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Prepared by Nina Budina, Sergi Lanau, and Petia Topalova (EUR). We thank Vizhdan Boranova and David Velazquez-Romero for excellent research assistance. This is a cross-country Selected Issues paper and will also serve as background material for the upcoming Executive Board Meeting on Spain 2015 Article IV Consultation.
The sample of firms for which 2014 financial statements were available was too small to conduct a systematic analysis. Where possible, the findings are complemented by a discussion of the corporate sector data available in the 2014 national accounts.
In 2012, more than 99.9 percent of businesses employed fewer than 50 people in Italy and in Spain. These businesses accounted for 70 percent of value added and 54 percent of overall employment in Italy (ISTAT, 2014). In Spain, they comprise slightly less than ½ of value added and about 60 percent of total employment (SME Performance review database, 2014).
An important caveat is that about half of the firms in the sample report their financials (e.g., debt, assets, etc.) due to simplified filing requirements for SMEs (Orbis, 2014).
Jones and Karasulu (2006), for example, found that stress testing applied to the balance sheets of Korean corporations in advance of the Asian crisis of the late 1990s would have shown the degree of vulnerabilities present in the country.
This estimate will present an upper bound since ICR do not capture all the resources companies may have to meet their obligations and to smooth over the idiosyncratic shocks to profits they may experience.
Kalemli-Özcan, Laeven and Moreno (2015) examine the role of debt overhang, leverage, and banking sector weakness in investment using a more detailed version of the Orbis database for all European economies.
More specifically, the downside from this approach is that (i) our analysis does not reflect the churn that might have occurred in response to the downturn, a potentially important margin of adjustment, and (ii) there might be differences in the time trends of the indicators we study relative to the available macro data due to survivors’ bias introduced by the sample selection. Namely, the decline in profitability or interest coverage ratios might be more pronounced within our sample, as firms that had successfully weathered the crisis and the protracted downturn were likely a stronger subset of the universe of firms in Italy and Spain—hence, their profitability and liquidity were likely higher prior to the crisis. That said, by the end of the sample period, the crisis had likely taken a heavy toll on these firms relative to the new entrants in the corporate sector, exacerbating the fall in measured profitability. Only firm census data could accurately capture the time trends in the corporate sector.
There are significant gaps in the coverage of number of employees for Italian firms in Orbis, hence we use firm assets to classify firms into micro, small, medium, and large. However, given this difference in the definitions, some caution is required when comparing directly levels and, to a smaller degree, dynamics of variables by firm size in the two countries. Classifying Spanish firms by asset size does not alter significantly the findings but results in an almost-empty group of large firms.
The broad sectors considered here include manufacturing, construction, utilities (electricity, gas, water supply and sewage), wholesale and retail trade, market services (transport and storage, accommodation, professional and technical, and real estate, entertainment and other services), and basic services (administrative support, education, health).
We define leverage as the sum of short term financial debt (Loans) and long term financial debt (long term loans and other noncurrent liabilities), divided by total assets. Note that this definition of debt excludes provisions, trade credits and other short term liabilities (such as pensions, deferred taxes, accounts receivables in advance) that are part of firms’ total debt. The patterns described above are similar if one uses a more restrictive definition of financial debt to include only long term and short-term loans as in ECB (2014).
Alternative measures of leverage, namely the ratio of debt to debt plus equity, suggest that among firms that had financial debt, leverage was the highest among the smallest companies, and the lowest among the large companies, in line with analysis by the Bank of Italy of a larger sample of firms with substantially more detailed financial data.
Using an alternative measure of earnings, EBIT yields qualitatively similar findings of the overall decline in ICR, and patterns across companies of different sizes and in different industries.
It is important to note the sample of surviving firm likely overstates the decline in ICR and the rise of the share of vulnerable firms over time relative to what actually occurred in the overall corporate sector. Firms that survived through the severe economic downturn were likely a stronger subset of the universe of firms and hence they had a higher ICR at the onset of the crisis.
A threshold of two was used in the 2013 joint IMF-Bank of Italy FSAP. The report notes that an ICR below two is broadly consistent with B ratings or lower by rating agencies, suggestive of about 20 percent probability of default over a 5-year horizon.
For this exercise, in both the Spanish and Italian sample of firms, we exclude firms with zero or negative reported debt in 2013, as well as firms with debt in the top 1 percentile of the distribution.
Note that these estimates are slightly different from debt-at-risk estimates of the Bank of Italy and Bank of Spain. In Italy, debt-at-risk is about 2 percentage points lower than Bank of Italy estimates, while in Spain it is about 5 percentage points higher than Bank of Spain estimates which, as mentioned, also point to improvements more recently. This reflects the smaller sample size, the less precise measurement of bank debt, and differences in data cleaning methodologies.
A large share of firms in both Spain and Italy report negative profits in 2013. This results in little change in the share of vulnerable firms in response to a positive shock modeled as a percent change in profits. To allow for the possibility of firms operating at a loss to swing into positive territory, we examine the consequence of a shock to operating revenue, holding expenses constant. The shock is calibrated to approximate a 10 percent increase in EBITDA for the average firm. As expected, such a shock leads to a more sizable reduction in the share of debt at risk in both countries.
Firm-level data suggest a much deeper decline in investment in 2010 than is discernible in the macro data. We use two different measures of investment. Gross investment is defined as the change in total fixed assets between t and t-1 plus depreciation and amortization over total fixed assets at t-1. Net investment is defined as the change in total tangible fixed assets over the total tangible fixed assets in the previous year.
We follow Kalemi-Ozcan and others (2015) and use the inverse of debt overhang (i.e., EBITDA over debt, rather than the debt-to-income ratio) since earnings may be zero or negative.
Data limitations prevent us from examining the role of firm-specific uncertainty shocks, which have been shown to significantly dampen investment in the case of Italy (see Bontempi, Golinelli, and Parigi, 2010).
A sector’s dependence on external finance is from Tong and Wei (2011), who build on the methodology first developed by Rajan and Zingales (1998). Specifically, financial dependence of a sector is constructed as the difference of the capital expenditures of the sector and its cash flow as a share of its total capital expenditures in the 1990–2006 period in the US.
The measure of credit supply reflects the response of banks to the question on whether they have tightened or relaxed lending standards in the previous three months.
Of course, the change in lending standards may reflect not only the strength of bank’s balance sheets and its willingness to lend but also the perceived riskiness of borrowers.