Journal of Economic Asymmetries最新文献

This paper provides fresh evidence of temperature effects on GDP per capita growth and economic policy uncertainty $\left(epu\right)$. We apply the quantile via moments methodology (Machado and Santos Silva, 2019) in a sample of 31 countries for the period 1980–2021, the most current time frame of the work we reviewed. To the best of our knowledge, temperature effects on $epu$, in a panel quantile setting, have not been examined before. Our empirical results provide evidence in favor of asymmetric temperature impacts on both growth rates and $epu$. Specifically, according to our main findings: First, the impact of temperature on the growth rate of GDP per capita is quadratic, negative and increases, in absolute terms, as we move from the upper (flourishing economy) to the lower (bearish economy) quantiles. Second, hotter countries are more vulnerable to economic policy uncertainty, with the effect being more pronounced as uncertainty increases. Third, the temperature effect on GDP is higher than the political effect in weaker economies, while the political effect becomes of greater magnitude in stronger economies. Overall, our results indicate that an increase in temperature due to climate change poses important threats for the development prospects especially, but not exclusively, of the poorer countries that usually have both higher temperatures and face severe issues of economic policy uncertainty due to political instability and lack of basic economic infrastructure.

This study investigates the heterogeneous impacts of eight categories of geopolitical risk on stock market performance across different market conditions in four Middle Eastern economies: Egypt, Israel, Saudi Arabia, and Turkey. Utilizing Quantile regression analysis and datasets spanning from September 2002 to August 2023, our findings reveal the complex and varied relationships between geopolitical risk factors and stock market performance. These results underscore the significance of comprehending specific political risk factors and their influence under various market conditions. We observe a consistent negative relationship between military buildups and stock market performance in Egypt and Israel, while other categories exhibit mixed effects. The Saudi Arabian and Turkish markets demonstrate varied sensitivity to different risks, with terrorism and war-related events significantly affecting market dynamics. Notably, all four markets consistently displayed negative reactions to terrorist activities, indicating the universally disruptive nature of such events. Understanding these dynamics assists investors and policymakers in adapting to global political changes.

This research delves into the effects of recent crises on investor behavior within the currency options market, particularly focusing on the relationship with underlying exchange rates. Analyzing daily EUR/USD currency call pair data from May 4, 2011, to June 19, 2023, we employ a genetic algorithm to calculate stochastic volatility in line with the Garman and Kohlhagen model. Through the application of the STAR model, we identified shifts in investor behavior across various crisis periods. These shifts are linked to inherent asymmetries in the time series data, illustrating the diverse strategies of different investor types, such as fundamentalists and chartists. Our findings reveal how each investor group tailors its approach to these market asymmetries, showcasing distinct strategies and responses to fluctuating market conditions and crises. This study contributes to the financial literature by offering a more nuanced understanding of how crises influence investor behavior and the dynamics of currency markets. Ultimately, it sheds light on the complexities of investor behavior during economic challenges.

Fostering innovation is one of the key roles of the Circular Economy (CE) that applies also to European Union (EU) firms, because entrepreneurs are persistently seeking new ways and means to create values, contributing with significant market opportunities, and depicting large potential for EU sustainable growth. This study explores the effects of firms’ investments in using highly disruptive technologies in the energy sector on the Eurozone (EU-27) in the last two decades (1990–2019). An Artificial Neural Networks (ANNs) experiment through a Deep Learning (DL) approach is implemented to test this hypothesis. The empirical findings show that investments in highly disruptive technologies, especially by large digitally qualified companies, boost economic growth. They are also a crucial driver of digitalization not only because they enhance a wide strategic change implying a radical innovation in business models, but they completely transform markets, from energy to food production, water resources, pollution, connectivity, and plastic waste. These expected benefits represent a possible policy measure to offset the decline in global activity due to the impact of the Russia-Ukraine war on global energy markets. In addition, a positive association between trade and output is confirmed. Finally, promising policy actions are discussed.

The purpose of the present investigation is to scrutinize the impacts of green energy technologies, trade, the per capita income, and oil price on the carbon dioxide emissions and ecological footprint in France over the 1980/2022 period. Therefore, to achieve this objective, the Non-linear Autoregressive Distributed Lag (NARDL) approach is employed.

