nep-ecm New Economics Papers
on Econometrics
Issue of 2006‒01‒29
seven papers chosen by
Sune Karlsson
Orebro University

  1. Time Series Factor Analysis with an Application to Measuring Money By Meijer, Erik; Gilbert, Paul D.
  2. Sieve Bootstrap for Strongly Dependent Stationary Processes By George Kapetanios; Zacharias Psaradakis
  3. Back to square one: identification issues in DSGE models By Fabio Canova; Luca Sala
  4. Input Aggregation in Models of Data Envelopment Analysis: A Statistical Test with an Application to Indian Manufacturing By Subhash C. Ray
  5. Parametric Properties of Semi-Nonparametric Distributions, With Applications to Option Valuation By León, Ángel; Mencía, Javier; Sentana, Enrique
  6. The Short-Run Dynamics of Optimal Growth Models with Delays By Collard, Fabrice; Licandro, Omar; Puch, Luis
  7. Similarities and Convergence in G-7 Cycles By Fabio Canova

  1. By: Meijer, Erik; Gilbert, Paul D. (Groningen University)
    Abstract: Time series factor analysis (TSFA) and its associated statistical theory is developed. Unlike dynamic factor analysis (DFA), TSFA obviates the need for explicitly modeling the process dynamics of the underlying phenomena. It also differs from standard factor analysis (FA) in important respects: the factor model has a nontrivial mean structure, the observations are allowed to be dependent over time, and the data does not need to be covariance stationary as long as differenced data satisfies a weak boundedness condition. The effects on the estimation of parameters and prediction of the factors is discussed. The statistical properties of the factor score predictor are studied in a simulation study, both over repeated samples and within a given sample. Some apparent anomalies are found in simulation experiments and explained analytically.
    Date: 2005
  2. By: George Kapetanios (Queen Mary, University of London); Zacharias Psaradakis (Birkbeck College, University of London)
    Abstract: This paper studies the properties of the sieve bootstrap for a class of linear processes which exhibit strong dependence. The sieve bootstrap scheme is based on residual resampling from autoregressive approximations the order of which increases slowly with the sample size. The first-order asymptotic validity of the sieve bootstrap is established in the case of the sample mean and sample autocovariances. The finite-sample properties of the method are also investigated by means of Monte Carlo experiments.
    Keywords: Autoregressive approximation, Linear process, Strong dependence, Sieve bootstrap, Stationary process
    JEL: C10 C22 C50
    Date: 2006–01
  3. By: Fabio Canova; Luca Sala
    Abstract: We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. We show that observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t-statistics and may induce investigators to select false models. We examine whether different objective functions affect identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to detect identification failures and apply them to a state-of-the-art model.
    Keywords: Identification, minimum distance estimators, likelihood function, new keynesian models
    JEL: C1 C3 E3
    Date: 2005–05
  4. By: Subhash C. Ray (University of Connecticut)
    Abstract: A problem frequently encountered in Data Envelopment Analysis (DEA) is that the total number of inputs and outputs included tend to be too many relative to the sample size. One way to counter this problem is to combine several inputs (or outputs) into (meaningful) aggregate variables reducing thereby the dimension of the input (or output) vector. A direct effect of input aggregation is to reduce the number of constraints. This, in its turn, alters the optimal value of the objective function. In this paper, we show how a statistical test proposed by Banker (1993) may be applied to test the validity of a specific way of aggregating several inputs. An empirical application using data from Indian manufacturing for the year 2002-03 is included as an example of the proposed test.
    Keywords: Efficiency distribution, F Tests
    JEL: C61 C43
    Date: 2005–10
  5. By: León, Ángel; Mencía, Javier; Sentana, Enrique
    Abstract: We derive the statistical properties of the SNP densities of Gallant and Nychka (1987). We show that these densities, which are always positive, are more general than the truncated Gram-Charlier expansions of Jondeau and Rockinger (2001), who impose parameter restrictions to ensure positivity. We also use the SNP densities for option valuation. We relate real and risk-neutral measures, obtain closed-form prices for European options, and study the 'Greeks'. We show that SNP densities generate wider option price ranges than the truncated expansions. In an empirical application to S&P 500 index options, we find that the SNP model beats the standard and Practitioner's Black-Scholes formulas, and the truncated expansions.
    Keywords: density expansions; Gram-Charlier; Kurtosis; S&P index options; skewness
    JEL: C16 G13
    Date: 2006–01
  6. By: Collard, Fabrice; Licandro, Omar; Puch, Luis
    Abstract: Differential equations with advanced and delayed time arguments may arise in the optimality conditions of simple growth models with delays. Models with delayed adoption of new technologies, habit formation or learning-by-using lie in this category. In this paper we present new insight on the role of advanced time arguments to mitigate the echo effects induced by lag structures. In so doing we use optimal control theory with delays, and we propose a shooting method to deal with leads and lags in the Euler system associated to dynamic general equilibrium models in continuous time. We implement these methods to solve for the short run dynamics of a neoclassical growth model with a simple time-to-build lag.
    Keywords: DDEs; delay; shooting method; time-to-build
    JEL: C63 E32 O40
    Date: 2006–01
  7. By: Fabio Canova
    Abstract: This paper examines the properties of G-7 cycles using a multicountry Bayesian panel VAR model with time variations, unit specific dynamics and cross country interdependences. We demonstrate the presence of a significant world cycle and show that country specific indicators play a much smaller role. We detect differences across business cycle phases but, apart from an increase in synchronicity in the late 1990s, find little evidence of major structural changes. We also find no evidence of the existence of an Euro area specific cycle or of its emergence in the 1990s.
    Keywords: Business cycle, G7, indicators, Panel Data, Bayesian methods
    JEL: C11 E32
    Date: 2003–02

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