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Does music soothe the soul? Evaluating the impact of a music education programme in Medellin, Colombia

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Abstract

Numerous studies have borne out the effects of cultural and music education on individuals’ well-being, considering music as a mainly systematic practice or skill or as established educational supply. However, few studies assess the impact of music programmes designed to achieve specific goals, where music is considered as a tool for social change. As a case study, we take the Medellin Music School Network (Colombia), whose education programme for music initiation has been running for 23 years. Our aim is to evaluate the economic and social impact generated by participating in this programme. We use a quasi-experimental propensity score matching technique as the evaluation method. Results show that the programme significantly reduces the probability of participants’ becoming involved in conflict, added to which they perceive a better quality of life. Students achieve better academic performance and intensify cultural consumption and participation in artistic activities. Institutional efficacy is reflected through beneficiaries expressing a positive and significant willingness to pay in order to maintain the programme. The work also aims to evidence the usefulness of the methodology for evaluating the impact of cultural policies, particularly in developing areas.

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Fig. 1

Source: REMM, www.redmusicamedellin.org

Fig. 2

Source: Own elaboration based on the management reports of the REMM

Fig. 3

Source: Own elaboration

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Notes

  1. For further details, see www.redmusicamedellin.org.

  2. For an assessment reference for this educational project, see the works of Cuesta (2011) and Alemán et al. (2017) who, respectively, apply cost–benefit analysis and experimental techniques (differences in differences) to gauge the social impact of this programme.

  3. A summary of the main characteristics and content of the music education programme may be found in “Appendix 1”.

  4. According to the programme information, the dropout rate is low and stands at less than 10% per year and is generally due to the academic workload at school or university. One reflection of the level of permanence is that 48% of the present-day teaching staff and musical instrument teachers are graduates of the programme.

  5. The 11 integrated ensembles are made up of four symphony orchestras, three choral orchestras and four popular music groups. The presence of popular music groups together with the Colombian music school (Pedregal) enables the REMM to explore autochthonous music, which is reflected in a wide and varied repertoire, ranging from universal classical works to contemporary works composed by school conductors or other musicians in the city, the country and the region.

  6. In accordance with the National Department of Statistics in Colombia, the socio-economic stratification of urban areas classifies the residential dwellings that receive public services into groups. It is mainly carried out in order to levy a differential charge, by different strata, for the public services provided to households, thus enabling subsidies to be allocated and contributions to be levied on these areas. This means that those who have the highest economic capacity pay more for public services and contribute so as to enable the lower strata to make their payments, following a progressive fiscal system. The classification in strata in Colombia is as follows: (1) low–low, (2) low, (3) medium–low, (4) medium, (5) medium–high and (6) high.

  7. The advantage of PSM is that it only requires information of the outcomes after the programme (cross section data), whereas when applying DD, it is necessary to measure outcomes both before and after the programme (panel data). Moreover, PSM assumes that only observed characteristics can influence participation and outcome, whereas DD can control for unobserved factors. However, for DD to be valid, the comparison group must accurately represent the change in outcomes that would have been experienced by the treatment group in the absence of treatment (i.e. unobserved factors must be time invariant). A more robust method is “matched DD”, which combines PSM and DD (Gertler et al. 2017).

  8. We also used a logit specification for the propensity score, and the results did not change significantly. These complementary results are available from the authors upon request. Machine learning methods may also provide an alternative nonparametric approach to propensity score estimation, but they are not suitable for small samples (Pirracchio et al. 2015).

  9. We chose an intermediate age to subsequently check (8  years later) the effects on academic improvement and job opportunities.

  10. Notable events were also recalled to help jog the interviewees’ memory, such as the IX South American Games or the World Cup held in South Africa that was won by Spain, with the official song sung by the Colombian singer Shakira (Waka Waka). The survey model and the primary results thereof are available upon request from the authors.

