scholarly journals China’s Infrastructure Financing and the Role of Infrastructure in Awakening African Economies

2021 ◽  
Vol 18 (2) ◽  
pp. 0-0
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Dynamic Models ◽  
Generalized Method Of Moments ◽  
Empirical Evaluation ◽  
Distinctive Character ◽  
Gmm Estimator ◽  
Insight Into ◽  
Agenda 2063

African economies, through Agenda 2063, recognize that developing infrastructure – transport, electricity, energy, water, and e-connectivity – will be critical for the region to assume a lasting place in the global economic system. As a result, this paper addresses the continent’s infrastructure gap and provides an important insight into the rapidly growing presence of China’s official infrastructure financing in Africa as well as the distinctive character of its involvement. In addition, the paper provides an empirical evaluation of the role of infrastructure in awakening African economies. The generalized-method-of-moments (GMM) estimator for dynamic models of panel data developed by Arellano and Bond (1991), and Arellano and Bover (1995) was employed to estimate an infrastructure-increased growth model.

scholarly journals China's Infrastructure Financing and the Role of Infrastructure in Awakening African Economies

2021 ◽  
Vol 18 (2) ◽  
pp. 1-25
Author(s):  
Michael Mitchell Omoruyi Ehizuelen
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Dynamic Models ◽  
Generalized Method Of Moments ◽  
Empirical Evaluation ◽  
Distinctive Character ◽  
Gmm Estimator ◽  
Insight Into ◽  
Agenda 2063

African economies, through Agenda 2063, recognize that developing infrastructure – transport, electricity, energy, water, and e-connectivity – will be critical for the region to assume a lasting place in the global economic system. As a result, this paper addresses the continent’s infrastructure gap and provides an important insight into the rapidly growing presence of China’s official infrastructure financing in Africa as well as the distinctive character of its involvement. In addition, the paper provides an empirical evaluation of the role of infrastructure in awakening African economies. The generalized-method-of-moments (GMM) estimator for dynamic models of panel data developed by Arellano and Bond (1991), and Arellano and Bover (1995) was employed to estimate an infrastructure-increased growth model.

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 Online Reviews and Product Sales: The Role of Review Visibility

2021 ◽  
Vol 16 (4) ◽  
pp. 638-669
Author(s):  
Miriam Alzate ◽  
Marta Arce-Urriza ◽  
Javier Cebollada
Keyword(s):  
Decision Making ◽  
Dynamic Models ◽  
Generalized Method Of Moments ◽  
Online Reviews ◽  
Consumer Decision Making ◽  
Product Sales ◽  
The Impact ◽  
The Relationship ◽  
The Empirical Analysis

When studying the impact of online reviews on product sales, previous scholars have usually assumed that every review for a product has the same probability of being viewed by consumers. However, decision-making and information processing theories underline that the accessibility of information plays a role in consumer decision-making. We incorporate the notion of review visibility to study the relationship between online reviews and product sales, which is proxied by sales rank information, studying three different cases: (1) when every online review is assumed to have the same probability of being viewed; (2) when we assume that consumers sort online reviews by the most helpful mechanism; and (3) when we assume that consumers sort online reviews by the most recent mechanism. Review non-textual and textual variables are analyzed. The empirical analysis is conducted using a panel of 119 cosmetic products over a period of nine weeks. Using the system generalized method of moments (system GMM) method for dynamic models of panel data, our findings reveal that review variables influence product sales, but the magnitude, and even the direction of the effect, vary amongst visibility cases. Overall, the characteristics of the most helpful reviews have a higher impact on sales.

scholarly journals THE ROLE OF INTEGRATED ISLAMIC COMMERCIAL AND SOCIAL FINANCE IN REDUCING INCOME INEQUALITY IN INDONESIA

