results are summarzed n Table 3. The coeffcent of the polcy rate s negatve, as expected, and statstcally sgnfcant n the equatons for the small banks, but statstcally nsgnfcant n the models for large banks. Moreover, as before, the coeffcents of the nteracton terms of the polcy rate and sze and captalzaton measures are statstcally sgnfcant at 5% and %, respectvely (model 2). Snce the coeffcent of the polcy rate for the small banks (model 2) s -37 compared to -08 for large banks (model 2), t s lkely that small banks are more responsve to a monetary polcy shock than large banks. In the short to long term, for example, reacton by small banks to a percentage pont ncrease n the polcy rate would lead to a fall n the share of credt to GDP by percentage ponts. 79

12 Table 3. Dstrbutonal effect of monetary polcy on small- and large-bank loan supply Dependant varable: Real bank credt to the prvate sector Small banks Large banks Model : Lag Model 2: Lag Model : Lag Model 2: Lag Varable Coeffcent Coeffent Coeffcent Coeffcent lnrlp(-) *** 0.783*** 0.655*** lnrgdp.338*** 5.73*** *** lncp '-2.9* -.828*** tbl '-26* -37*** S LQ '-.33* CA S*tbl 09 09** -2 2 LQ*tbl * CA*tbl 0.35*** Constant '-5.928*** -792*** Note: lnrlp s log real bank credt to the prvate sector, lnrgdp, log real GDP; lcp, log consumer prce ndex; S, LQ, and CA are bank sze, lqudty and captalzaton levels respectvely; and * s a multplcaton sgn. 2 Lags on the nteracton terms; System dynamc panel-data estmaton; Sample: 200- Number of obs Lags on Instruments Wald ch *** 275.3***.77*** 20.50*** H0: No autocorrelaton n frstdfferenced errors (AR())--p value for lag H0: No autocorrelaton n frstdfferenced errors (AR())--p value for lag *(**)*** mply statstcally sgnfcant at 0%(5%)% levels. Source: Author s computatons. 5.3 Role of Ownershp Structure n Explanng BLC In order to capture asymmetrc reacton of banks basng on the ownershp structure, separate estmatons were made for domestcally-owned banks aganst foregn-owned banks, as well as prvately-owned banks aganst publc-owned banks. The results are summarzed n tables and 5. Domestcally-owned banks aganst foregn-owned banks Results n Table support the argument that, BLC n Tanzana may be operatng through both domestcally- and foregn-owned banks (model 2 for domestcally- and foregn-owned banks). The effect of a polcy change s, however, stronger through domestcally-owned banks compared to foregn-owned banks, wth a long-run reducton of the rato of credt to GDP of.5 percentage ponts and. percentage ponts, respectvely. Ths notwthstandng, the source of asymmetrc reacton dffers across the banks, n whch bank sze plays an mportant role for domestcally-owned banks, whle both captalzaton and sze matter for foregn-owned banks. Wth an nteracton term coeffcent of 0.26, more captalzed foregn banks seem to be much less responsve to a polcy change than do large or more captalzed domestcally-owned banks. Ths may be due to the fact that foregn-owned banks have the ablty to access other sources of funds abroad such as equty, whch enable them to meet ther loan commtments even n an envronment of polcy rate ncreases. 80

13 Table. Effect of monetary polcy on domestcally- and foregn-owned bank loan supply Dependant varable: Real bank credt to the prvate sector Domestcally-owned banks Foregn-owned banks Model : Lag Model 2: Lag Model : Lag Model 2: Lag Varable Coeffcent Coeffcent Coeffcent Coeffcent lnrlp(-) 0.69*** 63*** *** lnrgdp 5.583*** 5.97** 3.897*** 7.507*** lncp -.667*** -.728* -2.25* 6.3*** tbl -39** -39* -2-6*** S 0.238** 0.33*** 0.28* 99*** LQ.55*** 0.737*** CA 2.5**.092*** '-.56* -.00*** S*tbl 08 5*** 09 08** LQ*tbl CA*tbl *** Constant -68.2*** ** '-8.57*** *** Note: lnrlp s log real bank credt to the prvate