A Markov–switching vector equilibrium correction model of the UK labour market

There is a wide literature on the dynamic adjustment of employment and its relationship with the business cycle. In this paper we present a statistical model that offers a congruent representation of part of the UK labour market since the mid 1960s. We use a cointegrated vector autoregressive Markov-switching model in which some parameters change according to the phase of the business cycle. Output, employment, labour supply and real earnings are found to have a common cyclical component. The long run dynamics are characterized by one cointegrating vector relating unemployment to trend-adjusted real wages and output. Despite there having been many changes affecting this sector of the UK economy, the Markov-switching vector-equilibrium-correction model with three regimes (representing recession, normal growth, and high growth) provides a good characterization of the sample data, and performs well relative to alternative linear and non-linear models. The results of an impulse-response analysis highlight the dangers of using VARs when the constancy of the estimated coefficients has not been established, and demonstrate the advantages of generating regime dependent responses. First Version Received: December 2000/Final Version Received: August 2001     

中国居民储蓄行为误差修正模型

近几年来，居民储蓄持续增加成为人们关注的焦点，央行七次降息且以20％的税率对利息征税，效果不显著。本文用整理论研究了中国居民储蓄行为，建立了误差修正模型，得到了结论。     

我国利率传导机制有效性：基于货币幻觉的实证研究

本文将货币幻觉纳入投资函数和储蓄函数．并利用2000年9月到2006年8月的月度数据，经过HP滤波处理后采用Almon多项式分布滞后模型估计出投资函数和储蓄函数。我们发现在考虑货币幻觉的情况下，一方面，投资者存在货币幻觉且利率对投资有很好的调控作用，另一方面，储户不存在货币幻觉并且利率对储蓄的调控作用不明显，其原因可能是社保制度的缺位增强了储户的安全性动机以及投资渠道的不完善导致了储蓄的利率刚性。     

中国区域金融发展水平与区域经济差异的协整检验

在建立金融发展与经济增长关系的理论模型和运用泰尔指数法测度中国29个省份1978～2005年区域金融发展水平和经济增长差异的基础上,采用计量经济学中的协整检验方法,对区域金融发展水平与区域经济的差距的动态均衡关系进行研究,结果表明:两者之间存在着长期均衡关系;区域金融发展水平的差异是导致区域经济增长差异的原因。     

Forecasting inflation in the European Monetary Union: A disaggregated approach by countries and by sectors

Inflation in the European Monetary Union is measured by the Harmonized Indices of Consumer Prices (HICP) and it can be analysed by breaking down the aggregate index in two different ways. One refers to the breakdown into price indexes corresponding to big groups of markets throughout the European countries and another considers the HICP by countries. Both disaggregations are of interest because in each one, the component prices are not fully cointegrated, having more than one common factor in their trends. The paper shows that the breakdown by group of markets improves the European inflation forecasts and constitutes a framework in which general and specific indicators can be introduced for further improvements.     

Gold and inflation(s) – A time-varying relationship

What is the relationship between the price of gold and inflation? How stable is it – over time and across measures of inflation? We examine this for three countries (the USA, the UK and Japan) - over forty years and with a variety of measures of inflation and monetary liquidity. We apply a formal test for time variation and proceed to extract time varying cointegration relationships. Both formal and graphical evidence points to a break in the relationship(s) of gold and official inflation in the mid 1990s in the USA but to less clear results for the UK and Japan. However, gold seems to have offered a protection against an increase in money supply throughout nearly the entire past 40 year period in the US and the UK but failed to do so in Japan. Supporting previous findings we find evidence for a time-varying relationship in cointegration between gold and both predicted and realized inflation in nearly all cases. Contrasting multiple inflation indicators, we find evidence for the importance of money supply in the gold/inflation relationship.     

基于VAR模型的广州经济增长的影响因素分析

本文在VAR模型的基础上,采用1987～2008年广州市的GDP、出口、服务业的有关统计数据,综合运用单位根检验、协整检验、格兰杰因果检验等实证分析方法对其进行比较研究。分析结果表明:出口和服务业对于经济增长都有促进拉动的作用,都具有正向效应。但是,相对于出口来说,服务业对于经济增长的作用更明显、更持久。这符合经济发展的规律,符合当今世界发达城市的发展规律,为广州市经济决策提供参考依据。     

Time-series evidence for Balassa’s export-led growth hypothesis

This paper investigates Balassa’s export-led growth hypothesis for Greece, Ireland, Mexico, Portugal and Turkey by constructing a vector autoregression (VAR) model. On the basis of the Granger non-causality procedure developed by Toda and Yamamoto (1995), the results show that export and output are causally related in the long run for Ireland, Mexico and Portugal. Our findings cannot offer support for the causality link between export and output for Greece and Turkey. Granger-causality is uni-directional, running from export growth to economic growth in Ireland and Mexico, and running from economic growth to export growth in Portugal.     

Using Artificial Neural Networks to forecast Exchange Rate,including VAR‐VECM residual analysis and prediction linear combination

The Euro US Dollar rate is one of the most important exchange rates in the world, making the analysis of its behavior fundamental for the global economy and for different decision‐makers at both the public and private level. Furthermore, given the market efficiency of the EUR/USD exchange rate, being able to predict the rate's future short‐term variation represents a great challenge. This study proposes a new framework to improve the forecasting accuracy of EUR/USD exchange rate returns through the use of an Artificial Neural Network (ANN) together with a Vector Auto Regressive (VAR) model, Vector Error Corrective model (VECM), and post‐processing. The motivation lies in the integration of different approaches, which should improve the ability to forecast regarding each separate model. This is especially true given that Artificial Neural Networks are capable of capturing the short and long‐term non‐linear components of a time series, which VECM and VAR models are unable to do. Post‐processing seeks to combine the best forecasts to make one that is better than its components. Model predictive capacity is compared according to the Root Mean Square Error (RMSE) as a loss function and its significance is analyzed using the Model Confidence Set. The results obtained show that the proposed framework outperforms the benchmark models, decreasing the RMSE of the best econometric model by 32.5% and by 19.3% the best hybrid. Thus, it is determined that forecast post‐processing increases forecasting accuracy.