DOCUMENT DE TREBALL XREAP2009-11 Small firms, growth and financial constraints Agustí Segarra (GRIT) Mercedes Teruel (GRIT) Small firms, growth and financial constraints Agustí Segarra Mercedes Teruel Abstract This paper analyses the impact of different sources of finance on the growth of firms. Using panel data from Spanish manufacturing firms for the period 2000-2006, we investigate the effects of internal and external finances on firm growth. In particular, we examine three dimensions of these financial sources: a) the performance of the firms’ capital structure in accordance with firm size; b) the effects of internal and external financial sources on growth performance; c) the combined effect of equity, external debt and cash flow on firm growth. We find that low-growth firms are sensitive to cash flow and short-term bank debt, while high-growth firms are more sensitive to long-term debt. Furthermore, equity capital seems to reduce barriers to external finance. Our main conclusion is that during the start-up phase, firms are unable to increase their financial leverage and so their capital structure fails to promote correct investment strategies. However, as their equity capital increases, alternative financial mechanisms, in particular long-term debt, become available, which have a positive impact on firm growth. JEL classification: L25, R12 Key words: firm growth, small firms () agusti.segarra@urv.cat, mercedes.teruel@urv.cat Industry and Territory Research Group Department of Economics (Rovira i Virgili University) Av. Universitat, 1; 43204 – Reus Tel. + 34 977 759 854 Fax + 34 977 300 661 We are grateful to Verònica Gombau Bertomeu for her research support. 1 1. Introduction Empirical research examining firm growth emphasises the importance of sectoral, territorial and individual factors, but attention to financial factors in this literature has been somewhat scarce. Three reasons would seem to account for this neglect. First, the field of industrial organization has traditionally ignored corporate finance and vice versa. Second, an increasing number of studies have chosen to analyse firm growth as a theoretical production function and, as such, have paid scarce attention regarding to the strategic relationships that might exist between financial decisions and output market decisions. And, third, scholars have only very recently acquired access to panel data that can provide information about production factors and financial flows at the firm level. The combined effect of these three trends has served to limit the analysis of the effects of financial factors on firm’s growth. Here, we seek to examine the effect of internal and external finance on firm’s growth. More specifically, we distinguish between firm sizes so as to provide empirical evidence of the differential impact of these financial channels. During a firm’s infancy the availability of finance tends to be extremely limited. In this start-up phase, a firm’s ability to capture financial resources is usually restricted to equity capital and bank debt, while its capacity for leverage is also limited. As the firm establishes itself, however, it gains access to resources from its own productive activity - commercial borrowings, internal cash flow - and sources of external finance. The firm’s ability to accede to these latter varies with macroeconomic environment and with microeconomic factors related to the territorial environment and the firm’s individual characteristics. A firm’s ability to obtain external finance is a key factor in its development, growth and survival. According with Aghion et al. (2007), access to external finance improves market selection by allowing small firms to be more competitive. Additionally, financial accessibility significantly facilitates the post-entry growth of firms. In addition, Winker (1999) and Savignac (2008), among others, report that credit constraints have a negative impact on innovation expenditures and overall investment; and Carpenter and Petersen (2002), in a study of 1,600 small US firms, find that asset growth is constrained by the availability of internal finance. Finally, Musso and Schiavo (2008), in a study of almost 15,000 French manufacturing firms, conclude that access to external financial resources has a positive impact on firm growth. In this paper we are interested in analysing the effects of different sources of finance on sales growth at the firm level, with particular attention to small firms, given the increasing recognition that they are gaining in the promotion of regional development (Acs, 1999). Although it is the large firms that tend to capture a larger share of employment and economic activity, small firms can act as catalysts for the development of local industrial 2 sectors. In fact, in recent decades the share of small firms in the economy has increased due to growing global competition, greater uncertainty, and technological advances (Audretsch et al. 2002). However, there is a general consensus that such firms suffer from a serie of financial constraints. In recent years, the larger financial constraints with which small firms have to contend have been the focus of many studies. In general, a well-developed finance system will seek to facilitate a firm’s access to productivityenhancing investments. However, even in well-developed financial systems, such as the Spanish one, small firms may be constrained and be more markedly sensitive to the possibilities of accessing external finance. The aim of this paper is to improve our understanding of the way in which access to financial sources can affect the capacity of small firms to increase their sales. We use an extensive database for Spanish manufacturing firms that includes balance sheet data from the Mercantile Register between the years 2000 and 2006. In order to provide quantitative evidence regarding the performance of a firm’s growth determinants we use quantile regressions to analyse manufacturing industries. Quantile regressions capture the different marginal effects of a firm’s growth determinants on firm growth (Koenker and Basset, 1978) and offer a different approach to the analysis of firm performance. Our main findings can be summarised as follows. First, we show that firms with low growth rates are more sensitive to the access of internal sources of finance. Second, our results suggest that access to external sources is crucial in order to increase these growth rates. Third, equity capital may be a signal for external borrowers and may reduce information asymmetries. As the weight of the ratio of equity to assets increases, the firm’s ability to accede to bank debt increases; in other words, financial leverage increases when share prices are high. Four, cash flow and short-term bank debt are of great importance when firms are small and their growth rates are low. Here, the Spanish case is particularly interesting as it has a market structure characterised by firms that are smaller than their European counterparts and which have a smaller capacity to grow. As such, the study sheds some light on the role played by various sources of finance on the growth of Spanish manufacturing firms. The paper is structured as follows. In section 2 we give an overview of the determinants of financial development and firm growth. Section 3 presents our data. Section 4 discusses our econometric model. Our results are presented in section 5, while the final section draws together our main conclusions. 2. Finance and firm growth Empirical studies emphasize the crucial role played by financial development on economic growth. However, access to broad, comprehensive 3 databases at the firm-level has given rise to contributions within the field that emphasize the fact that the asymmetries in access to finance are dependent on firm size. This section analyses the theoretical arguments that underpin the relationship between finance and growth at the macro- and microeconomic levels. 