Socio-demographics,political attitudes and informal sector employment: A cross-country analysis

In this paper, we empirically investigate the relationship between informal sector employment and micro-level socio-demographic characteristics, political acts and attitudes, and individual norms. Using self-reported individual micro-level data from the World Values Survey for seven developing countries (China, Ecuador, Egypt, Mexico, Peru, South Africa and Yemen), our cross-country regressions and principal component analysis reveal that socio-demographic characteristics of individuals are strong predictors of their informal sector employment. Our estimations further document that individual preferences for an economically strong, interventionist and egalitarian state and confidence in state and political institutions are positively and significantly correlated with informal sector employment, whereas variables associated with confidence in free market institutions and support for competition are negatively and significantly correlated with informal sector employment. We also show that individuals who participate either actively or inactively in peaceful and lawful political processes are significantly less likely to work in the informal sector. Finally, we document that individual norms, such as religiosity and tax morale, are negatively correlated with informal sector employment. Throughout our analysis, instead of having to rely on ad-hoc informality categorizations of third parties, we base our measurement of informal sector employment directly on the self-evaluation of individuals, who have the best information on the degree of their informality.     

MORE THAN A FEELING: CONFIDENCE,UNCERTAINTY, AND MACROECONOMIC FLUCTUATIONS

Economists, observers, and policy-makers often emphasize the role of sentiment as a potential driver of the business cycle. In this paper, we provide three contributions to this debate. First, we give an overview of the recent literature on the nexus between sentiment (considering both confidence and uncertainty) and economic activity. Second, we review existing empirical measures of sentiment, in particular consumer confidence, stock market volatility (SMV) and Economic Policy Uncertainty (EPU), on monthly data for 27 countries, 1985–2016. Third, we identify some new stylized facts based on international evidence. While different measures are surprisingly lowly correlated on average in each country, they are typically highly positively correlated across countries, suggesting the existence of a global factor or sizeable international spillovers of sentiment. Consumer confidence has the closest co-movement with economic and financial variables, and most of the correlations are contemporaneous or forward-looking, consistent with the view that economic sentiment is indeed a driver of activity.     

A useful tool for forecasting the Euro-area business cycle phases

Based on a novel extension of existing multivariate Markov-switching models, we provide the reader with a useful tool for analyzing current business conditions and making predictions about the future state of the Euro-area economy in real time. Apart from the Industrial Production Index, we find that the European Commission Industrial Confidence Indicator, which is issued with no delay, is very useful for constructing the real-time predictions.     

The asymmetry of judgemental confidence intervals in time series forecasting

In forecasting a time series, one may be asked to communicate the likely distribution of the future actual value, often expressed as a confidence interval. Whilst the accuracy (calibration) of these intervals has dominated most studies to date, this paper is concerned with other possible characteristics of the intervals. It reports a study in which the prevalence and determinants of the symmetry of judgemental confidence intervals in time series forecasting was examined. Most prior work has assumed that this interval is symmetrically placed around the forecast. However, this study shows that people generally estimate asymmetric confidence intervals where the forecast is not the midpoint of the estimated interval. Many of these intervals are grossly asymmetric. Results indicate that the placement of the forecast in relation to the last actual value of a time series is a major determinant of the direction and size of the asymmetry.     

Managers' emotional displays and employees' willingness to act entrepreneurially

In this study we draw on the literature of emotions and entrepreneurial motivation to analyze how and why emotional displays of managers influence the willingness of employees to act entrepreneurially. Using an experimental design and 2912 assessments nested within 91 employees from 31 small entrepreneurially oriented firms, we find that managers' displays of confidence and satisfaction about entrepreneurial projects enhance employees' willingness to act entrepreneurially, whereas displays of frustration, worry, and bewilderment diminish employees' willingness. Moreover, we find that displays of satisfaction, frustration, worry, and bewilderment moderate the effect of managers' displayed confidence on employees' willingness to act entrepreneurially. Our findings have implications for the emotions and entrepreneurial motivation literature.     

