Business reform outcomes: Why so different?

Post-crisis policy making increasingly focuses on doing business reforms. We argue that the effects of those reforms will be different across countries. To understand the reasons for the reform outcome divergence, we advance a novel firm-size distribution (FSDs) argument. At the center of the argument is the fact that FSDs are different across countries and stable over time. Then, if a given doing business reform induces firms of different size to grow differently, this will produce a variety of reform outcomes across countries. To advance the argument, we set up a tractable general equilibrium (GE) model and study how firms of different size grow after a doing business reform. The model predicts that larger firms will grow faster than smaller firms after the reform. The model predictions are tested on the Enterprise Surveys (ES) data, merged with the Doing Business indicators. We confirm that firms of different size grow differently after a Doing Business reform. Thus, based on the notable differences of firm size distributions across countries, identical reforms to start, operate and close a business will produce a variety of reform outcomes across countries.     

Goal attainability and performance: Evidence from Boston marathon qualifying standards

In this paper we test if performance improves once goals become more attainable. Goal-setting literature suggests that workers respond to challenging but achievable goals with increased performance. Empirical evidence supports the notion of goals increasing performance; however the evidence on how attainability of goals affects performance is mixed. This paper tests whether efforts increase, improving performance as the goals become more attainable. We are employing a unique set of publicly available marathon data from 1970 to 2015 to directly analyze the effect of goal attainability on performance. With the probable goal of qualifying for the Boston Marathon, we test if runners increase their effort, and consequently improve their performance if they enter a new age group and as a result have a more attainable goal. We find that runners who enter a new age group perform better than the runners whose qualifying time did not change. This effect is seen with runners in younger age groups, but not found in the results of runners in more advanced years.     

Missing value imputation method for disaster decision-making using K nearest neighbor

Due to destructiveness of natural disasters, restriction of disaster scenarios and some human causes, missing data usually occur in disaster decision-making problems. In order to estimate missing values of alternatives, this paper focuses on imputing heterogeneous attribute values of disaster based on an improved K nearest neighbor imputation (KNNI) method. Firstly, some definitions of trapezoidal fuzzy numbers (TFNs) are introduced and three types of attributes (i.e. linguistic term sets, intervals and real numbers) are converted to TFNs. Then the correlated degree model is utilized to extract related attributes to form instances that will be used in K nearest neighbor algorithm, and a novel KNNI method merging with correlated degree model is presented. Finally, an illustrative example is given to verify the proposed method and to demonstrate its feasibility and effectiveness.     

Estimation and goodness-of-fit procedures for Farlie–Gumbel–Morgenstern bivariate copula of order statistics

In this study, we provide the Farlie–Gumbel–Morgenstern bivariate copula of rth and sth order statistics. The main emphasis in this study is on the inference procedure which is based on the maximum pseudo-likelihood estimate for the copula parameter. As for the methodology, goodness-of-fit test statistic for copulas which is based on a Cramér–von Mises functional of the empirical copula process is applied for selecting an appropriate model by bootstrapping. An application of the methodology to simulated data set is also presented.     

Least squares estimation of varying‐coefficient hazard regression with application to breast cancer dose‐intensity data

To enhance modeling flexibility, the authors propose a nonparametric hazard regression model, for which the ordinary and weighted least squares estimation and inference procedures are studied. The proposed model does not assume any parametric specifications on the covariate effects, which is suitable for exploring the nonlinear interactions between covariates, time and some exposure variable. The authors propose the local ordinary and weighted least squares estimators for the varying‐coefficient functions and establish the corresponding asymptotic normality properties. Simulation studies are conducted to empirically examine the finite‐sample performance of the new methods, and a real data example from a recent breast cancer study is used as an illustration. The Canadian Journal of Statistics 37: 659–674; 2009 © 2009 Statistical Society of Canada     

职校内生产性实训基地建设的实践与思考

结合江苏省连云港中等专业学校机电专业校内生产性实训基地建设的具体案例,从中职学校校内实训基地建设现状入手,理论融合实践进行分析,对以教育功能为主体、校办企业为基础的主导式校内生产性实训基地的建设开展实践性研究,并从管理体系、运行体系、评价体系三个方面进行了阐述。     

Towards expenditure rules and fiscal sanity in the euro area

The study demonstrates the key role of expenditure policies in explaining fiscal developments during EMU in the euro area, its three largest members and four “macro-imbalances” countries. It compares actual primary expenditure trends with those that would have prevailed if countries had followed neutral policies based on expenditure rules since the start of EMU. Moreover, the implications for debt trends are calculated. Results show that all sample countries except Germany applied expansionary expenditure policies already before the crisis. Consequently, expenditure and debt paths were much higher compared to a counterfactual neutral expenditure stance. Rule-based expenditure policies could have led to much safer fiscal positions much more in line with the EU's Stability and Growth Pact. An empirical analysis of the determinants of countries’ expenditure stance confirms the need for stronger fiscal rules and institutions in the euro area.     

THE INEFFICIENCY OF WORKER TIME USE

Much work is carried out in short, interrupted segments. This phenomenon, which we label task juggling, has been overlooked by economists. We study the work schedules of some judges in Italy documenting that they do juggle tasks and that juggling causally lowers their productivity substantially. To measure the size of this effect, we show that although all these judges receive the same workload, those who juggle more trials at once instead of working sequentially on few of them at each unit of time, take longer to complete their portfolios of cases. Task juggling seems to have no adverse effect on the quality of the judges' decisions, as measured by the percent of decisions appealed. To identify these causal effects we estimate models with judge fixed effects and we exploit the lottery assigning cases to judges. We discuss whether task juggling can be viewed as inefficient, and provide a back‐of‐the‐envelope calculation of the social cost of longer trials due to task juggling.