2.1. Financial development and economic growth The literature examining the impact of finance on economic growth is extensive. In line with the approach proposed by Schumpeter, most studies report a positive effect of financial services on growth. The Schumpeterian argument holds that services provided by the financial sector, via the appropriate allocation of capital and risk in the economy, play a positive role in economic growth. Empirical evidence at the aggregate level has been provided from an early date by various authors. For example, Goldsmith (1969) found a temporal link between economic growth and financial development for 35 countries during the period 1860-1963. Today there exists a growing body of literature analysing this link between growth and the financial sector, but doubts remain as to the direction of this causation. So, it is unclear as to whether finances are an important catalyst of economic growth, or rather the causation runs in the opposite direction as proposed by Robinson (1952). She and other scholars have argued that the relationship is in fact the inverse of Say’s law. In the words of Robinson (1952) “where enterprise leads, finance follows”. It might be that, in line with the argument forwarded by Lucas (1988), the role of finances has been overemphasized, but recent evidence suggests that financial services are critical for economic growth. Financial markets and institutions facilitate the allocation of financial resources, manage the risk and facilitate investment in innovative projects. At the firm level, finances exert a major influence on the development of firms and innovative activities. Thus, Rajan and Zingales (1988b) argue that the financial system has two primary goals: to place risks where they are best borne, and to channel resources to their most productive uses. Proper empirical work in assessing the relationship between financial development and the real economy began with King and Levine (1993a,b,c). Those authors reported cross-country evidence suggesting that financial development affects economic growth by fostering productivity improvements (Love, 2003). However, few studies have subsequently analysed the impact of financial development on productivity at the firm level. A number of authors (Brito and Mello, 1995; Beck et al., 2006) have emphasised the importance of being able to access external finance. First, access to finance plays a key role in the general business environment, potentially serving as a constraint on both firm entry and performance. Further, it is also clearly important to foster a competitive business environment that permits the entry of new and innovative entrepreneurs resulting in the Schumpeterian process of “creative destruction” rather than 4 maintaining a large stock of SMEs with a low turnover (Beck et al., 2006). Second, taking into account joint financial and production decisions helps to provide a better understanding of the key drivers of entry-exit decisions, as well as the firms’ post-entry performance (Brito and Mello, 1995). Several models have defined, from a theoretical perspective, the mechanism by which the financial system affects productivity. Here, three principal arguments have been forwarded. The leading argument is that better access to finance increases a firm’s investment in productivity-enhancing projects. Such projects are more easily undertaken when there are liquid financial markets given that investors can sell their shares if they need to recover their savings before the project matures (Levine, 1991; Bencivenga et al., 1995). Furthermore, financial markets may help by evaluating prospective entrepreneurs, mobilizing savings to finance the most promising investment projects and diversifying the risks associated with these innovative activities (King and Levine, 1993c). Additionally, perfect credit markets increase the propensity to engage in long-term productivity-enhancing investment by decreasing the level of liquidity risk involved in those investments (see Aghion et al., 2007). As a consequence, the presence of financial constraints results in lower productivity. At the macro level, the empirical evidence focuses on the relationship between finance development and productivity. Recent evidence (Levine et al., 2000; Beck et al., 2000) is drawn from panel techniques that support the existence of a causal relationship between financial development and economic growth (i.e., growth in real GDP per capita, and productivity growth). For example, King and Levine (1993b,c) find that financial development has a positive effect on productivity. Beck et al. (2000) show that financial intermediaries help economic growth through more efficient resource allocation rather than through investments or savings. Adopting a macroeconomic approach, Akerloff (1970), Jaffe and Russell (1976), Stiglitz and Weiss (1981), Greenwald and Stiglitz (1990), Petersen and Rajan (1994) and Brito and Mello (1995) show how information asymmetries result in financial constraints. Finally, Ayyari et al. (2007) use a large panel of firms in 47 developing countries to show that external finance increases innovation. To sum up, the empirical evidence shows that an improvement in the financial system and its further development will increase economic growth at the country level. However, the mechanism by which finance affects economic growth is explained by the firms’ capacity to increase their productivity. Spain makes an interesting case since it has a well-developed financial system but encounters difficulties when seeking to enhance its productivity. 2.2. Small firms and financial constraints 5 In financial markets, information asymmetries represent a critical barrier in gaining access to finance1. However, the financial structure is not independent of firm size. In fact, firm size is a key variable in the analysis of financial restrictions (Beck et al., 2005). Thus, in general, large and small firms do not have equal opportunities in accessing external sources of finance. So while the presence of both large and small firms is important for market competition and, hence, for economic growth, in order to ensure industrial dynamics, firms must have access to financial markets. However, problems of agency costs, information asymmetries and fixed transaction costs result in capital market imperfections. The firms that are typically most severely affected by these imperfections are small firms, as their internal information can be rather opaque or, at least, not as public as it is in the case of their larger counterparts. Small firms seeking small loans face higher transaction costs and higher risk premiums since they are more opaque and have less collateral to offer (Beck and Demirguc-Kunt, 2006). Similar results have been found by Beck et al. (2005, 2006) and Schiffer and Weder (2001). Schiffer and Weder (2001) confirm that small firms have to confront higher barriers to their growth. Likewise, Beck et al. (2005, 2006) confirm that size, age and foreignownership are good predictors of the existence of barriers to growth. Oliveira and Fortunato (2006) find that small firms face greater financial constraints and that these have a negative impact on their growth. Audretsch and Elston (2002, 2006) also show that medium-sized firms face greater financial constraints than large firms. Birks and Ennew (1996) report that young firms are more financially constrained. Müller and Zimmermann (2008) also observe that SMEs face additional disadvantages. First, small firms cannot exploit scale economies in the same way as large firms can. Second, they face more financial constraints. These authors claim that since young companies have not accumulated sufficient cash flow and are unable to rely on bank financing, they have to depend on the original equity investment of their owners2. In general, analyses of the effects of financial constraints on firm performance have focused on distinct aspects: firm investment (Fazari et al., 1988; Lang et al., 1996; Cleary, 1999, 2006; Alti, 2003; Almeida and Campello, 2007; ), firm growth (Carpenter and Petersen, 2002; Beck et al., 2005; Audretsch and Elson, 2006; Fagiolo and Luzzi, 2006; Oliveira and Fortunato, 2006; Hutchinson and Xavier, 2006; Coad, 2008), firm innovation In order to solve some of these puzzles, corporate finance theory has extended the analysis to three strands of the literature: the free cash flow theory (agency costs), the trade-off theory (tax) and the pecking order theory (information asymmetries). However, we are not interested here in examining these theories. 2 In line with Cabral and Mata (2003), the disadvantages cause the firm size distribution (FSD) to be right skewed. 