Employment Forecasts Research Articles

From academia to industry: A framework to securely implement big data and AI to predict college graduates' employment trajectories

The transition from academia to industry can be unpredictable, but what if we could forecast college graduate employment outcomes with both accuracy and robust security? This study introduces an innovative framework that leverages secure data analysis and machine learning to predict the employment trajectories of college graduates. By integrating homomorphic encryption, we safeguard the privacy of sensitive personal and academic data while enabling complex machine learning operations. Our approach involves meticulous data collection, feature engineering, encryption, and model development, resulting in a robust model that addresses privacy concerns without sacrificing prediction accuracy. We demonstrate our model's superiority over traditional approaches, achieving a notable increase in both security and stability. This research illuminates the potential of encrypted data analysis in reshaping predictive modeling methods, offering insights for educational institutions, policymakers, and students. Our findings not only address a pressing issue in employment forecasting but also lay the groundwork for secure and ethical big data applications across various domains.

Rural employment in Russia: Present conditions and prospects for agricultural and non-agricultural sectors

Contributing to a discussion on rural employment forecast in Russia, this paper sys­tematizes the challenges for the rural labor market: population outflow, weak impulses to develop non-agricultural employment and rural entrepreneurship, changing labor needs in agriculture and a decline in the number of labor migrants. The results of the regional differentiation research show that the response strategies of Russian regions to stabilize employment differ significantly and include active intra-Russian labor migration or reliance on high agricultural state support, development of self-employment and jobs preservation in labor-intensive, low-productivity sectors of agricultural production. The article discusses rural development prospects associated with the return migration of urban residents to rural areas, which creates a new basis for rural employment growth. A theoretical implication of the rural employment perspectives discussion is the proposed concept of “out-of-urban employment” that actualizes the traditional approach of seeking employment only for indigenous rural people who have lost their jobs in agriculture, and includes new types and forms of employment for urban dwellers. Analysis of the current state support for rural employment in Russia shows that it is poorly aligned with the existing challenges. The scale of both financing and the number of potential participants is small; direct support measures are limited to the agricultural sector, while indirect ones — through support for rural infrastructure — create mainly public sector employment. The practical implications of the outcomes are some proposed ways of developing measures to support rural employment, taking into account non-agricultural rural economy needs.

Analysis and Advice on Employment Forecasts for Graduates Taking into Account the Characteristics of Employment Mobility

In the context of accelerating globalization, the emerging knowledge economy and rapid technological development have brought unprecedented opportunities and challenges to the employment choices of graduates. The employment mobility of graduates has been constantly increasing, and their employment decisions are no longer limited to majors or regions. Instead, graduates can consider various factors more comprehensively, including industrial and urban development, compensation and benefits, etc. This study attempted to understand the characteristics of graduate employment mobility from a more macro perspective, by deeply analyzing the spatial correlation measure and the city-industry integration effect. Then, detailed research and prediction were conducted on the mobility characteristics based on the dynamic decomposition prediction mechanism, which provided not only a more scientific and accurate theoretical basis for graduate employment prediction but also scientific decision-making references for policy makers and educational institutions when formulating relevant policies and educational training plans. The research results contribute to promoting close city-industry integration and have important reference value for promoting urban economic development and optimizing urban industrial structure.

Labor Demand Forecasting: The Case of Cambodia

Abstract Labor demand forecasting is crucial for Cambodia’s economic prosperity. This is because it enables the country to make well-informed decisions and implement effective policies that align with the changing dynamics of its labor market to promote sustainable economic progress. This study utilizes a demand-driven model; specifically, the autoregressive integrated moving average (ARIMA) model with a top-down approach to forecast Cambodia’s labor demand from 2020 to 2025. By capturing current and future labor market trends, we can identify skill requirements and ensure high employment rates for sustainable development. With labor demand forecasting, Cambodia can proactively address skill gaps, optimize workforce planning, and foster an environment conducive to economic growth and stability. JEL classification: C82, J21, J23. Keywords: Labor demand, Employment forecasting, ARIMA, Top-down forecasting.

Прогнозированиe трудоустройства студентов педагогического вуза на основе использования алгоритмов машинного обучения

One of the solutions to the problem, when not the best graduates enter the pedagogical profiles and after graduation are employed in the education system, is the prediction of professional orientation even at the stage of the student choosing their further professional trajectory. To solve this problem, the purpose of the study is to develop and experimentally prove the effectiveness of using a program for predicting the employment of students of a pedagogical university based on the introduction of various machine learning algorithms. Using a random selection of students, the collection and processing of their questionnaires (n=205) in 2011-2016 were carried out. Various machine learning algorithms were used to create the program: decision trees, logistic regression, and catboost. In the course of the experiment, the data of the questionnaires were loaded into the program for its training according to various algorithms, in order to ultimately obtain a finished intellectual product with the ability to predict the employment of graduates. In the final comparison, the program developed on the “decision trees” algorithm made only 2 out 19 questionnaires and 7 out 61, which was the best result - 89%. The implementation of this algorithm makes it possible to most accurately, with the least percentage of errors, identify students who will not be employed in the future according to their profile of study or not employed at all. Thus, the study developed an intelligent program that allows one to instantly process data and get an accurate forecast of employment with only a small probability of error.

