Traded Goods

In this situation, the country consumes qd units of the good, of which domestic production satisfies qs and imports supply the difference . As the government bids for goods, domestic demand increases from D1D1 to D2D2. Because the good is an import and the country is a price taker, however, additional imports satisfy additional demand. Imports increase by the amount qd* – qd. The total cost to society of the additional consumption is the area given by the rectangle abqd*qd, and the unit cost by the import price Pi.The relevant price is not necessarily the international price of the good, but the import parity price, that is, the border price adjusted for transport costs. Similar analysis leads to the conclusion that the relevant price for an export good is the export price or export parity price. We obtain

Analysts should use the import or export parity price for tradable goods, even if the country does not trade the goods. The justification for using the import or export parity price as the shadow price of tradable goods is similar to one used for traded goods, discussed in the previous section. In some rare cases the domestic price of a nontraded, but tradable good is below the border price plus the tariff, that is, there is water in the tariff.

In some countries certain goods cannot be traded for various reasons. One of the most common barriers is transport costs. The cost of producing the good domestically is lower than the price of imports plus transport costs. At the same time, the cost of domestic production plus transport costs makes it unprofitable to export, rendering the good nontradable for that particular country. In Zimbabwe, for example, steel might be such a good. Because Zimbabwe is landlocked, domestic production enjoys natural protection, but at the same time exports are unprofitable.

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The Mechanics of Discounting and Compounding

The mechanics of discounting are simple, and routines for discounting are now part of any spreadsheet program For the sake of illustration, we present here an example on compounding. Suppose we place US$100 at 10 percent per year for five years in a savings account, where a bank pays interest on the total amount in the account at the end of the year.

Net Present Value Criterion

The present value of the net benefits of a project is the basic economic criterion that we should use to accept or reject a project. Two conditions must be satisfied if a project is to be acceptable on economic grounds, namely

• The expected present value of the net benefits or net present value  of the project must not be negative when discounted at an appropriate rate.

• The project’s expected NPV must be at least as high as the NPV of mutually exclusive alternatives. For investments where no consensus exists on how to value benefits in monetary terms, the analyst should specify alternative project success criteria, yardsticks for monitoring progress during implementation, and measuring success on completion. Such projects must normally be shown to represent the expected least-cost condition for achieving the posited expected benefits.

Comparison of Mutually Exclusive Alternatives

So far, we have discussed the equivalence of the two rules in reference to a single project. When projects are independent, as long as the NPV is not negative, the project is acceptable. The fact that one project may have a higher IRR, though a lower NPV, than another project is irrelevant. However, when choosing among mutually exclusive projects or project designs, in the sense that they are alternative ways of producing exactly the same output—for example, hydroelectric versus thermal power production— differences in ranking are important. To illustrate these concepts, consider a small and a large irrigation scheme for the same site. If the small scheme were built, it would preempt use of the site for the large one; hence, they are mutually exclusive. The NPV, IRR, and total cost of each design appear. If we use the IRR to select between the two options, we would opt for the small-scale irrigation alternative. If we use the NPV to select between alternatives, we would choose the larger project. Which one is correct? Because the NPV criterion maximizes the net benefits accruing to the country, it is preferable. If we choose the smaller project, the country will forgo 241.9 million currency units in net benefits.

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Poverty Reduction

Public intervention to reduce poverty may be justified on ethical and political grounds. Even in the idealized Arrow-Debreu world, Pareto-efficient solutions achieved by the decentralized market system depend on the initial allocation of resources among all the actors in society. A Pareto-efficient solution could be glaringly inequitable, leaving some with too much and others with too little. A case can be made for public provision of goods that the poor consume relatively more than the nonpoor— for goods with low-income elasticity—on grounds of redistribution. Some types of health care may qualify. However, low income elasticity is not the only grounds for government intervention in the provision of goods and services for the poor. Governments provide many types of health and education services that have high income elasticity to the poor on grounds of redistribution. Although targeting project benefits toward the poor is always a good idea, sometimes leakage is either technically inescapable or is the political price of poverty reduction. To benefit the poor it may be necessary to benefit some of the nonpoor.

Discounting and Compounding Techniques

The decision on a project’s acceptability hinges on whether the benefits exceed the costs. If all benefits and costs occurred in the same year, the decision would be a simple one of comparing benefits and costs. Usually, however, benefits and costs occur at different times, with costs usually exceeding benefits during the first years of the project. This issue arises in both economic and financial analysis. The techniques used to compare costs and benefits occurring in different years are the same in both types of analysis. We call these discounting techniques.

