<table><caption>Table C9: The Influence of Christian Missions on School Curriculum and Study Sections: Win-sorized Distances</caption><thead><tr><th rowspan="3"></th><th colspan="4">Dependent Variable:</th></tr><tr><th>Log. Number of<br>Study Tracks</th><th colspan="3">School Offers Section [...]</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.067***<br>(0.002)</td><td>0.032***<br>(0.002)</td><td>0.058***<br>(0.002)</td><td>-0.026***<br>(0.002)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td>0.024***<br>(0.002)</td><td>0.013***<br>(0.002)</td><td>0.019***<br>(0.002)</td><td>-0.008***<br>(0.002)</td></tr><tr><td>β Catholic [std.]</td><td>0.053</td><td>0.092</td><td>0.150</td><td>-0.075</td></tr><tr><td>β Protestant [std.]</td><td>0.018</td><td>0.035</td><td>0.046</td><td>-0.023</td></tr><tr><td>Difference P-Value</td><td>0.000</td><td>0.000</td><td>0.000</td><td>0.000</td></tr><tr><td>Outcome Mean</td><td>2.02</td><td>0.30</td><td>0.51</td><td>0.73</td></tr><tr><td>Outcome SD</td><td>1.62</td><td>0.46</td><td>0.50</td><td>0.44</td></tr><tr><td>Adjusted R2</td><td>0.364</td><td>0.238</td><td>0.170</td><td>0.066</td></tr><tr><td>Observations</td><td>56,550</td><td>56,550</td><td>56,550</td><td>56,550</td></tr><tr><td>Educational Province × Year FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geography Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 1. The unit of observation is a secondary school in a year. Robust standard errors in parentheses. *Number of Study Tracks* refers to the total number of different study tracks offered by a school in a given year. *General, Technical, and Pedagogy* are dummy variables, each taking the value one if a school in a given year offers study tracks in the General, Technical or Pedagogy sections, respectively, and zero otherwise. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. *Educational Province × Year FEs* refer to fixed effects for each combination of educational province and year, controlling for all unobserved factors specific to a given province in a given year. *Disease Controls* include malaria suitability and tsetse suitability. *Historical Pop. Density Control* controls for population density as of 1950. Each estimation controls for the school's latitude longitude. \* *p* < 0.10, \*\* *p* < 0.05, \*\*\* *p* < 0.01.
<table><caption>Table C10: The Influence of Christian Missions on Students' Success at Examen National d'État: Winsorized Distances</caption><thead><tr><th colspan="5" style="text-align: center;">Dependent Variable:</th></tr><tr><th colspan="5" style="text-align: center;">Students' Success at Exetat</th></tr><tr><th scope="col"></th><th scope="col">(1)</th><th scope="col">(2)</th><th scope="col">(3)</th><th scope="col">(4)</th><th scope="col">(5)</th></tr></thead><tbody><tr><th scope="row">Ln(Inv. Distance) Catholic Mission</th><td>0.016***<br>(0.002)</td><td></td><td>0.016***<br>(0.002)</td><td>0.016***<br>(0.002)</td><td>0.019***<br>(0.002)</td></tr><tr><th scope="row">Ln(Inv. Distance) Protestant Mission</th><td></td><td>0.007***<br>(0.002)</td><td>-0.001<br>(0.002)</td><td>-0.000<br>(0.002)</td><td>0.003<br>(0.002)</td></tr><tr><th scope="row">β Catholic [std.]</th><td>0.047</td><td></td><td>0.047</td><td>0.048</td><td>0.055</td></tr><tr><th scope="row">β Protestant [std.]</th><td></td><td>0.019</td><td>-0.002</td><td>-0.000</td><td>0.009</td></tr><tr><th scope="row">Difference P-Value</th><td></td><td></td><td>0.000</td><td>0.000</td><td>0.000</td></tr><tr><th scope="row">Outcome Mean</th><td>0.70</td><td>0.70</td><td>0.70</td><td>0.70</td><td>0.70</td></tr><tr><th scope="row">Outcome SD</th><td>0.46</td><td>0.46</td><td>0.46</td><td>0.46</td><td>0.46</td></tr><tr><th scope="row">Adjusted R2</th><td>0.290</td><td>0.290</td><td>0.290</td><td>0.290</td><td>0.292</td></tr><tr><th scope="row">Observations</th><td>1,978,280</td><td>1,978,280</td><td>1,978,280</td><td>1,978,280</td><td>1,978,280</td></tr><tr><th scope="row">Clusters</th><td>18,642</td><td>18,642</td><td>18,642</td><td>18,642</td><td>18,642</td></tr><tr><th scope="row">Study Track-Center-Year FEs</th><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><th scope="row">Geography Controls</th><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><th scope="row">Disease Controls</th><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><th scope="row">Historical Pop. Density Control</th><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><th scope="row">Nearest Mission FEs</th><td>N</td><td>N</td><td>N</td><td>N</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 2. The unit of observation is a student taking the *Examen National d'État*. Robust standard errors clustered at the school level are in parentheses. The dependent variable *Students' Success at Exetat* is a dummy variable equal to one if a student successfully passed the *Exetat* and zero otherwise. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. *Study Track-Center-Year FEs* are fixed effects that account for the exam center where the student takes the *session ordinaire*, the study track and the year of the exam. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasaï rivers, and river length within a 10 km buffer around each school. *Disease Controls* include malaria suitability and tsetse suitability. *Historical Pop. Density Control* controls for population density as of 1950. Each column controls for gender with a dummy variable equal to 1 if the student is female and 0 otherwise. *Nearest Mission FEs* refers to fixed effects for the geographically closest historical Catholic and Protestant missions. Each estimation controls for the school's latitude longitude. * *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01.
<table><caption>Table C11: The Influence of Christian Missions on Students' Success at Examen National d'État: Alternative Exposure Variables</caption><thead><tr><th></th><th colspan="4">Dependent Variable:<br>Students' Success at Exetat</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.015***<br>(0.001)</td><td></td><td></td><td></td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td>0.002<br>(0.001)</td><td></td><td></td><td></td></tr><tr><td>Catholic Mission within 10 km</td><td></td><td>0.032***<br>(0.003)</td><td></td><td></td></tr><tr><td>Protestant Mission within 10 km</td><td></td><td>0.010**<br>(0.004)</td><td></td><td></td></tr><tr><td>Catholic Mission within 20 km</td><td></td><td></td><td>0.007**<br>(0.003)</td><td></td></tr><tr><td>Protestant Mission within 20 km</td><td></td><td></td><td>-0.003<br>(0.004)</td><td></td></tr><tr><td>Catholic Mission within 30 km</td><td></td><td></td><td></td><td>-0.002<br>(0.003)</td></tr><tr><td>Protestant Mission within 30 km</td><td></td><td></td><td></td><td>-0.002<br>(0.003)</td></tr><tr><td>β Catholic [std.]</td><td>0.046</td><td>0.035</td><td>0.007</td><td>-0.002</td></tr><tr><td>β Protestant [std.]</td><td>0.005</td><td>0.011</td><td>-0.004</td><td>-0.002</td></tr><tr><td>Difference P-Value</td><td>0.000</td><td>0.000</td><td>0.041</td><td>0.881</td></tr><tr><td>Outcome Mean</td><td>0.70</td><td>0.70</td><td>0.70</td><td>0.70</td></tr><tr><td>Outcome SD</td><td>0.46</td><td>0.46</td><td>0.46</td><td>0.46</td></tr><tr><td>Adjusted R2</td><td>0.295</td><td>0.295</td><td>0.295</td><td>0.295</td></tr><tr><td>Observations</td><td>2,128,302</td><td>2,128,302</td><td>2,128,302</td><td>2,128,302</td></tr><tr><td>Clusters</td><td>61,855</td><td>61,855</td><td>61,855</td><td>61,855</td></tr><tr><td>Study Track-Center-Year FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geography Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 2. The unit of observation is a student taking the Examen National d'État. Robust standard errors clustered at the school level are in parentheses. The dependent variable *Students' Success at Exetat* is a dummy variable equal to one if a student successfully passed the Exetat and zero otherwise. Ln(Inv. Distance) Catholic (Protestant) Mission represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission, Catholic (Protestant) Missions within 10km is a dummy variable equal to 1 if there is a Catholic (Protestant) located within a 10km radius around the school, Catholic (Protestant) Missions within 20km is a dummy variable equal to 1 if there is a Catholic (Protestant) located within a 20km radius around the school, and Catholic (Protestant) Missions within 30km is a dummy variable equal to 1 if there is a Catholic (Protestant) located within a 30km radius around the school. Study Track-Center-Year FEs are fixed effects that account for the study track chosen by the student, the exam center where the student takes the session ordinaire, and the year of the exam. Geography Controls include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasaï rivers, and river length within a 10 km buffer around each school. Disease Controls include malaria suitability and tsetse suitability. Historical Pop. Density Control controls for population density as of 1950. Each column controls for gender with a dummy variable equal to 1 if the student is female and 0 otherwise, and for the school's latitude longitude. * p < 0.10, ** p < 0.05, *** p < 0.01.
<table><caption>Table C12: The Influence of Christian Missions on School Curriculum and Study Sections: Rural Sample Only</caption><thead><tr><th rowspan="3"></th><th colspan="4">Dependent Variable:</th></tr><tr><th>Log. Number of<br>Study Tracks</th><th colspan="3">School Offers Section [...]</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.042***<br>(0.002)</td><td>0.026***<br>(0.002)</td><td>0.038***<br>(0.002)</td><td>-0.022***<br>(0.002)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td>0.026***<br>(0.002)</td><td>0.013***<br>(0.002)</td><td>0.023***<br>(0.002)</td><td>-0.012***<br>(0.002)</td></tr><tr><td>β Catholic [std.]</td><td>0.036</td><td>0.075</td><td>0.097</td><td>-0.062</td></tr><tr><td>β Protestant [std.]</td><td>0.020</td><td>0.035</td><td>0.053</td><td>-0.031</td></tr><tr><td>Difference P-Value</td><td>0.000</td><td>0.000</td><td>0.000</td><td>0.001</td></tr><tr><td>Outcome Mean</td><td>1.81</td><td>0.25</td><td>0.45</td><td>0.74</td></tr><tr><td>Outcome SD</td><td>1.50</td><td>0.43</td><td>0.50</td><td>0.44</td></tr><tr><td>Adjusted R2</td><td>0.378</td><td>0.238</td><td>0.157</td><td>0.068</td></tr><tr><td>Observations</td><td>51,053</td><td>51,053</td><td>51,053</td><td>51,053</td></tr><tr><td>Educational Province × Year FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geography Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 1. The unit of observation is a secondary school in a year. Robust standard errors in parentheses. *Number of Study Tracks* refers to the total number of different study tracks offered by a school in a given year. *General, Technical, and Pedagogy* are dummy variables, each taking the value one if a school in a given year offers study tracks in the General, Technical or Pedagogy sections, respectively, and zero otherwise. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. *Disease Controls* include malaria suitability and tsetse suitability. *Historical Pop. Density Control* controls for population density as of 1950. *Educational Province × Year FEs* refer to fixed effects for each combination of educational province and year, controlling for all unobserved factors specific to a given province in a given year. Each estimation controls for the school's latitude longitude. Sample restricted to rural schools. \* *p* < 0.10, \*\* *p* < 0.05, \*\*\* *p* < 0.01.
<table><caption>Table C13: The Influence of Christian Missions on Students' Success at Examen National d'État: Rural Sample Only</caption><thead><tr><th></th><th colspan="5">Dependent Variable:</th></tr><tr><th></th><th colspan="5">Students' Success at Exetat</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.012***<br>(0.002)</td><td></td><td>0.011***<br>(0.002)</td><td>0.009***<br>(0.002)</td><td>0.015***<br>(0.002)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td>0.009***<br>(0.002)</td><td>0.006***<br>(0.002)</td><td>0.006***<br>(0.002)</td><td>0.002<br>(0.003)</td></tr><tr><td>β Catholic [std.]</td><td>0.036</td><td></td><td>0.031</td><td>0.027</td><td>0.043</td></tr><tr><td>β Protestant [std.]</td><td></td><td>0.026</td><td>0.016</td><td>0.017</td><td>0.005</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td>0.048</td><td>0.177</td><td>0.000</td></tr><tr><td>Outcome Mean</td><td>0.70</td><td>0.70</td><td>0.70</td><td>0.70</td><td>0.70</td></tr><tr><td>Outcome SD</td><td>0.46</td><td>0.46</td><td>0.46</td><td>0.46</td><td>0.46</td></tr><tr><td>Adjusted R2</td><td>0.070</td><td>0.070</td><td>0.071</td><td>0.073</td><td>0.091</td></tr><tr><td>Observations</td><td>1,492,323</td><td>1,492,323</td><td>1,492,323</td><td>1,492,323</td><td>1,492,323</td></tr><tr><td>Clusters</td><td>17,016</td><td>17,016</td><td>17,016</td><td>17,016</td><td>17,016</td></tr><tr><td>Study Track-Center-Year FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geography Controls</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Nearest Mission FEs</td><td>N</td><td>N</td><td>N</td><td>N</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 2. The unit of observation is a student taking the *Examen National d'État*. Robust standard errors clustered at the school level are in parentheses. The dependent variable *Students' Success at Exetat* is a dummy variable equal to one if a student successfully passed the *Exetat* and zero otherwise. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. *Study Track-Center-Year FEs* are fixed effects that account for the exam center where the student takes the *session ordinaire*, the study track and the year of the exam. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasaï rivers, and river length within a 10 km buffer around each school. *Disease Controls* include malaria suitability and tsetse suitability. *Historical Pop. Density Control* controls for population density as of 1950. Each column controls for the school's latitude longitude, and gender with a dummy variable equal to 1 if the student is female and 0 otherwise. *Nearest Mission FEs* refers to fixed effects for the geographically closest historical Catholic and Protestant missions. Sample restricted to rural schools. *p* < 0.10, **p* < 0.05, ***p* < 0.01.
