What are Shadow Prices?

What are Shadow Prices?

The eternal dichotomy that exists between market prices and sale prices

Marxist analysis accepts the value of commodities for the value contained in them, and in the exchange between those who obtain extraordinary profits and those who lose their profits as well as the total distributed among the participants will be equal to the sum of the labor socially incorporated into them. the same in its entirety. If we accept this principle, a way to measure the individual value is through the integral analysis of all the goods that are exchanged at their market value including consumer and intermediate goods and in their terms of trade when determining their prices in competition. The value of each commodity generated in the market is determined by the payment to the factors of production (labor and capital) imposed on the government, profits of entrepreneurs, restitution to the environment and replacement of assets.

Given that market prices are not a valid indicator of the social value of goods or resources, due to the existence of market imperfections, taxes, public goods or externalities, Shadow Prices should be calculated instead. However, its estimation is unusual due to the calculation difficulties involved. In the absence of representativeness of market prices will be necessary to calculate prices that work in perfect competition. The Shadow Price of a good is defined as the price that said good would reach in a perfectly competitive market.

It is accepted that shadow prices are implicit in the exchanges that should be made to maximize a particular objective function (or to minimize a cost function), also when we explore a series of combined production possibilities (the maximum of Y for each quantity of X). that occurs). The models of mathematical programming and matrix algebra can help to calculate the shadow prices, of the goods in perfect competition, respecting the principle of marginal analysis that shows the irrecoverable social loss generated by the imperfect markets. Unlike the market prices that are evaluated from the investor's interest, the shadow prices are determined according to the cost-benefit analysis of the company that allows determining the convenience in the realization of plans and projects to the Nation. These prices are also known as social prices.

The opening of internal markets to the world market impacts the calculation of domestic prices in competition. It is expected that the goods acquired in the international markets are representative of the value of the goods in perfect competition, since upon being marketed, the plaintiffs have greater selection options. The establishment of prices of currencies generally below their real value, controls on imports, taxes imposed on market operations of goods that intervene in international trade and goods produced in the country with internal inputs, generate strong distortions in the market and away from domestic prices of the real value of goods and services.

Goods that have the possibility of being imported or exported in competitive markets, considering the indicated distortions, generate less difficulty to identify their prices in perfect competition (marginal cost = demand), however, those that are sold in the domestic markets keep hidden your account prices. The opportunities offered by international trade to a country are the basis for calculating the economic value of both its domestic production and the productive factors of the national economy. In a market open to international competition, merchandise can be negotiated under conditions of efficiency where the CIF values (cost of the product plus insurance and freight costs to the port of destination) and FOB (cost of the product in the port of origin before paying) the insurance and freight charges to the port of destination) become the competitive prices necessary for the adoption of decisions concerning the national activity.

The Shadow Prices system must distinguish two types of prices, the efficiency prices that are calculated on the basis that any additional unit of consumption is as valuable as any additional unit of investment and that the marginal utility of an additional unit of consumption it does not vary with the income level of your receiver. The second group is represented by social prices where the consequences on the distribution of income implied by the use or production of goods and services are incorporated. In a backward economy, goods can be classified as fully commercialized, those that are not commercialized, those that are partially commercialized that combine characteristics of one or another group, and those potentially commercialized that are protected by the government from international competition.

The domestic market presents different pricing modalities: The basic prices established at the point of production in which transactions are valued excluding indirect taxes and marketing and transportation costs. Producer Prices that include indirect taxes at producer level. User Prices as a result of the valuation of the transactions at the point of delivery that include indirect taxes and marketing and transportation margins. Non-traded goods, whose efficiency price is unknown, can be calculated through the marginal cost of production of all the inputs valued at account prices necessary to produce it.

For the calculation procedure, double-input input-output matrices are used, through the semi-input-output (SIO) method. With the input-output analysis, the adjustment of market prices is made with the interrelations between the different productive sectors. Market prices depend on the prices of all the inputs that are used in the production process and that at the same time will be outputs of the rest of the sectors, and even of themselves, since they are related to each other.

The empirical applications of the SIO method have been made in backward economies financed by organizations interested in economic development such as the Inter-American Development Bank (IDB), concerned about the profitability of their investment projects. The logic of the calculation model of the Shadow Price lies in the assumption that the economic value of a good produced can be found by adding the cost of all inputs, intermediate and primary, that have been used to obtain it. In turn, the cost of intermediate inputs, since they are the result of a previous production process, can also be decomposed into intermediate and primary input costs. The decomposition can be done as many times as necessary until, finally, the production cost of a good is expressed only in terms of the primary inputs used, both directly and indirectly.

