A second limitation of our analysis is that the estimated impact refers to the consumption response to a positive price shock. It is difficult to assess the extent to which the results would generalize to policy interventions inducing a fall in the price faced by consumers – e.g. binding price caps and subsidies. Indeed, existing research suggests that consumers react differently to price increases and decreases (see, e.g. Dargay [1993]).

A third caveat is that, while the tariff schedule we exploit offers a unique ground for examining consumption responses to price shocks, caution is needed in extrapolating our estimates to other price schemes. Upon exceeding the 1500 cubic meter threshold, households face both a discontinuous price shock and an increase in the marginal cost of each additional unit consumed. Furthermore, as discussed above, perfectly informed consumers could reverse this discontinuous shock on future bills with a small decrease in consumption. It is important to emphasize that this setting differs clearly from graduated price schemes, where consumers face a higher marginal cost for all consumption above a threshold but a lower rate for consumption below the threshold. Our estimates are potentially more informative on how consumers might be expected to respond to an across-the-board rate increase, in which the price of all units of gas (marginal and inframarginal) increases. However, valid extrapolation to those situations hinges on households believing that their efforts to reduce consumption have only a marginal effect, as opposed to a discontinuous effect, on subsequent bills. Although the evidence we provide suggests that consumers are generally unaware of (or do not understand well) the relevant threshold, and also that they do not manipulate strategically their gas consumption around it, we cannot exclude the possibility that (some) households realize that a marginal effort to reduce consumption might reduce discontinuously their subsequent gas bill.

With these caveats in mind, our paper offers solid evidence that prices do matter for energy consumption in energy markets, even over short-run durations. As Reiss and White [2008, pp.654] emphasize, this fact is important as it has not been widely recognized by policy makers, in part due to the absence of clear and unambiguous evidence of such behavior. It is therefore interesting to compare our estimates to those obtained in recent research on consumption responses to price changes in energy markets. At about -0.15, the short-run estimated elasticity we report is in line with recent estimates for the natural gas market.<sup>12</sup> Drawing on state-level panel data for the United States, Bernstein and Griffin [2006] estimate a short-run elasticity estimate of -0.12. Also for the United States, but using disaggregated panel data at the customer level in an instrumental variables approach, Davis and Muehlegger [2010] report an estimated price elasticity of demand of -0.28. Our estimates are also similar to those of recent studies using disaggregated data for the residential electricity market in California. Focusing on San Diego households, Reiss and White [2008] find that a price increase of 130% induced a consumption decline of 13% in about 60 days. Ito [2013] exploits a spatial discontinuity in service areas in southern California, which leads to nearly identical households experiencing different nonlinear price schedules, and estimates a short-run elasticity with respect to lagged average prices of - 0.11.<sup>13</sup> 14