Econometrics最新文献_第2页

On the Validity of Granger Causality for Ecological Count Time Series 论生态计数时间序列格兰杰因果关系的有效性

IF 1.5

Econometrics Pub Date : 2024-05-09 DOI: 10.3390/econometrics12020013

Konstantinos G. Papaspyropoulos, Dimitris Kugiumtzis

{"title":"On the Validity of Granger Causality for Ecological Count Time Series","authors":"Konstantinos G. Papaspyropoulos, Dimitris Kugiumtzis","doi":"10.3390/econometrics12020013","DOIUrl":"https://doi.org/10.3390/econometrics12020013","url":null,"abstract":"Knowledge of causal relationships is fundamental for understanding the dynamic mechanisms of ecological systems. To detect such relationships from multivariate time series, Granger causality, an idea first developed in econometrics, has been formulated in terms of vector autoregressive (VAR) models. Granger causality for count time series, often seen in ecology, has rarely been explored, and this may be due to the difficulty in estimating autoregressive models on multivariate count time series. The present research investigates the appropriateness of VAR-based Granger causality for ecological count time series by conducting a simulation study using several systems of different numbers of variables and time series lengths. VAR-based Granger causality for count time series (DVAR) seems to be estimated efficiently even for two counts in long time series. For all the studied time series lengths, DVAR for more than eight counts matches the Granger causality effects obtained by VAR on the continuous-valued time series well. The positive results, also in two ecological time series, suggest the use of VAR-based Granger causality for assessing causal relationships in real-world count time series even with few distinct integer values or many zeros.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":"33 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140936600","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

Short-Term Hourly Ozone Concentration Forecasting Using Functional Data Approach 利用功能数据法预测短期每小时臭氧浓度

IF 1.5

Econometrics Pub Date : 2024-05-05 DOI: 10.3390/econometrics12020012

Ismail Shah, Naveed Gul, Sajid Ali, Hassan Houmani

{"title":"Short-Term Hourly Ozone Concentration Forecasting Using Functional Data Approach","authors":"Ismail Shah, Naveed Gul, Sajid Ali, Hassan Houmani","doi":"10.3390/econometrics12020012","DOIUrl":"https://doi.org/10.3390/econometrics12020012","url":null,"abstract":"Air pollution, especially ground-level ozone, poses severe threats to human health and ecosystems. Accurate forecasting of ozone concentrations is essential for reducing its adverse effects. This study aims to use the functional time series approach to model ozone concentrations, a method less explored in the literature, and compare it with traditional time series and machine learning models. To this end, the ozone concentration hourly time series is first filtered for yearly seasonality using smoothing splines that lead us to the stochastic (residual) component. The stochastic component is modeled and forecast using a functional autoregressive model (FAR), where each daily ozone concentration profile is considered a single functional datum. For comparison purposes, different traditional and machine learning techniques, such as autoregressive integrated moving average (ARIMA), vector autoregressive (VAR), neural network autoregressive (NNAR), random forest (RF), and support vector machine (SVM), are also used to model and forecast the stochastic component. Once the forecast from the yearly seasonality component and stochastic component are obtained, both are added to obtain the final forecast. For empirical investigation, data consisting of hourly ozone measurements from Los Angeles from 2013 to 2017 are used, and one-day-ahead out-of-sample forecasts are obtained for a complete year. Based on the evaluation metrics, such as R2, root mean squared error (RMSE), and mean absolute error (MAE), the forecasting results indicate that the FAR outperforms the competitors in most scenarios, with the SVM model performing the least favorably across all cases.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":"13 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882196","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

Stein-like Common Correlated Effects Estimation under Structural Breaks 结构断裂下的斯坦因类共同相关效应估计

IF 1.5

Econometrics Pub Date : 2024-04-18 DOI: 10.3390/econometrics12020011

Shahnaz Parsaeian

引用次数: 0

The Gini and Mean Log Deviation Indices of Multivariate Inequality of Opportunity 多变量机会不平等的基尼指数和平均对数偏差指数

