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Utilizing the Vector Autoregression Model (VAR) for Short-Term Solar Irradiance Forecasting
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作者 Farah Z. Najdawi Ruben Villarreal 《Energy and Power Engineering》 2023年第11期353-362,共10页
Forecasting solar irradiance is a critical task in the renewable energy sector, as it provides essential information regarding the potential energy production from solar panels. This study aims to utilize the Vector A... Forecasting solar irradiance is a critical task in the renewable energy sector, as it provides essential information regarding the potential energy production from solar panels. This study aims to utilize the Vector Autoregression (VAR) model to forecast solar irradiance levels and weather characteristics in the San Francisco Bay Area. The results demonstrate a correlation between predicted and actual solar irradiance, indicating the effectiveness of the VAR model for this task. However, the model may not be sufficient for this region due to the requirement of additional weather features to reduce disparities between predictions and actual observations. Additionally, the current lag order in the model is relatively low, limiting its ability to capture all relevant information from past observations. As a result, the model’s forecasting capability is limited to short-term horizons, with a maximum horizon of four hours. 展开更多
关键词 vector Autoregression model Hyperparameter Parameters Augmented Dickey Fuller Durbin Watson’s Statistics
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PC-VAR Estimation of Vector Autoregressive Models
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作者 Claudio Morana 《Open Journal of Statistics》 2012年第3期251-259,共9页
In this paper PC-VAR estimation of vector autoregressive models (VAR) is proposed. The estimation strategy successfully lessens the curse of dimensionality affecting VAR models, when estimated using sample sizes typic... In this paper PC-VAR estimation of vector autoregressive models (VAR) is proposed. The estimation strategy successfully lessens the curse of dimensionality affecting VAR models, when estimated using sample sizes typically available in quarterly studies. The procedure involves a dynamic regression using a subset of principal components extracted from a vector time series, and the recovery of the implied unrestricted VAR parameter estimates by solving a set of linear constraints. PC-VAR and OLS estimation of unrestricted VAR models show the same asymptotic properties. Monte Carlo results strongly support PC-VAR estimation, yielding gains, in terms of both lower bias and higher efficiency, relatively to OLS estimation of high dimensional unrestricted VAR models in small samples. Guidance for the selection of the number of components to be used in empirical studies is provided. 展开更多
关键词 vector autoregressive model Principal COMPONENTS Analysis STATISTICAL REDUCTION Techniques
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Vector Autoregressive (VAR) Modeling and Projection of DSE
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作者 Ahammad Hossain Md. Kamruzzaman Md. Ayub Ali 《Chinese Business Review》 2015年第6期273-289,共17页
