Ever since Ghana gained independence, its policy makers have identified education as a tool to foster economic growth and development. In recognition of the vast potential for national development that education presents Ghana, various governments have invested considerably in the sector. These investments have been in the form of educational sector reforms, as well as yearly reoccurring expenditure. Despite these massive investments however, very little work has been done to empirically investigate the impact of such expenditure on the nation’s economy. This paper uses data from Ghana to empirically assess the nature of the relationship between education expenditure (a proxy for human capital development) and GDP growth (a proxy for economic growth). The Granger Causality Test is applied to education expenditure and GDP growth data, from 2003 to 2018. Using data from this same time frame, separate Granger Causality tests are also implemented to test the relationship between Gross Enrollment Rates/ Total Completion Rates, at some levels of education, and GDP growth.   Interestingly enough, the analysis shows no Granger causal relationship between our main variables of interest (Total Education Expenditure and GDP growth). Results also show that none of the education variables Granger cause GDP growth, if the test uses 1 lag and also if the test uses 3 lags. Additionally, results show that whether the test uses 1 lag or 2 lags, GDP growth Granger causes the percentage of total government expenditure that is dedicated to education. Results for tests that use 2 lags also shows that the only education variable that Granger causes GDP growth is enrolment rate at the primary level, with GDP growth also not Granger causing any education variable apart from the percentage of government expenditure dedicated to education. In the case of the test using 3 lags, results show that GDP growth Granger causes only one education variable which is expenditure on the Senior High School level. / Ända sedan Ghana blev självständigt har dess beslutsfattare identifierat utbildning som ett verktyg för att främja ekonomisk tillväxt och utveckling. Som ett erkännande av den enorma potential för nationell utveckling som utbildning erbjuder Ghana, har olika regeringar investerat avsevärt i sektorn. Dessa investeringar har varit i form av reformer av utbildningssektorn, såväl som årliga återkommande utgifter. Trots dessa massiva investeringar har dock mycket lite arbete gjorts för att empiriskt undersöka effekterna av sådana utgifter på landets ekonomi. Denna artikel använder data från Ghana för att empiriskt bedöma karaktären av sambandet mellan utbildningsutgifter (en proxy för utveckling av mänskligt kapital) och BNP-tillväxt (en proxy för ekonomisk tillväxt). Granger Causality Test tillämpas på utbildningsutgifter och BNP-tillväxtdata, från 2003 till 2018. Med hjälp av data från samma tidsram implementeras även separata Granger Causality-tester för att testa sambandet mellan bruttoinskrivningsfrekvenser/Totala slutförandefrekvenser, på vissa nivåer utbildning och BNP-tillväxt. Intressant nog visar analysen inget Granger-kausalt samband mellan våra huvudsakliga intressevariabler (Total Education Expenditure och BNP-tillväxt). Resultat visar också att ingen av utbildningsvariablerna Granger orsakar BNP-tillväxt, om testet använder 1 tidstidsfördröjning och även om testet använder 3 tidsfördröjningar. Dessutom visar resultaten att oavsett om testet använder 1 tidstidsfördröjning eller 2 tidsfördröjningar, Granger orsakar BNP-tillväxt andelen av de totala offentliga utgifterna som är dedikerade till utbildning. Resultat för tester som använder 2 tidsfördröjningar visar också att den enda utbildningsvariabeln som Granger orsakar BNP-tillväxt är inskrivningsgraden på primärnivå, där BNP-tillväxten inte heller Granger orsakar någon utbildningsvariabel förutom procentandelen av de statliga utgifterna som är avsatta till utbildning. I fallet med testet med 3 tidsfördröjningar visar resultaten att BNP-tillväxt Granger orsakar endast en utbildningsvariabel, vilken är utgifter på gymnasienivå.

This study examines the lagged short run and long-term relationships between output growth and related index returns of the industrial and financial sectors of the G-7 economies. This study examines this relationship using quarterly data for a maximum time period of 22 years ranging from 1994(Q4) to 2017(Q4). The relationship between sector specific output growth and related index returns of the G-7 is investigated within this study, in order to determine whether passive investors should incorporate expected growth prospects into their decision making in order to earn superior returns. In order to examine the relationship between sector specific output growth and the related index returns of the G-7, this study uses correlation, cointegration as well as causality testing. This study finds weak non-lagged correlation relationships between output growth and related index returns of the industrial and financial sectors of the G-7 economies, with the correlation relationships becoming stronger in all cases when lags are incorporated within the correlations analysis. This study also finds cointegrating relationships between financial sector output growth and related index returns of Italy and the United Kingdom and that financial index return data of the United Kingdom serves as a leading indicator for financial sector growth within the United Kingdom. The overall Implication of these results is that investors should not incorporate growth prospects into their decision making of which passive funds to invest in, of which these passive funds examined track the performance of industrial and the financial firms within the G-7 economies.

