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In the recent past, Zambia has increased its external borrowings significantly after reaching the Heavily Indebted Poor Countries (HIPC) completion point. The Zambian government has been on an ambitious borrowing spree with the intent that most of these funds would be channelled towards building and maintenance of key national infrastructure including roads and construction of new airports. This study undertook to answer the question, does increasing external debt affect growth of a nation’s economy? The thesis commenced an econometric study between the years 1980 to 2015 using publicly available data premised on the neoclassical economic growth model. The findings from this investigation show that shocks to external debt negatively impact the economic output of Zambia which is proxied by the Gross Domestic Product (GDP). Conversely, it was found that external debt stock could not reliably forecast future economic growth for the nation, a finding which in itself provides an area of further investigations. These research findings and recommendations make it clear that Zambia requires a comprehensive debt contraction and management framework to avoid the vagaries of short-term decisions which may not always be premised on sound economic thinking.

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The purpose of this study was to examine the economic implications of a rapid population growth on Nigeria's economic development. It was particularly interesting to study the relationship, because at the present Nigeria is making some economic progress while undergoing a demographic transition. Apparently, despite the acceptable growth of the national income, the growth of the per capita output has not been encouraging. This output growth must have been hampered by the rather rapid population growth in Nigeria. The neoclassical growth theory was basically employed to explain the growth of output in the economy in terms of both capital and labor inputs. For instance, the short-run impact of a possible fertility decline could lead to increased savings capability, possible through the curtailment of the consumption of the dependent population. The long-run impact, on the other hand, could be the opportunity to increase the rate of structural transformation needed to raise labor productivity and personal income in the economy. The model revealed that economic growth rates in Nigeria have been declining with rising affluence. It is more likely that such a slowing would arise from the population pressure and resource limitation rather than from the propensity to invest.

The study was undertaken in response to a prediction by the Virginia Department of Forestry (VDOF) that current harvest levels cannot be sustained into the future given an increasing growth to removal insufficiency throughout the state of Virginia. The purpose of the study is to determine how market signals, land and owner characteristics, and owner preferences affect landowners' decisions concerning their forestland. Particular emphasis is placed on the effects of absenteeism and land fragmentation on landowner behavior. Such information is important for targeting policies that will successfully maintain commercial timber levels throughout the state. / Master of Science

