Showing papers in "Journal of Econometrics in 2000"

TL;DR: In this paper, the authors examined two alternate explanations: stochastic volatility and jumps, and fitted them to S&P 500 futures options data over 1988-1993 and found that the stochassy volatility model requires extreme parameters (e.g., high volatility of volatility) that are implausible given the time series properties of option prices.

TL;DR: In the 50th anniversary of Neyman and Scott's Econometrica paper defining the incidental parameter problem, the authors surveys the history both of the paper and of the problem in the statistics and econometrics literature.

TL;DR: In this article, the problem of efficient estimation of vector error correction models containing exogenous I(1) variables is examined and the asymptotic distributions of the (log-)likelihood ratio statistics for testing cointegrating rank are derived under different intercepts and trend specifications and their respective critical values are tabulated.

TL;DR: In this paper, a nonparametric value-at-risk (VaR) measure is proposed that incorporates economic valuation according to the state-price density associated with the underlying price processes.

TL;DR: In this article, the authors derive the large sample distributions of the test statistics allowing for structural change in the marginal distribution of the regressors, including structural shifts, polynomial trends, and exogenous stochastic trends.

TL;DR: The Lagrange Multiplier (LM) test as mentioned in this paper examines the restrictions imposed on a model which encompasses the constant-correlation multivariate GARCH model, and is computationally convenient.

TL;DR: The authors provided estimators of discrete choice models, including binary, ordered, and multinomial response (choice) models, with root N consistent and asymptotically normal.

TL;DR: In this article, the moments for a range of Markov switching models are derived and the patterns of volatility, skewness and kurtosis that these models can produce as a function of the transition probabilities and parameters of the underlying state densities entering the switching process.

TL;DR: In this article, the authors present a new prior and corresponding algorithm for Bayesian analysis of the multinomial probit model, which places a prior directly on the identified parameter space.

TL;DR: In this article, the authors show that differences among alternative models usually may not surface when applied to short-term options, but do so when applying to long-term contracts, and they find that short-and longterm contracts indeed contain different information.

TL;DR: This article examined the ability of regime-switching models to capture the dynamics of foreign exchange rates and found that a regime switching option valuation model with independent shifts in mean and variance exhibits a closer fit and more accurate variance forecasts than a range of other models.

TL;DR: In this paper, the authors consider a general linear process that includes an ARMA process as a special one and derive a statistic for testing the occurrence of such a change and investigate asymptotic behavior of it.

TL;DR: In this article, the authors present analytical, empirical and simulation results concerning inference about the moments of nondifferentiable functions of out-of-sample forecasts and forecast errors, and special attention is given to the measurement of a model's predictive ability using the test of equal mean absolute error.

TL;DR: The authors proposed and implemented a coherent statistical framework for combining theoretical and empirical models of macroeconomic activity, which enables the formal yet probabilistic incorporation of uncertainty regarding the parameterization of theoretical models.

TL;DR: In this paper, the authors examine the behavior of the nonparametric maximum likelihood estimator (NPMLE) for a discrete duration model with unobserved heterogeneity and unknown duration dependence, and they find that a non-parametric specification of either the duration dependence or the other feature of the hazard is known to be absent, leads to estimators that are well behaved even in modestly sized samples.

TL;DR: In this article, a generalized option pricing model with a functional shape similar to the usual Black-Scholes formula is proposed. But instead of setting up a learning network mapping the ratio St/K and the time to maturity directly into the derivative price, the pricing function is broken down into two parts, one controlled by the ratio S/K, the other one by a function of time-to-maturity.

TL;DR: In this paper, the conditionally independent private information (CIPI) model is considered in the context of OCS wildcat auctions and the distributions of the common component and the idiosyncratic component are identified from observed bids in the CIPV case.

TL;DR: It is shown that h-block cross-validation is inconsistent in the sense of Shao (1993), and therefore is not asymptotically optimal, and a modification of the h- block method, dubbed ‘hv-block’ cross- validation, is proposed which is asymPTOTically optimal.

TL;DR: The main ideas are given specific form through consideration of the treatment choice problem of a planner who observes the treatments and outcomes realized in a classical randomized experiment, but who does not observe the covariates of the experimental subjects.

TL;DR: This paper used data from the Panel Survey of Income Dynamics (PSID) to address a number of questions about life cycle earnings mobility and developed a dynamic reduced form model of earnings and marital status that is nonstationary over the life cycle.

TL;DR: The authors developed a Markov chain Monte Carlo method for a linear regression model with an ARMA( p, q )-GARCH( r, s ) error, using the Metropolis-Hastings algorithm.

TL;DR: In this article, it is argued that recent developments in interior point methods for linear programming together with some new preprocessing ideas make it possible to compute quantile regressions as quickly as least-squares regressions throughout the entire range of problem sizes encountered in econometrics.

TL;DR: This article showed that the quality of the inference concerning long-memory dependencies in the conditional variance is intimately related to the sampling frequency of the data and proposed new estimators that succinctly aggregate the information in higher frequency returns.

TL;DR: In this article, a family of rational square-wave filters is described which enable designated frequency ranges to be selected or rejected, and their use is advocated in preference to other filters which are commonly used in quantitative economic analysis.

TL;DR: In this paper, the authors extended the theoretical analysis of the spurious regression and spurious detrending from the usual I(1) processes to the long memory fractionally integrated processes.

TL;DR: In this paper, the structural parameters of speculative storage were estimated using three simulation-based estimators and the results showed that the simulation estimators are less efficient than pseudo-maximum likelihood (PMLE) in a mean-squared sense.

TL;DR: The authors showed that the extra variation due to the presence of these estimated parameters in the weight matrix accounts for much of the difference between the finite sample and the asymptotic variance of the two-step generalised method of moments estimator that utilises moment conditions that are linear in the parameters.

TL;DR: In this paper, the authors proposed simple resampling methods by convexfying Powell's approach in the resample stage, which can be implemented by efficient linear programming and showed that the methods are reliable even with moderate sample sizes.

TL;DR: In this paper, modified tests for the cointegrating rank of a vector autoregressive (VAR) process have been considered which allow for deterministic linear trends in the data generation process (DGP).

TL;DR: In this paper, the authors derived a regime switching process that exhibits long memory and a heavy-tailed duration distribution, and used the EMM chi-squared statistic to fit the regime switching stochastic volatility model.