nep-ecm New Economics Papers
on Econometrics
Issue of 2005‒04‒03
ten papers chosen by
Sune Karlsson
Orebro University

  1. A Panel Unit Root Test with Good Size and Power in Small Samples By Claude Lopez
  3. Exactly Distribution-free Inference in Instrumental Variables Regression with Possibly Weak Instruments By Donald W.K. Andrews; Vadim Marmer
  4. Estimating the Stochastic Discount Factor without a Utility Function By Fabio Araujo; João Victor Issler; Marcelo Fernandes
  5. Univariate nonlinear time series models By Terasvirta, Timo
  6. Transition Variables in the Markov-switching Model: Some Small Sample Properties By Erlandsson, Ulf
  7. Rating Forecasts for Television Programs By Denny Meyer; Rob J. Hyndman
  8. On the Long-Run Variance Ratio Test for a Unit Root By Ye Cai; Mototsugu Shintani
  9. Reducing Bias of MLE in a Dynamic Panel Model By Jinyong Hahn; Hyungsik Roger Moon
  10. Convergence towards a Steady State Distribution By Don J Webber; Paul White

  1. By: Claude Lopez
    Abstract: This paper offers a panel extension of the unit root test proposed by Elliott, Rothenberg and Stock (1996). More specifically, the proposed approach allows for heterogeneous serial and contemporaneous correlation, while fixing the rate of convergence to be homogeneous across series. The new test demonstrates significantly better finite sample-power properties than the Levin, Lin and Chu (2002) or the Moon, Perron and Phillips (2003) tests, especially for highly persistent series. An application to the real exchange rate convergence illustrates the impact of such improvements. Analyzing the post Bretton Woods period, the new test provides strong and reliable evidence of Purchasing Power Parity among industrialized countries.
    Date: 2005
  2. By: Rebeca Albacete; Antoni Espasa
    Abstract: Economic agents and financial authorities require frequent updates to a path of accurate inflation forecasts and need forecasts to include an explanation of the factors by which they are determined. This paper studies how to approach this need, developing a method for analysing inflation in the euro area, measured according to HICP. Time series models using the most recent information on prices and an important functional and geographically disaggregation can provide monthly forecasts which are reasonably accurate, but they do not provide an explanation of the factors by which the forecast is determined. In this respect, it is important to enlarge the data set used considering explanatory variables and build congruent econometric models including variables which, following previous works by D. Hendry, capture disequilibria on different markets, goods and services, labour, monetary and international. The final result of this work shows that combining the forecasts from a monthly time series vector model, constructed on price subindexes from a disaggregation of the HICP by countries and sectors, with the forecasts derived from a quarterly econometric vector model on aggregate inflation and other economic variables, very accurate forecasts are obtained. Both vector models are specified including empirical cointegration restrictions, which in the first case capture the constrains necessary present between the trends of the price subindexes and in the second approximate the long-run restrictions postulated by economic theory.
    Date: 2005–01
  3. By: Donald W.K. Andrews (Cowles Foundation, Yale University); Vadim Marmer
    Abstract: This paper introduces a rank-based test for the instrumental variables regression model that dominates the Anderson-Rubin test in terms of finite sample size and asymptotic power in certain circumstances. The test has correct size for any distribution of the errors with weak or strong instruments. The test has noticeably higher power than the Anderson-Rubin test when the error distribution has thick tails and comparable power otherwise. Like the Anderson-Rubin test, the rank tests considered here perform best, relative to other available tests, in exactly-identified models.
    Keywords: Aligned ranks, Anderson-Rubin statistic, categorical covariates, exact size, normal scores, rank test, weak instruments, Wilcoxon scores
    JEL: C13 C30
    Date: 2005–03
  4. By: Fabio Araujo; João Victor Issler (EPGE/FGV); Marcelo Fernandes (EPGE/FGV)
    Date: 2005–03
  5. By: Terasvirta, Timo (Dept. of Economic Statistics, Stockholm School of Economics)
    Abstract: In this paper developments in the analysis of univariate nonlinear time series are considered. First a number of commonly used nonlinear models are presented. The next section is devoted to methods of testing linearity, which is an important part of nonlinear model building. Techniques of modelling nonlinear series within a predetermined family of models are discussed thereafter. Forecasting with nonlinear models also has its own section. A brief set of final remarks closes the chapter.
