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.     

From dilemmatic struggle to legitimized indifference: Expatriates’ host country language learning and its impact on the expatriate-HCE relationship

We address the lack of knowledge concerning the role of host country languages in multinational corporations based on an inductive qualitative study involving 70 interviews with Nordic expatriates and host country employees (HCE) in China. Building on the strongly discrepant views of expatriates and HCEs, we demonstrate how expatriates’ willingness to learn and use the host country language lead to different types of expatriate-HCE relationships, ranging from harmonious to distant or segregated. In doing so, we emphasize the subtle and fragile connection between expatriates’ attitude towards HCEs’ mother tongue and trust formation in addition to the construction of superiority-inferiority relationships.     

Pro-market institutions and outward FDI of emerging market firms: An institutional arbitrage logic

We offer new theory and evidence regarding the effects of pro-market institutions on outward foreign direct investment (FDI) of emerging market firms (EMFs). Drawing on the logic of institutional arbitrage, we integrate the escapism and exploitation mechanisms of EMF internationalization into a unified theoretical context. We propose an inverted U-shaped relationship between host market-supporting institutions (MSI) and the investment scale of an EMF’s FDI project in the country, showing an escape-driven upward slope for low-to-medium MSI levels and an exploitation-driven downward slope for medium-to-high MSI levels. We supplement this main argument with two boundary conditions: the alleviating effect of home market liberalization (HML) and the strengthening effect of home government subsidies (HGS), demonstrating the coexistence and variation of pro- and anti- market institutions in an emerging market. Using information on 1,450 FDI projects conducted by 288 Chinese listed firms in 116 host countries, we obtain supportive evidence for the predicted relationships between the three institutional forces. This study enriches the literatures on institutional arbitrage and pro-market institutions with evidence from EMFs.     

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.     

Identifying terms of trade shocks in a developing country using a sign restrictions approach

Using annual data for Botswana from 1960 to 2012, we examine the responses of macroeconomic variables to four generalized positive terms of trade shocks – global demand, globalizing, sector-specific and global supply. A sign-restricted structural vector autoregression model with a penalty function is estimated to identify the four possible shocks. While positive global demand and globalization shocks are both expansionary, they have opposite effects on inflation. A positive commodity market specific shock dampens real GDP growth and is inflationary, suggesting a possible Dutch disease response. A negative global supply shock suppresses both output growth and inflation. All but the last shock leads to a significant declining interest rate. Monetary policy contraction is recommended for the first shock and expansion for the others.     

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.     

Information and Investor Behavior Surrounding Earnings Announcements

The goal of this paper is to analyze the impact of annual earnings announcements on the market through the order flow data in addition to the usual transaction data. In this respect, examining order flow data can potentially reveal valuable information that is not available from transaction data. In fact, the data allow us to test hypotheses about asymmetric information and investor behavior and to test if the behavior varies with investor sophistication. In addition, the paper tries to identify the determinants of the impact on a firm's value using assumptions about investor behavior.