This page includes a more detailed results section connected to this post.
If you are interested in the Methods section, click here.
I included some of the regressions for those interested in peaking. On the Differences in Differences tables, you will notice that not all the numbers add up exactly, this is for rounding purposes. If you have any questions, comments, or criticisms, please feel free to contact me. One of the reasons I’m posting this here is so I can continue learning as well.
Results
Credit bureau arrival had a statistically and substantively significant relationship with one dependent variable, Access to Finance as an Obstacle (0-4). For firms in the treatment group, their perception of access to finance as an obstacle decreased by 9.82% from the pre period to the post period (See Figures 2-7). The control group actually experienced an increase in their perception of obstacles to finance by 12.5%. Comparatively, credit bureau arrival resulted in a 22.36% decrease in perceptions of access to finance as an obstacle. These results were consistent across each model. As expected, firms with more employees, foreign ownership, and external auditing procedures were also significantly related with a decrease in perceptions of access to finance as an obstacle. Credit registries had a statistically significant relationship with increased perceptions of access to finance as an obstacle, however, this relationship switched to decreased perceptions when I controlled for macro-economic conditions (See Tables 2-3 for Regressions).
Figure 2. Credit Bureau Arrival (w/o Kenya & Malawi & w/ Firm Controls)
| DV: Access to Finance as and Obstacle (0-4) | Pre-Bureau Arrival | Post Bureau Arrival | Difference (Post-Pre) |
| Treatment | 2.1071971 | 1.900372*** | -.2068251* |
| Control | 2.113403*** | 2.37777474 | .2643452*** |
| Difference (Treatment-Control) | -.0062051 | -.4773754*** | -.4711703*** |
p < 0.05, ** p < 0.01, *** p < 0.001
n=2285
Figure 3. Credit Bureau Arrival (w/o Kenya & Malawi & w/o Controls)
| DV: Access to Finance as and Obstacle (0-4) | Pre-Bureau Arrival | Post Bureau Arrival | Difference (Post-Pre) |
| Treatment | 1.8847 | 1.6284*** | -.2563** |
| Control | 2.0829*** | 2.1309 | .048 |
| Difference (Treatment-Control) | -.1982* | -.5025*** | -.3043** |
p < 0.05, ** p < 0.01, *** p < 0.001
n=3439
Figure 4. Credit Bureau Arrival (w/ Kenya and Malawi w/o Controls)
| DV: Access to Finance as and Obstacle (0-4) | Pre-Bureau Arrival | Post Bureau Arrival | Difference (Post-Pre) |
| Treatment | 1.8205 | 1.5945*** | -.2260*** |
| Control | 2.0819*** | 2.114 | .0320 |
| Difference (Treatment-Control) | -.2613*** | -.5193*** | -.258*** |
p < 0.05, ** p < 0.01, *** p < 0.001
n=3906
Figure 5. Credit Bureau Arrival (w/ Kenya & Malawi & w/ Firm Controls)
| DV: Access to Finance as and Obstacle (0-4) | Pre-Bureau Arrival | Post Bureau Arrival | Difference (Post-Pre) |
| Treatment | 2.0629 | 1.8806*** | -.1823* |
| Control | 2.1684*** | 2.3815 | .2131** |
| Difference (Treatment-Control) | -.1054 | -.5009*** | -.3954*** |
p < 0.05, ** p < 0.01, *** p < 0.001
n=2719
Figure 6. Credit Bureau Arrival (w/o Kenya & Malawi & w/ Firm and Macro Controls)
| DV: Access to Finance as and Obstacle (0-4) | Pre-Bureau Arrival | Post Bureau Arrival | Difference (Post-Pre) |
| Treatment | 2.6703 | 2.2902*** | -.3801** |
| Control | 2.8790*** | 2.999 | .1200 |
| Difference (Treatment-Control) | -.2086 | -.7088*** | -.5002*** |
p < 0.05, ** p < 0.01, *** p < 0.001
n=2220
Figure 7. Credit Bureau Arrival (w/ Kenya & Malawi & w/ Firm and Macro Controls)
| DV: Access to Finance as and Obstacle (0-4) | Pre-Bureau Arrival | Post Bureau Arrival | Difference (Post-Pre) |
| Treatment | 2.4405 | 2.2069*** | -.2337* |
| Control | 2.673*** | 2.8991 | .226** |
| Difference (Treatment-Control) | -.2325* | -.6922*** | -.4597*** |
p < 0.05, ** p < 0.01, *** p < 0.001
n=2654
There was no statistically significant relationship between credit bureau arrival and firms having a line of credit/loan from a financial institution nor a higher percentage of working capital borrowed from banks. However, countries in the treatment group were less likely to have a line of credit or loan, both with only firm-level controls and macro-economic controls. Experience of the top manager, number of employees, and financial audits were all associated with greater likelihood to have a loan or line of credit from a bank or an increased percentage of working capital borrowed from banks.
