Readability as a measure of textual complexity: determinants and evidence in Brazilian companies

ABSTRACT The aim of this article was to evaluate the effect of company earnings and of harmonization with IFRS on the readability of Management Reports in the Brazilian stock market. There is a gap to be filled both in the elaboration and adaptation of readability measures to the context studied, as the studies tend to replicate the original formulas, and in identifying the determinants of the readability of Brazilian company reports, as the research in this field remains in its infancy and the results are inconclusive. The results provide indications for investors to identify complex textual information and may help public policymakers to establish a simple writing manual, along the lines of the SEC’s 1998 Plain English Handbook. The modified metrics and the one developed overcome the criticisms regarding the use of readability formulas in accounting research and could be used in substitution of the original metrics in future studies. An econometric model was used that presents the determinants of readability. Readability was calculated for the Results Analysis section of the Management Report. The resulting construct is understood via three attributes: persistence, current performance, and the reference benchmark. Harmonization with IFRS is a dummy variable, which delimits the pre- and post-IFRS periods. The hypotheses were tested in a sample of Brazilian companies made up of 714 company-year observations covering the period from 2006 to 2019. The descriptive results show that there is an apparent improvement in the readability of the reports in the pre- and post-IFRS period comparison. The econometric evidence shows that, in general, companies with persistent and positive earnings present less complex reports and are more likely to have highly readable reports, because managers publish reports with better readability to signal positive results to the market.

Which Factors Determine the Adoption of the Internet of Things? Impacts and Benefits

This paper provides first econometric evidence on the determinants of the Internet of Things among firms and on potential performance impacts. The analysis is based on representative firm-level data from 874 German firms. A probit model and an instrumental variable regression serve as econometric approach. The results reveal that especially collaboration platforms and B2B e-commerce increase the propensity to use the Internet of Things. The results further indicate that product innovation is highest for firms jointly using the Internet of Things and collaboration platforms while a reduction of the workforce is also highest in this case. In contrast, there is no evidence for a potential impact on sales development.

ORGANISING FOR INNOVATION IN PROFESSIONAL SERVICES FIRMS: ECONOMETRIC EVIDENCE FROM THE UK

Undertaking innovation involves a range of different activities from ideation to the commercialisation of innovations. Each activity may have very different resources and organisational requirements, however, most prior studies treat innovation as a single un-differentiated activity. Here, using new survey data for professional service firms (PSFs) in the UK, we are able to examine separately how a range of organisational work practices influence success in ideation and commercialisation. In particular, we use principal component analysis (PCA) to identify and compare the benefits of four groups of organisational work practices relating to strategy & information sharing, recruitment & training, work flexibility & discretion and culture & leadership. Strong contrasts emerge between those work practices that are important for success in ideation and commercialisation. Work practices linked to culture & leadership are important for ideation activities, while strategy &information sharing practices are more strongly associated with commercialisation success. The results suggest clear managerial implications depending on the priority

The Middle-Income Trap and Premature Deindustrialization in South Africa

South Africa has been experiencing premature deindustrialization and poor growth over an extended period of time. Premature deindustrialization is among the key factors locking many middle-income countries in a trap of stagnant growth and thwarting their catching-up with advanced economies. Premature deindustrialization shrinks middle-income countries’ opportunities for technological development, and also their capacity to add value in global value chains (GVCs), which reduces their scope for the sustained increases in productivity required for catching up. This chapter analyses key structural factors contributing to a ‘middle-income technology trap’. Throughout the chapter, reference is made to the divergent experiences of three middle-income comparator countries to South Africa: Brazil, China, and Malaysia. Building on this framework, the chapter presents new econometric evidence of premature deindustrialization in South Africa through an international comparative lens. By studying the relationship between countries’ GDP per capita and their shares of manufacturing in total employment, the chapter identifies the level of GDP per capita and share of manufacturing in total employment associated with the ‘turning point’ at which the share of manufacturing levels off and begins to decline. The chapter groups countries into four categories based on their (de)industrialization dynamics, and identifies possible premature deindustrializers, among which South Africa is found. South Africa’s lack of structural transformation helps to explain its failure to escape the middle-income technology trap.

The demand impacts of train punctuality in great britain: systematic review, meta-analysis and some new econometric insights

This paper updates and extends the systematic review and meta-analysis of Wardman and Batley (Transportation 41:1041–1069, 2014), which hitherto was the most comprehensive study of the impacts of punctuality on passenger rail demand in the literature. Whereas the 2014 paper covered 51 elasticities from 6 studies in Great Britain published between 2003 and 2011, this updated paper adds 11 subsequent British studies yielding a further 201 observations. The meta-model recovers a range of significant effects, relating to whether the elasticity was short versus long run, flow type and distance, season versus nonseason tickets, the relevant measure of lateness, and whether the purpose of the study was specifically the estimation of late time elasticities. Allowance was also made for study quality-related issues. The data indicated that, despite dynamic models being commonplace, there is some uncertainty as to how long the long run is. Alongside the meta-model, the paper also reports new econometric evidence that addresses some gaps in existing evidence and knowledge, especially in relation to functional form and non-linearity of effects. Findings from both strands of analysis would seem to suggest that rail industry guidance has tended to overstate the demand impacts of punctuality.

Planning on the Potomac: A Review Essay on Jason E. Taylor’s Deconstructing the Monolith: The Microeconomics of the National Industrial Recovery Act

Taylor (2019) details heterogeneity in the effects of the National Industrial Recovery Act (NIRA) across industries and across time. Through first the President’s Reemployment Act (PRA) and then industry-specific “codes of fair competition,” the NIRA raised wages and restricted working hours. In some—but far from all—cases industries also used a NIRA code to collude, raising prices and restricting output. The effect of the NIRA peaked in fall 1933 and winter 1934; thereafter, compliance declined. I review the intellectual history of the NIRA, the implementation of the PRA and the NIRA codes, and Taylor’s econometric evidence on their effects. I end with a discussion of the implications of Taylor’s book for understanding the effect of the NIRA on US recovery from the Great Depression. (JEL D72, G01, H50, N32, N42)

The link between regional temperature and regional incomes: Econometric evidence with Sub-National data

We study the link between temperature and economic development at the sub-national level, employing cross-sectional data from two distinct sources. In contrast to much of the existing cross-country literature on the temperature-income relationship, our setting allows for the inclusion of country fixed effects. Once we account for country fixed effects, we do not find a statistically robust relationship between regional temperature and three different measures of regional economic development (per capita GDP, nightlights and gross cell production). We also test whether temperature is non-linearly related to regional income (with hotter regions being potentially particularly prone to adverse effects of temperature on income) but find no systematic evidence in favor of such a relationship. Finally, we examine whether the effect of temperature on economic development is especially pronounced in poorer regions (e.g., due to weaker adaptation). Again, we find no statistically robust link.