abstract: 中国证券市场一直存在着双重上市公司A、H股价差异现象，这一“同股同权不同价”的现象，长期以来都是国内外学者热议的课题之一。 本文在系统性整理前人研究成果基础上，首先对造成A、H股价差效应的内在逻辑进行了系统梳理，提炼出影响双重上市公司A、H股价格差异的9个潜在因素：信息不对称、需求差异、流动性差异、投机性差异、风险差异、公司治理结构、利率差异、市场强弱差异、汇率预期。其次，本文为各潜在影响因素构建了新的代理变量，建立面板数据模型，从全市场和行业两大视角做了实证分析，验证了影响双重上市公司A、H股价格差异的可能因素，且实证结果均通过了平稳性检验。实证结果显示：全市场视角下，仅公司治理结构和市场强弱差异对A、H价格差异的影响不显著。行业视角下，对于金融行业的双重上市公司而言，影响其A、H股价格差异的因素包括：需求差异、流动性差异、风险差异、市场强弱差异、利率差异；信息不对称、投机性差异、公司治理结构、汇率预期不具有显著影响。而对于非金融行业的双重上市公司而言，影响其A、H股价格差异的因素包括：信息不对称、需求差异、流动性差异、风险差异、投机性差异、市场强弱差异、利率差异、汇率预期；公司治理结构则不是显著的影响因素。 本文在实证分析所得结论的基础上，考虑到当前A、H股市场的现状，提出了加强资本市场双向开放、大力发展以基金为代表的机构投资者、坚定推行股票发行注册制改革、推动金融创新、丰富投资工具等建议。这一研究结果对于推动我国资本市场进一步完善，具有重要的理论与现实意义。 / Dissertation/Thesis / Doctoral Dissertation Business Administration 2019

This paper tests the regional convergence of GDP per capita across 27 Chinese provinces during the period 1961-2018 with considering the spatial interactions. First, this study only finds a slight divergence over the entire period. Furthermore, the flowing research of this paper divides the overall time span into three sub-period based on two major economic policies, namely the “Open Door Policy” and the “Western Development Strategy”. During the period 1961-1977, which is regarded as a phase of planned economy, this paper finds the evidence of regional convergence. Moreover, the results indicate a slight divergence in GDP per capita during the period 1978-1999, proving that the “Open Door Policy” intensifies regional gaps of China. Finally, this study verifies the role of the “Western Development Strategy” in reducing regional differences since a convergence is found during the last period 2000-2018. The outcomes of this research reveal a strong relationship between economic policies and regional convergence, and thus the transition of policies should be considered when investigating the economic convergence. Furthermore, this research also verifies the importance of spatial effects in the process of convergence or divergence. The results are likely to be biased if the spatial dependence is neglected.

For Chapter 1: This paper offers a meta-regression analysis of the controversial impact of EU structural funds on the growth of the recipient regions. It identifies the factors that explain the heterogeneity in the size of 323 estimates of their impact recorded in 17 econometric studies. Heterogeneity comes from the publication status, the period examined, controlling for endogeneity, from the presence of several regressors but not from differences in functional forms. For Chapter 2: Recent spatial econometric contributions call for theory-driven spatial models and W matrices capturing actual and time-varying interregional linkages. This paper answers this call by developing theoretically Griliches' well-known knowledge production function to add knowledge externalities to it. They capture how human and private capital originating from one region benefit the creation of innovation elsewhere. Furthermore, we measure interregional interaction based on the actual flows of patent creation-citation and of migration of the educated workers. They have the advantage of capturing clearly the direction of the knowledge transfers. Their presence in the theoretical model leads to a reduced-form spatial cross-regressive model which differentiates better the role of each type of externality - and displays a better goodness of fit - than the spatially lagged model where spillovers depend on geographical proximity only. Both models are estimated on spatial panel data covering the dynamics of innovation across US states over the 1986-1999 period. For Chapter 3: The Ricardian framework is increasingly used for the study of the impact of climate change on farmland values. While most of the Ricardian studies assume no interaction between the geographical units under study, the few that do rely on traditional proximity-based dependence. In this paper we argue that since the larger share of agricultural goods produced by a state is not for its own local market, including interregional trade in the Ricardian framework provides new perspectives, avoids a missing variable bias and prevents erroneous conclusions. Our new framework is applied to the system of the U.S. states over the four most recent censuses (1997-2012) and demonstrate that climate and socio-economic conditions experienced in a state's trade partners have a significant role on that state's local farmland values.

