This paper aims to infer about the possible consequences of the existence of moral hazard in the Brazilian’s electric sector for the final consumer. In 2013, the new regulatory framework in the Brazilian’s electric sector was settled, which aims to encourage investment in quality and continuity of this services. Thus, the fees started to incorporate the costs related to the investments needed to maintain the quality and continuity of the service, which opens the door to the emergence of moral hazard. Moral risk has its origin in asymmetric infor-mation, which is a market failure that justifies the existence of economics regu-lations. In this sense, it is necessary to verify if the new regulatory framework, in fact, can encourage behavior that, per theory, should mitigate and its effects on the population. We found indices that the actual system adopted may drive the firms to explore a new regulatory system, harming the consumers at this process.
Economic regulation aims to soften the so-called market failures, such as market power, information asymmetry, public goods, and externalities. Information asymmetry can be considered one of the main market failures and occurs when one of the parties involved in a transaction has relevant information that the other party does not know. The asymmetry of information can be easily verified in the agent-principal relationship. See, e.g., References [
In the context of regulation, the asymmetry arises given the police maker’s constraints to verify that all the decisions taken by the companies are in accordance with the pre-determined norms. Specifically, in the energy market, information asymmetry is related to the fact that the effectiveness effort to seek efficiency cannot be directly measured by a police maker.
The electric sector is a specific case of natural monopoly. Natural monopoly occurs when the cost of production makes a single producer more efficient than several producers. In this case, electricity, it is possible to see the distribution and transmission of energy as regional natural monopolies.
In this scenario, the regulation aims to contain possible abuses of the monopoly power that arise from the conflict between allocative efficiency and productive efficiency. One of the main tasks of the regulatory body is the choice of the tariff criterion, which is responsible for controlling price adjustments and the degree of price variation per different classes of consumers.
In 2013, Brazilian’s law No. 12,783/2013 came into force, responsible for some changes in the regulatory framework of the Brazilian electric sector; previous one had been in force since 2004. The objective of this new regulation was to provide the conditions and security for the agents to make the necessary investments for continuity and quality of services provided. The concessionaires began to be remunerated by the tariff of service rendering, which includes operation and maintenance, and no longer by the sale of energy.
To do so, the tariffs began to incorporate the costs related to the investments necessary to maintain the quality and continuity of the service. The readjustment of the electric energy price began to consider the cost involved in the energy sector alone, will not use the general price index of the economy, as was in the previous regulations system.
However, a risk associated with this new regulatory framework is the possibility that the agents do not try to reduce their costs, increasing their remuneration and raising the tariff for the final consumer. That is, the new regulatory framework of the Brazilian electric market leaves leverage for the occurrence of moral hazard.
In this sense, the objective of the present study is to verify the possible consequences of the existence of moral hazard in the Brazilian’s electric sector for the final consumer, considering the changes of the new regulatory framework of 2013. For that, we use the moral hazard model presented by [
The argument of the policy maker to support this new regulatory system was the necessity to improve the infrastructure investment. This work uses the moral hazard to check what will be the cost for society, that is, what could happen to the other sectors of the economy with this new framework; and compare with the others pos-sible regulatory systems.
In addition to this introduction, the literature on information asymmetry and moral hazard is briefly presented in the second section, followed by the model used to carry out the simulations, as well as their results, and some conclusive comments.
The relationship between agent-principal can be observed in different economic contexts and with different implications. Reference [
However, the agent-principal relationship is jeopardized when there is uncertainty, more specifically when the available information is different for the participants. Reference [
The asymmetry of information arises when one of the parties involved in a transaction has relevant information that the other party does not know. This is, see [
Adverse selection is the problem that occurs when the agent makes some observation that the principal did not do before the transaction occur. Reference [
Although widely applied in the context of insurance, adverse selection also has quite a few applications in the context of regulation. As noted by [
For [
One way to solve moral hazard would be by monitoring agents’ actions. In the case of complete monitoring, all information collected would be part of the contract that would penalize the agent’s dysfunctional behavior and the solution in this case would be optimal. However, as [
Reference [
Regulation is also used to mitigate moral hazard. As highlighted by [
However, as [
To simulate the Brazilian energy market, we will assume the firms will always try to maximize their profit, even when that means they will use privileged information against the police makers. The government can only decide what the general rule to apply to the market, it is, after decide what type the regulation the market will settled nothing else will be done by the government.
