Financing of Entrepreneurial Firms in Canada: Some Patterns

Abstract

This article analyzes the patterns of financing for entrepreneurial firms in Canada. We compare the predictions of major theories of entrepreneurial finance and some more recent ideas (e.g., crowdfunding-related ideas/theories) with empirical evidence. Regression and correlation analyses were used to analyze the connections between firms’ financing choices (e.g., debt/equity ratio) and different variables such as firm age, firm owner origin, and the fraction of intangibles assets. We found strong evidence that the financing choices of entrepreneurial firms in Canada are consistent with flexibility theory and credit rationing theory. We did not find evidence that taxes play a significant role in explaining these choices. We also found that the likelihood of using crowdfunding is consistent with local bias ideas and internet access. We also provide an overview of literature related to entrepreneurial financing in Canada and discuss its major challenges and directions for future research.

1. Introduction

In this article, we analyze the patterns of financing for entrepreneurial firms in Canada. Financing is an important and puzzling topic for large corporations (see, for example, a survey of managers by Graham and Harvey in 2001) as well as for entrepreneurial firms (Jõeveer 2013). Several theories that explain the ideas of firm capital structure and financing choice exist, including the flexibility theory of financing innovations, asymmetric information, credit rationing and the life cycle theory (for a review, see, for example, Harris and Raviv 1991; Klein et al. 2002; Miglo 2011). Firstly, most of these theories do not have unanimous empirical support (see, e.g., a discussion in Frank and Goyal 2003). Some of these theories find some support in some countries but not in others (see, e.g., de Jong et al. 2008; Jõeveer 2013)1. Secondly, the implications and relative importance of these theories are different for corporations and entrepreneurial firms (see, e.g., Frank and Goyal 2003; Lee et al. 2015). Thirdly, in recent years, some new theories that are focused on entrepreneurial firms (see, e.g., Robb and Robinson 2012) have been offered. Fourthly, debates still continue about which theory is the dominant one in the area of firm financing. For large firms, the trade-off theory and the pecking-order theory have emerged as the most important ones (see, e.g., the debates in Graham and Harvey 2001; Miglo 2016). However, what theories are more important for entrepreneurial firms? Finally, in the last decade or so, some new ways of financing entrepreneurial firms (such as crowdfunding) and several new ideas about these types of financing have been developed. For all these reasons, the topic of financing for entrepreneurial firms remains interesting and important.

Several articles address the capital structure choice by large corporations in Canada (see, e.g., King and Santor 2008; Gill and Mathur 2011). The financing of entrepreneurial firms has been studied in several articles that focus on some specific types of financing (e.g., Cumming and MacIntosh 2003, 2006; Suret 2008 (focused on venture capital finance)). An analysis of the effect of different theories on the financing choices of entrepreneurial firms that takes into account all types of financing, as well as a comparison of theories’ relative importance, has not been done. At the same time, Canada is one of the top countries in terms of developing new ways of financing, such as crowdfunding2, as well as one of the best countries in terms of entrepreneurial support3. In this article, we aim to analyze the implications of the main theories of financing with regard to entrepreneurial firms in Canada.

Below, we briefly describe the main theories of financing and formulate the hypothesis of our research.

Signalling by risk-bearing (Leland and Pyle 1977) predicts that the good quality entrepreneur would keep a higher fraction of shares in his/her company than the low-quality entrepreneur. It assumes that firms have private information about the quality of their projects, and on the other hand, entrepreneurs are risk-averse. By holding a relatively high fraction of equity, the entrepreneur sends a signal to market participants that the firm has good quality projects and that he/she is ready to bear the risk of these projects.

The flexibility theory (Diamond 1991) suggests that if a firm has too much debt or it does not have any credit experience, it will be harder for it to obtain loans when necessary. Firms, therefore, preserve debt capacity or hold back on issuing debt because they want to maintain flexibility. Firms maintain excess debt capacity or larger cash balances than warranted by current needs in order to meet unexpected future requirements. The flexibility theory predicts that firms with a lot of potential investment and growth opportunities should have a lower debt/equity ratio. While maintaining this financing flexibility has value to firms, it also has a cost; the excess debt capacity implies that the firm is giving up some value and has a higher cost of capital.

The credit rationing idea suggests that if an investment yields large returns, the firm’s owners capture most of the gains. If, however, the investment fails, debt holders bear the consequences. As a result, the firm’s owners may benefit from investing in high-risk projects, even if the projects are value-decreasing. This leads to a decrease in the value of debt and reduces the incentive to provide loans when the investment choice is difficult to monitor, especially in the case of start-up firms. In some cases, it leads to the credit rationing phenomenon (Stiglitz and Weiss 1981) when there is no equilibrium for bank loans, even if a firm has a positive net present value (NPV) project available. The main implication of the credit rationing idea is that banks may refuse to provide a loan if the uncertainty regarding the firm’s projects is very high, which is often the case for small or start-up companies.

