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时期总生育率预测：微观动态新古典生育模型的时间序列性质AI 解读

"This article demonstrates the value of microdata for understanding the effect of wages on life cycle fertility dynamics. Conventional estimates of neoclassical economic fertility models obtained from linear aggregate time series regressions are widely criticized for being nonrobust when adjusted for serial correlation. Moreover, the forecasting power of these aggregative neoclassical models has been shown to be inferior when compared with conventional time series models…

状态空间模型中的平滑与插值AI 解读

A new result dealing with smoothing and interpolation in the state-space model is developed and explored. The result simplifies the derivation of existing smoothing algorithms and provides alternate forms that have analytic and practical computing advantages. The connection to signal extraction and interpolation is explored, and diffuse specifications are considered.

总量时期生育率预测：微观动态新古典生育模型的时间序列性质AI 解读

This article demonstrates the value of microdata for understanding the effect of wages on life cycle fertility dynamics. Conventional estimates of neoclassical economic fertility models obtained from linear aggregate time series regressions are widely criticized for being nonrobust when adjusted for serial correlation. Moreover, the forecasting power of these aggregative neoclassical models has been shown to be inferior when compared with conventional time series models that…

多元时间序列序列相关系数的渐近协方差结构AI 解读

A simple proof of the asymptotic joint normality of any finite set of serial correlations of a general multivariate second-order stationary time series is presented and an explicit formula for the asymptotic covariance between two serial correlations is derived. The latter extends Bartlett's formula for the asymptotic covariance between two sample cross-correlations.

时间序列配对比较中的序列相关差值AI 解读

If observations are taken at the same set of time points on each of two time series whose nonnegative trends are proportional, the F statistic based on the differences of the two series at the time points may be used to test equality of trends against inequality of trends provided the paired differences are independently and identically distributed normal random variables. The present paper investigates the effect on the F test when the paired differences follow a stationary…

具有无限方差的一阶自回归过程AI 解读

For a first-order autoregressive process Y t = β Y t−1 + ∈ t where the ∈ t 'S are i.i.d. and belong to the domain of attraction of a stable law, the strong consistency of the ordinary least-squares estimator b n of β is obtained for β = 1, and the limiting distribution of b n is established as a functional of a Lévy process. Generalizations to seasonal difference models are also considered. These results are useful in testing for the presence of unit roots when the ∈ t 'S…

不可逆移动平均模型中极大似然与非线性最小二乘估计的渐近性质AI 解读

Dealing with noninvertible, infinite-order moving average (MA) models, we study the asymptotic properties of an estimator of the noninvertible coefficient. The estimator is constructed acting as if the data were generated from a Gaussian MA process. Allowing for two cases on the initial values of the error process, we first discuss the condition for the existence of a consistent estimator. We then compute the probability of the estimator occurring at the boundary of the…

动态非线性模型预测量的大样本性质AI 解读

The large-sample behavior of one-period-ahead and multiperiod-ahead predictors for a dynamic nonlinear simultaneous system is examined in this paper. Conditional on final values of the endogenous variables, the asymptotic moments of the deterministic, closed-form, Monte Carlo stochastic, and several variations of the residual-based stochastic predictor are analyzed. For one-period-ahead prediction, the results closely parallel our previous findings for static nonlinear…

利用多重协整与非对称误差修正模型研究生产、销售和库存关系AI 解读

The accumulated sum of a stationary series is called integrated. If a linear combination of some of the integrated series is stationary, it is said to be cointegrated. This paper presents empirical results on inventories to consider the possibility of a deeper form of cointegration called multicointegration, which is introduced in Granger and Lee (1989). A vector integrated series is multicointegrated if the accumulated sum of its stationary (cointegrated) linear combination…

大崩盘、石油价格冲击与单位根假说AI 解读

The unit root hypothesis is examined allowing a possible one-time change in the level or in the slope of the trend function. When fluctuations are stationary around a breaking trend function, standard tests cannot reject the unit root, even asymptotically. Consistent tests are derived and applied to the Nelson-Plosser data set (allowing a change in level for the 1929 crash) and to the postwar quarterly real GNP series (allowing a change in slope after 1973). The unit root…

摘要暂缺

计量时间序列半参数与非参数模型的假设检验AI 解读

A restriction on a semiparametric or nonparametric econometric time series model determines the value of a finite-dimensional functional τ of an infinite-dimensional nuisance function. The estimate of τ and its estimated covariance matrix use nonparametric probability and spectral density estimation. A consequent test of the restriction is given approximate large sample justification under absolute regularity on the time series and other conditions. The methodology relates…

