scholarly journals Hausman and Taylor Estimator Analysis on The Linear Data Panel Model

Jurnal Varian ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 81-88
Author(s):  
Bernadhita Herindri Samodera Utami ◽  
Agus Irawan ◽  
Miswan Gumanti ◽  
Gilang Primajati
Keyword(s):  
Panel Data ◽  
Linear Model ◽  
Random Effects ◽  
Fixed Effects ◽  
Real Data ◽  
Fixed Effect ◽  
Data Modelling ◽  
Good Estimator ◽  
Panel Model ◽  
Group A

Panel data modelling in the field of econometrics applies two main approaches, namely fixed effect estimators and random effects. The application of the Hausman and Taylor estimator to real data is used to test for fixed effects or random effects based on the idea that the set of estimated coefficients obtained from the fixed effect estimates is taken as a group. A good estimator is an estimator that is as close as possible to represent the characteristics of the population. The characteristics of a good estimator include unbiasedness, efficiency, and consistency. The purpose of this study is to identify the properties of the Hausman and Taylor estimator in the linear model of panel data. Based on the analysis using panel data, it is found that the Hausman and Taylor estimator on the random effects panel data is an estimator that is consistent and efficient even though it is not unbiased.

scholarly journals On modeling and analyzing barley malt data in different years

2019 ◽  
Vol 56 (1) ◽  
pp. 45-57
Author(s):  
Iwona Mejza ◽  
Katarzyna Ambroży-Deręgowska ◽  
Jan Bocianowski ◽  
Józef Błażewicz ◽  
Marek Liszewski ◽  
...  
Keyword(s):  
Linear Model ◽  
Random Effects ◽  
Fixed Effects ◽  
Linear Models ◽  
Model Fitting ◽  
Mixed Linear Model ◽  
Barley Grain ◽  
Barley Malt ◽  
Starting Point ◽  
Quality Coefficient

SummaryThe main purpose of this study was the model fitting of data deriving from a three-year experiment with barley malt. Two linear models were considered: a fixed linear model with fixed effects of years and other factors, and a mixed linear model with random effects of years and fixed effects of other factors. Two cultivars of brewing barley, Sebastian and Mauritia, six methods of nitrogen fertilization and four germination times were analyzed. Three quantitative traits were observed: practical extractivity of the malt, malting productivity, and a quality coefficient Q. The starting point for the statistical analyses was the available experimental material, which consisted of barley grain samples destined for malting. The analyses were performed over a series of years with respect to fixed or random effects of years. Due to the strong differentiation of the years of the study and some significant interactions of factors with years, annual analyses were also carried out.

scholarly journals Trade-Off Variables and Market Value: An Estimated Panel Data Study of Quoted Small and Medium Scale Enterprises from Nigeria

2021 ◽  
Vol 04 (08) ◽  
Author(s):  
Anyamaobi Chukwuemeka ◽  
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Significant Relationship ◽  
Firm Value ◽  
Fixed Effects ◽  
Market Value ◽  
Equity Capital ◽  
Trade Off ◽  
Medium Scale

This study was undertaken to examine the relationship between trade off variables and market value of quoted small and medium scale enterprises in Nigeria. Secondary data obtained from financial statement of 10 quoted small and medium scale enterprises from 2009 – 2018. Market value was modeled as the function of, non-tax shield, business risk and tangibility. Panel data methods were employed while the fixed and random effects models were used as estimation technique at 5% level of significance. Fixed effects, random effects and pooled estimates were tested while the Hausman test was used to determine the best fit. Panel unit roots and panel cointegration analysis were conducted on the study. The study found that trade off variables has significant relationship with market value of the small and medium scale enterprises. From the regression summary, we conclude that, trade off variables have significant relationship with market value of the small and medium scale enterprises. We recommend that financial managers should institute sound, efficient and coherent capital structure management policies such that will enable them determine the right mix or combination of debt, equity or both that will enhance firms’ value in Nigeria. Firm should expand to a level it does not result to diseconomies of scale and the eventual fall in the value of the small and medium scale enterprises. Government and policy makers should provide an enabling market environment capable of enhancing easy source of capital to enhance firm value in Nigeria. Management of the small and medium scale enterprises should employ more of long-term debt than equity capital in financing their operations, because it results in higher small and medium scale enterprises value. Corporate financial decision makers should employ more of long-term-debt than equity in their financial option. This is in line with the pecking order theory. Management of the small and medium scale enterprises should compare the marginal benefit of using long-term-debt to the marginal costs of long-term-debt before concluding on using it in financing their operations. This is because as shown by this work, long-term-debt impact positively on firm’s value unlike equity capital.

