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The Multilingual Assessment Instrument for Narratives (MAIN) was designed in order to assess narrative skills in children who acquire one or more languages from birth or from early age. MAIN is suitable for children from 3 to 10 years and evaluates both comprehension and production of narratives. Its design allows for the assessment of several languages in the same child, as well as for different elicitation modes: Model Story, Retelling, and Telling.
MAIN contains four parallel stories, each with a carefully designed six-picture sequence. The stories are controlled for cognitive and linguistic complexity, parallelism in macrostructure and microstructure, as well as for cultural appropriateness and robustness.
The instrument has been developed on the basis of extensive piloting with more than 550 monolingual and bilingual children aged 3 to 10, for 15 different languages and language combinations.
Even though MAIN has not been norm-referenced yet, its standardized procedures can be used for evaluation, intervention and research purposes. MAIN is currently available in the following languages: English, Afrikaans, Albanian, Basque, Bulgarian, Croatian, Cypriot Greek, Danish, Dutch, Estonian, Finnish, French, German, Greek, Hebrew, Icelandic, Italian, Lithuanian, Norwegian, Polish, Russian, Spanish, Standard Arabic, Swedish, Turkish, Vietnamese, and Welsh.
This paper investigates the accuracy of forecasts from four DSGE models for inflation, output growth and the federal funds rate using a real-time dataset synchronized with the Fed’s Greenbook projections. Conditioning the model forecasts on the Greenbook nowcasts leads to forecasts that are as accurate as the Greenbook projections for output growth and the federal funds rate. Only for inflation the model forecasts are dominated by the Greenbook projections. A comparison with forecasts from Bayesian VARs shows that the economic structure of the DSGE models which is useful for the interpretation of forecasts does not lower the accuracy of forecasts. Combining forecasts of several DSGE models increases precision in comparison to individual model forecasts. Comparing density forecasts with the actual distribution of observations shows that DSGE models overestimate uncertainty around point forecasts.
The calculus CHF models Concurrent Haskell extended by concurrent, implicit futures. It is a process calculus with concurrent threads, monadic concurrent evaluation, and includes a pure functional lambda-calculus which comprises data constructors, case-expressions, letrec-expressions, and Haskell’s seq. Futures can be implemented in Concurrent Haskell using the primitive unsafeInterleaveIO, which is available in most implementations of Haskell. Our main result is conservativity of CHF, that is, all equivalences of pure functional expressions are also valid in CHF. This implies that compiler optimizations and transformations from pure Haskell remain valid in Concurrent Haskell even if it is extended by futures. We also show that this is no longer valid if Concurrent Haskell is extended by the arbitrary use of unsafeInterleaveIO.
The 'de-allative'-pattern (Heine/ Kuteva 2008: 103) gives rise to the French grammaticalized periphrasis aller + INF and the Spanish grammaticalized periphrasis ir a + INF. This construction (anar + INF) also consists in Catalan, but here, however, with the periphrasis expressing a past tense. Concerning the grammaticalization path ir a + INF and aller + INF were formerly used to express a past (historical present), whereas anar + INF also expressed a future (and can still take on this function). This paper discusses possible reasons for the development and the thus exceptional position of the Catalan past-periphrasis. In addition to morphological and normative explanations, language contact between Catalan and Spanish/ French as well as sociolinguistic circumstances are factors which may possibly account for the development of the Catalan construction. After a separate presentation of the development and the former and actual use(s) and forms of the three periphrasis, the cognitive processes which took place during the grammaticalization are presented. Afterward the three periphrasis are compared using the parameters of Lehmann. The second part of this paper consists of a corpus which verifies and illustrates the results of the previous part.
The comprehension and production of single words involve a variety of processing stages. Which stages need to be accessed differs depending on whether objects (pictures in an experimental environment) or words are supposed to be named. Naming tasks are often employed in psycholinguistic studies in order to provide an insight into the function of mental processes during word production. Differences in naming latencies and naming accuracy between words suggest that the retrieval of some lexical items is easier or more difficult in contrast to others. The relative ease of word retrieval has been found to be strongly influenced by properties of these words, such as familiarity and written or spoken frequency.
Exploring which variables affect naming speed and accuracy will allow gaining more information about the storage and processing of words in general. If a variable has a discernable effect on a specific experimental task, the localization of this effect is of interest for psycholinguistic research. This is because finding the locus of the effect can help specify models of speech production with respect to what processes occur at which stage of lexical retrieval. Additionally, identifying which variables influence language processing is inevitable in order to control for these variables when necessary. Otherwise variance in naming latencies could not be explained by the variable that was to be tested because other, uncontrolled variables could have altered the results.
In this paper, we develop a state-dependent sensitivity value-at-risk (SDSVaR) approach that enables us to quantify the direction, size, and duration of risk spillovers among financial institutions as a function of the state of financial markets (tranquil, normal, and volatile). Within a system of quantile regressions for four sets of major financial institutions (commercial banks, investment banks, hedge funds, and insurance companies) we show that while small during normal times, equivalent shocks lead to considerable spillover effects in volatile market periods. Commercial banks and, especially, hedge funds appear to play a major role in the transmission of shocks to other financial institutions. Using daily data, we can trace out the spillover effects over time in a set of impulse response functions and find that they reach their peak after 10 to 15 days.