2 resultados para plant and machinery education

em Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest


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A tanulmányban 25 ország, kétezres évek közepi állapotot tükröző, reprezentatív keresztmetszeti mintáin egyrészt a Duncan-Hoffman-féle modellre támaszkodva megvizsgáljuk, hogy adatbázisunk milyen mértékben tükrözi az illeszkedés bérhozamával foglalkozó irodalom legfontosabb empirikus következtetéseit, másrészt - a Hartog- Oosterbeek-szerzőpáros által javasolt statisztikai próbák segítségével - azt elemezzük, hogy a becslések eredményei alapján mit mondhatunk Mincer emberitőke-, valamint Thurow állásversenymodelljének érvényességéről. Heckman szelekciós torzítást kiküszöbölő becslőfüggvényén alapuló eredményeink jórészt megerősítik az irodalomban vázolt legfontosabb empirikus sajátosságokat, ugyanakkor a statisztikai próbák az országok többségére nézve cáfolják mind az emberi tőke, mind az állásverseny modelljének empirikus érvényességét. / === / Using the Duncan–Hoffman model, the paper estimates returns for educational mismatch using comparable micro data for 25 European countries. The aim is to gauge the extent to which the main empirical regularities shown in other papers on the subject are confirmed by this data base. Based on tests proposed by Hartog and Oosterbeek, the author also considers whether the observed empirical patterns accord with the Mincerian basic human-capital model and Thurow's job-competition model. Heckman's sample-selection estimator shows the returns to be fairly consistent with those found in the literature; the job-competition model and the Mincerian human-capital model can be rejected for most countries.

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Climate change is one of the biggest environmental problems of the 21st century. The most sensitive indicators of the effects of the climatic changes are phenological processes of the biota. The effects of climate change which were observed the earliest are the remarkable changes in the phenology (i.e. the timing of the phenophases) of the plants and animals, which have been systematically monitored later. In our research we searched for the answer: which meteorological factors show the strongest statistical relationships with phenological phenomena based on some chosen plant and insect species (in case of which large phenological databases are available). Our study was based on two large databases: one of them is the Lepidoptera database of the Hungarian Plant Protection and Forestry Light Trap Network, the other one is the Geophytes Phenology Database of the Botanical Garden of Eötvös Loránd University. In the case of butterflies, statistically defined phenological dates were determined based on the daily collection data, while in the case of plants, observation data on blooming were available. The same meteorological indicators were applied for both groups in our study. On the basis of the data series, analyses of correlation were carried out and a new indicator, the so-called G index was introduced, summing up the number of correlations which were found to be significant on the different levels of significance. In our present study we compare the significant meteorological factors and analyse the differences based on the correlation data on plants and butterflies. Data on butterflies are much more varied regarding the effectiveness of the meteorological factors.