metadata: authors: 0: author: Laeven, Luc
1: author: Klingebiel, Daniela
2: author: Kroszner, Randy
docna: 0: docna: Financial crises, financial dependence, and
            industry growth
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Industrial Economics,Financial Intermediation,Poverty Impact Evaluation,Poverty Monitoring & Analysis,Economic Growth,Financial Economics,Finance and Development,Poverty Assessment,Poverty Diagnostics,Poverty Lines,Small Area Estimation Poverty Mapping,Financial Sector Policy
teratopic: Poverty Reduction
abstracts: cdata!: The authors investigate the link between
            financial crises and industry growth. They analyze data from
            19 industrial and developing countries that have experienced
            financial crises during the past 30 years to investigate how
            financial crises affect sectors dependent on external
            sources of finance. Specifically, the authors examine
            whether the impact of a financial crisis on externally
            dependent sectors varies with the depth of the financial
            system. They find that sectors highly dependent on external
            finance tend to experience a greater contraction of value
            added during a crisis in deeper financial systems than in
            countries with shallower financial systems. They hypothesize
            that the deepening of the financial system allows sectors
            dependent on external finance to obtain relatively more
            external funding in normal periods, so a crisis in such
            countries would have a disproportionately negative effect on
            externally dependent sectors. In contrast, since externally
            dependent firms tend to obtain relatively less external
            financing in shallower financial systems (and hence have
            relatively lower growth rates in such countries during
            normal times), a crisis in such countries has less of a
            disproportionately negative effect on the growth of
            externally dependent sectors.
repnme: repnme: Financial crises, financial dependence, and
            industry growth
display_title: Financial crises, financial
            dependence, and industry growth
listing_relative_url: /research/2002/06/1943366/financial-crises-financial-dependence-industry-growth
topicv3: Economic Growth m1326241 471,Economic and Social Mobility m1326259 1152,Financial Intermediaries m1326973 2196,Finance and Growth m1327404 1081,Financial Sector Development m1327681 1920
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Poverty Reduction
origu: Financial Sector Practice (FSP)
no_of_pages: 32
model_extractions: 1 **PULilC** RXESEARCH W iORKiNG P APER _28055_

# Abstract

Laeven, Klingebiel, and Kroszner investigate the link ke-LW,een financial crises anA inAustr y g rowth. Thley analyze data from 19 industrial and developing countries that have experienced financiat crises during tne past 30 years to investigate how financial crises affect sectors dependent on external sources of finance. Specifically, the authors examine whether the impact of a financial crisis on externally dependent sectors varies with the depth of the financial system. They find that sectors highly dependent on external finance tend to experience **a grpntpr cnntrnction** of **valiuie** addelped **tduring n** rrisis in deeper financial systems than in countries with shallower financial systems. They hypothesize that the deepening of **the** financial systemL allows sectors dependent on external finance to obtain relatively more external funding in normal perioas, so a crisis **in** sucn counrries wouia nave a disproportionately negative effect on externally dependent sectors. In contrast, since externally dependent firms tend to obtain relatively less external financing in shallower financial systems (and hence have relatively lower growth rates in such countries during normal times), a crisis in such countries has less of a **dispnronrtinnntelv** neantive effect on the grnwth of externally dependent sectors.

This paper-a product of the Financial Sector Strategy and Policy Department-is part of a larger effort in the department to study the link between financial development and economic growth. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Rose Vo, room MC9-624, telephone 202-473-3722, fax 202-522-2031, email address hvo 1 @worldbank.org. Policy Research Working Papers are also posted on the Web at http:/ /econ.-orldbank.org. The **author, may** be contacted at **llaevenunworldbannL orga** dlingebiel@aworldbank.org, or randy.kroszner@gsb.uchicago.edu. June 2002. (26 pages)

> _The aevelopment Th Policy Polic Research issues._ -- **_An_** _Working_ **_uobjective_** _- _Paper of_ - . _ie Series series disseminates is_ . **_w gei_** _ L **_the_** _the_ Z'___ irndngs findings_ **_ouI quic,kly,_** _of_ **_-'LI_** _work_ - **_even_** _in_ --- _progress if_ Z **_rL.-L thc_** -- -- **_pt,esent"tiUns -_** _to encourage_ **_-_** _ -- _are the_ **_les_** _exchange .han_ **_ful;y II_r .1._** _of_ **_pvoi'ed._** __ ideas 1.1 about_ -L **_The_ I** _papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this pape ar en:.-!y hoseof be-u,+-rs They, do no, n..eessan.l- rpent the viwf thelW..d Bank,,4 i- ts 17-,cutiv Drct, or-t_ **_the_** _countries they represent. l_

