Data on employment<sup>9</sup> come from several waves of standardized and harmonized household and labor force surveys (LFS).<sup>10</sup> Specifically, aggregate and sectoral employment data for Benin covering 2006, 2010, and 2015 were mainly taken from three waves of _Integrated Modular Survey on Household Living Conditions_ (EMICoV 2007, EMICoV 2011, and EMICoV 2015) and complemented with data from the World Bank’s _International Income Distribution Data Set_ (I2D2).<sup>11</sup> For Burkina Faso, sectoral employment data for 1998, 2005, 2009, and 2014 were extracted from the World Bank’s I2D2 database. The analysis for Côte d’Ivoire relies on standardized and comparable data on employment constructed based on information from the 2002 and 2008 household living standard surveys ‘ _Enquête Niveau de Vie des Ménages_ ’ (ENV 2002 and ENV 2008) and the 2014 Labor Force Survey (ENSETE<sup>12</sup> 2014).<sup>13</sup> To mitigate potential biases from data inconsistencies across surveys, the analysis focuses on major sectors. For all countries and periods, workers were categorized across sectors according to the latest revision of the International Standard Industry Classification (ISIC Rev. 4), which bears some distinctive features compared to earlier revisions. For instance, while fishing was classified as a separate economic activity in ISIC Rev. 3 and Rev. 3.1, it falls under the rubric of ‘ _agriculture, hunting and forestry_ ’ in the latest ISIC revision. We were unable to regroup a handful of sub-sectors due to a dearth of sectoral employment data. However, these economic activities represented only a negligible proportion of total employment and thus are unlikely to drive the empirical results.

Specifically, the decomposition analysis considers the following main sectors: agriculture (including fishing, hunting, and forestry), mining and quarrying (henceforth referred to as ‘mining’), manufacturing, utilities (electricity and water), construction, commerce (comprising wholesale and retail trade, and hotels and restaurants), transport and communications (hereafter ‘transport’), finance, and ‘other services’ (including public administration, education, health, real estate, renting and business activities, and community, social, and personal services). These sectors are grouped under ‘other services’ as they are relatively heterogeneous and thus not of particular interest here. In addition, as noted above, using more aggregated data helps dampen any potential bias associated with definitional changes across surveys.

We use data covering 2006 to 2015 for Benin, 1998 to 2014 for Burkina Faso, and 2002 to 2014 for Côte d’Ivoire. Special emphasis is, however, given to developments over the past decade because BBC generally experienced more robust and stable economic growth in recent years. Recent surveys generally use the latest ISIC revision and thus definitional discrepancies between surveys tend to be substantially smaller for the last decade compared to the 1990s and early 2000s. We could not use alternative time periods given the scantiness of data on sectoral employment. In other words, the cutoff points corresponding to each of the sub-periods above were determined by data availability.

This paper also benchmarks BBC against selected Asian and SSA economies using data from the Groningen Growth and Development Center (GGDC) database. We compare employment and

> 9Data on the number of workers by sector are based on the broadest employment concept, comprising self-employed, familyworkers and other informal workers.

> 10It should be pointed out upfront that we are fully cognizant of the potential shortcomings of the data on employment for the three countries. However, these are the only data available at our disposal and thus we rely on these imperfect figures. As shown later in this paper, analysis based on these data yields interesting insights about the pace and nature of structural change in BBC.

> 11We opted for the data from EMICoV given that it covers a longer period of time. However, the EMICoV data have been found to be generally consistent with the I2D2 data set. The employment data for 2015 had some aberrant observations which likely represent inexplicable measurement errors and need to be corrected prior to the empirical analysis. Thus, having checked our data against alternative sources and consulted several studies, we made some adjustments to the data to ensure consistency over time.

> 12ENSETE stands for _<mark>Enquête nationale sur la situation de l'emploi et du travail des enfants</mark>_ <mark>(National survey on the employment and child labor situation).</mark>

> 13It is important to note that these data are fairly consistent with those from the I2D2 data set at least for periods for which I2D2 data are available for Côte d’Ivoire. However, we use these employment data since they provide a more comprehensive and more recent picture of the labor market situation in Côte d’Ivoire.

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