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趋势变化的直接检验AI 解读

The authors consider tests for changing trend that do not require prior knowledge about the location of the changepoint. The limiting distribution is derived from the functional central limit theorem and the critical value from the hitting probability of a Brownian bridge. Applying a test sensitive to the alternative of trend stationarity with structural breaks, they find that for real gross national product, real per capita gross national product, and real wages before…

单位根与趋势突变假说的递归和序贯检验：理论与国际证据AI 解读

This paper investigates the possibility, raised by P. Perron (1989, 1990) and P. Rappoport and L. Reichlin (1989), that aggregate economic time series can be characterized as being stationary around broken trend lines. Unlike those authors, the authors treat the break date as unknown a priori. Asymptotic distributions are developed for recursive, rolling, and sequential tests for unit roots and/or changing coefficients in time series regressions. When applied to data on real…

含 I(1) 过程回归中的参数不稳定性检验AI 解读

This article derives the large-sample distributions of Lagrange multiplier (LM) tests for parameter instability against several alternatives of interest in the context of cointegrated regression models. The fully modified estimator of Phillips and Hansen is extended to cover general models with stochastic and deterministic trends. The test statistics considered include the SupF test of Quandt, as well as the LM tests of Nyblom and of Nabeya and Tanaka. It is found that the…

大萧条、石油价格冲击与单位根假说的进一步证据AI 解读

Perron (1989) has carried out tests of the unit root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil price shock. Here a variation of Perron's test is considered in which the break point is estimated rather than fixed. The asymptotic distribution of the "estimated break point" test statistic is determined and the data considered by Perron are reanalyzed. The authors find…

寻找 GNP 的趋势断点AI 解读

It has been suggested that existing estimates of the long-run impact of a surprise move in income may have a substantial upward bias due to the presence of a trend break in postwar U.S. gross national product data. This article shows that the statistical evidence does not warrant abandoning the no-trend-break null hypothesis. A key part of the argument is that conventionally computed p values overstate the likelihood of the trend-break alternative hypothesis. This is because…

有限样本中一般单位根检验的功效与水平之间的关系AI 解读

Abstract We show that the maximum power of a generic unit root test against any stationary alternative is equal to the true level of the test. We then use Monte Carlo methods to investigate the implications for several such tests. We show patterns of rejection probabilities over a variety of unit root and stationary processes. We discuss the implications of these results for some of the uses of unit root tests in applied work.

线性过程的渐近理论AI 解读

A method of deriving asymptotics for linear processes is introduced which uses an explicit algebraic decomposition of the linear filter. The technique is closely related to Gordin's method but has some advantages over it, especially in terms of its range of application. The method offers a simple unified approach to strong laws, central limit theory and invariance principles for linear processes. Sample means and sample covariances are covered. The results accommodate both…

非参数回归分析中的变化点AI 解读

Estimators for location and size of a discontinuity or change-point in an otherwise smooth regression model are proposed. The assumptions needed are much weaker than those made in parametric models. The proposed estimators apply as well to the detection of discontinuities in derivatives and therefore to the detection of change-points of slope and of higher order curvature. The proposed estimators are based on a comparison of left and right one-sided kernel smoothers. Weak…

用扩展卡尔曼滤波估计多变量动态广义线性模型的后验众数AI 解读

A family of multivariate dynamic generalized linear models is introduced as a general framework for the analysis of time series with observations from the exponential family. Besides common conditionally Gaussian models, this article deals with univariate models for counted and binary data and, as the most interesting multivariate case, models for nonstationary multicategorical time series. For univariate responses, a related yet different class of models has been introduced…

生物学中的随机化与蒙特卡洛方法AI 解读

Part 1 Randomization tests and confidence intervals: the idea of a randomization test examples of a randomization test aspects of randomization testing raised by the examples confidence intervals from randomization. Part 2 Monte Carlo and other computer intensive methods: Monte Carlo tests jackknifing bootstrapping bootstrap tests of significance and confidence intervals. Part 3 Some general considerations: power determining how many randomizations are needed determining a…

非线性时间序列建模中残差自相关的渐近标准误AI 解读

The asymptotic distribution of residual autocorrelations for some very general nonlinear time series models is derived. This includes the important class of threshold models. Consequently more accurate standard errors for residual autocorrelations can be obtained facilitating model diagnostic checkings in many situations. A small simulation result applying the methodology to threshold models is reported.

