Exporters in the financial crisis.
Gorg, Holger ; Spaliara, Marina-Eliza
I. Introduction
Trade was hit hard during the global financial crisis. Data in the
World Trade Report 2012 show that average export growth was around 2 per
cent and -12 per cent, respectively, in 2008 and 2009, and rebounded to
+14 and +5 per cent in 2010 and 2011, respectively (WTO, 2012). Indeed,
the drop in trade during the crisis far outpaced the decline in global
GDP (Alfaro and Chen, 2012). There have been various explanations for
this trade collapse during the crisis, attributing it to a strong fall
in demand, a rise in protectionism, a domino effect because of global
value chains, or restrictions in the access to finance for exporters
(e.g., Baldwin and Evenett, 2009; Chor and Manova, 2012; Bricongne et
al, 2012). The latter explanation in particular has received much
attention in the recent literature.
Corporate funding (or the lack thereof) has also been a major
concern for policymakers during the recent financial crisis. In the UK,
business lending, which has been falling steadily for the past four
years, plunged below 400 billion [pounds sterling] by the beginning of
May 2013. That is 20 per cent below its level four years ago.
Participants in the Funding for Lending Scheme group, which includes all
of the big high-street banks except HSBC, cut credit by 300 million
[pounds sterling] in the first quarter of 2013 (The Economist, 2013).
Bell and Young (2010) find evidence of a substantial tightening in
credit supply in the UK economy from mid-2007. They argue that loan
spreads on SMEs rose during the crisis period, with syndicated loan
spreads presenting a sharp increase from mid-2008.1 Access to finance
remains a major barrier to growth for more than one in five UK small
firms with 41 per cent of loan applications refused in the first quarter
of 2012 (Federation of Small Businesses).
According to the financial accelerator theory, deteriorations in
economic conditions increase the cost of finance, which in turn weakens
firms' balance sheet positions, thus influencing their activities
(Bernanke et ai, 1996). Therefore, the financial system can generate an
endogenous cycle (the accelerator) that propagates the initial shock
over time. It is evident from recent studies that the collapse of the
supply of loans to non-financial firms has negatively affected
firms' activities (employment, investment, survival prospects)
which in turn led to a sharp drop in economic activity. (2) While the
deterioration in access to bank finance affects all firms, it is likely
to be particularly severe for exporters since, as Amiti and Weinstein
(2011) discuss, exports are highly dependent on access to finance, much
more so than the domestic operations of firms.
In this paper we look at what happened to exporters during the
financial crisis, using firm-level data for the UK. We investigate
whether the entry of new firms into exporting was affected by the
financial crisis. Furthermore, we compare the performance of exporters
in terms of employment and sales growth, and survival, with that of
non-exporters before and during the crisis.
By doing so, this paper is complementary to some of our earlier
work, where we also use UK firm-level data to investigate the link
between access to finance and export activity. In Gorg and Spaliara
(2013) we examine the link between firms' financial health,
borrowing ratio and export market exit, paying special attention to the
recent financial crisis. We find, inter alia, that the deterioration in
the financial position of firms has increased the hazard of export
market exit during the crisis. While we look at exiting the export
market in that paper, the present paper considers export market entry,
as well as firm growth and firm survival during the crisis. More
recently, Gorg and Spaliara (2014b) assess the role of different
exporting statuses in the link between financial health and firm
survival. Results suggest that good financial health boosts the survival
prospects for continuous exporters and continuous non-exporters while it
has a modest impact on export starters and exiters. In the present paper
we look in addition at differential survival prospects during the
crisis.
Our paper is also related to a wider literature that looks at the
link between finance and exporting at the firm level. For example, Amiti
and Weinstein (2011) present a comprehensive study of the link between
firm's exports at the intensive margin and finance, focusing on the
health of the bank providing access to credit. They look at the Japanese
financial crisis from 1990 to 2010. Chor and Manova (2012) use product
level data on US imports, investigating the role of credit conditions as
the main culprit for reducing trade during the crisis. Bricongne et al.
(2012), using firm-level data for France, also investigate the effects
of the crisis, and focus on financial variables at the firm level.
Studies by Askenazy et al. (2011) and Engel et al. (2013) (also based on
French firm-level data) further consider the role of financial
indicators in exporting. The former study assesses theoretically and
empirically the role of credit constraints in export market entry and
exit, while the latter investigates the characteristics of companies
deciding to participate in foreign markets and engage in exporting or
foreign direct investment. There are also other studies which suggest
that financial health matters in firms' decisions to enter and
remain in export markets, see for example Minetti and Zhu (2011),
Bellone et al. (2010), and Greenaway et al. (2007).
