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For many years, India has been one of the top countries with an unnaturally skewed gender ratio towards the male gender. This implies the clear evidence of pre-natal selection and/or selective abortion in the country. While a lot of research has been conducted encapsulating the probable cultural factors (on a country-wide level) that adversely affect the gender ratio, only a few have used regression models to model the relationship between factors such as literacy rate and sex ratio. Hence, in this paper, I have utilised data that spans over 30 years from the Reserve Bank of India to model the relationship of various socio-economic factors such as poverty rate and literacy rate with the sex ratio in various Indian states. This was done through a multi-level model with the Indian states as the second level, in order to model the variation in sex-ratio due to the cultural and historical diversity in Indian states as well. It was found that over 90 per cent of variance in sex ratio could be explained through the random effects of Indian states. Findings also indicate a positive relationship of sex ratio with literacy rate and poverty rate. A negative relationship between the percentage of rural population in an Indian state and its sex ratio was also found.

Although the financial system development is vital for a country’s economic growth, it is still underdeveloped in most developing countries due to poor financial policies in terms of formulation and implementation. Therefore, this study aims to examine the effects of financial system development on the economic growth of Cameroon from 1980-2020. The study makes use of the ARDL bound test and multivariate Granger causality test. The results indicate that the financial development index and liquid liabilities have short and long run positive and significant effects on economic growth. Also, the result further reveals that in the short run, there is bidirectional causality between liquid liabilities and economic growth and a unidirectional causality running from financial development index to economic growth while in the long run, causal relationship runs from financial development to economic growth. The study recommends that the government should improve its financial system by constantly monitoring the sector to create an efficient, competitive, and stable financial sector that can contribute significantly to boosting economic growth.

Keywords: Cameroon, economic growth, financial development.

JEL Codes: G1, G23, O41

Recent studies have shown a growing tendency for trade to have an undetected effect on business cycle synchronisation. This seems to be due to an increase in the analysis comprising data from developing countries, advances in the control of the endogeneity of trade variables using instrumental variables, and the use of various control variables as explanatory variables other than trade variables. This study examines how the networking of trade, in which numerous countries participate, changes the relationship between trade and business cycle synchronisation in two countries. Thus, we examine the possibility that business cycle linkage would increase if countries with common trading partners had the same impact on each other from a third country rather than having a direct impact on each other. The analysis results indicate that trade networking enhances business cycle linkages, but bilateral trade has no such effects. This result is confirmed when tradables are divided into final and intermediate goods.

Keywords: Trade-networking effect, bilateral trade intensity, business cycle synchronisation

JEL: F14; F44; F62

In this paper we provide an empirical investigation on some properties of fan tokens of football clubs. Fan tokens are collectible virtual tokens mainly minted on the Socios Blockchain (using the Chiliz cryptocurrency) providing the opportunity to influence club's decisions, unlocking VIP rewards and access to exclusive promotions, games, chat, and a "superfan recognition". Fan tokens are a financial innovation that allows football clubs to retain and, at the same time, monetise their fan base without making any changes to their corporate and ownership structure and without being subject to the legal constraints that the issue of financial products would entail. As fan tokens are immaterial tokens based on a cryptocurrency, in this paper we fill a gap in the literature by studying to what extent several properties of cryptocurrency carry over to fan tokens. In particular, we investigate whether fan tokens exhibit (a) periods of exuberance, (ii) asymmetric volatility response to price changes and (iii) volatility connectedness among themselves and the Bitcoin and Chiliz cryptocurrencies. Our findings suggest that episodes of exuberance characterise the dynamics of fan token prices, that there is some evidence of reverse asymmetric response of volatility to price changes, and that total connectedness among fan tokens is quite sizeable and that most of them exhibit a rich dynamic with multiple reversal in terms of (net) transmitters and (net) receivers of shocks to the entire set of assets.

Keywords: fan tokens, asymmetric volatility, spillover effects, bubbles.

JEL code: G10, C20, Z23.

This paper examines the impact of inflation on economic growth between 1970 and 2020 using ARDL model. The results confirm a negative relationship between inflation and economic growth both in the short-term and in the long-term. We also found that money supply negatively affects economic growth in the long-term while it is fragile in the shortterm. However, the exchange rate has a negative and insignificant impact on economic growth both in the short-run and in the long-run. Therefore, it is necessary to apply some recommendations to fight inflation by trying to moderate it which increases productivity and consequently affects economic growth positively.