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This study aims to investigate if there is any causal relationship between human rights and economic growth. The causality is tested in both directions, from human rights to economic growth and from economic growth to human rights, using a panel data Granger Causality test. The variable used to represent human rights is a human rights score and the variable used to represent economic growth is annual growth of real GDP per capita. Both of these variables are retrieved from Our World in Data. There is a total number of 81 countries included in this study with yearly observations from 1962 until 2017 on both variables. To achieve a greater depth the 81 countries were categorized into three different categories: low-income, middle-income and high-income countries. Previous studies and theories indicate that it is possible to expect a two-way causal relationship between economic growth and human rights. However, the results in this study indicate that there is no statistically significant causal relationship in any direction for any of the income categories.

Yes / This study contributes to the existing literature on the relationship between oil market shocks and the green bond market by investigating the impact of the COVID-19 pandemic on their dynamic correlation. We first decompose the oil market shocks into components using a time-frequency framework. Then, we combine wavelet decomposition and quantile coherence and causality methods to discuss changes during the COVID-19 era. We observe positive effects of both supply-driven and demand-driven oil shocks on the green bond market at most quantile levels. However, supply-driven oil price changes play a major role. The results also indicate that long-term changes have a greater impact than short-term changes on the connection between oil and green bond markets. Nevertheless, the COVID-19 pandemic changed the nature of the causal relationship, as we observed no relationship under extreme market conditions during the pandemic era. We argue that the economic and social impacts of the COVID-19 pandemic have left investors focusing on the short-term substitution between oil and green bond markets. / This research was supported by the Major Projects of the National Natural Science Fund of China [NO. 71991483], the Natural Science Fund of Hunan Province [NO. 2022JJ40647] and the Fundamental Research Funds for the Central Universities of Central South University [NO. 2022ZZTS0353]. / The full-text of this article will be released for public view at the end of the publisher embargo on 06 Oct 2024.

自從中國實施經濟改革之後，其經濟快速成長。從1978到2002年之間，中國的年平均成長率為8.07﹪。但同時期，中國的不平等卻顯示不同的變動趨勢。在1980年代，經濟改革似乎同時促進經濟成長與不平等程度的下降。然而1990年代之後，不平等卻呈現向上爬升的趨勢。本論文的研究目的，即是探討改革後，中國經濟成長與不平等間的因果關係。 根據之前的文獻，經濟成長和不平等之間可能相互影響，但影響方向卻不確定。本論文研究方法採用Granger因果檢定，估計成長與分配的因果關係以及影響方向。本研究採用Toda and Yamamoto (1995)所提出的向量自迴歸程序，對Granger因果模型進行卡方檢定的統計推論。Toda和Yamamoto證明，研究者能夠估計一個k+dmax階的向量自迴歸模型，其中dmax是時間數列變數最大整合階數，k為落差期數。然而，進行統計推論時，研究者只需利用卡方統計量檢驗前k階的迴歸係數是否顯著，而不需檢驗最後的dmax階迴歸係數。利用此研究方法，本論文發現以下結果：一、經濟成長會正面且顯著地影響不平等；二、不平等不會影響到經濟成長；三、實證結果是穩健的，其不因使用不同的所得不平等指數或落差期數而有所變化。 會產生第一種結果的主要原因，在於中央政府傾斜政策的實施。與先前文獻完全集中研究自由經濟或計畫經濟不同，中國經濟正處於轉型過程，可能是本研究不能發現所得不均等對經濟成長的主要因素。 本研究的政策意涵為，由於經濟持續增長，使得不均等的情況更加惡化。因此，中央政府應該取消向東部沿海傾斜的政策，並且增加對中西部地區進行投資的意願。但是，將資源投入在中西部，使得到的收益遠遠小於投入在東部者。因此為了促進持續經濟成長，不建議採取某些能迅速降低不平等的政策，例如財政移轉。 / Ever since economic reform has been carried out in China, its economic growth rate has been remarkable. Its annual growth rate of per capita GDP was about 8.07% for the period 1978-2002, but its income inequality level presented a different moving trend during this time. In the 1980s, it seemed that economic reform decreased this inequality successfully, but the situation of income distribution started to deteriorate beginning in 1990. The purpose of this study is to research if the relationship between economic growth and inequality exists in post-reform China. According to previous literature, economic growth and inequality can influence each other, but their influential directions are uncertain. This study adopts the Granger-causality test as a methodology to estimate their relationship and influential directions. This study tests Granger-Causality with the chi-square statistic, which was proposed by Toda and Yamamoto (1995). They wrote that researchers could estimate a (k+dmax)th-order VAR where dmax is the maximal order of integration. Only the first k coefficients have to be jointly tested with the chi-square statistic, and the last dmax coefficients are ignored. This study finds the following results: (i) growth positively influences inequality; (ii) inequality does not influence growth; and (iii) the results are sturdy no matter what inequality index or what lag lengths are used in the empirical test. The result (i) can be attributed to the biased central government policy. Differencing from previous studies, which focused on democratic or undemocratic economies, this study researches a transitional economy. It could be the reason why this study finds no evidence of the effect of inequality on growth. The policy implications of this study are that China’s government has to give up biased policies and increase the incentives of investing in inland regions. Besides, in order to promote sustainable economic growth, some policies like fiscal transfers, which can reduce inequality quickly, are not recommended.