In this paper, vector autoregressive (VAR) models have been recognized for the selected indicators of Dhaka stock exchange (DSE). Bangladesh uses the micro economic variables, such as stock trade, invested stock c... In this paper, vector autoregressive (VAR) models have been recognized for the selected indicators of Dhaka stock exchange (DSE). Bangladesh uses the micro economic variables, such as stock trade, invested stock capital, stock volume, current market value, and DSE general indexes which have the direct impact on DSE prices. The data were collected for the period from June 2004 to July 2013 as the basis on daily scale. But to get the maximum explorative information and reduction of volatility, the data have been transformed to the monthly scale. The outliers and extreme values of the study variables are detected through box and whisker plot. To detect the unit root property of the study variables, various unit root tests have been applied. The forecast performance of the different VAR models is compared to have the minimum residual. Moreover, the dynamics of this financial market is analyzed through Granger causality and impulse response analysis. 展开更多
关键词 vector autoregressive var model impulse response analysis Granger causality
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Impact of Inflation, Dollar Exchange Rate and Interest Rate on Red Meat Production in Turkey: Vector Autoregressive (VAR) Analysis
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作者 Senol Celik 《Chinese Business Review》 2015年第8期367-381,共15页
In this study, impact of inflation (WPI--Wholesale Price Index), exchange rate, and interest rate on the production of red meat in Turkey was examined using the vector autoregressive (VAR) model. The model consist... In this study, impact of inflation (WPI--Wholesale Price Index), exchange rate, and interest rate on the production of red meat in Turkey was examined using the vector autoregressive (VAR) model. The model consisting of variables of dollar exchange rate, inflation rate, interest rate, beef, buffalo meat, mutton, and goat meat production amounts has been estimated for the period from 1981 to 2014. It has been detected that there is a tie among the dollar exchange rate, inflation rate, interest rate, and the amount of red meat production in Turkey. In order to determine the direction of this relation, Granger causality test was conducted. A one-way causal relation has been observed between: the goat meat production and dollar exchange rate; the buffalo meat production and the mutton production; and the beef production and the mutton production. To interpret VAR model, the impulse response function and variance decomposition analysis was used. As a result of variance decomposition, it has been detected that explanatory power of changes in the variance of dollar exchange rate, inflation rate, and interest rate in goat meat production amount is more than explanatory power of changes in the variances of mutton, beef, and buffalo meat variables. 展开更多
关键词 vector autoregressive var model impulse response analysis variance decomposition unit root test CAUSALITY red meat
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美国分类经济政策不确定性对中国省域经济的冲击效应——基于GVAR模型的实证分析
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作者 焦雨生 《荆楚理工学院学报》 2024年第3期32-43,共12页