Produced by the Research Advisory Staff
# Financial Crises, Financial Dependence, and Industry Growth

Luc Laeven, Daniela Klingebiel and Randy Kroszner** Preliminary drart Kevwords: financial criseq- financing constraints- financial development; industrv growth

****** The authors are at the World Bank, the World Bank, and the University of Chicago, the Council of Econornic Advisors and the National Bureau of Economic Research, respectively. Luc Laeven is corresponding author. E-mail: llaeveni)worldbank.org. Tel. 202 458 2939. We thank Stijn Claessens and Inessa Love for comments and Ying Lin for research assistance. Tihe opinions expressed do **not** necessarily **reiiect** euause **of the** 'Wor: **uriu vi thc Co-unti: oi** Economic Advisors. Comments welcome.
# **L. Introduction**

> While it is widely accepted that financial crises have adverse consequences for the economy as a whole, relatively little empirical work investigates the mechanisms by which financial crises generate problems in the real sector. In this paper, we analyze data from developed and developing countries that have experienced financial crises during the last 30 years to investigate the impact of cri1scs **onI** irLU1sUIal **roLWU** L i I oL&ULUIes. Understar **dIingU UUZi** i111pact **is C.ucial for ruILIaUinLg11** policies to mitigate the costs of a crisis in the financial sector to the economy as a whole and contributes to the literature on the mechanisms linking financial shocks and real economic activity.

Much theoretical work has been done on how financial intermediaries and financial markets facilitate investment by firms and, hence, promote economic growth (see Levine (1997) and Rajan and Zingales (1998) for comprehensive overviews). Financial intermediaries and financial markets **are grvaially UIVLou=L Lt reUuc ieiLiv** al aZatu **aiu** adverGVe **sIVle6LIVU jJIVLUeUI LIW.L** c **U Lar** mak raising extemal funds difficult and expensive for firms. Well-functioning and well-developed financial intermediaries and markets thus should disproportionately benefit firms that are most dependent on extemal funds to finance their growth. Conversely, crises in the financial sector should have a disproportionately negative impact on firms that rely heavily on external sources of finance. Specifically, we investigate whether the impact of a financial crisis on sectors dependent on extemal sources of finanLcing varies **witiL u1v** lvevl W. **UoVf** UPelII.etL o **UIV, MiBArLidI syLVItLI. Lv evaiuatL ui.** empirical relevance of this theoretical mechanism, our empirical work focuses on the differential impact of financial crises on sectoral growth.

To preview our results, we find that in well developed and deep financial systems, sectors highly dependent on extemal finance tend to experience a greater contraction of value added during a I
crisis than do externally dependent sectors in countries with shallower financial systems. As has been shown in previous work (Rajan and Zingales, 1998), the depth of the financial system appears to relax credit constraints to permit externally dependent sectors to grow faster during normal periods. To explain our results, we hypothesize that the depth of the financial system allows sectors dependent on external finance to obtain relatively more external funding in normal periods; so a ;Lsis **wJUl** hIave a UdFi VVIVtioateLY U&aLl V 1IeILVct **onU** VAL.Lally UIUepUeUVL LJlUs. **In V.ULUdbL,** since externally dependent firms tend to obtain relatively less external financing in shallower financial systems (hence, we observe relatively lower growth rates in externally dependent sectors in such countries during normal times), a crisis in such countries has less of a disproportionately negative effect on the growth of these sectors. These results provide evidence supporting the existence of a "credit channel" through which firms dependent on external finance are harmed **LLiOJ-oL** **_oi.iL_ JLmaely dLLU L1** peIrO1AJiod **oJf fLJL-La.iG** UisUCrs.

In the next section, we provide a more detailed motivation for the approach we are taking and relate our work to the existing literature. Section m explains our econometric approach. Section IV then describes the data and, in particular, how we measure financial dependence and how we define financial crises. Section V contains the results. Section VI presents a number of caveats and qualifications with respect to our analysis. Section VII concludes.

# **H. Motivations and relation to previous work**

There exists a large body of empirical literature on the link between finance and growth. Levine and Zervos (1998) study whether stock markets and banks promote economic growth. They find that measures of stock market liquidity and private sector credit have a strong independent 2
effect on growth. Controlling for potential biases, Beck, Levine, and Loayza (2000) argue that there exists a clear empirical relation between the level of financial intermediary development and economic growth. They find that financial intermediaries exert a large, positive impact on total factor productivity growth, which feeds through to overall economic growth.

