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If localized knowledge spillovers are present in the university setting, higher rates of both start-ups and/or survival than in the broader economy would be observed in areas that are geographically proximate to the university. Using a fully-disclosed Quarterly Census of Employment and Wages for Texas for the years 1999:3-2006:2, this paper analyzes start-ups and exit rates for high-tech firms in Texas. We find that there is evidence that the presence of a research institution will affect the likelihood of technology start-ups. However, results suggest that geographic proximity to knowledge centers does not reduce hazard rates.

In the last few decades, many low/middle-income countries have opened their stock markets to foreigners and as the global economy continues to develop, poverty problems are becoming more and more serious. Most previous studies address the correlation between income inequality and economic development, and the relationship between stock market liberalization and economy growth. This paper analyzes the effect of stock market liberalization on income inequality. I use the Fixed Effect Model to explore the effects of liberalization while controlling some variables and providing a dummy variable. The results indicate that liberalization is associated with an exacerbated income inequality. The findings remain consistent when the model includes more control variables. These results show that low-income group receives less income shares after liberalization and high-income group receives more labor shares after liberalization.

Applied Microeconomics connects economics theories with detailed micro-level data in order to test the theoretical foundation. My dissertation is comprised of two chapters, which include four essays, in applied microeconomics to define new modeling approach for cultural behaviors and energy economics. The first chapter demonstrates a proper model to measure the effect of culture on economic behaviors, particularly on women’s decisions to work and fertility. This chapter shows that the best way to measure the cultural effect is assessing second-generation immigrants’ behaviors in a host country. Each immigrant has a specific culture that he/she brings to the host country and may transmit to his/her own second generation. Accordingly, economic behaviors of second-generation immigrants may depend on the historical characteristics of their ancestors’ heritage countries. This study indicates that an ancestor’s female labor force participation and total fertility rate are more likely to have an impact on the number of hours a woman works and the number of children she has in the United States. This study suggests that the second-generation immigrant who kept their heritage languages can represent their heritage cultures. This study proposes a general model for quantifying cultural impact on individuals’ decisions that can be extended for other economic and financial behaviors such as saving behaviors, risk behaviors, investment behaviors, and so on. The second chapter displays two main studies for modeling residential energy demand. The two main approaches in energy-economy modeling exist: disaggregated studies and aggregated studies. The first study of this chapter uses disaggregated approach for modeling residential energy demand. This study employs detailed data for the energy consumption of more than 560,000 households in the U.S. to focus on gas and electricity consumption by using main factors including socio-economics and demographics, building characteristics, location situation, temperature, and energy prices. The findings show that all five main factors such as social and demographical compositions, building characteristics, location, temperatures, and energy prices have impact on the household energy demand. The second study of this chapter uses aggregated approach for estimating residential energy demand. This study uses the static panel estimation approach as well as the dynamic panel estimation approach with several robustness checks to estimate residential electricity and gas demand. The results show the impact of socio-economic and demographic characteristics, building age, energy prices, and weather conditions on the residential energy demand at the state level for both static and dynamic estimation models. The results indicate that short-run own price elasticities are negative and lower than 1 for both electricity and gas demand, meanwhile only long-run own price elasticities for electricity demand are lower than 1. Next, this study proposes two alternative scenarios to reduce residential energy demand based on the most precise model. For every 10,000 dollars of per capita income in each state: (1) increasing residential electricity price by 1 cent per kWh and (2) decreasing average building age by 1%. In the first scenario, the findings indicate that annual residential electricity demand would decrease by 7.3% on average and in the second scenario, residential gas demand would decrease by an average of 15.8% annually. These proposed scenarios assist policymakers in optimizing decisions and investments to reduce residential energy consumption.

