Academic literature on the topic 'Capital movements Econometric models'

Forecasting the future price trend of a stock traded on a financial exchange is the aim of stock market prediction. In recent decades, stock market prediction has been a fascinating topic in the domain of Data Science and Finance. In reality, the stock movement is ambiguous and chaotic due to various influencing factors such as government policy, current events, interest rates Etc. At the same time, accurate enough forecasting of stock price movement leads to substantial benefits for investors. This paper provides a comprehensive review of the application and comparison of Machine Learning (ML) algorithms and Econometric Models in stock market prediction. The mentioned models are categorized into (i) ML algorithms, including Linear Regression (LR), K-nearest neighbors (KNN), Support Vector Machine (SVM), and Long Short-Term Memory (LSTM). (ii) Econometric Models, including Autoregressive Integrated Moving Average (ARIMA) Model, Capital Asset Pricing Model (CAPM), and Fama-French (FF) Factor Model.

The paper re-examines the ?stylized facts? of the balanced growth in developed economies, looking specifically at capital productivity variable. The economic data is obtained from European Commission AMECO database, spanning 1961-2014 period. For a sample of 22 OECD economies, the paper applies univariate LM unit root tests with one or two structural breaks, and estimates error-correction and linear trend models with breaks. It is shown that diverse statistical patterns were present across economies and overall mixed evidence is provided as to the stability of capital productivity and balanced growth in general. Specifically, both upward and downward trends in capital productivity were present, while in several economies mean reversion and random walk patterns were observed. The data and results were largely in line with major theoretical explanations pertaining to capital productivity. With regard to determinants of the capital productivity movements, the structure of capital stock and the prices of capital goods were likely most salient.

This paper looks at the spatial relationship of the average per capita income growth using provincial data from 1988 to 2009. The results from the study provide insights on the geographical dimensions of provincial income growth and showed evidence on the role of spatial effects in the formal econometric analysis of intra-country income growth models. Despite data limitations, the study provides a strong empirical evidence of the presence of positive spatial dependence or degree of similarity in the average per capita income growth of the provinces, albeit the degree of positive spatial dependence weakens in the latter periods. This positive spatial correlation suggests the provinces may be converging in terms of their income growth and they do so in movements similar to their neighbors. Moreover, the study shows that spatial dependence weakened in the latter periods (1994-2000 and 2000-2009). The weakening of spatial dependence may provide insights on the uneven provincial/regional income growth experienced in the country. One possible explanation of the weak spatial dependence is that two or more groups of neighboring provinces are growing at similar rates within the group, but at different rates across groups. This opens the possibility of having different convergence clubs (of provinces) within the country.

One way to overcome resource constraints in the Russian economy, which could boost its efficiency, is implementing measures of structural policy that affect resource movement. The paper studies opportunities of growth through the development of the manufacturing sector and movement of the resources between sectors. Methodologically the research relies on the Keynesian approach to economic growth, which is of structural nature and appears to be the most relevant for scrutinizing structural specifics of growth and resources distribution within the economy. In terms of methods, the paper applies structural analysis and uses elements of econometric modelling. General and special industrialisation criteria allow establishing whether the economy is industrial by structure or by the level of technological development. On the basis of the obtained models the authors judge how the sectors’ risk / profitability ratio impacts on the movement of capital and labour between them. The findings reveal that if the structural policy affects the ratio between risk and profitability, as well as the level of sector’s technology-intensity due to spurring investment into new technologies (under decrease in risk), the manufacturing sector will receive an additional resource, improve its dynamics, and increase its contribution to GDP growth. The scenario forecast of the industrialisation criteria depending on the risk in the manufacturing sector points to the conclusion that the risk is to be diminished to raise the contribution of the manufacturing sector to GDP growth and simultaneously intensify the tech nological industrialisation.

In this paper, the situation in the Iraqi economy for the period of 2000-2020 has been analyzed using three hybrid models. The research hypothesis was launched from the necessity of interaction between the activity of the Iraqi market for securities and the local financial and economic institutions. The hypothesis has been verified accordingly using Kolmogorov-Smirnov Test, normality test and Multicollinearity Test. The statistical analysis was based on the three mathematical models to expect return and risk values of Iraqi money market. Three basic models (optimization (BO), Optimized Return Value (ORV), General Optimization Risk (GOR)) have been conducted to optimize and analyze the given data accordingly. The research reached several conclusions, the most prominent of which is the limited economic role of the Iraqi market for securities; the potential exposure to negative effects that could be produced by international crises because of the expected openness, due to the possibility of illegal capital movements resulting in irrational speculation; the difficulty of implementing monetary and financial policies, due to vulnerability to international challenges

When industrial relics, such as obsolete buildings, sites, and infrastructures, enter into a process of adaptive reuse, they become transformation engines capable of shaping the urban fabric. They provide tangible and intangible links to our past and have the potential to play a significant role in today’s cities’ futures. One unresolved issue is the quantification of the externalities of these transformation processes. If undertaken correctly, adaptive reuse can contribute to the development of social and cultural capital, environmental sustainability, urban regeneration, and, most importantly, economic benefits to the surrounding community. In this sense, understanding the value of heritage is particularly important in light of the new European urban environmental policy movement based on the circular economy, which aims to change the way Member States consume and produce materials and energy. After a review of the externalities generated by the adaptive reuse of disused industrial heritage, the paper will concentrate on the estimation of economic benefits given by a transformation process that affected Turin’s Aurora district (Northern Italy) during the last years. The hedonic pricing method (HPM) was used to investigate the effects of the construction of new headquarters and the redevelopment of an old power plant converted into a museum and conference center. This study used econometric models to identify a significant increase in market prices within 800 m of the site and calculated a EUR 16,650,445 capitalized benefit from the transformation on the surrounding residential building stock. The study thus contributed to the awareness that reused heritage not only improves the lives of residents, but it also has a positive impact on the real estate market, in terms of transactions, as well as market values.