2019 ◽  
Vol 5 (2) ◽  
Author(s):  
Arif Widodo
Keyword(s):  
Income Inequality ◽  
Method Of Moments ◽  
Wealth Distribution ◽  
Generalized Method Of Moments ◽  
Advanced Economies ◽  
The Social ◽  
Microfinance Institution ◽  
Islamic Microfinance ◽  
Commercial Finance

Recent years saw the heated debates among prominent economists on the growinginequality in advanced economies, and accordingly, many solutions to this seriousproblem have been put forward. Among the practical-cum-workable solution isprogressive taxation for wealth and income, especially the top one percent. Such asolution, however, has been implemented in Islamic perspective what so-called, zakahwhich is now referred to as social finance. In this paper, using the Gini coefficient datacovering 34 provinces in Indonesia over a decade, we examine whether the role ofsocial finance in tandem with commercial finance can adequately solve the problemof wealth distribution in Indonesia, one of the largest Democratic-Muslim countriesin the world. Using the Generalized Method of Moments (GMM) model, the resultsdemonstrated that Islamic commercial finance solely is proven statistically incapable oftackling inequality while the social finance (zakah) is performing very well in this matterover all specifications. Most importantly, when both are incorporated in a model, theresult showed a significant reduction in income inequality implying that the integratedIslamic finance which can be implemented in both Islamic microfinance institution andIslamic banking is more capable, as opposed to when both are separated, of helpingaddress the income inequality problem in Indonesia.

scholarly journals Determinants of Basmati Exports from Pakistan: A Panel Data Analysis

2021 ◽  
Vol 3 (1) ◽  
pp. 12-18
Author(s):  
Muhammad Munwar Hayat ◽  
Raheela Khatoon
Keyword(s):  
Panel Data ◽  
Method Of Moments ◽  
Negative Impact ◽  
Positive Impact ◽  
Panel Data Analysis ◽  
Generalized Method Of Moments ◽  
Trading Partner ◽  
Dummy Variable ◽  
Export Competitiveness ◽  
The Impact

This paper aims to estimate the impact of different factors of basmati exports from Pakistan to its trading partner. Results are obtained by using the Generalized Method of Moments (GMM) model and panel data methodology with a sample of 22 countries for the period of 2003-2019. To estimate the impact of different variables on basmati exports Generalized Method of Moments (GMM) model is used on the panel dataset. The results revealed that the inflation rate of Pakistan has a negative and significant effect on the export competitiveness of Pakistani basmati. The exchange rate of Pakistan has a positive and significant impact on the basmati export, the population of Pakistan has a negative and significant impact on basmati export. Basmati production in Pakistan also has a significant and negative impact on basmati export. The Gross Domestic Product (GDP) of Pakistan has a significant and positive impact on the basmati export while the GDP of the trading partner has a significant and negative impact on the basmati export. The dummy variable for joint border also has a positive and significant impact on basmati exports of Pakistan.

scholarly journals GEL METHODS FOR NONSMOOTH MOMENT INDICATORS

2010 ◽  
Vol 27 (1) ◽  
pp. 74-113 ◽  
Author(s):  
Paulo M.D.C. Parente ◽  
Richard J. Smith
Keyword(s):  
Empirical Likelihood ◽  
Method Of Moments ◽  
Jacobian Matrix ◽  
Generalized Method Of Moments ◽  
Gmm Estimator ◽  
First Order ◽  
Generalized Empirical Likelihood ◽  
Finite Samples ◽  
Class Of Estimators ◽  
Validity Of Tests

This paper considers the first-order large sample properties of the generalized empirical likelihood (GEL) class of estimators for models specified by nonsmooth indicators. The GEL class includes a number of estimators recently introduced as alternatives to the efficient generalized method of moments (GMM) estimator that may suffer from substantial biases in finite samples. These include empirical likelihood (EL), exponential tilting (ET), and the continuous updating estimator (CUE). This paper also establishes the validity of tests suggested in the smooth moment indicators case for overidentifying restrictions and specification. In particular, a number of these tests avoid the necessity of providing an estimator for the Jacobian matrix that may be problematic for the sample sizes typically encountered in practice.

