Diss. Uppsala : Uppsala universitet, 2007.

Ongoing globalisation has resulted in more liberalisation, integration, and competition among countries. An upshot of this has been higher levels of cross-border investment. Foreign direct investment (FDI), long considered an engine of growth, has led to widespread probe with its recent rapid spread. Nevertheless, while research on the contribution of FDI to host countries has concentrated heavily on the developed and developing economies, there has been a marked neglect of small, developed economies. This study proposes to focus on New Zealand, a country that falls within the latter category. The study seeks to verify econometrically the impact of FDI on the country through causality links with growth, trade, domestic investment and labour productivity. The analysis is based upon time-series data, the econometric techniques of single, autoregressive distributed lag (ARDL), and the multiple equations approach, vector error correction method (VECM). The study found that there have been substantial gains to the New Zealand economy. A positive effect of FDI on the variables mentioned above led to an improvement of the balance of payments through an increase in exports rather than in imports. Economic growth has mainly been achieved through FDI's impact on exports and domestic private investment. The dynamic innovation techniques indicated a bi-directional causality between FDI and the variables. The long-run causality, however, runs mainly from growth and labour productivity to FDI rather than in the opposite direction. Another noticeable feature is that New Zealand's regional agreement with Australia, Closer Economic Relations, has brought the country significant gains in terms of growth and development through FDI. Both the ARDL and VECM approaches suggest that for a small, developed country qualitative impacts are greater than quantitative ones. The policy implication is that maintaining sustainable economic growth with a positive domestic investment environment is vital for attracting foreign investors. New Zealand, while continuing to encourage inward FDI, should aim to channel it into 'innovative' tradable sectors. The challenge lies in providing the right kind of policy mix for this purpose.

<div> <div> <div> <p>First Chapter: The ordinary least squares (OLS) estimator for spatial autoregressions may be consistent as pointed out by Lee (2002), provided that each spatial unit is influenced aggregately by a significant portion of the total units. This paper presents a unified asymptotic distribution result of the properly recentered OLS estimator and proposes a new estimator that is based on the indirect inference (II) procedure. The resulting estimator can always be used regardless of the degree of aggregate influence on each spatial unit from other units and is consistent and asymptotically normal. The new estimator does not rely on distributional assumptions and is robust to unknown heteroscedasticity. Its good finite-sample performance, in comparison with existing estimators that are also robust to heteroscedasticity, is demonstrated by a Monte Carlo study.<br></p><p><br></p><p>Second Chapter: This paper proposes a new estimation procedure for the first-order spatial autoregressive (SAR) model, where the disturbance term also follows a first-order autoregression and its innovations may be heteroscedastic. The estimation procedure is based on the principle of indirect inference that matches the ordinary least squares estimator of the two SAR coefficients (one in the outcome equation and the other in the disturbance equation) with its approximate analytical expectation. The resulting estimator is shown to be consistent, asymptotically normal and robust to unknown heteroscedasticity. Monte Carlo experiments are provided to show its finite-sample performance in comparison with existing estimators that are based on the generalized method of moments. The new estimation procedure is applied to empirical studies on teenage pregnancy rates and Airbnb accommodation prices.<br></p><p><br></p><p>Third Chapter: This paper presents a sample selection model with spatial autoregressive interactions and studies the maximum likelihood (ML) approach to estimating this model. Consistency and asymptotic normality of the ML estimator are established by the spatial near-epoch dependent (NED) properties of the selection and outcome variables. Monte Carlo simulations, based on the characteristics of female labor supply example, show that the proposed estimator has good finite-sample performance. The new model is applied to empirical study on examining the impact of climate change on agriculture in Southeast Asia.<br></p></div></div></div><div><div><div> </div> </div> </div>

