Corporate cash holdings and disclosure violations: an empirical investigation of Jordanian listed companies

Purpose This study aims to examine the impact of low-quality financial statements; that is, disclosure violations reported by the Securities Exchange Commission related to the level of cash holdings (CH) of firms listed on the Amman Stock Exchange (ASE). Design/methodology/approach Using panel data from 107 ASE-listed companies from 2009 to 2018, the study uses generalized method of moment estimation to examine the research hypothesis. This study hypothesize that disclosure violations can affect the level of CH and control for several variables that affect this level. Findings The results show that disclosure violations significantly affect the level of CH and that cash flow, capital expenditure and debt issues have a significantly positive impact on corporate CH. On the other hand, the market to book ratio and sales growth were found to be insignificant. Research limitations/implications The limitations of the research include the fact that information on research and development and equity issues were not available, so were not included in the examination. Practical implications It is recommended that managers enhance the quality of disclosures since this allows them to hold lower levels of cash and exploit more investment opportunities. Policymakers are recommended to supervise firm disclosures closely and create ratings for disclosure quality. Originality/value To the best of the author’s knowledge, this is the first empirical research on the association between proven low-quality disclosures and the level of corporate CH among Jordanian listed companies.

Comparison of M Estimation, S Estimation, with MM Estimation to Get the Best Estimation of Robust Regression in Criminal Cases in Indonesia

Crime incidents that occurred in Indonesia in 2019 based on Survey Based Data on criminal data sourced from the National Socio-Economic Survey and Village Potential Data Collection produced by the Central Statistics Agency recorded 269,324 cases. The high crime rate is caused by several factors, including poverty and population density. Determination of the most influential factors in criminal acts in Indonesia can be done with Regression Analysis. One method of Regression Analysis that is very commonly used is the Least Square Method. However, Regression Analysis can be used if the assumption test is met. If outliers are found, then the assumption test is not completed. The outlier problem can be overcome by using a robust estimation method. This study aims to determine the best estimation method between Maximum Likelihood Type (M) estimation, Scale (S) estimation, and Method of Moment (MM) estimation on Robust Regression. The best estimate of Robust Regression is the smallest Residual Standard Error (RSE) value and the largest Adjusted R-square. The analysis of case studies of criminal acts in Indonesia in 2019 showed that the best estimate was the S estimate with an RSE value of 4226 and an Adjusted R-square of 0.98

The Nexus among Competition, Risk and Performance in Banking Sector of Saudi Arabia

The determination behind this research paper is to inspect the relation among competition, risk, and financial performance in the Saudi Arabian banking sector for 2011-2019. This paper used Two steps Generalized Method of Moment (GMM) as an estimation technique. This study focused on Lerner Index and Herfindahl-Hirschman Index to gauge bank competition and used three alternative measures for risk, namely credit risk, liquidity risk, and z-score. The coefficients of the Lerner Index and Herfindahl-Hirschman Index are significant and positive with profitability which signifies that higher competition in Saudi Arabian banks led to a decrease in profitability which is explained in the Structural Conduct Performance Hypothesis. Z-score shows a significant positive relationship with profitability. Credit risk has a positive relationship with profitability reveals that risk-adjusted returns are being targeted by risk-averse shareholders trying to gain more profits to compensate for the higher credit risk. The outcome of the study provides a comprehensive framework to the Central bank and other regulatory authorities to introduce micro and macro prudential policies that are aligned to the stability of the financial system.

PEMODELAN REGRESI RIDGE ROBUST S,M, MM-ESTIMATOR DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi Kemiskinan di Jawa Tengah Tahun 2020)

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linier regression parameters. If there is a violation of assumptions such as multicolliniearity especially coupled with the outliers, then the regression with OLS is no longer used. One method can be used to solved the multicollinearity and outliers problem is Ridge Robust Regression. Ridge Robust Regression is a modification of ridge regression method used to solve the multicolliniearity and using some estimators of robust regression used to solve the outlier, the estimator including : Maximum likelihood estimator (M-estimator), Scale estimator (S-estimator), and Method of moment estimator (MM-estimator). The case study can be used with this method is data with multicollinearity and outlier, the case study in this research is poverty in Central Java 2020 influenced by life expentancy, unemployment number, GRDP rate, dependency ratio, human development index, the precentage of population over 15 years of age with the highest education in primary school, mean years school. The result of estimation using OLS show that there is a multicollinearity and presence an outliers. Applied the ridge robust regression to case study prove that ridge robust regression can improve parameter estimation. The best ridge robust regression model is Ridge Robust Regression S-Estimator. The influence value of predictor variabels to poverty is 73,08% and the MSE value is 0,00791.

The Impact of Currency Misalignment on Trade Balance of Emerging Market Economies

This study is an attempt to examine the impact of currency misalignment on the trade balance of emerging market economies from 1980 through 2016. It firstly measures the equilibrium RER and corresponding misalignment series of 21 EMEs separately adopting a single equation approach and then includes them in the trade regression together with undervaluation and overvaluation to estimate the dynamic relationship between the trade balance and real exchange rate misalignment employing the system generalized method of moment estimation approach. The study suggests that, being a composite series of undervaluation and overvaluation, higher real exchange rate misalignment helps recover trade imbalances. It also identifies that undervaluation improves trade balance, while overvaluation cuts it down. The study identifies that the misalignment series of RER for most of the EMEs are substantially dominated by overvaluation episodes, and hence the opposing impact of undervaluation and currency misalignment on the trade balance of EMEs is not surprising. From the policy perspective, competitiveness achieved through currency movements helps emerging market economies not only to improve trade balance but also to withstand vulnerability that arises from huge external borrowings creating a strong external payment position.