在全球经济一体化的背景下,一国经济政策不确定性会通过贸易、投资等渠道溢出到其他国家和地区,为分析美国经济不确定性对中国各省域的影响,采用全局向量自回归模型分析美国贸易、财政和货币政策不确定性对中国各省域经济的冲击效应。... 在全球经济一体化的背景下,一国经济政策不确定性会通过贸易、投资等渠道溢出到其他国家和地区,为分析美国经济不确定性对中国各省域的影响,采用全局向量自回归模型分析美国贸易、财政和货币政策不确定性对中国各省域经济的冲击效应。研究发现:美国贸易政策不确定性对各省域宏观经济的脉冲冲击大于货币政策不确定性的冲击,而财政政策不确定性的脉冲冲击明显较小;美国贸易和货币政策不确定性对各省域的脉冲冲击具有较大的异质性,省域经济发展越“充分”,对各省域消费物价指数的冲击越倾向于负向冲击,且冲击越小,而对进出口的冲击越倾向于正向冲击,且冲击越大。各省需注意贸易和货币政策不确定性对地区消费物价指数和进出口的冲击,以提前做好应对;各省域应进一步提升创新能力和开放水平,弱化外部经济政策不确定性的负向冲击。 展开更多
关键词 国民经济管理 经济政策不确定性 省域经济 冲击效应 全局向量自回归模型
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基于在线LASSO VAR和EGARCH模型的风场功率集成概率预测 被引量:1
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作者 王鹏 李艳婷 张宇 《上海交通大学学报》 EI CAS CSCD 北大核心 2023年第7期845-858,共14页
由于风速波动性大,风力发电往往呈现一定的不确定性.传统风能预测模型以均值为0、方差固定的正态分布度量不确定性,但方差可能随时间变化,即具有异方差性.为提升预测精度,基于在线最小绝对收缩和选择算子的向量自回归(LASSO VAR)和指数... 由于风速波动性大,风力发电往往呈现一定的不确定性.传统风能预测模型以均值为0、方差固定的正态分布度量不确定性,但方差可能随时间变化,即具有异方差性.为提升预测精度,基于在线最小绝对收缩和选择算子的向量自回归(LASSO VAR)和指数自回归条件异方差(EGARCH)模型,提出一种考虑异方差性的风场级功率集成概率预测模型.首先使用在线LASSO VAR模型预测风力机的有功功率,再利用自回归条件异方差检验验证残差的异方差性,并利用信息冲击曲线和动态显著线评估正负残差对未来条件方差的不对称影响.然后针对异方差性和不对称性,使用EGARCH模型对单风力机有功功率的残差进行预测,得到有功功率的条件方差.最后,考虑各风力机有功功率的相关性,将风场中各风力机的有功功率求和,得到整个风场总有功功率的概率预测结果.将该方法应用于中国华东某地风场,验证了该模型能有效提高预测精度. 展开更多
关键词 在线LASSO var 异方差 指数条件异方差模型 概率预测
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基于TVP-VAR模型的安全生产时变特征及因素分析
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作者 张江石 冒香凝 刘伟 《中国安全生产科学技术》 CAS CSCD 北大核心 2023年第5期5-13,共9页
为研究安全生产受经济波动冲击所产生的时变特征,从而更好地匹配经济和安全发展速度,基于近30年(1990—2020年,下同)我国安全生产状况波动趋势,采用灰色关联度分析法计算各宏观因素对事故风险的累积贡献度,并引入具有时变参数的TVP-VAR... 为研究安全生产受经济波动冲击所产生的时变特征,从而更好地匹配经济和安全发展速度,基于近30年(1990—2020年,下同)我国安全生产状况波动趋势,采用灰色关联度分析法计算各宏观因素对事故风险的累积贡献度,并引入具有时变参数的TVP-VAR模型,探索各因素在不同时期对安全生产状况的动态冲击作用。研究结果表明:就业结构、产业结构、人口效应和城市化进程构成生产安全事故状况主要驱动力,在1998,2004,2015年3个重要时点的时变性较弱,在不同提前期受其自身特征影响较大;30年间就业结构、产业结构、人口效应的影响大小震荡衰减,短期内促使安全生产状况恶化,中长期内对其起抑制作用;城市化进程冲击效果循序渐进,短期内对安全生产状况起改善作用,中长期给维护安全生产带来新的威胁。研究结果可为未来经济发展和安全生产的持续良性互动提供一定参考思路。 展开更多
关键词 生产安全 宏观经济 动态特征 时变参数向量自回归模型(TVP-var)
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基于TVP-VAR模型的人民币国际化与经常账户关系研究
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作者 刘方 《金融教育研究》 2023年第5期45-53,共9页
采用TVP-VAR模型,实证研究人民币国际化与经常账户的双向影响。结果表明:人民币国际化对经常账户顺差具有持续的逆向调节作用,其强度随时间推移而减弱,且当期效果明显;经常账户顺差扩大则抑制人民币国际化水平上升,该抑制作用具有明显... 采用TVP-VAR模型,实证研究人民币国际化与经常账户的双向影响。结果表明:人民币国际化对经常账户顺差具有持续的逆向调节作用,其强度随时间推移而减弱,且当期效果明显;经常账户顺差扩大则抑制人民币国际化水平上升,该抑制作用具有明显的时滞性,表现为当期效果弱、中期效果强;进一步研究发现,人民币国际化和资本与金融账户相互促进,且外生冲击并未改变二者的内在关系。 展开更多
关键词 人民币国际化 经常账户 资本与金融账户 时变参数向量自回归模型
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绿色农业、农业保险、涉农贷款动态关系研究——基于省级面板VAR模型的实证分析
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作者 贾士彬 玄天雯 《保险职业学院学报》 2023年第4期32-40,共9页
选取我国2013—2020年31个省区市的面板数据,利用面板VAR模型分析了全国样本以及粮食主产区和非主产区样本下绿色农业、农业保险、涉农贷款之间的动态关系。脉冲响应和方差分解表明,农业保险和涉农贷款对绿色农业发展的支持效用更凸显,... 选取我国2013—2020年31个省区市的面板数据,利用面板VAR模型分析了全国样本以及粮食主产区和非主产区样本下绿色农业、农业保险、涉农贷款之间的动态关系。脉冲响应和方差分解表明,农业保险和涉农贷款对绿色农业发展的支持效用更凸显,绿色农业反哺农业保险和涉农贷款的效果微弱且存在差异,农业保险通过信用增级有效推动了涉农贷款发展。 展开更多
关键词 绿色农业 农业保险 涉农贷款 面板向量自回归模型
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Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks 被引量:1
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作者 Claudio Morana 《Open Journal of Statistics》 2014年第4期292-312,共21页
In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independentl... In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independently of persistence and heteroskedasticity properties, accounting for common deterministic and stochastic factors. Monte Carlo results strongly support the proposed methodology, validating its use also for relatively small cross-sectional and temporal samples. 展开更多
