Predicting the movement of arriving passengers to their landside destination is of great value to airport landside operations. This paper focuses on the arriving passengers who leave the airport by private cars in the terminal parking lots. Disregarding the micro-behavior of passengers, we limit our focus on the time consumption for passengers from flight arrival to parking exit. Traditionally, this information is usually obtained through costly passenger questionnaires. To reduce cost, we develop an alternative way based on time series analysis. Specifically, we try to identify direct causal paths that exhibit significant positive effects, as the lag time to be estimated is the time distribution of these positive lag effects. To overcome the influence of confounding factors, we propose a practical methodology based on developing a set of distributed lag models under different control schemes. The key features of our approach are low data requirements and low mathematical complexity, which make it applicable in the daily operation of airports. We further conduct a case study at Shanghai Pudong International Airport (PVG) to illustrate the proposed methodology. The lag time estimation results are consistent with practical experiences. Sensitivity analyses validate the consistency and reliability of our results. Our research provides a practical way for estimating the lag time between flight arrivals and parking exit volumes, as well as more support for evaluating and improving airport landside operations.INDEX TERMS Airport landside operations, parking exit volumes, flight arrivals, time series analysis, distributed lag model.