Forecasting Time Series Subject to Multiple Structural Breaks

This paper provides a new approach to forecasting time series that are subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks occurring over the forecast horizon, taking account of the size and duration of past breaks (if any) by means of a hierarchical hidden Markov chain model. Predictions are formed by integrating over the parameters from the meta-distribution that characterizes the stochastic break-point process. In an application to U.S. Treasury bill rates, we find that the method leads to better out-of-sample forecasts than a range of alternative methods.     

Testing for Asymmetries in UK Macroeconomic Time Series

This paper examines the asymmetric properties of a broad range of quarterly postwar UK macroeconomic time series using recently developed test statistics for contractionary 'deepness' and 'steepness' relative to trend. We also examine the robustness of these test statistics to two alternative methods of detrending, namely Hodrick-Prescott filtering and structural time series modelling. We find strong corroborative evidence of asymmetric steepness relative to trend in durable consumption, total investment, investment in plant and machinery, exports and unemployment. We find weaker evidence of asymmetric deepness in savings, exports, labour hours, consumption and unemployment.     

Time Series Dynamics of Sugar Export Earnings in Fiji with Multiple Endogenous Structural Breaks: Implications for EU Sugar and Industry Reforms

Journal of Quantitative Economics - The sugar industry has been the backbone of the Fijian economy since the late 1950s. Owing to its poor performance over the recent years, and especially the...     

Trend Breaks and the Unit-Root Hypothesis For Newly Industrializing and Newly Exporting Countries*

We examine trend breaks and unit roots in aggregate and per capita real GDP for mine newly industrializing (NIC) and newly exporting (NEC) countries in east and southeast Asia. In 15 of the 18 cases, we reject the unit-root hypothesis in favor of trend stationarity with breaks. Our findings allow us to trace the growth paths of these NICs and NECs. While the shifts are due to both external and internal factors, most of the breaks are country specific and can be partly attributed to changes in government policies.     

Structural Breaks,Biased Estimations,and Forecast Errors in a GDP Series of Canada versus the United States

International Advances in Economic Research - A structural break was suspected for the Canadian gross domestic product (GDP) time series when the reporting system switched from the Standard...     

Time Series Analysis of Inflation Targeting in Selected Countries

Abstract

We analyze a set of countries which adopted inflation targeting (IT) as a policy tool. We model the pre‐IT period with ARMA and GARCH methods, and conduct the one‐step ahead forecasting for the remainder of the times series data. The actual and forecasted inflation levels are compared for each country. We find that even though the actual inflation levels are lower than the forecasted ones, there is no statistical evidence to suggest that the adoption of IT causes a structural break in the inflation levels of the countries which adopt IT.     

20世纪90年代时间序列预测领域主要研究动态

20世纪90年代,预测领域取得了比较丰硕的研究成果.预测方法除主观判断方法外,主要有单变量方法和多变量方法.单变量方法在实际中使用最多,主要涉及分数差分模型、结构模型、贝叶斯预测方法.多元回归方法仍是最常用的多变量预测方法,但对经济时间序列拟合多元回归模型存在一些问题,于是人们对向量回归模型进行了大量的研究.本文着重分析了国外学者关于预测方法的选择以及非线性模型的研究动态.     

Testing for Seasonal Stability in Unemployment Series: International Evidence

Recently, it has been shown that seasonal and business cycles are related and a similar economic mechanism is at work in producing both types of cycles (Miron 1996). Thus, an analysis of seasonal fluctuations sheds light on the nature of the business cycle. This paper uses the classical test developed by Hylleberg et al. and the LM-type tests proposed by Canova and Hansen (1995) to investigate seasonal behavior in the unemployment series of Australia, Canada, Japan, New Zealand, the US and a number of OECD countries. The main findings are that the Australian, Austrian and Canadian series are non-stationary at all seasonal frequencies, French, Japan, the NZ and the UK series are stationary at all seasonal frequencies and the USA series is stationary only at the annual frequency. The test results for other series are mixed, suggesting that further analysis is required to reach a definite conclusion. The series, except for France, Japan, New Zealand and the UK, appear to possess unstable seasonal patterns, indicating changing business cycle conditions.     

Political Instability and Economic Growth: UK Time Series Evidence

This paper tests for the influence of political instability on UK economic growth between 1961 and 1997. We construct six variables that quantify political instability and examine the effect on growth. The results suggest that there is a strong link. GARCH‐M models reveal negative effects of instability on growth and positive effects on growth uncertainty. Uncertainty in itself does not affect growth.     

