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Asymptotic F -Test in a GMM Framework with Cross-Sectional Dependence

横截面相关下 GMM 框架中的渐近 F 检验

The paper develops an asymptotically valid F-test that is robust to spatial autocorrelation in a GMM framework. The validity of the F-test is established under mild conditions that can accommodate a wide range of spatial processes. The proposed F-test is very easy to implement, as critical values are from a standard F-distribution. The F-test achieves triple robustness: it is asymptotically valid regardless of the spatial autocorrelation, the sampling region, and the…

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R&D, Innovation and Knowledge Spillovers: A Reappraisal of Bottazzi and Peri (2007) in the Presence of Cross-Sectional Dependence

Bottazzi and Peri (Economic Journal 2007; 117: 486–511) show the existence of a cointegrating relationship between the domestic stock of knowledge, domestic R&D and the international knowledge stock for a panel of OECD countries and interpret it as evidence supporting the semi-endogenous versus the endogenous growth theory. We replicate the baseline specification of their study and we show that main results are robust to the use of a different estimation strategy (Bai et…

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A nondegenerate Vuong test

一种非退化的Vuong检验

In this paper, I propose a one-step nondegenerate test as an alternative to the classical Vuong (1989) tests. I show that the new test achieves uniform asymptotic size control in both the overlapping and the non-overlapping cases, while the classical Vuong tests do not. Meanwhile, the power of the new test can be substantially better than the two-step classical Vuong test and is not dominated by the one-step classical Vuong test. An extension to moment-based models is also…

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Maximum likelihood inference in weakly identified dynamic stochastic general equilibrium models

弱识别动态随机一般均衡模型中的最大似然推断

This paper examines the issue of weak identification in maximum likelihood, motivated by problems with estimation and inference in a multidimensional dynamic stochastic general equilibrium model. We show that two forms of the classical score (Lagrange multiplier) test for a simple hypothesis concerning the full parameter vector are robust to weak identification. We also suggest a test for a composite hypothesis regarding a subvector of parameters. The suggested subset test…

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Hypothesis testing for high-dimensional sparse binary regression

高维稀疏二元回归的假设检验

In this paper, we study the detection boundary for minimax hypothesis testing in the context of high-dimensional, sparse binary regression models. Motivated by genetic sequencing association studies for rare variant effects, we investigate the complexity of the hypothesis testing problem when the design matrix is sparse. We observe a new phenomenon in the behavior of detection boundary which does not occur in the case of Gaussian linear regression. We derive the detection…

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Sparsistency and agnostic inference in sparse PCA

稀疏主成分分析中的变量选择一致性与无真值假设推断

The presence of a sparse “truth” has been a constant assumption in the theoretical analysis of sparse PCA and is often implicit in its methodological development. This naturally raises questions about the properties of sparse PCA methods and how they depend on the assumption of sparsity. Under what conditions can the relevant variables be selected consistently if the truth is assumed to be sparse? What can be said about the results of sparse PCA without assuming a sparse and…

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A new permutation test statistic for complete block designs

完全区组设计的一种新置换检验统计量

We introduce a nonparametric test statistic for the permutation test in complete block designs. We find the region in which the statistic exists and consider particularly its properties on the boundary of the region. Further, we prove that saddlepoint approximations for tail probabilities can be obtained inside the interior of this region. Finally, numerical examples are given showing that both accuracy and power of the new statistic improves on these properties of the…

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Consistency of maximum likelihood estimation for some dynamical systems

若干动力系统中最大似然估计的一致性

We consider the asymptotic consistency of maximum likelihood parameter estimation for dynamical systems observed with noise. Under suitable conditions on the dynamical systems and the observations, we show that maximum likelihood parameter estimation is consistent. Our proof involves ideas from both information theory and dynamical systems. Furthermore, we show how some well-studied properties of dynamical systems imply the general statistical properties related to maximum…

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Graph-based change-point detection

基于图的变点检测

We consider the testing and estimation of change-points—locations where the distribution abruptly changes—in a data sequence. A new approach, based on scan statistics utilizing graphs representing the similarity between observations, is proposed. The graph-based approach is nonparametric, and can be applied to any data set as long as an informative similarity measure on the sample space can be defined. Accurate analytic approximations to the significance of graph-based scan…

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ROP: Matrix recovery via rank-one projections

ROP:通过秩一投影恢复矩阵

Estimation of low-rank matrices is of significant interest in a range of contemporary applications. In this paper, we introduce a rank-one projection model for low-rank matrix recovery and propose a constrained nuclear norm minimization method for stable recovery of low-rank matrices in the noisy case. The procedure is adaptive to the rank and robust against small perturbations. Both upper and lower bounds for the estimation accuracy under the Frobenius norm loss are…

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Tests for overidentifying restrictions in Factor-Augmented VAR models

因子增强向量自回归模型的过度识别约束检验

This paper develops tests for overidentifying restrictions in Factor-Augmented Vector Autoregressive (FAVAR) models. The identification of structural shocks in FAVAR can involve infinitely many restrictions as the number of cross sections goes to infinity. Our focus is to test the joint null hypothesis that all the restrictions are satisfied. Conventional tests cannot be used due to the large dimension. We transform the infinite-dimensional problem into a finite-dimensional…

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Econometrics of co-jumps in high-frequency data with noise

含噪声高频数据中共同跳跃的计量分析

We establish estimation methods to determine co-jumps in multivariate high-frequency data with non-synchronous observations and market microstructure. A rate-optimal estimator of the entire quadratic covariation of an Itô-semimartingale is constructed by a locally adaptive spectral approach. Thresholding allows to disentangle the co-jump from the continuous part. We derive a feasible limit theorem for a truncated estimator of integrated covolatility which facilitates…

