Spain: Drivers of Firm Productivity Growth1
Spain’s weak productivity performance has been linked to the dominance of many low productive small firms and inefficient allocation of resources. This paper identifies empirically the relative importance of the drivers for firm productivity and growth. The biggest gain can be expected from lowering regulatory barriers to competition and the cost of doing business, including at the regional level. Further improving the access to equity and credit financing, in particular for innovative start-up companies, and addressing potential disincentive effects of size-contingent rules, can also make important contributions to raising productivity growth. Finally, supporting innovation through increasing the efficiency of R&D incentives and enhancing the private R&D investment should generate positive spillovers, which are difficult to capture empirically, however.
1. In spite of recent improvements, a sizeable productivity gap remains between Spain and European peers. Labor productivity has been below that of Germany and France and the gap has widened since the 1990s, when Spanish productivity growth slowed signficiantly and even turned negative during the pre-crisis boom.2 During the global financial crisis, the gap between Spain and European peers narrowed somewhat, largely as a result of productivity gains in Spain in contrast to further productivity growth slowdown in European peers. In spite of these improvements, the productivity gap is still much higher today, compared to the 1970s through 1990s. Post-crisis total factor productivity (TFP) growth turned positive but remains below its long run average and a large part of this improvement is likely cyclical, related to massive labor shedding during the crisis. Still, at least in part, the recent improvements have also been linked to the exit of low-productivity firms during the crisis and impoved efficiency of resource allocation (Bank of Spain, 2015).
2. Spain’s weak productivity record has been linked to the dominance of many low productive small firms and inefficient allocation of resources. Spanish firms tend to be smaller, less productive and innovative; tend to grow at a slower pace, and are less export-oriented than European peers (Figure 2 and IMF, 2017). The productivity gap between small and large firms is also wider than in other European countries (IMF, 2015a). Significant within-sector heterogeneity in firm productivity points to inefficient resource allocation. Figure 2 shows that resource misallocation in Spain was among the highest in advanced European countries, though it declined somewhat in the post-crisis period, in line with previous empirical findings (2014 Bank of Spain Annual Report and Garcia-Santana, 2016).
Figure 1.The Productivity Challenge
Sources: RES ORBIS data, and IMF staff calculations.
Figure 2.Misallocation of Resources 1/
Sources: RES ORBIS data, and IMF staff calculations.
1/ See Hsieh and Klenow (2009), “Misallocation and Manufacturing TFP in China and India,” Quarterly Journal of Economics. The authors decompose the logarithm of sectoral TFP into the difference between the logarithms of the “clean” TFP, i.e. TFP that would exist in a sector without factor market distortions, and a measure of resource misallocation. Misallocation is proxied by the variance of the logarithm of the total factor revenue productivity of a firm in a specific sector, adjusted by the price elasticity of demand in the same sector. For illustration, imagine a two firm economy, where only one of the firms faces capital distortions, e.g. capital subsidies. Removing the distortion and reallocating the same amount of capital across all firms (so as to equalize their marginal products of capital) would increase the aggregate output. This would remove the firm-level distortion and also increase sectoral TFP, since the economy would produce more with the same inputs.
3. Against this background, this chapter assesses the importance of several policy and firm-specific factors for firm productivity and growth. Using firm-level data, the analysis investigates the following questions: (i) What are the main stylized facts of total factor productivity level and growth, key policy and firm-specific factors, particularly in recent post-crisis years? (ii) Why have productivity and productivity growth of Spanish companies been so low? What role was played by policy-related factors, such as regulations, size-related tax incentives, and innovation? What has been the impact of access to finance and firm-specific factors? and (iii) What is the relative importance of the factors and how can policies support growth?
4. This chapter is structured as follows. Section B summarizes key findings of the literature, and discusses data and the empirical strategy. Section C presents stylized facts of productivity and productivity growth and its determinants, focusing on the regulatory and business environment, size-related public policies, including CIT tax incentives for small firms, innovation activities, and the role of corporate balance sheets. Section D identifies the impact of these factors on firm growth and productivity. The last section offers policy considerations and conclusions.
