VARX-L: Structured regularization for large vector autoregressions with exogenous variables

Abstrak: Kualitas pembelajaran dan minat belajar memungkinkan hasil belajar mahasiswa meningkat. Sehingga diharapkan kualitas pembelajaran dan minat belajar mahasiswa tinggi untuk mencapai hasil belajar yang tinggi pula. Penelitian ini bertujuan untuk melihat bahwa kualitas pembelajaran dan minat belajar mahasiswa berpengaruh terhadap peningkatan hasil belajar mahasiswa Akuntansi pada mata kuliah Matematika Ekonomi. Penelitian ini merupakan penelitian survei dengan meggunakan teknik analisis jalur (path analysis), dimana terdapat dua variabel eksogen dan satu variabel endogen. Variabel eksogen berupa kualitas pembelajaran dan minat belajar, sedangkan variabel endogen berupa hasil belajar. Hasil penelitian ini adalah Kualitas Pembelajaran berpengaruh langsung positif terhadap Hasil Belajar, Minat Belajar berpengaruh langsung positif terhadap Hasil Belajar, dan Kualitas Pembelajaran berpengaruh langsung positif terhadap Minat Belajar Mahasiswa. Abstract: The quality of learning and interest in learning allows student learning outcomes to increase. It is hoped that the quality of learning and student interest in learning will be high to achieve high learning outcomes. This study aims to see that the quality of learning and student interest in learning has an effect on improving student learning outcomes in Accounting Economics Mathematics courses. This research is a survey research using path analysis technique, where there are two exogenous variables and one endogenous variable. Exogenous variables are learning quality and learning interest, while endogenous variables are learning outcomes. The results of this study are Learning Quality has a direct positive effect on Learning Outcomes, Learning Interest has a direct positive effect on Learning Outcomes, and Learning Quality has a direct positive effect on Student Learning Interest.

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Identifying Structural Vector Autoregressions Via Changes in Volatility

SSRN Electronic Journal ◽

10.2139/ssrn.2188433 ◽

2012 ◽

Cited By ~ 2

Author(s):

Helmut Luetkepohl

Keyword(s):

Vector Autoregressions ◽

Structural Vector

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Interstate disparities in the performances in combatting COVID-19 in India: efficiency estimates across states

BMC Public Health ◽

10.1186/s12889-020-10051-6 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Shrabanti Maity ◽

Nandini Ghosh ◽

Ummey Rummana Barlaskar

Keyword(s):

Disease Management ◽

Recovery Rate ◽

Tamil Nadu ◽

Health Determinants ◽

Stochastic Production Frontier ◽

Exogenous Variables ◽

Indian States ◽

Secondary Sources ◽

Comparative Efficiency ◽

Long Run

Abstract Background Currently, the novel coronavirus or COVID-19 pandemic poses the greatest global health threat worldwide, and India is no exception. As an overpopulated developing country, it is very difficult to maintain social distancing to restrict the spread of the disease in India. Under these circumstances, it is necessary to examine India’s interstate performances to combat COVID-19. This study aims to explore twin objectives: to investigate the comparative efficiency of Indian states to combat COVID-19 and to unfold the factors responsible for interstate disparities in the efficiency in combatting COVID-19. Methods The stochastic production frontier model was utilized for data analysis. The empirical analysis was facilitated by the inefficiency effects model, revealing the factors that influence interstate variability in disease management efficiency. Three types of variables, namely, output, inputs, and exogenous, were used to measure health system efficiency. The relevant variables were compiled from secondary sources. The recovery rate from COVID-19 was the output variable and health infrastructures were considered as the input variable. On the contrary, the non-health determinants considered to have a strong influence on the efficiency of states’ disease management, but could not be considered as input variables, were recognised as exogenous variables. These exogenous variables were specifically used for the inefficiency analysis. Results The empirical results demonstrated the existence of disparities across Indian states in the level of efficiency in combatting COVID-19. A non-trivial outcome of this study was that Tamil Nadu was the best performer and Manipur was the worst performer of the investigated states. Variables such as elderly people, sex ratio, literacy rate, population density, influenced the efficiency of states, and thus, affected the recovery rate. Conclusion This study argues for the efficient utilisation of the existing health infrastructures in India. Simultaneously, the study suggests improving the health infrastructure to achieve a long-run benefit.