The rest of the paper is structured as follows. Section 2 presents
the data and preliminary statistics. The next section models empirically
the decision of firms to enter into export markets, focusing
particularly on the role of the financial position. Section 4 examines
performance differences between different types of exporters and
non-exporters before and during the crisis, while Section 5 looks at
firm survival and firms' export status. Section 6 concludes.
2. Data and summary statistics
The data set we use in this paper is constructed from the profit
and loss and balance sheet data gathered by Bureau Van Dijk Electronic
Publishing in the FAME database. We use data for the period 2000-9 and
define the crisis years as the period 2008-9. FAME assigns companies a
four-digit UK SIC code which we use to classify firms into industries.
Our sample is limited to firms that operate in the manufacturing
industry. Our database includes a majority of firms (99.9 per cent)
which are not traded on the stock market or which are not quoted on
alternative exchanges such as the Alternative Investment Market (AIM)
and the Off-Exchange (OFEX) market. This feature of the data allows for
a wide degree of variation across observations in our sample. A
distinctive characteristic is that not only small and medium sized firms
are included in our sample but also some large firms that are more
likely to export. (3) Private companies in our data are generally the
smallest, youngest, and most bank-dependent firms. They are therefore
more likely than public companies to face financial constraints and
difficulties in accessing bank finance. (4)
[FIGURE 1 OMITTED]
The share of exporting firms in our sample is 52 per cent which is
comparable to Greenaway et al. (2007) who also use FAME data for UK
manufacturing firms. The median UK firm in our sample has an average of
85 employees, 4.7 million [pounds sterling] assets and 9.5 million
[pounds sterling] turnover which falls into the small and medium-sized
enterprise category. (5)
In order to see what happened to the financial position of firms in
our data set during the financial crisis, figure 1 illustrates the
average firm-specific interest rate (defined as the ratio of interest
payments to profit and loss after taxes plus depreciation) paid by firms
between 2000 and 2009. We distinguish firms based on the ratio of
short-term debt to the sum of short-term debt and trade credit. Firms
with ratios above the median are considered, for this simple exercise,
to be more bank dependent. The figure shows that after steadily
declining since 2001, the interest rate hiked up again in 2008 and 2009
as a result of the crisis. We also see that, consistently throughout the
years, more bank-dependent firms are faced with a higher borrowing ratio
compared to their less bank-dependent counterparts. (6) Hence, during
crisis periods, the worsening of the balance sheet position of firms and
the rise in debt servicing costs might be expected to affect firm
performance. This is what we investigate in what follows, with a
particular focus on looking at exporters vs non-exporters.
We start with some preliminary statistics before moving on to
econometric estimation. Table 1 gives an indication of the financial
condition of exporters and non-exporters during tranquil (pre-crisis)
and crisis periods. Our financial crisis dummy (CRISIS) takes the value
one over the period 2008-9, and zero otherwise The data show that, on
average, exporters are less indebted and more liquid compared to
non-exporters. This is in line with Greenaway et al. (2007) and also
with the view of much of the recent work on heterogeneous firms, which
shows that exporters are generally the better performing firms in an
economy (e.g., Bernard et al., 2007). When we distinguish different
stages of exporting (i.e starters, exiters, continuers, switchers and
non-exporters), we observe that export starters and exiters display the
highest level of debt and the lowest liquidity ratio compared to
continuous and switcher exporters. (7) The finding on starters is again
in line with Greenaway et al. (2007) and may indicate the importance of
costs that new exporters have to bear, which worsens their financial
position. The poor financial health of firms that exit from the export
market may indicate that these are poorly performing firms, which cannot
survive in international competition (see also Girma et al., 2004).
Comparing the crisis period (2008-9) with the pre-crisis period
(2000-7), we find that all types of firms, exporters and non-exporters
alike, display lower values of leverage and higher levels of liquidity.
This would, under normal circumstances, seem to indicate an improvement
in the financial position of a firm. However, in the wake of the crisis
the lower levels of leverage are consistent with the notion that firms
took a substantial amount of short-term debt in the pre-crisis period
and were unable to extend it further in the later years when the
financial crisis hit and bank lending collapsed. In addition, the
observation that liquidity is higher during the crisis than at other
times is likely to indicate that firms boosted their holdings of cash
and other liquid assets as a buffer due to the uncertainty in credit
markets. (8) Mean differences are statistically significant in most of
the cases, as indicated by a t-test.
