Dynamic Trade-off Research Articles

Testing Dynamic Tradeoff Theory

We revisit the well-established puzzle that leverage is negatively correlated with measures of profitability. In contrast, we find that at times when firms are at or close to their optimal level of leverage, the cross-sectional correlation between profitability and leverage is positive. At other times, it is negative. These results are consistent with dynamic trade-off models in which infrequent capital structure rebalancing is optimal. The time series of market leverage and profitability in the quarters prior to rebalancing events match the patterns predicted by these models. Our results are not driven by investment layouts, market timing, payout, or mechanical mean reversion of leverage.

Semantics and efficient simulation of accuracy-adaptive TLMs

In contrast to traditional fixed-accuracy transaction level models, the abstraction level of accuracy-adaptive models can be changed during simulation. This enables dynamic trade-off between simulation performance and accuracy. In this article we present a modeling style for systematic construction of accuracy-adaptive models. Additionally, we present the simulation semantics of those models in an abstract and rigorous manner which is independent of implementation language and simulation algorithm. This abstract formulation allows different sequential and parallel simulation schemes to be studied and compared. Based on the presented semantics, we present a high-performance parallel simulation scheme which offers considerable improvement over the performance of existing parallel simulation schemes.

Integration of dynamic reward schedules and speed-accuracy tradeoff in perceptual decision making

Integration of dynamic reward schedules and speed-accuracy tradeoff in perceptual decision making

Buried Silicon-Germanium pMOSFETs: Experimental Analysis in VLSI Logic Circuits Under Aggressive Voltage Scaling

In this paper, the potential of Silicon-Germanium (SiGe) technology for VLSI logic applications is investigated from a circuit perspective for the first time. The study is based on experimental measurements on 45-nm SiGe pMOSFETs with a high- κ/metal gate stack, as well as on 45-nm Si pMOSFETs with identical gate stack for comparison. In the reference SiGe technology, an innovative technological solution is adopted that limits the SiGe material only to the channel region. The resulting SiGe device merges the higher speed of the Ge technology with the lower leakage of the Si technology. Appropriate circuit- and system-level metrics are introduced to identify the advantages offered by SiGe technology in VLSI circuits. Analysis is performed in the context of next-generation VLSI circuits that fully exploit circuit- and system-level techniques to improve the energy efficiency through aggressive voltage scaling, other than low-leakage techniques. Analysis shows that the SiGe technology has more efficient leakage-delay and dynamic energy-delay trade-offs at nominal supply, compared to Si technology. Moreover, it is shown that the traditional analysis performed at nominal supply actually underestimates the benefits of SiGe pMOSFETs, since the speed advantage of SiGe VLSI circuits is further emphasized at low voltages. This demonstrates that SiGe VLSI circuits benefit from aggressive voltage scaling significantly more than Si circuits, thereby making SiGe devices a very promising alternative to Si transistors in next-generation VLSI systems.

Energy-efficient design of wireless sensor networks based on finite energy budget

Wireless sensor networks have the potential to be applied in different applications such as habitat, environmental and industrial monitoring. Each sensor node is responsible for performing sensing, processing and communication functions that depend on a power source, which is typically represented by a battery that has a limited energy capacity. Energy awareness is a very important design consideration for protocols and algorithms in sensor networks. Energy management in WSNs involves not only reducing the energy consumption of a single sensor node but also maximizing the lifetime of the entire network. Furthermore, energy awareness should be incorporated into every stage of the wireless sensor network design and operation with the goal of making dynamic tradeoffs between energy consumption, system performance, and operational fidelity.The design of a WSN should consider the amount of energy each protocol can spend to perform its tasks. Using this idea, we can associate a finite energy budget for each network activity, and ask this activity to achieve its best performance using only its budget. This should be considered a basic principle to design algorithms for networks that are battery powered, especially for wireless sensor networks. In this paper, we present this strategy and show how it can be used to construct the energy map of a wireless sensor network. Our goal is to construct the best energy map using only a defined amount of energy. Simulation results show that we can approach the performance limits using the proposed finite energy budget model.