In contrast to dividends, interest paid on debt reduces the firm’s taxable income. Debt also increases the probability of bankruptcy. Trade-off theory suggests that capital structure reflects a trade-off between the tax benefits of debt and the expected costs of bankruptcy (Kraus and Litzenberger 1973). As the expected bankruptcy costs increase, the advantages of using equity also increase. This result has several interpretations. Small firms that are less diversified and have a higher default risk should use less debt. Tangible assets suffer a smaller loss of value when firms go into distress. Hence, firms with more tangible assets should have higher leverage compared to those that have more intangible assets, such as research firms. Growth firms tend to lose more of their value than nongrowth firms when they go into distress. Thus, the theory predicts a negative relationship between leverage and growth. Higher taxes lead to the greater tax advantage of using debt. Hence, firms with higher tax rates should have higher debt ratios compared to firms with lower tax rates. Inversely, firms that have substantial nondebt tax shields, such as depreciation, should be less likely to use debt than firms that do not have these tax shields. If tax rates increase over time, debt ratios should also increase. Debt ratios in countries where debt has a much larger tax benefit should be higher than debt ratios in countries whose debt has a lower tax benefit.

The life cycle theory of capital structure (e.g., Damodaran 2003) predicts that firms in the development stage will abstain from issuing risky debt and will instead issue equity. Firms in the growth stage will begin generating positive earnings. Accordingly, these firms rely on debt financing to fund their growth options as they face less financing constraints and as they expect to repay their debt with growing future earnings. Thus, firms in the growth stage tend to have high leverage ratios. Firms in the maturity stage generate large cash flows from assets already in place and rely mainly on self-financing for their investment needs. They are more concerned with servicing the debt they raised during the growth stage than they are with issuing more debt because they expect future cash flows to deteriorate. Accordingly, mature firms prefer to maintain moderate debt levels.

In recent years, Canada has been quite successful in developing new forms of financing for entrepreneurial firms, including crowdfunding. This area belongs to FinTech, which refers to innovative technologies used to improve the financial sector (Das 2019). Crowdfunding is a form of fundraising usually performed online, where firms raise funds from a large number of investors/funders (see, e.g., Ahlers et al. 2015). In the literature, it has been suggested that crowdfunding relaxes geographic constraints on fundraising, which inhibit venture capital and angel financing (Agrawal et al. 2010). By volume of these sources of finance, Canada is consistently ranked among the top 10 countries (see, e.g., Huang et al. 2019)4. Research in these areas is quickly growing.

The main aim of this paper is to gain new scientific knowledge about the patterns of financing for entrepreneurial firms in Canada. In particular, we will look at different variables describing the financing strategies of these firms (such as the sources of finance used and debt/equity ratios) and connect them with different features of these firms, such as size, age of the owner, and asset structures. The key research question for us is to identify what theory of financing is able to highlight the behaviour of entrepreneurial firms in Canada. Based on the analysis of major theories of financing for entrepreneurial firms described previously, we will analyze the following hypotheses.

Hypothesis 1 (H1).

Smaller firms have a lower percentage of approved requests compared to larger firms.

Hypothesis 2 (H2).

Entrepreneurs born outside Canada have a lower approval rate.

Hypothesis 3 (H3).

Younger firms have a lower approval rate compared to mature firms.

Hypothesis 4 (H4).

Firms in knowledge-based industries and industries with a high fraction of intangible assets have lower debt/equity ratios compared to other industries.

Hypothesis 5 (H5).

Firms with higher expected bankruptcy costs have lower debt/equity ratios than firms with lower expected bankruptcy costs.

Hypothesis 6 (H6).

Firms with higher tax rates have higher debt/equity ratios than firms with lower tax rates.

Hypothesis 7 (H7).

Younger firms have lower debt/equity ratios than older firms.

Hypothesis 8 (H8).

The likelihood of using crowdfunding is positively correlated with the provincial population.

Hypothesis 9 (H9).

The likelihood of using crowdfunding is positively correlated with internet access.

The rest of the paper is organized as follows. Section 2 provides a literature review. Section 3 describes the methodology and data sources. Section 4 describes the results of our analysis. Section 5 provides concluding remarks, discusses the limitations of our analysis, directions for future research, as well as the state of entrepreneurial finance education in Canada.

2. Literature Review

Existing literature on traditional debt and equity financing for entrepreneurial firms in Canada usually focuses on explaining the problems of external financing for entrepreneurial firms or why interest rates on loans are typically higher for small- and medium-sized enterprises (SMEs) than for large firms5. For example, Beck et al. (2008) analyzed the financing patterns of firms in 48 countries, including Canada, and found that the ability of smaller cash-constrained firms to obtain external financing, including bank financing, was more limited as compared to larger firms.

Some literature focuses on venture capital financing for entrepreneurial firms. Historically, venture capital financing reached its peak in 2000, and afterwards, its growth rates were not very impressive. One factor behind this pattern was the great recession of 2008/2009. Furthermore, in Canada, the venture capital industry has problems such as relatively low listing requirements. This reduces the incentive for SMEs to partner with venture capital firms on the one hand, and on the other hand, it creates a lot of asymmetric information about SMEs (Carpentier and Suret 2010), which creates difficulties in raising public funds and a reduced interest from venture capital firms. Another interesting aspect of the venture capital industry in Canada is the large presence of labour-sponsored funds (LSVCF)6. Historically they played an important role in the creation of the venture capital industry, especially in Quebec. However, it seems like their institutional structure needs some major revisions in order to move the venture capital industry forward (Cumming and MacIntosh 2003, 2006; Cumming et al. 2007; Lerner 2009; MacIntosh 2012; Suret 2008). There have been some improvements in the venture capital industry during the last 10 years. The government implemented a venture capital support program in 2013 that included deploying CAD400 million in new capital over the next 7 to 10 years to reinvigorate the venture capital sector in Canada7. As a result, we observed a sharp increase (2014/2015) in the amounts of venture financing. Additionally, the growth of angel financing and accelerators is observed in most OCDE countries, including Canada.