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Inference in semiparametric binary response models with interval data

区间数据下半参数二元响应模型的推断

This paper studies the semiparametric binary response model with interval data investigated by Manski and Tamer (2002). In this partially identified model, we propose a new estimator based on MT’s modified maximum score (MMS) method by introducing density weights to the objective function, which allows us to develop asymptotic properties of the proposed set estimator for inference. We show that the density-weighted MMS estimator converges at a nearly cube-root-n rate. We…

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On the bootstrap for Moran’s I test for spatial dependence

空间依赖 Moran’s I 检验的自助法

This paper is concerned with the use of the bootstrap for statistics in spatial econometric models, with a focus on the test statistic for Moran’s I test for spatial dependence. We show that, for many statistics in spatial econometric models, the bootstrap can be studied based on linear–quadratic (LQ) forms of disturbances. By proving the uniform convergence of the cumulative distribution function for LQ forms to that of a normal distribution, we show that the bootstrap is…

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Goodness-of-fit tests based on series estimators in nonparametric instrumental regression

基于级数估计的非参数工具变量回归拟合优度检验

This paper proposes several tests of restricted specification in nonparametric instrumental regression. Based on series estimators, test statistics are established that allow for tests of the general model against a parametric or nonparametric specification as well as a test of exogeneity of the vector of regressors. The tests’ asymptotic distributions under correct specification are derived and their consistency against any alternative model is shown. Under a sequence of…

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Confidence sets for the date of a break in level and trend when the order of integration is unknown

积分阶数未知时水平与趋势突变日期的置信集合

We propose methods for constructing confidence sets for the timing of a break in level and/or trend that have asymptotically correct coverage for both I(0) and I(1) processes. These are based on inverting a sequence of tests for the break location, evaluated across all possible break dates. We separately derive locally best invariant tests for the I(0) and I(1) cases; under their respective assumptions, the resulting confidence sets provide correct asymptotic coverage…

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A residual-based ADF test for stationary cointegration in I ( 2 ) settings

I(2) 环境中平稳协整的残差 ADF 检验

We propose a residual-based augmented Dickey–Fuller (ADF) test statistic that allows for detection of stationary cointegration within a system that may contain both I(2) and I(1) observables. The test is also consistent under the alternative of multicointegration, where first differences of the I(2) observables enter the cointegrating relationships. We find the null limiting distribution of this statistic and justify why our proposal improves over related approaches.…

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Estimating a spatial autoregressive model with an endogenous spatial weight matrix

空间权重矩阵内生时的空间自回归模型估计

The spatial autoregressive (SAR) model is a standard tool for analyzing data with spatial correlation. Conventional estimation methods rely on the key assumption that the spatial weight matrix is strictly exogenous, which would likely be violated in some empirical applications where spatial weights are determined by economic factors. This paper presents model specification and estimation of the SAR model with an endogenous spatial weight matrix. We provide three estimation…

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TRYGVE HAAVELMO AND THE EMERGENCE OF CAUSAL CALCULUS

Haavelmo 与因果演算的形成

Haavelmo was the first to recognize the capacity of economic models to guide policies. This paper describes some of the barriers that Haavelmo’s ideas have had (and still have) to overcome and lays out a logical framework that has evolved from Haavelmo’s insight and matured into a coherent and comprehensive account of the relationships between theory, data, and policy questions. The mathematical tools that emerge from this framework now enable investigators to answer complex…

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Specification testing in nonstationary time series models

非平稳时间序列模型的设定检验

In this paper, we consider a specification testing problem in nonlinear time series models with nonstationary regressors, and we propose using a nonparametric kernel‐based test statistic. The null asymptotics for the proposed nonparametric test statistic have been well developed in the existing literature. In this paper, we study the local asymptotics of the test statistic (i.e. the asymptotic properties of the test statistic under a sequence of general nonparametric local…

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Non-parametric inference on the number of equilibria

均衡数量的非参数推断

This paper proposes an estimator and develops an inference procedure for the number of roots of functions that are non‐parametrically identified by conditional moment restrictions. It is shown that a smoothed plug‐in estimator of the number of roots is superconsistent under i.i.d. asymptotics, but asymptotically normal under non‐standard asymptotics. The smoothed estimator is furthermore asymptotically efficient relative to a simple plug‐in estimator. The procedure proposed…

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On bootstrap validity for specification tests with weak instruments

弱工具变量下设定检验的自助法有效性

We study the asymptotic validity of the bootstrap for Durbin–Wu–Hausman tests of exogeneity, with or without identification. We provide an analysis of the limiting distributions of the proposed bootstrap statistics under both the null hypothesis of exogeneity (size) and the alternative hypothesis of endogeneity (power). We show that when identification is strong, the bootstrap provides a high‐order approximation of the null limiting distributions of the statistics and is…

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More reliable inference for the dissimilarity index of segregation

隔离相异指数的更可靠统计推断

The most widely used measure of segregation is the so‐called dissimilarity index. It is now well understood that this measure also reflects randomness in the allocation of individuals to units (i.e. it measures deviations from evenness, not deviations from randomness). This leads to potentially large values of the segregation index when unit sizes and/or minority proportions are small, even if there is no underlying systematic segregation. Our response to this is to produce…

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Robust hypothesis tests for M-estimators with possibly non-differentiable estimating functions

估计函数可能不可微的M估计量稳健假设检验

We propose a new robust hypothesis test for (possibly non‐linear) constraints on M‐estimators with possibly non‐differentiable estimating functions. The proposed test employs a random normalizing matrix computed from recursive M‐estimators to eliminate the nuisance parameters arising from the asymptotic covariance matrix. It does not require consistent estimation of any nuisance parameters, in contrast with the conventional heteroscedasticity‐autocorrelation consistent…

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