The characteristics and dependence structures of financial cycles have become a central issue in macroeconomic policy. Our study quantifies the dependence of financial cycles in emerging and developed countries in January 1993–December 2017. We fit the marginal distributions of the financial cycles by applying an ARIMA-GARCH model and capture the dependence structures by selecting the optimal copula model. Our main findings indicate that the financial cycle has obvious characteristics that can be roughly divided into three stages. ARIMA (2,1,2) and GARCH (1,1) are fit the marginal distribution of the financial cycle. Emerging countries show more interdependence and a higher degree of dependence than developed countries. Several important policy and economic implications can be drawn from the empirical results of this study.

Geopolitical factors are considered a crucial factor that makes a difference in crude oil prices. Over the last three decades, many political events occurred frequently, causing short-term fluctuations in crude oil prices. This paper aims to examine the dynamic correlation and causal link between geopolitical factors and crude oil prices based on data from June 1987 to February 2020. By using a time-varying copula approach, it is shown that the correlation between geopolitical factors and crude oil prices is strong during periods of political tensions. The GPA (geopolitical acts) index, as the real factor, drives the rise in prices of crude oil. Moreover, the dynamic correlation between geopolitical factors and crude oil prices shows strong volatility over time during periods of political tensions. We also found unidirectional causality running from geopolitical factors to crude oil prices by using the Granger causality test.

The 2008 international financial crisis triggered a heated discussion of the relationship between public health and the economic environment. We test the relationship between the credit cycle and happiness using the fixed effects model and explore the transmission channels between them by adding the moderating effect. The results show the following empirical regularities. First, the credit cycle has a negative correlation with happiness. This means that credit growth will reduce the overall happiness score in a country/region. Second, the transmission channels between the credit cycle and happiness are different during credit expansion and recession. Life expectancy and generosity can moderate the relationship between the credit cycle and happiness only during credit expansion. GDP per capita can moderate this relationship only during credit recession. Social support, freedom, and positive affect can moderate this relationship throughout the credit cycle. Third, the total impact of the credit cycle on happiness will become positive by the changes in the moderating effects. In general, we can improve subjective well-being if one of the following five conditions holds: (1) with the adequate support from the family and society, (2) with enough freedom, (3) with social generosity, (4) with a positive and optimistic outlook, and (5) with a high level of GDP per capita.

We use the state space model to describe the financial cycles of China and G7 countries since 1990, and the DY spillover index to quantify the spillover effects of China's financial cycles on G7 countries. We find that China plays the role of a net recipient most of the time. China's financial cycle net spillover index fluctuates widely and is vulnerable to economic events such as the financial crisis. This implies that international capital flows have brought volatility and shocks to the Chinese financial market, such as the Asian financial crisis and the 2008 international financial crisis. In addition, during 2004-2005 and 2014-2015, the G7 countries also suffered from financial cycle spillover from China. The US received most of the financial cycle spillover from China, followed by Canada, Germany, and Italy.

In this paper, we quantify the spillovers of Chinese financial cycles from 1990Q1 to 2017Q4. We construct a spillover index for Chinese financial cycles and fit the Markov-switching autoregressive model. Our main findings indicate that Chinese financial cycle spillover shows several general characteristics and has significant time-varying features that are very sensitive to specific events. We examine the three different regimes of net spillovers, labeling them contraction, moderation, and expansion, and find that the moderation regime dominates.