Biodiversity conservation incurs substantial economic costs. We investigate how financial markets price the risks such costs induce, exploiting the “Green Shield Action,” a major regulatory initiative launched in China in 2017 to enforce biodiversity preservation rules in national nature reserves. While improving biodiversity, the initiative led to significant increases in bond yields for municipalities with these reserves. The effects are driven by increases in local governments’ fiscal risk due to expected increases in transition costs resulting from shutting down illegal economic activities within reserves and additional public spending on biodiversity. Investors show little non-financial consideration towards endeavors counteracting biodiversity loss.

We study the mandated introduction of a supervised auction for the primary bond market in China. The regulatory intervention significantly reduced the cost of debt for Chinese issuers. Most of the benefits flowed from reduced agency conflict between underwriters and issuers. Using unique bidder-level data from a lead underwriter, we develop replicable tools and techniques to identify collusive bidding behavior resulting in artificial (and economically costly) increases in bond yields. Such evidence can benefit global regulators, issuers, and investors currently using unsupervised auction mechanisms, for example, in securities issuance, construction projects, and procurement.

This paper examines the impact of a policy targeting firms with implicit government guarantees (IGGs). We focus on the debt management policy (DMP) proposed for state-owned enterprises in China. Our analysis shows that the DMP lowered the average yield of SOE bonds by 6.6 basis points. However, when accounting for the information effect of the policy announcement, the DMP’s impact ranged from 6.6 to 32.1 basis points. Our findings reveal that the information effect weakened the intended effect of the DMP and increased the average bond yields of both private-owned enterprises. We emphasize the need for policymakers to carefully design their policy communication to mitigate the information effect and consider the response of the financial market.

China’s financial prices are informative enough for the PBC to introduce a monetary policy framework centered around interest rates. While bond yields are not fully efficient—reflecting regulation, liquidity, and segmentation—we find they contain considerable information about the state of the economy as well as evidence of an emerging transmission channel: changes in PBC rates influence the structure of Treasury, financial, and corporate bond yield curves, which are then associated with changes in growth and inflation. Coporate spreads are also a leading indicator of growth and inflation. While further liberalization will strengthen both efficiency and transmission, several necessary elements to move towards indirect monetary policy are already in place.

Most existing empirical studies on affine term structure models have primarily focused on in-sample Þt of historical bond yields and ignored out-of-sample forecast of future bond yields. Using an omnibus nonparametric procedure for density forecast evaluation developed in this paper, we provide probably the first comprehensive empirical analysis of the out-of-sample performance of affine term structure models in forecasting the joint conditional probability density of bond yields. We show that although it is difficult to forecast the conditional mean of bond yields, some affine models have good forecasts of the joint conditional density of bond yields and they significantly outperform simple random walk models in density forecast. Our analysis demonstrates the great potential of affine models for financial risk management in fixed-income markets.