To represents the regulatory framework of the Brazilian energy market with the presence of moral hazard, that is, considering that the companies that offer electricity are subject to government supervision could take advantage of a failure in the supervision to appropriate a higher amount of profit. In this case the agent and the principal do not enjoy the same set of information, i.e., there is asymmetry of information. It is possible to use the equations proposed by [
x = x a , θ , (1)
in which, for this application, x represents the results perceived by the electric power companies, given the uncertainties of the nature θ and given an action a. In Brazil, different from several countries, the supply of electricity depends on an exogenous event, that is: the amount of rainfall received by the country during the year. This dependence on the rainfall regime occurs because more than 90% of the energy produced in Brazil is produced through hydroelectric plants. Thus, different values of θ will be simulated, to verify how the results behave in scenarios with different levels of shocks in the environment.
In this way, as if it were an insurance, the government could impose a limit for the increases in the electric energy tariff. Like what happened with the old Brazilian energy regulatory framework. A second possibility is that the government does not regulate the market and allow competition between electric power companies and the supply of energy with a free price. A final option would be the government regulates the companies in a way to allow readjustments according the costs perceived by the companies themselves. For example, in the first situation, if the increase in the general level price is 10% in a year, the maximum that electricity companies could raise their tariffs would be 10% in the following year. In the latter case, if the energy companies showed to the government that they suffered a cost increase of 20%, the contract would allow companies to increase their tariffs by the maximum of 20%, even with the general price level having grown by only by half of that. We use the latter case is used to simulate the effects of the new regulatory framework.
The value of a is known to all: governments, and companies. It is the value of demand for electricity, so the profit of companies in this sector will depend on the demand for their product and the impact perceive at the environment. In sequence, it is presented how the simulations were constructed and which results was found.
The virtual economy will be composed of residents, businesses, and the government. Residents may be workers or capitalists; workers will offer labor force and use their wages to consume goods; The capitalists are the owners of the companies, they make a profit and use this money to buy goods. Goods are produced by firms of consumer goods, which demand labor, energy, and capital goods. Capital goods companies demand work and energy. Energy companies demand natural resources, our θ. The government will only play a regulatory role in the energy sector, being able to opt for one of the three regulatory profiles: (i) Regulation Type Costs; (ii) Regulation Type Price Index; and (iii) Regulation Type Free Market.
It is an agent based model, with mid-level agents, with three thousand workers, two hundred consumer companies, fifty capital goods companies, ten companies supplying electricity, and a government. The model is available online, built in free software, can be downloaded, and modified by the reader if you wish to perform simulations with other parameters.
The model and the data utilized in this work is available at: http://modelingcommons.org/account/models/712. All data utilized was generated in our model, which was built in an open source code. Further details of this simulated macroeconomics can be found in [
The GDP of this economy will be the sum of all that was produced in a period, the general price level will be the average prices of all the goods consumed in this economy in period t, and the price of energy will be measured as the average prices practiced by the electricity companies in a period.
The companies participate in a game that is mixed because they practice competition via price and quantity, Bertrand and Cournot’s game, depending on whether their sales are above or below expected, that is, whether they are managing to hit the market or not. When your sales exceed your expectations and your prices are above the price index the company raises its quantity produced, if its price is below the price index it will raise its price and keep the quantity produced in summary:
Y i , t * = { Y i , t + ( − δ i , t ) s e δ i , t ≤ 0 e P i , t > P t Y i , t + ( δ i , t ) s e δ i , t > 0 e P i , t < P t . (2)
The Y i , t * represents the production of a single firm in period t, the sum of the output of all firms will be the GDP of this economy.
P i , t = { P i , t × ( 1 + ρ i , t ) s e δ i , t ≤ 0 e P i , t > P t P i , t × ( 1 − ρ i , t ) s e δ i , t > 0 e P i , t < P t (3)
In case of companies that produce capital goods and consumer goods, the value of ρ i , t is produced by a uniform distribution with support (0; 0.10). For companies that supply electricity here will be attributed the environmental fac-
tor that represents the abundance or absence of rainfall. Thus, the support value for this distribution will be governed by θ, so in the case of electric power companies we have: (0; θ).
To analyze the environmental impact, we run simulations with 100 periods, representing one hundred quarters or twenty-five years; which would be the approximate time of a contract of an electric power company has with the government, that is, the time the company will be under a certain regulatory framework. At the beginning of the simulation a value for the environmental shock, θ, is given; which a low value represents a good climatic condition that favor the production of electric and represents low production costs for the sector. The increase in environmental shocks meant severe shocks in the amount of the rainfall, which would lead to periods of low supply of raw material for electricity generation companies.