  11. Commune 1—Popular, Commune 2—Santa Cruz, Commune 3—Manrique, Commune 4—Aranjuez, Commune 5—Castilla, Commune 6—Doce de Octubre, Commune 7—Robledo, Commune 8—Villa Hermosa, Commune 9—Buenos Aires, Commune 10—La Candelaria, Commune 11—Laureles-Estadio, Commune 12—La América, Commune 13—San Javier, Commune 14—Poblado, Commune 15—Guayabal y Commune 16—Belén.

  12. All of the estimations performed in this study have been carried out using Stata software.

  13. When using the two other matching techniques posited in the research (Caliper and Kernel), the goodness-of-fit tables yield similar results. These complementary results are available from the authors upon request.

  14. Later on, in the estimations of the causal effects using the nearest neighbour and Kernel techniques, it can be seen that the sample used indeed corresponds to 176 observations (N = 176), whilst in the case of the nearest neighbour with Caliper (0.01) 13 observations are seen to lie outside the common support region, such that N = 167.

  15. It should be pointed out that it was not possible to apply this technique to all the outcome vectors, since the variable must be known both before and after treatment. The early age at which pupils join the REMM in the baseline (on average, when aged 14) means that certain variables (related to cultural consumption, WTP, labour market, and so on) lie outside the individual’s area of decision at the time, although this not the case for the proxy of academic performance (being enrolled in the school year corresponding to their age).

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Acknowledgements

The authors wish to thank the Medellin Music School Network (REMM) for granting access to its databases and information, which allowed the present study to be carried out. We would also like to thank the referee and participants at the 9th Spanish Workshop on Cultural Economics and Management for their comments and discussion on a preliminary version of the paper. We also wish to thank the comments and suggestions made by the anonymous referees of the Journal. The usual disclaimer applies.

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Appendices

Appendix 1: Characteristics of the REMM programme

Mission

Offering children and youngsters in the city of Medellin an education and a focus through music geared towards instilling an appreciation of life, fostering non-violent attitudes and changing young people through education, healthy coexistence and social appropriation

Character

An introduction to music education programme that is extracurricular and independent from the formal education process (school or university)

Publicity

General publicity for registration and activities made by the city council and REMM through information channels such as webpage, social networks, television, radio, posters, and so on.

Intake

Annual, voluntary and free

Age range between 7 and 24, resident in Medellin and enrolled in a formal education institution. No previous training in music is required

Once registered, students take a music aptitude test to distribute them and form groups of students who have similar levels

Each student must present a family member as a tutor to attend and take part in REMM activities

Organisation

27 schools: 13 bowed string instruments, 13 wind and percussion instruments, and one focusing on Colombian instruments

Four levels: “seedbed”, pre-orchestra or pre-band, orchestra or band, integrated ensembles

11 integrated ensembles: four symphony orchestras, three choral orchestras, and four popular music groups

Wide and varied repertoire based on universal classical works and including contemporary works composed by musicians from the city, the country and the region; this also provides for the possibility of performing autochthonous works

Training

Teaching model: collective training programme in an introduction to music and instruments, music language, body expression, instrument technique, choral practice and instrument ensembles; complemented by workshops and psychosocial activities. Students choose their instrument in accordance with the school at which they enrolled

Assessment: system of merit and recognition which mainly involves regular attendance and final presentation at the end of the year of a repertoire chosen together with their teachers. The children and youngsters who most stand out progress through the years until they come to form part of the integrated ensembles

Intensity: group lessons, two sessions per week of approximately 2 h for the basic levels and 8 h a week for the advanced levels

The members of the bands, orchestras and/or ensembles travel and perform together in various local, national and international tours

Costs

All of the costs associated with the running and functioning as well as the REMM’s cultural programme are met by the Medellin city council. The activities organised as part of the programme are free for all citizens

Average annual data

5000 students

1000 new students

132 teachers

Groups of 20 students

55,000 h of lessons

4000 own instruments

10% drop out rate

4100 families involved

Budget of two million US dollars

205 direct jobs

500 concerts

45,000 spectators

108 events around the city each year

One international tour

  1. Source: Own elaboration based on REMM

Appendix 2: Measures and definition of variables

Variable

Type

Measure

Treatment

Participation in the REMM

Binary

= 1 If you participated in the REMM program

Baseline variables (matching variables)

