scholarly journals What Does Recent Survey Data Say About the Effect of Corruption on Poverty in Africa?

2020 ◽  
pp. 1-13
Author(s):  
Joseph Eshun ◽  
Justice Ackom Baah
Keyword(s):  
Instrumental Variable ◽  
Fixed Effects ◽  
Random Effect ◽  
Public Institutions ◽  
Living Standards ◽  
Governance Model ◽  
Instrumental Variable Regression ◽  
Regression Techniques ◽  
The Impact ◽  
Poverty Levels

Poverty is perpetuated by increased levels of corruption. It diverts resources, which denies the poor masses their right to enjoy necessities to improve their living standards. To estimate the impact of corruption on poverty, the study relied on the random effect, fixed effects and the instrumental variable regression techniques. The estimates from the instrumental variable regression show that OLS underestimates the effect of corruption on poverty levels in Africa. That's, it shows that the OLS estimates are biased downwards due to inconsistencies as a result of the endogeneity of the levels of corruption. While the instrumental variable technique produces an estimated effect ranging from .805-1.073 increased levels of corruption on lived poverty index, the OLS estimates an impact within a range of approximately .058-.168. This paper confirms the governance model of the effect of corruption on poverty through its effects on reducing the credibility of public institutions. The study thus recommends that public institutions must be strengthened, financed and be equipped to be able to apply the rule of law, thereby helping reduce corruption.

scholarly journals Analysis Of Effect Of ZIS (Zakat, Infaq, And Shadaqah), Regional Domestic Products Of Bruto, Regional Minimum Wage And Inflation On Levels Poverty In Indonesia 2012 – 2016

2019 ◽  
Vol 2 (2) ◽  
pp. 193-211
Author(s):  
Fiky Nila Mustika ◽  
Eni Setyowati ◽  
Azhar Alam
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Random Effect Model ◽  
Secondary Data ◽  
Minimum Wages ◽  
Effect Model ◽  
Panel Data Regression ◽  
The Impact ◽  
Poverty Levels ◽  
Domestic Products

This study investigated the impact of ZIS (Zakat, Infaq, and Sadaqah) Gross Regional Domestic Products, Regional Minimum Wages, and Inflation on Poverty Levels in Indonesia during the 2012-2016 period. .This paper used secondary data in the panel data form. This research conducted a quantitative approach using panel data regression. Based on the results of the panel data testing, the best model chosen is the Random Effect Model (REM). Variables of gross regional domestic products and regional minimum wages have a significant effect on poverty levels in Indonesia while the variables of zakat, infaq, and shadaqah (ZIS) and inflation do not influence the level of poverty in Indonesia.

scholarly journals The Impact of Misspecified Random Effect Distribution in a Weibull Regression Mixed Model

Stats ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 48-76
Author(s):  
Freddy Hernández ◽  
Viviana Giampaoli
Keyword(s):  
Weibull Distribution ◽  
Random Effects ◽  
Mixed Models ◽  
Fixed Effects ◽  
Mixed Model ◽  
Random Effect ◽  
Estimation Procedure ◽  
Weibull Regression ◽  
Two Parameters ◽  
The Impact

Mixed models are useful tools for analyzing clustered and longitudinal data. These models assume that random effects are normally distributed. However, this may be unrealistic or restrictive when representing information of the data. Several papers have been published to quantify the impacts of misspecification of the shape of the random effects in mixed models. Notably, these studies primarily concentrated their efforts on models with response variables that have normal, logistic and Poisson distributions, and the results were not conclusive. As such, we investigated the misspecification of the shape of the random effects in a Weibull regression mixed model with random intercepts in the two parameters of the Weibull distribution. Through an extensive simulation study considering six random effect distributions and assuming normality for the random effects in the estimation procedure, we found an impact of misspecification on the estimations of the fixed effects associated with the second parameter σ of the Weibull distribution. Additionally, the variance components of the model were also affected by the misspecification.

scholarly journals Genetic instrumental variable regression: Explaining socioeconomic and health outcomes in nonexperimental data

