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1.
木质家具是我国最重要的出口林产品之一。人民币汇率改革后,人民币总体呈升值趋势,这一趋势提高了国产木质家具的出口价格,会产生阻碍出口的作用;与此同时其也会使进口原材料价格相对降低、促进原材料的进口,二者相互作用会共同影响木质家具出口额。通过建立回归模型,研究人民币汇率波动对中国木质家具出口贸易额的影响,结果表明人民币汇率与中国木质家具出口额呈负相关,但是通过人民币贬值来促进出口的策略并不明智。  相似文献   
2.
This study is the first attempt to examine the extreme risk spillovers between Malaysian crude palm oil (CPO) and foreign exchange currencies of the three largest CPO importers: India, the European Union and China throughout the global financial crisis. Using daily data of three currencies, CPO spot and futures from 2000 to 2018, our results show: First, before the crisis, the unexpected change in foreign exchange rates is the primary driver of risk spillover to the CPO market. Second, during the crisis, the extreme movement of CPO spot returns is dominant in the Malaysian exchange rates relative to the euro. Third, after the crisis, the spillover flows from the CPO market to the foreign exchange market. Overall, our findings show the importance of CPO pricing dynamics in mitigating foreign exchange risk over the crisis period. This paper contributes to the extant literature by recognizing the effect of risk spillover on the targeted foreign exchange rate for portfolio allocation.  相似文献   
3.
In this article, we investigate the existence of long-run common trends between imports and remittances in 11 Central and Eastern European countries which are part of the European Union. Using the Engle–Granger two-step procedure, we determine that for all countries in our sample there are no long-run common trends (no cointegration) between imports and remittances. However, the results are mixed when running a Granger causality test. For nine countries, we can establish either a bidirectional or unidirectional Granger causality, indicating that past values of one variable have predictive content on the other variable. In two countries, there is no Granger causality between imports and remittances.  相似文献   
4.
Using daily data from August 9, 2015, to July 7, 2020, this study examines the effects of economic policy uncertainty (EPU) on the returns of four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Ripple. To this end, two new measures of EPU (Twitter-based economic uncertainty and Twitter-based market uncertainty) are considered. A Granger causality test using the recursive evolving window approach shows a significant causality between the Twitter-based EPU measures and the BTC/USD exchange rate from October 2016 to July 2017. Moreover, a significant causality was noted from the EPU measures to the ETH/USD exchange rate from June 2019 to February 2020 and from the EPU measures to the XRP/USD exchange rate from January 2020 to February 2020. The Twitter-based EPU measures primarily positively affect the returns of the related cryptocurrencies during these periods. These results are robust to different measures of Twitter-based EPU and different econometric techniques. Potential implications, including the COVID-19 era, are also discussed.  相似文献   
5.
Using mostly theoretical models and traditional risk/uncertainty measures (VIX index, panic, precaution, scary bad news, etc.), the current literature tries to clarify the risk/uncertainty-deleveraging pattern. The findings are not sufficient to explain the dynamic empirical relationship between modern risk/uncertainty indicators and leverage. We fill this gap in the literature by using US quarterly data, from 1985:1 to 2018:4, Granger causality tests, and a structural vector autoregression model. We find that commercial bank leverage rises when geopolitical risk and macroeconomic, policy, and equity uncertainty increase. Client-based business relationships of banks and high government borrowing from banks during crises periods are responsible for this relationship. We find that the leverage of broker-dealers and shadow banks declines when Chicago risk and macroeconomic, policy, financial, and equity uncertainty increase. We argue that the vulnerability of broker-dealers and shadow banks to the risk/uncertainty of the entire market system is responsible for this relationship.  相似文献   
6.
