Causal analysis Impact evaluation and causal machine learning with applications in R

From the beginning of our life as human being until its end, we are permanently confronted
with questions about causes and effects, i.e. the consequences of doing one thing versus another.
Should I rather eat croissants or muesli (the Swiss version of cereal) for breakfast to enjoy it
most? Should I rather go skiing or snowboarding to optimally benefit from the current snow
conditions (snowboarding on icy slopes can be a hassle, as the fans of winter sports among us
might know)? Should I study for my statistics exam next week or will I pass anyway? This also
applies to broader and possibly socially more relevant questions concerning politics, business
or work life, health, and society in general, as for instance: Will more education increase my
or anyone’s salary? Does a discount on a product or service increase sales? Do smoking and
drinking kill? Does a harsher punishment reduce crime? Do mothers work more when childcare
is for free? Does trade and globalization increase or reduce wealth and/or income equality?
Does free education foster a more egalitarian society in terms of opportunities?