(Almlund et al. 2011) (Table 7). The three socioemotional skills, by contrast, correlate little between each other in Malaysia, except for personal growth and relationship skills that correlate around 0.3, reflecting that they mostly capture different facets of socioemotional skills. The correlations between the digital skills subsets are modest for Malaysia but significant between basic and intermediate (0.3), much higher between intermediate and advanced (0.5). The correlation is close to zero between basic and advanced digital skills in Malaysia.<sup>40</sup> This may be due to employers who wish to hire workers with advanced digital skills assume that the potential hires already have basic digital skills, so they do not mention the basic skills in the job postings. The last correlation is lower than estimated for professional occupations in the U.S. that have a correlation of 0.2 between their basic and advanced digital skills (Deming and Kahn 2018).

An alternative methodology to consider not only pairwise relationships between skills subsets but possible systematic association between more subsets shows stronger complementarities.<sup>41</sup> Exploratory factor analysis finds that three groups of skills break out across the 9 digital, cognitive, and socioemotional subsets for Malaysia. The first factor is a mix of the three cognitive skills subsets, relationship skills (socioemotional) and basic digital skills (Table 8). It appears to be a factor of less digital skills for a broad range of occupations in Malaysia. The occupations with more of this skills mix are low- and medium digital occupations, such as government professionals and plant and machine operators (Annex Table A.5.1). The second factor is based on intermediate and advanced digital skills and to a lesser extent thinking skills (cognitive) and personal growth (socioemotional).<sup>42</sup> The typical occupations in Malaysia requiring a high weight on these kinds of skills are highly digital occupations, such as software developers and network professionals. The third factor heavily loads on the socioemotional skills subsets of emotions and personal growth.<sup>43</sup> Typical Malaysian occupations using this skill set include occupations from all three levels of occupation digitalization, such as architects and primary school teachers. Similar factors emerge for the other three countries.<sup>44</sup>

> 40 The other three countries and the unweighted occupation profile data find similar results (Annex Table A.4.1).

> 41 Very similar results are found when not rotating factors and using oblique rotations (i.e. allowing for correlations across factors) (results available upon request).

> 42 The socioemotional skills that weighed most heavily in this factor in Vietnam was organization and in Thailand was relationship skills (Annex Table A.4.2).

> 43 The third factor is the least stable across the alternative subsamples. For example, in Cambodia, it only weighs heavily on advanced digital skills. In Thailand, the highest factor loadings are on personal growth and a lower loading on intermediate digital skills, though very low basic skills, as in the Malaysia-weighted sample. The Vietnam-weighted sample also weighs very heavily on personal growth and very low on all other skills (Annex Table A.4.2).

> 44 A notable exception is that an “advanced digital” factor emerges for Cambodia. No other skills weight positively heavily in this factor while socioemotional skills are particularly negative (Annex Table A.4.2).

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