Abstract

China’s wood industry is vulnerable to the COVID-19 pandemic since wood raw materials and sales of products are dependent on the international market. This study seeks to explore the speed of log price recovery under different control measures, and to perhaps find a better way to respond to the pandemic. With the daily data, we utilized the time-varying parameter autoregressive (TVP-VAR) model, which can incorporate structural changes in emergencies into the model through time-varying parameters, to estimate the dynamic impact of the pandemic on log prices at different time points. We found that the impact of the pandemic on oil prices and Renminbi exchange rate is synchronized with the severity of the pandemic, and the ascending in the exchange rate would lead to an increase in log prices, while oil prices would not. Moreover, the impulse response in June converged faster than in February 2020. Thus, partial quarantine is effective. However, the pandemic’s impact on log prices is not consistent with changes of the pandemic. After the pandemic eased in June 2020, the impact of the pandemic on log prices remained increasing. This means that the COVID-19 pandemic has long-term influences on the wood industry, and the work resumption was not smooth, thus the imbalance between supply and demand should be resolved as soon as possible. Therefore, it is necessary to promote the development of the domestic wood market and realize a “dual circulation” strategy as the pandemic becomes a “new normal”.

Highlights

  • The return series showed stationarity at 10% significance level, implying that they were integrated of order 1. It illustrates that the four series of the COVID-19, international oil prices, exchange rate, and China’s log prices were all the I (1) process, which met the data requirements of the time-varying parameter parameter (TVP)-vector autoregressive (VAR) model

  • The parameter estimates of the time-varying parameter vector autoregressive (TVP-VAR) model can change over time

  • In order to compare the impact of the COVID-19 pandemic on log prices in different periods and explore the speed of log prices recovery under different control measures, this paper uses the TVP-VAR model to conduct an empirical study on the dynamic transmission effect of the coronavirus pandemic on log prices

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Wood prices affect the supply and demand of wood and influence the expectations of forest managers and the public on the income of forest land and the choice of forest resource management methods [1]. The coronavirus (COVID-19) pandemic outbreak began in November 2019 and attracted attention in early 2020. In China, cases were exponentially increasing in just a few weeks and even exceeded 80,000 at the beginning of March. Due to effective control measures, the spread of the virus got under control

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