2018 ◽  
Vol 115 (22) ◽  
pp. E4970-E4979 ◽  
Author(s):  
Thomas A. DiPrete ◽  
Casper A. P. Burik ◽  
Philipp D. Koellinger
Keyword(s):  
Instrumental Variable ◽  
Fixed Effects ◽  
Genome Wide Association Study ◽  
Body Height ◽  
Outcome Variable ◽  
Endogeneity Bias ◽  
Multiple Indicators ◽  
Instrumental Variable Regression ◽  
Genome Wide ◽  
Polygenic Scores

Identifying causal effects in nonexperimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables [i.e., Mendelian randomization (MR)]. However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in nonexperimental data that would also undermine the ability of MR to correct for endogeneity bias from nongenetic sources. Here, we propose an alternative approach, genetic instrumental variable (GIV) regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGSs) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into nonoverlapping subsamples, we obtain multiple indicators of the outcome PGSs that can be used as instruments for each other and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA.

China’s hukou system and city economic growth: from the aspect of rural–urban migration

2019 ◽  
Vol 12 (1) ◽  
pp. 140-157 ◽  
Author(s):  
Kunling Zhang ◽  
Chunlai Chen ◽  
Jian Ding ◽  
Zhinan Zhang
Keyword(s):  
Economic Growth ◽  
Fixed Effects ◽  
System Reform ◽  
Urban Migration ◽  
Content Type ◽  
Economic Growth Model ◽  
Instrumental Variable Regression ◽  
Regression Techniques ◽  
The City ◽  
Practical Implications

Purpose The purpose of this paper is to evaluate the economic impacts of China’s hukou system and propose the possible direction for future reform. Design/methodology/approach The study develops a framework to incorporate the hukou system into the economic growth model. Using prefecture city-level panel data covering 241 cities over the period 2004–2016 and applying the fixed effects and instrumental variable regression techniques, the authors investigated empirically the impacts of the hukou system on city economic growth. Findings The study provides three main findings. First, the city sector conditionally benefits from labour mobility deregulation that allows migrants to work in cities. Second, the hukou system has different impacts on economic growth among cities with different sizes and administrative levels. Third, to offset the costs of providing exclusive public services to the migrants, the big or high-administrative-level cities can use their high-valued hukou to attract the high-skilled migrants, but the small- or low-administrative-level cities do not have this advantage. Practical implications This study suggests that the key for further hukou system reform is how to deal with the hukou–welfare binding relationship. Originality/value The authors developed a theoretical framework and conducted an empirical analysis on the direct relationship between the hukou system and economic growth to reveal the mechanism of how does the hukou system influence the city economic growth and answer the question of why is the hukou system reform so hard in China. The framework also sheds some lights on explaining the success and failure of the hukou system reforms in the past 40 years.

scholarly journals Port-of-Entry Neighborhood and Its Effects on the Economic Success of Refugees in Sweden

2018 ◽  
Vol 53 (3) ◽  
pp. 671-705 ◽  
Author(s):  
Roger Andersson ◽  
Sako Musterd ◽  
George Galster
Keyword(s):  
Labor Market ◽  
Panel Data ◽  
Ethnic Group ◽  
Instrumental Variable ◽  
Group Composition ◽  
Economic Success ◽  
Instrumental Variable Regression ◽  
Working Age ◽  
Permanent Settlement ◽  
The Impact

We investigate the degree to which the ethnic group composition of “port-of-entry neighborhood” (PoE), the first permanent settlement after immigration, affects the employment prospects of refugees in Sweden during the subsequent 10 years. We use panel data on working-age adults from Iran, Iraq, and Somalia immigrating into Sweden from 1995 to 2004. We control for initial individual and labor market characteristics, use instrumental variable regression to avoid bias from geographic selection, and stratify models by gender and co-ethnic employment and education rates within the neighborhood. We find that the impact of co-ethnic neighbors in the PoE varies dramatically by gender.

scholarly journals Prices of conventional and renewable energy as determinants of sustainable and secure energy development: regression model analysis

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Sandi Knez ◽  
Goran Šimić ◽  
Anica Milovanović ◽  
Sofia Starikova ◽  
Franc Željko Županič
Keyword(s):  
Developing Countries ◽  
Solar Energy ◽  
Fixed Effects ◽  
Sustainable Energy ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Energy Development ◽  
Energy Product ◽  
The Impact