Natural disasters have always been and probably always will be a problem for humans and their settlements. With global warming seemingly increasing the frequency and strength of the climate related disasters, and more and more people being settled in urban centers, the ability to model and predict damage is more important than ever.The aim of this thesis has been to model and analyze a broad range of disaster types and the kind of impact that they have. By modeling damage indices for disaster types as different as hurricanes and volcanic eruptions, the thesis helps with understanding both similarities and differences between how disasters work and what impact they have on societies experiencing them. The thesis comprises four different chapters in addition to this introduction, where all of them include modeling of one or more types of natural disasters and their impact on real world scenarios such as local budgets, birth rates and economic growth.Chapter 2 is titled “Natural Disaster Damage Indices Based on Remotely Sensed Data: An Application to Indonesia". The objective was to construct damage indices through remotely sensed and freely available data. In short, the methodology exploits that one can use nightlight data as a proxy for economic activity. Then the nightlights data is matched with remote sensing data typically used for natural hazard modeling. The data is then used to construct damage indices at the district level for Indonesia, for different disaster events such as floods, earthquakes, volcanic eruptions and the 2004 Christmas Tsunami. The chapter is forthcoming as a World Bank Policy Research Paper under Skoufias et al. (2017a).Chapter 3 utilizes the indices from Chapter 2 to showcase a potential area of use for them. The title is “The Reallocation of District-Level Spending and Natural Disasters: Evidence from Indonesia" and the focus is on Indonesian district-level budgets. The aim was to use the modeled intensity from Chapter 2 to a real world scenario that could affect policy makers. The results show that there is evidence that some disaster types cause districts to move costs away from more general line items to areas such as health and infrastructure, which are likely to experience added pressure due to disasters. Furthermore, volcanic eruptions and the tsunami led to less investment into more durable assets both for the year of the disaster and the following year. This chapter is also forthcoming as a World Bank Policy Research Paper under Skoufias et al. (2017b).The fourth chapter, titled “Urban Global Impact of Earthquakes from 2004 through 2013", is a short chapter focusing on earthquake damage and economic growth. This chapter is an expansion of the index used in the previous two chapters, where we use global data instead of focusing on a single country. Using a comprehensive remotely sensed dataset of contour mapsof global earthquakes from 2004 through 2013 and utilizing global nightlights as an economic proxy we model economic impact in the year of the quakes and the year after. Overall, it is shown that earthquakes negatively impact local urban light emissions by 0.7 percent.Chapter 5 is named “A Whirlwind Romance: The Effect of Hurricanes on Fertility in Early 20th Century Jamaica" and deviates from the prior chapters in that it is a historical chapter that looks at birth rates in the early 1900s. The goal was to use the complete and long-term birth database for Jamaica and match this with hurricane data to check fertility rates. We create a hurricane destruction index derived from a wind speed model that we combine with data on more than 1 million births across different parishes in Jamaica. Analyzing the birth rate following damaging hurricanes, we find that there is a strong and significant negative effect of hurricane destruction on the number of births. / Natural disasters have always been and probably always will be a problem for humans and their settlements. With global warming seemingly increasing the frequency and strength of the climate related disasters, and more and more people being settled in urban centers, the ability to model and predict damage is more important than ever.The aim of this thesis has been to model and analyze a broad range of disaster types and the kind of impact that they have. By modeling damage indices for disaster types as different as hurricanes and volcanic eruptions, the thesis helps with understanding both similarities and differences between how disasters work and what impact they have on societies experiencing them. The thesis comprises four different chapters in addition to this introduction, where all of them include modeling of one or more types of natural disasters and their impact on real world scenarios such as local budgets, birth rates and economic growth.Chapter 2 is titled “Natural Disaster Damage Indices Based on Remotely Sensed Data: An Application to Indonesia". The objective was to construct damage indices through remotely sensed and freely available data. In short, the methodology exploits that one can use nightlight data as a proxy for economic activity. Then the nightlights data is matched with remote sensing data typically used for natural hazard modeling. The data is then used to construct damage indices at the district level for Indonesia, for different disaster events such as floods, earthquakes, volcanic eruptions and the 2004 Christmas Tsunami. The chapter is forthcoming as a World Bank Policy Research Paper under Skoufias et al. (2017a).Chapter 3 utilizes the indices from Chapter 2 to showcase a potential area of use for them. The title is “The Reallocation of District-Level Spending and Natural Disasters: Evidence from Indonesia" and the focus is on Indonesian district-level budgets. The aim was to use the modeled intensity from Chapter 2 to a real world scenario that could affect policy makers. The results show that there is evidence that some disaster types cause districts to move costs away from more general line items to areas such as health and infrastructure, which are likely to experience added pressure due to disasters. Furthermore, volcanic eruptions and the tsunami led to less investment into more durable assets both for the year of the disaster and the following year. This chapter is also forthcoming as a World Bank Policy Research Paper under Skoufias et al. (2017b).The fourth chapter, titled “Urban Global Impact of Earthquakes from 2004 through 2013", is a short chapter focusing on earthquake damage and economic growth. This chapter is an expansion of the index used in the previous two chapters, where we use global data instead of focusing on a single country. Using a comprehensive remotely sensed dataset of contour mapsof global earthquakes from 2004 through 2013 and utilizing global nightlights as an economic proxy we model economic impact in the year of the quakes and the year after. Overall, it is shown that earthquakes negatively impact local urban light emissions by 0.7 percent.Chapter 5 is named “A Whirlwind Romance: The Effect of Hurricanes on Fertility in Early 20th Century Jamaica" and deviates from the prior chapters in that it is a historical chapter that looks at birth rates in the early 1900s. The goal was to use the complete and long-term birth database for Jamaica and match this with hurricane data to check fertility rates. We create a hurricane destruction index derived from a wind speed model that we combine with data on more than 1 million births across different parishes in Jamaica. Analyzing the birth rate following damaging hurricanes, we find that there is a strong and significant negative effect of hurricane destruction on the number of births.

