Which return regime induces overconfidence behavior? Artificial intelligence and a nonlinear approach.

Overconfidence behavior, one form of positive illusion, has drawn considerable attention throughout history because it is viewed as the main reason for many crises. Investors' overconfidence, which can be observed as overtrading following positive returns, may lead to inefficiencies in stock markets. To the best of our knowledge, this is the first study to examine the presence of investor overconfidence by employing an artificial intelligence technique and a nonlinear approach to impulse responses to analyze the impact of different return regimes on the overconfidence attitude. We examine whether investors in an emerging stock market (Borsa Istanbul) exhibit overconfidence behavior using a feed-forward, neural network, nonlinear Granger causality test and nonlinear impulse-response functions based on local projections. These are the first applications in the relevant literature due to the novelty of these models in forecasting high-dimensional, multivariate time series. The results obtained from distinguishing between the different market regimes to analyze the responses of trading volume to return shocks contradict those in the literature, which is the key contribution of the study. The empirical findings imply that overconfidence behavior exhibits asymmetries in different return regimes and is persistent during the 20-day forecasting horizon. Overconfidence is more persistent in the low- than in the high-return regime. In the negative interest-rate period, a high-return regime induces overconfidence behavior, whereas in the positive interest-rate period, a low-return regime induces overconfidence behavior. Based on the empirical findings, investors should be aware that portfolio gains may result in losses depending on aggressive and excessive trading strategies, particularly in low-return regimes.

The causal relationship between green finance and geopolitical risk: Implications for environmental management.

This study investigates the time-varying causal relationship between geopolitical risk and green finance during the period of 1 March 2012-February 16, 2022. By using the novel time-varying causality testing framework, our findings shed light on the nexus between geopolitical risk and green finance in informing environmental management decisions. First, we find that time heterogeneity does exist in the causal relations between geopolitical risk and green finance. Second, geopolitical risk has a more prolonged impact on the volatility of green bonds and renewable energy than the return. Yet, geopolitical risk tends to influence the return of clean energy more persistently than volatility. Third, we observe that geopolitical risk has a more sustained impact on the return and volatility of renewable energy than clean energy. This might be due to the distinct nature of the production of clean energy and renewable energy, thereby providing implications for effective environmental management. Lastly, this paper demonstrates that the impact of geopolitical risk on the return of European clean energy has diminished since the onset of 2015. The volatility of the European clean energy sector is not affected by global geopolitical risk, underscoring the necessity of promoting the development of this sector to reduce the dependence on fossil fuels and enhance energy independence.

Effects of pandemics uncertainty on fertility.

The COVID-19 pandemic has affected various dimensions of the economies and societies. At this juncture, this paper examines the effects of pandemics-related uncertainty on fertility in the panel dataset of 126 countries from 1996 to 2019. For this purpose, the World Pandemics Uncertainty Indices are used to measure the pandemics-related uncertainty. The novel empirical evidence is that pandemics-related uncertainty decreases fertility rates. These results are robust to estimate different models and include various controls. We also try to explain why the rise in uncertainty during the COVID-19 pandemic has resulted in the fertility decline.

Testing the Club Convergence Dynamics of the COVID-19 Vaccination Rates Across the OECD Countries.

Vaccines are essential to create a more resilient economic growth model. Ending the COVID-19 pandemic requires a more coordinated, effective, and equitable distribution of vaccines across the countries. Therefore, governments are in a race to increase the vaccination rates of the population. Given this backdrop, this paper focuses on the daily vaccinations per million data from March 1, 2021, to October 15, 2021, in 37 Organization for Economic Co-operation and Development (OECD) countries and examines the stochastic properties of the vaccination rates. We adopt the club convergence econometric methodology to investigate the club convergence paths of COVID-19 vaccination rates in OECD regions. The results indicate a significant convergence of the vaccination rates in seven clubs across 30 OECD countries. Moreover, there are seven OECD countries demonstrate non-convergent characteristics, which raises questions about ineffective vaccine balance. In addition, the paper also discusses the potential implications for the post-COVID-19 era.

Energy market uncertainty and the impact on the crude oil prices.

Our paper proposes a novel measure of global energy market uncertainty and studies its impact on oil prices. The current literature primarily relies on a single or small number of observable variables, or general macroeconomic uncertainty (JLN) and economic policy uncertainty (EPU) indices to reflect energy market uncertainty. Using a Factor Augmented Vector Autoregression model (FAVAR), we construct time-varying global energy market uncertainty in a data-rich environment. Our estimates show variations from JLN and EPU proxies. The results reveal that real oil prices respond strongly to our proposed aggregate energy market uncertainty shocks. We also find heterogeneous responses to different types and magnitudes of uncertainty shocks. The real price of oil is affected the most under unexpected strong demand for alternative energy sources scenario.

