【正文】 G. Wilmot, ,1 and G. Cheng, Abstract: The objective of this research was to develop a model that estimates future highway construction costs in Louisiana. The model describes overall highway construction cost in terms of a highway construction cost index. The index is a posite measure of the cost of construction labor, materials, and equipment。 the characteristics of contracts。 Costs。 also, they rise at an increasing rate each year into the future. Estimating future highway construction is the focus of this paper. The model developed in this study was developed with data from the Louisiana Department of Transportation and Development ~DOTD! and is therefore particular to that state. However, the methodology employed could be employed in other areas. Measuring Project Costs When construction in the field lags behind planned construction in the construction program, it is usually because the projects that have been constructed have cost more than anticipated. This is not random variation of actual costs about estimated costs, because, clearly, underestimates would cancel out overestimates over time in such a situation. Rather, it is evidence of a consistent underestimateof all projects collectively. The benefit of this is that it can be measured at the overall level, which is much easier to measure than at the individual project level. In the past, change in overall construction costs has been measured in terms of construction indices. These indices are weighted averages of the cost of a set of representative pay items over time. They have been used to display cost trends in the past. However, there is no reason why cost indices must be restricted to displaying past trends。 Hartgen et al. 1997） . Typically, construction costs have been collapsed in these analyses to a single overall expression of constructioncost such as the FHWA CBPI or the Engineering News Record’s Building Construction Index ~ENR BCI! or Construction Cost Index ~ENR CCI!. However, these types of models are usually only used for shortterm forecasting due to their reliance on the notion that past conditions are maintained in the future. Third, models have been established that describe construction costs as a function of factors believed to influence construction costs. The relationship between construction costs and these factors have been established from past records of construction costs. Typically, the models established in this manner have been used to estimate the cost of individual contracts. These models, with their relational structure, are the only models expected to provide reliable longterm estimates. The model developed in this study is of this type. Proposed Construction Cost Model It is clear that there are numerous factors that affect construction costs. However, it is striking that most construction cost models developed in the past have used only a few of the many influential factors identified above. One reason for this is that information is generally not available on many factors in data sets used to estimate models. Another reason is that information on the qualitative conditions surrounding each contract is difficult to obtain. These are problems that prevail in most circumstances and are difficult to overe. To mitigate against the effect of an inplete set of factors, two strategies can be employed. First, it may be possible to represent some of the absent factors by surrogate variables that are in the data set. For example, as mentioned earlier, annual bid volume has been used in the past as an inverse measure of the level of petition prevailing in the construction industry at that time （ Herbsman 1986） . Similarly, the number of plan changes each year can serve as a measure of design quality. Second, if the modeling of construction cost is changed from estimating the cost of individual projects to estimating overall construction costs each year, the modeling task is simplified. This is because it is no longer necessary to try to model individual projects in which conditions inflate the price in one case and deflate it in another, since such conditions would tend to cancel themselves out among projects in the same year. For example, firms that reduce their bid prices in an effort to win a particular contract could be balanced out within the same fiscal year by those that increase their prices because they already have enough work and are not particularly interested in winning the contract. Similarly, those firms with expertise in the type of construction required will be balanced out by those with low levels of expertise in that area. Thus, it is generally more tolerable to operate with fewer relevant factors when modeling at the aggregate or overall level than when modeling at the disaggregate level. The objective of this study is to establish a model, estimated on historical quantitative data, that incorporates as many relevant variables as possible and is capable of estimating the future overall cost of highway construction on an annual basis. The model is