Crowdfunding is a new way of financing for entrepreneurial firms that has become very popular around the world, including in Canada, in the last 10 years or so. It is a highly growing area of interest among practitioners and theorists (see, e.g., Ahlstrom et al. 2018). As we write this article, the number of empirical papers significantly exceeds the number of theoretical papers. Rainey et al. (2017) discussed major types of crowdfunding and their growth before focusing on equity crowdfunding as a method of financing for small businesses and start-ups in light of the recent legislative changes related to equity crowdfunding in both the United States (US) and Canada. The authors covered the current global market and both countries’ new legislation, as well as the specific challenges and benefits of equity crowdfunding. They also touched on what the new trends in crowdfunding could mean for impact investing, with a spotlight on the millennial generation’s investing patterns8.

For large companies, the implications of different theories of financing and capital structure have been analyzed, for example, by Gill and Mathur (2011). In this article, we aim to analyze the implications of the main theories of financing with regard to entrepreneurial firms.

We seek to make several conceptual and empirical contributions. Firstly, we hope to make an important contribution to our knowledge about the theories of financing and capital structure choice theories (Harris and Raviv 1991; Cumming et al. 2019). This topic remains controversial and puzzling for large companies (Graham and Harvey 2001) as well as for entrepreneurial firms (Bhaumik et al. 2015). Secondly, we would like to help fill the research gap related to the patterns of financing of entrepreneurial firms in Canada. Many previous studies have focused on some specific types of finance for these firms (e.g., private equity (Cumming et al. 2007)) but not on a systematic analysis of these patterns. Thirdly, this article contributes to the growing line of research in finance and entrepreneurship that uses surveys (see, e.g., Jude and Adamou 2018). The survey provided by Statistics Canada is quite unique and should help researchers with a lot of data about entrepreneurial firms’ access to finance, which, in many countries, is quite limited (Schmidt et al. 2017). Finally, this paper contributes to the entrepreneurship literature in general. The reason is that, as many studies argue and many surveys, including surveys we use, confirm, the financial activities of entrepreneurial firms are the key problem for the majority of these firms. For many of them, it is the key reason for failure. The problem of entrepreneurial firms is that they do not have a large number of assets, nor do they have a long credit history or liquid market for their shares. As a result, they do not have easy access to external sources of capital. Obviously, they do not generate a lot of profits, especially in the initial stages of their development, so the internal sources of financing for them are also limited. In these conditions, it is vital for these firms to understand the major theoretical ideas of financing, as well as the knowledge of how these ideas interact practically with available data in order to be as efficient as possible when dealing with different sources of financing and to increase the chances of their survival. In this regard, we also look at student education related to entrepreneurial finance in Canada. The quality of this education is crucial for developing entrepreneurial finance and, ultimately, for developing entrepreneurship in Canada (for similar ideas, see, e.g., Solesvik et al. 2014).

3. Methodology

We mostly use two sources of data. Firstly, we use OCDE data that compares entrepreneurial finance in Canada with other OCDE members9. Secondly, we use the Statistics Canada/Industry Canada data about the financial needs of small- and medium-sized businesses because most entrepreneurial businesses are found in this group10. Thus, we will use information about the financing of small- and medium-sized enterprises (SMEs) as a proxy for the financing experience of entrepreneurial businesses11.

Regression analysis (the ordinary least square model) and correlation analysis will be the methods used to determine the strength of the relationship between firm financing choices and other variables.

For example, to test H3, the formula for regression is

Debt/equity ratio = α + β₁ × ICT + β₂ × RD + β₃ × New + β₄ × C + ε,

where the dependent variable is the debt/equity ratio. The independent variables are the fraction of the firm’s total assets invested in communication and technology (ICT), research and development (RD) and new machinery (New), and the control variables (C) include different variables such as firm sales.

To test H7, the formula for regression is

Number of crowdfunding providers = α + β₁ × Population + β₂ × GDP/capita + β₃ × Market income/capita + β₄ × HC + β₅ × HI + β₆ × Entrepren + ε,

where the dependent variable is the number of crowdfunding providers in a province. The independent variables include provincial population (Population), GDP per capita (GDP/capita), market income per capita (Market income/capita), the number of households with a computer at home (HC), the number of households with access to the internet (HI) and a variable (Entrepren) that measures the level of provincial support for entrepreneurship (as a proxy, we used the international ranking of the province’s largest city). We normalized data using an approach similar to Beck et al. (2008).

In some cases where the available data were limited, comparison or qualitative methods were used.

4. Patterns of Financing for Entrepreneurial Firms in Canada

The main implication of the credit rationing idea (Stiglitz and Weiss 1981) is that banks may refuse to provide a loan if the uncertainty regarding the firm’s projects is very high, which is often the case for small or start-up companies. Typically, banks and other potential investors have more information about large companies.

