On the Relative Importance of Corporate Working Capital Determinants: Findings from the EU Countries

The corporate finance literature traditionally abounds in both theoretical discussion and empirical research concerning financing and long-term investment decisions. Managing short-term resources appears to be a much less remarkable issue, despite this resource’s significant share of a firm’s balance sheet and the time and effort required to manage the current assets and liabilities. This article provides insights into the relative importance of the selected working capital determinants from the European Union perspective. The determinants considered in the study include both external and internal factors, specifically the country in which a company operates, its industrial classification and the firm size. Using more than 10,000 aggregated observations from a sample of firms from 13 industries, 9 countries and 3 group sizes, covering the period 2000-2009, the findings provide evidence that corporate working capital is most affected by country-specific factors, followed by industrial factors and firm size.


Introduction
The problem of working capital (WC) determinants is crucial from the managers' perspective because they invest a significant amount of time and effort in searching for an optimal balance between liquidity and profitability and, consequently, between risk and return. WC management, which involves monitoring each component and minimizing deviations from the target level, is a complicated and time-consuming process (Appuhami, 2008;Kim & Srinivasan, 1991;Lam-berson, 1995). The deficiencies in knowledge regarding WC determinants may lead to the insolvency and bankruptcy of firms whose financial managers fail to effectively plan and control current assets and liabilities (Rafuse, 1996). Despite its importance for corporate health (Filbeck & Krueger, 2005), there is insufficient empirical evidence regarding the determinants of WC management, considering the combined effect of the main components: inventory, accounts receivable and accounts payable (Palombini & Nakamura, 2011).
In contrast to the richness of both theoretical and empirical studies on capital structure and its nearly countless determinants (Rajan & Zingales, 1995), the theories of WC are much less developed; in addition, as Palombini and Nakamura (2011) conclude from an overview of corporate finance literature, there are no robust and widely accepted theories explaining the WC management. According to Saarani and Shahadan (2012), the nearest relevant theory is the Pecking Order Theory of debt developed by Myers and Majluf (1984); however, this theory is meant to explain the internal and external factors affecting corporate financial leverage and not the use of short-term assets and liabilities.
The discussion regarding the factors that affect WC policy is complex. The majority of previous studies on WC management aimed at exploring its relation with corporate profitability by evaluating the influence of WC strategies on the value created for shareholders. Despite its importance for managers, there is little empirical research that attempts to prioritize WC determinants according to their significance. The objective of this study is to establish the hierarchy of the three factors that are commonly believed to impact WC, i.e., the country-and industryspecific factors and the firm size, and thus contribute to the corporate finance knowledge of short-term decisions. The research is based on a sample of firms of all sizes from 13 industries and 9 EU countries, and it covers the period 2000-2009. Because the efficiency of WC management affects the profitability and liquidity of the firm (Deloof, 2003) and, as a result, constitutes a fundamental part of the overall corporate strategy to create value for shareholders (Nazir & Afza, 2009) This study contributes to the corporate finance literature in several ways. First, it extends the empirical work on WC determinants by considering a number of European countries that are analyzed in a comparative manner. Although the topic has previously been explored on multiple occasions in other markets, the studies usually consist of single economies and not a complex, integrated area. Second, due to the easily accessible data, the majority of studies in the field focus on large public companies, whereas this study includes private companies of various sizes, including SMEs, which usually form the core of most economies. Third, many studies adopt an approach that verifies the statistical significance of potential WC determinants.