The Multidimensional Logistic Model According to the Forecast of Employment of Graduates of Institutions of Higher Education of the Republic of Kazakhstan

This article constructs a multidimensional logistic model for predicting the employment of graduates of higher educational institutions trained under the program of academic mobility, using the example of Kazakh universities. The purpose of the research is to identify the relationship between academic mobility and the employment of university graduates, as well as the necessary skills and competencies that can promote academic mobility in higher education institutions. This paper presents the results of calculating correlation coefficients and conducting a chi-square test, which demonstrated a relationship between the dependent variable and other questions in the graduate questionnaire. After the discovery of pairwise relationships, a multivariate logistic model was built that included statistically significant categories of responses. As a result, it was determined that the usefulness of participation in the academic mobility program is influenced by foreign language proficiency, an increase in academic mobility, the development of educational programs based on the needs of the labor market, as well as an increase in the weight of those methods that form practical skills in information analysis and the creation of public spaces in the labor market. The model demonstrated good predictive properties, which can be used to predict those individuals who were helped by academic mobility in finding employment.

Forecasting the sectoral structure of population employment

All the labor market subjects that can influence the labor resources dynamics are interested in employment forecasts by labor market sectors. Such subjects are state employees and municipal employees, employers and workers. The statistical data aggregation degree affects the quality of the labor resources dynamics forecasting. Each labor market indicator combines a set of detailed indicators in a high degree of aggregation case. When building the trends it is impossibile to take into account information on the detailed indicators trends. The labor market indicators for each specific year don’t contain information about the interaction with each other. This fact also negatively affects the forecast quality. The article discusses the use of a balance mathematical model of the labor resources dynamics, which relates the labor market sectoral indicators, to define the intersectoral movements indicators. The authors consider a calculating labor market indicators method that uses only statistical data on sectoral employment and unemployment. Thus, the statistical data on the labor resources dynamics provided by the Federal State Statistics Service is a sufficient condition for the Russian Federation labor market detailing using intersectoral movements’ indicators. The paper shows how a set of intersectoral movements indicators allows building the forecast values of these indicators and using them to calculate the forecast values of labor market indicators. The article considers examples of building employment estimates by Russian Federation economy sectors for 2011–2016 and 2019. The entry into force of the All-Russian classifier of types of economic activity second edition in 2017 is the reason for choosing such research intervals. The purpose of these examples was to determine the impact of the detailed labor market indicators of the sectoral employment estimates reliability. The authors compared the forecast obtained directly from labor market indicators with the forecasts obtained from intersectoral movements indicators. Intersectoral movements indicators are the results of applying balance models with varying degrees of detail. The reliability tables presented in this work to assess the forecasting quality indicate that the detailing of the sectoral employment indicators by using the balance model can increase reliability of the forecast.

A Multiple Case Study on Small and Mid-Size Enterprise Managers’ Lived Experiences on the Impact of Job Losses on Outsourcing Practices

There is a greater need to understand how economic insecurities contribute to outsourcing practices. Previous research documented that small and medium-sized enterprises gained limited advantages from outsourcing. The purpose of this qualitative multiple case study design was to explore the contribution of consumer job losses on outsourcing practices. A semi-structured open-ended interview was used to collect data from the 13 participants from the furniture, bedding, and wooden industries in Jamaica. From the analysis of the data collected, two themes emerge: (1) affordability and (2) market trends. The findings obtained from this research suggest that consumer job losses contributed to outsourcing practices. This knowledge might change current views on the factors that lead to outsourcing and the benefits of this strategy to manufacturing small and mid-size enterprise from developing countries. The results may also contribute to more informed macroeconomic policies. The following recommendations emerged from the findings: (a) utilize employment forecast to gauge production; (b) hedge prices for procured materials, and (c) quote selling price in primary outsourcing currency. Future research directed at SMEs managers’ lived experiences of a specific economic insecurity, additional manufacturing industries, and adopting different methodological designs could create a larger body of knowledge for comparisons.

Estimation of the Student Employment in the Aviation Industry Based on Novel Fractional Error Accumulation Grey Model

To improve the employment forecasting accuracy of traditional grey models, the grey model with the fractional error accumulation is proposed. The estimation error is accumulated. The proposed model can make use of the initial value x(1) and can give more attention to the error of new data. The monotonicity of the simulative value by the proposed model is data‐driven and uncertain. The comparison results show that the proposed model can enhance the forecasting accuracy of traditional grey model. It deserves to be applied to employment forecasting.