My dissertation consists of three chapters. In the first chapter, I analyze theeffect of the merger between American Airlines (AA) & US Airways (US) on market price and product quality. I use two complementary methodologies: difference-in-differences (DID) and merger simulation. Contrary to other results in the airline literature, the DID analysis shows that, overall, price has decreased as a result of themerger. While divestitures required as part of the merger had a strong price-reducing effect, the overall decrease involves non-divestiture markets as well. Interestingly, the decrease appears only in large airport-pair markets, whereas prices rose considerably in smaller ones. Effects on quality are mixed. The DID analysis shows that the merger reduced flight cancellations, increased flight delays, and had no effect on flight frequency or capacity overall. Using merger simulation, I find that the change in ownership leads to a 3% increase in price. The structural model performs betterin predicting the post-merger price if I allow the model to deviate from the Bertrand-Nash conduct. A 10% cost reduction due to the merger is able to predict the post-merger price quite well. When I incorporate a conduct parameter into the model, the required percentage of cost savings is lower. Given the divestiture and the subsequententry of low-cost carriers (LCCs), tacit collusion may break down. Thus both cost savings and reduced cooperation could explain a reduction in the price in the post-merger period.<div><br></div><div>In my second chapter, I analyze possible reasons why airline prices are higher inthe smaller markets compared to larger markets. In the literature, most of the studies ignore the fact that the smaller markets are different compared to larger markets in terms of the nature of competition. I find that a combination of lower competition, and lack of entry from low cost carriers (LCCs) are the reasons behind higher prices in the smaller city-pair markets. I show that price is substantially higher in a market with a fewer number of firms controlling for several other factors. My paper estimates the modified critical number of firms to be 5 and the critical value of the HHI to be .6.<br><div><br></div><div>In my third chapter, I study the effect of announcement of investment in research & development (R&D) on the value of a firm in the pharmaceutical industry. Three types of R&D by the pharmaceutical firms are considered for the analysis: acquisition of other smaller firms, internal investment in R&D, and collaborative investment in R&D. This chapter finds that few target specific characteristics and financial charac-teristics of the acquiring firm are important drivers of the abnormal returns around the announcement period.<br></div><div><br></div></div>

<p>Decades and policies come and go, and the ominous problem of corruption remains almost unaltered. Some of the most sought-after policies for corruption deterrence focus on institutional reforms aimed at assuring the right and effective access to information, reinforcing rule of law, tackling impunity, and increasing integrity standards for public servants. The aim of this dissertation is to test whether the impact of these policies over corruption is traceable at the subnational level of mexico and the united states. Seeking to accomplish this purpose, statistics measuring corruption, transparency and relevant variables are analyzed through ols regression and correlation methods. The findings point that spite of the evident benefits of transparency for democratic governance, under the methodology selected and with the ensuing subnational statistics, it is not possible to affirm that corruption is noticeable affected by transparency or integrity variables. Implications of these findings ask for a revision on the manner corruption is measured, and to devise which sort of circumstances bolster or thwart transparency´s prowess to cause a dent over corruption.</p> <p> </p>

<p>Fundamental changes have been happening in healthcare organizations and delivery in these decades, including more accessible physician information, the low-cost collection and sharing of clinical records, and decision support systems, among others. Emerging information systems and technologies play a signification role in these transformations. To extend the understanding and the implications of information systems on healthcare, my dissertation investigates the influence of information systems on enhancing healthcare operations. The findings reveal the practical value of digitalization in indicating healthcare providers' cognitive behaviors, responding to healthcare crises, and improving medical performance.</p> <p><br></p> <p>The first essay investigates the unrevealed value of a special type of user-generated content in healthcare operations. In today's social media world, individuals are willing to express themselves on various online platforms. This user-generated content posted online help readers get easy assess to individuals' features, including but not limited to personality traits. To study the impact of physicians' personality traits on medicine behaviours and performance, we take a view from the perspective of user generated content posted by their supplier side as well as using physician statements which have been made available in medical review websites. It has been found that a higher openness score leads to lower mortality rates, reduced lab test costs, shorter time usage in hospitals treated by physicians with greater openness scores. Furthermore, taking these personality traits into consideration in an optimization problem of ED scheduling, the estimation of counterfactual analysis shows an average of 11.4%, 18.4%, and 17.8% reduction in in-hospital mortality rates, lab test expenditures, and lengths of stay, respectively. In future operation of healthcare, physicians' personalities should be taken into account when healthcare resources are insufficient in times of healthcare pandemics like COVID-19, as our study indicates that health service providers personality is an actual influence on clinical quality.</p> <p><br></p> <p>In the second essay, we focus on the influences of the most severe healthcare pandemic in these decades, COVID-19, on digital goods consumption and examine whether digital goods consumption is resilient to an individual’s physical restriction induced by the pandemic. Leveraging the enforced quarantine policy during the COVID-19 pandemic as a quasi-experiment, we identify the influence of a specific factor, quarantine policy, on mobile app consumption in every Apple app store category in the short and long terms. In the perspective of better responding in the post-pandemic era, the quantitative findings provide managerial implications to the app industry as well as the stock market for accurately understanding the long-term impact of a significant intervention, quarantine, in the pandemic. Moreover, by using the conditional exogenous quarantine policy to instrument app users’ daily movement patterns, we are able to further investigate the digital resilience of physical mobility in different app categories and quantify the impact of an individual’s physical mobility on human behavior in app usage. For results, we find that the reduction in 10% of one’s physical mobility (measured in the radius of gyration) leads to a 2.68% increase in general app usage and a 5.44% rise in app usage time dispersion, suggesting practitioners should consider users’ physical mobility in future mobile app design, pricing, and marketing.</p> <p><br></p> <p>In the third essay, we investigate the role of an emerging AI-based clinical treatment method, robot-assisted surgery (RAS), in transforming the healthcare delivery. As an advanced technique to help diminish the human physical and intellectual limitations in surgeries, RAS is expected to but has not been empirically proven to improve clinical performance. In this work, we first investigate the effect of RAS on clinical outcomes, controlling physicians' self-selection behavior in choosing whether or not to use RAS treatment methods. In particular, we focus on the accessibility of RAS and explore how physician and patient heterogeneity affect the adoption of the RAS method, including learning RAS and using RAS. Investigating the decision-making process on RAS implementation in both the learning and using stages, we show the synergy of RAS implementation in alleviating healthcare racial disparity. Ultimately, the mechanism analysis will be conducted to reveal the underlying mechanism that induces the enhancement of surgical outcomes. For instance, the estimations tend to reveal that, more than surging clinical performance, RAS tends to increase standardization in time and steps when applying the treatment procedures. </p>

