Corporate social responsibility,credit rating,and private debt contracting: new evidence from syndicated loan market

We examine the impact of corporate social responsibility (CSR) activities on loan spreads of syndicated bank loans, with a particular interest in how CSR and credit ratings are interrelated as a joint determinant of loan spreads. Focusing on private debt contracts, we show that both CSR strengths and concerns are related to their loan spreads. CSR strengths work to lower firm risk, hence reducing the loan spread, whereas CSR concerns increase firm risk, thus increasing the loan spread. Once we include detailed credit rating information in the models, however, CSR concerns lose significance, but CSR strengths remain significantly related to the loan spread. We also find that both CSR strengths and CSR concerns are related to loan spread for non-rated firms, but the CSR concern effect is stronger than the CSR strength effect for these firms. A further test shows that firm risk measured by stock return volatility plays as a direct channel through which a firm’s CSR activities affect loan spreads, whose result lends further support to our main results. Overall, our results provide strong evidence that CSR matters to the pricing of loan contracts beyond credit rating information and the results remain robust to the possible firm size effect and the endogeneity issues.     

The evolution of a technological system: the case of CNC machine tools in Korea

Focusing on a product, this paper reconstructs the concept of technological systems first introduced by Carlsson and Stankiewicz (1991) in this Journal. Based on the model, we analyze the evolution process and performance of Korea's technological system for computer numerically controlled (CNC) machine tools as a catching-up case. The study shows that the length of 'learning period' for the system was substantial, even in a catching-up case. Especially, in the Korean case, the government played a 'macro-entrepreneurial' role in the molding of the technological system by giving legitimacy to the system, by mobilizing a nation-specific industrial organization of Chaebol system, and by enhancing the academia-industry-research institution links.JEL Classification: L52, L61, O30We thank two anonymous referees for very helpful comments and suggestions.Correspondence to: B. Carlsson     

Domestic value added and employment generated by Chinese exports: A quantitative estimation

We develop an input–output methodology to estimate how Chinese exports affected the country's total domestic value added (DVA) and employment in the years 2002 and 2007. For every US$1000 dollar of Chinese exports in 2007 (2002), DVA and employment are estimated to be US$591 (US$466) and 0.096 (0.242) person-year, respectively. To implement these estimations, we use hitherto unpublished Chinese government data to construct several completely new datasets, including an input–output table with separate input–output and employment-output coefficients for processing exports, non-processing exports, and output for domestic use. We hypothesize that, in comparison with the export sector, China's domestic sector would be relatively autarkic due to China's history of central planning. We expect that exports would generate less DVA and employment than output for domestic use. Processing exports, which are highly dependent on imported inputs, would similarly generate less DVA and employment than non-processing exports. Our findings support these expectations. For both 2002 and 2007, the DVA and employment effects of domestic final demand were higher than those of non-processing exports, which were in turn higher than those of processing exports. However, with the progress of economic reforms, we found that the total DVAs of exports and domestic final demand have converged from 2002 to 2007.     

Maximum entropy autoregressive conditional heteroskedasticity model

In many applications, it has been found that the autoregressive conditional heteroskedasticity (ARCH) model under the conditional normal or Student’s t distributions are not general enough to account for the excess kurtosis in the data. Moreover, asymmetry in the financial data is rarely modeled in a systematic way. In this paper, we suggest a general density function based on the maximum entropy (ME) approach that takes account of asymmetry, excess kurtosis and also of high peakedness. The ME principle is based on the efficient use of available information, and as is well known, many of the standard family of distributions can be derived from the ME approach. We demonstrate how we can extract information functional from the data in the form of moment functions. We also propose a test procedure for selecting appropriate moment functions. Our procedure is illustrated with an application to the NYSE stock returns. The empirical results reveal that the ME approach with a fewer moment functions leads to a model that captures the stylized facts quite effectively.