scholarly journals Corruption and Its Effects on Sustainable Economic Performance

2019 ◽  
Vol 6 (2) ◽  
pp. 12
Author(s):  
Michael Appiah ◽  
Derrick Yaw Idan Frowne ◽  
Anita Idan Frowne
Keyword(s):  
Model Selection ◽  
Human Development ◽  
Economic Performance ◽  
Fixed Effects ◽  
Theoretical Perspective ◽  
Fixed Effects Model ◽  
Data Set ◽  
Hausman Test ◽  
Explanatory Variables ◽  
Independent Variables

<p>The study examines corruption and its effects on achieving sustainable economic performance in Africa with a data set from 2002-2017. The Hausman Test for determining the appropriate model selection between Random and Fixed effects was employed with the fixed effects model of estimation chosen to be the appropriate method of estimation indicating that the degree of relationship and significant between corruption and sustainable economic performance in negative. The R² explains that 95% of variations in sustainable economic performance in the estimation of prime independent variables. Aside corruption having a negative and insignificant impact on sustainable economic performance, an increase in human development and labour resulted in a positive and significant relations on sustainable economic performance, with the rest of the explanatory variables having a poor and negative affiliation with sustainable economic performance. The above therefore follows the empirical, conventional and theoretical perspective that corruption declines growth and sustainability both domestically and globally.</p>

scholarly journals Not so Harmless After All: The Fixed-Effects Model

2018 ◽  
Vol 27 (1) ◽  
pp. 21-45 ◽  
Author(s):  
Thomas Plümper ◽  
Vera E. Troeger
Keyword(s):  
Model Selection ◽  
Fixed Effects ◽  
Time Varying ◽  
Multiple Model ◽  
Fixed Effects Model ◽  
Omitted Variables ◽  
Hausman Test ◽  
Fixed Effects Estimator ◽  
Time Invariant

The fixed-effects estimator is biased in the presence of dynamic misspecification and omitted within variation correlated with one of the regressors. We argue and demonstrate that fixed-effects estimates can amplify the bias from dynamic misspecification and that with omitted time-invariant variables and dynamic misspecifications, the fixed-effects estimator can be more biased than the ‘naïve’ OLS model. We also demonstrate that the Hausman test does not reliably identify the least biased estimator when time-invariant and time-varying omitted variables or dynamic misspecifications exist. Accordingly, empirical researchers are ill-advised to rely on the Hausman test for model selection or use the fixed-effects model as default unless they can convincingly justify the assumption of correctly specified dynamics. Our findings caution applied researchers to not overlook the potential drawbacks of relying on the fixed-effects estimator as a default. The results presented here also call upon methodologists to study the properties of estimators in the presence of multiple model misspecifications. Our results suggest that scholars ought to devote much more attention to modeling dynamics appropriately instead of relying on a default solution before they control for potentially omitted variables with constant effects using a fixed-effects specification.

scholarly journals EFFECTS OF SELECTED COMPANY-SPECIFIC VARIABLES IN THE DETERMINATION OF COMPANY LEVERAGE: EVIDENCE FROM TEXTILE INDUSTRY OF BANGLADESH

2021 ◽  
pp. 19-29
Keyword(s):  
Textile Industry ◽  
Fixed Effects ◽  
Negative Impact ◽  
Positive Impact ◽  
Stock Exchange ◽  
Fixed Effects Model ◽  
Data Set ◽  
Hausman Test ◽  
Asset Turnover

The purpose of this study is to investigate the effects of profitability, liquidity, size, tangibility, and asset turnover on the leverage of the textile industry of Bangladesh. This paper analyzed 20 companies out of 56 companies listed in the Dhaka Stock Exchange. The data set is for the periods from 2016 to 2019. To find the effects on the dependent variable, the Fixed Effects Model has been used which has been selected using the Hausman test. To test heteroskedasticity, the Breusch-Pagan heteroskedasticity test has been used. The study found size, profitability, and tangibility having a significant effect. While size and tangibility have a positive impact on leverage, profitability has a negative impact. The findings are diversified in nature. The results are not all consistent with the previous studies conducted in different developing countries. So, the policymakers should have in-depth insights while making decisions.