Siegel 复合周期性检验统计量的渐近分位点AI 解读

Fisher's test for a periodicity at a single Fourier frequency is often inadequate in practice where it is necessary to test for compound periodicities, i.e. spectral lines at several frequencies. Siegel (1980) derived a test statistic for compound periodicity and provided percentage points for m not exceeding 50, where N = 2m + 1 is the length of the time series. Here the distribution of the test statistic is rewritten to enable computation of exact percentage points for m…

具有自回归移动平均误差的非参数样条回归AI 解读

We estimate by spline nonparametric regression an unknown function observed with autocorrelated errors when the errors are modelled by an autoregressive moving average model. Unknown parameters are estimated by either maximum likelihood, cross-validation or generalized cross-validation. By expressing the problem in state space form we obtain O(n) algorithms to estimate the function and its derivatives and evaluate the marginal likelihood and cross-validation functions. The…

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二阶单整向量自回归过程的表示AI 解读

We investigate vector autoregressive processes and find the condition under which the processes are I (2). A representation theorem forsuch processes is proved and the interpretation of the AR model as an error correction model is discussed.

未知异方差形式下时间序列回归模型的自适应估计AI 解读

In a multiple time series regression model the residuals are heteroskedastic and serially correlated of unknown form. GLS estimates of the regression coefficients using kernel regression and spectral methods are shown to be adaptive, in the sense of having the same asymptotic distribution, to the first order, as GLS estimates based on knowledge of the actual heteroskedasticity and serial correlation. A Monte Carlo experiment about the performance of our estimator is…

自相关与条件异方差的相互作用：随机系数方法AI 解读

In applied econometrics, the authors tend to tackle specification problems one at a time rather than considering them jointly. This has serious consequences for statistical inference. One example of this is considering autocorrelation and autoregressive conditional heteroscedasticity separately. In this article, the authors consider a linear regression model with random coefficient autoregressive disturbances that provides a convenient framework to analyze autocorrelation…

推断预期行为随时间的变化：非线性时变参数估计的应用AI 解读

This article develops a new method for inferring the structure of agents' expectations from macroeconomic time series. Two versions of a somewhat stylized macroeconomic model are examined. Expectations of money growth are a central driving variable, assumed to be formed as a time-varying weighted average of alternative money-growth models. The weights are estimated as time-varying parameters jointly with the structural parameters for the model, using a nonlinear time-varying…

用自助法辅助选择向量时间序列的近似表示AI 解读

In this article, a procedure is presented to use the bootstrap in choosing the best approximation in terms of forecasting performance for the equivalent state-space representation of a vector autoregressive model. It is found that the proposed procedure, which uses each approximator's forecasting performance, can enhance considerably an approach based simply on the estimated Hankel singular values.

预测分歧与预测不确定性的关系：调查数据与 ARCH 模型证据AI 解读

Abstract This paper examines empirically the relationship between measures of forecast dispersion and forecast uncertainty from data on inflation expectations from the Livingston survey series and the Survey Research Center (SRC) survey series. Because the survey series do not provide probabilistic forecasts of inflation, we derive measures of inflation uncertainty by modelling the conditional variance of the inflation forecast errors from the survey series as an…

自相关系数的置换极值与检验序列依赖的 Pitman 检验AI 解读

Normal approximations, as provided by permutational central limit theorems, conditionally can be arbitrarily bad. Such approximations therefore are poorly suited to the construction of critical values for Pitman (permutation) tests. A classical remedy consists in substituting a beta approximation (over the appropriate conditional interval range) for the normal one. Whereas deriving permutational extreme values for usual, nonserial statistics is generally straightforward, the…

变点问题的乘积分割模型AI 解读

Product partition models assume that observations in different components of a random partition of the data are independent. If the probability distribution of random partitions is in a certain product form prior to making the observations, it is also in product form given the observations. The product model thus provides a convenient machinery for allowing the data to weight the partitions likely to hold; and inference about particular future observations may then be made…