Corporate Governance and Capital Structure Dynamics

ABSTRACTWe develop a dynamic tradeoff model to examine the importance of manager–shareholder conflicts in capital structure choice. In the model, firms face taxation, refinancing costs, and liquidation costs. Managers own a fraction of the firms’ equity, capture part of the free cash flow to equity as private benefits, and have control over financing decisions. Using data on leverage choices and the model's predictions for different statistical moments of leverage, we find that agency costs of 1.5% of equity value on average are sufficient to resolve the low‐leverage puzzle and to explain the dynamics of leverage ratios. Our estimates also reveal that agency costs vary significantly across firms and correlate with commonly used proxies for corporate governance.

Dimensions of Proximity and Knowledge Bases: Innovation between Spatial and Non-spatial Factors

Mattes J. Dimensions of proximity and knowledge bases: innovation between spatial and non-spatial factors, Regional Studies. Innovations face the challenge of integrating knowledge from heterogeneous sources by establishing an appropriate level of proximity. Proximity is thereby not a purely spatial phenomenon, but also includes organizational, institutional, social and cognitive dimensions. Geographical and social proximity are thereby auxiliary factors, whereas organizational, institutional and cognitive proximity act as critical enablers for learning. These dimensions can be connected to synthetic, analytical and symbolic knowledge bases. They thereby trigger a dynamic trade-off between various forms of proximity, whereby the proximity form varies depending on the underlying knowledge base. Hence, innovation is a complex combination of spatial and non-spatial factors. Mattes J. 空间毗邻性所涉及的层面及知识基础：基于空间与非空间因素的创新，区域研究。创新试图通过构建特定层面的空间毗邻性来应对整合异质性知识这一挑战。毗邻性因此不仅限于单纯的空间现象，同时还涉及到组织、制度、社会以及认知等多层面要素。在学习过程的形成中，地理以及社会毗邻性成为辅助要素，而组织、制度以及认知毗邻性发挥了关键性作用。上述各层面与综合性、分析性以及象征性的知识基础相关联，引发了基于不同知识基础的多种形式的毗邻性之间多样化的相互权衡过程。因此，创新是一个复杂的空间与非空间要素的综合体。 毗邻性 知识基础 学习 学习区域 地理毗邻性 Mattes J. Les dimensions des bases de proximité et de connaissance: l'innovation entre des facteurs géographiques et non-géographiques, Regional Studies. Les innovations font face au défi de l'intégration de la connaissance provenant des sources hétérogènes en établissant un niveau de proximité approprié. Il s'ensuit, alors, que la proximité n'est pas un phénomène purement géographique mais comprend également des dimensions organisationnelle, institutionnelle, sociale et cognitive. Les proximités géographique et sociale sont, donc, des facteurs auxiliaires, tandis que les proximités organisationnelle, institutionnelle et cognitive constituent des facteurs clés qui favorisent la connaissance. On peut lier ces dimensions à des bases de connaissance synthétique, analytique et symbolique. De cette façon, elles déclenchent un compromis dynamique entre divers types de proximité selon lesquels la proximité varie en fonction de la base de connaissance sous-jacente. Donc, l'innovation s'avère une combinaison complexe de facteurs géographiques et non-géographiques. Proximité Base de connaissance Apprentissage Régions d'apprentissage Proximité géographique Mattes J. Dimensionen von Nähe und Wissensbasen. Innovation zwischen räumlichen und nicht-räumlichen Faktoren, Regional Studies. Bei Innovationen ergibt sich das Problem, dass Wissen aus heterogenen Quellen durch Festlegung eines angemessenen Maßes an Nähe integriert werden muss. Nähe ist somit kein rein räumliches Phänomen, sondern umfasst auch organisationelle, institutionelle, soziale und kognitive Dimensionen. Geografische und soziale Nähe sind hierbei Hilfsfaktoren, während die organisationelle, institutionelle und kognitive Nähe als zentrale Faktoren zur Ermöglichung von Lernen wirken. Diese Dimensionen lassen sich mit synthetischen, analytischen und symbolischen Wissensbasen verknüpfen. Auf diese Weise lösen sie einen dynamischen Ausgleich zwischen verschiedenen Formen der Nähe aus, bei dem die Form der Nähe je nach der zugrundeliegenden Wissensbasis unterschiedlich ausfällt. Innovation ist also eine komplexe Kombination aus räumlichen und nicht-räumlichen Faktoren. Nähe Wissensbasis Lernen Lernregionen Geografische Nähe Mattes J. Dimensiones de proximidad y de las bases de conocimiento: innovación entre factores espaciales y no espaciales, Regional Studies. En el campo de las innovaciones surge el problema de integrar el conocimiento de fuentes heterogéneas estableciendo un nivel apropiado de proximidad. La proximidad no es, por tanto, un fenómeno puramente espacial sino que también incluye dimensiones organizativas, institucionales, sociales y cognitivas. Por consiguiente, las proximidades geográfica y social son factores auxiliares, mientras que las proximidades organizativa, institucional y cognitiva actúan como activadores fundamentales del aprendizaje. Estas dimensiones pueden conectarse a bases de conocimiento sintético, analítico y simbólico. En este sentido activan un intercambio dinámico entre las diferentes formas de proximidad de modo que la forma de proximidad varía en función de la base de conocimiento subyacente. Por ende, la innovación es una combinación compleja de factores espaciales y no espaciales. Proximidad Base de conocimiento Aprendizaje Regiones de aprendizaje Proximidad geográfica

