Comparing the day temperature and holiday effects on retail sales of alcoholic beverages - a time-series analysis

Purpose Little research on the influence of external factors, such as weather and holiday periods, on retail sales on alcoholic beverages is available. This study aims to investigate how weekly retail sales of different alcoholic beverages vary in association with daily maximum temperatures and annual federal holidays across selected US counties in the years 2013 to 2015. The research provides information, which can contribute to better sales forecasts. Design/methodology/approach Secondary data of weekly retail sales (volume) of alcoholic beverages from 37,346 stores in 651 counties in the USA are analysed. The data cover on average 21% of all existing US counties and 12% of the total US off-trade retail sales of alcoholic beverages in the period studied (Euromonitor, 2017). Additional data of federal holidays and meteorological data are collated for each county in the sample. Seasonal autoregressive integrated moving average models with exogenous regressors (SARIMAX) are applied to develop forecasting models and to investigate possible relationships and effects. Findings The results indicate that off-trade retail sales of beer, liquor, red and white wine are temperature sensitive throughout the year, while contrary to expectations rose, sparkling and other wines are not. Sales sensitivities to temperature also differ by geography. In the warmest regions, liquor and white wine sales do not respond to temperature changes, as opposed to the coolest regions, where they are responsive. Public holidays, particularly Easter, Thanksgiving, Christmas and New Year holidays, represent a constant influencing factor on short-term sales increases for all investigated alcoholic beverage categories. Originality/value This is the first large-scale study of weather and holiday-related sales variations over time, across geographies and different alcoholic beverage categories. Seasonal and non-seasonal short-term sales variations are important for retailers and manufacturers alike. Accounting for expected changes in demand accommodates efficiencies along the supply chain and has implications for retail management, as well as adjusting marketing efforts in competing categories.