nep-cta New Economics Papers
on Contract Theory and Applications
Issue of 2021‒10‒11
four papers chosen by
Guillem Roig
University of Melbourne

  1. The ambiguous competitive effects of passive partial forward integration By Papadopoulos, Konstantinos G.; Petrakis, Emmanuel; Skartados, Panagiotis
  2. Optimal pricing for electricity retailers By Rom\'an P\'erez-Santalla; Miguel Carri\'on; Carlos Ruiz
  3. Joint optimization of sales-mix and generation plan for a large electricity producer By Paolo Falbo; Carlos Ruiz
  4. Electoral violence and supply chain disruptions in Kenya's floriculture industry By Ksoll, Christopher; Macchiavello, Rocco; Morjaria, Ameet

  1. By: Papadopoulos, Konstantinos G.; Petrakis, Emmanuel; Skartados, Panagiotis
    Abstract: In a two-tier industry with an upstream monopolist supplier and downstream competition with differentiated goods, we show that passive partial forward integration (PPFI) has ambiguous effects on competition and welfare. When vertical trading is conducted via linear tariffs, PPFI is pro-competitive and welfare-increasing. While under two-part tariffs, it is anti-competitive and welfare-decreasing. These hold irrespectively of the degree of product differentiation, the observability or secrecy of contract terms, the mode of downstream competition, and the distribution of bargaining power between firms.
    Keywords: Partial Passive Forward Integration; Two-Part Tariffs; Linear Tariffs; Competition; Welfare
    JEL: D43 L13
    Date: 2021–10–01
    URL: http://d.repec.org/n?u=RePEc:cte:werepe:33354&r=
  2. By: Rom\'an P\'erez-Santalla; Miguel Carri\'on; Carlos Ruiz
    Abstract: In the present work we tackle the problem of finding the optimal price tariff to be set by a risk-averse electric retailer participating in the pool and whose customers are price-sensitive. We assume that the retailer has access to a sufficiently large smart-meter dataset from which it can statistically characterize the relationship between the tariff price and the demand load of its clients. Three different models are analyzed to predict the aggregated load as a function of the electricity prices and other parameters, as humidity or temperature. In particular, we train linear regression (predictive) models to forecast the resulting demand load as a function of the retail price. Then we will insert this model in a quadratic optimization problem which evaluates the optimal price to be offered. This optimization problem accounts for different sources of uncertainty including consumer's response and renewable source availability, and relies on a stochastic and risk-averse formulation. Moreover, we consider both standard forward based contracts and the recently introduced power purchase agreement contracts as risk-hedging tools for the retailer. The results are promising as profits are found for the retailer with highly competitive prices and some possible improvements are shown if a better dataset could be produced. A realistic case study and multiple sensitivity analyses have been performed to characterize the risk-aversion behavior of the retailer considering price-sensitive consumers. It has been assumed that the energy procurement of the retailer can be satisfied from the pool and different types of contracts. The obtained results reveal that the risk-aversion degree of the retailer strongly influences contracting decisions, whereas the price sensitiveness of consumers has a higher impact on the selling price offered.
    Date: 2021–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2110.02735&r=
  3. By: Paolo Falbo; Carlos Ruiz
    Abstract: The paper develops a typical management problem of a large power producer (i.e., he can partly influence the market price). In particular, he routinely needs to decide how much of his generation it is preferable to commit to fixed price bilateral contracts (e.g., futures) or to the spot market. However, he also needs to plan how to distribute the production across the different plants under his control. The two decisions, namely the sales-mix and the generation plan, naturally interact, since the opportunity to influence the spot price depends, among other things, by the amount of the energy that the producer directs on the spot market. We develop a risk management problem, since we consider an optimization problem combining a trade-off between expectation and conditional value at risk of the profit function of the producer. The sources of uncertainty are relatively large and encompass demand, renewables generation and the fuel costs of conventional plants. We also model endogenously the price of futures in a way reflecting an information advantage of a large power producer. In particular, it is assumed that the market forecast the price of futures in a naive way, namely not anticipating the impact of the large producer on the spot market. The paper provides a MILP formulation of the problem, and it analyzes the solution through a simulation based on Spanish power market data.
    Date: 2021–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2110.02016&r=
  4. By: Ksoll, Christopher; Macchiavello, Rocco; Morjaria, Ameet
    Abstract: Violent conflicts, particularly at election times in Africa, are a common cause of instability and economic disruption. This paper studies how firms react to electoral violence using the case of Kenyan flower exporters during the 2008 post-election violence as an example. The violence induced a large negative supply shock that reduced exports primarily through workers’ absence and had heterogeneous effects: larger firms and those with direct contractual relationships in export markets suffered smaller production and losses of workers. On the demand side, global buyers were not able to shift sourcing to Kenyan exporters located in areas not directly affected by the violence nor to neighboring Ethiopian suppliers. Consistent with difficulties in insuring against supply-chain risk disruptions caused by electoral violence, firms in direct contractual relationships ramp up shipments just before the subsequent 2013 presidential election to mitigate risk.
    Keywords: STICERD
    JEL: R14 J01
    Date: 2021–09–20
    URL: http://d.repec.org/n?u=RePEc:ehl:lserod:112128&r=

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