c Denotes corresponding authors; * Denotes equal contribution
S. Cencic A large-scale analysis of the heterogeneity of markets’ reactions to the disclosure of non-financial information Under Review
S. Cencic, M. Burato, M. Rei, and M. Zolloc Business sustainability behaviour and alignment with global climate targets Submitted
S. Cencic, M. Rei, and M. Zollo An analysis of corporate sustainability behaviour through the lens of empirical fitness landscapes Under Review
M. Burato, S. Tang, V. Vastola, and S. Cencic. Organizational system thinking as a cognitive framework to meet climate targets. In preparation.
S. Cencic, H. Asgharian, L. Liu, M.Rei, M.Zollo. Sustainability behaviour in competitive environments. In preparation.
S. Cencic and S. Kealhofer A causal approach to test empirical capital structure regularities The Journal of Finance and Data Science 8, 214-232 (2022) Short summary. We derive and empirically test a structural causal model for the determinant of leverage ratios. Our findings provide support for the causal role of variables that measure the potential for information asymmetry concerning firms’ market values. Overall, our work provide a crucial step to connect capital structure theories with their empirical tests beyond simple correlations.
R.G. Krishnan, S. Cenci, L. Bourouiba Mitigating bias in estimating epidemic severity due to heterogeneity of epidemic onset and data aggregation Annals of epidemiology 65, 1-14 (2022) Short summary. We characterise bias in the estimation of 𝑅0 from a merged data set when the epidemics of the sub-regions, used in the merger, exhibit delays in onset. We propose a method to mitigate this bias, and study its efficacy on synthetic data as well as real-world influenza and COVID-19 data.
S. Cenci, L. P. Medeiros, G. Sugihara, and S. Saavedra Assessing the predictability of nonlinear time series under smooth parameter changes Journal of the Royal Society Interface 17, 162 (2020) Short summary. We develop a systematic methodology to estimate the predictability of nonlinear dynamical systems evolving in continuously changing environments.
S. Cencic and S. Saavedra Nonparametric estimation of the structural stability of non-equilibrium community dynamics Nature Ecology & Evolution 3, 912–918 (2019) Short summary. We develop a data-driven nonparametric framework to estimate the time-varying tolerance of non-equilibrium community dynamics to environmental perturbations from nonlinear time series
S. Cenci, G. Sugihara and S. Saavedra Regularized S-map for inferring and forecasting with noisy ecological time series Methods in Ecology and Evolution 10: 650– 660 (2019) Short summary. We introduce regularized locally weighted linear fits with state-space-dependent kernel functions to estimate Jacobian coefficients from nonlinear stochastic time series.
S. Cenci and S. Saavedra Uncertainty quantification of the effect of biotic interactions on community dynamics from nonlinear time series data Journal of the Royal Society Interface, 15: 20180695 (2018) Short summary. We propose a statistical analysis to estimate the uncertainty associated with time-varying parameters inferred from non-equilibrium time series data
S. Cenci∗, C. Song∗ and S. Saavedra Rethinking the importance of the structure of ecological networks under an environment-dependent framework Ecology Evolution 8: 6852– 6859 (2018) Short summary. We challenge the view that network structure is a good predictor of resilience in complex systems. We propose a research agenda to systematically investigate the structural risk associated with network structures under an environment-dependent framework
S. Cenci and S. Saavedra Structural Stability of Nonlinear Population Dynamics Physical Review E 97, 012401 (2018) Short summary. We study the structural stability of deterministic and stochastic nonlinear population dynamics models
S. Cenci, A. Montero-Casta o and S. Saavedra Estimating the effect of the reorganization of the interactions on the adaptability of species to changing environments Journal of Theoretical Biology 437: 115-125 (2018) Short summary. We introduce a novel statistical analysis to compare species’ likelihood to adapt to fast changing environments
S. Saavedra, S. Cenci, E. del-Val, K. Boege and R. P. Rohr Reorganization of interaction networks modulates the persistence of species in late successional stages Journal of Animal Ecology 86: 1136-1146, (2017) Short summary. We introduce a novel statistical analysis to reveal the effect of the reorganization of species interactions on community persistence during community assembly.
Abdelrehim, N., Cenci, S., Corsini, L., Dixon, J., Jones, C., Khanna, S., Mathison, C., Petersen, K. T., Turley, C., Whitmarsh, L. (2022). The Urgency of Climate Mitigation for COP27 and Beyond. UUCN Briefing.