关键词 Long and Short Memory Structural BREAKS Common Factors Principal Components Analysis Fractionally Integrated Heteroskedastic Factor vector autoregressive model
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Prophet-VAR组合优化模型在高值卷烟销量预测中的应用 被引量:5
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作者 康静 姚春玲 《中国烟草学报》 CAS CSCD 北大核心 2023年第1期127-134,共8页
针对高值卷烟销量时间序列的非平稳性、趋势性、周期性和节假日性等特点,同时考虑到高值卷烟销量受行业政策的影响,结合Prophet模型、VAR模型和单箱结构因子法,构建了Prophet-VAR组合优化模型。选用2011—2021年全国高值卷烟销量数据分... 针对高值卷烟销量时间序列的非平稳性、趋势性、周期性和节假日性等特点,同时考虑到高值卷烟销量受行业政策的影响,结合Prophet模型、VAR模型和单箱结构因子法,构建了Prophet-VAR组合优化模型。选用2011—2021年全国高值卷烟销量数据分析检验Prophet-VAR组合模型,结果表明,单独Prophet和单独VAR的预测精度分别是87.97%和84.30%,Prophet-VAR组合模型的预测误差值约为4%,精度接近96%,比单一模型的预测效果提高了约10个百分点。考虑单箱结构等行业政策因素的影响,运用单箱结构因子法对预测结果进行优化,使得预测精度达到了98.75%。因此,优化后的组合模型较单一的模型能更好地表现高值卷烟销量时间序列的变化趋势,给出更好的预测结果。 展开更多
关键词 高值卷烟销量 时间序列 向量自回归 var PROPHET
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基于VAR和EGARCH的投资者情绪对股市收益率的影响研究 被引量:2
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作者 高振斌 梁兴碧 《浙江大学学报(理学版)》 CAS CSCD 北大核心 2023年第4期434-441,454,共9页
借鉴国内外已有成果,用主成分分析法将2个主观指标与4个客观指标相结合,形成一个能有效衡量投资者情绪的综合指标,其能反映6个原始指标的大部分信息,且与股市收益率显著相关。在研究投资者情绪波动和股市收益率波动时,用向量自回归(vect... 借鉴国内外已有成果,用主成分分析法将2个主观指标与4个客观指标相结合,形成一个能有效衡量投资者情绪的综合指标,其能反映6个原始指标的大部分信息,且与股市收益率显著相关。在研究投资者情绪波动和股市收益率波动时,用向量自回归(vector autoregression,VAR)模型探索了二者间的关系;考虑证券市场信息的不对称性,运用了指数广义自回归条件异方差(exponential generalized autoregressive conditional heteroskedasticity,EGARCH)模型。研究表明,投资者消极悲观情绪对股市收益率的冲击作用大于积极乐观情绪;投资者情绪受收益率下降的冲击影响远大于收益率上涨的影响。 展开更多
关键词 投资者情绪 向量自回归模型(var) 指数广义自回归条件异方差(EGARCH)模型
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Short Term Forecasting Performances of Classical VAR and Sims-Zha Bayesian VAR Models for Time Series with Collinear Variables and Correlated Error Terms
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作者 M. O. Adenomon V. A. Michael O. P. Evans 《Open Journal of Statistics》 2015年第7期742-753,共12页
Forecasts can either be short term, medium term or long term. In this work we considered short term forecast because of the problem of limited data or time series data that is often encounter in time series analysis. ... Forecasts can either be short term, medium term or long term. In this work we considered short term forecast because of the problem of limited data or time series data that is often encounter in time series analysis. This simulation study considered the performances of the classical VAR and Sims-Zha Bayesian VAR for short term series at different levels of collinearity and correlated error terms. The results from 10,000 iteration revealed that the BVAR models are excellent for time series length of T=8 for all levels of collinearity while the classical VAR is effective for time series length of T=16 for all collinearity levels except when ρ = -0.9 and ρ = -0.95. We therefore recommended that for effective short term forecasting, the time series length, forecasting horizon and the collinearity level should be considered. 展开更多
关键词 Short term Forecasting vector autoregressive (var) BAYESIAN var (Bvar) Sims-Zha Prior COLLINEARITY Error Terms
