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A marketable permit system (MPS) has been suggested as a solution to environmental problems. Although the properties of MPSs under non-trader settings, in which each player is exclusively either a seller or a buyer, are well documented, little research has explored how MPSs perform under trader settings, in which each player can be both a seller and a buyer. We institute two auctions of trader settings in MPS experiments: a double auction (DA) and a uniform price auction (UPA). We then evaluate and compare their performances both with each other and with those under non-trader settings. The main results are as follows: DAs under trader settings perform much worse than do DAs under non-trader settings, whereas UPAs perform well, regardless of the trader and non-trader settings. UPAs are more efficient and generate more stable prices than do DAs under trader settings, and a considerable proportion of trades in DAs under trader settings consist of “flips” that could be considered speculation or errors. Thus, UPAs are likely to work better than DAs under trader settings.

Most assets clear independently rather than jointly. This paper presents a model based on the uniform-price double auction which accommodates arbitrary restrictions on market clearing, including independent clearing across assets (allowed when demand for each asset is contingent only on the price of that asset) and joint market clearing for all assets (required when demand for each asset is contingent on the prices of all assets). Additional trading protocols for traded assets—neutral when the market clears jointly—are generally not redundant innovations, even if all traders participate in all protocols. Multiple trading protocols that clear independently can be designed to be at least as efficient as joint market clearing for all assets. The change in price impact brought by independence in market clearing can overcome the loss of information, and enhance diversification and risk sharing. Except when the market is competitive, market characteristics should guide innovation in trading technology.

Government agencies often rely on repeated discriminatory price auctions to procure ecosystem services from private landowners despite limited evidence on this mechanism’s performance. This study presents an agent-based model of a repeated discriminatory price procurement auction in which the auctioneer informs bidders of their respective bid outcomes and the average price of successful bids after each round. The model introduces a new learning algorithm through which bidders adapt to these price signals. Simulations are used to compare the mechanism’s performance to an equivalent uniform (second) price auction, providing several findings. First, the performance of the discriminatory mechanism tends to deteriorate over time relative to the uniform mechanism as bidders learn. Second, minimal changes in bidders’ price expectations have a large influence on the relative performance of the mechanisms. Third, the discriminatory mechanism maintains high levels of efficiency and cost-effectiveness over time if bidders have highly heterogeneous opportunity costs and neutral or moderately low price expectations. Fourth, the system’s price paths have a high degree of stochasticity and path dependency, making it difficult to predict a single realisation’s trajectory. Based on these findings, we provide several suggestions regarding auction design.

Procuring balancing power economically in accordance with the integration of variable renewable energy sources (VRE) presents a significant challenge. To meet this challenge, control reserves for balancing power have been traded through markets in many countries. Given the experience of European countries in this regard, there are two mainstream auction mechanisms in the balancing power market: uniform‐price and pay‐as‐bid auctions. For balancing power suppliers, one of the most important issues is how to determine the proper bidding strategy in the balancing power market to satisfy their profit‐maximising goals. On the other hand, it has become a trend for various players to participate in the balancing market through Virtual Power Plants (VPPs). In this paper, the fundamental characteristics of the above two auction mechanisms for tertiary control reserves are examined using a numerical simulation for VPP players based on the recommended practice for automatic generation control (AGC30) developed by IEEJ. The bidding strategy of each VPP player in the balancing power market is modelled using the Q ‐learning algorithm to maximise the player's expected profit under the uncertainty of imbalance. The clearing points in the balancing power market with the two auction mechanisms are compared based on simulation results.

We test the performance of deep deterministic policy gradient—a deep reinforcement learning algorithm, able to handle continuous state and action spaces—to find Nash equilibria in a setting where firms compete in offer prices through a uniform price auction. These algorithms are typically considered “model-free” although a large set of parameters is utilized by the algorithm. These parameters may include learning rates, memory buffers, state space dimensioning, normalizations, or noise decay rates, and the purpose of this work is to systematically test the effect of these parameter configurations on convergence to the analytically derived Bertrand equilibrium. We find parameter choices that can reach convergence rates of up to 99%. We show that the algorithm also converges in more complex settings with multiple players and different cost structures. Its reliable convergence may make the method a useful tool to studying strategic behavior of firms even in more complex settings.

