论文检索

长面板协整模型的统计推断AI 解读

This article presents a general likelihood-based framework for inference in panel vector autoregressive (VAR) models with cointegration restrictions. The cointegrating relationships are restricted to each cross section while the rest of the model is unrestricted. The homogeneous restriction of common cointegrating space is also considered. Asymptotic distributions of parameter estimators and the test statistics for the cointegrating rank and the homogeneous restriction are…

允许非高斯误差的均值—方差有效性多元检验AI 解读

We develop exact mean–variance efficiency tests of the market portfolio in the context of (conditional and unconditional) capital asset pricing models (CAPM), allowing for a wide class of possibly non-Gaussian error distributions. The proposed procedures are applicable in a general multivariate linear regression framework, and exactness is achieved through Monte Carlo test techniques. We also perform exact multivariate diagnostic checks. Empirical results show that the…

美国消费者价格指数的小样本解析偏差修正AI 解读

The U.S. Bureau of Labor Statistics (BLS) faces sample size constraints when computing its Consumer Price Index (CPI–U). The samples are not sufficiently large for the index to equal a true “fixed basket” price index. This study adjusts for this small-sample bias by estimating the second order of a stochastic expansion of the index. Unlike increasing sample size, this adjustment is inexpensive because it uses the same data used to compute the CPI–U. From the beginning of…

通过 LAD-lasso 实现稳健回归收缩与一致变量选择AI 解读

The least absolute deviation (LAD) regression is a useful method for robust regression, and the least absolute shrinkage and selection operator (lasso) is a popular choice for shrinkage estimation and variable selection. In this article we combine these two classical ideas together to produce LAD-lasso. Compared with the LAD regression, LAD-lasso can do parameter estimation and variable selection simultaneously. Compared with the traditional lasso, LAD-lasso is resistant to…

从不可比调查计算可比统计量：以印度贫困为例AI 解读

Applied economists are often interested in studying trends in economic indicators such as inequality or poverty; however, comparisons over time can be made impossible by changes in data collection methodology. We describe an easily implemented procedure, based on inverse probability weighting, that allows recovery of comparability of estimated parameters identified implicitly by a moment condition. The validity of the procedure requires the existence of a set of auxiliary…

分组数据的改进测量误差估计量AI 解读

Grouping models are widely used in economics but are subject to finite sample bias. I show that the standard errors-in-variables estimator is exactly equivalent to the jackknife instrumental variables estimator and use this relationship to develop an estimator which, unlike the standard errors-in-variables estimator, is unbiased in finite samples. The theoretical results are demonstrated using Monte Carlo experiments. Finally, I implement a model of intertemporal male labor…

通过变换回归构造分位数置信区间的修正代入法AI 解读

We propose a corrected plug-in method for constructing confidence intervals of the conditional quantiles of an original response variable through a transformed regression with heteroscedastic errors. The interval is easy to compute. Factors affecting the magnitude of the correction are examined analytically through the special case of Box–Cox regression. Monte Carlo simulations show that the new method works well in general and is superior over the commonly used delta method…

利用劳动者流动测量企业动态AI 解读

Information on firm dynamics is critical to understanding economic activity, yet is fundamentally difficult to measure. In this article we introduce a new way of capturing dynamics: following clusters of workers as they move across administrative entities. We show that a worker flow approach improves linkages across firms in longitudinal business databases. The approach also provides conceptual insights into the changing structure of businesses and employer–employee…

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

大缓和时期的宏观波动、可预测性与不确定性AI 解读

I examine the extent to which the large decline in observed real output volatility, that is, the great moderation, can be attributed to changes in macroeconomic uncertainty and macroeconomic predictability using forecasts of future real output growth from the Survey of Professional Forecasters (SPF). The results indicate that both predictability and uncertainty have declined over the great moderation. The results indicate that measuring the decline in macroeconomic…

摘要暂缺

基于市场的货币政策预期度量AI 解读

A number of recent articles have used different financial market instruments to measure near-term expectations of the federal funds rate and the high-frequency changes in these instruments around Federal Open Market Committee announcements to measure monetary policy shocks. This article evaluates the empirical success of a variety of financial market instruments in predicting the future path of monetary policy. All of the instruments we consider provide forecasts that are…

向量自回归脉冲响应的内在贝叶斯估计AI 解读

We propose an information-theoretic alternative to the conventional Bayesian posterior mean estimator of impulse responses in vector autoregression (VAR) models. The proposed estimator is based on the intrinsic entropy loss function, which is invariant to nonlinear transformations of parameters. Consequently, intrinsic estimation of impulse responses is equivalent to that of VAR parameters. The Bayesian estimator under the entropy loss involves a frequentist expectation of…

用加权似然比检验比较密度预测AI 解读

We propose a test for comparing the out-of-sample accuracy of competing density forecasts of a variable. The test is valid under general conditions: The data can be heterogeneous and the forecasts can be based on (nested or nonnested) parametric models or produced by semiparametric, nonparametric, or Bayesian estimation techniques. The evaluation is based on scoring rules, which are loss functions defined over the density forecast and the realizations of the variable. We…

动态效率估计AI 解读

The shadow cost approach is developed in the context of the dynamic duality model of intertemporal decision making to formulate theoretical and econometric models of dynamic efficiency. The dynamic efficiency model is applied to a panel of 72 U.S. major investor-owned electric utilities using fossil fuel–fired steam electric power generation over the period 1986–1999. The major results show that most electric utilities underutilized fuel relative to the aggregated labor and…

共同周期相关特征与机场日度数据中的存量和流量互动AI 解读

We propose the multivariate representation of univariate and bivariate (possibly nonstationary) periodic models as a benchmark for the imposition of common periodic correlation (CPC) feature restrictions to obtain parameter parsimony. CPCs are short-run common dynamic features that co-vary across the different days of the week and possibly also across weeks and that can be common across different time series. We also show how periodic models can be used to describe…

关于共同周期、共同趋势与收敛的札记AI 解读

This article compares and contrasts structural time series models and the common features methodology. The way in which trends are handled is highlighted by describing a recent structural time series model that allows convergence to a common growth path. Postsample data are used to test its forecasting performance for income per head in U.S. regions. A test for common cycles is proposed, its asymptotic distribution is given, and small-sample properties are studied by Monte…

协同结构突变（Co-breaking）AI 解读

This article has two aims. First, we provide a synopsis of the literature on co-breaking that has developed in several, seemingly disconnected, strands. We establish a consistent terminology, collect theoretical results, delimit co-breaking to cointegration and common features, and review recent contributions to co-breaking regressions and the budding analysis of co-breaking rank. Second, we present new results in the field, particularly, on the importance of co-breaking for…

因子模型中原始冲击数量的确定AI 解读

A widely held but untested assumption underlying macroeconomic analysis is that the number of shocks driving economic fluctuations, q, is small. In this article we associate q with the number of dynamic factors in a large panel of data. We propose a methodology to determineq without having to estimate the dynamic factors. We first estimate a VAR in r static factors, where the factors are obtained by applying the method of principal components to a large panel of data, then…