Cost-Benefit Analysis - Essay Example

Cost-benefit Analysis Before starting a new project or erecting a new plant, prudent managers conduct a thorough cost-benefit analysis as a way of scrutinizing all of the potential expenditures and any revenues if the project is completed. The result of such an analysis is very significant as it determines the financial feasibility of the project and whether the project should be carried on or if another project should be erected (Hahn 2010). Cost-benefit analysis (CBA) or otherwise referred to as benefit-cost analysis (BCA) is an approach that is done systematically to estimate the strengths and weaknesses of a business project or alternatives that satisfy business activities, transactions or functional requirements. It is a criterion that is used to determine alternatives that avail the best approach to adoption and practice in terms of financial feasibility, labor as well as time effectiveness. Although CBA is related to cost-effective analysis, the two approaches are ultimately different from each other in that the benefits of projects in CBA are represented in monetary terms. CBA is usually used by governments and in the private sector businesses, to discern the desirability of a given project or a policy. CBA gives an analysis of the balance of benefits and costs, which includes an account of forgone alternatives and is crucial in predicting whether there is more weight on the benefits of the project than the costs, and by how much in comparison to other alternatives (Hahn 2010). The idea of CBA first originated by a French engineer called Jules Dupuit; while a British economist by the name Alfred Marshall was responsible for formulating some of the concepts that validate CBA. However, the practical development of CBA came as a result of the US Corps of Engineers being required to carry out projects for the advancements of the waterway system by the Federal Navigation Act of 1936. The US Corps were required to improve the waterway system when the total benefits of a project exceeded that particular project. By so doing, the Engineers developed systematic criteria for measuring both the benefits and the costs and they did this without assistance from economic professionals. It was until the 1950s when the economists constructed rigorous and consisted ways of measuring the benefits and costs of a policy to determine its worth (Hahn 2010). To determine or conclude the desirability of a project, there must be a bottom line; there must be a common unit from which the aspects of the project are expressed and that is why they are expressed in terms of money. It is a requirement of CBA that there must be a common a common unit in which the aspects of the project will be expressed, implying that all the benefits and the costs will be measured in terms of their monetary value. It should not be forgotten that not only that all the benefits and costs should be expressed in monetary value, but also that they should be expressed in terms of monetary value of a specific time. This is because a dollar of five years ago is not as good as a dollar of today (Hahn 2010). Dynamic versus Static Scoring of budget Laws: Pros and Cons Dynamic score is a criterion for estimating the amount of revenue that would be lost or gained by a proposal change in tax and the amount of money that would be spent or saved by expending on proposals such as investment in roads or reduced expenditure on space exploration. It predicts the fiscal policy changes effect through forecasting the effect of economic agents’ reactions as a result of incentives that might have created by policy. This method requires the economists to infer from economic agents’ present behavior and how the agents would probably behave when subjected to the current policy (Ganelli & Tervala 2014). When feasibility is arrived at, dynamic scoring will yield a more accurate and reliable prediction of the impact of new policy on the country’s fiscal balance and economic output. The higher accuracy of dynamic scoring is as result of the recognition that there will be a definite change in behavior by the household and the firms, to continue maximizing profits and welfare under the protracted new policy. However, this precision of dynamic scoring is more evident than static scoring when the econometric model is able to correctly capture how household and firms will react to the protracted new policy. On the other hand, static scoring, otherwise called static analysis and static projection, can be referred to as a method for analysis of the impact of a new project wherein the effect of immediate change is only calculated, without considering the long-term effect of that very change to a policy. When the government proposes tax cuts, the economists then calculate the monetary value that that policy will cost the government. The assumption that static scoring employs is that there would be no change in the economic behavior of the households and the firms affected and that lower tax rates will not prompt the affected individuals and firms to behave any differently than they currently do. The two methods have their benefits and drawbacks, and while looking at the pros of dynamic scoring, it has the effect of improving the accuracy of the budget scoring. When there is an effect of a policy on the economic growth, and because the policy affects economic size and has influence on the level of public revenues and expenditures, a feedback effect can be expected in the budget (Ganelli & Tervala 2014). A feasible dynamic scoring operates under the principle that policies that promote growth shall have a small budgetary allocation and those that have slow growth shall have a larger budgetary allocation. This is not the case with the static scoring. Additionally, dynamic scoring has the effect of removing the bias against pro-growth policies when it comes to budget scoring. With the static scoring ignoring the effects of macroeconomics, it overstates the actual budgetary cost of the pro-growth policies, while understating the cost of the anti-growth policies. For instance, the static scoring of two policies deemed to have two opposite