Asymmetric capital structure adjustments: New evidence from dynamic panel threshold models

We develop a dynamic panel threshold model of capital structure to test the dynamic trade-off theory, allowing for asymmetries in firms' adjustments toward target leverage. Our novel estimation approach is able to consistently estimate heterogeneous speeds of adjustment in different regimes as well as to properly test for the threshold effect. We consider several proxies for adjustment costs that affect the asymmetries in capital structure adjustments and find evidence that firms with large financing imbalance (or a deficit), large investment or low earnings volatility adjust faster than those with the opposite characteristics. Firms not only adjust at different rates but also seem to adjust toward heterogeneous leverage targets. Moreover, we document a consistent pattern that firms undertaking quick adjustment are over-levered with a financing deficit and rely heavily on equity issues to make such adjustment.

As Certain as Debt and Taxes: Estimating the Tax Sensitivity of Leverage from Exogenous State Tax Changes

Using staggered corporate income tax changes across U.S. states, we show that taxes have a first-order effect on capital structure. Firms increase leverage by around 40 basis points for every percentage-point tax increase. Consistent with dynamic tradeoff theory, the effect is asymmetric: leverage does not respond to tax cuts. This is true even within firm: tax increases that are later reversed nonetheless lead to permanent leverage increases. The treatment effects are heterogeneous and confirm the tax channel: tax sensitivity is greater among profitable and investment-grade firms which respectively have a greater marginal tax benefit and lower marginal cost of issuing debt.

Industrial franchising strategies: some transactional concerns and managerial propositions

Even though industrial franchising agreements are common in the licensing world, the way patent and brand licensing interact together in such contracts is an issue that remains unexplored. This article aims to fill this gap by providing a simple model of brand licensing that enables managers to ground their decisions on this topic. More precisely I developed in this article a model that sheds light on the dynamic tradeoffs that arise when the license includes a trademark transfer. I first showed that the difference between the temporal horizons of the partners leads the licensee to under invest into the brand goodwill, in a way that increases as the term of the contract becomes closer. I then show how this problem can be solved at least partially by properly shaping the agreement. I finally used a licensing database of 553 contracts from the French Institute of Intellectual Property in order to see how the monitoring clauses, the resources transferred and the contract duration interact.

Asymmetric Capital Structure Adjustments: New Evidence from Dynamic Panel Threshold Models

We develop a dynamic panel threshold model of capital structure to test the dynamic trade-off theory, allowing for asymmetries in firms’ adjustments toward target leverage. Our novel estimation approach is able to consistently estimate heterogeneous speeds of adjustment in different regimes as well as to properly test for the threshold effect. We consider several proxies for adjustment costs that affect the asymmetries in capital structure adjustments and find evidence that firms with large financing imbalance (or a deficit), large investment or low earnings volatility adjust faster than those with the opposite characteristics. Firms not only adjust at different rates but also seem to adjust toward heterogeneous leverage targets. Moreover, we document a consistent pattern that firms undertaking quick adjustment are over-levered with a financing deficit and rely heavily on equity issues to make such adjustment.

