1-s2.0-S0929119915001236-main 1

The ?nancial crisis and corporate debt maturity:The role of banking structure

Víctor M.González ?

University of Oviedo,Department of Business Administration,Avda.del Cristo s/n,33071Oviedo,Spain

a r t i c l e i n f o a

b s t r a

c t

Article history:

Received 24February 2015

Received in revised form 1October 2015Accepted 3October 2015

Available online 12October 2015This paper analyses the in ?uence of the ?nancial crisis on corporate debt maturity for 39coun-tries during the period 1995–2012.The results reveal the importance of the dependence of ?rms on external ?nance and the banking structure of the countries on debt maturity during the ?nancial crisis.Corporate debt maturity was found to decline during the ?nancial crisis.However,only those ?rms that were more dependent on external ?nance before the onset of the ?nancial crisis suffered this reduction.The reduction in corporate debt maturity is the result of a higher average increase in short-term debt than in long-term debt.The ?nancial cri-sis had a stronger negative effect on corporate debt maturity in countries with less bank con-centration,while the debt maturity of larger ?rms decreased less as a result of the ?nancial crisis than the debt maturity of smaller ?rms in countries where banks play an important role in the ?nancing of the private sector.

?2015Elsevier B.V.All rights reserved.

JEL classi ?cation:G18G32

Keywords:

Financial crisis Debt maturity Institutions

Banking structure

1.Introduction

The global ?nancial crisis is considered by many economists the worst ?nancial crisis since the Great Depression of the 1930s.The current crisis has opened up an interesting debate regarding its consequences for the real economy.Financial institutions fac-ing losses may reduce the availability of credit and increase the cost of accessing credit.During the ?nancial crisis,this resulted in a credit crunch that played a crucial role in the failure of businesses,a decline in consumer wealth and a downturn in economic activity leading to the 2008–2012global recession and contributing to the European sovereign-debt crisis.An important strand of papers analysing the consequences of the ?nancial crisis has focused on its in ?uence on the lending channel.Most papers have shown that ?rm leverage and investment decreased as a consequence of the ?nancial crisis.

In this context,the aim of this paper is to study the impact of the current crisis on one aspect of capital structure,namely corporate debt maturity,analysing whether corporate debt maturity decreased as a result of the ?nancial crisis in line with the imposition of more stringent credit conditions for borrowers.The paper also considers how dependence on external ?nance and country-level determinants in ?uence the effect of the ?nancial crisis on debt maturity.

In contrast to the majority of previous papers analysing the impact of the ?nancial crisis on the real economy,we consider the in ?uence of the ?nancial crisis within an international context.1Fig.1shows the differences in the average ratio of long-term debt to total debt before and during the crisis for each country.The average ratio of long-term debt to total debt is calculated for the

Journal of Corporate Finance 35(2015)310–328

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Most of this literature has focused on the in ?uence of the ?nancial crisis within the US context (Almeida et al.,2011;Duchin et al.,2010;Ivashina and Scharfstein,2010;and Santos,2011,among others).The exception are the papers by Campello et al.(2010),Carvalho et al.(forthcoming)and Lins et al.(2013),which analyse the impact of the crisis on real decisions made by corporations in an international

context.

https://www.sodocs.net/doc/2f15120002.html,/10.1016/j.jcorp ?n.2015.10.0020929-1199/?2015Elsevier B.V.All rights

reserved.

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312V.M.González/Journal of Corporate Finance35(2015)310–328

periods1995–2007and2008–2012for each country.Differences in debt maturity can be seen to vary widely across countries.For example,the average percentage of long-term debt for?rms in South Korea,the USA and India decreased7%during the crisis compared to average values prior to2008.However,the average percentage of long-term debt increased sharply as a result of the?nancial crisis in countries such as Austria,Portugal and Brazil.In fact,the debt maturity of?rms increased in more than half of the countries included in the sample.This evidence thus reveals that the variation in corporate debt maturity during the?nancial crisis may be affected by differences in country characteristics.

The contribution of the paper comprises the analysis of the in?uence of the?nancial crisis on debt maturity in a large cross-country panel of data for the period1995–2012.We also study whether the effect of the?nancial crisis on corporate debt matu-rity is affected by?rm-and country-level determinants of debt maturity.In particular,we investigate whether this effect exists depending on the dependence of?rms on external?nance and on the banking structure of the country.First,Dell'Ariccia et al. (2008)and Duchin et al.(2010)provide evidence consistent with the bank lending supply shock being the origin of the reduction in performance or investment following banking crises.However,Kahle and Stulz(2013)show a decrease in borrowing and cap-ital expenditures for US industrial?rms that is not a consequence of a bank lending or credit supply shock.Within this context, we use the changes in corporate debt maturity during the crisis to investigate whether these changes are in line with a credit supply or a demand effect.Second,as the?nancial crisis had an important impact on the solvency of banks,the weight of bank credit in the?nancing of the private sector and bank concentration might in?uence the credit standards set by banks. We are not aware of any other study that has investigated the impact of the global?nancial crisis on corporate debt maturity within an international context.2Almeida et al.(2011)test whether US?rms with large fractions of their long-term debt maturing at the time of the crisis present more pronounced negative outcomes than otherwise similar?rms.Firms whose long-term debt was maturing right after the onset of the crisis cut their investment rates more than other?rms did.However,these authors do not analyse the effect of?nancial crisis on corporate debt maturity or how?rm and country characteristics in?uence the effect of the?nancial crisis on debt maturity.

The?ndings of the present paper are consistent with a small reduction in corporate debt maturity as a result of the?nancial crisis.However,this result conceals differences according to?rm dependence on external?nance and institutional features of the countries.Our?ndings show that the?nancial crisis had a negative effect on corporate debt maturity for those?rms with a great-er dependence on external?nance and in countries with lower levels of ef?ciency of the legal system and bank concentration.We thus show that the variation in corporate debt maturity during the?nancial crisis is consistent with a credit supply shock,as only ?rms that have more dependence on external?nance suffered reductions in debt maturity following the onset of the crisis. Furthermore,our results reveal that bank concentration helped to reduce the negative impact of the?nancial crisis on corporate debt maturity.This result is consistent with the idea that?rms in less concentrated credit markets are subject to greater?nancial constraints(Berlin and Mester,1999;Petersen and Rajan,1995)and in keeping with the bene?ts of relationship banking.How-ever,the negative effect of the?nancial crisis on corporate debt maturity was greater in countries where the weight of banks in the economy is signi?cant,affecting mainly smaller?rms.Finally,our results are robust to the use of alternative measures of the ?nancial crisis and reveal that the effect of the crisis on corporate debt maturity was greater during the period2010–2011.We also provide evidence that the effect of the?nancial crisis on corporate debt maturity depends on the intensity of the?nancial crisis.In fact,?rms in those countries where the decline in economic activity or the percentage of nonperforming loans are higher present a greater reduction in debt maturity.

The rest of the paper presents a review of the literature and discusses the implications tested in Section2,while Section3de-scribes the database and methodology employed.Section4discusses the empirical results and Section5provides robustness tests. Finally,Section6concludes the paper.

2.Literature review

The global?nancial crisis has opened up a debate regarding its consequences for the real economy.In this context,several pa-pers have analysed the impact of the?nancial crisis on the lending channel.Chari et al.(2008)call into question the way in which the?nancial crisis has affected the economy,showing that the crisis is not associated with a decline in bank lending.However, Ivashina and Scharfstein(2010)show that syndicated lending started to decline in mid-2007and fell sharply during the bank panic that began in September2008for US?rms.3They also highlight that there was a simultaneous run by borrowers who drew down their lines of credit,leading to an increase in loans reported on bank balance sheets.Their paper also shows that some banks were more adversely affected than others were.In fact,banks with more deposit?nancing cut their syndicated lend-ing less than banks without access to this more stable source of funding.

Evidence has not only revealed that lending has reduced as a consequence of the crisis,but that it has also led to an increase in borrowing costs and changes in investment decisions.Santos(2011)shows that?rms paid higher loan spreads during the

2Deesomsak et al.(2009)investigate the effects of?rm-speci?c and country-speci?c characteristics and the1997Asian?nancial crisis on the debt maturity structure of?rms in the Asia Paci?c region(Thailand,Malaysia,Singapore and Australia),comparing the consequences of the crisis for these four countries.Their paper reveals that the crisis had several signi?cant effects on both?rm-speci?c and market-wide determinants of debt maturity,especially in Thailand and Malaysia,where the crisis originated.

3The bank lending survey by the European Central Bank(ECB)shows that the?nancial crisis also reduced the credit issued by banks in European countries.This sur-vey is addressed to senior loan of?cers of a representative sample of euro area banks and is conducted four times a year.The sample group participating in the survey comprises around90banks from all euro area countries and takes into account the characteristics of their respective national banking structures.Detailed information on the survey and results are available at https://www.ecb.europa.eu/stats/money/surveys/lend/html/index.en.html.

subprime crisis and that the increase in loan spreads was higher for ?rms which borrowed from banks that incurred greater losses.In a survey of 1050CFOs,Campello et al.(2010)?nd that more than half the respondents cancelled or postponed their planned investments because of ?nancial constraints during the crisis.Furthermore,their evidence indicates that constrained ?rms report signi ?cantly larger planned percentage cuts compared to their peers in technology and capital spending and employ-ment.Carvalho et al.(forthcoming)show that the 2007–2009?nancial crisis is associated with equity valuation losses and invest-ment cuts to borrower ?rms with the strongest lending relationships with banks.Almeida et al.(2011)reveal that US ?rms whose long-term debt was largely maturating immediately after the third quarter of 2007cut their investment-to-capital ratio more than other similar ?rms whose debt was due well after the crisis.Duchin et al.(2010)also reveal that corporate investment by US ?rms declined signi ?cantly following the onset of the ?nancial crisis and this decline was greater for ?rms dependent on external ?nance.In line with this evidence,Vermoesen et al.(2013)report that Belgium ?rms which,at the start of the crisis,had a larger part of their long-term debt maturing within the next year experienced a signi ?cantly larger drop in investments in 2009.Moreover,this effect was mainly driven by ?rms which are more likely to be ?nancially constrained.Lins et al.(2013)show that family-controlled ?rms underperformed signi ?cantly compared to other ?rms during the global ?nancial crisis using a sample of 8584?rms from 35countries.All the above evidence thus reveals the important effects of the ?nancial crisis on the lending chan-nel,providing support for the existence of signi ?cant supply constraints in terms of both quantity and the price of the credit lead-ing to reductions in investment rates.

In this context,the present paper analyses the in ?uence of the recent ?nancial crisis on corporate debt maturity.Ivashina and Scharfstein (2010)and Campello et al.(2012)reveal that credit lines became particularly important during the ?rst quarters of the ?nancial crisis,as they replaced bank loans,providing the liquidity needed to invest during the crisis and ameliorating the negative impact of scarce credit on real activities.As most credit lines have a shorter maturity than bank loans (Jiménez et al.,2007),4we expect the ?nancial crisis to be associated with a shortening of corporate debt maturity.Moreover,the imposition of more stringent credit standards by banks,substituting long-term loans by shorter loans due to the solvency problems suffered by banks,may also lead to a reduction in debt maturity.Consequently,our ?rst hypothesis is as follows:H1.The ?nancial crisis has reduced corporate debt maturity as a result of the use of shorter debt.

However,we expect the in ?uence of the ?nancial crisis on corporate debt maturity not to have an equally detrimental effect on all ?rms and that the observed differences in debt maturities will depend on the dependence on external ?nance and on the structure of the banking system in each economy.

The in ?uence of ?nancial crises on corporate borrowing and investment may be explained from two alternative theories.On the one hand,credit supply shock theory poses that the credit system does not renew loans as a response to a shock in the ?nan-cial system 5(Brunnermeier,2009;Shleifer and Vishny,2010).According to this view,debt issuance and corporate investment should fall more for credit-dependent ?rms.On the other hand,the effect of the ?nancial crises on the real economy could be the result of a demand shock (Kahle and Stulz,2013).According to this theory,increases in uncertainty and decreases in the de-mand for products following ?nancial crises lead to a decrease in investment and hence in demand for credit to ?nance invest-ment.Dell'Ariccia et al.(2008)offer evidence that there is a real cost to banking crises,as sectors that are more dependent on external ?nance perform relatively worse during banking crises.Duchin et al.(2010)also provide evidence in line with a credit supply shock,as the decline in corporate investment following the recent ?nancial crisis is higher for ?rms that have low cash reserves or high net short-term debt,are ?nancially constrained or operate in industries dependent on external ?nance.However,Kahle and Stulz (2013)show evidence that is not in line with the view that a bank lending supply shock or a credit supply shock constitute predominant casual factors to explain the ?nancial and investment policies of ?rms during the recent crisis.In this con-text,our second hypothesis is the following:

H2.The reduction in debt maturity would be higher for ?rms with a greater dependence on external ?nance before the crisis if credit supply shock is the dominant effect.

Access to external ?nancing will partly depend on the banking structure of each economy.Banks are central to business activ-ity,as they are the main providers of debt ?nancing in most economies.Financial intermediaries directly in ?uence corporate ?nancial structure.They have advantages in collecting information (Diamond,1984)and incentives to use this information to discipline borrowers due to the fact that they bene ?t from economies of scale in obtaining information and do not suffer from free-rider problems.

Speci ?cally,we consider that the banking structure of the country might in ?uence the effect of the ?nancial crisis on corporate debt maturity.Fan et al.(2012)report a negative effect of the weight of banks in the economy on debt maturity as a result of bank preferences for short-term debt.Demirgü?-Kunt and Maksimovic (1999)also stress that short-term debt allows banks to use their advantages in monitoring borrowers.Short-term debt forces lenders to monitor corporate performance more frequently and enables the bank to change the terms of contract or not to renew the loan (Diamond,1991;Rajan,1992).Large ?rms have better access to domestic and international markets and are therefore usually less dependent on domestic bank credit.However,as they are subject to more ?nancing constraints,smaller ?rms will be affected to a greater extent by bank preferences.Conse-quently,we expect a negative relationship between the weight of banks in the economy and corporate debt maturity,particularly

4

Campello et al.(2012)?nd that the maturity of credit lines in their sample for European and US ?rms is about 30months before the crisis,while it is about 27months during the crisis (2008–2009).5

A more speci ?c theory is the bank supply shock theory,in which banks are the ones that reduce the supply of loans as a result of a shock in the ?nancial system.

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in the case of smaller ?rms.We forecast that this negative relationship will be stronger during the ?nancial crisis,as bank dif ?-culties lead banks to lend on a shorter-term basis,replacing long-term by short-term debt.In line with the above arguments,our third hypothesis is as follows:

H3.The weight of bank credit in the ?nancing of the private sector had a more negative effect on corporate debt maturity during the ?nancial crisis,especially in the case of smaller ?rms.

The banking literature suggests that bank concentration has two potential effects on ?rm leverage.In a market without asym-metric information,there will be a negative relationship between bank concentration and ?rm leverage given that higher bank market power results in a higher price for debt and less credit availability.However,in markets with asymmetric information,higher bank market concentration may increase the incentives of banks to invest in the acquisition of soft information by estab-lishing close relationships with borrowers over time.This will lead to greater availability of credit,thus reducing corporate ?nan-cial constraints (Boot,2000;Dell'Ariccia and Marquez,2004).

The importance of bank concentration has been argued by Petersen and Rajan (1995)and Berlin and Mester (1999).These authors show that US ?rms in less concentrated credit markets are subject to greater ?nancial constraints.They offer evidence from small business data indicating that creditors are more likely to ?nance credit-constrained ?rms when credit markets are concentrated be-cause it is easier for these creditors to internalize the bene ?ts of assisting ?rms.More recently,Barath et al.(2011)show the bene ?ts of borrowing from relationship lenders even for large ?rms with a much wider choice of ?nancing options available.The existence of a positive relationship between bank concentration and credit availability is in line with the fact that relationship banking serves to mit-igate information asymmetries between creditors and debtors.Given that long-term debt is subject to greater information asymmetries than short-term debt,the positive effect of bank concentration on leverage could be concentrated in long-term debt.Thus,a positive relationship might be assumed between bank concentration and debt maturity.From this point of view,the ?nancial crisis could have a weaker effect on corporate debt maturity because of the bene ?ts of relationship banking in those countries where bank concentration is higher,seeing as increased competition is likely to erode the bene ?ts of relationship lending.However,given that the ?nancial crisis has affected the solvency of banks,it could also result in the rupture of bank –?rm relationships.As both types of relation are theoretically possible,we make no a priori forecast as to whether relationship banking has increased or decreased as a result of the ?nancial crisis,treating it as an empirical issue.3.Databases,methodology and variables

Our source for ?rm data is the Worldscope database,which contains ?nancial statement data and stock prices from many countries in comparable form.Financial ?rms (SIC codes 6000–6999)were excluded.Finally,our sample comprises 30,727?rms and 171,892?rm-year observations for 39countries over the period 1995–2012.The sample includes countries with differ-ent institutional environments.

