Leukaemia incidence among workers in the shoe and boot manufacturing industry: a case-control study

BACKGROUND: Previous reports have indicated an excess of leukaemia in Broome County, New York, particularly in the Town of Union. Surveillance of cancer incidence data indicates that a large proportion of these cases occurred among males ages 65 and older. Shoe and boot manufacturing has been the largest single industry in this area throughout much of the past century. Occupational studies from Europe suggest a link between leukaemia and employment in the shoe and boot manufacturing industry. However, researchers have not found a positive association between leukaemia and employment in the shoe industry among workers in the United States. METHODS: A matched case-control study was conducted to investigate the association between leukaemia incidence among males 65 and older and employment in the shoe and boot manufacturing industry. Thirty-six cases of leukaemia occurring between 1981–1990; among males age 65 and older; residing in the town of Union met the study case criteria. Death certificates were obtained for each of the cases. These were matched to death certificates of 144 controls on date of death and date of birth +/- 1 year. Death certificates were then examined to determine the employer and occupation of each study subject. Conditional logistic regression was used to determine the risk of leukaemia among those working in the industry. RESULTS: The risk of both leukaemia (OR = 1.47; 95% CI 0.70, 3.09) and acute myeloid leukaemia (OR = 1.19; 95% CI 0.33, 4.28) were elevated among those employed in the shoe and boot manufacturing industry, however neither was statistically significant. CONCLUSION: The results, though suggestive of an association between leukaemia and employment in the shoe and boot manufacturing industry, were not statistically conclusive due mainly to limited study power. Several additional limitations may also have prevented the observance of more conclusive findings. Better exposure assessment, information on length of exposure and types of job held, control of confounding factors and information on chemicals used by this company would strengthen any future investigation

Costs of Change, Political Polarization, and Re-Election Hurdles

We develop and study a two-period model of political competition with office- and policymotivated candidates, in which (i) changes of policies impose costs on all individuals and (ii) such costs increase with the magnitude of the policy change. We show that there is an optimal positive level of costs of change that minimizes policy polarization and maximizes welfare. One interpretation of this finding is that societies with intermediate levels of conservatism achieve the highest welfare and the lowest polarization levels. We apply our model to the design of optimal re-election hurdles. In particular, we show that raising the vote-share needed for re-election above 50% weakly reduces policy polarization and tends to increase welfare. Furthermore, we identify circumstances where the optimal re-election hurdle is strictly larger than 50%

The demand and supply of favours in dynamic relationships

We characterise the optimal demand and supply of favours in a dynamic principal-agent model of joint production, in which heterogenous project opportunities arrive stochastically and are publicly observed upon arrival, utility from these projects is non-transferable and commitment to future production is limited. Our results characterise the optimal dynamic contract, and we establish that the principal’s supply of favours (the production of projects that benefit the agent but not the principal) is backloaded, that the principal’s demand for favours (the production of projects that benefit the principal but not the agent) is frontloaded, and that the production of projects is ordered by their comparative advantage, that is, by their associated efficiency in extracting (for demanded projects) and providing (for supplied projects) utility to the agent. Furthermore, we\nprovide an exact construction of the optimal contract when project opportunities follow a Markov process