Although such verification is useful and informative, this study goes beyond that scheme by attempting to prioritize the three determinants according to their relevance. Finally, the methodology used for this purpose is intuitively appealing and communicative because the classification process is one of the most common, simple and effective methodologies, thus enabling recognition of the reality.
Country, industry and size as working capital determinants -review of the literature Corporate decisions concerning WC can be affected by a number of factors of both external and internal character. One such factor is the impact of corporate financing decisions. In accordance with the Pecking Order Theory of capital structure in the context of the WC policy, companies with a higher financial leverage choose a more aggressive WC strategy, which includes tightening credit conditions for customers and inventory reduction, to provide internal financing and avoid issuing debt and equity. The negative relation between the firm's debt level and its WC is commonly noted in the literature (Chiou, Cheng & Wu, 2006;Nazir & Afza, 2008;Palombini & Nakamura, 2011).
The country specificity is a widely recognized and accepted factor for differentiating capital structure across firms from different countries. There are a number of country-specific factors that can influence corporate financing strategy (Bancel & Mittoo, 2004;Booth et al., 2001;Claessens, Djankov & Nenova, 2001;Demirgüç-Kunt & Maksimovic, 1999;Jõeveer, 2013), including political aspects, economic growth, capital market development and, in particular, the legal and institutional environments explored by La Porta et al. (1997). Electronic copy available at: https://ssrn.com/abstract=2548442 On the Relative Importance of Corporate Working Capital Determinants: Findings from the EU Countries If corporate capital structure depends on the country where a firm operates and if the WC policy is affected by the financial leverage, country-specific factors may also impact WC management. Surprisingly, however, to the best of the author's knowledge, empirical evidence on the relation between WC and national characteristics is missing from corporate finance literature.
However, as far as the other two types of factors are considered, i.e., the industry and size, the literature provides plenty of evidence on these factors' importance regarding WC, although opinions on their significance vary between researchers.
One of the earliest attempts to find a significant relation between industry and WC is the study by Nunn (1981), who used several industry variables, such as industry export, industry imports and industry concentration. After splitting WC into permanent and temporary, the author solely examined the permanent portion of WC, which does not fluctuate with short-run changes in the business activity. The study was based on a U.S. database from 1971 to 1978 and included product-line firms in a variety of industries.
The industry dependence of WC was also found by Hawawini, Viallet and Vora (1986), who examined a sample of 1,181 firms from 36 industries over a period of 19 years. The authors confirmed a significant and persistent industry effect on a firm's investment in WC.
Their results are also consistent with the concept that firms adhere to definite industry benchmarks when setting their WC policies. For instance, WC strategies of manufacturing firms are significantly different from service firms because the former usually carry substantial inventory levels, whereas the latter carry virtually no inventory.
Industry-wise differences in the level of aggressiveness with respect to WC investment over time were also reported by Weinraub and Visscher (1998).
Their study included ten diverse industry groups to examine the relative relation between their aggressive (conservative) WC policies. Regarding the degree of aggressive asset management, the authors concluded that industries had distinctive and significantly different policies. In addition, industry policies concerning the relative degree of aggressive liability management were also found to differ significantly, but not to the same extent. Their study also showed a negative cor-relation between industry asset and liability policies.
Thus, when relatively aggressive WC asset policies are followed, they are balanced by relatively conservative WC financial policies.
Industry significance in terms of WC was also found in a study by Filbeck and Krueger (2005) Similar to the industry effect in WC management, the effect of size has also received attention of many authors. These authors are often the same who analyze industrial factors, and this effect is noted in their research papers. Most find firm size to be significant in terms of its impact on WC.
