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Book part
Publication date: 10 April 2019

Antonio Cosma, Andreï V. Kostyrka and Gautam Tripathi

We show how to use a smoothed empirical likelihood approach to conduct efficient semiparametric inference in models characterized as conditional moment equalities when…

Abstract

We show how to use a smoothed empirical likelihood approach to conduct efficient semiparametric inference in models characterized as conditional moment equalities when data are collected by variable probability sampling. Results from a simulation experiment suggest that the smoothed empirical likelihood based estimator can estimate the model parameters very well in small to moderately sized stratified samples.

Book part
Publication date: 19 November 2014

Benjamin J. Gillen, Matthew Shum and Hyungsik Roger Moon

Structural models of demand founded on the classic work of Berry, Levinsohn, and Pakes (1995) link variation in aggregate market shares for a product to the influence of…

Abstract

Structural models of demand founded on the classic work of Berry, Levinsohn, and Pakes (1995) link variation in aggregate market shares for a product to the influence of product attributes on heterogeneous consumer tastes. We consider implementing these models in settings with complicated products where consumer preferences for product attributes are sparse, that is, where a small proportion of a high-dimensional product characteristics influence consumer tastes. We propose a multistep estimator to efficiently perform uniform inference. Our estimator employs a penalized pre-estimation model specification stage to consistently estimate nonlinear features of the BLP model. We then perform selection via a Triple-LASSO for explanatory controls, treatment selection controls, and instrument selection. After selecting variables, we use an unpenalized GMM estimator for inference. Monte Carlo simulations verify the performance of these estimators.

Book part
Publication date: 19 December 2012

Francesco Bravo, Juan Carlos Escanciano and Taisuke Otsu

This chapter proposes a simple, fairly general, test for global identification of unconditional moment restrictions implied from point-identified conditional moment…

Abstract

This chapter proposes a simple, fairly general, test for global identification of unconditional moment restrictions implied from point-identified conditional moment restrictions. The test is a Hausman-type test based on the Hausdorff distance between an estimator that is consistent even under global identification failure of the unconditional moment restrictions, and an estimator of the identified set of the unconditional moment restrictions. The proposed test has a χ2 limiting distribution and is also able to detect weak identification. Some Monte Carlo experiments show that the proposed test has competitive finite sample properties already for moderate sample sizes.

Book part
Publication date: 21 November 2014

John Chao, Myungsup Kim and Donggyu Sul

This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial…

Abstract

This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial condition. The new estimators we introduce are weighted averages of the well-known first difference (FD) GMM/IV estimator and the pooled ordinary least squares (POLS) estimator. The proposed procedure seeks to exploit the differing strengths of the FD GMM/IV estimator relative to the pooled OLS estimator. In particular, the latter is inconsistent in the stationary case but is consistent and asymptotically normal with a faster rate of convergence than the former when the underlying panel autoregressive process has a unit root. By averaging the two estimators in an appropriate way, we are able to construct a class of estimators which are consistent and asymptotically standard normal, when suitably standardized, in both the stationary and the unit root case. The results of our simulation study also show that our proposed estimator has favorable finite sample properties when compared to a number of existing estimators.

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

Keywords

Book part
Publication date: 15 April 2020

Yonghui Zhang and Qiankun Zhou

It is shown in the literature that the Arellano–Bond type generalized method of moments (GMM) of dynamic panel models is asymptotically biased (e.g., Hsiao & Zhang, 2015;…

Abstract

It is shown in the literature that the Arellano–Bond type generalized method of moments (GMM) of dynamic panel models is asymptotically biased (e.g., Hsiao & Zhang, 2015; Hsiao & Zhou, 2017). To correct the asymptotical bias of Arellano–Bond GMM, the authors suggest to use the jackknife instrumental variables estimation (JIVE) and also show that the JIVE of Arellano–Bond GMM is indeed asymptotically unbiased. Monte Carlo studies are conducted to compare the performance of the JIVE as well as Arellano–Bond GMM for linear dynamic panels. The authors demonstrate that the reliability of statistical inference depends critically on whether an estimator is asymptotically unbiased or not.

Book part
Publication date: 30 August 2019

Md. Nazmul Ahsan and Jean-Marie Dufour

Statistical inference (estimation and testing) for the stochastic volatility (SV) model Taylor (1982, 1986) is challenging, especially likelihood-based methods which are…

Abstract

Statistical inference (estimation and testing) for the stochastic volatility (SV) model Taylor (1982, 1986) is challenging, especially likelihood-based methods which are difficult to apply due to the presence of latent variables. The existing methods are either computationally costly and/or inefficient. In this paper, we propose computationally simple estimators for the SV model, which are at the same time highly efficient. The proposed class of estimators uses a small number of moment equations derived from an ARMA representation associated with the SV model, along with the possibility of using “winsorization” to improve stability and efficiency. We call these ARMA-SV estimators. Closed-form expressions for ARMA-SV estimators are obtained, and no numerical optimization procedure or choice of initial parameter values is required. The asymptotic distributional theory of the proposed estimators is studied. Due to their computational simplicity, the ARMA-SV estimators allow one to make reliable – even exact – simulation-based inference, through the application of Monte Carlo (MC) test or bootstrap methods. We compare them in a simulation experiment with a wide array of alternative estimation methods, in terms of bias, root mean square error and computation time. In addition to confirming the enormous computational advantage of the proposed estimators, the results show that ARMA-SV estimators match (or exceed) alternative estimators in terms of precision, including the widely used Bayesian estimator. The proposed methods are applied to daily observations on the returns for three major stock prices (Coca-Cola, Walmart, Ford) and the S&P Composite Price Index (2000–2017). The results confirm the presence of stochastic volatility with strong persistence.

