Shadow Cost Research Articles

Investment coordination in network industries: the case of electricity grid and electricity generation

Liberalization of network industries frequently separates the network from the other parts of the industry. This is important in particular for the electricity industry where private firms invest into generation facilities, while network investments usually are controlled by regulators. We discuss two regulatory regimes. First, the regulator can only decide on the network extension. Second, she can additionally use a “capacity market” with payments contingent on private generation investment. For the first case, we find that even absent asymmetric information, a lack of regulatory commitment can cause inefficiently high or inefficiently low investments. For the second case, we develop a standard handicap auction which implements the first best under asymmetric information if there are no shadow costs of public funds. With shadow costs, no simple mechanism can implement the second best outcome.

Optimal Keyword Auctions with Shadow Costs

Poor user experiences with search advertisements can lead to ad avoidance thus reduce search engine’s long-term revenue. We capture the effect of negative user experiences on search engine’s future revenue in a new variable called “shadow costs” and examine the optimal keyword auction mechanisms (KAMs) in a general model that takes into account advertiser-specific and positionspecific shadow costs. We show that the optimal KAMs can be implemented in an ex-post equilibrium with a “progressive second price” payment rule. Furthermore, under a few special but practically relevant cases, the optimal KAM takes the form of relatively simple scoring auctions. We show that minimum bids in these scoring auctions may be advertiser- or position- specific and the allocation rule may or may not be greedy. Our results highlight impact of shadow costs on keyword auction designs and hold implications for search engines, advertisers, and Internet users.

The Shadow Cost of Bank Capital Requirements

We estimate the shadow cost of capital requirements using data on a costly loophole that allowed banks to relax these constraints. This loophole — liquidity guarantees to asset-backed commercial paper conduits — was exploited by the largest banks before the crisis of 2008. We show theoretically that a bank's use of the loophole reveals its private compliance cost, which takes into account both the costs of issuing equity and the effectiveness of capital regulation. We find that increasing capital requirements would impose a modest cost — $220 million a year for all participating banks combined per 1pp increase, and $14 million on average.

Optimal keyword auctions for optimal user experiences

Poor user experiences with search advertisements can lead to ad avoidance thus reduce search engine's long-term revenue. We capture the effect of negative user experiences on search engine's future revenue in a new variable called “shadow costs” and examine the optimal keyword auction mechanisms (KAMs) in a general model that takes into account advertiser-specific and position-specific shadow costs. We show that the optimal KAMs can be implemented in an ex-post equilibrium with a “progressive second price” payment rule. Furthermore, under a few special but practically relevant cases, the optimal KAM takes the form of relatively simple scoring auctions. We show that minimum bids in these scoring auctions may be advertiser- or position-specific and the allocation rule may or may not be greedy. Our results highlight impact of shadow costs on keyword auction designs and hold implications for search engines, advertisers, and internet users.

Environmental efficiency among corn ethanol plants

Economic viability of the US corn ethanol industry depends on prices, technical and economic efficiency of plants and the extent of policy support. Public policy support is tied to the environmental efficiency of plants measured as their impact on emissions of greenhouse gases. This study evaluates the environmental efficiency of seven recently constructed ethanol plants in the North Central region of the US, using nonparametric data envelopment analysis (DEA). The minimum feasible level of GHG emissions per unit of ethanol is calculated for each plant and this level is decomposed into its technical and allocative sources. Results show that, on average, plants in our sample may be able to reduce GHG emissions by a maximum of 6% or by 2.94 Gg per quarter. Input and output allocations that maximize returns over operating costs (ROOC) are also found based on observed prices. The environmentally efficient allocation, the ROOC-maximizing allocation, and the observed allocation for each plant are combined to calculate economic (shadow) cost of reducing greenhouse gas emissions. These shadow costs gauge the extent to which there is a trade off or a complementarity between environmental and economic targets. Results reveal that, at current activity levels, plants may have room for simultaneous improvement of environmental efficiency and economic profitability.

