This study examines the use of high frequency data in finance, including volatility estimation and jump tests. High frequency data allows the construction of model-free volatility measures for asset returns. Realized variance is a consistent estimator of quadratic variation under mild regularity conditions. Other variation concepts, such as power variation and bipower variation, are useful and important for analyzing high frequency data when jumps are present. High frequency data can also be used to test jumps in asset prices. We discuss three jump tests: bipower variation test, power variation test, and variance swap test in this study. The presence of market microstructure noise complicates the analysis of high frequency data. The survey introduces several robust methods of volatility estimation and jump tests in the presence of market microstructure noise. Finally, some applications of jump tests in asset pricing are discussed in this article.
This article analyzes the economic impact of the COVID-19 outbreak, and puts forward with five basic insights concerning the degree of the impact, its duration, its key areas, and its quantitative calculation, among other aspects. The article holds that it is necessary to have a more objective understanding and judgement of how the virus affects the economy, particularly gross domestic product (GDP) growth for 2020Q1 and the entire year. Only on the basis of reasonable analysis can we better grasp measures required to cope with the economic impact, combined with more targeted policy launch and adjustment, so as to speed economic recovery to its normal level.
This study proposes a full Bayesian nonparametric procedure to investigate the predictive power of exchange rates in relation to commodity prices for three commodity-exporting countries: Canada, Australia, and New Zealand. We propose a new time-dependent infinite mixture of a normal linear regression model of the conditional distribution of the commodity price index. The mixing weights follow a set of Probit stick-breaking priors that are time-varying. We find that exchange rates have a positive predictive effect in general, but accounting for time variation does not improve forecasting performance. By contrast, the intercept in the regression and the lagged dependent variable show signs of parameter change over time in most cases, which is important in forecasting both the mean and the density of commodity prices one period ahead. The results also suggest that the variance is a large source of the time variation in the conditional distribution of commodity prices.
In this study, I explore smoking behavior among pregnant U.S. women using the 1979 cohort of the National Longitudinal Survey of Youth. The key aspect of this study is the availability of smoking participation data before and during pregnancy. I consider the probabilities of smoking cessation while pregnant as the outcome. I find that pregnant women who smoke are less responsive to price changes when they are more future-oriented. Women who are more present-oriented are more likely to smoke and consume more cigarettes given that they smoke more than those who are future-oriented. Moreover, those who discount the future more heavily are more sensitive to the money price of cigarettes than those who are more future-oriented. I focus on the role of time preference and the interaction between time preference and price in determining these outcomes.
This study revisits the Fisher effect using a different empirical method that considers a potential nonlinear relationship between interest rates (treasury bond rates) and inflation in China. The rising uncertainty and asymmetric information in financial markets between bond holders and bond issuers suggest such a potential nonlinear relationship. To this aim, we apply Shin et al.’s (2014) nonlinear autoregressive distributed lag (NARDL) model with asymmetric dynamic multipliers for the sample period 2002M7–2018M4. The empirical findings reveal symmetric and asymmetric partial Fisher effects for all sample bond rates in China. Furthermore, we find that 20-year bond rates experience the lowest partial Fisher effect.
There is no consensus on the impact of population aging on education investment. To explore this question, we first build an overlapping generations (OLG) model to theoretically analyze the effect of population aging on human capital investment in China, and then test our theory by conducting an empirical study based on micro household data. We find the following. (1) Theoretically, the OLG model shows that population aging has a crowding-out effect on education investment. (2) Empirically, the results show that the share of education and training expenditures decreases by 5.27 percentage points as the ratio of old people in the household increases by 100 percentage points, which confirms the crowding-out effect of population aging on human capital investment. (3) The crowding-out effect is far more intense on urban households than on rural households since health care expenditures will be greater in urban areas as population aging increases. (4) A quantile regression indicates that the negative effect of population aging on the share of educational expenditure is concentrated in households with higher shares of education expenditures. We confirm the robustness of our results using regional fixed effect and instrumental variable (IV) regressions.
To examine the correlation between regional economic growth and inter-region transportation costs in China, this study establishes a regional economic growth model embedded with inter-region transportation costs based on the Cobb-Douglas production function. Based on a balanced growth empirical model, this study verifies the correlation by conducting a regression analysis of the panel data of 29 provinces, municipalities, and autonomous regions from 1985 to 2015. The empirical results show that: (1) The per capita GDP growth among the three regions (namely, the eastern, central, and western regions of China) meets a conditional convergence trend, and the decreasing of the inter-region transportation costs increases the convergence speed; (2) The per capita GDP growth is in line with the club convergence trend within each of the three regions; (3) The trend of the output elasticity of the inter-region transportation costs shows that the gradual decrease of inter-region transportation costs has a positive correlation with the narrowing of economic disparity after the year 2000, accelerating "common prosperity" across different regions in China.