Gender

Binary

= 1 Man

Age

Discrete

Age of the interviewee in 2010

Educational level

 Secondary (6th to 9th)

Binary

School year in which the interviewee was in 2010

= 1 Secondary

 High school (10th to 11th)

Binary

School year in which the interviewee was in 2010

= 1 High school

Family size

Discrete

Number of people living with the interviewee in 2010

Maximum educational level of the mother

 Elementary school (1st to 5th)

Binary

= 1 Elementary school

 Secondary (6th to 9th)

Binary

= 1 Secondary

 High school (10th to 11th)

Binary

= 1 High school

 Technical

Binary

= 1 Technical

 Technological

Binary

= 1 Technological

 Undergraduate (college)

Binary

= 1 Undergraduate (college)

 Graduate

Binary

= 1 Graduate

Maximum educational level of the father

 Elementary school (1st to 5th)

Binary

= 1 Elementary school

 Secondary (6th to 9th)

Binary

= 1 Secondary

 High school (10th to 11th)

Binary

= 1 High school

 Technical

Binary

= 1 Technical

 Technological

Binary

= 1 Technological

 Undergraduate (college)

Binary

= 1 Undergraduate (college)

 Graduate

Binary

= 1 Graduate

Place of residence

 Commune 1—Popular

Binary

= 1 Popular

 Commune 3—Manrique

Binary

= 1 Manrique

 Commune 4—Aranjuez

Binary

= 1 Aranjuez

 Commune 7—Robledo

Binary

= 1 Robledo

 Commune 8—Villa Hermosa

Binary

= 1 Villa Hernisa

 Commune 9—Buenos Aires

Binary

= 1 Buenos Aires

 Commune 10—La Candelaria

Binary

= 1 La Candelaria

 Commune 11—Laureles-Estadio

Binary

= 1 Laureles-Estadio

 Commune 12—La América

Binary

= 1 La América

 Commune 13—San Javier

Binary

= 1 San Javier

 Commune 15—Guayabal

Binary

= 1 Guayabal

 Commune 16—Belén

Binary

= 1 Belén

 Out of Medellin

Binary

= 1 Out of Medellin

Outcome variables

Social efficacy

 Being involved in situations of conflict and/or violence

Binary

Direct question of the questionnaire

= 1 “You or any of the members of your family group have been involved in a conflict situation (discussion, civil conflict, altercation, violent events, dispute, fight, among others) in the last 5 years”

 Changing place of residence to areas of a higher stratum

Binary

= 1 If the interviewee changed their place of residence from 2010 to 2018, to an area of greater socio-economic status in the city

 Housing conditions

Continuous

For that outcome we built an indicator which allowed us to sum up the battery of questions relating to the number of spaces (living room, bedrooms, kitchens, bathroom, among others) and utilities (such as running water, electricity, garbage collection) in a house

Educational and labour efficacy

 Average marks of the studies

Continuous

Direct question of the questionnaire

“What was the average overall grade you graduated with?”

 Finishing studies in the expected time

Binary

= 1 If you finish higher studies than the interviewee agreed, in the time established according to your age

 Obtaining study grants

Binary

Direct question of the questionnaire

= 1 If you receive a scholarship for the development of your studies

 Professional vocation-studying arts

Binary

= 1 If the interviewee conducted or performs higher studies related to arts

 Entry into the labour market

Binary

= 1 If the interviewee entered the labour market

 Income above a legal monthly salary

Binary

= 1 If the interviewee receives a monthly salary higher than the regulated minimum

Cultural consumption

 Doing sports

Discrete

Direct question of the questionnaire:

“Number of times you performed or attended the following activities during the last year”

