CAN THE PRESIDENT REALLY AFFECT ECONOMIC GROWTH? PRESIDENTIAL EFFORT AND THE POLITICAL BUSINESS CYCLE

Presidential elections are often seen as referendums on the health of the economy; however, little evidence exists on the president's ability to influence gross domestic product (GDP). This study examines the effect of the incentive to be reelected and the resulting increase in presidential effort on GDP growth. Growth is found to rise in reelection years for first‐term presidents after 1932 and to fall in election years before 1932, when reelection was uncommon, and for second‐term presidents generally. This effect is largest for high‐quality presidents—who probably have the highest return to effort—and is spread across multiple sectors of the economy. (JEL D78, D72, E32, J24)     

Measures of Multigroup Segregation

In this paper we derive and evaluate measures of multigroup segregation. After describing four ways to conceptualize the measurement of multigroup segregation—as the disproportionality in group (e.g., race) proportions across organizational units (e.g., schools or census tracts), as the strength of association between nominal variables indexing group and organizational unit membership, as the ratio of between–unit diversity to total diversity, and as the weighted average of two–group segregation indices—we derive six multigroup segregation indices: a dissimilarity index (D), a Gini index (G), an information theory index (H), a squared coefficient of variation index (C), a relative diversity index (R), and a normalized exposure index (P). We evaluate these six indices against a set of seven desirable properties of segregation indices. We conclude that the information theory index H is the most conceptually and mathematically satisfactory index, since it alone obeys the principle of transfers in the multigroup case. Moreover, H is the only multigroup index that can be decomposed into a sum of between– and within–group components.     

Population constraints on pooled surveys in demographic hazard modeling

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.     

Distribution of exotic monk parakeets across an urban landscape

Monk parakeets (Myiopsitta monachus) are the most abundant and widely distributed of the naturalized parrots in the United States. Their presence is simultaneously encouraged by some humans (through use of bird feeders) and discouraged by others (through removal of their nests) and, as a result, they show an interesting spatial distribution across urban areas. We used an online public survey and field surveys to examine the influence of human activities and land use on the distribution of this exotic species around Chicago, IL (USA). These efforts resulted in detection of 249 nesting structures and approximately 778 birds across the region. A CART analysis successfully separated nesting sites from random sites and correctly classified 90?% of the nesting sites. The most important factor in the model was land use, with nests typically found in areas with less than 84?% residential zoning. We found nests on a wide variety of substrates including trees, cell phone towers, and stadium lights. Spatial point pattern analysis indicated that nests in trees and nests in built substrates were significantly dissociated with each other at all scales. Nests on built substrates were closer to railroads and highways or in areas with lower human population density, suggesting either a difference in substrate availability or human tolerance between these settings. While humans may have a positive effect on distribution of monk parakeets at large spatial scales, at the scale of this study we see a potentially negative effect of too many humans on the distribution of monk parakeet nests.