Detailing each regulatory framework; in the first case, which can be seen in
Regulation/θ | 0.01 | 0.02 | 0.03 | 0.04 | 0.05 | 0.06 | 0.07 | 0.08 | 0.09 | 0.1 |
---|---|---|---|---|---|---|---|---|---|---|
Costs | 1.13 | 1.30 | 1.48 | 1.61 | 1.86 | 2.07 | 2.37 | 2.80 | 3.17 | 3.60 |
Free Market | 1.83 | 1.51 | 1.36 | 1.51 | 1.05 | 1.39 | 1.53 | 1.51 | 1.26 | 1.71 |
General Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
charged by the electric energy triggers.
When the government uses another rule to regulate the energy’s price, such as a general price index, the result is different. Contrary to what happened in the previous case, prices did not diverge, even with different environmental impacts, at the end of the period the series of prices end up very close, as can be seen in
The best situation for the consumer is the free market with good weather conditions. However, as can be seen in
In all simulations, the economy stabilizes after a few years, there is neither population growth, nor capital or labor productivity changes, so that only shocks in the environment are capable of affect the economy. The fact that the Price Index Type Regulation stabilizes at some point reflects this. The economy finds a balance and the only point that still fluctuates is the energy costs, the production is stable, the prices practiced by the other sectors of the economy find a stable level of exchange, so that the energy sector starts to absorb resources from this economy.
In regulation type price, the government authorizes increases in energy’s price when the general price index goes up. Then, when the price index is reduced, electricity companies do not reduce their prices, stabilizing them at the highest point authorized by the government, thus improving their relative position through the other participants of this economy.
The situation of the regulation cost type performs even worse, since it is the series with the most expensive energy offered in the analysis in question, considering θ = 0.05. Note that for the same θ = 0.05, see
Shocks at rainfall: | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
Period/Regulation | 0.01 | 0.02 | 0.03 | 0.04 | 0.05 | 0.06 | 0.07 | 0.08 | 0.09 | 0.1 |
10 | ||||||||||
Costs | 1.01 | 1.03 | 1.04 | 1.05 | 1.07 | 1.07 | 1.08 | 1.09 | 1.15 | 1.10 |
Free Market | 1.03 | 1.05 | 0.93 | 1.08 | 1.01 | 0.98 | 1.04 | 1.04 | 1.03 | 1.09 |
Price Index | 1.39 | 1.39 | 1.37 | 1.36 | 1.38 | 1.34 | 1.31 | 1.35 | 1.33 | 1.30 |
20 | ||||||||||
Costs | 1.02 | 1.06 | 1.08 | 1.11 | 1.13 | 1.15 | 1.19 | 1.20 | 1.29 | 1.28 |
Free Market | 1.14 | 1.22 | 1.05 | 1.27 | 1.01 | 1.12 | 1.23 | 1.23 | 1.06 | 1.25 |
Price Index | 1.68 | 1.69 | 1.67 | 1.70 | 1.69 | 1.67 | 1.73 | 1.65 | 1.68 | 1.67 |
30 | ||||||||||
Costs | 1.04 | 1.09 | 1.13 | 1.17 | 1.22 | 1.22 | 1.29 | 1.31 | 1.45 | 1.44 |
Free Market | 1.30 | 1.30 | 1.13 | 1.35 | 1.06 | 1.18 | 1.34 | 1.36 | 1.20 | 1.37 |
Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
40 | ||||||||||
Costs | 1.05 | 1.12 | 1.17 | 1.22 | 1.31 | 1.31 | 1.41 | 1.49 | 1.65 | 1.65 |
Free Market | 1.45 | 1.42 | 1.20 | 1.40 | 1.09 | 1.21 | 1.42 | 1.51 | 1.16 | 1.43 |
Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
50 | ||||||||||
Costs | 1.06 | 1.14 | 1.22 | 1.27 | 1.37 | 1.42 | 1.53 | 1.66 | 1.90 | 1.85 |
Free Market | 1.56 | 1.43 | 1.26 | 1.51 | 1.06 | 1.28 | 1.37 | 1.48 | 1.12 | 1.46 |
Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
60 | ||||||||||
Costs | 1.07 | 1.17 | 1.26 | 1.33 | 1.46 | 1.53 | 1.66 | 1.87 | 2.06 | 2.13 |
Free Market | 1.62 | 1.49 | 1.24 | 1.48 | 1.08 | 1.29 | 1.45 | 1.47 | 1.19 | 1.55 |
Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
70 | ||||||||||
Costs | 1.09 | 1.20 | 1.31 | 1.39 | 1.54 | 1.65 | 1.83 | 2.01 | 2.25 | 2.46 |
Free Market | 1.72 | 1.51 | 1.23 | 1.48 | 1.08 | 1.31 | 1.38 | 1.50 | 1.18 | 1.69 |
Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
80 | ||||||||||
Costs | 1.10 | 1.23 | 1.37 | 1.45 | 1.66 | 1.79 | 1.99 | 2.30 | 2.57 | 2.77 |
