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This paper presents a methodology for producing a probability forecast of a turning point in U.S. economy using Composite Leading Indicators. This methodology is based on classical statistical decision theory and uses information-theoretic measurement to produce a probability. The methodology is flexible using as many historical data points as desired. This methodology is applied to producing probability forecasts of a downturn in U.S. economy in the 1970-1990 period. Four probability forecasts are produced using different amounts of information. The performance of these forecasts is evaluated using the actual downturn points and the scores measuring accuracy, calibration, and resolution. An indirect comparison of these forecasts with Diebold and Rudebusch's sequential probability recursion is also presented. It is shown that the performances of our best two models are statistically different from the performance of the three-consecutive-month decline model and are the same as the one for the best probit model. The probit model, however, is more conservative in its predictions than our two models.

Ordinary least squares (OLS) regression is relatively sensitive to the presence of outliers in a data set. In this paper, a robust estimation method, least median of squares (LMS) is used to identify outliers in land value data. Once the outliers are identified, are the land value equations re-estimated. The results show that a few observations can have a significant effect on the estimated coefficients. Finally, the observations which were identified as outliers were examined in more detail. One cause of outliers is an omitted variable. In this case, a large fraction of the outliers were found to be observations with high development potential.

This paper examines the effect of a zoning change on the land market in McHenry County, Illinois. One question addressed is whether zoning `'follows the market.” It is found that, for agricultural land, zoning does tend to follow the market. In addition, the effect of land prices on land use is examined. The results here, however, are mixed. In the initial years after the zoning change, a high relative price of residential land increases the probability that a parcel will be zoned residential. However, several years later, a high relative price of residential land decreases the probability that a parcel is zoned residential. This result suggests that it may take some time for a zoning change to have a significant impact on the local land market.

Does the formation of a customs union reduce and eventually eliminate tariffs among member countries to provide mechanisms or regional institutions for social, economic and political development? The literature examined suggests that, although many problems of trade liberalization continue to occur, greater benefits could be obtained by reducing tariffs on a non‐discriminatory basis, or by removing protection from domestic enterprises altogether, and by importing domestic requirements of the products of displaced industries from outside at world market prices. The literature also provides a valid case for protecting certain activities in ECOWAS — particularly trade and industrial enterprises — either for the purpose of increasing income or the rate of economic growth, or in order to achieve certain non‐economic objectives. The implications of economic integration in these terms can best be examined within a broader theoretical framework of developmental theory of trade liberalization. Copyright © 1993 John Wiley & Sons, Ltd

By 1965, Taiwan has changed from a labor surplus economy into a labor shortage economy. This article examines how rising demand for labor due lo rapid economic growth in Taiwan has been met since 1965. This article attempts to answer 1) Where did the labor supply come from? 2) Has all of the potential labor supply been tapped and exhausted? 3) Is it possible for labor shortage and unutilized labor reserve to occur simultaneously? The authors hope that this study will lead to a better understanding of the limitation of the free market mechanism and help identify the proper public policies to enhance labor utilization.

After surveying the evolution of the major methodologies in inflation hedging, this study presents a unique methodology that uses principal component factor analysis to separate the effects of variability in the real rate of return from the nominal rate of return. This approach allows the effects of both anticipated and unanticipated inflation on rates of return to be estimated more precisely. This study finds that art objects perform well in terms of average real rates of return and that the market, though not perfect, integrates anticipated inflation into the rates of return. However, unanticipated inflation is very often negatively related to the rates of return. Copyright © 1994, Wiley Blackwell. All rights reserved

This paper discusses a regulatory technique that consists of the use of a controlled chain reaction to influence social and economic processes. It claims that this method was employed by Hungarian control agencies to further centralize the farm sector in the 1970s. Section I of the paper presents three versions of this technique. Section II shows how the institutional structure of Hungarian agriculture made the application of this technique possible. (JEL P21).

This paper examines whether a more restrictive zoning ordinance actually reduces construction of new housing. This may seem at first to be a trivial issue, since why else would a zoning board make the ordinance more restrictive. However, it is possible for landowners to circumvent the zoning law. For example, they can subdivide their land before the zoning change occurs. In addition, they can bargain with the local zoning officials and offer side payments, also known as exactions, for the right to develop their land. This paper examines a famous case of agricultural downzoning in McHenry County, Illinois. It finds that although the number of building permits issued did not fall immediately, in the long run the number of permits issued by the county was significantly reduced. This suggests that developers were able to anticipate the zoning change and subdivide their land before it occurred. (C) 1997 Academic Press.