We use the following benchmark model to investigate the aggregate effect of the recent ?nancial crisis on the debt maturity structure of ?rms:

DEBT MAT it ?a 0ta 1ASSET MAT it ?1ta 2GROWTH it ?1ta 3SIZE it ?1ta 4FIRM QUALITY it ?1ta 5VOL EBIT it ?1ta 6LEV it ?1tb 1RULE OF LAW kt

tb 2C RIGHTS kt tb 3S RIGHTS kt tb 4BANK CREDIT kt tb 5BANK CONC kt ttb 6BOND kt tc 1DCRISIS tX kt

λkt tX jt

μjt tνi tεit

e1T

The dependent variable is debt maturity (DEBT_MAT);de ?ned as the percentage of the ?rm's total debt that has a maturity of

more than one year.DCRISIS is a dummy variable that takes the value of 1for the years 2008,2009,2010,2011and 2012,and zero otherwise.Our interest is focused on the coef ?cient of the DCRISIS variable and on the interaction of this variable with the ?rm's dependence on external ?nance and the country's banking structure.We therefore introduce interaction terms of the crisis dummy with the dependence of external ?nance and with the country variables considered in our benchmark model.

To analyse the in ?uence of the ?nancial crisis on corporate debt maturity,we control for the differences in the sample in terms of ?rm and country characteristics.We ?rst control for the differences in the sample in ?rm characteristics.To do so,we introduce ?rm-level variables suggested by theory which have been used in previous studies analysing ?rm debt maturity (Antoniou et al.,2006;Barclay and Smith,1995;Barnea et al.,1980;Guedes and Opler,1996;Myers,1977;Ozkan,2000;Scherr and Hulburt,2001;and Stohs and Mauer,1996).These variables include asset maturity (ASSET_MAT),growth opportunities (GROWTH),?rm size (SIZE),?rm quality (FIRM_QUALITY),earnings volatility (VOL_EBIT)and leverage (LEV).Our proxy measures of these determi-nants are constructed in line with the empirical literature on corporate debt maturity.Appendix A presents the de ?nitions of the variables used in the empirical analysis and their sources.

Second,identifying the impact of the ?nancial crisis on corporate debt maturity requires controlling for changes in country characteristics.The papers by Demirgü?-Kunt and Maksimovic (1999)and Fan et al.(2012)reveal that the institutional context in ?uences corporate debt maturity.Our estimations accordingly include proxies for country determinants of debt maturity.Fol-lowing the aforementioned papers,these variables are rule of law (RULE_OF_LAW),protection of investors'rights (C_RIGHTS and S_RIGHTS)and the weight of banks in the economy (BANK_CREDIT).In line with the potential effect of relationship banking on corporate debt maturity,we also include bank concentration (BANK_CONC).As corporate debt maturity might also depend on

314V.M.González /Journal of Corporate Finance 35(2015)310–328

the issuance of corporate bonds,we include a proxy of the ?rms'dependence on bond issues (BOND).This variable controls for potential substitution effects between bank debt and corporate bonds.6In countries where the corporate bond market is suf ?-ciently developed and ?rms are less dependent on bank loans,the effect of the ?nancial crisis on corporate debt maturity might depend on the evolution of bond markets during the crisis.

We have used the rule of law component from the Worldwide Governance Indicators (WGI)compiled by Kaufmann et al.(2009)to proxy the ef ?ciency of a country's legal system.Rule of law is one of the six dimensions of the WGI and captures per-ceptions of the extent to which agents have con ?dence in and abide by the rules of society,in particular the quality of contract enforcement,property rights,the police and the courts,as well as the likelihood of crime and violence (RULE_OF_LAW).The index ranges from ?2.5to 2.5,low levels denoting a less ef ?cient legal system.

We use the index developed in Djankov et al.(2007)to measure the legal rights of creditors against defaulting debtors (C_RIGHTS).This index is a development of the creditors'rights index proposed by La Porta et al.(1998),although the creditors'rights index is constructed in January each year in the former paper.It measures four powers of secured lenders in bankruptcy:

6

De Fiore and Uhlig (2014)show that non-?nancial corporations started shifting the composition of their debt from bank loans towards debt securities early in 2008.

Table 1

Descriptive statistics.

Panels A,B and C report the descriptive statistics of ?rm-level and country-level variables for the overall sample,before and during the crisis.DEBT_MAT is the percent-age of the ?rm's total debt that has a maturity of more than one year.ASSET_MAT is the ratio between net ?xed assets and total assets.GROWTH is the market-to-book ratio.SIZE is the natural logarithm of sales.FIRM_QUALITY is the ratio of net income plus depreciation to net debt.VOL_EBIT is the absolute value of change in earnings before interest and taxes.LEV is the ratio between total debt and the ?rm's market value.RULE OF LAW is one of the six dimensions of the Worldwide Governance In-dicators compiled by Kaufmann et al.(2009)and is a measure of the ef ?ciency of the legal system.S_RIGHTS measures the protection of property rights.C_RIGHTS mea-sures creditor rights.BANK_CONC is the fraction of assets held by the three largest commercial banks in each country.BANK_CREDIT is the ratio of private credit by deposit money banks to GDP.BOND is the sum of the private bond market capitalization to GDP plus the international debt issues to GDP.

Number of observations

Mean Median Standard deviation First quartile Third quartile Panel A:total sample DEBT_MAT (%)171,89247.1948.1934.0114.2377.35ASSET_MAT (%)171,89233.2230.3622.1915.5847.49GROWTH 171,892 1.79 1.21 2.020.69 2.15SIZE

171,892 5.19 5.15 2.09 3.88 6.50FIRM_QUALITY 171,892 2.220.3810.560.160.96VOL_EBIT 171,892 1.280.48 2.770.20 1.14LEV (%)

171,89233.0028.3125.0311.4550.88RULE_OF_LAW 171,892 1.09 1.320.700.75 1.66S_RIGHTS 171,89274.2870.0016.8970.0090.00C_RIGHTS

171,892 2.00 2.00 1.09 1.00 3.00BANK_CONC (%)164,50752.3046.7519.4436.1264.50BANK_CREDIT (%)154,38191.5998.4340.0154.98109.71BOND (%)

136,701

72.82

61.80

40.49

46.30

97.12

Panel B:before the crisis DEBT_MAT (%)99,15049.0950.6933.9217.5179.55ASSET_MAT (%)99,15033.7731.0021.6016.8647.47GROWTH 99,150 2.02 1.40 2.140.81 2.43SIZE

99,150 5.28 5.24 2.01 4.00 6.55FIRM_QUALITY 99,150 2.310.4210.670.18 1.01VOL_EBIT 99,150 1.220.45 2.670.19 1.08LEV (%)

99,15031.0525.9724.2210.4947.60RULE_OF_LAW 99,150 1.15 1.360.670.79 1.69S_RIGHTS 99,15076.5790.0016.3770.0090.00C_RIGHTS

99,150 1.99 2.00 1.11 1.00 3.00BANK_CONC (%)97,80750.9745.0320.0935.2663.68BANK_CREDIT (%)91,64886.5593.1436.4553.04110.93BOND (%)

82,02369.1960.4234.2147.2290.58

Panel C:during the crisis DEBT_MAT (%)72,74244.5844.4433.9610.2074.10ASSET_MAT (%)72,74232.4729.4622.9413.5947.50GROWTH 72,742 1.480.99 1.800.57 1.75SIZE

72,742 5.06 5.01 2.20 3.74 6.42FIRM_QUALITY 72,742 2.100.3410.410.130.88VOL_EBIT 72,742 1.370.52 2.890.21 1.23LEV (%)

72,74235.6431.8025.8513.0355.25RULE_OF_LAW 72,742 1.00 1.270.720.52 1.60S_RIGHTS 72,74271.1670.0017.0950.0090.00C_RIGHTS

72,742 2.02 2.00 1.05 1.00 3.00BANK_CONC (%)66,70054.2450.5818.2844.1667.03BANK_CREDIT (%)62,73398.96103.4143.6762.99107.13BOND (%)

54,67878.2667.3247.8945.05109.77

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316V.M.González/Journal of Corporate Finance35(2015)310–328

(1)whether there are restrictions,such as creditor consent,when a debtor?les for reorganization;(2)whether secured creditors are able to seize their collateral after the petition for reorganization is approved,i.e.whether there is no automatic stay or asset freeze imposed by the court;(3)whether secured creditors are paid?rst out of the proceeds of liquidating a bankrupt?rm;and(4)whether an administrator,and not management,is responsible for running the business during the reorganization.A value of one is added to the index when a country's laws and regulations provide each one of these powers to secured lenders.It consequently ranges be-tween0and4,with higher values indicating stronger creditors'rights or stronger protection against borrower expropriation.

We measure the protection of property rights by means of the index of private property rights(S_RIGHTS)published by the Heritage Foundation.This is an annual index of the degree to which private property rights are protected and the degree to which government enforces laws that protect private property.It also accounts for the possibility that private property may be expropriated, as well as analysing the independence of the judiciary,corruption within the judiciary and the ability of individuals and businesses to enforce contracts.This index ranges between0and100,a high score indicating greater legal protection of property rights.

We use two variables to proxy the country's banking structure.First,the weight of banks in the economy,measured as the annual ratio of private credit by deposit money banks to GDP(BANK_CREDIT).The data are obtained from the Financial Structure and Economic Database(Beck et al.,2006).Second,we also use a measure of bank concentration in a country.Following Demirgü?-Kunt et al.(2004)and Beck et al.(2006),we measure bank concentration as the annual fraction of bank assets held by the three largest commercial banks in the country(BANK_CONC).Figures are obtained from the World Bank Database, whose main source is Fitch IBCA's Bankscope Database.We control for the development of the bond market,measured annually as the sum of the private bond market capitalization to GDP plus the international debt issues to GDP(BOND).

Table2

Descriptive statistics by country.

This table reports the mean values of the dependent variables and country-level variables for each country.DEBT_MAT is the percentage of the?rm's total debt that has a maturity of more than one year.RULE OF LAW is one of the six dimensions of the Worldwide Governance Indicators compiled by Kaufmann et al.(2009)and is a mea-sure of the ef?ciency of the legal system and the protection of property rights.C_RIGHTS measures the protection of creditor rights.BANK_CONC is the fraction of assets held by the three largest commercial banks in each country.BANK_CREDIT is the ratio of private credit by deposit money banks to GDP.BOND is the sum of the private bond market capitalization to GDP plus the international debt issues to GDP.

Country Number of observations DEBT_MAT(%)RULE OF LAW S_RIGHTS C_RIGHTS BANK_CONC(%)BANK_CREDIT(%)BOND(%)

Argentina50345.16?0.5633.18140.4113.9532.94 Australia518649.76 1.7690.00365.45108.9995.84 Austria64950.71 1.8590.00364.64110.46109.74 Belgium104050.51 1.3985.91287.1382.86115.01 Brazil238551.38?0.2650.00151.4836.8026.18 Canada695859.88 1.7790.00160.2095.6161.99

Chile127857.30 1.2489.17254.9360.1023.04 Denmark126552.29 1.9090.34379.77124.06170.31 Finland117558.72 1.9390.43196.3574.8168.21 France527550.72 1.4272.15060.2698.7396.91 Germany575451.37 1.6890.00369.56110.50107.36 Greece251336.070.7255.09167.9778.7677.29 Hong Kong700937.65 1.4390.00470.17152.3848.95

India12,73353.870.0250.00231.4341.95–Indonesia249942.20?0.7333.29 2.0749.6025.67 6.73 Ireland40063.48 1.6890.00166.63152.15177.28 Israel163950.720.8970.00378.1590.92–

Italy211945.760.5359.12246.8893.4477.79 Japan29,63540.03 1.3376.26 1.2041.46104.7948.20 Malaysia734433.280.4953.00349.7599.8367.72 Mexico96863.71?0.4850.00060.9316.8823.87 Netherlands124956.71 1.7890.00378.94164.79166.93 New Zealand76965.90 1.8791.97478.60126.41–

Norway117766.98 1.9190.00293.2870.8441.56 Pakistan162134.71?0.8533.06146.5823.34–

Peru65241.66?0.6739.28074.3921.6213.17 Philippines103341.34?0.4939.66147.1030.2222.66 Portugal55951.35 1.1170.00185.00142.23102.71 Singapore463534.14 1.6590.00392.2896.7746.96 South Africa204944.690.1050.00377.7970.9027.30 South Korea11,48032.920.9073.26358.6992.2369.33 Spain122053.13 1.2070.00266.48146.62109.67 Sweden241658.89 1.8887.08195.4088.22107.83 Switzerland183660.02 1.8889.30184.63160.6896.81 Taiwan11,90133.060.8972.02228.92––

Thailand392732.840.0256.27 2.1048.4293.4917.43 Turkey191733.100.0353.15255.4626.857.29

UK893858.27 1.7289.27452.13159.6488.90

US16,18673.10 1.6189.54130.3351.78120.63

A potential problem when considering banking structure and the development of private bond market proxies is that these var-iables can themselves be affected by the development of other institutions or by corporate ?nancing decisions.We resolve this ques-tion regarding the potential endogeneity of these variables using instrumental variable estimation.We consider several variables as instruments of the weight of banks and bonds in the economy and bank concentration.The proxies for the role of banks and bonds in the ?nancing of ?rms in each economy are as follows:rule of law,the protection of creditor rights,the legal origin of the country,per capita GDP,the sum of short-term and long-term capital ?ows plus foreign direct investment into the country divided by GDP and the average ?rm size in each country (Demirgü?-Kunt and Maksimovic,1999).Similarly,we regress the observed value of bank concen-tration on the institutional quality of the country measured by the protection of property rights,on the legal origin of the country and on the market size proxied by the country's total population and total GDP (Cetorelli and Gambera,2001).Subsequently,we perform a Durbin –Wu –Hausman (DWH)test of overidentifying restrictions for each of the regressions.This test veri ?es the null hypothesis that the introduction of instrumental variables has no in ?uence on the coef ?cients of the estimations.We hence perform a DWH F test for each of the estimations in our paper,the results of which are reported in the bottom row of each table.When the p value of the F test falls below 10%,the null hypothesis is rejected and the instrumental variable estimations are reported.Otherwise,the estimations with the observed values of the banking structure variables are provided.

We include three speci ?c effects:country-year ∑kt

λkt

,industry-year ∑jt

μjt !and ?rm-speci ?c (νi )effects.These speci ?c

effects aim to control for most of the shocks affecting debt maturity.This approach has the advantage of being less likely to suffer from omitted variable bias or model speci ?cation than traditional regressions (Dell'Ariccia et al.,2008).

Table 1provides descriptive statistics on the ?rm-and country-level variables used in this paper,dividing the sample into the periods “before the crisis ”and “during the crisis ”.Panel A describes the entire 1995–2012period,while Panels B and C show the descriptive statistics before (1995–2007)and during (2008–2012)the crisis.Debt maturity can be seen to decrease during the crisis from a mean value of 49.09%to a mean value of 44.58%.This result is thus consistent with the ?nancial crisis shortening corporate debt maturity as per our prediction.However,this analysis does not take into account potentially signi ?cant differences in ?rm-and country-level characteristics resulting from the ?nancial crisis.As for ?rm control variables,asset maturity,growth opportunities,size and ?rm quality are seen to decrease during the crisis,while only volatility of earnings and leverage show an increase as a consequence of the crisis.Bank concentration and the role of banks and bond markets in the ?nancing of the pri-vate sector increased during the crisis.

Table 2reports the number of observations for each country and the mean values of country-level variables for each country.Debt maturity varies widely among countries:Thailand has the lowest level of long-term debt (32.84%),while the US has the highest per-centage of long-term debt (73.10%).There are also important differences in terms of the ef ?ciency of the legal system,protection of investors'rights,bank concentration,the weight of banks in the economy or the issuance of corporate bonds in each country.

Table 3presents the correlation matrix.DEBT_MAT shows a positive correlation with asset maturity,growth opportunities,size,leverage,rule of law,protection of property rights and development of the private bond market,but correlates negatively with ?rm quality,volatility of earnings,protection of creditor rights,bank concentration and the weight of banks in the economy.As noted previously,corporate debt maturity also correlates negatively with DCRISIS.In general,the correlations among ?rm-level variables are low.4.Empirical analysis

The estimations are carried out using panel data.Prior to testing,we used the Breusch –Pagan test (Breusch and Pagan,1980)to identify the existence of individual effects.The null hypothesis of no unobserved heterogeneity is rejected.In this context,a model that captures individual heterogeneity,as the panel data methodology does,is appropriate.The panel data methodology corrects for unobserved ?rm-speci ?c and time-speci ?c effects.The panel data estimation was calculated using ?xed effects,as the Hausman test (1978)rejects the null hypothesis of the lack of correlation between individual effects and observable variables in all regressions.All independent ?rm-level variables are lagged by one year to control for potential problems of endogeneity.