Finally, we perform a univariate analysis in order to look at the
survival prospects of different types of exporters taking into account
the effects of the 2008-9 crisis. Table 2 shows the proportion of failed
and surviving firms by exporting status. The data show, for example,
that 18.6 per cent of failed firms and 29.4 per cent of all surviving
firms are export starters. Non-exporters account for the largest share
of both failing and surviving firms. When we compare column 1 with
column 2 it becomes apparent that starters, continuous exporters and
switchers have a higher probability of survival compared to exiters and
non-exporters.
3 Exporting decisions and the financial position of the firm
In the first part of our analysis we consider whether the financial
crisis has had any implications for firms' decisions to enter into
export markets. Greenaway et al. (2007) also use British firm-level data
from FAME to establish that financial factors matter for export
decisions of firms. In particular, they show that firms that start
exporting generally have lower liquidity and higher leverage than
non-exporters. This may be due to the additional costs these firms have
to bear in order to enter export markets, such as costs for building up
new distribution networks, market research or legal costs. We follow up
on their analysis and consider in particular a firm's decision to
start exporting, the role of financial factors in this decision, and
whether the role of financial factors changed during the crisis. In
order to do so, we follow Greenaway et al. (2007) and employ two
financial variables to measure changes in the financial health of firms.
The first one is liquidity, which is defined as the firm's current
assets less current liabilities over total assets and is an indicator of
the liquid assets of the firm. The higher the liquidity ratio the better
the financial position of the firm. The second financial characteristic
is leverage, which is measured as the firm's short-term debt to
assets ratio. A high leverage ratio is associated with a worse balance
sheet situation. This may increase moral hazard and adverse selection
problems, and lead to the inability of firms to obtain external finance
at a reasonable cost.
In a next step, we investigate whether financial factors determine
a firm's decision to start to export, and whether this relationship
has changed during the financial crisis starting in 2008. In table 3, we
estimate the probability that a firm that is not an exporter in time t
becomes an exporter in t+1 conditional on its size and age and, most
importantly, its financial condition. In particular, we examine the
impact of liquidity and leverage on the likelihood of starting to export
before and during the crisis using a probit model.
We observe that liquidity positively affects the likelihood of
exporting during tranquil periods. This is in line with Greenaway et al.
(2007) and suggests that more liquid firms are more likely to be able to
pay their sunk cost of entry and start operating abroad. The
statistically insignificant coefficient on the term interacting
liquidity and a dummy for the crisis period reveals that the beneficial
impact of liquidity on exporting is not statistically different during
the crisis. This picture is somewhat different when we look at the level
of indebtedness of a firm. Leverage has a marginally significant
negative impact on the probability of exporting outside of the crisis.
However, this negative effect increases in magnitude during the crisis.
In other words, indebted companies seem somewhat less likely to start
exporting during tranquil periods. However, this negative effect becomes
much stronger during the crisis. We also find that the crisis dummy on
its own produces a negative and statistically significant sign. This
implies that, all other things equal, firms are less likely to start
exporting in the crisis period than before the crisis. As a robustness
check we define the crisis for the period 2007-9. This does not change
our conclusions on the impact of the crisis or the role of liquidity and
indebtedness in and out of the crisis. (9)
Overall, the results in this section show that fewer firms enter
the export market during the crisis, and that financial factors do play
a significant role for a firm's decision to start exporting. The
level of a firm's debt is a much stronger deterrent of exporting
during the crisis than in the period before the crisis. This suggests
that indebted firms find it more difficult to access during the crisis
the financial resources that would allow them to pay the additional sunk
costs of export market entry.
4. Firm growth and exporting
We now investigate what happened to firms after entering the export
market. How do they perform and, perhaps more importantly, how does the
performance of exporters compare to other firms? And, what is the effect
of the crisis for exporters and non-exporters? In order to do so, we
attempt to assess the effect of exporting on firm dynamics in terms of
output and employment with a particular emphasis on the recent financial
crisis.
We have charted the behaviour of several variables distinguishing
between different firm types. Table 4 summarises the graphical evidence.
(10) In what follows, we discuss our graphical findings. First, when we
distinguish exporters from non-exporters, we show that the levels of
sales and employment are higher for exporters compared to non-exporters
throughout the sample. This is consistent with a large literature that
documents performance premia for exporters vis-a-vis non-exporters in
terms of size, productivity, wages, etc. (e.g., Wagner, 2007). A drop in
the series is observed during the crisis years 2008-9. Employment and
sales are lower for both exporters and non-exporters, though the
reduction appears to be larger for exporters, reducing the gap between
exporters and their non-exporting counterparts. In line with the
aggregate picture, where, as we discussed in the introduction, trade
decreased by more than total GDP worldwide, this suggests that exporting
firms suffered relatively more from the crisis in terms of output and
employment losses than firms operating purely in the domestic market.