This table shows the amounts of requested and approved debt financing of different types by Canadian SMEs in 2013. In most cases (as follows from lines 2–6 of

Table 1. Canadian small- and medium-sized enterprises (SMEs) debt financing.

				Total Amount Authorized-to-Requested, %
			Nonresidential Mortgages	Term Loan	Line of Credit	Credit Card	Overall Debt Financing
All SMEs	1 to 499 employees		85.5	88.0	85.2	91.5	86.1
Employment Size	1 to 4 employees		81.7	X	84.4	X	82.8
	5 to 19 employees		83.8	86.2	76.5	88.8	81.2
	20 to 99 employees		84.6	92.2	86.9	94.9	87.8
	100 to 499 employees		98.8	X	97.5	X	98.2
Industries	Agriculture, Forestry, Fishing and Hunting, Mining and Oil and Gas Extraction		96.8	93.2	92.3	90.9	93.9
	Construction		85.9	94.2	88.3	93.0	89.1
	Manufacturing		91.2	90.2	84.7	90.2	87.1
	Wholesale Trade		96.4	95.9	92.4	98.4	94.1
	Retail Trade		87.2	88.4	74.8	92.3	80.9
	Transportation and Warehousing		98.2	84.3	89.0	90.6	89.9
	Professional, Scientific and Technical Services		83.1	96.0	88.6	93.3	89.1
	Accommodation and Food Services		68.4	75.7	48.7	74.8	67.2
	Other Services		82.1	84.2	78.3	84.0	81.2
	Information and Cultural Industries, Real Estate and Rental and Leasing, Administrative and Support, Waste Management and Remediation Services, Health Care and Social Assistance, Arts, Entertainment and Recreation		79.1	74.9	88.3	92.3	82.0
	Special industry aggregations	Tourism	52.9	98.1	64.8	86.1	66.5
		Information and Communication Technologies	83.9	94.1	69.9	99.6	81.3
		Knowledge-Based Industries	49.5	68.8	81.6	83.1	75.5
Age of Business	2012–2014 (2 years or younger)		77.2	63.4	79.6	86.0	75.0
	2004–2011 (3 to 10 years old)		81.9	80.5	79.6	92.2	81.4
	1994–2003 (11 to 20 years old)		86.8	91.6	87.6	91.3	88.3
	Prior to 1994 (more than 20 years old)		87.7	94.8	87.0	92.4	89.0
Place of birth	In Canada		86.6	89.3	87.0	91.7	87.6
	Outside Canada		81.0	80.5	74.2	90.5	78.6

Source: IndustryCanada/Statistics Canada, Survey on Financing and Growth of Small and Medium Enterprises, 2014.

), smaller firms had a lower percentage of approved requests compared to larger firms. Similarly, firms in knowledge-based industries also had a lower approval rate (75.5%) compared to the SME average (86.1%). Additionally, younger firms had a lower approval rate than older firms (see section “Age of Business”), and entrepreneurs born outside Canada had a lower approval rate (see section “Place of birth”). It is reasonable to assume that in all these cases, banks have less information regarding the category of firms with lower approval rates than the category(ies) with higher approval rates. This provides strong support for our Hypotheses H1–H3.

These patterns of financing of Canadian SMEs are consistent with patterns in many other countries. For example, in the Euro area, access to finance and finance conditions appear to be consistently more favourable for large enterprises than for SMEs, with a smaller percentage of large firms reporting supply restrictions in the provision of bank loans, consistently higher rates of success and lower rejection rates and a considerably lower net percentage of large firms reporting an increase in interest rates and collateral requirements (See e.g., Hashi and Toçi 2010; OECD 2012).

Signalling by risk-bearing (Leland and Pyle 1977) predicts that the good-quality entrepreneur would keep a higher fraction of shares in his/her company than the low-quality entrepreneur. One can see an implication of the signalling idea in some cases discussed in Appendix A. For example, it is often the case for government funding or different grants for entrepreneurial firms: it often requires the owner to keep a significant fraction of the firm’s equity or to make additional investments in the firm’s equity. It can be used as a signal of an entrepreneurial idea’s quality. For example, one of the requirements of the microvoucher program in Alberta is that the entrepreneur provides 25% of financing using his/her own funds in order to obtain government financing for research and development investments (

Table A2. Major government programs.

