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Beginning with January of 1987, the consumer price indexes (CPIs) have been seasonally adjusted by the X-11 autoregressive integrated moving average (ARIMA) procedure. This modification of the X-11 procedure was introduced following an empirical investigation into three aspects of seasonal adjustment methodology as applied to several CPI series--the choice of ARIMA models to fit and forecast those series, the improvements made by the ARIMA modification in terms of revision…

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…

the value of a that gave the smallest average value of the Brier score within the sample of 21 observations. The result was a = .01, which implies little or no serial dependence in the data. To further check the lack of serial dependence I performed a runs test on all 52 observations (probably a good thing to do first). The (approximate) standard normal test statistic was .2, confirming that the data were approximately serially independent. I then calculated successive…

In this article, I suggest two approaches for assessing the accuracy of the Harvey-Fernandes model forecasts. First, I suggest using measures of forecast accuracy that were originally developed to assess and compare the accuracy of weather forecasters. Second, I suggest using a simple nonparametric forecasting model, originally developed for use with computerized inventory-control algorithms, as a benchmark against which to gauge the amount of improvement afforded by the…

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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…

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.…

参数化年龄别生育率的多元时间序列预测AI 解读

Projection of individual age-specific fertility rates is a forecasting problem of high dimension. We solve this dimensionality problem by using parametric curves to approximate the annual age-specific rates and a multivariate time series model to forecast the curve parameters. These yield forecasts of future fertility curves, which are then used to compute age-specific fertility rate forecasts. This reduces the dimensionality of the forecasting problem and also guarantees…

线性预测模型中聚合问题的计量分析AI 解读

This paper deals with the problem of aggregation where the focus of the analysis is whether to predict aggregate variables using macro or micro equations. The GrunfeldGriliches prediction criterion for choosing between aggregate and disaggregate equations is generalized to allow for contemporaneous covariances between the disturbances of micro equations and the possibility of different parametric restrictions on the equations of the disaggregate model. A new test is proposed…

可计算性约束下的理性预期学习AI 解读

In this paper, the author considers how boundedly rational agents learn rational expectations when all equilibrium price functions or forecasts of future equilibrium prices are required to be computable. The paper examines two learning environments. In the first, agents have perfect information about the state of nature. In this case, the theory of machine inference can be applied to show that there is a broad class of computable economies whose rational expectations…

预测组合的基准化方法AI 解读

This article is concerned with the development of a statistical model-based approach to optimally combine forecasts derived from an extrapolative model, such as an autoregressive integrated moving average (ARIMA) time series model, with forecasts of a particular characteristic of the same series obtained from independent sources. The methods derived combine the strengths of all forecasting approaches considered in the combinational scheme. The implications of the general…

股票市场国际化与英国外汇管制的取消AI 解读

This paper aims to assess the impact of the abolition of U.K. exchange control on the degre of integration of U.K. and overseas stock markets. Using cointegration techniques, we find that although there is no significant increase in the correlation of short-run stock market returns for the United Kingdom and certain overseas markets post 1979, there does appear to be a marked increase in the degree to which these markets move together in the long run after this date--there…

动态模型预测中初步数据的最优利用AI 解读

Timely economic forecasts by means of dynamic models rely on updated time series, the last figure(s) of which are provisional and will be typically subjected to a number of revisions. A general approach to the efficient use of provisional observations in dynamic models is presented, based on the state-space methodology and the Kalman filter. Suitable adaptations are introduced, chiefly involving the measurement equations. Some applications are carried out for Italy,…

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多元时间序列结构稳定性的预测检验AI 解读

Comparing forecasts with actually observed values is one possible way to check the structural stability of time series. In this study, prediction tests based on this principle are investigated in the context of multiple time series analysis. It is found that the power of tests based on univariate series may exceed that of tests based on multivariate series and vice versa. Therefore, it is proposed to use both kinds of tests in practice. The tests are used to investigate the…

周期自回归模型预测英国季节性消费的表现AI 解读

The parameters of a periodic model are allowed to vary according to the time at which observations are made. Periodic autoregressive models are fitted to the quarterly values of seasonally unadjusted real nondurable consumers' expenditure for the United Kingdom and its components. The periodic model offers no improvement over conventional specifications if the aggregate is modeled directly. On the other hand, periodic models generally perform well for the components, which…

序列相关缓慢衰减数据的位置参数检验AI 解读

Slowly decaying serial correlations have, if ignored, disastrous effects on classical tests and confidence intervals. We propose a modified t test for the location parameter which takes into account such correlations. An approximate distribution function of the test statistic is given under the assumption of fractional Gaussian noise. The results are generalized to prediction intervals for a future average. An example is given to illustrate the methods.

利用面板数据估计向量自回归模型AI 解读

This paper considers estimation and testing of vector autoregressio n coefficients in panel data, and applies the techniques to analyze the dynamic relationships between wages an d hours worked in two samples of American males. The model allows for nonstationary individual effects and is estimated by applying instrumental variables to the quasi-differenced autoregressive equations. The empirical results suggest the absence of lagged hours in the wage forecasting equation.…

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操作性主观统计方法在理性预期中的应用AI 解读

This article presents a sequential scoring analysis of six econometric forecast distributions for the main components of the annual U.S. gross national product (GNP) accounts—nominal GNP, real GNP, and the implicit price deflator. Analysis of sequential forecasts is presented in terms of proper scoring rules. Computations relevant to the calibration and refinement properties of the forecast distributions are discussed. Annual data are studied for the period 1952–1982. The…

事前实际利率模型及其导出的通胀预测AI 解读

A methodology for estimating expected real interest rates and making inflation forecasts, together with appropriate confidence intervals, is presented. The role of price expectations in determining real interest rates is also analyzed. Structural breaks in the process generating real interest rates are detected in 1980 and 1983 by tracking the accuracy of interest-rate forecasts. Analysis of these structural breaks reveals that the break at the beginning of 1983 returns the…

异质条件 Logit 选择模型AI 解读

Aggregate forecasts using McFadden's conditional logit model of discrete choice harbor the unrealistic implicit assumption of a random-utility distribution that is homogeneous across both alternatives and individuals. This article relaxes that assumption. A choice model is developed that describes the random-utility component as a probability-mixture model. Some numerical results illustrate that the derived model is not constrained by the…