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Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.

The purpose of this paper is to examine the causal relationship between inward foreign direct investment (FDI) and economic growth in Southern African Development Community (SADC) countries over the period 1980-2012. It also investigates whether the causal relationship between FDI inflows and economic growth is dependent on the level of income.

In order to assess whether the causal relationship between FDI inflows and economic growth is dependent on the level of income, the study divided the SADC countries into two groups, namely, the middle-income countries and the low-income countries. The study used the recent panel-data analysis methods to examine this linkage. The Granger causality test for the middle-income countries was conducted within a vector-error correction mechanism framework; while that of the low-income countries was conducted within a vector autoregressions framework.

The results for the middle-income countries’ panel show that there is a uni-directional causal flow from GDP to FDI, and not vice versa. However, for the low-income countries’ panel, there was no evidence of causality in either direction. The study concludes that the FDI-led growth hypothesis does not apply to SADC countries.

Methodology applied in this study is a bivariate framework which is likely to suffer from the omission of variable bias (Odhiambo, 2008, 2011). Second, the Granger causality analysis employed in this only investigates the direction of causality and whether each variable can be used to explain another, but does not directly test for the mechanisms through which FDI leads to economic growth and economic growth leads to FDI.

Future studies may include a third variable such as domestic savings, exports, or financial development in a trivariate or multivariate panel causality model. A more complete analysis which seeks to explain the channels through which FDI impacts growth is suggested for future studies. Lastly, sector level analysis will help policy makers draft effective industrial policies, which can guide allocation of incentives.

The results of this study support the Growth-led FDI hypothesis, but not the FDI-led growth hypothesis. In other words, it is economic growth that drives FDI inflows into the SADC region and into Southern Africa, and not vice versa. This implies that the recent high economic growth rates that have been recorded in some of the SADC countries, especially the middle-income countries, have led to a massive inflow of FDI into this region.

At the regional level, SADC as a regional bloc has been actively pursuing policies and strategies aimed at attracting FDI into the region. Despite the important role of FDI in economic development, and the increase in FDI inflows into SADC countries in particular, there is a significant dearth of literature on the causal relationship between FDI and economic growth. The study used the recent panel-data analysis methods to examine the causal relationship between FDI and economic growth in SADC countries.

The purpose of this paper is to examine the relationship between renewable energy consumption and economic growth in non-oil countries in the Middle East and North Africa (non-oil-MENA) during the period from 2000 to 2014. The Pedroni (2000) test shows that there is a long-term cointegration relationship between those variables; however, the Granger causality test in the vector error correction model (VECM) shows that this relationship is bidirectional in the short and long term. Thus, to ensure sustainable economic growth without pollution and to reduce dependence on abroad, renewable energies can be chosen as substitutes for conventional energies in the non-oil-MENA countries.

First, LLC and IPS unit root tests are used to test the variables stationarity; and, second, Pedroni panel cointegration and Engle–Granger causality by VECM analysis are used to check the relationship between the studied variables.

Empirical results show that the renewable energy consumption and economic growth are cointegrated and that there are two-way causal relationships between them in the long and in the short term. These countries must therefore encourage the consumption of renewable energy instead of traditional energy to reduce their dependence on energy from abroad and CO₂ pollution.

The originality of this work lies in the measurements of the study variables and the empirical investigation methods used.

The purpose of this paper is to investigate empirically the channels through which Islamic and/or conventional banking can spur economic growth in MENA region.

The study uses a range of developed econometric approaches, including panel cointegration technique, panel Granger causality test and a panel-based vector error correction model (VECM), to analyze explicitly all the causal relationships among Islamic banking, conventional banking development and economic growth in a unified framework.

The empirical results show that Islamic banking in MENA countries not only leads to economic growth but also affects positively and significantly conventional banking development. Thus, Islamic banking has an active role and could be classified as “supply-following” since its development only leads to economic growth, whereas conventional banking, with passive role, could be classified as “demand-following” since it only reacts to economic growth in long run.

The study has two principal limitations. It is conducted within a relatively limited time period and sample of countries. Also, the used models did not take into account the impact of others financial and macroeconomic variables like stock market development, interest rate, inflation and financial crisis.

The results have two main implications. First, in MENA countries, well-functioning Islamic banking sector could not only promote economic growth but also can be served as a development factor for their conventional one. Second, unlike conventional banks, the customer of Islamic banks seems not to be motivated by interest and profits. Rather religious factors are recommended as the main motive for investing and saving in Islamic banks.

The study tries to perceive whether there exists a substitution or complementarity effect between Islamic and conventional banking in promoting economic growth for MENA countries. This situation is neither revealed nor clarified in the relevant literature.

The purpose of the paper is to empirically examine the relationship between energy consumption and economic growth for a panel of five South Asian economies, namely, India, Pakistan, Bangladesh, Sri Lanka and Nepal over the period from 1971 to 2010 within a multivariate framework.

The study uses Pedroni cointegration and Granger causality test based on panel vector error correction model to examine long-run equilibrium relationship and direction of causation in the short and long run between energy consumption and economic growth using energy inclusive Cobb–Douglas production function for a panel of five South Asia countries, namely India, Pakistan, Bangladesh, Sri Lanka and Nepal.

Pedroni’s panel cointegration test indicates the long-run equilibrium relationship between economic growth per capita, energy consumption per capita and real gross fixed capital formation per capita for panel. Further, 1 per cent increase in energy consumption per capita increases the gross domestic product (GDP) per capita by 0.8424 per cent for the panel. Causality results suggest bidirectional causality between energy consumption per capita, gross fixed capital formation per capita and GDP per capita in the long run and unidirectional causality running from energy consumption per capita and gross fixed capital formation per capita to GDP per capita in the short run.

