Inclusiveness and growth in the EU: a shift from pro-poor to pro-employed at risk of poverty approach

Liberia is labeled at the peak considered as one of the poorest countries in the world. Therefore, Liberia needs to take an effective trade policy approach to promote both domestic and international trade facilitation if it is to achieve sustainable and further economic growth. International trade is the engine for economic development, and it has become one of many economic discussions not only among West African States and member countries but globally that Liberia is no exception to since exports-trade leads to GDP growth and economic development. As a result of frequent trade deficits and Liberia’s economic reliance on extractive commodities for trade in agricultural goods, the study sought to analyze the role of exports-trade on economic growth and development with regard to Liberia. The study was conducted using secondary data generated from the World Bank Development Indicators (WBDI) for the period 2000-2019. The study employed a time series regression model of the Ordinary Least Squares (OLS) and technique by Stock and Wilson (1988) to analyze Liberia’s trade performance using macroeconomic indicators/variables that have an effect on economic growth, such as, Exports, Foreign Direct Investment (FDI), Population growth, Imports, Gross Fixed Capital Formation, (GFCF) and Gross Domestic Product (GDP) as the key indicators of analysis. The regression results obtained from the study on the Ordinary Least Squares tests show a linear association and a straight-line relationship among the variables, namely: export, foreign direct investment, population and economic growth in Liberia. With the estimated results, import has a negative impact and relationship with Liberia’s GDP growth. The effect of export was positive and highly statistically significant.

This study examines the relationship among inflation, economic growth, and imports in Malaysia using annual time-series data from 1970 to 2018. As an open developing economy, Malaysia is highly exposed to external trade dynamics, making imports a critical component of domestic consumption, production, and economic development. Fluctuations in inflation and economic growth are therefore expected to play an important role in shaping import behaviour and overall macroeconomic stability. The study adopts a quantitative research design and utilises secondary data obtained from the World Bank. Imports are specified as the dependent variable, while inflation, measured by the Consumer Price Index (CPI)and economic growth, proxied by Gross Domestic Product (GDP), are treated as independent variables. Prior to estimation, the stationarity properties of the variables are examined using the Augmented Dickey–Fuller (ADF) unit root test. Following confirmation of stationarity after first differencing, the Ordinary Least Squares (OLS) method is employed to estimate the relationship among the variables. Diagnostic tests, including serial correlation and heteroskedasticity tests, are conducted to ensure the robustness and reliability of the estimated model. The empirical results reveal that economic growth has a positive and statistically significant effect on imports, indicating that higher output and income levels stimulate import demand in Malaysia. In contrast, inflation is negatively associated with imports, suggesting that rising price levels suppress import demand by reducing purchasing power and increasing costs. These findings confirm that inflation and economic growth jointly influence import behaviour in Malaysia. Overall, the study provides empirical evidence that macroeconomic stability is essential for sustaining balanced trade performance. The findings offer valuable insights for policymakers in designing effective inflation management and trade strategies to support sustainable economic growth in Malaysia. Keywords: Inflation; Economic Growth; Imports; Malaysia; Ordinary Least Squares

Several empirical works have yielded mixed and controversial results with regard to the effects of FDI on employment and economic growth. The primary focus of this study is to investigate the contribution of FDI to domestic employment levels in the context of the South African economy. The analyses of the study were carried out using the annual time series data from 1980 to 2015. The macroeconomic variables employed in the empirical investigation include employment, FDI, GDP, inflation, trade openness and unit labour costs. The study used secondary data from the South African Reserve Bank and Statistics South Africa database. The study estimated a Vector Autoregressive/ Vector Error Correction Mechanism (VAR/VECM) approach to conduct empirical analysis. However, the study also employed single equation estimation techniques, including the Ordinary Least Squares (OLS), Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS) and Canonical Cointegrating Regression (CCR) models as supporting tools to verify the VAR/VECM results. This study provides strong evidence of a significant negative relationship between FDI and employment levels in the South African economy. Empirical analysis of the study suggests that the effect of economic growth on employment is highly positive and significant in South Africa’s economy. The study recommends that policymakers ought to invest more in productive sectors that aim to promote economic growth and development to boost employment opportunities in South Africa.