БАЛАНС ТРУДОВЫХ РЕСУРСОВ: ТРАДИЦИОННЫЕ И СОВРЕМЕННЫЕ МЕТОДЫ РАСЧЕТА И ФОРМИРОВАНИЯ

The purpose of the study is to show that the traditional interdisciplinary economic, demographic and macroeconomic method of forming the balance of the labor resources works reliably in modern conditions, allowing linking and verifying official demographic and macroeconomic forecasts, including the size, structure of the working-age population and the gross domestic product production, finding vulnerabilities and contradictions in these forecasts, develop warning forecasts about possible risks. The task of the paper is to identify the possibilities of the balance of labor resources for the analysis of the social and labor situation in the context of macroeconomic processes in order to regulate employment and unemployment in the country or regions. The research methods are the analysis of scientific literature, statistical data of the Federal State Statistics Service (Rosstat), and materials of the Ministry of Economic Development of the Russian Federation. The results of a review of the methodology for analyzing and forecasting balances of labor resources are presented. One of the practical results of the study is a simple and transparent, easily reproducible method developed and proposed by the author for forecasting labor resources, employment, and unemployment in the medium and long term. Forecasts of labor resources, employment, and unemployment for 2022–2025 have been developed. The author concludes that it is difficult to predict the main macroeconomic parameters of the labor market and employment in the specified period.

Short- and medium-term sectoral employment forecasts 2021–2027

Short- and medium-term sectoral employment forecasts 2021–2027

An Empirical Study on the Employment Monitoring and Early Warning Mechanism of Medical Graduates in Universities with Big Data and Complex Computing System

Based on the management of big data, the analysis and forecast of the employment demand cycle business situation studied in this article is based on the employment cycle theory and a complete set of employment monitoring, employment evaluation, employment forecasting, and policy selection theories and strategies developed around the employment cycle fluctuations, a specific employment phenomenon. First, systematically evaluate the current state of the employment demand boom, appropriately reflect the hot and cold degree of the employment demand boom, and provide necessary information for the government’s regulatory measures, content, and timing. Secondly, it reflects the regulatory effects of graduate employment monitoring, judging whether graduate employment monitoring measures are properly applied, whether they have the effect of smoothing out employment fluctuations, and promoting the country’s employment demand; in addition, business decision makers can take advantage of the employment demand boom, by monitoring the information provided by the early warning system and timely foreseeing the upcoming macrocontrol measures, so that enterprises’ labor adjustments can adapt to the government’s regulatory measures. At the same time, the model proposes a prosperity index method for monitoring and early warning of the employment demand cycle. After selecting and dividing three types of prosperity indicators, the DI index reflecting the trend of the prosperity change and the CI index reflecting the strength of the prosperity change are calculated and constructed. The national employment demand boom monitoring and early warning signal system predicts the trend of the employment boom cycle outside the sample period. The experimental results show that the cyclic prosperity forecast results are consistent not only with the national employment demand prosperity in recent months, but also with the use of the structural measurement ARIMA (p, d, q) model. The alertness value is close, indicating that this indicator system has a good effect on the national employment demand boom monitoring and early warning.

El efecto del teletrabajo en el empleo en Ecuador durante la crisis sanitaria 2019-2020

This article offers a preliminary result of the effect of teleworking in the Ecuadorian labor market in the framework of the period between December 2019 and December 2020. Various sources of official information were used to define state action; the employment levels were extracted from the Bulletin of labor indicators published in December, 2020 of the Encuesta Nacional de Empleo, Desempleo, y Subempleo (ENEMDU) by Instituto Nacional de Estadística y Censos (INEC). The journalistic and bibliographic information was contrasted, compared, and strictly interpreted using heuristic matrices. Employment forecasts were obtained by exponential smoothing, and the net effect of teleworking on the Ecuadorian labor market in the taken reference period, by diff-in-diff. The data were processed in Microsoft Excel. The analysis concludes that teleworking had an important (~ 10%), although decreasing, effect on the reactivation of the Ecuadorian labor market affected by the health crisis due to COVID-19.

The effciency of regional financial support estimation and the employment forecasting in the sector of small and medium-sized businesses of the Krasnodar krai

The effciency of regional financial support estimation and the employment forecasting in the sector of small and medium-sized businesses of the Krasnodar krai

Prediction model of college students entrepreneurship ability based on artificial intelligence and fuzzy logic model

The fundamental solution to the problems of college students’ employment is to encourage college students to start their own businesses. Only by using entrepreneurship to promote employment can the real solution of China’s higher education employment problems be truly solved. Aiming at the current situation of college students’ entrepreneurship and employment, this paper builds a model system suitable for college students’ employment and entrepreneurship forecast and guidance through artificial intelligence algorithms and fuzzy logic models. The diversity-enhanced employment recommendation system developed in this paper uses the MVC three-tier architecture. Moreover, the diversity-enhanced employment recommendation system designed in this paper provides two recommendation methods: individual diversity optimization and overall diversity optimization, which takes into account the relationship between students’ personal interests and employment work. In addition, the system uses the basic idea of user-based collaborative filtering. Finally, this paper designs a control experiment to analyze the performance of this research model. The research shows that the entrepreneurship employment forecast and guidance model constructed in this paper has a certain effect.