Program	Main Features
Canada Small Business Financing (CSBF) Program	Term loans of up to CAD500,000 for acquiring real property and equipment and making leasehold improvements. The government is liable to pay 85% of eligible losses on defaulted loans registered under the program, which allows private-sector lenders to comfortably increase the amount of financing extended to small businesses. The program is supported by charging 3% above prime and a 2% registration fee paid by the borrowers. The repayment of the loan can be amortized over a period longer than 10 or 15 years.
Business Development Bank of Canada (BDC)	Loans up to CAD100,000. The business should be Canadian-based. For the duration of the COVID-19 crisis, the small business loan is offered at a 2.80% interest rate, which is BDC’s floating base rate of 4.55% (effective 31 March 2020) minus 1.75%. The interest rate is subject to change without notice. The loans are repaid over 60 months. A capital postponement is offered for the first 6 months, and the initial six payments are interest only. Commencing on the 7th month, the loan is repaid in 60 monthly payments, and all payments are due on the 10th day of the month.
CanExport	Funding is provided on a cost-sharing basis between the recipient and CanExport SMEs. The program reimburses up to 75 percent of eligible expenses; the applicant is responsible for the remaining 25% (in-kind contributions do not count toward the 25%)
Futurpreneur Canada (former Canada Youth Business Foundation)	Several different financing programs to support entrepreneurs aged 18 to 34, including one that provides start-up small business loans of up to CAD20,000 with a term over five years. Interest is charged at CIBC’s prime rate + 3.75%. Interest-only payments for the first year. Principal repayments are made in equal monthly instalments together with interest, over the remaining four years. No penalty for early repayment.
Aboriginal Business Canada	Grants of up to CAD99,999 for eligible individual Aboriginal entrepreneurs
Western Economic Diversification Canada (WD)	Several programs (e.g., Western Innovation Initiative, Community Futures Loan Program) to strengthen western innovation, business development and community economic development.
Alberta Micro Voucher Program	Eligible applicants can apply for up to CAD10,000, paid directly to the service provider, to cover eligible expenses charged by the service provider for the purpose of one or more of the following activities: New product research and development; design, engineering and prototype development; product testing and refinement; patent development (excluding patent maintenance fees); advanced market assessment or segmentation analysis; advanced business and/or marketing strategies; other technology development activities that will be considered on a case-by-case basis. The applicant pays a minimum 25% cash contribution of the total eligible project costs.

Sources: https://www.ic.gc.ca/eic/site/csbfp-pfpec.nsf/eng/la03089.html; https://www.bdc.ca/en/financing/business-loans/pages/small-business-loan-up-50k.aspx?gclid=CLqHjpuqjs0CFQyEaQodltAI7g; http://www.international.gc.ca/canexport/applicant-guide-requerant.aspx?lang=eng; http://www.futurpreneur.ca/en/get-started/financing-and-mentoring/spin-master-innovation-fund/?gclid=COjtvOKqjs0CFQsPaQodJKMGJw; https://www.aadnc-aandc.gc.ca/eng/1375201178602/1375202816581; http://www.wd.gc.ca/eng/259.asp; https://albertainnovates.ca/programs/micro-voucher/.

).

The flexibility theory suggests that firms maintain excess debt capacity or larger cash balances than warranted by current needs in order to meet unexpected future requirements.

Table 2. Capital structure of SMEs in different industries.

		R&D/Assets	(R&D + ICT * + New Machine + Edu)/Assets	(ICT + New Machine + Edu)/Assets	Total Debt Provided/(Total Debt + Total Equity)
All SMEs		0.101423	0.185788	0.084365	0.876402
Industries	Agriculture, Forestry, Fishing and Hunting, Mining and Oil and Gas Extraction	0.030194	0.09795	0.067756	0.851103
	Construction	0.024912	0.103518	0.078606	0.879258
	Manufacturing	0.107341	0.187031	0.07969	0.914535
	Wholesale Trade	0.078696	0.155541	0.076845	0.932882
	Retail Trade	0.019579	0.144089	0.12451	0.954592
	Transportation and Warehousing	0.069976	0.31067	0.240694	0.820551
	Professional, Scientific and Technical Services	0.358487	0.447588	0.089101	0.839725
	Accommodation and Food Services	NA	NA	0.0661	0.948222
	Other Services	NA	NA	0.034778	0.636527
	Health Care and Social Assistance, Information and Cultural Industries, Arts, Entertainment and Recreation	0.054745	0.121457	0.066712	0.736784
	Knowledge-Based Industries	0.255537	0.344665	0.089128	0.668598

Sources: Statistics Canada, Survey on Financing and Growth of Small and Medium Enterprises 2011. * ICT—investments in communications and technology.

and

Table 3. Regression results. The dependent variable is the total debt provided/total liabilities (2011) ratio.

Variables	(1)	(2)	(3)	(4)
Intercept	0.8849 (15.0750) ***	0.8386 (21.0297) ***	0.8348 (24.2261) ***	0.8019 (142.2934) ***
R&D	−0.4138 (−1.1011) **	−0.4138 (−1.1011) ***	−0.7642 (−1.9316) ***	−0.3617 (−5.5060) ***
ICT	−5.7091 (−2.9636) **	−5.7091 (−2.9636) **	−3.6529 (−1.7157) **	−6.0310 (−16.6178) ***
new machine	−0.5933 (−1.1839) **	−0.5933 (−1.1839) ***	−1.0699 (−2.0147) ***	−1.2679 (−16.3216) ***
Personnel cost		23.8033 (2.9661) **	22.9318 (3.3036) **	30.9827 (25.8864) **
Sales			0.0339 (1.5433) *	0.0441 (13.5520) *
Income				−0.1426 (−12.0323) **
Adj. R2	0.4160	0.7718	0.8304	0.9965
F-value	2.9002	7.7671	8.8370	384.4273

*** indicates significance at a 1% level, ** indicates significance at a 5% level, and * indicates significance at a 10% level.

demonstrate that firms that invest in RD, new machinery and ICT (i.e., firms with uncertain growth) have a smaller fraction of debt12. Additionally, the debt/assets ratio in knowledge-based industries, which by their nature require a lot of flexibility, is significantly below the average ratio among all SMEs, and, in fact, knowledge-based industries have one of the lowest ratios among all industries13. This analysis provides strong support for H4.

