What is the role of a country’s financial system?
Introduction
The manner in which companies conduct their debt policies has historically been researched after two primary theoretical models. On the one hand, based on the trade-off theory, companies are looking for an optimal debt/equity ratio (e.g. Kraus & Litzenberger, 1973). With this theory, companies with a diversified business will utilize more debt. These companies have stable profits, cash flows and working capital and hence financial flexibility is comparatively less vital to them, they have lower distress costs and less informational obscurity (Berger & Udell, 1998). Conversely, based on the pecking order theory (e.g. Myers & Majluf, 1984) and the level of applicability of asymmetric information,1 companies have a pecking order of preference in funding decisions: they prefer to make use of internally generated funds first, then debt and finally equity. Over time, the level of informational opacity shifts and generates the financial life cycle (Kaplan & Stromberg, 2003). The life cycle of firm finance is a common empirical phenomenon in corporate finance that explains how the financial requirements, capital structure, and sources of funds of firms change with time (Berger & Udell, 1998). It draws its support from life cycle theory, which postulates that firms undergo stage-wise financial changes over time driven by internal and external determinants (Mueller, 1972). Companies usually go through distinct phases – start-up, growth, maturity and decline – each of which is defined by certain financial requirements and limitations on funding (Damodaran, 2007).
Despite a vast literature, tests of the pecking order and trade-off theories do not account for all general patterns of corporate financial decisions (e.g. Hadlock & Pierce, 2010). One of the possible reasons for contradictory evidence may lie with the possibility of a pro-tempore optimal capital structure or a pro-tempore pecking order that varies across the firm’s life cycle. As such, in analyzing the financing policies of SMEs, the theory of financial life cycle may account for violations of the trade-off and pecking order theories based on the age of a firm and related information opacity and financing constraints.
The financial life cycle of European SMEs during and after crisis times and before periods of crisis. What is the role of a country‘s financial system?How companies structure their debt policies has been classically researched according to two central theoretical frameworks. On the one hand, under the trade-off theory, companies are looking for the optimal combination of debt/equity (e.g. Kraus & Litzenberger, 1973). Under this perspective, it is argued that companies with a conglomerate business make greater use of debt. These companies have stable profit, working capital and cash flows and thus financial flexibility is comparatively less critical to them, with lower costs of distress and less informational opacity (Berger & Udell, 1998). Conversely, following the pecking order theory (e.g. Myers & Majluf, 1984) and the level of applicability of asymmetric information,1 companies have a hierarchical preference in capital structure choices: internally generated funds come first, followed by debt, and finally equity. The level of informational opacity evolves along time and shapes the financial life cycle (Kaplan & Stromberg, 2003). The financial life cycle of firms is a widely studied phenomenon in corporate finance, describing how companies’ financial needs, capital structure and funding sources evolve over time (Berger & Udell, 1998). It is grounded in life cycle theory, which suggests that firms experience predictable financial transitions over time, influenced by internal and external factors (Mueller, 1972). Companies generally progress through unique stages – start-up, growth, maturity and decline – each with particular financing requirements and constraints of finance (Damodaran, 2007).
Despite a big literature, empirical research testing the pecking order and the trade-off theories is not able to account for all the general patterns of corporate financial decisions (e.g. Hadlock & Pierce, 2010). There is one possible explanation for contentious prior evidence: the possibility that there is a pro-tempore optimal capital structure or a pro-tempore pecking order that varies over the firm’s life cycle. As a result, in examining the finance policies of SMEs, the theory of the financial life cycle may have explanations for trade-off and pecking order theory deviations based on the age of the firm, pertaining to information opacity and financial constrain.
We show that the typical inverse age/debt pattern – in which younger firms have a greater reliance on debt – faltered in both the SDC and GFC. Of particular concern, our results also reveal that the impact of crises on the financial life cycle of SMEs is significantly diminished in countries with advanced financial systems. In these conditions, corporations enjoy a more stable credit availability and stand a higher chance of resuming pre-crisis funding patterns. However, in financially underdeveloped countries the disruption is more severe and enduring, especially for newer and less transparent companies.