Abstract Background The prices of energy resources are important determinants of sustainable energy development, yet associated with significant unknowns. The estimates of the impact of prices of energy products in the domestic market (for domestic consumers) are rare—hence the importance and novelty of this research. Therefore, the main goal of the paper is to assess the impact of domestic prices of gasoline, gas, coal, and solar energy on sustainable and secure energy future. Methods The research includes 14 countries (of which 7 are developed and 7 are developing countries) and a period of 5 years (2014–2018). The model also includes discrete variables: level of development (developing or developed), and the fact as to whether the country is an energy exporter or not. For the purposes of analysis, the following elements were used: Panel Data Analysis, Linear regression (with random and fixed effects), Durbin–Wu–Hausman test, and Honda test, with the use of R-studio software for statistical computing. Results The research showed that the biggest negative impact on energy sustainability was recorded by an increase in the price of coal and the smallest one by an increase in the price of solar energy. An increase in the price of gasoline has a positive impact, while an increase in the price of gas has no impact. The basic methodological result showed that the fixed effects linear model is more accurate than the random effect model. Conclusions The results of the paper, important as a sustainable energy policy recommendation, showed that the impact of changes in energy product prices is significantly greater in developing countries, but that the status of the country as an energy exporter has no significance. In addition, the paper points to the need to intensify the research on the assessment of the impact of energy product prices for domestic consumers on their ability to pay that price, because with a certain (so far undefined) increase in energy product prices, a certain group of domestic consumers moves into a category that is not in line with sustainable energy development and is extremely undesirable in every respect—energy poverty.

scholarly journals Impact of Full IFRS, Accounting Standards for SMES and Company Demographics on Firms’ Return on Asset and Return on Equity using Panel Data Regression

2019 ◽  
Vol 8 (6S) ◽  
pp. 589-601 ◽  
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Random Effect ◽  
Ordinary Least Squares ◽  
Lagrangian Multiplier ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Real Property ◽  
The Impact

Due to globalization, markets are becoming more interconnected as the companies are engaged in doing cross-border offerings. Currently, competitions are intensified because Domestic organizations discover themselves competing with each nearby opposite numbers and worldwide companies. But one component that hinders SMEs is the need for reliable and similar monetary data. According to Abarca (2014), adoption of a high-quality and consistent set of accounting requirements is critical so as for the businesses to remain competitive in ASEAN member states. This paper ambitions to answer the query, what modified into the extent of the impact of compliance with full IFRS and IFRS for SMEs on profitability of agencies belong to real property enterprise? This paper moreover sought to decide whether there may be a sizeable distinction among the groups’ compliance with the overall PFRS and the PFRS for SMEs and to determine whether or now not there is a massive distinction among the companies’ financial normal overall performance earlier than and after the adoption of the PFRS for SMEs.Paired T-test have become employed in case you need to determine whether there is a big distinction between the agencies’ compliance with the entire PFRS and the PFRS for SMEs and to decide whether or not there may be a big difference some of the groups’ monetary performance earlier than and after the adoption of the PFRS for SMEs. Using STATA, the great appropriate version for every economic ratio on the subject of degree of compliance emerge as determined on. First, take a look at parm command became used to find out which most of the Least Squares Dummy Variable Regression Modes (LSDV1, LSDV2, LSDV3) underneath the Fixed Effects Model is the ideal version. Afterwards, Hausman Fixed Random Test changed into used to pick out out which is more suitable amongst Fixed Effects Model and Random Effects Model. If Fixed Effects Model modified into the more appropriate one, the Wald’s test turn out to be used to determine the best version among Fixed Effects Model and Ordinary Least Squares Model. On the alternative hand, if Random Effects Model became the more suitable one, the Breusch and Pagan Lagrangian Multiplier Test for Random Effect have become used to decide the satisfactory version amongst Random Effects Model and Ordinary Least Squares. Moreover, if Ordinary Least Squares became the splendid model, it is going to be in addition tested to check for heteroscedasticity and multicollinearity. White’s test became used to check for heterescedasticity and Variance Inflation Factor have become used to test if multicollinearity is gift. The results display that the adoption of PFRS for SMEs stepped forward the compliance of Philippine real property SMEs. However, no vast alternate became said inside the financial average performance of those companies (as measured with the resource of cross back on assets and go back on equity). This was further supported by the results of the panel regression. This means that despite having a relatively

scholarly journals The impact of financial variables on systematic risk – An empirical study in manufacturing industry on Ho Chi Minh stock exchange