Jayarante and Strahan (1996) provide evidence that financial markets can directly affect econorric g _Io,%?2b atIdylAthie_ rea.v **o** rgih f bar. re+;;cion ;r."^ 'he TT-;teA S0+t.- T.Mfind that the rates of real, per capita growth in income and output increase signiticantly following intrastate branch reform. Improvements in the quality of bank lending, not increased volume of bank lending, appear to be responsible for faster growth.

Rajan and Zingales (1998) examine whether financial development facilitates economic growth by reducing the costs of external finance to firms. They find that industrial sectors that are relat.ively morn.e in need of e W **i.Ance devel.op** `ropor.tion **oly** **_4 fat_** ;r.i con.es "a mth..oredeveloped financial markets. As we discuss in more detail in the next section, they also overcome some of the identification problems embedded in standard cross-country growth regressions by using an interaction between a country characteristic (financial development of a particular country) and an industry characteristic (external financial dependence of a particular industry) in addition to country indicators and industry indicators.

Demirga9-Kunt an.d M **_?irl.o1snovZc_ (1997)** show tuhat **w,ell-developed** finan.cial system.s are associated with extemally financed fimn growth. rhey also find that differences in legal systems affect firms' use of external financing to fund growth: in countries with efficient legal systems, a greater proportion of firms use long-term external financing.

There exists also a large empirical literature on the existence of a credit channel. This 3
literature tries to investigate to what extent adverse shocks to a borrower's net worth increase the cost of extemal financing, and through which channels these adverse effects occur. For households, Mishkin (1977) provides evidence of effects of household balance sheet conditions on consumer expenditures in the US during the 1973-75 depression.

Kashvap and Stein (2000) study the monetarv-transmission mechanism using quarterly data on every insured US comm.ercial bank for the period 19764993. They find that the im.pact of monetary policy on lending is stronger for banks with less liquid balance sheets, i.e., banks with lower ratios of securities to assets. Moreover, this pattem is largely attributable to the smaller banks. Their results support the existence of a "bank lending channel" of monetary transmission, though they do not allow us to make precise statements about its quantitative importance.

Peek and Rosengren (2000) use the Japanese banking crisis as a natural experiment to test WCUhICI a **ivan.** suply shJLJck Lafe **CLI I** LA **.ea** ecor.or... act CLiI **v .t.** B uts **1I'J...I"lY** was" to **_V.J_** US credit markets, yet connected through the Japanese bank penetration of US markets, this event allows one to identify an exogenous loan supply shock and ultimately link that shock to construction activity in U.S. commercial real estate markets. They exploit the variation across geographically distinct commercial real estate markets to establish conclusively that loan supply shocks emanating from Janan had real effects on economic activity in the United States.

**tiAggrea teL 4aIU** LiULarciai shvcAs canar.%AL thevcopvratLe **ui1c** seoLrU **_by_ ULL** LailJing **ceitGAUL,** iUr.L1u1g working capital and trade financing, to borrowers with valuable trading and investment opportunities (see Kashyap and Stein (1994) for a review). Real, financial or regulatory shocks can cause a real or perceived shortage of capital for banks. As a result, banks may become unwilling to lend even to viable companies and instead may prefer to invest excess liquidity in safe assets such as government

4
|WPS2854Rich_and_Powerful?Subjective|Michael Lokshin|June 2002|C.Cunanan|
|---|---|---|---|
|PowerandWelfareinRussia|MartinRavallion||32301|
bonds. A credit crunch can originate from weak financial institutions or from tightened<sup>regulation</sup> and supervision. Increased uncertainty about whether and at what price loans will<sup>be availablecan</sup> also result in a shortage of loanable funds (Stiglitz and Weiss, 1981). These effects<sup>can be</sup> particularly severe for bank lending because banks are more likely than other financial intermediaries or markets to lend to firms that suffer from a greater degree of informational asymmetries.