<table><caption>Table C14: The Influence of Christian Missions on Students' Success at Examen National d'État</caption><thead><tr><th></th><th colspan="5">Dependent Variable:</th></tr><tr><th></th><th colspan="5">Students' Success at Exetat</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.009***<br>(0.002)</td><td></td><td>0.009***<br>(0.002)</td><td>0.009***<br>(0.002)</td><td>0.012***<br>(0.002)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td>-0.005***<br>(0.002)</td><td>-0.003*<br>(0.002)</td><td>-0.002<br>(0.002)</td><td>0.001<br>(0.002)</td></tr><tr><td>Ln(Inv. Distance) Catholic Mission × Ln(Inv. Distance) Protestant Mission</td><td>-0.002***<br>(0.000)</td><td>-0.004***<br>(0.000)</td><td>-0.002***<br>(0.001)</td><td>-0.002***<br>(0.001)</td><td>-0.002***<br>(0.001)</td></tr><tr><td>β Catholic [std.]</td><td>0.029</td><td></td><td>0.026</td><td>0.026</td><td>0.036</td></tr><tr><td>β Protestant [std.]</td><td></td><td>-0.013</td><td>-0.009</td><td>-0.007</td><td>0.002</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td>0.000</td><td>0.000</td><td>0.000</td></tr><tr><td>Outcome Mean</td><td>0.70</td><td>0.70</td><td>0.70</td><td>0.70</td><td>0.70</td></tr><tr><td>Outcome SD</td><td>0.46</td><td>0.46</td><td>0.46</td><td>0.46</td><td>0.46</td></tr><tr><td>Adjusted R2</td><td>0.295</td><td>0.295</td><td>0.295</td><td>0.295</td><td>0.297</td></tr><tr><td>Observations</td><td>2,128,302</td><td>2,128,302</td><td>2,128,302</td><td>2,128,302</td><td>2,128,302</td></tr><tr><td>Clusters</td><td>61,855</td><td>61,855</td><td>61,855</td><td>61,855</td><td>61,855</td></tr><tr><td>Study track-Center-Year FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geography Controls</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Mission FEs</td><td>N</td><td>N</td><td>N</td><td>N</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 2. The unit of observation is a student taking the Examen National d'État. Robust standard errors clustered at the school level are in parentheses. The dependent variables *Students' Success at Exetat* are dummies variables equal to one if a student successfully passed the *General Technical or Pedagogy Exetat* and zero otherwise. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. *Ln(Inv. Distance) Catholic Mission × Ln(Inv. Distance) Protestant Mission* is the interaction between the inverted logged distance from each school to the nearest Catholic mission and the inverted logged distance from each school to the nearest Protestant mission. *Study Track-Center-Year FEs* are fixed effects that account for the exam center where the student takes the *session ordinaire*, the study track and the year of the exam. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. *Disease Controls* include malaria suitability and tsetse suitability. *Historical Pop. Density Control* controls for population density as of 1950. Each column controls for gender with a dummy variable equal to 1 if the student is female and 0 otherwise. *p* < 0.10, **p** < 0.05, ***p** < 0.01.
<table><caption>Table C15: Distance to Mission and Schools Characteristics</caption><thead><tr><th></th><th colspan="6" style="text-align:center;">Dependent Variable:</th></tr><tr><th></th><th colspan="6" style="text-align:center;">Secondary School With [...]</th></tr><tr><th></th><th colspan="3" style="text-align:center;">Kindergarten</th><th colspan="3" style="text-align:center;">Primary School</th></tr><tr><th></th><th style="text-align:center;">(1)</th><th style="text-align:center;">(2)</th><th style="text-align:center;">(3)</th><th style="text-align:center;">(4)</th><th style="text-align:center;">(5)</th><th style="text-align:center;">(6)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.037***<br>(0.013)</td><td></td><td>0.042***<br>(0.014)</td><td>-0.012<br>(0.015)</td><td></td><td>-0.008<br>(0.015)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td>-0.005<br>(0.014)</td><td>-0.018<br>(0.015)</td><td></td><td>-0.018<br>(0.017)</td><td>-0.015<br>(0.017)</td></tr><tr><td>β Catholic [std.]</td><td>0.138</td><td></td><td>0.155</td><td>-0.040</td><td></td><td>-0.026</td></tr><tr><td>β Protestant [std.]</td><td></td><td>-0.016</td><td>-0.059</td><td></td><td>-0.053</td><td>-0.046</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td>0.012</td><td></td><td></td><td>0.769</td></tr><tr><td>Outcome Mean</td><td>0.19</td><td>0.19</td><td>0.19</td><td>0.74</td><td>0.74</td><td>0.74</td></tr><tr><td>Outcome SD</td><td>0.40</td><td>0.40</td><td>0.40</td><td>0.44</td><td>0.44</td><td>0.44</td></tr><tr><td>Adjusted R2</td><td>0.087</td><td>0.073</td><td>0.088</td><td>0.062</td><td>0.063</td><td>0.062</td></tr><tr><td>Observations</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td></tr><tr><td>Educational Province FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Respondent Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geographic Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 4. The unit of observation is a secondary school. Robust standard errors in parentheses. Each estimation controls for the school's latitude longitude. Secondary School With [...] is a dummy variable equals 1 one if the secondary school own a Kindergarten (Primary School) and 0 otherwise. Ln(Inv. Distance) Catholic (Protestant) Mission represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. Each estimations include Educational Province fixed effects. Respondents controls include the respondent age, age squared and a dummy equal to 1 if the respondent is a male and 0 otherwise. Geography Controls include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. Disease Controls include malaria suitability and tsetse suitability. Historical Pop. Density Control controls for population density as of 1950. Each estimation also controls for the school's latitude longitude. * p < 0.10, ** p < 0.05, *** p < 0.01.
<table><caption>Table C16: Distance to Mission and Latrines</caption><thead><tr><th rowspan="3"></th><th colspan="9">Dependent Variable:</th></tr><tr><th colspan="9">School Has [...] Latrines</th></tr><tr><th colspan="3">Girls Only</th><th colspan="3">Boys Only</th><th colspan="3">Shared by Girls and Boys</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.017*<br>(0.010)</td><td></td><td>0.017<br>(0.010)</td><td>0.021**<br>(0.010)</td><td></td><td>0.020*<br>(0.011)</td><td>-0.008<br>(0.011)</td><td></td><td>-0.012<br>(0.011)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td>0.008<br>(0.011)</td><td>0.002<br>(0.011)</td><td></td><td>0.010<br>(0.011)</td><td>0.003<br>(0.012)</td><td></td><td>0.012<br>(0.014)</td><td>0.016<br>(0.014)</td></tr><tr><td>β Catholic [std.]</td><td>0.090</td><td></td><td>0.087</td><td>0.105</td><td></td><td>0.102</td><td>-0.031</td><td></td><td>-0.048</td></tr><tr><td>β Protestant [std.]</td><td></td><td>0.035</td><td>0.011</td><td></td><td>0.042</td><td>0.013</td><td></td><td>0.044</td><td>0.058</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td>0.396</td><td></td><td></td><td>0.329</td><td></td><td></td><td>0.110</td></tr><tr><td>Outcome Mean</td><td>0.91</td><td>0.91</td><td>0.91</td><td>0.90</td><td>0.90</td><td>0.90</td><td>0.15</td><td>0.15</td><td>0.15</td></tr><tr><td>Outcome SD</td><td>0.28</td><td>0.28</td><td>0.28</td><td>0.30</td><td>0.30</td><td>0.30</td><td>0.36</td><td>0.36</td><td>0.36</td></tr><tr><td>Adjusted R2</td><td>0.035</td><td>0.030</td><td>0.034</td><td>0.041</td><td>0.034</td><td>0.039</td><td>0.201</td><td>0.202</td><td>0.202</td></tr><tr><td>Observations</td><td>618</td><td>618</td><td>618</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td></tr><tr><td>Clusters</td><td>618</td><td>618</td><td>618</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td></tr><tr><td>Educational Province FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Respondent Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geographic Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 4. The unit of observation is a secondary school. Robust standard errors in parentheses. The dependent variables are dummies variables equals to 1 if *School Had Latrines* that are dedicated to *Girls Only*, *Boys Only*, or *Shared by Girls and Boys* and 0 otherwise. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. Each estimations include Educational Province fixed effects. Respondent controls include the respondent age, age squared and a dummy equal to 1 if the respondent is a male and 0 otherwise. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasaï rivers, and river length within a 10 km buffer around each school. *Disease Controls* include malaria suitability and tsetse suitability. *Historical Pop. Density Control* controls for population density as of 1950. Each estimation also controls for the school's latitude longitude. \* *p* < 0.10, \*\* *p* < 0.05, \*\*\* *p* < 0.01.
<table><caption>Table C17: Distance to Mission and Study Support</caption><thead><tr><th rowspan="3"></th><th colspan="9">Dependent Variable:</th></tr><tr><th colspan="9">School Offers [...]</th></tr><tr><th colspan="3">Classes during Holidays</th><th colspan="3">Time to Study</th><th colspan="3">Classes Days per Week</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.028**<br>(0.014)</td><td></td><td>0.025*<br>(0.015)</td><td>0.028*<br>(0.014)</td><td></td><td>0.035**<br>(0.015)</td><td>0.020***<br>(0.007)</td><td></td><td>0.020***<br>(0.008)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td>0.019<br>(0.016)</td><td>0.011<br>(0.017)</td><td></td><td>-0.016<br>(0.016)</td><td>-0.027<br>(0.017)</td><td></td><td>0.007<br>(0.008)</td><td>-0.000<br>(0.008)</td></tr><tr><td>β Catholic [std.]</td><td>0.083</td><td></td><td>0.075</td><td>0.082</td><td></td><td>0.103</td><td>0.108</td><td></td><td>0.108</td></tr><tr><td>β Protestant [std.]</td><td></td><td>0.050</td><td>0.029</td><td></td><td>-0.042</td><td>-0.071</td><td></td><td>0.031</td><td>-0.000</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td>0.572</td><td></td><td></td><td>0.020</td><td></td><td></td><td>0.118</td></tr><tr><td>Outcome Mean</td><td>0.54</td><td>0.54</td><td>0.54</td><td>0.43</td><td>0.43</td><td>0.43</td><td>5.92</td><td>5.92</td><td>5.92</td></tr><tr><td>Outcome SD</td><td>0.50</td><td>0.50</td><td>0.50</td><td>0.50</td><td>0.50</td><td>0.50</td><td>0.28</td><td>0.28</td><td>0.28</td></tr><tr><td>Adjusted R2</td><td>0.164</td><td>0.161</td><td>0.163</td><td>0.224</td><td>0.220</td><td>0.226</td><td>0.122</td><td>0.113</td><td>0.120</td></tr><tr><td>Observations</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>621</td><td>621</td><td>621</td></tr><tr><td>Educational Province FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Respondent Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geographic Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 4. The unit of observation is a secondary school. Robust standard errors in parentheses. *Classes during Holidays* is a dummy variable equals to 1 one if the secondary school offers classes during holidays for some students and 0 otherwise. *Time to Study* is a dummy variable equals to 1 one if the secondary school offers compulsory and supervised study time and 0 otherwise. *Classes Days per Week* is the number of classes per week. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. Each estimations include Educational Province fixed effects. Respondent controls include the respondent age, age squared and a dummy equal to 1 if the respondent is a male and 0 otherwise. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. *Disease Controls* include malaria suitability and tsetse suitability. *Historical Pop. Density Control* controls for population density as of 1950. Each estimation also controls for the school's latitude longitude. * p < 0.10, ** p < 0.05, *** p < 0.01.
<table><caption>Table C18: Distance to Mission and Share of Students Accessing to University</caption><thead><tr><th colspan="7" style="text-align: center;">Dependent Variable:</th></tr><tr><th colspan="7" style="text-align: center;">Share of [...] Access University (%)</th></tr><tr><th></th><th colspan="3" style="text-align: center;">Boys</th><th colspan="3" style="text-align: center;">Girls</th></tr><tr><th></th><th style="text-align: center;">(1)</th><th style="text-align: center;">(2)</th><th style="text-align: center;">(3)</th><th style="text-align: center;">(4)</th><th style="text-align: center;">(5)</th><th style="text-align: center;">(6)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td style="text-align: center;">0.631<br>(0.719)</td><td></td><td style="text-align: center;">0.202<br>(0.793)</td><td style="text-align: center;">0.288<br>(0.487)</td><td></td><td style="text-align: center;">0.064<br>(0.525)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td style="text-align: center;">1.701**<br>(0.807)</td><td style="text-align: center;">1.634*<br>(0.887)</td><td></td><td style="text-align: center;">0.877<br>(0.564)</td><td style="text-align: center;">0.856<br>(0.609)</td></tr><tr><td>β Catholic [std.]</td><td style="text-align: center;">0.039</td><td></td><td style="text-align: center;">0.013</td><td style="text-align: center;">0.023</td><td></td><td style="text-align: center;">0.005</td></tr><tr><td>β Protestant [std.]</td><td></td><td style="text-align: center;">0.093</td><td style="text-align: center;">0.089</td><td></td><td style="text-align: center;">0.060</td><td style="text-align: center;">0.059</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td style="text-align: center;">0.316</td><td></td><td></td><td style="text-align: center;">0.404</td></tr><tr><td>Outcome Mean</td><td style="text-align: center;">26.89</td><td style="text-align: center;">26.89</td><td style="text-align: center;">26.89</td><td style="text-align: center;">15.93</td><td style="text-align: center;">15.93</td><td style="text-align: center;">15.93</td></tr><tr><td>Outcome SD</td><td style="text-align: center;">23.64</td><td style="text-align: center;">23.64</td><td style="text-align: center;">23.64</td><td style="text-align: center;">18.82</td><td style="text-align: center;">18.82</td><td style="text-align: center;">18.82</td></tr><tr><td>Adjusted R2</td><td style="text-align: center;">0.101</td><td style="text-align: center;">0.107</td><td style="text-align: center;">0.105</td><td style="text-align: center;">0.194</td><td style="text-align: center;">0.196</td><td style="text-align: center;">0.195</td></tr><tr><td>Observations</td><td style="text-align: center;">608</td><td style="text-align: center;">608</td><td style="text-align: center;">608</td><td style="text-align: center;">612</td><td style="text-align: center;">612</td><td style="text-align: center;">612</td></tr><tr><td>Clusters</td><td style="text-align: center;">608</td><td style="text-align: center;">608</td><td style="text-align: center;">608</td><td style="text-align: center;">612</td><td style="text-align: center;">612</td><td style="text-align: center;">612</td></tr><tr><td>Educational Province FEs</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr><tr><td>Respondent Controls</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr><tr><td>Geographic Controls</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr><tr><td>Disease Controls</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr><tr><td>Historical Pop. Density Control</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 4. The unit of observation is a secondary school. Robust standard errors in parentheses. Share of [...] Access University is the share of boys or girls in each school who pursue university education after completing secondary school. Ln(Inv. Distance) Catholic (Protestant) Mission represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. Each estimations include Educational Province fixed effects. Respondents controls include the respondent age, age squared and a dummy equal to 1 if the respondent is a male and 0 otherwise. Geography Controls include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. Disease Controls include malaria suitability and tsetse suitability. Historical Pop. Density Control controls for population density as of 1950. Each estimation also controls for the school's latitude longitude. * p < 0.10, ** p < 0.05, *** p < 0.01.