A review of SMEs’ financial behavior at various stages in their lives as well as during times of economic hardship offers useful insights with important implications for firms, governments and financial institutions alike. The review offers recommendations for adapting financial policy to match a firm’s position in the life cycle and overall macroeconomic situation. In addition, it identifies the pivotal position undertaken by debt, Europe’s most utilized source of financing (European Central Bank, 2024), as an agent of economic restoration in difficult circumstances.
The paper is structured as follows. The second section describes the theoretical framework of the financial life cycle and sets out our hypotheses. The third section describes data and methodology. The fourth, fifth and sixth sections comprise the results. The paper concludes in section seven with conclusions and a discussion of implications.
We illustrate that the normative inverse age/debt relationship – where younger firms are more leveraged – lost strength over both the SDC and GFC. Of particular interest, our results also reveal that the impact of crises on the financial life cycle of SMEs is substantially attenuated in countries with more advanced financial systems. In those settings, firms have a more stable access to credit and better conditions to return to pre-crisis financing behaviors. In financially underdeveloped countries the break is more severe and lasting, especially for younger and more opaque companies.
A study of the financial behavior of SMEs during their life cycles and in times of economic adversity yields useful findings with important implications for firms, governments and financial institutions. The findings offer recommendations for fine-tuning financial policies according to the stage of the firm in the life cycle and the macroeconomic climate. In addition, it identifies the key role of debt, the most utilized source of finance in Europe (European Central Bank, 2024), as a tool of economic rehabilitation under duress.
The paper’s structure is as follows. The second section presents the theoretical framework of the financial life cycle and defines our hypotheses. The third section provides a summary of data and methodology. The fourth, fifth and sixth sections hold the results. The paper concludes in section seven with conclusions and discussion of implications.
This is a surprising research gap, since companies adjust their finance policies to the status of the economy, and macroeconomic variables may have a great impact on companies’ finance policies throughout their lifespan Indeed, debt benefits and costs are different during times of crisis, since debt may be riskier due to the general economic situation  In fact, the range of cost and benefit implications associated with debt usage has a considerable influence on firm value, particularly in times of credit crunches (Machokoto et al., 2020). Adjei (2012), for instance, illustrates that companies with greater dependence on debt suffered a larger drop in performance from the pre-crisis to crisis era. To the contrary, in the case of companies with lower debt levels, new borrowing did not have any notable effect on performance during the crisis.
Indeed, a company’s financial conduct is informed by financial shocks within the institutional environment ). The GFC crisis is a prime illustration of a credit shock that raised the likelihood of business default (Martinez et al., 2019), since it exaggerated asymmetric information issues and worsened firms’ financing constraints et al., 2010; Kahle & Stulz, 2013), particularly for SMEs . As proposed by (2018) and Zubair et al. (2020), in the event of a financial crisis, SMEs are likely to depend less on bank loans compared to the pre- or post-crisis period. A thought-provoking article by D’Amato (2020) highlighted the influence of age among SMEs on financial debt during the GFC due to debt costs and financial limitations. He observes that in the case of financial crisis, curbs are tighter for SMEs, even greater than for big firms. Consequently, in the event of a recession, credit-constrained SMEs might look more to alternative forms of external funding in order to finance their investments,5 particularly trade credit (Carbo-Valverde et al., 2016; Dottori et al., 2024) and cash balances (Zubair et al., 2020).
While earlier research predominantly addressed the 2008–2010 GFC and its dramatic occurrences and scandals (like the collapse of Lehman Brothers in the USA), some research also focused on another important financial shock that immediately occurred afterwards (Hoque, 2013), i.e. the sovereign debt crisis 2017; et al., 2021; Lane, 2012). This crisis was in the wake of the GFC and occurred in 2011–2013 when Euro-area members were experiencing sovereign debt tensions.conclude that a higher sovereign risk has tangible effects on corporate financial policies. Their research proved that the widening gap between the 10-year Italian government bond’s yield and the related BTP-Bund spread in Germany during 2011 raised the cost of borrowing for companies, curbing their external funding access. Ferrando et al. (2017) noted that SMEs in SDC-hit countries became more susceptible to credit denial.