Estimating Dynamic Panel Data Models in Political Science

2002 ◽  
Vol 10 (1) ◽  
pp. 25-48 ◽  
Author(s):  
Gregory Wawro
Keyword(s):  
Panel Data ◽  
Political Science ◽  
Dynamic Models ◽  
Party Identification ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Panel Data Models ◽  
Dynamic Panel ◽  
Cross Sectional ◽  
Moments Estimators

Panel data are a very valuable resource for finding empirical solutions to political science puzzles. Yet numerous published studies in political science that use panel data to estimate models with dynamics have failed to take into account important estimation issues, which calls into question the inferences we can make from these analyses. The failure to account explicitly for unobserved individual effects in dynamic panel data induces bias and inconsistency in cross-sectional estimators. The purpose of this paper is to review dynamic panel data estimators that eliminate these problems. I first show how the problems with cross-sectional estimators arise in dynamic models for panel data. I then show how to correct for these problems using generalized method of moments estimators. Finally, I demonstrate the usefulness of these methods with replications of analyses in the debate over the dynamics of party identification.

scholarly journals Comparing Credit Risk in Islamic and Conventional Banking Using Bank-Level Panel Data

2020 ◽  
Vol 11 (2) ◽  
pp. 235-262
Author(s):  
Akhmad Akbar Susamto ◽  
Danes Quirira Octavio ◽  
Dyah Titis Kusuma Wardani
Keyword(s):  
Economic Growth ◽  
Credit Risk ◽  
Method Of Moments ◽  
Generalized Method Of Moments ◽  
Dynamic Panel ◽  
Gmm Estimator ◽  
Panel Regressions ◽  
Conventional Banks ◽  
Risk Determinants ◽  
Asset Size

Abstract: This paper investigates if there is a difference in the level of the credit risk of Islamic as compared to the level of credit risk of conventional banks. This paper further investigates the importance of various credit risk determinants and possible differences in how such determinants affect credit risk in Islamic and conventional banking industries. This paper employs dynamic panel regressions using system GMM estimators. The sample includes 11 Islamic and 95 conventional banks in Indonesia throughout 2003-2018. Based on the results, it is concluded that there is no difference in the level of the credit risk of Islamic as compared to that of conventional banks. It is also concluded that credit risk is significantly affected by current and lagged asset size, lagged financing, current profitability, lagged economic growth, and current inflation. The effect of lagged financing, current profitability, and lagged economic growth is different in Islamic and conventional banking.Abstrak: Makalah ini menganalisis apakah terdapat perbedaan antara tingkat risiko kredit pada perbankan syariah dan tingkat risiko kredit pada perbankan konvensional. Makalah ini selanjutnya juga menganalisis signifikansi faktor-faktor yang diduga mempengaruhi risiko kredit dan kemungkinan perbedaan pengaruh faktor-faktor tersebut terhadap risiko kredit pada perbankan syariah dibandingkan pada perbankan konvensional. Makalah ini menggunakan regresi panel dinamis dengan system generalized method of moments (GMM) estimator. Sampel dalam makalah ini mencakup 11 bank syariah dan 95 bank konvensional di Indonesia selama periode 2003-2018. Berdasarkan hasil analisis, dapat disimpulkan bahwa tidak terdapat perbedaan perbedaan antara tingkat risiko kredit pada perbankan syariah dan tingkat risiko kredit pada perbankan konvensional. Begitu pula, dapat disimpulkan bahwa risiko kredit secara signifikan dipengaruhi oleh ukuran aset tahun ini dan tahun lalu, pembiayaan tahun lalu, profitabilitas tahun ini, pertumbuhan ekonomi tahun lalu dan inflasi tahun ini. Pengaruh pembiayaan tahun lalu, profitabilitas tahun ini, dan pertumbuhan ekonomi tahun lalu, secara khusus berbeda pada perbankan syariah dibandingkan pada perbankan konvensional.

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