<table><caption>Table C19: Distance to Mission and Poverty</caption><thead><tr><th colspan="7" style="text-align: center;">Dependent Variable:</th></tr><tr><th colspan="7" style="text-align: center;">School's</th></tr><tr><th></th><th colspan="3" style="text-align: center;">Share Very Poor (%)</th><th colspan="3" style="text-align: center;">Share Poor (%)</th><th colspan="3" style="text-align: center;">Share Rich (%)</th><th colspan="3" style="text-align: center;">Share Very Rich (%)</th></tr><tr><th></th><th style="text-align: center;">(1)</th><th style="text-align: center;">(2)</th><th style="text-align: center;">(3)</th><th style="text-align: center;">(4)</th><th style="text-align: center;">(5)</th><th style="text-align: center;">(6)</th><th style="text-align: center;">(7)</th><th style="text-align: center;">(8)</th><th style="text-align: center;">(9)</th><th style="text-align: center;">(10)</th><th style="text-align: center;">(11)</th><th style="text-align: center;">(12)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td style="text-align: center;">-2.107**<br>(0.830)</td><td style="text-align: center;">-2.039**<br>(0.887)</td><td style="text-align: center;">0.911<br>(0.605)</td><td style="text-align: center;">0.763<br>(0.645)</td><td style="text-align: center;">0.006<br>(0.004)</td><td></td><td style="text-align: center;">0.005<br>(0.004)</td><td style="text-align: center;">0.584*<br>(0.330)</td><td></td><td style="text-align: center;">0.714**<br>(0.363)</td><td></td><td></td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td style="text-align: center;">-0.923<br>(0.858)</td><td style="text-align: center;">-0.265<br>(0.908)</td><td style="text-align: center;">0.828<br>(0.623)</td><td style="text-align: center;">0.582<br>(0.664)</td><td></td><td style="text-align: center;">0.004<br>(0.005)</td><td style="text-align: center;">0.002<br>(0.005)</td><td></td><td style="text-align: center;">-0.279<br>(0.323)</td><td style="text-align: center;">-0.510<br>(0.353)</td><td></td></tr><tr><td>β Catholic [std.]</td><td style="text-align: center;">-0.100</td><td style="text-align: center;">-0.096</td><td style="text-align: center;">0.065</td><td style="text-align: center;">0.055</td><td style="text-align: center;">0.061</td><td></td><td style="text-align: center;">0.056</td><td style="text-align: center;">0.083</td><td></td><td style="text-align: center;">0.102</td><td></td><td></td></tr><tr><td>β Protestant [std.]</td><td></td><td style="text-align: center;">-0.038</td><td style="text-align: center;">-0.011</td><td style="text-align: center;">0.052</td><td style="text-align: center;">0.036</td><td></td><td style="text-align: center;">0.033</td><td style="text-align: center;">0.017</td><td></td><td style="text-align: center;">-0.035</td><td style="text-align: center;">-0.063</td><td></td></tr><tr><td>Difference P-Value</td><td></td><td></td><td style="text-align: center;">0.233</td><td></td><td style="text-align: center;">0.867</td><td></td><td></td><td style="text-align: center;">0.598</td><td></td><td></td><td style="text-align: center;">0.045</td><td></td></tr><tr><td>Outcome Mean</td><td style="text-align: center;">56.14</td><td style="text-align: center;">56.14</td><td style="text-align: center;">56.14</td><td style="text-align: center;">26.76</td><td style="text-align: center;">26.76</td><td style="text-align: center;">0.12</td><td style="text-align: center;">0.12</td><td style="text-align: center;">0.12</td><td style="text-align: center;">5.42</td><td style="text-align: center;">5.42</td><td style="text-align: center;">5.42</td><td></td></tr><tr><td>Outcome SD</td><td style="text-align: center;">31.26</td><td style="text-align: center;">31.26</td><td style="text-align: center;">31.26</td><td style="text-align: center;">20.66</td><td style="text-align: center;">20.66</td><td style="text-align: center;">0.14</td><td style="text-align: center;">0.14</td><td style="text-align: center;">0.14</td><td style="text-align: center;">10.37</td><td style="text-align: center;">10.37</td><td style="text-align: center;">10.37</td><td></td></tr><tr><td>Adjusted R2</td><td style="text-align: center;">0.356</td><td style="text-align: center;">0.350</td><td style="text-align: center;">0.355</td><td style="text-align: center;">0.155</td><td style="text-align: center;">0.154</td><td style="text-align: center;">0.154</td><td style="text-align: center;">0.322</td><td style="text-align: center;">0.320</td><td style="text-align: center;">0.321</td><td style="text-align: center;">0.195</td><td style="text-align: center;">0.191</td><td style="text-align: center;">0.197</td></tr><tr><td>Observations</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td></tr><tr><td>Clusters</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">622</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td><td style="text-align: center;">621</td></tr><tr><td>Educational Province FEs</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr><tr><td>Respondent Controls</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr><tr><td>Geographic Controls</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr><tr><td>Disease Controls</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr><tr><td>Historical Pop. Density Control</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td><td style="text-align: center;">Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 4. The unit of observation is a secondary school. Robust standard errors in parentheses. The dependent variables are the Share of Very Poor which is the share of students' families earning less than 5,000 Congolese francs daily, Share of Poor which represents the share of students' families earning between 5,000 and 10,000 Congolese francs daily, Share of Rich is the share of students' families earning between 10,000 and 20,000 Congolese francs daily, and Share of Very Rich is the share of students' families earning more than 20,000 Congolese francs daily. Ln(Inv. Distance) Catholic (Protestant) Mission represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. Each estimations include Educational Province fixed effects. Respondents controls include the respondent age, age squared and a dummy equal to 1 if the respondent is a male and 0 otherwise. Geography Controls include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. Disease Controls include malaria suitability and tsetse suitability. Historical Pop. Density Control controls for population density as of 1950. Each estimation also controls for the school's latitude longitude. * p < 0.10, ** p < 0.05, *** p < 0.01.
<table><caption>Table C20: Distance to Mission and Expectations</caption><thead><tr><th rowspan="3"></th><th colspan="9">Dependent Variable:</th><th colspan="3">Difference</th></tr><tr><th colspan="3">Good Grade at Exetat for [...]</th><th colspan="3">Boys</th><th colspan="3">Girls</th><th colspan="3">Btw Boys and Girls</th></tr><tr><th>All</th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th><th>(10)</th><th>(11)</th><th>(12)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.583**<br>(0.240)</td><td></td><td>0.614**<br>(0.245)</td><td>0.410*<br>(0.219)</td><td></td><td>0.425*<br>(0.228)</td><td>0.536**<br>(0.224)</td><td></td><td>0.588***<br>(0.227)</td><td>0.053<br>(0.119)</td><td></td><td>0.075<br>(0.115)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td>0.076<br>(0.284)</td><td>-0.121<br>(0.286)</td><td></td><td>0.077<br>(0.260)</td><td>-0.061<br>(0.268)</td><td>-0.013<br>(0.262)</td><td></td><td>-0.203<br>(0.268)</td><td>-0.063<br>(0.152)</td><td></td><td>-0.088<br>(0.148)</td></tr><tr><td>β Catholic [std.]</td><td>0.103</td><td></td><td>0.108</td><td>0.078</td><td></td><td>0.081</td><td>0.103</td><td></td><td>0.113</td><td>0.022</td><td></td><td>0.031</td></tr><tr><td>β Protestant [std.]</td><td></td><td>0.012</td><td>-0.019</td><td></td><td>0.013</td><td>-0.010</td><td></td><td>-0.002</td><td>-0.034</td><td></td><td>-0.023</td><td>-0.032</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td>0.078</td><td></td><td></td><td>0.221</td><td></td><td></td><td>0.041</td><td></td><td></td><td>0.389</td></tr><tr><td>Outcome Mean</td><td>63.61</td><td>63.61</td><td>63.61</td><td>63.07</td><td>63.07</td><td>63.07</td><td>61.76</td><td>61.76</td><td>61.76</td><td>1.91</td><td>1.91</td><td>1.91</td></tr><tr><td>Outcome SD</td><td>8.38</td><td>8.38</td><td>8.38</td><td>7.72</td><td>7.72</td><td>7.72</td><td>7.65</td><td>7.65</td><td>7.65</td><td>3.58</td><td>3.58</td><td>3.58</td></tr><tr><td>Adjusted R2</td><td>0.188</td><td>0.180</td><td>0.187</td><td>0.176</td><td>0.171</td><td>0.175</td><td>0.160</td><td>0.152</td><td>0.159</td><td>0.167</td><td>0.168</td><td>0.167</td></tr><tr><td>Observations</td><td>623</td><td>623</td><td>623</td><td>623</td><td>623</td><td>623</td><td>623</td><td>623</td><td>623</td><td>623</td><td>623</td><td>623</td></tr><tr><td>Educational Province FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Respondent Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geographic Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 4. The unit of observation is a secondary school. Robust standard errors in parentheses. Good Grade at Exetat [J] is a continuous variable that captures the respondent's perception of what constitutes a good score at the National State Exam for All students, for Boys and for Girls. Difference Btw Boys and Girls represents the difference in perceptions of what constitutes a good grade between boys and girls. Ln(Inv. Distance) Catholic (Protestant) Mission represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. Each estimations include Educational Province fixed effects. Respondents controls include the respondent age, age squared and a dummy equal to 1 if the respondent is a male and 0 otherwise. Geography Controls include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. Disease Controls include malaria suitability and tsetse suitability. Historical Pop. Density Control controls for population density as of 1950. Each estimation also controls for the school's latitude longitude. * *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01.

