No abstract

Persistent policy failures have been examined in recent years with a focus on the role of political systems. We evaluate the growth of dysfunctional policymaking in the U.S. and propose a countering approach. Policy failures often reflect partisan policy stalemate, errors or unintended consequences, polarized extremism or imbalance, or partisan reversals with changes in power. Extremes in partisanship are not new historically, but growing policy failures due to negative partisanship have now severely damaged public trust. More "party blind" conditions in policy formulation may be able to renew a more productive social contract. We propose a disruptive presidential leadership approach of bipartisan inclusion to seek to reframe the partisan divides, counter negative partisanship and extremes, re-establish better policymaking interactions, and improve governance and policy outcomes. Dysfunctional policymaking has been attributed to Republicans and Democrats in a Prisoner's Dilemma. Iterated Prisoner's Dilemmas often lead to higher rates of cooperation, and similarly, historical policymaking included greater cooperation, but in recent decades the bipartisan norms of governance have substantially eroded. We describe three complementary explanations, which suggest that non-cooperative partisan policymaking has become self-reinforcing, and institutional changes to promote cooperation should focus on lowering the risk-adjusted cost-benefit ratio, making cooperation safer and more attractive for policymakers.

This paper surveys estimates of the transmission features of the novel coronavirus, and then proposes a model to address sample-selection bias in estimated determinants of infection. Containment assumptions of the infection forecasting models depend on assumed effects of policies and self-regulating behavior. In the commons dilemma of the pandemic, the perceived ‘low risks’ of unregulated marginal choices do not reflect the full social cost, implying non-pharmaceutical interventions (NPI) to reduce mortality can enhance social welfare. As more economic activity renews with liftings of restrictive NPI (RNPI), a critical question concerns the ability of milder NPI (MNPI) and voluntary precautions to mitigate the risk of greater infections and deaths while also limiting the pandemic’s economic damage and its social costs. Ineffective NPI could lead to continued COVID-19 waves and new types of crises, worsened expectations and delayed economic recoveries. From the central range of surveyed estimates of transmission and alternative herd-immunity-threshold estimates, a ‘worst-case’ virus guidepost suggests eventual deaths of around 25 to 41 million worldwide and 1.1 to 1.7 million in the U.S. needed to reach herd immunity with no vaccine or treatment. The most optimistic study surveyed (theoretical model from a non-reviewed preprint study) combined with the low end of the range of the estimated mortality rate suggests 6 to 9 million deaths worldwide and 250 to 370 thousand in the U.S. to reach herd immunity. Successes in the mix of NPI, treatments, and vaccine can limit the eventual global death toll of the virus. Improved estimation models for forecasting and decision making may assist in better targeting the local timings and mix of NPI. Diagnostic tests for the virus have been largely limited to symptomatic cases, causing possible sample selection bias. A recursive bivariate probit model of infection and testing is proposed along with several possible applications from cross-section or panel-data estimation. Multiple potential explanatory variables, data sources, and estimation needs are specified and discussed.

In 1985 and 1990 studies, Norsworthy and Zabala reported evidence supporting the hypothesis that declining worker morale has reduced productivity and productivity growth. This study partly replicates Norsworthy and Zabala's work and extends it using U.S. auto industry data for 1958–80. Some problems are found with the original analysis. Particularly important is the finding that the substitution of random numbers for morale indicators in the translog econometric equations used by Norsworthy and Zabala yields levels of statistical significance comparable to, and in some trials even higher than, those found when morale indicators are used. Thus, the question of whether poor worker morale contributed to the slowdown in economic growth, this study concludes, is still unresolved.

This study surveys and assesses the implications from recent empirical studies and reports to highlight the characteristics of SARS-Cov-2 and the COVID-19 crisis, and then proposes a recursive bivariate probit (RBP) model specification and possible applications. The RBP model addresses sample selection bias to estimate key determinants of virus infection given nonrandom testing. Applicable to anonymized case-level or widely available local-area data in the U.S., multiple data sources are shown. With suitable data the model can control for observed (e.g. population density) and unobserved factors to estimate the marginal effects of varying state-prescribed measures and behavioral social distancing. Case-level scoring models may, in addition, eventually assist in clinical diagnostic assessments. Although not proposed to substitute for more random population testing and other methods, results could also be used in advance of more testing. Uncertain assumptions in epidemiological models reflect unclear effects from gradations of social distancing now occurring. Despite many calls for broader testing and targeted quarantining in the U.S., many practical obstacles remain, leaving unknowns, especially across local areas. Differing local transmission rates respond to stronger or weaker social distancing and quarantining. High risks from latent non-quarantining spread warn of potential overwhelming local outbreaks. The insidious nature of SARS-Cov-2 invites complacency, especially in non-hotspot areas. Complacent behaviors can fail to adequately address the public-goods problem, leading to various forms of continued local and macro COVID-19 waves and crises. To assess a worst case scenario, no model projection is needed, only the herd immunity threshold equation, estimates of the reproduction ratio, and the estimated mortality rate. With no ultimately successful countermeasures in treatment, vaccine, and non-pharmaceutical interventions (NPIs), the analysis here suggests an eventual number of deaths much like the 1918 pandemic in U.S. deaths per capita (1.8-2.7 million U.S. deaths) and in the total number of deaths worldwide (around 50 million). This toll also reflects a hypothetical global “surrender” strategy of business-as-usual and no social distancing, which in practice no nation has followed. Some successes across the three broad social countermeasure efforts – which appears most likely, in a mix of outcomes – can lessen the high social costs.