This dissertation examines two main research questions: Why do firms deviate from their predicted level of toxic emissions, and how do these differences relate to financial performance? The objective is threefold: (1) to understand deviation in corporate environmental performance by looking at both industry and firm level variables, (2) to see how this deviation relates to both profitability and fluctuations in financial performance, and (3) to see if, and how, corporate environmental legitimacy affects the relationship between corporate environmental deviation and corporate financial performance. To achieve this objective the construct “corporate environmental performance deviation” is developed. It is defined as the extent to which a firm’s environmental performance deviates from its predicted performance, and is used to capture within-firm strategic choices in environmental management. Predicted environmental performance is calculated based on certain firm characteristics such as size and industry. Actual environmental performance is calculated using a weighted score of air emissions obtained from the Toxic Release Inventory (TRI) database. The difference between these two values represents a corporation’s environmental performance deviation. Corporate environmental performance deviation focuses on strategic choices related to environmental management, while recognizing that environmental management is the result of both institutional pressures and within-firm strategic decisions. Aligned with this focus, variables 2 related to this strategic choice are used to explain deviation in environmental management, including an environmental integration capability, firm strategy, and industry munificence and dynamism. Associated with the internal and external organizational analysis, institutional theory and the resource-based view (RBV) are used to explore the tension between deviation to increase competitiveness versus isomorphism to attain legitimacy. The sample is composed of 311 U.S. firms who have reported their toxic air releases to the TRI from 1998-2007. The sample is broken down into two subsets, those that exceed (positive deviation) or fail to meet (negative deviation) predicted environmental performance. Results of a longitudinal analysis show that positive environmental deviation is related to a greater capacity to strategically integrate environmental issues into a firm’s existing business approach, less munificence and dynamism in the task environment, and reduced financial fluctuations. Negative environmental deviation is decreased through a demonstrated capacity to strategically integrate environmental issues into a firm’s existing strategic approach, and related to greater munificence and dynamism in the task environment, reduced profitability and increased financial fluctuations. Lastly, although there are no significant main effects for corporate environmental legitimacy, the paradoxical combination of negative deviation and environmental legitimacy can reduce the severity of the negative financial results to negative deviation, both in terms of profitability and financial fluctuations.

This paper looks at whether firms’ credit ratings are negatively affected by litigation risk after controlling for known factors that affect credit ratings. The conventional wisdom is that litigation risk and credit ratings have an inverse relationship. However, my hypothesis is that the inverse relationship will not be stable if the model of credit ratings has taken other factors into account. The methodology first constructs a model of litigation risk, and then regress the credit ratings on the measurement of litigation risk. Previous empirical research on litigation risk measurement uses industry proxies as indicators for litigation risk. In this paper, I include firm characteristics and the Beneish M-score (a determinant for earnings manipulation) in addition to the industry proxy to construct an alternative model measuring litigation risk. I find that supplementing the Francis, Philbrick and Schipper (1994a, b; hereafter FPS) industry proxy with measures of firm characteristics improves predictive ability. In the model of credit ratings, I find that the change of litigation risk has a negative correlation with the credit ratings. However, the negative coefficient on the change of litigation risk changes to a positive one after controlling for other variables such as firm size, return on asset, and interest coverage ratio. This finding provides support for the hypothesis that the negative correlation between the credit ratings and litigation risk is not stable. This suggests that credit ratings may not incorporate litigation risk specifically although litigation can lead to firms’ financial damage and reputation crisis. However, the negative coefficient on the change of litigation risk remains unchanged when I control for the year fixed effects. I also find a negative correlation between the year 2007 and credit ratings due to financial crisis. The results are not conclusive given the likely simultaneous determination of litigation risk and credit ratings.