All these arguments indicate that the two crises greatly impaired the ability of firms to obtain credit, and the most significant impact of the credit constraint fell on SMEs (Castaldo et al., 2023). Actually, as shown by the trade-off theory, large, consolidated firms are less constrained financially. Therefore, the GFC and the SDC created financial constraints, particularly for SMEs, which have traditionally been more afflicted with higher informational asymmetries (Berger & Udell, 1998), and this led to a decrease in the level of debt employed (Cowling et al., 2012). It is not only the level of debt employed that shifts tout court under and following a period of crisis, however. It is worth noting that financial decisions in periods before and after crises vary based on the age of the firm. In this respect, we enrich the existing literature by asking how the increased usage of debt in the early phase of the life cycle and diminishing usage in the later stages6 witnessed by all of the above contributions to the certification effect argument could be formulated in the context of crisis situations. Given that, as implied by the trade-off arguments, small firms had more constrained access to finance and are most negatively impacted by credit crunches, we assume that during the GFC and the SDC the negative age/debt relationship would be weaker. Limitations in the capital market, poor economic health and lack of liquid assets (which are a first preference based on the pecking order theories) may drive firms towards a shortage of alternatives to borrowing, thus reducing the decrease in debt with age.
 what about the post-crisis phase?
Although it is young firms that suffer most from a crisis (Cowling et al., 2018), a fascinating literature indicates that the barriers to access debt during the crisis period were not sufficient to deter companies from applying for loans during a following period (e.g. Mac an Bhaird, C., 2013). Brown and Lee (2019) examined the capital structure choices and credit availability following the GFC, noting that SMEs turned to external financing sources following the global financial crisis. The authors examine how such firms managed issues of funding access and which funding sources best facilitated their growth. Following episodes of crisis, there is in most cases a phase of recovery where companies recover the confidence in financial markets that they lost during the crisis. Once confidence is restored, companies then start seeking external debt. But following a crisis, credit challenges cannot be fully reversed in the short run, and economies cannot recover to pre-crisis levels within the short run (Tang & Upper, 2010). Thus, in the short run credit access cannot come back to where it was during the times leading up to the crisis. These barriers persist persistently higher for informationally opaque young SMEs, which Vermoesen et al. (2013) find were “ex ante more likely to be financially constrained“. In this kind of situation, financial markets will go back to pre-crisis credit conditions. This pre-crisis market conditions trend means a relaxation of constraints on finances for companies for which we assume the age/debt relationship will exhibit a slow shift back to pre-crisis trends. But we assume that this reversal might not follow in the same way for business with varying degrees of problems of asymmetric information, and consequently different potentialities of access to finance markets. As proven by Mac an Bhaird, C. (2013), the firms that are financially most distressed have the worst impacts of the credit crunch. Post-GFC, companies with higher informational asymmetries faced financial constraint issues. In particular, for more informationally opaque companies bank credit tightening lasted longer (Driver & Muñoz-Bugarin, 2019; Riley et al., 2014). To support this, Davis et al. (2013) noted that the denial of loan application requests to smaller companies (which experience greater informational issues than large ones) were greater after 2008 than they had been since 2001. Given that SMEs experience pertinent informational asymmetry matters, particularly during post-crisis times (Fosu et al., 2016), we anticipate that it will take time to return to pre-crisis levels. Additionally, Fort et al. (2013) claim that SMEs are more impacted by economic shocks than their larger peers.
In any event, while being delayed by the persistence of the effects of the crisis, we anticipate that the relationship between age and debt in the post-crisis period will be oriented towards what was seen before the crisis. Hence, we anticipate that the declining trend seen by La Rocca et al. (2011) and also by other scholars is lower for small firms in crisis times than in pre-crisis times. In a similar vein, we posit that the decreased slope observed during the crisis will distinguish this relationship from that of the post-crisis period, with a return to the pre-crisis pattern.