1 6 (Himmelberg and Petersen, 1994; Hyytinen and Toivanen, 2005; Savignac, 2008; Mohnen et al., 2008) and firm size distribution (Angelini and Generale, 20083; Cabral and Mata, 2003). In general, these studies demonstrate that small firms are more severely affected than their larger counterparts by financial constraints. At the micro level, recent empirical evidence has been presented. Using panel data on French manufacturing firms, Musso and Schiavo (2008) propose a new approach for identifying and measuring the degree of financial constraints faced by firms and they use it to investigate the effect of these constraints on firm survival and development. These authors found that (1) financial constraints significantly increase the probability of exiting the market, (2) access to external financial resources has a positive effect on the growth of firms in terms of sales, capital stock and employment, (3) financial constraints are positively related to productivity growth in the short-run. We interpret this last result as a sign that firms suffering constraints need to cut costs in order to generate the resources they cannot raise on the financial markets. When using a dataset for a panel of Bulgarian firms to study the empirical relationship between access to external finance and productivity, Gatti and Love (2008) find that access to credit has a significant positive impact on firm productivity in Bulgaria. In the case of Italy, Nucci et al. (2004) report evidence pointing to the causal effect of financial structure on a firm’s propensity to innovate and on its productivity. Furthermore, these authors show that the relationship between leverage and productivity is non-linear, being dependent on some firm-specific characteristics such as the share of short-run bank debt and the lower liquidity in relation to total assets. However, there is little evidence regarding the relationship between firm size, growth and financial sources at the firm level. Here, we assume that the mechanism that improves the technical change is provided by the access to internal and external financial sources. 3. Data and summary statistics The data for this study comprise an exhaustive sample of Spanish manufacturing firms including many annual variables expressed individually between 2000 and 2006. Our data are provided by the SABI (Sistema de Análisis de Balances Ibéricos) database which compiles information from the Mercantile Register. In this paper our data were gathered for a specific set of manufacturing industries, namely all two-digit industrial groups in the NACE classification (manufacturing industries Recently, Angelini and Generale (2008) have found that among OECD countries, the FSD of non-constrained firms virtually overlaps that of the entire sample, suggesting that the overall impact of financial constraints on the FSD is modest. The difference is more pronounced in a sample of firms from non-OECD countries. Thus, they conclude that financial constraints cannot be considered the main determinant of the FSD evolution in developed economies. 3 7 comprising 15 to 36 sectors). The SABI database has certain advantages when compared to other Spanish databases. First, it offers exhaustive data at the firm level and, second, it is a database in which there is information on nearly the whole firm population. The initial sample comprised 104,706 manufacturing firms and 453,707 observations. We applied a depuration process and the empirical work only considered the active firms, while those that were failing (either because of bankruptcy or because they were being absorbed) during the period 20002006 were not selected. After applying these filters, our sample was reduced to 98,572 firms. In the second step, we eliminated firms that presented disproportionate growth rates, which reduced the sample to 97,046 firms. Finally, since firms with few employees are usually hereditary societies without any economic activity, it is convenient to restrict the sample to firms with three or more workers. Thus, the eventual sample was made up of 59,420 firms and 391,228 yearly observations. This data set included annual information on firm performance, capital structure, and firm size. The panel is unbalanced in the sense that firms can enter the sample after the year 2000. Table 1 Summary statistics Year 2006 Workers 59420 23.60 99.63 60.73 5761.01 4 5 10 21 43 Firm age 59420 14.36 10.38 1.85 9.61 3 7 12 19 27 Equity / assets 59420 10.40 0.27 65.15 7823.05 0.0059 0.0148 0.0446 0.1234 0.2589 Cash flow / assets 59410 3.97 1.29 -112.34 15560.21 -0.0116 0.0279 0.0624 0.1077 0.1649 Short-term debt /assets 59407 58.05 2.21 129.65 20570.74 0.2034 0.3308 0.5103 0.7100 0.8869 Long-term debt/assets 56545 18.69 0.96 154.56 27002.24 0.0000 0.0125 0.1048 0.2741 0.4736 Obs. Mean Standard deviation Skewness Kurtosis Perc. 10 Perc. 25 Perc. 50 Perc. 75 Perc. 90 Note: authors’ own based on SABI database. Table 1 reports descriptive statistics for firm size, firm age and financial structure at the end of the year 2006. In order to control for the volume of the firm, we use financial variables scaled by total assets. On average, the surviving firms in our sample employ 23.60 workers and have been operating for 14.38 years. On average, firms are highly leveraged: 58.05% of the financial sources in their total assets are short-term debt. Long-term debt also plays an important role being recorded at 18.69% of total assets. Therefore, its seems that firms have more difficulties in obtaining a higher ratio of internal resources such as cash flow and equity in order to finance their projects. Furthermore, in general, the variables are highly skewed to 8 the right. The exception is the ratio of cash flow, which presents a right tail. Finally, the kurtosis indicates that the distribution is highly peaked on all the financial variables. However, the financial sources differ depending on firm age and size. In order to finance their projects (long-term assets, technological and innovative activities), firms turn to internal sources (equity and their other own resources, cash flow) and external debt. Access to external financial sources depends not only on the financial system but also on the firm’s individual characteristics. The firm’s ability to accede to financial sources varies in accordance with firm size and firm age. Small firms usually face greater difficulties in obtaining long-term bank debt and have limited equity capital. Small firms depend basically on internal cash-flow and commercial debt. Conversely, large firms access more easily long-term bank debt and engage in transactions with a larger number of banks. These differences are more marked among younger firms. For young firms (i.e., those operating for fewer than six years), the contribution made by equity capital is low as is access to long-term bank debt, while their access to short-term bank debt and commercial debt as a proportion of their overall liability is of great importance. Table 2 shows the evolution in the corporate capital structure in our sample of Spanish manufacturing firms in the year 2006. During infancy, a firm’s financial sources are restricted to the owner’s contributions (equity capital) and those provided by financial and commercial borrowings. In our sample, for firms operating for fewer than six years, equity capital represents just 6.9% of their total liabilities, while commercial borrowings account for up to 71.1%. As the firm matures, its ability to accede to and diversify its financial sources increases. Among older firms, capital equity, long-term bank debt and cash flow acquire a more important role. For firms operating for more than 50 years, their equity capital is equivalent to 27.3%; their short-term bank debt is equal to 36.5%, and their long-term bank debt is equal to 11.2% of total liability. Furthermore, internal cash flow increases with a firm’s age, in particular among those firms older than fifty years. Additionally, capital structure also varies in accordance with firm size. Small firms accede more easily to financial sources related to their current economic activity. As a consequence, for those firms with fewer than ten workers, their internal cash flow and commercial borrowings are their two main financial sources. On average, for small firms, 61.69% of their external resources are obtained from commercial borrowings, while only 8.23% is long-term bank debt. Table 2 Sources of financial funds by age and size Year 2006 9 Total (62,259 firms) Equity capital 1,202.10 15.92% 432.25 6.90% 664.86 10.26% 897.07 13.75% 1,594.78 23.76% 4,679.77 30.59% 13,117.50 27.46% 161.98 11.29% 875.37 19.97% 6,509.23 31.34% 45,620.18 29.05% 0-5 years (13,346 firms) 6-10 years (16,153 firms) 11-19 years (24,585 firms) 20-29 years (11,749 firms) 30-50 years (4,293 firms) More than 50 years (697 firms) 3-9 workers (30,167 firms) 10-49 workers (26,969 firms) 50-249 workers (4,562 firms) 250 or more workers (561 firms) Short term Long term bank debt bank debt 1,622.38 578.17 21.48% 7.66% By age 960.4 414.22 15.32% 6.61% 1,202.80 567.66 18.55% 8.76% 1,265.55 423.11 19.40% 6.49% 1,736.67 553.62 25.88% 8.25% 4,776.90 1,400.69 31.23% 9.16% 17,450.53 5,389.79 36.52% 11.28% By size 269.77 118.10 18.80% 8.23% 1,112.53 388.18 25.37% 8.85% 8,016.51 2,424.85 38.60% 11.68% 65,107.33 22,412.21 41.45% 14.27% Commercial borrowings 4,148.97 54.94% 4461.86 71.18% 4,047.67 62.44% 3,936.89 60.36% 2,826.35 42.11% 4,439.86 29.02% 11,820.16 24.74% 885.25 61.69% 2,008.41 45.81% 3,818.41 18.39% 23,926.84 15.23% Cash Flow 248.00 Total liability 