Keywords: Economic growth; inflation; short and long-term analysis; ARDL; Tunisia.

JEL Classification: O11 ; E31 ; C22 ; O55

This article aims to analyse the effects of foreign direct investment (IDE) on total factor productivity (PTF) in the Economic and Monetary Community of Central Africa (CEMAC). Using annual data for the period 1990-2020, the methodology was based on the Generalised Moments Method (MMG). The results of this research indicate that three variables positively influence total factor production. These are total factor productivity lagged one period, foreign direct investment and human capital. On the other hand, trade openness, labor force, gross fixed capital formation and political stability negatively explain total factor

production. This suggests a series of policy recommendations.

Keywords: Foreign direct investment, total factor productivity, spillovers, MMG, CEMAC.

JEL classification: F23, O4, F21.

This paper establishes a three-stage mixed monopoly model, and deeply discusses the impact of the shareholding reform on environmental tax rate or reward and subsidy intensity, green research and development level, environmental damage and social welfare under the two policies of collecting environmental tax and issuing incentive subsidy funds, and analyses the effect of the two policies. The results show that when implementing the environmental tax policy, the low degree of privatisation of state-owned enterprises will cause less damage to the environment and social welfare; when implementing the reward and subsidy policy, the higher degree of privatisation will cause less damage to the environment and social welfare. Comparing the effects of the two policies, it is better to implement the reward and subsidy fund policy when the privatisation degree of state-owned enterprises is relatively high. If the privatisation degree is not high, the policy choice is related to the social goals expected by the government.

Keywords: Mixed duopoly, Shareholding reform of state-owned enterprises, “Green” R&D, Emission taxation

JEL classification: E61; G38; H23

Recently, huge quantities of organised, unstructured, and semi structured data are being produced by different systems and machines around the world. Such a huge volume of heterogenous data set that typically cannot be managed by traditional system is described as big data. The healthcare sector continues to be confronted by the importance of managing the fundamental information created by numerous sources, known for creating high volumes of heterogeneous information. Different big data analytics programs, as well as strategies, have already been created for managing these substantial quantities of information in the healthcare market. In this particular paper, we go over the effect of big data on healthcare, as well as different methods offered in the Hadoop ecosystem for managing it. We also examine the conceptual structure of big data analytics for healthcare, which involves the information collecting historical past of various limbs, the genome database, electronic health records, text/imagery, and then the medical conclusions support program.

Keywords: big data, MapReduce, healthcare, Hadoop, management

This paper seeks to identify differences in unemployment among Brazilian youth during the Covid-19 pandemic using the least squares method and PNAD data. Among the results obtained, it is observed that the loss of occupation of youth decreases with income, being significant for the three lower per capita income groups, up to 2 minimum wages. This is true both for the general sample and for the subgroups considered, divided by gender and by large regions of the country. Another relevant fact is that women suffered a greater impact than men, characterised by an additional loss of 7 percentage points in occupation. These results show the importance of inclusion programs in the labour market to focus on socially vulnerable populations, giving greater support to the youth people from low-income families and considering the gender issues.

Keywords: labour market, youth unemployment, heterogeneity, social exclusion, Covid-19, income family.

JEL Classification: R11, R23, J63, J23.

Incorporating both supply and demand functions of working hours, we constructed a model of working hours. The model demonstrates that (1) working hours and wage earnings are determined jointly at an equilibrium point on a contract curve where the demand and supply of workers are equal, and (2) the contract curve passes through the intersection of the supply and demand curves of working hours. These results imply that (1) it is impossible to estimate the supply curve of working hours because equilibrium points are not usually located on a supply curve of working hours, and (2) a contract curve of working hours should be estimated to measure the wage elasticity of working hours. For the estimation of contract curves, geometric mean regression (GMR) was selected for three reasons. First, both variables in the contract curve equations are measured with errors. Second, the GMR estimator is the maximum likelihood estimator. Third, the coefficient of determination (R2) of both variables is equal in the GMR. Applying GMR, the contract curves of working hours and their wage elasticity were estimated. The estimated wage elasticity of working hours was between -0.13 and -0.23.