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)     

Lives in limbo: Temporary Protected Status and immigrant identities

The United States formulates much of its immigration and refugee policy to match economic and political circumstances. We interpret these policy shifts as a set of graduated positions on immigration and refugee flows that attempts to discipline the lives of newcomers and, in so doing, shapes immigrant identities. In this article, we analyse the interplay between the US government and Salvadoran asylum applicants negotiating procedures that grant only temporary relief from deportation via the policy of Temporary Protected Status (TPS). We find that each policy shift results in the strategic renegotiation of asylum applicants’ identities so as to achieve the best opportunity for a successful outcome. Based on Foucault’s ideas of governmentality and Ong’s concept of flexible citizenship, we argue that what appears more superficially as a patchwork strategy of immigration laws and asylum practices may be theorized more deeply as a set of flexible responses by the state that turn on identity construction at different scales, and that aim to mediate transnational relations.     

改善开发所致移民安置项目的后果——牛津大学难民研究中心研究成果报告

论文在讨论四个移民典型案例的基础上 ,讨论在项目中与政策相关的教训     

LOG-PERIODOGRAM ESTIMATION OF LONG MEMORY VOLATILITY DEPENDENCIES WITH CONDITIONALLY HEAVY TAILED RETURNS

Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies.     

Don't mention Stonehenge!

It rises massive and magnificent above Salisbury Plain. The extraordinary monoliths of Stonehenge leave us as impressed today as ever—and as baffled. Archaeologists argue about how it was made. Can statisticians tell the answer? Chris Jones thinks they can be of considerable assistance.     

CALGARY FAMILY INTERVENTION MODEL: ONE WAY TO THINK ABOUT CHANGE

This article defines and describes the Calgary Family Intervention Model (CFIM). CFIM is an organizing framework conceptualizing the intersect between a particular domain (i.e., cognitive, affective, or behavioral) of family functioning and a specific intervention offered by a health professional. Examples and discussion of interventions such as storying the illness experience, encouraging respite, and asking interventive questions are presented. CFIM is one way that health professionals can conceptualize about change.     

Was there a “golden past” for the introductory sociology textbook? A citation analysis of leading journals

Much debate over the years has centered around whether there was ever a “golden past” for the introductory sociology textbook, when high quality books influenced the development of scholarship and thinking. Some empirical evidence is added to this debate through an analysis of the citations to introductory sociology textbooks in all the articles and research notes appearing in theAmerican Journal of Sociology, theAmerican Sociological Review, andSocial Forces from 1960 to 1969 and from 1984 to 1993. The data show that, although seldom cited in recent journals, introductory sociology textbooks were often cited in the earlier period. The article concludes with some thoughts about why introductory sociology textbooks have had a declining influence on scholarship.     

What to Do at Low Doses: A Bounding Approach for Economic Analysis

To quantify the health benefits of environmental policies, economists generally require estimates of the reduced probability of illness or death. For policies that reduce exposure to carcinogenic substances, these estimates traditionally have been obtained through the linear extrapolation of experimental dose-response data to low-exposure scenarios as described in the U.S. Environmental Protection Agency's Guidelines for Carcinogen Risk Assessment (1986). In response to evolving scientific knowledge, EPA proposed revisions to the guidelines in 1996. Under the proposed revisions, dose-response relationships would not be estimated for carcinogens thought to exhibit nonlinear modes of action. Such a change in cancer-risk assessment methods and outputs will likely have serious consequences for how benefit-cost analyses of policies aimed at reducing cancer risks are conducted. Any tendency for reduced quantification of effects in environmental risk assessments, such as those contemplated in the revisions to EPA's cancer-risk assessment guidelines, impedes the ability of economic analysts to respond to increasing calls for benefit-cost analysis. This article examines the implications for benefit-cost analysis of carcinogenic exposures of the proposed changes to the 1986 Guidelines and proposes an approach for bounding dose-response relationships when no biologically based models are available. In spite of the more limited quantitative information provided in a carcinogen risk assessment under the proposed revisions to the guidelines, we argue that reasonable bounds on dose-response relationships can be estimated for low-level exposures to nonlinear carcinogens. This approach yields estimates of reduced illness for use in a benefit-cost analysis while incorporating evidence of nonlinearities in the dose-response relationship. As an illustration, the bounding approach is applied to the case of chloroform exposure.