 Attending football matches

Discrete

 Participating in sports competitions

Discrete

 Cinema attendance

Discrete

 Theatre attendance

Discrete

 Going dancing

Discrete

 Museum attendance

Discrete

 Book reading

Discrete

 Reading newspapers

Discrete

 Attending classical music concerts

Discrete

 Attending concerts

Discrete

 Visiting heritage

Discrete

 Videogames

Discrete

Institutional efficacy

 Willingness to pay

Continuous

Direct question of the questionnaire:

“How much would be the voluntary monetary contribution that I would be willing to give once for a year to support the REMM”

 Willingness to support the REMM

Binary

Direct question of the questionnaire:

= 1 If “Do you think it is important that the community in general be involved with the support of the REMM through a voluntary monetary contribution that allows a greater impact on its activities”

  1. Source: Own elaboration

Appendix 3: Descriptive statistics of the baseline and outcome variables

Sample

Complete

Treated

Controls

N = 180

N = 66

N = 114

Variable

Mean

SD

Min

Max

Mean

SD

Min

Max

Mean

SD

Min

Max

Treatment

Participation in the REMM

0.36

0.48

0

1

        

Baseline variables (matching variables)

Gender

0.5

0.50

0

1

0.46

0.50

0

1

0.51

0.50

0

1

Age

16.43

2.55

13

26

16.21

1.90

14

23

16.56

2.86

13

26

Educational level

 Secondary (6th to 9th)

0.07

0.25

0

1

0.03

0.17

0

1

0.09

0.29

0

1

 High school (10th to 11th)

0.12

0.33

0

1

0.12

0.32

0

1

0.13

0.33

0

1

Family size

4.40

1.41

1

11

4.60

1.49

2

10

4.28

1.35

1

11

Maximum educational level of the mother

 Elementary school (1st to 5th)

0.13

0.34

0

1

0.13

0.34

0

1

0.14

0.34

0

1

 Secondary (6th to 9th)

0.12

0.32

0

1

0.15

0.36

0

1

0.10

0.30

0

1

 High school (10th to 11th)

0.27

0.44

0

1

0.33

0.47

0

1

0.24

0.43

0

1

 Technical

0.16

0.36

0

1

0.15

0.36

0

1

0.16

0.37

0

1

 Technological

0.08

0.28

0

1

0.03

0.17

0

1

0.12

0.32

0

1

 Undergraduate (college)

0.14

0.35

0

1

0.15

0.36

0

1

0.14

0.34

0

1

 Graduate

0.05

0.21

0

1

0.03

0.17

0

1

0.06

0.24

0

1

Maximum educational level of the father

 Elementary school (1st to 5th)

0.20

0.40

0

1

0.28

0.45

0

1

0.14

0.35

0

1

 Secondary (6th to 9th)

0.09

0.29

0

1

0.04

0.20

0

1

0.12

0.32

0

1

 High school (10th to 11th)

0.27

0.44

0

1

0.30

0.46

0

1

0.25

0.43

0

1

 Technical

0.10

0.30

0

1

0.10

0.31

0

1

0.10

0.30

0

1

 Technological

0.07

0.25

0

1

0.03

0.17

0

1

0.09

0.29

0

1

 Undergraduate (college)

