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Record W6963809623 · doi:10.20381/ruor-27806

Essays on SME Growth and Financing

2022· other· en· W6963809623 on OpenAlexaboutno aff

Bibliographic record

VenueuO Research (University of Ottawa) · 2022
Typeother
Languageen
FieldEnvironmental Science
TopicPlant Ecology and Soil Science
Canadian institutionsnot available
Fundersnot available
KeywordsDebtRevenuePremiseProsperityTrade creditCredit crunchEmpirical evidenceScope (computer science)Loan

Abstract

fetched live from OpenAlex

The growth of small- and medium-sized enterprises (SME) accounts for a disproportionate share of employment, economic growth and prosperity (Adelino et al., 2017). However, it has been argued that SMEs suffer from severe information asymmetry and other types of market frictions and, thus, are more likely subject to credit constraints (Berger and Udell, 1998). This PhD thesis addresses this issue from three different, yet interrelated, perspectives: the relationship between SME growth and credit constraints; the impacts of firm characteristics on the full scope of the SME debt acquisition process; and the effectiveness of a credit guarantee scheme (CGS). The latter is a widely-used form of policy initiative that seeks to address SME credit constraints. Accordingly, this thesis comprises three chapters and draws on empirical analyses of unique datasets from Statistics Canada surveys, conducted from 2011 to 2017. The first chapter of this dissertation investigates the impacts of demand- and supply-side credit constraints on SME growth. It finds that evidence consistent with the premise that growth-oriented firms that apply and obtain either term loans or trade credit experience higher short-term growth than demand-constrained and supply-constrained firms. In the longer term, growth-oriented firms that apply and obtain term loans experience higher growth in revenues than supply-constrained firms. The second chapter estimates the three stages of the SME debt acquisition process (i.e., recognizing a need for capital, applying for a loan, and being approved for a loan) using a trivariate probit model that accounts for the correlation among the three stages of the SME debt acquisition process. It finds that while innovators and exporters are relatively more likely to need external financing, they do not face demand- or supply-side constraints. Conversely, firms majority-owned by women and members of visible minority groups are more likely to need credit, are more likely to be demand-constrained and are subject to statistical discrimination when seeking credit. When changing the definition of demand-constrained borrowers to a more narrow definition, innovators are relatively more likely to apply for needed financing, exporters are relatively less likely to do so, and visible minorities are relatively just as likely to apply for needed financing. The third chapter proposes a new means of assessing the economic impact of the Canadian CGS, the Canada Small Business Financing (CSBF) program. The Canadian CGS is a mechanism by which the Government of Canada guarantees a specific portion of a loan in the event of default. The new measure improves on an existing measure that seeks to evaluate the performance of CGSs: the incrementality rate (a measure that evaluates the extent to which loans advanced under the CGS program would not otherwise have been approved by lenders—the counterfactual). The new measure developed in this chapter gauges lenders’ moral hazard; that is, the extent to which lenders take excessive risks by betting on overly risky loans because they know that the losses would be covered by the program. This cannot be captured by the incrementality rate. The chapter reports on the evaluation of the CSBF performance based on both measures, the traditional incrementality rate and the new measure of lenders’ excess risk taking. It finds that the CSBF is not incremental, with a low incrementality rate of 5.3 per cent. The findings also suggest that lenders do not engage in excessive risk-taking behavior, as evidenced by an almost zero risk-taking rate. While Canadian banks do not particularly exhibit a willingness to allocate guaranteed loans to women and visible minorities (the groups of firms that are subject to statistical discrimination per Chapter II), they tend to allocate more guaranteed loans to growth-oriented borrowers, consistent with the CSBF’s objective to support the growth of small businesses (ISED Canada, 2016). Finally, the CSBF incrementality rate does not vary significantly between recession (following the 2007-2008 crisis) and post-recession time periods.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.056
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0450.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.240
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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