JU n audi-11ra z ll _A_ l.-,ce sheet **e,e** car **ltr ai.wplifi the** pffooft **of** shckhnsr nin corporations (see Bemanke and Gertier **(i995)** tor a review). Agenor and Aizenman<sup>**(Ii999),**Chan-</sup> Lau and Chen (1998), Kim and Stone (1999) in a domestic context and<sup>Greenwald (1999)inan</sup> international context show that generally weaknesses in the financial sector along with tighter regulation and supervision appear to contribute to corporate distress by curbing<sup>credit. Ding, Domac</sup> and Ferri (1998) and Ghosh and Ghosh (1999) provide some empirical evidence<sup>that tighter rules for</sup> 11i1llarlcal LllOtIL.^-JIOn zfetd h _upply MA larAU1,al L%nds%&_ insvrlco-;s ha.e n ntw. of corporates were also likely to have been important in reducing the supply of<sup>financing.</sup> Empirical research on identifying tools for the resolution and management of<sup>banking crises</sup> that are effective in resolving the crisis while limiting adverse economic spillover<sup>to the rest of the</sup> economy is sparse and most research in this area is limited to individual<sup>cases.Honohanand</sup> Klingebiel (2002) use cross-countrv evidence to determine whether specific<sup>crisis containmentand</sup> resoluLiVIn pol1icies syt...atiLcallJLLLy inluenceLL,JAV 141e fiscall costs _owf rewsolvir.g _a criisiss._ Tr1.-.e .fi.n.d hAct accommodating policies - such as blanket deposit guarantees, open-ended liquidity support, repeated recapitalizations, debtor bailouts, and regulatory forbearance<sup>-</sup> significantly increase fiscal costs of resolving a crisis. Claessens, Klingebiel and Laeven (2001) review<sup>the literature on crises</sup> resolution strategies.

5
# **III. Method**

> We apply the method in Rajan and Zingales (1998) to investigate the link between extemal financial dependence and industrial growth during financial crises. Rajan and Zingales (1998) relate re.al grnwth in va u e **_ndded nf_** a sertnr **tn** an intprqrtinn **ti'rm** that **inrhuiii1** a **pnrnoyv** f **foin2n,,-ial** development and an index of external financiai dependence. Tney snow tiat nrms that are reiatively more dependent on extemal finance develop disproportionally faster in countries with moredeveloped or deeper financial markets, that is, they find a positive relation between the interaction term and real growth in value added.

Their index of extemal dependence is constructed at the industry level based on data of US firrms Thevychonoe the finanrcial structure of US industriesaStheir be-ncimirk because the relatively open, sophisticated, and developed US financial markets shouid allow US firms to face the fewest obstacles to achieving their desired financial structure. This approach offers a valid and exogenous way to identify the extent of extemal dependence of an industry anywhere in the world under the assumption that there are technological and economic reasons why some industries depend more on extemal finance than others, and that these differences persist across countries. They also overcome some of thte identifirqtion prnblem.s emh.edded in standard cross-country growth rperessions by usingg an interaction between a counry cnaractenstic knnanciai aeveiopment of a particuiar country) and an industry characteristic (external financial dependence of a particular industry) in addition to country indicators and industry indicators. This approach allows them to isolate the impact of financial development on industry growth after controlling for cross-country and within-country differences, and is therefore less subject to criticism about an omitted variable bias or model 6
> specification than traditional approaches. Our main innovation is to apply this approach to industries

> in countries experiencing financial crises to be able to investigate the real impact of shocks to the financial system in a country over time.

> First, we estimate the basic model in Rajan and Zingales (1998) for our sample of countries

> (model 1).

> _RVAGR, = Ci + INDj +_ A _* SHARE, +_ P2 _* FDi *EDj + -,O_ (1)

where _R VA GR5,_ is the real growth in value added of sectorj in country _i, C,_ is a country dummy for country _i, ii-vD_ is an industry dummy for industryj, **_SHYLIEiJ_** is the snare ot sectorj in the totai value added of country _i, FDi_ is the development of the financial system of country _i, EDj_ is the external dependence ratio of sector ] according to Rajan and Zingales (1998). The specification thus _;nlVude_ ie o.tyrdi.us efcs euevLe at.ltvpUisfru. leveloffnrca **Ui!.UU~lkA~U AJUI_I O.IIU LULUUOUJ** '1 O YY **TV UOV UiILV il~LVLidLiaVCJVA** JLVO **ILU UIV** **_LVI_ U! 1UI1JAM4** development of a country: total credit to GDP, private sector credit to GDP, and M2 to GDP.

The main differences with the Rajan and Zingales (1998) setup is twofold. First, we estimate the model for two sub-periods, namely, before and during a financial crisis. When estimating the model for the crisis period, we use the pre-crisis levels of share in value added and our proxies for financial development to avoid potential endogeneity problems. Second, we estimate the model **for** crLisis **coLU Ucs** or.ly, **UIaL** is, for **lviu.uiv ulaL** arVe liLsteU :... **'aprii 4aU** Illlgvila (20u0.) as **IIdvil,g** experienced a financial crisis (and for which we have data). Note that by including country indicators into the regressions, we control for country-and industry-specifics. By including country 7
indicators for the crisis period, we are effectively controlling for the general severity of the crisis in each country.

