1,720,957 research outputs found
Consistent model specification testing
No full textThis paper proposes a consistent model specfication test that can be applied to a wide
class of models and estimators, including all variants of quasi-maximum likelihood and generalized method of moments. Our framework is independent of the form of the model and generalizes Bierens (1982, 1990) approach. It has particular applications in new cases such
as heteroskedastic errors, discrete data models, but the chief appeal of our approach is that
it provides a "one size fits all" test. We specify a test based on a linear combination of individual components of the indicator vector that can be computed routinely, does not need
to be tailored to the particular model, and is expected to have power against a wide class of
alternatives. Although primarily envisaged as a test of functional form, this type of moment
test can also be extended to testing for omitted variables
Consistent testing of functional form in time series models
No full textWe develop a consistent procedure for testing the adequacy of parametric time series models. The approach is to extend Herman Bierens’s idea of examining the covariances between regression residuals and an exponential weight function, to check the full range of orthogonalities predicted for the score contributions in quasi-maximum likelihood estimation. Tests of this type, which involve nuisance parameters, are constructed as either "sup"ed or integrated conditional moment tests, and are often implemented using bootstrap methods. However, our emphasis in this study is on practical implementation. We study a two-statistic approach that aims to exploit the available power while keeping computing requirements to a minimum
First-order asymptotic theory for parametric misspecification tests of Garch models
No full textThis paper develops a framework for the construction and analysis of parametric misspecification tests for generalized autoregressive conditional heteroskedastic (GARCH) models, based on first-order asymptotic theory. The principal finding is that estimation effects from the correct specification of the conditional mean (regression) function can be asymptotically nonnegligible. This implies that certain procedures, such as the asymmetry tests of Engle and No. (1993, Journal of Finance 48. 1749-1777) and the nonlinearity test of Lundbergh and Terasvirta (2002, Journal of Econometrics 110, 417-435), are asymptotically invalid. A second contribution is the proposed use of alternative tests for asymmetry and/or nonlinearity that, it is conjectured, should enjoy improved power properties. A Monte Carlo study supports the principal theoretical findings and also suggests that the new tests have fairly good size and very good power properties when compared with the Engle and Ng (1993) and Lundbergh and Terasvirta (2002) procedures
Ratio-based estimators for a change point in persistence
No full textWe study estimation of the date of change in persistence, from I(0) to I(1) or vice versa. Contrary
to statements in the original papers, our analytical results establish that the ratio-based break point
estimators of Kim [Kim, J.Y., 2000. Detection of change in persistence of a linear time series. Journal of
Econometrics 95, 97–116], Kim et al. [Kim, J.Y., Belaire-Franch, J., Badillo Amador, R., 2002. Corringendum
to ‘‘Detection of change in persistence of a linear time series’’. Journal of Econometrics 109, 389–392] and
Busetti and Taylor [Busetti, F., Taylor, A.M.R., 2004. Tests of stationarity against a change in persistence.
Journal of Econometrics 123, 33–66] are inconsistent when a mean (or other deterministic component) is
estimated for the process. In such cases, the estimators converge to random variables with upper bound
given by the true break date when persistence changes from I(0) to I(1). A Monte Carlo study confirms
the large sample downward bias and also finds substantial biases in moderate sized samples, partly due
to properties at the end points of the search interval
A heteroskedasticity robust Breusch-Pagan test for contemporaneous correlation in dynamic panel data models
No full textThis paper proposes a heteroskedasticity-robust Breusch-Pagan test of the null
hypothesis of zero cross-section (or contemporaneous) correlation in linear panel data
models. The procedure allows for either xed, strictly exogenous and/or lagged de-
pendent regressor variables, as well as quite general forms of both non-normality and
heteroskedasticity in the error distribution. Whilst the asymptotic validity of the test
procedure, under the null, is predicated on the number of time series observations,
T, being large relative to the number of cross-section units, N, independence of the
cross-sections is not assumed. Across a variety of experimental designs, a Monte Carlo
study suggests that, in general (but not always), the predictions from asymptotic the-
ory provide a good guide to the finite sample behaviour of the test. In particular,
with skewed errors and/or when N=T is not small, discrepancies can occur. However,
for all the experimental designs, any one of three asymptotically valid wild bootstrap
approximations (that are considered in this paper) gives very close agreement between
the nominal and empirical signi cance levels of the test. Moreover, in comparison with
wild bootstrap version of the original Breusch-Pagan test (Godfrey and Yamagata,
2011) the corresponding version of the heteroskedasticity-robust Breusch-Pagan test is
more reliable. As an illustration, the proposed tests are applied to a dynamic growth
model for a panel of 20 OECD countries
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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