876 resultados para Matthew Taylor
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2000 Mathematics Subject Classification: 47A10, 47A13.
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Cikkünkben a magyar monetáris politikát vizsgáljuk olyan szempontból, hogy kamatdöntései meghozatalakor figyelembe vette-e az országkockázatot, és ha igen, hogyan. A kérdés megválaszolásához a monetáris politika elemzésének leggyakoribb eszközét használjuk: az ország monetáris politikáját leíró Taylor-szabályokat becslünk. A becslést több kockázati mérőszámmal is elvégeztük több, különféle Taylor-szabályt használva. Az érzékenységvizsgálatban az inflációhoz és a kibocsátási réshez is alkalmaztunk más, az alapspecifikációban szereplőtől eltérő mérőszámokat. Eredményeink szerint a Magyar Nemzeti Bank kamatdöntései jól leírhatók egy rugalmas, inflációs célkövető rezsimmel: a Taylor-szabályban szignifikáns szerepe van az inflációs céltól való eltérésének és - a szabályok egy része esetén - a kibocsátási résnek. Emellett a döntéshozók figyelembe vették az országkockázatot is, annak növekedésére a kamat emelésével válaszoltak. Az országkockázat Taylor-szabályba történő beillesztése a megfelelő kockázati mérőszám kiválasztása esetén jelentős mértékben képes javítani a Taylor-szabály illeszkedését. _____ The paper investigates the degree to which Hungarian monetary policy has considered country risk in its decisions and if so, how. The answer was sought through the commonest method of analysing a countrys monetary policy: Taylor rules for describing it. The estimation of the rule was prepared using several risk indicators and applying various types of Taylor rules. As a sensitivity analysis, other indicators of inflation and output gap were employed than in the base rule. This showed that the interest-rate decisions of the National Bank of Hungary can be well described by a flexible inflation targeting regime: in the Taylor rules, deviation of inflation from its target has a significant role and the output gap is also significant in one part of the rules. The decision-makers also considered country risk and responded to an increase in it by raising interest rates. Insertion of country risk into the Taylor rule could improve the models fit to an important degree when choosing an appropriate risk measure.
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Magyarország társadalmi és gazdasági változásai kapcsán gyakran merül fel a kérdés, hogy egyes új fejlemények vajon a nemzetközi folyamatok hatására bontakoztak-e ki, és ha igen, azokkal egyidejűleg vagy bizonyos idővel később került-e sor rájuk? Egyidejűség vagy fáziskésés? Külföldi minták szolgai másolása vagy hazai viszonyokra történő alkalmazása, esetleg egy speciális „harmadik út” megfogalmazása volt-e jellemző az időszerűvé vált problémákra adott „magyar válaszra”?
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We analyzed the dynamics of freshwater marsh vegetation of Taylor Slough in eastern Everglades National Park for the 1979 to 2003 period, focusing on cover of individual plant species and on cover and composition of marsh communities in areas potentially influenced by a canal pump station (‘‘S332’’) and its successor station (‘‘S332D’’). Vegetation change analysis incorporated the hydrologic record at these sites for three intervals: pre-S332 (1961–1980), S332 (1980–1999), post-S332 (1999–2002). During S332 and post-S332 intervals, water level in Taylor Slough was affected by operations of S332 and S332D. To relate vegetation change to plot-level hydrological conditions in Taylor Slough, we developed a weighted averaging regression and calibration model (WA) using data from the marl prairies of Everglades National Park and Big Cypress National Preserve. We examined vegetation pattern along five transects. Transects 1–3 were established in 1979 south of the water delivery structures, and were influenced by their operations. Transects 4 and 5 were established in 1997, the latter west of these structures and possibly under their influence. Transect 4 was established in the northern drainage basin of Taylor Slough, beyond the likely zones of influence of S332 and S332D. The composition of all three southern transects changed similarly after 1979. Where muhly grass (Muhlenbergia capillaris var. filipes) was once dominant, sawgrass (Cladium jamaicense), replaced it, while where sawgrass initially predominated, hydric species such as spikerush (Eleocharis cellulosa Torr.) overtook it. Most of the changes in species dominance in Transects 1–3 occurred after 1992, were mostly in place by 1995–1996, and continued through 1999, indicating how rapidly vegetation in seasonal Everglades marshes can respond to hydrological modifications. During the post-S332 period, these long-term trends began reversing. In the two northern transects, total cover and dominance of both muhly grass and sawgrass increased from 1997 to 2003. Thus, during the 1990’s, vegetation composition south of S332 became more like that of long hydroperiod marshes, but afterward it partially returned to its 1979 condition, i.e., a community characteristic of less prolonged flooding. In contrast, the vegetation change along the two northern transects since 1997 showed little relationship to hydrologic status.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.