Some Economic Effects of Motor Trucks upon the Movement of Wheat from Country Elevators of Oklahoma

Agricultural Economic

Policy Brief: Who Won? Who Lost? The Distributional Impact of COVID-19 Government Support for Business.

Government support to business during the pandemic represented an unprecedented peacetime transfer of capital from the public to the private sector. Schemes to support businesses were consistently justified on the basis of broader interests, such as ‘protecting jobs and livelihoods’, but these rather abstract, universal goals potentially gloss over important questions about how government supports to business have been used, and to whose benefit.In this brief we summarise research examining how different stakeholders at the UK’s largest businesses – board executives, shareholders, and workers – fared during and after the peak of the pandemic. Among other things, the research explored how FTSE 350 companies in receipt of government supports adjusted executive compensation packages and payments to shareholders, how this compared to businesses that did not take government money, and how pay differences between chief executives and ordinary workers changed going into and coming out of the pandemic. In addition, the research looked at government support scheme restrictions on executive pay and capital distributions to shareholders (dividend payments) and examined the challenges involved in tracking which companies had taken advantage of government supports and by how much.Our findings indicate the existence of a post-pandemic restitution culture in executive pay, in which companies across the FTSE 350 have sought to make up losses in executive pay experienced during the peak of the pandemic. This restitution culture has reversed a longer run decline in executive pay and, significantly, is particularly apparent in companies that participated in government support schemes, which have seen substantial executive pay increases.In a narrow sense, our findings underline the importance of policymakers attaching clear conditions to government support on executive pay and capital distributions to shareholders, with appropriate transparency enforcement mechanisms. However, they also raise bigger questions about the relationship between corporations and society, and the potential role that government assistance, grants, and public procurement can play in ensuring companies and our broader economy are managed in the long-term interests of society

Analyses of Sensitivity to the Missing-at-Random Assumption Using Multiple Imputation With Delta Adjustment: Application to a Tuberculosis/HIV Prevalence Survey With Incomplete HIV-Status Data.

Multiple imputation with delta adjustment provides a flexible and transparent means to impute univariate missing data under general missing-not-at-random mechanisms. This facilitates the conduct of analyses assessing sensitivity to the missing-at-random (MAR) assumption. We review the delta-adjustment procedure and demonstrate how it can be used to assess sensitivity to departures from MAR, both when estimating the prevalence of a partially observed outcome and when performing parametric causal mediation analyses with a partially observed mediator. We illustrate the approach using data from 34,446 respondents to a tuberculosis and human immunodeficiency virus (HIV) prevalence survey that was conducted as part of the Zambia-South Africa TB and AIDS Reduction Study (2006-2010). In this study, information on partially observed HIV serological values was supplemented by additional information on self-reported HIV status. We present results from 2 types of sensitivity analysis: The first assumed that the degree of departure from MAR was the same for all individuals with missing HIV serological values; the second assumed that the degree of departure from MAR varied according to an individual's self-reported HIV status. Our analyses demonstrate that multiple imputation offers a principled approach by which to incorporate auxiliary information on self-reported HIV status into analyses based on partially observed HIV serological values

Analyses of Sensitivity to the Missing-at-Random Assumption Using Multiple Imputation With Delta Adjustment: Application to a Tuberculosis/HIV Prevalence Survey With Incomplete HIV-Status Data.

Multiple imputation with delta adjustment provides a flexible and transparent means to impute univariate missing data under general missing-not-at-random mechanisms. This facilitates the conduct of analyses assessing sensitivity to the missing-at-random (MAR) assumption. We review the delta-adjustment procedure and demonstrate how it can be used to assess sensitivity to departures from MAR, both when estimating the prevalence of a partially observed outcome and when performing parametric causal mediation analyses with a partially observed mediator. We illustrate the approach using data from 34,446 respondents to a tuberculosis and human immunodeficiency virus (HIV) prevalence survey that was conducted as part of the Zambia-South Africa TB and AIDS Reduction Study (2006-2010). In this study, information on partially observed HIV serological values was supplemented by additional information on self-reported HIV status. We present results from 2 types of sensitivity analysis: The first assumed that the degree of departure from MAR was the same for all individuals with missing HIV serological values; the second assumed that the degree of departure from MAR varied according to an individual's self-reported HIV status. Our analyses demonstrate that multiple imputation offers a principled approach by which to incorporate auxiliary information on self-reported HIV status into analyses based on partially observed HIV serological values

Testing the use of static chamber boxes to monitor greenhouse gas emissions from wood chip storage heaps

This study explores the use of static chamber boxes to detect whether there are fugitive emissions of greenhouse gases (GHGs) from a willow chip storage heap. The results from the boxes were compared with those from 3-m stainless steel probes inserted into the core of the heap horizontally and vertically at intervals. The results from probes showed that there were increases of carbon dioxide (CO2) concentrations in the heap over the first 10 days after heap establishment, which were correlated with a temperature rise to 60 °C. As the CO2 declined, there was a small peak in methane (CH4) concentration in probes orientated vertically in the heap. Static chambers positioned at the apex of the heap detected some CO2 fluxes as seen in the probes; however, the quantities were small and random in nature. A small (maximum 5 ppm) flux in CH4 occurred at the same time as the probe concentrations peaked. Overall, the static chamber method was not effective in monitoring fluxes from the heap as there was evidence that gases could enter and leave around the edges of the chambers during the course of the experiment. In general, the use of standard (25 cm high) static chambers for monitoring fluxes from wood chip heaps is not recommended