The objective of this dissertation is to explore how the observed bank characteristics (such as bank size, liquidity, capitalization) and the unobserved (random) bank characteristics generate heterogeneous response of bank loans to monetary policy shocks across the euro area countries and within the banks in each country. I use microeconomic panel data on 3,793 bank balance sheets of seventeen euro area member states. The data are drawn from BankScope on an annual basis, and they cover the period from 1999 to 2013. I also employ more harmonized macroeconomic data compared to what have been used in literature. I test for the differential reaction of the supply of bank loans by two ways: first, by following the traditional literature by employing a dynamic reduced-form model of bank loans and, second, by presenting a novel model specification known as the Random Coefficients Specification. The difference between this model and traditional model is that the parameters of this model are random rather than deterministic and, therefore, the random coefficients explain the variation in bank loans by not only the observed bank characteristics but also by the unobserved bank characteristics that are not covered in the traditional model. I measured the change in the monetary policy by the three-month euro interbank offered rate (EURIBOR). I used the most common bank characteristics that had been used in the literature (bank size, liquidity, and capitalization) in addition to another two factors: the return on average assets and the return on average equity. I estimated the traditional model by the ordinary least square in two ways: first, by pooling data without discriminating among country-specific characteristics, and second, by estimating the model separately for each of the four largest economies in the euro area (France, Germany, Italy, and Spain). In effort to gain greater insight of the heterogeneity within the countries, I extended the county-level analysis to include Austria, Belgium, Luxembourg, and the Netherlands. The random coefficients model is estimated for all banks in all euro area countries by applying the restricted maximum likelihood estimator. Several conclusions are reached in this study. The empirical estimation show that the random coefficients model appears to be more accurate to examine the pass-through of the monetary policy compared to the traditional model. Although the empirical outcomes of the two model seem similar in terms of the sign and the significance of the coefficients, the magnitude of the coefficients is greater for the random coefficients model. The bigger magnitude reflects the influence of the unobserved bank characteristics that are not reflected in the traditional model coefficients. Moreover, the findings demonstrate that the contractionary monetary policy reduces directly the supply of loans of the average bank in the euro area only in lags and all bank characteristics are found to affect the supply of loans only through the interaction with the monetary policy. The evidence support the argument that banks characteristics might be potential sources of the differential response of the banks to the monetary policy in the euro area. The effect of a restrictive monetary policy is found to be more pronounced for small, illiquid, poorly-capitalized, and less-profitable banks. These banks tend to react strongly to the raise in the policy rate by reducing their loans more than large, liquid, better-capitalized, and more-profitable banks. Although the lending channel is found to operate through all bank characteristics, liquidity emerges as the dominant device to distinguish the path-through of the monetary policy; it has the greater magnitude of its coefficients in the interaction terms with the monetary policy. Liquid banks are more likely to protect their lending activity by drawing on their liquid assets to compensate for the reduction in the deposits when monetary policy tightens. The total effect of the monetary policy on the growth rate of loans is calculated by performing a separate regression estimation as well as pooling estimation of the traditional model and by estimating the random model. It is found that the total effect varies across the euro area banks based on their characteristics and their typology. It is also found that the total effect are heterogeneous across countries. The average total effect of the monetary policy is found to be negative for small, poorly-capitalized, illiquid, and less-profitable banks, while it is positive for more-liquid and more-profitable banks. The total effect differs for large and better-capitalized banks based on the estimated model. Based on bank typology, it is found that loans of the cooperative banks decline when the monetary rate increases. Commercial and investment banks expand their lending activity, while the total effect for the real estate and mortgage and for the savings banks are found to differ based on the estimated model. The total effect of the monetary policy on bank loans across the euro area countries appears to be more harmonized and less sensitive to the model estimates. In the exception of German and Austrian banks that are affected negatively by the monetary policy, the other countries (France, Italy, Spain, the Netherlands, Luxembourg, and Belgium), surprisingly, respond positively to a tight monetary policy. On the country level, the findings provide evidence that the effectiveness of the monetary policy varies within the banks in each county. The evidence of Germany, France, Italy, and Austria supports that lending channel operates through all bank characteristics, but the potency of the monetary policy seems to be more affected by bank liquidity and to a lesser extent by bank size. However, the findings fail to provide evidence of the importance of liquidity and size in Spain. Lending channel seems to work weakly in Spanish banks, and it mainly operates through capitalization. In Belgium and the Netherlands, the importance is given to bank size, while liquidity is found to affect the behavior of bank loans in Luxembourg. Besides, it is found that bank profitability, specifically when it is measured by the return on average assets, is an important element in explaining the reaction of loan supply to monetary policy stance in all counters; loans of lower-profitable banks are more sensitive to the change in the policy rate than more-profitable banks.