effects on the growth of the economy could see policymakers weighing the two policies misled. This could reject the policy that depicts a positive effect on the economy since it would be erroneously estimated to demand a larger budgetary allocation than it should and would also be forced to select an anti-growth policy because it would be presented to be cheaper than it actually is (Ganelli & Tervala 2014). This bias is not present in the dynamic scoring. However, this method has a couple of disadvantages; economists are not informed on how to accurately determine the growth effects of most policies while using the dynamic scoring. There are numerous macroeconomic results that are not factored in such as growth, unemployment and inflation and which are a function of the policy. Unrelated factors such as outbreak of war, catastrophic events, technological innovations and the rest are also isolated in the policy but can have a big impact on the economic growth. Another problem is that dynamic scoring relies on macroeconomic models that are not satisfactorily accurate, theoretical and this may result inS different results in attempt to measure the growth effects and the subsequent feedback effects of a particular policy (Ganelli & Tervala 2014). Numerous and controversial assumptions that are in-built in the macro models that are used in the dynamic scoring is another reason that renders it questionable to be utilized. While these assumptions are not carefully empirically based, they seem to have overlooked the importance of understanding the theoretical and technical problem posed by dynamic scoring (Burgess & Zerbe 2011). To support this claim, a comparison of empirical estimates of supply-side results to estimates of such responses embedded in commonly used dynamic scoring macro models found out that some models make insignificant attempts to link the elasticity evident in labor supply to the ones in the empirical evidence. Discounting and time perspective in Cost-Benefit Analysis Discounting is a technique used in CBA that translates future costs and benefits into today’s monetary values. Time value of money stipulates that the worth of present-day money is more than that of future because of the propensity and the preference of people to spend money now than in future and because today’s money can be invested for bear some profit. When used in propriety, discounting future money gives a more reliable and accurate assessment of economic impact of a policy or a project (Burgess & Zerbe, 2011). Discounting reflects the amount of time between the present and the point at which the changes occur, the rate at which changes in consumption are expected in the absence of the policy, the rate at which marginal value of consumption diminishes with an increase in consumption and future utility rate of consumption which will be discounted with time. Selecting an ideal discount rate is very important because different rates are capable of producing different cost-benefit results and these can affect the recommendations of the policy (Burgess & Zerbe 2011). A high discount rate reduces a significant amount of future benefits and cost to a substantially small present-day value. On the other hand, a lower rate reduces future values in proportionally less values, thus, future values for benefits and costs are drawn closer to present-day currency values. Discounting involves annualization of costs and benefits; an annualized value being the amount one would have to pay at the end of each period t so that the sum of payments in current monetary value is equivalent to the original stream of values. Annualization of costs and benefits is very essential in CBA because it changes the time-varying stream of values to a consistent stream. When evaluating non-monetized benefits such as reductions in heath risks, reductions in emissions, when the benefits are constant over the time t.annualization is also essential (Burgess & Zerbe 2011). Valuing life in Cost-Benefit Analysis: Economics and Ethics One of the hoodoos that live in the midst of laymen is the issue of the value of life. People believe that life is invaluable, priceless; and that attaching a monetary value to an individual’s life can be termed as the biggest insult ever to exist. But is it really priceless economically? Never! This argument of impossibility of determination of monetary value can only be justifiable with regards to reasoning of ethics and language of a particular people. However, in economics and political science, valuation of human life is very essential and necessary in the analysis of risk. The cost of life, otherwise called the potency of life, is an economic value that is assigned to life in general (Robinson & Hammitt 2013). It is the marginal cost of preventing death in a particular caliber of circumstances in the context of social and political sciences. This economic value, as many studies have put through, includes the quality of life, the expected life time remaining of the living organism and the earning potential of the persons in question. Therefore, the cost of life could be argued as a statistical term of reducing the number of deaths by a unit. Individuals make decision, everyday, that map how they value health and issues related to mortality risks. For instance, the construction of a highway is expensive in terms of human lives, since live could be lost through accidents and so on; consumption of a risky product indicates the behavior of the consumer and their determination of the statistical value of their lives. Using evidences on market choices, economists have developed estimates of the values of a statistical life (Robinson & Hammitt 2013). In CBA, if a policy is meant to save 100 over a period of 10 years with a probability of 80%; implying that the expected number of caved lives is 80, this value is the statistical and should not be net, but an expected number. As such, if the problem of regulation is to reduce risks and increase safety, the policy’s goal should be gauged by the number of lives saved. Life has a value that is relative to other ends, hence, a tradeoff is evident between life and legal