On the Determinants of Firm Leverage: A Structural Dynamic Estimation

I provide further evidence on the determinants of corporate capital structure by estimating a dynamic trade-off model of the firm that includes investment, leverage, and payout decisions. The structural model generates a leverage ratio that oscillates around a long-run, time-invariant level and consistently reproduces the convergence and stability of leverage reported by Lemmon, Roberts, and Zender (2008). The dynamic model sheds light on the role played by the primitive characteristics of the firm (e.g., production technology) to explain the cross-sectional variation in capital structure. I use Efficient Method of Moments (EMM) to recover the structural parameters.

Ushering Buyers into Electronic Channels: An Empirical Analysis

Despite many success stories, B2B e-commerce penetration remains low. Many firms introduce electronic channels in addition to their traditional sales channels, but find that buyer usage of the e-channel over time does not keep up with initial expectations. Firms must understand the underlying factors that drive channel usage and how these factors change over time and across buyers. Using panel data pertaining to the purchase histories of 683 buyers over a 43-month period, we estimate a dynamic discrete choice model in a B2B setting that (i) recognizes how price, channel inertia, and inventory change over time, (ii) allows buyers to dynamically trade off these factors when making e-channel adoption decisions, and (iii) takes into account buyer heterogeneity. We find that channel usage is both heterogeneous and dynamic across buyers. Our findings reveal the dynamic tradeoff between channel inertia and the adverse price effect, which interact in opposing directions as the e-channel grows more popular over time: price increases resulting from more bids deter buyers, whereas channel inertia built from sampling experience helps retain repeat buyers for the new channel. Second, we find that the buyers’ size and diversity influence purchase decisions, and the e-channel appears more attractive to small and/or diversified buyers. Based on our analysis, we postulate that the seller’s allocation decisions of products across channels, if not aligned with buyer behavior, can alienate some buyers. Based on the parameter estimates from the buyer response model, we propose an improved channel allocation that enables firms to selectively attract more buyers to the e-channel and improve revenues. Channel acceptance increases as a result of smart allocation when firms understand and account for individual buyers’ channel usage behavior.

Ushering Buyers into Electronic Channels: An Empirical Analysis

Despite many success stories, B2B e-commerce penetration remains low. Many firms introduce electronic channels in addition to their traditional sales channels but find that buyer usage of the e-channel over time does not keep up with initial expectations. Firms must understand the underlying factors that drive channel usage and how these factors change over time and across buyers. Using panel data pertaining to the purchase histories of 683 buyers over a 43-month period, we estimate a dynamic discrete choice model in a B2B setting that (i) recognizes how price, channel inertia, and inventory change over time; (ii) allows buyers to dynamically trade off these factors when making e-channel adoption decisions; and (iii) takes into account buyer heterogeneity. We find that channel usage is both heterogeneous and dynamic across buyers. Our findings reveal the dynamic tradeoff between channel inertia and the adverse price effect, which interact in opposing directions as the e-channel grows more popular over time: price increases resulting from more bids deter buyers, whereas channel inertia built from sampling experience helps retain repeat buyers for the new channel. Second, we find that the buyers' size and diversity influence purchase decisions, and the e-channel appears more attractive to small and/or diversified buyers. Based on our analysis, we postulate that the seller's allocation decisions of products across channels, if not aligned with buyer behavior, can alienate some buyers. Based on the parameter estimates from the buyer response model, we propose an improved channel allocation that enables firms to selectively attract more buyers to the e-channel and improve revenues. Channel acceptance increases as a result of smart allocation when firms understand and account for individual buyers' channel usage behavior.