The direct correlation between the WC requirement and size is supported by Petersen and Rajan (1997), who claimed that firms may be financed by their suppliers rather than by financial institutions. The authors focused on small firms whose access to capital markets may be limited and found evidence suggesting that firms use more trade credit when credit from financial institutions is unavailable. Moreover, firms with better access to credit offer more trade credit. Padachi (2006) also found WC management of particular importance to the small business. According to the author, due to the limited access to the long-term capital markets, these firms tend to rely more on owner financing, trade credit and short-term bank loans to finance their investment in cash, accounts receivable and inventory (Chittenden, Poutziouris & Michaelas, 1998;Saccurato, 1994).
The efficiency of a company's WC management was also found to be significantly influenced by firm size in a previous study by Kieschnick et al. (2006), although the direction of the effect is not obvious. The authors suggested two alternatives: either larger firms may require larger investments in WC because of their larger sales levels, or larger firms may be able to use their size to build better relationships with suppliers that are necessary for reductions in WC investments.
Supply chain management practices require a great deal of coordination between companies and are usually easier for a larger firm to implement than they are for a smaller one. Thus, firm size is likely to influence the efficiency of a firm's WC management; in addition, the empirical evidence shows a positive correlation between the inefficiency of a firm's WC management and a firm's total assets used as a proxy for its size.
The recent findings by Hill et al. (2010) show that the WC requirement varies directly with lagged firm size and that this association is significant. Similar to other researchers, the authors interpreted the relation as size represents capital market access. Thus, smaller firms are more limited in their choices for financing a positive WC requirement because they are less able to issue commercial papers or obtain lines of credit.
The same reasoning is followed by Opler et al. (1999), who indicated, in their research examining corporate cash holdings, that cash and size are inversely related because large firms have less need to hold cash as they have better access to short-term debt markets. Firms that have the greatest access to the capital markets, i.e., large firms and those with high credit ratings, tend to hold lower ratios of cash to total non-cash assets. These results are consistent with the view that firms hold liquid assets to ensure that they will be able to invest when cash flow is insufficient, relative to investment, and when outside funds are too expensive. Consequently, smaller firms will monitor their operating WC strategies more closely because they have fewer alternatives available to finance the WC relative to larger firms.
Firm size was also one of the factors explored in the study by Chiou et al. (2006) in terms of their impact on WC management of the firms listed on the Taiwan Stock Exchange. The study is one of the few whose results did not provide evidence for the influence of the firm size on WC management. Firm size was also found to be insignificant by Nazir and Afza (2008), who explored the factors that determine the requirements of WC management with reference to Pakistani listed firms.
As is clear from the above review, the industrial influences and the effect of firm size were the subject of multiple studies aiming to evaluate their impact on corporate WC. However, the reported results do not provide information on the relative importance of the factors considered because the majority of research is limited solely to identifying the significance of a given factor, possibly with the direction of its impact on WC.
The authors of the discussed research papers did not attempt to prioritize the analyzed factors in terms of the importance of their impact on WC management.
The results generally focus solely on determining the statistical significance of each variable in the context of the WC or its components.
The lack of inference regarding the relative importance of the effect of industry, country and size makes On the Relative Importance of Corporate Working Capital Determinants: Findings from the EU Countries it useful to expand the research to fill this gap and establish the hierarchy of the factors in question.

