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.     

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.     

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.     

Stock price synchronicity to oil shocks across quantiles: Evidence from Chinese oil firms

This paper investigates behaviour of stock price synchronicity to oil shocks across quantiles for Chinese oil firms. The spillover effects of the oil market on a firm are segregated into firm-specific and market-wide information. First, our results report a higher level of synchronicity by dynamic conditional correlations than by R-square since the former better captures dynamic linear dependence. Second, we find strong evidence of size effect. In particular, stock price synchronicity is generally higher in large-cap firms than in small-cap ones. Oil shocks affect synchronicity in the upper quantiles differently based on firm size. Third, we also find that synchronicity responds to oil shocks significantly in extreme low quantiles, implying that shocks in the oil market are transmitted to Chinese oil firms via firm-specific information. Finally, we determine that oil shocks have little or no immediate impact on stock price synchronicity; instead, cumulative lagged effect is evident. This evidence highlights the lagging effect of spillover of oil shocks on Chinese oil firms.     

Inferring latent social networks from stock holdings

We infer the latent social networks of investors using data on their stock holdings. We map linkages to portfolio weights using a portfolio-choice model. The precision of an investor’s private signal about firm value is assumed to increase with his connections in the city where the firm is headquartered. Using money-manager data, we find that managerial linkages to a city are overly dispersed relative to the Erdös–Rényi model of i.i.d. connections. Managers at the tail of this distribution with non-i.i.d. linkages have more university alumni in that city. Their stock holdings there outperform their holdings in other cities.     

Latent vs. Observed Variables: Analysis of Irrigation Water Efficiency Using SEM and SUR

In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equation modeling (SEM), in the latter by seemingly unrelated regression (SUR). We compare estimation results of the two approaches based on a dataset on single factor irrigation water use efficiency obtained from a survey of 360 farmers in the Guanzhong Plain, China. The main methodological findings are that SEM allows identification of the most important dimension of irrigation water efficiency (technical efficiency) via comparison of their factor scores and reliability. Moreover, it reduces multicollinearity and attenuation bias. It thus is preferable to SUR. The SEM estimates show that perception of water scarcity is the most important positive determinant of both types of efficiency, followed by irrigation infrastructure, income and water price. Furthermore, there is a strong negative reverse effect from efficiency on perception.