Economic Policy Uncertainty in China and Bitcoin Returns: Evidence From the COVID-19 Period.

This paper analyses the effects of the Chinese Economic Policy Uncertainty (CEPU) index on the daily returns of Bitcoin for the period from December 31, 2019 to May 20, 2020. Utilizing the Ordinary Least Squares (OLS) and the Generalized Quantile Regression (GQR) estimation techniques, the paper illustrates that the current CEPU has a positive impact on the returns of Bitcoin. However, the positive impact is statistically significant only at the higher quantiles of the current CEPU. It is concluded that Bitcoin can be used in hedging against policy uncertainties in China since significant rises in uncertainty leads to a higher return in Bitcoin. JEL Codes: G32; G15; C22.

Does international cooperation affect CO2 emissions? Evidence from OECD countries.

This paper analyzes the role of international cooperation on CO2 emissions growth in 36 OECD economies over the period 1970-2016. The indices of political globalization are the benchmark measure of international cooperation since a higher value of the index of political globalization is an indicator of collaboration in the world. The paper finds that political globalization decreases CO2 emissions growth. The findings remain robust when we consider the sub-indices of political globalization and include various controls. Also, the findings of the panel quantile regressions with the fixed-effects via the method of moments indicate that the effects of per capita income and the initial level of CO2 emissions are higher in more pollutant countries. However, the impact of political globalization on CO2 emissions is stable at different quantiles. The paper also discusses the potential implications for the role of international cooperation on climate change.

Jumps beyond the realms of cricket: India's performance in One Day Internationals and stock market movements.

We examine the impact of the Indian cricket team's performance in one-day international cricket matches on return, realized volatility and jumps of the Indian stock market, based on intraday data covering the period of 30th October, 2006 to 31st March, 2017. Using a nonparametric causality-in-quantiles test, we were able to detect evidence of predictability from wins or losses for primarily volatility and jumps, especially over the lower-quantiles of the conditional distributions, with losses having stronger predictability than wins. However, the impact on the stock return is weak and restricted towards the upper end of the conditional distribution.

Does tourism investment improve the energy efficiency in transportation and residential sectors? Evidence from the OECD economies.

This paper investigates the impact of tourism investments on energy efficiency across the transportation and residential sectors of 32 Organization for Economic Co-operation and Development economies. Using annual data from 1995 to 2012, we employ various panel econometric techniques to achieve the study objectives. Given the nature of variables, the paper applies panel autoregressive distributed lag models to estimate the long-run elasticities of energy intensity. The long-run estimates confirm that tourism investments play an essential role in improving energy efficiency across the transportation and residential sectors. Furthermore, the results show that both the foreign direct investment inflows and trade openness also play a considerable role in reducing energy uses across these sectors. Finally, the findings suggest that the tourism investments Granger cause energy efficiency of transportation and residential sectors in the short-run. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

Natural disasters, climate change, and their impact on inclusive wealth in G20 countries.

This paper uses the 1990-2010 natural disaster and carbon emission data of G20 countries to examine the impact of natural disasters and climate change on the natural capital component of inclusive wealth. Our study shows that climate change and GDP have no positive impacts on the growth of natural capital. By contrast, trade openness and natural disaster frequency contribute to the accumulation of natural capital in G20 countries. There is an inverted U-shaped relationship between the growth of natural capital and the magnitude of natural disaster. Natural capital growth is not affected very much by small disasters. By contrast, large disasters tend to make the growth of natural capital fall sharply.

Effects of export concentration on CO2 emissions in developed countries: an empirical analysis.

This paper provides the evidence on the short- and the long-run effects of the export product concentration on the level of CO2 emissions in 19 developed (high-income) economies, spanning the period 1962-2010. To this end, the paper makes use of the nonlinear panel unit root and cointegration tests with multiple endogenous structural breaks. It also considers the mean group estimations, the autoregressive distributed lag model, and the panel quantile regression estimations. The findings illustrate that the environmental Kuznets curve (EKC) hypothesis is valid in the panel dataset of 19 developed economies. In addition, it documents that a higher level of the product concentration of exports leads to lower CO2 emissions. The results from the panel quantile regressions also indicate that the effect of the export product concentration upon the per capita CO2 emissions is relatively high at the higher quantiles.