Discounting enables us to compare the value of dollars in different time periods. A dollar received today enables us to increase our present consumption whereas a dollar received in the future can increase only future consumption. Therefore, a dollar received now is more valuable than a dollar received in the future. Postponing consumption makes tomorrow’s dollar less valuable than today’s, even if tomorrow’s dollar has as much purchasing power as today’s. The declining value of money over time has nothing to do with inflation, only with the postponement of consumption.

The declining value of money over time explains, in large measure, why we require interest whenever we lend money. Lending money entails postponing consumption. To compensate for this, we demand an amount that enables us to increase our consumption in the future for every dollar we lend. Thus, whenever we open a savings account and place our money at 5 percent interest per year, we implicitly state that US$1.05 one year from today

is worth at least as much as US$1 today. If we buy a five-year certificate of deposit paying 5 percent per year of compound interest, we will receive US$1.28 in five years for every dollar we give up today. We implicitly state that US$1.28, five years hence, is worth at least as much as US$1 today. Discounting involves the reverse procedure. It answers the question: How much is US$1.28, received in five years, worth today? The answer depends on the interest rate we are willing to accept. If we accept an interest rate of 5 percent per year, then US$1.28 in five years is worth US$1 today, which is equivalent to saying that US$0.78 today is worth US$1.00 in the future.

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Nonrival Goods—Exclusion Undesirable or Inefficient

Private goods also share another important characteristic, namely, that the marginal cost of consumption is nonnegligible. In the case of nonrival public goods, however, the marginal cost of consumption is zero or very low. Once a bridge is built, for example, the marginal cost of letting another car use it is virtually zero, up to the point of congestion. Likewise, the cost of informing 1,000 consumers over the air waves is the same as the cost of informing 2,000. The information available to 1,000 additional consumers does not reduce the amount available to others—the marginal cost of consumption is zero. Although private production of nonrival goods is possible, the private sector will produce suboptimal quantities. Socially optimal pricing requires that the price of goods or services be equal to the marginal cost of consumption. If the price equals marginal cost, private provision may be unprofitable. For an uncongested bridge, for example, optimal pricing would require a very low toll, too low to recover the initial investment and, hence, too low to interest the private sector. If the toll were set high enough to interest the private sector, too few cars would use the bridge. Low marginal cost of consumption is often used as an argument for public provision of research and extension, utility services, and public information services such as agricultural prices and weather patterns. The argument for public involvement in the provision of nonrival public goods is strong, but the nature of the involvement need not be provision of the good, as public funding of private provision may be optimal in many cases. For example, a government may achieve the optimal quantity of research and extension services with public funding of private provision

Complementary Markets

In some cases the production of a good requires the production of a complementary good: computers and computer programs, for example. Software companies flourished only after the advent of personal computers. This example of complementary markets involves only two goods. In some cases, many markets—and large-scale coordination—must be involved. Public intervention in urban renewal programs and rural development have been justified on the grounds of this market failure. The renewal of a large section of a city or the development of rural areas requires extensive coordination among many actors, including factories, retailers, landlords, transport, and so on. Similarly, the development of rural areas requires extensive coordination among various actors. If markets were complete, the coordination would take place through the price system. Incomplete markets require that someone act as coordinator.

Risk Aversion

The public sector, as representative of a country’s entire population, can spread risk over every citizen in the country and is, therefore, in a unique position as an investor. For this reason, Arrow and Lind  argued that when governments act as investors, they should be risk-neutral. They should neither prefer nor avoid risk. Governments should normally choose projects based on their expected net present value and disregard the variance around the mean of the net present value. For private investors, who are normally risk-averse, a tradeoff always exists between risk and return, often expressed as a tradeoff between the variance and the mean. If problems of moral hazard did not exist and insurance markets were complete, private investors would be able to buy insurance against commercial failure and undertake riskier projects. But investors cannot insure against commercial failure and normally shy away from excessively risky projects. The absence of an insurance market against commercial failure and government risk neutrality implies that some risky projects may be attractive to the public sector but not to the private sector If a project is not attractive to the private sector because of a high risk factor, public provision may be justified, even if the project produces a private good.

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Natural Monopolies

Natural monopolies, industries in which the conditions of demand and supply are such that production by a single firm minimizes costs, provide one of the oldest justifications for government provision of goods and services. Smith’s invisible hand works well only in competitive markets. In many markets competition does not exist; in others, competition is inefficient. Some production processes enjoy economies of scale; that is, unit costs of production fall as output rises. A common example is the supply of electricity. In densely populated regions, supplying electricity through an integrated network is more efficient than every household having its own generator.