<p>This dissertation is a collection of four essays on nonstationary time series econometrics, which are grouped into four chapters. The first chapter investigates the inference in mildly explosive autoregressions under unconditional heteroskedasticity. The second chapter develops a new approach to forecasting a highly persistent time series that employs feasible generalized least squares (FGLS) estimation of the deterministic components in conjunction with Mallows model averaging. The third chapter proposes new bootstrap procedures for detecting multiple persistence shifts in a time series driven by nonstationary volatility. The last chapter studies the problem of testing partial parameter stability in cointegrated regression models.</p>

<p dir="ltr">The passing of the Equity Executive Order by the US government in 2021 and the Equity Action Plan developed by the US Department of Transportation have made addressing equity a priority in transportation planning projects. The Equity Action Plan recognizes socio-economically disadvantaged (SED) and rural communities as overburdened and underserved in transportation services and highlights the need to provide basic equality of opportunities and a fair distribution of burdens in transportation. In response, several transportation planning agencies have proposed their own criteria, methods, metrics, and tools to quantify equity issues and use them in planning. However, transport equity is a multi-faceted phenomenon and its quantification faces challenges due to a lack of standards and a comprehensive assessment framework.</p><p dir="ltr">The first objective of this dissertation is to develop a nuanced understanding in three key aspects of transport equity – (i) accessibility to opportunities, (ii) environmental burden, and (iii) health outcomes – based on the concept of ‘compound disadvantage’. A detailed assessment of prominent accessibility measures reveals a substantial measurement bias in the current measures, which can result in inappropriate conclusions such as an overestimating accessibility to opportunities for SED neighborhoods on average by 16%. Despite this, spatial accessibility is found to be high for compact, urban areas which also tend to have higher concentration of SED communities. However, there are significant modal differences in accessibility that reveal a substantial lack of utilization of infrastructure for alternate modes of travel – public transit, walking, and bicycling.</p><p dir="ltr">Evaluation of inequalities in environmental and health outcomes shows substantial disadvantage faced by SED communities, particularly poor people and people of color. A proposed emission equity index shows that low-income and racial minority neighborhoods of Indiana’s largest cities disproportionately experience vehicular pollution from travelers residing in high-income, White-majority areas passing through their neighborhoods. Similarly, essential workers living in low-income areas are observed to have experienced significantly worse COVID-19 infection rates than in high-income areas in Chicago and New York City, and this effect was mediated by their ‘mobility vulnerability’. Together, these results suggest a strong compounding of disadvantage by the current transportation systems for already disadvantaged communities despite their higher accessibility to opportunities owing to their predominantly urban residences.</p><p dir="ltr">The second objective of this dissertation is to integrate the equity measures in an interactive screening tool for identifying the vulnerable and priority areas for investment. ‘Indiana Equity Atlas’, an equity-screening dashboard tool, is developed to allow transportation planners and analysts to identify priority areas in terms of compound disadvantage of two selected indicators of socio-economic, accessibility, environmental burden, and health disadvantage. With this tool and the associated data and metrics, this work seeks to provide a comprehensive framework for identifying vulnerable regions to formally capture equity issues in transportation and urban planning and analysis.</p>

