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Labor force transitions are empirically examined using Current Population Survey (CPS) data matched across months from 1996 to 2012 for Hispanics, African-Americans, and whites. Transition probabilities are contrasted prior to the Great Recession and afterward. Estimates indicate that minorities are more likely to be fired as business cycle conditions worsen. Estimates also show that minorities are usually more likely to be hired when business cycle conditions are weak. During the Great Recession, the odds of losing a job increased for minorities although cyclical sensitivity of the transition declined. Odds of becoming re-employed declined dramatically for blacks, by 2–4%, while the probability was unchanged for Hispanics.

This paper aims to identify the level of contribution of different levels of education to remaining in unemployment as well as the transition from unemployment to employment in Egypt.

In this paper, transition probabilities matrix differentiated by gender, age groups, educational levels, marital status and place of residence based on worker flows across employment, unemployment and out of labor force states during the period 2012–2018 using Egypt Labor Market Panel Survey of 2018. The results point to the highly static nature of the Egyptian labor market. Employment and the out of labor force states are the least mobile among labor market states. This is because employment state is very desirable and the out of labor force is the largest labor market states, especially for females. Also, this study examines the impact of different educational levels separately on remaining in unemployment and transition from unemployment to employment state using eight binary logistic regression models.

The main results of transitions from unemployment to employment are relatively large for males, elder-age, uneducated workers as well as workers who are not married and urban residents, and the results of the logistic regression models consistent with the transition probabilities matrix results, except for few cases. Based on the above findings, there is enough evidence to accept the null hypothesis that no education has a positive significant impact to transition unemployed individuals from unemployment to employment, while less than intermediate as well as higher education have a negative significant impact to transition unemployed individuals from unemployment to employment.

This paper proposes to address the problem of the unemployment among highly educated which is much higher compared with illiterates and try to understand the impact of different levels of education separately on the transition from unemployment to employment, to help the policymakers to eradicate the gap between education and the demand of the labor market in Egypt.

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.

Probability of Default (PD) is a crucial credit risk parameter. International accords have motivated banks and credit institutions to adopt objective systems of evaluating and monitoring the PD. This study examines retail unsecured loans of a major Greek bank during the period of the financial crisis. It focusses on the stochastic behaviour of the financial states of the loans. It is tested whether a first-order Markov chain (MC) model describes sufficiently the transitions from one state to another. Moreover, Poisson regression models are estimated in order to calculate the limiting transition matrix, the limiting state probabilities and the PD. It is proved that the MC of the financial states of loans is non-homogeneous suggesting that the transition probabilities from one financial state to another are not constant across time. From the Poisson regression models, the transition probability matrix is estimated from one state to another in alternative time periods. From the limiting transition matrix, it is shown that if a loan is delayed then it is very likely to move towards the next worst case. The findings of this research could be useful for bank management.

Compares labour market transitions of young people in Germany and Italy using panel data from the GSOEP and the SHIW. The aim is to investigate whether there are significant cross‐country differences in the patterns of labour market entrance and whether explanatory factors can be identified. The analysis shows that Germans have a significantly higher probability of moving from school to work and from unemployment to employment. They are also more likely to move back to studies if already in the labour force. Further investigation suggests that cross‐country differences in the educational and labour market systems are responsible for the differences found.

This study examines credit score migration rates of farm businesses, testing whether migration probabilities differ across business cycles. Results suggest that agricultural credit ratings are more likely to improve during expansions and deteriorate during recessions. The analysis also tests whether agricultural credit ratings depend on the previous period migration trends. The findings show that credit score ratings exhibit trend reversal where upgrades (downgrades) are more likely to be followed by downgrades (upgrades).

In this chapter we review the recent and growing literature on medium-term growth patterns. This strand of research emerged from the realization that for most countries economic development is a highly unstable process; over a course of a few decades, a typical country enjoys periods of rapid growth as well episodes of stagnation and economic decline. This approach highlights the complex nature of growth and implies that studying transitions between periods of fast growth, stagnation, and collapse is essential for understanding the process of long run growth. We document recent efforts to characterize and study such growth transitions. We also update and extend some of our earlier research. Specifically, we use historical data from Maddison to confirm a link between political institutions and propensity to experience large swings in growth. We also study the role of institutions and macroeconomic policies, such as inflation, openness to trade, size of government, and real exchange rate overvaluation, in the context of growth transitions. We find surprisingly complex effects of some policies. For example, trade makes fast growth more likely but also increases the frequency of crises. The size of government reduces the likelihood of fast miracle-like growth while at the same time limiting the risk of stagnation. Moreover, these effects are nonlinear and dependent on the quality of institutions. We conclude by highlighting potentially promising areas for future research.