When economies of scale are present, large firms produce more efficiently than small firms and tend to dominate their markets. Eventually they may drive smaller firms into bankruptcy and, in extreme cases, may become monopolies. Monopolies tend to charge too much and produce too little. Whenever natural monopolies arise, government intervention, at least in principle, can lead to more production at a lower price. However, before deciding on some form of government intervention, we need to assess the welfare losses from the exercise of monopoly power and the welfare gains from government intervention. 1

What kind of intervention is appropriate? The first option is to do nothing. This solution might be optimal when the product or service has close substitutes and monopoly power is weak, that is, when the ability to charge prices that result in excess profits is insignificant. In the case of cable television, for example, the presence of close substitutes reduces the monopoly power of cable providers enough to obviate the need for government intervention. A traditional solution is to provide the good or service through a public enterprise. In many countries

Externalities provide another traditional argument for government intervention. Sometimes activities generate benefits and costs that are not reflected in the firm’s benefits and costs. A forest, for example, may lower the level of carbon dioxide in the world, but the owner of the forest—who bears the full cost of planting and maintaining the forest—cannot charge

Public Goods

The strongest argument for public provision is rooted in the nature of the goods and services themselves. All goods provided by the private sector share one important feature: the provider of the good can charge those who wish to consume it and make a profit in the process. Not all goods,

Exclusion Difficult or Costly

Private markets do not produce no excludable public goods because of the impossibility of preventing anyone from consuming them, even if they do not want to pay for them. Consider national defense. If an army succeeds in defending the national territory against an enemy, every citizen benefits, whether he or she paid to sustain the army or not. Similarly, spraying an

area to rid it of malaria-carrying mosquitoes benefits every nearby inhabitant, but charging everyone for the service would be difficult. Those who refuse to pay get a free ride. If a sufficiently large number refuse, spraying may never take place. Because of these difficulties, the private sector will not usually produce no excludable public goods or will produce suboptimal.

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Exclusion Difficult or Costly

Private markets do not produce no excludable public goods because of the impossibility of preventing anyone from consuming them, even if they do not want to pay for them. Consider national defense. If an army succeeds in defending the national territory against an enemy, every citizen benefits, whether he or she paid to sustain the army or not. Similarly, spraying an area to rid it of malaria-carrying mosquitoes benefits every nearby inhabitant, but charging everyone for the service would be difficult. Those who refuse to pay get a free ride. If a sufficiently large number refuse, spraying may never take place. Because of these difficulties, the private sector will not usually produce no excludable public goods or will produce suboptimal quantities. Public production of no excludable public goods has been generally considered to enhance public welfare and therefore to be a proper function of government.

In some cases exclusion is possible, but costly. Roads are no excludable, but toll roads are excludable. The costs associated with building limited access roads, however, are considerably higher than those of normal roads; exclusion comes at a high cost. Whenever a project produces a good with a high exclusion cost, there is also a strong presumption for public provision.

No rival Goods—Exclusion Undesirable or Inefficient

Private goods also share another important characteristic, namely, that the marginal cost of consumption is no negligible. In the case of nontrivial public goods, however, the marginal cost of consumption is zero or very low. Once a bridge is built, for example, the marginal cost of letting another car use it is virtually zero, up to the point of congestion. Likewise, the cost of informing 1,000 consumers over the air waves is the same as the cost of informing 2,000. The information available to 1,000 additional consumers does not reduce the amount available to others—the marginal cost of consumption is zero. Although private production of no rival goods is possible, the private sector will produce suboptimal quantities. Socially optimal pricing requires that the price of goods or services be equal to the marginal cost of consumption. If the price equals marginal cost, private provision may be unprofitable. For an uncongested bridge, for example, optimal pricing would require a very low toll, too low to recover the initial investment and, hence, too low to interest the private sector. If the toll were set high enough to interest the private sector, too few cars would use the bridge. Low marginal cost of consumption is often used as an argument for public provision of research and extension, utility services, and public information services such as agricultural prices and weather patterns. The argument for public involvement in the provision of nonrival public goods is strong, but the nature of the involvement need not be provision of the good, as public funding of private provision may be optimal in many cases. For example, a government may achieve the optimal quantity of research and extension services with public funding of private provision

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Gainers and Losers

A project’s net stream of benefits and, hence, its NPV, is based on the assumption that the project functions as designed. The extent to which it does so depends not only on the quality of the design, but also on the incentives facing the various agents responsible for project implementation and on the costs and benefits that various groups in the society are likely to derive or incur from the project. The sustainability of a project relates intimately to its financial viability and to the distribution of project benefits. If the project requires monetary transfers for viability, analysts should estimate the magnitude and timing of the transfers.

