We describe a case of web scraping data-based price indices implemented in a mid-size city in a moderate inflationary country. Full consumer price (CPI) and construction cost (CCI) indices were implemented for an entire city obtaining efficient results compared to statistics using traditional data collection methods. We state that web scraping combined with big data techniques will allow estimating more individualized and efficient metrics comparable in quality to official statistics. Web scraping technologies empower civil society and small research groups alike by allowing them gather and interpret socioeconomic data. It also helps to create new dimensions of analysis by allowing changes in frequency and focus on specific groups of products and services.

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.

En este trabajo se analizan las variaciones semanales en el precio de 300 presentaciones de yerba mate publicadas en línea, para el período comprendido entre diciembre de 2015 y febrero del 2021, considerando atributos propios del producto, eventos temporales, costos y fluctuaciones cambiarias, recurriendo a estimaciones econométricas basadas en Efectos Aleatorios (EA) y Mínimos Cuadrados Generalizados. Factibles (MCGF). Los resultados derivados estas estimaciones, presentan significatividad para todos los grupos de variables explicativas consideradas. El impacto de cada una de ellas resulta ser desigual sobresaliendo el tipo de cambio oficial y logaritmo del precio promedio como las que mayor influencia tienen sobre la decisión de variar el precio de venta.

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Se estudia la evolución semanal de los precios de cortes de carne vacunos a través de datos en línea. Se modela dinámicamente las tasas de variación de precios de los cortes de carne como determinadas por las variaciones en precios de bienes sustitutos, insumos, diversas variables del mercado cambiario, shocks de oferta y efectos temporales. Se modela econométricamente y los resultados muestran efectos de sobreajuste de precios a corto plazo en diversos cortes, efecto de sustitución entre carnes alternativas de corto y largo plazo, y un rol limitado a cortes puntuales del tipo de cambio y efectos semanales.