UNEQUALLY SPACED PANEL DATA REGRESSIONS WITH AR(1) DISTURBANCES

1999 ◽  
Vol 15 (6) ◽  
pp. 814-823 ◽  
Author(s):  
Badi H. Baltagi ◽  
Ping X. Wu
Keyword(s):  
Panel Data ◽  
Least Squares ◽  
Serial Correlation ◽  
Weighted Least Squares ◽  
Generalized Least Squares ◽  
Unequally Spaced ◽  
Panel Data Regression ◽  
Data Regression ◽  
Wide Range ◽  
Invariant Test

This paper deals with the estimation of unequally spaced panel data regression models with AR(1) remainder disturbances. A feasible generalized least squares (GLS) procedure is proposed as a weighted least squares that can handle a wide range of unequally spaced panel data patterns. This procedure is simple to compute and provides natural estimates of the serial correlation and variance components parameters. The paper also provides a locally best invariant test for zero first-order serial correlation against positive or negative serial correlation in case of unequally spaced panel data.

scholarly journals Penyaluran Kredit dan Tingkat Likuiditas: Bukti Empiris pada Bank Umum di Indonesia

2021 ◽  
Vol 9 (1) ◽  
pp. 138
Author(s):  
Arnoldus Hesron Bhoka ◽  
Sari Yuniarti ◽  
Mohammad Burhan
Keyword(s):  
Panel Data ◽  
Stock Exchange ◽  
Generalized Least Squares ◽  
Bank Lending ◽  
Estimation Model ◽  
Return On Assets ◽  
Panel Data Regression ◽  
Data Regression ◽  
Positive Effect ◽  
Unbalanced Panel Data

This paper examines the effect of bank lending on liquidity. We use the loan-to-deposit ratio as a proxy for liquidity and total loan as a proxy for bank lending. We also consider the measurement of liquidity with non-performing loans (NPL) and return on assets (ROA) as control variables. The sample used is the banks listed on the Indonesia Stock Exchange as many as 42 banks with a total of 184 observations from unbalanced panel data. The analysis used is panel data regression (generalized least squares) with random effects as the best estimation model. We find bank lending to have a positive effect on liquidity, especially for banks that go public. We argue that banks avoid bankruptcy by increasing the proportion of reserves to absorb risk. The results support the “risk absorption” hypothesis (Berger Bouwman, 2009). We also find that return on assets (ROA) has a significant effect on liquidity, but non-performing loans (NPL) have no significant effect on liquidity, proving that banks has managed their reserves by absorbing risk properly.

scholarly journals KAJIAN KETIMPANGAN WILAYAH DI KAWASAN SUBOSUKAWONOSRATEN TAHUN 2001-2016

2019 ◽  
Vol 8 (3) ◽  
pp. 288
Author(s):  
Yetti Anita Sari ◽  
Sri Rum Giyarsih ◽  
Evita Hanie Pangaribowo
Keyword(s):  
Developing Countries ◽  
Panel Data ◽  
Weighted Least Squares ◽  
Regional Disparity ◽  
Theil Index ◽  
Enrollment Rate ◽  
Analysis Techniques ◽  
Agriculture Sector ◽  
Panel Data Regression ◽  
Data Regression

Regional disparity was a common problem in developing countries. Different regional potentials result in disparity between regions. This study aims to analyze regional disparity in Subosukwonosraten region during 2001-2016 and to determine factors that affect regional disparity in Subosukawonosraten. Analysis techniques used in this study were entropy theil index and panel data regression. The result showed that regional disparity in Subosukawonosraten tends to increase during 2001-2016. Showed by the results of the total theil index in 2001 was 8.8133 to 12.4879 in 2016. The results of panel data regression fixed effect with Weighted Least Squares were share indsutry sector and share agriculture sector have the negative and significant impact on regional disparity. Enrollment rate, morbidity, and population growth have the positive and significant impact on regional disparity.

scholarly journals The Cross-Provincial Data of Life Expectancy Effect on Pension Fund in Indonesia

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Sari Lestari Zainal Ridho ◽  
Habsah Binti Haji Mohamad Sabli ◽  
Heri Setiawan
Keyword(s):  
Panel Data ◽  
Life Expectancy ◽  
Financial Services ◽  
Pension Fund ◽  
Random Effect ◽  
Generalized Least Squares ◽  
Pension Funds ◽  
Expectancy Effect ◽  
Panel Data Regression ◽  
Data Regression

The data presented in this research is an observational cross-province study of life expectancy and pension funds. The data were extracted from the published database of Statistic Indonesia and Indonesia Financial Services Authority, covering a period of 2015 to 2019. The collected data were analyzed; using a panel data regression model on random effect assumptions with Generalized Least Squares. The finding of this research shows that there is a positive and significant effect of life expectancy on pension funds. This research paper data will assist in promoting the opportunity for pensions fund business or institution.

A mechanism to improve the allocation of public investment funds

2020 ◽  
Vol 26 (7) ◽  
pp. 1522-1533
Author(s):  
A.V. Larionov
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Public Investment ◽  
Allocative Efficiency ◽  
Investment Funds ◽  
The Public ◽  
Panel Data Regression ◽  
Data Regression ◽  
Efficiency And Effectiveness ◽  
Effective System

Subject. This article deals with the issue of improving the public investment allocative efficiency. Objectives. The article aims to develop an approach to improve the efficiency and effectiveness of public investment in the economy. Methods. The study is based on a panel data regression with random effects. Conclusions and Relevance. All sectors of the economy have different demand for investment resources attracted, determined by operational and technological aspects. The results of the study can be used to develop an effective system of public investment.