In fact, the obtained results showed that renewable energy is a contributor to the improvement of the French environment. In fact, a positive shock to renewable energy alleviates both the CO₂ emissions and the ecological footprint. Moreover, an upsurge in oil prices reduces the CO₂ emissions while their reduction enhances the ecological footprint. On the other hand, trade is proven to have a negative effect on the environmental damage. Furthermore, a positive variation in the GDP per capita exerts a positive upshot on the CO₂ emissions and ecological footprint, in the long run, whereas, a negative shock to the GDP per capita has a negative impact on the carbon dioxide emissions. Finally, a robustness check analysis is added using quantile regression (QR) in order to explore the effects of positive and negative variations of the different explanatory variables.

In fact, referring to these results, some strategic directions are proposed in order to decarbonize the French economy. Therefore, diversifying the electricity mix by introducing more renewable energies should be a priority. On the other hand, in order to avoid an increase of the State's energy bill in the event of an increase of the oil prices, it is important to reduce oil imports by increasing energy production from renewable sources such as hydraulic, solar, and wind energies.

This paper presents, first, a theoretical model that, by highlighting that commercial banks with market power are able to positively pass on to their clients variations in their costs and, furthermore, that the strength with which they can do so is in turn asymmetrically related to the elasticity of the demand for loans exhibited by those clients, explains the asymmetric empirical findings shortly described. Secondly, it empirically investigates the pass-through of monetary policy rates (MPR) changes into the consumer and commercial loans interest rates set by commercial banks in four Latin American countries with inflation targeting (IT) schemes, namely (in alphabetic order) Brazil, Chile, Colombia, and Peru, over a homogeneous period. To do so, it estimates Non-Linear Auto-Regressive Distributed Lag (NARDL) models for each country. Then, we find two types of important asymmetric responses in the interest rate channel of IT monetary policy. The first is that the long-run response of the consumer loans interest rates following increases in the MPR is greater than that of the commercial loans interest rates. The second is that, in general, when the demand is relatively more elastic (as in the case of commercial loans) then the banks interest rates tend to exhibit a greater response when the central bank lowers the MPR than when it raises it.

This study investigates the historical nexus between economic development and fertility in eight highly advanced European economies between 1870 and 2014. We employ the method of moments quantile regression (MMQR), which enables us to examine the impact of the different levels of economic development on fertility. We also consider the role of mortality and marriage to gain a more comprehensive view of the relationship. Our results from the linear and panel quantile models suggest an inverse J-shaped pattern between economic development and fertility. However, the inverse J-shape vanishes when time effects are considered in the quantile regression model, while the impact of mortality and marriage on fertility is reinforced. To further elaborate our findings, we also employ a nonparametric panel estimation method with time-varying coefficients. Our results also suggest that periods characterized by a positive economic development effect on fertility rarely coincide with an upward movement in the observed fertility trajectory. We infer that economic development per se did not drive either the historical baby-boom period or the recent fertility rebound.

Access to higher education in several countries still has many barriers, mainly represented by the high cost of tuition fees. Given the importance of higher education for innovation and economic growth, this paper analyzes the best financing scheme for needy students. Using an asymmetric information model, the paper shows that student loans involve a moral hazard problem with sub-optimal levels of effort and quality of education, and are socially inefficient and inequitable. On the other hand, merit-based scholarships and need-based grants pose no moral hazard, are socially efficient, and are no more expensive than alternative financing schemes. In particular, while scholarships may be more cost-effective than grants, the latter allow to achieve directly the first best. The paper also examines loan forgiveness policies and talent funding. The results of the model are supported by a large strand of empirical literature.

The objective of this work is to assess the linkages between conventional and organic milk markets in the US. To this end, it employs the recently developed Quantile Frequency Connectedness (QFC) model and monthly retail prices from January 2009 to February 2024. The empirical results suggest: First, price connectedness is both quantile- and frequency-dependent. Second, adjustments to incoming information are likely to completed within 3 months. Third, large (in absolute value) price shocks result in stronger price connectedness relative to small. Fourth, where asymmetric connectedness exists, it points to the conventional milk market as a net transmitter of shocks to organic. Fifth, although the retail share of organic milk has increased rapidly, the intensity of price connectedness remained fairly stable over time.

This paper investigates the impacts and heterogeneity of the ECB's large-scale asset purchasing programs of sovereign securities on real GDP, inflation, long-term sovereign bond yields, systemic stress, and the unemployment rate. A structural Bayesian VAR model with six endogenous variables was estimated for 11 euro area countries over the period 2012:M1 to 2023:M12. To provide robustness to the results, a structural panel BVAR model is estimated, enabling a straightforward comparison of impulse responses of vulnerable and non-vulnerable countries. The results suggest that the magnitudes of impulse responses were more favorable in countries that were more economically and financially vulnerable. These findings underscore that financial and economic distress was a source of heterogeneity in the responses to large scale asset purchases within the euro area.