We are also interested in the link between the interaction of financial dependence and financial development on the one hand and the difference in real growth in value added between the cr.isie ,pr:nd **_"nd_ thp** nr,-.ric ipriond **non** the **nthpr,khane Ti** _an_ in **altrrn,tivp** enpAfirnt.nn **nfmnroPl** (1), we therefore use the difference in real growtn in value added between the crisis period and the precrisis period as a dependent variable.

_ARVAGRU = Ci +NDj + Aj *SHAREij +p82 *FDi *EDj +e£_ (2) where _AR VAGR,_ is the difference in real growth in value added of sectorj in country i between the crisis period and the pre-crisis period. In other words, _AR VA GRi = R VA GRU Crais - R VA GRU,pre-crisis_ X where _RVAORiS,_ the re1 Qronwth in v21uenrl2ddedr nfePr-tnr _i_ **in** nniintrv _i_ **Am-rinc** thr s4is **npri.od** and _RVAGRy,pre-Crisij iS_ the real growth in value added of sectorj in country i during the pre-crisis period. To avoid potential endogeneity problems, we use the pre-crisis levels of share in value added and our proxies for financial development.

B101ecause +r **ar** - + **...** she i .fion FDi- * _EDjL -a_ the real growth in value added of sectorj in country _i, R VAGR 0,_ we also estimate the following model:

**_iVA_** _=_ **_Ci_** _+ lNL/j + p *_ + _i * HighEDj +_ **_ji_** _(3)_

8
> where _HighEDj_ is a dummy variable for "High External Dependence" that takes value of one if sectorj is among the top-50% of most financially dependent sectors of all sectors considered by Raian and Zingales (1998), and zero otherwise Thiq **sefip** provides a robustness che-k that controls for UiLeasuremenet error in **uie** extermai dependence ratio-of each sector estimated by Rajan and Zingales (1998). In other words, we may expect that the most financially dependent sectors show a different growth pattern in well-developed countries on average, but there may not necessarily be a different effect for the most financially dependent sector and the second most financially dependent

> sector. Similar to model (2), we also estimate the following model:

> . **_iK_ fTT** **_VA_ A L. tif** **_Li_** j **= Ct** **_fl_** ~ 17'VLj t . _Pi plSJHAR,_ **_f (Di_ 0 1** . **U** _+_ X **_-lT_ 2 *** **_T_** T T. _Hh_ **r** **_mn_ T.** **_+._** (4)

# IV. Data

The industry data is from Rajan and Zingales (1998). We use their measure of financial depe.n.denre **bh** sector based on US frn.-level data. Financial or external dendence is **colculat** as the fraction oI capital expenditures not financed with cash flow from operations. The sectors considered by Rajan and Zingales (1998) are a mix of three-digit and four-digit ISIC (International Standard of Industrial Classification) level industries. Rather than use the mix of four-digit level sectoral breakdowns for some industries and three-digit level sectorail breakdowns for other industries in Rajan and Zingales (1998) is somewhat arbitrary, we use external dependence ratios for sectors on a t.hree-digT4T*' **_SIC_** lee only. **WA f kotv.ntfo *e=ciSrulateI** t w **1he** h **_ed aveage_** exte.aldependence figure for the four-digit !SIC sectors on a tnree-digit ISIC level. For the sectors that are 9
already on a three-digit ISIC level in Rajan and Zingales (1998), we simply use their external dependence figures. For the sectors that are not already on a three-digit ISIC level, we apply the same method as in Rajan and Zingales (1998) to financial data on US finns from Compustat to estimate external dependence figures. Table 1 lists the three-digit ISIC level external dependence figures across sectors in the United States during the 1980s. We use these external dependence figures to cor-uc a hi. exe.aAeed.c _.IgL.D)d_ yval ht+le vlu foei etJi **~AL~LU** U%,a **L 1L"&11 V"%ALI.JLJaL** ~ **L.'IU** **_I&%5~_ L.JUUIILIIJ V** **_&JLUIO.1,_ LUCL&** "An.vo Y"iu"% **j.ii 'jJLIV iJ 0~.VLWJLJ wL** among the top-50% of most financially dependent sectors, and value of zero otherwise. Similarly, we construct a low external dependence _(LowED 1 )_ dummy variable that takes value of one if sectorj is among the bottom-50% of most financially dependent sectors, and value of zero otherwise.