摘要暂缺

商品相对价格与协整AI 解读

The Prebisch-Singer hypothesis of a secular decline in the relative price of primary commodities is reassessed, on the basis of recently available time series data, for 1900-86. Special attention is given to adequate dynnamic modeling of price fluctuations. Primary and manufactured-goods prices are found to be cointegrated. The hypothesis of stationarity for the long-run relative-price movements cannot be rejected. The empirical evidence does not support the Prebisch-Singer…

The main econometric issue in testing the Lucas (1973) hypothesis in a time series context is estimation of the forecast-error variance conditional on past information. The conditional variance may vary through time as monetary policy evolves and agents are obliged to infer its present state. Under the assumption that a monetary policy regime is continuously changing, a time-varying-parameter model is proposed for the monetary-growth function. Based on Kalman-filtering…

商品相对价格与协整AI 解读

The Prebisch-Singer hypothesis of a secular decline in the relative price of primary commodities is reassessed, on the basis of recently available time series data, for 1900-86. Special attention is given to adequate dynnamic modeling of price fluctuations. Primary and manufactured-goods prices are found to be cointegrated. The hypothesis of stationarity for the long-run relative-price movements cannot be rejected. The empirical evidence does not support the Prebisch-Singer…

线性回归模型中若干误差协方差矩阵检验的最优性AI 解读

SUMMARY This paper adopts the approach of conditional distributions to investigate the optimality of some tests of the error covariance matrix in the linear regression model. Specifically, we show that point optimal tests, advocated by King and Evans and King, are the most powerful similar test. We also derive the locally best similar and the locally best unbiased similar tests. Finding the latter cumbersome to apply, we then propose the asymptotically best similar and the…

具有双指数分布噪声的 ARMA 模型AI 解读

SUMMARY The marginal and bivariate distributions of the observations generated from a standard autoregressive moving average scheme are derived, assuming the noise to have a double-exponential (Laplace) distribution. The distributions may differ substantially from their Gaussian counterparts. The AR(1) model with double-exponential noise is applied to a series of weekly measurements of sulphate concentration and is shown to give a significantly better fit when compared with…

传递函数模型的估计与识别方法AI 解读

SUMMARY This paper proposes an approach to the simultaneous identification and estimation of transfer function models. An estimation procedure is advanced consisting of a sequence of four ordinary least squares calculations and the asymptotic properties of each step are presented, consistency and asymptotic efficiency being shown. A strategy for the identification of the model structure based on a selection criterion that arises naturally from the last step of the estimation…

边际似然在时间序列模型估计中的运用AI 解读

SUMMARY In the context of time series regression, with an error model of the ARIMA type, the fitting of the regression can seriously bias the ARIMA model parameter estimates. Moreover, choosing between different error models on the basis of the smallest residual variance may lead to incorrect selection with a high probability, even in samples of moderate size. The marginal likelihood procedure is considered as a solution to these problems and examples are presented in the…

自回归估计量偏差的不动点刻画AI 解读

Least squares estimators of the coefficients of an autoregression of known, finite order are biased to order $1/T$, where $T$ is the sample length, unless the observed time series is generated by a unique model for that order. The coefficients of this special model are the fixed point of a linear mapping defined by the bias of the least squares estimator. Separate results are given for models with known mean and unknown mean. The "fixed point models" for different orders of…

非平稳条件下的模型选择：自回归与随机线性回归模型AI 解读

We give sufficient conditions for strong consistency of estimators for the order of general nonstationary autoregressive models based on the minimization of an information criterion a la Akaike's (1969) AIC. The case of a time-dependent error variance is also covered by the analysis. Furthermore, the more general case of regressor selection in stochastic regression models is treated.

依赖观测下的稳健非参数回归估计AI 解读

Robust nonparametric estimators for regression and autoregression are proposed for $\varphi$- and $\alpha$-mixing processes. Two families of $M$-type robust equivariant estimators are considered: (i) estimators based on kernel methods and (ii) estimators based on $k$-nearest neighbor kernel methods. Strong consistency of both families is proved under mild conditions. For the first class the result is true under no assumptions whatsoever on the distribution of the…

非线性有界影响估计在美联储银行总借款中的应用AI 解读

Forecasting aggregate discount window borrowing has posed difficulties for the Federal Reserve, due in part to outliers resulting from numerous institutional changes and special borrowing situations. This article applies bounded influence estimation and influence diagnostics to identify and adjust for outliers in the case of discount window borrowing. Since most banks borrow from the Federal Reserve infrequently, the model is nonlinear and of the switching regression class.…