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变点问题的鞅方法AI 解读

The changepoint problem for a binary sequence is considered. A test statistic based on recursive residuals is compared to the test statistic suggested by Pettitt. The new test statistic has more interesting properties for use in sequential testing. However, neither of the two test statistics dominates the other. Sequential versions of the martingale-based test, forward and reverse, are given and compared to other tests by means of a simulation study. The reverse martingale…

用 TSMARS 建模海表温度的长程依赖、非线性与周期现象AI 解读

We analyze a time series of 20 years of daily sea surface temperatures measured off the California coast. The temperatures exhibit quite complicated features, such as effects on many different time scales, nonlinear effects, and long-range dependence. We show how a time series version of the multivariate adaptive regression splines (MARS) algorithm, TSMARS, can be used to obtain univariate adaptive spline threshold autoregressive models that capture many of the physical…

用小波分析沿岸次潮汐海平面波动AI 解读

Subtidal coastal sea level fluctuations affect coastal ecosystems and the consequences of destructive events such as tsunamis. We analyze a time series of subtidal fluctuations at Crescent City, California, during 1980–1991 using the maximal overlap discrete wavelet transform (MODWT). Our analysis shows that the variability in these fluctuations depends on the season for scales of 32 days and less. We show how the MODWT characterizes nonstationary behavior succinctly and how…

物理应用中的谱分析：多窗与传统单变量技术AI 解读

Glossary of symbols 1. Introduction to spectral analysis 2. Stationary stochastic processes 3. Deterministic spectral analysis 4. Foundations for stochastic spectral theory 5. Linear time-invariant filters 6. Non-parametric spectral estimation 7. Multiple taper spectral estimation 8. Calculation of discrete prolate spheroidal sequences 9. Parametric spectral estimation 10. Harmonic analysis References Appendix: data and code via e-mail Index.

用 TSMARS 建模海表温度的长程依赖、非线性与周期现象AI 解读

We analyze a time series of 20 years of daily sea surface temperatures measured off the California coast. The temperatures exhibit quite complicated features, such as effects on many different time scales, nonlinear effects, and long-range dependence. We show how a time series version of the multivariate adaptive regression splines (MARS) algorithm, TSMARS, can be used to obtain univariate adaptive spline threshold autoregressive models that capture many of the physical…

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回归变量与工具变量可能非平稳时的完全修正 IV、GIVE 与 GMM 估计AI 解读

This paper develops a general theory of instrumental variables (IV) estimation that allows for both I(1) and I(0) regressors and instruments. The main goal of this paper is to develop a theory in which one does not need to know the integration properties of the regressors in order to obtain efficient estimators. The estimation techniques involve an extension of the fully modified (FM) regression procedure that was introduced in earlier work by Phillips and Hansen (1990). FM…

个体与总量食品消费函数的对应关系：美国与荷兰的证据AI 解读

This paper provides evidence from the US and Dutch budget surveys that income elasticity of family food consumption is a function of family income and other observable characteristics of the household. It also finds that the conditional variance of family food consumption depends on family income. This complicated pattern of dependence of family food consumption on income breaks the exact correspondence between the family and the aggregate food consumption functions. Simple…

采用新信息复杂度方法的食品消费实证计量建模AI 解读

This paper is concerned with empirical econometric modeling of food consumption in the USA and the Netherlands. Using autoregressive distributed lag models (ADLs) selected via the Informational Complexity (ICOMP) criterion, we study the relationship between food consumption and income. Whether food consumption obeys the homogeneity postulate is tested using information criteria. Using information-theoretic techniques, we identify the optimal information set and lag order for…

数据：简要说明AI 解读

This paper provides a brief description of all the data we provided for use in our experiment in applied econometrics: aggregate time-series data for the USA and The Netherlands; cross-section sample-survey budget data for the USA; and cross-section household level budget data for The Netherlands. We include brief descriptions of the data sets, definitions of the variables involved and documentation of original sources. We indicate where full information about the data, and…

美国与荷兰的食品统计需求函数AI 解读

This paper reports results of an extensive analysis of statistical demand functions for food using household survey data and aggregate time-series data on food consumption in the USA and The Netherlands. Using the model put forward by Tobin (1950) for survey data, we find that socio-economic information on the composition, education, and status of households adds little to the explanation of food consumption. The income elasticity of food consumption decreases over time in…

