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Shrinkage estimators for periodic autoregressions

周期自回归模型的收缩估计

A periodic autoregression [PAR] is a seasonal time series model where the autoregressive parameters vary over the seasons. A drawback of PAR models is that the number of parameters increases dramatically when the number of seasons gets large. Hence, one needs many periods with intra-seasonal data to be able to get reliable parameter estimates. Therefore, these models are rarely applied for weekly or daily observations. In this paper we propose shrinkage estimators which…

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Cointegration in a historical perspective

历史视角下的协整

We analyse the impact of the Engle and Granger (1987) article by means of its citations over time, and find evidence of a second life starting in the new millennium. Next, we propose a possible explanation of the success of this citation classic. We argue that the conditions for its success were just right at the time of its appearance, because of the growing emphasis on time series properties in econometric modelling, the empirical importance of stochastic trends, the…

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Modeling Purchases as Repeated Events

将购买行为建模为重复事件

We put forward a statistical model for interpurchase times that incorporates all current and past information available for all purchases as time runs along the calendar time scale. It delivers forecasts for the number of purchases in the next period, as well as for the timing of subsequent and consecutive purchases. Purchase occasions are viewed as a counting process that counts the recurrent purchases for each house-hold as they evolve over time. We illustrate our model…

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Deriving target selection rules from endogenously selected samples

从内生选择样本推导目标客户选择规则

Abstract The selection of the most profitable customers in a customer database for targeted activities is often done based on observed behaviour in the past. Consequently, databases arising from the responses to, for example, direct mailings in the past are not random samples. When not all heterogeneity across customers is observed, target selection will be based on unobserved heterogeneity and hence it is endogenous. We develop a method to adjust the likelihood function of…

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A multi‐level panel STAR model for US manufacturing sectors

美国制造业部门的多层面板平滑转换自回归模型

Abstract We introduce a multi‐level smooth transition model for a panel of time series, which can be used to examine the presence of common nonlinear business cycle features across many variables. The model is positioned in between a fully pooled model, which imposes such common features, and a fully heterogeneous model, which allows for unrestricted nonlinearity. We introduce a second‐stage model linking the parameters that determine the timing of the switches between…

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On the Econometrics of the Bass Diffusion Model

Bass扩散模型的计量经济学问题

The parsimonious Bass diffusion model is frequently used to forecast adoptions of new products and to compare the life cycles of specific products across countries. To meet these goals, reliable parameter estimates are needed. We develop the asymptotic theory for the three key parameters in the Bass model. For this purpose, we need to make assumptions about the stochastic error process. On doing so, we arrive at an alternative version of the Bass model than the one usually…

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Financial volatility: an introduction

金融波动率:导论

Abstract It is now 20 years since the publication of Engle's ( 1982 ) seminal paper, which introduced ARCH to the world. The ARCH paper had an enormous influence on both theoretical and applied econometrics, and was influential in the establishment of the discipline of Financial Econometrics. In this paper we provide an introduction to the special issue on modelling and forecasting financial volatility, which commemorates the Twentieth Anniversary of the publication of ARCH.…

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Modelling and forecasting level shifts in absolute returns

绝对收益水平跳变的建模与预测

Abstract Due to high and low volatility periods, time series of absolute returns experience temporary level shifts which differ in length and size. In this paper we modify the basic Censored Latent Effects Autoregressive [CLEAR] model, such that it can describe and forecast the location and size of such level shifts. For our particular application, we assume that technical trading variables may have explanatory value for future level shifts, where these effects may differ…

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Censored latent effects autoregression, with an application to US unemployment

删失潜在效应自回归模型及其美国失业应用

Abstract A model is proposed to describe observed asymmetries in postwar unemployment time series data. We assume that recession periods, when unemployment increases rapidly, correspond with unobserved positive shocks. The generating mechanism of these latent shocks is a censored regression model, where linear combinations of lagged explanatory variables lead to positive shocks, while otherwise shocks are equal to zero. We apply this censored latent effects autoregression to…

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A dynamic multinomial probit model for brand choice with different long‐run and short‐run effects of marketing‐mix variables