2017 ◽  
Vol 1 (Q4) ◽  
pp. 88-94
Author(s):  
Minh Tien Pham ◽  
Bich Huy Hai Bui ◽  
Thao Thi Thu Nguyen
Keyword(s):  
Fixed Effects ◽  
Stock Exchange ◽  
Random Effect ◽  
Random Effect Model ◽  
Systematic Risk ◽  
Ordinary Least Squares ◽  
Operating Efficiency ◽  
Manufacturing Companies ◽  
Financial Variables ◽  
The Impact

The aim of this study is to examine the effect of financial variables on systematic risk, using the panel data of 64 manufacturing companies listed in Ho Chi Minh City Stock Exchange (HOSE) during the period of 2011-2015. The three models employed are pooled Ordinary Least Squares (OLS), Random Effect Model (REM), and Fixed Effects Model (FEM). The results of model tests show that FEM is the most suitable to carry out the analysis. In order to increase the efficiency of the model, the tests for model problems are conducted. The results point to the presence of heteroskedasticity problem in the model; therefore, the modified FEM is used to deal with this issue. Empirical evidence from HOSE indicates that leverage has a significantly positive impact while operating efficiency and profitability show significantly negative impact on systematic risk (beta).

scholarly journals The Impact of Ignoring a Crossed Factor in Cross-Classified Multilevel Modeling

2021 ◽  
Vol 12 ◽  
Author(s):  
Soyoung Kim ◽  
Yoonhwa Jeong ◽  
Sehee Hong
Keyword(s):  
Random Effects ◽  
Hierarchical Linear Modeling ◽  
Fixed Effects ◽  
Random Effect ◽  
Information Criteria ◽  
Linear Modeling ◽  
Random Effect Modeling ◽  
Error Bias ◽  
The Impact ◽  
Level 2

The present study investigated estimate biases in cross-classified random effect modeling (CCREM) and hierarchical linear modeling (HLM) when ignoring a crossed factor in CCREM considering the impact of the feeder and the magnitude of coefficients. There were six simulation factors: the magnitude of coefficient, the correlation between the level 2 residuals, the number of groups, the average number of individuals sampled from each group, the intra-unit correlation coefficient, and the number of feeders. The targeted interests of the coefficients were four fixed effects and two random effects. The results showed that ignoring a crossed factor in cross-classified data causes a parameter bias for the random effects of level 2 predictors and a standard error bias for the fixed effects of intercepts, level 1 predictors, and level 2 predictors. Bayesian information criteria generally outperformed Akaike information criteria in detecting the correct model.

scholarly journals The Impact of Remittances on Poverty Alleviation in Selected Emerging Markets

2018 ◽  
Vol 21 (2) ◽  
pp. 51-68 ◽  
Author(s):  
Kunofiwa Tsaurai
Keyword(s):  
Economic Growth ◽  
Emerging Markets ◽  
Fixed Effects ◽  
Poverty Reduction ◽  
Ordinary Least Squares ◽  
Income Per Capita ◽  
Per Capita ◽  
Migrant Remittances ◽  
The Impact ◽  
Poverty Levels

The study explored the impact of remittances on poverty in selected emerging markets. On the theoretical front, the optimistic view argued that remittances inflow into the labour exporting country reduces poverty whereas the pessimistic view proponents said that remittances dependence syndrome retards both economic growth and income per capita. Separately, using two measures of poverty [the poverty headcount ratio at US $1.90 and US $3.10 a day (% of population)] as dependent variables, the fixed effects approach produced results which supported the remittances led poverty reduction (optimistic) hypothesis whereas the pooled ordinary least squares (OLS) framework found that remittances inflow into the selected emerging markets led to an increase in poverty levels. The implication of the findings is that emerging markets should put in place policies that attract migrant remittances in order to reduce poverty levels. They should avoid over‑reliance on remittances as that might retard economic growth and income per capita.

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