KAUZALNOST IZMEĐU EMISIJE UGLJIKA, POTROŠNJE ENERGIJE I RASTA U INDIJI

This study attempts to investigate the long-run Granger causality relationship between energy consumption, carbon dioxide emission and economic growth in India over the period 1971-2007. The augmented Dickey–Fuller test (ADF), Phillips-Perron test (PP) and KPSS test are used to test for Granger causality in cointegration models which take account of the stochastic properties of the variables. The most important result is that there is feedback causal relationship between energy consumption and economic growth in India which implies that the level of economic activity and energy consumption mutually influence each other; a high level of economic growth leads to a high level of energy consumption and vice versa. The value of the error correction term confirms the expected convergence process in the long-run for carbon emissions and growth in India which implies that emission reduction policies will hurt economic growth in India if there are no supplementary policies which seek to modify this causal relationship.Ovaj rad istražuje dugoročnu Grangerovu kauzalnost između potrošnje energije, emisije ugljikovog dioksida i ekonomskog rasta u Indiji u periodu od 1971. do 2007. Za testiranje Grangerove kauzalnosti u kointegracijskim modelima koji uračunavaju stohastička svojstva varijabli korišteni su prošireni Dickey-Fuller test (ADF), Phillips-Perron test (PP) i KPSS test. Najvažniji rezultat je da je utvrđena povratna kauzalna veza između potrošnje energije i ekonomskog rasta, što ukazuje na međusoban utjecaj razine ekonomske aktivnosti i potrošnje energije; veliki ekonomski rast dovodi do visokog stupnja potrošnje energije i obrnuto. Vrijednost korekcije greške potvrđuje dugoročno očekivani proces konvergencije za emisiju ugljika i rast u Indiji što upućuje na zaključak da će politika smanjenja emisije ugljika oštetiti ekonomski rast Indije ukoliko ne bude zamjenskih politika koje će pokušati modificirati kauzalnu vezu

Global energy transition: From the main determinants to economic challenges

Dynamic global energy transition has been accelerating for the last decade. Interestingly, the energy transition is multidimensional and concerns both the dimensions of technique/ technology and the economic, social, institu-tional, and legal spheres

Brexit uncertainty and volatility persistence in tourism demand

Tourism has emerged as one of the leading components of aggregate economic growth in most developed economies, especially in the UK, where it is predicted to grow at an annual rate of 3.8% through 2025. Because tourism demand represents individuals’ choice between leisure and work, a persistence of negative shocks, such as Brexit uncertainty, can be detrimental to the growth of tourism via its impact on agents’ utility function of a directed consumption of leisure for a specific country. This note fills a gap in the literature by providing an econometric estimate of time-varying volatility in tourism demand following Brexit-driven Economic Policy Uncertainty. Using seasonally adjusted and trend-extracted tourist arrival series along with Brexit uncertainty, we find a strong evidence of long-run persistence in (asymmetric) volatility in tourist arrival. In particular, the BREXIT referendum appeared to create ambiguity among international visitors to the UK. Our results have important policy implications.©2020 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Current Issues in Tourism on 24 Sep 2020, available online: http://www.tandfonline.com/10.1080/13683500.2020.1822300.fi=vertaisarvioitu|en=peerReviewed

Forecasting mid-price movement of Bitcoin futures using machine learning

In the aftermath of the global financial crisis and ongoing COVID-19 pandemic, investors face challenges in understanding price dynamics across assets. This paper explores the performance of the various type of machine learning algorithms (MLAs) to predict mid-price movement for Bitcoin futures prices. We use high-frequency intraday data to evaluate the relative forecasting performances across various time frequencies, ranging between 5 and 60-min. Our findings show that the average classification accuracy for five out of the six MLAs is consistently above the 50% threshold, indicating that MLAs outperform benchmark models such as ARIMA and random walk in forecasting Bitcoin futures prices. This highlights the importance and relevance of MLAs to produce accurate forecasts for bitcoin futures prices during the COVID-19 turmoil