ABSTRACT This study provides theory and evidence to demonstrate how relative firm profitability within an industry affects stock return sensitivity to industry-level news. Extending the Cournot and Bertrand competition models, we predict that (1) the returns of less profitable firms in an industry are more sensitive to industry-level news than those of more profitable firms, and that (2) this inverse relation between relative profitability and return sensitivity is more pronounced when there is positive rather than negative industry news, especially in industries with high (versus low) capital intensity. Using industry returns to proxy for industry-level news, we obtain empirical results consistent with these predictions. We further find that the two fundamental factors that contribute to profitability—cost efficiency and market share—each exhibit an effect similar to that of relative profitability in affecting return sensitivity. Our results remain unchanged after controlling for stock price movements attributable to common risk factors and firm-specific accounting information, and they hold over a range of robustness tests.

The article critically analyzes the American economic model, focusing on the historical strengths of the US economy. It is pointed out that among American economists there is a different understanding of the specifics of the American economic model, which, along with its strengths, has many weaknesses and vulnerabilities. At the same time, it is stated that the concept of the "American economic model" is predominantly ideological in nature, reflecting the historically formed ideology of the American exceptionalism applied to the economic sphere of society. In the context of globalization, there is a process of leveling out many elements of the American economic system, claiming to be elevated to a certain kind of absolute, which are becoming widespread in the economies of other highly developed countries, since the globalization of the world economy over the past 25-30 years was built on the premises of the maximum possible free movement of capital, labor, goods and services. As a result, many parameters of the American economic system undergo evolutionary changes in which they increasingly become similar to the parameters of the economies of other countries. In addition, the practice of compiling the system of national economic accounts, which has formed over the past 70 years under the auspices of the UN, is based on the idea of their unification and applicability to economies with different levels of economic development without highlighting specific qualitative characteristics inherent in the economies of different countries. In parallel, economic modeling, including using econometric methods, practiced in American universities and think tanks, is also based on abstract models, which are based solely on quantitative indicators omitting the specific qualitative properties of the economy of each country, including the US economy. The parameters of the American economic system that evolve over time are turning into a steady reduction in the dominant role of the United States in the world economy, taken in terms of their share in world GDP, which has almost halved since 1960, from 40% to 24%, and according to the American forecasts will tend to decline further in the near foreseeable future.

Purpose The purpose of this paper is to compare business cycle fluctuations in Ethiopia under interest rate and money growth rules. Design/methodology/approach In order to achieve this objective, the author constructs a medium-scale open economy dynamic stochastic general equilibrium (DSGE) model. The model features several nominal and real distortions including habit formation in consumption, price rigidity, deviation from purchasing power parity and imperfect capital mobility. The paper also distinguishes between liquidity-constrained and Ricardian households. The model parameters are calibrated for the Ethiopian economy based on data covering the period January 2000–April 2015. Findings The main result suggests that: the model economy with money growth rule is substantially less powerful or more muted for the amplification and transmission of exogenous shocks originating from government spending programs, monetary policy, technological progress and exchange rate movements. The responses of output to fiscal policy shocks are relatively stronger under autarky which appears to confirm the findings of Ilzetzki et al. (2013) who suggest bigger multipliers in self-sufficient, closed economies. With regard to positive productivity shock, however, the model with interest rate feedback rule generates a decline in output and an increase in inflation, which are at odds with conventional empirical regularities. Research limitations/implications The major implication is that a central bank regulating some measure of monetary stocks should not expect (fear) as much expansion (contraction) in output following currency devaluation (liquidity withdrawal) as a sister central bank that relies on an interest rate feedback rule. As emphasized by Mishra et al. (2010) the necessary conditions for stronger transmission of interest-rule-based monetary policy shocks are hardly existent in emerging and developing economies targeting monetary aggregates; hence the relatively weaker responses of output and inflation in the model economy with money growth rule. Monetary policy authorities need to be cautious when using DSGE models to analyze business cycle dynamics. Quite often, DSGE models tend to mimic the proverbial “crooked house” built to every man’s advise. Whenever additional modification is made to an existing baseline model, previously established regularities break down. For instance, this paper documented negative response of output to technology shock. Such contradictions are not uncommon. For example, Furlanetto (2006) and Ramayandi (2008) have also found similarly inconsistent responses to fiscal and productivity shocks, respectively. Originality/value Using DSGE models for research and teaching purposes is not common in developing economies. To the best of the author’s knowledge, only one other Ethiopian author did apply DSGE model to study business cycle fluctuation in Ethiopia albeit under the implausible assumption of perfect capital mobility and a central bank following interest rate rule. The contribution of this paper is that it departs from these two unrealistic assumptions by allowing international risk premium as a function of the net foreign asset position of the country and by applying money growth rule which closely mimics the behavior of central banks in low-income economies such as Ethiopia.

The impact of financial risks on share prices concerns investors, company executives and accounting standards developers. Investors need this information in delineating their equity valuation models while company executives need the information to make appropriate capital structure decisions. Accounting standards developers use this information in their policy to make accounting standards contemporary. The authors examine the link between relative and absolute financial risks and share prices using a dynamic panel of non-financial listed companies on the Zimbabwe Stock Exchange after dollarization. Equity investors incurred losses before dollarization, which prompted this investigation into the sphere of financial risks in order to explain share price movements so that investors can use it to minimize losses in the future. Absolute financial risk is measured by the total debt, while debt/equity ratio measures relative financial risk. Market capitalization as a proxy for equity and debt is measured by total liabilities. An average debt/equity ratio greater or equal to one qualifies a firm into the high-risk category while ratios below one imply low-risk firms. Results from two-step System Generalised Method of Moments (GMM) show negative and significant connection between relative risk and share prices across risk categories. The impact of absolute risk on share prices differs by risk category. Firm managers are advised to keep total liabilities below market capitalization in order to enjoy the benefits of low-risk categorization. Debt ratio is a reasonable indicator of value and investors can use it in equity valuation. Mandatory reporting of debt ratios should be considered by accounting standards developers.

