The Italian Electricity Prices in Year 2025: an Agent-Based Simulation

In this paper, we build a realistic large-scale agent-based model of the Italian dayahead-electricity market based on a genetic algorithm and validated over several weeks of 2010, on the basis of exact historical data about supply, demand and network characteristics. A statistical analysis confirms that the simulator well replicates the observed prices. A future scenario for the year 2025 is then simulated, which takes into account market’s evolution and energy vectors’ price dynamics. The future electricity prices are contrasted with the ones that might arise considering also the possible (yet unlikely) construction of new nuclear power (NP) plants. It is shown that future prices will be higher than the actual ones. NP production can reduce the prices and their volatility, but the size of the impact depends on the pattern of the expected demand load, and can be negligible.Electricity market, PUN, Agent-based computational economics, Nuclear power.

Cost Efficiency and Returns to Scope in Italian Investment Firms

This paper estimates cost efficiency and returns to scope of Italian investment firms during the period 1998-2002, following the stochastic frontier function approach. Results indicate a large inefficiency for Italian investment firms (with a high standard deviation across sample) and the absence of significant returns to scopeStochastic Frontier, Efficiency, Returns to scope, Investment Firms

Collective reputation with stochastic production and unknown willingness to pay for quality

In many cases, consumers cannot observe a single firm\u2019s investment in environmental quality or safety, but only the average quality of the industry. The outcome of the investment is stochastic, since firms cannot control perfectly the technology or external factors that may affect production. In addition, firms do not know consumers\u2019 valuation of quality. We characterize the solution of the firms\u2019 investment game and show that the value of stopping investments when firms are already investing in quality can be negative when the free-riding incentives dominate. The existence of systematic uncertainty on the outcome of investment slows down investment in quality, compared to a situation without uncertainty. The uncertainty on consumers\u2019 willingness to pay for quality can speed up or slow down investment. We also obtain the counterintuitive result that information acquisition may decrease the overall level of quality

Quasi-option value under ambiguity

Real investments involving irreversibility and ambiguity embed a positive quasi-option value under ambiguity (q.o.v.a.), which modifies the evaluation of an investment decision involving depletion of natural resources by increasing the value of delaying. Q.o.v.a. depends on the specific decision-maker attitude towards ambiguity, expressed by a capacity on the state space. An empirical measure of q.o.v.a. is pointed out. Exploiting the properties of a capacity and its conjugate, the relationship has been established between the upper and lower Choquet integral with respect to a subadditive capacity and the bid and ask price of the underlying asset (output) of the investment decision. The empirical measure of q.o.v.a. is defined as the upper bound of the opportunity value. As an example, q.o.v.a. is applied to evaluate an off-shore petroleum lease under ambiguity.

Endogenous equilibria in liquid markets with frictions and boundedly rational agents

In this paper we propose a simple binary mean field game, where N agents may decide whether to trade or not a share of a risky asset in a liquid market. The asset's returns are endogenously determined taking into account demand and transaction costs. Agents' utility depends on the aggregate demand, which is determined by all agents' observed and forecasted actions. Agents are boundedly rational in the sense that they can go wrong choosing their optimal strategy. The explicit dependence on past actions generates endogenous dynamics of the system. We, firstly, study under a rather general setting (risk attitudes, pricing rules and noises) the aggregate demand for the asset, the emerging returns and the structure of the equilibria of the asymptotic game. It is shown that multiple Nash equilibria may arise. Stability conditions are characterized, in particular boom and crash cycles are detected. Then we precisely analyze properties of equilibria under significant examples, performing comparative statics exercises and showing the stabilizing property of exogenous transaction costs.Endogenous dynamics; Nash equilibria; Bounded rationality; Transaction costs; Mean field games; Random utility

The energy transition and the value of Capacity Remuneration Mechanisms

Capacity Remuneration Mechanisms (CRMs) can be introduced in power markets to address market failures and ensure security of supply. However, investment in capacity is a dynamic process that depends on the evolution of prices and costs over time. In this paper, we investigate the value of capacity under a CRM using a stochastic approach. We focus on three possible technologies participating in the market: a Variable Renewable Energy source, a thermal efficient power plant (such as a Combined Cycle one) and a coal-fired power plant. These three types of capacities can be framed within a common theoretical framework with an increasing level of complexity. We first present analytical models and then provide sensitivity analysis and calibration results. Our findings indicate that for all three technologies, the effect of the CRM is to cap the firm revenues and consequently to decrease their value. Moreover, the calibration provides a ranking of investments such that carbon emitting plants, in particular gas-fired ones, display higher values compared to renewable ones

Risk Heterogeneity, Productivity and Social Insurance

How does the unemployment risk and the personal risk may affect preferences on the desired (optimal) level of the tax rate (and public services) when workers have different productivities

Pricing reliability options under different electricity price regimes

Reliability Options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems. They can be framed as call options on electricity sold by power producers to System Operators. This paper provides a comprehensive mathematical treatment of Reliability Options. Their value is first derived by means of closed-form pricing formulae, which are obtained under several assumptions about the dynamics of electricity prices and strike prices. Then, the value of the Reliability Option is simulated under a real-market calibration, using data of the Italian power market. We perform sensitivity analyses to highlight the role of the level and volatility of both power and strike price, of the mean reversion speeds and of the correlation coefficient on the Reliability Options' value. Finally, we calculate the parameter model risk to quantify the impact that a model misspecification has on the equilibrium value of the RO

Optimal investment in an energy storage system

Renewable energy production plays a crucial role in the energy transition. However, many renewable energy sources (RES) are intermittent, and there is often a mismatch between energy production and consumption, which can be partially solved by storage. In this paper, we investigate the investment decision in a photovoltaic (PV) power plant coupled with a Battery Energy Storage System (BESS), namely an Energy Storage System (ESS). We aim to investigate the relationship between the net present value (NPV) of the investment and the technical implications related to the maximum amount of energy to be stored while also accounting for the impact of energy prices. In our setting, the BESS is connected to the national power grid and the PV plant. Energy can be produced, purchased from the grid, stored, self-consumed, and fed into the grid. PV production and energy consumption loads evolve stochastically over time. In addition, as BESS are costly, energy stored has an opportunity cost, which depends on the prices of energy purchased from the grid and energy fed in and sold to the grid, respectively. However, BESS can significantly contribute to increase ESS managerial flexibility and, in turn, ESS value. In detail, we investigate the optimal BESS size that minimizes ESS net operating costs. We also provide insights on ESS optimal management strategy. Our results show that ESS net operating costs are relatively small. They reduce for increasing selling prices of energy, whereas they increase for increasing volatility of the stock of energy stored in the battery