Hierarchical Bayesian conjoint models incorporating measurement uncertainty

The authors explore situations where consumers supplement their judgments with a measurement of uncertainty about their own preferences, either implicitly or explicitly, and develop two sets of hierarchical Bayesian conjoint models incorporating such measurements. The first set of models uses the relative location of a rating to determine the importance or weight given to the rating, in a regression setting. The second set uses interval judgment as a dependent variable in a regression setting. After specifying the models, the authors perform a theoretical comparison with a basic Bayesian regression model. They show that, under different conditions, the proposed models will yield more precise individual-level partworth estimates. Two simulated data examples and data from a conjoint study are used to illustrate the gains that could be obtained from modeling uncertainty. In the empirical application, the authors show that model fit improves when ratings for items that respondents do not like are given more weight compared to ratings for items that they do like. Electronic Supplementary Material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

The Coverage Properties of Confidence Regions After Model Selection

It is very common in applied frequentist ("classical") statistics to carry out a preliminary statistical (i.e. data-based) model selection by, for example, using preliminary hypothesis tests or minimizing AIC. This is usually followed by the inference of interest, using the same data, based on the assumption that the selected model had been given to us  a priori . This assumption is false and it can lead to an inaccurate and misleading inference. We consider the important case that the inference of interest is a confidence region. We review the literature that shows that the resulting confidence regions typically have very poor coverage properties. We also briefly review the closely related literature that describes the coverage properties of prediction intervals after preliminary statistical model selection. A possible motivation for preliminary statistical model selection is a wish to utilize uncertain prior information in the inference of interest. We review the literature in which the aim is to utilize uncertain prior information directly in the construction of confidence regions, without requiring the intermediate step of a preliminary statistical model selection. We also point out this aim as a future direction for research.     

Forecasting another’s enjoyment versus giving the right answer: Trust, shared values, task effects, and confidence in improving the acceptance of advice

In two experiments, participants received advice from another participant on a task either with a correct answer (intellective tasks) or without a correct answer (judgmental task), in which the participant had to make a forecast. In both experiments, the level of trust in the advisor and a perception of the advisor having similar values were important predictors of the acceptance of advice for a judgmental, taste forecast task, whereas advisor confidence was a more important predictor of the acceptance of advice on the intellective task. In Experiment 2, the face-to-face interactions between the decision-maker and the advisor were videotaped and coded. Advisors provided more information to decision-makers for the taste forecast than for the intellective task. Further, whether the advisor provided information to supplement their recommendation or not was a significant predictor of the acceptance of advice on the taste forecast, but not on the intellective task. The results are discussed in the context of previous research on advice, which has predominately used intellective tasks.     

Confidence intervals: An empirical investigation of the series in the M-competition

This paper empirically evaluates the uncertainty of forecasts. It does so using the 1001 series of the M-Competition. The study indicates that although, in model fitting the percentage of observations outside the confidence intervals is close to that postulated theoretically, this is not true for forecasting. In the latter case the percentage of observations outside the confidence intervals is much higher than that postulated theoretically. This is so for the great majority of series, forecasting horizonts, and methods. In addition to evaluating the extent of uncertainty, we provide tables to help users to construct more realistic confidence intervals for their forecasts.     

Joint estimation of technical efficiency and production risk for multi-output banks under a panel data cost frontier model

This article generalizes production risk from a single output production function to a multiple output cost frontier, which is able to examine input-oriented technical efficiencies and production risk simultaneously in the context of a panel data. Furthermore, the joint confidence interval estimates for technical efficiencies are constructed by means of multiple comparisons with the best approach. Whether taking production risk into account or not offers quite dissimilar implications in terms of the average technical efficiency measure and the identification of multiple efficient banks achieving the optimal cost frontier. It is suggested that inferences drawn on the basis of the confidence intervals of technical efficiency provide much more fruitful and insightful information than the point estimation alone. Bank specific risk parameters are found to be highly and positively correlated with fixed-effect estimates, implying that the more risk-averse a bank is, the more technically efficient it will be.