14 resultados para hermione granger

em CentAUR: Central Archive University of Reading - UK


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This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs oil the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO-the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%-30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.

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We seek to address formally the question raised by Gardner (2003) in his Elmhirst lecture as to the direction of causality between agricultural value added per worker and Gross Domestic Product (GDP) per capita. Using the Granger causality test in the panel data analyzed by Gardner for 85 countries, we find overwhelming evidence that supports the conclusion that agricultural value added is the causal variable in developing countries, while the direction of causality in developed countries is unclear. We also examine further the use of the Granger causality test in integrated data and provide evidence that the performance of the test can be increased in small samples through the use of the bootstrap.

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A predictability index was defined as the ratio of the variance of the optimal prediction to the variance of the original time series by Granger and Anderson (1976) and Bhansali (1989). A new simplified algorithm for estimating the predictability index is introduced and the new estimator is shown to be a simple and effective tool in applications of predictability ranking and as an aid in the preliminary analysis of time series. The relationship between the predictability index and the position of the poles and lag p of a time series which can be modelled as an AR(p) model are also investigated. The effectiveness of the algorithm is demonstrated using numerical examples including an application to stock prices.

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We test the response of the Oxford-RAL Aerosol and Cloud (ORAC) retrieval algorithm for MSG SEVIRI to changes in the aerosol properties used in the dust aerosol model, using data from the Dust Outflow and Deposition to the Ocean (DODO) flight campaign in August 2006. We find that using the observed DODO free tropospheric aerosol size distribution and refractive index increases simulated top of the atmosphere radiance at 0.55 µm assuming a fixed erosol optical depth of 0.5 by 10–15 %, reaching a maximum difference at low solar zenith angles. We test the sensitivity of the retrieval to the vertical distribution f the aerosol and find that this is unimportant in determining simulated radiance at 0.55 µm. We also test the ability of the ORAC retrieval when used to produce the GlobAerosol dataset to correctly identify continental aerosol outflow from the African continent and we find that it poorly constrains aerosol speciation. We develop spatially and temporally resolved prior distributions of aerosols to inform the retrieval which incorporates five aerosol models: desert dust, maritime, biomass burning, urban and continental. We use a Saharan Dust Index and the GEOS-Chem chemistry transport model to describe dust and biomass burning aerosol outflow, and compare AOD using our speciation against the GlobAerosol retrieval during January and July 2006. We find AOD discrepancies of 0.2–1 over regions of intense biomass burning outflow, where AOD from our aerosol speciation and GlobAerosol speciation can differ by as much as 50 - 70 %.

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Purpose – Expectations of future market conditions are acknowledged to be crucial for the development decision and hence for shaping the built environment. The purpose of this paper is to study the central London office market from 1987 to 2009 and test for evidence of rational, adaptive and naive expectations. Design/methodology/approach – Two parallel approaches are applied to test for either rational or adaptive/naive expectations: vector auto-regressive (VAR) approach with Granger causality tests and recursive OLS regression with one-step forecasts. Findings – Applying VAR models and a recursive OLS regression with one-step forecasts, the authors do not find evidence of adaptive and naïve expectations of developers. Although the magnitude of the errors and the length of time lags between market signal and construction starts vary over time and development cycles, the results confirm that developer decisions are explained, to a large extent, by contemporaneous and historic conditions in both the City and the West End, but this is more likely to stem from the lengthy design, financing and planning permission processes rather than adaptive or naive expectations. Research limitations/implications – More generally, the results of this study suggest that real estate cycles are largely generated endogenously rather than being the result of large demand shocks and/or irrational behaviour. Practical implications – Developers may be able to generate excess profits by exploiting market inefficiencies but this may be hindered in practice by the long periods necessary for planning and construction of the asset. Originality/value – This paper focuses the scholarly debate of real estate cycles on the role of expectations. It is also one of very few spatially disaggregate studies of the subject matter.

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Insect pests that have a root-feeding larval stage often cause the most sustained damage to plants because their attrition remains largely unseen, preventing early diagnosis and treatment. Characterising movement and dispersal patterns of subterranean insects is inherently difficult due to the difficulty in observing their behaviour. Our understanding of dispersal and movement patterns of soil-dwelling insects is therefore limited compared to above ground insect pests and tends to focus on vertical movements within the soil profile or assessments of coarse movement patterns taken from soil core measurements in the field. The objective of this study was to assess how the dispersal behaviour of the clover root weevil (CRW), Sitona lepidus larvae was affected by differing proportions of host (clover) and non-host (grass) plants under different soil water contents (SWC). This was undertaken in experimental mini-swards that allowed us to control plant community structure and soil water content. CRW larval survival was not affected either by white clover content or planting pattern or SWC in either experiment; however, lower clover composition in the sward resulted in CRW larvae dispersing further from where they hatched. Because survival was the same regardless of clover density, the proportion of infested plants was highest in sward boxes with the fewest clover plants (i.e. the low host plant density). Thus, there is potential for clover plants over a larger area to be colonised when the clover content of the sward is low.