Climate scientists, as well as the general public, have known for some time that carbon dioxide emissions are one of the leading contributors to global climate change. Despite this realization, environmental policy at all levels of government has been stymied by a lack of agreement on the nature and causes of CO2 emissions, as well as a lack of agreement on the proper policy instruments to implement. One of the reasons that carbon dioxide policy has failed to take root in the United States is because the nature of CO2 emissions are necessarily a more ‘macroeconomic’ problem, but the causes of CO2 emissions are the results of actions made on a more ‘microeconomic’ scale. The nexus between macroeconomic and microeconomic considerations serves as an impetus for the analysis of CO2 emissions presented here. The first chapter provides a view of CO2 emissions in the United States as a whole and discusses the causes and determinants of CO2 emissions. Unlike other analyses, though, this chapter uses data at the state-level; as opposed to national or international data which is the common aggregate. By focusing on state-level determinants I am able to define the driving forces behind CO2 emissions, and discuss policy implications that can be implemented at more microeconomic levels. The second chapter essentially breaks down the problem of CO2 emissions in the United States in an opposite way from chapter one. Instead of partitioning the United States, I disaggregate CO2 emissions and focus specifically on the most prevalent source of emissions, motor-gasoline. Using a structurally-founded Markov regime-switching model I find that emissions demand depends on the state of the economy. From this analysis I conclude that policies aimed at limiting CO2 emissions must be flexible enough to respond asymmetrically to changes in the macro economy. The culminating chapter in this dissertation employs the findings from the previous two chapters and models the United States in a dynamic stochastic general equilibrium model. Specifically, this chapter develops and simulates the effects of a dynamic carbon tax that is linked to changes in income and the price of energy. I find that consumer utility actually increases following the implementation of the tax, while carbon dioxide emissions decrease significantly.

The main objective of this paper is to study the effect of foreign direct investment on the level of output and its economic growth using recent growth theories and econometric techniques. Incorporating different groups of countries, we conducted cross sectional framework, panel data analysis, and dynamic panel estimation in the form of GMM estimation. We started the study by taking the work of Mankiw, Romer, and Weil (MRW, 1992) to test the validity of the Solow model in explaining income differences across countries. We constructed more comprehensive, revised, and extended data that covers the time period of 1980 to2010 and included better constructed groups of countries. We augmented the model with foreign direct investment and tested if it can further improve the results, and if it can be considered as a factor that helps explain income differences across countries. The issues of unconditional and conditional convergence are also considered in the study, with and without incorporating FDI. The results did not support the cross sectional framework for samples in MRW, nor the samples we constructed. Foreign Direct Investment is found to be positive, significant, growth enhancing engine, and important factor in explaining income differences across countries when panel estimation is employed. To form a comprehensive analysis, two types of GMM estimators were employed. The results provide more evidence of conditional convergence. The results support the validity of the Solow model or the augmented Solow model depending t on the samples that we investigated. The results also revealed that FDI positively affects the growth rate of income per capita, however, not significant for most of the samples. After all, there is no doubt that FDI is beneficial to the host economy and governments should work on their policies for their countries to be the destination of multinational corporations’ investment.

