• 제목/요약/키워드: Panel Data Approach

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A Comparison of Models for Predicting Discretionary Accruals: A Cross-Country Analysis

  • ACAR, Goksel;COSKUN, Ali
    • The Journal of Asian Finance, Economics and Business
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    • 제7권9호
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    • pp.315-328
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    • 2020
  • In this study, we examined various aspects of discretionary accruals. We compared the power of Jones Model (JM), Modified Jones Model (MJM) and Performance Matched Model (PMM). Furthermore, we tested whether accruals derived from cash flow approach or balance sheet approach provide better results and we investigated the significance of country and industry control variables in models. In order to perform these tests, we constructed thirty equations. The data consists of 319 non-financial companies over five years in the GCC region. We used panel data regression models, and testing suggests us to use random effect model as the most suitable one. The results show that PMM has the highest explanatory power among models and it is followed by JM and MJM, consecutively. Secondly, results reveal that accruals derived from cash flow approach provide more accurate results. Moreover, country dummies are significant in models with cash flow approach and they lose significance in balance sheet approach. We differentiated industries due to two different classifications: the first group with higher number of industries is more precise compared to the second group with a narrower scope and lower number of industries. The model including both industrial and country-wise dummies scores highest in significance.

The efficient data-driven solution to nonlinear continuum thermo-mechanics behavior of structural concrete panel reinforced by nanocomposites: Development of building construction in engineering

  • Hengbin Zheng;Wenjun Dai;Zeyu Wang;Adham E. Ragab
    • Advances in nano research
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    • 제16권3호
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    • pp.231-249
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    • 2024
  • When the amplitude of the vibrations is equivalent to that clearance, the vibrations for small amplitudes will really be significantly nonlinear. Nonlinearities will not be significant for amplitudes that are rather modest. Finally, nonlinearities will become crucial once again for big amplitudes. Therefore, the concrete panel system may experience a big amplitude in this work as a result of the high temperature. Based on the 3D modeling of the shell theory, the current work shows the influences of the von Kármán strain-displacement kinematic nonlinearity on the constitutive laws of the structure. The system's governing Equations in the nonlinear form are solved using Kronecker and Hadamard products, the discretization of Equations on the space domain, and Duffing-type Equations. Thermo-elasticity Equations. are used to represent the system's temperature. The harmonic solution technique for the displacement domain and the multiple-scale approach for the time domain are both covered in the section on solution procedures for solving nonlinear Equations. An effective data-driven solution is often utilized to predict how different systems would behave. The number of hidden layers and the learning rate are two hyperparameters for the network that are often chosen manually when required. Additionally, the data-driven method is offered for addressing the nonlinear vibration issue in order to reduce the computing cost of the current study. The conclusions of the present study may be validated by contrasting them with those of data-driven solutions and other published articles. The findings show that certain physical and geometrical characteristics have a significant effect on the existing concrete panel structure's susceptibility to temperature change and GPL weight fraction. For building construction industries, several useful recommendations for improving the thermo-mechanics' behavior of structural concrete panels are presented.

A Dynamic Approach to Understanding Business Performance

  • Kusuma Indawati HALIM
    • 유통과학연구
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    • 제22권6호
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    • pp.1-10
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    • 2024
  • Purpose: This study's objective is to examine the impact of firm-specific and macroeconomic factors on the business performance of non-cyclical and cyclical sectors in Indonesian listed firms. The evaluation of business performance holds paramount importance for the achievement and long-term viability of a company. Research Design Data and Methodology: The data for 61 non-cyclicals sector companies and 57 cyclicals sector companies was gathered over a 4-year period from 2018-2021. The model integrates firm size, leverage, and sales growth as firm-specific factors, with real GDP growth and inflation rate as macroeconomic variables. ROA and ROE are indicators of a firm's business performance. The regression models are estimated using the distribution of a dynamic approach with Arellano-Bond Panel Generalized Method of Moments (GMM) estimation. Results: The results of the pooled sample indicate that the historical ROA and ROE have a positive relationship with the business performance of all sectors, including both non-cyclical and cyclical industries. The ROE of non-cyclical enterprises is primarily influenced by firm-specific characteristics and macroeconomic influences. Conclusion: To ensure the successful implementation of the distribution of a dynamic approach towards enhancing corporate business performance, organizations need to take into account a combination of firm-specific factors and macroeconomic factors.