Over the last years, the growing availability of large datasets and the improvements in the computational speed of computers have further fostered the research in the fields of both macroeconomic modeling and forecasting analysis. A primary focus of these research areas is to improve the models performance by exploiting the informational content of several time series. Increasing the dimension of macro models is indeed crucial for a detailed structural understanding of the economic environment, as well as for an accurate forecasting analysis. As consequence, a new generation of large-scale macro models, based on the micro-foundations of a fully specified dynamic stochastic general equilibrium set-up, has became one of the most flourishing research areas of interest both in central banks and academia. At the same time, there has been a revival of forecasting methods dealing with many predictors, such as the factor models. The central idea of factor models is to exploit co-movements among variables through a parsimonious econometric structure. Few underlying common shocks or factors explain most of the co-variations among variables. The unexplained component of series movements is on the other hand due to pure idiosyncratic dynamics. The generality of their framework allows factor models to be suitable for describing a broad variety of models in a macroeconomic and a financial context. The revival of factor models, over the recent years, comes from important developments achieved by Stock and Watson (2002) and Forni, Hallin, Lippi and Reichlin (2000). These authors find the conditions under which some data averages become collinear to the space spanned by the factors when, the cross section dimension, becomes large. Moreover, their factor specifications allow the idiosyncratic dynamics to be mildly cross-correlated (an effect referred to as the 'approximate factor structure' by Chamberlain and Rothschild, 1983), a situation empirically verified in many applications. These findings have relevant implications. The most important being that the use of a large number of series is no longer representative of a dimensional constraint. On the other hand, it does help to identify the factor space. This new generation of factor models has been applied in several areas of macroeconomics and finance as well as for policy evaluation. It is consequently very likely to become a milestone in the literature of forecasting methods using many predictors. This thesis contributes to the empirical literature on factor models by proposing four original applications.

In the first chapter of this thesis, the generalized dynamic factor model of Forni et. al (2002) is employed to explore the predictive content of the asset returns in forecasting Consumer Price Index (CPI) inflation and the growth rate of Industrial Production (IP). The connection between stock markets and economic growth is well known. In the fundamental valuation of equity, the stock price is equal to the discounted future streams of expected dividends. Since the future dividends are related to future growth, a revision of prices, and hence returns, should signal movements in the future growth path. Though other important transmission channels, such as the Tobin's q theory (Tobin, 1969), the wealth effect as well as capital market imperfections, have been widely studied in this literature. I show that an aggregate index, such as the S&P500, could be misleading if used as a proxy for the informative content of the stock market as a whole. Despite the widespread wisdom of considering such index as a leading variable, only part of the assets included in the composition of the index has a leading behaviour with respect to the variables of interest. Its forecasting performance might be poor, leading to sceptical conclusions about the effectiveness of asset prices in forecasting macroeconomic variables. The main idea of the first essay is therefore to analyze the lead-lag structure of the assets composing the S&P500. The classification in leading, lagging and coincident variables is achieved by means of the cross correlation function cleaned of idiosyncratic noise and short run fluctuations. I assume that asset returns follow a factor structure. That is, they are the sum of two parts: a common part driven by few shocks common to all the assets and an idiosyncratic part, which is rather asset specific. The correlation

function, computed on the common part of the series, is not affected by the assets' specific dynamics and should provide information only on the series driven by the same common factors. Once the leading series are identified, they are grouped within the economic sector they belong to. The predictive content that such aggregates have in forecasting IP growth and CPI inflation is then explored and compared with the forecasting power of the S&P500 composite index. The forecasting exercise is addressed in the following way: first, in an autoregressive (AR) model I choose the truncation lag that minimizes the Mean Square Forecast Error (MSFE) in 11 years out of sample simulations for 1, 6 and 12 steps ahead, both for the IP growth rate and the CPI inflation. Second, the S&P500 is added as an explanatory variable to the previous AR specification. I repeat the simulation exercise and find that there are very small improvements of the MSFE statistics. Third, averages of stock return leading series, in the respective sector, are added as additional explanatory variables in the benchmark regression. Remarkable improvements are achieved with respect to the benchmark specification especially for one year horizon forecast. Significant improvements are also achieved for the shorter forecast horizons, when the leading series of the technology and energy sectors are used.

The second chapter of this thesis disentangles the sources of aggregate risk and measures the extent of co-movements in five European stock markets. Based on the static factor model of Stock and Watson (2002), it proposes a new method for measuring the impact of international, national and industry-specific shocks. The process of European economic and monetary integration with the advent of the EMU has been a central issue for investors and policy makers. During these years, the number of studies on the integration and linkages among European stock markets has increased enormously. Given their forward looking nature, stock prices are considered a key variable to use for establishing the developments in the economic and financial markets. Therefore, measuring the extent of co-movements between European stock markets has became, especially over the last years, one of the main concerns both for policy makers, who want to best shape their policy responses, and for investors who need to adapt their hedging strategies to the new political and economic environment. An optimal portfolio allocation strategy is based on a timely identification of the factors affecting asset returns. So far, literature dating back to Solnik (1974) identifies national factors as the main contributors to the co-variations among stock returns, with the industry factors playing a marginal role. The increasing financial and economic integration over the past years, fostered by the decline of trade barriers and a greater policy coordination, should have strongly reduced the importance of national factors and increased the importance of global determinants, such as industry determinants. However, somehow puzzling, recent studies demonstrated that countries sources are still very important and generally more important of the industry ones. This paper tries to cast some light on these conflicting results. The chapter proposes an econometric estimation strategy more flexible and suitable to disentangle and measure the impact of global and country factors. Results point to a declining influence of national determinants and to an increasing influence of the industries ones. The international influences remains the most important driving forces of excess returns. These findings overturn the results in the literature and have important implications for strategic portfolio allocation policies; they need to be revisited and adapted to the changed financial and economic scenario.

