Panel Data on a urban waste scenario generated via HyTex (Hybrid Textile) simulation model

Description

This is a longitudinal panel dataset that tracks textile waste generation across both spatial and temporal dimensions. This structure allows for the control of unobserved heterogeneity among collection points. The data is obtained by HyTex (Hybrid Textile) simulation model, combining both agent-based simulation and discrete-event simulation. HyTex model was calibrated using 2025 real-world data from the municipality of Parma, Italy. The panel data structure organises observations by N cross-sectional units (bins) observed over T time periods (weeks). Specifically, the panel consists of N = 145 bins, identified through their (x, y) coordinates within the model grid, observed over T= 158 weeks defined according to ISO standards. In addition to the bin and week identifiers, each unit includes the following observed variables: - Potential kg. Dependent variable of the model, representing the cumulative quantity citizens attempted to recycle at bin i-th during week t-th. - Generated kg. Total volume of waste generated by citizens assigned to bin i-th at week t-th. - Average GAw. Continuous variable ranging from 0 to 1, measuring the average propensity for sustainable behaviour (i.e., individual GAw) in week t, among all citizens assigned to bin i. This value is not fixed over time: behavioral dynamics within the simulation affect individual GAw levels, which in turn modify the weekly average observed at the bin level. It is important to clarify that by “citizens assigned to a bin” we refer to the individuals most likely to dispose of their textile waste in that specific bin. In the HyTex simulation, disposal behavior follows a distance-based mechanism: although the final choice of bin is stochastic, the probability of selecting a given bin decreases with the distance from the citizen’s residence. Accordingly, citizens are operationally assigned based on spatial proximity. Specifically, citizens assigned to bin i are those residing in the nodes for which bin i represents the nearest collection point, thus defining its primary catchment area according to a nearest-neighbor criterion within the spatial network. The panel is balanced, meaning there is exactly one observation for every entity at every time period, yielding 22,910 total observations. This completeness is what allows for the robust comparison between the Fixed-Effects (FE) model and benchmarks like Holt–Winters exponential smoothing.

Institutions

• University of Parma

  Emilia-Romagna, Parma

Categories

Funders

• SusTex: Sustainable Textile

  Grant ID: D53D23011410006

Licence