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dr. M (Maryam) Hajialibeigi

dr. M (Maryam) Hajialibeigi

quantitative economist in agri-food market analysis

Biography

Biography

Maryam Hajialibeigi is a quantitative economist in agri-food market analysis at Wageningen Economic Research. Her work centres on understanding how agri-food markets respond to policy, regulation and structural change — and on building the quantitative tools that make those responses measurable.

She combines applied econometrics with machine learning to analyse demand, supply and price dynamics across EU agri-food sectors, and to produce medium-term outlooks that support both public policy and commercial strategy. Her modelling work spans structural and simulation-based market models, causal designs for isolating policy effects from market noise, and time-series and machine-learning methods for forecasting. Recent contributions include quantifying the economic trade-offs of sustainability measures in agricultural production, developing a composite food-safety index that makes complex risks usable in subsidy and investment appraisal, and integrating machine-learning surrogates into economic market models to extend their coverage and responsiveness.

Maryam holds a PhD in Quantitative Economics from Ilmenau University of Technology, where she spent a decade as a researcher and lecturer, publishing on financial regulation, merger control and the link between external knowledge sourcing and firm innovation. Before joining Wageningen she was a data scientist at Evonik Industries, building global demand-forecasting and market-segmentation systems — experience that shaped her conviction that a market model earns its keep only when the people making decisions can act on it.

She works primarily in R and Python, with an interest in reproducible analytical pipelines, interpretable forecasting, and translating quantitative market signals into evidence decision-makers can weigh.

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Expertise

Agricultural economics, Agricultural policy, Decision models, Econometrics, Economic policy, Algorithms, Analytical methods, Artificial intelligence - AI, Weather forecasting, Quantitative methods, Machine learning

Subdivision

International Policy