Table 4presents the results from the panel data estimation.Column (1)shows the results when considering ?rm-level determinants of debt maturity and the DCRISIS variable.First,the coef ?cient of DCRISIS is negative and signi ?cant,revealing that the debt maturity of ?rms decreased during the period of ?nancial crisis.In fact,the coef ?cient of DCRISIS in column (1)shows that ?rms reduced their debt maturity by 1%on average during the ?nancial crisis after considering ?rm-level determinants of debt maturity.This effect is lower when we also include country-level determinants.According to the results obtained in column (2),this reduction is just 0.42%and is not sig-ni ?cant,suggesting that the ?nancial crisis had a detrimental,but non-signi ?cant effect on corporate debt maturity.

Analysis of the results for the ?rm control variables shows that debt maturity is positively related to asset maturity.This is consis-tent with the matching hypothesis,according to which ?rms match assets and liabilities in order to reduce risk.The GROWTH variable shows a positive and signi ?cant coef ?cient,a result that is inconsistent with the agency cost hypothesis.Although the underinvest-ment problem identi ?ed by Myers (1977)suggests that debt maturity should decrease with growth opportunities,the empirical ?nd-ings of Stohs and Mauer (1996)are also in line with a positive relationship between growth opportunities and debt maturity.This positive relationship between growth opportunities and corporate debt maturity could be supported by the liquidity risk argument,according to which ?rms with long-term investment opportunities prefer to hedge against liquidity risk by issuing long-term debt (Antoniou et al.,2006;Diamond,1991;Guedes and Opler,1996).The effect of size on debt maturity is positive,indicating that larger ?rms have longer debt maturities.This relationship is consistent with the idea that ?rms with greater agency problems,i.e.small

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318V.M.González/Journal of Corporate Finance35(2015)310–328

Table3

Correlations.

This table presents the correlation matrix.DEBT_MAT is the percentage of the?rm's total debt that has a maturity of more than one year.ASSET_MAT is the ratio be-tween net?xed assets and total assets.GROWTH is the market-to-book ratio.SIZE is the natural logarithm of sales.VOL_EBIT is the absolute value of change in earnings before interest and taxes.FIRM_QUALITY is the ratio of net income plus depreciation to net debt.LEV is the ratio between total debt and the?rm's market value.RULE OF LAW is one of the six dimensions of the Worldwide Governance Indicators compiled by Kaufmann et al.(2009)and is a measure of the ef?ciency of the legal system. S_RIGHTS measures the protection of property rights.C_RIGHTS measures creditor rights.BANK_CONC is the fraction of assets held by the three largest commercial banks in each country.BANK_CREDIT is the ratio of private credit by deposit money banks to GDP.DCRISIS is a dummy variable that takes the value of1for the years 2008,2009,2010,2011and2012,and zero otherwise.FD is the ratio of debt and total assets one year before the onset of the crisis,in December2006.DCRISIS1is a dummy variable that takes the value of1for the years2008and2009,and zero otherwise.DCRISIS2is a dummy variable that takes the value of1for the years2010 and2011,and zero otherwise.DCRISIS3is a dummy variable that takes the value of1for the year2012,and zero otherwise.CRISIS_INTENSITY1is the difference be-tween the mean GDP growth for the period2008–2012minus the mean GDP growth for the period2003–2007.CRISIS_INTENSITY2is the non-performing loans for each country during the period2008–2012.***,**,and*represent signi?cance at the1%,5%and10%levels,respectively.

DEBT_MAT ASSET_MAT GROWTH SIZE FIRM_QUALITY VOL_EBIT LEV RULE_OF_LAW S_RIGHTS

ASSET_MAT0.178***

GROWTH0.099***?0.103***

SIZE0.222***?0.011***0.067***

FIRM_QUALITY?0.115***?0.067***0.069***0.018***

VOL_EBIT?0.028***?0.004?0.022***?0.101***?0.037***

LEV0.071***0.219***?0.363***0.041***?0.240***0.067***

RULE_OF_LAW0.137***?0.148***0.099***0.164***?0.018***0.024***?0.170***

S_RIGHTS0.141***?0.117***0.094***0.152***?0.019***0.025***?0.142***0.908***

C_RIGHTS?0.092***?0.016***?0.021***?0.132***0.006**0.011***?0.020***0.068***0.167*** BANK_CONC?0.033***?0.056***0.016***?0.075***?0.006**0.021***?0.062***0.282***0.243*** BANK_CREDIT?0.078***?0.131***?0.037***0.059***?0.015***0.028***?0.059***0.563***0.495*** BOND0.206***?0.128***0.113***0.048***?0.018***0.012***?0.078***0.518***0.466*** DCRISIS?0.066***?0.029***?0.133***?0.052***?0.010***0.028***0.091***?0.104***?0.158*** DCRISIS?FD?0.030***0.061***?0.153***0.063***?0.069***0.026***0.308***?0.060***?0.104*** DCRISIS1?0.031***?0.010***?0.094***?0.056***?0.015***0.010***0.086***?0.063***?0.115*** DCRISIS2?0.039***?0.022***?0.053***?0.032***0.0010.028***0.019***?0.052***?0.070*** DCRISIS3?0.022***?0.008***?0.038***0.029***0.001?0.005*0.019***?0.032***?0.031*** CRISIS_INTENSITY1?0.038***?0.040***?0.109***?0.038***?0.010***0.022***0.099***?0.044***?0.095*** CRISIS_INTENSITY2?0.029***0.000?0.094***?0.028***?0.009***0.007**0.120***?0.248***?0.288***

?rms,may use shorter-term debt to reduce underinvestment and risk-shifting problems.FIRM_QUALITY has a negative in?uence on debt maturity,indicating that high-quality?rms tend to issue short-term debt as the incentives to lengthen the maturity of debt in-creases with the risk of not being able to refund debt.The coef?cient of VOL_EBIT is negative,though not statistically signi?cant at standard levels;hence,we do not obtain evidence in line with the tax hypothesis.According to this hypothesis,the maturity of debt should rise when the volatility of?rm value decreases.This is because?rms with high volatility in their value have to change their capital structure frequently to reduce bankruptcy costs and will hence use more short-term debt(Kane et al.,1985).Leverage shows a positive relationship with debt maturity in a way that is consistent with the arguments put forward by Diamond(1991), as liquidity risk increases with leverage and hence highly leveraged?rms can be expected to use more long-term debt.Moreover, this effect dominates the use of leverage and debt maturity as substitutes in mitigating under-and overinvestment problems.

To sum up,we?nd strong evidence that the?rm characteristics that have been found to affect debt maturity in the existing literature are also relevant for the?rms in our sample.As regards the?rm-level control variables,our results thus provide strong evidence in line with the matching maturity and liquidity risk explanations.

Column(2)shows the results when the country-speci?c determinants are considered.All the results for?rm-speci?c variables discussed previously are maintained when the country-level determinants of debt maturity are included in the estimations.The RULE_OF_LAW variable has a positive coef?cient,indicating that?rms in countries with strong legal enforcement have longer debt maturity.However,this coef?cient is not found to be statistically signi?cant.This lack of signi?cance of the RULE_OF_LAW variable could be explained by its high correlation with S_RIGHTS.7Consequently,we exclude the S_RIGHTS variable in column (3).In spite of the results being similar for RULE_OF_LAW when the S_RIGHTS variable is excluded,the proxy for the protection of property rights is excluded from the estimations in the rest of the paper and RULE_OF_LAW is considered as a proxy of the enforcement of law and the protection of property rights.

The level of protection of creditor rights(C_RIGHTS)is seen to positively in?uence corporate debt maturity.Firms in countries with strong protection of creditors'rights tend to issue debt with a longer maturity.Stronger creditor protection gives lenders more power during bankruptcy.Besides,a greater ability to force repayment will exert an ex ante in?uence on the terms of the credit.This increases the recovery rate of loans and reduces the risk to lenders.Moreover,stronger protection of creditors' rights reduces the likelihood of?rms engaging in excessive risk taking and asset substitution.The positive relationship between the protection of creditors'rights and corporate debt maturity suggests that creditors lend on more favourable terms when their rights are strongly protected and is consistent with the evidence provided by Qian and Strahan(2007)for bank loans.

7In fact,the measure of the ef?ciency of the legal system(RULE_OF_LAW)considers not only the quality of contract enforcement,but also the protection of property rights,while the measure of protection of property rights(S_RIGHTS)also takes into account the degree to which government enforces laws.

As far as the banking structure variables are concerned,the maturity of debt is seen to increase in countries in which bank concentration (BANK_CONC)is high.This result suggests that higher bank concentration increases bank incentives to establish close relationships with borrowers over time,thus reducing the ?nancial constraints on ?rms.It is consistent with the ?ndings of Hernández-Cánovas and Ko?ter-Kant (2008),who show that stronger ?rm –bank relationships lengthen the maturity of bank loans for a sample of small and medium-sized European enterprises.

The weight of banks in the economy (BANK_CREDIT)is seen to have a negative in ?uence on debt maturity.This result is in line with the evidence provided by Fan et al.(2012).These authors obtained a negative relationship between the weight of banks in the economy and debt maturity,which is consistent with the preferences of suppliers of capital having an in ?uence on debt maturity structures.As for the development of the private bond markets,we show that it has a positive effect on corpo-rate debt maturity,in line with the longer maturity of bonds than bank loans.

Following Dell'Ariccia et al.(2008)and Duchin et al.(2010),we assume that the debt maturity of ?rms which were more de-pendent on external ?nance before the onset of the crisis is more likely to be affected by the supply effect of the crisis.Columns (4)to (6)of Table 4report the analysis of the changes in debt maturity in more ?nancially dependent ?rms.We de ?ne a new variable,DCRISIS ?FD,which is the interaction term between the DCRISIS variable and the ratio of debt and total assets in December 2006(FD).The coef ?cient of this interaction term (DCRISIS ?FD)will be the differential effect of the ?nancial crisis on corporate debt maturity for those ?rms with a greater dependence on external ?nance before the onset of the crisis.A negative coef ?cient of DCRISIS ?FD would suggest that corporate debt maturity decreased more in more ?nancially-dependent ?rms as a consequence of the recent ?nancial crisis and would be the expected result if the reduction in corporate debt maturity were caused by a credit supply shock.

The coef ?cients of the interaction terms between the variable identifying the crisis years (DCRISIS)and the ?rms'external de-pendence (FD)are negative and statistically signi ?cant at conventional levels regardless of whether we control for ?rm-level char-acteristics or whether we also control for country-level determinants of corporate debt maturity.Thus,evidence consistent with the existence of a credit supply effect on corporate debt maturity following the recent ?nancial crisis is provided.

The results for the DCRISIS variable in columns (4)to (6)in fact reveal the existence of a positive effect of the ?nancial crisis on cor-porate debt maturity for those ?rms that depended less on external ?nance before the onset of the crisis,as the coef ?cient is positive and statistically signi ?cant at standard levels.The coef ?cients in columns (5)and (6)show that ?rms that were less dependent on external ?nance increased their debt maturity by 1.25–1.29%on average during the ?nancial crisis.The coef ?cients and their signi ?cance for the remaining explanatory variables,i.e.?rm-and country-level variables,are similar to those we found previously.Thus,the results are maintained when we consider whether a credit supply effect exists or not in corporate debt maturity.

Table 5shows the results when we investigate the way in which the ?nancial crisis in ?uenced corporate debt maturity.We consider three different dependent variables,the ratios between total debt (columns (1)and (2)),long-term debt (columns

C_RIGHTS BANK_CONC BANK_CREDIT BOND DCRISIS DCRISIS ?FD DCRISIS1DCRISIS2DCRISIS3CRISIS_INTENSITY1

0.464***0.283***0.385***0.030***0.075***0.285***0.014***0.082***0.152***0.110***?0.0030.064***0.109***0.0010.556***0.007***0.033***0.084***0.046***0.533***0.328***0.010***0.070***0.084***0.088***0.548***0.293***?0.214***0.0020.007***0.047***0.014***0.321***0.148***?0.125**?0.129***0.064***0.150***0.269***0.205***0.784***0.441***0.422***0.429***0.246***?0.080***

?0.002

0.043***

0.252***

0.673***

0.402***

0.331***

0.388***

0.220***

0.711***

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V.M.González /Journal of Corporate Finance 35(2015)310–328

(3)and (4)),and short-term debt (columns (5)and (6))and the market value of assets.8The market value of assets is de ?ned as total assets minus the book value of equity plus the market value of equity.By using these three measures of leverage as depen-dent variables,we aim to better understand the effect of the recent ?nancial crisis on corporate debt maturity.As ?rm-level con-trol variables,we use the traditional determinants of ?rms'capital structure indicated by Rajan and Zingales (1995):pro ?tability,growth opportunities,asset tangibility and ?rm size.We measure pro ?tability (PROFITABILITY)as earnings before interest and taxes plus depreciation expenses and provisions (non-cash deductions from earnings)divided by total assets.We use the market-to-book ratio,as in Rajan and Zingales (1995)and Flannery and Rangan (2006),as a measure of growth opportunities (GROWTH).Following Titman and Wessels (1988),we proxy the tangibility of assets by the percentage of property,plant and equipment in total assets (TANGIBILITY).We use the natural logarithm of total sales (SIZE)as the measure of ?rm size.We also control for the protection of creditors'rights (C_RIGHTS)using the index developed in Djankov et al.(2007),as the papers by Demirgü?-Kunt and Maksimovic (1999),Giannetti (2003)and González and González (2008)show that institutions that fa-vour creditors'rights and ensure stricter enforcement are associated with higher leverage.Additionally,we include DCRISIS to de-termine how the crisis affected leverage and DCRISIS ?FD to investigate whether the credit supply effect may explain the observed variation in corporate debt structure or not during the ?nancial crisis.

8

Welch (2004)argues that we should use market leverage ratios given that theories of target ratios are implicitly about market leverage ratios.

Table 4

Debt maturity and the ?nancial crisis.

Regressions are estimated using panel data.The dependent variable (DEBT_MAT)is the percentage of the ?rm's total debt that has a maturity of more than one year.ASSET_MAT is the ratio between net ?xed assets and total assets.GROWTH is the market-to-book ratio.SIZE is the natural logarithm of sales.FIRM_QUALITY is the ratio of net income plus depreciation to net debt.VOL_EBIT is the absolute value of change in earnings before interest and taxes.LEV is the ratio between total debt and the ?rm's market value.DCRISIS is a dummy variable that takes the value of 1for the years 2008,2009,2010,2011and 2012,and zero otherwise.FD is the ratio of debt and total assets one year before the onset of the crisis,in December 2006.RULE_OF_LAW is one of the six dimensions of the WGI and is a measure of the ef ?ciency of the legal system.S_RIGHTS measures the protection of property rights.C_RIGHTS measures creditor rights.BANK_CONC is the fraction of assets held by the three largest com-mercial banks in each country.BANK_CREDIT is the ratio of private credit by deposit money banks to GDP.BOND is the sum of the private bond market capitalization to GDP plus the international debt issues to GDP.The Durbin –Wu –Hausman statistic tests the null hypothesis that the introduction of instrumental variables has no in-?uence on the coef ?cients of the estimations.We report instrumental variable estimations if the test is signi ?cant at the 10%level.Country-year,industry-year and ?rm-speci ?c effects are included in all the estimations,although we do not report their coef ?cients.T-statistics are in parentheses.***,**,and *represent signi ?cance at the 1%,5%,and 10%levels,respectively.

