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I apologize for the cross-postings, but we are very proud of
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    Michael_Jensen@SSRN.Com or me. ;-) Enjoy....
        
     ____________________________________________________________

             E C O N O M E T R I C S   A B S T R A C T S

                         Working Paper Series

                    Volume 1 Number 1: July 23, 1996


     Publisher:     Economics Research Network (ERN)

                    a division of
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     T  A  B  L  E   of   C  O  N  T  E  N  T  S
     ____________________________________________________________


     "On the Efficiencies of Some Common Quick Estimators"

          MARSHALL FREIMER       University of Rochester
          ALAN D. HUTSON         University of Rochester
          GOVIND S. MUDHOLKAR    University of Rochester


     "Regime-Switching Models: A Guide to the Bank of Canada
      Gauss Procedures"

          SIMON VAN NORDEN       Bank of Canada
          ROBERT VIGFUSSON       Bank of Canada


     "Measuring Science: An Exploration"

          JAMES ADAMS            University of Florida and NBER
          ZVI GRILICHES          Harvard University and NBER


     "Error Bands for Impulse Responses"

          CHRISTOPHER A. SIMS    Yale University
          TAO ZHA                Federal Reserve Bank of Atlanta

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     W O R K I N G  Paper Abstracts


     "On the Efficiencies of Some Common Quick Estimators"

      BY: MARSHALL FREIMER
            University of Rochester
          ALAN D. HUTSON
            University of Rochester
          GOVIND S. MUDHOLKAR
            University of Rochester

          Paper ID: Simon School Working Paper QM 95-01
          Date:     December 1995

          Contact:  Marshall Freimer
          E-Mail:   MAILTO:Friemer@Mail.ssb.rochester.edu
          Postal:   William E. Simon Graduate School of Business
                    Administration, University of Rochester,
                    Rochester, NY  14627
          Phone:    (716) 275-3013
          Fax:      Not Available
          ERN Ref:  ECON:WPS96-101

     PAPER REQUESTS:  Please send an e-mail to:
     MAILTO:McWilliams@mail.ssb.rochester.edu   Or write
     to the Office of Public Affairs/Working Papers Office,
     William E. Simon Graduate School of Business Administration,
     University of Rochester, 2-352 Carol G. Simon Hall,
     Rochester, NY  14627.  Phone: (716) 275-3736, Fax: (716)
     275-9331.


     The quick estimators of location and scale have broad
     applications and are widely used. For a variety of symmetric
     populations we obtain the qualities and the weights for
     which the asymptotic variances of the quick estimators are
     minimum. These are then used to obtain the asymptotic
     relative efficiencies of the commonly used estimators such
     as trimean, gastwirth, median, midrange, and interquartile
     range with respect to the optimal quick estimators in order
     to determine a choice among them and to check whether they
     are unacceptably poor. In the process it is seen that the
     interquartile range is the optimal quick estimator of scale
     for Cauchy populations; but the interdecile range is in
     general preferable. Also the optimal estimator of the
     location for the logistic distribution puts weights 0.3 on
     each of the two quartiles and 0.4 on the median. It is shown
     that for the symmetric distributions, such as the beta and
     Tukey-lambda with > 0, which have finite support and short
     tails, i.e., the tail exponents (Parzen, 1979) satisfy < 1,
     the midrange and the range are the optimal quick estimators
     of location and scale respectively if < 1/2. The class of
     such distributions include the distributions with high
     discontinuous tails, e.g., Tukey-labmda with >1, as well as
     some distributions with p.d.f.'s going to zero at the ends
     of the finite support, such as Tukey-lambda with 1/2 < <1.
     As a byproduct an interesting tail correspondence between
     beta and Tukey-lambda distributions is seen.

     JEL Classification: C1
     __________________


     "Regime-Switching Models: A Guide to the Bank of Canada
      Gauss Procedures"

      BY: SIMON VAN NORDEN
            Bank of Canada
          ROBERT VIGFUSSON
            Bank of Canada

          Paper ID: Bank of Canada WP 96-3
          Date:     February 1996

          Contact:  Robert Vigfusson
           E-mail:  MAILTO:rvigfusson@bank-banque-canada.ca
           Postal:  International Department, Bank of Canada
                    Ottawa, Ontario  CANADA K1A 0G9
           Phone:   (613) 782-8597
           Fax:     (613) 782-7658
           Co-Auth: MAILTO:svannorden@bank-banque-canada.ca
           ERN Ref: ECON:WPS96-102

     PAPER REQUESTS: Printed copies: Publications Distribution,
     Bank of Canada, 234 Wellington Street, Ottawa, Ontario,
     CANADA K1A 0G9. PHONE: (613) 782-8248. FAX: (613) 782-8874.
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     This paper is a user's guide to a set of Gauss procedures
     developed at the Bank of Canada for estimating
     regime-switching models. The procedures can estimate
     relatively quickly a wide variety of switching models and so
     should prove useful to the applied researcher. Sample
     program listings are included.