A big data approach to examining social bots on Twitter

2019 ◽  
Vol 33 (4) ◽  
pp. 369-379 ◽  
Author(s):  
Xia Liu
Keyword(s):  
Big Data ◽  
Fixed Effects ◽  
Latent Dirichlet Allocation ◽  
User Generated Content ◽  
Fixed Effects Model ◽  
Data Set ◽  
Information Distortion ◽  
Content Type ◽  
Related Information ◽  
Brand Reputation

Purpose Social bots are prevalent on social media. Malicious bots can severely distort the true voices of customers. This paper aims to examine social bots in the context of big data of user-generated content. In particular, the author investigates the scope of information distortion for 24 brands across seven industries. Furthermore, the author studies the mechanisms that make social bots viral. Last, approaches to detecting and preventing malicious bots are recommended. Design/methodology/approach A Twitter data set of 29 million tweets was collected. Latent Dirichlet allocation and word cloud were used to visualize unstructured big data of textual content. Sentiment analysis was used to automatically classify 29 million tweets. A fixed-effects model was run on the final panel data. Findings The findings demonstrate that social bots significantly distort brand-related information across all industries and among all brands under study. Moreover, Twitter social bots are significantly more effective at spreading word of mouth. In addition, social bots use volumes and emotions as major effective mechanisms to influence and manipulate the spread of information about brands. Finally, the bot detection approaches are effective at identifying bots. Research limitations/implications As brand companies use social networks to monitor brand reputation and engage customers, it is critical for them to distinguish true consumer opinions from fake ones which are artificially created by social bots. Originality/value This is the first big data examination of social bots in the context of brand-related user-generated content.

scholarly journals The Negative Effect of Smartphone Use on Academic Performance May Be Overestimated: Evidence From a 2-Year Panel Study

2020 ◽  
Vol 31 (11) ◽  
pp. 1351-1362
Author(s):  
Andreas Bjerre-Nielsen ◽  
Asger Andersen ◽  
Kelton Minor ◽  
David Dreyer Lassen
Keyword(s):  
Academic Performance ◽  
Fixed Effects ◽  
Panel Study ◽  
Student Characteristics ◽  
Fixed Effects Model ◽  
Data Set ◽  
Course Characteristics ◽  
Negative Effect ◽  
Smartphone Use ◽  
The Relationship

In this study, we monitored 470 university students’ smartphone usage continuously over 2 years to assess the relationship between in-class smartphone use and academic performance. We used a novel data set in which smartphone use and grades were recorded across multiple courses, allowing us to examine this relationship at the student level and the student-in-course level. In accordance with the existing literature, our results showed that students’ in-class smartphone use was negatively associated with their grades, even when we controlled for a broad range of observed student characteristics. However, the magnitude of the association decreased substantially in a fixed-effects model, which leveraged the panel structure of the data to control for all stable student and course characteristics, including those not observed by researchers. This suggests that the size of the effect of smartphone usage on academic performance has been overestimated in studies that controlled for only observed student characteristics.

scholarly journals COMPOSITION OF THE JOB-SEEKER STOCK IN LABOUR MARKET MATCHING :A STOCHASTIC FRONTIER APPROACH

2016 ◽  
Vol 3 (1) ◽  
pp. 63
Author(s):  
Sanna Mari Hynninen
Keyword(s):  
Labour Market ◽  
Technical Efficiency ◽  
Fixed Effects ◽  
Labour Force ◽  
Stochastic Frontier ◽  
Matching Function ◽  
Fixed Effects Model ◽  
Job Seekers ◽  
Data Set ◽  
Local Labour

This paper investigates the technical efficiency of labour market matching taking a stochastic frontierapproach. The data set consists of monthly data from 145 Local Labour Offices (LLOs) in Finland over theperiod 1995/01-2004/09. The true fixed-effects model is utilised in order to separate cross-sectionalheterogeneity from inefficiency. According to the results, there are notable differences in matching efficiencybetween regions, and these differences contribute significantly to the number of filled vacancies. If all regionswere as efficient as the most efficient one, the number of total matches per month would increase by over 10%. If inefficiency had no role in the matching function, the number of matches would increase by almost 24 %.The weight of the composition of the job-seeker stock and other environmental variables in the determinationof matching inefficiency is on average 61 %. In particular, job seekers out of the labour force and highlyeducated job seekers improve technical efficiency in the matching function

scholarly journals Media and Economic Growth: Country Groups Difference via Panel Data

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Viktoriia Ahapova
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Press Freedom ◽  
Foreign Direct Investments ◽  
Fixed Effects Model ◽  
Data Set ◽  
The Press ◽  
Per Capita

The present article investigates the link between economic growth, namely GDP per capita, and the media activity represented with the indicator of the press freedom alongside other factors such as infrastructure, institutional conditions, and foreign direct investments. A panel of 179 countries was used for the period from 2000 to 2015. In particular, we run two panel data analysis models, fixed effects and random effects models, and examined their output with Hausman’s specification test, which pointed the fixed effects model as more efficient for the presented data set. However due to the presence of serial correlation, heteroskedastic, and cross-panel dependence, a Prais-Winsten regression with panel corrected standard errors (PCSE) was implemented. The comparative analysis of models of four country groups, divided by GNI per capita, was conducted. Both statistically significant correlation coefficients and models’ output provided evidence of an association between economic growth and the press activity.

