Shakeout in the early commercial airframe industry

The commercial airframe industry in the US experienced a shakeout from the early 1930s into the post‐Second World War period. Unlike shakeouts in automobiles, tyres, or televisions, the commercial airframe industry's early life cycle was affected by external factors, particularly government demand. Using newly digitized data on all planes introduced in the commercial market between 1926 and 1965, we find that commercial airframe manufacturers with bomber contracts during the Second World War were more likely to have postwar market share than firms without such contracts, controlling for plane characteristics and other forms of government contracting. We attribute the effect of bomber contracts to advantages in R&D learning capacity acquired by firms with military airframe contracts. Despite low (or zero) initial presence in the commercial market, these learning capacity advantages allowed such firms to survive the early period of the shakeout, and later to thrive.     

How efficient is the market for Australian firms’ earnings information?

We construct a measure of the speed with which forecasts issued by sell-side analysts accurately forecast future annual earnings. Following Marshall, we label this measure earnings information flow timeliness (EIFT). This measure avoids the aggregation problem inherent in price-based measures of information efficiency. We document large variation in EIFT across firm-years, and show that EIFT is positively associated with the extent of analyst following, consistent with increased analyst coverage improving the speed with which earnings-related information is recognised. We also find that EIFT is higher for firm-years classified as ‘bad news’ (i.e., where analysts’ forecasts at the start of the financial period exceed the reported outcome). However, when we separately consider instances where analysts appear to forecast non-GAAP (or ‘street’) earnings rather than GAAP earnings, we find that the greater timeliness of bad news is concentrated among observations where analysts forecast non-GAAP earnings, where unusual items are typically excluded. We conclude that the market for accounting information is more efficient for negative operating outcomes than for negative outcomes reflecting unusual items.     

A model of biased intermediation

We study situations in which consumers rely on a biased intermediary's advice when choosing among sellers. We introduce the notion that sellers' and consumers' payoffs can be congruent or conflicting, and show that this has important implications for the effects of bias. Under congruence, the firm benefiting from bias has an incentive to offer a better deal than its rival and consumers can be better‐off than under no bias. Under conflict, the favored firm offers lower utility, and bias harms consumers. We study various policies for dealing with bias and show that their efficacy also depends on whether the payoffs exhibit congruence or conflict.     

Portrayals of Minorities and Women in Super Bowl Advertising

Portrayals of women and minorities advertising have long been of interest to advertising scholars. While research has found that the overall representation of these groups has increased, some stereotypes persist, and so do questions about the quality and prominence of portrayals. This study examines portrayals of minorities and women in Super Bowl advertising, the main “pop culture” showcase for US advertising. A content analysis of 10 years of Super Bowl ads is conducted and a multinomial logit regression model is employed to delve deeper into the content analysis results. Findings show that while the overall representation of women and various minority groups is strong, a deeper analysis shows that these groups are seldom depicted as primary characters by themselves and that some subtle stereotypes persist. We also find that ads featuring female principal characters are more likely to feature home settings, sexual appeals, emotional messages, and music as a major element and that it is less likely for female (vs. male) celebrities to be used. Minority principal characters are more likely to be celebrities and be included in ads with music or for technical products but are less likely to be included in ads featuring corporate social responsibility messages.     

Using paradata to collect better survey data: Evidence from a household survey in Tanzania

Data are a key component in the design, implementation, and evaluation of economic and social policies. Monitoring data quality is an essential part of any serious, large‐scale data collection process. The purpose of this article is to show how paradata should be used before, during, and after data collection to monitor and improve data quality. To do this we use timestamps, global positioning system (GPS) coordinates, and other paradata collected from an 800‐household survey conducted in Tanzania in 2016. We demonstrate how key paradata can be used during each phase of a research project to identify and prevent issues in the data and the methods used to collect it. Our results corroborate the importance of collecting and analyzing paradata to monitor fieldwork and ensuring data quality for micro data collection in developing countries. Based on these findings we also make recommendations as to how researchers can make better use of paradata in the future to manage and improve data quality. We argue for an expansion in the understanding and use of varied paradata among researchers, and a greater focus on its use for improving data quality.     

Small Area Estimation for Disease Prevalence Mapping

Small area estimation (SAE) entails estimating characteristics of interest for domains, often geographical areas, in which there may be few or no samples available. SAE has a long history and a wide variety of methods have been suggested, from a bewildering range of philosophical standpoints. We describe design-based and model-based approaches and models that are specified at the area level and at the unit level, focusing on health applications and fully Bayesian spatial models. The use of auxiliary information is a key ingredient for successful inference when response data are sparse, and we discuss a number of approaches that allow the inclusion of covariate data. SAE for HIV prevalence, using data collected from a Demographic Health Survey in Malawi in 2015–2016, is used to illustrate a number of techniques. The potential use of SAE techniques for outcomes related to coronavirus disease 2019 is discussed.     

Rural school access and the agricultural transformation

Improving children's access to primary and secondary education is a strategic goal for many global development agencies and government policymakers. Nevertheless, there is relatively little research examining how changes in rural school supply affect future labor markets. We leverage variation in the timing and location of secondary school construction in Southern Mexico to identify the effects of school supply on labor outcomes. We find that school construction increases expected education for school-aged children by about 4 years and raises the share of years working in the nonagricultural sector between the ages of 18–22 by 29.8 percentage points. The magnitude of the effects on share of years doing nonagricultural work is smaller for individuals from homes where an indigenous language is spoken. Our findings indicate that rural school construction in less-developed countries can accelerate the transformation from agricultural to nonagricultural economies, but there may be heterogeneous effects across socioeconomic groups and ethnicities.     

Executive Compensation and Financial Performance Measures: Evidence from Significant Financial Institutions

We survey the use of financial performance measures in determining executive pay among significant Australian financial institutions. We document evidence of the pervasiveness with which externally disclosed non‐GAAP (non‐Generally Accepted Accounting Principles) financial measures are also used internally to determine variable remuneration, with the apparent popularity of cash profit after tax in short‐term incentives plans. Our evidence also highlights the increasing use of peer group‐adjusted measures (e.g., relative cash earnings per share and return on equity ranking against a peer group) in determining longer‐run incentives, despite the fact that members of the peer group do not measure financial performance in a directly comparable manner. Detailed analysis of the four major trading banks (Australia and New Zealand Banking Group, Commonwealth Bank, National Australia Bank and Westpac) reveals differences in the way non‐GAAP earnings measures are calculated across the major banks, as well as some variation over time in the way individual banks measure performance. We also document evidence of non‐GAAP earnings restatements, with around 25% of non‐GAAP results subsequently being restated. These restatements are more likely to result in a downward revision of the initially reported non‐GAAP result than an upward revision. We therefore conclude that existing measures of financial performance used to determine senior executive compensation are not as ‘objective’, as might be assumed.