As measure of firm performance we use real growth in industry value added (annually compounded), the same measure as in Raian and Zingales (1998). The data on value added for each _4_-_ **-nn-,** **_r, Cnn-d-,S . a a1.*-A 4rn*1-o T-A-. o4'~_ Q*n+ .44+n- VAr-4-nlr** **_A_ nfnk-ean++n~.. iL1lLU~L JL'** L **Ill I.GJ** _,_ **L UJU LLLJ L** _WULU 1_ **_%ALU_ L I %J JLII L1I'JA1.LL%ULLLL LL LI LULILLOLVUj** A VCLU WW% **_U L "JJ_ "UJ o'.** **_jFUL_ LW&J5UI4** **_U)'_** the United National Statistical Division. rhe value added data are corrected for inflation using CPI data from the Intemational Financial Statistics ofthe International Monetary Fund. We calculate the real growth in value added figures for sectors on a three-digit ISIC level as well. We also calculate the industry's share in total value added of the country, a variable used by Rajan and Zingales (1998). Our measures of financial deDth (total credit to GDP. Drivate sector credit to GDP. and M2 to GDP)F.u a,-uu,d he **evel** of Cj-DP p er c apitLa are fro,,,1 heI JLLtLerr.atioral inLancialC Statistics VI she International Monetary Fund.

We use the Caprio and Klingebiel (2002) data set to time crisis and pre-crisis periods. Since it is difficult to identify the crisis period precisely, we use (t- 1, t+l) as the crisis period, where t is the first crisis year reported in Caprio and Klingebiel (2002). To ensure that the pre-crisis period is a 10
**aisunct** penod not aiiectea by the cnsis, we separate the pre-cnsis penoa from me cnsis penoa Dy three years. We define the pre-crisis period to be (t-8, t-4), if t-8 is available, otherwise as many years towards t-8 as possible, where t is the first crisis year reported in Caprio and Klingebiel (2002). This restricts the pre-crisis period to a maximum of 5 years. We only allow for one crisis period in a country, which is the first crisis mentioned in Caprio and Klingebiel (2002). to avoid identification prbe. **1?** case **_o~f_ recp;r,-,** cr.ses.oo "J*^1%Jarnao ;i **ea0%** t%f* . **AA*r %I* flj0.a**

We started with the Caprio and Kiingebiei (2002) data set of systemic banking crisis countries. This data set includes 113 banlcing crises from 93 countries since the 1970s. Due to data constraints we need to drop a large number of countries. First, we do not have data on sectoral value added for many crisis countries. Second, we exclude countries for which we do not have data for both the pre-crisis and the crisis periods. This excludes, for example, Poland for which we do not have **LIaVY%** data **IWL" IVAl** _fo;_ +'ke U1%1 **_FL"-"'_** p-.4e=cii **_0 1 0_** period. **_j)I.LLlJ%A._** We **_TV_ %,** also "low'. **'.&Aj)** _A-o_ o-le for whic we **ZVJUU~II YWIUY%.., WV,** dop **UVF llIVJ** + hae-e-vau **114z** ' **V** --- **,i ,LLt.JL** +-- **V4LUv,** added data for at least five sectors. Tlhis excludes Argentina, for which we have only data available for four sectors during the pre-crisis period. The final data set includes 19 crisis countries, including both developing -and developed countries. Table 2 presents a list ofthese countries. For each country, the table also shows the average real growth in value added and the number of sectors during both the Dre-crisis and crisis period. We do not investigate the post-crisis periods, because we do not have suicieIntIL **UaLa** on pos-crisis yea.-s **foI** illaly **fU** the '-Lu s Hill **Ukvu baLuplv.** The number of sectors varies widely across countries from 10 sectors in Hungary to 28 sectors in Chile, Finland, Israel or Sweden. To ensure consistency in a country across periods, we examine the same sectors in both the pre-crisis and crisis periods. This excludes a number of sectors for several countries for which we could obtain data in only one sub-period. We note that this setup 11
may lead to a potential selection problem because the data in the Industrial Statistical Yearbook is gradually becoming more comprehensive over time. Another potential selection effect would exist if entire sectors disappear during the crisis period. The latter is however not the case in our sample. Since we are interested in the difference in growth between the pre-crisis and crisis period, we need to use a balanced panel. The final data set contains a total of 448 sector-country observations from 19 cr.sis cou,-,ies.

