This article presents a method for measuring the functional efficiency of agricultural futures markets in terms of social welfare using a standard futures market structural model. Employing the concept of social surplus, it can be shown that, when futures prices are used to estimate future spot prices, the errors in prediction produce to some degree resource misallocation, which in turn results in welfare losses. Therefore, the social welfare associated with the presence of futures markets can be measured using a Social Loss index. The indicator was calculated for the period 1975-2015 and for several subperiods, which allow us to analyse functional efficiency before and after the 2007-2008 spikes in the prices of agricultural commodities. Futures contracts for 12 products are evaluated. The products are grouped in three different categories: 'soft products', 'livestock' and 'grains and oilseeds'. The results indicate that livestock contracts tended to be more efficient than the rest of the contracts during the whole period, but in 2008-2015 their efficiency decreased visa -vis the rest of the products. Nevertheless, 2008-2015 proved to be the most efficient subperiod, confirming the remarkable development of agricultural futures markets over time.
This paper proposes a method to estimate the functional efficiency of energy futures markets in terms of social welfare. Using a standard futures markets structural model, it can be concluded that the error committed when using futures prices at moment t to predict spot prices at t+1 results in welfare losses through resource misallocation. Therefore, the social welfare associated with the presence of energy futures markets can be measured using a social loss (SL) statistic and its components. This statistic is computed for six energy futures contracts with eight maturities each with data from April 1992 to December 2012. The results confirm the consistency and robustness of the method. Finally, several practical uses for the SL statistic are suggested.
Fines remain an essential mechanism of competition enforcement and should deter anticompetitive practices. This article quantifies the deterrent power of fines imposed by the Spanish competition authority from 2011 to 2015. First, we compare the evolution of fines over three sub-periods: From January 2011 to the creation of the CNMC on October 2013, since then until the Supreme Court’s judgment on fines on January 2015, and for the rest of 2015. The average fine per firm is similar in the first two periods but significantly lower in the third period, and now fines are more concentrated around the mean than before. Second, we define three scenarios – according to low, average or high values of the relevant parameters – for which we compute deterrence ratios to compare actual and optimal deterrent fines. The results show that most of the fines were under deterrent – a deterrence ratio lower than one – even when using the lower optimal fines of the lower scenario. More specifically, 80% of the actual fines are under deterrent in that scenario (close to 100% in the other two scenarios), and the average value of the fines imposed to these companies was on average 64% below the optimal deterrent fine, with slight changes across subperiods. We conclude that the fining policy of the Spanish competition authority between 2011 and 2015 should be considered significantly under deterrent.
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