The aims of the dissertation thesis are to provide the comprehensive economic-statistical viewpoint on the issue of estimating labour productivity and total factor productivity; to evaluate the quality of the available data sources and to test the usage of new inputs to the production function in the Czech Republic. The first chapter provides a theoretical basis for subsequent estimates of labour productivity and total factor productivity. The second and third chapters concentrate on a detailed definition of data sources and definitions of input and output indicators in the production function. Moreover, the second chapter introduces new approaches to the estimation of the input indicators to the production function (labour services, capital services). The fourth chapter deals with estimates of labour productivity. Specifically, the relationship of labour productivity and educational structures are examined as well as estimates for regions of the Czech Republic and estimates for non-market industry that do not allow the use of the traditional approach. The fifth chapter focuses on possible particularization and improvement of the estimation of total factor productivity using new input variables. The same chapter further compares the index number approach and econometric approach including the test of constant returns to scale. The estimation of total factor productivity in individual Czech regions is also part of the chapter.

Submitted by MARCELO LORANDE (marcelomilq@gmail.com) on 2018-09-12T02:06:05Z No. of bitstreams: 1 Dissertação - MSL.pdf: 1806135 bytes, checksum: 104d4a7f94cee09c2d70b23ed78d5fad (MD5) / Rejected by Thais Oliveira (thais.oliveira@fgv.br), reason: Boa noite, Marcelo! Para que possamos aprovar sua Dissertação, serão necessárias apenas duas alterações: - "GETULIO" não tem acento; - Lista de Figuras e Tabelas são posicionadas ANTES do Sumário. Por gentileza, alterar e submeter novamente. Obrigada. on 2018-09-14T21:15:22Z (GMT) / Submitted by MARCELO LORANDE (marcelomilq@gmail.com) on 2018-09-17T02:46:44Z No. of bitstreams: 1 Dissertação - MSL.pdf: 1813262 bytes, checksum: d4225bb320038db9cfeb819e8804a5b8 (MD5) / Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2018-09-17T15:55:14Z (GMT) No. of bitstreams: 1 Dissertação - MSL.pdf: 1813262 bytes, checksum: d4225bb320038db9cfeb819e8804a5b8 (MD5) / Approved for entry into archive by Suzane Guimarães (suzane.guimaraes@fgv.br) on 2018-09-18T13:14:49Z (GMT) No. of bitstreams: 1 Dissertação - MSL.pdf: 1813262 bytes, checksum: d4225bb320038db9cfeb819e8804a5b8 (MD5) / Made available in DSpace on 2018-09-18T13:14:49Z (GMT). No. of bitstreams: 1 Dissertação - MSL.pdf: 1813262 bytes, checksum: d4225bb320038db9cfeb819e8804a5b8 (MD5) Previous issue date: 2018-08-17 / Este trabalho propõe a desagregação por componentes de localidade do índice de inflação no Brasil como forma de melhorar o desempenho preditivo de modelos econométricos. Foram desenvolvidos modelos autorregressivos com ou sem variáveis macroeconômicas explicativas para se avaliar como a desagregação impacta em cada um deles. Além disso, foram utilizados dois testes estatísticos para se comparar o desempenho dos modelos, o Model Confidence Set e o Superior Predictive Ability. Observou-se que para curto prazo, como horizontes de até 3 meses, modelos autorregressivos de 1ª ordem possuem desempenho imbatível, ao passo que para horizontes mais distantes, modelo macroeconômicos e desagregados geram previsões estatisticamente superiores. / This work proposes the disaggregation of locality components from Brazil´s inflation index to enhance predictive performance of econometric models. Autorregressive models were implemented with or without explicative macroeconomic variables, in order to evaluate how the disaggregation affects each one of them. Besides that, it has been used two statistical tests to compare model forecast performance, the Model Confidence Set and the Superior Predictive Ability. For short term, up to 3 months, autorregressive models showed unachievable performance, whereas for longer terms, macroeconomic disaggregated models generate statistically superior forecasts.