<table><caption>Table C21: Distance to Mission and Student Criterion for Secondary Entry</caption><thead><tr><th rowspan="3"></th><th colspan="9">Dependent Variable:</th><th colspan="3">Difference</th></tr><tr><th colspan="9">Schools Require [...] For Secondary Entry</th><th colspan="3">Btw Boys and Girls</th></tr><tr><th colspan="3">Entrance Exam</th><th colspan="3">Primary Completion Exam</th><th colspan="3">Minimum Score at Primary Exam</th><th colspan="3">Score Value at Primary Exam</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th><th>(10)</th><th>(11)</th><th>(12)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>-0.001<br>(0.012)</td><td></td><td>-0.002<br>(0.013)</td><td>-0.005<br>(0.011)</td><td></td><td>-0.005<br>(0.011)</td><td>0.020*<br>(0.010)</td><td></td><td>0.024**<br>(0.012)</td><td>0.356<br>(0.349)</td><td></td><td>0.330<br>(0.352)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td>0.004<br>(0.014)</td><td>0.005<br>(0.014)</td><td></td><td>-0.000<br>(0.011)</td><td>0.002<br>(0.011)</td><td></td><td>-0.009<br>(0.010)</td><td>-0.016<br>(0.011)</td><td></td><td>0.370<br>(0.342)</td><td>0.319<br>(0.342)</td></tr><tr><td>β Catholic [std.]</td><td>-0.004</td><td></td><td>-0.008</td><td>-0.022</td><td></td><td>-0.024</td><td>0.067</td><td></td><td>0.082</td><td>0.144</td><td></td><td>0.133</td></tr><tr><td>β Protestant [std.]</td><td></td><td>0.012</td><td>0.014</td><td></td><td>-0.000</td><td>0.007</td><td></td><td>-0.026</td><td>-0.049</td><td></td><td>0.104</td><td>0.090</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td>0.763</td><td></td><td></td><td>0.679</td><td></td><td></td><td>0.041</td><td></td><td></td><td>0.983</td></tr><tr><td>Outcome Mean</td><td>0.22</td><td>0.22</td><td>0.22</td><td>0.89</td><td>0.89</td><td>0.89</td><td>0.25</td><td>0.25</td><td>0.25</td><td>52.28</td><td>52.28</td><td>52.28</td></tr><tr><td>Outcome SD</td><td>0.42</td><td>0.42</td><td>0.42</td><td>0.31</td><td>0.31</td><td>0.31</td><td>0.43</td><td>0.43</td><td>0.43</td><td>3.81</td><td>3.81</td><td>3.81</td></tr><tr><td>Adjusted R2</td><td>0.088</td><td>0.088</td><td>0.086</td><td>0.103</td><td>0.102</td><td>0.101</td><td>0.383</td><td>0.381</td><td>0.384</td><td>0.250</td><td>0.244</td><td>0.249</td></tr><tr><td>Observations</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>624</td><td>155</td><td>155</td><td>155</td></tr><tr><td>Educational Province FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Respondent Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geographic Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

