House prices, non-fundamental components and interstate spillovers: The Australian experience

Using Australian capital city data from 1984Q3--2008Q2, this paper utilizes a dynamic present value model within a VAR framework to construct time series of house prices depicting what aggregate house prices should be given expectations of future real disposable income - the “fundamental price” - and continues by comparing capital city fundamental prices with actual prices. The extent to which revealed capital city “non-fundamental” components spillover from state to state, as well as their long-term impact is also investigated. Results provide evidence of periods of sustained deviations of house prices from values warranted by income for all state capitals with the greatest deviations arising in the NSW market and starting around 2000. In general NSW is relatively more susceptible to spillovers transmitted from other states while ACT and WA are most isolated from the rest of the country.     

Corporate social responsibility reporting: A comprehensive picture?

This study develops a content analysis framework that provides information on the comprehensiveness of corporate social responsibility (CSR) reporting, an important aspect of social and environmental accountability. Comprehensive reporting, as defined here, requires three types of information for each disclosed CSR item: (i) vision and goals, (ii) management approach, and (iii) performance indicators. The feasibility of the framework to assess the comprehensiveness of CSR reporting is demonstrated using the 2005 annual reports of a sample of publicly traded Belgian companies. The content analysis reveals a low level of comprehensive reporting. This finding complements those of prior studies on the completeness of CSR reporting and, therefore, feeds the debate regarding the extent to which CSR reporting can be considered a mechanism for discharging social and environmental accountability.     

Rethinking the liquidity puzzle: Application of a new measure of the economic money stock

Historically, attempts to solve the liquidity puzzle focus on narrowly defined monetary aggregates, such as non-borrowed reserves, the monetary base, or M1. Many of these efforts fail to find a short-term negative correlation between interest rates and monetary policy innovations. More recent research uses sophisticated macroeconomic and econometric modeling. However, little research has investigated the role measurement error plays in the liquidity puzzle, since in nearly every case, work investigating the liquidity puzzle has used one of the official monetary aggregates, which have been shown to exhibit significant measurement error. In this paper, we examine the role that measurement error plays in the liquidity puzzle by (i) providing a theoretical framework explaining how the official simple-sum methodology can lead to a liquidity puzzle, and (ii) testing for the liquidity effect by estimating an unrestricted VAR.     

Employee emotions during organizational change—Towards a new research agenda

In this research note, we address the role of employee emotions during organizational change processes. While prior studies have examined emotions during a single change, such research analyzes emotions and change as snapshot events. In addition, we lack sufficient knowledge of the role of employee emotions during repeated changes, despite the evidence that organizations increasingly need to adapt to dynamic environments. We address these shortcomings and offer a research agenda on emotions during change, which incorporates the so far neglected view of emotions as processes that unfold during and across organizational changes. Specifically, we illustrate the role of employee emotions during sequential and simultaneous changes and offer six suggestions for future research on emotions in such contexts.     

Mean Reversion in the Short Horizon Returns of UK Portfolios

This paper will show that short horizon stock returns for UK portfolios are more predictable than suggested by sample autocorrelation co-efficients. Four capitalisation based portfolios are constructed for the period 1976–1991. It is shown that the first order autocorrelation coefficient of monthly returns can explain no more than 10% of the variation in monthly portfolio returns. Monthly autocorrelation coefficients assume that each weekly return of the previous month contains the same amount of information. However, this will not be the case if short horizon returns contain predictable components which dissipate rapidly. In this case, the return of the most recent week would say a lot more about the future monthly portfolio return than other weeks. This suggests that when predicting future monthly portfolio returns more weight should be given to the most recent weeks of the previous month, because, the most recent weekly returns provide the most information about the subsequent months' performance. We construct a model which exploits the mean reverting characteristics of monthly portfolio returns. Using this model we forecast future monthly portfolio returns. When compared to forecasts that utilise the autocorrelation statistic the model which exploits the mean reverting characteristics of monthlyportfolio returns can forecast future returns better than the autocorrelation statistic, both in and out of sample.     

Catastrophe Modeling in the Classroom

Catastrophes are by definition rare, which makes it difficult to project future losses using historical loss information. Catastrophe modelers have developed alternative methodologies based on sophisticated techniques that combine physics, meteorology, engineering, statistics, actuarial sciences, and other disciplines to provide estimates of the likelihood of losses from extreme events. This article discusses the basics of catastrophe modeling and describes an approach to implementing a lesson on catastrophe modeling in the insurance curriculum.     

Violation of the iid-normal assumption: Effects on tests of asset-pricing models using Australian data

Financial data are typically not identically, independently and normally distributed (iid-normal). Yet, standard tests of asset-pricing models are based on this assumption, and we have little information on how sensitive the tests are to violations of iid-normality. Recent evidence suggests that test outcomes may be sensitive to these violations. In this paper, we use Australian data to compare the standard test results with those that do not require iid-normality: the GMM-J test and bootstrap-based tests. We find that different tests produce differences in prob values at least as large as those in US studies but that test outcomes are generally robust.     

Short-Term Water Consumption Patterns in Ciudad Juárez, Mexico

Water utility planning efforts are becoming increasingly difficult throughout the world. Located in a semi-arid region, Ciudad Juárez, Mexico is a fast growing municipality that faces both physical infrastructure and water supply constraints. This paper examines monthly water consumption in Ciudad Juárez utilizing a linear transfer function procedure (LTF). Analysis is carried out for per customer usage and for the total number of municipal water system accounts. Models estimated for both series are subjected to a series of simulation benchmark tests. Findings suggest that water consumption in Ciudad Juárez reacts quickly to changes in economic and weather conditions. Out-of-sample simulation results are mixed. Per customer usage forecasts do not fare as well those for total customers relative to random walk benchmarks.Financial support for this research was provided by Southwest Center for Environmental Research Policy Grant W-04-03. Additional financial support was provided by El Paso Electric Company, Wells Fargo Bank of El Paso, and National Science Foundation Grant SES-0332001. Helpful comments and suggestions were provided by Cely Ronquillo, Brian Kelley, and Cesar Olivas. Econometric research assistance was provided by Marycruz De Leon and Irma Torres.     

OPENING RETURNS,NOISE, AND OVERREACTION

In this article a partial‐adjustment model, which shows how equity prices fail to adjust instantaneously to new information, is estimated using a Kalman filter. For the components of the Dow Jones Industrial 30 index I aim to identify whether overreaction or noise is the cause of serial correlation and high volatility associated with opening returns. I find that the tendency for overreaction in opening prices is much stronger than for closing prices; therefore, overreaction rather than noise may account for differences in the return behavior of opening and closing returns. JEL classification: G15     

The President Versus the Senate: Appointments in the American System of Separated Powers and the Federal Reserve

For politicians, appointments are an instrument of policy influence.By installing their representatives in an institution, politicianscan count on policy influence for the duration of their appointees'terms. Given the stakes, the occasional controversy regardingnominees is understandable. On the whole, however, nominationsare not controversial; in fact, Senate confirmation votes areoften unanimous. Nevertheless, the Senate can have substantialinfluence in the appointment process. Using a formal model,this article examines how the president and Senate strategicallybargain with one another within the confines of the FederalReserve appointment process to influence monetary policy. Witha new way to estimate monetary policy preferences, this articleshows empirically that policy influence occurs via appointments.