Este trabalho teve como propósito a realização de um estudo que coloca no centro do debate a produção científica brasileira. Parte-se do princípio de que ela é um fator fundamental para um processo de desenvolvimento a partir do reconhecimento de que é por meio do conhecimento que as sociedades evoluem. Essa questão se torna ainda mais relevante quando se considera a necessidade imposta pelo modelo de produção vigente, de transformar conhecimento em riqueza. Este foi o ponto de partida para a realização de um estudo econométrico com o propósito de se formular um modelo que explicasse a produção científica brasileira no período de 1994 a 2014. O estudo mostrou que os programas de pós-graduação foram os que mais influenciaram o comportamento da publicação de artigos científicos, que é a variável que representa a produção científica. Por isso, se faz necessário o aparelhamento do sistema de pósgraduação brasileira. Ademais, como os resultados da produção científica são demorados, ou seja, no mínimo dois anos no mestrado e quatro anos no doutorado, concluiu-se que as crises econômicas ocorridas no período não interferiram diretamente no processo de geração do conhecimento no curto prazo. Outros fatores importantes que ajudaram a manter a produção científica no país foram a sólida estrutura acadêmica e o governo do período ter atuado nos momentos de crise para quebrar o ciclo econômico, diminuindo os efeitos das crises. / This work has purposed a study that placed at the core of the debate the Brazilian scientific production. It starts from the principle that scientific production is a key factor in a development process from the recognition that it is through knowledge that societies evolve. This question becomes even more relevant when considering the necessity imposed by the current production model, to transform knowledge into wealth. This was the starting point for leading an econometric study for the aim of formulating a model to explain the Brazilian scientific production from 1994 to 2014. The study shows that postgraduate programs were those that, statiscally, most influenced the behavior of the publication of Brazilian scientific articles. This last was the variable that represented the Brazilian scientific production in the econometric model. Therefore, it is necessary to equip the Brazilian postgraduate system to create the basis of a structure, which, in the near future, will produce knowledge in large scale and with high competitiveness. It was concluded that the economic crisis that occurred in the period did not directly interfere in the process of knowledge generation in the short term. Other important factors that helped maintaining scientific production in the country were the solid academic structure and the role of public policies that intervened in critical economic moments to break the economic cycle and to reduce the effects of the crisis.

abstract: Firms have increasingly taken on the commitment to sustainability due to environmental and social concerns. Environmental and social sustainability can create firm value and social welfare through cost reduction and revenue growth. While indicating a desire to do more, firms face challenges while engaging with stakeholders in their supply chains – suppliers and consumers. Suppliers are key partners to achieve cost reduction while customers can be the driver for revenue growth. If firms do not overcome the challenges properly, such a win-win situation of both firms and their supply chain stakeholders may not exist. This dissertation aims to understand and suggest ways to overcome the challenges which firms and their supply chain stakeholders face while collaboratively pursuing sustainability. In the first essay, I investigate the financial impact of a buyer-initiated supplier-focused sustainability improvement program on suppliers’ profitability. The results indicate that a supplier sustainability program may lead to short-term financial loss but long-term financial gain for suppliers, and this effect is contingent on supplier slack resources. The second essay of this dissertation focuses on the consumers and investigates their reactions to two types of firm environmental sustainability claims – sustainable production versus sustainable consumption. The results indicate that firm sustainable consumption claims increase consumers’ purchase, thus leads to larger firm sales, whereas firm sustainable production claims decrease consumers’ buying intention, then result in smaller firm sales. Therefore, I show that, contrary to extant belief, firm environmental sustainability can decrease consumers’ intention to buy. Finally, a firm may be impacted when some of its upstream or downstream stakeholders, or its own operations, are impacted by a natural disaster, which are becoming more frequent due to climate change. In the third essay I study the joint effect of market attention and donation timing on firm stock returns based on the experiences of firms who donated to the 2017 Hurricane Harvey. I conclude that neither the first donors nor the followers can mitigate the negative stock returns due to disasters. However, firms who match their donation timing with market attention experience less negative stock market returns compared to other counterparts. / Dissertation/Thesis / Doctoral Dissertation Business Administration 2020

