Bernard J. Morzuch

Teaching with Technology to Engage Students and Enhance Learning

Teaching technology effects on student learning in a large lecture introductory statistics course were tested. Findings show in-class personal response systems and on-line homework/quizzes significantly improve student exam scores. We infer proven small class techniques, participating in class and doing homework via technologies, can restore sound pedagogy in larger classes. The experiment was conducted using just one class, but factors usually unaccounted for in assessment research were controlled, especially the instructor and other materials. The technologies investigated here can provide learning benefits to students even in larger courses often criticized for their inability to provide students quality learning experiences.

International Financial Contagion: Why are Eastern Europe's banks not failing when everybody else's are?

While the Asian financial crisis spread to Russia and Brazil, the transition economies in Central and Eastern Europe (CEECs) are largely unaffected by international financial contagion. This is the more surprising considering that most economies have experienced severe banking sector problems in the past, that large bad loan ratios are still prevalent, that banking regulation and supervision are only slowly improving, and that stabilizing policies have slowly been eliminated. What insulated the CEECs from the recent wave of financial instability? To consider the counterfactual, we first provide a framework that links banking crises to financial deregulation. We then focus on a number of macro- and microeconomic factors, using data compiled from the IMFs International Financial Statistics, from the World Banks World Debt Tables, and from the BISs Consolidated International Banking Statistics. We first compare past experiences in CEECs with those in other emerging economies as a cross-sectional reference point. We then consider whether the situation in CEECs has changed since the last banking sector problems, in order to establish a reference point across time. Our results indicate that the factors leading up to past banking crises are generally different in CEECs from those in other emerging economies. However, in recent years, the characteristics of CEECs have become more similar to those of other emerging economies.

PROBABILITY-DISTRIBUTIONS OF SHORT-TERM ELECTRICITY PEAK LOAD FORECASTS

Abstract Electric companies schedule generator maintenance so as to equalize the risks of capacity shortfall. Distributions of peak loads for given future weeks, months and seasons provide information on the probability that a critical load level will be exceeded in the given time period. Day-to-day fluctuations in peak loads were assumed to be directly caused by weather variables whose distributions vary by week throughout the year. Forecast distributions of weekly peak loads were computed by non-parametric simulation and re-estimation for three regression models: (1) weekly peak loads dependent on time trend and dummy variables, (2) weekly peak loads dependent on socioeconomic and weather variables, and (3) a daily version of (2). Comparisons of actual peak loads against within-sample and post-sample forecast distributions of peak loads showed that (1) and (2) were statistically equivalent but (3) was significantly worse.

Comparing probability forecasts derived from theoretical distributions

Abstract Using the wrong forecast error distribution (typically the normal distribution) has been suggested as one reason why prediction intervals are too narrow. Extreme values are especially likely to be drawn from non-normal distributions. A simple way of selecting the appropriate theoretical distribution is to estimate parameters using historical data, transformed if necessary, to make them stationary. The method is demonstrated using daily electricity peak loads, a set of extreme values. Parameters for four specific distributions, the normal, gamma, Cauchy and Weibull, were estimated and used to make probabilistic forecasts. Although none of the distributions produced well-calibrated post-sample forecasts, the Weibull showed the most promise. Probability forecasts calculated from Chebychevs inequality were the worst-calibrated.

Water and growth: An econometric analysis of climate and policy impacts

Water-related hazards such as floods, droughts, and disease cause damage to an economy through the destruction of physical capital including property and infrastructure, the loss of human capital, and the interruption of economic activities, like trade and education. The question for policy makers is whether the impacts of water-related risk accrue to manifest as a drag on economic growth at a scale suggesting policy intervention. In this study, the average drag on economic growth from water-related hazards faced by society at a global level is estimated. We use panel regressions with various specifications to investigate the relationship between economic growth and hydroclimatic variables at the country-river basin level. In doing so, we make use of surface water runoff variables never used before. The analysis of the climate variables shows that water availability and water hazards have significant effects on economic growth, providing further evidence beyond earlier studies finding that precipitation extremes were at least as important or likely more important than temperature effects. We then incorporate a broad set of variables representing the areas of infrastructure, institutions, and information to identify the characteristics of a region that determine its vulnerability to water-related risks. The results identify water scarcity, governance, and agricultural intensity as the most relevant measures affecting vulnerabilities to climate variability effects.

Statistical analysis of pest-tolerant crop response with reference to corn weed control.

A statistical model of crop-weed competition is developed to permit, but not require, the existence of crop tolerance of weed pests. The popular rectangular hyperbolic model of crop-weed competition is shown to be a special case of the more comprehensive model. Application of the model to corn weed control in Massachusetts demonstrates its practicality and detects evidence of pest-tolerant crop response in this crop-weed system.

How Analysts and Whisperers Use Fundamental Accounting Signals to Make Quarterly EPS Forecasts

We examine the relative efficiency of whisperers’ and analysts’ forecasts of one-quarter-ahead earnings per share (EPS) and identify commonalities and differences in their use of fundamentals to forecast earnings. Results suggest that (a) fundamentals that focus on sales and cost of sales are relevant in explaining one-quarter-ahead EPS changes; (b) whisperers focus on cash flow fundamentals and accrual-based earnings measures in their one-quarter-ahead forecasts, whereas analysts focus on only cash flow fundamentals; and (c) although neither analysts nor whisperers fully incorporate information contained in fundamentals and accrual-based earnings measures in their forecasts, whisperers’ earnings forecast model (forecast errors model) exhibits higher (lower) explanatory power than that of analysts. We also examine robustness of our results by reestimating the models using a two-way random-effects panel data estimator. Although our conclusions remain the same, more statistically significant fundamentals emerge in panel regression results. Evidence presented in this article is consistent with (a) whisperers being different from analysts and (b) whisper forecasts containing unique incremental information beyond that of analysts’ forecasts. Market participants may want to consider using both forecasts when making investment decisions.

Desperate vs. Deadbeat: Can We Quantify the Effect of the Bankruptcy Abuse Prevention and Consumer Protection Act of 2005?

For decades, personal bankruptcies increased in the U.S., either reflecting growing economic distress of families or a declining stigma associated with filing for bankruptcy. In a nod to the latter argument, the U.S. Congress passed the Bankruptcy Abuse Prevention and Consumer Prevention Act of 2005 (BAPCPA), after bankruptcies had grown to record high rates. The assumption was that with the new law many if not most bankruptcies would eventually disappear since they supposedly were the result of a “bankruptcy of convenience”. The U.S. bankruptcy rate fell indeed sharply after the law went into effect, but increased quickly again afterwards. By the end of 2007, the U.S. bankruptcy rate exceeded all levels recorded during the 1980s, and approached the levels prevalent during the early 1990s. But it remains unclear how much of these changes resulted from BAPCPA and what was attributable to other factors. In this Working Paper, the authors establish a benchmark level of the U.S. bankruptcy rates after 2005 that likely would have been observed if the law had not changed. They then compare the actual U.S. bankruptcy rate to the benchmark for 2007 to provide a sense of the effectiveness of BAPCPA.