Inflation and the Exchange Rate: The Role of Aggregate Demand Elasticity

This paper examines the effect of aggregate demand elasticity on the exchange rate when inflation occurs. We discover that both the source of the inflation, whether demand-pull or cost-push, and the elasticity of aggregate demand with respect to the price level, are of consequence for the exchange rate. We obtain two primary conclusions. First, the effect on the exchange rate of cost push inflation is ambiguous and is partially determined by the price level elasticity of aggregate demand. In particular, and assuming that the two examined countries have equivalent aggregate supply elasticities, we conclude that the nation with the less elastic aggregate demand function will see its currency appreciate relative to the other. Second, demand-pull inflation results in an unambiguous increase in the exchange rate but the size of that increase is partially a function of aggregate demand elasticity. Assuming again that two countries have equivalent aggregate supply elasticities, that country with the more elastic aggregate demand will experience currency appreciation.     

The impact of vertical integration on inventory turnover and operating performance

This paper investigates how vertical integration may influence inventory turnover and firm operating performance. A causal model is developed to investigate the effects of vertical integration on three types of inventory, namely raw materials inventory (RMI), work in progress inventory (WIPI) and finished goods inventory (FGI). The model tests the interactions between inventory types and the consequences of inventory turnover performance on various aspects of firm performance including costs and profitability. In particular, path analysis supports systematic differences with respect to how vertical integration affects RMI, WIPI and FGI. Vertical integration has a positive effect on RMI and FGI turnover but no significant effect on WIPI turnover. FGI contributes to a reduction in supporting processes costs which causes an improvement in return on sales (ROSs). Vertical integration impacts ROS directly.     

Optimal constrained investment in the Cramer-Lundberg model

We consider an insurance company whose surplus is represented by the classical Cramer-Lundberg process. The company can invest its surplus in a risk-free asset and in a risky asset, governed by the Black-Scholes equation. There is a constraint that the insurance company can only invest in the risky asset at a limited leveraging level; more precisely, when purchasing, the ratio of the investment amount in the risky asset to the surplus level is no more than a; and when short-selling, the proportion of the proceeds from the short-selling to the surplus level is no more than b. The objective is to find an optimal investment policy that minimizes the probability of ruin. The minimal ruin probability as a function of the initial surplus is characterized by a classical solution to the corresponding Hamilton-Jacobi-Bellman (HJB) equation. We study the optimal control policy and its properties. The interrelation between the parameters of the model plays a crucial role in the qualitative behavior of the optimal policy. For example, for some ratios between a and b, quite unusual and at first ostensibly counterintuitive policies may appear, like short-selling a stock with a higher rate of return to earn lower interest, or borrowing at a higher rate to invest in a stock with lower rate of return. This is in sharp contrast with the unrestricted case, first studied in Hipp and Plum, or with the case of no short-selling and no borrowing studied in Azcue and Muler.     

Public–Private Sector Wage Gap in Australia: Variation along the Distribution

Previous research on public–private wage differentials in Australia has focused on the mean of the conditional wage distribution. Using six waves of the Household, Income and Labour Dynamics in Australia survey, this study employs quantile regressions to examine whether the sectoral wage effect varies along the wage distribution. For females, public sector wage premiums are relatively stable for almost the entire distribution. For males, they decrease monotonically and are negative for the top half of the distribution. The decomposition results show that the observed differences in individuals and job characteristics explain a substantial proportion of the sectoral wage gap.     

Cannabis use and mental health problems

This paper investigates whether cannabis use leads to worse mental health. To do so, we account for common unobserved factors affecting mental health and cannabis consumption by modeling mental health jointly with the dynamics of cannabis use. Our main finding is that using cannabis increases the likelihood of mental health problems, with current use having a larger effect than past use. The estimates suggest a dose–response relationship between the frequency of recent cannabis use and the probability of currently experiencing a mental health problem. Copyright © 2010 John Wiley & Sons, Ltd.     

Understanding the police response to fraud: the challenges in configuring a response to a low-priority crime on the rise

ABSTRACT

Previous research has demonstrated the comparative lack of priority fraud receives from government and law enforcement in the UK compared to other serious offences, as well as shortcomings in the overall approach to investigation. This paper examines the current state of affairs in the light of changes aimed at addressing these limitations. It incorporates findings from a national survey of police forces, as well as a local survey of police personnel in three forces supplemented by interviews. The findings suggest that the situation has become more complicated. Many police officers interviewed did not feel that the police response in their own area was effective, and that their colleagues often lacked the appropriate skill sets needed. Moreover, forces were not confident they were recruiting the right people to tackle fraud. The paper has important lessons for policing internationally.     

The relationship between legitimacy,reputation, sustainability and branding for companies and their supply chains

This paper aims at filling a gap that we perceive to exist in the scientific literature as to legitimacy, reputation and sustainability and their interrelationship to corporate and supply chain branding. A series of innovative theoretical frameworks are provided interrelating companies and their value (supply) chains with legitimacy, reputation, and branding which are essential conditions to achieve sustainability and competitive advantage based on dyadic and social context consonance to the benefit of society and all stakeholders involved. An urgently required better understanding of the concepts and their interrelations is enhanced by a synthesized explanatory basis entailing an eclectic mosaic of interdisciplinary theories (institutionalist, neo-institutionalist theories, the viable system approach, isomorphism and identity) to improve corporate and supply chain performance. To better inform managerial practice the theoretical considerations are spiced with case studies among which especially the currently debated supply chain case of the European horse meat scandal is illuminated suggesting concrete managerial cross-functional implications in the food industry. The paper culminates in the call for a newly to-be-established marketing stream we call ‘Sustainable and Curative Marketing’.     

Computer assisted text analysis in the social sciences

We use the term “Computer Assisted Text Analysis” in a broad sense to refer to a range of current techniques from quantitative social science and content analysis to ‘data mining’ and ‘text classification’, including the analysis of open-ended survey questions, transcribed interviews and speeches, wherever, in fact, the researcher is confronted with data in the form of natural language texts of social scientific interest. These methods are often used in exploratory data analysis, but can also be applied systematically with moderate statistical rigour in the development and testing of hypotheses at various theoretical levels, ranging from the statistics of word usage to changes within or between discourses over time. The general approach is in the tradition of content analysis, by which words which occur together in relatively close proximity in the same context are interpreted as relating to a common theme or concept in the discourse studied. We review a comprehensive set of tools to identify and visualize structures of co-occurrence of words and concepts both within, and in comparing, a number of texts. These produce results not essentially different from those reached by representing word co-occurrences in terms of network analysis or neural network programming using schematic linguistic templates of various kinds. A comparison of the relational data analysis vs. a dictionary-based MDS approach shows that these provide very close if not identical results, despite the fact that the underlying assumptions are frequently represented as different theoretical approaches.