7,551.62 79.49 162.93 211.55 292.76 847.92 2,685.30 6,268.73 6,482.99 6,522.62 6,711.42 15,297.22 47,777.98 885.25 164.93 1,290.61 10,508.03 1,435.10 4,384.49 20,769.00 157,066.56 Note: Mean in thousands of euros; weight as percentage of total liability. Note: Rajan and Zingales (1995) define external finance as a fraction of total finance. In other words, it is the ratio of net external finance over the sum of cash-flow from economic activity and net external financing. * Capital Equity also includes a firm’s other own resources. * Short-term bank debt is the liquid liability; long-term bank debt is the fixed liability * External/total financing = (Short-term bank debt + long-term bank debt + Commercial borrowings) / (Capital equity + Other own resources + Short-term bank debt + long-term bank debt + Commercial borrowings); * Total liability = Capital equity + Other own resources + Short-term bank debt + long-term bank debt + Commercial borrowings Note: authors’ own based on SABI database. Conversely, as firm size increases, equity capital and bank debt acquire greater importance. In this sense, banks base their lending decisions on several considerations, including their exposure to bad risks and the likelihood that the value of their claims can be reduced by specific borrower actions. These concerns are especially relevant for firm growth loans since the risk of failure is greater among small and young firms. According to Myers (1977), banks may prefer lending on a short-term contract in order to gain control over the firm and its investment decisions, while long-term debt is more suited for firms that invest in projects that do not provide an immediate pay-off. 4. Theoretical framework 10 This section presents the theoretical model for our empirical estimations. Our model relaxes some of the neoclassical conditions: constant economies of scale, competitive markets and exogenous technical progress. Here, the representative firm “i” in year “t” depends on the labour, capital and intermediate materials and a measure of productivity that incorporates the product changes not explained by the previous factors. Given a continuous production function, changes in output are expressed in terms of, dyi,t = dai,t + 1dni,t + 2dki,t + 3dmi,t + ui,t [1] where dyi,t, dni,t, dki,t, dmi,t and dai,t represent log growth rates in terms of sales, employment, capital stock, intermediate assets and technical change. As is usual, the technical change is neutral (in the sense of Hicks), and  are the elasticities of the output with reference to the productive factors. If equation 1 presents constant economies of scale and market competitiveness, the production function is homogenous of degree one with respect to labour and capital, where dai,t is Solow’s residual (1957) or the growth of total factor productivity (TFP). One of the main problems of this production function is that elasticities are non-observable, but under the previous assumptions, the output elasticity of productive factors may be measured by the contribution of the factorial rents to sales. In our empirical research we are interested in analysing the relationship between growth rates and financial sources. In order to introduce the financial effects we incorporate the impact of internal and external financial sources on firm productivity. In other words, dait =  + i Xi + vi,t where X is the firm’s set of financial sources. Introducing these parameters in 1 we obtain an equation that includes economies of scale and the effect of financial sources on technical change, dyi,t =  + 1dni,t + 2dki,t + 3dmi,t + i Xi,t + vi,t + i,t [2] where i represents the output elasticity of the different financial sources. Thus, our contribution is to analyse the direct effect of financial sources on production growth at the firm level. Econometric methodology Here, we design a model to capture the direct impact of financial sources on a firm’s production. The ability to gain access to financial sources may have an impact on the firm’s capacity to bring about technical change. As has been pointed out in the literature, greater financial access may facilitate investment in projects or innovations that can increase a firm’s productivity. Thus, we focus our analysis on the relationship between the changes in a set 11 of different inputs and the change in output by estimating a direct model that can capture the increase in investment. We are especially interested in observing the evolution in financial elasticity across the entire conditional distribution of production. We estimate the following linear regression model, dyi,t =  + 1 dni,t + 2 dki,t +3 dmi,t + 4 Agei,t + 5 Equityi,t-1 + ….+ 6CFi,t-1 + 6 LTdebti,t-1 + 7 STdebti,t-1 + i [3] where for each individual firm ‘i’, y is its production measured in terms of sales. The independent variables are as follows: n is the labour, k is the capital measured as fixed assets, m is the intermediate materials, and a is the technical measure. Both dependent and independent variables are calculated as log growth between period “t” and period “t-1”. Given our assumption that part of the technical change is attributable to better access to financial sources, we include a set of financial variables: Equity is the value of equity divided by assets, CF is the value of cash flow divided by assets, LTdebt is the ratio of long-term debt divided by assets, STdebt is the ratio of short-term debt divided by assets, and LnAge is the logarithmic firm age measured as the difference between the current age and the year of creation. In order to capture the temporal displacement between financial flows on investment and production, we consider lagged financial variables in all our regressions. The empirical literature measuring the presence of financial constraints is extremely broad and there is no consensus as to the identity of these variables. For example, some authors apply the ratio of cash flow to assets (Alti, 2003; Cleary, 1999; Fazzari et al., 1988; Almeida and Campello, 2004; Hutchinson and Xavier, 2006; Gilchrist and Himmelbert, 1995; Lang et al., 1996); the ratio of cash flow to sales (Fagiolo and Luzzi, 2006); the ratio of debt to assets (Petersen and Rajan, 2004); and the ratio of debt to profits (Coad, 2007). To the best of our knowledge, very few studies analyse the impact of different financial sources. Consequently, our analysis seeks to contribute to the empirical evidence regarding the linkages generated between financial sources. It is our claim that financial resources are complementary and as such act as a strategic tool in the firm’s production decision. In order to capture the different effects that financial sources might have on firms with low- and high-growth rates, we estimate Equation (1) using quantile regressions. The initial quantile regression method was proposed for application by Koenker and Bassett (1978) as an alternative to OLS when errors are not normally distributed. The central idea in quantile regression is to minimize the sum of absolute residuals by giving different weights to the quantiles being investigated. It is a powerful tool that, given a set of explanatory variables, can characterize the entire distribution of a dependent variable in greater detail than OLS methods (see the survey in Koenker and Hallock, 2001). Quantile regression is useful in the study of 12 firm productivity as the influence of a covariate may differ markedly between individuals with high, medium or low productivity levels. Thus, changes in a firm’s financial sources may have a very different impact on the increase in its production depending on whether it belongs to a high, medium or low profit groups. Thus, quantile regressions reveal asymmetries in the data that cannot be detected by simple OLS estimations Quantile regression was considered preferable to usual regression methods for several reasons. First, the standard least-squares assumption of normally distributed errors does not hold for our data, because the firms’ growth rates follow a Laplace distribution and do not fulfil the principle of normality. Second, while conventional regressions focus on the average firm, quantile regression can describe the complete conditional distribution of the dependent variable. And third, quantile regression is more efficient at treating outliers and heavy-tailed distributions. In our case, the quantile regression procedure allows us to estimate a whole set of numbers (the conditional quantiles) which give a more complete picture of the underlying relationship between sources of finance and sales growth. In addition, we include sector dummies and time dummies in order to control for specific industrial characteristics and different time periods that might serve as an