(1)

(2)(3)(4)(5)(6)Intercept 0.4404***(50.35)0.4084???(14.96)0.4049???(14.93)0.4423???(50.56)0.4154???(15.21)0.4124???(15.19)ASSET_MAT 0.0553***(6.34)0.0353???(3.42)0.0354???(3.43)0.0536???(6.14)0.0333???(3.22)0.0333???(3.23)GROWTH 0.0035***(6.76)0.0034???(5.75)0.0034???(5.74)0.0037???(7.15)0.0036???(6.12)0.0036???(6.11)SIZE

0.0039**(2.54)

0.0081???(4.46)

0.0082???(4.50)

0.0032??(2.08)

0.0074???(4.05)

0.0074???(4.08)

FIRM_QUALITY ?0.0009***(?9.77)?0.0008???(?8.03)?0.0008???(?8.02)?0.0009???(?9.64)?0.0008???(?7.92)?0.0008???(?7.92)VOL_EBIT ?0.0002(?0.85)?0.0000(?0.05)?0.0000(?0.07)?0.0002(?0.80)?0.0000(?0.01)?0.0000(?0.02)LEV 0.0497***(9.59)

0.0628???(10.19)0.0623???(10.13)0.0472???(9.09)0.0602???(9.74)0.0597???(9.69)DCRISIS ?0.0100***(?4.94)

?0.0042(?1.40)

?0.0038(?1.29)

0.0061??(2.04)

0.0125???(3.18)

0.0129???(3.29)

DCRISIS ?FD ?0.0566???(?7.20)

?0.0583???(?6.51)?0.0586???(?6.54)RULE_OF_LAW 0.0109(0.83)0.0090(0.69)0.0099(0.75)0.0083(0.63)C_RIGHTS 0.0186???(4.44)0.0181???(4.35)

0.0183???(4.37)0.0179???(4.29)

S_RIGHTS ?0.0002(?1.15)?0.0002(?0.98)BANK_CONC 0.0849???(5.96)

0.0832???(5.87)

0.0790???(5.54)

0.0776???(5.47)

BANK_CREDIT ?0.1258???(?3.76)?0.1383???(?4.38)?0.1290???(?3.86)?0.1397???(?4.42)BOND

0.0007???(3.75)

0.0008???(4.27)

0.0007???(3.93)

0.0008???(4.41)

Hausman test 1418.97***1211.82***1117.94***1538.29***1251.58***1179.62***F test

45.59***23.88***25.49***46.23***25.05***26.65***#observations 135,621101,460101,460135,621101,460101,460#?rms

27,88121,59521,59527,88121,59521,595Durbin –Wu –Hausman test

–

4.00***

5.36***

–

4.72***

5.99***

320V.M.González /Journal of Corporate Finance 35(2015)310–328

The coef ?cients of the ?rm-level control variables are as expected.The coef ?cient of PROFITABILITY is negative for total and short-term leverage.This ?nding is in line with the pecking order theory,as higher pro ?tability increases the possibility of retaining earnings,thus reducing the use of debt.The negative coef ?cients for growth opportunities re ?ect higher agency costs between shareholders and debtholders and higher costs of ?nancial distress.The positive coef ?cients of TANGIBILITY in all the estimations are consistent with the greater value of these assets as collateral.Firm size has a positive impact on the total and long-term debt of ?rms,which is consistent with size being an inverse proxy for the probability of bankruptcy.The positive coef ?cients for C_RIGHTS con ?rm that legal protection of creditor rights can reduce the agency cost of debt,as reported by Demirgü?-Kunt and Maksimovic (1999),Giannetti (2003)and González and González (2008).

The signi ?cant and positive coef ?cients of DCRISIS in column (1)reveal that leverage increased during the ?nancial crisis.Columns (3)and (5)respectively show the variation in long-term and short-term debt leverage ratios during the recent crisis.The results also reveal an increase in long-and short-term debt as a result of the crisis,the increase being higher for short-term debt.The coef ?cients of DCRISIS in columns (3)and (5)show that ?rms respectively increased the ratios of long-and short-term debt and the market value of assets by 1.86and 2.55%on average during the ?nancial crisis.

The coef ?cients of the interaction terms between the DCRISIS variable and the ?rms'external dependence (FD)are negative and statistically signi ?cant at conventional levels regardless of whether the dependent variable is total,long-or short-term lever-age.These negative coef ?cients of DCRISIS ?FD reveal that there is a negative differential effect of the ?nancial crisis on corporate leverage for those ?rms that depended more on external ?nance before the onset of the recent crisis,providing evidence of a credit supply effect in corporate leverage.Furthermore,short-term leverage is seen to increase more for less ?nancially-dependent ?rms and to decrease less for more ?nancially-dependent ?rms compared to long-term leverage in these groups of ?rms.These results suggest that the effect of the recent crisis on corporate maturity shown in Table 4is caused by higher average increases in short-term debt than long-term debt.

The debt maturity regressions in Table 6show that the effect of the ?nancial crisis on debt maturity is related to institutional and banking structure characteristics.Columns (1)to (5)present the results when the interactions between DCRISIS and the country-level characteristics considered in this paper are included sequentially in the speci ?cation.The coef ?cients of RULE_OF_LAW,C_RIGHTS,BANK_CONC,BANK_CREDIT and BOND show the effect of these variables before the ?nancial crisis,while the interaction terms of these variables with the DCRISIS variable show the differential in ?uence of country variables during the crisis.The in ?uences of ?rm-and country-level characteristics are similar to those shown in Table 4.

The coef ?cient of DCRISIS in column (6)shows that ?rms reduced their debt maturity by almost 3%on average during the ?nancial crisis in countries with low levels of the country characteristics.As for the interaction terms,the positive coef ?cients of DCRISIS ?RULE_OF_LAW and DCRISIS ?BANK_CONC reveal that higher levels of rule of law and bank concentration can be seen to lead to a reduction in the negative impact of the ?nancial crisis on corporate debt maturity.Higher levels of legal enforce-ment and greater banking concentration thus helped ?rms to avoid the reduction in debt maturity resulting from the ?nancial crisis.These results provide evidence in line with the role of relationship banking,as bank concentration is found to ameliorate

Table 5

Debt and the ?nancial crisis.

Regressions are estimated using panel data.The dependent variables are the ratios between total debt (columns (1)and (2)),long-term debt (columns (3)and (4)),and short-term debt (columns (5)and (6))and the market value of assets.The market value of assets is de ?ned as total assets minus the book value of equity plus the mar-ket value of equity.PROFITABILITY is measured as EBIT plus depreciation expenses and provisions (non-cash deductions from earnings)divided by total assets.GROWTH is the market-to-book ratio.TANGIBILITY is the ratio between property,plant and equipment and total assets.SIZE is the natural logarithm of sales.C_RIGHTS measures creditor rights.DCRISIS is a dummy variable that takes the value of 1for the years 2008,2009,2010,2011and 2012,and zero otherwise.FD is the ratio of debt and total assets one year before the onset of the crisis,in December 2006.Country-year,industry-year and ?rm-speci ?c effects are included in all the estimations,al-though we do not report their coef ?cients.T-statistics are in parentheses.***,**,and *represent signi ?cance at the 1%,5%,and 10%levels,respectively.

(1)

(2)(3)(4)(5)(6)Intercept 0.2104???(30.80)0.2126???(31.17)0.0773???(15.87)0.0786???(16.15)0.1331???(27.72)0.1340???(27.93)PROFITABILITY ?0.0002?(?1.68)?0.0002?(?1.68)0.0000(0.16)

0.0000(0.16)

?0.0002??(?2.55)?0.0002??(?2.55)GROWTH ?0.0209???(?66.58)?0.0204???(?64.72)?0.0107???(?47.74)?0.0104???(?46.25)?0.0102???(?46.26)?0.0100???(?45.06)TANGIBILITY 0.1706???(32.09)0.1682???(31.67)0.1265???(33.34)0.1251???(32.99)0.0441???(11.81)0.0431???(11.53)SIZE 0.0017?(1.82)0.0007(0.78)0.0042???(6.30)0.0037???(5.47)?0.0025???(?3.82)?0.0029???(?4.45)C_RIGHTS 0.0077???(4.53)0.0076???(4.46)0.0044???(3.64)0.0043???(3.58)0.0033???(2.75)0.0032???(2.70)DCRISIS 0.0441???(35.64)

0.0677???(36.88)0.0186???(21.11)

0.0321???(24.47)0.0255???(29.28)

0.0357???(27.61)DCRISIS ?FD ?0.0824???(?17.38)?0.0469???(?13.85)?0.0356???(?10.66)Hausman test 204.34***3521.43***300.00***1137.41***525.47***3149.89***F test

1049.04***968.68***575.10***533.43***513.54***469.58***#observations 135,421135,421135,421135,421135,421135,421#?rms

27,86227,862

27,86227,862

27,862

27,862

321

V.M.González /Journal of Corporate Finance 35(2015)310–328

the reduction in corporate debt maturity during the ?nancial crisis.This means that ?rms in countries with a higher level of bank concentration suffered less stringent restrictions on debt maturity.This result is consistent with evidence provided by Petersen and Rajan (1995)that ?rms in less concentrated credit markets are subject to greater ?nancial constraints.

We test our third hypothesis in columns (7)and (8),analysing the effect of the weight of banks on corporate debt maturity during the ?nancial crisis and whether this in ?uence varies according to ?rm size.BANK_CREDIT measures the effect of this variable during the period before the ?nancial crisis for small ?rms.The DCRISIS ?BANK_CREDIT interaction term identi ?es the differential effect of BANK_CREDIT on corporate debt maturity during the ?nancial crisis.The DCRISIS ?SIZE variable measures the differential effect of the ?nancial crisis on corporate debt maturity in larger ?rms.Finally,the coef ?cient of the DCRISIS ?SIZE ?BANK_CREDIT variable shows the differential impact of the ?nancial crisis for larger ?rms in countries with a large

Table 6

Country-level determinants of ?rm debt maturity and ?nancial crisis.

Regressions are estimated using panel data.The dependent variable (DEBT_MAT)is the percentage of the ?rm's total debt that has a maturity of more than one year.ASSET_MAT is the ratio between net ?xed assets and total assets.GROWTH is the growth rate of the GDP.SIZE is the natural logarithm of sales.VOL_EBIT is the absolute value of change in earnings before interest and taxes.FIRM_QUALITY is the ratio of net income plus depreciation to net debt.LEV is the ratio between total debt and the ?rm's market value.DCRISIS is a dummy variable that takes the value of 1for the years 2008,2009,2010,2011and 2012,and zero otherwise.RULE_OF_LAW is one of the six dimensions of the WGI and is a measure of the ef ?ciency of the legal system.C_RIGHTS measures creditor rights.BANK_CONC is the fraction of assets held by the three largest commercial banks in each country.BANK_CREDIT is the ratio of private credit by deposit money banks to GDP.BOND is the sum of the private bond market capitalization to GDP plus the international debt issues to GDP.The Durbin –Wu –Hausman statistic tests the null hypothesis that the introduction of instrumental var-iables has no in ?uence on the coef ?cients of the estimations.We report instrumental variable estimations if the test is signi ?cant at the 10%level.Country-year,indus-try-year and ?rm-speci ?c effects are included in all the estimations,although we do not report their coef ?cients.T-statistics are in parentheses.***,**,and *represent signi ?cance at the 1%,5%,and 10%levels,respectively.

(1)

(2)(3)(4)(5)(6)(7)(8)Intercept 0.4092???(15.02)0.3981???(14.51)0.4140???(15.22)0.4050???(14.93)0.4038???(14.88)0.4152???(14.83)0.4286???(15.21)0.4284???(15.20)ASSET_MAT 0.0352???(3.41)0.0367???(3.54)0.0381???(3.68)0.0352???(3.41)0.0355???(3.43)0.0377???(3.64)0.0369???(3.56)0.0370???(3.57)GROWTH 0.0034???(5.80)0.0033???(5.70)0.0033???(5.65)0.0034???(5.71)0.0034???(5.79)0.0033???(5.57)0.0033???(5.56)0.0033???(5.55)SIZE

0.0083???(4.54)

0.0080???(4.41)

0.0078???(4.28)

0.0082???(4.49)

0.0082???(4.49)

0.0077???(4.23)

0.0059???(3.16)

0.0059???(3.17)

FIRM_QUALITY ?0.0008???(?8.04)?0.0008???(?8.01)?0.0008???(?7.95)?0.0008???(?8.02)?0.0008???(?8.03)?0.0008???(?7.92)?0.0008???(?7.93)?0.0008???(?7.93)VOL_EBIT ?0.0000(?0.06)?0.0000(?0.07)?0.0000(?0.05)?0.0000(?0.07)?0.0000(?0.06)?0.0000(?0.07)?0.0000(?0.09)?0.0000(?0.09)LEV 0.0621???(10.11)0.0625???(10.16)0.0626???(10.19)0.0624???(10.15)0.0618???(10.04)0.0637???(10.33)0.0638???(10.35)0.0639???(10.35)DCRISIS ?0.0089??(?2.09)?0.0095??(?2.08)?0.0364???(?4.69)?0.0009(?0.15)?0.0078?(?1.80)?0.0296???(?3.62)?0.0262(?1.61)?0.0396?(?1.73)RULE_OF_LAW 0.0084(0.64)0.0098(0.75)0.0059(0.45)0.0087(0.66)0.0075(0.57)0.0020(0.15)0.0001(0.01)0.0005(0.04)C_RIGHTS 0.0189???(4.50)0.0173???(4.12)0.0195???(4.66)0.0183???(4.38)0.0177???(4.24)0.0211???(4.88)0.0209???(4.83)0.0209???(4.84)BANK_CONC 0.0822???(5.79)

0.0858***(6.02)

0.0724***(5.04)

0.0836???(5.90)

0.0831???(5.87)

0.0762???(5.18)

0.0777***(5.28)

0.0772***(5.24)

BANK_CREDIT ?0.1448???(?4.55)?0.1294***(?4.04)?0.1363***(?4.32)?0.1384***(?4.38)?0.1324???(?4.15)?0.1360***(?4.08)?0.1396???(?4.18)?0.1397???(?4.19)BOND

0.0008???(4.32)0.0008???(4.13)

0.0007???(3.85)

0.0008???(4.24)

0.0008***(4.15)

0.0006???(3.39)0.0007???(3.60)0.0007???(3.59)DCRISIS ?RULE_OF_LAW 0.0048?(1.66)

0.0086??(2.21)0.0083??(2.11)0.0078??(1.98)DCRISIS ?C_RIGHTS 0.0027(1.64)

0.0029(1.42)0.0044??(2.15)0.0043??(2.11)DCRISIS ?BANK_CONC 0.0565???(4.54)

0.0598***(4.20)

0.0600???(4.22)

0.0901??(2.31)

DCRISIS ?BANK_CREDIT ?0.0027(?0.60)

?0.0243???(?3.56)?0.0478???(?3.57)?0.0512???(?3.65)DCRISIS ?BOND 0.0000(1.25)

0.0000(0.62)

0.0000(0.38)0.0000(0.42)DCRISIS ?SIZE

?0.0005(?0.20)0.0018(0.48)DCRISIS ?SIZE ?BANK_CREDIT 0.0039?(1.96)

0.0045??(2.12)DCRISIS ?SIZE ?BANK_CONC ?0.0052(?0.83)Hausman test 1149.83***1154.81***1234.22***1180.83***1112.42***1379.09***1409.41***1401.73***F test

23.98***23.97***25.17***23.82***23.90***20.56***19.61***18.75***#observations 101,460101,460101,460101,460101,460101,460101,460101,460#?rms

21,59521,59521,59521,59521,59521,59521,59521,595Durbin –Wu –Hausman test

6.24***

3.75**

4.77***

5.98***

5.86***

3.86***

4.21***

4.27***

322V.M.González /Journal of Corporate Finance 35(2015)310–328

weight of banks in the economy.9The results in column (7)reveal that both the BANK_CREDIT and DCRISIS ?BANK_CREDIT variables have a negative in ?uence on corporate debt maturity,in line with the banking preference for short-term debt in both periods.These effects are economically signi ?cant,given that a one-standard deviation increase in the ?tted value of BANK_CREDIT and DCRISIS ?BANK_CREDIT would cause a reduction in debt maturity of ?11.25and ?5.68%,respectively.However,the positive coef-?cient of DCRISIS ?SIZE ?BANK_CREDIT shows that larger ?rms suffered a lower reduction in debt maturity compared to smaller ?rms during the ?nancial crisis in countries where banks play an important role in the ?nancing of the private sector.A one-standard deviation increase in the value of DCRISIS ?SIZE ?BANK_CREDIT would cause an increase of 2.88%in the average value of the dependent variable.This positive differential effect of BANK_CREDIT on corporate debt maturity during the ?nancial crisis for large ?rms is also maintained when we control for a potential size effect of bank concentration (column (8)).

5.Robustness

In this section,we present additional robustness tests for our measure of the ?nancial crisis.An important concern is that our measure of the ?nancial crisis does not consider the fact that the crisis did not affect all the countries with the same intensity simultaneously.We address these issues taking into account proxies of the ?nancial crisis that vary during the period 2008–2012as well as measures of the intensity of the ?nancial crisis.

First,we separately consider dummy variables identifying different sub-periods of the period 2008–2012instead of one dummy variable for the overall period.DCRISIS1,DCRISIS2and DCRISIS3are three dummy variables that take the value of 1for the periods 2008–2009,2010–2011and 2012,respectively,and 0otherwise.The results using this de ?nition of the ?nancial crisis are shown in Table 7.The coef ?cients of DCRISIS1,DCRISIS2and DCRISIS3are negative and signi ?cant in column (1)when only ?rm-level determinants of corporate debt maturity are considered,revealing a reduction in debt maturity during the differ-ent sub-periods of the ?nancial crisis.In columns (2)to (4),when the ?rm-and country-level determinants of corporate debt maturity and the interaction effects of the crisis dummies and country-level variables are considered,at least one of the dummies measuring the ?nancial crisis is negative and signi ?cant.In general,the results reveal that the negative effect of the crisis on cor-porate debt maturity was higher during the years 2010and 2011.

