A reexamination of state fiscal health and amnesty enactment

We use event history analysis to separately model a state’s first and then repeated tax amnesties and test the revenue yield versus the fiscal stress hypotheses using a panel of annual data from all 50 states for the period 1982–2010. We also split our sample into two sub-periods, 1982–1988 and 1989–2010, to more easily compare our results to other studies and to see if there is a significant difference between early tax amnesties and more recent ones. We find that state fiscal stress is more important than the potential yield from an amnesty, particularly for more recent amnesties. Our findings contrast with the existing literature which found evidence that states are likely to enact tax amnesties due to a revenue yield motive rather than a fiscal stress motive.     

WHO BENEFITS FROM JOB CORPS? A DISTRIBUTIONAL ANALYSIS OF AN ACTIVE LABOR MARKET PROGRAM

Using recently developed econometric techniques to estimate quantile treatment effects (QTE) and experimental data, we examine the impact of Job Corps on earnings distribution. Our results indicate a great deal of heterogeneity in the effects of Job Corps. The QTEs show an increasing pattern along the earnings distribution, with much more pronounced differences at the upper quantiles for males, whites, and ages 20–24. Moreover, we find the QTEs to be very small at quantiles below the median for males, ages 16–17 and 18–19, and non‐resident students. We propose strong economic conditions and skill hypotheses to explain the heterogeneity observed over the earnings distribution. Copyright © 2013 John Wiley & Sons, Ltd.     

The inflation and inflation uncertainty relationship for Turkey: a dynamic framework

This article assesses the interaction between inflation and inflation uncertainty in a dynamic framework for Turkey by using monthly data for the time period 1984–2009. The bulk of previous studies investigating the link between inflation and inflation uncertainty employ Autoregressive Conditional Heteroskedasticity (ARCH)-type models, which consider inflation uncertainty as a predetermined function of innovations to inflation specification. The stochastic volatility in mean (SVM) models that we use allow for gathering innovations to inflation uncertainty and assess the effect of inflation volatility shocks on inflation over time. When we assess the interaction between inflation and its volatility, the empirical findings indicate that response of inflation to inflation volatility is positive and statistically significant. However, the response of inflation volatility to inflation is negative but not statistically significant.     

Re-assessment of E-S-Qual and E-RecS-Qual in a pure service setting

Understanding and measuring electronic service quality including its dimensions has become crucial since a growing volume of business takes place in the cyber world. This paper focuses on measuring electronic service quality and service recovery issues by means of E-S-QUAL and E-RecS-QUAL scales in a pure service oriented setting and across a culturally different consumer group than the original scale. This research covers 2017 customers' assessment of the electronic service quality offered by 13 banks in Turkey. Findings suggest a refined and more stable version of the E-S-QUAL scale for the internet banks. Comprehensive psychometric tests also suggest that E-RecS-QUAL is an appropriate tool to evaluate online service recovery in consumer research.     

Distribution of run statistics in partially exchangeable processes

Let { X_i} _{i 3 1}{\{ X_{i}\} _{i\geq 1}} be an infinite sequence of recurrent partially exchangeable binary random variables. We study the exact distributions of two run statistics (total number of success runs and the longest success run) in { X_i} _{i 3 1}{\{ X_{i}\} _{i\geq1}} . Since a flexible class of models for binary sequences can be obtained using the concept of partial exchangeability, as a special case of our results one can obtain the distribution of runs in ordinary Markov chains, exchangeable and independent sequences. The results also enable us to study the distribution of runs in particular urn models.     

OPTIMAL PORTFOLIO SELECTION WITH A SHORTFALL PROBABILITY CONSTRAINT: EVIDENCE FROM ALTERNATIVE DISTRIBUTION FUNCTIONS

We propose a new approach to optimal portfolio selection in a downside risk framework that allocates assets by maximizing expected return subject to a shortfall probability constraint, reflecting the typical desire of a risk-averse investor to limit the maximum likely loss. Our empirical results indicate that the loss-averse portfolio outperforms the widely used mean-variance approach based on the cumulative cash values, geometric mean returns, and average risk-adjusted returns. We also evaluate the relative performance of the loss-averse portfolio with normal, symmetric thin-tailed, symmetric fat-tailed, and skewed fat-tailed return distributions in terms of average return, risk, and average risk-adjusted return.     

The effect of inflation uncertainty on inflation: Stochastic volatility in mean model within a dynamic framework

This paper investigates the effect of inflation uncertainty innovations on inflation over time by considering the monthly United States data for the time period 1976–2006. In order to investigate the effect of inflation uncertainty innovation on inflation, a Stochastic Volatility in Mean model (SVM) has been employed. SVM models are generally used to capture the innovation to inflation uncertainty, which cannot be achieved in the framework of popular deterministic ARCH type of models. Empirical evidence provided here suggests that innovations in inflation volatility increases inflation persistently. This evidence is robust across various definitions of inflation and different sub-periods.