scholarly journals Indirect Inference: Which Moments to Match?

Econometrics ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 14 ◽  
Author(s):  
David Frazier ◽  
Eric Renault
Keyword(s):  
Structural Parameters ◽  
Generalized Method Of Moments ◽  
Estimation Procedure ◽  
Efficient Estimation ◽  
Indirect Inference ◽  
General Context ◽  
Moment Matching ◽  
Parameter Matching ◽  
The Moment ◽  
Two Step Estimation

The standard approach to indirect inference estimation considers that the auxiliary parameters, which carry the identifying information about the structural parameters of interest, are obtained from some recently identified vector of estimating equations. In contrast to this standard interpretation, we demonstrate that the case of overidentified auxiliary parameters is both possible, and, indeed, more commonly encountered than one may initially realize. We then revisit the “moment matching” and “parameter matching” versions of indirect inference in this context and devise efficient estimation strategies in this more general framework. Perhaps surprisingly, we demonstrate that if one were to consider the naive choice of an efficient Generalized Method of Moments (GMM)-based estimator for the auxiliary parameters, the resulting indirect inference estimators would be inefficient. In this general context, we demonstrate that efficient indirect inference estimation actually requires a two-step estimation procedure, whereby the goal of the first step is to obtain an efficient version of the auxiliary model. These two-step estimators are presented both within the context of moment matching and parameter matching.

scholarly journals Calculating Expected Value of Sample Information Adjusting for Imperfect Implementation

2022 ◽  
pp. 0272989X2110730
Author(s):  
Anna Heath
Keyword(s):  
Computational Cost ◽  
Expected Value ◽  
Efficient Estimation ◽  
Estimation Methods ◽  
Computation Method ◽  
Moment Matching ◽  
Strength Of Evidence ◽  
Treatment Implementation ◽  
Sample Information ◽  
The Moment

Background The expected value of sample information (EVSI) calculates the value of collecting additional information through a research study with a given design. However, standard EVSI analyses do not account for the slow and often incomplete implementation of the treatment recommendations that follow research. Thus, standard EVSI analyses do not correctly capture the value of the study. Previous research has developed measures to calculate the research value while adjusting for implementation challenges, but estimating these measures is a challenge. Methods Based on a method that assumes the implementation level is related to the strength of evidence in favor of the treatment, 2 implementation-adjusted EVSI calculation methods are developed. These novel methods circumvent the need for analytical calculations, which were restricted to settings in which normality could be assumed. The first method developed in this article uses computationally demanding nested simulations, based on the definition of the implementation-adjusted EVSI. The second method is based on adapting the moment matching method, a recently developed efficient EVSI computation method, to adjust for imperfect implementation. The implementation-adjusted EVSI is then calculated with the 2 methods across 3 examples. Results The maximum difference between the 2 methods is at most 6% in all examples. The efficient computation method is between 6 and 60 times faster than the nested simulation method in this case study and could be used in practice. Conclusions This article permits the calculation of an implementation-adjusted EVSI using realistic assumptions. The efficient estimation method is accurate and can estimate the implementation-adjusted EVSI in practice. By adapting standard EVSI estimation methods, adjustments for imperfect implementation can be made with the same computational cost as a standard EVSI analysis. Highlights Standard expected value of sample information (EVSI) analyses do not account for the fact that treatment implementation following research is often slow and incomplete, meaning they incorrectly capture the value of the study. Two methods, based on nested Monte Carlo sampling and the moment matching EVSI calculation method, are developed to adjust EVSI calculations for imperfect implementation when the speed and level of the implementation of a new treatment depends on the strength of evidence in favor of the treatment. The 2 methods we develop provide similar estimates for the implementation-adjusted EVSI. Our methods extend current EVSI calculation algorithms and thus require limited additional computational complexity.

scholarly journals GENERALIZATION OF GMM TO A CONTINUUM OF MOMENT CONDITIONS

2000 ◽  
Vol 16 (6) ◽  
pp. 797-834 ◽  
Author(s):  
Marine Carrasco ◽  
Jean-Pierre Florens
Keyword(s):  
Hilbert Space ◽  
Reproducing Kernel ◽  
Diffusion Processes ◽  
Generalized Method Of Moments ◽  
Efficient Estimation ◽  
Conditional Moment ◽  
Cross Sectional ◽  
Moment Conditions ◽  
Optimal Estimator ◽  
The Moment

This paper proposes a version of the generalized method of moments procedure that handles both the case where the number of moment conditions is finite and the case where there is a continuum of moment conditions. Typically, the moment conditions are indexed by an index parameter that takes its values in an interval. The objective function to minimize is then the norm of the moment conditions in a Hilbert space. The estimator is shown to be consistent and asymptotically normal. The optimal estimator is obtained by minimizing the norm of the moment conditions in the reproducing kernel Hilbert space associated with the covariance. We show an easy way to calculate this estimator. Finally, we study properties of a specification test using overidentifying restrictions. Results of this paper are useful in many instances where a continuum of moment conditions arises. Examples include efficient estimation of continuous time regression models, cross-sectional models that satisfy conditional moment restrictions, and scalar diffusion processes.