When we differentiate between different stages of exporting (i.e
starters, exiters, continuers, switchers and non-exporters), we observe
that continuous exporters display the highest level of employment and
sales followed by starters and switchers. Export exiters and
non-exporters are found at the bottom of the graphs. All types of
exporters face a decrease in employment and sales during the recent
financial crisis.
Next, we consider the role of credit constraints. There is an
established literature on financing constraints and firms' real
activities that was initiated by the influential work of Fazzari et al.
(1988). Following this literature (e.g., Gertler and Gilchrist, 1994;
Spaliara, 2009 and 2011; Mizen and Tsoukas, 2012; Tsoukas and Spaliara,
forthcoming) we split firms by age into old and young, and by size into
large and small. (11) The assumption is that small and young firms are
more likely to face credit constraints as it is, all other things equal,
more difficult for them to obtain external finance from banks. (12)
Based on these categories, we observe the change in the growth of
firms for more and less credit constrained firms. In particular, we
compare the change in the mean of employment and sales for small and
young firms with the corresponding change for their old and large
counterparts. As one would expect, employment and sales are higher for
large and old firms throughout our sample. Between 2008-9 we witness a
drop in both series. This drop appears to be larger for old and large
firms compared to young and small establishments, reducing the gap
between financially constrained and unconstrained firms.
Finally, we consider the average firm's export intensity and
its relationship with firm dynamics. Based on a firm's share of
exports in total sales, we classify firms into high and low
export-intensive firms. (13) We chart average sales and employment for
these two groups of firms. We observe that higher export intensity is
related to larger sales and employment. Flowever, the gap in sales
between high and low intensity exporters diminished consistently over
the 2000s, while the picture is not as clear cut for employment. Both
sales and employment dropped considerably in 2009. In fact, the gap in
employment between high and low intensity exporters all but vanished in
2009 during the crisis.
Next we provide some additional formal econometric evidence to
account for the role of exporting and the effect of the crisis on firm
dynamics. We employ simple OLS regressions to assess the effect of
different exporting status on firm dynamics in and out of the crisis.
Time and industry dummies are included to account for business cycle
effects and industry dynamics. Table 5 presents results of explorative
regressions where we regress employment (in column 1) and sales (in
column 2), respectively, on dummies for groups of exporting and a dummy
for the crisis period. To capture the indirect effect of the crisis, we
interact the different facets of exporting with the crisis dummy. The
interaction gauges the change in exporting groups relative to the
reference category, continuous non-exporters, for the crisis period. The
financial condition of the firm is taken into account by including
variables such as leverage and liquidity. We also control for size and
age of the firm.
Results show statistically significant positive coefficients for
all different types of exporters during tranquil periods. This implies
that compared to non-exporters, all exporter categories have higher
levels of employment and sales. In other words, there are performance
differences in line with the literature (e.g., Wagner, 2007). Comparing
the coefficients for the different groups, we find that the positive
relationship with employment and sales appears strongest for continuous
exporters and switchers rather than for starters and exiters. This is in
line with the ideas of sunk costs of export entry and performance
disadvantages for export exiters.
However, the interaction terms are largely statistically
insignificant. When the crisis is defined differently (2007-9) some
interesting results emerge. (14) We find that the performance advantage
for export starters and continuous exporters is stronger during the
crisis, at least in terms of employment. Hence, this suggests that the
gap between export starters and continuous, respectively, and
non-exporters is larger during the crisis period than out of it. Hence,
these types of exporters appear to have fared better during the crisis
than the average non-exporter. By contrast, the performance difference
between export switchers and non-exporters has diminished during the
crisis, while there is no statistically significant difference in the
link between export and performance in and out of the crisis for firms
that exit the export market. Hence, in order to discern a differential
impact of the crisis for different types of exporters, it is crucial how
one defines the timing of the recent financial crisis.
5. The hazard of failure and exporting
In the final part of the analysis we look at the survival prospects
of different types of exporters taking into consideration the effects of
the recent crisis. We therefore turn to estimating the hazard of firm
failure conditional on the export status of firms during and outside the
crisis. As in Gorg and Spaliara (2013, 2014a), we use a complementary
log-log model (cloglog), a discrete time version of the Cox proportional
hazard model in order to model firm survival. We include dummies for
different export statuses (starter, continuous, exiter, switcher) as in
table 5 and also control for the financial position of the firm by
including measures of leverage and liquidity. Furthermore, we control
for size and age of the firm.
