Studies in Nonlinear Dynamics & Econometrics最新文献_第3页

Challenges and Opportunities for Twenty First Century Bayesian Econometricians: A Personal View 二十一世纪贝叶斯计量经济学的挑战与机遇：个人观点

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2024-03-11 DOI: 10.1515/snde-2024-0003

Herman K. van Dijk

{"title":"Challenges and Opportunities for Twenty First Century Bayesian Econometricians: A Personal View","authors":"Herman K. van Dijk","doi":"10.1515/snde-2024-0003","DOIUrl":"https://doi.org/10.1515/snde-2024-0003","url":null,"abstract":"This essay is about Bayesian econometrics with a purpose. Specifically, six societal challenges and research opportunities that confront twenty first century Bayesian econometricians are discussed using an important feature of modern Bayesian econometrics: conditional probabilities of a wide range of economic events of interest can be evaluated by using simulation-based Bayesian inference. The enormous advances in hardware and software have made this Bayesian computational approach a very attractive vehicle of research in many subfields in economics where novel data patterns and substantial model complexity are predominant. In this essay the following challenges and opportunities are briefly discussed, including the scientific results obtained in the twentieth century leading up to these challenges: Posterior and predictive analysis of everything: connecting micro-economic causality with macro-economic issues; the need for speed: model complexity and the golden age of algorithms; learning about models, forecasts and policies including their uncertainty; temporal distributional change due to polarisation, imbalances and shocks; climate change and the macroeconomy; finally and most importantly, widespread, accessible, advanced high-level training.","PeriodicalId":501448,"journal":{"name":"Studies in Nonlinear Dynamics & Econometrics","volume":"291 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140115746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generalized Autoregressive Conditional Betas: A New Multivariate Score-Driven Filter 广义自回归条件 Betas：一种新的多元分数驱动过滤器

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2024-03-07 DOI: 10.1515/snde-2023-0019

Szabolcs Blazsek, August Jörding, Simran Rai

{"title":"Generalized Autoregressive Conditional Betas: A New Multivariate Score-Driven Filter","authors":"Szabolcs Blazsek, August Jörding, Simran Rai","doi":"10.1515/snde-2023-0019","DOIUrl":"https://doi.org/10.1515/snde-2023-0019","url":null,"abstract":"In this paper, we extend the recent Gaussian autoregressive conditional beta (Gaussian-ACB) model from the literature on score-driven models. In the new asset pricing model, named the t generalized ACB (t-GACB) model, a multivariate score-driven filter for the t-distribution drives dynamic interaction effects among the beta coefficients. We present the econometric formulation and statistical inference for the t-GACB model, which we apply to 15 stocks from the United States (US) from 1999 to 2022. In our empirical application, we use the three Fama–French factors as asset pricing factors, and we also use the Volatility Index, TED Spread, and ICE BofA US High Yield Index Option-Adjusted Spread as exogenous explanatory variables that influence the beta coefficients. We compare the statistical and realized tracking error performances of the Gaussian-ACB, t-ACB, and t-GACB models, and we find that the t-GACB model improves the Gaussian-ACB model.","PeriodicalId":501448,"journal":{"name":"Studies in Nonlinear Dynamics & Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140071088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Information Content of Inflation Expectations: A Copula-Based Model 通胀预期的信息含量：基于 Copula 的模型

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2024-03-01 DOI: 10.1515/snde-2023-0075

Omid M. Ardakani

引用次数: 0

Controlling Chaotic Fluctuations through Monetary Policy 通过货币政策控制混乱波动

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2024-01-09 DOI: 10.1515/snde-2023-0015

Takao Asano, Akihisa Shibata, Masanori Yokoo

引用次数: 0

Investigating the Impact of Consumption Distribution on CRRA Estimation: Quantile-CCAPM-Based Approach 研究消费分布对 CRRA 估算的影响：基于定量-CCAPM 的方法

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2024-01-08 DOI: 10.1515/snde-2023-0005

