Ethical issues in corporate speechwriting

Executive speechwriting is a common practice in most large organizations. This activity, however, raises a number of ethical questions about responsibility and about audience deception. This essay explores the ethics of speechwriting from three perspectives and offers some general guidelines for maintaining ethical standards when using speechwriters.Matthew W. Seeger is an Associate Professor of Speech Communication and Director of Graduate Studies at Wayne State University in Detroit. His major research interests lie in the area of organizational communication including crisis communication, leadership and ethics. His article Free Speech and Institutional Constraint was published in theFree Speech Yearbook and won the 1986 Wichelns Award for Research in Free Speech and Law.     

How fast to run in the Red Queen race?

This paper creates a market ecosystem, via an agent‐based model, that combines the dynamic features of the Red Queen effect with well‐accepted business world performance indicators. Essentially, firms are tasked with remaining ‘alive’ by adapting to their environment through implementing a competitive response of innovating or imitating. An analysis of the firms’ behaviours delivers a deep understanding of the drivers of innovative behaviour within the economy. The key findings of the paper are (1) that concentrated markets are not entirely detrimental to innovative behaviour, with the blend of firm type being a more important consideration, and (2) that the rate at which an innovation impairs existing markets affects the activity levels of the firms within the population. The model's results are validated against a matching study based on real‐world data.     

Toward an ontology‐driven blockchain design for supply‐chain provenance

An interesting research problem in our age of Big Data is that of determining provenance. Granular evaluation of provenance of physical goods (e.g., tracking ingredients of a pharmaceutical or demonstrating authenticity of luxury goods) has often not been possible with today's items that are produced and transported in complex, interorganizational, often internationally spanning supply chains. Recent adoptions of the Internet of Things and blockchain technologies give promise at better supply‐chain provenance. We are particularly interested in the blockchain, as many favored use cases of blockchain are for provenance tracking. We are also interested in applying ontologies, as there has been some work done on knowledge provenance, traceability, and food provenance using ontologies. In this paper, we make a case for why ontologies can contribute to blockchain design. To support this case, we analyze a traceability ontology and translate some of its representations to smart contracts that execute a provenance trace and enforce traceability constraints on the Ethereum blockchain platform.     

Tempered stable structural model in pricing credit spread and credit default swap

In this paper, we explore the features of a structural credit risk model wherein the firm value is driven by normal tempered stable (NTS) process belonging to the larger class of Lévy processes. For the purpose of comparability, the calibration to the term structure of a corporate bond credit spread is conducted under both NTS structural model and Merton structural model. We find that NTS structural model provides better fit for all credit ratings than Merton structural model. However, it is noticed that probabilities of default derived from the calibration of the term structure of a bond credit spread might be overestimated since the bond credit spread could contain non-default components such as illiquidity risk or asymmetric tax treatment. Hence, considering CDS spread as a reflection of the pure credit risk for the reference entity, we calibrate it in order to obtain more reasonable probability of default and obtain valid results in calibration of the market CDS spread with NTS structural model.     

The importance of informal professional networks in developing a proactive organizational culture: a public value perspective

Public value theory was used by the authors to investigate informal professional networks, perceived discretionary power, and the organizational culture that forms in physical asset management organizations. The results, from a structural equation model, indicated that informal professional networks are positively associated with higher discretionary power and a proactive asset maintenance organizational culture. In the absence of public managers promoting public value, professionals use their informal networks as a source of power to be proactive and contribute to asset reliability and public safety (public value).     

Job hopping, earnings dynamics, and industrial agglomeration in the software publishing industry

This paper investigates the implications of industrial clustering for labor mobility and earnings dynamics in one large and increasingly important high-technology sector. Taking advantage of longitudinal employee-employer matched data, I exploit establishment-level variation in agglomeration to explore how clustering in the software publishing industry affects labor market outcomes. The results show that clustering makes it easier for workers to job hop within the sector. Higher earnings levels in more agglomerated areas are partly attributable to sorting across locations among workers and firms in the industry on the basis of observable and unobservable characteristics. Controlling for this heterogeneity, workers in clusters have relatively steep earnings-tenure profiles, accepting lower wages early in their careers in exchange for stronger earnings growth and higher wages later. These findings are consistent with theoretical models in which agglomeration improves labor market coordination and facilitates greater learning and human capital formation.     