DETERMINANTS OF FINANCIAL DEVELOPMENT: IMPACT OF HUMAN CAPITAL IN EMERGING MARKETS COUNTRIES

This study aims to examine determinants of financial development and see role of quality of human capital in financial development in 19 Emerging Market countries during 2008-2017. Financial development in this study is proxied using the financial development index to accommodate multi-dimensional of financial development. Estimation is using the dynamic panel method Generalize Method of Moment (GMM). The results show that the quality of human capital has contributed to increasing financial development in emerging market countries in 2008-2017. Meanwhile, trade openness and government expenditure do not have a statistically significant effect and domestic savings have a significant positive effect on financial development.

How Selected Macroeconomic Factors Affect the Corporate Profitability of Transportation and Storage Companies in Selected European Economies

The goal of most companies is to make a certain amount of profit, to which all-important business decisions are a subject. The importance of this goal is evidenced by the fact that profitability indicators belong to the key indicators of business success. Unfortunately, profitability is affected by many often-unpredictable factors, which usually come from the external environment of the company. In this research, these factors are represented by GDP growth rate, inflation rate, reference interest rate, unemployment rate, gross fixed capital formation and the exchange rate against the euro. The aim of the research is to find out whether selected factors influence the company’s profitability or not. Companies of the transportation and storage industry coming from eight selected economies of Central and Eastern Europe are the subject of the analysis. The industry will be analysed at the level of fifteen sub-industries using the Generalized Method of Moment. The data cover the period 2010–2018 and provide information on approximately 25,000 companies. The size of the sample does not allow the results to be summarized in one sentence, but they showed that companies in the selected industry are for the most part negatively affected by the reference interest rate of the economy.

The Impact of Globalization on Forest Growth: Evidence from Multinational Panel Data

Even though some existing literature has studied the impact of globalization on forest growth, this research remains inconclusive; moreover, little clarification has emerged as to whether the influence of globalization on forest growth is consistent among different countries. To fill this research gap, we investigated the impact of globalization on forest growth and considered what factors could change the influence of the former upon the latter. To empirically investigate these essential issues, we utilized cross-country data covering 108 countries during the period 1991–2018 to conduct a system generalized method of moment (GMM) estimation. The baseline results confirm the positive impact of globalization on forest growth, which is also supported by several robustness tests, such as changing the measurements and setting new samples. Furthermore, an increase in globalization would bring about higher forest growth. Aside from this, two specific dimensions of globalization, namely economics and trade, can also protect forest growth. Additionally, a higher FDI strengthens the positive impact of globalization on forest growth, while aging, industrial share, and CO2 emissions weaken it. Finally, the impact of globalization on forests is weaker in democracies, emerging markets, and countries with higher fiscal freedoms, while it is stronger in countries with higher political stability. Our study provides substantial policy implications for governments participating in international treaties related to forest growth. The structure of this paper is organized as follows.

Electromagnetic plane wave diffraction by a cylindrical arc with edges: H-polarized case

An accurate hybrid method (numerical-analytical method) for the diffraction of H-polarized electromagnetic plane wave by perfectly electric conducting cylindrical bodies containing edges and a longitudinal slit aperture is proposed. This method is the combination of the Method of Moment and semi-inversion method. The current density function is expressed as the Chebyshev polynomials forming a complete orthogonal set of basis functions. Then, the initial problem is reduced to a system of linear algebraic equations. After inversion, the unknown coefficients are obtained. Then, near and far-field distributions, radar cross-sections are obtained. The resonances are observed for different values of the aperture size, radius of the arc, and the results are compared with previous outcomes.

Political business cycle and fiscal discipline in Sub-Saharan Africa

We tested the Political Business Cycle theory in Sub-Sahara Africa. To provide an empirical explanation for this nexus, this paper used unbalanced panel data from thirty-six (36) Sub-Saharan African countries between 1990 and 2018. The system Generalized Method of Moment (GMM) developed by Arrelano-Bover/Blundell-Bond was employed to analyze the collected data. The results of the system GMM revealed that the fiscal deficit is significantly large in election years and the deficit spending spills into the year after the election, though not as high as in the election year. We could not, however, find a significant effect in the pre-election year. In addition, we found evidence suggesting that though democracy significantly lowers the fiscal deficit, it promotes higher deficit spending in the election year and the year after the election. Hence, the study established the existence of a political business cycle in Sub-Saharan African countries. The study thus recommends that sound economic policies should be put in place to reduce the persistent deficit in SSA so as to maintain sustainable fiscal health, as well as the sustainability of macroeconomics, particularly enhanced industrialization, as the study found that countries' fiscal deficits are lower in more industrialized countries in the region.