Portfolio underdiversification is one of the most costly losses accumulated over a household’s life cycle. We provide new evidence on the impact of financial inclusion services on households’ portfolio choice and investment efficiency using 2015, 2017, and 2019 survey data for Chinese households. We hypothesize that higher financial inclusion penetration encourages households to participate in the financial market, leading to better portfolio diversification and investment efficiency. The results of the baseline model are consistent with our proposed hypothesis that higher accessibility to financial inclusion encourages households to invest in risky assets and increases investment efficiency. We further estimate a dynamic double machine learning model to quantitatively investigate the non-linear causal effects and track the dynamic change of those effects over time. We observe that the marginal effect increases over time, and those effects are more pronounced among low-asset, less-educated households and those located in non-rural areas, except for investment efficiency for high-asset households.

We develop an information choice model where information costs are sticky and co-move with firm-level intrinsic uncertainty as opposed to temporal variations in uncertainty. Incorporating analysts' forecasts, we predict a negative relationship between information costs and information acquisition, as proxied by the predictability of analysts' forecast biases. Finally, the model shows a contrasting pattern between information acquisition and intrinsic and temporal uncertainty, where intrinsic uncertainty strengthens return predictability of analysts' biases through the information cost channel, while temporal uncertainty weakens it through the information benefit channel. We empirically confirm these opposing relationships that existing theories struggle to explain.

The e-CNY, with its information transparency and financial inclusion, activates an innovative solution to cure the financing obstacles among the small and medium enterprises in China. The research establishes a game model between enterprises and commercial banks embedded in information asymmetry, and incorporates the e-CNY payment choice within the framework to analyse the cure effect of e-CNY on enterprise financing obstacles. With equilibrium results calculated, it simulates the outcomes of changing parameters on the behaviours of enterprises and banks. The findings involve that, based on the incremental utility of e-CNY and subsidies attached, e-CNY is preferred in transaction, reducing the bad debt risk caused by misalignment when both achieving excess returns. The People’s Bank of China must strengthen a more transparent publicity of e-CNY and structure an inclusive system of financial regulation to well use digital currency and realise high-quality socio-economic development.

We study the effects of mortgage debt and informal home loans on stock ownership. Mortgage debt is typically originated with licensed financial institutions while informal home loans are obtained from private lending. Using the China Household Finance Survey data, we show that mortgage debt has a positive relationship, while informal home loans have a negative relationship, with a household’s likelihood and degree of subsequent stock market participation. Instrumental variable estimates identify a causal impact of these effects. Further tests demonstrate cross-sectional variations of these effects across urban development, education, financial literacy, loan interest rate, maturity, and funding sources.

We develop a signaling game model of investment to explore the effects of ambiguity aversion on corporate equilibrium strategies, investment dynamics, and financing decisions in incomplete markets with asymmetric information. Our analysis shows that volatility ambiguity aversion has a similar but more pronounced effect than asymmetric information, leading to higher financing costs, lower investment probabilities, and a greater likelihood of non-participation in investment. Importantly, volatility ambiguity aversion exhibits an amplifier effect, magnifying financing costs, adverse selection costs, and distortion in investment choices under asymmetric information. This increased ambiguity aversion raises the chances of inefficient separating and pooling equilibria, resulting in notable welfare losses. These findings highlight the significant impact of ambiguity aversion on strategic decision-making and equilibrium outcomes in investment, particularly in settings marked by information asymmetry and incomplete markets.

This study explores the relationship between board chairs' early-life experience in the Great Chinese Famine and the debt maturity choices made by Chinese listed firms between 2000 and 2017. Our findings indicate that board chairs with famine experience exhibit a propensity towards long-term debt usage. We argue that this finding can be attributed to a risk-averse rather than altruistic orientation among board chairs who have experienced famine. Our results are particularly salient for firms with lower asset redeployability, higher distress risk, no political affiliations, and those that are not stateowned enterprises. Furthermore, this study provides three analyses to support the risk aversion traits: (1) board chairs with disaster experience underestimate their company's profit potential, (2) board chairs located in areas with higher mortality rates exhibit more obvious risk aversion behavior, and (3) extending the debt maturity date, board chairs can effectively increase company investment and mitigate the underinvestment problem.

This paper studies a novel channel through which climate risks affect households’ choices of risky asset allocation: a stringent climate change regulation elevates labor income risk for households employed by high-emission industries which in turn discourages households' financial risk-taking. Using staggered adoptions of climate change action plans across states, we find that climate change action plans lead to a reduction in the share of risky assets by 15% for households in high-emission industries. We also find a reduction in risky asset holdings after the stringent EPA regulation. These results are stronger with experiences of climate change-related disasters. Our study implies an unintended consequence of climate regulations for wealth inequality by discouraging low-wealth households' financial risk-taking.

In reality, we find assets traded in the transparent centralized market and opaque decentralized market. To explain the traders' choices of venues, we develop a model of dynamic learning and dynamic market choice between the centralized market and decentralized markets. With heterogeneous trader value correlation, we find that when asset sensitivity or volatility is sufficiently low, traders prefer the decentralized market; when asset sensitivity or volatility is intermediate, switching between centralized and decentralized markets can be the optimal market choice; when asset values are sensitive to volatile fundamentals, assets are traded only in the centralized market. We provide empirical evidence in support of the model predictions. We discussed the welfare implications of various market designs under endogenous market choices. We find that introducing post-trade transparency in the decentralized market improves welfare. Surprisingly, introducing pre-trade transparency in the decentralized market may decrease welfare as it increases traders' incentives to choose a decentralized market earlier and hurts future traders in the centralized market.

We construct a stock learning index in China A-share market, which is based on a theoretical model of information and investment choice. The higher the learning index value, the more thoroughly the individual stock is learned. Our study shows that a stock with a high learning index will have a lower expected future return compared to a stock with a low learning index. Additionally, decomposition of predictive power shows that the predictive power of the learning index mainly comes from the persistence of its own predictive power, while the rest cannot be explained by changes in the volume of news (proxy for information flow). Moreover, the learning index can explain many market anomalies in China A-share market.

The implementation of prefabricated housing (PH) has become prevalent in China recently because of its advantages in improving production efficiency and saving energy. However, the benefits of adopting PH cannot always be accrued by the stakeholders because of the arising transaction costs (TCs) in the projects’ development process. This study investigates the strategies for developers to make rational choices for minimizing the TCs of the PH project considering their own attributes and external constraints. A Bayesian Belief Network model was applied as the analytical method, based on the surveys in China. The single sensitive analysis indicated that developers influence the TCs of PH through the three most impactful factors: Prefabrication rate, PH experience, and Contract payment method. Furthermore, combined strategies were recommended for developers in various situations based on the multiple sensitivity analysis. Developers facing high prefabrication rate challenges are suggested to reduce the risks by procuring high-qualified general contractors and adopting unit-price contracts type. For developers with limited PH experience, adopting the Engineering-Procurement-Construction procurement method is the most efficient in reducing their TCs in the context of China’s PH market. This study contributes to the current body of knowledge concerning the effect of traders’ attributes and choices on TCs, expanding the application of TCs theory and fulfilling the study on the determinants of TCs in construction management.