Spatial contiguity relationships represent a frequently ignored source of information that is available to economists modeling cross-sections of metropolitan areas, counties, states, regions, and countries. Shown here is how contiguity relationships can be incorporated as prior information in Bayesian vector autoregressive and error correction models with little or no effort, using existing software, to produce improvements in forecasting performance. A comparison of alternative forecasting methods is undertaken using annual postwar time series of agricultural output for a sample of 15 corn-producing states. The models that incorporate prior information regarding spatial contiguity are found to dominate those that ignore this information, producing much better forecasts.

This paper investigates the role of environmental, social, and governance (ESG) performance in stock prices during the market financial crisis caused by the COVID-19 pandemic. We use the Chinese listed company data as the bases for adopting an event-study method to identify the impact of ESG performance on cumulative abnormal returns. Empirical results suggest that ESG performance significantly increases firms’ cumulative abnormal returns and has asymmetric effects during the pandemic. Our results are robust to various robustness checks that consider the replacement of event window period, ESG measurement, adding other control variables, and sample exclusion of Hubei Province. We further find that reputation and insurance effects are important mechanisms through which ESG performance influences stock prices. Lastly, heterogeneous analyses show that ESG effects are considerably pronounced among firms with low human capital and bad image and in high-impact regions.

No abstract

No abstract

No abstract