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The Impact of the Selection of Exogenous Variables in the ANFIS Model on the Results of the Daily Load Forecast in the Power Company

Energies ◽

10.3390/en14020345 ◽

2021 ◽

Vol 14 (2) ◽

pp. 345

Author(s):

Janusz Sowinski

Keyword(s):

Load Forecasting ◽

Large Set ◽

Exogenous Variables ◽

Anfis Model ◽

Load Forecast ◽

Forecasting Models ◽

Power Company ◽

Ex Post ◽

Daily Load ◽

Selection Of

Forecasting of daily loads is crucial for the Distribution System Operators (DSO). Contemporary short-term load forecasting models (STLF) are very well recognized and described in numerous articles. One of such models is the Adaptive Neuro-Fuzzy Inference System (ANFIS), which requires a large set of historical data. A well-recognized issue both for the ANFIS and other daily load forecasting models is the selection of exogenous variables. This article attempts to verify the statement that an appropriate selection of exogenous variables of the ANFIS model affects the accuracy of the forecasts obtained ex post. This proposal seems to be a return to the roots of the Polish econometrics school and the use of the Hellwig method to select exogenous variables of the ANFIS model. In this context, it is also worth asking whether the use of the Hellwig method in conjunction with the ANFIS model makes it possible to investigate the significance of weather variables on the profile of the daily load in an energy company. The functioning of the ANFIS model was tested for some consumers exhibiting high load randomness located within the area under supervision of the examined power company. The load curves featuring seasonal variability and weekly similarity are suitable for forecasting with the ANFIS model. The Hellwig method has been used to select exogenous variables in the ANFIS model. The optimal set of variables has been determined on the basis of integral indicators of information capacity H. Including an additional variable, i.e., air temperature, has also been taken into consideration. Some results of ex post daily load forecast are presented.

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Exploring dotcom failure: A mediator modeling approach

Human Systems Management ◽

10.3233/hsm-2004-23407 ◽

2004 ◽

Vol 23 (4) ◽

pp. 257-268

Author(s):

Muhammad A. Razi ◽

J. Michael Tarn

Keyword(s):

Correlation Analysis ◽

Business Model ◽

Business Strategy ◽

Practical Implication ◽

Exogenous Variables ◽

Front End ◽

Endogenous Variables ◽

Strategic Position ◽

Angle Of View ◽

Technology Strategies

In this research, the vital factors responsible for the demise of many dotcoms are identified and investigated. A mediator model is presented to explore possible relationships among the exogenous and endogenous variables in accordance with business and technology strategies. Two major analyses are conducted to examine the primary causes for dotcom failure. The first analysis examines the relationships between exogenous and endogenous variables based on the quasi-empirical findings from 50 failed dotcoms. The second analysis conducts a non-parametric correlation analysis of the variables. The results indicate that exogenous variables, fund and competition, influence the endogenous variables, staff, front-end operation, back-end operation, and business strategy. The practical implication of this study is to provide current and future dotcoms with another angle of view for assessing and adjusting their strategic position by evaluating those critical determinants and their inter-relationships so that a robust business model can be implemented.

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Robust SURE estimates of profitability in the Egyptian insurance market

Statistical Journal of the IAOS ◽

10.3233/sji-200734 ◽

2021 ◽

pp. 1-13

Author(s):

Ahmed H. Youssef ◽

Amr R. Kamel ◽

Mohamed R. Abonazel

Keyword(s):

Robust Regression ◽

Ordinary Least Squares ◽

Seemingly Unrelated Regression ◽

Insurance Market ◽

Insurance Companies ◽

Regression Equations ◽

Robust Estimators ◽

Exogenous Variables ◽

Net Profit ◽

Mm Estimation

This paper proposed three robust estimators (M-estimation, S-estimation, and MM-estimation) for handling the problem of outlier values in seemingly unrelated regression equations (SURE) models. The SURE model is one of regression multivariate cases, which have especially assumption, i.e., correlation between errors on the multivariate linear models; by considering multiple regression equations that are linked by contemporaneously correlated disturbances. Moreover, the effects of outliers may permeate through the system of equations; the primary aim of SURE which is to achieve efficiency in estimation, but this is questionable. The goal of robust regression is to develop methods that are resistant to the possibility that one or several unknown outliers may occur anywhere in the data. In this paper, we study and compare the performance of robust estimations with the traditional non-robust (ordinary least squares and Zellner) estimations based on a real dataset of the Egyptian insurance market during the financial year from 1999 to 2018. In our study, we selected the three most important insurance companies in Egypt operating in the same field of insurance activity (personal and property insurance). The effect of some important indicators (exogenous variables) issued by insurance corporations on the net profit has been studied. The results showed that robust estimators greatly improved the efficiency of the SURE estimation, and the best robust estimation is MM-estimation. Moreover, the selected exogenous variables in our study have a significant effect on the net profit in the Egyptian insurance market.

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