A study of stock market linkages between the US and frontier countries

My dissertation investigates the financial linkages and transmission of economic shocks between the US and the smallest emerging markets (frontier markets). The first chapter sets up an empirical model that examines the impact of US market returns and conditional volatility on the returns and conditional volatilities of twenty-one frontier markets. The model is estimated via maximum likelihood; utilizes the GARCH model of errors, and is applied to daily country data from the MSCI Barra. We find limited, but statistically significant exposure of Frontier markets to shocks from the US. Our results suggest that it is not the lagged US market returns that have impact; rather it is the expected US market returns that influence frontier market returns The second chapter sets up an empirical time-varying parameter (TVP) model to explore the time-variation in the impact of mean US returns on mean Frontier market returns. The model utilizes the Kalman filter algorithm as well as the GARCH model of errors and is applied to daily country data from the MSCI Barra. The TVP model detects statistically significant time-variation in the impact of US returns and low, but statistically and quantitatively important impact of US market conditional volatility. The third chapter studies the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model. The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns. Both the systematic risk and risk premium are time-varying in our model. We also incorporate own country variances as additional determinants of Frontier country returns. Our results suggest statistically significant impact of both world and own country risk in explaining Frontier country returns. Time-variation in the world risk premium is also found to be statistically significant for most Frontier market returns. However, own country risk is found to be quantitatively more important.

Treefrogs in Forested Swamps at the La Selva Biological Station: Assemblage Variation through Space and Time

Swamp-breeding treefrogs form conspicuous components of many tropical forest sites, yet remain largely understudied. The La Selva Biological Station, a rainforest reserve in Costa Rica, harbors a rich swamp-breeding treefrog fauna that has been studied in only one of the many swamps found at the site. To understand if the species composition of treefrogs at La Selva varies over space or time, frogs were censused in 1982-83, 1994-95, 2005 and 2011 at two ponds located in the reserve. Data on treefrog habitat utilization were also collected. Species composition varied spatially only in 2011. Temporal variation was observed at both ponds for all groups tested. Habitat use varied among species and between swamps. The pattern of variation suggests that temporally dynamic systems such as temporary Neotropical forest swamps will converge and diverge in species composition over time.

Geochemical variation among small eruptive centers in the central SVZ of the Andes: An evaluation of subduction, mantle and crustal influences

Subduction zone magmatism is an important and extensively studied topic in igneous geochemistry. Recent studies focus on from where arc magmas are generated, how subduction components (fluids or melts) are fluxed into the source of the magmas, and whether or how the subduction components affect partial melting processes beneath volcanic arcs at convergent boundaries. ^ At 39.5°S in the Central Southern Volcanic Zone of the Andes, Volcano Villarrica is surrounded by a suite of Small Eruptive Centers (SEC). The SECs are located mostly to the east and northeast of the stratovolcano and aligned along the Liquine-Ofqui Fault Zone, the major fracture system in this area. Former studies observed the geochemical patterns of the SECs differ distinctively from those of V. Villarrica and suggested there may be a relationship between the compositions of the volcanic units and their edifice sizes. This work is a comprehensive geochemical study on the SECs near V. Villarrica, using a variety of geochemical tracers and tools including major, trace and REE elements, Li-Be-B elements, Sr-Nd-Pb isotopes and short-lived isotopes such as U-series and 10Be. In this work, systematic differences between the elemental and isotopic compositions of the SECs and those of V. Villarrica are revealed and more importantly, modeled in terms of magmatic processes occurring at continental arc margins. Detailed modeling calculations in this work reconstruct chemical compositions of the primary magmas, source compositions, compositions and percentages of different subduction endmembers mixed into the source, degrees of partial melting and different time scales of the SECs and V. Villarrica, respectively. Geochemical characteristics and possible origins of the two special SECs—andesitic Llizan, with crustal signatures, and Rucapillan, to the northwest toward the trench, are also discussed in this work. ^

Investigating the origin of PM2.5 in Baltimore using highly time-resolved organic molecular markers measured during the Baltimore PM-supersite

