Multi-Population Enhanced Slime Mould Algorithm and with Application to Postgraduate Employment Stability Prediction

In this study, the authors aimed to study an effective intelligent method for employment stability prediction in order to provide a reasonable reference for postgraduate employment decision and for policy formulation in related departments. First, this paper introduces an enhanced slime mould algorithm (MSMA) with a multi-population strategy. Moreover, this paper proposes a prediction model based on the modified algorithm and the support vector machine (SVM) algorithm called MSMA-SVM. Among them, the multi-population strategy balances the exploitation and exploration ability of the algorithm and improves the solution accuracy of the algorithm. Additionally, the proposed model enhances the ability to optimize the support vector machine for parameter tuning and for identifying compact feature subsets to obtain more appropriate parameters and feature subsets. Then, the proposed modified slime mould algorithm is compared against various other famous algorithms in experiments on the 30 IEEE CEC2017 benchmark functions. The experimental results indicate that the established modified slime mould algorithm has an observably better performance compared to the algorithms on most functions. Meanwhile, a comparison between the optimal support vector machine model and other several machine learning methods on their ability to predict employment stability was conducted, and the results showed that the suggested the optimal support vector machine model has better classification ability and more stable performance. Therefore, it is possible to infer that the optimal support vector machine model is likely to be an effective tool that can be used to predict employment stability.

The Impact of Business Obstacles on Firm Growth and Job Stability in East Asia and Pacific Nations

Economic sustainability is closely linked to firm growth and employment stability, making them of great interest to policymakers and business leaders. Insights into the factors that impact employment growth and employment stability aid decision makers to develop policies that encourage economic growth and economic sustainability. This study used World Bank Enterprise Survey data to examine the effect of the business obstacles of financing, labour regulation, and under-skilled workforce on firm growth and on employment stability, estimated by the proportion of permanent to non-permanent workforce in East Asia and Pacific nations. The instrumental variables (IV) method was used with two-stage least squares (2SLS) to account for potential endogeneity between the business obstacles and employment growth and the proportion of permanent to non-permanent workers employed by firms. In addition, the quantile method was applied to capture the partial effect of the reported obstacles across different segments of firm growth. Findings included a significant negative effect of the financing obstacle on employment growth and therefore firm growth, particularly at the lowest levels thereof. In addition, financing and labour regulations obstacles have a significant, negative effect on the proportion of permanent employees in a firm’s workforce.

Immigrants' Employment Stability Over the Great Recession and Its Aftermath

We examine immigrant men's employment stability during the Great Recession and its aftermath using a longitudinal approach that draws on data from the Survey of Income and Program Participation (SIPP), a nationally representative panel survey of U.S. residents. Discrete-time event-history models are used to estimate male immigrants' relative risk of experiencing an involuntary job loss or underemployment, defined as working less than full-time involuntarily. The analysis also investigates differences in job stability by immigrant documentation status. Undocumented immigrants are identified using a logical allocation method augmented with external information about whether the respondent was successfully matched with administrative data. We find that immigrants are at significantly higher risk of involuntary job loss, and especially of underemployment relative to native-born workers. Undocumented immigrants face a greater risk of adverse job transitions, particularly underemployment in the first part of the recession. When demographic and job characteristics are taken into account, immigrant-native and documented-undocumented differences attenuate but remain in many instances. A comparison of our findings with those from an earlier nonrecessionary period from 2004 to 2006 suggests that immigrants' higher risk of employment instability may be attributed to the recession.