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).

scholarly journals A Crook is a Crook . . . But is He Still a Crook Abroad? On the Effect of Immigration on Destination-Country Corruption

2015 ◽  
Vol 16 (4) ◽  
pp. 464-489 ◽  
Author(s):  
Eugen Dimant ◽  
Margarete Redlin ◽  
Tim Krieger
Keyword(s):  
Method Of Moments ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Destination Country ◽  
Estimation Methods ◽  
Econometric Methodology ◽  
Migration Flows ◽  
The Difference ◽  
Method Of Moments Estimator ◽  
The Impact

AbstractThis paper analyzes the impact of migration on destination-country corruption levels. Capitalizing on a comprehensive dataset consisting of annual immigration stocks of OECD countries from 207 countries of origin for the period 1984-2008, we explore different channels through which corruption might migrate. We employ different estimation methods using fixed effects and Tobit regressions in order to validate our findings. Moreover, we also address the issue of endogeneity by using the Difference- Generalized Method of Moments estimator. Independent of the econometric methodology, we consistently find that while general migration has an insignificant effect on the destination country’s corruption level, immigration from corruption-ridden origin countries boosts corruption in the destination country. Our findings provide a more profound understanding of the socioeconomic implications associated with migration flows.

Non-performing Loans and Moral Hazard in the Indian Banking Sector: A Threshold Panel Regression Approach

2020 ◽  
pp. 097215092092613
Author(s):  
Robin Thomas ◽  
Shailesh Singh Thakur
Keyword(s):  
Panel Data ◽  
Moral Hazard ◽  
Regression Model ◽  
Fixed Effects ◽  
Bank Lending ◽  
Empirical Literature ◽  
Data Set ◽  
Panel Data Regression ◽  
Data Regression ◽  
Indian Banks

This article attempts to examine the effect of non-performing assets (NPA) on behaviour of banks in India. The objectives of this article is to test if lending choices of Indian Banks demonstrate moral hazard and to test whether an increase in NPA ratio of banks raises riskier bank lending. We employ a threshold panel data regression model on a data set retrieved from the Reserve bank of India, which covered 45 commercial banks during the period 2009–2015, to test if lending choices of Indian banks demonstrate moral hazard. The results establish that the moral hazard hypothesis does not hold true for the given sample of India Banks, suggesting that an increase in the NPA ratio does not potentially increase riskier lending in sample banks. We find empirical evidence for the notion that ‘too-big-to-fail’ banks possibly have certain incentives to take higher risks and thus have higher NPA ratios. Graphical approach to NPA threshold explanation reveals presence of threshold; however, it could not be statistically established. Future implications of findings are evaluated. The study seminally adds to the empirical literature on use of fixed effects threshold panel data regression model in the context of Indian banks.

Legal source, institutional quality and FDI flows in Africa

2017 ◽  
Vol 59 (5) ◽  
pp. 687-698 ◽  
Author(s):  
Godfred A. Bokpin ◽  
Lord Mensah ◽  
Michael E. Asamoah
Keyword(s):  
Panel Data ◽  
South African ◽  
Legal System ◽  
Generalized Method Of Moments ◽  
Institutional Quality ◽  
Policy Implications ◽  
African Countries ◽  
Content Type ◽  
Panel Data Regression ◽  
Data Regression

Purpose This paper aims to find out how the legal system interacts with other institutions in attracting Foreign Direct Investment (FDI) into Africa. Design/methodology/approach The authors use annual panel data of 49 African countries over the period 1980 to 2011, and use the system generalized method of moments (GMM) estimation technique and pooled panel data regression. Findings The authors find that the source of a country’s legal system deters FDI inflow as institutions alone cannot bring in the needed quantum of FDI. In terms of trading blocs, it was found that there is negative significant relationship between institutional quality and FDI for South African Development Community (SADC) as well as Economic Community of West Africa States (ECOWAS) countries. Practical implications For policy implications, the results suggest that reliance on institutions alone cannot project the continent to attract the needed FDI. Originality/value Empiricists have devoted considerable effort to estimating the relationship between institutions and FDI on the African continent, but this paper seeks to ascertain the effect of legal systems and institutional quality within African specific trade and regional blocks.

scholarly journals Estimation of Indonesia Wooden Furniture Export Demand Function

2021 ◽  
Vol 9 (3) ◽  
pp. 357-367
Author(s):  
Hanna Sri Meiliani Uli Simangunsong ◽  
Bintang Charles Hamonangan Simangunsong ◽  
Elisa Ganda Togu Manurung
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Demand Function ◽  
Relative Price ◽  
Export Demand ◽  
Fixed Effects Model ◽  
Price And Income Elasticities ◽  
Panel Data Regression ◽  
Data Regression ◽  
Wooden Furniture

The export value of Indonesia’s wooden furniture was sharply decreased by about 31.9% over the period in 2007-2018. On the other hand, global wooden furniture export was increased by 5.8% during the same period. Understanding the behavior of the demand side of Indonesia’s wooden furniture exports that is reflected by its relative price and income elasticities is needed for the policy development of Indonesia’s wooden furniture industry in the future. The objective of this study was to estimate the export demand function of Indonesia wooden furniture using a panel data regression model. Three types of panel data models, such as pooled ordinary least squares model, fixed-effects model, and random effects model, were investigated. The results showed that the export demand function of Indonesia wooden furniture could be well estimated using the fixed effects model. Relative price elasticity and income elasticity were -0.45 and 0.8, respectively. The adjusted R2 value obtained was 0.99. Keywords: export demand function, panel data regression, wooden furniture

scholarly journals Country innovative development: impact of the shadow economy

2020 ◽  
pp. 41-49
Author(s):  
Alina Vysochyna ◽  
Olena Kryklii ◽  
Mariia Minchenko ◽  
Aygun Akbar Aliyeva ◽  
Kateryna Demchuk
Keyword(s):  
Regression Analysis ◽  
Panel Data ◽  
Fixed Effects ◽  
Shadow Economy ◽  
Slovak Republic ◽  
Panel Data Analysis ◽  
Innovative Development ◽  
State Management ◽  
Panel Data Regression ◽  
Data Regression