A dynamic model of the evolution of health for those over the age of 50 is embedded in a structural, econometric model of retirement and saving. Effects of smoking, obesity, alcohol consumption, depression, and other proclivities on medical conditions are analyzed, including hypertension, diabetes, cancer, lung disease, heart problems, stroke, psychiatric problems, and arthritis. Compared to a population in good health, the current health of the population reduces retirement age by about one year. Including detailed health dynamics in a retirement model does not influence estimates of the marginal effects of economic incentives on retirement.

Typically, the budgetary requirements for executing a supplier’s process quality improvement program are often done in unstructured ways in that quality improvement managers purely use their previous experiences and pertinent historical information. In this backdrop, the purpose of this paper is to ascertain the expected cost of carrying out suppliers’ process quality improvement programs that are driven by original equipment manufacturers (OEMs).

Using inputs from experts who had prior experience executing suppliers’ quality improvement programs and employing the Bayesian theory, transition probabilities to various quality levels from an initial quality level are ascertained. Thereafter, the Markov chain concept enables the authors to determine steady-state probabilities. These steady-state probabilities in conjunction with quality level cost coefficients yield the expected cost of quality improvement programs.

The novel method devised in this research is a key contribution of the work. Furthermore, various implications related to experts’ inputs, dynamics related to Markov chain, etc., are discussed. The method is illustrated using a real life of automotive industry in India.

The research contributes to the extant literature in that a new method of determining the expected cost of quality improvement is proposed. Furthermore, the method would be of value to OEMs and suppliers wherein the quality levels at a given time are the function of quality levels in preceding period(s).

This study aims to determine the number of segments of green consumer behavior on toiletries products, and the tendency of transition between clusters is estimated. This study also provides recommendations based on the results.

This study used primary data collected through an online and offline questionnaire. The questionnaire was intended to identify the socio-demographic characteristics, green consumer behavior state according to the environment as well as the willingness of the respondents to purchase various toiletries products (current, less green, and greener). Prior to segmenting green consumer behavior, scale purification using confirmatory factor analysis was performed to ensure the indicators used were valid. The k-means clustering algorithm was used for the segmentation, while discriminant analysis was used to validate the segmentation result. The Markov chain approach was performed to estimate the tendency of the transition between constructed segments, where the logistic regression model was applied to predict the individual transition probability.

The clustering algorithm resulted in three segments: light green, green and dark green. The light green segment has the lowest attitude toward the environmental criteria while the members of the dark green segment have the highest attitude among the other segments. The logistic regression indicated that the tendency of individuals to stay in the current segment or move to the adjacent segment was influenced by socio-demographic factors. The one-step transition probability matrix revealed that the tendency of a particular segment to move to the greener segment was greater than to stay or even move to the less green segment. The Markov chain approach then showed that the steady-state condition will emerge after 18 steps.

This study was limited geographically and by the criteria used for segmenting the green consumer behavior; therefore, it is recommended that this study be replicated on a greater scale with more criteria. A wider geographic area could be considered, including a national study, and more criteria, such as social influences, could be considered. This study does not focus on specific toiletries products. Selecting more specific toiletries products could be considered to provide a more reliable response from the respondents. Moreover, factors around the willingness to pay for green products were not investigated in greater detail although these factors might become indicators that can distinguish between two or more segments.

This study empirically supports the theory that consumer environmentally friendly behavior can be used to appropriately categorize consumers into several segments, and thereby guide the development of a more differentiated policy approach for business and government.

Green consumer behavior may help save the environment and it will be beneficial in reducing environmental damage.

The study extends the existing literature related to green consumer behavior by segmenting the green consumer behavior based on the environmental criteria and applying the Markov chain approach to estimate the tendency of transition between segments.