The third chapter presents a new stylized fact which can be helpful for discriminating among alternative explanations of the U.S. macroeconomic stability. The main finding is that the fall in time series volatility is associated with a sizable decline, of the order of 30% on average, in the predictive accuracy of several widely used forecasting models, included the factor models proposed by Stock and Watson (2002). This pattern is not limited to the measures of inflation but also extends to several indicators of real economic activity and interest rates. The generalized fall in predictive ability after the mid-1980s is particularly pronounced for forecast horizons beyond one quarter. Furthermore, this empirical regularity is not simply specific to a single method, rather it is a common feature of all models including those used by public and private institutions. In particular, the forecasts for output and inflation of the Fed's Green book and the Survey of Professional Forecasters (SPF) are significantly more accurate than a random walk only before 1985. After this date, in contrast, the hypothesis of equal predictive ability between naive random walk forecasts and the predictions of those institutions is not rejected for all horizons, the only exception being the current quarter. The results of this chapter may also be of interest for the empirical literature on asymmetric information. Romer and Romer (2000), for instance, consider a sample ending in the early 1990s and find that the Fed produced more accurate forecasts of inflation and output compared to several commercial providers. The results imply that the informational advantage of the Fed and those private forecasters is in fact limited to the 1970s and the beginning of the 1980s. In contrast, during the last two decades no forecasting model is better than "tossing a coin" beyond the first quarter horizon, thereby implying that on average uninformed economic agents can effectively anticipate future macroeconomics developments. On the other hand, econometric models and economists' judgement are quite helpful for the forecasts over the very short horizon, that is relevant for conjunctural analysis. Moreover, the literature on forecasting methods, recently surveyed by Stock and Watson (2005), has devoted a great deal of attention towards identifying the best model for predicting inflation and output. The majority of studies however are based on full-sample periods. The main findings in the chapter reveal that most of the full sample predictability of U.S. macroeconomic series arises from the years before 1985. Long time series appear

to attach a far larger weight on the earlier sub-sample, which is characterized by a larger volatility of inflation and output. Results also suggest that some caution should be used in evaluating the performance of alternative forecasting models on the basis of a pool of different sub-periods as full sample analysis are likely to miss parameter instability.

The fourth chapter performs a detailed forecast comparison between the static factor model of Stock and Watson (2002) (SW) and the dynamic factor model of Forni et. al. (2005) (FHLR). It is not the first work in performing such an evaluation. Boivin and Ng (2005) focus on a very similar problem, while Stock and Watson (2005) compare the performances of a larger class of predictors. The SW and FHLR methods essentially differ in the computation of the forecast of the common component. In particular, they differ in the estimation of the factor space and in the way projections onto this space are performed. In SW, the factors are estimated by static Principal Components (PC) of the sample covariance matrix and the forecast of the common component is simply the projection of the predicted variable on the factors. FHLR propose efficiency improvements in two directions. First, they estimate the common factors based on Generalized Principal Components (GPC) in which observations are weighted according to their signal to noise ratio. Second, they impose the constraints implied by the dynamic factors structure when the variables of interest are projected on the common factors. Specifically, they take into account the leading and lagging relations across series by means of principal components in the frequency domain. This allows for an efficient aggregation of variables that may be out of phase. Whether these efficiency improvements are helpful to forecast in a finite sample is however an empirical question. Literature has not yet reached a consensus. On the one hand, Stock and Watson (2005) show that both methods perform similarly (although they focus on the weighting of the idiosyncratic and not on the dynamic restrictions), while Boivin and Ng (2005) show that SW's method largely outperforms the FHLR's and, in particular, conjecture that the dynamic restrictions implied by the method are harmful for the forecast accuracy of the model. This chapter tries to shed some new light on these conflicting results. It

focuses on the Industrial Production index (IP) and the Consumer Price Index (CPI) and bases the evaluation on a simulated out-of sample forecasting exercise. The data set, borrowed from Stock and Watson (2002), consists of 146 monthly observations for the US economy. The data spans from 1959 to 1999. In order to isolate and evaluate specific characteristics of the methods, a procedure, where the

two non-parametric approaches are nested in a common framework, is designed. In addition, for both versions of the factor model forecasts, the chapter studies the contribution of the idiosyncratic component to the forecast. Other non-core aspects of the model are also investigated: robustness with respect to the choice of the number of factors and variable transformations. Finally, the chapter performs a sub-sample performances of the factor based forecasts. The purpose of this exercise is to design an experiment for assessing the contribution of the core characteristics of different models to the forecasting performance and discussing auxiliary issues. Hopefully this may also serve as a guide for practitioners in the field. As in Stock and Watson (2005), results show that efficiency improvements due to the weighting of the idiosyncratic components do not lead to significant more accurate forecasts, but, in contrast to Boivin and Ng (2005), it is shown that the dynamic restrictions imposed by the procedure of Forni et al. (2005) are not harmful for predictability. The main conclusion is that the two methods have a similar performance and produce highly collinear forecasts.

Doctorat en sciences économiques, Orientation économie
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Historically, the Consumption Capital Asset Pricing Method (C-CAPM) has performed poorly in that estimated parameters are implausible, model restrictions are often rejected and inferences appear to be very sensitive to the choice of economic agents' preferences. In this study, we estimate and test the C-CAPM with Constant Relative Risk Aversion (CRRA) using time series data from Germany, South Africa, Britain and America during relatively short time periods with the latest available data sets. Hansen's GMM approach is applied to estimate the parameters arising from this model. In general, estimated parameters fall outside the bounds specified by Lund & Engsted (1996) and Cuthbertson & Nitzsche (2004), even though the models are not rejected by the J-test and are associated with relatively small minimum distances.