Looking at the estimation results in table 6, we find that export
starters, continuous exporters and export switchers are more likely to
survive than non-exporters (the reference category). By contrast, firms
that exit the export market are also more likely to die than
non-exporters. These coefficients are not statistically significantly
different during the crisis and non-crisis periods for all groups but
one. In particular, continuous exporters are even more likely to survive
than non-exporters during the financial crisis. (15) This might be due
to their good financial health and established reputation in the
exporting market. The crisis dummy on its own is statistically
significant, indicating that deteriorations in economic activity will
affect firms' prospects of survival negatively. Furthermore, we
find that financial factors play a role in firm survival; more liquid
firms and firms with lower leverage, respectively, are more likely to
survive. This result does not change when redefining the crisis dummy
for 2007-9.
6. Conclusion
Firms' ability to raise external finance has always been an
important issue in the corporate finance literature. The recent global
financial crisis has re-ignited interest in this link, since there is
evidence that banks interrupted their lines of credit and firms were
unable or had to incur substantial costs in order to finance their
operations. The present paper relies on a large panel of UK
manufacturing firms, the vast majority of which are unlisted, to explore
the importance of financial health for a number of firms'
decisions. We begin our enquiry by examining whether the entry of new
firms into exporting was affected by the financial crisis. We then
compare the performance of exporters in terms of employment and sales
growth, and survival, with that of non-exporters before and during the
crisis.
The analysis finds evidence that financial variables are important
in predicting export entry, especially in the midst of the global
financial crisis. More importantly, the level of a firm's debt is a
much stronger deterrent of exporting during the crisis than in the
period before the crisis. With respect to firm dynamics, we find that
starters and continuous exporters are more likely to perform well in and
out of the crisis than non-exporters.
There are a number of interesting policy implications arising from
our findings, which are of relevance to policymakers and firms'
managers seeking to understand the mechanism through which financial
health affects firms' performance. First, the results presented in
this paper suggest that maintaining healthy balance sheets would
substantially increase the probability of exporting and ultimately help
firms weather the negative effects of a financial crisis. Thus, in good
times firms should build up liquidity buffers which can be used during
recessions, in order to perform well throughout the cycle. Second, given
the apparent importance of a healthy balance sheet position, managers
should actively pursue the communication of managerial statements of
liquidity to both investors and lenders as a signal of their
company's financial health.
REFERENCES
Alfaro, L. and Chen, M. (2012), 'Surviving the global
financial crisis: foreign ownership and establishment performance',
American Economic Journal: Economic Policy, 4, pp. 30-55.
Amiti, M. and Weinstein, D. (201 I), 'Exports and financial
shocks', Quarterly Journal of Economics, 126, pp. 1841-77.
Askenazy, P., Caldera, A., Gaulier, G. and Irac, D. (2011),
'Financial constraints and foreign market entries or exits: firm
level evidence from France', Working Paper 328, Banque de France.
Baldwin, R. and Evenett, S. (2009), 'The collapse of global
trade, murky protectionism, and the crisis. Recommendations for the
G20', Working paper, Centre for Economic Policy Research.
Bell, V. and Young, G. (2010), 'Understanding the weakness of
bank lending', Quarterly Bulletin Q4, Bank of England.
Bellone, F., Musso, P., Nesta, L. and Schiavo, S. (2010),
'Financial constraints and firm export behaviour', The World
Economy, 33, pp. 347-73.
Bernanke, B., Gertler, M. and Gilchrist, S. (1996), 'The
financial accelerator and the flight to quality', Review of
Economics and Statistics, 78, pp. I -15.
Bernard, A., Jensen, B., Redding, S. and Schott, P. (2007),
'Firms in international trade', Journal of Economic
Perspectives, 21, pp. 105-30.
Bricongne, J., Fontagn, L., Gaulier, G., Taglioni, D. and Vicard,
V. (2012), 'Firms and the global crisis: French exports in the
turmoil', Journal of International Economics, 87, pp. 134-46.
Chodorow-Reich, G. (2012), 'The employment effects of credit
market disruptions: firm-level evidence from the 2008-09 financial
crisis', Mimeo, UC Berkeley.
Chor, D. and Manova, K. (2012), 'On the cliff and back? Credit
conditions and international trade during the global financial
crisis', Journal of International Economics, 87, pp. I 17-33.