Motion Simulation of Key Components in a Package Machine

2012 ◽  
Vol 557-559 ◽  
pp. 2303-2306
Author(s):  
Shu Bin Kan
Keyword(s):  
Structural Parameters ◽  
Center Of Mass ◽  
Motion Simulation ◽  
Software Environment ◽  
Optimization Result ◽  
Adams Software ◽  
Motion Characteristic ◽  
The Moment ◽  
Selection Of

The motion characteristic of key components is a decisional factor to the working reliability and stability of a package machine. In this paper, the motion simulation of a key component is carried out in the ADAMS software environment. By analysis of the force, variance of the center-of-mass and the moment of the component, the mutation point in the motion is found, and then the structure is optimized by selection of different structural parameters. The optimization result shows a significant improvement for the reliability and stability of the whole machine.

Influences of Diaphragm Springs on Operation Performances of Sight-Stabilizing Mechanism

2011 ◽  
Vol 211-212 ◽  
pp. 384-388
Author(s):  
Gui Mei Guo ◽  
Lin Hong
Keyword(s):  
Rigid Body ◽  
Structural Parameters ◽  
Angular Displacement ◽  
Kinematics And Dynamics ◽  
Analysis Method ◽  
Structure Form ◽  
Simulation Results ◽  
Fix Point ◽  
The Moment

Sight-stabilizing mechanisms controlled by diaphragm springs and other damping elements is an important subordinate system of airborne sight stabilizing System. The performances of sight-stabilizing system depend on the characteristics of kinematics and dynamics of the system in a great extent. Among various external moments acting on the rod of the manipulator, such as those moments caused by damper, positioning spring, and restoration spring, the forces by diaphragm springs are most obvious. According to the structure form and motion peculiarity, the rod can be equivalent to a rigid body turning around a fix point. Simulation results reveal that the moment of the restoration spring to the rod is proportional to the angular displacement, and that the moment is the most prominent factor influencing the operating performances among all these moments. Through reasonable adjustments of structural parameters of the restoration spring, the performances of the sight-stabilizing system can be improved greatly; the analysis method provides a basis for guiding the design of concerned structural parameters of sight-stabilizing system.

scholarly journals Indirect inference with(out) constraints

10.3982/qe986 ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 113-159 ◽  
Author(s):  
David T. Frazier ◽  
Eric Renault
Keyword(s):  
Asymptotic Theory ◽  
Structural Parameters ◽  
Inequality Constraints ◽  
Structural Data ◽  
Statistical Information ◽  
Strict Inequality ◽  
Indirect Inference ◽  
Auxiliary Model ◽  
Binding Function

Indirect Inference (I‐I) estimation of structural parameters θ requires matching observed and simulated statistics, which are most often generated using an auxiliary model that depends on instrumental parameters β. The estimators of the instrumental parameters will encapsulate the statistical information used for inference about the structural parameters. As such, artificially constraining these parameters may restrict the ability of the auxiliary model to accurately replicate features in the structural data, which may lead to a range of issues, such as a loss of identification. However, in certain situations the parameters β naturally come with a set of q restrictions. Examples include settings where β must be estimated subject to q possibly strict inequality constraints g( β)>0, such as, when I‐I is based on GARCH auxiliary models. In these settings, we propose a novel I‐I approach that uses appropriately modified unconstrained auxiliary statistics, which are simple to compute and always exists. We state the relevant asymptotic theory for this I‐I approach without constraints and show that it can be reinterpreted as a standard implementation of I‐I through a properly modified binding function. Several examples that have featured in the literature illustrate our approach.

scholarly journals Estimation for Nonnegative Lévy-Driven Ornstein-Uhlenbeck Processes

2007 ◽  
Vol 44 (04) ◽  
pp. 977-989 ◽  
Author(s):  
Peter J. Brockwell ◽  
Richard A. Davis ◽  
Yu Yang
Keyword(s):  
Continuous Time ◽  
Lévy Process ◽  
Moving Average ◽  
Asymptotic Properties ◽  
Estimation Procedure ◽  
Financial Econometrics ◽  
Levy Process ◽  
Efficient Estimation ◽  
Autoregressive Moving Average ◽  
Continuous Time Processes

