Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

This paper introduces the expected goals concept to limited overs cricket where ideas are illustrated using the economy rate statistic. The approach is primarily explored as a proof of concept since the detailed data that are required for full adoption of the proposed methods are not currently widely available. The approach is based on the estimation of batting outcome probabilities given detailed data on each ball that is bowled in a match. Machine learning techniques are used for the estimation procedure.

This paper aims to give novel evidence by examining the impact of oil price, gold price on the equity market of South Africa (JSE), by employing the newly established bootstrap (B-ARDL) approach as suggested by (McNown et al., 2018).  The ARDL, Dynamic OLS (DOLS), Canonical Cointegrating Regression (CCR), and Fully Modified OLS (FMOLS) testing approaches are used in analyzing a long-term linkage among the selected parameters. Furthermore, the Granger causality (GC) testing approach is adopted to test the causality amidst the selected parameters. The outcomes of ARDL, FMOLS, DOLS, and CCR tests discovered that gold price has an inverse influence on the equity market in South Africa. In contrast, oil prices affect positively the South African equity market.  The Granger causality revealed a uni-direction from gold price, oil price to equity market (  ln ). The paper suggests that gold is a secure investment asset that should be used to protect against risks and the positive interaction between oil prices and equity market fluctuations implies that oil should not be used as a hedge towards equity market uncertainty in South Africa.

The importance of organisation commitment and organisation citizenship to the effectiveness of the organisation is inarguable, especially in this current environment which moving towards industrial revolution 4.0 and globalisation. This study examines the effect of Servant Leadership Model on organizational commitment and organization citizenship behavior and lecturer’s performance. Respondents of this study were 225 permanent lecturers at private universities in Bandung, Indonesia. The research method uses in this study is quantitative approach. Data collected were analysed using structural equation modeling to address the research hypotheses. The results of the study prove that the servant leadership does not directly affect lecturer performance, but servant leadership has a significant effect on lecturer performance through organizational commitment or organization citizenship behavior. A better alternative is to improve lecturer performance by encouraging the application of servant leadership to increase organizational commitment which has an impact on lecturer performance.

The present study is an attempt to provide new evidence on the long-run effects of global warming (via greenhouse gas emissions (GHG), carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), economic development (GDP growth rate), and forest area on the life expectancy by undertaking the annual time-series data of Pakistan during 1990 – 2016. The study employs the augmented Dickey-Fuller (ADF) test, Johansen co-integration, and Generalized Linear Model (GLM) to estimate the long-run effects, whereas, for robustness, this study employed the Least Squares Method (LSM) and Robust Least Squares Method (ROBUSTLS). In addition to this, the study undertakes the Granger causality test to predict the causality among the study variables. The outcomes of the GLM estimations provide the negative association of the total greenhouse gas emissions, carbon dioxide emissions, and forest area, and positive association of methane and nitrous oxide emissions with life expectancy. Further, Granger causality results provide the presence of bidirectional causality between carbon dioxide emissions and life expectancy and a unidirectional causality running from life expectancy to greenhouse gas emissions, methane emissions, and GDP. Based on the findings, the authors suggest controlling greenhouse gas emissions, including methane and nitrous oxide emissions, and focusing on the health sector to improve the life expectancy in Pakistan.

This study investigates the dynamic interference of economic policy uncertainties on sectoral performances in an emerging economy - Nigeria. This step becomes expedient considering the vulnerability of developing countries to economic shocks and the lack of convincing explanations in previous studies. The dynamic autoregressive distributed lag (DARDL) and Kernel Regularized Least Squares (KRLS) techniques, as well as annual time series for the period 1981 to 2019, were relied upon for empirical expositions. Accordingly, a long-run relationship is established among the performance of each sector and the relevant explanatory variables. Overall, the empirical details reveal time-varying negative and significant effects of uncertainties on the performances of all the sectors, especially, the agricultural and the services sectors. Also, it is established that trade openness is a significant growth inhibitor, suggesting that the vulnerability of Nigeria economy to the waves of uncertainties is heightened by the levels of trade openness. Meanwhile, productivity levels in all the sectors are positive and significant functions of the exchange rate and investments. On this note, policies to shield the local economy from uncertainties must be sensitive to sectoral peculiarities and time variations. However, such efforts will be futile if trade openness is not taken into considerations. Expectedly, these discoveries are equally beneficial to the government, the local and international investors.