The results for the ?rm-and country-level variables and the interaction terms between the variables measuring the ?nancial crisis and country-level variables are similar to those obtained when using DCRISIS as the measure of the ?nancial crisis.Specif-ically,we obtain results that are consistent with an increase in corporate debt maturity in countries with higher bank concentra-tion,as the coef ?cients of BANK_CONC and the interaction terms of this variable with the different periods of the ?nancial crisis are always positive and signi ?cant.Similar to the results shown in Table 6,the coef ?cients for the interaction terms of BANK_CREDIT and DCRISIS1,DCRISIS2and DCRISIS3are negative and signi ?cant.Furthermore,the results in column (4)reveal that a large weight of banks in the ?nancing of the private sector led to a higher reduction in corporate debt maturity during the period of the ?nancial crisis,and this reduction affected smaller ?rms to a greater extent.

Columns (5)to (8)con ?rm our evidence in line with the view that a credit supply shock is the predominant casual factor to explain corporate debt maturity during the recent crisis.The coef ?cients of the interaction terms between DCRISIS1,DCRISIS2and DCRISIS3identifying the crisis years and the ?rms'external dependence (FD)are negative and statistically signi ?cant at conven-tional levels regardless of whether we control for ?rm-level characteristics or whether we also control for country-level determi-nants of corporate debt maturity.

Second,as the crisis has not had the same intensity in all economies,its consequences may have had a different in ?uence on corporate debt maturity in different countries.We therefore check the robustness of our results by considering two measures of the intensity of the crisis in each country.On the one hand,we measure the intensity of the ?nancial crisis as the difference be-tween the average GDP growth rate for the period 2003–2007minus the average GDP growth rate during the period 2008–2012for each country.Thus,the greater the intensity of the crisis,the higher the value of this variable.On the other,we consider the percentage of non-performing loans for each country during the period 2008–2012as a proxy for the intensity of the ?nancial crisis.In both de ?nitions,the variable (CRISIS_INTENSITY)only shows a measure of the intensity during the years 2008–2012,being zero in the remaining years.These results are reported in Table 8,in columns (1)to (4)for the former measure of the in-tensity of the ?nancial crisis and in columns (5)to (8)for the latter measure.

For both measures of the intensity of the ?nancial crisis (CRISIS_INTENSITY),the results show a negative relationship between this variable and corporate debt maturity (except for the coef ?cient in column (8)),suggesting that ?rms in those countries that suffered a stronger ?nancial crisis present a greater reduction in their debt maturity.Firm-and country-level determinants of cor-porate debt maturity maintain the sign and signi ?cance reported in previous tables.Columns (3),(4),(7),and (8)present the results for the interactions between CRISIS_INTENSITY and institutional characteristics and banking structure variables on corpo-rate debt maturity during the ?nancial crisis.As for the in ?uence of country-level determinants during the ?nancial crisis,higher levels of rule of law (except in column (8)),protection of creditor rights and bank concentration are seen to reduce the negative impact of the ?nancial crisis on corporate debt maturity.

The results also show that there is a negative effect of the weight of banks in the economy in the period before the ?nancial crisis as well as during the ?nancial crisis.However,the positive coef ?cient of CRISIS_INTENSITY ?SIZE ?BANK_CREDIT suggests

9

We also control for the in ?uence of bank concentration on corporate debt maturity depending on ?rm size.

323

V.M.González /Journal of Corporate Finance 35(2015)310–328

Table7

Debt maturity and evolution of the?nancial crisis.

Regressions are estimated using panel data.The dependent variable(DEBT_MAT)is the percentage of the?rm's total debt that has a maturity of more than one year. ASSET_MAT is the ratio between net?xed assets and total assets.GROWTH is the growth rate of the GDP.SIZE is the natural logarithm of sales.VOL_EBIT is the absolute value of change in earnings before interest and taxes.FIRM_QUALITY is the ratio of net income plus depreciation to net debt.LEV is the ratio between total debt and the ?rm's market value.DCRISIS1is a dummy variable that takes the value of1for the years2008and2009,and zero otherwise.DCRISIS2is a dummy variable that takes the value of1for the years2010and2011,and zero otherwise.DCRISIS3is a dummy variable that takes the value of1for the year2012,and zero otherwise.FD is the ratio of debt and total assets one year before the onset of the crisis,in December2006.RULE_OF_LAW is one of the six dimensions of the WGI and is a measure of the ef?ciency of the legal system.C_RIGHTS measures creditor rights.BANK_CREDIT is the ratio of private credit by deposit money banks to GDP.BANK_CONC is the fraction of assets held by the three largest commercial banks in each country.BOND is the sum of the private bond market capitalization to GDP plus the international debt issues to GDP. The Durbin–Wu–Hausman statistic tests the null hypothesis that the introduction of instrumental variables has no in?uence on the coef?cients of the estimations.We report instrumental variable estimations if the test is signi?cant at the10%level.Country-year,industry-year and?rm-speci?c effects are included in all the estimations, although we do not report their coef?cients.T-statistics are in parentheses.***,**,and*represent signi?cance at the1%,5%,and10%levels,respectively.

(1)(2)(3)(4)(5)(6)(7)(8)

Intercept0.4200???

(46.37)0.3845???

(13.23)

0.4087???

(13.47)

0.4223???

(13.85)

0.4198???

(46.30)

0.3939???

(13.54)

0.4141???

(13.64)

0.4283???

(14.04)

ASSET_MAT0.0557???

(6.38)0.0374???

(3.62)

0.0393???

(3.79)

0.0383???

(3.69)

0.0545???

(6.25)

0.0353???

(3.42)

0.0374???

(3.60)

0.0362???

(3.49)

GROWTH0.0035???

(6.79)0.0033???

(5.71)

0.0032???

(5.49)

0.0032???

(5.51)

0.0037???

(7.12)

0.0036???

(6.09)

0.0034???

(5.81)

0.0034???

(5.84)

SIZE0.0045???

(2.95)0.0078???

(4.28)

0.0075???

(4.10)

0.0054???

(2.85)

0.0042???

(2.76)

0.0071???

(3.87)

0.0068???

(3.68)

0.0046??

(2.43)

FIRM_QUALITY?0.0009???

(?9.82)?0.0008???

(?8.03)

?0.0008???

(?7.90)

?0.0008???

(?7.84)

?0.0009???

(?9.72)

?0.0008???

(?7.91)

?0.0008???

(?7.78)

?0.0008???

(?7.71)

VOL_EBIT?0.0002

(?0.92)0.0000

(0.07)

0.0000

(0.05)

?0.0000

(?0.11)

?0.0002

(?0.77)

0.0000

(0.12)

0.0000

(0.10)

?0.0000

(?0.06)

LEV0.0495???

(9.55)0.0638???

(10.35)

0.0647???

(10.44)

0.0661???

(10.67)

0.0481???

(9.25)

0.0611???

(9.89)

0.0623???

(10.02)

0.0637???

(10.24)

DCRISIS1?0.0091???

(?4.38)?0.0007

(?0.22)

?0.0288???

(?3.12)

?0.0043

(?0.26)

0.0089???

(2.80)

0.0148???

(3.53)

?0.0099

(?1.00)

0.0179

(1.05)

DCRISIS2?0.0159???

(?6.39)?0.0120???

(?3.29)

?0.0375???

(?3.72)

?0.0294?

(?1.75)

0.0015

(0.43)

0.0067

(1.43)

?0.0145

(?1.35)

?0.0035

(?0.20)

DCRISIS3?0.0337???

(?10.15)?0.0084

(?1.55)

?0.0292??

(?2.01)

?0.0135

(?0.55)

?0.0285???

(?6.50)

0.0067

(1.03)

?0.0112

(?0.73)

0.0083

(0.33)

DCRISIS1?FD?0.0655???

(?7.42)?0.0536???

(?5.22)

?0.0509???

(?4.89)

?0.0509???

(?4.88)

DCRISIS2?FD?0.0636???

(?7.07)?0.0652???

(?6.23)

?0.0629???

(?5.93)

?0.0652???

(?6.13)

DCRISIS3?FD?0.0023

(?0.20)?0.0482???

(?3.40)

?0.0440???

(?3.07)

?0.0478???

(?3.34)

RULE_OF_LAW0.0212

(1.58)0.0151

(1.09)

0.0218

(1.56)

0.0199

(1.48)

0.0144

(1.04)

0.0216

(1.54)

C_RIGHTS0.0216???

(4.91)0.0277???

(5.90)

0.0296???

(6.26)

0.0211???

(4.81)

0.0265???

(5.65)

0.0286???

(6.04)

BANK_CONC0.0831???

(5.86)0.0707???

(4.75)

0.0753???

(5.05)

0.0771???

(5.43)

0.0665???

(4.45)

0.0708???

(4.74)

BANK CREDIT?0.1455???

(?4.44)?0.1679???

(?4.54)

?0.1943???

(?5.13)

?0.1479???

(?4.51)

?0.1654???

(?4.47)

?0.1935???

(?5.11)

BOND0.0007???

(3.12)0.0006??

(2.42)

0.0006???

(2.75)

0.0007???

(3.31)

0.0006???

(2.59)

0.0007???

(2.95)

DCRISIS1?RULE_OF_LAW0.0065

(1.46)0.0031

(0.69)

0.0039

(0.88)

0.0003

(0.07)

DCRISIS2?RULE_OF_LAW0.0102??

(2.13)0.0022

(0.45)

0.0067

(1.40)

?0.0017

(?0.33)

DCRISIS3?RULE_OF_LAW0.0176??

(2.42)0.0054

(0.70)

0.0147??

(2.01)

0.0021

(0.28)

DCRISIS1?C_RIGHTS0.0050??

(2.15)0.0039?

(1.65)

0.0053??

(2.30)

0.0042?

(1.75)

DCRISIS2?C_RIGHTS?0.0009

(?0.39)0.0006

(0.24)

?0.0007

(?0.30)

0.0007

(0.30)

DCRISIS3?C_RIGHTS0.0051

(1.55)0.0079??

(2.34)

0.0053

(1.63)

0.0080??

(2.38)

DCRISIS1?BANK_CONC0.0490???

(3.08)0.0490???

(3.07)

0.0454???

(2.86)

0.0450???

(2.83)

DCRISIS2?BANK_CONC0.0815???

(4.39)0.0817???

(4.40)

0.0767???

(4.13)

0.0768???

(4.13)

DCRISIS3?BANK_CONC0.0564??

(2.13)0.0520?

(1.95)

0.0525??

(1.98)

0.0480?

(1.80)

DCRISIS1?BANK_CREDIT?0.0193??

(?2.39)?0.0394???

(?3.26)

?0.0191??

(?2.38)

?0.0415???

(?3.42)

DCRISIS2?BANK_CREDIT?0.0261???

(?3.08)?0.0589???

(?4.69)

?0.0249???

(?2.94)

?0.0595???

(?4.74)

324V.M.González/Journal of Corporate Finance35(2015)310–328

that smaller ?rms suffered more restrictions in terms of debt maturity during the ?nancial crisis in countries where banks play an important role in the ?nancing of the private sector.

The results also show that the coef ?cient of DCRISIS ?SIZE is negative and signi ?cant in column (8),while that of CRISIS_INTENSITY is not signi ?cant.This reveals that the negative effect of the crisis on corporate debt maturity seems to be concen-trated in large ?rms.This seemingly surprising result is consistent with the data provided by the ECB bank lending survey,which in-dicates that the crisis had a greater impact on large ?rms than on small ?rms.The ECB survey shows an increase in the tightening of credit standards for loans or credit lines to enterprises as a result of the ?nancial crisis,although this tightening is not equally distrib-uted across ?rms according to size.For the ?rst quarter of 2008,a net percentage of 53%of banks reported a tightening of the credit standards they applied to large ?rms,while this percentage was only 34%for small and medium-sized enterprises.Furthermore,non-price terms and conditions also contributed more strongly to the net tightening for large ?rms than for SMEs,especially as regards the size of loans and credit lines,but also in terms of collateral,loan covenants and loan maturity.

Summing up,when we consider the different intensity of the ?nancial crisis on corporate debt maturity,we con ?rm our main re-sults:(1)the ?nancial crisis reduced corporate debt maturity;(2)the effect of bank concentration on corporate debt maturity was more positive during the ?nancial crisis,revealing the value of relationship banking as a way of improving the credit conditions of borrowers during periods of uncertainty;and (3)the debt maturity of larger ?rms decreased less as a result of the ?nancial crisis than the debt maturity of smaller ?rms in countries where banks play an important role in the ?nancing of the private sector.6.Conclusions

This paper analyses the effect of the global ?nancial crisis on corporate debt maturity for a sample of 39countries.Although corporate debt maturity was found to decline during the ?nancial crisis,the effect is weak for the average ?rm.Total,long-and short-term leverage increased during the ?nancial crisis compared to the average leverage in the period before the crisis.The re-sults highlight that the increase in short-term debt is higher than in long-term debt,leading to a reduction in corporate debt ma-turity.Furthermore,the negative effect of the crisis on corporate debt maturity was stronger in those ?rms that are more dependent on external ?nance before the onset of the crisis.This result is addressed by a higher negative effect of the crisis on long-term debt than in short-term debt for ?rms with a greater dependence on external ?nance.These results provide evidence in line with the crisis having a credit supply effect that reduced the availability of corporate debt,especially long-term debt,short-ening the corporate debt maturity of ?rms that were more dependent of external ?nance before the onset of the ?nancial crisis.

We also analyse how the banking structure of the country affects the impact of the ?nancial crisis on corporate debt maturity.The impact of the ?nancial crisis on corporate debt maturity varied depending on banking concentration and the role played by banks in the ?nancing of the private sector.Higher levels of bank concentration are seen to reduce the negative impact of the ?nancial crisis on corporate debt maturity,suggesting that higher bank concentration increases bank incentives to establish close relations with borrowers over time.This last result is consistent with the importance of bank concentration (Berlin and Mester,1999;Petersen and Rajan,1995),as ?rms in less concentrated credit markets are subject to greater ?nancial constraints.

We likewise show that the reduction in debt maturity was greater in countries where banks play an important role in the ?nancing of the private sector,in keeping with the preferences of banks having an even greater in ?uence on debt maturity

Table 7(continued)

(1)

(2)

(3)(4)(5)

(6)

(7)(8)

DCRISIS3?BANK_CREDIT ?0.0368???(?3.20)?0.0867???(?4.80)?0.0364???(?3.15)?0.0874???(?4.83)DCRISIS1?BOND 0.0001(1.23)0.0001(1.49)0.0001(1.16)0.0001(1.45)DCRISIS2?BOND ?0.0000(?0.15)0.0000(0.24)?0.0000(?0.21)0.0000(0.19)DCRISIS3?BOND ?0.0000(?0.26)

?0.0000(?0.15)?0.0000(?0.21)

?0.0000(?0.11)DCRISIS1?SIZE ?0.0057??(?1.99)?0.0064??(?2.24)DCRISIS2?SIZE ?0.0036(?1.24)?0.0041(?1.41)DCRISIS3?SIZE

?0.0051(?1.25)?0.0056(?1.38)DCRISIS1?SIZE ?BANK_CREDIT 0.0057??(2.44)0.0063???(2.69)DCRISIS2?SIZE ?BANK_CREDIT 0.0086???(3.60)0.0091???(3.81)DCRISIS3?SIZE ?BANK_CREDIT 0.0123???(3.73)

0.0127???(3.84)

Hausman test 1386.19***1104.82***1625.50***1722.48***1509.64***1422.26***1602.97***1665.29***F test

44.71***23.59***13.80***13.63***41.47***22.18***13.74***13.64***#observations 135,621101,460101,460101,460135,621101,460101,460101,460#?rms

27,88121,59521,59521,59527,88121,59521,59521,595Durbin –Wu –Hausman test

–

5.32***

5.24***

6.86***

– 5.94*** 5.10***

6.89***

325

V.M.González /Journal of Corporate Finance 35(2015)310–328

structures during the ?nancial crisis.Moreover,the reduction in debt maturity was lower for larger ?rms compared to smaller ?rms during the ?nancial crisis in countries where banks play an important role in the ?nancing of the private sector,suggesting that smaller ?rms were affected to a greater extent by bank preferences as they also are more dependent on domestic bank credit.

The evidence provided in the paper is robust to alternative measures of the ?nancial crisis which consider that the recent crisis did not affect all countries with the same intensity simultaneously.Speci ?cally,our results reveal that the effect of the crisis on corporate debt maturity was stronger during the years 2010and 2011and in those countries where the intensity of the crisis was greater.

Our results have potential policy implications,as they suggest that the ?nancial crisis systematically affected corporate debt structure,but did so in an unequal way across ?rms and across countries,con ?rming the relevance of banking structure in cor-porate ?nancing both in normal times and during economic and ?nancial downturns.Bank concentration and the weight of banks in the ?nancing of the private sector are revealed to affect the bank incentives to extend debt maturity during the crisis.Thus,

Table 8

Debt maturity and intensity of the ?nancial crisis.