    Keywords: Hidden Markov model; linearity test; neural network; nonlinear model building; threshold autoregressive model; smooth transition autoregressive model
    JEL: C22 C52
    Date: 2005–03–29
  6. By: Erlandsson, Ulf (Department of Economics, Lund University)
    Abstract: This paper researches small-sample properties of the Markov-switching model with time-varying transition probabilities. By means of simulation, it is shown that the likelihood ratio statistic is over-sized for sample sizes relevant in many empirical applications. The number of regime switches occurring in the sample rather than the total number of observations is central to the magnitude of the distortion, with other factors such a persistence in transition equation variables and the precision at which states are inferred being influential on size. In an application to possible predictors of switches to recessions in U.S. data, it is shown that critical values for the likelihood ratio statistic need to be adjusted far upwards to reflect true confidence levels.
    Keywords: regime switching; transition probability; small-sample
    JEL: C13 C32 E32
    Date: 2005–03–21
  7. By: Denny Meyer; Rob J. Hyndman
    Abstract: This paper investigates the effect of aggregation and non-linearity in relation to television rating forecasts. Several linear models for aggregated and disaggregated television viewing have appeared in the literature. The current analysis extends this work using an empirical approach. We compare the accuracy of population rating models, segment rating models and individual viewing behaviour models. Linear and non-linear models are fitted using regression, decision trees and neural networks, with a two-stage procedure being used to model network choice and viewing time for the individual viewing behaviour model. The most accurate forecast results are obtained from the non-linear segment rating models.
    Keywords: Decision Trees, Disaggregation, Discrete Choice Models, Neural Networks, Rating Benchmarks
    JEL: C53 C51 C35 M37
    Date: 2005–03
  8. By: Ye Cai (Graduate Student, Department of Economics, Vanderbilt University); Mototsugu Shintani (Department of Economics, Vanderbilt University)
    Abstract: This paper investigates the effects of consistent and inconsistent long-run variance estimation on a unit root test based on the generalization of the von Neumann ratio. The results from the Monte Carlo experiments suggest that the tests based on an inconsistent estimator have less size distortion and more stability of size across different autocorrelation specifications as compared to the tests based on a consistent estimator. This improvement in size property, however, comes at the cost of a loss in power. The finite sample power, as well as the local asymptotic power, of the tests with an inconsistent estimator is shown to be much lower than that of conventional tests. This finding resembles the case of the autocorrelation robust test in the standard regression context. The paper also points out that combining consistent and inconsistent estimators in the long-run variance ratio test for a unit root is one possibility of balancing the size and power.
    Keywords: Bandwidth, local asymptotic power, von Neumann ratio
    JEL: C12 C22
    Date: 2005–03
  9. By: Jinyong Hahn; Hyungsik Roger Moon
    Abstract: This paper investigates a simple dynamic linear panel regression model with both fixed effects and time effects. Using "large n and large T " asymptotics, we approximate the distribution of the fixed effect estimator of the autoregressive parameter in the dynamic linear panel model and derive its asymptotic bias. We find that the same higher order bias correction approach proposed by Hahn and Kuersteiner (2002) can be applied to the dynamic linear panel model even when time specifc effects are present.
    Date: 2004–12
  10. By: Don J Webber (School of Economics, University of the West of England); Paul White (Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England)
    Abstract: The convergence literature frequently presupposes some unidentified steady state distribution. This paper presents a new method to identify the presence and rate of convergence to a steady state distribution. The method is illustrated with application to UK regional male wages.
    Keywords: Convergence; Steady state; Average UK regional male wages
    JEL: C1 O4
    Date: 2005–01

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