This dissertation addresses two important issues in the literature estimating the Value of a Statistical Life. The first issue is the potential endogeneity bias in cross-section hedonic wage models. The second issue is the transferability of the VSL between different policy contexts. To address the first issue, we estimate cross-section and panel hedonic wage models to identify the bias due to the time-invariant worker heterogeneity. We also consider potential endogeneity bias due to measurement error associated with risk variable, time-variant worker heterogeneity and simultaneity between wage and risk in panel models. We obtain labor market data from the 1996 Survey of Income and Program Participation panel, and occupational fatal risk data from Scotton (2000). We find that the cross-section hedonic wage model is significantly biased upward due to unobserved time-invariant worker heterogeneity, but not from time-variant worker heterogeneity or simultaneity between wage and risk. Our results are sensitive to the inclusion of industry variables, but not sensitive to the sample of workers used in estimation. To address the second issue, we examine whether or not workers and firms differentiate heterogeneous risks to determine the risk-wage compensation levels. We focus on two very different fatal risks in terms of the degree of workers’ control over the risk and the degree of dread associated with risk: violent assaults and risks related to non-violent events. We use occupational drivers to mitigate potential unobserved heterogeneity of job characteristics and measurement error associated with risk variables. The labor market data comes from the basic CPS, and the occupation-geographic specific risk rates for each cause of death are created from the non-public Census of Fatal Occupational Injuries. We find that occupational drivers require larger compensation to accept a marginal increase of violent risk as compared to non-violent risk. This is true for both fatal and non-fatal risks. Our results are quite robust. This study suggests that current direct use of VSL obtained from hedonic wage studies in benefit estimation of various governmental programs should be reconsidered.

Paskutiniais metais aktualiu klausimu tampa inovacijų modeliavimas. Pasirodant kiekvienai naujovei, verslininkams reikia suprasti ir prognozuoti rinkos vystymąsi, kad galėtų numatyti pardavimų eigą, planuoti pardavimų kiekius ir atlikti finansinį planavimą. Šiame darbe tyrinėsime kompiuterių skverbties koeficientus (penetration rate) 23 skirtingose pasaulio šalyse ir mėginsime parinkti geriausiai prognozavimui tinkantį modelį. Skverbties koeficientas paprastai parodo prekės ženklo ar produkto kategorijos populiarumą. Jis apskaičiuojamas dalinant žmonių, kurie perka kažkokią prekę ar paslaugą, skaičių iš tos rinkos visos populiacijos skaičiaus tam tikru periodu. Taigi, skverbties koeficientas yra procentas žmonių populiacijoje, kurie per stebimą periodą nusipirko tam tikrą prekę ar paslaugą. Marketinge dažnai yra spendžiama problema: didinti pardavimus stengiantis privilioti klientus iš konkurentų ar plečiant potencialių pirkėjų populiaciją, t.y. einant į naujas rinkas. Darbo pradžioje bus pristatyti panelinių duomenų vertinimo būdai, analizei reikalinga teorinė dalis, kai kurių reikalingų statistikų skaičiavimas. Vėliau pereisime prie pagrindinės darbo dalies - geriausio modelio parinkimo. Pirmiausia bus nagrinėjami paprasčiausi tiesinio trendo modeliai, įtraukiant autoregresijos procesą bei egzogeninius kintamuosius. Toliau įvairiais metodais mėginsime modeliuoti difuzijos procesą. Bandysime jį aproksimuoti kvadratiniu trendu, taikyti logistinį bei Gompertz modelius ir... [toliau žr. visą tekstą] / Lately the modelling of innovation process is a constantly recurring problem. As with any new service for managers it is important to understand and to able to forecast the market developement for strategic, capacity and financial planning purposes. This master thesis analyses computer penetration data in 23 different countries and tries to propose the best fitting model for forcasting. Penetration rate usually shows the popularity of a brand or a product. It is given as a percentage of the countries’ households who have bought that particular brand or product at least once within a defined period of time. In marketing there is a decision to make: enlarge sales by trying to attract more costumers in the sales region or by expanding the population of potential buyers, i.e. by expanding to other emerging markets. In the beginning of this thesis we will introduce some basic information about the panel data and some approaches of the theory needed for estimation. Later on we will pass to the main part of the work which is devoted to choosing the model. At first, we analyze some linear trend models with autoregression terms and exogenous variables. Then we examine a diffusion process by approximating it with a quadratic trend, logistic and Gompertz models. Also some basic information about the Bass diffusion model will be provided.