In particular, the project’s fiscal impact is of crucial importance: one of the common causes of unsatisfactory performance in World Bank-financed projects is insufficient counterpart funds. Moreover, groups that derive a benefit from the project will have an interest in its success, and those who lose because of it will likely oppose it. The intensity with which gainers defend the project and losers attack it is related to the size of the respective benefits and costs. Thus, in assessing a project’s sustainability, it is helpful to identify (a) the various agents responsible for project implementation, assessing whether each has the incentives required to make the project work as designed, and (b) the various groups likely to gain or lose from the project.

This section provides tools that are helpful in these endeavors.

We begin at the difference between economic and financial prices and economic and financial flows. These differences represent rents or monetary flows that accrue to someone other than the project entity. Taxes represent monetary flows accruing to the government, but not to the project entity. Subsidies are transfers in the other direction, from the government to the project entity. We can identify winners and losers by decomposing the shadow prices used in economic analysis and showing exactly how and why financial and economic prices differ. We can also use the tools ofiation economic analysis to assess the project’s fiscal impact, shed light on whether the project should be a public or a private sector project, and decide if the

project is likely to contribute to the country’s welfare.

To illustrate how one uses the tools of economic analysis to answer these questions, we turn to two examples. The first is a typical private sector project included to show, among other things, how the tools help us decide that the private sector should undertake the project. The example also shows a good identification of the incremental costs and benefits of the project and of its fiscal impact. The second example is based on a World Bank project in the education sector and shows the application of most of the tools developed in this blog.

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Assigning Correlations among Project Components

After the analyst has identified all the relevant variables and specified their probability distributions, the next step is to make some judgments about the covariances among the different variables. Failure to specify covariances and to take them into account may lead to large errors in judging risk. For example, in a pioneering study on the use of risk analysis, Pouliquen  noted that the risk of project failure was estimated at about 15 percent when two important variables—labor productivity and port capacity—were treated as independent, and at about 40 percent when their positive correlation was introduced into the analysis.

Analysts may need to treat variables jointly if they are statistically dependent. In such a case they should specify, in principle, the multivariate joint distributions involved. Specification of multivariate distributions can be extremely complex, but to resort to comprehensive descriptions of statistical polygons, dependence is seldom necessary in applied project work. Rather, pragmatic methods are readily available for imposing arbitrary levels of statistical dependence. Analysts usually do this by specifying a rank correlation coefficient for each designated pair of variables. The individual variables can be of any specified type, and many different types are available in commercial software: normal, triangular, beta, exponential, and the like, as well as arbitrary continuous and discrete distributions. The final step consists of putting it all together—estimating the expected NPV and its attendant probability distribution, which includes the probability that the project’s NPV is negative.

The results of the analysis can be reported in condensed form through summary statistical measures such as the expected NPV and its coefficient of variation. Analysts will also naturally wish to examine the complete probability distribution of project performance, for example, by depicting graphically the complete CDFs for the project’s NPV   Analysts can read one key measure—the probability that the project’s NPV is less than zero—directly from such CDFs. An illustration of such an analysis based on a hypothetical example using a spreadsheet-based program follows.

A Hypothetical Example: Advantages of Estimating Expected NPV and Assessing Risk

The Caneland Republic is typical of several efficient producers and exporters of cane sugar in that because sugar makes up about 35 percent of exports, it is a major source of foreign exchange. Because the price of sugar fluctuates considerably, however, earnings from sugar exports are unstable, which contributes to significant macroeconomic fluctuations. Gross value of sugar production constitutes about 10 percent of GDP, but this is varies considerably, from 27 percent in 1974 to 4 percent in 1978. GDP and sugar prices are highly correlated. For a recent 21-year period, there is a simple correlation of 0.32 between the residuals from constant  growth rate trends of real GDP and sugar output valued at the real international price. This valuation ignores domestic sugar pricing and the price realized on privileged sales to the United States and other importers.