This study investigates the relevance of physicochemical properties of 34 NSAIDs to their chemical characteristics using total quadratic indices $q_k(x)$ modeled as pseudographs with atomic number and atomic radius weighting schemes, compared against traditional indices modeled using unweighted graphs. The objective was to assess the predictive capabilities of these indices in modeling drug properties. Multiple Ordinary Least Squares (OLS) regression revealed significant multicollinearity in the models. Principal Component Analysis (PCA) was employed to address this issue, leading to a reduction in multicollinearity, although it was accompanied by a slight decrease in model performance metrics such as \( R^2 \). Despite this, quadratic indices demonstrated competitive performance when compared to traditional indices. Notably, the quadratic indices showed higher relevance in predicting the physicochemical properties complexity (C), molecular weight (MW), refractivity (RV) and polarizability (P) compared to traditional indices. The model validated by parameters like coefficient of determination ($R^{2}$), $p$ - value, standard error (S.E), F-statistic and Durbin-Watson (DW) statistics. These results underscore the potential of quadratic indices in enhancing predictive modeling of drug properties, offering improved insights compared to traditional topological indices.

Relationship between economic growth and mismanaged e-waste: Panel data evidence from 27 EU countries analyzed under the Kuznets curve hypothesis

The relationship between financial sector development and economic growth is a crucial issue for both developing and developed nations. To keep up with the changing world economy, there is need for developing countries like Kenya to develop their financial sectors. Kenya’s financial sector development has had a major role in its economic growth and this study provides a selected review of the literature and the relationship between Kenya’s financial sector and its economic growth. Numerous studies have been done on the effect of the financial sector on economic growth and the general conclusion is that the financial sector plays a central role in economic development and growth of the country. However, there is a limitation of empirical and theoretical work supporting the concept in developing countries. Most of the studies done focus on the direction of causality between finance development and economic growth and their relationship. For this reason, the study set out to analyze the influence of financial sector development on Kenya’s economic growth. The Neo-classical theory of growth was used to inform the study variables; banking sector, export market and economic growth. The study adopted an ex-post facto research design with Ordinary Least Square (OLS) method. The data used was secondary in nature obtained from the Kenya National Bureau of Statistics from the period 2010-2019. The findings revealed that there was a positive influence of financial sector development on economic growth. This implies that financial sector development promotes economic growth in Kenya. In policy terms, the findings, imply that Kenya can accelerate economic growth by improving the financial sector since financial development can be an engine of growth in this country. The study recommended that other major components of the financial sector development apart from the two studied; banking sector and export market, in this paper should be studied and put up in place well -structured policies that will support them and further develop the financial sector with the aspirations under the Kenya Vision 2030. Keywords : Financial sector development, Economic growth DOI: 10.7176/RJFA/12-2-01 Publication date: January 31 st 2021

Financial inclusion involves decreasing the number of unbanked population through series of activities that will enhance the participation in the financial system. The objective of this study is examining financial inclusion and its implications on growth of small and medium sized enterprises (SMEs) in Nigeria from 1992 to 2020 using data obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin. The study used the classical linear regression model using Ordinary least square (OLS) and Dynamic Ordinary Least Square (DOLS) to analyse the data. The outcome of the analysis revealed that the growth of small and medium sized enterprises (SMEs) in Nigeria is positively and significantly influenced by financial inclusion. The findings further revealed that government needs to steer up efforts in ensuring the dissemination of all banking services to reach everyone at affordability fees regardless of income group and location.

Banks credit by usage (working capital, investment and consumer credit) and by economic sectors (agricultural, mining, industrial, trade and services) on Indonesian economic growth explainedthe role of banks credit as a monetary transmission channel. Banks credit for investment, agricultural, industrial, trade and services, have a significant effect on economic growth. Thus, as a growth accelerating factor, investment credit aimed to financing agricultural, industrial, trade and services areable to promote qualified growth of Indonesian economy as well as reducing unemployment rate. This study uses bankscredit data by usage, economic sectors, economic growth and unemployment rate in the period of 1991-2014. Model estimation on the relationship between banks credit by usage on economic growth and unemployment using ECM (Error Correction Mechanism) model, while the relationship between banks credit by economic sectors oneconomic growth using in–difference regressionon OLS (Ordinary Least Square) model.Credit depth as the ratio between banks credit and economic growth is only appropriate for the analysis of banks credit relationship usage on economic growth, while by economic sectors, their role depend on the magnitude of credit portfolio to total banks credit. Keywords: credit by economic sectors; credit by usage; economic growth JEL Codes: E6, O2, O4