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A Simulation Study on the Performances of Classical Var and Sims-Zha Bayesian Var Models in the Presence of Autocorrelated Errors
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作者 M. O. Adenomon V. A. Michael O. P. Evans 《Open Journal of Modelling and Simulation》 2015年第4期146-158,共13页
It is well known that a high degree of positive dependency among the errors generally leads to 1) serious underestimation of standard errors for regression coefficients;2) prediction intervals that are excessively wid... It is well known that a high degree of positive dependency among the errors generally leads to 1) serious underestimation of standard errors for regression coefficients;2) prediction intervals that are excessively wide. This paper set out to study the performances of classical VAR and Sims-Zha Bayesian VAR models in the presence of autocorrelated errors. Autocorrelation levels of (-0.99, -0.95, -0.9, -0.85, -0.8, 0.8, 0.85, 0.9, 0.95, 0.99) were considered for short term (T = 8, 16);medium term (T = 32, 64) and long term (T = 128, 256). The results from 10,000 simulation revealed that BVAR model with loose prior is suitable for negative autocorrelations and BVAR model with tight prior is suitable for positive autocorrelations in the short term. While for medium term, the BVAR model with loose prior is suitable for the autocorrelation levels considered except in few cases. Lastly, for long term, the classical VAR is suitable for all the autocorrelation levels considered except in some cases where the BVAR models are preferred. This work therefore concludes that the performance of the classical VAR and Sims-Zha Bayesian VAR varies in terms of the autocorrelation levels and the time series lengths. 展开更多
关键词 Simulation PERFORMANCES vector Autoregression (var) CLASSICAL var Sims-Zha Prior BAYESIAN var (Bvar) Autocorrelated Errors
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On the Performances of Classical VAR and Sims-Zha Bayesian VAR Models in the Presence of Collinearity and Autocorrelated Error Terms
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作者 M. O. Adenomon V. A. Michael O. P. Evans 《Open Journal of Statistics》 2016年第1期96-132,共37页
In time series literature, many authors have found out that multicollinearity and autocorrelation usually afflict time series data. In this paper, we compare the performances of classical VAR and Sims-Zha Bayesian VAR... In time series literature, many authors have found out that multicollinearity and autocorrelation usually afflict time series data. In this paper, we compare the performances of classical VAR and Sims-Zha Bayesian VAR models with quadratic decay on bivariate time series data jointly influenced by collinearity and autocorrelation. We simulate bivariate time series data for different collinearity levels (﹣0.99, ﹣0.95, ﹣0.9, ﹣0.85, ﹣0.8, 0.8, 0.85, 0.9, 0.95, 0.99) and autocorrelation levels (﹣0.99, ﹣0.95, ﹣0.9, ﹣0.85, ﹣0.8, 0.8, 0.85, 0.9, 0.95, 0.99) for time series length of 8, 16, 32, 64, 128, 256 respectively. The results from 10,000 simulations reveal that the models performance varies with the collinearity and autocorrelation levels, and with the time series lengths. In addition, the results reveal that the BVAR4 model is a viable model for forecasting. Therefore, we recommend that the levels of collinearity and autocorrelation, and the time series length should be considered in using an appropriate model for forecasting. 展开更多