The effect of age on SME debt policies is lessened during crisis periods than it is in pre- and post-crisis periods.
The significant work of Rajan and Zingales (1998) proved that financial development in a nation has a serious impact on capital structure choices. In fact, highly developed financial institutions are able to reduce agency issues (Giannetti, 2003), lower the cost of borrowing (Beck et al., 2011) and enhance SME credit accessibility (Fasano & Deloof, 2021), but there are some other advantages as well (Basha et al., 2023; Li et al., 2024). These financial institutions not only ensure access to outside funds, but also enhance market liquidity to ensure a better diversified financial environment (Levine, 2005). Enabling the development of the banking sector would also result in easier business transactions, more bank competition and therefore a better allocation of funding (Antzoulatos et al., 2016; Fan et al., 2012; Holmstrom & Tirole, 1997; Leary, 2009). Empirical evidence indicates that in more developed financial systems companies use more bank debt, whereas in less mature financial systems alternative finance sources predominate (Beck & Demirguc-Kunt, 2006). Such financial institution impact can be varied based on the life cycle stages of a company (Deloof & Vanacker, 2018; Hanssens et al., 2016) and also the macroeconomic environment of a company’s operation (La Rocca et al., 2019). In fact, financial advancement influences the debt capacity of firms differently based on their age as well as informational opacity, whereby younger SMEs in countries that have highly advanced financial systems are likely to secure credit under better terms (Brown & Lee, 2019).
Therefore, the crisis’s effect on the real economy also introduces the question of whether and how the age/debt effect is dependent on the financial development of a nation (Fornari et al., 2012). It is worth exploring whether and how the level of development of a nation‘s financial system may influence the relationships examined in our first hypothesis.
This can be argued to be a primary basis through which the required debt is obtained based on asymmetric information theory, whereby an efficient financial system closes the information gap between firms and financial intermediaries, thus enhancing the utilization of debt (Fasano & Cappa, 2022; Fasano & La Rocca, 2023). In times of crisis, nations with a more developed financial system have greater ability to narrow down the asymmetric information gap and cushion companies against adverse contingencies (La Rocca et al., 2019). Such assistance has also been noted by Beck et al. (2008), as per whom companies in weaker institutional countries use less external financing, especially from banks. Ge and Qiu (2007) observe that companies in those nations with underdeveloped financial systems struggle to finance their operations on bank debt terms as the classic source of funding. This may mean that in highly developed financial environments, in times of crisis companies might experience less information opacity and might thus have more access to debt than companies doing business in financially less developed environments. Empirical evidence indicates that the development of the financial system mitigates the effect of economic crises on financing firms. In very advanced settings, firms face reduced information opacity and enjoy superior credit access even in times of crises (Allen et al., 2018). Actually, Demirgüç-Kunt et al. (2020) note that in countries that have “shallower financial markets and less developed financial infrastructure” the GFC’s influence was more pronounced. On the other hand, in weaker financial systems of countries, increased asymmetric information problems could limit the capacity of firms to obtain debt finance, extending the adverse impacts of crises (Beck et al., 2008; Love and MartÃnez PerÃa, 2015). In addition, the post-crisis recovery path will be easier in developed economies where banking systems can effectively revive credit provision, as compared to in settings with low financial development where chronic credit friction might impede recovery (Anginer et al., 2020; Gambacorta et al., 2014).
Therefore, the lower impact proposed by our first hypothesis may be less pronounced for SMEs located in highly financially developed countries (or, conversely, more intense for SMEs located in financially under-developed countries). By the same logic, following the crises the access to the pre-crisis trends of SMEs may be less difficult in those countries with a more highly developed financial system. Conversely, in developing economies the increased asymmetric information problems may actually restrict such a reversion. In fact, in such economies SMEs might experience more serious financing constraints in crises, with a time lag in resuming pre-crisis financing trends.
A crisis’s effect on the financial life cycle is tempered by how developed the financial system is.