sector, lnrgdp, log real GDP; lcp, log consumer prce ndex; S, LQ, and CA are bank sze, lqudty and captalzaton levels respectvely; and * s a multplcaton sgn. 2 Lags on the nteracton terms; System dynamc panel-data estmaton; Sample: 200- Number of obs Lags on Instruments Wald ch *** *** 79.85*** *** H0: No autocorrelaton n frstdfferenced errors (AR())--p value for lag H0: No autocorrelaton n frstdfferenced errors (AR())--p value for lag *(**)*** mply statstcally sgnfcant at 0%(5%)% levels. Source: Author s computatons. Prvately-owned banks aganst publc-owned banks The presence of both prvately- and publc-owned banks may as well be a source of asymmetrc reacton n the bankng system. Ths s because, unlke prvately-owned banks, publc-owned banks are not under pressure to make proft and, therefore, may opt not to cut-down ther loans followng a monetary polcy shock. In Table 5, the coeffcent of polcy rate for prvately-owned banks (model 2) s statstcally sgnfcant, whereas that for publc-owned banks (model 2) s nsgnfcant. Ths supports the presence of a weak BLC through publc-owned banks. Conversely, for prvately-owned banks, the effect of one percentage pont ncrease n the polcy rate would lead to a reducton of the rato of credt to GDP by percentage ponts n the short to long term. 8

14 Table 5. Effect of monetary polcy on prvately- and publc-owned banks loan supply Dependant varable: Real bank credt to the prvate sector Prvately-owned banks Publc-owned banks Model : Lag Model 2: Lag Model : Lag Model 2: Lag Varable Lag Lag Lag Lag lnrlp(-) 0.763*** 0.563*** 0.69** 3*** lnrgdp 3.552*** 5.222*** *** lncp *** -.653*** *** tbl -0-38*** S * *** LQ ** * CA * * 6.099*** S*tbl 05 0*** 56 28*** LQ*tbl 0.86*** 7-28 CA*tbl 0.6*** 5*** Constant *** *** *** Note: lnrlp s log real bank credt to the prvate sector, lnrgdp, log real GDP; lcp, log consumer prce ndex; S, LQ, and CA are bank sze, lqudty and captalzaton levels respectvely; and * s a multplcaton sgn. 2 Lags on the nteracton terms; System dynamc panel-data estmaton; Sample: 200- Number of obs Lags on Instruments.000 Wald ch *** *** 3.09*** 82.37*** H0: No autocorrelaton n frstdfferenced errors (AR())--p value for lag H0: No autocorrelaton n frstdfferenced errors (AR())--p value for lag *(**)*** mply statstcally sgnfcant at 0%(5%)% levels. Source: Author s computatons. 5. Economc Importance of BLC The dscusson n the subsectons above has concentrated on the statstcal sgnfcance of the model estmates. In ths sub-secton, we assess whether BLC has any economc sgnfcance n Tanzana. The focus s put on the coeffcent of the nteracton term between the polcy rate and the bank captalzaton measure (Table 2, model 2). The estmate of the coeffcent of the nteracton term s Further, n 20, the rato of captal (equty plus reserves) to total assets for the fve largest banks was 57, whle that for the small banks ( other 6 banks) was 338. Multplyng the coeffcent of the nteracton term (.e., 0.57) by the dfference between the ratos of captal to total assets (whch s 8) gves a dfference n the change n log lendng of approxmately 03. Ths mples that, n response to a 00 bass ponts (bps) change n the polcy rate, more captalzed bank would record an annual growth n lendng of approxmately 30 bps more than the poorly captalzed bank. Ths level s non-trval for a developng fnancal sector such as that of Tanzana Concluson and Polcy Implcatons Monetary polcy can nfluence economc actvty n the short to medum term, through a number of channels, ncludng nterest rate, bank lendng, balance sheet, and exchange rate channels. An mportant requrement n the desgn of approprate monetary polcy s, therefore, to understand the major transmsson channels for the specfc economy. Ths study uses a dynamc panel data models to emprcally nvestgate whether changes n the monetary polcy n Tanzana Captalzaton s chosen because t appears to be useful, not only n the general equaton, but also n the equatons for small banks and prvately-owned banks, relatvely more affected by monetary polcy changes. 2 Kashyap and Sten (2000) found an annual lendng growth of 60 bps between categores of large and small banks n the US. 82

