In late January 2020, China’s government initiated its first aggressive measures to combat COVID-19 by forbidding individuals from leaving their homes, radically limiting public transportation, cancelling or postponing large public events, and closing schools across the country. The rollout of these measures coincided with China’s Lunar New Year holiday, during which more than 280 million people had returned from their places of work to their home villages in rural areas. The disease control policies remained in place until late February and early March, when they were gradually loosened to
We find that rapid worker turnover significantly disrupts the productivity of responsive manufacturers. Our study uses a uniquely rich dataset drawn from China-based FATP (final assembly, testing, and packaging) facilities that produce millions of units of consumer electronic goods weekly yet exhibit high worker turnover exceeding 300% annually. The data cover the firm's weekly production plans, 52,214 workers' compensations and assignments, and assembly station productivity. To study managerial prescriptions, we extend the classical production planning problem to include endogenous worker turnover as an Experience-Based Equilibrium and use advances in reinforcement learning and approximate dynamic programming to estimate and simulate our model. Our empirical analyses exploit instrumental variables, including the firm's demand forecasts as demand shifters". We find that turnover's impact on yield waste is conservatively $146-178M, and that a well-calibrated wage increase reduces the manufacturer's variable production costs (including wages) by up to 21%, or $594M for the product we study. The wage increase reduces the firm's reliance on a larger workforce and overtime to hedge against yield disruptions from turnover; it stabilizes a leaner workforce and improves both production reliability and exibility. In settings where performance depends on workers repeating known tasks in coordinated groups, our results suggest that firms responsively matching supply to demand can pay a steep price for a disruptively turnover-prone workforce.
Previous literature suggests subpar teaching is a primary reason why rural Chinese students lag behind academically. We initiate an investigation into the potential of educational technology (EdTech) to increase teaching quality in rural China. First, we discuss why conventional approaches of improving teaching in remote schools are infeasible in China’s context, referring to past research. We then explore the capacity of technology-assisted instruction to improve academic performance by examining previous empirical analyses. Third, we show that China is not limited by the resource constraints of other developing countries due to substantial policy support and a thriving EdTech industry. Finally, we identify potential implementation-related challenges based on the results of a preliminary qualitative survey of pilots of EdTech interventions. With this paper, we lay the foundation for a long-term research investigation into whether EdTech can narrow China’s education gap.
Empirical evidence from developed countries supports the idea that parent-teacher interaction is high and improves student outcomes. The evidence from developing countries is, however, decidedly mixed. Using longitudinal data from nearly 6000 students and their 600 teachers in rural China, we show the prevalence of parent-teacher interaction is generally much lower than that of developed countries. We also show parent-teacher interaction, when it exists, can have positive effects on raising academic achievement and reducing learning anxiety. We demonstrate that the prevalence and effectiveness of parent-teacher interaction in a developing country context varies considerably due to both demand-side and supply-side factors.
Studies suggest that students’ prior performance can shape subsequent teacher evaluations, but the magnitude of reputational effects and their implications for educational inequality remain unclear. Existing scholarship presents two major perspectives that exist in tension: do teachers primarily use reputational information as a temporary signal that is subsequently updated in response to actual student performance? Or do teachers primarily use reputational information as a filter that biases perception of subsequent evidence, thus crystallizing student reputations and keeping previously poor-performing students stuck in place? In a field experiment, we recruited a random sample of 832 junior high school teachers from the second-most populous province of China to grade a sequence of four essays written by the same student, and we randomly assign both the academic reputation of the student and the quality of the essays produced. We find that (1) reputational information influences how teachers grade, (2) teachers rely on negative information more heavily than positive information, and (3) negative reputations are crystallized by a single behavioral confirmation. These results suggest that students can escape their prior reputations, but to do so, they must contradict them immediately, with a single confirmation sufficient to crystallize a negative reputation.
There is a significant gap in academic achievement between rural and urban students in China. Policymakers have sought to close this gap by improving the quality of teaching in rural areas through teacher professional development (PD) programs. However, there is limited evidence on the effectiveness of such programs. In this paper, we evaluate the impact of a PD program-National Teacher Training Program (NTTP) and find that the NTTP has no effect on math achievement. We also find that while the program has a positive effect on math teaching knowledge of teachers, it has no significant effect on teaching practices in the classroom. Taken together, these results indicate that teachers may have improved their knowledge for teaching from NTTP, but did not apply what they learned to improve teaching practices or student learning.
Abstract: We present results of a randomized trial testing alternative approaches of mapping student achievement into rewards for teachers. Teachers in 216 schools in western China were assigned to performance pay schemes where teacher performance was assessed by one of three different methods. We find that teachers offered “pay-for-percentile” incentives (Barlevy and Neal 2012) outperform teachers offered simpler schemes based on class average achievement or average gains over a school year. Moreover, pay-for-percentile incentives produced broad-based gains across students within classes. That teachers respond to relatively intricate features of incentive schemes highlights the importance of close attention to performance pay design.
We assess and compare computer science skills among final-year computer science undergraduates (seniors) in four major economic and political powers that produce approximately half of the science, technology, engineering, and mathematics graduates in the world. We find that seniors in the United States substantially outperform seniors in China, India, and Russia by 0.76–0.88 SDs and score comparably with seniors in elite institutions in these countries. Seniors in elite institutions in the United States further outperform seniors in elite institutions in China, India, and Russia by ∼0.85 SDs. The skills advantage of the United States is not because it has a large proportion of high-scoring international students. Finally, males score consistently but only moderately higher (0.16–0.41 SDs) than females within all four countries.
Educational tracks create differential expectations of student ability, raising concerns that the negative stereotypes associated with lower tracks might threaten student performance. The authors test this concern by drawing on a field experiment enrolling 11,624 Chinese vocational high school students, half of whom were randomly primed about their tracks before taking technical skill and math exams. As in almost all countries, Chinese students are sorted between vocational and academic tracks, and vocational students are stereotyped as having poor academic abilities. Priming had no effect on technical skills and, contrary to hypotheses, modestly improved math performance. In exploring multiple interpretations, the authors highlight how vocational tracking may crystallize stereotypes but simultaneously diminishes stereotype threat by removing academic performance as a central measure of merit. Taken together, the study implies that reminding students about their vocational or academic identities is unlikely to further contribute to achievement gaps by educational track.
The goal of this paper is to describe and analyze the relationship between ability tracking and student social trust, in the context of low-income students in developing countries. Drawing on the results from a longitudinal study among 1,436 low-income students across 132 schools in rural China, we found a significant lack of interpersonal trust and confidence in public institutions among poor rural young adults. We also found that slow-tracked students have a significantly lower level of social trust, comprised of interpersonal trust and confidence in public institutions, relative to their fast-tracked peers. This disparity might further widen the gap between relatively privileged students who stay in school and less privileged students who drop out of school. These results suggest that making high school accessible to more students may improve social trust among rural low-income young adults.
In the 1990s, rural youth from poor counties in China had limited access to college. After mass college expansion started in 1998, however, it was unclear whether rural youth from poor counties would gain greater access. The aim of this paper is to examine the gap in college and elite college access between rural youth from poor counties and other students after expansion. We estimate the gaps in access by using data on all students who took the college entrance exam in 2003. Our results show that gaps in access remained high even after expansion.