B. Literature Review, Data, and Empirical Strategy
5. The literature has identified several key policy and firm-specific factors that affect firm productivity dynamics. Labor market duality, proxied by the share of temporary workers, and the use of sector level collective bargaining agreements, affected negatively firm TFP in Spain (Hospido and Moreno-Galbis, 2015). Stringent labor market regulations also tend to reduce efficiency of resource allocation (Hopenhayn and Rogerson, 1993; and Garicano et al., 2013 for France). In addition, weak productivity and resource misallocation has been linked to financial frictions from size-dependent borrowing constraints (Gopinath et al., 2015, Garcia-Santana, 2016), functioning of the product market and the quality of the resources available to the economy (Bank of Spain, 2016). Financial constraints related to weak firm balance sheets have been particularly important in the Euro Area in the aftermath of the global financial crisis (Aghion, 2014, IMF 2015a, IMF 2015b, IMF 2016c). Product market regulation has been found to be increasingly detrimental to productivity dynamics in sectors more exposed to regulation, through its impact on misallocation of resources (Andrews and Cingano, 2014). Size-related policies, including tax incentives for small firms, tend to create a “small business trap”, constraining firm and productivity growth (IMF, 2016a; Almunia and Lopez Rodriguez, 2014). Innovation is found to be positively linked to productivity growth (Aghion et al., 2014). Finally, empirical analysis shows that young and innovative firms contribute more to productivity growth than small firms (IMF, 2016a).
6. The paper uses data for about 500,000 Spanish companies for the 2000–13 period3. Firm-level data used in the analysis are from the ORBIS database of Bureau Van Dijk (BvD), compiled by the Research Department of the IMF (Gal and Hijzen, 2016). The database includes all companies reporting to the country business registries. It captures a significant fraction of all micro, small and medium-size enterprises (Annex Table A1). The coverage of this dataset is relatively large, with firms included in the sample accounting for about half of corporate gross value added and two thirds of total cost of employees. Nevertheless, micro firms are somewhat underrepresented compared to the data from the National Statistical Institute, reflecting, among other things, lighter reporting standards for those firms. ORBIS contains balance sheets, income statements, several productivity variables, location and sectoral classification over 2000-13 and the data exclude outliers. See the Annex for the variables description.
7. We study the association between various policy and firm-specific factors and firm productivity dynamics. Specifically, we regress several measures of firm performance—total factor productivity, productivity growth, and value added growth—on various policy and firm-specific factors, exploring both panel and cross-section data driven by data availability.
Where Yist measures TFP level, growth or value added growth of firm i operating in sector s at time t. The first explanatory variable (Exps* Regt) is an industry level index, proxying the impact of regulation on firms operating in different sectors. The second explanatory variable (Emtr_nti,s,t − Emtrr,s,t) measures the impact of size-related tax incentives, Xist is a vector of other proxies for firm-specific factors, such as firm innovation activity, access to finance, and firm-size. The year fixed effects, αt , directly control for macroeconomic fluctuations and all other factors that may affect productivity equally across firms. The estimations also include a set of dummies for five age related categories of firms αa to control for the differing effect of firm age on productivity, firm fixed effects, αi and an error term, εist, estimated as robust standard errors, clustered at the firm level. This equation is estimated on annual firm level data.
8. Product market regulation: The coefficient β captures the extent to which product market liberalization is associated with better firm outcomes in sectors highly exposed to stringent regulation. We proxy stringency of product market regulation using the OECD Product Market Regulation (PMR) index, which is based on de jure data on laws and regulations, abstracting from implementation issues that might impact effectiveness of regulation. The index varies in the (0,6) range, with higher values denoting more stringent regulation. The PMR index is interacted with sectors’ exposure to regulation, proxied by the U.S. firm turnover at the two-digit NACE level, under the assumption that the marginal impact of product market liberalization would be greater for firms operating in industries with naturally low barriers, compared to firms operating in industries with naturally high barriers (Andrews and others, 2015).4 A negative β coefficient on the interaction between the PMR index and the exposure indicator would imply that easing regulation would boost firm performance disproportionally more in sectors highly exposed to regulation.