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This paper considers the effect of short- and long-term interest rates, and interest rate spreads upon real estate index returns in the UK. Using Johansen's vector autoregressive framework, it is found that the real estate index cointegrates with the term spread, but not with the short or long rates themselves. Granger causality tests indicate that movements in short term interest rates and the spread cause movements in the returns series. However, decomposition of the forecast error variances from VAR models indicate that changes in these variables can only explain a small proportion of the overall variability of the returns, and that the effect has fully worked through after two months. The results suggest that these financial variables could potentially be used as leading indicators for real estate markets, with corresponding implications for return predictability.

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This paper uses a recently developed nonlinear Granger causality test to determine whether linear orthogonalization really does remove general stock market influences on real estate returns to leave pure industry effects in the latter. The results suggest that there is no nonlinear relationship between the US equity-based property index returns and returns on a general stock market index, although there is evidence of nonlinear causality for the corresponding UK series.

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This paper explores a number of statistical models for predicting the daily stock return volatility of an aggregate of all stocks traded on the NYSE. An application of linear and non-linear Granger causality tests highlights evidence of bidirectional causality, although the relationship is stronger from volatility to volume than the other way around. The out-of-sample forecasting performance of various linear, GARCH, EGARCH, GJR and neural network models of volatility are evaluated and compared. The models are also augmented by the addition of a measure of lagged volume to form more general ex-ante forecasting models. The results indicate that augmenting models of volatility with measures of lagged volume leads only to very modest improvements, if any, in forecasting performance.

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This paper investigates the behavior of residential property and examines the linkages between house price dynamics and bank herding behavior. The analysis presents evidence that irrational behaviour may have played a significant role in several countries, including; United Kingdom, Spain, Denmark, Sweden and Ireland. In addition, we also provide evidence indicative of herding behaviour in the European residential mortgage loan market. Granger Causality tests indicate that non-fundamentally justified prices dynamics contributed to herding by lenders and that this behaviour was a response by the banks as a group to common information on residential property assets. In contrast, in Germany, Portugal and Austria, residential property prices were largely explained by fundamentals. Furthermore, these countries show no evidence of either irrational price bubbles or herd behaviour in the mortgage market. Granger Causality tests indicate that both variables are independent.

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We use both Granger-causality and instrumental variables (IV) methods to examine the impact of index fund positions on price returns for the main US grains and oilseed futures markets. Our analysis supports earlier conclusions that Granger-causal impacts are generally not discernible. However, market microstructure theory suggests trading impacts should be instantaneous. IV-based tests for contemporaneous causality provide stronger evidence of price impact. We find even stronger evidence that changes in index positions can help predict future changes in aggregate commodity price indices. This result suggests that changes in index investment are in part driven by information which predicts commodity price changes over the coming months.

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According to the 2000 census, 35.3 million Hispanics live in the United States. This number comprises 12.5% of the overall population rendering the Latino community the largest minority in the United States. The Mexican community is not only the largest Hispanic group but also the fastest growing: from 1990 to 2000, the Mexican population grew 52.9% increasing from 13.5 million to 20.6 million (U.S. Department of Commerce News, 2001). The influx of Mexican immigrants coupled with the expansion of their community within the United States has created an unparalleled situation of language contact. Language is synonymous with identity (cf. Granger, 2004, and works cited within). To the extent that this is true, Spanish is synonymous with being Mexican and by extension, Chicano. With the advent of amnesty programs such as Immigration Reform and Control Act (IRCA), which naturalized millions of Mexican migrants, what was once a temporal migratory population has become increasingly permanent (Durand et al., 1999). In an effort to conserve Mexican traditions and identity, the struggle to preserve the mother tongue while at the same time acculturate to mainstream Americana has resulted in a variant of Spanglish that has received little attention. This paper will examine the variant of Spanglish seen in the greater Los Angeles area and liken it to the bi-national identity under which these Mexican Americans thrive.