I'm struggling to understand how to effectively determine the time complexity of recursive code. While I can see how we can find the time complexity for code that has two recursive calls (e. g. recursive fib) as O(2^n), I struggle to dertime it when there are n recursions. Here is an example:

Quick note: I tried to come up with an easy example. I admit that there's very likely a formula to calculate size of the "powerset/superset" and gives us the work needed. My question is more generic and should relate to all times when one resursion can produce n additional recursions.

var subsets = function(nums) {
    const result = [];
    
    function traverse(arr, start) {
        result.push(arr)
       for (let i = start; i < nums.length; i++) {
           traverse([...arr, nums[i]], i + 1);
       } 
    }
    
    traverse([], 0)
    
    return result;
};