9. Tax incentives: Size-related tax incentives are measured as the difference between effective marginal tax rates under the standard corporate income tax (CIT) rate and those under the targeted (lower) CIT rates for targeted (smaller) firms. Firm-specific forward-looking effective marginal tax rates, in turn, are simulated combining firm-level data with information from the tax code (Box 1). A negative γ coefficient on the difference between effective marginal tax rates under the standard CIT rate and those under the targeted (lower) CIT rates for smaller firms implies that lowering the differential between effective marginal tax rate under the standard CIT rate and that under the targeted (lower) CIT rate for smaller firms would boost the dependent variable (TFP level and growth and value added growth).5
Box 1.Measuring Size-Related CIT Tax Incentives1
CIT tax incentive estimates are based on effective marginal tax rates. This approach uses a forward-looking hypothetical marginal investment project to evaluate the impact of taxes on the firm cost of capital. Forward-looking effective tax rates measure the effective tax burden on a hypothetical investment project using information from the tax code and firm level variables, such as investment, financing, and repatriation decisions (Devereux and Griffith, 1999). The effective tax burden on a hypothetical investment depends on the statutory tax rate, the net present value of tax depreciation, and the tax treatment of debt and equity financing. For a marginal investment the expected after-tax rate of return is equal to the after-tax rate of return of an alternative investment. The pre-tax rate of return necessary to generate this after tax rate of return is called the cost of capital (p) (see Egger and Loretz, 2010). The effective marginal tax rate (EMTR) is then defined as the difference between the cost of capital and the after-tax rate of return of an alternative asset, relative to the cost of capital. Size-related tax incentive is defined in turn as the differential between the EMTR calculated using the standard CIT rate and EMTR calculated using the targeted (lower) CIT rates for SMEs.
Key Assumptions. Information on the standard and SME-specific CIT rates and threshold for eligibility for the tax incentive are based on the OECD database. For some of the parameters required for the calculation, firm-level data have been used, but where those are not available, assumptions based on ZEW (2012) have been used, following Egger et al. (2009). Country-specific depreciation rules are also taken from ZEW (2012). Key assumptions are: (i) real rate of return of 5 percent, annual inflation of 2 percent and a pre-tax real rate of return on capital of 20 percent; (ii) economic depreciation rates for four categories: machinery, buildings, intangibles, and land and the share of assets by these categories, resulting in tax saving on depreciation allowance; and (iii) firm-level data used to compute the share of debt financing.
10. Access to finance. The analysis uses debt-to-asset ratio as a proxy for the strength of firm balance sheets and access to finance.6 This proxy has been typically used in earlier empirical analysis. Given the excessive reliance on bank financing and very low availability of venture capital in Spain, such constraints are particularly important for R&D investment, leading in turn to lower productivity growth (Aghion, 2014). There is evidence for the importance of this channel for firm investment growth, efficiency of resource allocation and TFP level and growth in Spain (Hospido and Moreno-Galbis, 2015, and Moral Benito and others, 2016). Moreover, access to finance maybe much more of an issue for small companies with relatively smaller tangible assets, often used as collateral when obtaining bank credit. To check if access to finance matters more for small firms, the empirical analysis also includes access to finance proxy interacted with a dummy variable for SMEs.
11. Other factors.7 Innovation, proxied by the share of intangibles to total assets, is also included in the empirical analysis (following IMF, 2016c). Sustained innovation is a key driver of TFP growth and generates knowledge spillovers to other firms and sectors (IMF, 2016a). In addition, the analysis includes firm-specific factors, like firm size and age. Intuitively, smaller firms are in general less productive than the large ones, (Haltiwanger and others, 2011; IMF, 2016a), though recent evidence suggests that firm size is endogenous to firm productivity (Garcia-Santana and others, 2016). To this end, we have proxied firm size by lagged value added growth and found that lagged firm size was an important determinant of firm productivity and growth, with smaller firms being less productive compared to larger firms. We also found evidence that the same policy factors play critical importance for firm output growth.
C. Stylized Facts
Larger Spanish firms enjoy higher median productivity levels and lower productivity dispersion relative to smaller firms, in particularly micro firms. Yet, the share of small firms is very high and even increased slightly, following the global financial crisis. In 2013, micro and small firms (with less than 20 employees) comprised 90 and 95 percent of the total number of non-financial firms in Spain, respectively.
As expected, there are also sizeable TFP gaps across sectors, with relatively low productivity and large productivity differentials in market services, agriculture, and energy and the highest productivity of manufacturing.
Firm TFP has been declining well before the global financial crisis. While following the crisis, real TFP has stabilized and even started to recover among the larger firms, the declining trend is yet to be reversed among the micro firms.
Firm growth, proxied here by the real value added growth, has lost its dynamism for the larger firms particularly during the post-crisis period, while the real value added of micro firms even declined during the same period.
Figure 3.Spain: Trends in Firm TFP and Value Added
Sources: Orbis data and IMF staff calculations.
