32,818 research outputs found
Would Mandatory Attendance Be Effective for Economics Classes?
Romer (1993) suggests that universities should undertake experiments that would test the value of mandatory attendance for economics courses. He presents evidence showing that those who attended his classes received higher grades on his exams and concluded that ^San important part of the relationship [to the course grade] reflects a genuine effect of attendance.^T This conclusion is likely to be welcomed by some economics professors. In this note, I address two issues. First, what does prior research imply about a relationship between attendance and learning? Second, does Romer^Rs own evidence support his conclusion that mandatory attendance is beneficial?learning, universities, business schools
Decomposition by Causal Forces: A Procedure for Forecasting Complex Time Series
Causal forces are a way of summarizing forecasters expectations about what will happen to a time series in the future. Contrary to the common assumption for extrapolation, time series are not always subject to consistent forces that point in the same direction. Some are affected by conflicting causal forces; we refer to these as complex times series. It would seem that forecasting these times series would be easier if one could decompose the series to eliminate the effects of the conflicts. Given forecasts subject to high uncertainty, we hypothesized that a time series could be effectively decomposed under two conditions: 1) if domain knowledge can be used to structure the problem so that causal forces are consistent for two or more component series, and 2) when it is possible to obtain relatively accurate forecasts for each component. Forecast accuracy for the components can be assessed by testing how well they can be forecast on early hold-out data. When such data are not available, historical variability may be an adequate substitute. We tested decomposition by causal forces on 12 complex annual time series for automobile accidents, airline accidents, personal computer sales, airline revenues, and cigarette production. The length of these series ranged from 16 years for airline revenues to 56 years for highway safety data. We made forecasts for one to ten horizons, obtaining 800 forecasts through successive updating. For nine series in which the conditions were completely or partially met, the forecast error (MdAPE) was reduced by more than half. For three series in which the conditions were not met, decomposition by causal forces had little effect on accuracy.airline accidents, extrapolation, Holt s exponential smoothing, model formulation, personal computers, revenue forecasting, transportation safety.
The Devil s Advocate Responds to an MBA Student s Claim that Research Harms Learning
Snapshots from Hell describes a first-year student s experience in the Stanford Master of Business Administration (MBA) program in 1989. Peter Robinson, formerly a speech writer for President Reagan, tells about his experiences in applying to business schools, living with other MBA students, taking courses, interacting with faculty, and interviewing for summer jobs. The experience was a hellish one for Robinson for a number of reasons. He found the transition from the White House to business school wrenching. He was, at first, quite lonely. And he was a poet (weak mathematically) which made him feel vulnerable in the quantitative courses. But Robinson also lays a degree of the blame for the uglier aspects of his business school experience on Stanford Business School and, in particular, on the faculty. Much of the teaching was mediocre, Robinson says, and some of it was appalling. The reason? Robinson suggests that the faculty was paying too much attention to research.learning, universities, MBA
The Case for Minimum Teaching Standards
We all share the desire to improve the learning environment at Wharton and to have students who will be satisfied with this environment. While most of the Wharton Teaching Committee's recommendations are consistent with these aims, I believe that recommendation #1, to 'Establish Minimum Standards for Acceptable Teaching,'' will be detrimental to learning. I therefore recommend that we reject proposal #1. This letter describes how I reached this conclusion, suggests alternatives, and recommends a process for resolving tie issues.learning, universities, business schools
Damped Seasonality Factors: Introduction
Previous research has shown that seasonal factors provide one of the most important ways to improve forecast accuracy. For example, in forecasts over an 18-month horizon for 68 monthly economic series from the M-Competition, Makridakis et al. (1984, Table 14) found that seasonal adjustments reduced the MAPE from 23.0 to 17.7 percent, an error reduction of 23%. On the other hand, research has also shown that seasonal factors sometimes increase forecast errors (e.g., Nelson, 1972). So, when forecasting with a data series measured in intervals that represent part of a year, should one use seasonal factors or not? Statistical tests have been devised to answer this question, and they have been quite useful. However, some people might say that the question is not fair. Why does it have to be either/or? Shouldn^Rt the question be ^Sto what extent should seasonal factors be used for a given series?^Tseasonal factors, forecast, accuracy
Business School Prestige ^V Research versus Teaching
We examined the relationships between the research originating at business schools, students^R satisfaction with the schools, and the published ratings of the school^Rs prestige. Research was positively correlated to prestige (where prestige was based on the perceptions of academics, firms, and student candidates). The satisfaction of recent graduates was not related to a school^Rs prestige (based on the perceptions of academics and business firms). Research productivity of schools was not associated with lower satisfaction among their recent graduates. We conclude that schools should emphasize research instead of teaching if they desire high prestige.learning, universities, business schools
Commentary on the Makridakis Time Series Competition (M- Competition)
In 1982, the Journal of Forecasting published the results of a forecasting competition organized by Spyros Makridakis (Makridakis et al., 1982). In this, the ex ante forecast errors of 21 methods were compared for forecasts of a variety of economic time series, generally using 1001 time series. Only extrapolative methods were used, as no data were available on causal variables. The accuracies of methods were compared using a variety of accuracy measures for different types of data and for varying forecast horizons. The original paper did not contain much interpretation or discussion. Partly this was by design, to be unbiased in the presentation. A more important factor, however, was the difficulty in gaining consensus on interpretation and presentation among the diverse group of authors, many of whom have a vested interest in certain methods. In the belief that this study was of major importance, we decided to obtain a more complete discussion of the results. We do not believe that the data speak for themselves.Makridakis, commentary, time series competition, m competition
Communication of Research on Forecasting: The Journal
It seems trivial to point out that one of the major goals of the International Institute of Forecasters is to communicate research findings. In particular, the IIF tries to foster communication among researchers, between researchers and practitioners, across nationalities, and across disciplines. We have two major vehicles for this: the annual symposiums and the journal. This editorial examines the results that we have had to date with our journals.research, forecasting, communication
Teacher vs. Learner Responsibility in Management Education
A literature review suggested that behavioral changes occur more rapidly when the learner assumed responsibility. Natural learning, an approach to help learners assume responsibility, was compared with the traditional strategy in seven field experiments. It produced more than twice as many long-term behavioral changes. It was superior also for attitude change, but not for gains in knowledge.learning, universities, teachers, management, education
Commentary by J. Scott Armstrong on Fildes et al.: Generalizing about univariate forecasting methods: further empirical evidence,
Fildes, Hibon, Makridakis and Meade (1998), which will be referred to as FHMM, extends two important published papers. The idea of taking findings from each study and testing them against the data used in the other study is a good one. Such replications and extensions are important in the effort to develop useful generalizations and publication of this paper reflects the commitment of International Journal of Forecasting to replication research. In addition the study examines procedures for estimating smoothing parameters, and it evaluates the need for using multiple starting points when evaluating forecasting methods. On the negative side, FHMM does not fully describe the conditions under which one might expect a given extrapolation method to provide more accurate forecasts than competing methods. This limits the generalizability of its findings. In addition, I believe that the FHMM generalizations are even more limited than they might appear at first glance.forecasting, univariate forecasting methods
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