The hypothetical project involves a major new sugar estate and associated infrastructure of mills, roads, and other handling facilities. When the project is fully on stream, farmers will harvest an additional 30,000 hectares of cane annually. When processed, the farmers will have to sell the sugar on the international market, within the limits agreed under the International Sugar Agreement.

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Monte Carlo Simulation and Risk Analysis

Proper estimation of the expected NPV of a project normally requires the use of simulation techniques. Simulation is the only simple and generally applicable procedure for overcoming the limitations of sensitivity analysis, calculating the expected NPV, and analyzing risk. Simulation usually requires more information than sensitivity analysis, but the results in terms of improved project design are worth the effort. Proper estimation of the expected NPV requires three steps:

• Specifying the probability distribution of the important uncertain components

• Specifying the correlations between the components

• Combining this information to generate the expected NPV and the underlying probability distribution of project outcomes.

Generating the underlying distribution and calculating the expected NPV through mathematical analysis is generally impossible. The analyst must rely on computer-generated simulations. Using the specified probability distributions of the uncertain project components, the computer simulates as many outcomes as the analyst wishes. In Monte Carlo simulation, the computer acts as if we were implementing the same project hundreds or thousands of times under the specified conditions. Because we assume that some of the project variables are uncertain, the simulated results are different each time. Sometimes the resulting NPV may be negative, sometimes it may be highly positive. The computer pools the results to obtain an estimate of the average result and of its probability distribution. From the simulations, the computer generates a probability distribution for the NPV, including the probability that the project is a failure and the expected NPV. Analysts can readily obtain such software for performing these analyses. Although the techniques are as easy to use as estimating the NPV or IRR of a project, they do require additional information and expert judgment concerning the probability distributions of the critical project components.

Assigning Probability Distributions of Project Components

Assigning probability distributions to project component variables and specifying correlations is the most difficult step. Analysts should base economic analysis on a realistic assessment of costs and benefits, which in turn requires that the estimates of all relevant variables draw on experience in the sector and the country. Quantity forecasts should be based on clearly identified market factors and on experience-based behavioral, technical, financial, institutional, and environmental assumptions.

Analysts can quantify judgment and experience at several levels of sophistication, but even a rather simplified approach is useful in project design. We do not usually need to consider a large number of variables.

Sensitivity analysis can help identify the variables for which probability distributions should be most carefully specified. If, for example, sensitivity analysis shows that the influence of a particular variable is relatively minor, we can treat that variable as if it were certain without introducing large errors. Also, the specification of the probability distribution for a selected variable need not be based on hard data. For example, a large sample of past observations may be available that permits fits against assumed probability distributions, or the analyst may have access to evidence of a more qualitative and subjective nature. The subjective judgments of experienced engineers, financial analysts, and others involved may be valuable in this context.

Finally, if the distributions are unknown, project analysts can also make simplifying assumptions about the probability distribution of variables. One of the simplest and most popular distributions used in empirical risk analysis is the triangular distribution. Three parameters completely describe this distribution: the most likely value (the mode), the lowest possible value, and the highest possible value. The expected value of a triangular distribution is one-third of the sum of the three parameters.

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Selection of Variables and Depth of Analysis

When conducting sensitivity analysis, the analyst should normally consider

three specific areas:

• Aggregate costs and benefits. Simple sensitivity analysis of the effects of variations in total project costs and total project benefits often helps to indicate the joint influence of underlying variables. Except in special cases, however, this type of aggregate analysis alone does not assist judgments on the range of likely variation or on the specific measures that might  reduce project risks.

• Critical cost and benefit items. Sensitivity tests are usually most effective if costs and benefits are disaggregated in some detail. While the use of subaggregates—investment costs, operating costs, and the like—can be helpful, sensitivity analysis is best done in respect of individual parameters that are most critical to the project. On the benefit side, detailed sensitivity analysis typically includes such parameters as output prices or tariff levels, unit cost savings, and expected rate of growth in demand for project outputs. On the cost side, such analysis typically involves productivity coefficients and prices of major inputs. Shadow prices used in the economic analysis should normally be examined in sensitivity analysis.