The trade-off theory suggests that capital structure reflects a trade-off between the tax benefits of debt and the expected costs of bankruptcy (Kraus and Litzenberger 1973).

Expected Bankruptcy Costs and Debt. As the expected bankruptcy costs increase, the advantages of using equity also increase. This result has several interpretations. Large firms should have more debt because they are more diversified and have a lower default risk (see, e.g., Adair and Adaskou 2015). Start-up and small firms should use less debt. Tangible assets suffer a smaller loss of value when firms go into distress. Hence, firms with more tangible assets, such as airplane manufacturers, should have higher leverage compared to those that have more intangible assets, such as research firms (Ozkan 1996). Growth firms tend to lose more of their value than nongrowth firms when they go into distress. Thus, the theory predicts a negative relationship between leverage and growth. Table 2 and Table 3 provide some evidence that is consistent with these predictions. Firms with high amounts of intangible assets (and respectively high indirect bankruptcy costs) have smaller debt/equity ratios. This supports the hypothesis H5.

Taxes and Debt. Higher taxes lead to the greater tax advantage of using debt. Hence, firms with higher tax rates should have higher debt ratios compared to firms with lower tax rates (see, e.g., Modigliani and Miller 1963; Devereux et al. 2017). Inversely, firms that have substantial nondebt tax shields, such as depreciation, should be less likely to use debt than firms that do not have these tax shields. If tax rates increase over time, debt ratios should also increase. Debt ratios in countries where debt has a much larger tax benefit should be higher than debt ratios in countries whose debt has a lower tax benefit. In Canada, the tax rate is lower for small businesses. This implies that there is less incentive to issue debt for tax-saving purposes.

From the above tables, we can see that for small businesses, the tax argument of capital structure does not have a strong confirmation. Otherwise, one should see a positive correlation between the tax rate and the debt ratio. One does not see this relationship when looking at data from different countries and different provinces in Canada. For example, from

Table 4. Debt and tax rates.

		Total Debt Provided/(Total Debt + Total Equity)	Average Debt/(Average Debt + Average Equity)	Small Business Tax Rate
All SMEs	1 to 499 employees	0.876402	0.370954
Region	Atlantic	0.877895	0.281993	14.3 *
	Quebec	0.908257	0.339092	15.49
	Ontario	0.884781	0.452786	15.5
	Manitoba	0.948693	0.468568	11
	Saskatchewan	0.896066	0.386107	13
	Alberta	0.79838	0.299392	14
	British Columbia and Territories	0.840542	0.313839	14.25 **

* Average among Nova Scotia, Newfoundland and Labrador and New Brunswick. ** Average among British Columbia and Northwestern Territories.

, Manitoba has smaller tax rates for small businesses than the Atlantic Provinces, while the debt ratio is lower in Manitoba. The correlation coefficients between debt ratios and small business tax rates are negative in

Table 5. Correlation coefficients (X–Y).

X	Y	Corr
Small business tax rate	Total debt provided/(total debt + total equity)	−0.0126
Small business tax rate	Average debt/(average debt + average equity)	−0.019

Sources: http://www.taxplanningguide.ca/tables/corporate-taxation-cpp-ei/table-1-business-income-eligible-sbd/. Statistics Canada, Survey on Financing and Growth of Small and Medium Enterprises 2011.

. As follows from

Table 6. International debt and tax rates for SMEs.

Year	2015		2014
Targeted Corporate Income Tax	Small Business Corporate Tax Rates		SME Financing Sources			Business Loans/(Business Loans + VC)
	Central Government	All Levels of Government	Unit	Business Loans, SME	VC Investments
Country
Belgium	24.25	24.98	EUR mil	109776	0.323408	0.99999705	VC + growth capital
Canada	11	15.19	CAD bil	93.7	2.4	0.97502601	VC + growth capital
France	15	15	EUR mil	219647	3234	0.98549001	VC + growth capital
Hungary	10	10	HUF mil	4831238	18759	0.99613216
Japan	15	21.42	JPY tril	251.7	0.117	0.99953538	VC + growth capital
Korea	10	12.2	KRW tril	522.43	1.6393	0.99687198
Netherlands	20	20	EUR bil	18	0.434	0.97645655
Spain	25	25	EUR bil, 2013	134	0.555	0.99587529
United States	15	19.92	USD mil	589772	50297	0.92141941	Growth capital

Sources: http://www.keepeek.com/Digital-Asset-Management/oecd/industry-and-services/financing-smes-and-entrepreneurs-2016_fin_sme_ent-2016-en#page118; http://stats.oecd.org//Index.aspx?QueryId=59543.

, the debt ratio is higher in Korea, for example, than in Canada, while the tax rates for small businesses are lower in Korea. The correlation coefficients are insignificant in

Table 7. Correlation coefficients (X–Y).

