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This paper explores the evidence of a long-run co-movement between aggregate unemployment insurance spending and the labor force participation rate in the USA. The unemployment insurance (UI) program tends to expand during an economic downturn and contract during an expansion. UI may incentivize unemployment and may also facilitate better matching in the labor market. Statistical evidence of the presence of a co-movement will thus shed new light on their dynamics.

This research applies time-series econometric approach using monthly data from 1959:1 to 2020:3 to test threshold cointegration and estimate a threshold vector error-correction (TVEC) model. The estimates from the TVEC model investigating the nature of short-run dynamics.

The Enders and Siklos (2001) test find evidence of threshold cointegration between the two indicating the presence of long-run co-movement. The estimates from the TVEC model investigating the nature of short-run dynamics find evidence that the growth in aggregate UI spending and the growth in labor force participation rate adjust simultaneously to maintain the long-run co-movement above the threshold in the short run. The author also observes the same short-run dynamics for the growth in aggregate UI spending and the growth in the labor force participation rate for females.

This model is bi-variate by construction and does not address causality.

The author argues that the UI program positively impacts the female labor market outcomes, for example, better matching. This finding may explain the upward trend in the labor force participation rate for females in the USA.

The research findings may justify the transfer programs for minority and immigrants.

This is first research that analyzes the UI programs impact on the labor force participation using a macroeconometric approach. To the best of the author's knowledge, this is the first study in this genre.

The purpose of this paper is to investigate the behavior peculiarities of the labor force participation in Eastern European countries.

The authors provide the analysis of nonlinearity in dynamics of economic active population and perform the econometric analysis using logistic smooth transition autoregressive models that are flexible and capture various kinds of behavior for different modes. The paper investigates labor markets of six Eastern European countries, Hungary, Bulgaria, Poland, Slovakia, Romania and Croatia that are characterized by lower level of labor force participation rate (LFPR) than average level in EU.

The results of modeling quantitatively characterize smooth changes in the behavior modes of labor force activity for each country and indicate how population economic activity depends on previous labor market states. The estimated slope parameters that determine the smoothness of transition between regimes show that, in all countries, the labor force participation quite quickly reacts to changes that occurred on the labor market in the past. During recession periods, households of European countries that joint EU last decade in order to prevent the depletion of their total income increased labor supply and showed increased activity in job search.

This paper indicates the nonlinearity and asymmetry in LFPR in transition economies, discovers variety of its dynamics in the different regimes and determines the indicators that cause the change of the population economic activity behavior in each country.

The purpose of this paper is to investigate area-level labour market dynamics from a spatial perspective. This analysis is aimed at better understanding what socio-economic actors are associated with shifts in unemployment rates across a major metropolitan city.

Based on two waves of New Zealand census data, this paper combines a seemingly unrelated regression approach (allowing for relaxation of the assumption that residuals from models of different employment states are unrelated) with a spatial lag model.

The key socio-economic drivers associated with intra-city employment dynamics were vehicle access, dependency rates and educational attainment. Importantly, the identification of spatial autocorrelation with respect to employment status patterns within this major New Zealand city motivates a case for heterogeneous employment policies across the city.

This research improves the understanding of changes in labour market status rates within a city region. This is done by inclusion of two important considerations: a spatial perspective to labour market dynamics at an intra-city level; and formally modelling the interdependence across the four potential labour market outcomes (being full-time, part-time, unemployed or out of the labour force). Overall, there was clear empirical support for the need to include spatial considerations when using targeted policy to help lift areas out of unemployment.

Latin America experienced a long period of sustained growth since 2003 that positively impacted social and labor market indicators, including poverty. This paper contributes to the understanding of this process as it carries out a comparative study of poverty and indigence dynamics in five Latin American countries during 2003–2012. Specifically, it extends the analysis of a previously published study by broadening the time coverage and examining indigence mobility. It analyzes the extent to which countries with different levels of poverty (extreme poverty) incidence diverge in terms of exit and entry rates, and identifies the relative importance of the frequency and impact of events associated with poverty transitions. For this, a dynamic analysis of panel data is carried out using regular household surveys. Sizeable rates of poverty and indigence movements were observed in all five countries and it was found that a large proportion of poor or indigent households experienced positive events, mainly related to the labor market; however, only a small fraction of them actually exited poverty and indigence. It appeared, therefore, that even when the economy behaved reasonably well, high levels of labor turnover and income mobility (even of a negative nature) still prevail, mainly associated with the high level of precariousness and the undeveloped system of social protection that characterize the studied countries.

This paper, the first one to use individual-level Turkish panel data, examines the labor market transitions in Turkey along the formal/informal employment divide. The purpose of this paper is to contribute to the limited body of empirical evidence available on mobility and informality in the Turkish labor market.

Toward this end, the authors use Turkish income and Living Conditions Survey panel data for 2006, 2007, 2008 and 2009 to compute the Markov transition probabilities of individuals moving across six different labor market states: formal-salaried (FS), informal-salaried, formal self-employed, informal self-employed, unemployed and inactive. In order to examine the nature of mobility patterns in more detail, the authors then estimate six multinomial logit models individually for each transition adopting a number of individual and employment characteristics as explanatory variables.

The authors find evidence that mobility patterns are fairly similar across different time spans, the probability of remaining in initial state is higher than the probability of transition into another state for all the labor market states, except for unemployment, there is only very limited mobility into the FS state. Gender, education and sector of economic activity are observed to display significant effects on mobility patterns. The results reveal several relationships between the covariates and likelihood of variant transitions.

This study provides a comprehensive and detailed diagnosis of the Turkish labor market. The market is observed to display a rather static structure throughout the period considered. The results indicate that a well recognition of underlying dynamics may help policy makers to produce various effective tools for addressing informality.

First study to analyze labor market mobility across formal/informal sectors using newly available panel data.

The study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.

An analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.

The study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.

While this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.

This paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.

The South African government actively intervenes in the labor market in the pursuit of redress of social injustice. These interventions are complicated by economics and have a direct effect on intentions to turnover. In addition, South Africa has a dual labor market, with a high unemployment rate among lesser skilled workers, and a skills shortage at the top of the labor market.

There are four clear eras in the labor market of post-Apartheid South Africa. The first era was after democratic elections in 1994, when the government focused on nation-building with the introduction of indigenization programs. The second era was characterized by economic prosperity and an intensification of indigenization programs. The third era was characterized by rampant state corruption and increased regulatory uncertainty. During this period, the economy stagnated and unemployment increased. Firms restructured and lower-level workers were retrenched and higher-level skilled workers left the country. In 2018, a new president undertook to grow the South African economy and attract foreign direct investment. Despite these efforts, there was a spike in South Africans emigrating, increasing the turnover of highly skilled South Africans of all races.

Economics and politics create both push and pull factors and many unintended consequences, and the dual labor market reacts differently to labor markets than in developed economies. The lower-skilled employees lose their jobs as the economy contracts, while highly skilled jobs remain difficult to fill. However, skilled professionals nonetheless feel increasingly uncertain about their future employability.