Engel, D., Procherc, V. and Schmidt, C. (2013), 'Does firm
heterogeneity affect foreign market entry and exit symmetrically?
Empirical evidence for French firms 'Journal of Economic Behavior
and Organization, 18, pp. 381-97.
Fazzari, S., Hubbard, G. and Petersen, B. (1988), 'Financing
constraints and corporate investment', Brookings Papers on Economic
Activity, 2, pp. 141-95.
Gertler, M. and Gilchrist, S. (1994), 'Monetary policy,
business cycles, and the behavior of small manufacturing firms',
Quarterly Journal of Economics, 109, pp. 309-40.
Girma, S., Gorg, H. and Strobl, E. (2004), 'Exports,
international investment, and plant performance: evidence from a
nonparametric test', Economics Letters, 83, pp. 3 17-24.
Godart, O., Gorg, H. and Hanley, A. (2012), 'Surviving the
crisis: foreign multinationals vs domestic firms', The World
Economy, 35, pp. 1305-21.
Gorg, H. and Spaliara, M.-E. (2013), 'Export market exit,
financial pressure and the crisis', Working Paper 9599, CEPR.
--(2014a), 'Exporters in the financial crisis', Mimeo,
University of Glasgow.
--(2014b), 'Financial health, exports, and firm survival:
evidence from UK and French firms', Economica (forthcoming).
Greenaway, D., Guariglia, A. and Kneller, R. (2007),
'Financial factors and exporting', Journal of International
Economics, 73, pp. 377-95.
Hadlock, C. and Pierce, J. (2010), 'New evidence on measuring
financial constraints: moving beyond the KZ index', Review of
Financial Studies, 23, pp. 1909-40.
Ivashina, V. and Scharfstein, D. (2010), 'Bank lending during
the financial crisis of 2008', Journal of Financial Economics, 97,
pp. 319-38.
Iyer, R., Da-Rocha-Lopes, S., Peydr, J. and Schoar, A. (2014),
'Interbank liquidity crunch and the firm credit crunch: evidence
from the 2007-2009 crisis', Review of Financial Studies, 27, pp.
347-72.
Minetti, R. and Zhu, S. (201 I), 'Credit constraints and firm
export: microeconomic evidence from Italy', Journal of
International Economics, 83, pp. 109-25.
Mizen, P. and Tsoukas, S. (2012), 'The response of the
external finance premium in Asian corporate bond markets to financial
characteristics, financial constraints and two financial crises',
Journal of Banking and Finance, 36, pp. 3048-59.
Spaliara, M. (2009), 'Do financial factors affect the
capital-labour ratio? Evidence from UK firm-level data 'Journal of
Banking and Finance, 33, pp. 1932-47.
--(2011), 'Financial frictions and the K/L ratio in UK
manufacturing', Economics Letters, 112, pp. 23-25.
The Economist (2013), 'Innovative new lenders are easing the
credit crunch for British firms', article 8 June.
Tsoukas, S. and Spaliara, M.-E. (2014), ' Market implied
ratings and financing constraints: evidence from US firms 'Journal
of Business Finance and Accounting, 41, pp. 242-69.
Wagner, J. (2007), 'Exports and productivity: a survey of the
evidence from firm-level data', The World Economy, 30, pp. 60-82.
WTO (2012), World Trade Technical Report, World Trade Organization.
NOTES
(1) Evidence for Europe provided by Iyer et al. (2014), show that
banks decreased their credit supply to firms during the 2007-09 crisis.
The drop in credit supply was stronger for small firms which could not
compensate the reduction in loan supply via other sources of debt.
(2) For example, Chodorow-Reich (2012) finds that the withdrawal of
credit explains between 1/3 to 1/2 of the employment decline of small
and medium firms in the US in the year following the collapse of Lehman.
By contrast, the availability of credit supply had no effect on the
employment level of large firms.
(3) Exporting is reported as 'overseas turnover' and some
firms may be exporters, but may fail to report this.
(4) To ensure that our sample is representative we contrast it to
aggregate data for the UK manufacturing sector. We compare the growth of
profitability in our sample with those of the UK manufacturing sector,
as reported in the ONS database. Our sample is reasonably representative
of the broader aggregate. The series are highly correlated and exhibit
similar business cycle dynamics.