Hypotheses, data and methodology
The main objective of the study is to evaluate the impact of the country effect, the industry effect and the size effect in the corporate WC ratios in selected EU countries. The intended result of the analysis is, therefore, to determine which of these factors has the greatest influence on WC policy. As a result, the study should provide a hierarchy of the factors according to the strength of their impact on the WC. To solve this research problem, which can be defined as the assessment of the relative importance of the three effects, the analysis is conducted in three sections: across countries, across industries and across size groups.
The hypotheses to be verified matches pairs of factors, which are subject to a comparative analysis in terms of their impact on the WC. The pairs are as follows: • country-specific and industry-specific factors, • industry-specific and size-specific factors, and • country-specific and size-specific factors.
For example, the prevalence of the country factors over the industrial factors would mean that companies from different industries in the same country are characterized by a larger mutual similarity in terms of WC than companies in the same industry but from different countries. The prevalence of the industrial factors over the factors related to the size of the company would be associated with a greater cross-industry diversity of corporate WC than across different size groups. However, a firmly uniform diversity of the WC ratios in the three cross-sections would make it difficult to identify the dominant factor accurately and prioritize the others. and Portugal. Table 1 shows the industries covered by the study and the three-letter symbols assigned to each sector used in the following part of the paper.

NACE Section Symbol
According to the Banque de France (2012)  of the population is usually quite high (more than 70% on average), it is much lower for some countries and is even unknown for others, such as Poland.
The harmonized and aggregated data from the an- The ratios used in the analysis are continuous variables, which is why they may be analyzed using descriptive statistics, including the mean value, minimum, maximum and standard deviation. The descriptive statistics for the total sample are presented in Table 3.
It is also relevant and informative to examine the basic statistics of the ratios by categories, i.e., by year, and particularly, by country, industry and company size, as shown in  ner, 1972;Helg et al., 1995;Sell, 2005).
The initial phase of the empirical research is the analysis of the descriptive statistics of the WC ratios across countries, industries, size groups and years. It is aimed at the preliminary recognition of the WC diversity in the above cross-sections and at detecting basic regularities within the population.   In the event of finding differences in the ratio means among countries, industries, and (or) size groups, it should be established whether these differences are statistically significant. Then, the analysis of variance (ANOVA) is applicable as a method of studying observations that are dependent on one or more factors acting simultaneously. These factors are also known as grouping or manipulative variables. The analysis of variance (Fisher, 1954) allows us to assess the significance of differences between many means and explains the probability with which the considered factors may be the reason for the discrepancies between the observed group means. If the means differ significantly from each other, it can be intuitively concluded that the analyzed factor affects the dependent variable.
The heterogeneity of the objects from the examined population and some of the similarities found between them imply the need to organize these objects by classifying them according to certain criteria.
The idea of classification can be defined as a process of linking objects into categories (called clusters) based on their properties. Therefore, the grouping procedure is the next step of the analysis. One of the many clustering methods that allows us to extract internally coherent groups of objects is k-means grouping, which aims at partitioning observations. The partitioning is performed by creating k different, possibly distinct, clusters that are formed by relocating objects among these clusters to minimize the within-group variance while maximizing the between-group variance (Wishart 2003).
The following sets of binominal objects were subject to the k-means grouping procedure: • industries in countries -in individual size groups separately and in all size groups overall, • size groups in countries -in individual industries separately and in all industries overall, • size groups in industries -in individual countries separately and in all countries overall.
The advantage of the k-means algorithm is the ease of application, even with large data sets. In addition, the target number of clusters must be determined a priori, which can be helpful when that number is based on certain criteria.

Results
A glance at the descriptive statistics by year, country, industry and size ( Thus, it would be particularly interesting to analyze the population across these three cross-sections.
The one-way ANOVA procedure was conducted in four sections, where the qualitative predictors were country, industry, size and year. The discrimination power of the ratios can be analyzed based on the F statistic and probability p calculated for the entire data set, as presented in Table 5.        Table 7. Summary of the cluster analysis results of size groups in countries -the number of clusters of a national character (C), size character (S), and unspecified (C/S) Note: The table presents a synthetic summary of the k-means clustering results of binominal objects (size groups in countries), which were grouped into 9 clusters (corresponding to the number of countries analyzed). The procedure was carried out for all industries overall and for each industry separately, as indicated in each row. Source: Author's calculations based on the Banque de France (    Theoretically, the examined countries represent bank-oriented financial systems. However, many empirical findings tend to question the importance of the financial system, arguing that the role of banks as capital providers decreases systematically (Corbett & Jenkinson, 1996;Mayer, 1988;1990;Mayer & Alexander, 1990;Edwards & Fischer 1994

Appendix B. K-means grouping results for industries in countries (average for all size groups, 13 clusters)
Note: The table presents the content of each cluster resulting from the k-means grouping of binominal objects (industries in countries) into 13 clusters (corresponding to the number of industries analyzed) for all size groups overall. The first two letters in each item refer to the country, and the last three letters indicate an industrial sector within this country. Source: Author's calculations based on the Banque de France (2012) On the Relative Importance of Corporate Working Capital Determinants: Findings from the EU Countries

Appendix D. K-means grouping results for size groups in industries (average for all countries)
Note: The table presents the content of each cluster resulting from the k-means grouping of binominal objects (size groups in countries) into 9 clusters (corresponding to the number of countries analyzed) for all industries overall. The first two letters in each item refer to the country, and the last one indicates the size group within this country. Source: Author's calculations based on the Banque de France (2012) Note: The table presents the content of each cluster resulting from the k-means grouping of binominal objects (size groups in industries) into 13 clusters (corresponding to the number of industries analyzed) for all countries overall. The first three letters in each item refer to the industry, and the last one indicates the size group within this industry. Source: Author's calculations based on the Banque de France (2012)