Ascending combinatorial auctions are being used in an increasing number of spectrum sales worldwide, as well as in other multi-item markets in procurement and logistics. Much research has focused on pricing and payment rules in such ascending auctions. However, recent game-theoretical research has shown that such auctions can even lead to inefficient perfect Bayesian equilibria with risk-neutral bidders. There is a fundamental free-rider problem without a simple solution, raising the question whether ascending combinatorial auctions can be expected to be efficient in the field. Risk aversion is arguably a significant driver of bidding behavior in high-stakes auctions. We analyze the impact of risk aversion on equilibrium bidding strategies and efficiency in a threshold problem with one global and several local bidders. Due to the underlying free-rider problem, the impact of risk-aversion on equilibrium bidding strategies of local bidders is not obvious. We characterize the necessary and sufficient conditions for the perfect Bayesian equilibria of the ascending auction mechanism to have the local bidders to drop at the reserve price. Interestingly, in spite of the free-riding opportunities of local bidders, risk-aversion reduces the scope of the non-bidding equilibrium. The results help explain the high efficiency of ascending combinatorial auctions observed in the lab.