Abstract
Do financial crises have an impact on trade flows via a shock to corporate risk or to bank risk? Focusing on Italy’s exports during a period characterized by both the global financial crisis and by the sovereign debt crisis, we exploit the prediction of standard trade models according to which financial shocks should be magnified by the time needed to ship a good to the importer’s country and by sector-level financial vulnerability. We also use bank-pair data on Italian banks’ assets and liabilities vis-à-vis their foreign bank counterparts in a specific country to construct proxies for the availability of trade finance in a given market. We find evidence of a negative impact of financial shocks on exports, especially to more distant countries and in more financially vulnerable sectors. The main channels seem to be related to an increase in corporate risk (reflecting shocks to bank finance and to buyer-supplier trade credit), while the ‘contagion effect’ of shocks stemming from bank risk seems to be much less significant.
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Notes
The views expressed in this paper are those of the authors and do not necessarily reflect those of the Bank of Italy. The authors are grateful to two anonymous referees, Rym Ayadi, Guglielmo Barone, Silvia Fabiani, Alberto Felettigh, Sara Formai, Roberto Tedeschi, and participants at the Banking Research Network Workshop at the Bank of Italy (September 2016), at the World Finance Conference at Cagliari University (July 2017), at the Seminar held at the Department of Economics and Business at the Florence University (November 2017), at the Workshop on territorial economies held at the Bank of Italy (December 2017), at a Seminar held at the University of Turin (April 2018) and at the NETEF2018 Workshop held at IMT Lucca (September 2018) for their useful comments.
For example, a sudden freeze in the interbank market may reduce the availability of funding for banks that are therefore forced to reduce their lending to their borrowers.
There are significant differences in the time-to-ship between Italy and its trading partners: as an example, it takes about two days to ship a good by sea from Genoa to Barcelona and about a month to ship a good from Genoa to Shanghai. Additional time may be needed after reaching the foreign country’s port for customs clearance, inspection procedures, handling at the port and domestic transport until delivery to the importer.
While the model in Berman et al. (2013) assumes that exports are settled on an open account basis, this assumption is not strictly necessary to derive similar conclusions when financial conditions become tighter not only in the source country but also in the destination country. For instance, tighter financial conditions due to a global crisis will have an analogous effect on exports (i.e. varying with time-to-ship) even when trade is settled on a cash in advance basis rather than on open account. The implications of the third most common payment method for trade transactions (i.e. letters of credit or other forms of bank-intermediated transactions) is instead discussed below in this Section.
Distance increases the sensitivity of exports to financial shocks as the exporter faces a longer wait between shipping the good and collecting the payment once the importer has received the good. An additional channel might arise if distance is positively correlated with the average risk in the destination countries: this might apply to the case of Italy’s exports, as the country is located close to several advanced European economies, which should be characterized by a lower average riskiness than many emerging or developing economies.
Schmidt-Eisenlohr (2013) studies the optimal choice between letters of credit and the alternative forms of payment (open account, cash in advance). The equilibrium contract is determined by financial market characteristics and contracting environments in both the source and the destination country.
The evidence is fairly mixed: on the one hand, various surveys point to a lower supply and higher costs of trade finance during the crisis; on the other hand, the letter-of-credit intensity of trade increased during the financial crisis, as shown by Niepmann and Schmidt-Eisenlohr (2017b), thus suggesting that trade finance might have potentially attenuated the tensions for the financing of trade transactions.
Data for 2008Q4 are proxied by December 2008 data, given that no data are available for the earlier months.
Our measures of bank linkages, based on assets, liabilities and guarantees among correspondent banks in the interbank markets, are the unique we can adequately build. Alternative measures, based on the duration of interbank relationships (Affinito and Piazza 2018), are not available for our purpose, due to data limitations (specifically, the lack of detailed information before 2008, which would be needed to compute duration measures over a sufficiently long time span). Furthermore, these measures are less feasible in the context of the interbank market, where by definition interbank positions have very short durations (e.g. overnight) and a higher turnover (even within the same banking group).
