High frequency multiscale relationships among major cryptocurrencies: portfolio management implications

This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin, Ethereum, Monero, Dash, Ripple, and Litecoin. We apply nonlinear Granger causality and rolling window wavelet correlation (RWCC) to 15 min—data. Empirical RWCC results indicate mostly positive co-movements and long-term memory between the cryptocurrencies, especially between Bitcoin, Ethereum, and Monero. The nonlinear Granger causality tests reveal dual causation between most of the cryptocurrency pairs. We advance evidence to improve portfolio risk assessment, and hedging strategies.

The Business Cycle, Inflation, and Unemployment Rate Nexus: An Empirical Approach

This paper revisits the main assumption regarding the original Phillips curve regarding the American economy, in which one assumes that the unemployment rate causes an inflation rate. In this context, this paper aims to evaluate if the variance of the inflation rate affects the unemployment rate and, besides, if there is a one-way causality from the variance of the inflation rate to the unemployment rate. Based on quarterly time series from 1959:04 to 2019:04 the empirical results show, via OLS and GMM methods, that the monetary policy affects the business cycle, and, in turn, the business cycle impacts the unemployment rate. Hence, the monetary policy affects indirectly the unemployment rate via the business cycle. On the other hand, the variance of the inflation rate contributes to an increase in the unemployment rate, consequently, there isn’t a trade-off between the unemployment rate and the variance of the inflation rate. Moreover, there is a one-way causality from the variance of the inflation rate to the unemployment rate. This is the contribution of this paper. At last, based on the Phillips curve, one expects that the unemployment rate causes the inflation rate. However, the Granger causality tests display a two-way causality relation between both variables.

Testing the absorber hypothesis of exchange rates for the overshooting of agricultural prices in China

This study aims to test the overshooting effect of agricultural prices and the absorber hypothesis of exchange rates by extending the existing overshooting model. Using a combination of modern time series methods and monthly aggregate data from China, we demonstrate that overshooting of agricultural prices does indeed occur since the impact of monetary expansion on flexible agricultural prices is significantly larger than on relatively sticky industrial prices. Granger causality tests confirm that monetary expansion is a possible determinant of the movements of both agricultural and industrial prices, thus providing a solid empirical foundation for the overshooting hypothesis. Our findings also confirm the absorber hypothesis, in that the overshooting effect of agricultural prices under a fixed exchange rate regime (ERR) is shown to be greater than that under a floating ERR. The main policy implication is that policymakers should pay attention to the spillover effect of monetary expansion on agricultural prices when adjusting macroeconomic policies, especially under a fixed ERR.

Do Operating Profits Induce a Wage Premium Equally Shared among Employees Earning High or Low Incomes?

Panel data show that between 2001 and 2014 Norwegian industries’ increasing aggregated operating profits per employee increased average wages and wage inequality. The data imply that increasing profits, perhaps unsurprisingly, induce a wage premium. The data further imply that employees earning high incomes at the outset had the highest wage increase percentage-wise. Decreasing operating profits per employee had opposite but less robust effects on average wages and wage inequality. Panel data Granger causality tests finally showed that average wages, but not wage inequality, reversely and positively affect operating profits per employee.

Innovative Development of the Agricultural Sector in the Visegrad Group Countries

Subject and purpose of work: Analysis of the innovative development trends of the agricultural sector in the Visegrad Group countries in 1995–2019. Investigation of the impact of innovation on value added to GDP by the sector and the patent activity. Materials and methods: Secondary data used in the current research were taken from Eurostat, World Bank and European Patent Office databases. They were analyzed by applying OLS models and Granger causality tests. Results: First, composition of R&D expenses in each Visegrad country was examined. Then its relationship to agricultural GDP and the number of the patents granted was tested by means of OLS models. Forecasting the relationship between variables examined was carried out by running Granger causality tests. Conclusions: There was a constant growth in agricultural innovation activity investment from 1995 to 2019. Nevertheless, the countries examined have not yet reached the EU’s objective concerning the R&D intensities. Innovation activity had a positive impact on the value added to GDP by agriculture and on the number of the patents granted.

The Effect of Sectoral Division on GDP per Capita in the Slovak Republic

The paper aims to analyse the sectoral division of the national economy in the Slovak Republic from various points of view. The authors examine the developmental changes in the number of people employed in different economic sectors (primary, secondary, tertiary, and quaternary) from 1948 to 2018 reflecting the natural development of the economy over that time. In order to do this, they have used a logical and comparative study of theoretical knowledge in accordance with the analysis of empirical data. The descriptive statistics are based on a sample of aggregate data about sectoral division in the Slovak Republic for the period 1948–2018. A cluster analysis on the data of sectoral division in all EU member states in 2010 and in 2017 was carried out in order to obtain a basic overview and opportunity to compare. The main focus of this paper is to examine the impact of sectoral division of the national economy on the Slovak Republic’s real GDP per capita. The research is based on panel regression as well as Granger causality tests on a sample of all 8 Slovak regions between 2001 and 2018. The results of the Granger causality tests show that causality runs one-way from all four sectors to real GDP per capita. Based on this, it is appropriate to carry out panel regression analysis. The results of this analysis suggest that all given sectors in period t−1 have had a significant impact on GDP per capita. In particular, the primary and secondary sectors have both had a relatively significant negative impact while the tertiary and quaternary sectors have had a positive one. It is interesting that the tertiary sector has had a greater positive impact than the quaternary one in the Slovak Republic.

Dynamics between Vietnamese real consumption and economic growth

This article uses recent developments in econometric techniques to examine the consumption-led growth hypothesis for Vietnam from 1990–2012. The Granger-causality tests were based on two testing approaches: the vector error correction modeling approach outlined in Toda and Philips, and the augmented level VAR modeling with integrated and cointegrated processes (of arbitrary orders) separately introduced by Toda and Yamamoto (1993) and Dolado and Lütkepohl (1996). Empirical results reveal the mutual exogeneity between the Vietnamese real consumption and GDP growth. This exogeneity poses great challenges for the Vietnamese policymakers who must rebalance their transitional economy. This change, necessitated by recent crises in the international economic landscape, necessitates a shift in the Vietnamese economy from an export-led growth economy to a more inclusive, services-oriented, and consumer-based.