Traditional financial theories see capital structure as a result of mainly financial, tax and growth factors (Modigliani & Miller, 1958). But corporate governance theories (Jensen & Meckling, 1976) and business strategy theories (Barton & Gordon, 1988) suggest that ownership structure and ownership concentration, product diversification and asset specificity may also influence capital structure. Focusing on the examination of the determinants of capital structure in Chinese listed companies, this research goes beyond financial factors and considered business strategy and corporate governance approaches, and their impact on capital structure, in a transitioning Chinese context where institutions, expertise and regulatory processes are different to, but converging on, Western approaches. A panel data set of 1,098 Chinese listed companies for the period of 1991 to 2000 was collected from published sources, and conventional and innovative econometric methodologies were used to model a range of relationships between capital structure and its financial and non-financial determinants. The statistical approaches used in this study included Ordinary Least Squares Model and also Linear Mixed Model, which is a powerful tool to examine panel data where independence of explanatory variables is not assumed. The analysis also involved Hox’s model building procedures to measure model fit. The capital structure of listed companies in both the Shenzhen Stock Exchange and the Shanghai Securities Exchange is positively related to a firm’s tax rate, growth and capital intensity and negatively related to a firm’s profit and size. Other financial factors such as tangibility, risk and duration are non-significant. The capital structure of listed companies, particularly in the Shenzhen Stock Exchange, is positively related to product diversification and negatively related to asset specificity. The capital structure of listed companies in the Shanghai Securities Exchange is positively related to government ownership and ownership concentration of the largest shareholder and negatively related to legal person ownership and ownership concentration of the ten largest shareholders. The data and modelling support financial and non-financial determinants of capital structure. In particular, information asymmetry, business diversity and asset specificity have a significant impact on capital structure. In addition the empirical work in the study supports agency cost explanations of debt and equity. Finally the research demonstrates that the two main financial markets in China, Shenzhen and Shanghai, have operated differently but are converging towards a common norm. The research contributes to the general field of capital structure and provides valuable insights into the nature of the Chinese firm and the evolution of the Chinese financial system.
Doctor of Philosophy

Traditional financial theories see capital structure as a result of mainly financial, tax and growth factors (Modigliani & Miller, 1958). But corporate governance theories (Jensen & Meckling, 1976) and business strategy theories (Barton & Gordon, 1988) suggest that ownership structure and ownership concentration, product diversification and asset specificity may also influence capital structure. Focusing on the examination of the determinants of capital structure in Chinese listed companies, this research goes beyond financial factors and considered business strategy and corporate governance approaches, and their impact on capital structure, in a transitioning Chinese context where institutions, expertise and regulatory processes are different to, but converging on, Western approaches. A panel data set of 1,098 Chinese listed companies for the period of 1991 to 2000 was collected from published sources, and conventional and innovative econometric methodologies were used to model a range of relationships between capital structure and its financial and non-financial determinants. The statistical approaches used in this study included Ordinary Least Squares Model and also Linear Mixed Model, which is a powerful tool to examine panel data where independence of explanatory variables is not assumed. The analysis also involved Hox’s model building procedures to measure model fit. The capital structure of listed companies in both the Shenzhen Stock Exchange and the Shanghai Securities Exchange is positively related to a firm’s tax rate, growth and capital intensity and negatively related to a firm’s profit and size. Other financial factors such as tangibility, risk and duration are non-significant. The capital structure of listed companies, particularly in the Shenzhen Stock Exchange, is positively related to product diversification and negatively related to asset specificity. The capital structure of listed companies in the Shanghai Securities Exchange is positively related to government ownership and ownership concentration of the largest shareholder and negatively related to legal person ownership and ownership concentration of the ten largest shareholders. The data and modelling support financial and non-financial determinants of capital structure. In particular, information asymmetry, business diversity and asset specificity have a significant impact on capital structure. In addition the empirical work in the study supports agency cost explanations of debt and equity. Finally the research demonstrates that the two main financial markets in China, Shenzhen and Shanghai, have operated differently but are converging towards a common norm. The research contributes to the general field of capital structure and provides valuable insights into the nature of the Chinese firm and the evolution of the Chinese financial system.
Doctor of Philosophy

[Truncated abstract] This thesis examines competing asset-pricing models in Australia with the goal of establishing the model which best explains cross-sectional stock returns. The research employs Australian equity data over the period 1980-2001, with the major analyses covering the more recent period 1990-2001. The study first documents that existing asset-pricing models namely the capital asset pricing model (CAPM) and domestic Fama-French three-factor model fail to meet the widely applied Merton?s zero-intercept criterion for a well-specified pricing model. This study instead documents that the US three-factor model provides the best description of Australian stock returns. The three US Fama-French factors are statistically significant for the majority of portfolios consisting of large stocks. However, no significant coefficients are found for portfolios in the smallest size quintile. This result initially suggests that the largest firms in the Australian market are globally integrated with the US market while the smallest firms are not. Therefore, the evidence at this point implies domestic segmentation in the Australian market. This is an unsatisfying outcome, considering that the goal of this research is to establish the pricing model that best describes portfolio returns. Given pervasive evidence that liquidity is strongly related to stock returns, the second part of the major analyses derives and incorporates this potentially priced factor to the specified pricing models ... This study also introduces a methodology for individual security analysis, which implements the portfolio analysis, in this part of analyses. The technique makes use of visual impressions conveyed by the histogram plots of coefficients' p-values. A statistically significant coefficient will have its p-values concentrated at below a 5% level of significance; a histogram of p-values will not have a uniform distribution ... The final stage of this study employs daily return data as an examination of what is indeed the best pricing model as well as to provide a robustness check on monthly return results. The daily result indicates that all three US Fama-French factors, namely the US market, size and book-to-market factors as well as LIQT are statistically significant, while the Australian three-factor model only exhibits one significant market factor. This study has discovered that it is in fact the US three-factor model with LIQT and not the domestic model, which qualifies for the criterion of a well-specified asset-pricing model and that it best describes Australian stock returns.