13. Regulation remains a burden for competition in product and service markets (Figure 4). As evident by the OECD index of product market regulation, in spite of recent improvements, the strictness of “de jure” regulation is still elevated compared to peers, as well as barriers to entrepreneurship, barriers to entry in the service sector, and relatively more cumbersome license and permit systems. This tends to hamper entrepreneurial activity, market entry and growth of small firms in Spain (Scarpetta and others, 2002, IMF, 2016b, Bank of Spain, 2016). In addition, the “de facto” regulation, factoring the effects of the “de facto” institutional environment could have even more important effects (Mora-Sanguinetti, 2016). There is also evidence of regulatory barriers and market fragmentation across regions (World Bank, 2015; Bank of Spain, 2016; European Commission, 2016). For example, the time to open an industrial SME varies greatly across the regions, with some regions in southern Spain taking twice the time to open an industrial SMEs compared to some of the northern regions.
Figure 4.Firm Size, Productivity and Regulation
Sources: ORBIS, and Subnational Doing Business, World Bank, 2015.
1/ Region names are abbreviated as follows: AD-Andalusia, AR-Aragon, AS-Asturias, CA-Ceuta, CH-Castile-La Mancha, CS-Castile-Leon, CT-Cantabria, CY-Catalonia, EX-Extremadura, GA-Galicia, MA-Madrid, ML-Melilla, OJ-La Rioja, RL-Balearic Islands, RU-Murcia, SC-Basque Community, VR-Navarre, VV-Valencian Community.
14. Size-related tax incentives vary across sectors, firm age and firm size (Figure 5). The effective marginal tax rate (EMTR) increases with firm size in our sample. Within SMEs, smaller firms get higher benefits. During 2010–14 the CIT rate varied between 20 and 30 percent, with the smallest firms (those with less than 25 employees and with turnover below €5 million) taxed at the lowest end of this range; larger SMEs were taxed at 25 percent for the first €300,000 of their profit and at 30 percent for profits exceeding this threshold, while large firms were taxed at the upper end of this range. However, this has changed with the 2015 tax reform that lowered the CIT rate to 25 percent for all firms and replaced the lower CIT rate for small firms with a 15 percent CIT rate for new firms. Given the variation in the composition and size of assets and the debt-to-asset ratio, there are also significant differences in the tax incentives by sectors as well, with firms in agricultural, service and energy sectors benefiting from relatively larger tax incentives, compared to other sectors. In terms of age, the current incentive structure does not favor young companies in Spain, as they have lower tax benefits, compared to older firms.
Figure 5.Spain: Size-Related Tax Incentives
Sources: ORBIS and IMF staff calculations. Note: EMTR = effective marginal tax rate.
15. There are also a number of rules and regulations that depend on the employment size. A number of rules and regulations exist that include certain requirements, once a firm reaches a particular threshold for firm employment, total assets, company turnover or a combination of those (Bank of Spain, 2015; European Commission, 2016). For example, these include certain audit requirements, accounting rules or labor regulations that apply to firms with more than 10, 30, and 50 employees. As a result, the firm density drops around several employment thresholds including at 50 workers (Figure 6). In addition, other potential obstacles include thresholds on the firm turnover (€450,000 and €6 million) for the application of the simplified VAT regime and the CIT collection of advance payments, though recent reforms have reduced the burden of some of these regulations (European Commission, 2016, Almunia and Rodriguez, 2014).
Figure 6.Size-Related Rules Firm Density by Number of Employees 1/
Sources: ORBIS data and IMF staff calculations.
1/ Firm density around the threshold of 50 employees.
16. Debt-to-asset ratios have been relatively high and increased for SMEs further during the crisis (Figure 7). Given the excessive reliance of Spanish corporate sector on bank financing, such constraints have been particularly strong during the crisis, affecting particularly the R&D investment (Aghion, 2014). Financing constraints, proxied by the firm debt-to-asset ratio, prevent firms from investing and growing that in turn result in inefficient resource allocation, thereby affecting productivity level and growth (Bank of Spain, 2016, Hospido and Moreno-Galbis, 2015).
Figure 7.Access to Credit and Other Financing
Sources: BIS, Debt Securities Statistics and Locational Banking Statistics; EC;OECD; ORBIS; INE;IMF, International Financial Statistics; and IMF staff calculations.
D. Determinants of Firm Productivity Performance: Empirical Results
17. We estimated the impact of various factors on TFP growth, level, and growth of value added, using several econometric specifications. Specifically, we estimated the model on panel data over 2000–13, using fixed effects regressions (Table A3).
18. Results indicate the role of several policy and firm-level factors for firm productivity growth (Figure 8):
Regulation. Regulatory entry barriers and administrative burden from licensing requirements and market fragmentation across regions by preventing creative destruction are found to be detrimental to productivity and productivity growth. This is even more in sectors more exposed to regulation. The findings are consistent with Bank of Spain (2016), European Commission (2016), and OECD (2015).
