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线性结构方程模型一般可识别性的半 trek 判据AI 解读

A linear structural equation model relates random variables of interest and corresponding Gaussian noise terms via a linear equation system. Each such model can be represented by a mixed graph in which directed edges encode the linear equations and bidirected edges indicate possible correlations among noise terms. We study parameter identifiability in these models, that is, we ask for conditions that ensure that the edge coefficients and correlations appearing in a linear…

离散观测过程的逐级 Blumenthal–Getoor 指数识别AI 解读

This paper studies the identification of the Lévy jump measure of a discretely-sampled semimartingale. We define successive Blumenthal–Getoor indices of jump activity, and show that the leading index can always be identified, but that higher order indices are only identifiable if they are sufficiently close to the previous one, even if the path is fully observed. This result establishes a clear boundary on which aspects of the jump measure can be identified on the basis of…

高维线性模型中单个变量效应的估计AI 解读

A problem encountered in some empirical research, e.g. growth empirics, is that the potential number of explanatory variables is large compared to the number of observations. This makes it infeasible to condition on all variables in order to determine whether a variable of interest has an effect. We assume that the effect is identified in a high‐dimensional linear model specified by unconditional moment restrictions. We propose a new method that provides a consistent…

部分线性模型中的工具变量回归AI 解读

We consider the semiparametric regression Xtβ + φ (Z) where β and φ(.) are unknown slope coefficient vector and function, and where the variables (X, Z) are endogeneous. We propose necessary and sufficient conditions for the identification of the parameters in the presence of instrumental variables. We also focus on the estimation of β. An incorrect parametrization of φ generally leads to an inconsistent estimator of β, whereas consistent nonparametric estimators for β have…

具有广义固定效应的非可分面板模型的非参数识别AI 解读

This paper extends the familiar notion of fixed effects to nonlinear structures with infinite-dimensional unobservables, like preferences. The main result is that a generalized version of differencing identifies local average responses (LARs) in nonseparable structures. In contrast to existing results, this does not require either substantial restrictions on functional form or independence between the persistent unobservables and the explanatory variables of interest, and it…

高斯仿射期限结构模型的识别与估计AI 解读

This paper develops new results for identification and estimation of Gaussian affine term structure models. We establish that three popular canonical representations are unidentified, and demonstrate how unidentified regions can complicate numerical optimization. A separate contribution of the paper is the proposal of minimum-chi-square estimation as an alternative to MLE. We show that, although it is asymptotically equivalent to MLE, it can be much easier to compute. In…

非参数工具变量函数估计的一致置信带AI 解读

This paper is concerned with developing uniform confidence bands for functions estimated nonparametrically with instrumental variables. We show that a sieve nonparametric instrumental variables estimator is pointwise asymptotically normally distributed. The asymptotic normality result holds in both mildly and severely ill-posed cases. We present methods to obtain a uniform confidence band and show that the bootstrap can be used to obtain the required critical values. Monte…

婚姻会提高男性工资吗？面板固定效应回归中的处理效应识别AI 解读

Social scientists have generated a large and inconclusive literature on the effect(s) of marriage on men’s wages. Researchers have hypothesized that the wage premium enjoyed by married men may reflect both a tendency for more productive men to marry and an effect of marriage on productivity. To sort out these explanations, researchers have used fixed effects regression models for panel data to adjust for selection on unobserved time-invariant confounders, interpreting…

验证性自适应设计的概率基础AI 解读

Adaptive designs allow the investigator of a confirmatory trial to react to unforeseen developments by changing the design. This broad flexibility comes at the price of a complex statistical model where important components, such as the adaptation rule, remain unspecified. It has thus been doubted whether Type I error control can be guaranteed in general adaptive designs. This criticism is fully justified as long as the probabilistic framework on which an adaptive design is…

高维环境下的贝叶斯模型选择AI 解读

Standard assumptions incorporated into Bayesian model selection procedures result in procedures that are not competitive with commonly used penalized likelihood methods. We propose modifications of these methods by imposing nonlocal prior densities on model parameters. We show that the resulting model selection procedures are consistent in linear model settings when the number of possible covariates p is bounded by the number of observations n, a property that has not been…

广义可加交互非线性波动模型的局部工具变量估计AI 解读

In this article we consider a new separable nonparametric volatility model that includes second-order interaction terms in both mean and conditional variance functions. This is a very flexible nonparametric ARCH model that can potentially explain the behavior of the wide variety of financial assets. The model is estimated using the generalized version of the local instrumental variable estimation method first introduced in Kim and Linton (2004, Econometric Theory 20,…

弱识别下的非线性协整回归AI 解读

An asymptotic theory is developed for a weakly identified cointegrating regression model in which the regressor is a nonlinear transformation of an integrated process. Weak identification arises from the presence of a loading coefficient for the nonlinear function that may be close to zero. In that case, standard nonlinear cointegrating limit theory does not provide good approximations to the finite-sample distributions of nonlinear least squares estimators, resulting in…