policy ends. The question of the value of a life is only raised to determine the feasibility of a certain policy. Therefore, reduction of mortality rates as a government policy must be on par with a certain criteria for a reasonable decision, and CBA is the best mechanism to attain such reasonability (Robinson & Hammitt 2013). Uncertainty in Cost-Benefit Analysis CBA as an important tool in the assessment of a government’s projects and policies incorporates risks and uncertainty in the analysis and while in practice, risks and uncertainties of the variables entered in CBA will affect the precision and the effectiveness of the estimated expected values of Net Present Value (NPV) and the expected NPV itself. It is therefore important to consider the impacts of the risks and the uncertainties when using CBA. Uncertainty can be defined to be a form of randomness which can not be quantified, or in other words, that can not be measured or captured by a probability distribution. Uncertainties can range from catastrophes, like earthquakes, bad weather and so on; terrorist attacks, diseases and the rest. They can be said to be events that are not perceivable (Horowitz & Lange 2014). In CBA, most of the uncertainties arise as result of two factors; difficulty in measuring or predicting the impacts of the policies or programs and the difficulty in monetizing the value of those impacts. Feasible CBA considers a wide range of possible uncertainties and explains the probable outcomes at the wake of their occurrence. Government possesses a wide range of instruments that are capable of affecting the market solution and the social welfare of the households and the firms as well. These include taxes, subsidies, mandatory injunctions, standards and others. The government then faces a colossal maximization problem: choose for all future periods all different instruments contingent on all possible sources of randomness in order to maximize social welfare subject to the functioning of the economy – including the impacts of all market failures – and the reactions of firms and individuals. This problem can not be solved easily, even theoretically, and therefore, CBA breaks down this problem into smaller parts to reduce its complexity (Horowitz & Lange 2014). Contingent Valuation Analysis Economists tend to think that markets work well mostly, with the phrase “work well” implying that they efficiently allocate resources. When there is efficient allocation of resources by markets, the government does not need to intervene in any way in the economy, unless there is a need to transfer the advantage to some particular group. However, government intervention is required when there is failure of the market in resource allocation. Coat Benefit Analysis allows the demonstration of whether government intervention is superior to the existing market mechanisms of efficiency in resource allocation. CBA asks questions like: are the social benefits of a particular government intervention greater than the social costs? The aim of CBA is to inform the social policymaking and enhance are more efficient allocation of resources (Price 2000). The contingent valuation method is referred as contingent valuation because it employs information on how households suggest they would behave under certain hypothetical economic circumstances, contingent on being in the real situation. While, contingent value analysis is used in CBA to estimate the monetary value of the impacts of a project or a policy that are non-market, decisions that are made on the other parts of the CBA will have an influence on the decisions made in the contingent value analysis or study. Taking questions about the areas covered by the project and the various alternatives available will influence the range of the hypothetical questions that must be presented (Price 2000). Therefore, the economists dealing with the contingent value analysis must work in conjunction with other economists and scientists working on the research of public policy decision-making, so that their work correlate to give consistent inferences. Contingent value analysis has various advantages in comparison to other preference methods. CVM (contingent value method) are more flexible in comparison to the other preference methods, allowing the estimation of a wide range of policies. CMV is used to estimate the benefits more accurately beyond the range of experience. Additionally, CVM can be used to estimated non-use values and the willingness to pay (WTP) under demand and supply uncertainty (Price 2000). Conclusion Having discussed various components of the Cost Benefit Analysis, it is clear that this is an important part of public economics. Before starting a new project or erecting a new plant, prudent managers should conduct a thorough cost-benefit analysis as a way of scrutinizing all of the potential expenditures and any revenues if the project is completed. The result of such an analysis is very significant as it determines the financial feasibility of the project and whether the project should be carried on or if another project should be erected. This can only possible when Cost Benefit Analysis is employed, which has the ability to bring out all the strengths and weaknesses of any project or policy. Works Cited Burgess, David F, and Richard O Zerbe. Appropriate Discounting For Benefit-Cost Analysis. Journal of Benefit-Cost Analysis 2.2 (2011): n. pag. Web. Ganelli, Giovanni, and Juha Tervala. Dynamic Scoring In Open Economies. finanzarchiv 70.1 (2014): 31-66. Web. Hahn, Robert. Designing Smarter Regulation With Improved Benefit-Cost Analysis. Journal of Benefit-Cost Analysis 1.1 (2010): n. pag. Web. Horowitz, John, and Andreas Lange. Cost–Benefit Analysis Under Uncertainty — A Note On Weitzmans Dismal Theorem. Energy Economics 42 (2014): 201-203. Web. Price, Colin. Valuation Of Unpriced Products: Contingent Valuation, Cost–Benefit Analysis And Participatory Democracy. Land Use Policy 17.3 (2000): 187-196. Web. Robinson, Lisa A., and James K. Hammitt. Skills Of The Trade: Valuing Health Risk Reductions In Benefit-Cost Analysis. Journal of Benefit-Cost Analysis 4.1 (2013): n. pag. Web. Read More