Numerical Analysis of Added Resistances of a Large Container Ship in WavesNumerical Analysis of Added Resistances of a Large Container Ship in Waves

  • Lee, Jae-Hoon;Kim, Beom-Soo;Kim, Yonghwan
    • Journal of Advanced Research in Ocean Engineering
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    • 제3권2호
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    • pp.83-101
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    • 2017
  • In this study, the added resistances of the large container ship in head and oblique seas are evaluated using a time-domain Rankine panel method. The mean forces and moments are computed by the near-field method, namely, the integration of the second-order pressure directly on the ship surface. Furthermore, a weakly nonlinear approach in which the nonlinear restoring and Froude-Krylov forces on the exact wetted surface of a ship are included in order to examine the effects of amplitudes of waves on ship motions and added resistances. The computation results for various advance speeds and heading angles are validated by comparing with the experimental data, and the validation shows reasonable consistency. Nevertheless, there exist discrepancies between the numerical and experimental results, especially for a shorter wave length, a higher advance speed, and stern quartering seas. Therefore, the accuracies of the linear and weakly nonlinear methods in the evaluation of the mean drift forces and moments are also discussed considering the characteristics of the hull such as the small incline angle of the non-wall-sided stern and the fine geometry around the high-nose bulbous bow.

Nonlinear structural finite element model updating with a focus on model uncertainty

  • Mehrdad, Ebrahimi;Reza Karami, Mohammadi;Elnaz, Nobahar;Ehsan Noroozinejad, Farsangi
    • Earthquakes and Structures
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    • 제23권6호
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    • pp.549-580
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    • 2022
  • This paper assesses the influences of modeling assumptions and uncertainties on the performance of the non-linear finite element (FE) model updating procedure and model clustering method. The results of a shaking table test on a four-story steel moment-resisting frame are employed for both calibrations and clustering of the FE models. In the first part, simple to detailed non-linear FE models of the test frame is calibrated to minimize the difference between the various data features of the models and the structure. To investigate the effect of the specified data feature, four of which include the acceleration, displacement, hysteretic energy, and instantaneous features of responses, have been considered. In the last part of the work, a model-based clustering approach to group models of a four-story frame with similar behavior is introduced to detect abnormal ones. The approach is a composition of property derivation, outlier removal based on k-Nearest neighbors, and a K-means clustering approach using specified data features. The clustering results showed correlations among similar models. Moreover, it also helped to detect the best strategy for modeling different structural components.

패널 데이터모형을 이용한 지역별 취업자 수 결정요인 추정에 관한 연구 (Estimating the Determinants for employment number by areas : A Panel Data Model Approach)

  • 이현주;김희철
    • 디지털산업정보학회논문지
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    • 제6권4호
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    • pp.297-305
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    • 2010
  • Employment number by areas is composed of various factors for groups and time series. In this paper, we use the panel data for finding various variables and using this, we analyzed the factors that is major influence to employment number by areas. For analysis we looked at employment number by areas, the region for analysis consist of seven groups, that is, the metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 63 time points(2005.01.- 2010.03). We examined the data in relation to the employment number by occupational job, unemployment rate, monthly household income, preceding business composite index, consumer price index, composite stock price index. In looking at the factors which determine employment number by areas job, evidence was produced supporting the hypothesis that there is a significant negative relationship between unemployment rate and monthly household income the consumer price index. The consumer price index and composite stock price index are significant positive relationship, preceding business composite index is positive relationship, it are not significant variables in terms of employment number by areas job.

Macroeconomic and Firm-specific Factors Influencing Non-Performing Loans in Bangladesh: A Panel Data Regression Approach

  • AMIN, Md. Iftekharul;AHSAN, Aumit;Al MUKTADIR, Mahmud;AZAD, Muntasir;REZANUR, Razib Hasan Bin
    • The Journal of Asian Finance, Economics and Business
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    • 제8권12호
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    • pp.95-105
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    • 2021
  • A prerequisite of a sound financial system is effective channeling of financial resources to efficient users; hence maximizing economic and societal welfare. To that end, the prevalence of bad loans in banks in emerging economies is a major policy concern. In an attempt to add to the growing body of literature explaining the interrelationship between macroeconomic and firm-specific factors, and non-performing loans (NPL), this paper examines data from 24 scheduled commercial banks in Bangladesh from 2008 to 2019. Macroeconomic factors as well as firm-specific factors related to profitability, capital strength, and efficiency are considered. Panel data regression analysis is performed to estimate pooled OLS, fixed effects, and random effects models. Following the necessary testing, it was found that the fixed effects model with robust standard error is appropriate. Results show that return on assets and inflation have a negative influence on NPL, but GDP growth has a favorable impact. The paper concludes by asserting that the evidence supports similar findings from studies both in Bangladesh and elsewhere and it is noted that a combination of these macroeconomic and firm-specific factors explains only a small portion of the total variation in NPL.

