日期精度：到日 5 篇 · 到月 31 篇 · 到年 0 篇
矩阵微积分入门
Matrix calculus is an important tool when we wish to optimize functions involving matrices or perform sensitivity analyses. This tutorial is designed to make matrix calculus more accessible to graduate students and young researchers. It contains the theory that would suffice in most applications, many fully worked-out exercises and examples, and presents some of the ‘tacit knowledge’ that is prevalent in this field.
贝叶斯后验均值的抽样性质及其在 WALS 估计中的应用
Many statistical and econometric learning methods rely on Bayesian ideas. When applied in a frequentist setting, their precision is often assessed using the posterior variance. This is permissible asymptotically, but not necessarily in finite samples. We explore this issue focusing on weighted-average least squares (WALS), a Bayesian-frequentist ‘fusion’. Exploiting the sampling properties of the posterior mean in the normal location model, we derive estimators of the…
随机经济—气候模型中的期望效用与灾难性风险
We analyze a stochastic dynamic finite-horizon economic model with climate change, in which the social planner faces uncertainty about future climate change and its economic damages. Our model (SDICE*) incorporates, possibly heavy-tailed, stochasticity in Nordhaus’ deterministic DICE model. We develop a regression-based numerical method for solving a general class of dynamic finite-horizon economy–climate models with potentially heavy-tailed uncertainty and general utility…
关于“不可观测选择与系数稳定性：理论与证据”及“测量不准的混杂因素放在左侧比右侧更有用”的评论
We establish a link between the approaches proposed by Oster (2019) and Pei, Pischke, and Schwandt (2019) which contribute to the development of inferential procedures for causal effects in the challenging and empirically relevant situation where the unknown data-generation process is not included in the set of models considered by the investigator. We use the general misspecification framework recently proposed by De Luca, Magnus, and Peracchi (2018) to analyze and…
广义线性模型的加权平均最小二乘估计
The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model-averaging estimators when accounting for problems of uncertainty in the choice of the regressors. In this paper we extend the WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of…
两种模型平均技术的比较及其在增长实证中的应用
Parameter estimation under model uncertainty is a difficult and fundamental issue in econometrics. This paper compares the performance of various model averaging techniques. In particular, it contrasts Bayesian model averaging (BMA) -- currently one of the standard methods used in growth empirics -- with a new method called weighted-average least squares (WALS). The new method has two major advantages over BMA: its computational burden is trivial and it is based on a…
面板数据模型的方差矩阵设定
Many regression models have two dimensions, say time ( t = 1,…, T ) and households ( i = 1,…, N ), as in panel data, error components, or spatial econometrics. In estimating such models we need to specify the structure of the error variance matrix Ω , which is of dimension T N × T N . If T N is large, then direct computation of the determinant and inverse of Ω is not practical. In this note we define structures of Ω that allow the computation of its determinant and inverse,…
多元正态混合模型的最大似然估计
The Hessian of the multivariate normal mixture model is derived, and estimators of the information matrix are obtained, thus enabling consistent estimation of all parameters and their precisions. The usefulness of the new theory is illustrated with two examples and some simulation experiments. The newly proposed estimators appear to be superior to the existing ones.
利用极值理论分析田径世界纪录
We are interested in two questions on extremes relating to world records in athletics. The first question is: What is the ultimate world record in a specific athletic event (such as the 100-m race for men or the high jump for women), given today’s state of the art? Our second question is: How “good” is a current athletic world record? An answer to the second question also enables us to compare the quality of world records in different athletic events. We consider these…
Breitung 统计量极限分布的一般界
We consider the Breitung (2002, Journal of Econometrics 108, 343–363) statistic ξ n , which provides a nonparametric test of the I(1) hypothesis. If ξ denotes the limit in distribution of ξ n as n → ∞, we prove (Theorem 1) that 0 ≤ ξ ≤ 1/π 2 , a result that holds under any assumption on the underlying random variables. The result is a special case of a more general result (Theorem 3), which we prove using the so-called cotangent method associated with Cauchy's residue…
利用宏观数据改善微观预测
We consider the problem of combining forecasts from two different levels (called “macro” and “micro”), where we have access to the forecasts and their precisions but not to the full data set. We develop a theoretical framework and provide Monte Carlo evidence in the cases of both perfect and imperfect aggregation. Our proposed procedure is simple and robust. We also extend the procedure to time series and propose a forecast model for the European zero rates, combining…
伪最大似然估计量的渐近方差
We present an analytical closed-form expression for the asymptotic variance matrix in the misspecified multivariate regression model.I am grateful to Hamparsum Bozdogan of the University of Tennessee for bringing the idea of the sandwich variance matrix within the context of the misspecified multivariate regression model to my attention and to two referees for their constructive and useful comments.
In this paper, we confront sensitivity analysis with diagnostic testing. Every model is misspecified (in the sense that no model coincides with the data-generating process), but a model is useful if the parameters of interest (the focus) are not sensitive to small perturbations in the underlying assumptions. The study of the effect of these violations on the focus is called sensitivity analysis. Diagnostic testing, on the other hand, attempts to find out whether a nuisance…
Solution to Normal's deconvolution and the independence of sample mean and variance problem.
Normal's deconvolution and the independence of sample mean and variance.
We consider the estimation of the unknown mean "&eegr;" of a univariate normal distribution N("&eegr;", 1) given a single observation "x". We wish to obtain an estimator which is admissible and has good risk (and regret) properties. We first argue that the "usual" estimator "t" ("x") = "x" is not necessarily suitable. Next, we show that the traditional pretest estimator of the mean has many undesirable properties. Thus motivated, we suggest the Laplace estimator, based on a…
数据：简要说明
This paper provides a brief description of all the data we provided for use in our experiment in applied econometrics: aggregate time-series data for the USA and The Netherlands; cross-section sample-survey budget data for the USA; and cross-section household level budget data for The Netherlands. We include brief descriptions of the data sets, definitions of the variables involved and documentation of original sources. We indicate where full information about the data, and…
一阶自回归预测的偏差
The exact finite sample behavior is investigated on the bias of multiperiod leastsquares forecasts in the normal autoregressive model y t = α + β y t –1 + u t . Necessary and sufficient conditions are given for the existence of the bias and an expression is presented which we use to obtain exact numerical results for finite samples. The unit root and near unit root behavior is studied in detail and some popular preconceptions about the behavior of the bias are shown to be…