Cost of Equity and S&P 500 Index Revisions

We examine how the cost of equity changes when firms are added to or removed from the S&P 500 Index during index revisions. Newly added firms experience a significant decline in the cost of equity, while recently removed firms show a significant increase. Liquidity improves for addition firms and declines for removed firms. Addition firms also experience a decline in shadow cost. Changes in cost of equity for included firms are explained by changes in liquidity, shadow cost, and firm size. Finally, included firms with greater investment opportunities benefit more from the reduction in cost of capital.

The Cost of Financial Frictions for Life Insurers

During the financial crisis, life insurers sold long-term policies at deep discounts relative to actuarial value. The average markup was as low as −19 percent for annuities and −57 percent for life insurance. This extraordinary pricing behavior was due to financial and product market frictions, interacting with statutory reserve regulation that allowed life insurers to record far less than a dollar of reserve per dollar of future insurance liability. We identify the shadow cost of capital through exogenous variation in required reserves across different types of policies. The shadow cost was $0.96 per dollar of statutory capital for the average company in November 2008. (JEL G01, G22, G28, G32)

Measuring performance, development and growth when restricting flexibility

In industries with heterogeneous firms and fast-changing productivity, it is necessary to consider both firm and time effects if one is interested in technology adoption and efficiency. Since it is not possible to estimate individual firm effects for each time period due to degree-of-freedom problems, a trade-off is necessary with respect to where one is employing a flexible specification and where one is more restrictive. While most studies choose to account for variation, either in cross-sectional or temporal dimensions, we are in this paper, by clustering firms together in groups, allowing for variation in both cross-sectional and temporal dimensions. By modifying a shadow cost system, we are able to measure group-specific temporal patterns of technical and allocative efficiency and technological change without restricting the patterns to any parametric form.

The Cost of Financial Frictions for Life Insurers

During the financial crisis, life insurers sold long-term policies at deep discounts relative to actuarial value. The average markup was as low as −19 percent for annuities and −57 percent for life insurance. This extraordinary pricing behavior was due to financial and product market frictions, interacting with statutory reserve regulation that allowed life insurers to record far less than a dollar of reserve per dollar of future insurance liability. We identify the shadow cost of capital through exogenous variation in required reserves across different types of policies. The shadow cost was $0.96 per dollar of statutory capital for the average company in November 2008.

Does the Oil Price Adjust Optimally to Oil Field Discoveries?

The Hotelling rule argues that the price for a non-renewable resource adjusts to the shadow value of the resource, reflecting its remaining availability. This study provides an empirical test of this hypothesis. It investigates whether the price of crude oil does adjust to unexpected news about oil field discoveries. The observed price reaction is compared with a prediction of the price decline as derived from the Hotelling model. This study finds evidence for an adjustment of the price to news about greater resource availability: the price of crude oil declines on average by 0.88% on discovery days. The degree of adjustment to the new level of scarcity is not found to differ significantly from the social optimum. Thus, there is evidence for the existence of a shadow cost component - a necessary pre-requisite for the Hotelling rule to hold.

Financing from Family and Friends

The majority of informal finance, in developed and developing countries, is provided by family and friends. Yet existing models of informal finance better fit “informal moneylenders” insomuch as they fail to match two salient characteristics of family finance: family investors often accept below-market or even negative returns, and despite this, borrowers tend to prefer formal finance. We explain both of these characteristics in a model of external financing that allows for social preferences between relatives or friends. The social preferences make family finance cheap but also create shadow costs that nonetheless discourage its use: Committing family funds to a risky investment crowds out familial transfers in low-consumption states, and undermines limited liability. The very characteristics that generate intra-family insurance thus render family finance a poor source of risk capital. In contexts where contracts must harness social ties to overcome capital constraints, our findings suggest that third-party intermediation and semi-formalization may be crucial for promoting risky investment. This is relevant to the limited success of group-based microfinance in generating entrepreneurial growth, and to the emergence of social lending intermediaries and crowd funding.