The detailed organic composition of atmospheric fine particles with an aerodynamic diameter smaller than or equal to 2.5 micrometers (PM2.5) is an integral part of the knowledge needed in order to fully characterize its sources and transformation in the environment. For the study presented here, samples were collected at 3-hour intervals. This high time resolution allows gaining unique insights on the influence of short- and long-range transport phenomena, and dynamic atmospheric processes. A specially designed sequential sampler was deployed at the 2002-2003 Baltimore PM-Supersite to collect PM2.5 samples at a 3-hourly resolution for extended periods of consecutive days, during both summer and winter seasons. Established solvent-extraction and GC-MS techniques were used to extract and analyze the organic compounds in 119 samples from each season. Over 100 individual compounds were quantified in each sample. For primary organics, averaging the diurnal ambient concentrations over the sampled periods revealed ambient patterns that relate to diurnal emission patterns of major source classes. Several short-term releases of pollutants from local sources were detected, and local meteorological data was used to pinpoint possible source regions. Biogenic secondary organic compounds were detected as well, and possible mechanisms of formation were evaluated. The relationships between the observed continuous variations of the concentrations of selected organic markers and both the on-site meteorological measurements conducted parallel to the PM2.5 sampling, and the synoptic patterns of weather and wind conditions were also examined. Several one-to-two days episodes were identified from the sequential variation of the concentration observed for specific marker compounds and markers ratios. The influence of the meteorological events on the concentrations of the organic compounds during selected episodes was discussed. It was observed that during the summer, under conditions of pervasive influence of air masses originated from the west/northwest, some organic species displayed characteristics consistent with the measured PM2.5 being strongly influenced by the aged nature of these long-traveling background parcels. During the winter, intrusions from more regional air masses originating from the south and the southwest were more important.

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

Variation and Uncertainty in Evaporation from a Subtropical Estuary: Florida Bay

Variation and uncertainty in estimated evaporation was determined over time and between two locations in Florida Bay, a subtropical estuary. Meteorological data were collected from September 2001 to August 2002 at Rabbit Key and Butternut Key within the Bay. Evaporation was estimated using both vapor flux and energy budget methods. The results were placed into a long-term context using 33 years of temperature and rainfall data collected in south Florida. Evaporation also was estimated from this long-term data using an empirical formula relating evaporation to clear sky solar radiation and air temperature. Evaporation estimates for the 12-mo period ranged from 144 to 175 cm yr21, depending on location and method, with an average of 163 cm yr21 (6 9%). Monthly values ranged from 9.2 to 18.5 cm, with the highest value observed in May, corresponding with the maximum in measured net radiation. Uncertainty estimates derived from measurement errors in the data were as much as 10%, and were large enough to obscure differences in evaporation between the two sites. Differences among all estimates for any month indicate the overall uncertainty in monthly evaporation, and ranged from 9% to 26%. Over a 33-yr period (1970–2002), estimated annual evaporation from Florida Bay ranged from 148 to 181 cm yr21, with an average of 166 cm yr21. Rainfall was consistently lower in Florida Bay than evaporation, with a long-term average of 106 cm yr21. Rainfall considered alone was uncorrelated with evaporation at both monthly and annual time scales; when the seasonal variation in clear sky radiation was also taken into account both net radiation and evaporation were significantly suppressed in months with high rainfall.

Seasonal and spatial variation in the stable isotopic composition (δ18O and δD) of precipitation in south Florida

Precipitation data collected from five sites in south Florida indicate a strong seasonal and spatial variation in δ18O and δD, despite the relatively limited geographic coverage and low-lying elevation of each of the collection sites. Based upon the weighted-mean stable isotope values, the sites were classified as coastal Atlantic, inland, and lower Florida Keys. The coastal Atlantic sites had weighted-mean values of δ18O and δD of −2.86‰ and −12.8‰, respectively, and exhibited a seasonal variation with lower δ18O and δD values in the summer wet-season precipitation (δ18O = −3.38‰, δD = −16.5‰) as compared to the winter-time precipitation (δ18O = −1.66‰, δD = −3.2‰). The inland site was characterized as having the highest d-excess value (+13.3‰), signifying a contribution of evaporated Everglades surface water to the local atmospheric moisture. In spite of its lower latitude, the lower Keys site located at Long Key had the lowest weighted-mean stable isotope values (δ18O = −3.64‰, δD = −20.2‰) as well as the lowest d-excess value of (+8.8‰). The lower δD and δ18O values observed at the Long Key site reflect the combined effects of oceanic vapor source, fractionation due to local precipitation, and slower equilibration of the larger raindrops nucleated by a maritime aerosol. Very low δ18O and δD values (δ18O < −6‰, δD < −40‰) were observed just prior to the passage of hurricanes from the Gulf of Mexico as well as during cold fronts from the north-west. These results suggest that an oceanic vapor source region to the west, may be responsible for the extremely low δD and δ18O values observed during some tropical storms and cold fronts.