This thesis studies the value of branding in the smartphone market. Measuring brand value with data available at product level potentially entails computational and econometric challenges due to data constraints. These issues motivate the three studies of the thesis. Chapter 2 studies the smartphone market to understand how operating system platform providers can grow one of the most important intangible assets, i.e., brand value, by leveraging the indirect network between two user groups in a two-sided platform. The main finding is that iPhone achieved the greatest brand value growth by opening its platform to the participation of third-party developers, thereby indirectly connecting the consumers and the developers via its app store effectively. Without the open app store, I find that iPhone would have lost its brand value by becoming a two-sided platform. Hence these findings provide an important lesson that open platform strategy is vital to the success of building platform brands. Chapter 3 solves a computational challenge in structural estimation of aggregate demand. I develop a computationally efficient MCMC algorithm for the GMM estimation framework developed by Berry, Levinsohn and Pakes (1995) and Gowrisankaran and Rysman (forthcoming). I combine the MCMC method with the classical approach by transforming the GMM into a Laplace type estimation framework, therefore avoiding the need to formulate a likelihood model. The proposed algorithm solves the two fixed point problems, i.e., the market share inversion and the dynamic programming, incrementally with MCMC iteration. Hence the proposed approach achieves computational efficiency without compromising the advantages of the conventional GMM approach. Chapter 4 reviews recently developed econometric methods to control for endogeneity bias when the random slope coefficient is correlated with treatment variables. I examine how standard instrumental variables and control function approaches can solve the slope endogeneity problem under two general frameworks commonly used in the literature.

This thesis studies the value of branding in the smartphone market. Measuring brand value with data available at product level potentially entails computational and econometric challenges due to data constraints. These issues motivate the three studies of the thesis. Chapter 2 studies the smartphone market to understand how operating system platform providers can grow one of the most important intangible assets, i.e., brand value, by leveraging the indirect network between two user groups in a two-sided platform. The main finding is that iPhone achieved the greatest brand value growth by opening its platform to the participation of third-party developers, thereby indirectly connecting the consumers and the developers via its app store effectively. Without the open app store, I find that iPhone would have lost its brand value by becoming a two-sided platform. Hence these findings provide an important lesson that open platform strategy is vital to the success of building platform brands. Chapter 3 solves a computational challenge in structural estimation of aggregate demand. I develop a computationally efficient MCMC algorithm for the GMM estimation framework developed by Berry, Levinsohn and Pakes (1995) and Gowrisankaran and Rysman (forthcoming). I combine the MCMC method with the classical approach by transforming the GMM into a Laplace type estimation framework, therefore avoiding the need to formulate a likelihood model. The proposed algorithm solves the two fixed point problems, i.e., the market share inversion and the dynamic programming, incrementally with MCMC iteration. Hence the proposed approach achieves computational efficiency without compromising the advantages of the conventional GMM approach. Chapter 4 reviews recently developed econometric methods to control for endogeneity bias when the random slope coefficient is correlated with treatment variables. I examine how standard instrumental variables and control function approaches can solve the slope endogeneity problem under two general frameworks commonly used in the literature.

Σκοπός της παρούσας εργασίας είναι η παρουσίαση των OLS και IV εκτιμήσεων που προκύπτουν απο μια σειρά εμπειρικών μελετών οι οποίες εκτιμούν το βαθμό απόδοσης της εκπαίδευσης. Μέσα απο την ανασκόπηση της βιβλιογραφίας και λαμβάνοντας υπόψη προβλήματα που σχετίζονται με το θέμα, όπως η ενδογένεια και το σφάλμα μέτρησης, η εργασία καταλήγει επισημαίνοντας τη σπουδαιότητα που έχει η συνάρτηση αποδοχών του Mincer ακόμα και στις μέρες μας, καθιστώντας την το πιο χρήσιμο εργαλείο των οικονομικών της εκπαίδευσης. / The purpose of this paper is to present the OLS and IV estimates derived from a number of empirical studies that assess the efficiency of education. Through the literature review and taking into account problems associated with it,such as endogeneity and measurement error, the work concludes by pointing out the importance of the Μincer's earnings function even in our days, making it the most usefull tool for the economics of education.

