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Are more data always better for factor analysis?

因子分析中更多数据总是更好吗?

Factors estimated from large macroeconomic panels are being used in an increasing number of applications. However, little is known about how the size and the composition of the data affect the factor estimates. In this paper, we question whether it is possible to use more series to extract the factors, and yet the resulting factors are less useful for forecasting, and the answer is yes. Such a problem tends to arise when the idiosyncratic errors are cross-correlated. It can…

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Testing Cross-Section Correlation in Panel Data Using Spacings

利用间距检验面板数据的横截面相关性

This article provides tools for characterizing the extent of cross-section correlation in panel data when we do not know a priori how many and which series are correlated. Our tests are based on the probability integral transformation of the ordered correlations. We first split the transformed correlations by their size into two groups, then evaluate the variance ratio of the two subsamples. The problem of testing cross-section correlation thus becomes one of identifying…

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Demand Systems with Nonstationary Prices

Relative prices are nonstationary and standard root-T inference is invalid for demand systems. But demand systems are nonlinear functions of relative prices, and standard methods for dealing with nonstationarity in linear models cannot be used. Demand system residuals are also frequently found to be highly persistent, further complicating estimation and inference. We propose a variant of the translog demand system, the NTLOG, and an associated estimator that can be applied…

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Tests for Skewness, Kurtosis, and Normality for Time Series Data

时间序列数据的偏度、峰度与正态性检验

We present the sampling distributions for the coefficient of skewness, kurtosis, and a joint test of normality for time series observations. We show that when the data are serially correlated, consistent estimates of three-dimensional long-run covariance matrices are needed for testing symmetry or kurtosis. These tests can be used to make inference about any conjectured coefficients of skewness and kurtosis. In the special case of normality, a joint test for the skewness…

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A PANIC Attack on Unit Roots and Cointegration

This paper develops a new methodology that makes use of the factor structure of large dimensional panels to understand the nature of nonstationarity in the data. We refer to it as PANIC-Panel Analysis of Nonstationarity in Idiosyncratic and Common components. PANIC can detect whether the nonstationarity in a series is pervasive, or variable-specific, or both. It can determine the number of independent stochastic trends driving the common factors. PANIC also permits valid…

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Determining the Number of Factors in Approximate Factor Models

确定近似因子模型中的因子数

In this paper we develop some econometric theory for factor models of large dimensions. The focus is the determination of the number of factors (r), which is an unresolved issue in the rapidly growing literature on multifactor models. We first establish the convergence rate for the factor estimates that will allow for consistent estimation of r. We then propose some panel criteria and show that the number of factors can be consistently estimated using the criteria. The…

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LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power

滞后阶数选择与兼具良好尺寸和功效的单位根检验

It is widely known that when there are errors with a moving-average root close to −1, a high order augmented autoregression is necessary for unit root tests to have good size, but that information criteria such as the AIC and the BIC tend to select a truncation lag (k) that is very small. We consider a class of Modified Information Criteria (MIC) with a penalty factor that is sample dependent. It takes into account the fact that the bias in the sum of the autoregressive…

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AN AUTOREGRESSIVE SPECTRAL DENSITY ESTIMATOR AT FREQUENCY ZERO FOR NONSTATIONARITY TESTS

用于非平稳性检验的零频自回归谱密度估计量

Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero of some process. Commonly used are kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression. However, it is known that with substantially correlated errors, the OLS estimate of the AR(1) parameter is severely biased. In this paper, we first show that this least-squares bias induces a significant…

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Parametric and Nonparametric Approaches to Price and Tax Reform

价格与税制改革的参数和非参数分析方法

In many public policy problems, we need to estimate the way in which policy changes affect people's behavior. In the analysis of tax and subsidy reform—the topic of this article—we need to know how tax-induced price changes affect the amounts that people buy of the taxed goods. We present various economic and statistical approaches to obtaining the required estimates. We consider the standard structural methods in economics, where the behavior and welfare of individual…

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Parametric and Nonparametric Approaches to Price and Tax Reform

价格与税制改革的参数和非参数方法

In many public policy problems, we need to estimate the way in which policy changes affect people's behavior. In the analysis of tax and subsidy reform—the topic of this article—we need to know how tax-induced price changes affect the amounts that people buy of the taxed goods. We present various economic and statistical approaches to obtaining the required estimates. We consider the standard structural methods in economics, where the behavior and welfare of individual…

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Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties

Many unit root tests have distorted sizes when the root of the error process is close to the unit circle. This paper analyses the properties of the Phillips-Perron tests and some of their variants in the problematic parameter space. We use local asymptotic analyses to explain why the Phillips-Perron tests suffer from severe size distortions regardless of the choice of the spectral density estimator but that the modified statistics show dramatic improvements in size when used…

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Testing for homogeneity in demand systems when the regressors are nonstationary

解释变量非平稳时需求系统的齐次性检验

Abstract An implication of optimizing theory is that demand functions are homogeneous of degree zero in prices and nominal income. Evidence based on estimations of demand systems has repeatedly found this restriction to be rejected by the data. However, the hypothesis is often formulated in terms of regressors that are non‐stationary. This paper re‐examines the evidence for homogeneity in light of recent developments in time‐series econometrics with special emphasis on the…

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Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag

ARMA 模型单位根检验中的数据驱动截断滞后选择

We analyze the choice of the truncation lag in the context of the Said-Dickey test for the presence of a unit root in a general autoregressive moving average model. It is shown that a deterministic relationship between the truncation lag and the sample size is dominated by data-dependent rules that take sample information into account. In particular, we study data-dependent rules that are not constrained to satisfy the lower bound condition imposed by Said-Dickey. Akaike's…

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