15 nfluence bank lendng behavour. It also evaluates the dstrbutonal effects of the monetary polcy on banks wth dfferent balance sheet characterstcs and ownershp structures. The fndngs suggest that, the coeffcent of the polcy rate s negatve and statstcally sgnfcant, as expected. Lkewse, all coeffcents of the nteracton terms between the polcy rate and bank sze and captalzaton measures are postve and statstcally sgnfcant at % level. In separatng the data set, n lne wth ownershp structures, bank sze, and captalzaton, the respectve coeffcents were also statstcally sgnfcant. Furthermore, the lendng channel seems to be stronger through domestcally- and prvately-owned banks than t s wth foregn- and publc-owned banks. The fndngs lend support to the hypotheses that: frst, BLC operates n Tanzana, suggestng that bank loans are mportant channel through whch monetary polcy shocks are transmtted to the economy. The fndngs mrror the arguments that the bankng sector stll domnates the fnancal system n the country, whereas money, captal, and real estate markets are stll at ther nfant stages. Banks account for about three-quarters of the fnancal sector s assets, reflectng banks domnance of sources of fundng. Also, about two-thrds of bank fundng comes from prvate sector deposts, probably constranng banks n offsettng the decrease n funds from deposts by rasng funds from other sources. Second, banks react asymmetrcally to polcy changes nfluenced by sze, captal strength and ownershp structure. The lendng channel s stronger through domestcally-owned banks and prvately-owned banks than t s wth foregn-owned banks and publc-owned banks. The reason s that, for foregn-owned banks, they could enhance ther captal through rasng of equty abroad and/or beneft from retaned earnngs (reserves), whle for publc-owned banks, t could be because they are not under pressure to make proft and, therefore, may opt not to cut-down ther loans followng a monetary polcy shock. The fndngs on asymmetrc reacton to monetary polcy due to ownershp structure, together wth the quantfcaton of the economc mportance of BLC borrowng from Tanzanan data consttute the man contrbuton of ths study snce they were not covered n the prevous studes on Afrca (see, for example, Sche, 2005; Chbundu, 2009; and Sche and Njenga, 200). Although bank lqudty appears to be statstcally nsgnfcant n most of the estmatons, ths does not completely rule out ts role n nfluencng banks lendng behavour n the country. As shown earler, the rato of banks lqud assets to total assets was on average 25.63% between 200 and 202, and the polcy rate s negatvely correlated wth the lqudty ndcator. To the extent that the bankng sector holds sgnfcant lqudty, more lqud banks may be n a better poston to offset an exogenous contracton n deposts wthout cuttng ther loan s portfolo, thus solatng loan growth from monetary polcy changes. The anomaly wth the lqudty measure could partly be attrbuted to the modellng approach. Further tests could, therefore, be done allowng for monopolstc tendences and excess lqud condton n the model. Future studes could also attempt to shade lght on how monetary polcy changes affect the economc actvty through BLC. These weaknesses notwthstandng, the fndngs n ths study provde useful nsghts on the bank lendng channel of monetary polcy transmsson n Tanzana. The polcy mplcatons are that, n assessng