UK World War I and interwar data for business cycle and growth analysis

This article contributes new time series for studying the UK economy during World War I and the interwar period. The time series are per capita hours worked and average capital income, labor income, and consumption tax rates. Uninterrupted time series of these variables are provided for an annual sample that runs from 1913 to 1938. We highlight the usefulness of these time series with several empirical applications. The per capita hours worked data are used in a growth accounting exercise to measure the contributions of capital, labor, and productivity to output growth. The average tax rates are employed in a Bayesian model averaging experiment to reevaluate the Benjamin and Kochin (J Political Econ 87:441–478, 1979) regression.     

The Changing Pattern of Productive Efficiency in the Chinese Iron and Steel Industry

This study aims to explain the changing pattern of productive efficiency of the Chinese iron and steel industry during the 1980s. By decomposing productive inefficiency into technical, allocative and scale inefficiencies, the effect of market-oriented reform measures on inefficient resource utilization is empirically tested. A consistent improvement is found in technical efficiency from different sized firms. An improvement in allocative efficiency of investment in upgrading and innovation from different sized firms is also found. Allocative efficiency of working capital was found to have hardly improved which could be largely due to distorted factor markets. Different sized firms exhibited scale inefficiency which could be due to segmented local production and the impact of a two-tier price system on the distribution of production share among firms.     

Media visibility and corporate social responsibility investment evidence in Spain

Despite the extensive research in both the determinants and the results of corporate social responsibility (CSR), relatively few studies have considered extra-legal institutions as potential determinants of CSR. Our work fills this gap by looking at how media attention affects CSR over a long-term period in a continental European setting. Our results show that media coverage positively affects CSR. Additional scrutiny triggered by media coverage encourages dominant owners to signal their commitment to limiting self-dealing transactions and their orientation toward stakeholders' needs through CSR investments. Additionally, our results reveal that this signaling device offers greater benefits and lower costs in firms where controlling owners show a voting-cash flow wedge. Our results are relevant to different actors such as investors, auditors, and policy makers as they provide solid evidence that media coverage is an important driver of CSR orientation in a continental European setting.     

E-commerce sellers' ratings: Is user feedback adequate?

The literature on the theory of public procurement points out two well-known informational problems arising out of information asymmetry: (i) adverse selection and (ii) moral hazard. To reduce these issues and foster credibility and trust in the procurement process while maintaining quality and efficiency in public procurement, e-procurement platforms have turned to reputation or rating systems. Therefore, the research and design of such rating systems are crucial. In this study, we discuss the theoretical underpinnings of procurement and employ the information-theoretic, regression analysis, artificial neural network and principal component analysis (PCA) approaches to estimate the weights of the variables entering the rating system. Using real data from Government e-Marketplace, a business-to-business public e-commerce portal, we empirically determine the weights of the rating variables derived from the transaction-level and user feedback data for sellers. The weights obtained from the PCA are the most applicable compared with the other three methods. We compare the old rating system with the newly proposed design using the Wilcoxon signed-rank test. This results in a statistically significant difference between the two ratings. The canonical correlation and Wilks' trial reveal that the ratings derived from transaction-level data and user feedback are uncorrelated to a great extent. Hence, considering only transaction-level data or user feedback is unlikely to divulge sellers' intrinsic worth. E-commerce platforms can use this approach to quickly implement methods to obtain rating scores on a real-time basis for sellers on online platforms.