Pricing Models for German Wine: Hedonic Regression vs. Machine Learning

2020 ◽  
Vol 15 (3) ◽  
pp. 284-311
Author(s):  
Britta Niklas ◽  
Wolfram Rinke
Keyword(s):  
Machine Learning ◽  
Explanatory Power ◽  
Pinot Noir ◽  
Hedonic Price ◽  
Grape Variety ◽  
Weather Variables ◽  
Hedonic Price Models ◽  
Maximum Temperatures ◽  
Log Linear ◽  
Quality Categories

AbstractThis article examines whether there are different hedonic price models for different German wines by grape variety, and identifies influential factors that focus on weather variables and direct and indirect quality measures for wine prices. A log linear regression model is first applied only for Riesling, and then machine learning is used to find hedonic price models for Riesling, Silvaner, Pinot Blanc, and Pinot Noir. Machine learning exhibits slightly greater explanatory power, suggests adding additional variables, and allows for a more detailed interpretation of results. Gault&Millau points are shown to have a significant positive impact on German wine prices. The log linear approach suggests a huge effect of different quality categories on the wine prices for Riesling with the highest price premiums for Auslese and “Beerenauslese/Trockenbeerenauslese/Eiswein (Batbaice),” while the machine learning model shows, that additionally the alcohol level has a positive effect on wines in the quality categories “QbA,” “Kabinett,” and “Spätlese,” and a mostly negative one in the categories “Auslese” and “Batbaice.” Weather variables exert different affects per grape variety, but all grape varieties have problems coping with rising maximum temperatures in the winter and with rising minimum and maximum temperatures in the harvest season. (JEL Classifications: C45, L11, Q11)

Modeling Urban Systems

2012 ◽  
pp. 322-351 ◽  
Author(s):  
John D. Landis
Keyword(s):  
Land Use ◽  
Urban Growth ◽  
Travel Behavior ◽  
Growth Models ◽  
Urban Systems ◽  
Economic Base ◽  
Hedonic Price ◽  
Hedonic Price Models ◽  
Different Types ◽  
Behavior Models

This article examines the different types of urban model used in urban planning in North America, and to a lesser extent, in Europe, Asia, and South Americam, which include the population-projection models, economic base models, hedonic price models, and travel-behavior models. It describes emerging procedures such as land-use change and urban-growth models, and looks at Charles Tiebout's model of efficient public choice and Thomas Schelling's model of spatial segregation.

Retail strategies for rosé wines in Italy: a hedonic price analysis

2019 ◽  
Vol 31 (3) ◽  
pp. 282-302 ◽  
Author(s):  
Luca Rossetto ◽  
Luigi Galletto
Keyword(s):  
Model Performance ◽  
Hedonic Model ◽  
Hedonic Price ◽  
Hedonic Analysis ◽  
Grape Variety ◽  
Content Type ◽  
Hedonic Price Analysis ◽  
The Usa ◽  
Data Survey ◽  
Rosé Wine

Purpose The purpose of this paper is to analyze the market of rosé wines in Italy, to outline retail strategies and to investigate to what extent the price is affected by branding these wines. Design/methodology/approach A survey has been carried out on retailers by collecting data about wines as intrinsic attributes (grape variety, blending, origin, alcohol content, etc.) and extrinsic attributes (brand, price, packaging, etc.) and about outlet and retail environment. The hedonic analysis required a rearrangement of data survey, while a Box-Cox transformation allowed to control the strong heteroskedasticity detected of the data. Findings Results provide strategies for still, semi-sparkling and sparkling rosé market segments. Still rosé wines are strongly differentiated, while the price is affected by the appellation, grape variety, blending, brand and outlet features. Two main strategies are suggested: the first focuses on appellations endorsing consumer’s brand loyalty; the second is driven by retailers while involving weaker brands. Different pictures emerged for semi-sparkling and sparkling wines, as producers and retailers tend to follow consumer’s preferences for fresh and easy drinking wines as well as to extend the product assortment. Research limitations/implications Results for sparkling rosé wines cannot be generalized. The high fragmentation hinders the hedonic model performance in capturing the price effects of brands, appellations, grape variety and wine blend. Practical implications The hedonic analysis provides suggestions for rosé wine producers that should reinforce their brand through associations among intrinsic attributes, such as appellation, and extrinsic ones, such as price, while satisfying retailer requirements. Originality/value The paper contributes to the knowledge base about the Italian rosé wine market, which is mostly export-oriented. Model results help to understand why the domestic consumption is stagnant with respect to other countries such as France or the USA.