incentive for an increase in production. On the one hand, industrial dummies control for those firms that experience a greater increment in production because of increased demand or the fact that they form part of growth industries. On the other hand, time dummies control for growth in production that is attributable to general economic growth. Table 3. Description of variables Variable Description dy Log difference of sales. Log difference of workers. Log difference of capital. Log difference of materials. Ratio of equity over assets (in the previous period). Ratio of cash flow over assets (in the previous period). Ratio of log-term bank debt over assets (in the previous period). Ratio of short-term bank debt over assets (in the previous period) Log firm age during the previous year (in the previous period). Sector dummies identifying sectors at two-digit level. Temporal dummies. Production factors dn dk dm Financial variables Equity CF LTdebt STdebt Age Other variables Sector dummies Time dummies The explanatory variables are divided into two groups (Table 3). The first group comprises the production factors employed by the firm during the year. The second group presents four variables related to the firm’s financial sources: equity, cash flow, short-term bank debt and long-term 13 bank debt. Finally, we add the important characteristic of the firm’s age and the sector and time dummies. We should stress the fact that all the financial variables are reported as a proportion of the firm’s total assets. Equity capital and internal cash-flow constitute the firm’s internal financial sources, while short- and long-term bank debt are the loans and credits it is granted by the banking sector. Finally, we include an age variable to measure the effect a firm’s life cycle can have on its capital structure and the evolution of its financial sources. 5. Empirical results The empirical results are presented below in two steps. First, Table 4 presents five conditional regression quantile results for θ = 0.10, 0.25, 0.50 (hence the median), 0.75 and 0.90. Second, Table 5 offers the marginal effect on firm growth for five conditional regression quantiles depending on firm size. In order to facilitate the analysis of the effects of financial sources according to firm size, we classify firms in three groups: small firms, those employing between three and nine workers; medium-sized firms, those with between ten and 249 workers; and large firms, those with 250 or more employees. Our initial analysis of the whole sample (Table 4) shows that equity has a negative impact on firm growth, but not significant in the lowest and highest quantiles, while variables such as cash flow and short-term debt have a positive impact. We should stress that the impact of both variables falls as we consider firms with higher growth rates. Greater access to longterm debt also has a significant and positive impact on firm growth, although it is not significant among those firms that grow at a lower rate (quantile 0.1). Furthermore, we should highlight the fact that in the case of those firms that present the highest growth rates, the impact of access to long-term debt is greatest. A firm’s age also presents the expected outcome since it has a positive impact among the less productive firms, while its impact is negative among the more productive. Thus, we find a negative relationship between a firm’s age and growth in sales. In the case of the productive factors, the impact was as expected significant and positive. However, we should stress that these effects differ from one quantile to another. In the case of growth in number of workers and capital, we observe a higher impact among firms with the highest growth rates. Meanwhile, the growth in expenditure on materials has an inverted U-shaped impact on growth in sales. When we analyse the three groups according to firm size, interesting results emerge. Small firms are more sensitive to cash flow and short-term bank debt. The elasticity of both financial sources is high, especially, among those firms that register moderate growth of sales. As we move across the quantile distribution, the elasticity of sales growth with respect to cash flow 14 and short-term bank debt falls. Equity capital follows identical patterns to those of cash flow and short-term bank debt, but the impact on a firm’s growth is more moderate. By contrast, long-term bank debt presents an inverse evolution. Firms that present expanding sales growth are more sensitive to long-term bank debt than firms that register more moderate rates of growth. Table 4. Quantile regression for the whole database. Productive Factors dni,t dki,t Quantile 0.1 Quantile 0.25 Quantile 0.5 Quantile 0.75 Quantile 0.9 dmi,t Financial sources 0.1157 (0.0027)* 0.0384 (0.0014)* 0.4456 (0.0016)* -0.0002 (0.0004) 0.0288 (0.0006)* -0.0003 (0.0004) 0.0363 (0.0011)* 0.0128 (0.0006)* -0.0546 (0.0037)* Yes Yes 0.4008 0.1019 (0.0012)* 0.0310 (0.0006)* 0.4990 (0.0007)* 0.0002 (0.0002) 0.0216 (0.0003)* 0.0011 (0.0002)* 0.0244 (0.0006)* -0.0004 (0.0004) 0.0435 (0.0020)* Yes Yes 0.4268 0.1097 (0.0007)* 0.0317 (0.0004)* 0.5254 (0.0004)* -0.0005 (0.0001)* 0.0172 (0.0002)* 0.0021 (0.0001)* 0.0170 (0.0004)* -0.0110 (0.0003)* 0.1070 (0.0014)* Yes Yes 0.4475 201143 0.1322 (0.0013)* 0.0401 (0.0007)* 0.5106 (0.0008)* -0.0010 (0.0002)* 0.0164 (0.0004)* 0.0028 (0.0002)* 0.0126 (0.0007)* -0.0264 (0.0004)* 0.1959 (0.0023)* Yes Yes 0.4494 0.1697 (0.0031)* 0.0566 (0.0015)* 0.4672 (0.0020)* -0.0007 (0.0005) 0.0151 (0.0008)* 0.0042 (0.0005)* 0.0108 (0.0013)* -0.0501 (0.0008)* 0.3414 (0.0044)* Yes Yes 0.4416 Equityi,t-1 CFi,t-1 LTdebti,t-1 STdebti,t-1 Agei,t-1 Constantt Sector dummies Temporal dummies R2 N Note: The significance levels of the parameters are computed using bootstrapped standard errors (100 replications). Quantile regression coefficients can be interpreted as the marginal change in y at the θth conditional quantile due to a marginal change in a particular regressor, ΔQθ (yi|xi) / Δx. *, **, *** significant at 1%, 5% and 10%. Our empirical results, therefore, reveal marked differences between their internal and external sources of finance and between their short- and longterm bank debt. In fact, there would appear to be a complementary effect between internal and external financial sources on sales growth. The impact of internal finances in relation to total assets is of relevance when firms present low sales growth, but the parameter decreases in importance as firms grow. The short-term bank debt parameter behaves in a similar manner to that of internal finance cash flow. However, long-term bank debt differs from cash flow and short-term bank debt. The long-term bank debt presents an increasing coefficient parameter that highlights the direct relation between sales growth rates and previous access to long-term external finances. 15 When we compare the evolution in the financial coefficients of small and large firms, interesting results emerge (Table 5). For small firms’ growth is more sensitive to sources of finance and their parameters are more sensitive than they are to those of large firms. In line with Clementi and Hopenhayn’s (2006) model, the sensitivity of investment and growth to cash flow decreases with firm age and size. For large firms, the capital structure is characterised by a larger share of equity capital and long-term bank debt and a lower percentage of commercial debt. Large firms enjoy a more diversified capital structure which is more neutral with respect to their investment strategy and their growth performance. How can we, therefore, interpret these results? What contribution can we make to the debate concerning the financial constraints placed on young small firms? The descriptive data included in Table 2 show that small firms, and, in particular, young, small firms, are underinvested and have limited access to external sources of finance. Among small firms, and again especially among young, small firms, commercial debt constitutes an important source of finance. The Spanish evidence presented here is in line with a growing body of empirical literature presented in the debate concerning the existence of financial restrictions. Fazzari et al. (1988) were the first to introduce the concept of financial restrictions. According to Fazzari and co-authors, “small and medium-sized firms are less likely to have access to impersonal centralized debt markets. [...] during periods of tight credit, small and medium-sized borrowers are often denied loans in favour of better-quality borrowers.” (Fazzari et al., 1988). For these authors, a firm’s investment is directly related to changes in cash flow and its sensitivity reveals the presence of financial restrictions. These authors initiated a debate which is far from over. In this sense, Kaplan and Zingales (1997, 2000) develop a theoretical model which demonstrates that the sensitivity of cash flow to investment cannot be interpreted as the existence of financial restrictions. Here, we consider the possibility that financial restrictions emerge not only through the relationship between growth and cash flow but also as an effect of other financial sources. In fact, the cost of external and internal sources of finance can affect the firm’s financial structure. When a firm, and more specifically a small firm, experiences increasing difficulties in gaining access to external financial sources, its ability to finance its projects is conditioned by its capacity to obtain internal cash flow and commercial borrowings. The key point that we wish to highlight here is that financial decisions taken by a firm will affect its growth and, ultimately, its chances of survival. 