High debt-to-asset ratio, proxing credit constraints, is found to be negatively and significantly correlated with TFP level and growth. This effect is even stronger for the SMEs, as they tend to have weaker financial position compared to other firms. This is in line with previous studies suggesting that investment growth was relatively more constrained when firms face financing constraints, resulting from weaker balance sheets (IMF, 2016b Euro Area Policies, Article IV Report, Box 2). Investment constraints could prevent firms from growing and result in inefficient resource allocation, thereby affecting productivity level and growth (Bank of Spain, 2016). Such constraints might be particularly important for R&D investment, leading in turn to lower productivity growth (Aghion, 2014).
Figure 8.Estimation Results: Factors of Firm Productivity and Growth 1/
Sources: ORBIS data, OECD and IMF staff calculations.
1/ Cross-reference the tables with detailed regression results in the Annex.
Note: EMRT = effective marginal tax rate; PMR = product market regulation index.
Size-related tax incentives affected negatively and significantly TFP level, TFP growth, and growth in value added. Thus, tax incentives were on average more harmful than helpful for productivity level and growth as they create disincentives for firms to grow, resulting in “small business trap.”
Innovation. The results suggest that more innovative firms, as proxied by the share of intangibles to total assets were more productive and have grown faster. However, the impact is relatively small possibly due to the relatively low level of R&D investment in Spain compared to peers. The finding may also not fully account for positive knowledge spillovers, generated by innovation, affecting positively TFP level and growth. The effect of the innovation proxy is larger positive, but this is offset by a negative effect from the interaction between regulation and innovation, suggesting that stringent regulation could affect productivity growth negatively also through its negative impact on innovation (Table A3). Innovation is important, but it becomes less so in the presence of regulation, which explains why the overall effect of innovation is small.
Determinants of TFP growth
Sources: OECD, ORBIS data, and IMF staff calculations.
Firm size and age. While smaller firms were in general less productive than the large ones, regressions indicate that productivity growth tended to be negatively related with firm size and firm age, in line with existing literature (Haltiwanger and others, 2011; IMF, 2016a). Specifically, firm size was an important determinant of firm productivity and growth (proxied here by the lagged value added growth), with smaller firms less productive compared to larger firms. Larger firms could reap benefits from economies of scale, but were less dynamic and tended to grow at a relatively slower pace, compared to smaller firms.
19. The analysis suggests that policy factors have played an important role for firm productivity and growth. Specifically, policy factors, in particular those related to strictness of product and service market regulation, size-related tax incentives and finance constraints were negatively correlated with firm productivity level and growth, and firm growth, proxied by the growth in real value added. This suggests that reforms should continue to focus on fostering the competition in product and service markets and on further improving access to equity and credit financing, in particular for small and innovative firms. Furthermore, the elimination of the CIT size-related tax incentives with the recent tax reform should also help and further progress towards reducing other size-related rules and regulations would further stimulate firm growth and productivity. Finally, other reforms that aim at improving the quality of labor input, such as labor market and education reforms could boost firm productivity further.
20. This chapter uses firm-level data to examine policy and firm-specific factors that explain TFP level and dynamics of Spanish firms. In line with the literature, the analysis suggests that TFP level and growth was uneven across the Spanish firms. Specifically, the results show that firm size is the key determinant of productivity growth—while small firms are less productive compared to larger firms, large firms are less dynamic and have lower productivity and value -added growth. On average, younger firms tend to grow faster compared to older firms, while firms with higher innovation activity tend to growth faster. Firms that receive more size-related tax incentives witness lower TFP growth and firm growth. Importantly, the impact of such incentives on productivity level and growth is comparable to the effect of financial constraints and regulatory hurdles. Other size-related rules and regulations also seem to create disincentives for firms to grow, lowering firm productivity and growth. Market inefficiencies and lack of competition due to excessive strictness of regulatory requirements and practices (such as permits and standards) in particular at the regional and local level affects negatively barriers to entry and inhibit competition, in particular in sectors more exposed to regulation, which can hurt firm productivity and growth.
21. High productivity growth requires frontier innovations and efficient allocation of resources. This chapter examined in turn firm readiness to innovate and the efficiency of within sector allocation of resources. Both call for policies to address barriers to competition, disincentives for firm growth, ability to innovate, and further improvements in access to financing.
