1,721,237 research outputs found
Advance praise (as on the back cover of the book)
No full textAdvance praise by Martina Navratilova, Lord Mervyn King, Geoff Pollard, Richard Blundell, Carl Morris, Peter C.B. Phillips, and Hal Stern.</p
Advance praise (as on the back cover of the book Analyzing Wimbledon)
No full textAdvance praise by Martina Navratilova, Lord Mervyn King, Geoff Pollard, Richard Blundell, Carl Morris, Peter C.B. Phillips, and Hal Stern.</p
Advance praise (as on the back cover of the book)
No full textAdvance praise by Martina Navratilova, Lord Mervyn King, Geoff Pollard, Richard Blundell, Carl Morris, Peter C.B. Phillips, and Hal Stern.</p
Advance praise (as on the back cover of the book Analyzing Wimbledon)
No full textAdvance praise by Martina Navratilova, Lord Mervyn King, Geoff Pollard, Richard Blundell, Carl Morris, Peter C.B. Phillips, and Hal Stern.</p
Explosive Behavior in the 1990s Nasdaq: When Did Exuberance Escalate Asset Values?
Full text linkA recursive test procedure is suggested that provides a mechanism for testing explosive behavior, date-stamping the origination and collapse of economic exuberance, and providing valid confidence intervals for explosive growth rates. The method involves the recursive implementation of a right-side unit root test and a sup test, both of which are easy to use in practical applications, and some new limit theory for mildly explosive processes. The test procedure is shown to have discriminatory power in detecting periodically collapsing bubbles, thereby overcoming a weakness in earlier applications of unit root tests for economic bubbles. An empirical application to Nasdaq stock price index in the 1990s provides confirmation of explosiveness and date-stamps the origination of financial exuberance to mid -1995, prior to the famous remark in December 1996 by Alan Greenspan about irrational exuberance in financial markets, thereby giving the remark empirical content.Explosive root, Irrational exuberance, Mildly explosive process, Nasdaq bubble, Periodically collapsing bubble, Sup test, Unit root test
Time Series Regression with a Unit Root and Infinite Variance Errors
No full textChan and Tran give the limit theory for the least squares coefficient in a random walk with the iid errors that are in the domain of attraction of a stable law. This note discusses their results and provides generalizations to the case of I(q) processes with weakly dependent errors whose distributions are in the domain of attraction of a stable law. General unit root tests are also studied. It is shown that the semiparametric corrections suggested by the author for the finite variance case continue to work when the errors have infinite variance. The limit laws are expressed in terms of ratios of quadratic functionals of a stable process rather than Brownian motion. The correction terms that eliminate nuisance parameter dependencies are random in the limit and involve multiple stochastic integrals that may be written in terms of the quadratic variation of the limiting stable process.Integrated process, unit roots, random walk, time series
Fractional Matrix Calculus and the Distribution of Multivariate Tests
No full textFractional matrix operator methods are introduced as a new tool of distribution theory for use in multivariate analysis and econometrics. Earlier work by the author on this operational calculus is reviewed and to illustrate the use of these methods we give an exact distribution theory for a general class of tests in the multivariate linear model. This distribution theory unifies and generalizes previously known results, including those for the standard F statistic in linear regression, for Hotelling's T^{2} test and for Hotelling's generalized T^{-2} test. We also provide a simple and novel derivation of conventional asymptotic theory as a specialization of exact theory. This approach is extended to generate general formulae for higher order asymptotic expansions. Thus, the results of the paper provide a meaningful unification of conventional asymptotics, higher order asymptotic expansions and exact finite sample distribution theory in this context.Fractional matrix calculus, multivariate tests, exact distribution theory, asymptotic expansions
Descriptive Econometrics for Nonstationary Time Series with Empirical Illustrations
Full text linkRecent work by the author on methods of spatial density analysis for time series data with stochastic trends is reviewed and extended. The methods are illustrated in some empirical applications and simulations. The empirical applications include macroeconomic data on inflation, financial data on exchange rates and political opinion poll data. It is shown how the methods can be used to measure empirical hazard rates for inflation and deflation. Empirical estimates based on historical US data over the last 60 years indicate that the predominant inflation risks are at low levels (2-6%) and low two-digit levels (10-12%), and that there is also a significant risk of deflation around the -1% level.Descriptive statistics, hazard rate, kernel estimate, soujourn time, spatial density, spatial moments, unit root nonstationarity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
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