Modelling of repairable systems with various degrees of repair

The availability of a stochastic repairable system depends on the failure behaviour and on repair strategies. In this paper, we deal with a general repair model for a system using auxiliary counting processes and corresponding intensities which include various degrees of repair (between minimal repair and perfect repair). For determining the model parameters we need estimators depending on failure times and repair times: maximum likelihood (ML) estimator and Bayes estimators are considered. Special results are obtained by the use of Weibull-type intensities and random observation times.     

Will the (German) NAIRU Please Stand Up?

Abstract. This paper deals with a critical assessment of the ‘non‐accelerating inflation rate of unemployment’ (NAIRU) for Germany. There are quite a few obstacles to perceiving the NAIRU as an easy‐to‐use analytical instrument: the possibility of a non‐vertical Phillips curve, the occurrence of shocks and hysteresis effects, and the (mis‐)measurement of important variables, cointegration issues and a time variability of the NAIRU. A new attempt is made to estimate a NAIRU for Germany using direct measures of inflationary expectations. However, by any method, the NAIRU is very hard to determine and subject to considerable arbitrariness.     

Forecasting market turbulence using regime-switching models

We propose an early warning system to timely forecast turbulence in the US stock market. In a first step, a Markov-switching model with two regimes (a calm market and a turbulent market) is developed. Based on the time series of the monthly returns of the S&P 500 price index, the corresponding filtered probabilities are successively estimated. In a second step, the turbulent phase of the model is further specified to distinguish between bullish and bearish trends. For comparison only, a Markov-switching model with three states (a calm market, a turbulent bullish market, and a turbulent bearish market) is examined as well. In a third step, logistic regression models are employed to forecast the filtered probabilities provided by the Markov-switching models. A major advantage of the presented modeling framework is the timely identification of the factors driving the different phases of the capital market. In a fourth step, the early warning system is applied to an asset management case study. The results show that explicit consideration of the models’ signals yields better portfolio performance and lower portfolio risk compared to standard buy-and-hold and constant proportion portfolio insurance strategies.     

The perceived probability of job loss and future labour market outcomes

Longitudinal survey data are used to test the degree to which worker expectations of future job loss are correlated with changes in labour market status. Three major findings are reported. First, perceived probabilities of expected job loss are only weakly related to both exogenous job separations and subsequent transitions to unemployment and inactivity. Second, while fears of job loss tend to persist across time and job spells, they do so at a highly diminishing rate. Third, quit intentions are strongly correlated with both voluntary separations and transitions to alternative employment, and do not diminish greatly across successive employment spells.     

Will FinTech make regional banks superfluous for small firm finance? Observations from soft information-based lending in Germany

Regional banks have a competitive advantage in that short distances to clients enable the use of soft information for superior lending decisions. If the ambition of FinTech start-ups to create superior screening and monitoring technologies materialises, this advantage would be diminished and regional banks would become superfluous for small firm finance. To explore this claim, the paper in hand analyses qualitative empirical data about the lending processes and rating system use of regional German savings banks. In essence, the results from participant observation and interviews clarify the importance of “real” soft information for critical lending decisions. The context specificity and limited verifiability of “real” soft information hamper it from being hardened through the use of rating systems and other bank-ICT. Though FinTech's scoring technologies may overcome the first limitation, it appears likely that in the course of scoring development “real” soft information will be systematically crowded out due to the manipulation problem. The paper expects improved access to finance for SMEs if FinTech solutions overcome both limitations of “real” soft information use, or if peer-to-peer lending and regional banks coexist. Deteriorated access to finance is expected if FinTech companies displace the relationship banking of regional banks due to enhanced competition, without preserving the advantages of “real” soft information with superior screening and monitoring technologies. The paper concludes with recommendations on how to prevent deteriorated access to finance for small firms by promoting fair competition and FinTech innovations.     

A NOTE ON SEMIPARAMETRIC ESTIMATION OF FINITE MIXTURES OF DISCRETE CHOICE MODELS WITH APPLICATION TO GAME THEORETIC MODELS*

We view a game abstractly as a semiparametric mixture distribution and study the semiparametric efficiency bound of this model. Our results suggest that a key issue for inference is the number of equilibria compared to the number of outcomes. If the number of equilibria is sufficiently large compared to the number of outcomes, root‐n consistent estimation of the model will not be possible. We also provide a simple estimator in the case when the efficiency bound is strictly above zero.     

The comprehensive business exam: Usefulness for assessing instructional and student performance outcomes

The authors explore the results of the Comprehensive Business Exam (CBE) administered to business majors during their senior-year business capstone course. The study results identified students' SAT and grade point average as a predictor of CBE performance, and variables that explain the correlation between CBE performance, SAT score, and grade point average are discussed. This study expands the research stream by demonstrating how faculty can use CBE information to more deeply assess student learning at both the course and instructor level than is possible with the Major Field Test for Bachelor's Degree in Business.     

The impacts of international tourism demand on economic growth of small economies dependent on tourism

This paper studies the impacts on economic growth of a small tourism-driven economy caused by an increase in the growth rate of international tourism demand. We present a formal model and empirical evidence. The ingredients of the dynamic model are a large population of intertemporally optimizing agents and an AK technology representing tourism production. The model shows that an increase in the growth of tourism demand leads to transitional dynamics with gradually increasing economic growth and increasing terms of trade. In our empirical application, an econometric methodology is applied to annual data of Antigua and Barbuda from 1970 to 2008. We perform a cointegration analysis to look for the existence of a long-run relationship among variables of economic growth, international tourism earnings and the real exchange rate. The exercise confirms the theoretical findings.     

The Effect of Employment while in High School on Educational Attainment: A Conditional Difference‐in‐Differences Approach*

Using American panel data from the National Education Longitudinal Study of 1988, this article investigates the effect of working during grade 12 on attainment. We employ, for the first time in the related literature, a semiparametric propensity score matching approach combined with difference‐in‐differences. We address selection on both observables and unobservables associated with part‐time work decisions, without the need for instrumental variable. Once such factors are controlled for, little to no effects on reading and math scores are found. Overall, our results therefore suggest a negligible academic cost from part‐time working by the end of high school.