Regressions are estimated using panel data.The dependent variable (DEBT_MAT)is the percentage of the ?rm's total debt that has a maturity of more than one year.ASSET_MAT is the ratio between net ?xed assets and total assets.GROWTH is the growth rate of the GDP.SIZE is the natural logarithm of sales.VOL_EBIT is the absolute value of change in earnings before interest and taxes.FIRM_QUALITY is the ratio of net income plus depreciation to net debt.LEV is the ratio between total debt and the ?rm's market value.CRISIS_INTENSITY in columns (1)to (4)is CRISIS_INTENSITY1and is de ?ned as the difference between the mean GDP growth rates for the periods 2003–2007and 2008–2012for each country,and zero otherwise.CRISIS_INTENSITY in columns (5)to (8)is CRISIS_INTENSITY2and is the non-performing loans for each country during the period 2008–2012.RULE_OF_LAW is one of the six dimensions of the WGI and is a measure of the ef ?ciency of the legal system.C_RIGHTS measures creditor rights.BANK_CREDIT is the ratio of private credit by deposit money banks to GDP.BANK_CONC is the fraction of assets held by the three largest com-mercial banks in each country.BOND is the sum of the private bond market capitalization to GDP plus the international debt issues to GDP.The Durbin –Wu –Hausman statistic tests the null hypothesis that the introduction of instrumental variables has no in ?uence on the coef ?cients of the estimations.We report instrumental variable estimations if the test is signi ?cant at the 10%level.Country-year,industry-year and ?rm-speci ?c effects are included in all the estimations,although we do not report their coef ?cients.T-statistics are in parentheses.***,**,and *represent signi ?cance at the 1%,5%,and 10%levels,respectively.

(1)

(2)(3)(4)(5)(6)(7)(8)Intercept 0.4447***(51.33)0.4040???(16.16)0.4168???(16.05)0.4291???(16.38)0.4578???(51.20)0.3934???(15.73)0.4136???(15.04)0.4221???(15.27)ASSET_MAT 0.0556***(6.36)0.0346???(3.35)0.0370???(3.57)0.0356???(3.44)0.0474???(5.24)0.0362???(3.48)0.0391???(3.76)0.0384???(3.69)GROWTH 0.0035***(6.79)0.0034???(5.73)0.0033???(5.55)0.0033???(5.57)0.0031???(5.93)0.0033???(5.64)0.0033???(5.54)0.0033???(5.54)SIZE

0.0035**(2.32)

0.0082???(4.49)

0.0079???(4.33)

0.0066???(3.53)

0.0035??(2.24)

0.0077???(4.24)

0.0073???(3.97)

0.0067???(3.64)

FIRM_QUALITY ?0.0009***(?9.76)?0.0008???(?8.02)?0.0008???(?7.94)?0.0008???(?7.95)?0.0009???(?9.65)?0.0008???(?7.79)?0.0008???(?7.68)?0.0008???(?7.64)VOL_EBIT ?0.0002(?0.86)?0.0000(?0.08)?0.0000(?0.09)?0.0000(?0.11)?0.0001(?0.56)?0.0000(?0.09)?0.0000(?0.08)?0.0000(?0.13)LEV

0.0496***(9.55)

0.0630???(10.23)0.0657???(10.63)0.0659???(10.66)0.0568???(10.46)0.0653???(10.48)0.0666???(10.68)0.0680???(10.89)CRISIS_INTENSITY ?0.2635***(?3.43)

?0.2095??(?2.29)?0.9858???(?2.83)?0.8820?(?1.69)?0.0033???(?6.62)

?0.0024???(?4.07)?0.0072???(?2.82)0.0035(0.94)RULE_OF_LAW 0.0070(0.54)?0.0018(?0.13)?0.0001(?0.01)0.0090(0.69)0.0069(0.52)0.0133(0.99)C_RIGHTS 0.0186???(4.56)0.0221???(5.23)0.0229???(5.38)0.0188???(4.63)0.0218???(5.13)0.0240???(5.61)BANK_CONC 0.0855???(6.02)

0.0842???(5.84)

0.0833???(5.78)

0.0936???(6.45)

0.0868???(5.85)

0.0869???(5.84)

BANK CREDIT ?0.1354???(?4.89)?0.1423???(?4.72)?0.1549???(?5.08)?0.1271???(?4.87)?0.1484???(?4.90)?0.1753???(?5.71)BOND

0.0007???(4.29)

0.0006???(3.58)0.0007???(3.84)0.0007???(4.06)

0.0007???(3.83)0.0007???(4.24)CRISIS_INTENSITY ?RULE_OF_LAW 0.5501???(3.72)0.3866??(2.49)0.0031???(2.80)0.0005(0.41)CRISIS_INTENSITY ?C_RIGHTS 0.2027??(2.42)0.1876??(2.17)0.0025???(4.03)0.0019???(2.91)CRISIS_INTENSITY ?BANK_CONC 1.4830???(2.88)

1.7214???(3.32)

0.0132???(2.90)

0.0161???(3.54)

CRISIS_INTENSITY ?BANK_CREDIT ?0.9786???(?3.78)?1.4949???(?4.54)?0.0079???(?3.98)?0.0194???(?6.86)CRISIS_INTENSITY ?BOND ?0.0001(?0.04)

0.0003(0.17)?0.0000(?0.29)

0.0000(0.73)

CRISIS_INTENSITY ?SIZE

?0.0663(?0.75)?0.0026???(?4.21)CRISIS_INTENSITY ?SIZE ?BANK_CREDIT 0.1523??(2.30)

0.0029???(5.55)

Hausman test 1426.92***1045.96***1452.05***1352.55***1321.08***1028.45***1214.44***1264.99***F test

44.18***25.75***21.27***20.06***46.28***26.06***21.17***20.89***#observations 135,621101,460101,460101,460124,877100,393100,393100,393#?rms

27,88121,59521,59521,59525,48321,34421,34421,344Durbin –Wu –Hausman test

–

5.70***

3.19**

3.83***

– 2.48* 2.26*

4.15***

326V.M.González /Journal of Corporate Finance 35(2015)310–328

regulators should consider the externalities for the real economy of the?nancial system when designing policies to develop or support the?nancial system.

Acknowledgements

I am grateful for the helpful comments and suggestions provided by Francisco González and by the participants in the Finance Workshop at Cardiff Business School,the XXI Finance Forum in Segovia(2013)and the ACEDE Conference in Jaén(2015).Finan-cial support from the Spanish Ministry of Economy and Competitiveness,Project ECO2012-31772,and a researcher mobility grant from the University of Oviedo International Campus of Excellence are gratefully acknowledged.

Appendix A.Variables

The table shows the de?nition of variables used in the paper and their sources.

Name De?nition Source

Crisis variables

DCRISIS A dummy variable that takes the value of1for the years2008,2009,2010,2011and2012,

and0otherwise.

DCRISIS1A dummy variable that takes the value of1for the years2008and2009,and0otherwise.

DCRISIS2A dummy variable that takes the value of1for the years2010and2012,and0otherwise.

DCRISIS3A dummy variable that takes the value of1for the year2012,and0otherwise.

CRISIS_INTENSITY1The difference between the mean GDP growth for the period2003–2007minus the mean

GDP growth for the period2008–2012and zero for the remaining years.

World Bank

CRISIS_INTENSITY2The percentage of non-performing loans for each country during the period2008–2012.

Bank non-performing loans to total gross loans are the value of non-performing loans

divided by the total value of the loan portfolio(including non-performing loans before the

deduction of speci?c loan-loss provisions).The loan amount recorded as non-performing

should be the gross value of the loan as recorded on the balance sheet,not just the

amount that is overdue.

World Bank

Firm-level variables

DEBT_MAT The percentage of the?rm's total debt(long-term debt plus debt in current liabilities)

that has a maturity of more than one year.

Worldscope

ASSET_MAT The ratio between net?xed assets and total assets.Worldscope

GROWTH The market-to-book ratio.Worldscope

SIZE The natural logarithm of sales.Worldscope

FIRM_QUALITY The ratio of net income plus depreciation to net debt Worldscope

VOL_EBIT The absolute value of change in earnings before interest and taxes.Worldscope

LEV The ratio between total debt and the?rm's market value.The market value of assets is

de?ned as total assets minus the book value of equity plus the market value of equity.

Worldscope

Country-level variables

RULE_OF_LAW Rule of law is one of the six dimensions of the Worldwide Governance Indicators.Rule of

law captures perceptions of the extent to which agents have con?dence in and abide by

the rules of society and,in particular,the quality of contract enforcement,property rights,

the police and the courts,as well as the likelihood of crime and violence.

Kaufmann et al.(2009)

S_RIGHTS An indicator of the degree to which private property rights are protected and the degree

to which government enforces laws that protect private property.It also accounts for the

possibility that private property may be expropriated and analyses the independence of

the judiciary,corruption within the judiciary and the ability of individuals and businesses

to enforce contracts.It ranges between0and100,a high score indicating greater legal

protection of property rights.

Heritage Foundation

C_RIGHTS This index measures four powers of secured lenders in bankruptcy:(1)whether there are

restrictions,such as creditor consent,when a debtor?les for reorganization;(2)whether

secured creditors are able to seize their collateral after the petition for reorganization is

approved,i.e.whether there is no automatic stay or asset freeze imposed by the court;

(3)whether secured creditors are paid?rst out of the proceeds of liquidating a bankrupt

?rm;and(4)whether an administrator,and not management,is responsible for running

the business during the reorganization.A value of one is added to the index when a

country's laws and regulations provide each one of these powers to secured lenders;it

thus varies between0(poor creditor rights)and4(strong creditor rights).

Djankov et al.(2007)

BANK_CONC The fraction of bank assets held by the three largest commercial banks in the country.Financial Development and Structure

Dataset(World Bank).Beck et al.(2006) BANK_CREDIT The ratio of the private credit by deposit money banks to GDP.Financial Development and Structure

Dataset(World Bank).Beck et al.(2006)

BOND The sum of the private bond market capitalization to GDP plus the international debt issues to GDP.Financial Development and Structure Dataset(World Bank).Beck et al.(2006)

327

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328V.M.González/Journal of Corporate Finance35(2015)310–328

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【高中】2017人教版高中物理必修一第一章运动的描述单元检测

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第一章 概 论 1.1 干结空气中N 2、O 2、Ar 和CO 2气体所占的质量百分数是多少？ 解：按1mol 干空气计算，空气中各组分摩尔比即体积比，故n N2=0.781mol ，n O2=0.209mol ，n Ar =0.00934mol ，n CO2=0.00033mol 。质量百分数为 %51.75%100197.2801.28781.0%2=???= N ，%08.23%100197.2800 .32209.0%2=???=O ； % 29.1%1001 97.2894 .3900934.0%=???=Ar ，%05.0%100197.2801 .4400033.0%2=???=CO 。 1.2 根据我国的《环境空气质量标准》的二级标准，求出SO 2、NO 2、CO 三种污染物日平均浓度限值的体积分数。 解：由我国《环境空气质量标准》二级标准查得三种污染物日平均浓度限值如下： SO2：0.15mg/m 3，NO2：0.12mg/m 3，CO ：4.00mg/m 3。按标准状态下1m 3 干空气计算，其摩尔数为mol 643.444 .221013 =?。故三种污染物体积百分数分别为：

SO 2： ppm 052.0643.44641015.03=??-，NO 2：ppm 058.0643.44461012.03 =??- CO ： ppm 20.3643 .44281000.43 =??-。 1.3 CCl 4气体与空气混合成体积分数为1.50×10－4的混合气体，在管道中流动的流量为10m 3N 、/s ，试确定：1）CCl 4在混合气体中的质量浓度ρ（g/m 3N ）和摩尔浓度c （mol/m 3N ）；2）每天流经管道的CCl 4质量是多少千克？ 解：1）ρ（g/m 3 N ）3 3 4/031.110 4.221541050.1N m g =???=-- c （mol/m 3 N ）3 33 4/1070.610 4.221050.1N m mol ---?=??=。 2）每天流经管道的CCl 4质量为1.031×10×3600×24×10－3kg=891kg 1.4 成人每次吸入的空气量平均为500cm 3，假若每分钟呼吸15次，空气中颗粒物的浓度为200g μ/m 3，试计算每小时沉积于肺泡内的颗粒物质量。已知该颗粒物在肺泡中的沉降系数为0.12。 解：每小时沉积量200×（500×15×60×10－6）×0.12g μ=10.8g μ 1.5 设人体肺中的气体含CO 为2.2×10－4，平均含氧量为19.5%。如果这种浓度保持不变，求COHb 浓度最终将达到饱和水平的百分率。 解：由《大气污染控制工程》P14 （1－1），取M=210 2369.0105.19102.22102 4 22=???==--∝O p p M Hb O COHb ，

高一物理第一章《运动的描述》单元测试试题A卷

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第一章.运动的描述

第一章.运动的描述 考点一：时刻与时间间隔的关系 时间间隔能展示运动的一个过程，时刻只能显示运动的一个瞬间。对一些关于时间间隔和时刻的表述，能够正确理解。如：第4s末、4s时、第5s初均为时刻；4s内、第4s、第2s至第4s内均为时间间隔。 区别：时刻在时间轴上表示一点，时间间隔在时间轴上表示一段。 考点二：路程与位移的关系 位移表示位置变化，用由初位置到末位置的有向线段表示，是矢量。路程是运动轨迹的长度，是标量。只有当物体做单向直线运动时，位移的大小.等于路程。一般情况下，路程邈移的大小。 考点三：速度与速率的关系 考点四：速度、加速度与速度变化量的关系 考点五：运动图象的理解及应用 由于图象能直观地表示出物理过程和各物理量之间的关系，所以在解题的过程中被广泛应用。在运动学中，经常用到的有x—t图象和v —t图象。 1.理解图象的含义 (1)x —t图象是描述位移随时间的变化规律 (2)v—t图象是描述速度随时间的变化规律 2.明确图象斜率的含义

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第一章运动的描述单元测试题及答案

第一章《运动的描述》单元测试题及答案． 运动的描述单元测试题 一、单项选择题。是质点的中，不能看作下1.列物体

）（ 计算从北京开往广州的的火车途中所用的时、A 间研究绕地球飞行的航天飞机相对地球的飞行、B 周期时，、沿地面翻滚前进的体操运动员C 比较两辆行驶中的车的快慢D、是正，确的中描系参关下2.列于考的述）（ A、参考系必须是和地面连在一起的物体、被研究的物体必须沿与参考系的连线运动B 参考系必须是正在做匀速直线运动的物体

或、C 是相对于地面静止的物体、参考系 是为了研究物体的运动而假定D A为不动的 那个物体B的半圆弧3.如右图，某一物体 沿两个半径为R C ，则它的位移和路程分别 C运动到由A 是 2 ( ) A、0，0 B、4 R向下， πR C、4πR向下、4R D、4R向下，2 πR

4.氢气球升到离地面80m的高空时从上面掉落下一物体，物体又上升了10m后开始下落，若取 向上为正，则物体从掉落开始至最终落在地面时的位移和经过的路程分别为 （） A、80m，100m B、－80m，100m C、80m，100 m D、－90 m，180 m 5.下列关于平均速度和瞬时速度的说法中

正确的是 （） A、做变速运动的物体在相同时间间隔里的平均速度是相同的 B、瞬时速度就是运动的物体在一段较短的时间内的平均速度 C、平均速度就是初末时刻瞬时速度的平均值 D、某物体在某段时间里的瞬时速度都为零，则该物体在这段时间内静止 是的确正，法说的度速加于关列下 6.( ) A、物体的速度越大，加速度也就越大 B、物体的速度为零，加速度也一定为零 3 C、物体的加速度大小等于速度的变化量与时间的比值 D、物体的加速度的方向和速度的方向总是一致

