Data for: Asymmetric fuel price responses under heterogeneity

Abstract of associated article: We explore the effect of cross-sectional aggregation of data on estimation and test of asymmetric retail fuel price responses to wholesale price shocks. The analysis is performed on data collected daily from individual fuel stations in the Spanish metropolitan areas of Madrid and Barcelona. While the standard OLS estimator is applied to an error correction model in the case of the aggregated time series, we use the mean group approaches developed by Pesaran and Smith (1995) and Pesaran (2006) to estimate the short- and long-run micro-relations under heterogeneity. We found remarkable differences between the results of estimations using aggregated and disaggregated data, which are highly robust to both datasets considered. Our findings could help to explain many of the results in the literature on this research topic. On the one hand, they suggest that the typical estimation with aggregated data clearly tends to overestimate the persistence of shocks. On the other hand, we show that aggregation may generate a loss of efficiency in econometric estimates that is sufficiently large to hide the existence of the “rockets and feathers” phenomenon.

本研究探讨了数据横截面聚合对不对称零售燃油价格对批发价格冲击响应的估计和测试的影响。分析基于从西班牙马德里和巴塞罗那都市区的独立加油站收集的每日数据。在聚合时间序列的情况下，我们应用了标准的最小二乘估计量对误差修正模型进行估计，同时采用Pesaran和Smith（1995年）及Pesaran（2006年）提出的均值组方法来估计异质性条件下的短期和长期微观关系。我们发现，使用聚合数据和分解数据进行的估计结果之间存在显著差异，这两种数据集都表现出高度稳健性。我们的研究结果有助于解释该研究领域文献中的许多结论。一方面，它们表明，使用聚合数据进行典型估计往往会导致对冲击持续性的高估。另一方面，我们展示了聚合可能会在计量估计中产生效率损失，这种损失足够大，以至于可能掩盖“火箭和羽毛”现象的存在。