Guillermo Souto

Notes on Fair Value in Accounting

Notes on Fair Value in Accounting

The International Accounting Standard, identified with number 13, defines Fair Value as the price that is received in an orderly transaction between market participants on the measurement date due to the sale of an asset or the transfer of a liability. Two assumptions apply to it: that the transaction takes place in the corresponding main market or in the most advantageous market for the asset or liability, and that the parties involved act in their best economic interest. The Fair Value evaluation is done with the help of adequate procedures that have sufficient data. Among them, we can mention the market focus, the cost approach and the income approach. The parameters used in the calculation of fair value can be classified hierarchically as follows:

• The first level parameters are the prices for identical assets or liabilities (market prices).

• The second level input parameters refer to directly or indirectly detectable prices for identical or very similar assets or liabilities (comparative values).

• The third level input parameters are the prices of assets or liabilities that can not be observed (estimates).

The norm indicate that companies are obliged to provide all information about the resulting Fair Value. It should be clarified what evaluation procedures and what input parameters were used, as well as presenting basic information about the assessed value of the asset or liability. Additionally, the impact of the valuations must be explained on the basis of the third level input parameters, that is, of the supposed benefits or losses. The Fair Value aims to assign greater objectivity, transparency and relevance to the information in the annual balance sheets. Since it is a commercial evaluation criterion, it does not incur fiscal consequences for companies. Its greatest advantage is relevance, resulting in the timely evaluation of active and passive values.

Historical data such as acquisition and production costs, which would otherwise serve as an indicator, do not enjoy such current information content. For current and future lenders and partners, fair values represent the best way to evaluate the chances of an investment's success. On the other hand, Fair Value serves as a basis to classify future cash flows. As a criterion of commercial evaluation, fair value plays an important role in both the initial and final assessment. Therefore, it is decisive when acquiring an asset or a liability, as well as when calculating it regularly in later stages, as long as there are losses or decisive gains that require it.

For the following assets and liabilities, Fair Value is an essential measurement requirement:

• All assets that are part of an asset plan (retirement pensions).

• Pension provisions, as long as their amount depends on fair value and is above the minimum guaranteed value.

• Assets, liabilities, accruals and special items that are connected to subsidiary companies - the exceptions are provisions and deferred taxes.

• The assets, liabilities, accruals and special items resulting from the investment in foreign companies (limited to the acquisition price). Here the exceptions are also provisions and deferred taxes.

As mentioned, there are three procedures for determining Fair Value. While the market approach aims at the reference market and can be included in the measurement of the fair value of the first and second level input parameters, the cost approach and the capital approach (income approach) are calculated on the basis of the third level evaluation criteria.

1) Market approach: Is a market-oriented calculation procedure. Here we can distinguish between the direct use of current market prices and the use of analogies to determine fair value. In the first case, the market price serves as a guide to calculate the fair value. The only condition that exists is that the market is active and complies with the following three points:

• The assets traded must be, to a large extent, homogeneous (independently of any spatial reference or market participants).

• As a general rule, it is always possible to find interested buyers and sellers.

• The prices of the goods or services exchanged are available to the public. In the second case there is no specific market price for the asset to be classified, which is why the fair value is determined on the basis of affordable assets.

For this purpose, the comparison values are modified, for example, through discounts or reloads. It also allows the use of multipliers that are coupled to sales or profits. Thanks to its traceability, the market approach is the preferred one when calculating Fair Value. However, its application is difficult if you do not have enough data, either because you do not know the specific market price nor the comparable values.

2) Capital approach (income approach): The capital approach, also known as the net present value method, is based on all the relevant cash flows (cash flows) with a risk interest rate until the valuation date. The Fair Value is determined using the values for the amount and duration of the payment flows. Some of the procedures are:

• Immediate cash flow method: the value is determined by the sum of future income that can be associated to each asset. This is done directly in the form of cash flow or cash.

• Royalty method: with this method the Fair Value is calculated on the basis of future royalties that will be paid to a third party for an asset. To this end, the royalty rate for sales is multiplied.

• Residual value method: the idea is that any residual income is assigned to the assets to be valued. For this purpose it is necessary to deduct the cash flows (tangible and intangible) of all other assets in the total revenues.