scholarly journals FORECASTING MONEY DEMAND WITH THE INCLUSION OF FINANCIAL INNOVATION FOR THE ASSOCIATION OF SOUTHEAST ASIAN NATIONS: EVIDENCE FROM PANEL DATA ANALYSIS

2019 ◽  
Vol 1 (1) ◽  
pp. 59-74
Author(s):  
Payam Mohammad Aliha ◽  
Tamat Sarmidi ◽  
Fathin Faizah Said
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Random Effects ◽  
Money Demand ◽  
Fixed Effects ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Demand For Money ◽  
Financial Innovations ◽  
The Impact

This paper investigates the impact of financial innovations on the demand for money using a dynamic panel data for 10 ASEAN member states from 2004 to 2012 and attempt to forecast the demand for money during 2013 – 2016 to compare between forecasting performance of the fixed effects model with that of random effects model and also to compare the forecasting accuracy of dynamic forecasting and static forecasting obtained from these two models. An autoregressive model by definition is when a value from a time series is regressed on previous values from that same time series. There are two types of forecasting namely dynamic forecast and static forecast. “Dynamic forecast will take previously forecasted values while static forecast will take actual values to make next step forecast. Panel effects models assist in controlling for unobserved heterogeneity when this heterogeneity is constant over time and correlated (fixed effects) or uncorrelated (random effects) with independent variables. Hausman test indicates that the random-effects model is appropriate. We use the conventional money demand that is enriched with the number of automated teller machines (ATM) to proxy for the effect of financial innovations on money demand. By comparing the magnitude of “Root Mean Squared Error” (RMSE) as a benchmark for the two forecasts (0.1164 for dynamic forecast versus 0.0635 for static forecast) we simply find out that static forecast is superior to dynamic forecast meaning that static forecast provides more accurate forecast compared to a dynamic forecast for the fixed-effects model. Therefore, we conclude the static forecast on the basis of the random-effects model provides the most accurate forecasting. The estimation result of the chosen random-effects regression also indicates the estimated coefficient of ATM is not significant meaning that ATM does not impact money demand in ASEAN countries.

MODELLING AND ESTIMATING INDIVIDUAL AND FIRM EFFECTS WITH COUNT PANEL DATA

2018 ◽  
Vol 48 (3) ◽  
pp. 1049-1078 ◽  
Author(s):  
Jean-François Angers ◽  
Denise Desjardins ◽  
Georges Dionne ◽  
François Guertin
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Fixed Effects ◽  
Parametric Model ◽  
Random Effects Model ◽  
Road Accidents ◽  
Fixed Effects Model ◽  
Insurance Pricing ◽  
Count Panel Data ◽  
Unobservable Factors

AbstractWe propose a new parametric model for the modelling and estimation of event distributions for individuals in different firms. The analysis uses panel data and takes into account individual and firm effects in a non-linear model. Non-observable factors are treated as random effects. In our application, the distribution of accidents is affected by observable and non-observable factors from vehicles, drivers and fleets of vehicles. Observable and unobservable factors are significant to explain road accidents, which mean that insurance pricing should take into account all these factors. A fixed effects model is also estimated to test the consistency of the random effects model.