• The effects of delays. Several types of delays can occur in projects: delays in starting the project, delays during the construction phase, or delays in reaching full capacity utilization (as in industrial projects) or in reaching full development  Analysts should include the relevant delay factors in sensitivity tests.1 The amount of detail desirable in sensitivity tests varies considerably from case to case. Analysts should analyze delays in terms of the effects on the NPV of delays of specified time intervals  although it may occasionally be useful to calculate the maximum permissible delay or switching value. The switching value method is, however, the preferred form of analysis for other variables, esp

The Expected Net Present Value Criterion

For projects with benefits measurable in monetary terms, the criterion for project acceptability should be the project’s expected NPV. This criterion requires that the project’s expected NPV must not be negative and must be at least as high as that of other mutually exclusive options. In most cases, this criterion is equivalent to requiring that the expected IRR exceed the opportunity cost of capital. The expected value, calculated by weighting all possible project outcomes with their corresponding relative frequencies or probabilities, takes account of the entire range of possible present values of net benefits from the project. For instance, the expected NPV of the following project is 3.6.

NPV versus Best Estimates

We often refer to the NPVs and IRRs reported in project appraisal documents as best estimates, sometimes meaning expected, and sometimes meaning most likely, values. The expected value, or mean, is not the same as the most likely value, or mode. The mode is the most frequently occurring value, or the most likely value, among all the possible values the NPV can take. Although for some statistical distributions the mode and the mean  coincide, often they do not. In the example, the mode—the value with the highest probability—is 7, whereas the mean is only 3.6.

Unfortunately, the use of modal values instead of means seems to be somewhat common. In many cases, analysts choose the most likely values for quantities, prices, and other uncertain variables. This approach may lead to wrong decisions, because the sum of most likely values is not always the most likely value of the sum. 

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Fiscal Impact

To the extent that transport projects produce public goods, the beneficiaries either cannot or should not be charged directly by the government for the benefits received. The costs of transport projects must, therefore, be recovered through taxes. As discussed in older article, for every tax dollar collected, society incurs an extra cost that is likely to be in the neighborhood of 30 percent. This marginal cost of public funds reduces the net benefits of transport projects and needs to be added to the cost of projects. If any of these costs can be recovered directly from the beneficiaries through user charges, it would be preferable to do so rather than relying on the tax system. Note that if a road is partially financed from tolls, the 30 percent premium on public funds applies only to that portion of the project that is not financed from tolls.

Risk and Sensitivity Analysis

Project outcomes necessarily depend on uncertain future events. The basic elements in the cost and benefit streams of projects—such as input and output prices and quantities—seldom represent certain, or almost certain, events in the sense that they can be reasonably represented by single values. Uncertainty and risk are present whenever a project has more than one possible outcome. The measurement of economic costs and benefits, therefore, inevitably involves explicit or implicit probability judgments.

Take the example of someone who wants to buy coffee today, hold it for a year, and then sell it. Because commodity prices are extremely variable, the outcome of this simple project is uncertain and the person undertaking the project is taking a risk. Such a project would have made money in 12 out of 23 years between 1970 and 1993, lost money in 10 out of 23 years, and broken even in 1 out of 23 years. If we use the past as a guide to the future, we would recognize the possibility of at least three outcomes, each with a different probability of occurring. If the project entailed renovating coffee plantations, uncertainty about yields and costs would be added to uncertainty about coffee prices. As a result, the number of possible outcomes would increase dramatically.

The preferred approach to sensitivity analysis uses switching values. The switching value of a variable is that value at which the project’s NPV becomes zero or the IRR equals the discount rate. We usually present switching values in terms of the percentage change in the value of variable needed to turn the project’s NPV equal to zero. We may use switching values to identify which variables have the greatest effect on project outcomes. We may also present the switching values of the relatively more important variables in order of declining sensitivity

In this example, the most critical variable is yield. A decrease of more than 25 percent in the posited expected yield will make the NPV negative if other values remain as expected. If experience suggests that yield can easily be that much less than expected, perhaps because of poor quality.

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Environmental Impact

Most transportation projects generate environmental externalities. Roads, in particular, have sizable direct or indirect environmental impacts. These impacts may be particularly profound in the case of roads that penetrate virgin lands, and analysts need to take them into account to the extent possible in the calculation of the costs and benefits of transport projects.

New roads may have direct environmental impacts along the construction routes and indirect impacts through the improved access they provide. The indirect effects may be more serious than those directly related to the project, because access may encourage deforestation, result in the loss of fertile soil, and reduce the levels of plants and wildlife. Higher traffic volume also increases air pollution, noise, vibration, and construction of aesthetically displeasing structures.

Mitigating environmental impacts is costly, and environmental benefits do not have infinite value. Therefore, the costs and benefits of measures that reduce environmental impacts need to be assessed.

The Highway Development Model

As the preceding discussion indicates, selecting the optimal alternative in transportation projects can be a very complex task. The analysts must consider numerous options, namely,

          • The baseline data and projections of traffic flows with and without  the project

• The project’s impact on generated demand

• The project’s impact on existing services.

