Oil,the Baltic Dry index,market (il)liquidity and business cycles: evidence from net oil-exporting/oil-importing countries

Financial Markets and Portfolio Management - The recent financial crisis has made (il)liquidity research more significant than ever. Galariotis and Giouvris (Int Rev Financ Anal 38:44–69,...     

On the prediction of financial distress in developed and emerging markets: Does the choice of accounting and market information matter? A comparison of UK and Indian Firms

We examine differences in price delay for a sample of real estate investment trust (REIT) and non-REIT matched pairs. Results suggest an economically and statistically higher level of price delay for REIT securities, which implies heightened frictions that increase the time needed for new information to be impounded into the prices of REIT shares. The primary drivers for the observed delay differential include differences in idiosyncratic volatility, market risk, and the number of days traded. Within-REIT determinants of delay confirm findings for the pooled sample of matched pairs. Importantly, we infer find that REIT investors are not compensated for restricted information flow, as excess returns are unrelated to the price delay.     

A robust VaR model under different time periods and weighting schemes

This paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by using non parametric, semi parametric and parametric methods. In order to choose one model among the various forecasting methods, a two-stage backtesting procedure is implemented. In the first stage the unconditional coverage test is used to examine the statistical accuracy of the models. In the second stage a loss function is applied to investigate whether the differences between the models, that calculated accurately the VaR, are statistically significant. Under this framework, the combination of a parametric model with the historical simulation produced robust results across the sample periods, market capitalization schemes, trading positions and confidence levels and therefore there is a risk measure that is reliable.

The M4 Competition: Results,findings, conclusion and way forward

The M4 competition is the continuation of three previous competitions started more than 45 years ago whose purpose was to learn how to improve forecasting accuracy, and how such learning can be applied to advance the theory and practice of forecasting. The purpose of M4 was to replicate the results of the previous ones and extend them into three directions: First significantly increase the number of series, second include Machine Learning (ML) forecasting methods, and third evaluate both point forecasts and prediction intervals. The five major findings of the M4 Competitions are: 1. Out Of the 17 most accurate methods, 12 were “combinations” of mostly statistical approaches. 2. The biggest surprise was a “hybrid” approach that utilized both statistical and ML features. This method’s average sMAPE was close to 10% more accurate than the combination benchmark used to compare the submitted methods. 3. The second most accurate method was a combination of seven statistical methods and one ML one, with the weights for the averaging being calculated by a ML algorithm that was trained to minimize the forecasting. 4. The two most accurate methods also achieved an amazing success in specifying the 95% prediction intervals correctly. 5. The six pure ML methods performed poorly, with none of them being more accurate than the combination benchmark and only one being more accurate than Naïve2. This paper presents some initial results of M4, its major findings and a logical conclusion. Finally, it outlines what the authors consider to be the way forward for the field of forecasting.     

A Quantile Regression Analysis of Wages in Panama

Differences in the effects of worker characteristics on wages in Panama at different points of the conditional wage distribution are investigated. Public sector employment increases wages relatively more at lower quantiles. Within the public sector, employment in that sector increases wages of the median worker and reduces wage inequality. Presence of a labor union increases relatively more private sector wages at lower quantiles. Unions reduce wage inequality within the union private sector and increase average wages within that sector. In the public sector, the presence of a labor union increases wages of men at lower quantiles at a lower rate than in the private sector. Self-employment decreases wages at lower quantiles and increases wages at higher quantiles. Urban location affects wages in a U-shaped pattern as one moves from lower to higher quantiles. Rates of return to experience are higher for men at higher quantiles. Experience increases men's wage inequality.     

Spatial and economic patterns in life expectancy among US States

This study investigates the determinants of gender-specific life expectancy across US states over the period 1995–2007. We employ a production function specification where life expectancy depends on health expenditure, income, education and lifestyle variables, allowing for spatial effects. Empirical results suggest that education attainment and health expenditure are the main factors behind improving longevity, whereas smoking bears a strong negative influence. For robustness purposes, we also use health spending as well as education criteria, apart from geographical ones to model interstate spillovers. In the former case, states with similar health expenditure are ‘neighbors’ and affect positively the life expectancy process. If education is applied instead of health spending together with geographic proximity, the spatial correlation is insignificant, i.e. education ‘neighbors’ do not affect life expectancy. Our findings do not imply significant gender differences regarding health production. The results suggest that health care policy will have to focus on wider economic and social considerations, like education and lifestyle changes, except medical care provision in order to exploit the full potential for life expectancy improvements of the US population.     

An investigation of factors affecting the visits of online crowdsourcing and labor platforms

Nowadays, the economic activities have become increasingly digital since hundreds of millions of Internet users are using crowdsourcing platforms either to work at an online job as workers, or as a model of problem-solving and production as requesters. This growing workforce makes it necessary from the perspective of the online platforms, to fully understand the business dimensions of this emerging and innovative “online labor” phenomenon, which can rapidly change the future of work and work organization in the online world. This paper aims to investigate and analyze the visits of online labor platforms that offer crowdsourcing and crowdfunding services. Using websites’ metrics data drawn from Alexa for the time period 2012-2016 the paper uses Ordinary Least Squares (OLS) and Fixed Effects (FE) regression analysis to examine correlations between visits and website characteristics. The research shows that the sessions of an online labor marketplace website from mobile devices have an increasing trend to be positively correlated to the quality mechanisms a website deploys as well as on location-dependent factors. The results are expected to provide insights on how the online labor website characteristics affect their traffic and thus inform about their evolution and improvement.     

DYNAMIC STATUS EFFECTS,SAVINGS, AND INCOME INEQUALITY

This article advances the hypothesis that the intensity of status preferences depends negatively on the average wealth of society (endogenous dynamic status effect), in accordance with empirical evidence. Our theory replicates the contradictory historical facts of an increasing saving rate along with declining returns to capital over time. By affecting the dynamics of the saving rate, the dynamic status effect raises inequality, thereby providing a behavioral mechanism for the observed diverse dynamics of income inequality across countries. In countries in which the dynamic status effect is strong (weak), inequality rises (declines) over time in response to a positive productivity shock.