Determinants Of Capital Structure For Multinational And Domestic Companies In India: Panel Data Regression Model

2019 ◽  
Vol 118 (7) ◽  
pp. 147-154
Author(s):  
K. Maheswari ◽  
Dr. J. Gayathri ◽  
Dr. M. Babu ◽  
Dr.G. Indhumathi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Regression Model ◽  
Business Risk ◽  
Return On Assets ◽  
Panel Data Regression ◽  
Data Regression ◽  
Return On Capital ◽  
Domestic Companies ◽  
The Capital Structure

The capital structure refers to the components of capital needed to establish and expand its business activities. The study was made with an objective to examine the determinants of capital structure of multinational and domestic companies listed in S&P BSE automobile sector. The study concluded that there is significant impact on capital structure determinants such as size, business risk, non debt shield tax, return on assets, tangibility, profit, return on capital employed and liquidity on the capital structure of multinational and domestic companies of Indian Automobile Sector.  

FAKTOR DETERMINAN PEMBENTUK STRUKTUR MODAL PADA PERUSAHAAN SEKTOR FARMASI PERIODE 2012 - 2016

2017 ◽  
Vol 2 ◽  
pp. 241-250
Author(s):  
Neng Ria Kanita ◽  
Hendryadi Hendryadi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Firm Size ◽  
Stock Exchange ◽  
Pharmaceutical Manufacturing ◽  
Manufacturing Companies ◽  
Purposive Sampling ◽  
Panel Data Regression ◽  
Data Regression ◽  
Partial Effects

This study aims to examine the simultaneous and partial effects of profitability, liquidity, and firm size on capital structure. The sample is 10 pharmaceutical manufacturing companies listed in Indonesia Stock Exchange period 2012-2016, using purposive sampling. The technique of analysis used is panel data regression (pooled regression). The results showed that the selected model is the fixed effect. Simultaneously NPM, CR, and Firm Size have a significant effect on capital structure. Partially NPM has a negative and significant effect on capital structure. CR partially have a negative and not significant effect on capital structure. Partially Firm Size have a positive and significant effect on capital structure. Variables that have a significant effect on capital structure are NPM and Firm Size. While CR does not significantly affect the capital structure. Keywords: Capital Structure, Profitability, Liquidity, Firm Size

A Study of Multilayered Profitability Analysis by Using DuPont Model: Evidence from Indian Pharmaceutical Industry

2021 ◽  
pp. 097215092199305
Author(s):  
Pinku Paul
Keyword(s):  
Panel Data ◽  
Pharmaceutical Industry ◽  
Profit Margin ◽  
Pharmaceutical Firms ◽  
Sustainable Performance ◽  
Profitability Analysis ◽  
Panel Data Regression ◽  
Data Regression ◽  
Negative Effect ◽  
Positive Effect

Profitability is used as a prime indicator to measure the sustainable performance of an organization. The current study made an attempt to apply the DuPont model to investigate the multilevel profitability determinants for the pharmaceutical industry of India. The study also estimates an empirical model to predict the association of profitability with factors such as profit margin, asset utilization, leverage, interest load and tax load of firms in the pharmaceutical industry of India. For this purpose, a dataset for 170 companies from 2010–2011 to 2018–2019 was analysed initially by using panel data regression followed by stepwise panel data regression. The study successfully applied and tested the DuPont model with respect to the firms of the pharmaceutical industry in India. It was found that the factors such as profit margin, asset utilization and leverage had a significant positive effect on the firms’ profitability and the factor interest load had a significant negative effect on the firms’ profitability. The tax load does not have an impact on the profitability of the pharmaceutical firms in India. These findings are expected to provide a guide for understanding the profitability of the firms in a better way.

Using information from singletons in fixed-effects estimation: xtfesing

2020 ◽  
Vol 20 (4) ◽  
pp. 965-975
Author(s):  
Laura Magazzini ◽  
Randolph Luca Bruno ◽  
Marco Stampini
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Panel Data Regression ◽  
Data Regression ◽  
Method Of Moments Estimator ◽  
Fixed Effects Estimation

In this article, we describe the xtfesing command. The command implements a generalized method of moments estimator that allows exploiting singleton information in fixed-effects panel-data regression as in Bruno, Magazzini, and Stampini (2020, Economics Letters 186: Article 108519).

Nonparametric panel data regression with parametric cross-sectional dependence

2021 ◽  
Author(s):  
Alexandra Soberon ◽  
Juan M Rodriguez-Poo ◽  
Peter M Robinson
Keyword(s):  
Panel Data ◽  
Monte Carlo Study ◽  
Generalized Least Squares ◽  
Linear Estimator ◽  
Dependence Structure ◽  
Finite Sample ◽  
Cross Sectional ◽  
Panel Data Regression ◽  
Local Linear Estimator ◽  
Cross Sectional Dependence

Abstract In this paper, we consider efficiency improvement in a nonparametric panel data model with cross-sectional dependence. A Generalized Least Squares (GLS)-type estimator is proposed by taking into account this dependence structure. Parameterizing the cross-sectional dependence, a local linear estimator is shown to be dominated by this type of GLS estimator. Also, possible gains in terms of rate of convergence are studied. Asymptotically optimal bandwidth choice is justified. To assess the finite sample performance of the proposed estimators, a Monte Carlo study is carried out. Further, some empirical applications are conducted with the aim of analyzing the implications of the European Monetary Union for its member countries.

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