Real estate investment trusts (REITs) is a useful way to channel and structure the capital flow to the real estate market. Historical statistics indicate that the market capitalization of the REITs industry amounted to $600 billion at the end of 2012, representing an increase of 260 times since 1972. REITs have emerged as means for both institutional and small investors to hold, and invest in, diverse property assets after 1992. Like any other publically traded stocks, REITs are listed and traded on major stock exchanges, and most listed on NYSE. The study consists of three empirical essays. This fist essay provides a cross-sectional and time-series investigation of conditional and unconditional expected returns of real REITs index momentum portfolios against real estate property, big-cap stock small-cap stock, and bond index. The results indicate that REITs returns exhibit a higher correlation with up move of financial market, but a lower correlation in market downturns. REITs may possibly provide diversification benefits to multi-asset investment portfolios. The results also show that the returns of momentum portfolios are different from the NAREIT index, and display asymmetric volatility as well. The results of regressions also indicate that REITs return exhibit the greater sensitivity to large- and small-cap stock index, and less closely with those of bond and real estate index. The second essay explores the time-varying relationship between the return and risk for the portfolios in the U.S. real estate investment trust market. Three categories of REITs portfolios are formed based on the features of size, momentum and book-to-market portfolios. Under the conditional capital asset pricing model this essay uses the generalized autoregressive conditional heteroskedasticity in mean model by pooling the time-series and cross-sectional effects to estimate the conditional covariance with the market portfolio and test whether the dynamic conditional covariation predicts the time-varying expected. When restricting the slope to be the same within the REITs portfolios, the empirical results place a positive tradeoff between the return and predictable covariation in all REITs portfolios. On the other hand, relaxing to different slopes across the portfolio also conclude a positive return-risk tradeoff, besides the Winner portfolio in momentum portfolio shows a higher return at a lower covariance level. Furthermore, this paper examines the significance of intertemporal hedging demand in each REITs portfolio by extending the intertemporal capital asset pricing model with a set of prevailing macroeconomic variables and financial market indicators. This essay successfully examines the predictable movements that in return could be attributed to changes in covariances with innovations in macroeconomic variables and financial market indicators. Overall, the conclusive results show that innovations in inflation rate, de-trended short-term interest rate, Fama-French momentum factor, S&P/Case-Shiller home price index, and Barclay Capital long-term government/corporate bond index play a crucial role in hedging demand for the REITs portfolios. The third essay gives empirical evidence of time-series predictive capability of average variance and average correlation on the return of U.S. REITs market. Using an approach based on quantile regression, this essay explores the ability of average variance and average correlation to predict the distribution of REITs returns. The results indicate that lower average variance is significantly related to large future loss, whereas higher average variance is positively related to large gain. Finally, this essay studies investment trading strategies that condition on average variance and average correlation, and shows that the implementation of these strategies, by focusing on the tails of the return distribution of REITs returns, would generate a better performance than the benchmark return.

When determining the means by which to finance the operations of a local government, officials must choose methods that are appropriate to the tax base and do not place too large a burden on the population. One method that seems favorable from this standpoint is the hotel occupancy tax because it is supposed to fall on non-residents. There is some question, however, about whether such a tax might have a negative impact for localities that boast a large tourism industry. To date, most of the literature dealing with hotel taxes and their effect on the lodging industry is focused on the effect of the tax on resort hotels. A second group of hotels that have not been studied as thoroughly are hotels that exist in an area where there are many separate taxing jurisdictions that are adjacent to each other. Hotels in such an area may be faced with different tax rates depending on which jurisdiction they belong to. This thesis seeks to determine whether imposing a hotel tax in such an area would be detrimental to the lodging industry in the jurisdictions with a higher tax. To do this, the hotel industry in the Dallas-Fort Worth Metroplex is analyzed using two-stage least squares and fixed effects models to determine the elasticity of demand for hotel rooms. Although there are some issues with the data that is available for use, the results indicate that imposing a tax on hotel rooms does not have a significant impact on the industry.

