Juan M. C. Larrosa, Emiliano Gutiérrez, Gonzalo R. Ramírez Muñoz de Toro, Juan I. Uriarte
{"title":"A dynamic analysis of wine pricing in Argentina","authors":"Juan M. C. Larrosa, Emiliano Gutiérrez, Gonzalo R. Ramírez Muñoz de Toro, Juan I. Uriarte","doi":"10.1108/ijwbr-09-2021-0052","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe purpose of the study is to investigate micro determinants for dynamic wine pricing in Argentina. We test whether attributes and time affect the price rate of change. The rate of change is selected given the inflationary context of the country. The analysis provides valuable information for wine marketing decisions.\n\n\nDesign/methodology/approach\nThe modeling approach relies on panel data analysis for exploiting the data cross-section and time dimension. The contribution explores a massive price dataset at a weekly frequency. The dependent variable is the weekly price variation rate for product/wine and covariates are attributes, time and nominal variables. Given that endogeneity issues arose, the estimations rely on a two-stage least squares and instrumental variables with cluster-robust errors.\n\n\nFindings\nEstimations show that attributes, time and cost variables are statistically significant, with clear seasonal patterns and quality segmentation affecting pricing: wines made out of specific grapes such as Chenin, Merlot and Seedling or composing a broad category such as red wine, exhibit price undershooting (price rate of change below average). On the other hand, wines out of grapes such as Bonarda, Margaux, Mistela, Moscatel, Oporto, Tannat and Sauvignon Blanc show price overshooting (rate of change above average). In summary, wine made from determined grapes and specific wineries show divergent pricing.\n\n\nResearch limitations/implications\nCovariates such as alcohol content, label descriptor information, winery history, substitute competition and vintage, among others, have not been considered given that the research analyzes more than 750 wine products. Another limitation is that the work does not explore many time-series covariates, such as promotions and idiosyncratic shocks.\n\n\nPractical implications\nThe contribution presents new information on wine pricing patterns affected by weeks, months and years, including the effect of the prolonged 2020 Argentine lockdown. It also analyzes estimations on pricing at the level of grape/blend and wineries previously unknown in this market. The information can influence inventory decisions on the side of the sellers and purchase decisions on the side of consumers.\n\n\nSocial implications\nThe analysis includes fine but also low-cost wines that form part of the diet of low-income families in the country. The work detects a divergent pattern in pricing divided by the quality/price of the wine. It also presents information on price timing that may help consumers in the best moment to buy.\n\n\nOriginality/value\nThe contribution analyzes unprecedented information on weekly wine prices and presents evidence of pricing tactics from a point-of-sale perspective: It identifies different adjustment speeds related to product features and time effects.\n","PeriodicalId":46955,"journal":{"name":"International Journal of Wine Business Research","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Wine Business Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijwbr-09-2021-0052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 2
Abstract
Purpose
The purpose of the study is to investigate micro determinants for dynamic wine pricing in Argentina. We test whether attributes and time affect the price rate of change. The rate of change is selected given the inflationary context of the country. The analysis provides valuable information for wine marketing decisions.
Design/methodology/approach
The modeling approach relies on panel data analysis for exploiting the data cross-section and time dimension. The contribution explores a massive price dataset at a weekly frequency. The dependent variable is the weekly price variation rate for product/wine and covariates are attributes, time and nominal variables. Given that endogeneity issues arose, the estimations rely on a two-stage least squares and instrumental variables with cluster-robust errors.
Findings
Estimations show that attributes, time and cost variables are statistically significant, with clear seasonal patterns and quality segmentation affecting pricing: wines made out of specific grapes such as Chenin, Merlot and Seedling or composing a broad category such as red wine, exhibit price undershooting (price rate of change below average). On the other hand, wines out of grapes such as Bonarda, Margaux, Mistela, Moscatel, Oporto, Tannat and Sauvignon Blanc show price overshooting (rate of change above average). In summary, wine made from determined grapes and specific wineries show divergent pricing.
Research limitations/implications
Covariates such as alcohol content, label descriptor information, winery history, substitute competition and vintage, among others, have not been considered given that the research analyzes more than 750 wine products. Another limitation is that the work does not explore many time-series covariates, such as promotions and idiosyncratic shocks.
Practical implications
The contribution presents new information on wine pricing patterns affected by weeks, months and years, including the effect of the prolonged 2020 Argentine lockdown. It also analyzes estimations on pricing at the level of grape/blend and wineries previously unknown in this market. The information can influence inventory decisions on the side of the sellers and purchase decisions on the side of consumers.
Social implications
The analysis includes fine but also low-cost wines that form part of the diet of low-income families in the country. The work detects a divergent pattern in pricing divided by the quality/price of the wine. It also presents information on price timing that may help consumers in the best moment to buy.
Originality/value
The contribution analyzes unprecedented information on weekly wine prices and presents evidence of pricing tactics from a point-of-sale perspective: It identifies different adjustment speeds related to product features and time effects.