基于ARINA模型的我国广义货币供应量变动规律研究

货币供给对我国货币政策运行乃至整个宏观经济调控具有重要意义,广义货币供应量的规模及其变化趋势直接影响到中央银行货币政策的执行效果。本文运用ARIMA模型,对1996年1月至2012年1月期间我国广义货币供应量的变动规律进行研究,并运用模型对给定样本期内的M2值进行了预测,结果表明本文建立的ARIMA模型具有良好的预测精度。     

人民币汇率预测和分析——基于ARIMA模型和GARCH模型

自2005年7月人民币汇改以来,人民币持续升值。人民币汇率变动对货币政策的制定和在遏制经济过热,降低通货膨胀压力方面都有重要影响。本文采取时间序列分析方法中的ARIMA模型和GARCH模型对人民币／美元汇率日中间价进行预测分析,发现ARIMA模型的预测能力要强于GARCH模型。但尽管如此,两模型的Thcd不相等系数都十分接近,表明汇率预测效果不理想,原因是人民币汇率受到国家管制,汇率形成机制市场化程度不高。     

我国通货膨胀非线性动态特征与通货膨胀预测模型的选择

通货膨胀预测对于中央银行制定和实施货币政策非常重要,目前我国尚未形成完备的通货膨胀预测机制,系统的、全面的通货膨胀预测模型和方法也相对匮乏,造成中央银行在制定和调整货币政策时缺乏直接依据。针对这一现状,采用LSTAR模型刻画了我国通货膨胀非线性动态特征,并在此基础上比较无限制VAR模型、LSTAR模型和贝叶斯向量自回归模型(BVAR模型)的预测效果。实证结果表明,加入国际原油价格指数、银行间同业拆借利率和贷款规模变量的BVAR模型预测精度较高,并且模型的解释力较强,能够较好地预测我国现阶段的通货膨胀趋势。     

我国利率期限结构的货币政策含义

本文从理论上考察了利率期限结构在货币政策制定和实施中的作用:利率期限结构的变化可以体现货币政策态势,可以预测未来的GDP,可以预测未来通货膨胀。进一步地,本文利用无约束VAR模型对我国利率期限结构中货币政策含义进行了实证检验,结果表明,在2002年1月至2009年7月这一时期内,我国利率期限结构对货币政策态势的反应比较迅速;利率期限结构的变化可以预测大约半年后国内生产总值的变化,但对未来通货膨胀的预测能力受到较大限制。由此,我国利率期限结构的变化可以为评估货币政策调控的效果、提高货币政策制定的前瞻性和灵活性提供有价值的信息。     

通胀预测、不确定性与先行指标体系的构建

高通货膨胀不仅带来严重的社会成本,其导致的高通货膨胀不确定性还可能推高未来的通货膨胀水平,我国货币政策的滞后期较长,合理预测将有利于通货膨胀的有效管理。尝试在对Phillips曲线改进的基础上,建立我国通货膨胀预测的理论模型。以此为基础推衍出货币经济指标、生产价格指标和资产价格指标三类通货膨胀预测的先行指标,三类指标的预测先行期依次递减,由此构建出我国通货膨胀预测的多层次先行指标体系。该指标体系对于政府制定有关宏观经济政策、管理通货膨胀有重要指导意义。     

通货膨胀动态与我国货币政策走向

本文首先在理论上分析了通货膨胀在货币政策制定与实施中的地位,然后深入探讨通货膨胀的决定因素与通货膨胀惯性之间的关系,最后在简要总结我国2009年上半年的宏观经济金融形势的基础上对未来一段时期我国的通货膨胀态势与货币政策走向进行预测.     

基于ARIMA模型对我国货币供应量的研究

货币供应量作为货币政策中介目标在基本理论中一直占有重要地位,并在实践中被广泛应用.但是,近几年来,经过不断的深化改革.我国经济与金融活动发生了很大变化,所以能够对货币供应量作出预测,进而为政府制定相应的货币政策提供依据.本文利用今年来的月度数据,通过对货币供应量的自相关函数和偏自相关函数的纯计识别,建立了一个ARIMA模型,并运用Eviews软件估计出其参数.利用这个模型对我国的货币供应量进行了合理的预测.     

基于产出缺口的菲利普斯曲线对我国通胀预测的研究

基于菲利普斯曲线理论中产出缺口与通货膨胀率的关系,应用卡尔曼滤波方法估算我国的潜在产出与产出缺口,通过格兰杰因果关系验证产出缺口与通货膨胀的因果关系,并建立产出缺口的菲利普斯曲线模型进行通货膨胀预测。实证结果表明该模型能够较好地预测我国通货膨胀,从而能为制定相应的货币政策提供良好的参考。     

我国通货比率的预测研究——基于ARIMA模型

本文以通货比率为研究对象,在初步探讨改革开放以来通货比率变动规律的基础上,选取1978～2012年的数据,首次采用ARIMA模型分析该时间序列,模型拟合效果良好,最后预测通货比率在未来两年有持续下降趋势,对货币乘数和货币供给的控制以及货币政策的制定有一定的参考意义。     

银行间债券市场国债利率期限结构与通货膨胀预测

国外已有实证研究证明利率期限结构具有预测未来通货膨胀率的作用,本文采用我国银行间债券市场国债交易数据,对Mishkin模型和扩展的Mishkin模型进行实证分析,研究了不同期限的名义利率差与通货膨胀率的关系.结果发现:9个月与3个月的国债到期收益率之差与2年期与6个月的国债收益率之差含有一定的未来通货膨胀的信息,其他期限的国债收益率之差则不能用来预测未来通货膨胀.这表明,我国银行间债券市场国债利率期限结构可以作为央行制定货币政策的辅助工具.     

