ECONOMIC FOUNDATIONS OF OHIO RIVER NAVIGATION INVESTMENT MODEL
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- land use - planning, ridership - elasticity, ridership - demand, policy - environment, economics - willingness to pay, organisation - management, mode - rail; Willingness to pay; Water transportation; Supply; Regulatory policy; Rates; Railroad transportation; Rail transportation; Policy; Policies; Ohio River Navigation Investment Model; Ohio River; Maritime transport; Marine transportation; Inland waterways; Improvements; Government policy; Estimates; Environmental policy; Environmental planning; Environmental management; Energy utilization; Energy consumption; Elasticity (Economics); Economic models; Demand; Decision making; Cost benefit analysis; Bias (Statistics); Benefit cost analysis
The Ohio River Navigation Investment Model (ORNIM) estimates the benefits of navigation improvements and balances those estimated benefits against the estimated costs of improvements. The economic assumptions within ORNIM are identified; the rationale for these assumptions is provided; and how these assumptions alter the estimates of inland-water navigation benefits, as compared with those of the theoretical model, are addressed. ORNIM is a spatially detailed partial equilibrium model that incorporates the following assumptions: (a) demand for individual movements, provided exogenously, is perfectly inelastic; (b) willingness to pay (WTP) for individual river movements is equal to the exogenously given least-cost alternative rail rate; and (c) the supply of rail for individual movements is perfectly elastic at the exogenously given rail rate. The first assumption biases upward estimates of with-project benefits. However, empirical evidence on demand elasticity and WTP suggests that these assumptions are reasonable in the short run. In the long run, decisions to move cargo by water depend only in part on river rates, with environmental and energy policies also being critical. The demand for waterway movements is determined exogenously to ORNIM, and the U.S. Army Corps of Engineers' recent scenario-based approach to demand projection is laudable. The third assumption unequivocally biases downward ORNIM's estimate of with-project benefits. Future ORNIM enhancements include improvements in analyzing congestion fees, environmental externalities, traffic management, and system reliability as well as improvements in data quantity and quality. ORNIM, like other navigation models, is data constrained. Without significant data improvements, attempts to relax economic assumptions within ORNIM are of questionable value.