Chapter 1: The Determinants of the Production of Research by US Universities

Chapter 2: Investment in Vocational and General Human Capital: A Theoretical Approach

Chapter 3: Urban Migrations and the Labor Market

Chapter 4: Local social capital and geographical mobility

Chapter 5: Social Supervision and Electoral Stability on the Geographical Scale in Belgium
Doctorat en Sciences économiques et de gestion
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Orientador: Daniela Magalhães Prates
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Economia
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Resumo: Uma das características fundamentais da dinâmica das finanças internacionais no contexto de globalização financeira é a volatilidade dos fluxos de capitais. Essa volatilidade é decorrente da dominância da lógica financeira sobre a produtiva no capitalismo contemporâneo e das atuais características do sistema monetário internacional (SMI). Em períodos de elevado apetite pelo risco, os fluxos de capitais tendem a elevar sua participação nos países em desesnvolvimento. Já nos momentos de elevada preferência por liquidez, esses fluxos migram para os países desenvolvidos, principalmente para os Estados Unidos. Esta tese pretende dar uma contribuição à literatura empírica sobre os determinantes dos fluxos de capitais aos países em desenvolvimento por meio de um modelo econométrico de dados em painel com a utilização de diferentes métodos: mínimos quadrados ordinários (Ordinary Least Squares), efeitos fixos (fixed effects), efeitos aleatórios (random effects), primeira diferença (first difference) e método dos momentos generalizados (Generalized method of moments). Os resultados obtidos contribuíram com os estudos anteriores que apontaram para um predomínio dos fatores externos sobre os internos na determinação dos fluxos de capitais. Merece destaque o indicador de volatilidade VIX CBOE, o qual se mostrou significativo e com sinal esperado nas quinze equações testadas
Abstract: One of the key features of the dynamics of international finance in the context of financial globalization is the volatility of capital flows. This volatility is due to the dominance of the financial over the productive logic of contemporary capitalism and the current characteristics of the international monetary system (IMS). In periods of high risk appetite, capital flows tend to raise its share in developing countries. But in the periods of high liquidity preference, these flows migrate to developed countries, mainly to the United States. This thesis aims to give a contribution to the empirical literature on the determinants of capital flows to developing countries using an econometric panel data model with the use of different methods: ordinary least squares, fixed effects, random effects, first difference and generalized method of moments. The results contributed to earlier studies that showed a predominance of external factors over internal ones in determining capital flows. Also noteworthy is the CBOE VIX volatility indicator, which showed significant and with the expected sign on the fifteen tested equations
Doutorado
Teoria Economica
Doutor em Ciências Econômicas

Measures of entrepreneurship, such as average establishment size and the prevalence of start-ups, correlate strongly with employment growth across and within urban areas. Is it possible for entrepreneurship to occur outside of urban areas and be active in rural areas such as Ohio, Pennsylvania, and West Virginia? There are causal links of entrepreneurial finance to industry or city growth but little link of the evidence of entrepreneurship outside of urban areas overall. This chapter examines the regional variation in startup concentration used to predict employment in the rural areas of Pennsylvania, Ohio, and West Virginia by metropolitan statistical area (MSA)/micropolitan areas for the year 2017. The authors find significant differences in new firm formation rates from industrial regions to technologically progressive regions using the generalized linear models (GLM). Variations in firm birth rates are explained by industrial size, population growth, the number of startups, human capital variables, and establishments.

A lot of research has been focusing on incorporating online data into models of various phenomena. The chapter focuses on one specific problem coming from the domain of capital markets where the information contained in online environments is quite topical. The presented experiments were designed to reveal the association between online texts (from Yahoo! Finance, Facebook, and Twitter) and changes in stock prices of the corresponding companies. As the method for quantifying the association, machine learning-based classification was chosen. The experiments showed that the data preparation procedure had a substantial impact on the results. Thus, different stock price smoothing, the lags between the release of documents and related stock price changes, levels of a minimal stock price change, different weighting schemes for structured document representation, and classifiers were studied. The chapter also shows how to use currently available open source technologies to implement a system for accomplishing the task.

A lot of research has been focusing on incorporating online data into models of various phenomena. The chapter focuses on one specific problem coming from the domain of capital markets where the information contained in online environments is quite topical. The presented experiments were designed to reveal the association between online texts (from Yahoo! Finance, Facebook, and Twitter) and changes in stock prices of the corresponding companies. As the method for quantifying the association, machine learning-based classification was chosen. The experiments showed that the data preparation procedure had a substantial impact on the results. Thus, different stock price smoothing, the lags between the release of documents and related stock price changes, levels of a minimal stock price change, different weighting schemes for structured document representation, and classifiers were studied. The chapter also shows how to use currently available open source technologies to implement a system for accomplishing the task.

In this chapter, interlinkages between stock markets in CEE-4 countries and capital markets in developed countries are analyzed. Changes of variance on stock markets in Poland, the Czech Republic, Slovakia, and Hungary are identified. Differences among countries are analyzed. Capital markets of these countries are compared in terms of market efficiency. Moreover, co-movements of stock markets in Visegrad countries with capital markets in developed countries are studied. Different specifications of multivariate GARCH models are studied. Asymmetric GARCH-BEKK model and Asymmetric Generalized Dynamic Conditional Correlation model are considered.

Housing markets are known to be affected by adverse environments (i.e., environmental air pollution incidents affect Indian urban residents). Urban atmosphere quality has changed extensively with PM2.5 and O3 becoming the primary atmosphere indicators of concern because of dense cities in recent years. There is a correlation between the air pollution of Amaravati with the housing market model. When estimating the housing market, the chapter makes use of the extended regression model together with several constant results in conformity with higher rule. However, there is an insignificant affinity including the concentration regarding SO2 and the concentration of O3 appears according to positively increase the housing values. This chapter therefore examines the influence of actual real estate investment over atmosphere characteristics through the use of a sample on 26 prefecture-level cities in India from 2010–2019 through countless econometric models.

Information Technologies are transforming traditional educational models based on new communication skills. Using a comparative analysis, the scope of this work is two-fold: (1) to study the importance of entrepreneurship and R&D in tertiary education and (2) to analyze which conditions must change in order to contribute to adopt this new IT-based model by the more traditional countries or university institutions that do not research, arguing they are focused on short-term goals only. Using a single OLS econometric model, the author demonstrates that R&D in companies and universities, both public and private, are complementary, R&D applied in education guarantees future positive externalities and creates IT educational societies, while globalization favors capital and human resources mobility, not only nationally but also internationally.