The number of firms within the sectors varies widely over time. In particular we see a large increase in the number of firms within certain sectors at certain points in time. This maybe the result of a re-classification or the inclusion of firms that were previously excluded from the statistics on value added. In both cases, changes in value added are not related to firm performance, and such observations need therefore be excluded from the analysis. We have deleted all sectoral observations **if LUe rLU.Ver** of LIJLS **lWULL** UI, sectoLraULU **OlVi.LL JL-L1 ULWar.** **_LV0U0 VI_ -/0 ,/0 (ubLL'U UL oLralIVeUj** between the pre-crisis and crisis periods. This criterion deletes around 5% of observations across the different sub-periods. We also have deleted observations if the real growth in value added exceeds 100%, which excludes only a small number of cases.

Table 3 presents the summary statistics of some variables that indicate changes in real sector and financial sector activity for both the pre-crisis and during crisis periods. When comparing the summary statistics of **tue** pre-L[I1b1 **d Lrbis cU** periods, we **irnu** Uth folluwigU C w lbi4almuLLisics. During crises periods, on average countries experience lower real GDP growth, lower real growth in sectoral value added (both for sectors that are highly dependent on external finance and sectors that are not), lower real growth of M2, and lower growth of (private sector) credit. Financial crises thus 12
> are negat-iiy **corrieyc** du wiui reut and **financial** sector activity and performance. T nese statistics aiso

> indirectly provide some reassurance about the appropriateness of the timing of the crisis periods. Table 4 presents the pre-crisis levels of our proxies for financial development for our crisis countries. The financial development proxies indicate relatively low levels of financial development in countries like Bolivia, Chile, Columbia, and Mexico, and relatively high levels of financial

> developm.enmt in Hulngar, Japan, and Spain.

# V. Results

First, we investigate the role of financial development on the link between external finance and sector growth for both pre-crisis and crisis periods. To this end, we estimate model (1) both for the pre-crisis period and the crisis period. The regression results are presented in panel A of Table 5. Each "pre-cr.sis" and "crisis" pair of columns Qes a dif,feren^.t r..easij of fin an.cial developm.,e.n.t. sAll standard errors are corrected for heteroskedasticity. Consistent with the findings in Rajan and Zingales (1998), we find for the pre-crisis "normal" period that financially dependent sectors grow on average disproportionally faster in countries with well-developed or deeper financial systems. In our sample, however, this result is statistically significant at the 10 percent level for only the total credit to GDP measure of financial development. This difference could partly be attributed to the fact th.at **,ve hav7e fewver obsei-.ations** th.an **Po2x,i 9mA** Zigae **(199)** since wefo.cus onc.ssw.ti Another reason could be that we use extemal dependence figures on a three-digit level only. Our coefficient estimates for both the value-added share and the interaction term also are somewhat smaller than in Rajan and Zingales (1998).

During crisis periods, we find the opposite relationship, namely, that financially dependent 13
> sectors grow disproportionably slower in countries with well-developed or deeper financial systems.

> In none of our specifications, however, is the coefficient on the interaction term between financial depth and external dependence statistically significantly different from zero.

In Panel B of Table _5;_ we investigate whether the crisis relation differs from the pre-crisis **relatinn hv iiuing the differe nce in real grnwth in vallie adiied hetwpen the rrkiq npinnd and the nre-** crisis period, _AR_ **_VALGRI,_** as dependent variabie (modei _(2)_ in tne previous section). As in Panel A we have three alternative specifications with each using a different measure of financial development. The reduction in growth rate from the pre-crisis period to the crisis period is _larger_ for financially dependent firms in countries with well-developed financial systems. The coefficient of the interact.ion ter is statistically significantly different from zero in two ofthe three specification. in other words, financially dependent firms appear to be hit aisproportionally by a financial cnsis it they operate in countries with developed financial systems. The effect is economically significant. A one standard deviation increase in credit-to-GDP, for example, would reduce the difference in real growth in value added between the crisis period and the pre-crisis period by 1.0 percent (and the mean decline in real growth in value added between the crisis period and the pre-crisis period is 6.0 Next, we use a dummy variable that indicates high or low extemral dependence rather than a continuous variable (models (3) and (4) in the previous section). The regression results are presented in Table 6. The coefficient estimates and levels of statistical significance in Table 6 are very similar to those in Table 5. The main difference with the results in Table 5 is that in Panel B the interaction term between _HighAED_ and _FD, is_ now statistically qianificantlv different frnm zero in 211 **three** specificalouls. LUCne rIesuls in T ables 5 and 6 suggests that in tiMies of crisis tere is a negative 14
relationsimp between the interacton term ot financial development or depth ot the financial system and external dependence and real growth in value added.