          Even in relatively straightforward projects, such as roads, they have a wide range of options to consider, including

          • The design of the road

— Whether or not to pave

— How thick the pavement should be

— How wide and how straight the road should be

• Limitations on vehicle size and weights

• Limitations on access.

Each of these factors affects vehicle operating costs, time savings, accident rates, environmental impacts, and, therefore, the costs and benefits of roads. Several computer models are available to help calculate road benefits under different conditions and savings resulting from road improvements. The Highway Design and Maintenance Standard Model III  is a computer program the World Bank developed to analyze the total transport costs of alternative road improvement and maintenance strategies. The program assesses the total annual costs of road construction, maintenance, vehicle operation, and travel time costs over the life of a project as a function of road design, maintenance standards, and other variables. The program compares the cost and benefit streams of alternative strategies, including different timing and staging options, and assesses the strategy that yields the highest net benefits to society, subject to a budget constraint.

Analysts can use the HDM III to compare the costs and benefits of different policies; estimate total costs for alternative project designs; and to test the sensitivity of the results to changes in the basic assumptions, including unit costs, traffic growth, and value of time. The model does not endogenously calculate accidents and environmental impacts, but these may be added exogenously. The model also does not incorporate demand reactions to changes in prices.

Gainers and Losers

A rural road may be intended to benefit producers, but the actual benefits may accrue to truckers, middlemen, or consumers; therefore, the analyst should carefully assess the distribution of benefits from transportation projects. Improving a port may reduce turnaround time for ships, but the distribution of the benefits will depend on the degree of competition in shipping and on the pricing policy of the port authority.

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Network Effects within a Mode

Improving a network link is likely to attract traffic to that link and thus change traffic levels elsewhere. In links that are alternatives to the improved link, traffic levels are likely to fall and users are likely to experience less congestion and reduced travel time. They might also experience reduced VOC. In addition, some savings may be gained from reduced road maintenance costs. Links that are complementary to the improved link, that is, links that feed the improved segment, may see increases in traffic and thus some deterioration of performance. Whether traffic volumes increase or decrease, summing the basic measure of benefits over all affected links in the network gives a good approximation to the total benefits of an improvement.

The same analysis as applied to the aforementioned situation can be applied to intermodal effects. Improving a link in a road network may, for example, attract passengers from public to private transport. If this involves no other adjustment, the withdrawal of patronage from a public transport system will reduce its revenues and its operating costs. The decrease in net revenue will be equal to the difference in gross revenue minus the difference in cost. The analyst should subtract that amount from the calculated benefits for road users.

Alternative responses are possible for the public transport operating agency, for instance, fares may be lowered. In that event, public transport users would receive a windfall gain at the expense of the provider, but the net loss to society would still be equal to the net revenue loss.

         

Most typically the response will be some combination of the above. If possible, the analyst should forecast that response and the actual losses estimated on the basis of the expected conjectural response. The converse of these arguments applies where public transport service improves because of an investment. The direct benefits in this case would be the financial effect on the operator, plus any financial effect on public transport users, plus any change in waiting time of public transport users, plus any effect on the generalized costs of private transport users in the system.

Just because a project’s benefits exceeds its costs does not mean that the project should begin immediately. Hence, the timing of a project should be analyzed in every case. Postponing a project may change the time profile of costs and benefits and the project’s NPV. If the profile of benefits and costs does not change, but is only postponed, then timing is not an issue. The present value of the benefits and costs will change proportionally by the discount factor used. Consider a situation in which the present value of a project’s benefits discounted at 20 percent is US$12, the present value of costs is US$6, and postponing the project one year merely shifts all costs and benefits by one year. Then the present value of both benefits and costs will be reduced by the same percentage, as will the NPV of the project itself. In these cases the sooner the project starts, the higher the NPV. If, by contrast, the benefit or cost profile changes with postponement, then timing becomes an issue.

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Estimating the Incidence of Accidents

It is common practice to estimate the incidence of accidents based on road type and traffic conditions. Analysts first estimate the impact of projects on expected traffic levels and conditions. With this estimate as a basis, they forecast the rate and severity of accidents. The incidence of accidents, however, is often sensitive to local conditions and road design, both of which are difficult to incorporate into the forecasting procedure. As a result, forecasts of accident rates are usually unreliable. Therefore, we recommend careful risk analysis for infrastructure investment projects that rely substantially on accident savings for their justification. Most developing countries lack documentation on the impact of safety measures on accident reduction. Consequently, estimating the benefits of projects usually entails comparing the baseline figures with accident rates in conditions similar to the ones prevailing with the project elsewhere in the country or in other countries.

