This dissertation explores how cities achieve fiscal sustainability—the financial capacity to consistently meet basic public service responsibilities regardless of economic conditions. Two research questions arise from the interplay between the local economy and fiscal sustainability. First, what management tools do cities use to achieve fiscal sustainability given that economic conditions are largely outside their control? Second, what explains the variation among cities in the financial management tools used to achieve fiscal sustainability? The financial management tools of interest in this study are revenue diversity and the size of the fund balance. It is conjectured that financial management tools interact with each other prompting the tools to function as policy substitutes for each other. Cities achieve fiscal sustainability by strategically choosing budget-balancing tools appropriate to their economic conditions. The study utilizes a cross-state comparison from 351 Massachusetts municipal governments using panel data from 2000 to 2009 and 993 New York municipal governments using panel data from 2001 to 2010. Using theories of fiscal sustainability and revenue diversification, several models are proposed that test the interactive effects of fund balance size and revenue diversity on fiscal sustainability. The results from the empirical analyses show that cities use various financial management tools to stabilize spending during economic downturns. Cities pursue strategies that help maintain fiscal sustainability. Furthermore, it is discovered that interaction of fund balance and revenue diversity on municipal expenditures is stronger as the level of revenue diversity decreases. This interaction has a large effect during periods of economic downturns as compared to periods of economic growth.

A large number of studies have shown that both temperature and air pollution (eg, particulate matter and ozone) are associated with health outcomes. So far, it has received limited attention whether air pollution and temperature interact to affect health outcomes. A few studies have examined interactive effects between temperature and air pollution, but produced conflicting results. This thesis aimed to examine whether air pollution (including ozone and particulate matter) and temperature interacted to affect health outcomes in Brisbane, Australia and 95 large US communities. In order to examine the consistency across different cities and different countries, we used two datasets to examine interactive effects of temperature and air pollution. One dataset was collected in Brisbane City, Australia, during 1996-2000. The dataset included air pollution (PM10, ozone and nitrogen dioxide), weather conditions (minimum temperature, maximum temperature, relative humidity and rainfall) and different health outcomes. Another dataset was collected from the 95 large US communities, which included air pollution (ozone was used in the thesis), weather conditions (maximum temperature and dew point temperature) and mortality (all non-external cause mortality and cardiorespiratory mortality). Firstly, we used three parallel time-series models to examine whether maximum temperature modified PM10 effects on cardiovascular hospital admissions (CHA), respiratory hospital admissions (RHA), cardiovascular emergency visits (CEV), respiratory emergency visits (REV), cardiovascular mortality (CM) and non-external cause mortality (NECM), at lags of 0-2 days in Brisbane. We used a Poisson generalized additive model (GAM) to fit a bivariate model to explore joint response surfaces of both maximum temperature and particulate matter less than 10 μm in diameter (PM10) on individual health outcomes at each lag. Results show that temperature and PM10 interacted to affect different health outcomes at various lags. Then, we separately fitted non-stratification and stratification GAM models to quantify the interactive effects. In the non-stratification model, we examined the interactive effects by including a pointwise product for both temperature and the pollutant. In the stratification model, we categorized temperature into two levels using different cut-offs and then included an interactive term for both pollutant and temperature. Results show that maximum temperature significantly and positively modified the associations of PM10 with RHA, CEV, REV, CM and NECM at various lags, but not for CHA. Then, we used the above Poisson regression models to examine whether PM10 modified the associations of minimum temperature with CHA, RHA, CEV, REV, CM and NECM at lags of 0-2 days. In this part, we categorized PM10 into two levels using the mean as cut-off to fit the stratification model. The results show that PM10 significantly modified the effects of temperature on CHA, RHA, CM and NECM at various lags. The enhanced adverse temperature effects were found at higher levels of PM10, but there was no clear evidence for synergistic effects on CEV and REV at various lags. Three parallel models produced similar results, which strengthened the validity of these findings. Thirdly, we examined whether there were the interactive effects between maximum temperature and ozone on NECM in individual communities between April and October, 1987-2000, using the data of 60 eastern US communities from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS). We divided these communities into two regions (northeast and southeast) according to the NMMAPS study. We first used the bivariate model to examine the joint effects between temperature and ozone on NECM in each community, and then fit a stratification model in each community by categorizing temperature into three levels. After that, we used Bayesian meta-analysis to estimate overall effects across regions and temperature levels from the stratification model. The bivariate model shows that temperature obviously modified ozone effects in most of the northeast communities, but the trend was not obviously in the southeast region. Bayesian meta-analysis shows that in the northeast region, a 10-ppb increment in ozone was associated with 2.2% (95% posterior interval [PI]: 1.2%, 3.1 %), 3.1% (95% PI: 2.2%, 3.8 %) and 6.2 % (95% PI: 4.8%, 7.6 %) increase in mortality for low, moderate and high temperature levels, respectively, while in the southeast region, a 10-ppb increment in ozone was associated with 1.1% (95% PI: -1.1%, 3.2 %), 1.5% (95% PI: 0.2%, 2.8%) and 1.3% (95% PI: -0.3%, 3.0 %) increase in mortality. In addition, we examined whether temperature modified ozone effects on cardiovascular mortality in 95 large US communities between May and October, 1987-2000 using the same models as the above. We divided the communities into 7 regions according to the NMMAPS study (Northeast, Industrial Midwest, Upper Midwest, Northwest, Southeast, Southwest and Southern California). The bivariate model shows that temperature modified ozone effects in most of the communities in the northern regions (Northeast, Industrial Midwest, Upper Midwest, Northwest), but such modification was not obvious in the southern regions (Southeast, Southwest and Southern California). Bayesian meta-analysis shows that temperature significantly modified ozone effects in the Northeast, Industrial Midwest and Northwest regions, but not significant in Upper Midwest, Southeast, Southwest and Southern California. Nationally, temperature marginally positively modified ozone effects on cardiovascular mortality. A 10-ppb increment in ozone was associated with 0.4% (95% posterior interval [PI]: -0.2, 0.9 %), 0.3% (95% PI: -0.3%, 1.0%) and 1.6% (95% PI: 4.8%, 7.6%) increase in mortality for low, moderate and high temperature levels, respectively. The difference of overall effects between high and low temperature levels was 1.3% (95% PI: - 0.4%, 2.9%) in the 95 communities. Finally, we examined whether ozone modified the association between maximum temperature and cardiovascular mortality in 60 large eastern US communities during the warmer days, 1987-2000. The communities were divided into the northeast and southeast regions. We restricted the analyses to the warmer days when temperature was equal to or higher than the median in each community throughout the study period. We fitted a bivariate model to explore the joint effects between temperature and ozone on cardiovascular mortality in individual communities and results show that in general, ozone positively modified the association between temperature and mortality in the northeast region, but such modification was not obvious in the southeast region. Because temperature effects on mortality might partly intermediate by ozone, we divided the dataset into four equal subsets using quartiles as cut-offs. Then, we fitted a parametric model to examine the associations between temperature and mortality across different levels of ozone using the subsets. Results show that the higher the ozone concentrations, the stronger the temperature-mortality associations in the northeast region. However, such a trend was not obvious in the southeast region. Overall, this study found strong evidence that temperature and air pollution interacted to affect health outcomes. PM10 and temperature interacted to affect different health outcomes at various lags in Brisbane, Australia. Temperature and ozone also interacted to affect NECM and CM in US communities and such modification varied considerably across different regions. The symmetric modification between temperature and air pollution was observed in the study. This implies that it is considerably important to evaluate the interactive effect while estimating temperature or air pollution effects and further investigate reasons behind the regional variability.