Wybrane zasoby przedsiębiorcze studentów kierunków społecznych

W konsekwencji przemian i charakterystyk współczesnego rynku pracy przedsiębiorczość wkracza w przestrzeń szkolnictwa wyższego. W oparciu o analizę prognoz zatrudnienia dla absolwentów kierunków o profilu społecznym znaczenie ich potencjału, zdolności, zasobów i cech przedsiębiorczych kształtowanych w trakcie studiów uwidacznia się bardzo wyraźnie. W artykule zreferowano wyniki badań zasobów przedsiębiorczych studentów kończących studia na kierunkach społecznych. Wskazano również na oczekiwania studentów odnośnie do działań uczelni wyższych w zakresie rozwijania ich zasobów przedsiębiorczych. Prezentowane badania zostały zrealizowane z wykorzystaniem narzędzia do diagnozy uzdolnień przedsiębiorczych Czesława Noworola, stosowanego w obszarze doradztwa zawodowego.

Development and Forecast of Employment in Forestry in the Czech Republic

Employment in forestry is an essential component of the forestry industry. It is a socio-economic phenomenon, which has been at the edge of economists’ interest for quite a long time. The proportion of employees in the forestry sector is relatively small, standing at only 0.6%. However, forestry as a sector has a very significant multiplier effect which is reflected in the growth of related jobs. Examples of this can be found in the production of forestry machinery and equipment, the construction of wooden and timber structures, and the furniture sector. These sectors are kept separately in economic and statistical records, but forestry remains their natural determinant. The aim of this work is to describe, analyze, and formulate the prognosis for the development of these types of jobs. Conclusions of the work show that there has been a decrease in employment and simultaneously an increase in labor productivity. This is due to a increasingly high use of technological equipment. Development forecasts show that the Czech Republic does not differ from the overall surveyed trends in other selected countries. It is therefore evident that forecasts of the development of employment in forestry are also relevant in other similar countries. Our results show a statistically significant reduction in forestry employment. The analysis focused on the Czech Republic, but the results may also apply to other European countries. A significant decrease in employment leads to instability in the forestry sector. It means a skilled labor force leaves the forestry sector and is not replaced. Disruption of knowledge continuity leads to a negative impact on the environment.

Hysteresis in Labor Markets? Evidence from Professional Long-Term Forecasts

We explore the long-term impact of economic booms on labor market outcomes using a novel approach based on revisions to professional forecasts over the past 30 years for 34 advanced economies. We find that when employment rises unexpectedly, forecasters typically raise their long-term forecasts of employment by more than one-for-one and also expect a strong rise in labor force participation, suggesting more persistent effects than is traditionally assumed. Economic booms associated with changes in aggregate demand, when inflation is rising and unemployment falling unexpectedly, also come with persistent long-term effects on expected employment and labor force participation, suggesting positive hysteresis. Our forecast evaluation tests indicate that forecasters are, on average, unbiased in their assessment of these positive, persistent effects.

Hysteresis in Labor Markets? Evidence from Professional Long-Term Forecasts

We explore the long-term impact of economic booms on labor market outcomes using a novel approach based on revisions to professional forecasts over the past 30 years for 34 advanced economies. We find that when employment rises unexpectedly, forecasters typically raise their long-term forecasts of employment by more than one-for-one and also expect a strong rise in labor force participation, suggesting more persistent effects than is traditionally assumed. Economic booms associated with changes in aggregate demand, when inflation is rising and unemployment falling unexpectedly, also come with persistent long-term effects on expected employment and labor force participation, suggesting positive hysteresis. Our forecast evaluation tests indicate that forecasters are, on average, unbiased in their assessment of these positive, persistent effects.

Forecasting, impact analysis and uncertainty propagation in regional integrated models: A case study of Australia

The integration of input–output and econometric models at regional level has gained popularity for its superior performance in forecasting employment and examining the impacts of policies. There are a number of approaches to integrate the two models. This paper examines the integration of input–output with econometric modelling using two merging methodologies, namely coupling and holistic embedding. Each methodology is analysed with respect to the accuracy of its results of total and sectoral employment forecasting. Both methodologies are applied to a regional economy in Australia. The methodology which shows superior forecasting accuracy is applied to examine the significance of sectors that generate the highest number of employments relative to other sectors.