A theory of BOT concession contracts

In this paper, we discuss the choice for build–operate-and-transfer (BOT) concessions when governments and firm managers do not share the same information regarding the operation characteristics of a facility. We show that larger shadow costs of public funds and larger information asymmetries entice governments to choose BOT concessions. This result stems from a trade-off between the government's shadow costs of financing the construction and the operation of the facility and the excessive usage price that the consumer may face during the concession period. The incentives to choose BOT concessions increase as a function of informational asymmetries between governments and potential BOT concession holders and with the possibility of transferring the concession project characteristics to the public authority at the termination of the concession.

Measuring dynamic efficiency under uncertainty

In this paper we develop a theoretical model that links dynamic efficiency measurement and optimal investment under uncertainty. It is widely acknowledged that uncertainty has an impact on the optimal factor use of a profit maximizing firm. This is particularly true for the optimal adjustment of the firm’s capital stock. While uncertainty has been considered in the static efficiency measurement literature it has been ignored so far in the context of dynamic efficiency measurement. This paper targets at closing this gap. For that purpose we take up a dynamic efficiency model which embeds a stochastic intertemporal duality model into a shadow cost framework and allows for measuring technical and allocative inefficiency. We derive hypotheses on how uncertainty affects the measurement of efficiency. The factor demand equations, which we derive, may serve as a starting point for an empirical validation of these hypotheses.

How much does an antiinflammatory treatment cost?

NSAIDs are among the most popular drugs in the world for their efficacy in controlling pain and acute and chronic inflammation. The efficacy of these therapies is hampered by their safety profile, in particular regarding the gastroenteric tract. The NSAIDs' side effects may heavily influence the health of the single patient and the economy of the health systems. The pharmacoeconomic evaluation of antinflammatory treatment usually considers, in addition to the drug purchase prize, also the shadow costs. This cost is mainly due to the management and prevention of gastropathy. Coxibs, even if more expensive, may become cost-effective for their better gastronteric safety. As a matter of fact, coxib treatment can be considered equivalent to a treatment with NSAID plus PPI. However, the first requirement of these drugs, that should control pain, must be the efficacy and not only safety. In this case the NNT (Number Needed to Treat) is a good marker of efficacy. To calculate the real cost we must pay to reach the target (pain resolution in one patient), we can multiply NNT for the prize of a specific drug. The total cost will depend on drug prize (the cheaper, the better) and on the efficacy expressed by NNT (the lower, the better). In a recent meta-analysis, the NNT of several antinflammatory drugs has been calculated. When the treatment cost was adjusted for its efficacy (NNT), the difference in favour of NSAIDs became so little to disappear because of the higher safety of coxibs (especially of etoricoxiband the possibility to reach antinflammatory and analgesic doses that are difficult to obtain with NSAIDs. Moreover, if also the cost of gastroprotection is considered, the economic impact of NSAIDs can be much higher. In conclusion the pharmacoeconomic analysis of an antinflammatory therapy cannot be based only on safety issues but also on efficacy evaluation that is the main effect we ask to these drugs.

Economic and environmental effects of decoupled agricultural support in the EU

This article reports findings from a simulation model representing the European farming system disaggregated at different scales. This modeling experiment explores the effects of various decoupling options associated with the 2003 European agreement on gross margins, land use, shadow cost of land, and greenhouse gas emissions. Our results show increases in the farmers' gross margins when decoupled support is maintained equal to the amount of direct aid previously attributed to agricultural production, assuming unchanged prices. Land used for pasture increases at the expense of land used for cereals and protein crops. The extent to which these effects materialize depends on the policy options selected by Member States when implementing the Luxembourg agreement. When they opt for some recoupling of support, adverse net economic impacts occur for producers. Regional differences in impacts are more pronounced than the analysis aggregated at European and national scales suggests. This highlights the need for further work based on geostatistical downscaling.