the stance of the monetary polcy, besde short-term nterest rates, t s crtcal for the monetary authorty to trace banks reacton to monetary polcy changes as reflected n loan supply to the prvate sector. Such analyss should also factor n possble asymmetrc responses by banks nfluenced by sze, captalzaton, as well as ownershp structure. Acknowledgement I would lke to thank the Afrcan Economc Research Consortum for ther fnancal support and, for provdng forums to present drafts of ths paper. I am very grateful to Prof. Chrstopher Adam, Prof. Bo Sjöand Prof. Vctor Murnde for ther very constructve comments. Also, my grattude goes to the management of the Bank of Tanzana for allowng me to carry out the study. However, any omssons or remanng errors n ths paper should entrely be ascrbed to the author alone. References Altunvas, Y., Fazyloz, O., & Molyneux, P. (2002). Evdence on the bank lendng channel n Europe. Journal of Bankng and Fnance, 26, Angelon, I., Kashyap, A., & Mojon, B. (eds). (2003). Monetary Polcy Transmsson n the Euro Area. Cambrdge, Unted Kngdom: Cambrdge Unversty Press. Arellano, M., & Bond, S. (99). Some tests of specfcaton for panel data: Monte Carlo evdence and applcaton to employment equatons. Revew of Economc Studes, 78, Ashcraft, A. (2006). New evdence on the lendng channel. Journal of Money, Credt, and Bankng, 38, Bank of Tanzana (BoT). (200a). Tanzana Manland s 50 Years of Independence: A Revew of the Role and Functons of the Bank of Tanzana (96-20). Bank of Tanzana, Dar es Salaam. 83

16 Bank of Tanzana (BoT). (200b). Bankng Supervson Annual Report for 20, 5 th Edton. Bank of Tanzana, Dar es Salaam. Bank of Tanzana (BoT). (200). Bankng Supervson Annual Report for 200, th Edton. Bank of Tanzana, Dar es Salaam. Bernanke, B., & Blnder, A. (988). Money, credt and aggregate demand. Amercan Economc Assocaton, Paper and Proceedngs, 78(2), Bernanke, B., & Blnder, A. (992). The federal funds rate and the channel of monetary transmsson. The Amercan Economc Revew, 82, Blundell, R., & Bond, S. (998). Intal condtons and moment restrctons n dynamc panel data models. Journal of Econometrcs, 87, Brssms, S. N., & Dels, M. D. (2007). Identfcaton of a loan supply functon: A cross-country test for the exstence of a bank lendng channel. Workng Paper No. 5. Bank of Greece, January. Cetorell, N., & Goldberg, L. S. (2008). Bankng globalzaton, monetary transmsson, and the lendng channel. NBER Workng Paper No Chbundu, E. C. (2009). Bank specfc characterstcs and monetary polcy transmsson n Ngera: Evdence of bank lendng channel n an emergng market economy. Paper Presented at the 65 th Annual Congress of the Insttute of Internatonal Publc Fnance (IIPF), Cape Town, South Afrca, 3-6 August. Demrguc-Kunt, A., & Maksmovc, V. (998). Law, fnance, and frm growth. Journal of Fnance, 53, Erhmann, M., Gambarcota, L., Martnes-Pages, J., Sevestre, P., & Worms, A. (200). Fnancal systems and the role of banks n monetary transmsson n the Euro area. ECB Workng Paper No. 05. Gambacorta, L. (2005). Insde the bank lendng channel. European Economc Revew, 9, Ghosh, S. R., & Gosh, A. (999). East Asa n the aftermath: Was there a crunch? IMF Workng Paper No. 99/38. Guo, K., & Stepanyan, V. (20). Determnants of bank credt n emergng market economes. IMF Workng Paper No. /5. Huang, Z. (2003). Evdence of a bank lendng channel n the UK. Journal of Bankng and Fnance, 27, Kashyap, A. K., & Sten, J. C. (995). The mpact of monetary polcy on bank balance sheets. Carnege-Rochester Conference Seres on Publc Polcy, 2, Kashyap, A. K., & Sten, J. C. (2000). What do a mllon observatons on banks say about the transmsson of monetary polcy? Amercan Economc Revew, 90, Kashyap, A. K., Sten, J. C., & Wlcox, D. W. (993). Monetary polcy and credt