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This paper provides new evidence about the link between firm-level total factor productivity (TFP) and stock returns. We estimate firm-level TFP and show that it is strongly related to several firm characteristics such as size, the book-to-market ratio, investment, and hiring rate. Low productivity firms earn a significant premium over high productivity firms in the following year, and this premium is countercyclical. We show that a production-based asset pricing model calibrated to match the cross section of measured firm-level TFPs can replicate the empirical relationship between TFP, many firm characteristics, and stock returns. Our results offer an explanation as to how these firm characteristics rationally predict returns. This paper was accepted by Wei Jiang, finance.

The past half-century has seen enormous changes in the demographic makeup of Latin America and the Caribbean (LAC). In the 1950s, LAC had a small population of about 160 million people, less than today's population of Brazil. Two-thirds of Latin Americans lived in rural areas. Families were large and women had one of the highest fertility rates in the world, low levels of education, and few opportunities for work outside the household. Investments in health and education reached only a small fraction of the children, many of whom died before reaching age five. Since then, the size of the LAC population has tripled and the mostly rural population has been transformed into a largely urban population. There have been steep reductions in child mortality, and investments in health and education have increased, today reaching a majority of children. Fertility has been more than halved and the opportunities for women in education and for work outside the household have improved significantly. Life expectancy has grown by 22 years. Less obvious to the casual observer, but of significance for policy makers, a population with a large fraction of dependent children has evolved into a population with fewer dependents and a very large proportion of working-age adults. This overview seeks to introduce the reader to three groups of issues related to population aging in LAC. First is a group of issues related to the support of the aging and poverty in the life cycle. Second is the question of the health transition. Third is an understanding of the fiscal pressures that are likely to accompany population aging and to disentangle the role of demography from the role of policy in that process.

Increasing construction productivity appears to be a complicated process due to the interconnected nature of construction work and the absence of a standardised method for measuring different construction activities. In this study, grounded theory was adopted as the research methodology for the theoretical development of the productivity model. This paper suggests a theoretical productivity measurement model (PMM) for the construction industry to address the challenges associated with productivity assessment. The proposed model consists of three levels: operational efficiencies (OE), management/administration efficiencies (ME), and industry/sector efficiencies (IE). Each level represents a different aspect of productivity and contributes to the overall performance of the construction sector. The paper discusses the detailed elements, responsibilities, and efficiency measures that are associated with each productivity level and provides a comprehensive framework for productivity evaluation. The suggested PMM enables the collection of data about all the inputs provided and outputs produced, thereby, facilitating effective management and control of construction activities. By adopting this suggested standardized approach to productivity measurement, the construction industry can achieve long-term development and enhance its contribution to the economy.

Introduction Literature has established that offering protection for workers’ health and safety is one method of preserving an organization’s human resources and increase worker productivity. The purpose of this study was to examine occupational health and safety practices among selected private hospitals in the central region of Ghana and how it affects work productivity. Methods This study was a descriptive cross-sectional quantitative study and structured questionnaires were used to collect data from 344 healthcare workers at sixteen (16) selected private health facilities in the Central Region of Ghana, through the convenience sampling technique. Data entry and analysis were conducted using Statistical Package for Social Sciences (SPSS). Results A greater majority of the respondents exhibited positive perceptions and attitudes towards occupational health and safety protocols. The healthcare facilities of almost 6 out of every 10 sampled respondents had high compliance levels with occupational health and safety measures. Also, Pearson correlation analysis revealed a significant positive relationship between OHS implementation and overall productivity (r(344) = 0.255, p  < 0.018). This relationship remained significant after controlling for demographic variables through partial correlation analysis (r(344) = 0.272, p  = 0.015), indicating a stable and consistent association. The most mentioned potential areas for improvement to optimize employee well-being and productivity were safety training, safety satisfaction and feedback and management safety commitment while the least mentioned were safety reporting, safety involvement and working environment. Conclusion This study has demonstrated that the implementation of OHS measures has a positive and significant relationship with the overall productivity of healthcare workers in private health facilities in the Central Region of Ghana.