This thesis focuses on the analysis of Catastrophe bond mutual funds [CBMFs] and is organized into four chapters. The first chapter, "An identification-robust analysis of Catastrophe bond mutual funds: zero-beta neutrality under tradability", offers identification-robust evidence on whether CBMFs are zero-beta based on the analysis with only tradable risk factors. Statistical significance of factor risk premiums and cross-sectional loadings is examined in a multivariate, identification-robust setting to inform on the zero-beta performance of CBMFs. The latter is assessed against the Capital Asset Pricing Model [CAPM] without the risk-less asset proposed by Black (1972) [BCAPM], Quadratic CAPM, Cummins-Weiss, Fama-French-Carhart benchmarks and models with Fontaine and Garcia (2012) and Pástor and Stambaugh (2003) liquidity factors. Multiple markets are considered individually and jointly. Beta pricing inference proceeds using the method of Beaulieu, Dufour and Khalaf (2013) robust to weak identification. Instead of non-tradable factors, their mimicking portfolio returns are used in the analysis to facilitate tradable-only factor setting. Results indicate that coskewness, funding liquidity and fixed-income factors are often priced or incur significant factor betas. There is also evidence of risk premiums and joint beta significance for stock, corporate bond and commercial mortgage-backed securities benchmarks. Empirical findings overall suggests that CBMFs underperformed as zero-beta assets. The second chapter, "Zero-beta inference on Catastrophe bond mutual funds: identification- robust evidence with non-tradable factors", examines formally the zero-beta neutrality of CBMFs allowing for some risk factors to be non-tradable. Zero-beta analysis focuses on cross-sectional betas with their joint significance tested for each factor. This is augmented with inference on risk prices and the zero-beta rate to assess whether factor risks are priced. CBMFs are modeled in the QCAPM setting with either stock, corporate bond, government bond or commercial mortgage-backed security [CMBS] market return and its square as respectively tradable and non-tradable factors. The zero-beta performance of CBMFs is also assessed against an extended BCAPM benchmark with either Fontaine and Garcia (2012) or Pástor and Stambaugh (2003) non-tradable liquidity factor considered in addition to the tradable market return. Inference on risk prices and the zero-beta rate builds on the method of Beaulieu, Dufour and Khalaf (2018) which remains exact and simultaneous for any sample size even if the parameter recovery is impaired. Empirically, although identification strength diminishes in the setting with non-tradable factors, relaxing tradability improves model fit across all benchmarks. In particular, QCAPM (reix gardless of the market) is no longer rejected for any period and so is the model with the funding liquidity factor. Goodness-of-fit also improves for the model with the marketwide liquidity factor. In periods for which models were rejected under factor tradability, allowing for some factors to be non-tradable also yields set estimates for the zero-beta rate and risk prices that are informative for beta pricing. In particular, this reveals evidence of priced coskewness risk across all markets over the long-run and for stock, corporate bond and CMBS benchmarks after the 2007-09 US recession. In the same periods, funding liquidity risk is also priced and so is the marketwide liquidity risk over the full sample. Given significant betas on the market return, the latter prevails as a relevant factor even in a setting with other factors being non-tradable. Overall, there is evidence suggesting that CBMFs deviated from performing as zero-beta investments with coskewness and liquidity as contributing factors. These results reinforce findings in the Chapter 1. The third chapter, "An alpha and risk analysis of Catastrophe bond mutual funds: exact, simultaneous inference", examines CBMFs in terms of their ability to produce a positive alpha and the extent of their sensitivity to the developments in financial markets. Inference on alphas and the riskiness of CBMFs relies on exact, simultaneous confidence sets assembled respectively for cross-sectional intercepts and factor loadings in the multivariate linear regression [MLR] model. Set construction proceeds using the analytical inversion procedure of Beaulieu, Dufour and Khalaf (2018) in a Least-Squares case and its extension to a Student-t setting. Proposed in this chapter, the extension involves replacing the Fisher-based cut-off point in the analytical solution of Beaulieu, Dufour and Khalaf (2018) with its simulation-based counterpart obtained under Student-t errors. The empirical analysis of CBMFs reveals evidence of a positive alpha following the 2011 Tohoku earthquake in Japan and indicate that CBMFs are likely to have at most moderate sensitivity to fluctuations in financial markets. These results are robust against CAPM, QCAPM and Fama-French benchmarks and observed in both Gaussian and Student-t settings. The fourth chapter, "Endogeneity in a zero-beta analysis: joint, finite sample inference on Catastrophe bond mutual funds", revisits the zero-beta assessment of CBMFs taking into account factor endogeneity. In particular, this chapter extends the univariate Durbin-Wu-Hausman [DWH] test (Durbin, 1954; Wu, 1973; Hausman, 1978) of exogeneity to a multivariate setting. Unlike the univariate DWH test, the proposed multivariate extension allows to assess factor exogeneity jointly across equations. This chapter also proposes an extended version of the multivariate Wilks-based instrumental variables [IV] test of Dufour, Khalaf and Kichian (2013) to a setting with regressors, and consequently their instruments, that remain the same across equations. Both extended tests allow for possibly non-Gaussian errors and maintain size correctness for a sample with any number of observations even in the setting with weak instruments. Applying the extended methods to the analysis CBMFs provides evidence against joint factor exogeneity in some cases across CAPM and QCAPM in both Gaussian and Student-t settings. In some periods when the joint factor exogeneity is rejected, results for the zero-beta analysis differ depending on whether the IV-based or non-IV test was applied. Unlike in the case without instrumenting, extended Wilks-based IV test of joint beta significance is significant at the 5% level before the 2007-09 US recession for both CAPM and QCAPM regardless of the distributional setting (Gaussian or Student-t). The same result also obtains for QCAPM during the economic downturn. Over the long-run, there is evidence of jointly significant factor loadings obtained with and without instrumenting. Overall, empirical results suggest that performance of CBMFs differs from that of zero-beta assets.