This study investigates the impact of agriculture, industry, and the service sector on Nigeria's economic growth from 1990 to 2022, using data obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin. Employing an Ordinary Least Squares (OLS) regression model, the research explores the contributions of these key sectors to Nigeria's Gross Domestic Product (GDP). The findings reveal that the industrial sector has a significant positive effect on GDP, emphasizing its crucial role in driving economic growth. The agricultural sector also contributes positively, though its impact is relatively modest, highlighting the need for modernization and investment to enhance productivity. Surprisingly, the service sector shows a statistically significant negative impact on GDP, contrary to its traditionally recognized role in economic expansion. This anomaly suggests underlying structural issues within the sector that require further investigation. The study's model explains approximately 59.65% of the variation in GDP, with no significant evidence of autocorrelation, heteroskedasticity, or multicollinearity affecting the results. Based on these findings, the study recommends targeted policy interventions to improve agricultural productivity, strengthen industrialization efforts, and reform the service sector to foster balanced and sustainable economic growth in Nigeria.

Background: Nepal, a low-income South Asian country, faces significant challenges in achieving sustainable economic growth. Various macroeconomic determinants such as inflation, government expenditure, foreign direct investment, and net exports play critical roles in shaping its economic trajectory. Despite global research on growth determinants, limited studies focus on Nepal’s context, particularly over the long term. Objective: This study investigates the impact of key macroeconomic determinants—gross fixed capital formation (GFCF), net export (NE), and total expenditure (TE)—on Nepal’s real gross domestic product (RGDP) from 1980 to 2022. Methods: Using time-series data from credible sources like the World Bank and IMF, the research employs an Ordinary Least Squares (OLS) regression model. Diagnostic tests including heteroscedasticity, serial correlation, and normality assessments ensure model reliability. Findings: Gross fixed capital formation significantly positively affects economic growth, while net exports show a negligible and negative relationship with RGDP. Total expenditure positively influences growth, though with modest significance. Diagnostic tests confirm the robustness of the model, with R-squared values indicating high explanatory power. Conclusion: Investments in capital formation drive economic growth in Nepal, while high import-export imbalances and recurrent expenditure hinder progress. The study recommends policy adjustments to enhance trade competitiveness and efficient resource allocation. Novelty: This study provides a comprehensive analysis of Nepal’s economic growth determinants over a four-decade period, bridging research gaps with its detailed econometric approach.

Banks credit by usage (working capital, investment and consumer credit) and by economic sectors (agricultural, mining, industrial, trade and services) on Indonesian economic growth explainedthe role of banks credit as a monetary transmission channel. Banks credit for investment, agricultural, industrial, trade and services, have a significant effect on economic growth. Thus, as a growth accelerating factor, investment credit aimed to financing agricultural, industrial, trade and services areable to promote qualified growth of Indonesian economy as well as reducing unemployment rate. This study uses bankscredit data by usage, economic sectors, economic growth and unemployment rate in the period of 1991-2014. Model estimation on the relationship between banks credit by usage on economic growth and unemployment using ECM (Error Correction Mechanism) model, while the relationship between banks credit by economic sectors oneconomic growth using in–difference regressionon OLS (Ordinary Least Square) model.Credit depth as the ratio between banks credit and economic growth is only appropriate for the analysis of banks credit relationship usage on economic growth, while by economic sectors, their role depend on the magnitude of credit portfolio to total banks credit. Keywords: credit by economic sectors; credit by usage; economic growth JEL Codes: E6, O2, O4

Purpose This study aims to contribute to the ongoing assessment of executive compensation by investigating the nexus between managerial entrenchment factors, adopting a multifaceted perspective encompassing both economic and non-economic dimensions. Design/methodology/approach This research employs pooled cross-sectional Ordinary Least Squares (OLS) regression and Least Squares with Dummy Variables (LSDV) models with fixed effects to examine the determinants of Chief Executive Officer (CEO) compensation. Findings This research identifies firm size, performance (via ROA and Tobin’s Q), and CEO characteristics (age, tenure, stock ownership, MBA degree) as significant determinants of executive compensation at the 0.05 level. In contrast, the prestige of educational institutions, doctoral degrees, and the MBA’s relevance to short-term performance, along with CEO tenure, do not significantly affect pay. Additionally, the study highlights the significance of industry type (manufacturing vs technology) in shaping compensation, emphasizing the role of firm metrics and CEO credentials in designing executive pay packages. Originality/value This research introduces an innovative approach to controlling unobserved heterogeneity and adjusting for the dynamic nature of CEO compensation attributes across diverse CEO characteristics. By integrating both pooled Ordinary Least Squares (OLS) and Least Squares Dummy Variable (LSDV) models, the study addresses the challenges posed by time-invariant variables and unobservable heterogeneity. Such issues have historically skewed the accuracy of traditional OLS models in identifying the comprehensive array of factors—both economic and non-economic—that influence CEO compensation. This novel methodological framework significantly advances the examination of unobservable variables that may vary not only across the firms selected for analysis but also over time periods, thereby offering a more detailed understanding of the determinants of CEO pay.

