The Outcomes of Physical Punishment are Typical of All Corrective Actions: A Response to Heilmann et al's (2021) Narrative Review

The reputation of psychological science depends on the adequacy of the science underlying its policy recommendations. This commentary raises concerns about the science used by Heilman et al. (2021) in their recent narrative (not meta-analytic) review that encourages spanking bans worldwide. By reviewing controlled longitudinal studies, Heilmann et al. provided stronger causal evidence than the two meta-analyses of unadjusted correlations most frequently cited to support spanking bans. However, the two previously published meta-analyses of controlled longitudinal studies of spanking do not support spanking bans, due to the trivial size of the average adverse-looking effect of customary spanking in those studies. Moreover, several lines of evidence indicate that this trivial average effect is likely due to inadequate statistical controls rather than an actual adverse causal effect of typical spanking. We need stronger causal evidence for policy recommendations for both the welfare of children and the reputation of psychological science.

Empirical evidence against U.S. H1-B visa restrictions, the case of employment in the manufacturing industry

This empirical research paper provides ample evidence for policy makers to readdress the immigration policy--especially H1-B visa cap restrictions. The paper is focused on employment shifts and human capital achievement for two groups: the U.S. born and foreign-born working within the United States manufacturing industry. The manufacturing industry is the largest industry employer in the country, and it is in the brink of being at a disadvantage in the global stage due to labor shortage as the workforce ages. The paper uses data for three-year periods--2000, 2010, and 2019--from U.S. Census, The American Community Survey (ACS), Public Use Microdata Sample (PUMS) files, thus providing an overview in labor trends and the human capital needed for the industry to be competitive. The paper builds from the Mincer (1974) earnings function to determine hourly wages for the two groups and then uses the Oaxaca-Blinder (1973) method to measure potential bias between the U.S. born and foreign-born employees in the manufacturing industry. The results in this paper align with other recent research findings (Gest et al., 2021; Eckstein & Peri, 2018) that show immigration as a tool to economic competitiveness. The data trends and findings in this paper synchronize with Borjas and Edo (2021) insights indicating that the native-born may respond to supply shocks of immigration by moving to other labor markets that are not directly affected by immigration.

Conclusion

To better understand the effects of broadband use, there must first be a commitment from policymakers to support evaluation. This volume has made an argument about why policymakers should undertake this investment and has outlined needs and strategies for advancing this knowledge. It has also examined the profession of broadband evaluation itself. The complexity of broadband use demands an evaluation approach that values generalizability and applies multiple research methods. But it also requires a further development of common concepts, improved collection of and access to data, and comparison across policy areas, programs, scales, and time. To do all of this, we need not only more and better evaluation methods but also a research community around broadband evaluation that shares knowledge and effectively communicates evidence for policy. The future impact of broadband technology on effective and equitable use depends on concerted attention by both the research community and policymakers.

Risk Management Committee, Auditor Choice and Audit Fees

We find that risk management committees and BIG4 audit firms contribute to audit fees. We use observations of 895 companies registered in Indonesia for 2014–2018, and to answer our hypothesis we used ordinary least squares analysis. The results show that BIG4 weakens the relationship between RMC and audit fees. Our study proves that higher demand for audit coverage will occur if there is a risk management committee within the company. As a result, audit fees increase. RMC may demand high-quality external guarantees, but the presence of BIG4 as a moderating variable reduces the relationship between the two variables. We assume that this can happen because auditors can work more efficiently if the company has an RMC, auditor(s) could indirectly reduce the risk because it is partially results from the performance of the RMC. In addition, we also use the robustness test to handle the endogeneity problem with consistent results as OLS. These findings provide evidence for policy makers about the relationship between audit fees and risk management committees.

