The ability of fifth grade children to discriminate between fact and opinion statement

Thesis (Ed.M.)--Boston Universit

Chi-squared tests of interval and density forecasts and the Bank of England's fan charts

This paper reviews recently proposed likelihood ratio tests of goodness-of-fit and independence of interval forecasts. It recasts them in the framework of Pearson chi-squared statistics, and considers their extension to density forecasts and their exact small-sample distributions. The use of the familiar framework of contingency tables will increase the accessibility of these methods. The tests are applied to two series of density forecasts of inflation, namely the US Survey of Professional Forecasters and the Bank of England fan charts. This first evaluation of the fan chart forecasts finds that whereas the current-quarter forecasts are well-calibrated, this is less true of the one-year-ahead forecasts. The fan charts fan out too quickly, and the excessive concern with the upside risks was not justified over the period considered JEL Classification: C53, E37interval and density forecasts

Inflation Targets as a Stabilisation Device

Over 80% of countries using explicit inflation targets in 2000 were doing so either as part of a disinflation strategy, or when inflation was neither low nor stable. Our illustrative theoretical model suggests annual revisions to short-run targets are endogenous to inflation outcomes during disinflation as long as the policymaker cares about misses from both the short-run target and a long-run target. Furthermore, target revisions will are larger when the target is undershot compared to when the target is overshot. We confirm the result using cross-country panel estimates from a unique data-set of inflation target misses in 60 countries in the 1990s. During disinflation it is therefore relatively difficult to separate decisions about target-setting from implementation. Short-term targets on a disinflation path may be more akin to conditional forecasts than policy rules, but their publication may nevertheless increase transparency and hence help policymakers to achieve lower inflation.

Jaccard/Tanimoto similarity test and estimation methods

Binary data are used in a broad area of biological sciences. Using binary presence-absence data, we can evaluate species co-occurrences that help elucidate relationships among organisms and environments. To summarize similarity between occurrences of species, we routinely use the Jaccard/Tanimoto coefficient, which is the ratio of their intersection to their union. It is natural, then, to identify statistically significant Jaccard/Tanimoto coefficients, which suggest non-random co-occurrences of species. However, statistical hypothesis testing using this similarity coefficient has been seldom used or studied. We introduce a hypothesis test for similarity for biological presence-absence data, using the Jaccard/Tanimoto coefficient. Several key improvements are presented including unbiased estimation of expectation and centered Jaccard/Tanimoto coefficients, that account for occurrence probabilities. We derived the exact and asymptotic solutions and developed the bootstrap and measurement concentration algorithms to compute statistical significance of binary similarity. Comprehensive simulation studies demonstrate that our proposed methods produce accurate p-values and false discovery rates. The proposed estimation methods are orders of magnitude faster than the exact solution. The proposed methods are implemented in an open source R package called jaccard (https://cran.r-project.org/package=jaccard). We introduce a suite of statistical methods for the Jaccard/Tanimoto similarity coefficient, that enable straightforward incorporation of probabilistic measures in analysis for species co-occurrences. Due to their generality, the proposed methods and implementations are applicable to a wide range of binary data arising from genomics, biochemistry, and other areas of science