Esse trabalho traz os resultados do retorno salarial de se investir em educação no Brasil e desagregado para cada Estado da Unidade da Federação. Diferentes técnicas econométricas foram estimadas, como Mincer, Mincer Adaptado, Método de Variáveis Instrumentais, Método de Heckman e por fim Metodologia de Hansen (2000) que permite inovar a idéia de não linearidade na equação de rendimento proposta por Jaccob Mincer estimada de forma endógena. A analise empírica foi feita com base nas PNAD´s de 2001 a 2008 com dados em dados cross-section. Os resultados apresentados diferenciam em magnitude de cada método econométrico utilizado em destaque o Método de Hansen que permitiu identificar limiares em que o retorno de se investir em educação muda a partir de certo nível de escolaridade quebrada a hipótese de linearidade. Implicando que a não consideração de tal hipótese pode acabar distorcendo a compreensão da função que a educação em si exerce, por exemplo, na distribuição de renda. / This paper presents the results of the wage return of investing in education in Brazil and the disaggregated for each member of the Office of the Federation. Others Different from econometric were estimated as Mincer, Mincer Adapted, All Variable Instrumental, Method of Heckman and finally Methodology Hansen (2000) to innovation to go from no linearity in the equation the revenue proposed by Mincer Jaccob estimated and endogen. The analysis empiric was based on PNAD´s from 2001 to 2008 data with data in cross-section. The presented results differ in magnitude for each method used econometric highlighted the method of which Hansen identified thresholds at which the return of investing in education change it from a certain point of education to broken hypothesis linearity. Implying that if consideration in such a hypothesis can end up distorting the understanding of the function what education the exercise it, for example, distribution the income.

Esse trabalho traz os resultados do retorno salarial de se investir em educação no Brasil e desagregado para cada Estado da Unidade da Federação. Diferentes técnicas econométricas foram estimadas, como Mincer, Mincer Adaptado, Método de Variáveis Instrumentais, Método de Heckman e por fim Metodologia de Hansen (2000) que permite inovar a idéia de não linearidade na equação de rendimento proposta por Jaccob Mincer estimada de forma endógena. A analise empírica foi feita com base nas PNAD´s de 2001 a 2008 com dados em dados cross-section. Os resultados apresentados diferenciam em magnitude de cada método econométrico utilizado em destaque o Método de Hansen que permitiu identificar limiares em que o retorno de se investir em educação muda a partir de certo nível de escolaridade quebrada a hipótese de linearidade. Implicando que a não consideração de tal hipótese pode acabar distorcendo a compreensão da função que a educação em si exerce, por exemplo, na distribuição de renda. / This paper presents the results of the wage return of investing in education in Brazil and the disaggregated for each member of the Office of the Federation. Others Different from econometric were estimated as Mincer, Mincer Adapted, All Variable Instrumental, Method of Heckman and finally Methodology Hansen (2000) to innovation to go from no linearity in the equation the revenue proposed by Mincer Jaccob estimated and endogen. The analysis empiric was based on PNAD´s from 2001 to 2008 data with data in cross-section. The presented results differ in magnitude for each method used econometric highlighted the method of which Hansen identified thresholds at which the return of investing in education change it from a certain point of education to broken hypothesis linearity. Implying that if consideration in such a hypothesis can end up distorting the understanding of the function what education the exercise it, for example, distribution the income.