Producer Surplus or Net National Income Approach

Transport projects sometimes break new ground. Workers occasionally construct new rural roads, for example, in areas where no conventional roads exist. In these cases, analysts have extreme difficulty obtaining baseline data as well as predicting future traffic flows. For these reasons, estimating the benefits of penetration roads uses alternative approaches, such as national income increments.

The problems that arise as one estimates the benefits of penetration roads can be illustrated as follows. When a road is built into an area where motor vehicles cannot enter, the initial traffic volume is zero. As a result, the benefits of the project will stem solely from the traffic generated by the new road, that is, from the increase in consumer surplus.

As can be seen from older article, in road improvement projects the benefits from cost reduction are likely to be larger than the benefits from increased consumer surplus Moreover, the estimates of actual costs and actual traffic are usually reliable, whereas the estimates of consumer surplus  which depend on traffic projections, are subject to larger margins of error. The estimated benefits of penetration roads, however, are based solely on projections of traffic and costs. In summary, analysts can estimate benefits of road improvements more accurately than benefits of penetration roads. As can be seen from older article, in road improvement projects the benefits from cost reduction  area C1C2da  are likely to be larger than the benefits from increased consumer surplus  Moreover, the estimates of actual costs and actual traffic  are usually reliable, whereas the estimates of consumer surplus  which depend on traffic projections, are subject to larger margins of error. The estimated benefits of penetration roads, however, are based solely on projections of traffic and costs. In summary, analysts can estimate benefits of road improvements more accurately than benefits of penetration roads. 

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Reduction of Vehicle Operating Costs

Savings in VOC are the most easily measurable and frequently the most important benefit from transport projects. Such savings usually include fuel and lubricants; tires; maintenance; and economic depreciation, such as vehicle wear and tear. These costs depend in turn on road geometry  surface conditions driver behavior, and traffic control. VOC are higher on grades, curves, rough surfaces, and slower roads. Changes in any of these parameters will result in a change in vehicle operating costs.

Time is valuable. Any transport project that saves time produces important and measurable benefits. In many cases, the value of time saved is reflected in demand for faster service and the price that consumers are willing to pay for it, as in the case of airplane services. The value that consumers attach to time saved must be derived indirectly, especially for most roads. This section presents a methodology for valuing time savings when their monetary value cannot be measured directly.

The Value of Working Time

If a working person undertakes a trip during working hours, the time employed is time not used at work. Working time saved, then, is working time that can be used to produce goods and services, and its value is the wage rate plus any other costs associated with employment, such as social security taxes. On this basis, savings in working time may be valued at the cost to the employer.

The Value of Nonworking Time

Individuals’ willingness to pay determines the value of time saved in trips undertaken for nonworking purposes. Because no explicit market exists for time spent at leisure, no market price for that time can be observed and the value of time, therefore, must be inferred. In principle, willingness to pay for savings of leisure time should be lower than willingness to pay for savings of work time, because the wage rate includes payment both for the effort and the scarce skills embodied in the work activity.

Walking and Waiting Time

Most people dislike waiting and walking for nonrecreational purposes. Consequently, projects that reduce waiting time and walking generate more benefits than projects that only reduce travel time. Recent studies in Europe have shown that the value of time saved in transfer and waiting is valued at a third to two times more than in-vehicle traveling time. Chilean studies  have shown even higher ratios. We should value walking, waiting, and transfer times—excess travel time—at a premium. Whereas estimating country-specific values is always preferable, in the absence of such values a good rule of thumb is to value walking, waiting, and transfer time 50 percent higher than in-vehicle traveling time. Box 10.1 shows an example of these concepts applied to a transport project in Brazil.

Freight Traffic

Time saved for freight vehicles entails cost savings for vehicle owners. At the margin, the willingness to pay to save time is equal to the marginal cost of resources saved. The factor cost method of valuing time saved for freight involves identifying the components of vehicle costs. These may vary with the amount of elapsed time, and include wages, interest on capital employed or tied up in inventory on wheels, and licensing fees. The stated preference method, which involves carefully customized studies of shipper choice, may pick up additional, subtler, sources of value and, hence, yield somewhat higher values for time savings. In the absence of such studies, we suggest the resource cost approach.

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