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Lower Risk Bounds and Properties of Confidence Sets for Ill-Posed Estimation Problems with Applications to Spectral Density and Persistence Estimation, Unit Roots, and Estimation of Long Memory Parameters

病态估计问题的风险下界与置信集合:谱密度、持续性、单位根及长记忆参数的应用

Important estimation problems in econometrics like estimating the value of a spectral density at frequency zero, which appears in the econometrics literature in the guises of heteroskedasticity and autocorrelation consistent variance estimation and long run variance estimation, are shown to be “ill-posed” estimation problems. A prototypical result obtained in the paper is that the minimax risk for estimating the value of the spectral density at frequency zero is infinite…

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Dynamic Nonlinear Econometric Models: Asymptotic Theory

动态非线性计量经济模型:渐近理论

1 Introduction.- 2 Models, Data Generating Processes, and Estimators.- 3 Basic Structure of the Classical Consistency Proof.- 4 Further Comments on Consistency Proofs.- 5 Uniform Laws of Large Numbers.- 6 Approximation Concepts and Limit Theorems.- 7 Consistency: Catalogues of Assumptions.- 8 Basic Structure of the Asymptotic Normality Proof.- 9 Asymptotic Normality under Nonstandard Conditions.- 10 Central Limit Theorems.- 11 Asymptotic Normality: Catalogues of…

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A Uniform Law of Large Numbers for Dependent and Heterogeneous Data Processes

依赖且异质数据过程的一致大数定律

Uniform laws of large numbers (ULLNs) consider sums of the form: n −1 Σ t n =1 [q t (z t , θ)-Eq t (z t , θ)], where (z t ) denotes a stochastic data generating process that takes its values in a space Z, θ is an element of the parameter space Θ, and q t : Z×Θ→R. ULLNs provide conditions under which the above sum converges to zero uniformly over the parameter space. The purpose of the present note is to introduce a new generic ULLN. It maintains a set of assumptions that is…

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