scholarly journals Governance and Domestic Investment in Africa

2019 ◽  
Vol 8 (1) ◽  
pp. 63-80 ◽  
Author(s):  
Chimere Okechukwu Iheonu
Keyword(s):  
Fixed Effects ◽  
Principal Component ◽  
Domestic Investment ◽  
Fixed Effects Model ◽  
African Countries ◽  
Cross Sectional ◽  
Data Set ◽  
Governance Indicators ◽  
World Governance Indicators ◽  
The Impact

The study empirically examined the impact of governance on domestic investment in 16 African countries with a balanced panel data set, between the years 2002 and 2015. The study employed six unbundled governance indicators from the World Bank, World Governance Indicators and constructed three bundled governance indicators using the Principal Component Analysis. The Driscoll and Kraay Fixed Effects model which accounts for serial correlation, groupwise heteroskedasticity and cross-sectional dependence were employed with empirical results revealing that all the indicators of governance positively and significantly influence domestic investment in Africa, except for government effectiveness which happens to be insignificant. Also, Voice/Accountability and the Control of Corruption exert more influence on domestic investment as indicated by their coefficient values. Furthermore, economic growth is also an important factor in explaining domestic investment in Africa. Policy recommendations are discussed.

scholarly journals Do White Police Officers Unfairly Target Black Suspects?

2022 ◽  
Vol 4 (2) ◽  
pp. p12
Author(s):  
John R. Lott, Jr ◽  
Carlisle E. Moody
Keyword(s):  
Panel Data ◽  
Police Officers ◽  
Fixed Effects ◽  
The United States ◽  
Fixed Effects Model ◽  
Discrimination Test ◽  
Data Set ◽  
Unique Data ◽  
Fbi Data ◽  
The City

Using a unique data set we link the race of police officers who kill suspects with the race of those who are killed across the United States. We have data on a total of 2,706 fatal police killings for the years 2013 to 2015. This is 1,333 more killings by police than is provided by the FBI data on justifiable police homicides. We conducted three tests of discrimination. The results of these tests are different. In the first test we find some evidence that white officers are more likely to kill a black suspect who is later found to be unarmed than they are to kill an unarmed white suspect. However, this result could not be confirmed using a fixed effects model on panel data aggregated to the city level. In the second test, we find that white police officers are no more likely to kill an unarmed black suspect than are black or Hispanic officers. The results of this test are confirmed by the panel data version of the test. The third discrimination test indicated that black suspects, whether armed or not, are no more likely to be killed by a white officer than they are to be killed by black or Hispanic officers. Similarly, Hispanic suspects are no more likely to be killed by white offices than officers of other races. These results are also confirmed by panel data analyses. We find that when there is more than one officer on the scene, unarmed black suspects are not more likely to be killed by white police officers than unarmed white suspects. This could be evidence supporting a policy of reducing the number of officers working alone. Also, we find no evidence that body cameras affect either the number of police killings or the racial composition of those killings.

Abstract MP37: Macroeconomic Growth is Associated with Increases in Cardiovascular Mortality in Countries with Lower Social Protection Spending

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Usama Bilal ◽  
Manuel Franco ◽  
Thomas A Glass
Keyword(s):  
Economic Growth ◽  
Cardiovascular Mortality ◽  
Fixed Effects ◽  
Social Protection ◽  
Welfare States ◽  
Time Varying ◽  
Fixed Effects Model ◽  
Data Set ◽  
Macroeconomic Growth ◽  
Cvd Mortality

Background: Macroeconomic growth has been shown to be associated with increases in cardiovascular (CVD) mortality. However, it is unclear whether concurrent social protection policies may mitigate the observed associations. Objective: To study if social protection expenditure modifies the association between macroeconomic growth and cardiovascular mortality. Methods: We included 21 OECD countries from 1980 to 2010 with available data in the Comparative Welfare States Data Set and the WHO Mortality Database. Gross Domestic Product (GDP) was used as a proxy for economic growth. Age-adjusted cardiovascular mortality rates were calculated. Countries were divided into tertiles of average Social Protection expenditure. We used fixed-effect models to study the association of GDP growth with CVD mortality stratified by tertile of social protection expenditure. We included four lagged GDP terms to account for the cyclical nature of GDP. A second fixed-effects model was fitted with time-varying linear and quadratic social protection expenditure and its interaction with GDP. Results: Overall, a 1% increase in GDP was associated with an increase in CVD mortality of 0.5% (95% CI: 0.21-0.83%, p=0.001). In countries with high and medium social protection expenditure, GDP increases were not associated with changes in CVD mortality (p=0.80 and p=0.52 respectively). In countries with the lowest social protection expenditure, a 1% GDP increase was associated with a significant increase in CVD mortality of 0.7% (95% CI: 0.04-1.32% p=0.03). These results were consistent in analysis using time-varying social protection expenditure (Figure). Conclusion: Our results highlight the need for social protection policies to accompany economic growth to mitigate its potential deleterious effects on cardiovascular diseases. Further research should study specific policies that mitigate the harmful effects of macroeconomic growth.

Sign in / Sign up

Export Citation Format

Share Document