0.17

0.38

0

1

0.16

0.37

0

1

0.18

0.38

0

1

 Graduate

0.03

0.19

0

1

0.03

0.17

0

1

0.04

0.20

0

1

Place of residence

 Commune 1—Popular

0.05

0.21

0

1

0.06

0.24

0

1

0.04

0.20

0

1

 Commune 3—Manrique

0.07

0.26

0

1

0.09

0.28

0

1

0.07

0.25

0

1

 Commune 4—Aranjuez

0.04

0.20

0

1

0.07

0.26

0

1

0.02

0.16

0

1

 Commune 7—Robledo

0.06

0.24

0

1

0.07

0.26

0

1

0.05

0.22

0

1

 Commune 8—Villa Hermosa

0.03

0.18

0

1

0.06

0.24

0

1

0.17

0.13

0

1

 Commune 9—Buenos Aires

0.05

0.22

0

1

0.04

0.20

0

1

0.06

0.24

0

1

 Commune 10—La Candelaria

0.05

0.22

0

1

0.04

0.20

0

1

0.06

0.24

0

1

 Commune 11—Laureles-Estadio

0.05

0.21

0

1

0.06

0.24

0

1

0.04

0.20

0

1

 Commune 12—La América

0.04

0.20

0

1

0.03

0.17

0

1

0.05

0.22

0

1

 Commune 13—San Javier

0.03

0.18

0

1

0.04

0.20

0

1

0.02

0.16

0

1

 Commune 15—Guayabal

0.06

0.25

0

1

0.13

0.34

0

1

0.02

0.16

0

1

 Commune 16—Belén

0.04

0.20

0

1

0.03

0.17

0

1

0.05

0.22

0

1

 Out of Medellin

0.27

0.44

0

1

0.18

0.38

0

1

0.32

0.47

0

1

Outcome variables

Social efficacy

 Being involved in situations of conflict and/or violence

0.21

0.41

0

1

0.15

0.36

0

1

0.25

0.43

0

1

 Changing place of residence to areas of a higher stratum

0.10

0.30

0

1

0.12

0.32

0

1

0.08

0.28

0

1

 Housing conditions

1.07

0.12

0.69

1.57

1.05

0.13

0.80

1.57

1.07

0.12

0.69

1.38

Educational and labour efficacy

 Average marks of the studies

4.15

0.27

3.5

4.8

4.2

0.30

3.5

4.8

4.12

0.25

3.5

4.8

 Finishing studies in the expected time

0.62

0.48

0

1

0.77

0.42

0

1

0.53

0.50

0

1

 Obtaining study grants

0.18

0.39

0

1

0.25

0.44

0

1

0.14

0.35

0

1

 Professional vocation-studying arts

0.07

0.26

0

1

0.15

0.36

0

1

0.03

0.18

0

1

 Entry into the labour market

0.64

0.48

0

1

0.68

0.46

0

1

0.62

0.48

0

1

 Income above a legal monthly salary

0.35

0.48

0

1

0.39

0.49

0

1

0.33

0.47

0

1

Cultural consumption

 Doing sports

0.41

0.49

0

1

0.33

0.47

0

1

0.45

0.50

0

1

 Attending football matches

4.70

11.24

0

92

2.22

4.94

0

25

6.14

13.43

0

92

 Participating in sports competitions

1.58

3.94

0

30

1.37

2.69

0

16

1.71

4.51

0

30

 Cinema attendance

8.75

10.88

0

100

10.48

13.96

0

100

7.75

8.52

0

50

 Theatre attendance

2.53

5.06

0

40

3.80

6.93

0

40

1.79

3.39

0

20

 Going dancing

1.58

5.86

0

52

2.13

5.15

0

30

1.26

6.23

0

52

 Museum attendance

2.20

5.69

0

50

2.21

2.70

0

10

2.20

6.86

0

50

 Book reading

33.77

75.50

0

365

46.03

88.37

0

365

26.67

66.32

0

365

 Reading newspapers

131.27

149.80

0

365

162.22

153.26

0

365

113.35

145.44

0

365

 Attending classical music concerts

2.20

8.15

0

100

5.31

12.81

0

100

0.40

1.40

0

12

 Attending concerts

2.16

3.23

0

27

3.31

4.48

0

27

1.49

1.92

0

10

 Visiting heritage

2.98

13.64

0

150

1.54

3.10

0

20

3.81

16.95

0

150

 Videogames

28.32

72.93

0

365

36.87

89.12

0

365

23.37

61.55

0

365

Institutional efficacy

 Willingness to pay

51,811.07

85,081.35

0

700

82,749.62

126,179.6

0

700

33,899.28

37,760.02

0

200

 Willingness to support the REMM

0.78

0.41

0

1

0.83

0.37

0

1

0.75

0.43

0

1

  1. Source: Own elaboration

Appendix 4: Diagnostic statistics for one-to-one nearest matching procedure (NN(1))

