Local GMM estimation of time series models with conditional moment restrictions

This paper investigates statistical properties of the local generalized method of moments (LGMM) estimator for some time series models defined by conditional moment restrictions. First, we consider Markov processes with possible conditional heteroskedasticity of unknown forms and establish the consistency, asymptotic normality, and semi-parametric efficiency of the LGMM estimator. Second, we undertake a higher-order asymptotic expansion and demonstrate that the LGMM estimator possesses some appealing bias reduction properties for positively autocorrelated processes. Our analysis of the asymptotic expansion of the LGMM estimator reveals an interesting contrast with the OLS estimator that helps to shed light on the nature of the bias correction performed by the LGMM estimator. The practical importance of these findings is evaluated in terms of a bond and option pricing exercise based on a diffusion model for spot interest rate.     

Market consistent valuations with financial imperfection

In this paper, we study market consistent valuations in imperfect markets. In the first part of the paper, we observe that in an imperfect market one needs to distinguish two type of market consistencies, namely types I and II. We show that while market consistency of type I holds without very strong conditions, market consistency of type II (which in the literature is known as the usual definition of market consistency) is only well defined in perfect markets. This is important since the existing literature on market consistency considers perfect markets where the two market consistencies are equivalent. In the second part of the paper, by introducing a best estimator we find strong connections between hedging and market consistency of either type. We show under very general conditions, the type I and the type II market consistent evaluators are best estimators, and establish a two-step representation for the market consistent risk evaluators. In the third part of the paper, we present several families of market consistent evaluators in imperfect markets.     

Risk premiums and predictive ability of BAX futures

This study provides an in‐depth analysis of risk premiums in the Canadian Bankers' Acceptances futures (BAX) market. The predictive regressions for excess and holding‐period returns on BAX futures lend empirical support to the presence of time‐varying risk premiums especially at longer horizons. Despite the evidence of time variation in the risk premium, however, the unbiasedness of the basis as a predictor of spot returns in forecast efficiency regressions cannot be rejected. The out‐of‐sample forecasts of spot returns demonstrate the excellent predictive ability of models that exploit the restrictions implied by the unbiasedness hypothesis. Overall, our findings support the presence of a slowly moving risk premium and entail important practical implications for measuring monetary policy expectations and portfolio allocation. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark     

The effects of Federal funds rate surprises on S&P 500 volatility and volatility risk premium

In this paper, we examine the effects of expected and surprise components in Federal funds target rate changes on realized and implied volatility. We find that surprise changes in the target rate significantly increase volatility. Consistent with the efficient market hypothesis, our analysis suggests that the expected component of a target rate change as well as the target rate change itself, do not significantly affect volatility. We also show that larger than expected decreases in the Federal funds target rate tend to lower the volatility risk premium.     

A 'long march' perspective on tobacco use in Canada

Abstract.  In this paper we present a model of tobacco demand in Canada, with a view to establishing if price and tax policy on the one hand or educational, regulatory, and demographic influences on the other have been primarily responsible for the substantial drop in consumption since 1980. We address some methodological and econometric issues that have escaped the attention of some analysts to this point. Using data for the period 1972–2000, we find that non‐price developments have had a strong deterrent effect and that the price elasticity of demand is now lower than even the recently obtained low estimates propose. These findings have strong public policy content. JEL Classification: I12, C13, C22     

A MOMENT‐MATCHING METHOD FOR APPROXIMATING VECTOR AUTOREGRESSIVE PROCESSES BY FINITE‐STATE MARKOV CHAINS

This paper proposes a moment‐matching method for approximating vector autoregressions by finite‐state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and tends to outperform the existing methods for approximating multivariate processes over a wide range of the parameter space, especially for highly persistent vector autoregressions with roots near the unit circle. Copyright © 2013 John Wiley & Sons, Ltd.     

Testing For Threshold Nonlinearity in Short-Term Interest Rates

This article addresses some empirical problems in the term structureof interest rates using a threshold autoregressive frameworkwith GARCH errors. This framework provides a parsimonious representationof some stylized features of interest rate data and facilitatesstatistical inference in the presence of high persistence andconditional heteroskedasticity. We propose a bootstrap-basedLM test for linearity in the conditional mean and variance functions.The empirical results indicate a presence of threshold nonlinearitiesin the AR and GARCH representations of the conditional momentsof short-term rate. The explicit modeling of these nonlinearitiesappears to improve the stability properties of the process forspot rate. The article also reports that allowing for thresholdnonlinearities in conditional mean and variance leads to significantforecast improvements. The economic significance of these findingsis evaluated by the term structure implications of the estimatedTAR-GARCH model.     

Asymptotic and bootstrap tests for linearity in a TAR-GARCH(1,1) model with a unit root

This paper derives the limiting distribution of the Lagrange Multiplier (LM) test for threshold nonlinearity in a TAR model with GARCH errors when one of the regimes contains a unit root. It is shown that the asymptotic distribution is nonstandard and depends on nuisance parameters that capture the degree of conditional heteroskedasticity and non-Gaussian nature of the process. We propose a bootstrap procedure for approximating the exact finite-sample distribution of the test for linearity and establish its asymptotic validity.     

Chi-squared tests for evaluation and comparison of asset pricing models

This paper presents a general statistical framework for estimation, testing and comparison of asset pricing models using the unconstrained distance measure of Hansen and Jagannathan (1997). The limiting results cover both linear and nonlinear models that could be correctly specified or misspecified. We propose modified versions of the existing model selection tests and new pivotal specification and model comparison tests with improved finite-sample properties. In addition, we provide formal tests of multiple model comparison. The excellent size and power properties of the proposed tests are demonstrated using simulated data from linear and nonlinear asset pricing models.