These South Asian countries should implement an expansionary energy policies through improving the energy infrastructure, energy efficiency measures and exploiting massive renewables’ availability for low-cost, affordable clean energy access for all, especially in the yet unserved rural and remote areas for further stimulating economic growth.

Implementing energy efficiency measures and massive renewables development (wind, solar and hydropower) may help the affordable and clean energy access and reducing fossils fuel dependence and its associated greenhouse emissions in South Asia.

The aim of this paper is to evaluate empirically the impact of oil price fluctuations on the relationship between banking sector development and economic growth in oil-importing MENA countries.

The study used the newly developed panel autoregressive distributed lagged (ARDL) approach in order to address any potential endogeneity between research variables.

The empirical results show a unidirectional causality in the long run from oil price to both economic growth and banking sector development for oil-importing countries. Also, banking sector development not only leads directly to economic growth but also can play a moderator role in the oil price—economic growth nexus.

The study has two principal limitations. On the one hand, this study was conducted in a relatively limited sample of countries. On the other hand, the study did not consider others indicators for banking sector development and others macroeconomic variables.

The results found have imperative implications for banks' managers, regulators and researchers. Bank managers should be more concerned with the negative repercussions of oil price fluctuations on the development of their banks. The regulatory authorities must emphasize policies and strategies to further strengthen their banking sector in order to alleviate the negative influence of oil price shocks on economic growth. Researchers focused on finance-growth nexus must take into account the potential influence of oil price shocks.

The developed conceptual model allows examining to what extent the oil price fluctuations might affect the relationship between economic growth and banking sector development. This effect is neither evaluated nor clarified in the relevant literature.

This paper aims to analyze the internal relationships and tendency of residential energy consumption, income and carbon emissions.

Taking 30 provinces of China as the analysis unit and dividing them into two types of urban and rural consumer groups, the panel data model was built. In addition, panel unit root test, panel cointegration test and panel Granger causality test were also used.

The results showed that there are long-run equilibrium relationships between the three variables, which show the regular tendency in the spatial process. The elasticity coefficients of residential energy consumption and CO₂ emissions vary across the three regions and decline continuously from the western to central and eastern regions. In addition, geographic location is also an important factor on the energy consumption and CO₂ emissions in residential sector.

This paper provides some points for policies on cutting energy use and pollution in residential sector.

The purpose of this study is to measure the impact of technology spend on bank profitability focusing on Indian public and private sector commercial banks. The study also assesses the longevity duration of impact for both public and private sector banks. The trade-off is created between the bank’s profitability and technology spent across four identified columns: increase product sales, reduce cost, enhance employee efficiency and optimally use existing resources.

The metrics of four columns converted to measurable 11 financial alarming indicators and impact is again checked on profitability indicator ROE. The data used for empirical analysis for the study are between the year 2003 and 2019, across 12 public and 15 private banks. The interface between technology spend and profitability is measured using panel vector autoregression (VAR) and panel vector error correction model (VECM) and further the link between 11 financial indicators and profitability measures is established using panel data analysis.

The study found that there is a mixed effect of technology spent on profitability and performance of Indian banks, where public sector banks were found to be more unstructured over private sector banks. The study advises the optimal technology spend strategies to gain enhanced productivity for banking business which are to name a few – planned technology reserves, customer awareness campaigns for products, robust employee-customer motivation policy and customized technologies aligned to existing infrastructure.

The data was original and extracted from the Reserve bank of India website and respective banks’ annual reports.

The purpose of this paper is to explore the effects of total assets, stock performances, CEOs’ tenures, ages, and board sizes on total CEO compensations of 249 publicly listed US companies over a nine-year period from 2004-2012.

Pedroni’s panel cointegration, generalized method of moments, and dynamic ordinary least squares methodologies are applied.

All variables are non-stationary in log-levels. The findings show significant positive effects of total assets and stock performances on total CEO compensations. The effects of CEO’s tenure and age as well as board size on total CEO compensation deem negative. However, short-run net interactive feedback effects are generally positive with some exceptions.

The above variables matter in rewarding the CEOs. They should be carefully weighed in for proper formulation of CEO compensation policy.

This paper applies relatively new econometric tools for a large panel data set. This work considers some new variables for determining CEO compensation in USA. The findings are relatively new with empirical originality.

This paper empirically examines the short-term and long-term associations between risk, capital and efficiency (R-C-E) in the Indian banking sector across 2008–2019 to answer the presence of causation or contemporaneousness in the R-C-E nexus.

The paper focuses on three objectives. First, the authors determine short-term causality in the risk–efficiency relationship by studying the simultaneous influence of a wide array of banking risks on DEA-based technical and cost efficiency in static and dynamic situations. Second, the authors introduce bank capital and contemporaneously determine the interplay between R-C-E using seemingly unrelated regression equation (SURE) and three-staged least squares (3SLS). Last, the authors assess stability in inter-temporal associations using Granger causality in an autoregressive distributed lag (ARDL) generalized method of moments (GMM) framework.

The authors contend that high capital buffers reduce insolvency risk and increase bank stability. Technically efficient banks carry lesser equity buffers, suggesting a trade-off between capital and efficiency. However, capitalization makes banks more technically efficient but not cost-efficient, implying that over-capitalization creates cost inefficiencies, which, in line with the cost skimping hypothesis, forces banks to undertake risk. Concerning causal relationships, the authors conclude that inefficiency Granger-causes insolvency and increases bank risk. Further, steady increases in capital precede technical and cost efficiency improvements. The converse also holds as more efficient banks depict temporal increases in capitalization levels.

The paper is perhaps the first that acknowledges the influence of the “time” perspective on the R-C-E nexus in an emerging economy and advocates that prudential regulations must focus on short-term and long-term intricacies among the triumvirate to foster a stable banking environment.