Time variation paths of factors affecting financial institutions and stock returns

This study finds evidence that three risk factors relating to the stock market, bond market, and real estate market are important in explaining the risk premiums included in financial institutions and bank stock returns. Stock returns for insurance companies are not sensitive to changes in the bond market. The Flexible Least Squares (FLS) results indicate that the stock market factor has the most important and stable impact on risk premiums for financial institutions, banks, and insurance companies. The bond market is the primary source of instability in stock returns for these three groups of stocks. This research adds further support for using market discipline, especially as it relates to equity returns to enhance the prudential regulation of the financial sector.     

The information content of regional employment data for forecasting aggregate conditions

We consider whether disaggregated data enhance the efficiency of aggregate employment forecasts. We find that incorporating spatial interaction into a disaggregated forecasting model lowers the out-of-sample mean squared error from a univariate aggregate model by 70% at a two-year horizon.     

Rational expectations for large CGE models: A practical algorithm and a policy application

We describe a simple iterative method for solving large dynamic CGE models under rational expectations. Details are given for Australia's MONASH model but the approach applies to a wide range of CGE models. The method is automated in the RunMONASH Windows software, putting CGE modelling under rational expectations within the reach of non-specialist modellers. We provide an illustrative application in which MONASH results under rational expectations are compared with results under static expectations. The application and supporting software can be downloaded. Results from the application are interpreted in terms of elementary economic mechanisms.     

Bedrohlicher Wirtschaftspatriotismus

Ohne Zusammenfassung     

Revisiting the corroboration effects of earnings and dividend announcements

Using a unique market setting in Hong Kong, where (i) all firms release earnings and dividend information in the same announcement; (ii) corporate transparency is low; (iii) dividend income is non‐taxable and (iv) corporate ownership is highly concentrated, we re‐examine the corroboration effects of earnings and dividends. We use the control firm approach to avoid the return estimation bias resulting from observation clustering. We also add in variables and use econometric procedure to control for the potential impacts of earnings management, special dividends and heteroskedasticity. Our findings show that there exists a corroboration effect between the jointly announced signals.     

Conflicting threat perceptions at a rural agricultural fair

Tourism is a major industry in Pennsylvania, second only to agriculture. This paper examines their nexus, the rural agricultural fair. The Bloomsburg Fair provides an opportunity to explore risk management for tourism. This event, now in its 150th year, inundates a town of 12,000 with 500,000+ visitors in an 8-day period. Employing a survey of fairgoer behavior, this study explored contrasts between fairgoer and management concerns over a variety of natural and human-induced threats. It also investigated the challenges present in maintaining a quality recreational experience while simultaneously providing adequate fairgoer protection. The findings indicate that fairgoers place greater emphasis on high-probability, low-consequence events while the fair emergency management plan is largely focused on low-probability, high-consequence events such as terrorism. This disconnect suggests that a failure to understand the concerns of the fairgoer or to recognize other threats facing a destination while focusing heavily on low-probability events may create a recreation environment that is relatively less safe overall.     

Two-stage flowshop earliness and tardiness machine scheduling involving a common due window

This paper studies a non-preemptive two-stage flowshop scheduling problem to minimize the earliness and tardiness under the environment of a common due window. The window size and the window location are considered to be given parameters. The just-in-time problem exists naturally and has many practical applications. The problem is shown to be NP-complete in the strong sense. We develop a branch and bound algorithm and a heuristic to solve the problem. We conduct the computational experiments to test the performances of the algorithms. A strong lower bound is derived for the branch and bound algorithm that can efficiently solve 15 jobs problem for about 5 minutes. The heuristic is shown to be efficient and effective, which can solve the problem of 150 jobs for about 20 seconds and provide near-optimal solution. We justify that the heuristic is an excellent solution approach for large problem instances. We also show that four special cases are either polynomial solvable or NP-complete in the ordinary sense.