scholarly journals The Impact of Foreign Direct Investment in the Western Balkan Countries - A Panel Data Analysis

2021 ◽  
Vol 16 (6) ◽  
pp. 1185-1190
Author(s):  
Nexhat Shkodra ◽  
Xhevat Sopi ◽  
Florentina Xhelili Krasniqi
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Panel Data ◽  
Random Effects ◽  
Direct Investment ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Random Effects Model ◽  
Balkan Countries ◽  
The Impact

Foreign Direct Investment (FDI) has a significant effect on the economic growth and development of host economies, but also on international economic integration through globalization. Particular aspects of this topic are being extensively addressed by scientific research in recent decades. The purpose of this paper is to determine whether globalization and through it the Foreign Direct Investment (FDI) has an impact on the economic growth (GDPgr) of the Western Balkan countries which are facing a transitional phase. The relation between FDI and economic growth has been analyzed by employing econometric models with panel data approach: linear regression with poled data, the Fixed Effects model, and the Random-Effects model (GLS). The study is based on panel data of six countries for the period between 2004-2018, obtained by the World Bank. The results of the Random Effects model (GLS) shown that lagged FDI has a significant impact on the economic growth (GDPgr) of the Western Balkans (p<0.05%), as well as gross capital formation (Cap) and government expenditure (Gov) whereas export (Ex) has been excluded from the model. The results also shown that there are significant differences in the factors influencing economic growth among countries in the region (LM Method - Breusch-Pagan test; p=0.02455 < 0.05).

scholarly journals Estimating the impact of export costs on Vietnam‟s export

2018 ◽  
Vol 1 (Q5) ◽  
pp. 74-81
Author(s):  
Tu Thi Cam Mai
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Fixed Effects ◽  
Trade Costs ◽  
Export Growth ◽  
International Competition ◽  
Data Set ◽  
Factors Affecting ◽  
Domestic Trade ◽  
The Impact

In the context of increasing international competition, production and export costs are the two crucial factors affecting the competitiveness and sustainability of developing ountries’ export growth The p per hen e fo use on estim ting the imp t of export ost on Vien m’s export value. This paper employed panel data set which covers the annual export from 2001 to 2013 of 70 Vietnamese major exporters with 910 observations. Hausman – Taylor (1981) test is used to compare the Random-effects (RE) and Fixed-effects (FE) estimations to determine the most appropriate. The findings confirmed that export cost plays an import nt role in the Vietn m’s export perform n e in the period 2001-2013. The determinants of Vietn m’s export v lue re tr e ost (-2.965), Vietn m’s GDP (0 658) importer’s GDP (0 413) importer’s popul tion (0 289) importer’s openness (0.252). This suggests that the Vietnamese Government should attempt to reduce domestic trade costs to enhance competitiveness and boost export growth sustainably.

scholarly journals Board of Directors’ Size and Firm Performance: Evidence from Non-Financial French Firms Listed on CAC 40

2020 ◽  
Vol 15 (2) ◽  
pp. 46-61
Author(s):  
Hemza Boussenna
Keyword(s):  
Firm Performance ◽  
Panel Data ◽  
Board Of Directors ◽  
Random Effects ◽  
Fixed Effects ◽  
Optimal Number ◽  
Board Size ◽  
The Relationship ◽  
Positive Effect

AbstractThe study aims to investigate the relationship between board size and firm’s performance for a sample of non-financial French firms listed on the CAC 40 between 2005 and 2017. We estimated the firm’s performance using two types of metrics, the accounting-based measures (ROA and ROE) and the market-based measures (Tobin Q and MTB). By applying the panel data regressions (fixed-effects and random-effects), the findings show that there is a positive effect of board size on firm performance. In addition, our results show that the optimal number of the board size should be between 13 and 17 members in order to achieve good performance for non-financial French firms.

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