This paper deals with measuring total factor productivity (TFP) growth of China’s construction industry using a translog production function model. We estimate the TFP growth indexes and their decomposition using a stochastic frontier analysis (SFA) approach. TFP growth is decomposed into technical progress, changes in technical efficiency, allocative efficiency, and scale effects. A panel data analysis, using the construction industry of China’s 31 provinces over 1997 to 2013, indicates that productivity growth was driven mainly by technical progress that scale effects and allocative efficiency had a positive effect, but changes in technical efficiency had a negative effect. The comparison of the four regions show that there are gaps in productivity development level among western, central, eastern, and northeast regions but the regional disparities shortened over time. The SFA approach provides a good tool to adopt effective policies and strategy to improve the productivity and competitiveness of China’s construction industry.

Considering the high variability of Covid-19 and unknown sequelae of rebound infections. We may be caught in a long-term struggle against the virus. The evaluation and summary of past anti-epidemic policies highlight profound practical significance for either decision makers or individuals. This paper applies both theoretical and empirical approaches to study the impact of city lockdown and air pollution on Covid-19. First, we apply an extended Susceptible-Infected-Removed (SIR) model to identify the relationship between lockdown, air pollution, and Covid-19 cases. Second, we apply the Differences-in-Differences (DID) model and Poisson Pseudo-Maximum Likelihood (PPML) model to test the impact of lockdown on Covid-19, by sorting out lockdown policies implemented by cities during the epidemic. Third, we empirically analyze the impact of air pollution on Covid-19, based on daily data from 257 cities in China. Finally, we examine the mechanism by which lockdown impacts Covid-19. Newly confirmed Covid-19 cases are reduced by 31.1% nationwide (excluding Wuhan) during the lockdown period. Regions with lower air pollution experience fewer Covid-19 cases. Air pollution aggravates Covid-19, with the pollutants PM2.5, PM10, NO2, CO, and O3 having the greatest impact. The results indicate that an increase in one unit of air quality index (AQI) concentrations is associated with 1.723 more newly confirmed cases. The effects of air pollution on the spread of Covid-19 diminish as the population size increases. Lockdown can inhibit the spread of Covid-19 by reducing air pollution and population movement.