Identification of Hedonic Equilibrium and Nonseparable Simultaneous Equations

Chernozhukov, Victor; Galichon, Alfred; Henry, Marc; Pass, Brendan

doi:10.1086/712447

Cited by 13 publications

(2 citation statements)

References 53 publications

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“…There is a substantial body of research on economics and the empirics of hedonic price models. On the theory side, economists have developed a theory of demand in terms of product characteristics (Lancaster, 1966;McFadden, 1974); they also established various existence results and characterizations for the hedonic price functions under various assumptions (Berry et al, 1995(Berry et al, , 2004Ekeland et al, 2004;Chiappori et al, 2010;Chernozhukov et al, 2020); they developed the use of hedonic prices for bounding changes in consumer surplus and welfare . On the empirical side, economists have estimated a variety of hedonic price models and linked them to the consumer's utility (and marginal willingness to pay for certain characteristics), see Nesheim and others ( 2006) and also have used them for valuation of non-tradable goods (for example, valuation of the effects of improving the ecological environment on housing prices, e.g.…”

Section: Hedonic Prices and Hedonic Price Indicesmentioning

confidence: 99%

Hedonic prices and quality adjusted price indices powered by AI

2023

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Accurate, real-time measurements of price index changes using electronic records are essential for tracking inflation and productivity in today's economic environment. We develop empirical hedonic models that can process large amounts of unstructured product data (text, images, prices, quantities) and output accurate hedonic price estimates and derived indices. To accomplish this, we generate abstract product attributes, or "features," from text descriptions and images using deep neural networks, and then use these attributes to estimate the hedonic price function. Specifically, we convert textual information about the product to numeric features using large language models based on transformers, trained or fine-tuned using product descriptions, and convert the product image to numeric features using a residual network model. To produce the estimated hedonic price function, we again use a multi-task neural network trained to predict a product's price in all time periods simultaneously. To demonstrate the performance of this approach, we apply the models to Amazon's data for first-party apparel sales and estimate hedonic prices. The resulting models have high predictive accuracy, with R 2 ranging from 80% to 90%. Finally, we construct the AI-based hedonic Fisher price index, chained at the year-over-year frequency. We contrast the index with the CPI and other electronic indices.

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Section: Hedonic Prices and Hedonic Price Indicesmentioning

confidence: 99%

Hedonic prices and quality adjusted price indices powered by AI

2023

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“…Unfortunately, this solution to our technical problem comes at the cost of interpretability. Indeed, while the co-monotonicity condition (2) simply means that the two production functions h 0 and h 1 do not evolve in opposite directions, the cyclical co-comonotonicity condition (5) remains obscure despite attempts a finding justification for cyclical monotonicity in some applications (Chernozhukov et al, 2021;Shi et al, 2018).…”

Section: Challenges In Higher Dimensionsmentioning

confidence: 99%

An Optimal Transport Approach to Causal Inference

Torous,

Gunsilius,

Rigollet

2021

Preprint

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We propose a method based on optimal transport theory for causal inference in classical treatment and control study designs. Our approach sheds a new light on existing approaches and generalizes them to settings with high-dimensional data. The implementation of our method leverages recent advances in computational optimal transport to produce an estimate of high-dimensional counterfactual outcomes. The benefits of this extension are demonstrated both on synthetic and real data that are beyond the reach of existing methods. In particular, we revisit the classical Card & Krueger dataset on the effect of a minimum wage increase on employment in fast food restaurants and obtain new insights about the impact of raising the minimum wage on employment of full-and part-time workers in the fast food industry.

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Geometry of vectorial martingale optimal transportations and duality

Lim

2023

Math. Program.

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Identification of Hedonic Equilibrium and Nonseparable Simultaneous Equations

Cited by 13 publications

References 53 publications

Hedonic prices and quality adjusted price indices powered by AI

Hedonic prices and quality adjusted price indices powered by AI

An Optimal Transport Approach to Causal Inference

Geometry of vectorial martingale optimal transportations and duality

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