13,785 research outputs found

    Effect of Prey Density on Diurnal Activity and Ovarian Development in \u3ci\u3eCalosoma Calidum\u3c/i\u3e (Coleoptera: Carabidae): Implications for Biological Control of the Gypsy Moth, \u3ci\u3eLymantria Dispar (Lepidoptera: Lymantriidae)\u3c/i\u3e in the Midwest

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    Four feeding treatments were used in the laboratory to study the effects of the availability of prey on diurnal behavior and ovarian development of Calosoma calidum. Activity was closely monitored for six weeks. No significant differences were found between male and female behavior patterns. Diurnal beetle activity was found to be inversely related to prey density; in treatments where prey was available, diurnal activity declined during the course of the experiment. At the end of six weeks, dissections of female beetles showed that ovarian development and fat body quantity were dependent upon the number of prey available for consumption

    Combining Models of Approximation with Partial Learning

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    In Gold's framework of inductive inference, the model of partial learning requires the learner to output exactly one correct index for the target object and only the target object infinitely often. Since infinitely many of the learner's hypotheses may be incorrect, it is not obvious whether a partial learner can be modifed to "approximate" the target object. Fulk and Jain (Approximate inference and scientific method. Information and Computation 114(2):179--191, 1994) introduced a model of approximate learning of recursive functions. The present work extends their research and solves an open problem of Fulk and Jain by showing that there is a learner which approximates and partially identifies every recursive function by outputting a sequence of hypotheses which, in addition, are also almost all finite variants of the target function. The subsequent study is dedicated to the question how these findings generalise to the learning of r.e. languages from positive data. Here three variants of approximate learning will be introduced and investigated with respect to the question whether they can be combined with partial learning. Following the line of Fulk and Jain's research, further investigations provide conditions under which partial language learners can eventually output only finite variants of the target language. The combinabilities of other partial learning criteria will also be briefly studied.Comment: 28 page

    Is There a Bubble in the Housing Market?

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    This paper looks for evidence of a bubble in U.S. housing prices. It analyzes quarterly state-level data over 1985-2002, focusing on the relationship between home prices and selected fundamental variables. Income per capita alone largely explains price changes in all but eight states; in the latter, large price movements are observed unrelated to the fundamentals. Results from a new survey of recent homebuyers in the Los Angeles, San Francisco, Boston, and Milwaukee metropolitan areas are reported. This survey replicates an almost identical 1988 survey and finds, as before, that buyers in most of these markets perceive little risk in their housing investment, have unrealistic expectations about future price increases, and hold economically implausible beliefs about home price behavior—findings consistent with a bubble. Prices in such markets could stall or decline, but only if such declines are simultaneous or spread to other markets are significant effects on the national economy likely.macroeconomics, Bubble, Housing Market

    The Efficiency of the Market for Single-Family Homes

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    Tests of weak-form efficiency of the market for single family homes are performed using data on repeat sales prices of 39,210 individual homes, each for two sales dates. Tests were done for Atlanta, Chicago, Dallas, and San Francisco/Oakland for 1970-86. While evidence for seasonality in real housing prices is weak, we do find some evidence of inertia in housing prices. A city-wide real log price index change in a given year tends to be followed by a city-wide real log price index change in the same direction (and between a quarter to a half as large in magnitude) in the subsequent year. However, the inertia cannot account for much of the variation in individual housing real price changes. There is so much noise in individual housing prices relative to city-wide price index changes that the R[squared] in forecasting regressions for annual real price change in individual homes is never more than .04.

    Housing Price Dynamics Within a Metropolitan Area

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    This paper analyzes the pattern of cross-sectional house price appreciation in the Boston metropolitan area from 1982 to 1994. The empirical results are consistent with many of the predictions of a standard urban model in which towns have a fixed set of locational attributes and amenities. In particular, the evidence suggests that house prices in towns with a large share of residents working in the manufacturing sector in 1980 grew less quickly in the ensuing years when aggregate manufacturing employment fell. As baby boomers moved into middle age, house values appreciated faster in towns with a larger initial percentage of middle-aged residents. Housing values rose more slowly in towns that allowed additional construction, and values rose faster in towns closer to Boston. Finally, as fewer families had children who attended public schools statewide, the price premium associated with housing in towns with good schools fell. All of these findings support the view that town amenities and public services are not easily replicated or quickly adaptable to shifts in demand, even within a metropolitan area.

    Forecasting Prices and Excess Returns in the Housing Market

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    The U. S. market for homes appears not to be efficient. A number of information variables predict housing price changes and excess returns of housing relative to debt over the succeeding year. Price changes observed over one year tend to continue for one more year in the same direction. Construction cost divided by price, the change in per capita real income, the change in adult population are all positively related to price changes or excess returns over the subsequent year. The results are based on time-series cross section regressions with quarterly data 1970-1 to 1987-3 and for cities Atlanta, Chicago, Dallas, and San Francisco.
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