(5) In the UK, sections 382 and 465 of the Companies Act 2006
define an SME for the purpose of accounting requirements. According to
this, a small company is one that has a turnover of not more than 6.5
million [pounds sterling], a balance sheet total of not more than 3.26
million [pounds sterling] and not more than 50 employees. A medium-sized
company has a turnover of not more than 25.9 million [pounds sterling],
a balance sheet total of not more than 12.9 million [pounds sterling]
and not more than 250 employees.
(6) As an alternative measure of bank dependency, we have used the
ratio of short-term debt to total debt to distinguish between more and
less bank dependent firms. This results in a similar picture to that
shown in figure I.
(7) We distinguish exporting firms that continuously export
(continuous exporters) from those that start exporting their products
(export starters), that never export their products (continuous
non-exporters), those that fail to continue exporting and exit the
exporting market (export exiters), and those that enter and exit more
than once (export switchers).
(8) According to SEC Filings (Securities and Exchange Commission),
the main reason that firms drew down on the credit line was to enhance
their liquidity and financial flexibility during the credit crisis
(Ivashina and Scharfstein, 2010).
(9) Results are available upon request.
(10) These graphs are available in the working paper version Gorg
and Spaliara (2014a).
(11) We generate a dummy variable, SMALL,,, which is equal to I if
firm i's real assets are in the bottom 50 per cent of the
distribution of the real assets of all firms operating in the same
industry as firm i in year t, and equal to 0 otherwise. The dummy
[YOUNG.sub.it] is equal to I if age for firm i is in the bottom 50 per
cent of the distribution of the age of all firms operating in the same
industry as firm i in year t, and equal to 0 otherwise. As a robustness
check, we also use a 75 per cent cut-off point.
(12) According to Hadlock and Pierce (2010), firm age and size are
the two variables reported by firms themselves regarding the importance
of financing constraints.
(13) Firms having a high share of exports in total sales and whose
ratio is at the top 50 per cent (75 per cent) of the distribution, are
classified as high export-intensive.
(14) Results are available upon request.
(15) This is somewhat in contrast to a similar study for the
Republic of Ireland (Godart et al., 2012) which finds that exporting
firms are indeed more likely to die than non-exporting firms during the
crisis.
Holger Gorg * and Marina-Eliza Spaliara **
* Kiel Institute for the World Economy and
Christian-Albrechts-University of Kiel. ** University of Glasgow and
Kiel Institute for the World Economy. E-mail:
Marina.Spaliara@glasgow.ac.uk. We would like to thank Rebecca Riley and
two anonymous referees for helpful comments and suggestions on an
earlier draft of the paper.
Table 1. Summary statistics by exporting status before and during the
2008-9 crisis
Leverage Liquidity Leverage
crisis
(1) (2) (3)
Exporters 0.436 0.180 0.414
(0.74) (0.32) (0.52)
Continuous non-exporters 0.515 0.150 0.512
(16.89) (0.32) (5.15)
Starters exporters 0.423 0.164 0.411
(0.778) (0.323) (0.53)
Continuous exporters 0.410 0.209 0.359
(0.56) (0.30) (0.31)
Exiters exporters 0.493 0.164 0.423
(5.12) (0.33) (0.44)
Switchers exporters 0.417 0.176 0.413
(0.42) (0.33) (0.54)
Leverage Diff. Liquidity
non-crisis crisis
H) (5) (6)
Exporters 0.440 0.032 0.231
(0.77) (0.34)
Continuous non-exporters 0.516 0.983 0.179
(18.21) (0.33)
Starters exporters 0.425 0.266 0.215
(0.81) (0.34)
Continuous exporters 0.421 0.000 0.266
(0.60) (0.33)
Exiters exporters 0.499 0.259 0.238
(5.35) (0.36)
Switchers exporters 0.418 0.843 0.232
(0.40) (0.33)
Liquidity Diff.
non-crisis
(7) (8)
Exporters 0.169 0.000
(0.32)
Continuous non-exporters 0.165 0.000
(0.32)
Starters exporters 0.158 0.000
(0.32)
Continuous exporters 0.153 0.000
(0.32)
Exiters exporters 0.153 0.000
(0.32)
Switchers exporters 0.157 0.000
(0.32)
Notes: The table presents sample means. Standard deviations are
reported in parentheses. The p-values of a test of the equality of
means before and after the crisis are reported in columns 5 and 8.
Leverage is measured as the firm's short-term debt to assets ratio.
Liquidity is defined as the ratio of the firm's current assets less
current liabilities over total assets. Exporters are defined as those
firms that report a positive amount of exports throughout the sample
period. The time period is 2000-9.