 Methodology and data
We obtained accounting information from the Amadeus database of the Bureau van Dijk. We considered only SMEs based on the definition of the European Commission in relation to companies with total assets not above 43 million euros and with less than 50 million euros of annual total revenue (Serrasqueiro & Nunes, 2012). Our sample SMEs are from 28 European nations.7 We excluded observations whose accounting data were missing and financial sector firms. For minimizing the effect of outliers, all the accounting variables were winsorized using the 1st and 99th percentiles of distribution. Real GDP data and financial development of countries were obtained from the World Bank. The last sample is unbalanced panel data of 97,327 SMEs for a total of 961,249 observations between the years 2005 and 2016. We chose particularly this period because it captures the last three years prior to the GFC, the three years of the GFC, the following three years of the subsequent SDC, and the following three years of the entire crisis period.
Model and variables
We used the ordinary least squares cluster technique with standard errors clustered at the country and industry level (OLS Cluster).8 This approach further enriches the findings of previous studies because it allows for controlling for observations that are correlated under two dimensions, and because regressions correct the standard errors for the possible dependence of the residuals within clusters. Two-way clustered standard errors give stronger estimates than those derived from one-way clustering, and they do so at the expense of less possibility in underestimating or overestimating statistical significance. Specifically, this method accounts for the potential that the data drawn upon may be correlated both within nations (because of shared macroeconomic or institutional influences) and within industries (because of similar sector-specific dynamics). We do not consider firm fixed effects because the level of national financial development changes very little over the period considered in our study. Clustering the errors enables this variability to be preserved in the regressions. The dependent variable is Debt, a proxy for the debt/equity mix (the so-called capital structure) and computed as the ratio of financial (or interest-bearing) long-term and short-term debt (excluding trade debt) scaled by total assets (La Rocca et al., 2011). The variable Age is computed as the natural logarithm of the age of the firm in years.
In order to test hypothesis 1 we have to control for three sub-periods: 1) the pre-crisis period 2005–2007, (2) a crisis period involving the GFC (2008–2010) and the SDC (2011−2013), (3) the post-crisis period 2014–2016. We thus utilized the baseline model with interactions of variable Age and the variable Dummy Crisis period, which equals 1 for observations in the years 2008–2013, and the variable Dummy Post-Crisis period, which equals 1 for observations in the years 2014–2016. This is the model used.
 Descriptives and correlations
The average debt level for European SMEs is 19.6 % and is consistent with the most relevant existing empirical studies in this research area. In Table A.2 of the appendix we present the countries’ list in our sample, for each country reporting the mean debt level.
The findings indicate a high heterogeneity in the employment of debt between countries. We also identified a high country-level heterogeneity in the employment of debt in the periods both before and after the two crisis periods examined.9 In Table A.3 we examine the use of debt differences at industry level.
Table A.3 indicates that the debt level employed by SMEs also significantly differs across industries, as noted by recent research (e.g. Fasano et al., 2023). As a further descriptive statistic, Table A.4 presents the mean value of debt for the subsamples by Age using a five-year range for each subsample.
Fig. A.2 and Table A.4 point out the different debt usage by young and old SMEs (based on the appropriate 25 and 75 percentiles of the Age variable) in the pre-crisis period. In the crisis, young SMEs lowered their debt stock, while old SMEs raised their debt stock. Both SME types lowered their debt stock in their capital structures in the post-crisis period. This indicates that the shock of the financial crisis had different effects based on SMEs’ age, thereby proving the necessity of examining this phenomenon.
In addition, it would be worth recreating Fig. A.3, classifying the sample according to the median between highly and lowly financially developed countries. Applying the World Bank variable, we took the pre-crisis year (2007) in order to divide the samples into two sub-samples, from high to low level of financial development. We employed the pre-crisis year to account for how the ex-ante financial development of the country was able to moderate the crisis’s impact on our main relationship. This methodology is comparable to that applied by Deloof and Vanacker (2018), who looked at bank dependence prior to the crisis.
Table A.5 presents the country list ranked by the median value of financial development across two sub-groups (High v Low).