According to the 2001 census, the majority of Slovakia's population statistically follows the Catholic confession of Roman or Byzantine rites. In both rites, the Marian devotion has a consider- able place in religious reflection and spirituality. This study explores the religious discourse of the Marian devotion as it appears in available books and booklets on this topic. The main focus of the chapter is a comparison of the Marian discourse in Slovakia (representing a post-socialist country) and the Marian discourse in neighbouring Austria (representing a ‘Western’ country with no socialist history). For this purpose, a sample of Mariological reflections and spiritual texts was created based on their availability in all Catholic bookstores in the capital of Slovakia (Bratislava) and the capital of Austria (Vienna). The reason for this choice is that these bookstores offer books that mirror the living intellectual and religious brainstorming and reflect Christianity, in par-ticularly the pattern of the Marian discourse of the recent decades in both countries. The study comments on the absence of modern Marian literature in Slovak bookstores. The author also analyses the Marian vocabulary and topics in the both samples. The author distinguishes three existing models of the Marian discourse in Slovakia, all of traditional origin, portraying Mary as an unselfish and patient mother, Mary loving conditionally and restraining God's anger; Mary leading the legions against Satan and crushing his head. All three models are based on the traditional images of Mary and, within the Christian communities, are not understood as contradictory, but complementary. Compared to Western Christianity, the Marian discourse in Slovakia lacks two recurrent models: (1) the progressive 20th/21st century model, and (2) the traditionalist and fundamentalist mod- el. The first model has created a Marian vocabulary and contents representing a self-confident, social and communicative model of Mary. This model presents an alternative to the old models combining mild or triumphant vocabulary with mild or triumphant contents. The second model which is absent among Slovak believers is the Marian discourse of the traditionalist and fundamentalist groups of each age tolerated by official Church structures. These traditionalist and fundamentalist groups return to the old Marian vocabulary and contents that is triumphant, militant and – in this modern version – has an offensive character. This form of discourse, created as a reaction to progressive Christian groups – did not emerge in Slovakia, since there were no progressive Christian movements. Based on the research of the author, the Slovak Marian re- flection and spirituality result from traditional beliefs, having no affinity to Western progressive and traditionalist models. In this regard, it can be stated that Slovakia's isolation from the European spiritual development, which has caused traditional devotion to be fixed in its forms, is, paradoxically, continuing also after the fall of Communism in the era of religious freedom. The comparative discoursive analysis of Mariological literature in Slovakia and its Western neighbour – Austria has showed that the Slovak religious landscape is far more traditional (but not traditionalist) than the current trends in the ‘Western’ religious discourse.

Evidence from wills highlight the striking number of non-elite women living outside of marriage who successfully professed as lay Franciscan tertiaries, that is, as members of the powerful Franciscan Third Order. Chapter 2 explores how and why priests in Guatemala’s colonial capital, especially Franciscans and Jesuits, allied with poor single and widowed laywomen and supported active and unenclosed female religiosity. Santiago de Guatemala’s status as a distant provincial capital, removed from the Inquisition’s close oversight and without the institutional resources necessary to enforce female enclosure, led to greater tolerance of lay female religiosity and single women compared to larger cities like Mexico City and Lima. At the same time, global missionary movements forged diverse models of female piety and sustained support for active female ministries. These findings suggest the need to modify interpretations of early modern Catholicism as primarily hostile towards single women and lay female religiosity.

Career ecosystem theory have been developed to explain interactions between individuals, organizations, and other actors, which influence the flow of human capital in response to the inadequacy of traditional career models. The aim of this chapter is to examine the relevance and applicability of career ecosystem theory to the Turkish academic labor market. In line with this aim, theoretical underpinnings and basic assumptions of ecosystem theory was elaborated. Individual and institutional factors affecting career movements of academics are identified, and changes in the landscape of Turkish higher education system are discussed. Results indicated that the theory is a powerful tool of understanding the complexity of academic careers in Turkish academic labor market.

The globalization process has accelerated the liberalization of foreign trade and capital movements. This acceleration is caused in widening and intensifying relations between foreign direct investment and foreign trade. This paper examines the foreign direct investments’ contribution to the foreign trade. The empirical study is based on time series analysis for Turkey and used monthly data over the period 1992-2017. Econometric techniques for time series are applied to test unit roots, Johansen cointegration test, ARDL bound model and Granger causality test. The test results indicate that there is a correlative relation between foreign trade and foreign direct investment. As a result foreign trade affects foreign direct investments.

This study is found to find out how Weighted Average Funding Cost, which is new policy tool implemented by The Central Bank of Turkey (CBRT) in 2011, weighted average funding cost -aiming at removing the ambiguities seen in the financial variables and minimizing the effect of capital movements on these variables is reviewed. In this study, the effects of the interest rate policy of the Central Bank of the Republic of Turkey (CBRT) on BIST100 index, BISTXBANK index and exchange rate are tested by Augmented Dickey Fuller Test (ADF), ML-GARCH and DCC GARCH models based on ENGLE, R.F. and SHEPPARD, K. (2001). According to the findings obtained, it is concluded that the decisions of the Weighted Average Funding Cost related to Central Bank of the Republic of Turkey (CBTR) lending and borrowing interest rates are direct effective on BIST100 index, BISTXBANK index but indirect with Exchange rate.