Details

Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A
Type: Book
ISBN: 978-1-78973-241-2

Keywords

Book part
Publication date: 13 February 2001

Richard Blundell, Stephen Bond and Frank Windmeijer

This chapter reviews developments to improve on the poor performance of the standard GMM estimator for highly autoregressive panel series. It considers the use of the…

Abstract

This chapter reviews developments to improve on the poor performance of the standard GMM estimator for highly autoregressive panel series. It considers the use of the ‘system’ GMM estimator that relies on relatively mild restrictions on the initial condition process. This system GMM estimator encompasses the GMM estimator based on the non-linear moment conditions available in the dynamic error components model and has substantial asymptotic efficiency gains. Simulations, that include weakly exogenous covariates, find large finite sample biases and very low precision for the standard first differenced estimator. The use of the system GMM estimator not only greatly improves the precision but also greatly reduces the finite sample bias. An application to panel production function data for the U.S. is provided and confirms these theoretical and experimental findings.

Details

Nonstationary Panels, Panel Cointegration, and Dynamic Panels
Type: Book
ISBN: 978-1-84950-065-4

Article
Publication date: 27 September 2011

Isao Ishida, Michael McAleer and Kosuke Oya

The purpose of this paper is to propose a new method for estimating continuous‐time stochastic volatility (SV) models for the S&P 500 stock index process using intraday…

Abstract

Purpose

The purpose of this paper is to propose a new method for estimating continuous‐time stochastic volatility (SV) models for the S&P 500 stock index process using intraday high‐frequency observations of both the S&P 500 index and the Chicago Board Options Exchange (CBOE) implied (or expected) volatility index (VIX).

Design/methodology/approach

A primary purpose of the paper is to provide a framework for using intraday high‐frequency data of both the indices' estimates, in particular, for improving the estimation accuracy of the leverage parameter, that is, the correlation between the two Brownian motions driving the diffusive components of the price process and its spot variance process, respectively.

Findings

Finite sample simulation results show that the proposed estimator delivers more accurate estimates of the leverage parameter than do existing methods.

Research limitations/implications

The focus of the paper is on the Heston and non‐Heston leverage parameters.

Practical implications

Finite sample simulation results show that the proposed estimator delivers more accurate estimates of the leverage parameter than do existing methods.

Social implications

The research findings are important for the analysis of ultra high‐frequency financial data.

Originality/value

The paper provides a framework for using intraday high‐frequency data of both indices' estimates, in particular, for improving the estimation accuracy of the leverage parameter, that is, the correlation between the two Brownian motions driving the diffusive components of the price process and its spot variance process, respectively.

Details

Managerial Finance, vol. 37 no. 11
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 28 July 2020

Van Bon Nguyen

The paper attempts to empirically examine the difference in the foreign direct investment (FDI) – private investment relationship between developed and developing…

Abstract

Purpose

The paper attempts to empirically examine the difference in the foreign direct investment (FDI) – private investment relationship between developed and developing countries over the period 2000–2013.

Design/methodology/approach

The paper uses the two-step GMM Arellano-Bond estimators (both system and difference) for a group of 25 developed countries and a group of 72 developing ones. Then, the PMG estimator is employed to check the robustness of estimates.

Findings

First, there is a clear difference in the FDI – private investment relationship between developed countries and developing ones. Second, governance environment, economic growth and trade openness stimulate private investment. Third, the effect of tax revenue on private investment in developed countries is completely opposite to that in developing ones.

Originality/value

The paper is the first to provide empirical evidence to confirm the dependence of FDI – private investment relationship on governance environment. In fact, contrary to the view (arguments) in Morrissey and Udomkerdmongkol (2012), the paper indicates that FDI crowds out private investment in developed countries (good governance environment), but crowds in developing countries (poor governance environment).

Details

Journal of Economic Studies, vol. 48 no. 4
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 20 February 2009

Zélia Maria Silva Serrasqueiro and Márcia Cristina Rêgo Rogão

This study aims to evaluate the impact of listed Portuguese companies' specific determinants on adjustment of actual debt towards target debt ratio. The specific…

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Abstract

Purpose

This study aims to evaluate the impact of listed Portuguese companies' specific determinants on adjustment of actual debt towards target debt ratio. The specific determinants on adjustment of actual debt towards target debt ratio that we consider are: asset tangibility, size, profitability and market to book ratio.

Design/methodology/approach

Dynamic panel estimators are used to determine adjustment of the actual level of debt towards optimal level of debt, revealing the level of transaction costs borne by companies. OLS regressions are also used, in order to estimate the impacts of companies' specific determinants on debt adjustment.

Findings

The results suggest that transaction costs are relevant in listed Portuguese companies' access to debt. Tangibility of assets and size are determinants that contribute for a greater adjustment of debt towards optimal level. The results also suggest that the capital structure decisions of listed Portuguese companies can be explained in the light of trade‐off and pecking order theories, and not according to what is forecast by market timing theory.

Originality/value

Through this study, the level of adjustment of actual debt towards target debt ratio in the context of companies belonging to under‐developed capital markets are determined, in the particular case of this study, belonging to the Portuguese capital market. Furthermore, from target debt ratio depending on companies' specific determinants, the explanatory power of trade‐off, pecking order and market timing theories are investigated. The results contribute for a deeper understanding about companies' capital structure decisions.

Details

Review of Accounting and Finance, vol. 8 no. 1
Type: Research Article
ISSN: 1475-7702

Keywords

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