Table 2. Surviving and failing by exporting status
Failed Surviving Diff.
firms firms
(1) (2) (3)
Starters exporters 0.186 0.294 0.000
(0.389) (0.45)
Continuous exporters 0.001 0.063 0.000
(0.02) (0.24)
Exiters exporters 0.211 0.125 0.000
(0.41) (0.33)
Switchers exporters 0.048 0.066 0.000
(0.21) (0.25)
Continuous non-exporters 0.602 0.517 0.000
(0.48) (0.49)
Notes: Fail is a dummy that equals 1 if a firm fails in year t, and
0 otherwise. The p-values of a test of equality are reported in
column 3. The percentages do not add exactly to 1.0 due to a very
small overlap in the construction of the export dummies.
Table 3. Probability of starting exporting during the crisis
Liquidity 0.221 ***
(4.28)
Leverage -0.068 *
(-1.68)
Liquidity * Crisis 0.025
(0.35)
Leverage * Crisis -0.058 *
(-1.87)
Size 0.192 ***
(18.78)
Age 0.000
(0.12)
Crisis -0.109 ***
(-3.18)
Observations 46,429
Notes: Estimates are obtained from a pooled Probit model. Standard
errors are corrected for clustering. The figures reported in
parentheses are t-statistics. * signifiant at 10 per cent; **
significant at 5 per cent; *** significant at I per cent. Time dummies
and industry dummies were included in the specification.
Table 4. Summary of graphical evidence
Covariates Analysis of series Graphical evidence
Log of sales Exporters/non-exporters Higher for exporters but
less so 2008-9
Exporters with different Lower for exiters and higher
status for continuous exporters
Old/young Higher for old firms but
less so 2008-9
Large/Small Higher for large firms but
less so 2008-9
Export Intensity Higher for high intensity
exporters but less so
2008-9
Log of Exporters/non-exporters Higher for exporters but
Employment less so 2008-9
Exporters with different Lower for exiters and higher
status for continuous exporters
Old/young and Higher for old firms but
less so 2008-9
Large/Small Higher for large firms but
less so 2008-9
Export Intensity Higher for high intensity
exporters but less so
2008-9
Table 5. Firm growth and exporting during the crisis
Lo? Log of Log of
employment sales
(1) (2)
Starters exporters 0.017 ** 0.031 ***
(2.15) (3.41)
Continuous exporters 0.085 *** 0.105 ***
(2.95) (8.21)
Exiters exporters 0.054 * 0.072 ***
(1.85) (7.23)
Switchers exporters 0.073 *** 0.089 ***
(2.62) (3.77)
Starters exporters *Crisis 0.008 0.015
(0.23) (0.71)
Continuous exporters *Crisis 0.014 0.019
(0.27) (0.61)
Exiters exporters *Crisis -0.031 -0.062 *
-0.57) (-1.90)
Switchers exporters *Crisis -0.007 -0.023
-0.11) (-0.67)
Crisis -0.170 *** 0.190 ***
(-5.85) (10.26)
Leverage -0.044 *** -0.027 ***
(-7.33) (-8.77)
Liquidity 0.011 0.001
(0.55) (0.08)
Size 0.756 *** 0.844 ***
(213.85) (397.25)
Age 0.001 0.001 ***
(0.24) (8.71)
Observations 38,276 37,294
Notes: All specifications were estimated using the OLS regressions.
The figures reported in parentheses are t-statistics. * significant
at 10 per cent; ** significant at 5 per cent; *** significant at 1
per cent. Time dummies and industry dummies were included in all
specifications.
Table 6. Hazard of failure by exporting status during the
crisis
Starters exporters -0.431 ***
(-10.90)
Continuous exporters -5.983 ***
(-15.15)
Exiters exporters 0.449 ***
(12.88)
Switchers exporters -0.182 **
(-2.95)
Starters exporters * Crisis 0.229
(1.20)
Continuous exporters * Crisis -0.895 ***
(-4.85)
Exiters exporters * Crisis 0.338
(0.97)
Switchers exporters * Crisis -0.101
(-1.15)
Crisis 0.765 ***
-2.58
Leverage 0.048 *
-1.269
Liquidity -1.018 ***
-2.25
Size -0.239 ***
-6.35
Age 0.000
(0.42)
Observations 46,429
Notes: Proportional hazard model results are reported. The dependent
variable is a dummy equal to I if the firm fails, and 0 otherwise.
Robust z-statistics are presented in parentheses, * significant at 10
per cent; ** significant at 5 per cent; *** significant at 1 per cent.
Time and industry dummies are included in all models.