     JEL Classification:  C87
     __________________


     "Measuring Science: An Exploration"

      BY: JAMES ADAMS
            University of Florida and NBER
          ZVI GRILICHES
            Harvard University and NBER

          Paper ID: NBER Working Paper 5478
          Date:     March 1996

          Contact:  Zvi Griliches
          E-Mail:   MAILTO:Grilic@kuznets.harvard.edu
          Postal:   Department of Economics, Harvard University,
                    Cambridge, MA 02138
          Phone:    (617) 495-2181
          Fax:      Not Available
          ERN Ref:  ECON:WPS96-103

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     This paper examines the available U.S. data on academic R&D
     expenditures and the number of papers published and the
     number of citations to these papers as possible measures of
     "output" of this enterprise.  We look at these numbers for
     science and engineering as a whole, for 5 selected major
     fields, and at the individual university-field level.  The
     published data in Science and Engineering Indicators imply
     sharply diminishing returns to academic R&D using published
     papers as an "output" measure.  These data are quite
     problematic.  Using a newer set of data on papers and
     citations, based on an "expanding" set of journals and the
     newly released BEA R&D deflators, changes the picture
     drastically, eliminating the appearance of diminishing
     returns but raising the question of why the input prices of
     academic R&D are rising so much faster than either the GDP
     deflator or the implicit R&D deflator in industry.  A
     production function analysis of such data at the individual
     field-university level follows.  It indicates significant
     diminishing returns to "own" R&D, with the R&D coefficients
     hovering around 0.5 for estimates with paper numbers as the
     dependent variable and around 0.6 if total citations are
     used as the dependent variable.  When we substitute
     scientists and engineers in place of R&D as the right hand
     side variables, the coefficient on papers rises from 0.5 to
     0.8, and the coefficient on citations rises from 0.6 to 0.9,
     indicating systematic measurement problems with R&D as the
     sole input into the production of scientific output.  But
     allowing for individual university-field effects drives
     these numbers down significantly below unity.  Since in the
     aggregate both paper numbers and citations are growing as
     fast or faster than R&D, this finding can be interpreted as
     leaving a major, yet unmeasured role, for the contribution
     of spillovers from other fields, other universities, and
     other countries.

     JEL Classification: C1
     __________________


     "Error Bands for Impulse Responses"

      BY:CHRISTOPHER A. SIMS
           Yale University
         TAO ZHA
           Federal Reserve Bank of Atlanta

          Paper ID: Federal Reserve Bank of Atlanta WP 95-6
          Date:     Undated

          Contact:  Tao Zha
          E-Mail:   MAILTO:tzha@frbatlanta.org
          Postal:   Research Department, Federal Reserve Bank
                    of Atlanta, 104 Marietta Street, NW,
                    Atlanta GA  30303
          Phone:    (404) 521-8353
          Fax:      (404) 521-8956
          ERN Ref:  ECON:WPS96-104

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     Marietta Street, NW, Atlanta, GA 30303 Phone: (404) 521-8020
     Fax: (404) 521-8050.


     We examine the theory and behavior in practice of Bayesian
     and bootstrap methods for generating error bands on impulse
     responses in dynamic linear models. The Bayesian intervals
     have a firmer theoretical foundation in small samples, are
     easier to compute, and are about as good in small samples by
     classical criteria as are the best bootstrap intervals.
     Bootstrap intervals based directly on the simulated small-
     sample distribution of an estimator, without bias
     correction, perform very badly. We show that a method that
     has been used to extend to the overidentified case standard
     algorithms for Bayesian intervals in reduced form models is
     incorrect, and we show how to obtain correct Bayesian
     intervals for this case.

     JEL Classification: C1

     ____________________________________________________________

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     ECONOMETRICS ABSTRACTS


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