<p dir="ltr">This thesis investigated the international trade dynamics of wood pellets within the context of renewable energy transitions amid climate change concerns. In the first chapter, by employing gravity models with different estimators and specifications, we analyzed the determinants of trade flows of wood pellets. Additionally, we forecasted the future trade values of wood pellets under five shared socioeconomic pathways (SSP) scenarios. Our results showed the effects of some factors such as GDP of exporters, contiguity, and the distance between the two trading countries, were consistent with the economic theory. On the other hand, some other factors exhibited unexpected effects or conflicting results across the models. Regarding projections under five SSP scenarios, our results indicated substantial growth in trade flows, although potential overestimations are acknowledged due to the imposed assumptions. SSP3, which reflects a nationalistic scenario, is projected to have the smallest trade flows, while SSP5 anticipates the highest trade flows due to diminishing inequality and high GDP growth. Also, regional shifts in trade patterns were forecasted, with East Asia and Southeast Asia gaining prominence in imports and exports, respectively. Conversely, Europe’s imports and exports as well as North America’s exports are expected to decrease their shares in the global trade. Overall, our findings emphasize the complexity of trade determinants and underscore the need for nuanced forecasting methodologies to anticipate future trade dynamics accurately amidst evolving global scenarios of wood pellet trade.</p><p dir="ltr">The second chapter evaluated the effects of the Paris Agreement on the international trade of wood pellets. The growing concern about climate change has encouraged the global communities to take actions toward climate-change mitigation. As a form of such efforts, the Paris Agreement was signed in 2015 by 196 parties around the world and went into force in 2016. As a means to mitigate climate change, wood pellets have been used as fuels alternative to fossil fuels. Traditionally, Europe was the primary importer of wood pellets, mostly sourced from the United States and Canada. In the last decade, there has also been a significant uptake in East Asia, indicating shifting trade patterns and market dynamics in the wood pellet industry. This study employed an event-study framework to analyze the impact of the Paris Agreement on the global trade of wood pellets from 2014 to 2019, using import and export data at the regional level. Our results revealed distinct patterns in responses to the Paris Agreement in terms of adjustment speed and magnitude. Europe exhibited a rapid increase in both imports and exports immediately after the Paris Agreement. East Asia demonstrated a delayed yet substantial rise in imports, particularly after 2018. North America also swiftly expanded exports, following the agreement, while Southeast Asia emerged as an important exporter, particularly in supporting the East Asian market from 2017 onwards. We also found an increase in exports of non-pellet wood fuels from Africa. This finding indicates that international climate agreements not only contribute to the overall expansion of the global market of wood pellets but also reshape the market by involving more countries in international efforts to mitigate climate change.</p>

<p dir="ltr">Extensive tree-cutting operations and prioritization of crop production a century ago caused a significant decline in maple syrup production in Indiana. Today, there is an increasing consumer interest in natural and locally produced food, creating potential for regrowth in the industry. Understanding both production and consumption behaviors is crucial to capitalize on this potential and ensure sustainable sugarbush resources in the state. This thesis comprised two chapters, presenting the findings on consumers and producers, respectively. The first chapter examined the factors influencing consumers' behavior toward maple syrup purchase and satisfaction. Results suggested that suburban residency, education, age, income, and lifestyle factors – such as visiting farmers' markets and purchasing organic food – may influence consumers' attitudes toward purchasing maple syrup. Moreover, consumers who purchase organic food tended to be satisfied with maple syrup and were more likely to recommend it to others. The second chapter explored the factors motivating maple syrup producers to manage their forests and investigated whether crowd-in or crowd-out effects exist among different management practices. I used logistic regressions to identify relationships among the adoption of a variety of forest management practices and a variety of independent variables, using data pooled from two producer surveys conducted in Indiana in 2022 and 2023, respectively. Production as a hobby, owning a sugarbush, and production capacity all positively affected the likelihood of management practice adoption. In addition, crowding-in effects were identified in adopting forest management practices, suggesting that producers were more likely to adopt multiple practices simultaneously. These chapters emphasized the importance of understanding maple syrup consumer socio-demographic characteristics for effective marketing strategies and producer behavior for sustainable production practices to promote industry growth.</p>