Sofia B. Ramos, A. Taamouti, Helena Veiga

{"title":"Investigating the Impact of Consumption Distribution on CRRA Estimation: Quantile-CCAPM-Based Approach","authors":"Sofia B. Ramos, A. Taamouti, Helena Veiga","doi":"10.1515/snde-2023-0005","DOIUrl":"https://doi.org/10.1515/snde-2023-0005","url":null,"abstract":"Abstract Using quantile maximization decision theory, this paper considers a quantile-based Euler equation that states that the asset price is a function of the quantiles of the payoff, consumption growth, the stochastic discount factor, risk aversion, and the distribution of the consumption growth rate. We use a more general distribution assumption (log-elliptical distributions) than the log-normality of the consumption growth rate assumed in the literature. The simulation results show that: (1) the higher the downside risk aversion, the lower the constant relative risk aversion; (2) the heavier the tails of the Student-t distribution, the higher the risk aversion for each level of downside risk aversion; and (3) the curve of the relationship between risk aversion and downside risk aversion shifts upward when the normality assumption is dropped, and the magnitude of this shift is high even for high degrees of freedom of the Student-t distribution. Our results suggest that using normally distributed errors to model stock returns and consumption growth rates could lead to an underestimation of the risk aversion coefficient.","PeriodicalId":501448,"journal":{"name":"Studies in Nonlinear Dynamics & Econometrics","volume":"13 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Examining the Impact of Energy Policies on CO2 Emissions with Information and Communication Technologies and Renewable Energy 利用信息通信技术和可再生能源研究能源政策对二氧化碳排放的影响

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2024-01-04 DOI: 10.1515/snde-2022-0065

Mei Xue, Daniela Mihai, Madalina Brutu, Luigi Popescu, Crenguta Ileana Sinisi, Ajay Bansal, Mady A. A. Mohammad, Taseer Muhammad, Malik Shahzad Shabbir

{"title":"Examining the Impact of Energy Policies on CO2 Emissions with Information and Communication Technologies and Renewable Energy","authors":"Mei Xue, Daniela Mihai, Madalina Brutu, Luigi Popescu, Crenguta Ileana Sinisi, Ajay Bansal, Mady A. A. Mohammad, Taseer Muhammad, Malik Shahzad Shabbir","doi":"10.1515/snde-2022-0065","DOIUrl":"https://doi.org/10.1515/snde-2022-0065","url":null,"abstract":"The world today presents significant environmental concerns for humans, such as smog and warmer temperatures, but we also need to think about how to accomplish economic growth that is sustainable. Therefore, this exploration researches the asymmetric effect of renewable energy consumption, economic growth and financial development on carbon emanation in the emerging economies. For this reason, this investigation uses Panel ARDL and PMG estimator. The consequences of PMG estimator demonstrate that information and communication technologies reduce the carbon emanations in the sample region. Additionally, renewable energy consumption also impedes the carbon emanations. The results also suggest that financial development additionally builds the carbon emissions but the impact is very minor. Finally, economic growth and population are also contributing toward carbon emissions. The power effective recommendation is vital to present the ICT assistance to confine the utilization of obsolete machinery for power generation.","PeriodicalId":501448,"journal":{"name":"Studies in Nonlinear Dynamics & Econometrics","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139373563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Core Inflation Rate for China and the ASEAN-10 Countries: Smoothed Signal for Score-Driven Local Level Plus Scale Models 中国和东盟十国的核心通货膨胀率：分数驱动的地方水平加规模模型的平滑信号

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2024-01-01 DOI: 10.2139/ssrn.4644236

Szabolcs Blazsek, Adrián Licht, A. Ayala, Su-Ping Liu

引用次数: 0

Bayesian Reconciliation of Return Predictability 回报可预测性的贝叶斯调节法

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2023-12-26 DOI: 10.1515/snde-2022-0110