This study initially presents historical trends in both the capitalized value and market value of farmland in the eight states comprising the Corn Belt and Lake States production regions as defined by the USDA. An econometric analysis of annual real cash rents per acre prior to determining the capitalized value of farmland in the eight states is then conducted. Two distributed lag models were hypothesized. The comparison of regression results of these two distributed lag models indicates that current year real cash rent can be best explained by current year real net farm income, lagged real net farm income over a period of years, and real cash rent in the previous year. A spreadsheet simulation model is used to project capitalized farmland values in each state as well as regional averages over the 2012-2015 period. These projections reflect alternative assumptions regarding future trends in real net farm income at the state level as well as the rate on 10-year constant maturity U.S. government bonds to assess the potential sensitivity of capitalized farmland values under adverse economic conditions. The projected trends in capitalized farmland values under two alternative stress scenarios reflecting higher interest rates levels and lower net farm income levels indicates that capitalized farmland values are particularly sensitive to interest rate fluctuations since cash rent expectations of landlords are based on current and lagged historical profit performance.

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This dissertation conducted an extensive examination of dockless e-scooter dynamics using high-resolution trip data from Austin, Texas. Four studies were conducted to capture the multifaceted nature of e-scooter operations and demand. The first study aimed to identify and quantify the influence of contributing factors affecting e-scooter demand by partitioning the data by time period for weekdays and weekends. Utilizing a joint panel linear regression (JPLR) model, significant associations were observed between e-scooter demand and variables such as sociodemographic attributes, transportation infrastructure, land use, meteorological attributes, and situational factors. The second study shifted focus to shared e-scooter origin-destination (OD) flows in the urban region. By employing a joint binary logit-fractional split model, e-scooter OD flows were analyzed, emphasizing variations across distinct time periods and the subsequent implications for e-scooter deployment and rebalancing strategies. The third study delved into e-scooter utilization efficiency, introducing a time-to-book (TtB) measure. Through a Mixed Grouped Ordered Logit (MGOL) model, the study highlighted variations between regular and peak weeks, offering operators a chance to enhance fleet utilization. The final study addressed the broader context of the e-scooter industry, investigating the impact of the COVID-19 pandemic. By analyzing datasets spanning January 2019 through December 2021, a spatial approach illuminated changes in e-scooter demand patterns before, during, and after the pandemic, highlighting the effects of COVID-19-related factors and vaccine attributes on e-scooter trends. These collective insights from the four studies provide valuable contributions to understanding and enhancing e-scooter operations in urban landscapes

New Zealand experienced dramatic restructuring programs after the Labor party won the national elections in 1984. Deregulation of price controls, removal of the log export ban, and privatization of public assets were the main shocks to the forest sector. The purpose of this paper is to analyze the impacts of these reforms on wood and paper industry cost, production, and cost efficiency. Unlike previous work, the effects of privatization and deregulation are compared to determine which shock had the most influence on the forest sector. Results show that production decreased, total cost increased, and cost efficiency decreased after deregulation for the sector, and that deregulation was more significant than privatization for the wood and paper sectors. In particular, removal of the log export ban had the greatest impact, while privatization had little effect on industry production and cost. This suggests that countries with comparative advantages in wood processing who implement deregulation or privatization may suffer through a short term period of lower cost efficiency as the economy adjusts to higher input costs in those sectors. In New Zealand's case, the adjustments most likely affecting efficiency have been investments in new technologies, which require time to attain maximum efficiency. The results are contrary to other studies that have predicted increased efficiency as a result of privatization. / Ph. D.