Agro-terrorism has become a major concern since the September 11, 2001, terrorist attacks due to characteristics that create unique problems for managing the threat of an agro-terrorist attack. The costs of trucking delays alone were in the tens of millions of dollars. Over the last few years, the government has spent billions of dollars on biological surveillance and record keeping in preventing potential attacks. Several public and private initiatives are currently in use. Examples include 1) the bio-terrorism regulation of 2004 on maintenance of records; 2) establishment of food protection centers for research and teaching excellence; and 3) investments in emerging technology, such as radio frequency monitoring (RFEM) technology, with the potential to track shipments and provide real-time data that can be used to prevent agro-terrorism risks along food supply chains. This thesis addresses the costs and risk premiums associated with alternative tracking strategies, where and when along the milk supply chain these strategies will reduce the most risks, and what policy implications are associated with the most costeffective tracking strategy. To accomplish these objectives, stochastic optimization is used to determine the costs and risk premiums of alternative tracking strategies. Next, the realoptions method along with a portfolio of options, also referred to as the "tomato garden" framework, is used to determine where and when alternative intervention strategies should be implemented to reduce the most risks. Finally, policy implications are derived on the cost-risk tradeoffs, probability of attacks, and containment efforts if there is an attack by using game theory to determine the incentives needed to motivate participants in the milk supply chain to invest in security measures.

The research examines how the banking sector in Zambia faired in the wake of the global financial crisis, and the ensuing global recession that followed. Even prior to the crisis, weaknesses within the Zambian Banking sector were already identified by a World Bank/IMF financial sector assessment. The research therefore aims to gain a better understanding of the potential destabilizing factors to the Zambia Banking sector, and provide key players (Policymakers, Regulators and Banks) with knowledge on how best to manage and overcome these adverse effects, in times of a financial crisis. A Vector Error Correction Model (VECM) is estimated using commonly identified macroeconomic and banking sector indicators from selected Anglophonic African countries that were affected by the crisis at the time. The selected variables include, Return on Assets (ROA); Non-Performing Loans (NPL); Foreign Assets (FA); Interbank Lending Rate (IBLR); Liquidity (LQD); Credit to Private Sector (PRV); Foreign Exchange Rate (FOREX); Inflation (INFL); Copper Price (CU); and a ‘dummy’ variable (CRISIS). The direction of causality between the variables is further established using the VAR Granger Causality Test. Results of the model suggests that although the CRISIS was found to cause the ROA, it had no significant effect on its outcome, implying that overall the crisis had very little effect on the Zambian banking sector’s profitability. It was the liquidity (LQD) variable instead which was found to have a significant effect on the ROA. In times of a financial crisis, it is therefore recommended that policy makers and regulators apply more stringent regulatory and monetary policy instruments. This would counter the adverse effects on the liquidity and profitability of the Banking sector, and thus ensure its stability.

