# Bank Accessibility and Entrepreneurial Activity: Evidence from Brazil

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## Abstract

**:**

## 1. Introduction

## 2. Institutional Background

## 3. Literature Review and Hypothesis Development

**H1.**

## 4. Empirical Strategy

#### 4.1. Data

#### 4.2. Estimations

## 5. Results

#### 5.1. Main Results

#### 5.2. Heterogeneity of the Number of Bank Branches

#### 5.3. Closings and Openings of Bank Branches

#### 5.4. Firm Sizes

## 6. Discussion, Conclusions, and Implications

## Author Contributions

## Funding

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 3.**Average Loan Volume in the Brazilian financial market and yearly inflation rate from 2008 to 2022.

**Table 1.**We present descriptive statistics of our main variables, including the number of observations, mean, and standard deviation. Data are composed of observations from 2010 to 2021. A total of 2104 municipalities from all Brazilian states areincluded in the dataset, forming an unbalanced panel of 23,769 observations.

Variable | Obs. | Mean | SD |
---|---|---|---|

Number of Firms | 23,769 | 13,271.42 | 113,810.60 |

Small Firms | 23,769 | 1312.44 | 8137.85 |

Large Firms | 23,769 | 5857.21 | 57,490.66 |

Number of Bank Branches | 23,769 | 7.19 | 62.01 |

**Table 2.**We provide results from panel data regressions using the ln(Number of Firms) per municipality as the dependent variable. The variable Number of Bank Branches is a variable that measures the total number of bank branches in that municipality for that specific year. We use Year, State, and Municipality fixed effects when noted. Municipality clustered standard errors are disclosed in parentheses. Significance levels: *** p < 0.01, ** p < 0.05, * p < 0.10.

Model 1 | Model 2 | Model 3 | |
---|---|---|---|

Number of Bank Branches | 0.003 ** | 0.003 ** | 0.001 ** |

(0.001) | (0.001) | (0.000) | |

N | 23,769 | 23,769 | 23,769 |

R^{2} | 0.07 | 0.15 | 0.96 |

Year FE | Y | Y | Y |

State FE | N | Y | N |

Municipality FE | N | N | Y |

Clustered SE | Y | Y | Y |

**Table 3.**We provide results from panel data regressions using the ln(Number of Firms) per municipality as the dependent variable. The variable “Low Number of Bank Branches” is a dummy variable that assumes the value of 1 if the municipality had 5 or fewer branches for that specific year. The variable “Single Bank Branch” functions in the same way, but the variable only assumes the value of 1 if the municipality has just one bank branch. The variable Δ(Number of Bank Branches) takes the first difference of the number of bank branches in the municipality in the current year minus the value for the previous year. We use Year and State fixed effects when noted. Municipality clustered standard errors are disclosed in parentheses. Significance levels: *** p < 0.01, ** p < 0.05, * p < 0.10.

Model 4 | Model 5 | Model 6 | |
---|---|---|---|

Low Number of Bank Branches | −0.297 *** | ||

(0.039) | |||

Single Bank Branch | −0.146 *** | ||

(0.019) | |||

Δ(Number of Bank Branches) | 0.002 * | ||

(0.001) | |||

N | 23,769 | 23,769 | 21,629 |

R^{2} | 0.19 | 0.20 | 0.11 |

Year FE | Y | Y | Y |

State FE | Y | Y | Y |

Clustered SE | Y | Y | Y |

**Table 4.**We provide results from panel data regressions using the ln(Number of Firms) per municipality as the dependent variable. The variable Number of Bank Branches is a variable that measures the total number of bank branches in that municipality for that specific year. The dependent variable “Small” is the natural logarithm of the number of firms in that municipality that had fewer than 5 employees in that year. The dependent variable “Large” is the natural logarithm of the number of firms in that municipality that had 100 or more employees in that year. The dependent variable “Ratio” is the ratio between the number of small companies in that municipality divided by the total number of firms in that year. We use Year and State fixed effects when noted. Municipality clustered standard errors are disclosed in parentheses. Significance levels: *** p < 0.01, ** p < 0.05, * p < 0.10.

Model 7 | Model 8 | Model 9 | |
---|---|---|---|

Dependent variable: | Small | Large | Ratio |

Number of Bank Branches | 0.002 ** | 0.006 ** | −0.0001 * |

(0.001) | (0.003) | (0.00007) | |

N | 23,769 | 23,769 | 23,769 |

R^{2} | 0.15 | 0.12 | 0.10 |

Year FE | Y | Y | Y |

State FE | Y | Y | Y |

Clustered SE | Y | Y | Y |

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## Share and Cite

**MDPI and ACS Style**

Leite, R.d.O.; Moura, M.; Mendes, L.; Lima de Pilla, L.H.
Bank Accessibility and Entrepreneurial Activity: Evidence from Brazil. *Int. J. Financial Stud.* **2024**, *12*, 50.
https://doi.org/10.3390/ijfs12020050

**AMA Style**

Leite RdO, Moura M, Mendes L, Lima de Pilla LH.
Bank Accessibility and Entrepreneurial Activity: Evidence from Brazil. *International Journal of Financial Studies*. 2024; 12(2):50.
https://doi.org/10.3390/ijfs12020050

**Chicago/Turabian Style**

Leite, Rodrigo de Oliveira, Matheus Moura, Layla Mendes, and Leonardo Henrique Lima de Pilla.
2024. "Bank Accessibility and Entrepreneurial Activity: Evidence from Brazil" *International Journal of Financial Studies* 12, no. 2: 50.
https://doi.org/10.3390/ijfs12020050