An alternative case refers to the specular case of Italian importers. An exogenous financial crisis in Italy, which raises the probability of default of the Italian importer, is expected to lower aggregate imports, in particular from countries with a longer time-to-ship and in more financially vulnerable sectors. Since we focus on the export-side, we analyze this second dimension in the vein to run some robustness checks.
As our dependent variable is the log of exports, our regressions exclude country-sector-time pairs with zero flows. The incidence of zero flows is quite low for the export regressions (which include about 284 thousand observations, compared to a maximum of about 316 thousand observations). While other approaches, such as Poisson pseudo-maximum likelihood, may be considered to take into account the issue of zero flows, they may not necessarily be appropriate or easily converge, given the extensive set of fixed effects.
It corresponds to the distance between the most populated cities in each country pair. The results are robust to various alternative measures of distance, such as the distance between capital cities or a population-weighted distance.
The selection of the crisis periods is supported by a survey-based indicator published by Istat: a measure of the financial constraints on exports, as reported by a sample of manufacturing companies, shows indeed a clear peak around the end of 2008 and starts rising again towards the summer of 2011. Its subsequent decrease is observed during 2013; we prefer nonetheless to restrict the second crisis period until 2012Q2 in order to capture the most acute phase of the sovereign debt crisis only.
By taking into account industry-level differences in financial vulnerability, our specification differs therefore from Berman et al. (2013), which looks at the effect of the interaction between financial crisis and distance on aggregate trade flows between country pairs (i.e. pooling together all sectors). Our approach can be therefore seen as complementary to Berman et al. (2013).
For the import regressions, which are discussed in Sect. 6.4, we define the variable as the ratio of import loans and guarantees on sales. We use sales as a denominator because our firm-level data do not include any information on imports.
We therefore replicate the regressions using two alternative measures: accounts payable and net borrowing position in trade credit (accounts payable minus accounts receivable). The results on accounts payable are very similar to those on accounts receivable, although the interaction variable is slightly below the conventional significance threshold; the results using the net borrowing position in trade are also not significant.
Measures of trade finance intensity are computed using data for the year 2006.
By descriptive evidence on Italian banking sector, we know that small firms are those with more difficulties on loans’ payments, generating a higher share of NPLs in bank balance sheets.
We will report additional findings using imports as the dependent variable in Sect. 6.4.
Given that our sample includes 100 countries, 88 sectors, and 36 time periods, a typical regression includes more than 15,000 dummies.
When we split the sample between countries with distance from Italy above the median and those with distance below the median, we find that the crisis dummy is negative and significant in both subsamples (column (1) of Tables A2 and A3 of the Online Appendix, respectively). The interaction between distance and the crisis dummy (column (2)) is instead only negative and significant for countries above median distance from Italy, i.e. exactly those countries where distance is expected to weigh more intensely on export flows.
The estimated magnitude is larger if distance is included in the interaction term as a dummy (above or below the median) rather than as a continuous variable. It would also be considerably larger of course if we considered two sectors with the lowest and highest financial vulnerability, rather than sectors at the two ends of the interquartile range.
The inclusion of this new variable does not affect the estimated coefficients of the triple interaction between financial crisis dummy, distance and financial vulnerability, whose magnitude and statistical significance are unchanged.
This result might be explained taking into account either a composition effect (where goods that disproportionately fall during financial crises—such as investment goods—are mainly imported from less distant economies, such as Germany and the other European countries) or the regional nature of the sovereign debt crisis, which hit only selected euro area countries.
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Del Prete, S., Federico, S. Do links between banks matter for bilateral trade? Evidence from financial crises. Rev World Econ 156, 859–885 (2020). https://doi.org/10.1007/s10290-020-00383-1
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DOI: https://doi.org/10.1007/s10290-020-00383-1