Abstract
AbstractThis paper applies alternative panel data models to a cross‐sectional dataset that contains observations at the plot level for a sample of wine‐grape farms in Central Chile. The input–output data as well as key attributes of the production system are at the plot level, at which individualized management exists. However, plots belonging to a particular farm are also subject to overall centralized (farm‐level) management. Thus, this data configuration offers the possibility of analyzing technical efficiency (TE) both across plots and across farms. A Generalized True Random Effects model, which permits the separate identification of farm‐level and plot‐level inefficiency while controlling for unobserved farm‐level heterogeneity, shows that TE varies across farms but not among plots within the same farm. Geographical location also affects grape production and agro‐climatic conditions influence production levels, with grape farms located on cooler zones producing significantly less than their counterparts in warmer zones, as expected. The analysis underscores the value of using recent methodologies typically applied to panel data when cross‐sectional information is available for individual plots within a farm unit or in similar settings.
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