Leverage and pricing of debt in LBOs

We show that the structure and pricing of debt in LBOs mostly depend on a single characteristic of the target firm, pre-LBO profitability. We find a positive relationship between pre-LBO profitability and deal leverage that is consistent with a dynamic trade-off theory of capital structure in the presence of adjustment costs. We argue that the wide range of debt tranches used in LBO financing can be folded into two main categories, senior and junior debt, where the pricing of senior and junior debt depends on their relative use and on bankruptcy risk. Our evidence also suggests that senior lenders oversupply cheap credit during hot buyout markets.

Capital Structure Deviation and Speed of Adjustment

As a firm deviates from its target leverage, marginal bankruptcy costs change at a faster speed than marginal tax shield. This renders the speed of adjustment (SOA) of capital structure an increasing function of the starting deviation from the target. Adopting a bootstrapping-based estimation, we confirm the existence of such heterogeneity in SOA that is statistically significant and economically nontrivial. Typically, if Firm A is one standard deviation (about 17%) and Firm B is two standard deviations away from their leverage targets, then B’s SOA is 41% greater than that of A, and the half life of B’s leverage deviation is shorter by 2.5 years. The findings are consistent with the dynamic tradeoff theory in the presence of reasonable adjustment costs.

Institutional determinants of capital structure adjustment speeds

Many authors relate a firm's performance to legal and political features and the regulatory environment in which it operates. This article compares firms' capital structure adjustments across countries and investigates whether institutional differences help explain the variance in estimated adjustment speeds. We find that legal and financial traditions significantly correlate with firm adjustment speeds. More narrowly, institutional features also relate to adjustment speeds, consistent with the hypothesis that better institutions lower the transaction costs associated with adjusting a firm's leverage. Such associations between institutional arrangements and leverage adjustment speeds are consistent with the dynamic trade-off theory of capital structure choice.

Capital structure and financing decision - Evidence from the four Asian Tigers and Japan

This paper examines the relative importance of the Modigliani-Miller theorem, the trade-off theory, the pecking order theory and the market timing theory in the financing decisions of the firms for the Four Asian Tigers (Hong Kong, Korea, Singapore and Taiwan) and Japan. According to our findings, although several elements impact on capital structure temporarily, firms from all countries rebalance their leverage following equity issuances. The results are more in line with the dynamic trade-off theory rather than the equity market timing or pecking order hypothesis of capital structure. In other words, firms have their target capital structures, determined by the marginal benefits of debt and costs associated with debt. Therefore, this implies that firms adjust their capital structure in response to the temporary shocks that cause their leverage to deviate from the target in the Four Asian Tigers and Japan. This outcome would be consistent with the previous empirical evidences of the US and the other of the Group of Seven (G7). Key words: Capital structure, trade-off theory, market timing hypothesis, pecking order theory.

Testing Dynamic Tradeoff Theory: Evidence from Rebalancing Points.

We develop a simple methodology to identify firms that are at or close to their optimal capital structure. Using this methodology we present cross-sectional and time series evidence in favor of dynamic tradeoff theory. In particular, at rebalancing points the relationship between profitability and leverage is positive, consistent with theoretical predictions. Also, the time series of market leverage, profitability, and equity payouts in the years prior to rebalancing events match the patterns obtained from simulated data. Our methodology is robust to recent critiques of empirical tests of dynamic tradeoff theory.

LEDs IN LIGHTING WITH TAILORED COLOR QUALITY

Polychromatic lighting sources that are composed of at least four different colored light-emitting diodes (LEDs) offer versatility in color quality of illumination. In this paper, different methods of assessment of color quality of white light are discussed and a general approach to the solution of the color-mixing problem by means of optimization in respect of several color rendition characteristics is considered. Spectral power distributions of model tetrachromatic solid-state sources obtained by maximizing various figures of merit, such as color rendering index, gamut area index, color quality scale, and indices based on the statistical analysis of the just perceivable chromaticity differences for a large number of test color samples, are demonstrated. A concept tetrachromatic lighting source that can be operated within a dynamical trade-off between two opposing color rendition characteristics, the ability to render colors with high fidelity and the ability to render colors with increased chromatic saturation, is introduced. Such "smart" sources with tailored color quality can meet individual needs and preferences of color vision and find numerous applications in lighting.