There have been several studies that have investigated the effect of zoning on housing prices. One hypothesis is that the restrictiveness of zoning laws will vary with the monopoly power of a town. The degree of monopoly power varies with the number of towns in the urban area. Urban areas with few zoning jurisdictions are likely to have higher housing prices than more fragmented urban areas. Previous research on this topic has shown mixed results. The results in this article suggest that towns with more monopoly power do tend to have significantly higher housing prices than more fragmented urban areas.

Application of forward coastal sediment transport models in situations involving large temporal and spatial scales or topographically complex environments can be highly problematic since the distribution of hydrodynamic parameters is rarely adequately known. Where rocky topography is present, flow patterns may be altered and sediments trapped by topographic barriers. A frequently employed approach to these problems is the application of the statistical technique known as empirical orthogonal function (EOF) analysis. One limitation of EOF analysis of grain size and mineralogical data is that EOF is a purely geometric technique which does not allow incorporation of a priori knowledge we may have regarding the physical environment. In fact, there is no guarantee that a meaningful physical interpretation of the results of an EOF analysis actually exists. This is not true of geophysical inverse theory, which is capable of incorporating diverse forms of information and is not limited to purely geometric manipulations of data. We have formulated an inverse theoretical approach to study sediment transport which we call STI, short for source-transport inversion. STI relaxes the nonphysical assumption of orthogonal endmembers and can handle many forms of a priori information. STI has been developed initially in the context of modeling the sediment supply and dispersal system of Monterey Bay, California. Using the geographical distribution of heavy mineralogy data, significant sources are identified and sediments traced from those sources along transport pathways. Model results are encouraging both in terms of goodness of fit between model and data and in terms of the agreement of model results with the sediment sourcing and dispersal patterns inferred in previous studies. Model results indicate that beach sediments are primarily derived from the open coast north of the bay, that a littoral cell boundary exists in the center of the bay at Moss Landing, and that beach deposits produced by paleolittoral drift during a sea level low stand lie along the 100-m isobath. Copyright 1998 by the American Geophysical Union.

Despite reports that substance abuse among young Americans is on the decline, the problem among young male African Americans continues to be of major concern. School-based prevention strategies offer promising alternatives for reducing the risk factors for substance abuse among this group. The most successful of these programs appear to be those that include the entire school ecology as part of the prevention strategy and focus on the unique psychosocial development needs of these youth. in this article we discuss the prevalence of substance abuse among male African American youth, examine school correlates and risk factors, and review school-based prevention strategies that have shown varying degrees of effectiveness in addressing the substance abuse problems, directly through changing values, attitudes, and behaviors, and indirectly by reducing risk factors and strengthening protective mechanisms.

Temporal analysis has been applied to a sequence of cloud top pressure (CTP) images and cloud optical thickness (TAU) images stored in the International Satellite Cloud Climatology Project (ISCCP) D1 database located at the NASA Goddard Institute for Space Studies (GISS). Each pixel in the D1 data set has a resolution of 2.5 degrees or 280 kilometers. These images were collected in consecutive three-hour intervals for the entire month of April 1989. The primary objective of this project was to develop a sequence of storm tracks from the satellite images to follow the formation, progression and dissipation of storm systems over time. Composite images where created by projecting ahead in time and substituting the first available valid pixel for missing data and a variety of CTP and TAU cut-off values were used to identify regions of interest. Region correspondences were determined from one time frame to another yielding the coordinates of storm centers. These tracks were compared to storm tracks computed from sea level pressure data obtain from the National Meteorological Center (NMC) for the same time period. The location of sea level storm center provides insight as to whether storms have occurred anywhere in a region and can be helpful in determining the presence or absence of storms in a general geographic region.

The primary objective of this project is to define a methodology to depict the motion of deep convective cloud systems as observed form satellite imagery. These clouds are defined as clusters of pixels with Cloud Top Pressure (IPC) <EQ 440 millibars and Cloud Optical Thickness (TAU) >= 23 which are high in the atmosphere and sufficiently thick to produce significant rainfall. Clouds are one of the major factors in understanding the earth's climate. Evaluating cloud motion is important in understanding atmospheric dynamics and visualizations are vital because they provide a good way to observe change. IPC and TAU values have been collected for April of 1989 from the International Satellite Cloud Climatology Project, low resolution database for the northern latitudes between 30 and 60 degrees. Each of the 240 IPC and 240 TAU images consisted of 12 rows and 144 columns with each pixel representing a 280 km square on the globe collected in three-hour intervals. Individual images were color coded according to land, sea and clouds before being put into motion. Six animations have been produced which start with the original images, progress to include daily composite images and culminate with a collage. Animations of the original images have the advantage of relatively short intervals between still frames but have many undefined pixels, which are eliminated in the composites. The results of this project can serve as an example of how to improve the visualization of time varying image sequences.