Borys Koval, Sylvia Frühwirth-Schnatter, Leopold Sögner

{"title":"Bayesian Reconciliation of Return Predictability","authors":"Borys Koval, Sylvia Frühwirth-Schnatter, Leopold Sögner","doi":"10.1515/snde-2022-0110","DOIUrl":"https://doi.org/10.1515/snde-2022-0110","url":null,"abstract":"This article considers a stable vector autoregressive (VAR) model and investigates return predictability in a Bayesian context. The bivariate VAR system comprises asset returns and a further prediction variable, such as the dividend-price ratio, and allows pinning down the question of return predictability to the value of one particular model parameter. We develop a new shrinkage type prior for this parameter and compare our Bayesian approach to ordinary least squares estimation and to the reduced-bias estimator proposed in Amihud and Hurvich (2004. “Predictive Regressions: A Reduced-Bias Estimation Method.” Journal of Financial and Quantitative Analysis 39: 813–41). A simulation study shows that the Bayesian approach dominates the reduced-bias estimator in terms of observed size (false positive) and power (false negative). We apply our methodology to a system comprising annual CRSP value-weighted returns running, respectively, from 1926 to 2004 and from 1953 to 2021, and the logarithmic dividend-price ratio. For the first sample, the Bayesian approach supports the hypothesis of no return predictability, while for the second data set weak evidence for predictability is observed. Then, instead of the dividend-price ratio, some prediction variables proposed in Welch and Goyal (2008. “A Comprehensive Look at the Empirical Performance of Equity Premium Prediction.” Review of Financial Studies 21: 1455–508) are used. Also with these prediction variables, only weak evidence for return predictability is supported by Bayesian testing. These results are corroborated with an out-of-sample forecasting analysis.","PeriodicalId":501448,"journal":{"name":"Studies in Nonlinear Dynamics & Econometrics","volume":"79 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139056095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Posterior Manifolds over Prior Parameter Regions: Beyond Pointwise Sensitivity Assessments for Posterior Statistics from MCMC Inference 先验参数区域上的后验平面：超越对 MCMC 推理后验统计的点敏感性评估

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2023-12-22 DOI: 10.1515/snde-2022-0116

Liana Jacobi, C. Kwok, A. Ramírez‐Hassan, N. Nghiem

{"title":"Posterior Manifolds over Prior Parameter Regions: Beyond Pointwise Sensitivity Assessments for Posterior Statistics from MCMC Inference","authors":"Liana Jacobi, C. Kwok, A. Ramírez‐Hassan, N. Nghiem","doi":"10.1515/snde-2022-0116","DOIUrl":"https://doi.org/10.1515/snde-2022-0116","url":null,"abstract":"Abstract Increases in the use of Bayesian inference in applied analysis, the complexity of estimated models, and the popularity of efficient Markov chain Monte Carlo (MCMC) inference under conjugate priors have led to more scrutiny regarding the specification of the parameters in prior distributions. Impact of prior parameter assumptions on posterior statistics is commonly investigated in terms of local or pointwise assessments, in the form of derivatives or more often multiple evaluations under a set of alternative prior parameter specifications. This paper expands upon these localized strategies and introduces a new approach based on the graph of posterior statistics over prior parameter regions (sensitivity manifolds) that offers additional measures and graphical assessments of prior parameter dependence. Estimation is based on multiple point evaluations with Gaussian processes, with efficient selection of evaluation points via active learning, and is further complemented with derivative information. The application introduces a strategy to assess prior parameter dependence in a multivariate demand model with a high dimensional prior parameter space, where complex prior-posterior dependence arises from model parameter constraints. The new measures uncover a considerable prior dependence beyond parameters suggested by theory, and reveal novel interactions between the prior parameters and the elasticities.","PeriodicalId":501448,"journal":{"name":"Studies in Nonlinear Dynamics & Econometrics","volume":"9 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138944714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Financial Condition Indices in an Incomplete Data Environment 不完整数据环境下的财务状况指数

Studies in Nonlinear Dynamics & Econometrics Pub Date : 2023-12-20 DOI: 10.1515/snde-2022-0115

Miguel C. Herculano, Punnoose Jacob

引用次数: 0