Earthquake triggered networked risk and response: based on relevant literature

Death, injury, conflict, and disorder caused by natural and man-made disasters have resulted in significant challenges to good governance and impeded the goal of achieving the benign development of society. This paper uses a particular method for analyzing the research situation and identifying current trends and focuses. It then proceeds to explore future research needs. The study finds that future researchers will shift their emphasis from the risks caused by natural disasters to those arising from man-made disasters; meanwhile, the study will consider the complex systems of interaction to understand causality. The objectives of management, hence, should change from investigating the impacts of risks to crisis control. Eventually, an evolutionary disaster-based social-risk framework is established, and some suggestions for future research are provided.     

What do professional forecasters actually predict?

This paper studies what professional forecasters predict. We use spectral analysis and state space modeling to decompose economic time series into trend, business cycle, and irregular components. We examine which components are captured by professional forecasters by regressing their forecasts on the estimated components extracted from both the spectral analysis and the state space model. For both decomposition methods, we find that, in the short run, the Survey of Professional Forecasters can predict almost all of the variation in the time series due to the trend and the business cycle, but that the forecasts contain little or no significant information about the variation in the irregular component.     

Management in production: from unobserved to observed

Are productivity estimates good proxies for unobserved management? And, does management affect production in a neutral and monotonic fashion as assumed by these proxies? We use Bloom and Van Reenen’s management data to show that two popular proxies, fixed effects and inefficiency scores, correlate with observed management practices. We find that the correlations are positive but weak. Also, management explains only a fraction of the proxies’ variances. The data rejects the assumptions of neutrality and monotonicity. Last, our results suggest that management has characteristics both of a technology and an input.     

A decomposition of US business sector TFP growth into technical progress and cost efficiency components

A problem with index number methods for computing TFP growth is that during recessions these methods show declines in TFP. This is rather implausible since it implies technological regress. We develop a new method to decompose TFP growth into technical progress and inefficiency arising from the short run fixity of capital and labour, and apply this to new data on the US corporate nonfinancial sector and the noncorporate nonfinancial sector. The analysis sheds light on sources of the productivity growth slowdowns over the period 1960–2014.     

Stochastic non-smooth envelopment of data for multi-dimensional output

The proposed method of Stochastic Non-smooth Envelopment of Data (StoNED) for measuring efficiency has to date mainly found application in the analysis of production systems which have exactly one output. Therefore, the objective of this paper is to examine the applicability of StoNED when a ray production function models a production technology with multi-dimensional input and output. In addition to a general analysis of properties required by a ray production function for StoNED to be applicable, we conduct a Monte Carlo simulation in order to evaluate the quality of the frontier and efficiencies estimated by StoNED. The results are compared with those derived via Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). We show that StoNED provides competitive estimates in regard to other methods and especially in regard to the real functional form and efficiency.