We assess the conditional relationship in the time-frequency domain between the return on S&P 500 and confirmed cases and deaths by COVID-19 in Hubei, China, countries with record deaths and the world, for the period from January 29 to June 30, 2020. Methodologically, we follow Aguiar-Conraria et al. (2018), by using partial coherencies, phase-difference diagrams, and gains. We also perform a parametric test for Granger-causality in quantiles developed by Troster (2018). We find that short-term cycles of deaths in Italy in the first days of March, and soon afterwards, cycles of deaths in the world are able to lead out-of-phase US stock market. We find that low frequency cycles of the US market index in the first half of April are useful to anticipate in an anti-phasic way the cycles of deaths in the US. We also explore sectoral contagion, based on dissimilarities, Granger causality and partial coherencies between S&P sector indices. Our findings, such as the strategic role of the energy sector, which first reacted to the pandemic, or the evidence about predictability of the Telecom cycles, are useful to tell the history of the pass-through of this recent health crises across the sectors of the US economy.  相似文献   
7.
Are the forecast errors of election-eve polls themselves forecastable? We present evidence from the 2008 Democratic Party nomination race between Barack Obama and Hillary Clinton showing that the answer is yes. Both cross-sectional and time series evidence suggests that market prices contain information about election outcomes that polls taken shortly before the contests do not. Conversely, election surprises relative to polls too Granger cause subsequent price movements. We then investigate whether the additional information in prices could come from the media coverage of these campaigns, and uncover a set of complex relationships between pollster’s surprise, price movements, and various aspects of media coverage. Prices anticipate the balance and content of media coverage, but not the volume. On the other hand, it is the volume of media coverage, not the balance or content, that anticipates the surprise element in election outcomes. Moreover, Granger causality between prices and election surprises barely changes after controlling for media coverage, and causality from media volume to surprises persists too after controlling for price movements. Taken together, the results suggest that both prices and the volume of media coverage contain independent election-relevant information that is not captured in polls.  相似文献   
8.
Dynamic interactions between policy uncertainty and economic activity, including oil prices, have attracted increasing amounts of scholarly interest, but few studies have considered the inherent feature that the entire market is composed of different stakeholders operating in different time horizons. To fill this gap and address this issue, this paper proposes a multi-scale correlation framework. Specifically, we use the wavelet coherence method and scale-by-scale linear Granger causality tests to explore the co-movement and causality of pairs of economic policy uncertainty indices of G7 countries, China, Brazil, and Russia and West Texas Intermediate (WTI) oil prices. Our results show that the interaction between economic policy uncertainty and oil prices in the short-term is weak but gradually strengthens towards the long-term, especially when significant historical political or financial events occurred. Moreover, a consistent conclusion is that the interaction is negative in the medium-term, while it is positive in the long-term. Further, Granger causality tests at different time-scales show that no Granger causality from economic policy uncertainty to oil prices exists in the short-term for all sample countries, except the US, while there is a strong unidirectional or bidirectional Granger causality for all researched countries in the medium- and the long-term.  相似文献   
9.
Abstract:

This study focuses on the measurement of spillover effects from macroeconomic factors to commodity volatility. It argues that such measurement is sensitive to volatility computation and to causality testing. To this end, I analyze two commodity data sets-gold and the Continuous Commodity Index (1969-2011), and twenty-four Dow Jones futures indexes (1991-2011)-and various macroeconomic indicators. I conclude that the macroeconomic factors that influence volatility generally depend on the commodity under consideration. I also explore whether commodities of the same class experience volatility shifts around the same dates, and find that this is not the case except for energy commodities.  相似文献   
10.
本文首先从理论上深刻剖析了房地产泡沫与银行信贷规模相互之间的作用与传导机制,在此基础上选取2006年-2018年相关指标的年度数据,对房地产泡沫与银行信贷规模进行了图形拟合与周期性波动规律分析,分析发现二者存在极高的契合度。建立房地产泡沫的函数,构建协整方程实证发现银行信贷规模对房地产泡沫的长期弹性系数为0.51,从长期来看银行信贷规模每增加1%,房地产泡沫也相应增加0.51%,进一步建立VAR模型实证发现房地产泡沫与银行信贷规模互为格兰杰因果关系,二者相互影响、相互促进。通过方差分解实证发现银行信贷规模对房地产泡沫的变动具有重要的影响,另一方面,房地产泡沫是影响银行信贷规模变动最主要的因素。  相似文献   
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