nep-ecm New Economics Papers
on Econometrics
Issue of 2008‒12‒21
seven papers chosen by
Sune Karlsson
Orebro University

  1. Sequential Estimation of Structural Models with a Fixed Point Constraint By Hiroyuki Kasahara; Katsumi Shimotsu
  2. Filtered Log-periodogram Regression of long memory processes By Jan Beran; Yuanhua Feng
  3. Multivariate Quantiles and Multiple-Output Regression Quantiles: From L1 Optimization to Halfspace Depth By Marc Hallin; Davy Paindaveine; Miroslav Siman
  4. Business Cycle Measurement with Semantic Filtering: A Micro Data Approach By Christian Müller; Eva Köberl
  5. On Jarque-Bera normality test By Ciuiu, Daniel
  6. Modelling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture By Colombo, Sergio; Hanley, Nick; Louviere, Jordan
  7. Forecast with judgment and models By Francesca Monti

  1. By: Hiroyuki Kasahara (University of Western Ontario); Katsumi Shimotsu (Queen's University)
    Abstract: This paper considers the estimation problem of structural models for which empirical restrictions are characterized by a fixed point constraint, such as structural dynamic discrete choice models or models of dynamic games. We analyze the conditions under which the nested pseudo-likelihood (NPL) algorithm achieves convergence and derive its convergence rate. We find that the NPL algorithm may not necessarily converge when the fixed point mapping does not have a local contraction property. To address the issue of non-convergence, we propose alternative sequential estimation procedures that can achieve convergence even when the NPL algorithm does not. Upon convergence, some of our proposed estimation algorithms produce more efficient estimators than the NPL estimator.
    Keywords: contraction, dynamic games, nested pseudo likelihood, recursive projection method
    JEL: C13 C14 C63
    Date: 2008–12
  2. By: Jan Beran (Universität Konstanz); Yuanhua Feng
    Abstract: Filtered log-periodogram regression estimation of the fractional differencing parameter d is considered. Asymptotic properties are derived and the effect of filtering on ˆ d is investigated. It is shown that the estimator by Geweke and Porter-Hudak (1983) can be improved significantly using a simple family of filters. The essential improvement is based on a binary decision that is asymptotically correct with probability one. The idea is closely related to the well known technique of pre-whitening.
    Date: 2008–11–01
  3. By: Marc Hallin; Davy Paindaveine; Miroslav Siman
    Abstract: A new multivariate concept of quantile, based on a directional version of Koenker and Bassett’s traditional regression quantiles, is introduced for multivariate location and multiple-output regression problems. In their empirical version, those quantiles can be computed efficiently via linear programming techniques. Consistency, Bahadur representation and asymptotic normality results are established. Most importantly, the contours generated by those quantiles are shown to coincide with the classical halfspace depth contours associated with the name of Tukey. This relation does not only allow for efficient depth contour computations by means of parametric linear programming, but also for transferring from the quantile to the depth universe such asymptotic results as Bahadur representations. Finally, linear programming duality opens the way to promising developments in depth-related multivariate rank-based inference.
    Keywords: Multivariate quantiles, Quantile regression, Halfspace depth
    Date: 2008
  4. By: Christian Müller (Zurich University of Applied Sciences, School of Management and ETH Zurich, KOF Swiss Economic Institute); Eva Köberl (KOF Swiss Economic Institute, ETH Zurich, Switzerland)
    Abstract: In this paper we develop a business cycle measure that can be shown to have excellent ex-ante forecasting properties for GDP growth. For identifying business cycle movements, we use a semantic approach. We infer nine different states of the economy directly from firms’ responses in business tendency surveys. Hence, we can identify the current state of the economy. We therewith measure business cycle fluctuations. One of the main advantages of our methodology is that it is a structural concept based on shock identification and therefore does not need any - often rather arbitrary - statistical filtering. Futhermore, it is not subject to revisions, it is available in real-time and has a publication lead to official GDP data of at least one quarter. It can therefore be used for one quarter ahead forecasting real GDP growth.
    Keywords: business cycle measurement, semantic cross validation, shock identification
    JEL: E32 C4 C5
    Date: 2008–11
  5. By: Ciuiu, Daniel (Technical University of Civil Engineering, Bucharest)
    Date: 2008–09
  6. By: Colombo, Sergio; Hanley, Nick; Louviere, Jordan
    Abstract: Stated choice models based on the random utility framework are becoming increasingly popular in the applied economics literature. The need to account for respondents' preference heterogeneity in such models has motivated researchers in agricultural, environmental, health and transport economics to apply random parameter logit and latent class models. In most of the published literature these models incorporate heterogeneity in preferences through the systematic component of utility. An alternative approach is to investigate heterogeneity through the random component of utility, and covariance heterogeneity models are one means of doing this. In this paper we compare these alternative ways of incorporating preference heterogeneity in stated choice models and evaluate how the selection of approach affects welfare estimates in a given empirical application. We find that a Latent Class approach fits our data best but all the models perform well in terms of out-of-sample predictions. Finally, we discuss what criteria a researcher can use to decide which approach is most appropriate for a given data set.
    Keywords: choice experiments; covariance heterogeneity model; agri-environmental policy; landscape values; latent class model; preference heterogeneity; random parameter logit model; error component models; welfare measure s
    Date: 2008–12
  7. By: Francesca Monti (ECARES, Université Libre de Bruxelles)
    Abstract: This paper proposes a simple and model-consistent method for combining forecasts generated by structural micro-founded models and judgmental forecasts. The method also enables the judgmental forecasts to be interpreted through the lens of the model. We illustrate the proposed methodology with a real-time forecasting exercise, using a simple neo-Keynesian dynamic stochastic general equilibrium model and prediction from the Survey of Professional Forecasters
    Keywords: forecasting, judgment, structural models, Kalman Filter, real time
    JEL: C32 C53
    Date: 2008–12

This nep-ecm issue is ©2008 by Sune Karlsson. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.