A consistent, four-moment-based approach for quantifying time and economic risks is presented. The goal is to produce a computationally economical approach that can be used to explore the time and economic feasibility of various strategies for executing and sequencing major work packages that describe an engineering project. A three-level hierarchy of variables is used, starting with time, cost and revenue performance at the work package/revenue stream level to net present value and internal rate of return at the project decision level. The treatment of correlations between primary variables at all levels of the hierarchy is included. A modified form of the probabilistic network evaluation technique (PNET) algorithm is presented for quantifying time uncertainty. Use of limiting values (0, 1) of the PNET transitional correlation provides bounds for all decision variables. A comparison with Monte Carlo simulation of a case study is presented to demonstrate the validity and the computational economy of the analytical approach. Key words: economic risk quantification, large engineering projects, probability analysis, moment analysis, Monte Carlo simulation.