Margin-based Asset Pricing and Deviations from the Law of One Price

In a model with heterogeneous-risk-aversion agents facing margin constraints, we show how securities' required returns increase in both their betas and their margin requirements. Negative shocks to fundamentals make margin constraints bind, lowering risk-free rates and raising Sharpe ratios of risky securities, especially for high-margin securities. Such a funding-liquidity crisis gives rise to “bases,” that is, price gaps between securities with identical cash-flows but different margins. In the time series, bases depend on the shadow cost of capital, which can be captured through the interest-rate spread between collateralized and uncollateralized loans and, in the cross-section, they depend on relative margins. We test the model empirically using the credit default swap–bond bases and other deviations from the Law of One Price, and use it to evaluate central banks' lending facilities.

Types of liquidity and limits to arbitrage—the case of credit default swaps

AbstractUsing a sample of Credit Default Swap (CDS) prices and corresponding reference corporate bond yield spreads for the period June 2008 to September 2009, we show that funding liquidity (shadow cost of capital for arbitrageurs) as well as asset‐specific liquidity (determinants of margin requirements) explain recent deviations in the arbitrage‐based parity relationship between the CDS prices and bond yield spreads (CDS‐Bond spread basis). Collectively, our analysis corroborates the theory on the determinants of the basis, and suggests that it is important to distinguish between these types of liquidity in determining the circumstances in which relative prices will converge. Median annualized returns for a sample convergence type trading strategy with typical levels of leverage are 80% with a median holding‐period of 127 days, but the path to convergence is not smooth. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark

The impact of investor base on the costs of capital for IPOs

This study examines the Merton (1987) ‘investor recognition’ hypothesis, which postulates that an increase in the total number of investors with prior knowledge of a firm will lower the expected returns of investors by reducing the ‘shadow costs’ arising from the lack of knowledge of a particular security; this will invariably result in an increase in the market value of the firm's shares. We analyze a unique dataset in this study, comprised of information on trading activities relating to 208 IPO firms obtained from the transaction record database of the Taiwan Stock Exchange. In contrast to prior studies, we employ the number of traders as a proxy for investors’ awareness of any given firm and find a discernible decline in the average daily abnormal returns in the second year after listing. Finally, the results confirm the association between investor recognition and the required rate of return.

Estimation of Allocative Inefficiency and Productivity Growth with Dynamic Adjustment Costs

A substantial literature has been generated on the estimation of allocative and technical inefficiency using static production, cost, profit, and distance functions. We develop a dynamic shadow distance system that integrates dynamic adjustment costs into a long-run shadow cost-minimization problem, which allows us to distinguish static allocative distortions from short-run inefficiencies that arise due to period-to-period adjustment costs. The set of estimating equations is comprised of the first-order conditions from the short-run shadow cost-minimization problem for the variable shadow input quantities, a set of Euler equations derived from subsequent shadow cost minimization with respect to the quasi-fixed inputs, and the input distance function, expressed in terms of shadow quantities. This system nests within it the static model with zero adjustment costs. Using panel data on U.S. electric utilities, we contrast the results of static and dynamic shadow distance systems. First, the zero-adjustment-cost restriction is strongly rejected. Second, we find that adjustment costs represent about 0.42% of total cost, and about 1.26% of capital costs. Third, while both models reveal that labor is not utilized efficiently, the dynamic model indicates a longer period of over-use and less variance over time in the degree of inefficiency. With the dynamic model, productivity growth is larger but more stable.

Evaluation of Real Options with Information Costs

This paper presents a simple framework for the analysis, valuation and simulation of several real options in the presence of shadow costs of incomplete information. Information costs can be viewed as sunk costs in the spirit of Merton’s (1987) model of capital market equilibrium with incomplete information. We incorporate these sunk costs in standard discounted cash flow techniques and present the basic concepts of real options. The justification of information costs in real projects is based on the observation that R&D needs to be done before investment decisions. These costs account for all the expenses needed to be informed about an investment opportunity and the management of projects. This analysis extends the models in Bellalah (1999, 2001) for the valuation of real options within information uncertainty. We present valuation procedures and simulations for the values of common real options in the presence of shadow costs of incomplete information.