Probabilistic Infrastructure Deterioration Models with Panel Data

Statistical models of infrastructure facility deterioration are typically estimated using panel data sets of in-service facilities. For example, biannual ratings of bridges have been used to develop discrete models of component deterioration by a number of researchers. Unfortunately, these models have not accounted for the presence of heterogeneity in the panel data, which may lead to biased coefficient estimates. Furthermore, researchers have usually imposed a Markovian specification in the development of such models, implying that the probabilistic deterioration in a given period is independent of history. This assumption may be unrealistic for some types of facilities in which early distress initiation leads to accelerated deterioration in later stages of their lives. In this paper, we adopt a random-effects specification to control for heterogeneity in a probit model of bridge-deck deterioration and extend the model to investigate the presence of state dependence. The proposed model yields improved results in comparison with a simple probit model and provides evidence that is inconsistent with the Markovian assumption in bridge-deck deterioration. An implication of this study is that both heterogeneity and state dependence may need to be accounted for in developing probabilistic infrastructure deterioration models.

[1]  Samuel H Carpenter,et al.  PAVEMENT PERFORMANCE PREDICTION MODEL USING THE MARKOV PROCESS , 1987 .

[2]  Samer Madanat,et al.  Poisson Regression Models of Infrastructure Transition Probabilities , 1995 .

[3]  Moshe Ben-Akiva,et al.  ESTIMATION OF LATENT PAVEMENT PERFORMANCE FROM DAMAGE MEASUREMENTS . THIRD INTERNATIONAL CONFERENCE ON BEARING CAPACITY OF ROADS AND AIRFIELDS. PROCEEDINGS, NORWEGIAN INSTITUTE OF TECHNOLOGY, TRONDHEIM, NORWAY, JULY 3-5 1990. VOLUMES 1-2 , 1989 .

[4]  Wayne J. Davis,et al.  Optimal maintenance decisions for pavement management , 1987 .

[5]  Chamberlain Omitted Variable Bias in Panel Data: Estimating the Returns to Schooling , 1978 .

[6]  Paul Klieger,et al.  DURABILITY OF CONCRETE BRIDGE DECKS - A REVIEW OF COOPERATIVE STUDIES , 1970 .

[7]  Michael North,et al.  BRIDGE DECK PERFORMANCE IN VIRGINIA , 1973 .

[8]  William T. Scherer,et al.  Markovian Models for Bridge Maintenance Management , 1994 .

[9]  Kumares C. Sinha,et al.  APPLICATION OF DYNAMIC PROGRAMMING AND OTHER MATHEMATICAL TECHNIQUES TO PAVEMENT MANAGEMENT SYSTEMS , 1988 .

[10]  J. Heckman Heterogeneity and State Dependence , 1981 .

[11]  Sheldon M. Ross Introduction to Probability Models. , 1995 .

[12]  Cheng Hsiao,et al.  Analysis of Panel Data , 1987 .

[13]  R. McKelvey,et al.  A statistical model for the analysis of ordinal level dependent variables , 1975 .

[14]  Samer Madanat,et al.  Estimation of infrastructure transition probabilities from condition rating data , 1995 .