3) Cost approach: It brings together two approaches to determine Fair Value: the reproduction cost method and the substitution method. The first establishes the fair value of all the expenses necessary to replicate the asset in the event that identical resources and measures are used. The substitution is also aimed at the costs involved in the replication of an asset (with the same benefits), although, unlike the cost of reproduction method, the latter includes current resources and methods. Among the costs included in the evaluation are direct costs, such as cash flows, general and opportunity, such as the company's salaries. If the value object has been previously evaluated, the incurred loss of the economic value must be determined and deducted when calculating the final value. The strengths of the cost approach are the traceability and the verifiability of the valuation criteria, although for many items of intangible value, the replication process is hardly feasible. Another problem is the fact that the potential of future income is not shown.

Guillermo Souto

Predictions on Economy

Predictions on Economy

In economy, the problem of decision-making is always raised, that is, the choice of an option between different alternatives. When making a decision it is very important to have a vision of what is going to happen in the future: taking a decision requires considering all those alterations that may occur during the relevant time horizon for the subject in question. No decision should be made without considering the future evolution of all those events that condition it. In recent years a great emphasis has been placed on improving the decision-making process and this is where the idea of prediction comes in.

Origin

Predicting is a complex task, since it involves calculating some future event, in general, as a result of a rational analysis or a study of existing data. The aim of this document is to summarize the most important aspects that denote the most used prediction techniques in the area of economy and business.

In a broad sense we can say that the object of economic science is the study of the way in which economic agents make their decisions and the analysis of the consequences that result from the adoption of such decisions. Both in the economy of the company and in the macroeconomic field, the problem of decision-making is posed, that is, the choice of an option between different alternatives. Each option will result in a different result that can be measured in terms of utility, cost, benefit, or any other magnitude, depending on the problem being considered. However, the concrete result obtained will depend on situations that may occur outside the sphere of influence of the decision maker.

When making a decision it is very important to have a vision of what is going to happen in the future: taking a decision requires considering all those alterations that may occur during the relevant time horizon for the subject in question. In good logic, a decision should not be made without considering the future evolution of all those events that condition it. In recent years a great emphasis has been placed on improving the decision-making process and this is where the idea of prediction comes in.

When decisions are made, the decision maker is, in general, in an environment of uncertainty regarding the events that may occur in the future. The problem faced by the decision maker is to choose between alternative decisions, taking into account the usefulness of their decisions before each of the possible events. These events are facts, usually located in the future, or that the decision maker does not know. In any case, the decision maker will be able to achieve better results if to some extent he manages to reduce the uncertainty about future events, or that the decision maker does not know.

Prediction techniques are aimed, precisely, at reducing uncertainty about the future and, therefore, reducing the risk when making decisions. When predicting, it is a matter of calculating some future event, in general, as a result of a rational analysis or a study of existing data. For prediction to be useful in the planning process.

The field of application of the prediction is very broad in the area of the economy, and the following examples can be considered:

1. Predictions on macroeconomic variables such as GDP, inflation, current and investment spending, and others matters.

2. Predictions on the expected profitability in the international securities and merchandise markets.

3. Predictions on the behavior and economic results of companies.

There are different types of predictions depending on what is predicted and what approaches will require and different techniques will require, for example:

1. Predicting the effects of an event: In this case, we know that an event will occur in the future with certainty, and we want to determine what its effects will be. For example, to know who will win the next elections, or what effects will a law that will be promulgated soon or what will be the future sales of a new brand that comes to market, etc. The problem that arises is that the event can be unique, but with multiple effects or consequences, so the best possible approach is to search or generate the largest amount of relevant data.

2. Predicting the time an event occurs: This kind of predictions is questioned when, and if, a certain event is going to occur, that is, when the next elections will be or when the economy will recover, or when the competitors of a company will produce a new product at the time of the recovery of the economy market. In some of these examples, there was a sequence of similar events in the past, for example, the dates of the elections. In this case, observing the pattern of times between events, one could predict when the next one will occur. However, the usual way of working is to look for leading indicators, which are events that can happen before we are trying to predict. This approach is widely used to predict points of change in the evolution of the economy. For example, before launching a product on the market it can be seen that a company has reserved a lot of television advertising time.