大气污染课后答案-4章

四章 大气扩散浓度估算模式 4.1 污染源的东侧为峭壁，其高度比污染源高得多。设有效源高为H ，污染源到峭壁的距离为L ，峭壁对烟流扩散起全反射作用。试推导吹南风时高架连续点源的扩散模式。当吹北风时，这一模式又变成何种形式？ 解： 吹南风时以风向为x 轴，y 轴指向峭壁，原点为点源在地面上的投影。若不存在峭壁，则有 ]}2)(exp[]2)(){exp[2exp(2),,,(2 2 2222' z z y z y H z H z y u Q H z y x σσσσσπρ+-+---= 现存在峭壁，可考虑ρ为实源与虚源在所关心点贡献之和。 实源]}2)(exp[]2)(){exp[2exp(22 2 22221z z y z y H z H z y u Q σσσσσπρ+-+---= 虚源]}2)(exp[]2)(]{exp[2)2(exp[222 222 22z z y z y H z H z y L u Q σσσσσπρ+-+----= 因此]}2)(exp[]2)(){exp[2exp(22 2 2222z z y z y H z H z y u Q σσσσσπρ+-+---=+ ]}2)(exp[]2)(]{exp[2)2(exp[22 2 2222z z y z y H z H z y L u Q σσσσσπ+-+---- =]}2)(exp[]2)(]}{exp[2)2(exp[)2{exp(22 2 222222z z y y z y H z H z y L y u Q σσσσσσπ+-+----+- 刮北风时，坐标系建立不变，则结果仍为上式。 4.2 某发电厂烟囱高度120m ，内径5m ，排放速度13.5m/s ，烟气温度为418K 。大气温度288K ，大气为中性层结，源高处的平均风速为4m/s 。试用霍兰德、布里格斯（x<=10H s ）、国家标准GB/T13201－91中的公式计算烟气抬升高度。 解： 霍兰德公式 m D T T T u D v H s a s s 16.96)5418 288 4187.25.1(455.13)7 .25.1(=?-?+?=-+= ?。 布里格斯公式 kW kW D v T T T Q s s a s H 210002952155.1341828841810 6.9 7.2106.97.22 3 23>=??-??=-??= --且x<=10Hs 。此时 3/23/213/11 3 /23/180.2429521362.0362.0x x u x Q H H =??==?--。

第一章运动的描述

第一篇力学基础 第一章运动的描述 教学时间：5学时 本章教学目标：理解运动的绝对性和相对性；理解位置矢量和位移的不同含义；能够根据运动方程求速度和加速度，能够根据速度和加速度求运动方程的表达式；掌握伽利略变换公式，能够根据相对运动公式解决相关问题。 教学方式：讲授法、讨论法等 教学重点：能够根据运动方程求速度和加速度，能够根据速度和加速度求运动方程的表达式。 在经典力学中，通常将力学分为运动学、动力学和静力学。本章只研究运动学规律。运动学是从几何的观点来描述物体的运动，即研究物体的空间位置随时间的变化关系，不涉及引发物体运动和改变运动状态的原因。 §1.1 参考系坐标系物理模型 一、运动的绝对性和相对性 运动是物质的固有属性。从这种意义上讲，运动是绝对的。 但我们所讨论的运动，还不是这种哲学意义上的广义运动。 即使以机械运动形式而言，任何物体在任何时刻都在不停地运动着。例如，地球就在自转的同时绕太阳公转，太阳又相对于银河系中心以大约250 km/s。的速率运动，而我们所处的银河系又相对于其他银河系大约以600 km/s。的速率运动着。总之，绝对不运动的物体是不存在的。 然而运动又是相对的。

因为我们所研究的物体的运动，都是在一定的环境和特定的条件下运动。例如，当我们说一列火车开动了，这显然是指火车相对于地球(即车站)而言的因此离开特定的环境、特定的条件谈论运动没有任何意义正如恩格斯所说：“单个物体的运动是不存在的——只有在相对的意义下才可以谈运动。” 二、参考系 运动是绝对的，但运动的描述却是相对的因此，在确定研究对象的位置时，必须先选定一个标准物体(或相对静止的几个物体)作为基准；那么这个被选作标准的物体或物体群，就称为参考系。 同一物体的运动，由于我们所选参考系不同，对其运动的描述就会不同。 从运动学的角度讲，参考系的选择是任意的，通常以对问题的研究最方便最简单为原则。研究地球上物体的运动，在大多数情况下，以地球为参考系最为方便(以后如不作特别说明，研究地面上物体的运动，都是以地球为参考系)但是。当我们在地球上发射人造“宇宙小天体”时，则应以太阳为参考系。 三、坐标系 要想定量地描述物体的运动，就必须在参考系上建立适当的坐标系。 在力学中常用的有直角坐标系。根据需要，我们也可选用极坐标系、自然坐标系、球面坐标系或柱面坐标系等。 总的说来，当参考系选定后，无论选择何种坐标系，物体的运动性质都不会改变。然而，坐标系选择得当，可使计算简化。 四、物理模型 任何一个真实的物理过程都是极其复杂的。为了寻找过程中最本质、最基本的规律，我们总是根据所提问题(或所要回答的问题)，对真实过程进行理想化的简化，然后经过抽象提出一个可供数学描述的物理模型 现在我们所提的问题是确定物体在空间的位置。若物体的线度比它运动的空间范围小很多时，例如绕太阳公转的地球和调度室中铁路运行图上的列车等；或当物

第一章 运动的描述单元测试(含答案)

《运动的描述》单元测试 一．选择题（每题4分，共36分有的小题只有一个答案正确，有的小题有多个答案正确）1．“小小竹排江中游，巍巍青山两岸走。”这两句诗描述的运动的参考系分别是（） A．竹排，流水 B．流水，青山 C．青山，河岸 D．河岸，竹排 2．以下几种关于质点的说法，你认为正确的是（） A．只有体积很小或质量很小的物体才可发看作质点 B．只要物体运动得不是很快，物体就可以看作质点 C．质点是一种特殊的实际物体D．物体的大小和形状在所研究的问题中起的作用很小，可以忽略不计时，我们就可以把物体看作质点 3．下列说法正确的是（） A．“北京时间10点整”，指的是时间，一节课是40min，指的是时刻 B．列车在上海站停了20min，指的是时间 C．在有些情况下，时间就是时刻，时刻就是时间 D．电台报时时说：“现在是北京时间8点整”，这里实际上指的是时刻 4．短跑运动员在100m竞赛中，测得75m速度为9m/s，10s末到达终点时速度为10.2m/s，则运动员在全程中的平均速度为（） A ． 9 m/s B ． 9.6 m/s C ． 10 m/s D． 10.2 m/s 5．下列说法中，正确的是（） A．质点做直线运动时，其位移的大小和路程一定相等 B．质点做曲线运动时，某段时间内位移的大小一定小于路程 C．两个位移相同的质点，它们所通过的路程一定相等 D ．两个质点通过相同的路程，它们的位移大小一定相等 6．氢氢气球升到离地面80m的高空时从上面掉落下一物体，物体又上升了10m后开始下落，若取向上为正，则物体从掉落开始至地面时位移和经过的路程分别为（） A．80m，100m B．-80m，100m C．80m，100 m D．-90 m，180 m 7．如图所示为同一打点计时器在四条水平运动的纸带上打出的点,其中a , b间的平均速度最大的是哪一条? 8.以下关于加速度的说法中，正确的是： A．加速度为0的物体一定处于静止状态 B．物体的加速度减小，其速度必随之减小C．物体的加速度增加，其速度不一定增大 D．物体的加速度越大，其速度变化越快9. 关于速度，速度改变量，加速度，正确的说法是： A．物体运动的速度改变量很大，它的加速度一定很大 B．速度很大的物体，其加速度可以很小，可以为零 C．某时刻物体的速度为零，其加速度不可能为零 D．加速度很大时，运动物体的速度一定很大

第一章运动的描述

第一章运动的描述 【本章阅读材料】 一．参考系 1.定义：在描述一个物体的运动时，选来作为标准的假定不动的物体，叫做参考系。 2.对同一运动，取不同的参考系，观察的结果可能不同。 3.运动学中的同一公式中涉及的各物理量应以同一参考系为标准，如果没有特别指明，都是取地面为参考系。 二．质点 1.定义：质点是指有质量而不考虑大小和形状的物体。 2.质点是物理学中一个理想化模型，能否将物体看作质点，取决于所研究的具体问题，而不是取决于这一物体的大小、形状及质量，只有当所研究物体的大小和形状对所研究的问题没有影响或影响很小，可以将其形状和大小忽略时，才能将物体看作质点。 三．时间与时刻 1.时刻：指某一瞬时，在时间轴上表示为某一点。 2.时间：指两个时刻之间的间隔，在时间轴上表示为两点间线段的长度。 3.时刻与物体运动过程中的某一位置相对应，时间与物体运动过程中的位移（或路程）相对应。 四．位移和路程 1.位移：表示物体位置的变化，是一个矢量，物体的位移是指从初位置到末位置的有向线段，其大小就是此线段的长度，方向从初位置指向末位置。 2.路程：路程等于运动轨迹的长度，是一个标量。 当物体做单向直线运动时，位移的大小等于路程。 五．速度、平均速度、瞬时速度 1.速度：是表示质点运动快慢的物理量，在匀速直线运动中它等于位移与发生这段位移所用时间的比值，速度是矢量，它的方向就是物体运动的方向。

2.平均速度：物体所发生的位移跟发生这一位移所用时间的比值叫这段时间内的平均速度，即t v x =，平均速度是矢量，其方向就是相应位移的方向。仅能粗略描述物体的运动的快慢程度。 3.瞬时速度：运动物体经过某一时刻（或某一位置）的速度，其方向就是物体经过某有一位置时的运动方向。大小称之为速率。 它能精确描述物体运动的快慢程度。 （4）极短时间内的平均速度等于某时刻的瞬时速度。 六．加速度 1.加速度是描述物体速度变化快慢的的物理量，是一个矢量，方向与速度变化的方向相同。 2.做匀变速直线运动的物体，速度的变化量与发生这一变化所需时间的比值叫加速度，即t v v t v a 0-=??= 3.对加速度的理解要点： （1）加速度的大小和速度无直接关系。质点的运动的速度大，加速度 不一定大；速度小，其加速度不一定小；速度为零，其加速度不一定为零； （2）加速度的方向不一定和速度方向相同。质点做加速直线运动时，加速度与速度方向相同；质点做减速直线运动时，加速度与速度方向相反； （3）物体做加速直线运动还是做减速直线运动，判断的依据是加速度的方向和速度方向是相同还是相反，只要加速度方向跟速度方向相同，物体的速度一定增大（即加速直线运动），只要加速度方向跟速度方向相反，物体的速度一定减小（即减速直线运动）。

第1章运动的描述章末检测

第一章运动的描述 (时间：90分钟满分：100分) 一、选择题(本题共10小题，每小题4分，共40分) 1．2008年9月25日晚21点10分，在九泉卫星发射中心将我国自行研制的“神舟”七号载人航天飞船成功地送上太空，飞船绕地球飞行一圈时间为90分钟，则() A．“21点10分”和“90分钟”前者表示“时刻”后者表示“时间” B．飞船绕地球飞行一圈，它的位移和路程都为0 C．飞船绕地球飞行一圈平均速度为0，但它在每一时刻的瞬时速度都不为0 D．地面卫星控制中心在对飞船进行飞行姿态调整时可以将飞船看成质点 2．明代诗人曾写下这样一首诗：“空手把锄头，步行骑水牛；人在桥上走，桥流水不流．”其“桥流水不流”中的“桥流”应理解成其选择的参考系是() A．水B．桥C．人D．地面 3．物体沿一直线运动，下列说法中正确的是() A．物体在第一秒末的速度是5 m/s，则物体在第一秒内的位移一定是5 m B．物体在第一秒内的平均速度是5 m/s，则物体在第一秒内的位移一定是5 m C．物体在某段时间内的平均速度是5 m/s，则物体在每一秒内的位移都是5 m D．物体在某段位移内的平均速度是5 m/s，则物体在经过这段位移一半时的速度一定是5 m/s 4．甲、乙两个物体在同一直线上运动(始终没有相遇)，当规定向东为正方向时，它们的加速度分别为a甲＝4 m/s2，a乙＝－4 m/s2.下列对甲、乙两物体运动情况的判断中，正确的是() A．甲的加速度大于乙的加速度 B．甲、乙两物体的运动方向一定相反 C．甲的加速度方向和速度方向一致，乙的加速度方向和速度方向相反 D．甲、乙两物体的速度都有可能越来越大 5．一辆汽车从静止开始由甲地出发，沿平直公路开往乙地，汽车先做匀加速运动．接着做匀减速运动，到达乙地刚好停止，其速度图象如图1所示，那么在0～t0和t0～3t0两段时间内() 图1 A．加速度大小之比为2∶1，且方向相反 B．位移大小之比为1∶2，且方向相反 C．平均速度大小之比为2∶1 D．平均速度大小之比为1∶1 6．物体由静止开始运动，加速度恒定，在第7 s内的初速度是2.6 m/s，则物体的加速度是() A．0.46 m/s2B．0.37 m/s2 C．2.6 m/s2D．0.43 m/s2 7. 图2

第一章运动的描述

第1章 怎样描述物体的运动测评 (时间：45分钟，满分：100分) 一、本题共8小题，每小题5分，共40分不定项选择． 1．如图所示的是体育摄影中“追拍法”的成功之作，摄影师眼中清晰的运动员是静止的，而模糊的背景是运动的，摄影师用自己的方式表达了运动的美．请问摄影师选择的参考系是 A ．大地 B ．太阳 C ．运动员 D ．步行的人 2．在下列各种情况中，物体可看做质点的是 A ．正在做课间操的同学们都可以看做质点 B ．从地面控制中心的屏幕上观察“嫦娥一号”的运动情况 时，“嫦娥一号”可以看做质点 C ．观察航空母舰上的舰载飞机起飞时，可以把航空母舰看做质点 D ．在作战地图上确定航空母舰的准确位置时，可以把航空母舰看做质点 3．中国飞人刘翔，在2008年5月10日的大阪国际田径大奖赛男子110米栏的比赛中，以13秒19的成绩如愿摘金，在大阪大奖赛上夺得五连冠．关于比赛的下列说法中正确的是 A ．110 m 是刘翔比赛中位移的大小 B ．13秒19是刘翔夺冠的时刻 C ．刘翔比赛中的平均速度约是8.3 m/s D ．刘翔经过终点线时的速度一定等于8.3 m/s 4．让一个小球从2 m 高处落下，被地面弹回，在1 m 高处被接住，则小球在这一过程中 A ．位移大小是3 m B ．位移大小是1 m C ．位移大小是2 m D ．路程是2 m 5．(2008山东学业水平测试，4)下列事例中有关速度的说法，正确的是 A ．汽车速度计上显示80 km/h ，指的是平均速度 B ．某高速公路上的限速为110 km/h, 指的是平均速度 C ．火车从济南到北京的速度约为220 km/h, 指的是瞬时速度 D ．子弹以900 km/h 的速度从枪口射出，指的是瞬时速度 6．下列对加速度的定义式a ＝Δv Δt 的理解正确的是 A ．加速度a 与速度变化量Δv 成正比 B ．加速度a 的大小由速度变化量Δv 决定 C ．加速度a 的方向与Δv 方向相同 D ．加速度a 决定于速度变化率Δv Δt 7．如图所示分别为甲、乙两物体的st 图像，则下列关于甲、乙两物体的速度都正确的是 A ．v 甲＝30 m/s v 乙＝30 m/s B ．v 甲＝20 m/s v 乙＝30 m/s C ．v 甲＝30 m/s v 乙＝20 m/s D ．v 甲＝45 m/s v 乙＝15 m/s 8．甲、乙两个物体在同一直线上运动的vt 图像如图所示，由 图像可知两物体 A ．速度方向相同，加速度方向相反 B ．速度方向相反，加速度方 向相同 C ．甲的加速度大于乙的加速度 D ．甲的加速度小于乙的加速度 第Ⅱ卷(非选择题 共60分) 二、实验题：本题15分，把答案填在题中横线上． 9．在研究匀变速直线运动的实验中，一记录小车运动情况的纸带 如图所示，图中A 、B 、C 、D 、E 、F 为相邻的计数点，相邻的计数点 间的时间间隔为T ＝0.1 s ．求： (1)各点的瞬时速度v B ＝______m/s ，v C ＝______m/s ，v D ＝______m/s ，v E ＝______m/s. (2)打点计时器打A 点开始计时，在下面图中作出小车的vt 图像．

人教版物理必修一试题第一章：运动的描述单元练习题(新课标有答案).docx

& 鑫达捷致力于精品文档精心制作仅供参考& 高中物理学习材料 高一物理(必修1)第一章<<运动的描述>>单元练习 班级姓名：座号 一、选择题（不定项） 1.下面关于质点的说法正确的是：（ C ） A、地球很大，不能看作质点 B、原子核很小，可以看作质点 C、研究地球公转时可把地球看作质点 D、研究地球自转时可把地球看作质点 2.一小球从4m高处落下，被地面弹回，在1m高处被接住，则小球的路程和位移大小分别为： （ A ） A、5m，3m B、4m，1m C、4m，3m D、 5m，5m 3.某人坐在甲船看到乙船在运动，那么相对河岸两船的运动情况不可能的是（ D ） A、甲船不动，乙船在运动 B、甲船运动，乙船不动 C、甲、乙两船都在运动 D、甲、乙两船都以相同的速度运动 4.两辆汽车在平直公路上行驶，甲车内的人看见树木向东移动，乙车内的人发现甲车没有运动，如果以 大地为参考系，上述事实说明：（ D ） A、甲车向西运动，乙车不动 B、乙车向西运动，甲车不动 C、甲车向西运动，乙车向东运动 D、甲、乙两车以相同速度向西运动 5.下列说法正确的是：（ B ） A、质点一定是体积很小、质量很小的物体 B、地球虽大，且有自转，但有时仍可将地球看作质点 C、研究自行车的运动时，因为车轮在转动，所以无论什么情况下，自行车都不能看成质点 D、当研究一列火车全部通过桥所需的时间，因为火车上各点的运动状态相同，所以可以把火车视为 质点 6.关于位移和路程的说法中正确的是：（ CD ） A、位移的大小和路程的大小总是相等的，只不过位移是矢量，而路程是标量 B、位移是描述直线运动的，路程是描述曲线运动的 C、位移取决于始末位置，路程取决于实际运动的路线 D、运动物体的路程总大于或等于位移的大小 7.如图所示，一质点绕半径为R的圆周运动，当质点由A点运动到B点时，其位移大小和路程分别是（ C ） A．R R