Notes: The table reports OLS estimates of equation 4. The unit of observation is a secondary school. Robust standard errors in parentheses. Each estimation represents a school requirement of secondary entry. Entrance Exam is a binary variable that equals 1 if the secondary school requires students to pass an entrance exam for admission. Primary Completion Exam is a binary variable equal to 1 if the school requires students to have completed the national primary exam for entry, and 0 otherwise. Minimum Score at Primary Exam is a binary variable equal to 1 if the school requires a minimum score on the national primary exam for entry, and 0 otherwise. Score Value at Primary Exam represents the specific minimum score required on the national primary exam for admission. Ln(Inv. Distance) Catholic (Protestant) Mission represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. Each estimations include Educational Province fixed effects. Respondents controls include the respondent age, age squared and a dummy equal to 1 if the respondent is a male and 0 otherwise. Geography Controls include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. Disease Controls include malaria suitability and tsetse suitability. Historical Pop. Density Control controls for population density as of 1950. Each estimation also controls for the school's latitude longitude. * *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01.
### C.6. Correlates of Historical Christian Missions' Location

This section investigates the correlates of historical Christian missions' exposure. We perform this exercise to identify a set of geo-climatic features that influenced the establishment of missionaries and may be directly correlated with our outcomes of interest. Informed by existing literature, we investigate disease environment, topography, climate, and access. In this exercise, our unit of observation is a ten by ten kilometers grid cell. We estimate the following specification separately for Catholic and Protestant missions:

$$y_c = \alpha + \beta \text{Mission}_c + \epsilon_c \quad (A2)$$

where, $y_c$ is the outcome of interest, *Mission*<sub>c</sub> a dummy variable equal to one if a ten by ten kilometers grid cell hosts a Catholic or a Protestant mission, and $\epsilon_c$ is the error term. Our outcomes of interest are suitability for malaria (Kiszewski et al., 2004), Tsetse fly suitability (Alsan, 2015), ruggedness (Nunn and Puga, 2012), elevation (NOAA National Geophysical Data Center, 2009), precipitation (Fick and Hijmans, 2017), and temperature (Fick and Hijmans, 2017), caloric suitability (Galor and Özak, 2016), distance to the nearest 18th century mission (Van Straelen, 1898), length of navigable river within the grid cell, and distance to the Congo and Kasaï rivers which were main access routes to the interior of the country during the colonial period.

Figure C10 presents the results. Missions were established in areas with higher elevation, lower temperatures and precipitation, reduced disease prevalence, and greater access to waterways. Interestingly, the findings suggest that Catholic missions settled in areas with lower caloric suitability. In contrast, Protestant missions appear to have favored areas with higher caloric suitability.

Overall, these results support the notion that Christian missionaries strategically selected the locations for their missions. This exercise underscores the importance of controlling for these covariates in analyses of missionary legacies to disentangle their specific effects from underlying environmental advantages.
<figure><img src="image_20.png" /><figcaption>Figure C10: Correlates of Historical Christian Missions' Location</figcaption></figure>

*Notes:* This figure shows the correlates of historical Christian Missions' Location. The dependent variables are the share of a 10 x 10 kilometer cell's area within 10 kilometers of a Catholic (Protestant) mission. *Elevation* refers to the average elevation, *Temperature* to the average temperature, *Precipitation* to the average rainfall, and *Caloric Suitability* to average potential for growing caloric-rich crops, *Malaria Suitability* and *Tse-Tse Suitability* to the average area's malaria and tse-tse fly risk, *Ruggedness* to the terrain's roughness, *River Length* is the total river length in kilometers, all measured within a 10 x 10 kilometer grid. *Distance Congo* and *Distance Kasai* are respectively the distance from the grid centroid to the Congo river and Kasai river. *Distance to Early Catholic (Protestant)* Missions represents the distance from the grid centroids to earliest Catholic (Protestant) mission settlements.

## C.7. Robustness Test

<table><caption>Table C22: Oster (2019)'s δ Statistics: Selection on Unobservables</caption><thead><tr><th rowspan="3"></th><th colspan="4">Dependent Variable:</th></tr><tr><th>Log. Number of</th><th colspan="3">School Offers Section [...]</th></tr><tr><th>Study Tracks<br>(1)</th><th>General<br>(2)</th><th>Technical<br>(3)</th><th>Pedagogy<br>(4)</th></tr></thead><tbody><tr><td>Oster δ for γ<sub>1</sub> = 0</td><td></td><td></td><td></td><td></td></tr><tr><td>Catholic</td><td>1.459</td><td>1.269</td><td>2.008</td><td>4.165</td></tr><tr><td>Protestant</td><td>0.652</td><td>0.622</td><td>1.105</td><td>7.195</td></tr></tbody></table>

*Notes:* This table reports the δ statistic from the robustness test proposed by Oster (2019).
# Appendix D. Phone Survey

We conducted a phone survey across Eastern Democratic Republic of Congo (DRC) to gather data from rural secondary schools. The Marakuja Kivu Research, headquartered in Goma, Eastern DRC, was responsible for the data collection process, which spanned over two periods, one from December 27, 2023, to February 25, 2024, the other from September 2, 2024, to September 15, 2024. Approval for this research was obtained from the Institutional Review Board (IRB) at the Paris School of Economics (Application 2023-051 dated December 15, 2023).

## D.1. Sampling Procedure

We targeted 12 provinces in the Eastern DRC, namely Haut Katanga, Haut Lomami, Lomami, Lualaba, Manama, Nord Kivu, Sankuru, Sud Kivu, Nord Kivu, Ituri, Tanganyika, and Tshopo. We selected these provinces due to proximity to Goma where Marakuja Kivu Research is based. The selection of schools within these provinces was based on a probability proportional to size sampling procedure, with the “size” being determined by the number of students as per the 2018 census of all schools in the DRC. This method ensured a representative sample of 52 rural secondary schools was chosen for the study. Figure D11 shows the location of the surveyed schools.