Y	X	Corr
Business Loans/(Business Loans + VC)	Small business corporate tax rates (Central Government)	0.0006
Business Loans/(Business Loans + VC)	Small business corporate tax rates (All levels of Government)	−0.0002

, although it is slightly negative between the small business tax rate (all levels of government) and the debt ratio. The fact that the tax argument does not have a lot of support among small businesses is consistent, for instance, with Kashefi-Pour et al. (2010).

The life cycle theory of capital structure (Damodaran 2003) argues that mature firms should have higher debt ratios compared to younger firms.

Table 8. Debt and firm age.

	Numbers (Average)	Total Debt Provided/(Total Debt + Total Equity)	Liabilities/Assets
All SMEs	1 to 499 employees	0.876402	0.493849
Age of Business	2009–2011 (2 years or younger)	0.442206	0.382821
	2001–2008 (3 to 10 years old)	0.753462	0.493482
	1991–2000 (11 to 20 years old)	0.902901	0.459491
	Prior to 1991 (more than 20 years old)	0.930078	0.515598

Sources: Statistics Canada, Survey on Financing and Growth of Small and Medium Enterprises 2011.

shows that young firms have lower debt ratios than older firms (H7), which is consistent with the life cycle theory.

Crowdfunding.

Table 9. Crowdfunding statistics for Canada.

	Number of Crowdfunding Service Providers, Jan 2019										Households Having
	Equity-Based Crowdfunding	Debt-Based Crowdfunding	Service-Based Providers	Royalty	Total	Total, %	Population	Population, % of Total	GDP Per Capita	Market Income Per Capita	A Home Computer	Internet Use from Home	Entrepreneurship Opportunities Rankings
Alberta	0	1	5	0	6	0.0984	4,067,175	0.1157	80,175	39,056	86.1	91.9	97
British Columbia	4	1	5	0	10	0.1639	4,648,055	0.1322	59,066	34,426	88.8	93.2	37
Manitoba	0	0	0	0	0	0.0000	1,278,365	0.0364	53,708	28,853	79.6	86.1
New Brunswick	0	0	0	0	0	0.0000	747,101	0.0213	47,950	26,992	79.8	88.3
Newfoundland and Labrador	0	0	0	0	0	0.0000	519,716	0.0148	63,243	29,646	79	87
Northwest Territories	0	0	0	0	0	0.0000	41,786	0.0012	105,214	41,324
Nova Scotia	0	0	0	0	0	0.0000	923,598	0.0263	46,226	28,672	77	85	223
Nunavut	0	0	0	0	0	0.0000	35,944	0.0010	89,698	26,174
Ontario	13	6	18	0	37	0.6066	13,448,494	0.3826	59,879	34,033	85	89.3	24
Prince Edward Island	0	0	0	0	0	0.0000	142,907	0.0041	45,539	27,043	81.6	88.1
Quebec	2	1	4	1	8	0.1311	8,164,361	0.2323	52,384	29,689	82.3	85.9
Saskachewan	0	0	0	0	0	0.0000	1,098,352	0.0312	69,373	31,724	77.8	88.4
Yukon	0	0	0	0	0	0.0000	35,874	0.0010	75,002	39,708
Total	19	9	32	1	61		35,151,728

Sources: https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1110022801&pickMembers%5B0%5D=1.5; https://www.startupblink.com/; https://en.wikipedia.org/wiki/Population_of_Canada_by_province_and_territory.

presents the statistics of crowdfunding data for Canada by provinces.

The regression results are reported in

Table 10. Regression results. The dependent variable is the number of crowdfunding providers (2019) ratio.

Variables	(1)	(2)	(3)
Intercept	−0.0910 (−0.7535) *	−1.4917 (−1.2905) ***	0.5889 (0.6729) **
Population	1.4026 (7.7045) ***	1.7009 (5.064) ***	1.0872 (4.2437) ***
GDP/capita	6.4698 × 10−7 (0.4431)	−4.4505 × 10−6 (−0.7015)	9.1594 × 10−6 (1.7314)
Market income/capita	5.5746 × 10−7 (0.1105)	5.8075 × 10−6 (0.2473)	−0.0001 (−2.2404)
Households having a home computer		−0.0272 (−1.3228)	−0.0004 (−0.0343)
Households having Internet use from home		0.0421 (1.5887) *	0.0017 (0.0926) *
entrepreneurship opportunities rankings			0.0967 (3.3395) **
Adj. R2	0.8459	0.8384	0.9543
F-value	22.9649	10.3405	32.3468

*** indicates significance at a 1% level, ** indicates significance at a 5% level, and * indicates significance at a 10% level.

