Option theory offers a useful way of modeling land value under uncertainty. While this approach underlies much theoretical analysis, the unanswered question is, to what extent does the market value of land reflect this option value? This paper exploits a unique natural experiment to obtain the first direct estimates of the option value of land based on observed transactions. Comparing land sold under constraints that strip away real options to land sold in the same market without such restrictions, we find that approximately 45% of the market value of developable land represents the value of these embedded real options.

Classic real options theory rests on two debatable assumptions: projects require a fixed investment and generate cash flows that follow a random walk. Relaxing both assumptions leads to radically different conclusions regarding the optimal timing of investment. We model investment using a Stone-Geary production function (Leontief and Cobb-Douglas are special cases) and growth as a mean-reverting Brownian motion. The solution method for this option valuation problem is non-trivial because the state space is two dimensional (level of the cash flow and its growth). For Leontief, the optimal policy is intuitive; the moment of investment involves a trade-off between the level of the cash ow and its growth. For Cobb-Douglas, in contrast, the optimal moment of investment depends only on the growth. More surprisingly, investment should be delayed when growth is high. This conclusion persists in the general Stone-Geary case. Applied to urban real estate, this suggests that up to 20% of cities should delay new construction because of high growth. The option value of vacant land may represent 60% of the value of new construction. High prices of vacant land may thus result from rational investor behavior rather than regulatory inefficiency. Our analysis should be widely applicable, for example to investment in high-growth companies.

"Classic real options theory rests on two debatable assumptions: projects require a fixed investment and generate cash flows that follow a random walk. Relaxing both assumptions leads to radically different conclusions regarding the optimal timing of investment. We model investment using a Stone-Geary production function (Leontief and Cobb-Douglas are special cases) and growth as a mean-reverting Brownian motion. The solution method for this option valuation problem is non-trivial because the state space is two dimensional (level of the cash flow and its growth). For Leontief, the optimal policy is intuitive; the moment of investment involves a trade-off between the level of the cash ow and its growth. For Cobb-Douglas, in contrast, the optimal moment of investment depends only on the growth. More surprisingly, investment should be delayed when growth is high. This conclusion persists in the general Stone-Geary case. Applied to urban real estate, this suggests that up to 20% of cities should delay new construction because of high growth. The option value of vacant land may represent 60% of the value of new construction. High prices of vacant land may thus result from rational investor behavior rather than regulatory inefficiency. Our analysis should be widely applicable, for example to investment in high-growth companies."--Abstract.

Urban structures and urban growth rates are highly persistent. This has far-reaching implications for the optimal size and timing of new construction. We prove that rational developers postpone construction not because prospects are gloomy, but because they are bright. The slow mean reversion in urban growth rates for the Netherlands and the United States (estimated at ~0.07 per annum) implies that a substantial share of cities should optimally postpone construction due to high growth. Observed heterogeneity in floorspace density across cities can be explained not by differences in population levels, but in growth rates.

Supporting investment profitability analysis and decision-making with real option analysis is an issue of increasing interest among both practitioners and managers. This special issue of the Journal of Applied Operational Research (JAOR) presents some new progress in applying real option analysis and valuation to real world problems in a number of industries.

Randall B, Lowe Piper & Marbury, L.L.R The issue of costing and pricing in the telecommunications industry has been hotly debated for the last twenty years. Indeed, we are still wrestling today over the cost of the local exchange for access by interexchange and competitive local ex change carriers, as well as for universal service funding. The U.S. telecommunications world was a simple one before the emergence of competition, comprising only AT&T and independent local exchange carriers. Costs were allocated between intrastate and interstate jurisdictions and then again, between intrastate local and toll. The Bell System then divided those costs among itself (using a process referred to as the division of revenues) and independents (using a process called settlements). Tolls subsidized local calls to keep the politi cians happy, and the firm, as a whole, covered its costs and made a fair return. State regulators, however, lacked the wherewithal to audit this process. Their con cerns centered generally on whether local rates, irrespective of costs, were at a po litically acceptable level. Although federal regulators were better able to determine the reasonableness of the process and the resulting costs, they adopted an approach of "continuous surveillance" where, like the state regulator, the appearance of rea sonableness was what mattered. With the advent of competition, this historical costing predicate had to change. The Bell System, as well as the independents, were suddenly held accountable.