The arrival of a credit bureau had a statistically significant relationship with a subjective measure, but no relationship, or a negative relationship with objective measures regarding access to finance or overall lending in a country. While more research is required for the objective measures, the results from this study show that firms reported less trouble accessing finance after credit bureau arrival, both with controls and without.
Summary Statistics
Table 1 Firm-Level Summary Statistics
| Mean | Std. Dev. | Min. | Max. | ||
| How Much Of An Obstacle: Access To Finance | 2.10 | 1.41 | 0.00 | 4.00 | |
| % Of Working Capital Borrowed From Banks | 8.23 | 19.53 | 0.00 | 100.00 | |
| Establishment has A Line Of Credit Or Loan From A Financial Institution? | 0.23 | 0.42 | 0.00 | 1.00 | |
| Treatment Group | 0.35 | 0.48 | 0.00 | 1.00 | |
| Post Treatment | 0.49 | 0.50 | 0.00 | 1.00 | |
| Firm Age | 23.01 | 121.86 | 1.00 | 2019.00 | |
| How Many Years Of Experience Working In This Sector Does The Top Manager Have? | 14.67 | 9.61 | 1.00 | 55.00 | |
| Num. Permanent, Full-Time Employees At End Of Last Fiscal Year | 62.23 | 267.33 | 1.00 | 8000.00 | |
| Financial Statements Checked & Certified By External Auditor In Last Fiscal Yr? | 0.46 | 0.50 | 0.00 | 1.00 | |
| % owned by Private Foreign Individuals, Companies Or Organizations | 11.86 | 30.05 | 0.00 | 100.00 | |
| Commercial Banks per 100,00 Adults | 3.72 | 3.62 | 0.62 | 28.18 | |
| Domestic Credit to the Private Sector (% of GDP) | 16.85 | 9.33 | 3.92 | 57.96 | |
| GDP Per Capita | 1121.30 | 890.62 | 311.25 | 3886.48 | |
| GDP Per Capita Growth | 3.80 | 4.24 | -4.43 | 16.64 | |
| Inflation | 7.71 | 6.6! | -0.77 | 22.39 | |
| Observations | 2724.00 |
Source: World Development Indicators, Enterprise Surveys (http://www.enterprisesurveys.org), The World Bank.