16 Table 5. Quantile regression for the whole database. Productive Factors Q0.1 0.1220 (0.0045)* 0.0399 (0.0024)* 0.4345 (0.0029)* 0.0023 (0.0008)* 0.0255 (0.0011)* 0.0001 (0.0008) 0.0331 (0.0019)* 0.0030 (0.0013)** -0.0621 (0.0070)* Q 0.25 Small firms Q0.5 Q 0.75 0.0936 (0.0012)* 0.0300 (0.0006)* 0.5037 (0.0006)* 0.0001 (0.0003) 0.0177 (0.0004)* 0.0032 (0.0003)* 0.0155 (0.0007)* -0.0159 (0.0005)* 0.1204 (0.0025)* 0.1050 (0.0019)* 0.0350 (0.0010)* 0.4876 (0.0012)* -0.0018 (0.0005)* 0.0185 (0.0007)* 0.0038 (0.0005)* 0.0122 (0.0011)* -0.0314 (0.0008)* 0.2198 (0.0040)* Q 0.9 0.1375 (0.0049)* 0.0445 (0.0026)* 0.4381 (0.0037)* -0.0046 (0.0010)* 0.0191 (0.0016)* 0.0048 (0.0011)* 0.0121 (0.0024)* -0.0566 (0.0018)* 0.3684 (0.0085)* Q0.1 0.1057 (0.0034)* 0.0362 (0.0017)* 0.4518 (0.0020)* -0.00002 (0.0004) 0.0291 (0.0007)* 0.0002 (0.0004) 0.0384 (0.0013)* 0.0093 (0.0008)* -0.0050 (0.0043)* Medium-sized firms Q 0.25 Q0.5 Q 0.75 0.1048 (0.0016)* 0.0310 (0.0008)* 0.5134 (0.0008)* 0.0002 (0.0002) 0.0212 (0.0004)* 0.0009 (0.0002)* 0.0270 (0.0007)* -0.0007 (0.0004) 0.0563 (0.0024)* 0.1273 (0.0010)* 0.0327 (0.0005)* 0.5426 (0.0005)* -0.0005 (0.0002)* 0.0170 (0.0016)* 0.0016 (0.0002)* 0.0185 (0.0005)* -0.0084 (0.0003)* 0.0992 (0.0000)* 0.1654 (0.0015)* 0.0426 (0.0007)* 0.5285 (0.0008)* -0.0008 (0.0002)* 0.0153 (0.0004)* 0.0020 (0.0002)* 0.0131 (0.0007)* -0.0198 (0.0004)* 0.1652 (0.0025)* Q 0.9 0.2149 (0.0040)* 0.0657 (0.0019)* 0.4857 (0.0025)* 0.0004 (0.0005) 0.0124 (0.0010)* 0.0027 (0.0005)* 0.0077 (0.0016)* -0.0382 (0.0010)* 0.2754 (0.0053)* Q0.1 0.1104 (0.0309)* 0.0096 (0.0141) 0.6672 (0.0202)* 0.0008 (0.0020) 0.0239 (0.0052)* 0.0003 (0.0019) 0.0152 (0.0070)* 0.0063 (0.0032)** 0.0197 (0.0301) Q 0.25 0.1241 (0.0093)* 0.0119 (0.0046)* 0.6977 (0.0055)* 0.00002 (0.0009) 0.0147 (0.0018)* 0.0008 (0.0007) 0.0135 (0.0030)* 0.0016 (0.0014) 0.0177 (0.0119) Large firms Q0.5 Q 0.75 0.1282 (0.0074)* 0.0186 (0.0035)* 0.7206 (0.0043)* -0.0006 (0.0009) 0.0127 (0.0017)* 0.0004 (0.0008) 0.0081 (0.0029)* -0.0025 (0.0013)*** 0.0496 (0.0117)* 0.1686 (0.0098)* 0.0302 (0.0045)* 0.7160 (0.0061)* -0.0011 (0.0011) 0.0117 (0.0020)* 0.0011 (0.0009) 0.0051 (0.0036) -0.0038 (0.0016)** 0.0693 (0.0139)* Q 0.9 0.1982 (0.0316)* 0.0316 (0.0152)** 0.7321 (0.0235)* -0.0054 (0.0029)*** 0.0142 (0.0057)* 0.0005 (0.0025) -0.0039 (0.0101) -0.0150 (0.0043)* 0.1171 (0.0370)* dni,t dki,t dmi,t Equityi,t-1 CFi,t-1 LTdebti,t-1 STdebti,t-1 Agei,t-1 Constantt R2 0.0950 (0.0017)* 0.0306 (0.0009)* 0.4790 (0.0010)* 0.0010 (0.0004)* 0.0204 (0.0005)* 0.0023 (0.0004)* 0.0214 (0.0009)* -0.0067 (0.0006)* 0.0415 (0.0033)* Financial sources 82,471 116,325 2347 N Note: The significance levels of the parameters are computed using bootstrapped standard errors (100 replications). Quantile regression coefficients can be interpreted as the marginal change in y at the θth conditional quantile due to marginal change in a particular regressor, ΔQθ (yi|xi) / Δx. *, **, *** significant at 1%, 5% and 10%. 0.3948 0.4112 0.4251 0.4179 0.3956 0.4057 0.4414 0.4685 0.4772 0.4805 0.5298 0.5581 0.5862 0.6109 0.6336 17 Decisions regarding the financial structure are of great consequence for small firms since they experience greater difficulties in accessing external financial sources. Such firms have to rely more heavily on their internal sources of finance, in particular cash flow and commercial borrowings. This result is consistent with the theory that information problems primarily affect small firms. The latter, which are typically undercapitalized, encounter increasing barriers impeding their access to external financial debt, especially for high-risk investment projects under conditions of asymmetric information. In order to invest in strategic projects (R&D and innovative activities), small firms usually increase their equity capital in order to give a signal to external borrowers that their projects involve a moderate risk (Magri, 2009). Our results show that SMEs are more sensitive than larger firms to cash flow. The cash flow coefficient decreases monotonically with the firms’ sales growth, indicating that cash flow plays an important role in moderating firm growth. Equity and short-term debt present similar parametric evolutions. In general, when firms have few options to obtain leverage their capital structure depends on internal financial sources and this has a negative impact on their investment, growth, profits and survival performance. Conversely, long-term bank debt presents a monotonically increasing coefficient in small and medium-sized firms. This indicates that long-term financial sources enable a firm to carry out projects that present greater growth opportunities because of their technological or innovative nature. 6. Conclusions This paper has examined the capital structure of Spanish manufacturing firms. In recent years, enhanced accessibility to a comprehensive database holding financial and economic information at the firm level has facilitated the analysis of the effect of financial services on these firms’ investment strategies and growth patterns. Using a broad sample of firms we have observed the sensitivity shown by sales growth to internal and external sources of finance. We are unable to draw definitive conclusions, but there is sufficient evidence to suggest that the link between the firms’ capital structure and their growth patterns is non-linear and readily understandable by applying traditional econometric methods. Small Spanish firms present marked differences with respect to their larger counterparts. Studies conducted elsewhere show that small firms tend to be more dependent on internal resources and less reliant on bank loans. Further, small firms are more likely to generate cash flows and commercial debt than they are bank debt. This limitation on their external finances acquires greater relevance with firms in their start-up phase. Thus, young, small firms that are undercapitalized encounter greater barriers when 18 attempting to access finances, in particular long-term bank debt, and they also suffer information problems when seeking to finance their investments. Our analysis of the effects of financial sources on firm growth indicates that the growth rates of small firms are more sensitive to these sources than are those of large firms. The cash flow and short-term bank debt parameters were found to be positive and to decrease as a firm gains higher growth rates. Equity capital offered only moderate elasticity, but a similar coefficient pattern, while long-term bank debt was found to be less sensitive with an increase being recorded as we moved across the quantile distribution. In general, small firms are more sensitive than large firms to cash flow. In the case of Spain’s small firms, the cash flow parameter was found to fall monotonically with the growth in their sales, but cash flow played a key role in firms that presented moderate growth rates. The equity capital and short-term bank debt parameters recorded a similar evolution. These results highlight the fact that firms with little relative ability to obtain leverage suffer from their limited access to long-term debt, which in turn has a negative impact on firm growth. Specifically, therefore, the corporate capital structure of young, small firms would seem to be biased toward internal sources of finance, which tends to limit their capacity to implement appropriate investment strategies. This restriction has a negative impact on the firms’ technological level, and impacts negatively on their productivity and growth. Equity capital among Spain’s manufacturers was found to increase with a firm’s age and size. A high percentage of equity among a firm’s total financial sources is of great importance, since it eases information problems and eliminates barriers limiting access to bank loans. Further, a