The effect of age and selected characteristics on the asking price of movable property

The aim of this study was to quantify the impact of age and technical condition on the asking price of three categories of movable goods – passenger cars, smartphones, and laptops – and to compare the dynamics of their depreciation over time. Data were collected through web scraping of the Czech classified advertisement platform Bazos.cz; a total of 2,100 listings were obtained, with 1,350 observations retained after the data-cleaning process. The analysis encompassed descriptive statistics, multiple linear regression (linear and log-linear specifications), and a Random Forest model with hyperparameter tuning via GridSearchCV. Age was identified as the most significant price determinant across all examined categories. Smartphones exhibited the fastest depreciation, with an annual rate of 28.2%, followed by laptops at 14.4% and passenger cars at 5.2%. The Random Forest model achieved the best predictive performance for smartphones, reaching a coefficient of determination of 0.87 on the test set, while log-linear regression provided more stable results for passenger cars and laptops. Research limitations include reliance on a single data source, a pilot-scale sample size, missing information on technical condition, and the subjective coding of technical condition from advertisement descriptions.