I examine a model of a uniform price auction of a perfectly divisible good with private information in which the bidders submit discrete bidpoints rather than continuous downward sloping demand functions. I characterize necessary conditions for equilibrium bidding. The characterization reveals a close relationship between bidding in multiunit auctions and oligopolistic behaviour. I demonstrate that a recently proposed indirect approach to the revenue comparisons of discriminatory and uniform price auctions is not valid if bid functions have steps. In particular, bidders may bid above their marginal valuation in a uniform price auction. In order to demonstrate that discrete bidding can have important consequences for empirical analysis I use my model to examine a data set consisting of individual bids in uniform price treasury auctions of the Czech government. I propose an alternative method for evaluating the performance of the employed mechanism. My results suggest that the uniform price auction performs well, both in terms of efficiency of the allocation and in terms of revenue maximization. I estimate that the employed mechanism failed to extract at most 3 basis points in terms of the annual yield of T-bills worth of expected surplus while implementing an allocation resulting in almost all the efficient surplus. Failing to account for discreteness of bids would in my application result in overestimating the unextracted revenue by more than 50%.

During the liberalization process the UK regulatory authority introduced a behavioral remedy (through price-cap regulation) and structural remedy (through divestment series) in order to mitigate an exercise of market power and lower the influence of incumbent producers on wholesale electricity prices. We study the impact of these remedies on the dynamics of the wholesale electricity price during the peak-demand period over trading days. An extended autoregressive and autoregressive conditional heteroscedasticity (AR–ARCH) model with a novel skew generalized error distribution is used. This distribution allows one to capture the features of asymmetry, excess kurtosis, and heavy tails. The model is extended to include individual incumbent producers’ market shares and other explanatory variables reflecting seasonal patterns and regulatory regimes. We find that the structural remedy was more successful than the behavioral remedy because the effect of market share of the previously larger incumbent producer on the wholesale price is statistically insignificant. Moreover, after the second series of divestments, price volatility reduced.

Germany is among the leading countries regarding the promotion of renewable energy towards a sustainable energy system transition. In this paper, we investigate the German pilot auction scheme for solar photovoltaics introduced in the Renewable Energies Act 2014 (EEG 2014) that serves as a pilot for the auction-based promotion of the three major large-scale renewable electricity generation technologies (wind, solar, biomass) as of 2017. A strategic bidding model is used to determine the optimal bidding strategy and to determine the resulting project value. We consider pay-as-bid and uniform pricing and single and multiple bids. Moreover, we investigate the impact of investment cost uncertainty. In a sensitivity analysis we show how bid strategy adjustments affect the outcome. Specifically, higher uncertainty regarding the market clearing price increases the project value, as this additional uncertainty can be used to raise the probability of obtaining a higher level of remuneration by an adjusted auction strategy. The first-price auction can generate additional profits by placing a second, higher bid with a low probability of success. Investment cost uncertainty can have either a positive or negative impact on the project value, depending on the auction parameter values chosen.

This paper describes the design, implementation and results of a uniform-price reverse auction and real payment system to incentivize the avoidance of open-field burning of rice straw by smallholder farmers in Nepal. The main objective of the study was to reveal the private costs to farmers of avoiding rice straw burning. The study used survey and auction data from a sample of 317 farmers from 18 villages in Southern Nepal. Using a sealed bid one-shot reverse auction a level of payment was determined at which farmers would find acceptable to not engage in residue burning. Based on the bid amount, 167 winner farmers were enrolled in a real payment programme. The results revealed that 86 % of the farmers complied with the programme to refrain from burning rice straw with an average payment of US$ 78.76/ha of paddy farm, which represents US$ 13.17/ton of [Formula: see text] of emissions. To identify the policy variables, linear and log-linear regressions were fitted with the bid amount using socioeconomic variables. Land area, farmer education, practice of joint household decision making, wage rate for farm labour and straw yield increased the bid amount. The design and methods of field implementation of the reverse auction gave useful information for the advancement of conservation auctions and their replication in developing countries.

When agents (bidders) have multi-demand preferences, uniform price auctions are generally not immune to agents’ strategic manipulation, and they may achieve an inefficient allocation. We consider economies in which a large number of identical objects have to be allocated. Agents have quasi-linear preferences with non-increasing incremental valuations. We explore the incentives of agents in uniform price auctions. An important assumption on preferences is proposed, called “no monopoly.” It requires that preferences should be correlated in such a way that no agent’s incremental valuation for an additional object when he receives sufficiently many objects is higher than those of the other agents. We show that under no monopoly and other mild assumptions on preferences, as the number of objects goes to infinity, the payment in any uniform price auction converges to that in a Vickrey auction. We deduce that when there are sufficiently many objects, truth-telling is an approximate Bayesian Nash equilibrium in each uniform price auction.