Econometric models for pavement routine maintenance expenditure

Routine maintenance expenditures make up a significant fraction of the overall life-cycle costs incurred by highway agencies, and thus constitute a key input in cost evaluation. Most life-cycle cost analyses have proceeded only with very rough approximations of average annual maintenance expenditure due to difficulty in acquiring data. In addressing this issue, this thesis uses data from in-house maintenance records and other data sources to develop a cohesive and comprehensive dataset covering state highway pavement sections in Indiana, a state located in the wet-freeze climatic region in the United States. To assist in budgeting and life-cycle cost analysis, this thesis developed annual maintenance expenditure models using an array of statistical and econometric techniques, including ordinary least square, tobit, panel, and two-stage regression. This thesis identifies a number of explanatory variables that significantly influence maintenance expenditures and examines the sensitivity of the response to each of these variables. Specifically, the geographic region, pavement segment length, and age were found to be significant indicators annual routine pavement maintenance expenditure.