high proportion of long-term bank debt among these sources ensures an enhanced financing of its strategic projects. In contrast with a firm’s other financial sources, the long-term bank debt shows a rising pattern across the quantile distribution. These results indicate the presence of a positive link between long-term financial sources and a firm’s growth. The implications of our results are, we believe, very clear. While internal cash flow may be indicative of the existence of financial constraints related to a firm’s physical investment, its investment policy is not related to its short-term financial sources. It is essential that a new, small firm is able to gain progressive access to collateral equity, via owners and venture funds, so as to increase the amount of equity as a share of its overall financial funds. As a firm increases its equity capital, the barriers hindering access to bank loans progressively disappear and the firm encounters the optimum conditions for taking greater risks and implementing more ambitious projects. Likewise, access to external funds, in particular long-term debt, should guarantee that Spanish manufacturing firms are able to increase their capitalization and raise their levels of productivity. We believe our 19 results to have important implications and policy makers should be made aware of them. Acs, Z.J. (1999): Are Small Firms Important? Their Role and Impact, Kluwer Academic Publishers. Acs, Z.J.; Morck, R. and Yeung, B. (1999): “Productivity Growth and Firm Size Distribution”, in Acs, Z.J., Carlsson, B. And Karlsson, Ch. (eds.); Entrepreneurship, Small & Medium-Sized Enterprises and the Macroeconomy, Cambridge University Press. Aghion, P., Angeletos, G., Banerjee, A., and K. Manova (2007). “Volatility and Growth: Credit Constraints and Productivity-Enhancing Investment, unpublished manuscript. Aghion, P., Fally, T. and Scarpetta, S. (2007): “Credit constraints as a barrier to the entry and post-entry growth of firms”, Economic Policy, vol. 22 (52): 731-790. Almeida, H., M. Campello and M. S. Weisbach (2004): “The Cash Flow Sensitivity of Cash”, The Journal of Finance, 59(4), 1777-1804. Alti, A. (2003): “How sensitive is investment to cash flow when financing is frictionless?”, The Journal of Finance, 58(2), 707-722. Beck, T.; Degirgüc-Kunt, A. and Maksimovic, V. (2005): “Financial and Legal Constraints to Growth: Does Firm Size Matter?”, The Journal of Finance,60(1), 137-177. Bencivenga, V.R., Smith, B.D., and Starr, R.M. (1995): “Transaction Costs, Technology Choice, and Endogenous growth”, Journal of Economic Theory, 67, 153-177. Cabral, L. M. B. and Mata, J. (2003): “On the Evolution of the Firm Size Distribution: Facts and Theory.” American Economic Review, 93(4):+, 1075–90. Carpenter, R. E. and Petersen, B.C. (2002): “Is the Growth of Small Firms Constrained by Internal Finance?” Review of Economics and Statistics, 84(2): 298–309. Cleary, S. (1999): “The Relationship between Firm Investment and Financial Status”, The Journal of Finance, 54(2), 673-692. Cleary, S. (1999): The relationship between firm investment and financial status. J Finance 54(2),673–92 Cleary, S. (2006) International corporate investment and the relationships between financial constraint measures. J Banking & Finance 30(5), 1559–80 Clementi, G.L. and Hopenhayn, H.A. (2006): “A theory of financing constraints and firm dynamics”, Quarterly Journal of Economics, 121 (2), 229-265. Coad, A. (2007): ‘Testing the principle of «growth of the fitter»’ : The relationship between profits and firm growth’, Structural Change and Economic Dynamics, 18, 370-386. Coad, A. and Rao, R. (2008). Innovation and firm growth in high-tech sectors: a quantile regression approach. Research Policy, 37 (4), 636-648. Fagiolo, G. and Luzzi, A. (2006): “Do liquidity constraints matter in explaining firm size and growth? Some evidence from the Italian manufacturing industry”, Industrial and Corporate Change, 15, 1–39. Fazzari, S.M., Hubbard, R.G. and Petersen, B.C. (1988): “Financing Constraints and Corporate Investment”, Brookings Papers on Economic Activity, 1988(1), 141-206. Gatti, R. and Love, I. (2008). “Does Access to Credit Improve Productivity? Evidence from Bulgarian Firms”. CEPR working paper N. 6676 (London: Centre for Economic Policy Research). Gilchrist, s. and Himmelberg, C.P. (1995): “Evidence on the role of cash flow for investment”, Journal of Monetary Economics, 36, 541-572. Himmelberg, C. and Petersen, B. (1994), ‘R&D and Internal Finance: A Panel Study of Small Firms in High-tech Industries’, Review of Economics and Statistics, 76, 38–51. Hutchinson, J. and Xavier, A. (2006): “Comparing the Impact of Credit Constraints on the Growth of SMEs in a Transition Country with an Established Market Economy”, Small Business Economics, 27, 169-179. Hyytinen, A. and Toivanen, O. (2005): “Do financial constraints hold back innovation and growth? Evidence on the role of public policy”, Research Policy, 34, 1385-1403. References 20 King, R. G. and Levine, R. (1993a): “Financial Intermediation and Economic Development,” in Colin Mayer and Xavier Vives, eds., Capital Markets and Financial Intermediation. London: Centre for Economic Policy Research, 156-89. King, R. G. and Levine, R. (1993b): “Finance and Growth: Schumpeter Might Be Right.” Quarterly Journal of Economics, 108(3), 717-37. King, R. G. and Levine, R. (1993c): “Finance, Entrepreneurship, and Growth: Theory and Evidence.” Journal of Monetary Economics, December 1993c, 32(3), 513-42. Koenker, R. and Bassett, G. (1978). “Regression Quantiles”, Econometrica, 46, 33-50. Koenker, R. and Hallock, K.F. (2001): “Quantile Regression”, Journal of Economic Perspectives, 15 (4), 143–156. Lang, L., E. Ofck and Stulz, R.M. (1996): “Leverage, investment, and firm growth”, Journal of Financial Economics, 40, 3-29. Levine, R., Loayza, N. and Beck, T. (2000): “Financial Intermediation and Growth: Causality and Causes,” Journal of Monetary Economics, 46, 31—77. Love, I. (2003): “Financial Development and Financing Constraints: International Evidence from the Structural Investment Model”, The Review of Financial Studies, 16(3): 765791. Lucas, R. E. (1988): “On the mechanics of economic development”, Journal of Monetary Economics, 22, 3–42. Machado, J.A.F. and Mata, J. (2005): “Counterfactual decomposition of changes in wage distributions using quantile regressions”, Journal of Applied Econometrics, 20(4), 445465. Magri, S. (2009): “The financing of small innovative firms: the Italian case”, Economics of Innovation and New Technology, 18 (2): 181-204. Mohnen, P.; Palm, F.C., Loeff, S. S., and Tiwari, A. (2008): Financial Constraints and Other Obstacles: Are they a Threat to Innovation Activity?”, De Economist, 156(2): 201-214. Musso, P. and Schiavo, S. (2008): “The impact of financial constraints on firm survival and growth”, Journal of Evolutionary Economics, 18: 135-149. Nucci, F., Pozzolo, A. and Schivardi, F. (2004): “Is firm’s productivity related to its financial structure? Evidence from microeconomic data”, unpublished working paper. Petersen, M. and Rajan, R. (1994): “The benefits of firm-creditor relationships: Evidence from small business data”, Journal of Finance, 49, 3–38. Robinson, J. (1952): “The eneralization of the General Theory”, in The Rate of Interest and Other Essays, London: Macmillan. Savignac, F. (2008): “The impact of financial constraints on innovation: what can be learned from a direct measure?”, Economics of Innovation and New Technology, Volume 17 (6): 553-569. Winker, P. (1999):“Causes and effects of financing constraints at the firm level”, Small Business Economics, 12 (2): 169-181. 