Microstructure in the Machine Age

2020 ◽  
Author(s):  
David Easley ◽  
Marcos López de Prado ◽  
Maureen O’Hara ◽  
Zhibai Zhang
Keyword(s):  
Machine Learning ◽  
Market Efficiency ◽  
Predictive Power ◽  
Explanatory Power ◽  
Futures Contracts ◽  
Machine Age ◽  
Price Process ◽  
Out Of Sample ◽  
Asset Classes ◽  
Out Of Sample Prediction

Abstract Understanding modern market microstructure phenomena requires large amounts of data and advanced mathematical tools. We demonstrate how machine learning can be applied to microstructural research. We find that microstructure measures continue to provide insights into the price process in current complex markets. Some microstructure features with high explanatory power exhibit low predictive power, while others with less explanatory power have more predictive power. We find that some microstructure-based measures are useful for out-of-sample prediction of various market statistics, leading to questions about market efficiency. We also show how microstructure measures can have important cross-asset effects. Our results are derived using 87 liquid futures contracts across all asset classes.

scholarly journals Flooding risks and housing markets: a spatial hedonic analysis for La Plata City

2016 ◽  
Vol 21 (4) ◽  
pp. 464-489 ◽  
Author(s):  
Mariano Javier Rabassa ◽  
Juan Ignacio Zoloa
Keyword(s):  
Housing Markets ◽  
Hedonic Price ◽  
La Plata ◽  
Hedonic Price Models ◽  
Flooding Event ◽  
Hydraulic Infrastructure ◽  
Real Estate Prices ◽  
Spatial Hedonic Price Models ◽  
The City ◽  
La Plata City

AbstractOn 2 April 2013 a major flood struck the City of La Plata, Argentina, killing 89 people and displacing thousands of others. That event, the worst flood the city has suffered in the past 100 years, prompted plans for a new hydraulic infrastructure. Although such an investment is necessary, little is known about its benefits. This paper intends to shed some light on this issue by estimating the willingness to pay to avoid the risk of experiencing a flooding event. For this purpose, we have taken thousands of real estate prices in the La Plata Metropolitan Area and combined them with a high-resolution flood risks map to estimate spatial hedonic price models. The results show significant price discounting for properties in flood-prone areas.

scholarly journals Climate zoning of the Burgundy winegrowing region

2018 ◽  
Vol 50 ◽  
pp. 01003
Author(s):  
Catinca Gavrilescu ◽  
Yves Richard ◽  
Daniel Joly ◽  
Benjamin Bois
Keyword(s):  
Heat Stress ◽  
Regional Climate ◽  
Pinot Noir ◽  
The South ◽  
Time Step ◽  
Phenological Model ◽  
Wine Production ◽  
Frost Risk ◽  
Maximum Temperatures ◽  
The Impact

As one of the most emblematic wine regions of cool climate terroir viticulture, Burgundy is endowed with a set of very specific natural features suitable to the production of high quality wines, where climate is arguably one of the main factors to profoundly influence vine physiology/phenology and grape composition. These environmental nuances have led to a wide variety of styles in Pinot noir and Chardonnay wines that have been largely acknowledged and appreciated by the international market and vitivinicultural industry. However, individual grape varieties optimum quality is known to be closely related to well-defined climate and geographical ranges. Climate change and global warming latest trends make them more susceptible to undergo modifications in terms of berry ripening processes and advancements in harvest dates due to short-term and long-term spatiotemporal fluctuations in climate variability. The impact of air temperature on grapevine development and harvest outcomes has been widely documented by the scientific community, its influence translating as quality and quantity fluctuations in space (“terroir” effect) and time (“vintage” effect). Through this study we aim to assess the extent of these threats by means of modelling and spatializing the regional climate variations based on 5 agricultural climatic indices: the number of days with temperatures equal or greater than 35°C (heat stress), the number of days indicating a frost risk (equal or greater than -1°C), the mid-flowering, the mid-véraison and the theoretical grape maturity (200g/l of sugar) occurrence dates. Mid-flowering, mid-véraison as well as the theoretical grape maturity were estimated through the summation of temperatures over 10°C (starting 1st of March) based on the GFV (Grapevine Flowering Véraison) linear phenological model and were calculated for the 2 prime varieties cultivated in Burgundy (Chardonnay and Pinot noir). Daily minimum and maximum temperatures issued from a network of 64 weather stations scattered throughout the main 9 wine production subregions of Burgundy were spatially interpolated on a grid with a 75m resolution over a 41751ha area (74556 pixels). Spatial interpolations were performed at a daily time step integrating various topographical features through a regression-kriging model for the 2011-2015 period. Daily grid minimum and maximum temperatures were further used to calculate the 5 agroclimatic indices for each of the years of the study period. The entirety of the 74556 pixels were later classified at regular intervals in 6 groups which were assigned to each of the three phenological stages: “very early”, “early”, “intermediate”, “late”, “very late” and “variable”. The number of heat stress days as well as those presenting a frost risk were equally classified based on their occurrence as “very rare”, “rare”, “intermediate”, “frequent” and “very frequent”. The annual spatial structure of the individual classes was very similar due to temperature distribution being strongly governed by terrain features. We were able to identify observable differences between the north and the south subregions of Burgundy with a potential variation ranging from 7 to 15 days in terms of phenological and theoretical maturity occurrence dates. Côte de Nuits and Côte de Beaune vineyards indicate similar climate characteristics with early phenological timing (97% and 82% respectively of the area classified as “early”) and little frost and heat risks. The number of days with a frost risk is a lot more elevated in the Côte Châtillonnaise and the Chablis subregions, while the number of heat stress days was larger in the subregions located in the south of Burgundy.

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