The effect of retirement on the health of elderly people: evidence from China

The low retirement age has imposed a heavy economic burden on the pension system in China, leading to an ongoing debate about raising the retirement age. To understand the potential costs of raising the retirement age, we need to consider the health effects of retirement policies. Using the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015, this study employs the statutory retirement age as the exogenous variable of retirement and applies a fuzzy regression discontinuity design (RDD) to examine the effect of retirement on the health of Chinese elderly people. We find that retirement has a non-significant effect on health with respect to a series of health indicators, different bandwidths of RDD and sub-sample groups. The finding is also robust across different retirement definitions and retirement ages. This result may be attributed to the minimal changes in income and lifestyles before and after retirement. Moreover, the findings of this study provide important evidence for policy makers to increase retirement ages in China.

Comparison of two simulators for individual based models in HIV epidemiology in a population with HSV 2 in Yaoundé (Cameroon)

Model comparisons have been widely used to guide intervention strategies to control infectious diseases. Agreement between different models is crucial for providing robust evidence for policy-makers because differences in model properties can influence their predictions. In this study, we compared models implemented by two individual-based model simulators for HIV epidemiology in a heterosexual population with Herpes simplex virus type-2 (HSV-2). For each model simulator, we constructed four models, starting from a simplified basic model and stepwise including more model complexity. For the resulting eight models, the predictions of the impact of behavioural interventions on the HIV epidemic in Yaoundé-Cameroon were compared. The results show that differences in model assumptions and model complexity can influence the size of the predicted impact of the intervention, as well as the predicted qualitative behaviour of the HIV epidemic after the intervention. These differences in predictions of an intervention were also observed for two models that agreed in their predictions of the HIV epidemic in the absence of that intervention. Without additional data, it is impossible to determine which of these two models is the most reliable. These findings highlight the importance of making more data available for the calibration and validation of epidemiological models.

A Bayesian Framework for Patient-Level Partitioned Survival Cost-Utility Analysis

Patient-level health economic data collected alongside clinical trials are an important component of the process of technology appraisal. For end-of-life treatments, the modeling of cost-effectiveness data may involve some form of partitioned survival analysis, in which measures of quality of life and survival for pre- and postprogression periods are combined to generate aggregate measures of clinical benefits (e.g., quality-adjusted survival). In addition, resource use data are often collected and costs are calculated for each type of health service (e.g., treatment, hospital, or adverse events costs). A critical problem in these analyses is that effectiveness and cost data present some complexities, such as nonnormality, spikes, and missingness, which should be addressed using appropriate methods to avoid biased results. This article proposes a general Bayesian framework that takes into account the complexities of trial-based partitioned survival cost-utility data to provide more adequate evidence for policy makers. Our approach is motivated by, and applied to, a working example based on data from a trial assessing the cost-effectiveness of a new treatment for patients with advanced non–small-cell lung cancer. [Box: see text]

On evidence fiascos and judgments in COVID-19 policy

Calls for evidence-based approaches to COVID-19 have sparked up discussions on the use of evidence for policy. In this note, we expand these discussions: while the debate has mostly focused on the types of evidence to be used for policy, we argue that the assessment of judgments involved in data practices and evidence production should play a central role in evaluating policy.

Child Well-being Across the Life Course: What Do We Know, What Should We Know?

Child well-being has an explicit connection with UN Sustainable Development Goals. Progress in tackling these goals require robust evidence, such as can be provided by high quality survey data. Birth cohort surveys are an important source of evidence for policy makers seeking to protect and enhance the lives of children as they grow up. Until now such surveys have been developed independently and in order to compare data in different countries there are many challenges in post-hoc data harmonisation. The merits of collecting national longitudinal data are widely recognised, and yet the current studies are not easily comparable as they contain different questions and are conducted at different times and on different age groups. It is, therefore, time for an input harmonised comparative birth cohort survey. The European Cohort Development Project has been developing the design and business case for such a survey since 2018. This survey will allow a direct comparison of the well-being of children as they grow up across Europe in different national contexts. In the future, researchers the world over will be able to learn from the lived experiences of children and young people as they grow up in a diverse range of European countries.