Background and Aims: Cross-sectional models are useful for estimating the impact that climate and climate change have on grape prices due to changes in grape composition. The aim of this study is to estimate the impact of growing season temperature (GST) on grape prices in Australia using cross-sectional data. Methods and Results: We use data on average price by cultivar and region for a 10Â year period. We estimate a model using (area-) weighted least squares and variables from a principal component analysis to control for 103 characteristics that relate to the production system used in each of 26 regions. Results suggest that a GST increase of 1Â°C leads to a decrease of 9% in the average price of grapes. A LASSO model that we use as a robustness check suggests similar results: a GST increase of 1Â°C leads to a decrease of 7.3% in the average price of grapes. Conclusions: Failing to control for characteristics that relate to the production system overestimates the impact of GST on grape prices, suggesting that changes to variables in a production system may mitigate deleterious changes to grape composition due to climate change. Significance of the Study: This study contributes to the understanding of the issue of omitted variable bias in cross-sectional models, and how to deal with this issue when analysing the impact of climate and climate change in grape and wine research.