<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>

Before making a choice, we often have the opportunity to learn more about the options that are available. For example, we can check the characteristics of a product before buying it, or read different newspapers before a political election. Understanding what shapes the demand for information, and its role in the decision process, is important to study economic choices. This dissertation contains three essays in behavioral and information economics that utilize experimental data and modeling to analyze how people choose and use information to make decisions. The first chapter, "Coarse and Precise Information in Food Labeling," uses experimental data to determine whether precise food labels can be more effective and informative than coarse ones. In a preregistered online study conducted on a representative US sample, I manipulate front-of-package labels about foods' calorie content. I find that coarse-categorical labels generate a larger reduction in calories per serving compared to detailed-numerical labels despite providing less information. Choices violate the predictions of Bayesian decision theory, suggesting that consumers are less responsive to detailed information. Results also show that participants prefer coarse labels, suggesting a general preference for simple, easy-to-interpret information. The second chapter, "The Status Quo and Belief Polarization of Inattentive Agents," studies how differences across agents can drive information acquisition and generate polarization. In a rational inattention model, optimal information acquisition and subsequent belief formation depend crucially on the agent-specific status quo valuation. Beliefs can systematically update away from the realized truth and even agents with the same initial beliefs might become polarized. A laboratory experiment confirms the model's predictions about the information acquisition and its effect on beliefs. Differently from the model's predictions, participants display preferences for simple messages that can provide certainty. The third chapter, "Dynamic Information Choice with Biased Information Sources," uses experimental data to study how people decide what kind of information to acquire when they have multiple opportunities to learn. Standard theory predicts that decision makers should collect the stream of information that leads to the maximization of the expected reward from the final choice. An online experiment on sequential information acquisition shows that people systematically deviate from the predictions of the standard normative model. Participants display a certainty-seeking information acquisition behavior and under-respond to the new evidence collected, reviewing rarely their own information acquisition strategy.

My dissertation within monetary macroeconomics focuses on uncovering the impact of micro level heterogeneity in household wealth portfolios and firm size on aggregate macroeconomic variables. Using household- and firm-level datasets, I study these outcomes in the context of exploring the effects of monetary policy shocks. Most macroeconomic models use a representative agent framework to study the effects of monetary policy. In such models all consumers are assumed to be similar, therefore, it is only required to know the size of the monetary policy shock and its average impact to estimate the overall effect. But recent literature has emphasized the importance of agent heterogeneity for explaining observed aggregate dynamics and optimal policy design. Here, it matters which consumers get the extra income as people react differently to the shock. In a model with a realistically calibrated household balance sheet, monetary policy has redistribution effects because different agents have differential exposure to the interest rate and inflation risk born in their portfolios. For example, short-term or nominal borrowers will win from a sudden decrease in the interest rate and a sudden increase in inflation, while short-term lenders or nominal lenders will lose. In the first chapter of the dissertation, co authored with Anastasia Burya, we study the effect of heterogeneity in consumers' portfolios on the unemployment response to monetary policy. We develop a search efforts model with heterogeneous agents and then decompose the effect of the monetary policy shock on aggregate unemployment. The direction and the magnitude of the wealth effect will determine whether people search for jobs more actively after a monetary contraction. For example, if unemployed consumers are indebted, they experience a negative wealth effect after a contraction, search for jobs more actively and increase their probability of finding a job, therefore, reducing unemployment. In this framework, the sign of the overall effect of monetary policy on unemployment will depend on whether unemployed consumers are indebted and the magnitude of their debt. We test the prediction of the model in both micro and aggregate data. To test the prediction of the model in the micro data using the PSID panel dataset, we estimate the coefficient of the interaction term between various mortgage measures and Romer \& Romer monetary policy shocks while looking at five main transition probabilities that indicate a higher increase in search efforts for indebted people after a monetary contraction: dynamic transition probability of moving from non employment to employment, moving from non participation in the labor force to employment, remaining a non participant in the labor force, remaining unemployed and taking up an extra job. In the aggregate data, we use a similar estimation approach with debt to income ratio. We also subject this to a variety of checks using age and Saiz instruments for increased robustness. In the second chapter of the dissertation, co-authored with Anastasia Burya and Martsella Davitaya, we show that inflation expectations are anchored. If inflation expectations are anchored, then their sensitivity to monetary policy should be smaller than if they are de-anchored. When the Fed pursues inflation targeting, the market expectations of Fed's reaction should affect the response to current monetary policy shocks. We use daily bond yield data to show that the sensitivity of inflation expectations to monetary policy is lower if the Fed is more responsive to inflation during the previous CPI release. Intuitively, the Fed announcement leading to a rate change that is higher than expected from the CPI release indicates that the markets expect the Fed to react more aggressively in the future. Therefore, markets do not adjust inflation expectations as much (leading to anchored inflation expectations). The empirical strategy consists of two steps. First, we measure market expectations about the Fed's reaction to inflation by regressing the changes of different interest rates around the CPI release dates on the surprise change in CPI. Second, we estimate the sensitivity of inflation expectations' response to monetary policy based on the expectations about the Fed's reaction to inflation. Product markets are characterized by the significant heterogeneity of demand elasticity between large and small firms. In many cases, the ability of larger firms to dictate prices is such that they are able to charge higher markups. In the third chapter, co-authored with Anastasia Burya, we develop a simple model of firms with heterogeneous market power. We connect the recent trend of increasing market power to the flattening of the Phillips Curve through the decreasing aggregate pass-through. We explore the sufficient statistic arising from this model and then proceed to estimate it in the data. Here, we consider heterogeneity in demand elasticity and superelasticity. In the recent literature as well, papers such as Baqaee, Farhi and Sangani (2021) and Wang and Werning (2020) have brought to attention that certain parameters of demand are important for various macroeconomic dynamics such as the flattening of the Phillips Curve. It was also shown that the degree of these effects depends on the demand parameters, such as elasticity and superelasticity. We estimate these parameters in a novel format using an empirical procedure called Granular IV, which was first described in Gabaix and Koijen (2020) and makes use of the fact that in reality, unlike baseline macroeconomic models, some firms are big enough to impact the aggregates. For this estimation, we use firm-level price data from ACNielsen Retail Scanner database. Employing the novel empirical approach we estimate these relevant demand parameters. We estimate a demand elasticity of 3.23, in line with the literature. Our estimate for super elasticity is 3.74 which is in line with Marshall's second law of demand and for constant superelasticity parametrisation would signify the curvature of the demand curve between that of CES and linear demand.