This article generalizes arguments and counterarguments within the scientific discussion regarding the determination of the influence of illegal economic activity and expansion of the shadow economy on innovative country development. The systematization of the scientific works on the above problems proves that there is no one no complexity and unity in the above-mentioned scientific findings, which, in turn, demonstrates the necessity of further theoretical and empirical search in this sphere. Thus, it was developed a scientific hypothesis about the negative influence of the shadow economy on innovative country development. In order to test this hypothesis it was developed a scientific and methodological approach that consists of several stages: 1) correlation analysis in order to eliminate multicollinearity problem between control variables; 2) analysis of dataset descriptive statistics; 3) running Hausman test in order to clarify specification of the regression model (fixed or random effects model); 4) realization of the panel data regression analysis for the whole country sample and separately for Ukraine, characteristics of its results. Technically all stages of the research are realized with the help of Stata 12/S.E. software. The country sample consists of 9 countries (Azerbaijan, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic, Slovenia, and Ukraine). Time horizon – 2008-2018. Running of the panel data regression analysis (model specification – with fixed effects) allow confirming research hypothesis for the whole country sample (an increase of shadow economy negatively affected innovative country development: an increase of shadow economy to GDP ratio in 1 % leads to the decrease of the Global Innovation Index in 0.5 points). However, it was not proved for Ukraine separately. It leads to the conclusion that innovative development in Ukraine does not highly dependent on the shadow economy scale because of more significant obstacles on the way to innovation adoption (institutional inefficiency, regulatory drawbacks, etc.). Keywords: innovative economic growth, innovative state management, panel data analysis, shadow economy.

Social Factors Associated with the Decline in Caries in Brazilian Children between 1996 and 2010

2016 ◽  
Vol 50 (6) ◽  
pp. 551-559 ◽  
Author(s):  
Angelo Giuseppe Roncalli ◽  
Aubrey Sheiham ◽  
Georgios Tsakos ◽  
Georgia Costa de Araújo-Souza ◽  
Richard G. Watt
Keyword(s):  
Panel Data ◽  
Dental Caries ◽  
Human Development ◽  
Social Factors ◽  
Fixed Effects ◽  
Secondary Analysis ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Relationship ◽  
Brazilian Children

Dental caries levels have declined in children since the 1970s in many countries. Most of the postulated main reasons for the decline are speculative and have not been rigorously evaluated. The objective of this study was to assess the relationship between some social factors and the decline in dental caries in Brazilian 12-year-old children from 1996 to 2010. Secondary analysis of national data was performed in 27 Brazilian state capitals. A panel data regression model with fixed effects and multiple linear regression were used to verify the relationship between the explanatory and the dependent variables and also the time-trend effect. The results showed that the DMFT (decayed, missing, and filled teeth) decreased by about 3% per year, and the percentage of caries-free children increased by 4.5% per year. For DMFT and percentage caries free, the results for the panel data regression showed a significant association for the Human Development Index (HDI) in the adjusted model (p = 0.010). When the overall changes over time were compared, the Gini index had a significant association with the overall change in DMFT in the final model of the multiple regression analysis (p = 0.033). Our results indicate that the maintenance of good levels of human development, which includes better education, income, and longevity, are important factors relating to improving levels of oral health in 12-year-old Brazilian children. However, to accelerate this process in cities with the worst caries situation, income inequality should be tackled.

scholarly journals PEMODELAN DATA KEMISKINAN PROVINSI JAWA TENGAH MENGGUNAKAN FIXED EFFECT SPATIAL DURBIN MODEL

2019 ◽  
Vol 8 (2) ◽  
pp. 220-232
Author(s):  
Siska Alvitiani ◽  
Hasbi Yasin ◽  
Mochammad Abdul Mukid
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Spatial Durbin Model ◽  
Spatial Panel ◽  
Central Java ◽  
Panel Data Regression ◽  
Data Regression ◽  
Spatial Panel Data ◽  
Independent Variable ◽  
Poor Population

Based on data from the Central Statistics Agency, Central Java has 4,20 million people (12,23%) poor population in 2017 with Rp333.224,00 per capita per month poverty line. So, Central Java has got the second rank after East Java as the province which has the highest poor population in indonesia in 2017. In this research use the fixed effects spatial durbin model method for modeling poor population in each city in Central Java at 2014-2017. The spatial durbin model is a spatial regression model which contains a spatial dependence on dependent variable and independent variable. If the spatial dependence on dependent variable or independent variables is ignored, the resulting coefficient estimator will be biased and inconsistent. The fixed effect is one of the panel data regression models which assumes a different intercept value at each observation but fixed at each time, and slope coefficient is constant. The advantage of using fixed effects in spatial panel data regression is able to know the different characteristics in each region. The dependent variable used is poor population in each city in Central Java, and the independent variable is Minimum Wage, Life Expectancy, School Participation Rate 16-18 Years, Expected Years of Schooling, Total Population, and Per Capita Expenditure. The results of the analysis shows that the fixed effects spatial durbin model is significant and can be used. The variables that significantly affect the model are the Life Expectancy and Expected Years of Schooling, and the coefficient of determination (R2) is 99.95%. Keywords: Poverty, Spatial, Panel Data, Fixed Effects Spatial Durbin Model

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