能源价格动态中时变参数的识别稳健检验AI 解读

SUMMARY We test for the presence of time‐varying parameters (TVP) in the long‐run dynamics of energy prices for oil, natural gas and coal, within a standard class of mean‐reverting models. We also propose residual‐based diagnostic tests and examine out‐of‐sample forecasts. In‐sample LR tests support the TVP model for coal and gas but not for oil, though companion diagnostics suggest that the model is too restrictive to conclusively fit the data. Out‐of‐sample analysis…

GVAR 框架下产出增长、通胀与贸易差额的概率预测AI 解读

SUMMARY We apply a global vector autoregressive (GVAR) model to the analysis of inflation, output growth and global imbalances among a group of 33 countries (26 regions). We account for structural instability by use of country‐specific intercept shifts, the timings of which are identified taking into account both statistical evidence and our knowledge of historic economic conditions and events. Using this model, we compute both central forecasts and scenario‐based…

存在企业层面无效率时的市场势力估计AI 解读

“The quiet life hypothesis” (QLH) by Hicks (1935) argues that, due to management’s subjective cost of reaching optimal profits, firms use their market power to allow inefficient allocation of resources. Increasing competitive pressure is therefore likely to force management to work harder to reach optimal profits. Another hypothesis, which also relates market power to efficiency is “the efficient structure hypothesis” (ESH) by Demsetz (1973). ESH argues that firms with…

采购拍卖中的风险厌恶与非对称性：识别、估计及建筑采购应用AI 解读

This article studies a model of asymmetric risk averse bidding within the independent private value paradigm. The inherent asymmetry in cost and risk aversion imposes an original restriction on the observed bid data, an exact equality which leads to the model semiparametric identification and estimation. The unobserved arguments of this equality need to be simulated in order to estimate the bidders’ Constant Relative Risk Aversion or Constant Absolute Risk Aversion…

具有信号关联性的第一价格密封投标拍卖模型的半参数估计AI 解读

Within the affiliated private-values paradigm, we develop a tractable empirical model of equilibrium behaviour at first-price, sealed-bid auctions. The model is non-parametrically identified, but the rate of convergence in estimation is slow when the number of bidders is even moderately large, so we develop a semiparametric estimation strategy, focusing on the Archimedean family of copulae and implementing this framework using particular members—the Clayton, Frank, and…

经验拍卖模型的有效局部工具变量估计AI 解读

In this paper we examine semiparametric efficiency bounds and efficient estimators for the case of a linear local instrument variable (LIV) model under the assumptions studied in Abadie et al. (2002). We apply the semiparametrically efficient estimation method to analyze the relation between bid dispersion and early bidding in an online auction dataset, which is collected from a natural experiment conducted in Nekipelov (2007). The results confirm the theoretical findings…

Kullback–Leibler 聚合与误设广义线性模型AI 解读

In a regression setup with deterministic design, we study the pure aggregation problem and introduce a natural extension from the Gaussian distribution to distributions in the exponential family. While this extension bears strong connections with generalized linear models, it does not require identifiability of the parameter or even that the model on the systematic component is true. It is shown that this problem can be solved by constrained and/or penalized likelihood…

确定性设计矩阵下高维线性模型的估计AI 解读

Because of the advance in technologies, modern statistical studies often encounter linear models with the number of explanatory variables much larger than the sample size. Estimation and variable selection in these high-dimensional problems with deterministic design points is very different from those in the case of random covariates, due to the identifiability of the high-dimensional regression parameter vector. We show that a reasonable approach is to focus on the…

截断回归模型的半参数估计AI 解读

This paper proposes a new semiparametric estimator for the truncated regression model under the independence restriction. Many existing approaches such as those in Lee (1992) and Honoré and Powell (1994) are moment-based methods, whereas our approach makes use of the entire truncated distribution. As a result, our approach is expected to require weaker identification and to have more favorable performance. Our simulation results suggest that our estimator outperforms that of…

空间依赖回归的统计推断AI 解读

Central limit theorems are developed for instrumental variables estimates of linear and semiparametric partly linear regression models for spatial data. General forms of spatial dependence and heterogeneity in explanatory variables and unobservable disturbances are permitted. We discuss estimation of the variance matrix, including estimates that are robust to disturbance heteroscedasticity and/or dependence. A Monte Carlo study of finite-sample performance is included. In an…

相关面板中基于残差的协整检验AI 解读

In the paper, we propose residual based tests for cointegration in general panels with cross-sectional dependency, endogeneity and various heterogeneities. The residuals are obtained from the usual least squares estimation of the postulated cointegrating relationships from each individual unit, and the nonlinear IV panel unit root testing procedure is applied to the panels of the fitted residuals using as instruments the nonlinear transformations of the adaptively fitted…

随机实验中处理效应分位数的置信区间AI 解读

In this paper, we explore partial identification and inference for the quantile of treatment effects for randomized experiments. First, we propose nonparametric estimators of sharp bounds on the quantile of treatment effects and establish their asymptotic properties under general conditions. Second, we construct confidence intervals for the bounds and the true quantile by using the approach in Chernozhukov et al. (2009). Third, under additional conditions, we develop a new…