关键词 vector Autoregression (var) Classical var Bayesian var (Bvar) Sims-Zha Prior COLLINEARITY Autocorrelation
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基于GMR和VAR的复杂工况下齿轮箱早期异常检测
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作者 李鑫 沈希 +2 位作者 左洪福 李伟男 马新宇 《机械设计与制造工程》 2023年第8期87-92,共6页
针对复杂工况下齿轮箱的全寿命周期振动信号进行早期异常检测分析。首先,使用时域同步平均算法对原始数据进行预处理;其次,为了减小工况变化对信号的干扰,基于齿轮运行残差(GMR)信号去除基础啮合频率及其谐波信号,运用EVIEWS软件建立向... 针对复杂工况下齿轮箱的全寿命周期振动信号进行早期异常检测分析。首先,使用时域同步平均算法对原始数据进行预处理;其次,为了减小工况变化对信号的干扰,基于齿轮运行残差(GMR)信号去除基础啮合频率及其谐波信号,运用EVIEWS软件建立向量自回归(VAR)模型并计算残差;最后,通过计算残差的峭度、标准差和均方根等判断齿轮异常发生的时间点,并与基于时域同步平均的方法进行对比。结果表明,所提方法能够在第109号文件检测出齿轮箱发生早期故障,比现有方法提前20个文件发现异常,为齿轮箱的早期故障诊断和维修决策奠定了基础。 展开更多
关键词 齿轮箱 时域同步平均 齿轮运行残差 向量自回归模型 故障检测
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互联网及交通发展对广西旅游经济效率的影响——基于PVAR模型的实证分析
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作者 崔梓楠 周武生 《科技和产业》 2023年第15期128-134,共7页
利用DEA-Malmquist指数测算2005—2019年广西14个地级市全要素生产率,构建面板向量自回归(PVAR)模型探究互联网及交通发展对广西旅游经济效率的影响,并对两者的影响作用机制差异进行分析。研究发现:从短期看,互联网及交通发展显著提升... 利用DEA-Malmquist指数测算2005—2019年广西14个地级市全要素生产率,构建面板向量自回归(PVAR)模型探究互联网及交通发展对广西旅游经济效率的影响,并对两者的影响作用机制差异进行分析。研究发现:从短期看,互联网及交通发展显著提升了广西旅游经济效率;从长期看,互联网及交通发展对广西旅游经济效率的作用呈先上升后逐渐减弱趋势,但前者提升作用效果显现更快;从作用机制看,互联网发展加快了要素投入向产出的转化进程,而交通发展则确保了产出成果的实现。 展开更多
关键词 旅游经济效率 面板向量自回归(Pvar)模型 互联网发展 交通发展 DEA-MALMQUIST指数
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绿色创新效率与产业结构升级的互动关系研究--基于城市面板数据的PVAR分析
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作者 张玲梅 王金河 《荆楚理工学院学报》 2023年第2期56-62,共7页
以全国284个城市为样本,综合运用Super-SBM模型、ArcGIS可视化分析、面板向量自回归(PVAR)模型等方法,测算城市绿色创新效率,分析时空分布特征,并对城市绿色创新效率与产业结构升级的互动关系进行检验。结果表明:城市绿色创新效率与产... 以全国284个城市为样本,综合运用Super-SBM模型、ArcGIS可视化分析、面板向量自回归(PVAR)模型等方法,测算城市绿色创新效率,分析时空分布特征,并对城市绿色创新效率与产业结构升级的互动关系进行检验。结果表明:城市绿色创新效率与产业结构升级存在自我加强机制;城市绿色创新效率与产业结构升级存在相互促进关系。最后对城市提高绿色创新效率,优化产业结构提出相应的建议。 展开更多
关键词 绿色创新效率 产业结构升级 向量自回归模型
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中国海洋产业结构升级与海洋生态效率关系研究——基于PVAR模型的实证分析
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作者 黑朱峰 王好辉 +1 位作者 乔毅 马骋 《青岛大学学报(自然科学版)》 CAS 2023年第2期117-122,共6页
采用考虑非期望产出的数据包络分析(SBM)模型构建海洋生态效率评价指标体系,选取2006—2018年中国11个沿海省份的海洋产业结构升级和海洋生态效率的面板数据,建立面板向量自回归(PVAR)模型,从海洋产业结构升级的视角实证分析了如何提高... 采用考虑非期望产出的数据包络分析(SBM)模型构建海洋生态效率评价指标体系,选取2006—2018年中国11个沿海省份的海洋产业结构升级和海洋生态效率的面板数据,建立面板向量自回归(PVAR)模型,从海洋产业结构升级的视角实证分析了如何提高海洋生态效率。研究结果表明,在1%的显著水平上,海洋产业结构升级和海洋生态效率对自身为负向影响;海洋生态效率对海洋产业结构升级为正向影响;海洋产业结构升级在10%的显著水平上对海洋生态效率为负向影响。 展开更多
关键词 海洋产业结构升级 海洋生态效率 面板向量自回归模型 数据包络分析模型
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基于改进BVAR模型和MS-VECM模型的能源消费分析 被引量:1
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作者 王星 《重庆工商大学学报(自然科学版)》 2023年第6期111-118,共8页
针对向量自回归模型(VAR)的高维估计问题,结合贝叶斯理论提出了一种融合正态-逆Wishart共轭先验分布的估计方法。在该估计方法中,所提出的模型引入Metropolis-Hastings(MH)算法,从以往数据集中确定先验分布超参数,并通过设定与模型尺寸... 针对向量自回归模型(VAR)的高维估计问题,结合贝叶斯理论提出了一种融合正态-逆Wishart共轭先验分布的估计方法。在该估计方法中,所提出的模型引入Metropolis-Hastings(MH)算法,从以往数据集中确定先验分布超参数,并通过设定与模型尺寸相关的收缩系数从而进行估计。与传统VAR模型相比,基于贝叶斯理论的估计方法可在保留相关样本信息的同时控制过度拟合,具有较好的稳健性和有效性。此外,在改进的BVAR模型基础上,结合区制转移技术与误差修正模型提出了MS-BVECM模型,该模型能够有效分析经济周期内各变量之间长期与短期均衡状态变化,当短期内经济变量受到波动而与长期均衡状态发生偏离时,误差修正模型机制会使其逐渐重新回到长期均衡状态,以保证模型的稳健性。最后,以重庆市为例,利用所提模型对其能源消费、产业结构升级和经济增长的动态关系进行了分析与预测并提供了可行建议。 展开更多
关键词 向量自回归模型 正态-逆Wishart共轭先验分布 贝叶斯理论 误差修正模型 能源消费
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