Free Market | 1.73 | 1.49 | 1.24 | 1.54 | 1.10 | 1.34 | 1.45 | 1.52 | 1.16 | 1.65 |
Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
90 | ||||||||||
Costs | 1.12 | 1.27 | 1.42 | 1.53 | 1.75 | 1.93 | 2.20 | 2.61 | 2.85 | 3.15 |
Free Market | 1.81 | 1.51 | 1.26 | 1.52 | 1.07 | 1.43 | 1.54 | 1.47 | 1.22 | 1.60 |
Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
100 | ||||||||||
Costs | 1.13 | 1.30 | 1.48 | 1.61 | 1.86 | 2.07 | 2.37 | 2.80 | 3.17 | 3.60 |
Free Market | 1.83 | 1.51 | 1.36 | 1.51 | 1.05 | 1.39 | 1.53 | 1.51 | 1.26 | 1.71 |
Price Index | 1.68 | 1.69 | 1.68 | 1.71 | 1.69 | 1.72 | 1.73 | 1.67 | 1.73 | 1.70 |
ment authorizes a new increase, a cascade effect that cumulatively penalizes the consumers.
In 2013 Brazil adopted a new regulatory framework for the electric energy sector, a milestone that approaches what in this model we consider the Regulation Type Costs. The perceived costs by the electricity sector are passed on to consumers via the price of their tariffs. Part of this is already observed in the light bill, with successive readjustments during the subsequent years. The government’s argument for such a practice is that with this regulation the electricity companies will have fewer risks, thus increasing their investments, increasing the quality of service provided.
Our analysis show it imply a higher impact to the last consumer, that is, the electricity sector absorbs wealth from other entities of this economy, making it an attractive business. However, it should be noted that consumers never benefit in this scenario. In
The previous regulatory framework, in force until 2013, the Price Index Regulation, it is, energy companies can raise their prices up to the general price level of the economy. The simulations show that the general level of price stabilizes when the economy reaches level, nearly the fifth year of contract. Even if the electric companies ask for permission to raise their prices to the maximum possible in each period this situation is less onerous than the Regulation Type Costs.
We explain this behavior thru moral hazard. The government would need companies to take social welfare into account, not just their profit maximization, by calling for tariff increases. Moreover, under the new regulatory framework, companies must continuously seek to reduce their internal costs by investing in improvements in productivity to reduce the impact in other sectors of the economy.
The free market energy could be the best scenario in case of good patterns into the rainfall. But goes against the will of the government to provide more incentives to companies to invest. The risk to seek, providing energy in a competitive market, could restrain investment in the sector, which exactly what the police maker is trying to avoid. However, the regulation which uses the general price index of the economy could provide some security to investor if lowest cost.
In this work, we see the new policies implemented by the policy maker in Brazil may drive to a non-optimal condition. If the firms use their privileged position the others sectors of Brazilian economy will suffer, will occur transfer of resources to the energy sector. The argument of the policy maker at the time to implement the actual rule was to improve conditions for new investment in infrastructure, nevertheless we think this will be achieve through inhibitions of growth from others sectors.
This work considers as taken the proportion of hydraulic source of Brazilian matrix energy. For future works this scenario could be change. Once the rainfall fluctuation is the major source of instability in the system, addicting other sources of energy may drive to new challenges.
The authors gratefully acknowledge the CAPES (Coordenação de aperfeiçoa- mento de pessoal de nível superior―Brazil) for financial support.
Couto, S.V.V. and Silva, E.M. (2017) A Theoretical Appli- cation of Moral Risk in the Brazilian Ener- gy Market. Open Access Library Journal, 4: e3401. https://doi.org/10.4236/oalib.1103401