MUSET-TE is a young independent teams research project dedicated to Modelling Uncertainty and Spatial Effects in Time. We forecast to reduce uncertainty. But, in the same time, we have a share of uncertainty when we address different aspects, and there are individual, time and spatial processes that condition this. The main goal of the present research proposal is to address uncertainty in the presence of spatial effects and see how they evolve in time. For this, we have two main research directions. The first one is assessing uncertainty in survey data based on ordinal responses. The main novelty of this research is that it takes the famous CUB model family and adds the longitudinal dimension by developing a new methodology to evaluate how uncertainty and feeling vary in time and within the sample. This new method is named CUBT (CUB in Time). In this way, the impact of latent variables like feeling and uncertainty will also be able to be modeled in datasets like repeated measurements or panel data. The new CUBT is developed and, after validation, implemented at least in R. After the new method construction, spatial effects are introduced to see how feeling and uncertainty vary not only in time, but also in space. This is the second research direction of this proposal. As a first step, a new dataset is constructed based on repeated measurements survey data collected in space. The new CUBT model will be used to address it. On the other hand, spatiotemporal effects will be evaluated in uncertain and volatile fields like cryptocurrencies. The newly developed Spatial ARCH model will be employed.
Codruța is Prof. of Statistics and Econometrics at the Babes-Bolyai University, Cluj-Napoca, Romania. She has been involved in several national and international projects, including MSCA projects or COST Actions. Her interests are related to Statistics, Econometrics and Spatial Econometrics applied for daily life, along with forecasting techniques.
Gabriela holds a PhD in Finance and is currently an Associate Professor in the Department of Finance at the Faculty of Economics and Business Administration, Babeș-Bolyai University. Her research interests span the fields of behavioral finance, economic psychology, insurance, and financial analysis.
Ioana is a lecturer at the Faculty of Economics and Business Administration, Babeș-Bolyai University from Cluj-Napoca, Romania. She received the PhD degree in management from the Babeș-Bolyai University in 2012, and obtained the habilitation in 2022 at the University of Economics in Bucharest, Romania. Her research interests relate to project management, governance, entrepreneurship. She took part of our MUSET-TE project team during the first year of implementation.
Mihai graduated on 2023 the Faculty of Economics and Business Administration, Babeș-Bolyai University, Cluj-Napoca, specialization Statistics and Economic Forecasting. His bachelor thesis was on determinants of shadow economy. in 2025, he graduated the Masters on Statistics, and currently he is a PhD student within the same Faculty.
Ștefana holds a PhD in Space-Time Predictive Econometrics and works as a Research Assistant in the Department of Mathematics-Forecasts Satistics in the Faculty of Economics and Business Administration at Babeș-Bolyai University. She teaches at Bachelor and Master levels and works as a Senior Data Science Consultant at Endava, with expertise in NLP, LLMs, (web)GIS, geospatial analysis, predictive modeling, spatial statistics, and econometrics using ML and GenAI.
Exploration of the CUB Models for modelling uncertainty and their relevance to the MUSET-TE project.
Listen to episodeHow CUB Models untangle preference from uncertainty in rating scales.
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