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My research fields are empirical industrial organisation, computational economics, and applied economics. In my current work, I study the estimation of high-dimensional dynamic demand systems. In my job market paper I develop a dynamic discrete-continuous demand model for storable goods. The model relaxes assumptions of existing models while retaining computational tractability. As a result it can capture rich intra- and inter-temporal substitution patterns and can be readily adapted for use in other storable good industries. In the paper, the model is applied to the UK laundry detergent sector
- Empirical Industrial Organisation
- Computational Economics
- Applied Economics
High-dimensional inventories and consumer dynamics: demand estimation for fast moving consumer goods
Abstract
This paper develops a high-dimensional dynamic discrete-continuous demand model for storable fast moving consumer goods. Assumptions of existing models are relaxed while retaining computational tractability. As a result, the model captures rich inter- and intra-temporal substitution patterns, allows for a detailed understanding of dynamic consumer behaviour, and provides a framework with wide applicability. To estimate and solve the dynamic demand model, I use techniques from approximate dynamic programming, large-scale dynamic programming in economics, machine learning, and statistical computing. In this paper I apply the model to the UK laundry detergent sector using household level purchase data.
- Lars Nesheim (UCL)
- Dennis Kristensen (UCL)
- Aureo de Paula (UCL)