Regressions
Table 2. Credit Bureau Arrival Treatment (a)
| (1) | (2) | (3) | |
| DV: How Much of an Obstacle: Access to Finance | Firm-Level Controls without Kenya and Malawi | Firm-Level Controls with Kenya and Malawi | Macro-Economic and Firm-Level Controls without Kenya and Malawi |
| Treatment Group | -0.0062 | -0.1054 | -0.2086 |
| (-0.05) | (-1.11) | (-1.51) | |
| Post-Treatment | 0.2643*** | 0.2131** | 0.1200 |
| (3.55) | (3.05) | (1.12) | |
| Treatment Group * Post-Treatment | -0.4712*** | -0.3954*** | -0.5002*** |
| (-3.86) | (-3.64) | (-4.01) | |
| How Many Years Of Experience Working In This Sector Does The Top Manager Have? | 0.0009 | -0.0005 | 0.0058 |
| (0.28) | (-0.18) | (1.73) | |
| Num. Permanent, Full-Time Employees At End Of Last Fiscal Year | -0.0006*** | -0.0004*** | -0.0006*** |
| (-4.55) | (-4.39) | (-4.88) | |
| Credit Registry | 0.2501** | 0.2370** | -0.0509 |
| (2.89) | (3.23) | (-0.34) | |
| Firm Age | -0.0002 | -0.0002 | -0.0002 |
| (-0.85) | (-0.93) | (-0.99) | |
| Financial Statements Checked & Certified By External Auditor In Last Fiscal Yr? | -0.2374*** | -0.2606*** | -0.2442*** |
| (-3.71) | (-4.45) | (-3.58) | |
| % owned by Private Foreign Individuals, Companies Or Organizations | -0.0047*** | -0.0034*** | -0.0052*** |
| (-4.61) | (-3.68) | (-5.05) | |
| Domestic Credit to the Private Sector (% of GDP) | -0.0289*** | ||
| (-3.93) | |||
| Commercial Bank Branches (Per 100,000 Adults) | -0.0319 | ||
| (-1.82) | |||
| GDP Per Capita Growth | -0.0180 | ||
| (-1.76) | |||
| GDP Per Capita | 0.0005*** | ||
| (4.45) | |||
| Inflation | -0.0631*** | ||
| (-4.76) | |||
| Constant | 2.1134*** | 2.1684*** | 2.8790*** |
| (20.55) | (24.62) | (12.73) | |
| Observations | 2285 | 2719 | 2220 |
| R^2 | 0.075 | 0.077 | 0.092 |
Note: OLS estimates with t-stats in parentheses.
p < 0.05, ** p < 0.01, *** p < 0.001
Table 3. Credit Bureau Arrival Treatment
| (1) | (2) | (3) | |
| DV: How Much of an Obstacle: Access to Finance | No Controls without Kenya and Malawi | No Controls with Kenya and Malawi | Macro-Economic and Firm-Level Controls with Kenya and Malawi |
| Treatment Group | -0.1982* | -0.2613*** | -0.2325* |
| (-2.47) | (-3.67) | (-2.09) | |
| Post-Treatment | 0.0480 | 0.0320 | 0.2260** |
| (0.84) | (0.59) | (2.73) | |
| -0.3043** | -0.2580** | -0.4597*** | |
| (-2.83) | (-2.67) | (-4.10) | |
| How Many Years Of Experience Working In This Sector Does The Top Manager Have? | 0.0037 | ||
| (1.24) | |||
| Num. Permanent, Full-Time Employees At End Of Last Fiscal Year | -0.0004*** | ||
| (-4.10) | |||
| Credit Registry | -0.0274 | ||
| (-0.22) | |||
| Firm Age | -0.0002 | ||
| (-0.97) | |||
| Financial Statements Checked & Certified By External Auditor In Last Fiscal Yr? | -0.2548*** | ||
| (-4.22) | |||
| % owned by Private Foreign Individuals, Companies Or Organizations | -0.0037*** | ||
| (-3.92) | |||
| Domestic Credit to the Private Sector (% of GDP) | -0.0197*** | ||
| (-3.64) | |||
| Commercial Bank Branches (Per 100,000 Adults) | -0.0216 | ||
| (-1.53) | |||
| GDP Per Capita Growth | -0.0036 | ||
| (-0.42) | |||
| GDP Per Capita | 0.0003*** | ||
| (4.24) | |||
| Inflation | -0.0405*** | ||
| (-4.98) | |||
| Constant | 2.0829*** | 2.0819*** | 2.6730*** |
| (47.42) | (49.54) | (16.43) | |
| Observations | 3439 | 3906 | 2654 |
| R^2 | 0.014 | 0.018 | 0.091 |
Note: OLS estimates with t-stats in parentheses.
p < 0.05, ** p < 0.01, *** p < 0.001
Data Source: Enterprise Surveys (http://www.enterprisesurveys.org), The World Bank.
Due North 