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The Causality between Agriculture and Economic Growth in the Arab World
Rezgar Mohammed
DOI: 10.15604/ejef.2020.08.02.001
Abstract
This paper contributes to the controversy that exists among scholars on the link between agriculture and economic growth. Although there is much literature on the importance of the agricultural sector for economic growth, there is a lack of empirical evidence regarding the Arab World. This paper is one of the very few studies which examine the causality between agriculture and economic growth in a selection of eight Arab countries using time series econometric methods. Time series data from 1980-2018 are employed in this study which is obtained from the official website of the World Bank. However, agriculture is a variable of interest, exports and terms of trade are also included in the estimated models as additional determinants of economic growth. Both the Johansen test and the autoregressive distributed lag bound test are used to study the cointegration between agriculture and economic growth. The results suggest that agriculture could be used as an engine to promote economic growth for some Arab countries since a long-run relationship exists between the variables. Therefore, these countries would be able to enhance the value-added of agriculture through further investment in this sector. However, the direction of the causal relationship between agriculture and economic growth varies across countries. In most Arab countries, the economic growth could be used as a catalyst for growth in the agricultural sector since the direction of causality is from economic growth towards agriculture.
Keywords: Agriculture, Cointegration, Development, Economic Growth
Tourism and Economic Growth in African Largest Economy
Mary Kehinde Salawu
DOI: 10.15604/ejef.2020.08.02.002
Abstract
The study examines the nexus between tourism and economic growth in Nigeria from 1995-2017. Data were sourced from World Development Indicator and World Tourism Council data base online. Autoregressive distributed lag model (ARDL) was used in analyzing the data. The result of the Bounds test shows that the value of the F – statistics is greater than the value of the upper bound of the Pesaran, Chin and Smith statistics table at 1% level of significance, which showed that there is a long run relationship among economic growth (GRGDP), growth in the receipt from tourism (GRTR) and exchange rate (EXR). The long run result stipulates that there is no significant relationship between GRTR and GRGDP on one hand and LEXR and GRGDP on the other hand. In the short run, tourism had negative impact on Nigeria’s economic growth. The estimate indicates substantial role for time, previous state of the economy and tourism growth. While this result seems a contrast to theory, there may have been many factors connected to tourism development and practices which are anti-growth in the case of Nigeria. Furthermore, a percentage change in exchange rate reveals an ignorable though negative relationship with GRGDP. This may be due to uncertainty which surrounds exchange rate in a flexible regime. The study recommends that the government should invest in infrastructural facilities and tourist centers in order to boost economy of the country. Budgetary allocation can be channeled to tourism industry. Tax incentives to tourism firms should be encouraged.
Keywords: Tourism, Economic Growth, Autoregressive Distributed Lag Model, Nigeria
Trends and Derivers of Tax Effort: International Empirical Evidence
Mohammed Kalloub, Ibrahim Demir, and Ahmed Musabeh
DOI: 10.15604/ejef.2020.08.02.003
Abstract
This paper aims to identify the tax effort and its macroeconomic determinants in a sample composed of 13 countries from the MENA region and European countries using a set of macroeconomic variables considered by previous studies. This study employs two empirical methods to capture tax effort, and to analyze macroeconomic determinants of tax effort. Firstly, the paper uses a panel-stochastic frontier method to identify the tax effort and inefficiency term. Then, it uses a panel data regression model to analyze the determinants of tax effort in the years between 2005 to 2013. However, the selected sample includes two groups; the first group involves 6 European countries known with their high tax collections and low corruption. And the second group contains 7 developing countries with low tax collections and high corruption levels from the MENA region. The main findings of the study indicate that trade openness, inflation, and corruption are vital determinants for tax effort in sample countries. It is also found that developed countries have a higher tax effort than developing countries in general. However, Algeria has the most efficient tax administration with more than 98% tax effort, while Jordan is the least efficient among sample countries with 75% tax effort.
