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

This article aims to analyze the performance of Brazilian yerba mate exports from 2001 to 2020, as well as their main sources of growth. For this, the constant market share model was applied for the first two decades of the 21st century, with emphasis on the subperiods 2001-2004, 2005-2010, 2011-2015 and 2016-2020. The results show that the effect of the growth of world trade and competitiveness were the ones that most influenced the growth of exports in this sector in Brazil.  The effect of the regional market or destination of exports was the one that most affected the performance of the sector, except in the last subperiod analyzed, in which yerba mate exports showed a significant improvement in relation to previous years. From this analysis, it can be deduced that Brazil is very important in this international trade and that prominent positions can be achieved in addition to primary exports of this product.

The concept of marketing has evolved from a first stage (marketing 1.0), based on the product, to the present scenario (marketing 5.0), characterized by the incorporation of new technologies and the implementation of digital marketing policies and online sales. A quantitative and qualitative analysis of a group of companies before and after the pandemic shows that the arrival of the virus has increased the use of the internet, mainly to overcome the difficulties caused by social distancing measures, although the effect has been temporary. However, there is still work to be done when it comes to the analysis of big data for market research purposes or to the development of other technologies like Artificial Intelligence (AI) or the Internet of Things (IoT).

The study has two purposes. The first purpose is, using the economic and financial risk factors determined by the International Country Risk Guide (ICRG) rating agency, to reclassify the scores that countries get from these factors with the Jenks Natural Breaks (JNB) classification technique and to compare countries by creating their thematic maps according to this classification. The second purpose of our study  is to create economic and financial risk maps of countries by using the Geographical Weighted Regression (GWR) method, which is one of the Geographical Information System (GIS) analysis techniques, based on the economic and financial risk factors determined by the ICRG. Before the GWR analysis for the variables included in the research, Moran Index analysis was performed as the main measurement of spatial autocorrelation. As a result of the Moran analysis, it was determined that there was a statistically significant positive autocorrelation between the countries. In other words, it has been seen that the countries examined have spatial dependence on each other in terms of economic and financial risk. According to the results of the GWR analysis, risk maps of the examined countries were created and more dynamic, more meaningful or more sensitive, more specific and visually easier to understand results were revealed. And according to these results, it has been seen that the GWR technique can also be used in the fields of economy and finance. In addition, the study brought a different interdisciplinary perspective  by bringing together the fields of economy, finance and geography.

This study investigates the relationships between foreign trade, employment and economic growth in Sudan over the period 1970-2017, with inflation and budget deficit as policy variables. Two autoregressive distributed lags (ARDL) models were estimated with trade and economic growth as determinants of youth employment and total employment. Two other models were estimated to investigate how trade and each type of employment affect economic growth separately. The empirical results from the four models revealed existence of long run relationships between foreign trade, employment and economic growth. In the short run, trade, economic and population growth rates have stronger effects on youth employment than on total employment. In the long run, youth employment is found to be positively affected by economic growth and investment but negatively affected by population growth and the budget deficit, while total employment is only affected by population growth rate. Economic growth is found to be much explained by youth employment than by total employment and foreign trade. The study concludes that the internal factors in terms of inflation, budget deficit, investment and salaried workers are more important to employment and economic growth than the performance of foreign trade sector of Sudan. The policy implication is that youth employment should be given priority in labor and trade openness policy than targeting employment as a whole. For trade openness to play positive roles on employment and economic growth in Sudan, corrective policies for volumes and types of exports and imports are urgently needed.

This study examines the determinants of wage gap differences based on gender, ethnicity, and area of residence (urban vs. rural) in Ecuador for the years 2007 and 2017. By combining the Oaxaca-Blinder decomposition with unconditional quantile regression, we identify the extent to which the wage gap between two groups is due to characteristics (endowment) or unexplained factors at various points of the distribution, i.e. for low-, medium- and high-income workers. Results show that, on average, the gender and ethnic wage gap in 2017 increased slightly with respect to 2007, while the area wage gaps remained stable. However, progresses have mainly benefited those at the top of the income distribution, while disparities have widened for those at the bottom. As regards endowment effects, education mainly explains area and ethnicity wage gaps, while there is an important unexplained part that contributes more to gender wage differentials.

In the 1990s it happened a real burst of innovation in the Spanish financial markets, and specifically with the creation of real estate mutual funds. Nevertheless, in the following decade, with the real estate bubble explosion, the real estate funds began to loss money and even it must stop temporarily the redemptions due to the lack of cash, till the current times in which there are only two real estate mutual funds, both in dissolution procedure. Today never invest in real estate mutual funds in Spain, and however it is a suitable financial product to solve the current problems of lacking real estate supply and the real estate crunch.

There is an open debate about the motivation of football referees to start and progress in their careers. Identifying altruistic and self-servicing factors is critical for the federations to establish the most effective policies to enlarge the referee’s career and minimise turnover. In this article, we analyse how the willingness to become a referee is determined by the average income level in the referee’s neighbourhood. More specifically, our alternate hypothesis is that the number of referees per district is affected by the average income level in that postcode. Sequential linear regressions generated six models using data from the Instituto Nacional de Estadística (INE) and the Real Federación de Fútbol de Madrid (RFFM). The best-fit outcome shows that the number of referees is partly determined by the income level in their postcode at the beginning of the referee’s career, although the overall fit of the model decreases for experienced referees.

Research studies and policies have stressed the impact of private vehicles on the air quality and the significance of the public transportation. But, such studies have rarely proved the quantitative impact of the same. The present paper has established a long-run relationship between vehicular population and the air quality deterioration using time series data from one of the major metropolitan city of India, Bengaluru. Adopting the cointegration method: ARDL, the paper has provided quantitative impact of public transportation in improving the air quality of the city. The result is found to have significant impact on the transportation policies which can direct the urban planners in improving the public transportation in order to have positive impact on the air quality.

The paper presents a new approach for price dynamic assessment on the Ukrainian stock market based on a qualitative modification of the Black-Scholes-Merton model for estimating unknown parameters with a stochastic trend. The mean-reverting Ornstein-Uhlenbeck process was chosen as the time-dependent trend parameter since it is both mathematically convenient and has a natural economic interpretation. In order to estimate the parameters of the corresponding stochastic diffusion, the trajectory-fitting technique based on the Kalman-Bucy filter was used. The proposed approach was then tested on UX-index assets.

In this study , governments in oil-producing countries rely heavily on oil income to fund their budgets and exert political influence. Increases in government expenditure are a direct result of a surplus of funds, as would be expected from standard economic theory. This is precisely why Extremely high oil prices in 2010and 2020 caused tremendous budgets in the Iraqi economy. Investment, which would have been the primary beneficiary of the government expenditure process, was ignored. They missed a chance to diversify their economies and industries by concentrating solely on leisure and consumption. The progress of the Iraqi economy is unimpeded by a shortage of resources or money. Oil earnings and governmental spending are the primary factors studied due to their close relationship. The sample size was organized , and the data collected was quarterly, which is more timely than annual data. Keeping an eye on it all the way from 2010 till 2020. A quiet test was performed on the series to see if those two factors were present, and the results showed that they were not. As soon as they take the first difference and the graph examination, they find their footing and are able to continue on with the rest of the exams with ease. The right model was chosen, and an autoregressive distributed-lag (ARDL) technique was used..