Corporate Investment Behavior and Level of Participation in the Global Value Chain: A Dynamic Panel Data Approach

  • KUANTAN, Dhaha Praviandi;SIREGAR, Hermanto;RATNAWATI, Anny;JUHRO, Solikin M.
    • The Journal of Asian Finance, Economics and Business
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    • 제8권12호
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    • pp.117-127
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    • 2021
  • This study was conducted to comprehensively identify factors that potentially influence corporate investment behavior, including micro, macro, and sectoral variables. Furthermore, investment behavior was studied across nations based on their participation in the global value chain (GVC), which was evaluated based on commodities, limited manufacturing, advanced manufacturing, and innovative activities. The study uses the dynamic panel data analysis and Generalized Method of Moment (GMM) estimation for a sample of 800 corporations, with data spanning over 2000-2019. The study result shows that in all types of countries, the coefficient lag indicator of capital expenditure statistically has a significant effect on capital expenditure. Sales growth, exchange rate, and GDP have a significant positive effect on corporate investment growth, while DER has a negative effect. In commodity countries, corporate investment is influenced by sales growth, exchange rate, and FCI. The variables that influence corporate investment in manufacturing countries are the FCI, exchange rate, sales growth, GDP, and DER. In innovative countries, variables that significantly affect capital expenditure are DER, GDP, and Tobin Q. In each type of country, the interaction terms between exchange rate and commodity price are positive and statistically significant.

Household, personal, and financial determinants of surrender in Korean health insurance

  • Shim, Hyunoo;Min, Jung Yeun;Choi, Yang Ho
    • Communications for Statistical Applications and Methods
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    • 제28권5호
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    • pp.447-462
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    • 2021
  • In insurance, the surrender rate is an important variable that threatens the sustainability of insurers and determines the profitability of the contract. Unlike other actuarial assumptions that determine the cash flow of an insurance contract, however, it is characterized by endogenous variables such as people's economic, social, and subjective decisions. Therefore, a microscopic approach is required to identify and analyze the factors that determine the lapse rate. Specifically, micro-level characteristics including the individual, demographic, microeconomic, and household characteristics of policyholders are necessary for the analysis. In this study, we select panel survey data of Korean Retirement Income Study (KReIS) with many diverse dimensions to determine which variables have a decisive effect on the lapse and apply the lasso regularized regression model to analyze it empirically. As the data contain many missing values, they are imputed using the random forest method. Among the household variables, we find that the non-existence of old dependents, the existence of young dependents, and employed family members increase the surrender rate. Among the individual variables, divorce, non-urban residential areas, apartment type of housing, non-ownership of homes, and bad relationship with siblings increase the lapse rate. Finally, among the financial variables, low income, low expenditure, the existence of children that incur child care expenditure, not expecting to bequest from spouse, not holding public health insurance, and expecting to benefit from a retirement pension increase the lapse rate. Some of these findings are consistent with those in the literature.

한국의 무역상대국간 무역수지와 환율간의 장기관계분석: 패널분석의 적용 (Bilataral Trade Balance between Korea and Her Trading Partners: Using Panel Approach)

  • 김종구
    • 국제지역연구
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    • 제14권1호
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    • pp.185-202
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    • 2010
  • 이 연구는 1999년 1분기부터 2008년 4분기까지 SITC 10개 산업분류 자료를 이용하여 우리나라 무역상대국인 인도네시아, 인도, 중국, 일본에 대한 무역수지와 환율간의 장기관계를 분석하였다. 실증분석은 소표본 문제를 완화하고 추정과 검정의 효율성을 제고시키기 위하여 비안정적인 패널자료에 대한 패널분석기법을 적용하였다. 그룹간 패널 DOLS로 산업분류별 무역상대국별 무역수지함수를 추정한 결과 패널전체의 경우 인도와 일본, 중국의 경우 Marshall-Lerner 조건을 지지하였으나 인도네시아의 경우 기각하였다. 개별 산업에 대해서는 인도네시아 2개 산업, 인도 5개 산업, 일본 4개 산업, 중국 6개 산업이 Marshall-Lerner 조건을 지지하였다.