Continuous-time autoregressive moving average (CARMA) processes with a nonnegative kernel and driven by a nondecreasing Lévy process constitute a very general class of stationary, nonnegative continuous-time processes. In financial econometrics a stationary Ornstein-Uhlenbeck (or CAR(1)) process, driven by a nondecreasing Lévy process, was introduced by Barndorff-Nielsen and Shephard (2001) as a model for stochastic volatility to allow for a wide variety of possible marginal distributions and the possibility of jumps. For such processes, we take advantage of the nonnegativity of the increments of the driving Lévy process to study the properties of a highly efficient estimation procedure for the parameters when observations are available of the CAR(1) process at uniformly spaced times 0,h,…,Nh. We also show how to reconstruct the background driving Lévy process from a continuously observed realization of the process and use this result to estimate the increments of the Lévy process itself when h is small. Asymptotic properties of the coefficient estimator are derived and the results illustrated using a simulated gamma-driven Ornstein-Uhlenbeck process.

Plan Choice and Changes in Access to Care over Time for SSI-Eligible Children with Disabilities

2005 ◽  
Vol 42 (2) ◽  
pp. 145-159 ◽  
Author(s):  
Pamela N. Roberto ◽  
Jean M. Mitchell ◽  
Darrell J. Gaskin
Keyword(s):  
Managed Care ◽  
Access To Care ◽  
Estimation Procedure ◽  
Care Plan ◽  
Care Hospital ◽  
Fee For Service ◽  
Special Needs Children ◽  
Plan Choice ◽  
Two Step Estimation ◽  
Over Time

This paper analyzes how voluntary enrollment in the fee-for-service (FFS) system versus a partially capitated managed care plan affects changes in access to care over time for special needs children who receive Supplemental Security Income (SSI) due to a disability. Four indicators of access are evaluated, including specialty care, hospital care, emergency care, and access to a regular doctor. We employ the Heckman two-step estimation procedure to correct for the potential nonrandom selection bias linked to plan choice. The findings show that relative to their counterparts in the partially capitated managed care plan, SSI children enrolled in the FFS plan are significantly more likely to encounter an access problem during either of the time periods studied. Similarly, FFS enrollees are significantly more likely than partially capitated managed care participants to experience persistent access problems across three of the four dimensions of care. Possible explanations for the deterioration in access associated with FFS include the lack of case management services, lower reimbursement relative to the partially capitated managed care plan, and provider availability.

Board financial expertise and dividend-paying behavior of firms

2018 ◽  
Vol 56 (9) ◽  
pp. 1839-1868 ◽  
Author(s):  
Bushra Sarwar ◽  
Ming Xiao ◽  
Muhammad Husnain ◽  
Rehana Naheed
Keyword(s):  
Dividend Policy ◽  
Dynamic Models ◽  
Control Mechanism ◽  
Generalized Method Of Moments ◽  
Equity Markets ◽  
Content Type ◽  
Estimation Techniques ◽  
Financial Expertise ◽  
Policy Dynamics ◽  
Two Step Estimation

Purpose Numerous researchers have developed theories and studies to uncover the issues pertinent to dividend policy dynamics, but it is still one of the unresolved problems of finance. The purpose of this paper is to focus on a new dimension, i.e., financial expertise on the corporate board for explaining the dividend policy dynamics in the emerging equity markets of China and Pakistan. Design/methodology/approach The study employs static (fixed effect (FE) and random effect (RE)) and dynamic models – two-step generalized method of moments (GMM) estimation techniques by Arellano and Bond (1991) and Arellano and Bover (1995) – during the timespan from 2009 to 2014. Further, this study re-estimated FE, RE and GMM two-step estimation techniques by excluding the non-dividend-paying companies, and also employed instrumental variable regressing by using two instrumental variables – industry average financial expertise of the board and board size – as proxies for board financial expertise to control the possible endogeneity. Findings The study reveals that Chinese firms having more financial expertise on the board do not take dividends as a control mechanism (substitution hypothesis), while Pakistani firms support the compliment hypothesis and use dividends as a control mechanism to mitigate agency conflict to protect shareholders’ interests and keep additional funds from the manager’s opportunism. Further robustness models also confirm the presence of a significant association between dividend policy and board financial expertise in both equity markets. Originality/value This study introduces the financial expertise on a board as a determinant of dividend policy. To the best of the authors’ knowledge, no previous studies have focused on board-level financial expertise as a contributing factor toward dividend policy.

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