个体与总量食品消费函数的对应关系：美国与荷兰的证据AI 解读

This paper provides evidence from the US and Dutch budget surveys that income elasticity of family food consumption is a function of family income and other observable characteristics of the household. It also finds that the conditional variance of family food consumption depends on family income. This complicated pattern of dependence of family food consumption on income breaks the exact correspondence between the family and the aggregate food consumption functions. Simple…

依赖指数半参数估计量收敛速率的说明AI 解读

Considerable recent attention has been devoted to semiparametric estimation of the dependence index, or the Hurst constant, using methods based on information in either frequency or time domains. Convergence rates of estimators in the frequency domain have been derived, and in the present paper we obtain them for estimators in the time domain. It is shown that the latter can have superior performance for moderate-range time series, but are inferior in the context of…

This note examines the asymptotic properties of the Wald statistic in vector autoregressions (VAR) that may have unit roots. Within this framework we extend the theoretical results to nonlinear restrictions. As an example we study constraints derived from linear(ized) rational expectations models focusing on the expectations hypothesis using U.S. term structure data. For such cross-equation restrictions the statistic has a nonstandard distribution because the restrictions…

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协整下两阶段最小二乘估计量的统计性质AI 解读

We derive the limiting properties of the two-stage least squares estimator of an equation in a dynamic simultaneous model when variables are nonstationary and cointegrated. The implication on hypothesis testing is also discussed. It is shown that in a structural equation approach what one needs to worry about are the classical issues of identification and estimation, not nonstationarity and cointegration. Conventional formulae for computing the asymptotic covariance of the…

长期识别限制何时能够给出可靠结果？AI 解读

Many recent articles have identified behavioral disturbances in vector autoregressions by imposing restrictions on the long-run effects of shocks. This article demonstrates that this approach will be unreliable unless the underlying economy satisfies three types of strong restrictions. Although many aspects of these issues have been raised before, this article draws out and illustrates the implications for inferences under the long-run scheme. Furthermore, it provides…

周度观测的建模与季节调整AI 解读

Several important economic time series are recorded on a particular day every week. Seasonal adjustment of such series is difficult because the number of weeks varies between 52 and 53 and the position of the recording day changes from year to year. In addition certain festivals, most notably Easter, take place at different times according to the year. This article presents a solution to problems of this kind by setting up a structural time series model that allows the…

自回归时间序列面板数据的贝叶斯分析AI 解读

The authors describe a Bayesian hierarchical model to analyze autoregressive time series panel data. They develop two algorithms using Markov-chain Monte Carlo methods, a restricted algorithm that enforces stationarity or nonstationarity conditions on the series, and an unrestricted algorithm that does not. Two examples show that restricting stationary series to be stationary provides no new information but restricting nonstationary series to be stationary leads to…

随机趋势、确定性趋势与经济周期转折点AI 解读

This study examines the relationship between specifications for long-run output patterns and specifications for business cycle dynamics. In an application to US GDP, it is found that inferences about the nature of the trend in output are not robust to changes in the specification for short-run fluctuations. Similarly, the choice of which model best describes the transitory movements in output depends on the way in which the trend is specified. The empirical analysis makes…

多国经验随机 Solow 模型中的增长与收敛AI 解读

The paper considers international per capita output and its growth using a panel of data for 102 countries between 1960 and 1989. It sets out an explicitly stochastic Solow growth model and shows that this has quite different properties from the standard approach where the output equation is obtained by adding an error term to the linearized solution of a deterministic Solow model. It examines the econometric properties of estimates of beta convergence as traditionally…

通胀率存在单位根吗？序贯突变与面板模型的证据AI 解读

Using sequential trend break and panel data models, we investigate the unit root hypothesis for the inflation rates of thirteen OECD countries. With individual country tests, we find evidence of stationarity in only four of the thirteen countries. The results are more striking with the panel data model. We can strongly reject the unit root hypothesis both for a panel of all thirteen countries and for a number of smaller panels consisting of as few as three countries. The…

随机趋势、确定性趋势与经济周期转折点AI 解读

This study examines the relationship between specifications for long-run output patterns and specifications for business cycle dynamics. In an application to US GDP, it is found that inferences about the nature of the trend in output are not robust to changes in the specification for short-run fluctuations. Similarly, the choice of which model best describes the transitory movements in output depends on the way in which the trend is specified. The empirical analysis makes…