Do macro variables, asset markets, or surveys forecast inflation better?

Surveys do! We examine the forecasting power of four alternative methods of forecasting U.S. inflation out-of-sample: time-series ARIMA models; regressions using real activity measures motivated from the Phillips curve; term structure models that include linear, non-linear, and arbitrage-free specifications; and survey-based measures. We also investigate several methods of combining forecasts. Our results show that surveys outperform the other forecasting methods and that the term structure specifications perform relatively poorly. We find little evidence that combining forecasts produces superior forecasts to survey information alone. When combining forecasts, the data consistently places the highest weights on survey information.     

A ‘rational’ explanation for ‘irrational’ forecasts of inflation

This paper analyzes professionals' forecasts of nominal income and the inflation rate. The analysis indicates that both monetary and fiscal policy data was used efficiently to forecast income, but the monetary policy data was not used efficiently to forecast the inflation rate. Further analysis suggests that the apparent inefficient use of the monetary data results from the non-stationary money-inflation relationship predicted by rational expectations models. These models then provide an explanation for the inconsistent conclusions regarding the income forecasts and the inflation rate forecasts.     

FOMC Forecasts as a Focal Point for Private Expectations

We explore empirically the theoretical prediction that public information acts as a focal point in the context of the U.S. monetary policy. We aim at establishing whether the publication of Federal Open Market Committee (FOMC) inflation forecasts affects the cross‐sectional dispersion of private inflation expectations. Our main finding is that publishing FOMC inflation forecasts has a negative effect on the cross‐sectional dispersion of private current‐year inflation forecasts. This effect is found to be robust to another survey data set and to various macroeconomic controls. Moreover, we find that the dispersion of private inflation forecasts is not affected by the dispersion of views among FOMC members.     

Forecast rationality and monetary policy frameworks: Evidence from UK interest rate forecasts

We find evidence of heterogeneity and irrationality among professional forecasts for three-month inter-bank rates and ten-year gilt yields at both short and long forecast horizons over the period 1989-2006. The majority of biased forecasts overestimate the future spot rate, consistent with slow adjustment to the declining trend in inflation and interest rates. Furthermore, we produce evidence indicating that both monetary policy actions and elements of communication policy have information content regarding the rationality of forecasts. Changes in official bank rates and disagreement among the Monetary Policy Committee influence the rationality of forecasts. The publication of inflation reports has no effect.     

Analysts versus time-series forecasts of quarterly earnings: A maintained hypothesis revisited

We re-examine the maintained hypothesis of analysts' quarterly earnings per share (EPS) superiority versus ARIMA time-series forecasts. While our empirical results are consistent with overall analysts' dominance, they suggest a more contextual interpretation of this important relationship. Specifically, we find that for a relatively large number of cases (approximately 40%) ARIMA time-series forecasts of quarterly EPS are equal to or more accurate than consensus analysts' forecasts. Moreover, the percentage of time-series superiority increases: (1) for longer forecast horizons, (2) as firm size decreases, and (3) for high-technology firms. Due to the data demands that ARIMA forecasting requires we also examine using a seasonal random walk (SRW) model that requires only one year of data to create quarterly forecasts. Although the ARIMA time-series model results in a significant reduction in sample size it dominates the SRW model. Our findings support the analyst dominance over time series models but suggest that ARIMA time-series models may provide useful input to researchers seeking quarterly EPS expectation models for certain types of firms.     

Do Central Bank Forecasts Influence Private Agents? Forecasting Performance versus Signals

Focusing on a set of central banks that publish inflation forecasts in real time, this paper aims to establish whether central bank inflation forecasts influence private inflation forecasts. The response is positive in the five countries studied: Sweden, the United Kingdom, Canada, Switzerland, and Japan. Three hypotheses may explain this central bank influence: central bank forecasts are more accurate than private ones, are based on different information sets, and/or convey signals about future policy decisions and policymakers’ preferences and objectives. We provide evidence that the source of these central banks’ influence is not linked to their forecasting performance.     

A New Model of Inflation,Trend Inflation,and Long‐Run Inflation Expectations

This paper develops a bivariate model of inflation and a survey‐based long‐run forecast of inflation that allows for the estimation of the link between trend inflation and the long‐run forecast. Thus, our model allows for the possibilities that long‐run forecasts taken from surveys can be equated with trend inflation, that the two are completely unrelated, or anything in between. Using a variety of inflation measures and survey‐based forecasts for several countries, we find that long‐run forecasts can provide substantial help in refining estimates and fitting and forecasting inflation. It is less helpful to simply equate trend inflation with the long‐run forecasts.     

Survey forecasts in Brazil: A prismatic assessment of epidemiology,performance, and determinants

This paper assesses the behavior of survey forecasts in Brazil during the inflation targeting regime, when managing expectations is one of the cornerstones of the conduct of monetary policy. The distinctive database of the survey conducted by the Central Bank of Brazil (BCB) among professional forecasters allows for a thorough investigation of the epidemiology, determinants, and performance of forecasts. The main results are: i) top performing forecasters are influential to other forecasters; ii) survey forecasts perform better than vector autoregressive model-based forecasts; iii) common forecast errors prevail over idiosyncratic components across respondents; iv) inflation targets play an important role in inflation expectations; and v) agents perceive the BCB as following a Taylor rule consistent with inflation targeting. The last two suggest high credibility of the monetary authority.