condtons: Evdence from the composton of external fnance. Amercan Economc Revew, 83(), Kng, R. G., & Levne, R. (993a). Fnance and growth: Schumpeter mght be rght. Quarterly Journal of Economcs, 08, Kng, R. G., & Levne, R. (993b). Fnance, entrepreneurshp, and growth: Theory and evdence. Journal of Monetary Economcs, 32, Kshan, R., & Opela, T. (2000). Bank sze, bank captal and the bank lendng channel. Journal of Money, Credt and Bankng, 32, Levne, R., & Zervos, S. (998). Stock markets, banks, and economc growth. Amercan Economc Revew, 88, Mbowe, W. E. N. (200). Fnancal Sector Reforms and Development and ther Macroeconomc Implcatons n Tanzana. The Prnt Factory, Dar es Salaam. Mshkn, S. F. (995). Symposum on the monetary transmsson mechansm. Journal of Economc perspectves, 9(), Mshra, P., Montel, P., & Splmbergo, A. (200). Monetary transmsson n low ncome countres. IMF Workng Paper No. 0/223. Montel, P., Adam, C., Mbowe, W., & O Connell, S.. (202). Fnancal archtecture and the monetary transmsson mechansm n Tanzana. Internatonal Growth Centre, Workng Paper No. 2/033. 8

17 Morgan, P. D. (998). The credt effects of monetary polcy: Evdence usng loan commtments. Journal of Money Credt and Bankng, 30, Nord R., Sobolev, Y., Dunn, D., Hajdenberg, A., Hobdar, N., Mazad, S., & Rondet, S. (2009). Tanzana: The Story of an Afrcan Transton. Washngton, D.C.: IMF. Peek, J., & Rosengren, E. S. (995). Is bank lendng mportant for the transmsson of monetary polcy? An overvew. New England Economc Revew, Federal Reserve Bank of Boston, Issue November, 3-. Ramlogan, C. (200). The transmsson mechansm of monetary polcy: Evdence from the Carbbean. Journal of Economc Studes, 3(5/6), Sche, M. M. (2005). Bank lendng channel n South Afrca: Bank level dynamc panel data analyss. Department of Economcs, Unversty of Pretora, South Afrca. Sche, M. M., & Njenga, G. (200). Does bank-lendng channel exst n Kenya? Bank-Level Panel Data. Mmeo. Central Bank of Kenya, Narob. Sten, J. (998). An adverse selecton model of bank asset and lablty management wth mplcatons for the transmsson of monetary polcy, RAND Journal of Economcs, 29(3), Westerlund, J. (2003). A panel data test of the bank lendng channel n Sweden. Department of Economcs, Lund Unversty, December World Bank. (20). World Development Indcators 20. The World Bank, USA. Appendx I: Descrptve statstcs Table I-A. Descrptve statstcs of the varables Note: Annual data, sample: 200 to 20. Source: Author s computatons. 85

18 Appled Economcs and Fnance Vol., No. ; 207 Table I-B. Bank characterstcs Item Asset ratos Top 5 banks assets/total assets Bottom 5 banks assets/total assets Medum sze banks assets/total assets Foregn banks assets/total assets Domestc banks assets/total assets Publc banks assets/total assets Prvate banks assets/total assets Captalzaton ratos Top 5 banks captal/topp 5 banks assetss Bottom 5 banks captal/bottom 5 banks assets Medum sze banks captal/medum sze banks assets Top 5 banks captal/total assets Bottom 5 banks captal/total assets Medum sze banks captal/total assetss Foregn banks captal/total assets Domestc banks captal/total assets Publc banks captal/total assets Prvate banks captal/total assets Lqudty ratos Top 5 banks lqudy assets/top 5 banks assets Bottom 5 banks lqudy assets/bottom 5 banks assets Medum sze banks lqudy assets/medum sze banks assets Top 5 banks lqud assets/total assets Bottom 5 banks lqud assets/total assets Medum sze banks lqud assets/total assets Foregn banks lqud assets/total assets Domestc banks lqud aseets/total assets Publc banks lqud assets/total assets Prvate banks lqud assets/total assetss Source: Author s computatons. Table I-C. Correlaton coeffcents of the varables Note: Annual data, sample: 200 to 20. Source: Author s computatons. 86