# **VI. Data and Measurement Caveats**

We note a number of caveats and qualifications with respect to our analysis. First, there is the qus^;no **fuh.** velibiiyo **d,~4ata+** dA..g crse.iMny **_._** leve.v aable **,,.L** rec **+...;** a **lag t.ad.** oe 'J%Aw~.W. **lwax'** "&W **IWI1A"WA"tjP** **_MJL~_** _%s"LL"r,_ %ILL% **IVJ.UIIY 1LILLUI-IVV%L VCGLIGUII..O** I **Va'L WI UI aG IrLU OuVF.I1'** shocks. Firm performance variables such as growth in value added tend to respond to financial crises with a lag. Perhaps growth in value added is not a good measure of firm performance, in particular during periods of crisis. In addition, financial development indicators such as credit to GDP tend to increase during periods of crises as GDP decreases to a larger extent than credit.

Second, determining the precise timing of crises is difficult, both in terms of identifying the **_4_** ~~ **'ninA** beE,=n..g **IJ~'&W1I** **_fka_ II''** **_p"A_ '1I1 6 41A4** r.dfheer. **_nfr_** of **.J±~11GW** a c.sis **_nr.co_** A **V A ..** **_-,_** .si **'IOIa11(13UULIAUj** **_cvo_** .. **-,n** ay **k ...** ld **A** **_-t_** p **_ni-nul-_ OLU** lol **V IY 13UIIU** a.drla **_.- A_ 111(a7 -nn. nn** not **LU** be **_U~_** r-esoleson **I** **_I-.a_** N **_.A_ CU U 0'JUh1.** Especially in the case of a typical V-shape pattern of recovery from a crisis it is crucial to get the timing right in order not to under- or overestimate the impact on firm performance. We use the data in Caprio and Klingebiel (2002) to define the beginning of a crisis and allow for a certain degree of mistiming by using a three year period around the Caprio and Klingebiel (2002) year as crisis period. Third, measures for the size of the financial system relative to GDP may not be good proxies for financial dev,elopmren.t. Durg periods of credit boomns, ofen. pr-eceding financial crises (see Kaminsky and Reinhart, 1999), for example, (private) credit over GDP may overstate the level of financial development or depth of the financial system. In addition, the political-economy of the policy responses to a financial crisis could affect the availability of credit in crises (see Kroszner (1998) and Klingebiel, Kroszner, Laeven and Van Oijen (2001)).

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Finally, one may question the appropriateness of the Rajan and Zingales (1998) proxy for financial dependence for our sample. Their approach uses US external dependence as proxy and assumes the same technological reasons that make a particular industry in the US more dependent on external finance than other industries in the US, also make this particular industry more depeder.t **on xtarnol** finance **in** all **ot4her co,uis** **_-ow,,i,A +'he_** ,rorldA **A 1*nirv** this asslaption is plausible, it may not hold for all countries for country-specific reasons. Many developing countries, for example, support certain industries through subsidies. These industries maybe less dependent on external finance than without those subsidies.

# VII. **Conclusions**

Trn normal crisic **_r,pinr.Aa_ tze** f;nA **th at fvikof** 4that **awe** ow,.l1 i **,n,we rn l awt** **_,rn_ vvtrnal** ... k _L -_ **VT** -Vr * **_I_** _ **_b-b_ A** **_a_** _ I **V** **_J_** *-SD **vlAf** W^_*__-J* **_L 0___** grow disproportionally faster in countries with deep financial systems consistent with Rajan Zingaies (1998). When we examine crisis periods, however, we find the opposite relation: crises in the financial sector have a disproportionately negative impact on sectors that rely heavily on external sources of finance in countries with deep financial systems. Our results provide evidence on the mechanisms linking the financial and real sectors in a financial crisis.

**4 WTe ma '.aesie th,at a** deeper0, fi.ncia~l **s..+... allows,** sectors~ depe.nde. **nt on.,+,....nl** **_Sfi.nn.-n_** _U-C&_ **aQ II J LJUL. U JIQI'.LUILOj** OLJ~ **LLJL "JLJL'J VY** 0 **_0%IA,L%J1 0 UV~LL A%JJIL LI.L VJLI_ VAI.%%J.LLUa IL111a1ln.%** to obtain relatively more external funding in normal periods, so a crisis would have a disproportionately negative effect on externally dependent firms in deeper financial systems. In contrast, since extemally dependent firms tend to obtain relatively less external financing in a shallower financial systems (hence the relatively lower growth rates in extemally dependent sectors in such countries during normal times)- a crisis in such countries has less of an effect on the arowth

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of these sectors. in addition, it could also be that deeper financiai systems are more efficient in enforcing hard budget constraints on firms during a financial crisis than are financial institutions in underdeveloped financial systems.

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