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This thesis consists of three papers that makes independent contributions to the fields of forecast evaluation and financial econometrics. As such, the papers, chapter 1-3, can be read independently of each other. In Chapter 1, “Inferring an agent’s loss function based on a term structure of forecasts”, we provide conditions for identification, estimation and inference of an agent’s loss function based on an observed term structure of point forecasts. The loss function specification is flexible as we allow the preferences to be both asymmetric and to vary non-linearly across the forecast horizon. In addition, we introduce a novel forecast rationality test based on the estimated loss function. We employ the approach to analyse the U.S. Government’s preferences over budget surplus forecast errors. Interestingly, we find that it is relatively more costly for the government to underestimate the budget surplus and that this asymmetry is stronger at long forecast horizons. In Chapter 2, “Monitoring Systemic Risk”, we define systemic risk as the conditional probability of a systemic banking crisis. This conditional probability is modelled in a fixed effect binary response panel-model framework that allows for cross-sectional dependence (e.g. due to contagion effects). In the empirical application we identify several risk factors and it is shown that the level of systemic risk contains a predictable component which varies through time. Furthermore, we illustrate how the forecasts of systemic risk map into dynamic policy thresholds in this framework. Finally, by conducting a pseudo out-of-sample exercise we find that the systemic risk estimates provided reliable early-warning signals ahead of the recent financial crisis for several economies. Finally, in Chapter 3, “Equity Premium Predictability”, we reassess the evidence of out-of- sample equity premium predictability. The empirical finance literature has identified several financial variables that appear to predict the equity premium in-sample. However, Welch & Goyal (2008) find that none of these variables have any predictive power out-of-sample. We show that the equity premium is predictable out-of-sample once you impose certain shrinkage restrictions on the model parameters. The approach is motivated by the observation that many of the proposed financial variables can be characterised as ’weak predictors’ and this suggest that a James-Stein type estimator will provide a substantial risk reduction. The out-of-sample explanatory power is small, but we show that it is, in fact, economically meaningful to an investor with time-invariant risk aversion. Using a shrinkage decomposition we also show that standard combination forecast techniques tends to ’overshrink’ the model parameters leading to suboptimal model forecasts.

Submitted by Lueh Polsinelli Bedin (lueh.bedin@gmail.com) on 2015-09-05T00:28:34Z No. of bitstreams: 1 ANÁLISE EMPÍRICA DA RELAÇÃO ENTRE A TAXA DE DESEMPREGO E A INADIMPLÊNCIA.pdf: 1177272 bytes, checksum: 2c80629f70420824b1b799532acd09d5 (MD5) / Approved for entry into archive by Renata de Souza Nascimento (renata.souza@fgv.br) on 2015-09-08T17:23:08Z (GMT) No. of bitstreams: 1 ANÁLISE EMPÍRICA DA RELAÇÃO ENTRE A TAXA DE DESEMPREGO E A INADIMPLÊNCIA.pdf: 1177272 bytes, checksum: 2c80629f70420824b1b799532acd09d5 (MD5) / Made available in DSpace on 2015-09-08T20:04:44Z (GMT). No. of bitstreams: 1 ANÁLISE EMPÍRICA DA RELAÇÃO ENTRE A TAXA DE DESEMPREGO E A INADIMPLÊNCIA.pdf: 1177272 bytes, checksum: 2c80629f70420824b1b799532acd09d5 (MD5) Previous issue date: 2015-08-18 / Dentro de um cenário de recessão econômica é razoável existir uma preocupação maior com o risco de crédito. Algumas variáveis macroeconômicas, como taxa de desemprego, taxa de juros e inflação, são apontadas como responsáveis por choques no sistema financeiro. Esses choques podem provocar efeitos adversos como aumento da inadimplência, provisionamentos de crédito e, num caso extremo, quebra de instituições financeiras. Este trabalho contribuiu na linha da economia comportamental e do risco de crédito, analisando uma possível reação da taxa de inadimplência sob um efeito de variações da taxa de desemprego brasileira. Os dados utilizados foram de inadimplência e taxa de desemprego de pessoas físicas de seis regiões metropolitanas do Brasil. Construímos modelos estatísticos em painel utilizando efeitos fixos. Realizamos também uma breve análise dos dados utilizando conceitos de séries temporais, aplicando funções de impulso resposta. E, no intuito de tornar o estudo mais robusto, analisamos também o efeito do choque da taxa de desemprego nas variáveis de inadimplência e atraso curto prazo do BACEN de forma comparativa. Nas metodologias aplicadas, os resultados nos mostraram uma baixa significância estatística ao utilizarmos a taxa de desemprego para responder a inadimplência. Já para explicar o atraso curto prazo, encontramos significância estatística. / In a recession scenario it is reasonable to be a greater concern for the credit risk. Some macroeconomic variables such as unemployment, interest rates and inflation, are seen as responsible for shocks in the financial system. These shocks can cause adverse effects such as rising defaults, provision for credit losses and, in an extreme case, breaking financial institutions. This work contributed in the line of behavioral economics and credit risk, analyzing a possible reaction of default under the effect of variations of the Brazilian unemployment rate. The data used were default and unemployment rate of individuals of six metropolitan areas of Brazil. We build statistical models panel using fixed effects. We also do a brief analysis of the data using concepts of time series, applying impulse response functions. And in order to make a robust study we also analyzed the effect of the shock of the unemployment rate in default variables and short-term delay of the Brazilian Central Bank in a comparative way. The results showed us a low statistical significance when we use the unemployment rate to explain the relationship of unemployment and default. But to explain the short-term delay of the Brazilian Central Bank, we met statistical significance.

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