IF 1.5

Econometrics Pub Date : 2024-04-17 DOI: 10.3390/econometrics12020010

Marek Kapera, Martyna Kobus

引用次数: 0

A Pretest Estimator for the Two-Way Error Component Model 双向误差分量模型的预测试估计器

IF 1.5

Econometrics Pub Date : 2024-04-16 DOI: 10.3390/econometrics12020009

Badi H. Baltagi, Georges Bresson, Jean-Michel Etienne

{"title":"A Pretest Estimator for the Two-Way Error Component Model","authors":"Badi H. Baltagi, Georges Bresson, Jean-Michel Etienne","doi":"10.3390/econometrics12020009","DOIUrl":"https://doi.org/10.3390/econometrics12020009","url":null,"abstract":"For a panel data linear regression model with both individual and time effects, empirical studies select the two-way random-effects (TWRE) estimator if the Hausman test based on the contrast between the two-way fixed-effects (TWFE) estimator and the TWRE estimator is not rejected. Alternatively, they select the TWFE estimator in cases where this Hausman test rejects the null hypothesis. Not all the regressors may be correlated with these individual and time effects. The one-way Hausman-Taylor model has been generalized to the two-way error component model and allow some but not all regressors to be correlated with these individual and time effects. This paper proposes a pretest estimator for this two-way error component panel data regression model based on two Hausman tests. The first Hausman test is based upon the contrast between the TWFE and the TWRE estimators. The second Hausman test is based on the contrast between the two-way Hausman and Taylor (TWHT) estimator and the TWFE estimator. The Monte Carlo results show that this pretest estimator is always second best in MSE performance compared to the efficient estimator, whether the model is random-effects, fixed-effects or Hausman and Taylor. This paper generalizes the one-way pretest estimator to the two-way error component model.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":"1 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140571831","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

Biases in the Maximum Simulated Likelihood Estimation of the Mixed Logit Model 混合对数模型最大模拟似然估计中的偏差

IF 1.5

Econometrics Pub Date : 2024-03-27 DOI: 10.3390/econometrics12020008

Maksat Jumamyradov, Murat Munkin, William H. Greene, Benjamin M. Craig

引用次数: 0

Public Debt and Economic Growth: A Panel Kink Regression Latent Group Structures Approach 公共债务与经济增长：面板 Kink 回归潜在群体结构方法

IF 1.5

Econometrics Pub Date : 2024-03-05 DOI: 10.3390/econometrics12010007

Chaoyi Chen, Thanasis Stengos, Jianhan Zhang

引用次数: 0

Introduction to the Special Issue “High-Dimensional Time Series in Macroeconomics and Finance” 特刊 "宏观经济学和金融学中的高维时间序列 "导言

IF 1.5

Econometrics Pub Date : 2024-02-22 DOI: 10.3390/econometrics12010006

Benedikt M. Pötscher, Leopold Sögner, Martin Wagner

引用次数: 0

Multivariate Stochastic Volatility Modeling via Integrated Nested Laplace Approximations: A Multifactor Extension 通过集成嵌套拉普拉斯逼近法建立多变量随机波动模型：多因素扩展

IF 1.5

Econometrics Pub Date : 2024-02-19 DOI: 10.3390/econometrics12010005

João Pedro Coli de Souza Monteneri Nacinben, Márcio Laurini

引用次数: 0

Influence of Digitalisation on Business Success in Austrian Traded Prime Market Companies—A Longitudinal Study 数字化对奥地利主要市场上市公司商业成功的影响--纵向研究

IF 1.5

Econometrics Pub Date : 2024-02-09 DOI: 10.3390/econometrics12010004

Christa Hangl

{"title":"Influence of Digitalisation on Business Success in Austrian Traded Prime Market Companies—A Longitudinal Study","authors":"Christa Hangl","doi":"10.3390/econometrics12010004","DOIUrl":"https://doi.org/10.3390/econometrics12010004","url":null,"abstract":"Software investments can significantly contribute to corporate success by optimising productivity, stimulating creativity, elevating customer satisfaction, and equipping organisations with the essential resources to adapt and thrive in a rapidly changing market. This paper examines whether software investments have an impact on the economic success of the companies listed on the Austrian Traded Prime market (ATX companies). A literature review and qualitative content analysis are performed to answer the research questions. For testing hypotheses, a longitudinal study is conducted. Over a ten-year period, the consolidated financial statements of the businesses under review are evaluated. A panel will assist with the data analysis. This study offers notable distinctions from other research that has investigated the correlation between digitalisation and economic success. In contrast to prior studies that relied on surveys to assess the level of digitalisation, this study obtained the required data by conducting a comprehensive examination of the annual reports of all the organisations included in the analysis. The regression analysis of all businesses revealed no correlation between software expenditures and economic success. The regression models were subsequently calculated independently for financial and non-financial companies. The correlation between software investments and economic success in both industries is evident.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":"14 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139758546","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