1-：第一章 运动的描述(知识框架)

第一章 运动的描述（知识框架） - 1 - 第一章 运动的描述（知识框架） 运 动 的 描 述 质点：形状、大小可忽略不计的有质量的点 物体可看成质点的条件：物体的大小、形状对研究问题的影响可忽略不计 参考系：描述一个物体运动时，用来选作标准的另外的物体 坐标系：用来准确描述物体位置及位置变化 基本概念 概念对比 时刻：是指某一瞬时，在时间轴上是一个点 时间：是时间间隔的简称，指一段持续的时间间隔， 两个时刻的间隔表示时间 路程：质点实际运动的轨迹的长度；单位m 。 位移：从物体运动的起点指向运动的终点的有向线段，表示位置的变化； 单位：m 矢量：既有大小，又有方向的物理量；如：速度、位移 标量：只有大小，没有方向的物理量；如：路程、时间 定义：物体运动的位移与时间的比值 物理意义：表示物体运动的快慢 速度 公式：t x t x =??=ν；单位：m/s 矢量性：矢量 定义：某一过程中的一段位移与其所对应的时间的比值 物理意义：粗略地表示物体运动的快慢 公式：t x t x =? ?= ν ；单位：m/s 矢量性：矢量 平均速度 速率：表示速度的大小；标量。 平均速率：表示某义过程中的一段路程与其所用的时间的比值 是一个标量 速率 速度 定义：速度的变化量与时间的比值 物理意义：表示速度变化的快慢 公式： t v v t v a t 0-=??=; 单位：m/s 2 矢量性：矢量，与速度变化量方向相同 加速度 实验 打点计时器分类：电磁打点计时器和电火花打点计时器 振动频率：均为50Hz ，即每隔0.02s 打一个点 纸带分析：a.可计算物体运动的平均速度 b ．粗略计算瞬时速度

人教版高一物理上册 运动的描述检测题(Word版 含答案)

一、第一章运动的描述易错题培优（难） 1．质点做直线运动的v-t 图象如图所示，则（） A．3 ~ 4 s 内质点做匀减速直线运动 B．3 s 末质点的速度为零，且运动方向改变 C．0 ~ 2 s 内质点做匀加速直线运动，4 ~ 6 s 内质点做匀减速直线运动，加速度大小均为 2 m/s2 D．6 s内质点发生的位移为 8 m 【答案】BC 【解析】 试题分析：矢量的负号，只表示物体运动的方向，不参与大小的比较，所以3 s～4 s内质点的速度负方向增大，所以做加速运动，A错误，3s质点的速度为零，之后开始向负方向运动，运动方向发生变化，B错误，图线的斜率表示物体运动的加速度，所以0～2 s内质点做匀加速直线运动，4 s～6 s内质点做匀减速直线运动，加速度大小均为2 m/s2，C正确，v-t图像围成的面积表示物体的位移，所以6 s内质点发生的位移为0，D错误， 考点：考查了对v-t图像的理解 点评：做本题的关键是理解v-t图像的斜率表示运动的加速度，围成的面积表示运动的位移，负面积表示负方向位移， 2．如图，直线a和曲线b分别是在平直公路上行驶的汽车a和b的位置一时间（x一t）图线，由图可知 A．在时刻t1，a车追上b车 B．在时刻t2，a、b两车运动方向相反 C．在t1到t2这段时间内，b车的速率先减少后增加 D．在t1到t2这段时间内，b车的速率一直比a车大 【答案】BC 【解析】 【分析】

【详解】 由x—t图象可知，在0-t1时间内，b追a，t1时刻相遇，所以A错误；在时刻t2，b的斜率为负，则b的速度与x方向相反，所以B正确；b图象在最高点的斜率为零，所以速度为零，故b的速度先减小为零，再反向增大，所以C正确，D错误． 3．高速公路上用位移传感器测车速，它的原理如图所示，汽车D向右匀速运动，仪器C 在某一时刻发射超声波脉冲（即持续时间很短的一束超声波），经过时间t1接收到被D反射回来的超声波，过一小段时间后又发射一个超声波脉冲，发出后经过时间t2再次接收到反射回来的信号，已知超声波传播的速度为v0，两次发射超声波脉冲的时间间隔为△t，则下面说法正确的是（） A．第一次脉冲测得汽车和仪器C的距离为 01 1 2 v t B．第二次脉冲测得汽车和仪器C的距离为02 v t C．位移传感器在两次测量期间，汽车前进距离为 021 1 () 2 v t t- D．测得汽车前进速度为021 21 () 2 v t t t t t - +?- 【答案】ACD 【解析】 【分析】 【详解】 AB．超声波是匀速运动的，往返时间相同，第一次脉冲测得汽车和仪器C的距离为01 1 2 v t，第二次脉冲测得汽车和仪器C的距离为 02 1 2 v t，故A正确，B错误； C．则两次测量期间，汽车前进的距离为 () 021 1 2 s v t t =- 故C正确； D．超声波两次追上汽车的时间间隔为 12 22 t t t t ' ?=?-+ 故速度

第一章 运动的描述

§1.1 质点、参考系和坐标系 一.机械运动：一个物体相对于另一个物体的位置变化，叫做机械运动（简称运动）。机械运动包括：平动、转动、机械振动。物体的运动轨迹可能是直线也可能是曲 线。 二.质点：一个有质量的点，把实际物体看做一个有质量的点。质点是一个理想化的物 理模型，实际并不存在，是为了方便描述物体的运动将实际物体抽象成一个点。这个点不同于几何点，尽管它们都是零维（零维指没有长、宽、高的维）的，但质点是有质量的，它代表着实际的物体。把一个实际的物体看做质点是抓住了事物的主要矛盾而忽略了次要因素，这也是物理学研究的一种很重要的方法。今后在物理学中经常会用到这种方法。 三.实际物体能被看做质点的条件：实际物体能否被看做质点要看问题本身，同一 个物体在甲问题中能看做质点而在乙问题中就不能看成质点了。具体要注意以下几点：①如果物体的几何形状和尺度对研究问题本身影响很小，以至于可以不考虑物体的形状时可以把物体看做质点。 比如，我们要计算一列火车从北京到上海的时间，因为火车的几何尺度与北京到上海的距离无法比拟，因此我们可以把火车看成质点。 ②作平动的物体一般可以被视为质点，但这也不是绝对的。 比如，火车的运动可以被看做平动，我们要计算一列火车从北京到上海的时间，因为火车的几何尺度与北京到上海的距离无法比拟，因此我们可以把火车看成质点。但是要计算一列火车穿越一个山洞的时间时，就不能把火车看做质点了。 ③作转动的物体一般不能看作质点，但这也不是绝对的。 比如，研究一根绕固定轴转动的木棒的运动情况，就不能把木棒看作质点。但是研究作圆周运动的物体时可以把物体看做质点。 ④并不是很小的物体就一定能视为质点，而很大的物体就不能视为质点。 在高中阶段我们所接触到的物体大部分是可以被视为质点的。 例题： 1.关于运动员和球类能否看成质点，以下说法正确的是（） A.研究跳高运动员的起跳和过杆动作时，可以把运动员看成质点 B.研究花样滑冰运动员的冰上动作时，能把运动员看成质点 C.研究足球的射门速度时，可以把足球看成质点 D.研究乒乓球弧圈球的接球时，能把乒乓球看成质点 2.在下列物体的运动中，可把物体视为质点的是（） A.研究“神州七号”绕地球运动的圈数时 B.对“神州七号”进行姿态调整时 C.研究跳水运动员在空中的翻滚运动时 D.研究从滑梯上滑下的小孩 四.参考系：为了描述物体的运动，需要先选定一个假定不动的物体作标准，看要描述 的那个物体相对于这个标准物体是如何运动的，这个被选作标准的物体就叫做参考系（参照物）。

大气扩散浓度估算模式

第四章 大气扩散浓度估算模式 4.1 污染源的东侧为峭壁，其高度比污染源高得多。设有效源高为H ，污染源到峭壁的距离为L ，峭壁对烟流扩散起全反射作用。试推导吹南风时高架连续点源的扩散模式。当吹北风时，这一模式又变成何种形式？ 解： 吹南风时以风向为x 轴，y 轴指向峭壁，原点为点源在地面上的投影。若不存在峭壁，则有 ]}2)(exp[]2)(){exp[2exp(2),,,(22 22 22' z z y z y H z H z y u Q H z y x σ σ σ σ σπρ+- +-- - = 现存在峭壁，可考虑ρ为实源与虚源在所关心点贡献之和。 实源]}2)(exp[]2)(){exp[2exp(222 22 221z z y z y H z H z y u Q σ σ σ σ σπρ+- +-- - = 虚源]}2)(exp[]2)(]{exp[2)2(exp[222 22 22 2z z y z y H z H z y L u Q σ σ σσσπρ+- +-- -- = 因此]}2)(exp[]2)(){exp[2exp(222 22 22z z y z y H z H z y u Q σ σ σ σ σπρ+- +-- - =+ ]}2)(exp[]2)(]{exp[2)2(exp[222 22 22 z z y z y H z H z y L u Q σ σ σ σ σπ+- +-- -- = ]}2)(exp[]2)(]}{exp[2)2(exp[)2{exp(222 22 22 22z z y y z y H z H z y L y u Q σ σ σ σ σ σπ+- +-- -- +- 刮北风时，坐标系建立不变，则结果仍为上式。 4.2 某发电厂烟囱高度120m ，内径5m ，排放速度13.5m/s ，烟气温度为418K 。大气温度288K ，大气为中性层结，源高处的平均风速为4m/s 。试用霍兰德、布里格斯（x<=10H s ）、国家标准GB/T13201－91中的公式计算烟气抬升高度。 解： 霍兰德公式 m D T T T u D v H s a s s 16.96)5418 2884187.25.1(4 5 5.13)7 .25.1(=?-? +?= -+= ?。 布里格斯公式 kW kW D v T T T Q s s a s H 210002952155.13418 28841810 6.9 7.210 6.9 7.22 3 2 3 >=??-? ?= -? ?= --且x<=10Hs 。此时 3 /23 /21 3 /11 3 /23 /180.24 29521 362.0362.0x x u x Q H H =??==?--。

人教版必修一第一章《运动的描述》单元教学设计1(精品).doc

第一章运动的描述 （一）全章知识脉络，知识体系 基本概念图解

一、质点、参考系、位移、路程 1.下列物体中，不能看作质点的是（） A.计算从北京开往上海的途中，与上海的距离时的火车 B.研究航天飞机相对地球的飞行周期时，绕地球飞行的航天飞机 C.沿地面翻滚前进的体操运动员 D. 比较两辆行驶中的车的快慢 2.下列关于参考系的描述中，正确的是（） A.参考系必须是和地面连在一起的物体 B.被研究的物体必须沿与参考系的连线运动 C.参考系必须是正在做匀速直线运动的物体或是相对于地面静止的物体 D.参考系是为了研究物体的运动而假定为不动的那个物体 四、计算题(共27分) 16.（8分）已知一汽车在平直公路上运动，它的位移一时间图象如图（甲）所示. （1）根据图象在图（乙）所示的位置坐标轴上标出A、B、C、D、E各点代表的汽车的位置 （2）求出下列各段时间内汽车的路程和位移大小 ①第 l h内．②前6 h内③前7 h内④前8 h内 17. （9分）A、B、C三地彼此间的距离均为 a，如图所示物体以每秒走完距离a的速度从A点出发，沿折线经B、C点又回到A点试分析说明从运动开始经1 s、2 s、

3 s ，物体的位移大小和路程各为多少？ 18.（10分）如图所示为一物体沿直线运动的s-t 图象，根据图象：求 （1）第2 s 内的位移，第4 s 内的位移，前5 s 的总路程和位移 （2）各段的速度 （3）画出对应的v -t 图象 二、速度（瞬时速度、平均速度） 1．试判断下面的几个速度中哪个是瞬时速度 A ．子弹出枪口的速度是800 m/s ，以790 m/s 的速度击中目标 B ．汽车从甲站行驶到乙站的速度是40 km/h C ．汽车通过站牌时的速度是72 km/h D ．小球第3ｓ末的速度是6 m/s 2．下列说法中正确的是 A ．做匀速直线运动的物体，相等时间内的位移相等 B ．做匀速直线运动的物体，任一时刻的瞬时速度都相等 C ．任意时间内的平均速度都相等的运动是匀速直线运动 D ．如果物体运动的路程跟所需时间的比值是一个恒量，则此运动是匀速直线运动 3．下面关于瞬时速度和平均速度的说法正确的是 A ．若物体在某段时间内每时刻的瞬时速度都等于零，则它在这段时间内的平均速度一 定等于零 B ．若物体在某段时间内的平均速度等于零，则它在这段时间内任一时刻的瞬时速度一 定等于零 B

高一物理必修一第一章《运动的描述》单元测试题(含详细解答)[1]

《运动的描述》单元测试题 本卷分第Ⅰ卷(选择题)和第Ⅱ卷(非选择题)两部分．满分100分，时间90分钟． 第Ⅰ卷(选择题共40分) 一、选择题(共10小题，每小题4分，共40分，在每小题给出的四个选项中，有的小题只有一个选项符合题目要求，有些小题有多个选项符合题目要求，全部选对的得4分，选不全的得2分，有选错或不答的得0分) 1．下列关于质点的说法正确的是() A．研究和观察日食时，可以把太阳看成质点 B．研究地球的公转时，可以把地球看成质点 C．研究地球的自转时，可以把地球看成质点 D．原子核很小，必须把它看成质点 2．(广东惠阳08－09学年高一上学期期中)2008年9月25日晚21点10分，我国在九泉卫星发射中心将我国自行研制的“神舟7号”宇宙飞船成功地送上太空，飞船绕地球飞行一圈时间为90分钟．则() A．“21点10分”和“90分钟”前者表示“时刻”后者表示“时间” B．卫星绕地球飞行一圈，它的位移和路程都为0 C．卫星绕地球飞行一圈平均速度为0，但它在每一时刻的瞬时速度都不为0 D．地面卫星控制中心在对飞船进行飞行姿态调整时可以将飞船看作质点 3．甲物体以乙物体为参考系是静止的，甲物体以丙物体为参考系又是运动的，那么，以乙物体为参考系，丙物体的运动情况是() A．一定是静止的 B．运动或静止都有可能 C．一定是运动的 D．条件不足，无法判断 ． 4．(福建厦门一中09－10学年高一上学期期中)两个人以相同的速率同时从圆形轨道的A点出发，分别沿ABC和ADC行走，如图所示，当他们相遇时不相同的物理量是() A．速度B．位移 C．路程D．速率

5．两个质点甲和乙，同时由同一地点向同一方向做直线运动，它们的v －t 图象如图所示，则下列说法中正确的是( ) A ．质点乙静止，质点甲的初速度为零 B ．质点乙运动的速度大小、方向不变 C ．第2s 末质点甲、乙速度相同 D ．第2s 末质点甲、乙相遇 6．某人爬山，从山脚爬上山顶，然后又从原路返回到山脚，上山的平均速率为v 1，下山的平均速率为v 2，则往返的平均速度的大小和平均速率是( ) A.v 1＋v 22，v 1＋v 22 B.v 1－v 22，v 1－v 2 2 C ．0，v 1－v 2 v 1＋v 2 D ．0，2v 1v 2 v 1＋v 2 7．(银川一中09－10学年高一上学期期中)下列关于物体运动的说法，正确的是( ) A ．物体速度不为零，其加速度也一定不为零 B ．物体具有加速度时，它的速度可能不会改变 C ．物体的加速度变大时，速度也一定随之变大 D ．物体加速度方向改变时，速度方向可以保持不变 8．下表是四种交通工具的速度改变情况，下列说法正确的是( ) 初始速度(m/s) 经过时间(s) 末速度(m/s) ① 2 3 11 ② 0 3 6 ③ 0 20 6 ④ 100 20 A.①的速度变化最大，加速度最大 B ．②的速度变化最慢 C ．③的速度变化最快 D ．④的末速度最大，但加速度最小