22. The analysis suggests that policies could help enhance firm TFP dynamics by:
Fostering competition in product and service markets by addressing the delays in the implementation of the Market Unity Law and lowering the regulatory barriers and the administrative burden faced by firms from the three government layers and by pressing ahead with the long delayed liberalization of professional services would enhance firm TFP dynamics.
Further reducing and eliminating size-related rules and regulations (in reporting, auditing, and labor-related regulation) that create small business trap and can hurt productivity and growth. Some of these disincentive effects have been reduced recently, in particular with the 2015 tax reform that equalized the CIT rate across firms of different sizes, to 25 percent and replaced lower CIT rates for small firms with a 15 percent CIT rate for new firms.
Further improving access to finance, in particular equity financing for small firms, would be critical to maintain robust investment growth, including sustained growth in R&D investment, therefore enhancing firms’ TFP growth.
Other policies include further enhancing firms’ innovation capacity through addressing the remaining weaknesses with public R&D spending efficiency and weak public-private sector cooperation. Last, but not least, addressing labor market duality through further labor market reforms and the quality of labor input through education reforms would also be important to sustain TFP growth and encourage innovation.
|Year||Average SME share||Sample size|
|Economic Sectors||Av. SME share||Sample size|
|Electricity, gas, steam and air condition||0.93||8,157|
|Water supply, sewerage, waste management||0.95||11,595|
|Wholesale and retail trade; repair||0.99||795,370|
|Transportation and storage||0.99||150,075|
|Accommodation and food service||0.99||172,459|
|Information and communication||0.98||66,680|
|Financial and insurance activities||0.98||31,861|
|Real estate activities||1.00||103,785|
|Professional, scientific and tech. services||0.99||230,614|
|Administrative and support services||0.97||97,266|
|TFP Growth||TFP level||Value Added Growth|
|Lagged total factor productivity||−0 84***||−0.84***||−0.84***||−0.29***||−0.29***||−0.29***|
|Tax incentive (EMTR)||−5 57***||−5.58***||−5.58***||−5.52***||−5.53***||−5.53***||−5.91***||−5.95***||−5.95***|
|Innovation (share of intangibles)||0||0||0.11***||0.00*||0.00*||0.11***||0.01||0.01||0.18***|
|Size (lagged value added)||−0.06***||−0.06***||−0.06***||0.06***||0.06***||0.06***||−0.58***||−0.59***||−0.59***|
|Age (2-5 years)||−0.01**||−0.01**||−0.01**||−0.03***||−0.03***||−0.03***||−0.08***||−0.08***||−0.08***|
|Age (5-10 years)||−0.01***||−0.01***||−0.01***||−0.05***||−0.05***||−0.05***||−0.08***||−0.08***||−0.08***|
|Age (10-15 years)||−0.02***||−0.02***||−0.02***||−0.06***||−0.06***||−0.06***||−0.08***||−0.09***||−0.08***|
|Age (15-20 years)||−0.01**||−0.01**||−0.01**||−0.05***||−0.05***||−0.05***||−0.09***||−0.09***||−0.09***|
|Age (Over 20 years)||−0.02**||−0.02**||−0.02**||−0.05***||−0.05***||−0.05***||−0.09***||−0.09***||−0.09***|
|Time dummie s||Yes||Yes||Yes||Yes||Yes||Yes||Yes||Yes||Yes|
|Number of observations||2,051,207||2,051,207||2,051,207||2,051,352||2,051,352||2,051,352||2,089,036||2,089,036||2,089,036|
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Prepared by Nina Budina (EUR). I would like to thank Alexander Hijzen, Peter Gal, and Romain Duval for sharing their cleaned firm-level database based on various vintages of Orbis.
Note that the size of the gaps could differ somewhat when using constant purchasing power parities (PPPs), which ignores the changes in relative prices over time (Mora-Sanguinetti and others, 2012).
See Table A1 and A2, containing information for the temporal, sectoral, and size structure of the.
Using the data for the U.S. firm turnover (a country with low regulation) would mitigate concerns regarding possible endogeneity of the exposure indicator to the level of regulation.
For a cross-country analysis and Benedek and others (forthcoming).
We define debt as the sum of short-term financial debt (loans) and long-term financial debt (long-term liabilities), as in ECB (2014).
Note that the analysis did not include a proxy for labor market distortions, because suitable proxy was not available. Despite this, the impact of any other factors beyond those included explicitly in the analysis is implicitly accounted for by the time and firm fixed effects.
Real total factor productivity (in logarithms) is calculated as a Solow-type residual, based on firm-level production function (Cobb-Douglas) and individual firm inputs.