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Research summary: Combining the concept of resource relatedness with the economic notion of sunk costs, we assess how the potential for resource redeployment affects market entry and exit by multi-business firms. If the performance of a new business falls below expectations, a diversified firm may be able to redeploy its resources back into related businesses. In effect, relatedness reduces the sunk costs associated with a new business, which facilitates exit. This, in turn, has implications for entry: By decreasing the cost of failure, the potential for redeployment justifies the undertaking of riskier entries and greater experimentation. These dynamic benefits of relatedness are distinct from standard notions of \"synergy.\" To show support for this idea, we provide a mathematical model, descriptive data, and company examples. Managerial summary: The ability to redeploy resources inside the firm reduces the cost of entry \"mistakes.\" If a new business turns out to have poor profitability, the ability to redeploy more of its resources back into the firm's other businesses allows recycling of investment and can speed up the retreat. This reduces not only the cost of exit, but also the cost of entry. Managers should therefore be more willing to experiment and take risks in developing businesses that are more related to the firm's existing businesses, whereas if redeployment is likely to be difficult, managers should be cautious about entering. New businesses should be chosen in ways that facilitate redeployment, and managers should consider the implications of redeployment when setting the performance thresholds that justify entry and exit.

This article deals with the identification and estimation of dynamic games when players’ beliefs about other players’ actions are biased, that is, beliefs do not represent the probability distribution of the actual behaviour of other players conditional on the information available. First, we show that an exclusion restriction, typically used to identify empirical games, provides testable non-parametric restrictions of the null hypothesis of equilibrium beliefs in dynamic games with either finite or infinite horizon. We use this result to construct a simple Likelihood Ratio test of equilibrium beliefs. Second, we prove that this exclusion restriction, together with consistent estimates of beliefs at two points in the support of the variable involved in the exclusion restriction, is sufficient for non-parametric point-identification of players’ belief functions as well as useful functions of payoffs. Third, we propose a simple two-step estimation method. We illustrate our model and methods using both Monte Carlo experiments and an empirical application of a dynamic game of store location by retail chains. The key conditions for the identification of beliefs and payoffs in our application are the following: (1) the previous year’s network of stores of the competitor does not have a direct effect on the profit of a firm, but the firm’s own network of stores at previous year does affect its profit because the existence of sunk entry costs and economies of density in these costs; and (2) firms’ beliefs are unbiased in those markets that are close, in a geographic sense, to the opponent’s network of stores, though beliefs are unrestricted, and potentially biased, for unexplored markets which are farther away from the competitors’ network. Our estimates show significant evidence of biased beliefs. Furthermore, imposing the restriction of unbiased beliefs generates a substantial attenuation bias in the estimate of competition effects.

We show that deciding the feasibility of a booking (FB) in the European entry-exit gas market is coNP-hard if a nonlinear potential-based flow model is used. The feasibility of a booking can be characterized by polynomially many load flow scenarios with maximum potential-difference, which are computed by solving nonlinear potential-based flow models. We use this existing characterization of the literature to prove that FB is coNP-hard by reducing Partition to the infeasibility of a booking. We further prove that computing a potential-difference maximizing load flow scenario is NP-hard even if we can determine the flow direction a priori. From the literature, it is known that FB can be decided in polynomial time on trees and a single cycle. Thus, our hardness result draws the first line that separates the easy from the hard variants of FB and finally answers that FB is hard in general.

The European gas market is organized as a so-called entry-exit system with the main goal to decouple transport and trading. To this end, gas traders and the transmission system operator (TSO) sign so-called booking contracts that grant capacity rights to traders to inject or withdraw gas at certain nodes up to this capacity. On a day-ahead basis, traders then nominate the actual amount of gas within the previously booked capacities. By signing a booking contract, the TSO guarantees that all nominations within the booking bounds can be transported through the network. This results in a highly challenging mathematical problem. Using potential-based flows to model stationary gas physics, feasible bookings on passive networks, i.e., networks without controllable elements, have been characterized in the recent literature. In this paper, we consider networks with linearly modeled active elements such as compressors or control valves. Since these active elements allow the TSO to control the gas flow, the single-level approaches for passive networks from the literature are no longer applicable. We thus present a bilevel model to decide the feasibility of bookings in networks with active elements. While this model is well-defined for general active networks, we focus on the class of networks for which active elements do not lie on cycles. This assumption allows us to reformulate the original bilevel model such that the lower-level problem is linear for every given upper-level decision. Consequently, we derive several single-level reformulations for this case. Besides the classic Karush–Kuhn–Tucker reformulation, we obtain three problem-specific optimal-value-function reformulations. The latter also lead to novel characterizations of feasible bookings in networks with active elements that do not lie on cycles. We compare the performance of our methods by a case study based on data from the GasLib.

