Trade shocks and credit reallocation: Lessons from Italy
There are winners and losers from trade liberalisation. The overall effect on welfare and economic activity, especially in the short term, depends crucially on the ease by which factors of production can move across firms, sectors, and regions, according to the changing patterns of comparative advantage. Historically, research shows that this reallocation of factors after trade shocks to be slow due to frictions on labour mobility across regions and sectors (Topalova 2010, Autor et al. 2013, Kovak 2013, Dix-Carneiro 2014, Autor et al. 2014, Bloom et al. 2015, Acemoglu et al. 2016, Pierce and Schott 2016, Hakobyan and McLaren 2016, Dix-Carneiro and Kovak 2017, Utar 2018).
In Federico et al. (2020) we contribute to this debate by empirically identifying a financial friction that hinders the reallocation of credit across firms and sectors in the aftermath of a trade shock: the endogenous funding constraint of banks whose loan portfolios are affected by the liberalisation.
We reached this conclusion after analysing the activities of banks and firms in Italy upon China’s accession to the World Trade Organization (WTO) at the end of 2001. Following the approach in Autor et al. (2013), we identify the sectors directly hit by import competition from China. Not surprisingly, firms in those affected sectors were more likely to fail on their bank credit. Non-performing loans (NPLs) increased by 40% in the six years after China’s entry to the WTO, relative to firms not directly hit by the trade shock.
This increase in NPLs did not affect all Italian banks to the same extent. Banks tend to specialise in lending to certain sectors, in line with evidence for other countries (Paravisini et al. 2020). Those banks that specialised in sectors hit by import competition from China suffered a disproportionate increase in NPLs after China’s accession to the WTO, and they did not offset the losses with additional equity or external credit lines. They therefore reduced their lending capacity as a result. To get a sense of the magnitude of these results, compare two hypothetical banks, lending to the same firm, that differ by ten percentage points in their share of loans towards import-competing sectors. The more exposed bank would cut credit by 5% relative to the other bank, during the period 2002-2007.
The reduction in credit supply by affected banks reached firms subject to competition from China, (which we should expect to shrink). However, it also affected highly productive and exporting firms in sectors where Italy has a comparative advantage, as well as (more generally) firms non-hit by competition from China (see Figure 1 for the aggregate trends in credit). These are firms that should presumably expand and absorb more resources after the liberalisation.
Figure 1 Credit by exposed and non-exposed banks
Note: Credit by exposed and non-exposed banks to firms in sectors directly hit, and non-directly hit by import competition from China.
We compared the real outcomes of firms in Italy depending on the exposure of their related bank to the trade shock. We found that the contraction in credit supply by affected banks led to significant losses in terms of employment, investments, and output (with relevant macroeconomic consequences), as affected banks accounted for a significant fraction of firms’ credit, even among firms not subject to import competition from China. Comparing firms in the top 75 percentile relative to those in the bottom 25 percentile (in terms of their share of credit in exposed banks), we find a reduction of between 1% and 1.3% in employment, and between 1.3% and 2% in investment (depending on the sector of activity). In other words, we find that the lending channel deepened the negative impact of the trade shock among firms directly competing with imports from China and transmitted the shock to the presumptive ‘winners’ of trade liberalisation.
We further explore the geographical dimension of the trade shock and find that the reduction in credit supply by exposed banks was general across regions in Italy. Banks operate nationally and transmitted the shock geographically to otherwise non-affected areas. So, while the labour market effects of a trade shock tend to be localised, the credit effects are not.
Banks play a crucial role in the allocation of factors in the economy. Their role is even more relevant in the aftermath of a trade liberalisation episode (when the changing pattern of comparative advantages calls for an efficient reallocation of resources across firms, sectors and regions). Our findings show that this role may be hindered when banks’ balance sheets are endogenously affected by the liberalisation shock. This lending channel ends up constraining the growth of firms, sectors, and regions not affected by the trade shock, which are presumably the supposed winners of the liberalisation episode itself. More generally, our work emphasizes the role of the credit channel in deepening, and propagating, sectoral or regional demand shocks to otherwise unaffected areas of the economy.
Acemoglu, D, D Autor, D Dorn, G H Hanson and B Price (2016), “Import competition and the great US employment sag of the 2000s”, Journal of Labor Economics 34(S1): 141–198.
Autor, D H, D Dorn and G H Hanson (2013), “The china syndrome: Local labor market effects of import competition in the united states”, American Economic Review 103(6): 2121–2168.
Autor, D H, D Dorn, G H Hanson and J Song (2014), “Trade adjustment: Worker-level evidence”, The Quarterly Journal of Economics 129(4): 1799–1860.
Bloom, N, M Draca and J Van Reenen (2015), “Trade Induced Technical Change? The Impact of Chinese Imports on Innovation, IT and Productivity”, Review of Economic Studies Volume 83(1): 87–117.
Dix-Carneiro, R (2014), “Trade liberalization and labor market dynamics”, Econometrica 82(3): 825–885.
Dix-Carneiro, R and B K Kovak (2017), “Trade liberalization and regional dynamics”, American Economic Review 107(10): 2908–2946.