## D.2. Data Collection

The data collection was conducted by the Marakuja Kivu Research with a team of six enumerators and one supervisor. We trained the team remotely for two days. The survey process, designed to last approximately 1.5 hours, initiated with a preliminary call to potential respondents. During this call, the enumerators introduced the study, read the IRB protocol to inform respondents about their rights and the potential benefits of the study, and provided contact information for the principal investigator for any further queries. Respondents were then asked for their willingness to participate in the survey and to schedule a convenient time for it.

The approach to reaching potential respondents involved a stratified technique, where enumerators used a list of phone numbers obtained from the census of all schools in the DRC, starting with the first number selected through our sampling procedure and continuing to the last. Despite a low refusal rate, the primary limitation to reaching potential respondents was the challenging phone network in some provinces. The surveys were conducted on tablets, in Lingala, Swahili and French and were supervised by a supervisor from the Marakuja Kivu Research, who also made corrections as necessary. Respondents had the flexibility to pause the survey, leave at any time, or choose not to answer any questions. At the end of the survey, respondents were offered compensation equivalent to two hours of work for a school director, either in phone credit or cash. The data was collected using Geo ODK and at the end of each day, submitted to a server. The collected data was then downloaded, cleaned, anonymized, back-checked, and finally erased from the server and tablets. Discrepancies and clarifications were addressed at the end of the survey process, with some respondents contacted again for further clarification.
<figure><img src="image_21.png" /><figcaption>Figure D11: Location of Surveyed Respondents</figcaption></figure>

Notes: This figure shows the location of the 624 rural secondary schools surveyed. We surveyed 52 schools in each of the 10 Eastern provinces. Schools were selected with probability proportional to size. Our partner, the Marakuja Kivu Research, who performed the phone surveys, is located in Goma.
## D.3. Phone Survey: Summary Statistics

Table D23 reports descriptive statistics for variables collected from the schools included in the phone survey and used in our analysis.

<table><caption>Table D23: Statistics Survey Variables</caption><thead><tr><th></th><th>Count</th><th>Mean</th><th>SD</th><th>Min</th><th>Max</th></tr></thead><tbody><tr><td><strong>Schools Characteristics:</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>School Has Kindergarten</td><td>624</td><td>0.194</td><td>0.396</td><td>0</td><td>1</td></tr><tr><td>School Has Primary School</td><td>624</td><td>0.744</td><td>0.437</td><td>0</td><td>1</td></tr><tr><td>Share of Girls</td><td>622</td><td>45.69</td><td>14.44</td><td>3</td><td>100</td></tr><tr><td><strong>School Had [...] Latrines:</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Girls Only</td><td>618</td><td>0.911</td><td>0.285</td><td>0</td><td>1</td></tr><tr><td>Boys Only</td><td>624</td><td>0.904</td><td>0.295</td><td>0</td><td>1</td></tr><tr><td>Shared by Girls and Boys</td><td>624</td><td>0.151</td><td>0.358</td><td>0</td><td>1</td></tr><tr><td><strong>Study Support:</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Nb. Class days per week</td><td>621</td><td>5.916</td><td>0.277</td><td>5</td><td>6</td></tr><tr><td>School offers time to study</td><td>624</td><td>0.433</td><td>0.496</td><td>0</td><td>1</td></tr><tr><td>School offers classes during holidays</td><td>624</td><td>0.540</td><td>0.499</td><td>0</td><td>1</td></tr><tr><td><strong>School's Revenue Composition (%):</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Share Very Poor</td><td>622</td><td>56.14</td><td>31.26</td><td>0</td><td>100</td></tr><tr><td>Share Poor</td><td>622</td><td>26.76</td><td>20.66</td><td>0</td><td>100</td></tr><tr><td>Share Rich</td><td>621</td><td>11.70</td><td>14.32</td><td>0</td><td>80</td></tr><tr><td>Share Very Rich</td><td>621</td><td>5.424</td><td>10.37</td><td>0</td><td>80</td></tr><tr><td><strong>Schools' Heterogeneity:</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>HHI Ethnicity</td><td>610</td><td>0.552</td><td>0.272</td><td>0.0850</td><td>1</td></tr><tr><td>HHI Religion</td><td>604</td><td>0.399</td><td>0.158</td><td>0.0249</td><td>1</td></tr><tr><td>HHI Income</td><td>621</td><td>0.540</td><td>0.280</td><td>0.0201</td><td>1</td></tr><tr><td><strong>Schools' Expectations of Good Grade at Exetat:</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>For all</td><td>623</td><td>63.61</td><td>8.383</td><td>50</td><td>90</td></tr><tr><td>For boys</td><td>623</td><td>63.07</td><td>7.718</td><td>50</td><td>90</td></tr><tr><td>For girls</td><td>623</td><td>61.76</td><td>7.653</td><td>50</td><td>90</td></tr><tr><td>Difference btw boys and girls</td><td>623</td><td>1.915</td><td>3.579</td><td>0</td><td>30</td></tr><tr><td><strong>Share of [...] Access University:</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Boys</td><td>608</td><td>26.89</td><td>23.64</td><td>0</td><td>100</td></tr><tr><td>Girls</td><td>612</td><td>15.93</td><td>18.82</td><td>0</td><td>100</td></tr><tr><td><strong>Criterium for Secondary Entry:</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Entrance Exam</td><td>624</td><td>0.224</td><td>0.417</td><td>0</td><td>1</td></tr><tr><td>Primary Completion Exam</td><td>624</td><td>0.893</td><td>0.310</td><td>0</td><td>1</td></tr><tr><td>Minimum Score at Primary Exam</td><td>624</td><td>0.248</td><td>0.432</td><td>0</td><td>1</td></tr><tr><td>Score Value at Primary Exam</td><td>155</td><td>52.28</td><td>3.806</td><td>50</td><td>70</td></tr></tbody></table>

Notes: Descriptive statistics on the variables from the phone survey. The number of observations varies between variables due to missing values.
D.4. Phone Survey: Exetat Results

In this section, we replicate our main analysis using data from schools surveyed in the phone
survey. Table D24 examines how proximity to Catholic and Protestant missions affects both the
number of study tracks offered and the likelihood of offering at least one track within each
educational section. Table D25, meanwhile, analyzes the relationship between mission proximity
and student success rates at the *Examen National d'État*. This exercise serves as a validation
check of our primary findings. Consistent with results from the broader sample, we find that
proximity to Catholic missions is associated with a more diverse and higher-quality curriculum,
particularly through an increased likelihood of offering study tracks beyond the basic Pedagogy
section. Conversely, proximity to Protestant missions has virtually no effect. Regarding student
success rates, our results – although based on a much smaller sample of 481 schools – remain
positive for Catholic missions, broadly aligning with our main analysis.
<table><caption>Table D24: The Influence of Christian Missions on School Curriculum and Study Sections</caption><thead><tr><th rowspan="3"></th><th colspan="4">Dependent Variable:</th></tr><tr><th>Log. Number of</th><th colspan="3">School Offers Section [...]</th></tr><tr><th>Study Tracks<br>(1)</th><th>General<br>(2)</th><th>Technical<br>(3)</th><th>Pedagogy<br>(4)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.079***<br>(0.009)</td><td>0.045***<br>(0.007)</td><td>0.054***<br>(0.008)</td><td>-0.026***<br>(0.007)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td>-0.020**<br>(0.009)</td><td>-0.012<br>(0.008)</td><td>-0.024***<br>(0.009)</td><td>-0.001<br>(0.008)</td></tr><tr><td>β Catholic [std.]</td><td>0.103</td><td>0.155</td><td>0.156</td><td>-0.091</td></tr><tr><td>β Protestant [std.]</td><td>-0.023</td><td>-0.035</td><td>-0.059</td><td>-0.002</td></tr><tr><td>Difference P-Value</td><td>0.000</td><td>0.000</td><td>0.000</td><td>0.035</td></tr><tr><td>Outcome Mean</td><td>1.78</td><td>0.22</td><td>0.47</td><td>0.78</td></tr><tr><td>Outcome SD</td><td>1.10</td><td>0.41</td><td>0.50</td><td>0.41</td></tr><tr><td>Adjusted R2</td><td>0.234</td><td>0.148</td><td>0.187</td><td>0.157</td></tr><tr><td>Observations</td><td>2,636</td><td>2,636</td><td>2,636</td><td>2,636</td></tr><tr><td>Clusters</td><td>2,629</td><td>2,629</td><td>2,629</td><td>2,629</td></tr><tr><td>Educational Province × Year FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geography Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr></tbody></table>