Connectedness of energy markets around the world during the COVID-19 pandemic

his paper studies the connectedness among energy equity indices of oil-exporting and oil-importing countries around the world. For each country, we construct time-varying measures of how much shocks this country transmits to other countries and how much shocks this country receives from other countries. We analyze the network of countries and find that, on average, oil-exporting countries are mainly transmitting shocks, and oil-importing countries are mainly receiving shocks. Furthermore, we use panel data regressions to evaluate whether the connectedness among countries is influenced by economic sentiment, uncertainty, and the global COVID-19 pandemic. We find that the connectedness among countries increases significantly in periods of uncertainty, low economic sentiment, and COVID-19 problems. This implies that diversification benefits across countries are severely reduced exactly during crises, that is, during the times when diversification benefits are most important

Climate risk and green investments : New evidence

The academic literature on green energy equity markets has increased extensively over the last decade due to growing concerns about climate change and the substantial flow of investments into alternative energy markets. This study contributes by investigating the effect of climate risk on the return and volatility of green energy assets. This is one of the first papers to assess such effects using the recently developed climate policy uncertainty index as an indicator of climate risk. In particular, we seek to answer the following research questions. Firstly, does rising climate risk lead to a significant increase in green energy asset returns? Secondly, does climate risk affect the volatility of green energy assets negatively? Employing various models, we provide statistical evidence in favour of our hypotheses. Rising climate risk seems to encourage investment in alternative energy, which leads to an upward demand for green energy, which in turn increases the prices of green energy investments and decreases their volatility levels. Our analysis further shows that when climate risk increases, the correlation between crude oil and green energy returns decreases. Furthermore, green energy assets are more effective than gold for hedging oil market risk, without ignoring the hedging ability of technology stock investment.© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Systemic risk contribution of banks and non-bank financial institutions across frequencies: The Australian experience

The Australian financial sector (AFS) is highly concentrated and interconnected. Besides, Australian banks' lending portfolios are dominated by residential mortgage loans, and 70% of insurance companies' revenues arise from non-policyholder sources. The AFS also performed relatively well during the global financial crisis (GFC). Given these distinctive features, in this paper, we examine the systemic risk contribution of Australian banks, insurance companies, and other financial services providers. We use a flexible copula-based delta conditional value-at-risk (ΔCoVaR) method across different frequencies. Further, we study the systemic risk determinants in a panel setting. We find that the major Australian banks are systemically more important than all other financial institutions. Systemic risk is typically higher after the GFC than in the pre-crisis period, despite the introduction of more stringent capital requirements. In addition, the short-term ΔCoVaR is significantly higher than the medium- and long-term ΔCoVaRs. Finally, institution-specific characteristics and market-wide variables explain the cross-sectional and time-series variation in systemic risk, and their explanatory power varies across frequencies.publishedVersio

Does J-Curve Phenomenon Exist in Case of Laos? An ARDL Approach

This study aims to test the existence of J-curve phenomenon in Laos’s economy using quarterly data over the period of 1993-2010. The ARDL bounds testing approach to cointegration is used to examine short run as well as long run impact of real depreciation of Lao kip on Lao trade balance. The empirical results suggest that there is J-curve effect in case of Laos. The impact of real depreciation of the Lao kip on Lao trade balance is insignificant in long run. In short-run, real depreciation has inverse impact on Lao’s trade balance. The long-run trade balance is determined by domestic income

The Causal Nexus between Financial Development and Economic Growth in Kenya

This paper aims to reexamine the relationship between financial development and economic growth in Kenya over the period of 1971-2011. Since, financial sector plays a vital role in mobilizing and allocating savings into productive ventures, the core issue of this investigation remains important for developing economics. The examination is based on a Cobb-Douglas production augmented by incorporating financial development. A simulation based ARDL bounds testing and Gregory and Hansen’s structural break cointegration approaches are being utilized in this study. Cointegration is being found between the series in the presence of a structural break in 1992. It is also being established that, in the long run, development of financial sector has positive impact on economic growth. Here remains an important policy implication for the concerned individuals of Kenya, that is, they may emphasize on financial development to ignite economic growth

A Note on Nominal and Real Devaluation in Laos

In this paper, we investigate whether or not nominal devaluation leads to real devaluation in Laos by using the ARDL bounds testing and the Granger causality test in a VECM framework. Our empirical evidence shows that nominal devaluation Granger causes real devaluation in short run and long run. This finding implies that nominal devaluation leads to real devaluation