The objective of this study is to compare statistical and unsupervised neural network techniques for determination of correspondences between storm system regions extracted from sequences of satellite images. Analysis was applied to the International Satellite Cloud Climatology Project (ISCCP) low resolution D1 database for selected storm systems during the period April 5 - 9, 1989. Cloud top pressure was used to delineate regions of interest and cloud optical thickness combined with spatial location was used to track regions throughout a given time sequence. The ability of the k-nearest neighbor classifier and of self-organizing maps to determine correspondences between storm regions was assessed. The two techniques generally yielded similar associations between regions of interest throughout the time sequence. Differences in final tracking results between the two techniques occurred primarily as a result of differences in the collections of points from a region in a time step t<SUB>2</SUB> that corresponded to a region in an earlier time step t<SUB>1</SUB>. The tracking results were also compared to the results obtained at the NASA Goddard Institute for Space Studies using sea level pressure data from the National Meteorological Center (NMC). For the storm systems investigated in this study, the storm tracks exhibited the same general tracking behavior with expected variations between cloud system storm centers and low sea level pressure centers.

A view of interactions in the undergraduate classroom is presented from several perspectives. Topics discussed include class perceptions of teacher as facilitator/authority/leader, grades versus performance appraisals, mixed-gender interactions, and subtle forms of cultural variations.

Accurate identification and tracking of synoptic-scale storm systems in the northern midlatitudes is important for understanding the structure and movement of the midlatitude cloud field which plays a major role in climate change. In this paper, a hybrid neural network/genetic algorithm (NN/GA) approach is presented that analyzes the behavior of storm systems from one time frame to the next. The goal of the hybrid neural network algorithm is to improve classifier output by reducing the number of infeasible solutions using constraint optimization techniques. The input to the hybrid neural network algorithm is the output from a traditional backpropagation neural network. The hybrid NN/GA analyzes the backpropagation neural network output for logical consistencies and makes changes to the classification results based on strength of neural network classifications and satisfaction of logical constraints. The results are compared with classification results obtained using linear discriminant analysis, k-nearest neighbor rule, and backpropagation neural network techniques.

An evolutionary system was developed for generation of complete tracks of northern midlatitude synoptic-scale storm systems based on optical flow and cloud motion analyses of global satellite-based datasets produced by the International Satellite Cloud Climatology Project (ISCCP). The tracking results were compared with low sea level pressure anomaly (SLPA) tracks obtained from the NASA Goddard Institute for Space Studies (GISS). The SLPA tracks were produced at GISS by analysis of meteorological, ground-based National Center for Environmental Prediction (NCEP) datasets. Results from the evolutionary system were also compared with results from using (a) the k-nearest neighbor rule (k-NN) and (b) self-organizing maps (SOM) to determine correspondences between consecutive locations within a track. The consistency of our evolutionary storm tracking results with the behavior of the low sea level pressure anomaly tracks, the ability of our evolutionary system to generate and evaluate complete tracks, and the close comparison between the results obtained by the evolutionary, k-NN, and SOM analyses of the ISCCP-derived datasets at tracking steps in which proximity or optical flow information sufficed to determine movement, demonstrate the applicability and the potential of evolutionary systems for tracking midlatitude storm systems through low-resolution ISCCP cloud product datasets.

This preliminary investigation considers undergraduate student perceptions with respect to their professional future. `No one warned me it would be like this,' and `These are the things that college never taught me,' are typical comments that are heard from the young workforce. This paper addresses future plans and predictions of students from two New England institutions of higher learning by utilizing a variety of strategies. Methods to elicit data include in-class activities and carefully designed questionnaires. These exercises have been designed to uncover images and themes concerning transition from college to the workplace. Issues include technical and communication skills, leadership roles, corporate politics, group dynamics, and gender diversity in the workplace.

The objective of this research is to automate the classification of the temporal behavior of storm cloud systems based on measurements derived from consecutive satellite images. The motivation behind this study is to develop improved descriptions of cloud dynamics which can be used in general circulation models for prediction of global climate change. Analysis was applied to the International Satellite Cloud Climatology Project (ISCCP) low resolution cloud top pressure database for the first six days in April, 1989. A total of 296 midlatitude storm cloud components were tracked between consecutive 3-hour time frames. For each pair of components, temporal correspondence events were classified as either 1.) direct, 2.) merge, 3.) split, or 4.) reject. The reject class, which was used primarily to categorize pairs of unrelated systems, included storm cloud system dissipation and creation as well. Statistical, neural network, and evolutionary techniques were developed for finding solutions to the storm cloud correspondence problem. Evolutionary techniques applied to the problem consisted of 1.) a constraint-handling hybrid evolutionary technique and 2.) a genetic local search algorithm. The results demonstrate the potential of evolutionary techniques to yield meteorologically-feasible solutions, given appropriate constraints, to the two-frame storm tracking problem. © 1998 SPIE. All rights reserved.