3. Prediction of time series: A time series is a set of observations collected at regular intervals of time. For example, the hourly temperatures, the daily prices of shares at the close of the stock exchange, the monthly unemployment rate or the annual National Income, that is, if we are at time T and we want to predict what will happen to a variable at time T + 1. By definition this is the most complex type of prediction to perform, since it must involve the construction of a mathematical model that explains the behavior of the variable and is capable of predicting its quantification in the future.

Limitations on predictions

Most of the criticisms made to predictions (unexpected developments, predicted events that never happen, large prediction errors, errors in the moment, intensity of predicted changes, etc.) are well founded. However, it is necessary to understand or know how to interpret the predictions.

A necessary prerequisite to be able to predict, by whatever method, is that there is a pattern of behavior in the phenomenon we are studying. If a pattern of behavior does not exist, it is not possible to predict with a certain degree of precision, although, sometimes, subjective opinions can be given based on similar past situations.

In economics the predictability of a phenomenon varies from being almost nil (daily price of an action) to being excellent (Seasonal patterns based mainly on climatological reasons). The problem is that in economics, patterns and relationships are mixed with random components and can change unpredictably over time. Generally, changes in patterns or relationships are due to: i) Randomness of human behavior; and ii) Ability of people to influence the future with their own actions.

Factors of influence on predictability

When extracting the pattern of behavior followed in the past and being able to make conjectures about the future, a very important point is the amount of information that we have. For example, focusing on the time series, let us first consider a time series consisting of daily observations about the time of sunrise for fifty years. The problem would be to predict what time the sun will rise tomorrow. With a series of data of this type, it is very easy to make this prediction. It is true that, instead of using the observations of the past, prediction can also be made based on knowledge of the laws about the movement of the stars.

In any case and this is what we want to emphasize here, in a phenomenon of this type from the observation of the past, a good forecast can be made of what the future will be. Why does this happen? Simply because the series contains a lot of information being the past values of great utility to predict the future.

The choice of the prediction method to be used in a given situation entails finding a technique that satisfactorily answers the questions posed. The "best" prediction method is not always the most "accurate". The prediction method that should be used is one that covers our needs with the least cost and inconvenience. The professional should try to build simple models, easy to understand and, therefore, to explain. An elaborate model can generate more accurate predictions, but it can be very expensive and difficult to implement. The principle of parsimony tells us that when choosing between prediction models, if everything else is the same, we have to choose the simplest one.

Sometimes we just need very crude predictions, in other cases, accuracy is essential. In some applications the accuracy can be very expensive, for example; an imprecise prediction of an economic indicator can lead to the US Federal Reserve, to raise interest rates wrongly with all the consequences that this would have. On the other hand, increasing accuracy tends to increase the costs of both data acquisition, as well as of personnel or the use of data processing technology. If a small loss of precision is not very important, and the cost goes down substantially, we may prefer the simpler, less precise model, than the complexes that have been held over the last fifty years.

On the other hand, the greater the prediction horizon the greater the possibility of change in patterns or relationships because the behavior or attitudes of people can change. For example, fundamental changes in the environment may occur, for example, technological changes.

The short-term predictions are predictions for a period of less than three months, so there are two aspects to consider. On the one hand, changes in economic patterns and relationships can occur and actually occur. But due to the great inertia that most economic phenomena present, when a relationship changes, the result of this change is not immediate. This concept of inertia is very important in the economic field. For example, has taken almost a year since the so-called "oil crisis" for Western economies to enter recession. Due to this inertia and delays in the response, the current state of many variables is a good predictor of its value in the near future. That is, short-term established patterns can be extrapolated with a certain degree of precision.

Mid-term forecasts are those that cover the period from three months to two years and, in general, are derived from long-term predictions, or are constructed by accumulating short-term predictions. These predictions are usually not very accurate and, in general, it is often difficult to predict the points of change in business cycles, nor are recessions or periods of expansion. But these predictions are also necessary to make decisions about budgets or allocation of resources, therefore, planners must accept their limitations to predict recessions and booms in the economy and develop flexible plans that are capable of adjusting to cyclical changes.

The long-term predictions are those that cover a period of two years or more. The conclusions that are collected in the literature on the accuracy of these predictions are generally pessimistic; since in the long term there are many behaviors of variables directly or indirectly related to the fact that it tries to predict or simply generate new variables whose effect could not be estimated at the initial moment. In summary, long-term predictions tend to be imprecise, but they are necessary for strategic and budgetary planning. Therefore, all problems created by the uncertainty of these predictions should be studied and not ignored.

Guillermo Souto