# **IV. RESEARCH DESIGN AND METHODS**

With respect to the statistical model, this research utilizes ordinary least squares (OLS) multivariate regression equations to capture the associations between the variables<sup>114</sup> (see Annex 2 for a listing of all regression specifications). As such, in premise 1, the key independent variable is OGD and the regression specification aims to test its relationship on accountability, controlling for the Publicity condition, Political Agency condition, and log GDP. In premise 2, the key independent variable is accountability and the regression specification aims to test its relationship on service delivery—including both provision and outcomes—controlling for the Public Management condition and log GDP. Building on these first two regressions, in premise 3, the key independent variable is OGD and the regression specification aims to test its relationship on service delivery—including both provision and outcomes—controlling for the intermediating effects of accountability as well as log GDP. Finally, in premise 4, the key independent variable is OGD and the regression specification aims to test its relationship on service delivery—including both provision and outcomes—controlling for the Public Management condition, the Client Power condition, and log GDP.

# **_Sample Selection_**

Based on the most recently available data, the sample will include 25 countries in Sub-Saharan Africa<sup>115</sup> over a four-year period, 2013-2016. As such, the unit of analysis is country by year (e.g. Ghana 2014, Tanzania 2016, etc.) for a total of 86 data points.<sup>116</sup> These countries were chosen because they are at reasonably similar levels of human development and per capita income, which allows for good comparability between cases.<sup>117</sup> Likewise, the country sample presents relatively good variation with respect to the key variables over the period, allowing the research to better isolate key associations. Finally, the country selection will allow comparison at the sub-regional level, as key differences may emerge between the southern/eastern cluster versus the western cluster of African countries.

# **_Primary Variable/Indicator Construction_**

To perform these regressions, this research will rely on a customized data set that operationalizes the key variables, namely OGD, accountability, and service delivery provision and outcomes. All variables have indices that can be used to compare countries across the Sub-Saharan Africa region with respect to the levels of OGD and the resulting levels of accountability and service delivery. To address potential endogeneity issues, the direction of the relationship will be strengthened by the sequencing of data gathered, which would imply that OGD changes occur _prior_ to changes in accountability and service delivery.<sup>118</sup>

- **Open Government Data:** This index will draw upon the Open Data Barometer (ODB), produced on an annual basis by the World Wide Web Foundation, which scores countries on the openness of their data. In particular, the ODB analyzes global trends, and provides comparative data on countries and

> 114 In the future, more robust statistical techniques may be employed to the extent that data availability provides the necessary degrees of freedom to perform such analyses. The current limitations to doing so are discussed subsequently in the paper. 115 Twenty-five countries are included in the study, including: Benin, Botswana, Burkina Faso, Cameroon, Côte d’Ivoire, Democratic Republic of Congo, Ethiopia, Ghana, Kenya, Malawi, Mali, Mauritius, Mozambique, Namibia, Nigeria, Rwanda, Senegal, Sierra Leone, South Africa, Swaziland, Tanzania, Togo, Uganda, Zambia, and Zimbabwe.

> 116 While this number of data points allows for sufficiently significant and robust results, the n-size will be subsequently increased as more data become available in mid-/late-2019.

> 117 For instance, comparing countries in Sub-Saharan Africa with OECD countries, Latin America, or East Asia would not be as instructive as the latter are much closer to the frontier in key service delivery areas and would not have the same variation. 118 Fortunately, the data available support this method, since annual OGD evaluations are released in January of each year, and accountability and service delivery indicators are released in October, thus allowing a nine-month lag.

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