Fig. A.3 and Fig. A.4 indicate the broad disparity in the Age/Debt relationship that seems to exist between nations with different financial development. There is disparity at the beginning of the analysis (prior to the crisis), and even during the crisis and also in the post-crisis period there was a disparate outcome in the form of mean indebtedness by firms based on the financial environment.
 Empirical results
Regarding hypothesis 1, columns 1, 2 and 3 in Table 3 report the results using the continuous variable Age with respect to Debt for the entire period of observation. In particular, column 3 shows our main model findings. Additionally, columns 4, 5 and 6 are about regression findings based on the subsamples of pre-, during and post-crisis periods.
We discovered that European SMEs’ age has a negative relationship with debt use. European SMEs have a tendency to successively reduce the utilization of debt along their life cycles. Such findings are in line with those experienced by the numerous contributions within the context of theories of the life cycle that emphasize the significance of debt in new start-ups (e.g. Robb & Robinson, 2014 or Deloof et al., 2019), confirming the certification effect argument. In addition, they validate the significance of a firm’s age on its financial choices (Michaelas et al., 1999). Nevertheless, these findings are specially significant since they validate that the conclusions of the work of La Rocca et al. (2011) still exist over ten years later even in a more extensive and generalised European environment. Therefore, in line with La Rocca et al. (2011), our analysis verifies the long-documented negative association between firm age and debt financing. In order to examine the interaction between firm Age and Debt conditioned by two consecutive macro-economic financial shocks, i.e., the GFC and the SDC (complete period 2008–2013), column 2 reports the full sample regressions including crisis and post-crisis dummy variables, while column 3 accounts for the interaction of Age with both the crisis and post-crisis dummy variables.
Column 3 has a negative significant effect for the variable Age, for the two dummies for the crisis and post-crisis period, and for two positive interaction terms. It is interesting to see what occurs during the crisis period. The coefficient of the variable Age (−0.031) and of the interaction between Age and Crisis Dummy (0.031) are equal but with opposite sign. Briefly, the negative correlation between Age and Debt is entirely offset during the financial crisis phase. This finding is supported also when considering the non-significance of the coefficient of Age in the crisis period sub-sample.
 Robustness and other tests
ther testThe role of industry’s dependence on external finance
Here we check the industry-specific influences, since companies face various debt options, possibilities and limitations based on their industry (Deloof & Vanacker, 2018; Garay et al., 2019; Harris & Raviv, 1991). So the financial life cycle and the crisis periods‘ role can be influenced by the degree of an industry’s reliance upon external finance (Cetorelli & Strahan, 2006) and on the external financial assets needed by each individual industry (Rajan & Zingales, 1998). As per Deloof and Vanacker (2018), we employ the bank dependence variable represented as the median value of bank debt to total assets ratio in four-digit industries computed in non-crisis years. The results of the regression presented in Table A.10 indicate that the external finance dependence of the industry does not alter the SMEs’ financial life patterns and the impact of macroeconomic shocks on the financial life cycle.
6.2. Other test via a sample-period extension: The financial life cycle prior, during and subsequent to the Covid crisis
As the Covid crisis is a significant recent crisis (Cheema et al., 2022), we performed an analysis to investigate the differences and similarities with our results when compared to those achieved using a sample of companies hit by the pandemic. We therefore expanded our database by obtaining firm-level data and GDP for the countries under study up to the year 2023, which gave us a substantial sample of 4,464,897 firm-year observations. Subsequently, we re-estimated the regressions of our baseline model, defining three dummy variables for the pre-Covid period (2018–2019), the Covid period (2020−2021) and the post-Covid period (2022−2023). The findings, in the new Table 5, verify the presence of a negative association between debt and firm age. They also indicate that during the Covid crisis firms seem to use bank credit differently than during the GFC and the SDC. This activity could be the result of incentives given to companies to access debt for covering liquidity requirements during the crisis, as Fasano et al. (2022) and others point out. Following the Covid crisis, the traditional negative trend is verified. Our findings provide new horizons for research into firms’ financial life cycles during the pandemic due to the forthcoming access to further data over the next few years for more complete analysis.