This paper investigates the relationships between unemployment, inflation, and economic growth in the UK. Quarterly data for the period 1990: Q1 to 2020: Q4. The ARDL bounds test model, Vector Error Correction Model (VECM), and Granger causality test are applied to examine the variables' short-run and long-run causal relationship. Unemployment rate (UR), inflation rate (INFR) and GDP growth rate (GDPGR) as a proxy of economic growth have been taken to study the relationships among unemployment, inflation, and economic growth. The short-run ARDL model in the study suggests that the entire variables (GDPGR, DUR and INFR) have a short-run causal relationship with each other. It follows the economic theories of Okun’s Law and the short-run Philips curve that there is an interrelationship among economic growth, unemployment, and inflation. The ARDL bounds test and VECM findings suggest strong evidence of cointegration between the three variables, which indicates a long-run equilibrium relationship. The pairwise Granger Causality test suggests a bi-directional relationship between economic growth and unemployment and a unidirectional relationship between inflation and economic growth (INFR→GDPGR) and between inflation and unemployment (INFR→DUR). In this case, monetary and fiscal policies may no longer effectively achieve policymakers’ economic growth and development goals.

Murcia is one of the regions of Spain with the highest rate of risk of poverty and social exclusion, also being a territory that presents serious inequalities. One of these inequalities refers to the rural population, however, there is no current source available in this regard. This leads us to analyze the risk of poverty and social exclusion of the Murcian population according to the degree of urbanization of the territory where they live. The sample belongs to a field work carried out by the University of Murcia during the years 2017-2018. We confirm our starting hypothesis: the set of rural population shows a higher incidence of risk of poverty and social exclusion than their urban counterparts. Likewise, the set of rural population has worse working conditions, more difficulty reaching the end of the month and greater dissatisfaction in their standard of living. The analysis presented serves as support for the formulation of public policies, especially those aimed at improving the living conditions of rural Murcia.

Investment and saving are critical for a country's economic development. The primary goal of this research was to determine whether there is a long-run or short-run causal relationship between saving, investment, and economic growth(GDP). We used Vector Error Correction Model  and Augmented Dickey-Fulle and Phillips-Perron tests were used to verify the Unit root test. The Johansen Cointegration Test shows that economic growth, savings, and investment are reconciled and are in long-run equilibrium. Vector error correction tests show that there is a unidirectional causal relationship between saving and investment to economic growth in the short-term as well as long-term. There is a bidirectional causal relationship from total domestic savings to total domestic investment. In other words, savings and investment lead to economic growth. Therefore, for this purpose, policymakers need to formulate and implement policies that promote economic growth. Such policies lead to higher growth in savings and investment.

Banks' digitalization is impartments a future trend and a national financial technology policy in Taiwan. This research aims to study which factors will affect digital accounts' promotion of digital banking. Specifically, we apply the grey relational analysis (GRA) methodology to analyze and identify the main factors of digital banking development. The empirical findings can briefly be summarized as follows: A bank wants to promote digital accounts, it must start with a credit card, because the use of digital finance must bind be bound to a credit card and let the people know that digital accounts have many advantages, such as no deposit limit and interest, free cross-bank withdrawals, etc. In general, the following crucial factors such as number of free transfers, deposit limit, the card in force, active cards and number of free withdrawal need to be considered since these factors can strongly assist digital banking development in Taiwan and banks effectively promote and attract people to apply for digital accounts.

In today’ s times, while measuring an organization’s performance in terms of best results, productivity, and profits, more and more is referred not to the material resources, but to the human resources and their competencies in terms of knowledge, skills and attitudes. Human resource management system is a process of making people and organizations to come together so that the objectives of each other are met with a win-win approach. Competency is an underlying feature of an individual which enables him/her to deliver superior performance in a given job, role or any situation. Competency mapping is one of the prominent human resource management initiative to identify the knowledge, skills and attributes required to perform a job effectively and efficiently in best possible manner. At present, development of competencies has become one of the key priorities of the organizations. It is also important to realize the factors responsible for enhancement of the competencies to ensure high performance of the employees. This calls for the Human resource management to initiate for competency mapping and identifying the skills affecting the employee’s performance at workplace. Now a days, most of the organizations are utilizing the competency mapping as a tool to identify high performers.  The present study focuses on identifying the competencies for Disaster management professionals that enhances their performance in the management of disasters. The study describes the main goal of conducting competency mapping and how it influences the performance of the disaster management professionals. The overall objective of the study is to explore the factors which ensure high performance of the disaster management professionals.  The study validates that competency-based management and related HR practices are gaining momentum in the field of Disaster Management sector in the context of performance management of the disaster management professionals.