<footnote>Notes: The table reports OLS estimates of equation 1. The unit of observation is a secondary school in a year. Robust standard errors in parentheses. *Number of Study Tracks* refers to the total number of different study tracks offered by a school in a given year. *General, Technical, and Pedagogy* are dummy variables, each taking the value one if a school in a given year offers study tracks in the General, Technical or Pedagogy sections, respectively, and zero otherwise. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. *Educational Province × Year FEs* refer to fixed effects for each combination of educational province and year, controlling for all unobserved factors specific to a given province in a given year. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasai rivers, and river length within a 10 km buffer around each school. *Disease Controls* include malaria suitability and tsetse suitability. \* *p* < 0.10, \*\* *p* < 0.05, \*\*\* *p* < 0.01.</footnote>
<table><caption>Table D25: The Influence of Christian Missions on Students' Success at Examen National d'État</caption><thead><tr><th></th><th colspan="5">Dependent Variable:</th></tr><tr><th></th><th colspan="5">Students' Success at Exetat</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th></tr></thead><tbody><tr><td>Ln(Inv. Distance) Catholic Mission</td><td>0.004<br>(0.004)</td><td></td><td>0.005<br>(0.004)</td><td>0.005<br>(0.004)</td><td>0.002<br>(0.007)</td></tr><tr><td>Ln(Inv. Distance) Protestant Mission</td><td></td><td>-0.004<br>(0.004)</td><td>-0.005<br>(0.004)</td><td>-0.005<br>(0.004)</td><td>0.005<br>(0.009)</td></tr><tr><td>β Catholic [std.]</td><td>0.014</td><td></td><td>0.017</td><td>0.017</td><td>0.007</td></tr><tr><td>β Protestant [std.]</td><td></td><td>-0.011</td><td>-0.014</td><td>-0.014</td><td>0.014</td></tr><tr><td>Difference P-Value</td><td></td><td></td><td>0.135</td><td>0.135</td><td>0.835</td></tr><tr><td>Outcome Mean</td><td>0.72</td><td>0.72</td><td>0.72</td><td>0.72</td><td>0.72</td></tr><tr><td>Outcome SD</td><td>0.45</td><td>0.45</td><td>0.45</td><td>0.45</td><td>0.45</td></tr><tr><td>Adjusted R2</td><td>0.274</td><td>0.274</td><td>0.274</td><td>0.274</td><td>0.299</td></tr><tr><td>Observations</td><td>96,740</td><td>96,740</td><td>96,740</td><td>96,740</td><td>96,740</td></tr><tr><td>Clusters</td><td>2,626</td><td>2,626</td><td>2,626</td><td>2,626</td><td>2,626</td></tr><tr><td>Study Track-Educ Prov-Year FEs</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td><td>Y</td></tr><tr><td>Geography Controls</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Disease Controls</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Historical Pop. Density Control</td><td>N</td><td>N</td><td>N</td><td>Y</td><td>Y</td></tr><tr><td>Nearest Mission FEs</td><td>N</td><td>N</td><td>N</td><td>N</td><td>Y</td></tr></tbody></table>

Notes: The unit of observation is a student taking the *Examen National d'État*. Robust standard errors clustered at the school level are in parentheses. The dependent variable *Students' Success at Exetat* is a dummy variable equal to one if a student successfully passed the *Exetat* and zero otherwise. *Ln(Inv. Distance) Catholic (Protestant) Mission* represents the inverted logged distance from each school to the nearest Catholic (Protestant) mission. *Study Track-Prov Educ-Year FEs* are fixed effects that account for the exam center where the student takes the *session ordinaire*, and the year of the exam. *Geography Controls* include caloric suitability, maize suitability, cassava suitability, elevation, ruggedness, precipitation, temperature, distance to the Congo and Kasaï rivers, and river length within a 10 km buffer around each school. *Disease Controls* include malaria suitability and tsetse suitability. *Historical Pop. Density Control* controls for population density as of 1950. Each column controls for gender with a dummy variable equal to 1 if the student is female and 0 otherwise. * *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01.
Additional Material for

EDUCATIONAL LEGACIES OF CHRISTIAN MISSIONS: EVIDENCE
FROM THE DEMOCRATIC REPUBLIC OF THE CONGO

(Not for Publication)

12 June 2025

Most Recent Version Here

PIERRE DONAT BOUILLUD

Czech Technical University

CORALIE HIRSCHI

Centre d'Économie de la Sorbonne

ETIENNE LE ROSSIGNOL

Université de Namur
# Appendix E. Digitization and Geocoding Procedures

## E.1. Digitization of Examen National d'État Results

We downloaded the *Examen National d'État* results from the webpage of the Congolese Ministry of Education. Our data results from the automatic extraction of the raw pdf files. We built a R package to extract the results from the pdfs as structured R dataframes.

The relevant result information in the original pdf file is represented as text. As shown in Figure E12, the text on the pages is not always written in only one column, but mostly in 3. It means that we have to use information about the position of each of the text boxes in a page in order not to mangle text that would happen to be on adjacent lines in 2 different columns.

For a given province, there are pages for each study track (or option). For each study track, each school has its name, its code, a header with the number of students who took the exam, including how many female students, and the number of students who passed it, also including how many female students.

We use the `pdftools` package and its function `pdf_data` to get the text boxes in the pdf. A text box contains its enclosing text with its bounding box, i.e., its width, height and the position of its upper left corner.

Some columns have bounding boxes that are visually supposed to be aligned but are actually a few pixels vertically apart. We heuristically coalesce them together on a same line.

**Data cleaning.** Sometimes, the gender is missing, either on the total number of female students, or a specific student has no gender or some other marking than M or F (for instance, X). In that case, we set it as NA in the resulting data frame. However, if the global number of female students was missing but we can infer it from the list of students, we add it.

We also add 2 columns that can indicate discrepancies: one counts the number of disagreements between the number of female students who passed Examen d'État for a given school according to the header data of that school, and by counting how many got more than 50 points out of the 100 total, and the other one computes the same metric for the combined number of successes for male and female students.

Sometimes, schools have duplicated students. We can optionally remove the duplicated students and keep information about that removal in the resulting data frame.

**Supporting all the years.** Although all the result pdfs across the years (2008 to 2022)<fnref n="15" /> share the same overall structure, some details had to be taken into account for our tool to numerize all of them. For instance, some years have their results displayed scaled down compared to the more recent years; we automatically compute the scaling factor and then perform the usual extraction.

**The resulting data frame.** We heavily use packages from the `tidverse` to process the bounding boxes from the pdf so we decided to use the richer `tibble` class for the resulting data frame.

```r
tibble(
  option = character(0),
  code_option = integer(0),
)
```

<footnote n="15">¹⁵ Note that our article focuses on years 2016-2022.</footnote>
```r
province = character(0),
code_province = integer(0),
year = Date(0),
page = integer(0),
school_index = integer(0),
school = character(0),
code_school = character(0),
nb_participants = integer(0),
nb_females = integer(0),
nbsuccess = integer(0),
nb success females = integer(0),
ranking = integer(0),
name = character(0),
gender = factor(levels = c("M", "F")),
mark = integer(0)
)
```

`school_index` is a unique numerical identifier for each school block on the page.

**An open source R package.** The exam result extractor is distributed under `GPLv3` as a R package, accessible on github at https://github.com/programLyrique/RDCexams.

You can install it as follows:

```r
install.packages("remotes")
remotes::install_github("programLyrique/RDCexams")
```

The package provides 2 main functions to extract the exam results from the pdfs:

```r
extract_from_file <- function(filename, pages=NULL, correct = FALSE)
extract_from folder <- function (foldername, destdir = ".", only_missing =
FALSE, correct = FALSE)
```

`extract_from_file` extracts the exam results from a given pdf and returns a data frame. If you need a CSV, you need to write it yourself, for instance with `readr::write_csv`. Parameter `pages` for `extract_from_file` can be used to specify a range of pages to extract from the pdf; `correct` indicates whether to apply some corrections on the data frame, such as deduplicating students.

`extract_from folder` can be used to perform batch extraction of several pdfs stored in the same folder, as CSV files. By default, they are exported into the same directory but you can use `destdir` to save them in another one. If `only_missing` is set to True, only pdfs which have not been processed yet will have the exam results extracted. This assumes that the extracted data frames have been saved as CSV files obtained by replacing the extension `pdf` in the pdf file name.

The package also contains functions `validate`, `validate_file`, `validate folder` that check multiple correctness properties on the resulting data frame, to detect any possible extraction error. Properties include that each student has a grade or that the grades are one the right scale.
<figure><img src="image_22.png" /><figcaption>Figure E12: Examen National d'État: Raw Data from 2019</figcaption></figure>

Notes: This figure is an extract of the PDF containing the *Examen National d'État* results downloaded from the *Ministère de l'Enseignement Primaire, Secondaire et Technique*'s webpage. It shows the results for the year 2019, study track Latin and Philosophy in the province of Bas-Uele. The page shows the results for students registered in twelve schools. The dark grey areas hide the names of successful candidates. The school in the first column is the *Institut I'embo*. The code 54001 / 101 / 02 / 2 informs about the center's unique identifier where students took the test (54001), the study track's code (101), the schools' number in the list (02), and the schools' type (2) which stands for Protestant school. In 2019, four students participated in the exam in that study track, one of which was a girl. Two candidates were successful (i.e., scored above 50). The girl failed. The score and gender of each successful candidate are displayed next to the grey area.
## E.2. Geocoding Schools from the Examen National d'État

This section explains how we link school-level characteristics (GPS) with student-level outcomes on the *Examen National d'État*. We match the extract from the PDF with the national school census using a combination of string and geographic matching methods.

For each year between 2016 and 2022, we geocoded schools that sent students to take the *Examen National d'État* using the 2018 census of all schools in the Democratic Republic of the Congo, which we obtained through the *Direction de l'Information et de la Gestion de l'Éducation* (DIGE).

As shown in Figure E12, which is an extract from the *Examen National d'État* data, our raw data includes the following information: the name of the educational province where the school is located, the school name, and a unique code for each school. For example, the first school in the top-left corner of the PDF, *Institut Ibembo*, is located in the educational province *Bas-Uele*. The code 54001 / 101 / 02 / 2 provides the unique identifier of the exam center (54001), the code for the study track (101, representing Latin-Philosophy), the school's number in the PDF for that exam center (02), and the school's regime (2, indicating a Protestant school). These are the key pieces of information available from the *Examen National d'État* data downloaded from the Congolese Ministry of Education's webpage.

In the census of all schools, we have the following information for each school: the school name, the province name, the school regime, and the latitude and longitude coordinates of the school.

Unfortunately, we are unable to perform a direct match between the two databases based solely on school name, province, and school regime. This is due to the presence of duplicate school names in both the *Examen National d'État* raw data and the census (e.g., there may be more than one Catholic school named Groupe Scolaire Saint Antoine within the same province).

