In continuation of the discussion on selecting control variables. For the case when there are too many variables have been found to be used as control variables, then we can divide them intro groups of social, economic, or financial variables and shorten them (using Factor Analysis) make indices of them (using Structure Analysis). This approach is common in cross sectional studies, especially when the data is collected via survey. Few examples in economics include (Arshed et al., 2017; Hassan et al., 2019)
This approach is handy when there is multicollinearity between the variables. Further details can be explored from Exploratory Factor Analysis and Confirmatory Factor Analysis. You can learn this approach in AMOS here.
Your participation and suggestions are welcomed
References
Arshed, N., Alamgir, S., & Aziz, O. (2017). Structural Determinants of Poverty in Pakistan. International Journal of Economics and Financial Research, 3(1), 1-7.
Hassan, M. S., Bukhari, S., & Arshed, N. (2019). Competitiveness, governance and globalization: What matters for poverty alleviation?. Environment, Development and Sustainability, 1-28.