The Capital Tax and Welfare Effects from Asymmetric Information on Equity Markets

This paper explores the implications of informational asymmetries between domestic and foreign investors for optimal capital tax rates and welfare. It adopts a model in which asymmetric information implies a home bias in equity. The paper finds that asymmetric information may raise capital tax rates by reducing the marginal cost of taxation. Furthermore, it shows that investors may gain from informational asymmetries. Although asymmetric information increases the uncertainty as perceived by investors, it may also increase tax rates and allow for a higher consumption of public goods. This reflects that asymmetric information may reduce the distortionary effects of competition among governments.     

The survivorship bias, share price effect, and small firm effect in Canadian markets

After controlling for survivorship bias, we examine the relation between average returns, firm size, and price levels for Canadian stocks during the 1975-1994 period. Our findings indicate that there is a significant inverse share price level effect in Canadian markets. When we compare the results of the overall sample with the groups of surviving firms and delisted stocks, the latter group shows strong performance for large-size, high-priced stocks. Evidence that supports an independent size effect is less clear for Canadian stocks. A small size effect exists only among the higher share price denominations, which suggests a confounded size-price effect. Although the delisted group returns are statistically different from those of the survivor and the overall groups, which implies some evidence of survivorship bias, the difference between the survivor group and the overall group is weak at best.     

Another look at long memory in common stock returns

We apply the modified rescaled range test to the return series of 1,952 common stocks. The results indicate that long memory is not a widespread characteristic of these stocks. But logit models of the event of a test rejection reveal that rejections are linked to firms with large risk-adjusted average returns. The maximal moment of a return distribution is also found to influence the event of a rejection, but not in a way suggestive of moment-condition failure. Evidence suggestive of survivorship bias is also uncovered. We conclude that there is some evidence consistent with persistent long memory in the returns of a small proportion of stocks.     

Communicating risk for issues that involve ‘uncertainty bias’: what can the Israeli case of water fluoridation teach us?

Water fluoridation is a controversial issue in public health. Despite the uncertainty regarding its efficacy and safety, health officials continue to communicate it as ‘unequivocally’ safe and effective. Our focus is on how health officials and policy-makers in Israel frame the issue of water fluoridation in terms of certainty while promoting a mandatory fluoridation policy. According to van Asselt and Vos, the uncertainty paradox describes situations in which uncertainty is acknowledged, but the role of science is framed as providing certainty. Our study is an analysis of documents and media articles emphasizing the paradoxical language used by official representatives on the controversial topic of fluoridation. A central contribution of this study is that we coin the term ‘uncertainty bias,’ in which policy-makers do exactly what they accuse laypeople of doing, framing uncertainty in biased terms. We found that in order to establish mandatory regulation, health ministry officials expressed information in an unbalanced format, promoting the topic of fluoridation by framing it in exclusively positive terms. This study does not focus on the practice of water fluoridation per se, and is not intended to decide for or against it, but rather, to explore how the debate regarding it is communicated. Understanding this particular case can shed light on how other controversial topics are transformed into health policy that is characterized in equivocal terms.     

Sample attrition in the RLMS, 2001–10

The data of the Russian Longitudinal Monitoring Survey (RLMS) – Higher School of Economics represents one of the few nationally representative sources of household and individual data for Russia. These data have been collected since 1992 and in recent years, thanks to more secure financial and logistical support, have become a resource increasingly drawn upon by scholars and students for national and cross-national studies. In this paper, we examine the extent of non-random attrition in the RLMS and discuss the circumstances under which this might give rise to biases in econometric analysis. We illustrate this with an example drawn from the health sphere.     

Properties of Census Dual System Population Size Estimators

We study parametric and non‐parametric approaches for assessing the accuracy and coverage of a population census based on dual system surveys. The two parametric approaches being considered are post‐stratification and logistic regression, which have been or will be implemented for the US Census dual system surveys. We show that the parametric model‐based approaches are generally biased unless the model is correctly specified. We then study a local post‐stratification approach based on a non‐parametric kernel estimate of the Census enumeration functions. We illustrate that the non‐parametric approach avoids the risk of model mis‐specification and is consistent under relatively weak conditions. The performances of these estimators are evaluated numerically via simulation studies and an empirical analysis based on the 2000 US Census post‐enumeration survey data.     

On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.     

Students' persistent preconceptions and learning economic principles

Economic views held by the general public tend to differ significantly from those of economic experts. Would these differences fade away if people were exposed to some economic instruction? In this article, the authors identify college students' preconceptions about economic issues at the beginning of the semester, verify their persistence throughout the semester, and test whether their beliefs are correlated to course performance. The authors conduct a survey at the beginning and end of the semester on a sample of first-year students taking an economic principles course. They find evidence of preconception persistence and reasoning inconsistencies, pointing to some cognitive biases as a plausible cause. Most students do not integrate the newly learned tools into their thinking process, even if they perform well in tests.     

Wheat variety yield data: Do commercial and public performance tests provide the same information?

Wheat yields from reported performance test results are of economic importance to wheat producers, since their profits depend on selecting the optimal variety for their location. However, our data shows differences in absolute and relative wheat yields between commercial and public wheat breeding program's performance test data in Kansas. Newly available data are used to test if the difference in yields arose from potential selectivity bias, and to determine the contribution of private and public wheat breeding programs to varietal yield improvement during 2007–2012. Both Heckman selection models and multiple regression showed no statistical evidence of the potential presence of selectivity bias rather, managerial practices, agronomic conditions, field location, and inherent genetic traits of the seed variety were identify as the source of yield differences.