# **Table 5: Prediction Accuracy for Total Employment, Monthly Sales and Monthly Profits**

||||||Total E|mploymen|t||Monthl|y Sales|||Monthl|yProfits||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||||Non-w|inners|Win|ners|Non-w|inners|Win|ners|Non-|winners|Win|ners|
|||Model|Predictors|MSE|R<sup>2</sup>|MSE|R<sup>2</sup>|MSE|R<sup>2</sup>|MSE|R<sup>2</sup>|MSE|R<sup>2</sup>|MSE|R<sup>2</sup>|
||1|OLS|Application Score|34.26|2.4%|99.11|5.6%|43.66|4.0%|20.74|2.4%|37.54|3.9%|22.02|2.9%|
|Judges|2|OLS|Business Score|34.32|1.8%|98.77|5.9%|43.89|3.5%|20.94|2.0%|37.79|3.2%|22.21|2.1%|
||3|OLS|SubScore|34.29|2.0%|98.62|6.4%|44.00|3.4%|21.13|1.5%|37.98|2.9%|22.55|1.2%|
||4|OLS|Gender|34.16|2.4%|99.12|5.6%|43.14|5.3%|20.71|2.3%|37.17|4.9%|22.03|2.5%|
||5|OLS|Age|33.97|2.6%|98.93|6.1%|43.10|5.3%|20.74|2.4%|37.26|4.8%|22.02|2.9%|
|Sil|6|OLS|Necessity Firm|34.53|1.0%|99.79|5.0%|43.97|3.4%|20.69|2.7%|37.91|2.9%|22.32|1.5%|
|nge<br>Pdit|7|OLS|Grit|34.46|1.8%|99.09|5.6%|43.35|4.6%|20.83|2.1%|37.35|4.2%|22.10|2.6%|
|recor|8|OLS|Digit-span Recall|34.47|1.5%|99.35|5.4%|43.36|5.0%|21.04|1.8%|37.39|4.6%|22.30|1.8%|
||9|OLS|Raven Test|34.19|1.7%|99.42|5.3%|41.96|8.0%|20.73|2.2%|36.47|6.6%|21.94|2.8%|
||10|OLS|Registration time|34.33|1.9%|98.81|6.0%|43.62|4.0%|20.69|2.1%|37.54|3.9%|22.08|2.1%|
||11|OLS|McKenzie|33.98|2.9%|99.87|5.8%|42.02|8.0%|21.01|1.9%|36.62|6.5%|22.54|1.6%|
|Economist|<br>12|OLS|FaWo|33.40|4.8%|101.05|5.6%|40.18|12.0%|21.05|1.9%|35.02|10.7%|<br>22.53|1.7%|
|Models|13|OLS|FaWo + BusScores|33.42|4.8%|100.61|5.9%|40.49|11.4%|21.26|1.6%|35.26|10.1%|<br>22.74|1.6%|
||14|OLS|FaWo+ Baseline|39.96|4.9%|91.20|17.2%|NA|NA|NA|NA|NA|NA|NA|NA|
|Mhi|15|Post-LASSO|All|34.03|3.0%|94.77|13.0%|41.96|8.5%|21.46|0.1%|37.20|6.2%|23.01|1.0%|
|acne-<br>Learnin|16|SVR|All|34.07|3.0%|105.80|3.3%|40.57|11.1%|21.13|0.8%|35.25|10.0%|<br>22.34|1.0%|
|g|17|Boosting|All|35.31|1.3%|104.20|12.4%|40.17|11.9%|21.17|1.3%|36.14|8.2%|22.17|1.2%|

Notes: the first outcome is total employment in the firm three years after applying, coded as zero for applicants not operating firms. The second outcome is the inverse hyperbolic sine of monthly sales in the firm three years after applying, coded as zero for applicants not operating firms. The third outcome is the inverse hyperbolic sine of monthly profits in the firm three years after applying, coded as zero for applicants not operating firms. Models are estimating separately for competition non-winners and winners. MSE is the outof-sample average mean-squared error over 5-fold estimation, and R<sup>2</sup> is the squared correlation between the fitted outcome and actual outcome. Judges use scores from competition judges to predict the outcome. Single predictor models use a single survey measure. The economist models are the models of McKenzie (2015) and Fafchamps and Woodruff (2017) (abbreviated as FaWo) used in Tables 1-3. The three machine learning models are based on 393 predictors, along with interaction terms in the case of post-LASSO. All models include a dummy for whether the applicant was for an existing firm compared to a new firm, and models for winners also control for the total award received (in logs).

35