This study empirically explored economic growth implications of services sector in Nigeria. Time series data for the period 1981 to 2017 were extracted from the Central Bank of Nigeria (CBN) Statistical Bulletins and National Bureau of Statistics (NBS). Data were analyzed using Augumented Dickey Fuller (ADF) unit root test, Phillips-Perron (PP) unit root test, Johansen Cointegration test and Ordinary Least Square (OLS) multiple regression analysis. Empirical findings from the study revealed that financial services (FINS), real estate services (REES)), utilities (UTS), professional, scientific and technical services (PSTS) and information and communication services (IACS) have statistically significant positive relationships with economic growth (RGDP) in Nigeria. A one percent increment in FINS, REES, UTS, PSTS and IACS would cause economic growth to increase by 50.57, 31.76, 22.58, 81.79 and 31.06 percent respectively. The results further showed that education services (EDUCS), human health and social services (HHSS) and inflation rate (INFR) have statistically significant negative correlation with economic growth. A one percent upward adjustment in EDUCS, HHSS and INFR would bring about 0.077, 38.71 and 13.61 percent reductions in economic growth. Based on the findings, government at all levels should offer tariff and tax reduction for investment projects in many services sub-sectors like hotels and restaurants, hospitals, shipping, railways, tourism, telecommunications, distribution and others; public and private policies should be directed towards the adoption of an overall reforming plan where capital and knowledge intensive services should play a prominent role in order to enhance the productivity in the services sector; and there should be creation of enabling environment for services sector to thrive by the various tiers of government through the provision of key infrastructural amenities such as uninterrupted power supply, good roads network and regular water supply. Finally, most services’ subsectors, and especially distribution services should invest much more heavily in knowledge and information and communication technology within their supply chain in order to accelerate the rate of economic growth. Keywords: Services sector, Economic growth, Ordinary least square, Unit root test, Johansen Cointegration test, Nigeria DOI : 10.7176/JPID/49-06 Publication date : April 30 th 2019

This study explored the linkage between financial development, human resources, and economic growth in a group of twenty-five transition countries during the period 1995–2019. The author applied a range of estimations such as Ordinary Least Squares (OLS), fixed effects model, and two-step GMM methods in order to estimate the empirical research model. Different from previous research, financial development in this paper was a proxy variable that was assessed based on the level of outcomes of financial institutions and the financial market in three aspects: depth, access, and efficiency. In addition, the labor force participation rate and the human development index were employed as the comprehensive proxies for human resources. Generally, financial development and human resources exert positive impacts on economic growth. Financial access and financial efficiency boost economic growth, while financial depth does not. Human development was also documented as the driver of economic growth. In addition, the interaction between aggregate financial development and the human development index demonstrated a robust spur to economic growth. These findings contribute to the literature on economic growth and have considerable implications for policymakers in transition economies.

Within the modern perspective of globalization, digitalization may be perceived as a key driver of technological development, a factor strongly affecting economic efficiency and the growth of Gross Domestic Product (GDP). However, this assumption still requires deeper empirical confirmation in developing nations whose economies depend on oil revenues. This paper investigates the causal and cointegration relationship between socioeconomic globalization, digitalization, and its impact on economic growth, using the kingdom of Saudi Arabia (KSA) as a specific case of global economic transformation between 1990 and 2022. Using the Autoregressive Distributed Lag (ARDL) model with various estimation methods, including Ordinary Least Squares (OLS), Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR), we identified the most statistically significant factors contributing to economic growth. Our findings indicate that globalization has a negative and significant effect on GDP per capita at the 1 percent significance level. On the other hand, the results suggest that digitalization significantly contributes to economic growth in the short and long run. From these findings, this paper provides some key policy recommendations for improving the economic outlook of Saudi Arabia and other developing countries.