nep-ecm New Economics Papers
on Econometrics
Issue of 2006‒02‒19
six papers chosen by
Sune Karlsson
Orebro University
  1. New Improved Tests for Cointegration with Structural Breaks By Westerlund, Joakim; Edgerton , David
  2. Bootstrapping Systems Cointegration Tests with a Prior Adjustment for Deterministic Terms By Carsten Trenkler
  3. ON THE SMALL SAMPLE PROPERTIES OF DICKEY FULLER AND MAXIMUM LIKELIHOOD UNIT ROOT TESTS ON DISCRETE-SAMPLED SHORT-TERM INTEREST RATES By Paulo M.M. Rodrigues; Antonio Rubia
  4. COUNTS WITH AN ENDOGENOUS BINARY REGRESSOR: A SERIES EXPANSION APPROACH By Andrés Romeu; Marcos Vera-Hernández
  5. Generalized Empirical Likelihood Tests in Time Series Models With Potential Identification Failure (with R.J.Smith), August 2003, this version April 2005 By Patrik Guggenberger
  6. The limit of finite sample size and a problem with subsampling (joint with Donald Andrews), June 2005, this version December 2005 By Patrik Guggenberger
  1. By: Westerlund, Joakim (Department of Economics, Lund University); Edgerton , David (Department of Economics, Lund University)
    Abstract: This paper proposes Lagrange multiplier based tests for the null hypothesis of no cointegration. The tests are general enough to allow for heteroskedastic and serially correlated errors, deterministic trends, and a structural break of unknown timing in both the intercept and slope. The limiting distributions of the test statistics are derived, and are found to be invariant not only with respect to trend and structural break, but also with respect to the regressors. A small Monte Carlo study is also con- ducted to investigate the small-sample properties of the tests. The results reveal that the tests have small size distortions and good power relative to other tests.
    Keywords: Cointegration Test; Lagrange Multiplier Principle; Structural Break; Deterministic Trend.
    JEL: C12 C32 C33
    Date: 2006–01–14
    URL: http://d.repec.org/n?u=RePEc:hhs:lunewp:2006_003&r=ecm
  2. By: Carsten Trenkler
    Abstract: In this paper we analyse bootstrap procedures for systems cointegration tests with a prior adjustment for deterministic terms suggested by Saikkonen & Lütkepohl (2000b) and Saikkonen, Lütkepohl & Trenkler (2006). The asymptotic properties of the bootstrap test procedures are derived and their small sample properties are studied. The simulation study also considers the standard asymptotic test versions and the Johansen cointegration test for comparison.
    Keywords: Bootstrap, Systems cointegration tests, VEC models
    JEL: C12 C13 C15 C32
    Date: 2006–02
    URL: http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2006-012&r=ecm
  3. By: Paulo M.M. Rodrigues (University of Algarve); Antonio Rubia (Universidad de Alicante)
    Abstract: Testing for unit roots in short-term interest rates plays a key role in the empirical modelling of these series. It is widely assumed that the volatility of interest rates follows some time-varying function which is dependent of the level of the series. This may cause distortions in the performance of conventional tests for unit root nonstationarity since these are typically derived under the assumption of homoskedasticity. Given the relative unfamiliarity on the issue, we conducted an extensive Monte Carlo investigation in order to assess the performance of the DF unit root tests, and examined the effects on the limiting distributions of test procedures (t- and likelihood ratio tests) based on maximum likelihood estimation of models for short-term rates with a linear drift.
    Keywords: Unit root, interest rates, CKLS model.
    JEL: C12 C15 C52 E43
    Date: 2004–03
    URL: http://d.repec.org/n?u=RePEc:ivi:wpasad:2004-11&r=ecm
  4. By: Andrés Romeu (Universidad de Alicante); Marcos Vera-Hernández (Institute for Fiscal Studies)
    Abstract: We propose an estimator for count data regression models where a binary regressor is endogenously determined. This estimator departs from previous approaches by using a flexible form for the conditional probability function of the counts. Using a Monte Carlo experiment we show that our estimator improves the fit and provides a more reliable estimate of the impact of regressors on the count when compared to alternatives which do restrict the mean to be linear-exponential. In an application to the number of trips by households in the US, we find that the estimate of the treatment effect obtained is considerably different from the one obtained under a linear-exponential mean specification.
    Keywords: Count data, Polynominal Poisson Expansions, Flexible Functional Form.
    JEL: C35 C52
    Date: 2004–09
    URL: http://d.repec.org/n?u=RePEc:ivi:wpasad:2004-36&r=ecm
  5. By: Patrik Guggenberger
    Date: 2005–04–10
    URL: http://d.repec.org/n?u=RePEc:cla:uclaol:357&r=ecm
  6. By: Patrik Guggenberger
    Date: 2006–01–09
    URL: http://d.repec.org/n?u=RePEc:cla:uclaol:372&r=ecm
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