. The results show that the number of crowdfunding providers is positively associated with the provincial population, internet access and entrepreneurial support. The relationship with GDP per capita and the market income per capita is insignificant. In general, the regression results are very strong. Ideally, raising funds via the internet should remove geographical barriers for firms (Agrawal et al. 2010). However, the analysis suggests that provincial features are important for crowdfunding data. It may be related to the cost and efficiency arguments. First, consider them on the supply side. From the providers’ point of view, the population size provides an indication of potential economies of scale for their business. Note that crowdfunding regulation in Canada is two-fold: there is the federal level and the provincial level as well. As we discussed in the previous section, some provinces are more advanced in terms of regulation on crowdfunding, e.g., Ontario. Hence, providers of crowdfunding services understand that their services depend on the regulations, and, therefore, the provincial population is a strong factor for them. Provinces with a small population do not have a significant number of providers. Secondly, on the demand side, the population can reflect the potential amount of feedback and benefits funders can receive from a platform (Belleflamme et al. 2014): a large platform implies more interactions between funders and, therefore, more benefits for many of them (see, for example, Belleflamme et al. 2015). GDP per capita does not have a significant impact, probably because the difference between provinces is minimal. Perhaps it also reflects the idea that crowdfunding is suitable for different types of investors, including small and large ones. Entrepreneurial reputation has a positive impact on the number of crowdfunding providers. These results also suggest that cost and efficiency are important factors for crowdfunding. This also contributes to recent debates about local bias in crowdfunding (see, e.g., Hornuf et al. 2020).

Limitation Analysis

The limitations of our analysis are mostly related to data availability. Statistics Canada conducts an entrepreneurs’ survey every 3–4 years. If these data were available on an annual basis, this would lead to more precise results. Secondly, much more data is needed to analyze the patterns of crowdfunding. The data are very limited as of now. Much more data are expected in the future, including features of the firms conducting different types of crowdfunding campaigns (including their accounting and financial data), and not only the campaign features themselves. In general, it is known that small business data are more limited compared to large public companies. Nevertheless, recent developments in online accounting and other areas of Fintech will hopefully reduce the cost of collecting information for small firms, which can lead to more data about these firms in the future. Statistics Canada provides an enormously helpful service for researchers by conducting these surveys, but, in the future, it would be good to have more detailed information about the businesses and their operations.

5. Conclusions

This article analyzes the patterns of financing for entrepreneurial firms in Canada. We compared the predictions of the major theories of entrepreneurial finance (the flexibility theory of capital structure, the asymmetric information theory, the credit rationing theory, and the life cycle theory) with empirical evidence. We found, for example, that the flexibility theory and the credit rationing theory are consistent with many patterns of financing of SMEs in Canada. On the other hand, the tax theory of capital structure does not seem to play a significant role for SMEs, as opposed to large companies, but it may affect the choice of securities by firms that use venture capital. New forms of financing, such as crowdfunding, are on the rise. Ideally, raising funds via the internet should remove geographical barriers for firms. However, the analysis suggests that provincial features such as population size are important for crowdfunding data. It suggests that cost and efficiency are important factors for crowdfunding, and future research should continue aiming at revealing the most important factors that can help reduce the costs and improve the efficiency of crowdfunding campaigns.

As was mentioned, credit rationing plays a significant role in explaining the patterns of financing for entrepreneurial firms in Canada. Hence, debt financing is strongly affected by such factors as firm age, its size and firm owner’s origin. In addition, small business interest rates margins are higher in Canada compared to average numbers from OCDE countries. As an avenue for future research, we think more ideas should be received regarding debt financing developments for entrepreneurial firms. This is consistent with a new wave of interest towards debt financing among theorists and practitioners (see, for example, Robb and Robinson 2012; Miglo 2016, chp. 8; Miglo 2020). Potential developments in this area can be related to improvements in intellectual property rights and patents and the usage of patents as collateral for loans, which is consistent with observed patterns in other countries (Gallini and Hollis 2019; Mann 2018; Bellucci et al. 2014). With regard to Canada, note that some researchers have pointed out that the Canadian ratio of patents to GDP is relatively low compared to other developed countries (Gallini and Hollis 2019) and that Canadian researchers often participate in joint research with researchers from other countries (mostly US) but do not own the intellectual property rights of much of the research. Gallini and Hollis (2019) have suggested several directions for potential improvements in this area of intellectual property regulation. Given our previous point that intellectual property and patents are directly related to debt financing (including SMEs that are responsible for a large part of innovative activities), this can be the next step in improving debt financing for SMEs in Canada.

As was previously mentioned, although crowdfunding is a new and potentially more efficient way of financing for entrepreneurial firms as compared to traditional financing, the analysis shows that cost and efficiency are important factors for crowdfunding and research should continue aiming at revealing the most important factors that can help to reduce the costs and improve the efficiency of crowdfunding campaigns. Perhaps, in the future, the focus of research should be on factors such as asymmetric information (Miglo and Miglo 2019), moral hazards (Strausz 2017; Chemla and Tinn 2019; Schwienbacher 2018), and behavioural finance elements (Fairchild et al. 2017)14, discovered in the literature on crowdfunding. With the accumulation of more data, more research is expected in these areas.

Finally, note that a high-quality education system is an essential part of the successful development of entrepreneurial finance in Canada. It is hard to overstate the importance of education since the area is very complicated and requires a superior knowledge of econometrics, microeconomics, accounting, mathematics, game theory, contracts and law. Part of the research done for this article was collecting information about existing finance programs in Canada15. Finance programs exist in most universities. Most of them are not specifically focused on small- or medium-sized companies. Some universities, however, are working on creating such a program. For example, Nipissing University is implementing a finance program that offers a certificate in entrepreneurial finance, and many universities, including the University of British Columbia, McGill, and Western University, offer entrepreneurial finance and/or small business finance lectures/courses.