Estimation of Markov regime-switching regression models with endogenous switching

Following Hamilton [1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57, 357–384], estimation of Markov regime-switching regressions typically relies on the assumption that the latent state variable controlling regime change is exogenous. We relax this assumption and develop a parsimonious model of endogenous Markov regime-switching. Inference via maximum likelihood estimation is possible with relatively minor modifications to existing recursive filters. The model nests the exogenous switching model, yielding straightforward tests for endogeneity. In Monte Carlo experiments, maximum likelihood estimates of the endogenous switching model parameters were quite accurate, even in the presence of certain model misspecifications. As an application, we extend the volatility feedback model of equity returns given in Turner et al. [1989. A Markov model of heteroskedasticity, risk, and learning in the stock market. Journal of Financial Economics 25, 3–22] to allow for endogenous switching.     

Sovereign rating changes—Do they provide new information for stock markets?

The purpose of this paper is to examine the impact of sovereign rating changes on international financial markets using a comprehensive database of 42 countries, covering the major regions in the world over the period 1995–2003. In general, we find that rating agencies provide stock and foreign exchange markets with new tradable information. Specifically, rating upgrades (downgrades) significantly increased (decreased) USD denominated stock market returns and decreased (increased) volatility. Whereas the mean response is contributed evenly by the local currency stock returns and exchange rate changes that make up the USD returns, only the foreign exchange volatility was behind the USD denominated return volatility. In addition, we find significant asymmetric effects of rating announcements. The market responses – both return and volatility – are more pronounced in the cases of downgrades, foreign currency debt, emerging market debt, and during crisis periods. This study has important policy implications for international investors’ asset allocation plans and for regulatory bodies such as the Basel Committee who increasingly rely upon Moody's, Standard and Poor's and Fitch's ratings for their regulatory regimes.     

Financial market models with Lévy processes and time-varying volatility

Asset management and pricing models require the proper modeling of the return distribution of financial assets. While the return distribution used in the traditional theories of asset pricing and portfolio selection is the normal distribution, numerous studies that have investigated the empirical behavior of asset returns in financial markets throughout the world reject the hypothesis that asset return distributions are normally distribution. Alternative models for describing return distributions have been proposed since the 1960s, with the strongest empirical and theoretical support being provided for the family of stable distributions (with the normal distribution being a special case of this distribution). Since the turn of the century, specific forms of the stable distribution have been proposed and tested that better fit the observed behavior of historical return distributions. More specifically, subclasses of the tempered stable distribution have been proposed. In this paper, we propose one such subclass of the tempered stable distribution which we refer to as the “KR distribution”. We empirically test this distribution as well as two other recently proposed subclasses of the tempered stable distribution: the Carr–Geman–Madan–Yor (CGMY) distribution and the modified tempered stable (MTS) distribution. The advantage of the KR distribution over the other two distributions is that it has more flexible tail parameters. For these three subclasses of the tempered stable distribution, which are infinitely divisible and have exponential moments for some neighborhood of zero, we generate the exponential Lévy market models induced from them. We then construct a new GARCH model with the infinitely divisible distributed innovation and three subclasses of that GARCH model that incorporates three observed properties of asset returns: volatility clustering, fat tails, and skewness. We formulate the algorithm to find the risk-neutral return processes for those GARCH models using the “change of measure” for the tempered stable distributions. To compare the performance of those exponential Lévy models and the GARCH models, we report the results of the parameters estimated for the S&P 500 index and investigate the out-of-sample forecasting performance for those GARCH models for the S&P 500 option prices.     

A theory of factor allocation and plant size

This article develops a theory of how capital, skilled labor, and unskilled labor interact at the plant level. The theory has implications for the relationship between factor allocation and plant size and the effects of trade and growth on the skill premium. The theory is consistent with certain facts about factor allocation and factor price changes in the 19th and 20th centuries.