混沌经济时间序列的建模与系统识别

利用时间序列分析方法对混沌经济时间序列进行研究。通过介绍有关时间序列分析的理论及混沌时间序列的建模方法,阐述了混沌经济时间序列中非线性(混沌)信息的提取方法,并对系统进行混沌识别,讨论了混沌系统混沌临界点的区间确定问题。     

Estimation and Forecasting in Models with Multiple Breaks

This paper develops a new approach to change-point modelling that allows the number of change-points in the observed sample to be unknown. The model we develop assumes that regime durations have a Poisson distribution. It approximately nests the two most common approaches: the time-varying parameter (TVP) model with a change-point every period and the change-point model with a small number of regimes. We focus considerable attention on the construction of reasonable hierarchical priors both for regime durations and for the parameters that characterize each regime. A Markov chain Monte Carlo posterior sampler is constructed to estimate a version of our model, which allows for change in conditional means and variances. We show how real-time forecasting can be done in an efficient manner using sequential importance sampling. Our techniques are found to work well in an empirical exercise involving U.S. GDP growth and inflation. Empirical results suggest that the number of change-points is larger than previously estimated in these series and the implied model is similar to a TVP (with stochastic volatility) model.     

An Empirical Investigation of Shock Persistence in Economic Time Series*

Whether or not shocks persist has important implications in economics. An empirical study investigates this issue for key Australian and US macroeconomic time series. The existence of persistence is investigated by unit root tests and its magnitude estimated by recently proposed techniques. Results from these different approaches are compared.     

Continuous Versus Discrete Time in Dynamic Common Pool Resource Game Experiments

Environmental and Resource Economics - We study the impact of discrete versus continuous time on the behavior of agents in the context of a dynamic common pool resource game. To this purpose, we...     

Chernobyl Effects on Domestic and Inbound Tourism in Sweden -- A Time Series Analysis

This paper estimates the impact of the Chernobyl nuclear accident on domestic and international tourism in Sweden. From ARIMA time series forecasts, outlier search, and intervention analysis based on regional monthly accommodation data from 1978–1989, no effect on domestic tourism is found. However, there is an enduring deterrence effect on incoming tourism. The loss of gross revenue from incoming tourism because of the Chernobyl accident, is estimated to 2.5 billion SEK.     

Export-led Growth and Import Compression: Further Time Series Evidence From LDCs

This paper conducts tests of the export-led growth and the import-compression hypotheses for four less developed countries (LDCs) – India, Nigeria, Fiji and Papua New Guinea (PNG). Based on Johansen's multiple cointegration test preceded by unit root tests, we test for cointegration between real output, exports and imports. Non-rejection of cointegration between the variables excludes the possibility of Granger non-causality and suggests at least one way Granger causality. Real output, exports and imports are found to be cointegrated in two of the countries and the resulting error-correction models suggest that Granger causality runs from exports and imports to real output in these cases. Exogeneity tests are conducted for exports with respect to real output. However, while the assumption of weak exogeneity is validated in two of the countries, the null hypothesis of super exogeneity is rejected. The test results therefore cast doubts on policy recommendations for the LDCs based on the export-led growth hypothesis.     

International Trade and Environmental Regulation: Time Series Evidence and Cross Section Test

This paper examines empiricallywhether more stringent domestic environmental policiesreduce the international competitiveness ofenvironmentally sensitive goods (ESGs). Our timeseries evidence indicates that there are no systematicchanges in trade patterns of ESGs in the last threedecades, despite the introduction of more stringentenvironmental regulations in most of the developedcountries in the 1970s and 1980s. This observedphenomenon is then subjected to a multi-countryeconometric test using an extended gravity-equationframework. The test suggests that, overall, morestringent environmental regulations do not reducetotal exports, exports of ESGs and exports ofnon-resource-based ESGs. Neither was there anyevidence to support the hypothesis that new tradebarriers emerge to offset the effects of morestringent environmental regulations.     

实际经济时间序列的计算、季节调整及相关经济含义

本文首先讨论了计算中国实际经济时间序列的不同做法 ,并分析了其对季节调整的影响 ,指出通过同比增长率计算实际变量并进行季节调整是一个可以接受的做法 ,可以得到非常接近真实的季调后序列 ,并且在中国现有数据资源的限制下拥有一些特别的优势。然后本文具体讨论了对几个不同经济变量进行季节调整的方法 ,并给出了一些在经济数据分析与预测中的简单应用。方法的关键是采用regARIMA模型 ,从而可以对工作日变化、放长假、春节因素等作出一个估计和调整。作为一个副产品 ,本文引荐了一个相对较新的季节调整程序 (方法 ) ,TRAMO SEATS ,简单介绍了它的原理和优势 ,希望今后能得到更广泛的应用。     

Rethinking Long Memory and Structural Breaks in the Forward Premium

This paper documents new results that the ability of structural breaks to explain away non‐stationary long memory in the forward premium weakens considerably with higher‐frequency data. For daily data, removing structural breaks does not make non‐stationary long memory stationary, contrary to the evidence for monthly data reported in the recent literature. Simulating data on a daily basis, we show that using monthly data tends to overstate the importance of structural breaks, and obfuscate the true nature of persistence, in the forward premium. Our results thus corroborate earlier findings that long memory bears primary responsibility for the forward premium anomaly.