21 Graphs showing the effects of financial sources on sales growth Graph 1. Effect of financial sources Small firms lnCsuscLAG -0.01 -0.01 0.00 0.01 0.01 lnCFactLAG 0.010.010.020.030.030.04 0 .2 .4 .6 Quantile .8 1 0 .2 .4 .6 Quantile .8 1 lnLTdebtAssLAG 0.00 0.01 0.01 -0.01 0 .2 .4 .6 Quantile .8 1 lnSTdebtAssLAG 0.000.010.020.030.040.05 0 .2 .4 .6 Quantile .8 1 Graph 2. Effect of financial sources Medium-sized firms lnCsuscLAG -0.00 -0.00 0.00 0.00 0.00 0.04 0 .2 .4 .6 Quantile .8 1 0.01 0 lnCFactLAG 0.02 0.03 .2 .4 .6 Quantile .8 1 lnLTdebtAssLAG -0.00 0.00 0.00 0.00 0.01 0 .2 .4 .6 Quantile .8 1 lnSTdebtAssLAG 0.00 0.02 0.04 0.06 0 .2 .4 .6 Quantile .8 1 Graph 3. Effect of financial sources Large firms 0.01 lnCFactLAG 0.00 0.01 0.02 0.03 0.04 0 .2 .4 .6 Quantile .8 1 0 -0.02 lnCsuscLAG -0.01 0.00 .2 .4 .6 Quantile .8 1 lnLTdebtAssLAG -0.01 -0.01 0.00 0.01 0.01 0 .2 .4 .6 Quantile .8 1 -0.05 0 lnSTdebtAssLAG 0.00 0.05 .2 .4 .6 Quantile .8 1 22 SÈRIE DE DOCUMENTS DE TREBALL DE LA XREAP 2006 CREAP2006-01 Matas, A. (GEAP); Raymond, J.Ll. (GEAP) "Economic development and changes in car ownership patterns" (Juny 2006) CREAP2006-02 Trillas, F. (IEB); Montolio, D. (IEB); Duch, N. (IEB) "Productive efficiency and regulatory reform: The case of Vehicle Inspection Services" (Setembre 2006) CREAP2006-03 Bel, G. (PPRE-IREA); Fageda, X. (PPRE-IREA) "Factors explaining local privatization: A meta-regression analysis" (Octubre 2006) CREAP2006-04 Fernàndez-Villadangos, L. (PPRE-IREA) "Are two-part tariffs efficient when consumers plan ahead?: An empirical study" (Octubre 2006) CREAP2006-05 Artís, M. (AQR-IREA); Ramos, R. (AQR-IREA); Suriñach, J. (AQR-IREA) "Job losses, outsourcing and relocation: Empirical evidence using microdata" (Octubre 2006) CREAP2006-06 Alcañiz, M. (RISC-IREA); Costa, A.; Guillén, M. (RISC-IREA); Luna, C.; Rovira, C. "Calculation of the variance in surveys of the economic climate” (Novembre 2006) CREAP2006-07 Albalate, D. (PPRE-IREA) "Lowering blood alcohol content levels to save lives: The European Experience” (Desembre 2006) CREAP2006-08 Garrido, A. (IEB); Arqué, P. (IEB) “The choice of banking firm: Are the interest rate a significant criteria?” (Desembre 2006) SÈRIE DE DOCUMENTS DE TREBALL DE LA XREAP CREAP2006-09 Segarra, A. (GRIT); Teruel-Carrizosa, M. (GRIT) "Productivity growth and competition in spanish manufacturing firms: What has happened in recent years?” (Desembre 2006) CREAP2006-10 Andonova, V.; Díaz-Serrano, Luis. (CREB) "Political institutions and the development of telecommunications” (Desembre 2006) CREAP2006-11 Raymond, J.L.(GEAP); Roig, J.L.. (GEAP) "Capital humano: un análisis comparativo Catalunya-España” (Desembre 2006) CREAP2006-12 Rodríguez, M.(CREB); Stoyanova, A. (CREB) "Changes in the demand for private medical insurance following a shift in tax incentives” (Desembre 2006) CREAP2006-13 Royuela, V. (AQR-IREA); Lambiri, D.; Biagi, B. "Economía urbana y calidad de vida. Una revisión del estado del conocimiento en España” (Desembre 2006) CREAP2006-14 Camarero, M.; Carrion-i-Silvestre, J.LL. (AQR-IREA).;Tamarit, C. "New evidence of the real interest rate parity for OECD countries using panel unit root tests with breaks” (Desembre 2006) CREAP2006-15 Karanassou, M.; Sala, H. (GEAP).;Snower , D. J. "The macroeconomics of the labor market: Three fundamental views” (Desembre 2006) SÈRIE DE DOCUMENTS DE TREBALL DE LA XREAP 2007 XREAP2007-01 Castany, L (AQR-IREA); López-Bazo, E. (AQR-IREA).;Moreno , R. (AQR-IREA) "Decomposing differences in total factor productivity across firm size” (Març 2007) XREAP2007-02 Raymond, J. Ll. (GEAP); Roig, J. Ll. (GEAP) “Una propuesta de evaluación de las externalidades de capital humano en la empresa" (Abril 2007) XREAP2007-03 Durán, J. M. (IEB); Esteller, A. (IEB) “An empirical analysis of wealth taxation: Equity vs. Tax compliance” (Juny 2007) XREAP2007-04 Matas, A. (GEAP); Raymond, J.Ll. (GEAP) “Cross-section data, disequilibrium situations and estimated coefficients: evidence from car ownership demand” (Juny 2007) XREAP2007-05 Jofre-Montseny, J. (IEB); Solé-Ollé, A. (IEB) “Tax differentials and agglomeration economies in intraregional firm location” (Juny 2007) XREAP2007-06 Álvarez-Albelo, C. (CREB); Hernández-Martín, R. “Explaining high economic growth in small tourism countries with a dynamic general equilibrium model” (Juliol 2007) XREAP2007-07 Duch, N. (IEB); Montolio, D. (IEB); Mediavilla, M. “Evaluating the impact of public subsidies on a firm’s performance: a quasi-experimental approach” (Juliol 2007) XREAP2007-08 Segarra-Blasco, A. (GRIT) “Innovation sources and productivity: a quantile regression analysis” (Octubre 2007) SÈRIE DE DOCUMENTS DE TREBALL DE LA XREAP XREAP2007-09 Albalate, D. (PPRE-IREA) “Shifting death to their Alternatives: The case of Toll Motorways” (Octubre 2007) XREAP2007-10 Segarra-Blasco, A. (GRIT); Garcia-Quevedo, J. (IEB); Teruel-Carrizosa, M. (GRIT) “Barriers to innovation and public policy in catalonia” (Novembre 2007) XREAP2007-11 Bel, G. (PPRE-IREA); Foote, J. “Comparison of recent toll road concession transactions in the United States and France” (Novembre 2007) XREAP2007-12 Segarra-Blasco, A. (GRIT); “Innovation, R&D spillovers and productivity: the role of knowledge-intensive services” (Novembre 2007) XREAP2007-13 Bermúdez Morata, Ll. (RFA-IREA); Guillén Estany, M. (RFA-IREA), Solé Auró, A. (RFA-IREA) “Impacto de la inmigración sobre la esperanza de vida en salud y en discapacidad de la población española” (Novembre 2007) XREAP2007-14 Calaeys, P. (AQR-IREA); Ramos, R. (AQR-IREA), Suriñach, J. (AQR-IREA) “Fiscal sustainability across government tiers” (Desembre 2007) XREAP2007-15 Sánchez Hugalbe, A. (IEB) “Influencia de la inmigración en la elección escolar” (Desembre 2007) SÈRIE DE DOCUMENTS DE TREBALL DE LA XREAP 2008 XREAP2008-01 Durán Weitkamp, C. (GRIT); Martín Bofarull, M. (GRIT) ; Pablo Martí, F. “Economic effects of road accessibility in the Pyrenees: User perspective” (Gener 2008) XREAP2008-02 Díaz-Serrano, L.; Stoyanova, A. P. (CREB) “The Causal Relationship between Individual’s Choice Behavior and Self-Reported Satisfaction: the Case of Residential Mobility in the EU” (Març 2008) XREAP2008-03 Matas, A. (GEAP); Raymond, J. L. (GEAP); Roig, J. L. (GEAP) “Car ownership and access to jobs in Spain” (Abril 2008) XREAP2008-04 Bel, G. (PPRE-IREA) ; Fageda, X. (PPRE-IREA) “Privatization and competition in the delivery of local services: An empirical examination of the dual market hypothesis” (Abril 2008) XREAP2008-05 Matas, A. (GEAP); Raymond, J. L. (GEAP); Roig, J. L. (GEAP) “Job accessibility and employment probability” (Maig 2008) XREAP2008-06 Basher, S. A.; Carrión, J. Ll. (AQR-IREA) Deconstructing Shocks and Persistence in OECD Real Exchange Rates (Juny 2008) XREAP2008-07 Sanromá, E. (IEB); Ramos, R. (AQR-IREA); Simón, H. Portabilidad del capital humano y asimilación de los inmigrantes. Evidencia para España (Juliol 2008) XREAP2008-08 Basher, S. A.; Carrión, J. Ll. (AQR-IREA) Price level convergence, purchasing power parity and multiple structural breaks: An application to US cities (Juliol 2008) XREAP2008-09 Bermúdez, Ll. (RFA-IREA) A priori ratemaking using bivariate poisson regression models (Juliol 2008) SÈRIE DE DOCUMENTS DE TREBALL DE LA XREAP XREAP2008-10 Solé-Ollé, A. (IEB), Hortas Rico, M. (IEB) Does urban sprawl increase the costs of providing local public services? Evidence from Spanish municipalities (Novembre 2008) XREAP2008-11 Teruel-Carrizosa, M. (GRIT), Segarra-Blasco, A. (GRIT) Immigration and Firm Growth: Evidence from Spanish cities (Novembre 2008) XREAP2008-12 Duch-Brown, N. (IEB), García-Quevedo, J. (IEB), Montolio, D. (IEB) Assessing the assignation of public subsidies: Do the experts choose the most efficient R&D projects? (Novembre 2008) XREAP2008-13 Bilotkach, V., Fageda, X. (PPRE-IREA), Flores-Fillol, R. Scheduled service versus personal transportation: the role of distance (Desembre 2008) XREAP2008-14 Albalate, D. (PPRE-IREA), Gel, G. (PPRE-IREA) Tourism and urban transport: Holding demand pressure under supply constraints (Desembre 2008) SÈRIE DE DOCUMENTS DE TREBALL DE LA XREAP 2009 XREAP2009-01 Calonge, S. (CREB); Tejada, O. “A theoretical and practical study on linear reforms of dual taxes” (Febrer 2009) XREAP2009-02 Albalate, D. (PPRE-IREA); Fernández-Villadangos, L. (PPRE-IREA) “Exploring Determinants of Urban Motorcycle Accident Severity: The Case of Barcelona” (Març 2009) XREAP2009-03 Borrell, J. R. (PPRE-IREA); Fernández-Villadangos, L. (PPRE-IREA) “Assessing excess profits from different entry regulations” (Abril 2009) XREAP2009-04 Sanromá, E. (IEB); Ramos, R. (AQR-IREA), Simon, H. “Los salarios de los inmigrantes en el mercado de trabajo español. ¿Importa el origen del capital humano?” (Abril 2009) XREAP2009-05 Jiménez, J. L.; Perdiguero, J. (PPRE-IREA) “(No)competition in the Spanish retailing gasoline market: a variance filter approach” (Maig 2009) XREAP2009-06 Álvarez-Albelo,C. D. (CREB), Manresa, A. (CREB), Pigem-Vigo, M. (CREB) “International trade as the sole engine of growth for an economy” (Juny 2009) XREAP2009-07 Callejón, M. (PPRE-IREA), Ortún V, M. “The Black Box of Business Dynamics” (Setembre 2009) XREAP2009-08 Lucena, A. (CREB) “The antecedents and innovation consequences of organizational search: empirical evidence for Spain” (Octubre 2009) XREAP2009-09 Domènech Campmajó, L. (PPRE-IREA) “Competition between TV Platforms” (Octubre 2009) SÈRIE DE DOCUMENTS DE TREBALL DE LA XREAP XREAP2009-10 Solé-Auró,A. (RFA-IREA),Guillén, M. (RFA-IREA), Crimmins, E. M. “Health care utilization among immigrants and native-born populations in 11 European countries. Results from the Survey of Health, Ageing and Retirement in Europe” (Octubre 2009) XREAP2009-11 Segarra,A. (GRIT), Teruel, M. (GRIT) “Small firms, growth and financial constraints” (Octubre 2009) xreap@pcb.ub.es