abstract: Total digital media advertising spending of $72.5 billion surpassed total television Ad spending of $71.3 billion for the first time ever in 2016. Approximately $39 billion, or 54% of the digital media advertising spend, involved pre-programmed software that purchased Ads on behalf of a buyer in Real-Time Bidding (RTB) settings. A major concern for Ad buyers is sub-optimal spending in RTB settings owing to biases in the attribution of customer conversions to Ad impressions. The purpose of this research is twofold. First, identify and propose a novel experimental design and analysis plan for to handling a previously unidentified and unaddressed source of endogeneity: count/quality simultaneity bias (CQB). Second, conduct a field study using data for Ad response rates, cost, and observed consumer behavior to solve for the profit maximizing daily Ad frequency per customer. One large online retailer provided data for Ad impressions, bid costs, response rates, revenue per visit, and operating costs for 153,561 unique users over 23 days. Unique visitors were randomly assigned to one of seven treatment groups with one, two, three, four, five, and six impressions per day limits as well as a final condition with no daily impression cap. Ordinary least square models (OLS) were fit to the data and a non-linear relationship between Ad impressions and site visits demonstrating declining marginal effect of Ad impression on site visits after an optimal point. The results of the field study confirmed the existence of negative CQB and demonstrated how my novel experimental design and analysis can reduce the negative bias in the estimate of impression quantity on customer response. Second, managers interested in improving the efficiency of advertising spend should restrict display advertising to only the highest quality inventory through specific site targeting and by leveraging direct buys and private marketplace deals. This strategy ensures that subsequent impressions are not of lower quality by restricting the pool of possible impressions from a homogenous set of high quality inventory. / Dissertation/Thesis / Doctoral Dissertation Business Administration 2017

Esse trabalho traz os resultados do retorno salarial de se investir em educação no Brasil e desagregado para cada Estado da Unidade da Federação. Diferentes técnicas econométricas foram estimadas, como Mincer, Mincer Adaptado, Método de Variáveis Instrumentais, Método de Heckman e por fim Metodologia de Hansen (2000) que permite inovar a idéia de não linearidade na equação de rendimento proposta por Jaccob Mincer estimada de forma endógena. A analise empírica foi feita com base nas PNAD´s de 2001 a 2008 com dados em dados cross-section. Os resultados apresentados diferenciam em magnitude de cada método econométrico utilizado em destaque o Método de Hansen que permitiu identificar limiares em que o retorno de se investir em educação muda a partir de certo nível de escolaridade quebrada a hipótese de linearidade. Implicando que a não consideração de tal hipótese pode acabar distorcendo a compreensão da função que a educação em si exerce, por exemplo, na distribuição de renda. / This paper presents the results of the wage return of investing in education in Brazil and the disaggregated for each member of the Office of the Federation. Others Different from econometric were estimated as Mincer, Mincer Adapted, All Variable Instrumental, Method of Heckman and finally Methodology Hansen (2000) to innovation to go from no linearity in the equation the revenue proposed by Mincer Jaccob estimated and endogen. The analysis empiric was based on PNAD´s from 2001 to 2008 data with data in cross-section. The presented results differ in magnitude for each method used econometric highlighted the method of which Hansen identified thresholds at which the return of investing in education change it from a certain point of education to broken hypothesis linearity. Implying that if consideration in such a hypothesis can end up distorting the understanding of the function what education the exercise it, for example, distribution the income.