Variable

Sample

Mean

% Reduct

Treated

Control

% Biasb

Bias

T testa

p value

Gender

Unmatched

0.4697

0.5175

− 9.5

 

− 0.62

0.539

Matched

0.4838

0.4516

6.4

32.6

− 0.36

0.722

Age

Unmatched

16.212

16.561

− 14.4

 

− 0.88

0.378

Matched

16.258

15.766

20.2

− 40.8

1.38

0.171

Educational level

 Secondary

Unmatched

0.0303

0.0964

− 27.3

 

− 1.66

0.099

Matched

0.0322

0.0249

3.3

87.8

0.27

0.788

 High school

Unmatched

0.1212

0.1315

− 3.1

 

− 0.20

0.842

Matched

0.1290

0.1129

4.8

− 55.6

0.27

0.785

Family size

Unmatched

4.6061

4.2895

22.2

 

1.45

0.148

Matched

4.5968

4.5806

1.1

94.9

0.06

0.953

Maximum educational level of the mother

 Elementary school

Unmatched

0.1363

0.1403

− 1.1

 

− 0.07

0.941

Matched

0.1451

0.0806

18.6

− 1518.1

1.13

0.260

 Secondary

Unmatched

0.1515

0.1052

13.8

 

0.91

0.364

Matched

0.1290

0.1532

− 7.2

47.7

− 0.38

0.702

 High school

Unmatched

0.3333

0.2456

19.3

 

1.26

0.208

Matched

0.3387

0.3951

− 12.4

35.6

− 0.65

0.518

 Technical

Unmatched

0.1515

0.1666

− 4.1

 

− 0.27

0.791

Matched

0.1451

0.1129

8.8

− 112.9

0.53

0.596

 Technological

Unmatched

0.0303

0.1228

− 35.2

 

− 2.12

0.036

Matched

0.0322

0.0564

− 9.2

73.8

− 0.65

0.517

 Undergraduate

Unmatched

0.1515

0.1403

3.1

 

0.20

0.838

Matched

0.1612

0.1612

0.0

100.0

0.00

1.000

 Graduate

Unmatched

0.0303

0.0614

− 14.8

 

− 0.92

0.359

Matched

0.0322

0.0249

3.8

74.1

0.27

0.788

Maximum educational level of father

 Elementary school

Unmatched

0.2878

0.1912

33.8

 

2.26

0.025

Matched

0.2741

0.1935

19.7

41.9

1.06

0.293

 Secondary

Unmatched

0.0454

0.1228

− 28.0

 

− 1.71

0.088

Matched

0.0483

0.0806

− 11.7

58.3

− 0.73

0.469

 High school

Unmatched

0.3030

0.2543

10.8

 

0.70

0.483

Matched

0.2903

0.3306

− 9.0

17.1

− 0.48

0.631

 Technical

Unmatched

0.1060

0.1052

0.3

 

0.02

0.987

Matched

0.1129

0.1693

− 18.3

− 6979.0

− 0.90

0.371

 Technological

Unmatched

0.0303

0.0964

− 27.3

 

− 1.66

0.099

Matched

0.0322

0.0161

6.6

75.6

0.58

0.563

 Undergraduate

Unmatched

0.1666

0.1842

− 4.6

 

− 0.30

0.768

Matched

0.1774

0.0967

21.1

− 359.7

1.30

0.195

 Graduate

Unmatched

0.0303

0.0438

− 7.1

 

− 0.45

0.652

Matched

0.3226

0.4839

− 8.5

− 19.0

− 0.45

0.651

Place of residence

 Commune 1—Popular

Unmatched

0.0606

0.0438

7.5

 

0.49

0.622

Matched

0.0645

0.0887

− 10.8

− 44.5

− 0.50

0.616

 Commune 3—Manrique

Unmatched

0.09091

0.0701

7.6

 

