The impacts of school management reforms in Madagascar: do the impacts vary by teacher type?

Abstract

This paper exploits a recently implemented randomised control trial in Madagascar that focused on management reforms. It investigates whether the impact of the reforms varies by the type of teacher. This is an important issue because Madagascar, like many other developing countries, has recently hired a large number of contract or temporary teachers, who have less training but may be motivated to work harder in order to have their contracts renewed. The management reforms did not have any impact on student test scores. This lack of an impact holds for all types of teachers. It may be that two years is not enough time for the programme to have had a measurable impact, but it is also possible that the programme is ineffective, at least in the context of Madagascar's educational system.

Keywords:

• education
• school management
• developing countries
• Madagascar

Acknowledgements

The authors are indebted to Esther Duflo for her contribution to setting up the experimental design for this impact evaluation. They also thank the staff at Madagascar's Ministry of Education, led by Tahinarinoro Razafindramary and Paul Randrianirina, and the staff of Aide et Action for help in designing the workflow tools, implementing the experiment, and collecting the data. The authors also appreciate Pierre-Emmanuel Couralet and Erika Strand for on-the-ground supervision during the experiment, and Mathieu Laroche and Muriel Nicot-Guillorel for technical support to the Malagasy counterparts. The authors also thank Sajitha Bashir, Benu Bidani, Robert Blake, Deon Filmer, Elizabeth King, Arianna Legovini, Robert Prouty, Lina Rajonhson, Patrick Ramanantoanina, and Venkatesh Sundararaman who provided input, advice, and comment to guide the design of the experiment, among them. Finally, the authors acknowledge the support of the World Bank and the governments of France, Ireland, Madagascar, and Norway, as well as that of the donor partners of the Education for All Fast Track Initiative through the Education Program Development Fund.

Notes

1.More details on the AGEMAD programme are given below in Section 3.

2.Tools that are necessary for a teacher to properly manage his/her classroom and teach more effectively.

3.Well-managed schools are defined as schools where ‘the school director and all the teachers perform all their essential tasks’ (Lassibile et al. 2010, p. 10). See Table A.1 in Appendix 1 for a list of the essential tasks.

4.See Angrist and Pischke (2009, pp. 22–24) on this point. They also point out that adding controls could increase precision, as explained in the next paragraph, but that this is not necessarily the case.

5.Separate results for each subject (available from the authors on request) are similar to the overall numbers. For example, when the regressions in Table 4 are estimated for each subject, all the intervention effects are insignificant.

6.The standard errors in Table 4 allow for heteroskedasticity of unknown form, including allowing for arbitrary correlation in the error terms of the estimated equations for any schools in the same CISCO. Clustering at the ZAP or the school level reduces the standard errors somewhat, but not enough to lead to statistically significant results.

7.Adding covariates and interaction terms reduces the sample size by about 10–15 per cent. This raises the possibility that any changes in results due to the introduction of covariates and interaction terms is due to a change in the sample, not the change in the specification. To check this, we re-estimated all regressions including only observations that had all the covariates and interaction terms; the results (available from the authors) were essentially unchanged.

8.A related issue is whether student characteristics varied by type of teacher. In fact, there is very little variation of this type. For example, the distribution of high-income (low-income) students by type of teacher was: 55.7 per cent (51.8 per cent) had regular civil service teachers; 7.3 per cent (8.3 per cent) had regular contract teachers; 33.7 per cent (37.6 per cent) had FRAM contract teachers; and 3.2 per cent (2.3 per cent) had student-teachers.