Space-for-Time Substitution Works in Everglades Ecological Forecasting Models

Space-for-time substitution is often used in predictive models because long-term time-series data are not available. Critics of this method suggest factors other than the target driver may affect ecosystem response and could vary spatially, producing misleading results. Monitoring data from the Florida Everglades were used to test whether spatial data can be substituted for temporal data in forecasting models. Spatial models that predicted bluefin killifish (Lucania goodei) population response to a drying event performed comparably and sometimes better than temporal models. Models worked best when results were not extrapolated beyond the range of variation encompassed by the original dataset. These results were compared to other studies to determine whether ecosystem features influence whether space-for-time substitution is feasible. Taken in the context of other studies, these results suggest space-for-time substitution may work best in ecosystems with low beta-diversity, high connectivity between sites, and small lag in organismal response to the driver variable.

Space-for-Time Substitution Works in Everglades Ecological Forecasting Models

Space-for-time substitution is often used in predictive models because long-term time-series data are not available. Critics of this method suggest factors other than the target driver may affect ecosystem response and could vary spatially, producing misleading results. Monitoring data from the Florida Everglades were used to test whether spatial data can be substituted for temporal data in forecasting models. Spatial models that predicted bluefin killifish (Lucania goodei) population response to a drying event performed comparably and sometimes better than temporal models. Models worked best when results were not extrapolated beyond the range of variation encompassed by the original dataset. These results were compared to other studies to determine whether ecosystem features influence whether space-for-time substitution is feasible. Taken in the context of other studies, these results suggest space-fortime substitution may work best in ecosystems with low beta-diversity, high connectivity between sites, and small lag in organismal response to the driver variable.

Size-based variation in intertissue comparisons of stable carbon and nitrogen isotopic signatures of bull sharks (Carcharhinus leucas) and tiger sharks (Galeocerdo cuvier)

Stable isotopes are important tools for understanding the trophic roles of elasmobranchs. However, whether different tissues provide consistent stable isotope values within an individual are largely unknown. To address this, the relationships among carbon and nitrogen isotope values were quantified for blood, muscle, and fin from juvenile bull sharks (Carcharhinus leucas) and blood and fin from large tiger sharks (Galeocerdo cuvier) collected in two different ecosystems. We also investigated the relationship between shark size and the magnitude of differences in isotopic values between tissues. Isotope values were significantly positively correlated for all paired tissue comparisons, but R2 values were much higher for δ13C than for δ15N. Paired differences between isotopic values of tissues were relatively small but varied significantly with shark total length, suggesting that shark size can be an important factor influencing the magnitude of differences in isotope values of different tissues. For studies of juvenile sharks, care should be taken in using slow turnover tissues like muscle and fin, because they may retain a maternal signature for an extended time. Although correlations were relatively strong, results suggest that correction factors should be generated for the desired study species and may only allow coarse-scale comparisons between studies using different tissue types.

Investigating the origin of PM2.5 in Baltimore using highly time-resolved organic molecular markers measured during the Baltimore PM-supersite

The detailed organic composition of atmospheric fine particles with an aerodynamic diameter smaller than or equal to 2.5 micrometers (PM 2.5) is an integral part of the knowledge needed in order to fully characterize its sources and transformation in the environment. For the study presented here, samples were collected at 3-hour intervals. This high time resolution allows gaining unique insights on the influence of short- and long-range transport phenomena, and dynamic atmospheric processes. A specially designed sequential sampler was deployed at the 2002-2003 Baltimore PM Supersite to collect PM2.5 samples at a 3-hourly resolution for extended periods of consecutive days, during both summer and winter seasons. Established solvent-extraction and GC-MS techniques were used to extract and analyze the organic compounds in 119 samples from each season. Over 100 individual compounds were quantified in each sample. For primary organics, averaging the diurnal ambient concentrations over the sampled periods revealed ambient patterns that relate to diurnal emission patterns of major source classes. Several short-term releases of pollutants from local sources were detected, and local meteorological data was used to pinpoint possible source regions. Biogenic secondary organic compounds were detected as well, and possible mechanisms of formation were evaluated. The relationships between the observed continuous variations of the concentrations of selected organic markers and both the on-site meteorological measurements conducted parallel to the PM2.5 sampling, and the synoptic patterns of weather and wind conditions were also examined. Several one-to-two days episodes were identified from the sequential variation of the concentration observed for specific marker compounds and markers ratios. The influence of the meteorological events on the concentrations of the organic compounds during selected episodes was discussed. It was observed that during the summer, under conditions of pervasive influence of air masses originated from the west/northwest, some organic species displayed characteristics consistent with the measured PM2.5 being strongly influenced by the aged nature of these long-traveling background parcels. During the winter, intrusions from more regional air masses originating from the south and the southwest were more important.