PITFALLS IN CROSS‐SECTION STUDIES WITH INTEGRATED REGRESSORS: A SURVEY AND NEW DEVELOPMENTS

In cross‐section studies, if the dependent variable is I(0) but the regressor is I(1), the true slope must be zero in the resulting “unbalanced regression.” A spuriously significant relationship may be found in large cross‐sections, however, if the integrated regressor is related to a stationary variable that enters the DGP but is omitted from the regression. The solution is to search for the related stationary variable, in some cases the first difference of the integrated regressor, in other cases, a categorical variable that can take on limited number of values which depend on the integrated variable. We present an extensive survey, new developments, and applications particularly in finance.     

Predictive regressions under asymmetric loss: Factor augmentation and model selection

This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly.     

Tourism as an alternative source of regional growth in Portugal: a panel data analysis at NUTS II and III levels

The role of tourism is of vital economic importance, particularly for small countries with a privileged geographical location and favourable weather conditions. This paper examines the importance of tourism as a conditioning factor for higher regional growth in Portugal by employing the conditional convergence hypothesis of Barro and Sala-i-Martin, associated with the endogenous growth theory. The panel data estimation approach provides evidence of the positive impact of tourism (through the accommodation capacity) on the growth in per-capita income among the Portuguese regions, increasing the rate of convergence. Therefore, tourism can be considered as an alternative source for stimulating higher regional growth in Portugal, if the supply characteristics of this sector are improved.     

结构异质性对中国能源高质量发展的影响研究

基于结构异质性对能源高质量发展影响的理论分析,使用稀疏主成分分析方法测度中国能源高质量发展水平,构建中国和八大经济区域面板分位数回归模型,实证研究了结构异质性对中国能源高质量发展的影响。结果表明：2003—2020年中国能源高质量发展水平有所提升,但仍存在明显的区域发展不平衡问题,西部地区和北部沿海地区的能源高质量发展水平更高。产业结构与能源高质量发展水平呈负相关关系,能源消费结构、资本配置结构与能源高质量发展水平呈正相关关系。     

价值型投资在中国证券市场上的有力证据

本文给出了1994年至2005年间价值型投资在中国A股市场中的有力证据。Fama—MacBeth回归表明在中国A股市场中存在着显著的市盈率和市净率溢价，1994年至2005年中牛市和熊市的滚动策略显示了我国A股市场中的价值效应，并且风险和收益之间基本上呈现出收益大、风险大的特征。本文的实证研究结果将有助于中小投资者以及机构投资者的长期投资决策。     

Do labor market institutions matter for business cycles?

Using panel data of 19 OECD countries observed over 40 years and data on specific labor market reform episodes we conclude that labor market institutions matter for business cycle fluctuations. Spearman partial rank correlations reveal that more flexible institutions are associated with lower business cycle volatility. Turning to the analysis of reform episodes, wage bargaining reforms increase the correlation of the real wage with labor productivity and the volatility of unemployment. Employment protection reforms increase the volatility of employment and decrease the correlation of the real wage with labor productivity. Reforms reducing replacement rates make labor productivity more procyclical.     

How can investors build a better portfolio in small open economies? Evidence from Asia’s Four Little Dragons

This study investigates the role of hedging and portfolio design among stocks, exchange rates, and gold in small open economies (SOEs) from 4 January 2000 to 31 March 2020. We adopt the trivariate dynamic conditional correlation-fractionally integrated asymmetric power ARCH model and unconditional quantile regression model, and our findings show that the hedging role of the U.S. dollar (USD) and gold against stocks differs under regular and extreme market conditions. The USD can act as a powerful hedge asset for stocks in regular market periods. Moreover, during the global financial crisis and COVID-19 outbreak, the safe-haven effect of gold becomes stronger for almost all stocks, whereas the USD can serve as a strong safe haven against stock markets of Korea, Taiwan, and Singapore when stock returns are extremely low. In terms of portfolio designing, we find that adding the USD and gold to portfolios improves their hedging effectiveness, and the optimally weighted stock-USD-gold portfolio is the best portfolio strategy, irrespective of referring to return or risk.     

The effect of education on the minimum wage

This research shows for the first time that the level of education has a causal, negative effect on the minimum wage. I use 2SLS, with historical educational data as an instrument for the level of education in 2010, and I find that across the US states a one percentage point greater proportion of college graduates is associated with a real minimum wage that is lower by 1.5%–1.6%. Also, in order to control for state-level omitted variables, I regress the change in the minimum wage on the change in education and I find again a negative, and significantly at the 1% level, effect. Minimum wage is a policy that is chosen by governments according to voters’ preferences. The results of this research imply that when the level of education increases voters prefer a lower minimum wage.     

Does US news impact Asian emerging markets? Evidence from nonparametric causality-in-quantiles test

This paper aims to analyze whether US news on inflation and unemployment causes returns and volatility of seven emerging Asian stock markets from 1994 to 2014, by employing the causality-in-quantile approach. We find evidence that US news affect returns and/or volatility of all the seven stock markets considered, with these effects clustered around the tails of the conditional distribution of returns and volatility when they are either in bear or bull modes. In general, our results highlight the importance of modeling nonlinearity and studying entire conditional distributions of stock returns and volatility to draw correct inferences.     

Stock Price Index and Exchange Rate Nexus in African Markets

This paper examines the relationship between stock price index and exchange rate in six African markets using monthly data for the period January 2007 to October 2015. A quantile regression approach is used. This methodology is shown to perform better than the ordinary least squares estimators, particularly when the conditional distribution is heterogeneous. Our empirical evidence reveals an interesting pattern in the association of these two financial markets in Africa, which shows that the negative relationship between stock and foreign exchange markets is more apparent when exchange rates are extremely low or high. The negative relationship between the two variables is in line with the portfolio balance effect.