As a result of its liberalization, the European gas market is organized as an entry-exit system in order to decouple the trading and transport of natural gas. Roughly summarized, the gas market organization consists of four subsequent stages. First, the transmission system operator (TSO) is obliged to allocate so-called maximal technical capacities for the nodes of the network. Second, the TSO and the gas traders sign mid- to long-term capacity-right contracts, where the capacity is bounded above by the allocated technical capacities. These contracts are called bookings. Third, on a day-ahead basis, gas traders can nominate the amount of gas that they inject or withdraw from the network at entry and exit nodes, where the nominated amount is bounded above by the respective booking. Fourth and finally, the TSO has to operate the network such that the nominated amounts of gas can be transported. By signing the booking contract, the TSO guarantees that all possibly resulting nominations can indeed be transported. Consequently, maximal technical capacities have to satisfy that all nominations that comply with these technical capacities can be transported through the network. This leads to a highly challenging mathematical optimization problem. We consider the specific instantiations of this problem in which we assume capacitated linear as well as potential-based flow models. In this contribution, we formally introduce the problem of Computing Technical Capacities (CTC) and prove that it is NP-complete on trees and NP-hard in general. To this end, we first reduce the Subset Sum problem to CTC for the case of capacitated linear flows in trees. Afterward, we extend this result to CTC with potential-based flows and show that this problem is also NP-complete on trees by reducing it to the case of capacitated linear flow. Since the hardness results are obtained for the easiest case, i.e., on tree-shaped networks with capacitated linear as well as potential-based flows, this implies the hardness of CTC for more general graph classes.

Several important breakthroughs within portfolio theory, capital asset pricing and return volatility have been made in the past few decades. Together with the liberalization of international capital asset trading, the global markets are set for an ever-improved efficiency and stability in the near future. Yet, from a small bank client's viewpoint, little has changed during almost five decades within the domain of financial investment support offered by the banks. With the focus of the contemporary research placed on advanced issues within portfolio theory, well-functioning financial markets and the growth impact of the banking sector, it seems as if the decision needs of the small bank client have been largely neglected. The risk measures currently used do not focus on the time of entry in a risky investment. Selecting a wrong entry point for fund investments can usually not be compensated by active governance within a reasonable investment period. In order to utilize the common practices in mutual fund investment services of the banks, a significant amount of knowledge of the underlying mechanisms of asset pricing and the fund dynamics is required from the investor. In the current note, we present a simple statistic, the Growth Potential Index (GPI), which captures the essential characteristics of relevance for determining the time of entry in a mutual fund investment. The mirror image of the GPI, the Decline Potential Index (DPI), is also presented. The DPI may provide valuable decision support information for specifying the time of exit from a long position in the fund. As GPI and DPI are simple to understand and calculate and contain valuable decision support information for a small client, their inclusion in the websites would seem to be a worthwhile effort for any esteemed financial institution offering stock governance services. [PUBLICATION ABSTRACT]

In entry-exit gas markets as they are currently implemented in Europe, network constraints do not affect market interaction beyond the technical capacities determined by the TSO that restrict the quantities individual firms can trade at the market. It is an up to now unanswered question to what extent existing network capacity remains unused in an entry-exit design and to what extent feasible adjustments of the market design could alleviate inefficiencies. In this paper, we offer a four-level modeling framework that is capable of analyzing these issues and provide some first results on the model structure. In order to decouple gas trading from network congestion management, the TSO is required to determine technical capacities and corresponding booking fees at every entry and exit node up front. Firms book those capacities, which gives them the right to charge or discharge an amount of gas at a certain node up to this capacity in every scenario. Beyond these technical capacities and the resulting bookings, gas trade is unaffected by network constraints. The technical capacities have to ensure that transportation of traded quantities is always feasible. We assume that the TSO is regulated and determines technical capacities, fees, and transportation costs under a welfare objective. As a first step we moreover assume perfect competition among gas traders and show that the booking and nomination decisions can be analyzed in a single level. We prove that this aggregated model has a unique solution. We also show that the TSO’s decisions can be subsumed in one level as well. If so, the model boils down to a mixed-integer nonlinear bilevel problem with robust aspects. In addition, we provide a first-best benchmark that allows to assess welfare losses that occur in an entry-exit system. Our approach provides a generic framework to analyze various aspects in the context of semi-liberalized gas markets. Therefore, we finally discuss and provide guidance on how to include several important aspects into the approach, such as network and production capacity investment, uncertain data, market power, and intra-day trading.

The economics of geographical indications (GIs) is assessed within a vertical product differentiation framework that is consistent with the competitive structure of agriculture. It is assumed that certification costs are needed for GIs to serve as (collective) credible quality certification devices, and production of high-quality product is endogenously determined. We find that GIs can support a competitive provision of quality and lead to clear welfare gains, although they fall short of delivering the (constrained) first best. The main beneficiaries are consumers. Producers may also accrue some benefit if production of the high-quality products draws on scarce factors that they own.

Research estimating market supply often focuses on parametric models. In this paper, we study a non-parametric approach to market supply. We characterize the necessary and sufficient conditions of profit maximization for aggregate market behavior when individual firm supply is unobservable and participants on the supply side vary. We also show how the result changes as additional properties are added such as constraints on net outputs, non-negative profits, and increasing production sets.

We study the impact that mimimum quality standards have on industry structure, trade, and welfare when firms can develop their own private standard with a higher quality than the public standard. We introduce vertical differentiation in a firm-based trade model in which firms differ in terms of their productivity and non-cooperatively select the quality and price of their product. A higher public standard increases prices set by constrained and unconstrained firms, but the effect on firms' output is generally ambiguous for both types of firms. The most productive firms raise their private standard and enjoy higher profits at the expense of less productive firms. A public standard can increase welfare, especially when there is a high concentration of low productivity domestic firms because of a better allocation of resources.