Hurricane Katrina forced the evacuation of an estimated 130,000 persons to Houston, TX, causing its population to increase by 3% virtually overnight. Most of these evacuees were younger and less-educated than existing residents and remained in the Houston area for at least a year. The first objective of this dissertation is to estimate the effect of this massive in-migration on workers’ earnings in non-tradable goods industries in the Houston Metropolitan Statistical Area (MSA). Using establishment-level data from the Quarterly Census of Employment and Wages (QCEW) and gross sales and use tax receipts from the Texas Comptroller of Public Accounts, the study compares relative earnings per worker within the non-traded goods industries in the Houston and Dallas-Fort Worth MSAs before and after the Katrina-induced in-migration. Unlike previous studies, this study controls for the influence of an increase in the demand for local goods and services on the demand for labor in normally non-tradable goods and services activities. The study finds evidence that the average payroll per employee in the low-skill non-tradable industries decreased by 3.0% in the Houston MSA relative to the Dallas-Fort Worth MSA as a result of the Katrina-induced shift in labor supply. The study finds no evidence of any effect in the set of high-skill non-tradable industries. The findings also suggest that the failure to control for demand-side influences confounds this effect and severely underestimates the supply-side effect on wages. The second objective of this dissertation is to estimate the possible damage that a natural disaster of the magnitude of Hurricane Katrina could cause in the Houston MSA. Using Census-Track and QCEW data, this study estimates the expected damage, payroll loss, and expected number of affected employees that could be sustained by the Houston MSA. The storm surge analysis is conducted using GIS and the hurricane-related damage is estimated using HAZUS-MH. The study points out the advantages of using GIS to analyze the expected storm surge damage estimation. The advantage of using the HAZUS-MH is that it provides results for a county-wise breakdown in terms of affected essential facilities and debris by tonnage. Also, it provides expected building damage by occupancy type and building type.

This research is empirical study for technology industry in Texas. The previous researches for firm performance mainly focus on the entry and exit method. However, we approach to firm entry and exit using the knowledge spillovers differently from previous studies. We interpret a proxy of knowledge spillover by investigating the relationship between the total amount of external funding and number of entrants in technology industry. The objective of this study is to identify how the geographic distribution of the knowledge center affects the closely existed technology firm's performance in the market. We focus on the relationship between entry and technology spillover as well as the characteristics of the base county and neighbor counties. We employ a count data model, specifically a Poisson model, to measure the number of entrants as a proxy of knowledge spillovers from knowledge centers. The Poisson regression results fully provide the impacts of external funding relative to distance from knowledge centers and county's characteristics on entrants in technology industry.

The hearing loss population has been increasing consistently, yet the market rate of hearing aid penetration has remained relatively stagnant. This research is an in-depth study of the risk factors associated with hearing impairment using patient profiles and audiograms. Furthermore, it explores how demographic and socio-economic factors influence consumers' purchasing decisions and analyzes the impact of technology on the hearing aid prices. The study consists of three empirical essays. The first essay uses a probit model with marginal effect to determine the causes of hearing loss. Findings indicate that age, gender, ear infection, and diabetes are the most critical factors in predicting adult hearing loss. The results from the ordered probit models imply that these same factors are likely to result in a higher degree of hearing loss. The second essay employs two separate multinomial logit regressions for hearing aid style and signal processing scheme. Findings suggest that consumers with financial stability are prone to select the more stylish hearing aids. There is a negative relationship between hearing aid procurement and payment method. The third essay examines how functional and technical characteristics of hearing aids affect their prices using a conventional hedonic price method. Empirical findings show that signal processing scheme and style are the two most important determinants of hearing aid wholesale prices. On average, the price-cost margin for a typical dispenser is .352.