Keywords: Tax Effort, Macroeconomic Variables, Stochastic Frontier, Panel Data
Predicting Regime Shifts in Johannesburg Stock Exchange All-Share Index (JSE-ALSI): A Markov-Switching Approach
Katleho Daniel Makatjane and Edward Kagiso Molefe
DOI: 10.15604/ejef.2020.08.02.004
Abstract
It has been proven several times that linear models are unable to encapsulate nonlinear dynamics of macroeconomic and financial data such as inflation rates, exchange rates and stock prices to mention fewer. As a result, to overcome this problem, this current study adopted the nonlinear models due to the fact that they have required qualities to apprehend nonlinearity in a dataset. In order to predict a regime shifts, a five-day Johannesburg stock exchange all-share index (JSE-ALSI) spanning period from 02 January 2003 to 28 June 2019 was used as an experimental unit. This current study firstly employed Teräsvirta neural network test to detect the presence of nonlinearity and proceeded to estimate a two regime Markov-Switching autoregressive (MS-AR). The results of Teräsvirta neural network test revealed a highly significant nonlinearity with permanent seasonality as demonstrated by Kruskal-Wallis test. The predicted regime shifts by a latent dynamic allowed the autoregressive and variance parameters to promptly react to vital systemic shocks. As a result, this current study allowed volatility to oscillate between high and low volatility regimes that produced an expected duration of high volatility of two year and two months. This was a clear indication that there is a regime shifts in JSE-ALI which are modeled using Markov-Chain (MC) stochastic process. These findings may be used to inform robust policy making with the aim of safeguarding both the JSE and other global stock markets from the episodes of stock market crash. Moreover, other researchers can utilize the results of this study to calculate the risk associated with structural breaks and high volatility periods.
Keywords: All Share Index, Johannesburg Stock Exchange, Markov-Switching, Nonlinear Modeling
The Seasonal Effect on the Chinese Gold Market using an Empirical Analysis of the Shanghai Gold Exchange
Bing Xiao and Philippe Maillebuau
DOI: 10.15604/ejef.2020.08.02.005
Abstract
Gold is considered as a hedge against inflation, it offers an opportunity for portfolio diversification. This paper examines the recent evolution of seasonal anomalies in the Chinese Gold market. It studies the day of the week effect and the monthly effect through gold prices at the Shanghai Gold Exchange (SGE) over the 2002 to 2016 period. We investigate seasonal patterns in economically favorable times and unfavorable times by using a UCM model and an ARCH model. The reforms in regulations have rendered the Chinese financial market more efficient, in such cases; we expect an alteration in seasonal anomalies in the Chinese Gold market. However, it would seem that seasonality does exist in the Chinese Gold Market. The Monday returns have been positive and the Tuesday returns have been negative for the whole period. We also highlight that January and February generate the best returns. The return in the middle of the year is negative. This paper contributes to the existing finance literature by investigating the anomalies during the recent period. Although in the Chinese stock market, the seasonal anomalies persist, the index may be efficient despite the regularity in price formation, in this case, a study over a more recent period is necessary.
Keywords: Gold, ARCH, GARCH, Shanghai Gold Exchange, Seasonality, Chinese Calendar, Return, Volatility
Foreign Direct Investment, Human Capital and Economic Growth in Africa: A Panel Threshold Regression Approach
Marvellous Ngundu and Nicholas Ngepah
DOI: 10.15604/ejef.2020.08.02.006
Abstract
This paper examines how FDI from China, US, EU and the rest of Asia can transmit to sub-Sahara Africa’s growth through human capital development for the period (2003-2012). We utilize the education index developed by the UNDP to proxy for the quality of human capital. Using the PTR model, our results show that the human capital threshold level required to absorb knowledge embodied in all FDI sources is 0.51 years in terms of educational attainment. Nevertheless, only FDI from the EU can enhance sub-Sahara Africa’s growth through the development of less-skilled stock of human capital (less than 0.51 years). The impact of the latter turns negative and insignificant as the quality of human capital required to absorb knowledge spillovers increases beyond 0.51 years. For other FDI sources, 0.51 years demonstrates a sign-change threshold due to the regime shift from positive to negative. While our findings reveal that Africa is short of quality human capital stock required to absorb advanced knowledge embodied in FDI from both its traditional and emerging investors, it can be argued that the knowledge spillover effects depend on the technicalities and capital intensity of the economic sectors targeted by FDI sources. Based on the EU’s result, it could be possible that the knowledge spillover effects in Africa can be effective in less industrialized sectors.
Keywords: Economic Growth, Foreign Direct Investment, Human Capital, Panel Threshold Regression, Knowledge Spillovers
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