My dissertation combines structural macroeconomic models with analyses of macro and micro data and broadly contributes to two research agendas. The first relates to the channels through which monetary policy impacts the economy. The second aims to understand how heterogeneity observed at the micro level affects the economy. The first two chapters, "Monetary Policy and Heterogeneous Mortgage Refinancing" and "A Model of Heterogeneous Mortgage Refinancing," focus on the refinancing channel of monetary policy. Since fixed-rate mortgages are the most significant source of household debt in the U.S., monetary policy can stimulate household consumption and wealth by lowering mortgage costs through refinancing. The potency of this channel will depend on households’ outstanding mortgage rates, as well as their willingness and ability to refinance. I combine empirical patterns from monthly loan-level data (from joint work with A.Burya) and a heterogeneous agent model of mortgage refinancing to show that credit score heterogeneity dampens the aggregate consumption response to monetary policy by 11%. The third and fourth chapters, "Anchoring of Inflation Expectations: An Empirical Test" and "Anchoring of Inflation Expectations: Role of Risk Premia," study the effectiveness of monetary policy in the U.S. by exploring the degree to which inflation expectations are anchored. If inflation expectations are well-anchored, then the Fed has a higher capacity to support aggregate employment when necessary, without destabilizing inflation. In joint work with A. Burya and S. Mishra, I construct a proxy of the change in the Fed's aggressiveness to inflation and develop an empirical test for inflation expectations anchoring. The proxy of the changes in the Fed's aggressiveness is equal to changes in expectations of future policy rates that are unexplained by the information contained in the inflation news release. The empirical test involves examining the sensitivity of inflation expectations to monetary policy shocks conditional on that proxy. I then use a measure of inflation expectations adjusted for inflation and liquidity risk premia to demonstrate that bond yield data in the U.S. is consistent with the anchoring of the long-term inflation expectations.