Abstract A review of the utilization of Drilling Equipment highlighted an opportunity to lower operational cost for the Operator, reduce Capital Employed for the Service Company, and reduce industry Scope 1 CO2 emissions. The Operator and the Oilfield Services Company set the objective of developing a risk-based probability model that could be used to assess the positive and negative financial impacts of reducing, or perhaps entirely removing, the need for backup drilling tools in the historically risk-averse UK North Sea. The scope of the analysis was to be a drilling campaign on a single rig contracted by the Operator (Rig A). The last three years of Drilling tool reliability data from North Sea operations, as recorded by the Drilling Service Provider, were used as an input. To assess the probability of failure, a Binomial Model was developed to create a Binomial Distribution for each tool, before determining the probability of failure of a given drilling string. The method calculates the probability of having 0 to X failures for a selected Drilling tool/string for a given number of runs. Three Binomial Models were developed to analyze the effect of "Easy", "Moderate" and "Challenging" drilling environments on drilling tool reliability. A financial risk model was developed that balanced the probability-weighted cost of failure for the Operator against the lower costs resulting from reduced tool provision by the Service Provider. In order to better estimate the risks and financial impacts on the project, Sensitivity Analysis was performed on the financial risk model using the three Binomial Models. Scope 1 CO2 emission reductions result from fewer logistical movements and diminished backup tool manufacturing requirements. As a result of the analysis, it was shown that recent improvements in tool reliability support a reduction in backup Drilling tools for the majority of North Sea drilling scenarios, meeting the objective of reducing well construction cost while lowering carbon footprint. Open discussions, focused on maximizing economic hydrocarbon recovery, reducing costs for the Operator, improving Return on Capital Employed for the Oilfield Services Provider and reducing Scope 1 CO2 emissions, resulted in a commercial model that could deliver a Win-Win scenario for all parties. It was observed that the approach was scalable, and would deliver further benefit from a broader workscope, generating "network" benefits when applied to a cluster of rigs, and/or an entire play/basin. In addition, the risk model can be applied to alternative industry scenarios where strong reliability data exist.

Over recent decades Islamic traditions have emerged in new forms in different parts of the Muslim world, interacting differently with secular and neo-liberal patterns of thought and action. In Turkey Fethullah Gülen’s community has been a powerful player in the national debate about the place of Islam in individual and collective life. Through emphasis on the im- portance of ‘secular education’ and a commitment to the defence of both democratic princi- ples and international human rights, Gülen has diffused a new and appealing version of how a ‘good Muslim’ should act in contemporary society. In particular he has defended the role of Islam in the formation of individuals as ethically-responsible moral subjects, a project that overlaps significantly with the ‘secular’ one of forming responsible citizens. Concomitantly, he has shifted the Sufi emphasis on self-discipline/self-denial towards an active, socially- oriented service of others – a form of religious effort that implies a strongly ‘secular’ faith in the human ability to make this world better. This paper looks at the lives of some members of the community to show how this pattern of conduct has affected them. They say that teaching and learning ‘secular’ scientific subjects, combined with total dedication to the project of the movement, constitute, for them, ways to accomplish Islamic deeds and come closer to God. This leads to a consideration of how such a rethinking of Islamic activism has influenced po- litical and sociological transition in Turkey, and a discussion of the potential contribution of the movement towards the development of a more human society in contemporary Europe. From the 1920s onwards, in the context offered by the decline and collapse of the Ottoman Empire, Islamic thinkers, associations and social movements have proliferated their efforts in order to suggest ways to live a good “Muslim life” under newly emerging conditions. Prior to this period, different generations of Muslim Reformers had already argued the compat- ibility of Islam with reason and “modernity”, claiming for the need to renew Islamic tradition recurring to ijtihad. Yet until the end of the XIX century, traditional educational systems, public forms of Islam and models of government had not been dismissed. Only with the dismantlement of the Empire and the constitution of national governments in its different regions, Islamic intellectuals had to face the problem of arranging new patterns of action for Muslim people. With the establishment of multiple nation-states in the so-called Middle East, Islamic intel- lectuals had to cope with secular conceptions about the subject and its place and space for action in society. They had to come to terms with the definitive affirmation of secularism and the consequent process of reconfiguration of local sensibilities, forms of social organisation, and modes of action. As a consequence of these processes, Islamic thinkers started to place emphasis over believers’ individual choice and responsibility both in maintaining an Islamic conduct daily and in realising the values of Islamic society. While under the Ottoman rule to be part of the Islamic ummah was considered an implicit consequence of being a subject of the empire. Not many scientific works have looked at contemporary forms of Islam from this perspective. Usually Islamic instances are considered the outcome of an enduring and unchanging tradition, which try to reproduce itself in opposition to outer-imposed secular practices. Rarely present-day forms of Islamic reasoning and practice have been considered as the result of a process of adjustment to new styles of governance under the modern state. Instead, I argue that new Islamic patterns of action depend on a history of practical and conceptual revision they undertake under different and locally specific versions of secularism. From this perspective I will deal with the specific case of Fethullah Gülen, the head of one of the most famous and influent “renewalist” Islamic movements of contemporary Turkey. From the 1980s this Islamic leader has been able to weave a powerful network of invisible social ties from which he gets both economic and cultural capital. Yet what interests me most in this paper, is that with his open-minded and moderate arguments, Gülen has inspired many people in Turkey to live Islam in a new way. Recurring to ijtihad and drawing from secular epistemology specific ideas about moral agency, he has proposed to a wide public a very at- tractive path for being “good Muslims” in their daily conduct. After an introductive explanation of the movement’s project and of the ideas on which it is based, my aim will be to focus on such a pattern of action. Particular attention will be dedi- cated to Gülen’s conception of a “good Muslim” as a morally-guided agent, because such a conception reveals underneath secular ideas on both responsibility and moral agency. These considerations will constitute the basis from which we can look at the transformation of Islam – and more generally of “the religion” – in the contemporary world. Then a part will be dedicated to defining the specificity of Gülen’s proposal, which will be compared with that of other Islamic revivalist movements in other contexts. Some common point between them will merge from this comparison. Both indeed use the concept of respon- sibility in order to push subjects to actively engage in reviving Islam. Yet, on the other hand, I will show how Gülen’s followers distinguish themselves by the fact their commitment pos- sesses a socially-oriented and reformist character. Finally I will consider the proximity of Gülen’s conceptualisation of moral agency with that the modern state has organised around the idea of “civic virtues”. I argue Gülen’s recall for taking responsibility of social moral decline is a way of charging his followers with a similar burden the modern state has charged its citizens. Thus I suggest the Islamic leader’s pro- posal can be seen as the tentative of supporting the modernity project by defining a new and specific space to Islam and religion into it. This proposal opens the possibility of new and interesting forms of interconnection between secular ideas of modernity and the so-called “Islamic” ones. At the same time I think it sheds a new light over contemporary “renewalist” movements, which can be considered a concrete proposal about how to realise, in a different background, modern forms of governance by reconsidering their moral basis.