Three Essays on Health and Environmental Economics: Applications of Spatial Econometrics and Spatial Analysis

Spatial interaction and the locational structure between observations play key roles in the field of econometrics for both cross-sectional and panel data analysis. Compared to a non-spatial econometric model, a spatial model relaxes the assumption of independency in observations. This research applies spatial and non-spatial econometrics in three different fields of applied economics: (1) drinking water and air quality violations impacts on lung and bronchus cancer incidence in the contiguous United States (U.S.); (2) spillover effects of non-pharmaceutical interventions (NPIs) on COVID-19 cases across the contiguous U.S. counties; and (3) urbanization impacts on carbon dioxide (CO2) emissions in selected 119 countries. In Chapter 2, ordinary least squares (OLS) and Spatial Durbin Model (SDM) are applied to data from 48 states plus Washington D.C. in the contiguous U.S. for the period of 2006-2016 to examine the impacts of population-level exposures to environmental quality standards non-compliance on the lung and bronchus cancer incidence. The SDM reveals statistically significant impacts of population-level exposures to violations of environmental pollution standards on lung and bronchus cancer incidence. While impacts are statistically significant (direct effect for water and total effect for air), they are small relative to smoking behavior. Example calculations show that a 10% reduction in population exposure rate to drinking water quality violations across the state of Oklahoma results in a decrease of five cancer cases annually with an estimated annual monetary benefit of $20.6 million. A 10$24.7 million annual monetary benefit in Utah and three-neighboring states. Chapter 3 examines the spatial spillover effects of NPIs policies on reductions of COVID-19 cases in the contiguous U.S. Using annual cross-sectional data for the year 2020, I apply a spatial Durbin model (SDM) to find statistically significant spillover effects from stay-at-home mandatory orders and mask mandates on COVID-19 cases per 100,000 people. Nationally, on average, 4 cases per 100,000 people can be reduced within the mandate county while an additional 9 cases per 100,000 people can be reduced in 6-nearest neighboring counties as the spillover effect from implementing a mask mandate policy for a month. On the other hand, the direct effect of mandatory stay-at-home orders is 15 cases per 100,000 people while the spillover (indirect) effect is 38 cases per 100,000 people when this NPI is implemented for one month. Thus, mandatory stay-at-home orders show a greater impact on reducing COVID-19 case rates than mask mandates. Further, the indirect effect in neighboring counties is larger than the direct effect for both NPI policies, showing the importance of accounting for spillover effects when determining NPI policy benefits. Based on the SDM model, an example of mask mandate and mandatory stay-at-home policies in Powder River County in Montana (as a mandate state) with three neighboring non-mandate counties in the state of Wyoming is examined. A month-long implementation of mask mandate, stay-at-home order, and both these policies contributes $0.01 million,$0.04 million, and $0.05 million of direct benefits, respectively from reduced COVID-19 costs in Powder River County in the state of Montana. The spillover benefits of about$0.70 million, $2.95 million, and$3.65 million, respectively are estimated based on reduced COVID-19 costs in the three neighboring counties of Wyoming (Sheridan, Campbell, Crook) from one-month implementation of public mask mandate, mandatory stay-at-home orders and both these policies in Powder River County in the state of Montana. Most of this benefit is the result of reduced hospitalizations in the states of Montana and Wyoming. The results of this research will help to design cost-efficient interventions to tackle future pandemics. Finally, Chapter 4 relates urbanization to greenhouse gases (GHG) emissions based on data from 105 countries in 1990-2018. Using pooled mean group (PMG) estimation technique, significant nonlinear relationships are found between urbanization and both carbon dioxide (CO2) intensity and CO2 emissions. For CO2 intensity, urbanization impacts hit a turning point at 59.16 percent such that urbanization prior to this percentage increases CO2 intensity while rates of urbanization rate above this percentage decrease CO2 intensity. No such turning point is observed for CO2 emissions. Based on the PMG model, renewable energy consumption significantly reduces both CO2 intensity and emissions. However, at a given rate of renewable energy consumption, urbanization only reduces CO2 emissions. Empirical results from this study highlight the importance of global scale action on urban buildings and transportation to reduce GHG emissions in both developing and under-developed countries with technical support from developed economies

Estimation of the Optimal Forest Rotation of Sissoo (Dalbergia sissoo) Plantations in Bangladesh

Using various criteria, the paper estimates the optimal rotation period for Sissoo (Dalbergia sissoo) plantations in Bangladesh. Plantations data were collected during 1999-2000 from purposively selected Forest Divisions aged at least 5 years. Under the present management system, mode of marketing, market mechanism and all economic criteria for Bangladesh as a whole, the optimal rotation of Sissoo tree is estimated to be at 8 years for fuel wood and 12 or 13 years for timber. If the Mean Annual Increment (MAI) is considered as rotation criterion, rotation period as 6 years for fuel wood and 11 to 13 years for timber are suggested. The elimination rates varied from 10% to 72% depending on plantation year, location, biotic interference and sissoo mortality. Irrespective of locations, it was revealed that the highest NPV (Tk 6395599), IRR (85%), B/C ratio (6.57), and  (Tk 2608031) start from the 13 year-old plantation. Keywords: Sissoo, Optimal rotation, Forest management, Bangladesh

Investment Performance of Islamic Bank: An Empirical Study

The article undertakes an empirical study on investment of Islamic Bank. The aim of the study is to examine and evaluate the performance of investment of Islamic Bank for the time period 2005-2009 in comparison with a conventional Bank. Several financial ratios are applied for this purpose. For the empirical investigation data has been collected from Islami Bank Bangladesh Limited and Mutual Trust Bank Limited. The study found that Islami Bank Bangladesh Limited (IBBL) is relatively less profitable and less risky (more solvent) during 2005-2009 compared to a conventional bank (Mutual Trust Bank Limited), however, it is improving considerably over time indicating convergence with the performance of the conventional banks

How does Tourist Value the Nature-based Tourism Sites in North-eastern Bangladesh? How does the Tourist Value the Nature-based Tourism Sites in North-eastern Bangladesh?

Abstract: The underlying goal of this paper is to estimate the willingness to pay for different nature-based tourism sites in Sreemangal-Kamalganj area of Bangladesh. Primarily, a semistructured questionnaire survey was carried out during the period 4 to