This dissertation presents three essays examining some of the issues concerning poverty, microfinance and returns to education. The first essay examines the micro-level determinants and correlates of poverty, and presents a poverty profile for Sri Lanka. This is the first study that examines the probable determinants and correlates of Sri Lankan poverty in a multivariate framework employing both logit and quantile regressions. The empirical findings are broadly encouraging. The estimation results show that the education of the household head, being salary employed and being engaged in business to have a significant positive effect on the standard of living. The probability of being poor increases with the household size, household head being female, living in a rural area, and being a casual wage earner. The second essay applied recent advances in propensity score matching to assess the impact of microfinance on household per-capita income and savings. Microfinance for the poor has become a focus of attention in the development community over the last several years. To date, there has been no comprehensive investigation of their impact on household income and savings. The results for the mean impact indicate that program participation significantly increases household per capita savings for the bottom four quintiles, though the magnitude varies by matching method. Even though there are sizable gains in household per capita savings for program participants, this is not evident for household per capita income. Results suggest that there is no impact on household per capita income across all quintiles. The third essay investigates the returns to education in Sri Lankan labor market using the latest Consumer Finance and Socio-economic Survey. This essay employs the quantile regression technique for each conditional quantile wage group rather than mean regression analysis used in most labor market analysis. Quantile regression results suggest that returns to education are positive and significant across all quantiles. However, a comparison of wage returns to education between ethnic groups reveals that returns are higher for Sinhalese workers than for Tamil Workers.

Wallace Oates classic study which provided empirical support for the Tiebout hypothesis has been used as the basis for numerous future attempts to explain residential sorting among local jurisdictions. Oates and many others have focussed on school quality, specifically expenditure per pupil, as a reason for citizen voters' decisions to move. Data from Dallas suburbs seems to provide support for Tiebout's original hypothesis, that people choose a community based on the set of public goods that are provided there, but the expenditure per pupil variable was not significant. Texas school finance policy, which redistributes wealth from wealthier districts to poorer districts, makes the expenditure per pupil variable meaningless. Using a two stage least squares model, this study shows that standardized test scores from the Texas Assessment of Knowledge and Skills (TAKS) test can be substituted as a school quality variable. Results of the study provide additional support for the Tiebout hypothesis in the Dallas, Texas area.

Most developed countries face increasing challenges to the sustainability of their public pension systems, which were created in an era when the life expectancy of retirees was much shorter than today. In Italy, these challenges are exacerbated by additional factors: Very low birth rates, little immigration and a historically generous public pension system. In this dissertation, the factors affecting future sustainability of the Italian Pay-As-You-Go (PAYG) system are systematically analyzed. First, the development of the population over the next 75 years is studied. The effects of (changes in) mortality coefficients, fertility rates and immigration levels on the population’s size and age distribution are determined stochastically, with a computer program that was specifically developed for this purpose. A unique feature of these calculations is that a distinction is made between the fertility of native Italian and first-generation immigrant women. The latter is much higher, which causes substantial differences when extrapolated over 75 years. It turns out that all reasonable models predict a sharp increase in the dependency ratio, with a peak around 2040 followed by a slow decline. A second computer program uses the predicted population composition as input and calculates the consequences for the PAYG system. This program was designed to study the effects of specific changes in the system's rules, changes regarding the official retirement age, contribution levels, the relationship between pension levels and life expectancy, etc. It turns out that, even after the 1995 reforms, which intended to improve long-term sustainability, public pension expenditures would rise from their current level (~14% of GDP, highest among European countries) to well above 20% of GDP by the middle of the century. It is shown that additional modifications, in particular gradual adaptation of pension levels to the retirees’ remaining life expectancy, may restore sustainability once the population has regained a stable composition. However, because of the current distorted age distribution (cohorts born between 1945 and 1980 being on average 48% more populous than cohorts born after 1980), the pension crisis that looms for the period 2030-2050 calls for major increases in the participation of especially women and elderly (>55) workers.