To address this issue, we leveraged a specific feature of the *Examen National d'État*: the fact that exam centers are secondary schools. Specifically, some schools serve as exam centers, while students from secondary schools that are not exam centers travel to these nearby designated schools to take the exam. The selection of an exam center for a given school is based on proximity and the study track offered. Although we have information from the census of all schools indicating which schools were exam centers around the time of data collection (2018-2020), we cannot extrapolate this information for the entire period covered by our *Examen National d'État* data, which spans from 2016 to 2022. Additionally, the exact timing of data collection for each school in the census is unknown, making it difficult to determine whether a school classified as an exam center in the census was consistently an exam center in other years.

To overcome this limitation, we use geographical proximity to aid in the matching process. The matching is performed as follows: for a given exam center in the *Examen National d'État* data (e.g., exam center 11001), we iteratively treat each school as a potential exam center and attempt to match associated schools within a 60 km radius, using both exact and fuzzy matching criteria. For each potential exam center, we perform an exact match on school names and management types with the census data to obtain GPS coordinates. If an exact match is found, we draw a 60 km buffer around the latitude and longitude of that school and retain all secondary and primary
schools from the census that fall within this radius. These schools are considered potential matches for other schools associated with that exam center.

Next, for each exam center, we attempt to match the associated schools with those within the 60 km radius using a series of matching techniques, starting with strict exact matching on multiple columns and progressively relaxing the criteria to include fuzzy string matching. We perform both strict and loose fuzzy matching on school names, considering the province and management type when available.

We repeat this process for all schools associated with that exam center, treating each as a potential exam center, and retain the scenario with the highest number of matches as the final match. This procedure is repeated for all exam centers and the best matching scenario is chosen based on a priority system. The result is a geocoded database where each exam center is matched to the most likely set of schools within its proximity.

Finally, schools that we are unable to match to a specific exam center are assigned the average latitude and longitude of all successfully matched schools within that exam center. In all specifications, we control for this georeferencing strategy by including a dummy variable that equals one if a school was assigned the average latitude and longitude. Table E28 summarize the range of matching techniques used.

While the matching procedure successfully geocodes over 80% of schools and students across years, unmatched cases may introduce a small degree of selection bias. However, as Table E27 shows, matched and unmatched units differ only modestly on key characteristics, suggesting that any bias is unlikely to affect our main conclusions.

<table><caption>Table E26: Matching Results Between the 2018 School Census and *Examen National d'État* Schools</caption><thead><tr><th rowspan="3">Years</th><th rowspan="3">Total</th><th colspan="4">Exetat Schools [...]</th><th colspan="4">Exetat Students [...]</th></tr><tr><th colspan="2">Matched</th><th colspan="2">Not Matched</th><th colspan="2">Matched</th><th colspan="2">Not Matched</th></tr><tr><th>N</th><th>%</th><th>N</th><th>%</th><th>Total</th><th>N</th><th>%</th><th>N</th><th>%</th></tr></thead><tbody><tr><td>2016</td><td>19422</td><td>15422</td><td>79.40</td><td>4000</td><td>20.60</td><td>604324</td><td>490407</td><td>81.15</td><td>113917</td><td>18.85</td></tr><tr><td>2017</td><td>20902</td><td>16931</td><td>81.00</td><td>3971</td><td>19.00</td><td>615783</td><td>508483</td><td>82.58</td><td>107300</td><td>17.42</td></tr><tr><td>2018</td><td>22297</td><td>18188</td><td>81.57</td><td>4109</td><td>18.43</td><td>665292</td><td>559950</td><td>84.17</td><td>105342</td><td>15.83</td></tr><tr><td>2019</td><td>22186</td><td>18000</td><td>81.13</td><td>4186</td><td>18.87</td><td>676891</td><td>565905</td><td>83.60</td><td>110986</td><td>16.40</td></tr><tr><td>2020</td><td>24936</td><td>20379</td><td>81.73</td><td>4557</td><td>18.27</td><td>812284</td><td>683305</td><td>84.12</td><td>128979</td><td>15.88</td></tr><tr><td>2021</td><td>26689</td><td>21761</td><td>81.54</td><td>4928</td><td>18.46</td><td>820742</td><td>686206</td><td>83.61</td><td>134536</td><td>16.39</td></tr><tr><td>2022</td><td>24491</td><td>19604</td><td>80.05</td><td>4887</td><td>19.95</td><td>805071</td><td>655480</td><td>81.42</td><td>149591</td><td>18.58</td></tr></tbody></table>

Notes: This table presents the number of geocoded Exetat schools (students) for each year from 2016 to 2022, along with the percentage of total schools (students) that these geocoded schools (students) represent.
<table><caption>Table E27: Balance Test between Matched and Not Matched Exetat Students and Schools</caption><thead><tr><th></th><th>Mean</th><th>Mean Difference</th><th>N</th></tr></thead><tbody><tr><td><strong>School Level</strong></td><td></td><td></td><td></td></tr><tr><td>Number of Participant</td><td>32.031</td><td>4.053***<br>(0.432)</td><td>76116</td></tr><tr><td><strong>Student Level</strong></td><td></td><td></td><td></td></tr><tr><td>Success</td><td>0.700</td><td>0.017***<br>(0.001)</td><td>2451893</td></tr><tr><td>Score</td><td>57.481</td><td>-0.103***<br>(0.012)</td><td>1716984</td></tr><tr><td>Female</td><td>0.462</td><td>-0.004***<br>(0.001)</td><td>2451869</td></tr></tbody></table>

Notes: This table presents a balance test comparing geocoded schools with those that were not geocoded. * p < 0.10, ** p < 0.05, *** p < 0.01.
<table><caption>Table E28: Statistics Matching Sources</caption><thead><tr><th colspan="4">Matching [...]</th></tr><tr><th>Variables</th><th>Type</th><th>N</th><th>%</th></tr></thead><tbody><tr><td><strong>Secondary Schools</strong></td><td></td><td></td><td></td></tr><tr><td><em>With Buffers</em></td><td></td><td></td><td></td></tr><tr><td>Name + Regime + Prov Educ</td><td>Exact</td><td>9221</td><td>5.73</td></tr><tr><td>Name + Prov Educ</td><td>Exact</td><td>1830</td><td>1.14</td></tr><tr><td>Name + Regime + Prov Educ</td><td>Fuzzy Strict</td><td>1623</td><td>1.01</td></tr><tr><td>Name + Regime + Prov Educ</td><td>Fuzzy Loose</td><td>550</td><td>0.34</td></tr><tr><td>Name + Regime</td><td>Exact</td><td>131</td><td>0.08</td></tr><tr><td><em>Without Buffers</em></td><td></td><td></td><td></td></tr><tr><td>Name + Regime + Prov Educ</td><td>Exact</td><td>70361</td><td>43.72</td></tr><tr><td>Name + Prov Educ</td><td>Exact</td><td>5936</td><td>3.69</td></tr><tr><td>Name + Regime + Prov Educ</td><td>Fuzzy Strict</td><td>2879</td><td>1.79</td></tr><tr><td>Name + Regime + Prov</td><td>Fuzzy Strict</td><td>21682</td><td>13.47</td></tr><tr><td>Name + Prov</td><td>Fuzzy Strict</td><td>54</td><td>0.03</td></tr><tr><td>Name + Prov Educ</td><td>Fuzzy Strict</td><td>18</td><td>0.01</td></tr><tr><td>Name + Regime + Prov Educ</td><td>Fuzzy Loose</td><td>407</td><td>0.25</td></tr><tr><td>Name + Regime + Prov</td><td>Fuzzy Loose</td><td>1214</td><td>0.75</td></tr><tr><td>Name + Prov</td><td>Fuzzy Loose</td><td>57</td><td>0.04</td></tr><tr><td>Name + Prov Educ</td><td>Fuzzy Loose</td><td>11</td><td>0.01</td></tr><tr><td>Name + Regime + Prov</td><td>Exact</td><td>1459</td><td>0.91</td></tr><tr><td>Name + Prov</td><td>Exact</td><td>310</td><td>0.19</td></tr><tr><td><strong>Primary Schools</strong></td><td></td><td></td><td></td></tr><tr><td><em>Without Buffers</em></td><td></td><td></td><td></td></tr><tr><td>Name + Regime + Prov Educ</td><td>Exact</td><td>4050</td><td>2.52</td></tr><tr><td>Name + Prov Educ</td><td>Exact</td><td>460</td><td>0.29</td></tr><tr><td>Name + Regime + Prov Educ</td><td>Fuzzy Loose</td><td>2138</td><td>1.33</td></tr><tr><td>Name + Regime + Prov</td><td>Exact</td><td>144</td><td>0.09</td></tr><tr><td>Name + Prov</td><td>Exact</td><td>26</td><td>0.02</td></tr><tr><td>Name + Regime + Prov</td><td>Fuzzy Loose</td><td>5724</td><td>3.56</td></tr><tr><td><strong>Missing</strong></td><td></td><td>30638</td><td>19.04</td></tr><tr><td><strong>Total</strong></td><td></td><td>160923</td><td>100</td></tr></tbody></table>

Notes: This table presents the different strategies used to geocode schools based on three key variables: the school name, the educational province or the province, and the school's management type (regime). To retrieve the location of Exetat schools we use data from the secondary and primary school census. The geocoding process involves several matching approaches, including direct exact matching, strict fuzzy matching, and loose fuzzy matching. To address challenges caused by duplicate school names, we use geographical proximity in the matching process. Specifically, as described in the previous section, we apply 60 km buffers to refine matches, combining the three matching methods with different combinations of the variables: school names, educational provinces or provinces, and school management types.