营销组合变量具有不同长期与短期效应的动态多项 Probit 品牌选择模型

Abstract In this paper we propose a dynamic multinomial probit model in order to estimate the long‐run and short‐ run effects of marketing mix variables on brand choice. The latent variables, which contain the unobserved perceived utilities, follow a first‐order vector error correction autoregressive process of order 1 with current and lagged explanatory variables. The unrestricted autoregressive parameter matrix concerns the intertemporal correlation in perceived utilities…

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Asymptotically perfect and relative convergence of productivity

生产率的渐近完全收敛与相对收敛

In this paper we examine the extent to which countries are converging in per capita productivity levels. We propose to use cluster analysis in order to allow for the endogenous selection of converging countries. We formally define convergence in a time series analytical context, derive the necessary and sufficient conditions for convergence, and introduce a cluster analytical procedure that distinguishes several convergence clubs by testing for these conditions using a…

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Testing for ARCH in the presence of additive outliers

存在加性异常值时的 ARCH 检验

In this paper we investigate the properties of the Lagrange Multiplier (LM) test for autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AOs). We show analytically that both the asymptotic size and power are adversely affected if AOs are neglected: the test rejects the null hypothesis of homoscedasticity too often when it is in fact true, while the test has difficulty detecting genuine GARCH effects. Several…

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Testing for ARCH in the presence of additive outliers

存在加性异常值时的 ARCH 检验

In this paper we investigate the properties of the Lagrange Multiplier (LM) test for autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AOs). We show analytically that both the asymptotic size and power are adversely affected if AOs are neglected: the test rejects the null hypothesis of homoscedasticity too often when it is in fact true, while the test has difficulty detecting genuine GARCH effects. Several…

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Testing for Smooth Transition Nonlinearity in the Presence of Outliers

存在异常值时的平滑转换非线性检验

Regime-switching models, like the smooth transition autoregressive (STAR) model, are typically applied to time series of moderate length. Hence, the nonlinear features that these models intend to describe may be reflected in only a few observations. Conversely, neglected outliers in a linear time series of moderate length may incorrectly suggest STAR (or other) type(s of) nonlinearity. In this article, the authors propose outlier robust tests for STAR-type nonlinearity.…

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Outlier Detection in Cointegration Analysis

协整分析中的异常值检测

Standard unit-root and cointegration tests are sensitive to atypical events such as outliers and structural breaks. In this article, the authors use outlier-robust estimation techniques to examine the impact of these events on cointegration analysis. Their outlier-robust cointegration test provides a new diagnostic tool for signaling when standard cointegration results might be driven by a few aberrant observations. A main feature of the authors' approach is that the…

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On Seasonal Cycles, Unit Roots, and Mean Shifts

The interpretation of seasonality in terms of economic behavior depends on the form of the econometric time-series model that allows for a description of seasonality. Popular models often assume either approximate deterministic seasonality (cf. Miron (1996)) or stochastic trend seasonality (cf. Hylleberg (1994)). Inference from an inappropriate model can be shown to be invalid. Since much graphical evidence clearly suggests that seasonal fluctuations are not constant over…

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ON PHILLIPS–PERRON-TYPE TESTS FOR SEASONAL UNIT ROOTS

季节单位根的 Phillips–Perron 型检验

In this paper we consider a semiparametric version of the test for seasonal unit roots suggested by Hylleberg, Engle, Granger, and Yoo (1990, Journal of Econometrics 44, 215–238). The asymptotic theory is based on the analysis of a simple regression problem, and the results apply to tests at any given frequency in the range (0,π]. Monte Carlo simulations suggest that the test may have more power than the parametric test of Hylleberg et al. (1990). On the other hand, the…

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On Periodic Correlations Between Estimated Seasonal and Nonseasonal Components in German and U.S. Unemployment

德国与美国失业序列中估计季节与非季节成分的周期相关性

The authors examine the orthogonality assumption of seasonal and nonseasonal components for official quarterly unemployment figures in Germany and the United States. Although nonperiodic correlations do not seem to reject the orthogonality assumption, a periodic analysis based on correlation functions that vary with the seasons indicates the violation of orthogonality. The authors find that the unadjusted data can be described by periodic autoregressive models with a unit…

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