This thesis explores the price determinants of Bitcoin using a macroeconomic model based on the economic equation of exchange presented by Joseph Wang (2014). The thesis provides a concise and structured introduction to Bitcoin and a comprehensive literature review on Bitcoin. The analysis begins with the application of the functions of money to Bitcoin, arguing that while Bitcoin does fulfill the three classical functions of money to a certain extent, its use remains mainly as a speculative instrument. Wang's model is criticized and amended to reflect the realities of empirically analyzing the Bitcoin market. Using the daily number of transactions and Bitcoin days destroyed as proxies for economic activity and inactivity - to measure Bitcoin's velocity on the block chain - vector autoregression modelling is used to determine if there is Granger causality between the price of bitcoin and the two proxies. The results demonstrate that there is a bidirectional Granger-causal relationship between Bitcoin days destroyed and the price of bitcoin and that there is none between the daily number of transactions and the price of bitcoin; proving Wang's two main assumptions. Impulse- response functions are provided to illustrate and discuss this bidirectional relationship. The results are in line with the...

Os programas de computador têm apoiado o estudo de sistemas biomédicos em que um volume considerável de dados são empregados. Na biomecânica, a análise das influências entre as articulações pode melhorar o conhecimento das lesões relacionadas à corrida associadas ao uso excessivo durante a atividade de corrida. Compreender os padrões de interação entre diferentes articulações anatômicas, durante o movimento, pode contribuir para o aprimoramento de programas de treinamento, reabilitação e prevenção a lesões. Neste trabalho, um software personalizado foi desenvolvido para implementar a Coerência Parcial Direcionada (PDC), uma abordagem no domínio da freqüência da Causalidade de Granger (GC), adequado às especificidades da fisioterapia. Com entradas independentes e padronizadas, modularização e parametrização, as rotinas investigaram a direção de interação entre diferentes canais, registrando e salvando arquivos intermediários. Separados nos três planos anatômicos, sagital, frontal e transverso, foram utilizados dados cinemáticos para analisar as interações entre tornozelo, joelho, quadril, pelve e tronco durante a corrida. Três modificações de técnica de corrida foram abordadas: com aterrissagem iniciada com o antepé, com aumento de 10% na taxa de passo e com aumento de flexão de tronco, além da habitual. As análises foram realizadas para o ciclo completo (apoio e balanço) e com separação da fase de apoio, e revelaram que essas duas estratégias de processamento são complementares. Comparando as influências proximal e distal, os procedimentos sugeriram uma predominância das interações proximal a distal, mostrando uma origem central de movimentos. Dessa forma, destaca-se a relevância em controlar e fortalecer tronco e quadril para a minimização de lesões. Considerando os resultados e a oportunidade de configuração, o software pode ser empregado para estudar outras articulações e aplicações, bem como evoluir para um sistema automatizado de apoio à decisão. / Computer programs have supported the study of biomedical systems in which a considerable amount of data is employed. In biomechanics, analysis of influences between joints can improve the knowledge of the Running-Related-Injuries (RRI) associated to overuse during running activity. Understanding the patterns of interaction among anatomical joints during movement can contribute to the improvement of training, rehabilitation and injury prevention programs. In this work, a customized software was developed to implement Partial Directed Coherence (PDC), an approach in the frequency domain of Granger Causality (GC), adapted to the physical therapy specificities. With independent and standardized inputs, modularization and parameterization, the routines investigated the interaction direction between different channels, logging and saving intermediate files. Separated in the three anatomical planes, sagittal, frontal and transverse, kinematic data were employed to analyze the interactions between ankle, knee, hip, pelvis and trunk during running. Three running technique modifications were addressed: forefoot strike landing pattern, increasing 10% of the step rate and increasing trunk flexion, in addition to usual running. The analyzes were performed for the complete cycle (stance and swing) and with separation of the stance phase, and revealed that these two processing strategies are complementary. Comparing proximal and distal influences, procedures suggested a predominance of proximal to distal interactions, showing a central origin of movements. In this way, the importance of controlling and strengthening trunk and hip to minimize injuries is highlighted. Considering the results and the processing configuration opportunity, the software can be employed to study other joints and applications, as well as evolve to an automated decision support system.

This study examined the effects of government expenditure on different components of economic growth in South Africa using quarterly data from the period 1970Q1 to 2016Q4. The six key policy variables employed in the analysis were derived from the Ram (1986) production model and the New Growth Path (NGP), a macroeconomic framework designed to address the main challenges (unemployment, poverty and inequality) facing the economy as a result of its political past. The analysis of the relationship was carried out using the VECM while the findings from the analysis revealed that though there exists a long-run equilibrium relationship among the variables. The long-run estimates showed that aggregate private consumption expenditure and employment-to-population ratio are significant but negatively, related to economic growth. However, the net inflows of foreign direct investment and gross fixed capital formation are negatively related to gross government expenditure. This implies that excessive public capital expenditure might reduce the positive impact of the two variables on economic growth. The study therefore suggests that government should consider increasing its expenditure on the significant variables that support labour and capital development, in order to enhance economic growth in South Africa. / Economics