0.50

0.619

Matched

0.0967

0.0645

11.8

− 55.6

0.66

0.513

 Commune 4—Aranjuez

Unmatched

0.0757

0.0263

22.5

 

1.55

0.122

Matched

0.0806

0.0645

7.3

67.4

0.34

0.732

 Commune 7—Robledo

Unmatched

0.0757

0.0526

9.4

 

0.62

0.535

Matched

0.0806

0.1048

− 9.8

− 4.6

− 0.46

0.646

 Commune 8—Villa Hermosa

Unmatched

0.0606

0.0175

22.2

 

1.55

0.122

Matched

0.0483

0.0645

− 8.3

62.5

− 0.39

0.700

 Commune 9—Buenos Aires

Unmatched

0.0454

0.0614

− 7.1

 

− 0.45

0.655

Matched

0.0483

0.0564

− 3.6

49.4

− 0.20

0.842

 Commune 10—La Candelaria

Unmatched

0.0454

0.0614

− 7.1

 

− 0.45

0.655

Matched

0.0483

0.0564

− 3.6

49.4

− 0.20

0.842

 Commune 11—Laureles-Estadio

Unmatched

0.0606

0.0438

7.5

 

0.49

0.622

Matched

0.6452

0.0725

− 3.6

51.8

− 0.18

0.860

 Commune 12—La América

Unmatched

0.0303

0.0526

− 11.2

 

− 0.70

0.486

Matched

0.0322

0.0322

0.0

100.0

− 0.00

1.000

 Commune 13—San Javier

Unmatched

0.0454

0.0263

10.2

 

0.69

0.493

Matched

0.0483

0.0241

12.9

− 26.4

0.72

0.475

 Commune 15—Guayabal

Unmatched

0.1363

0.0263

40.8

 

2.90

0.004

Matched

0.0967

0.0806

6.0

85.3

0.31

0.755

 Commune 16—Belén

Unmatched

0.0303

0.0563

− 11.2

 

− 0.70

0.486

Matched

0.0322

0.1613

8.1

27.8

0.58

0.563

 Out of Medellin

Unmatched

0.1818

0.3245

− 33.1

 

− 2.09

0.038

Matched

0.1935

0.2338

− 9.3

71.8

− 0.54

0.588

  1. Source: Own elaboration
  2. at test for equal means between treated and control samples. p values < 0.10 indicate significant mean differences at 10%. p values > 0.10 indicate non-significant differences
  3. bStandardised percentage bias

Appendix 5: Aggregated diagnostic statistics for matching procedures

 

Pseudo R2a

LR testb

p > χ2b

Mean biasc

Median biasc

Out of common supportd

Unmatched sample

0.197

46.70

0.045

14.9

11.0

 

Matched sample

 NN(1)

0.075

12.88

0.999

8.9

8.4

4

 NN(1) with Caliper

0.107

15.66

0.993

10.2

7.6

13

 Kernel

0.042

7.30

1.000

6.8

5.9

4

  1. Source: Own elaboration
  2. aPseudo-R2 of propensity score model
  3. bLikelihood ratio test of insignificance of all regressors and p value
  4. cMean and median bias are summary indicators of the distribution of the abs(bias)
  5. dTreated observation out of common support

Appendix 6: Average treatment effects (matched differences in differences)

Finishing studies within the expected time

Treated

Controls

ATT

T stat

NN(1)

N = 176

− 0.04838

− 0.3225

0.2741

2.21**

NN(1) with Caliper

N = 167

− 0.0566

− 0.3396

0.2830

2.15**

Kernel

N = 176

− 0.0483

− 0.2845

0.2361

2.49**

  1. Source: Own elaboration
  2. *p value < 0.1; **p value < 0.05; ***p value < 0.01

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Gómez-Zapata, J.D., Herrero-Prieto, L.C. & Rodríguez-Prado, B. Does music soothe the soul? Evaluating the impact of a music education programme in Medellin, Colombia. J Cult Econ 45, 63–104 (2021). https://doi.org/10.1007/s10824-020-09387-z

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