In this paper, we incorporate spatial analysis to estimate industry-level productivity in the presence of inter-sectoral linkages. Since each industry plays a role in providing intermediate goods to other sectors, the interdependence of economic activities across industries is inevitable. We exploit the linkage patterns from the input-output relationship to define cross-industry dependencies in economic space. We propose a spatial stochastic frontier model, which extends the stochastic frontier model to a spatially dependent specification. The models are estimated using quasi-maximum likelihood methods. Applying the approach to U.S. industry-level data from 1947 to 2010, we find that sectoral dependencies are the consequences of indirect effects via the supply chain network of industries resulting in larger output elasticities as well as scale effects for the networked production processes. However, productivity growth is estimated comparably across different spatial and non-spatial model specifications.

To overcome the absence of a standardized budget quota system for high-standard farmland projects and the resultant extended compilation cycles and high workloads, this study systematically analyzes quota consumption and innovatively proposes an integrated DEMATEL-ISM-BN and gray clustering analytical model. Through a literature review and engineering feature analysis, a hierarchical factor system was established, encompassing six dimensions (environmental, technical, labor, machinery, material, and management) and 24 indicators. The DEMATEL-ISM method quantified factor weights and structured them into a five-level hierarchy, while Bayesian networks (BNs) enabled probabilistic productivity predictions (29% conservative, 45% moderate, and 26% advanced). Gray clustering was integrated to derive a comprehensive representative consumption value, and validation across six regions demonstrated a comprehensive productivity index of 0.986 (CV = 2.6%) for 17 earthwork projects, confirming model robustness. This research constructs a standardized “factor structure analysis–probabilistic deduction–regional clustering” framework, providing a theoretical foundation for precise budget compilation in high-standard farmland and proposing a novel methodological paradigm for quota consumption research.

This paper discusses the role played by the recent Brazilian Labour Reform (BLR) in conditioning the level and the rate of growth of employment, value added and productivity in the Brazilian economy from 2017. Our main findings are that after BLR, the share of informal employment, value added and productivity increased, as well as those shares in low productivity sectors. Furthermore, we show that the employment created in low-productivity sectors (formal and informal) were moved to high-productivity sectors in the years after the implementation of the 2017 labour reform, the aggregate levels of value added and productivity would have been much higher than otherwise.

We study the effects of firm-level microeconomic fluctuations on aggregate productivity in the United Kingdom. We show that a standard measure of residual productivity growth of the largest UK firms (the ‘granular residual’) produces results that are partly counter-intuitive and statistically insignificant. To combat this, we propose a refinement to the widely used control function approach to estimating technology shocks in a production function, which is aimed at accounting for firm-level heterogeneity and the potential existence of common shocks. Using this approach, we find that idiosyncratic firm-level shocks matter for the UK; the ‘granular residual’ can explain around 30% of aggregate UK productivity dynamics. We also show that simplifications of our approach, which do not control for firm-level heterogeneity and the existence of common shocks, do not perform well empirically, highlighting the importance of identifying firm-specific shocks correctly in order to properly test the ‘granularity hypothesis’.

This paper extends a global slack-based productivity indicator and constructs a unified framework that consists of global and factor levels of total factor productivity (TFP) to evaluate the performance of regional industries, thus enabling global productivity improvement based on factor-level sources. Evaluating regional industrial performance in China during 1995–2014, the findings reveal that rapid growth of industry in China is not only driven by a huge amount of input, but also by TFP improvement, with industrial productivity driven mainly by technology progress and presenting a gradually increasing trend. Regional productivity performances are imbalanced, in which the east ranks first due to its dual advantages of input and output factors. For source identification, input and output jointly contribute to industrial productivity improvement, but output has a much higher contribution ratio to industrial productivity improvement than input, because it is mainly rooted in desirable output. Finally, on the input side, labor is the primary factor driving input productivity improvement followed by energy, while capital productivity shows very slight growth.

This paper presents an empirical analysis of the impact of climate change on agriculture in a typical developing country. The economic implications of climate change are estimated by using both a farm productivity and a Ricardian framework. Data are drawn from about 1,000 farms producing cereal crops in the Nile Basin of Ethiopia. The thin plate spline method of spatial interpolation was used to predict household specific rainfall and temperature values using meteorological station data collected for 30 years across the regions. We found that climate change adaptation has a significant impact on both farm productivity and farm net revenues. We complement the analysis by providing an estimation of the determinants of adaptation. Extension services (both formal and farmer to farmer), as well as access to credit and information on future climate changes are key drivers of adaptation.