This paper develops a network to analyze inter-industry risk spillovers during high and low volatility periods. Our findings indicate that China's Industrials and Consumer Discretionary exhibit the greatest levels of spillovers in both high and low volatility states. Notably, our results demonstrate the "event-driven" character of structural changes to the network during periods of pronounced risk events. At the same time, the economic and financial network exhibits clear "small world" characteristics. Additionally, in the high volatility stage, the inter-industry risk contagion network becomes more complex, featuring greater connectivity and direct contagion paths. Furthermore, concerning the spillover connection between finance and the real sector, the real economy serves as a net exporter of risk. The study's findings can assist government agencies in preventing risk contagion between the financial market and the real economy. The empirical evidence and policy lessons provide valuable insights for effective risk management.

This paper examines return spillovers within and between different DeFi, cryptocurrency, stock and safe-haven assets. The results show that DeFi and cryptocurrency asset markets exhibit strong within-market and between-market return spillovers, that stock and safe-haven markets show weak connectedness, and that safe-haven assets are minor receivers and transmitters of between-market spillover effects. The connectedness between markets is time varying and reveals structural changes in early 2020. Furthermore, we document that financial conditions shape the dynamics of return spillover effects between markets.

Developing countries are characterized by frictions that impede the mobility of workers across occupations and space. We disentangle the role of insecure property rights from other labor mobility frictions for the reallocation of labor from agriculture to non-agriculture and from rural to urban areas. We combine rich household and individual-level panel data from China and an equilibrium quantitative framework that features the sorting of workers across locations and occupations. We explicitly model the farming household and the endogenous decisions of who operates the family farm and who potentially migrates, capturing an additional channel of selection within the household. We find that land insecurity has substantial negative effects on agricultural productivity and structural change, raising the share of households operating farms by almost 30 percentage points and depressing agricultural productivity by more than 10 percent. Quantitatively, land insecurity is as important as all other labor mobility frictions. We measure a sharp reduction in overall labor mobility barriers over 2004-2018 in the Chinese economy, all of which can be accounted for by improved land security, consistent with reforms covering rural land in China during the period.

We investigate, for China’s investable companies, the relation between stock returns and firm characteristics, and the impacts on the relation of the 2001-2003 financial reforms to further liberalize stock markets. For the first time in the literature, we document coexistence of a positive size effect and a growth effect, and the importance of liquidity and positive earnings for returns; and we also show that they underwent a structural break upon the reforms. These results are robust across 12 alternative panel model specifications with different ways of estimating and controlling for the market beta, different proxies for market portfolios, the problem of outliers considered, and the January effect allowed for.

Early-stage ?rms usually have a single large Research and Development (R&D) project that requires multi-stage investment. Firms? volatility can dramatically change due to the evolvement of R&D e¤orts and stage clearing. First, the success (failure) of R&D e¤orts within each stage (jump risk) decreases (increases) the un- certainty (i.e. volatility) level of the ?rms?future returns ?"jump e¤ect". Second, at the end of each stage, ?rms decide whether to continue next stage investment upon re-evaluating the project prospect conditional on the resolution of technical uncertainty and other information; as ?rms survive each investment stage and are becoming mature, the uncertainty level of their future returns should eventually decrease in later investment stages that lead to maturity ?"stage-clearing e¤ect". Ignoring these e¤ects results in incorrect estimation of ?rms?future volatility, an important element for early-stage ?rm valuation. In this paper, I develop a gener- alized Markov-Switching EARCH methodology for early-stage ?rms with discrete stage-clearing and jumps. My methodology can identify structural changes in the idiosyncratic volatility and also explore the relation between price changes and future volatility. Using a hand-collected dataset of early-stage biotech ?rms, I con?rmed the existence of the "stage-clearing e¤ect" and the "jump e¤ect". In the second part of my paper, I model early-stage ?rms as sequences of nested call options with jumps that lead to mature ?rms. "Jump e¤ect" arises because the early-stage ?rms are modeled as compound call options with jumps on the underly- ing cash ?ows, the volatility of the early-stage ?rms at each stage is determined by the compound call option elasticity to the underlying cash ?ows. If the downside (upside) jump happens, the value of the underlying cash ?ows decreases (increases), which makes the compound call option elasticity go up (down). As a result, the compound call option becomes riskier (less risky). "Stage-clearing e¤ect" arises because as ?rms exercise their option to continue investment, the new options that ?rms enter into will eventually become a less risky option.

本文提出的综合理论框架全面分析描述了以稳定物价水平、促进国民经济持续增长为目的的货币政策与股票市场的关系，着重对中央银行干预股票市场的必要性和有效性进行理论分析和实证检验。本文应用的动态滚动式的计量检验方法适应中国经济体制不断调整的特征，不但可以完成我们的理论分析，更可以检测中央银行对股票市场干预的机制及干预的有效性，从而分析进一步的政策含义，为中央银行的货币政策制订和预期效果提供一个前瞻性的预测分析框架。This paper develops a comprehensive framework to analyze the relationship of monetary policy and stock market.We focus on the necessity and efficacy of central bank intervention in the stock market in China. We applied rolling VAR estimation and augmented VAR Granger causality testing technique to capture the frequent structural changes in China due to her gradual economic and financial reforms.