Enabling environments

A strong and growing private sector is a critical factor for the promotion of growth and the increase of opportunities for all. A vibrant business sector would mean economic investment, job creation, improvement in overall productivity, and an increase in the economic pie for all those involved in a society. To foster the growth of a legal business sector, governments and policy makers around the world have been interested in learning about effective policies and implementing wide-ranging reforms. This general policy climate which supports and enhances the growth of the formal private business sector has been called a business-enabling environment. The fundamental premise is that growth of the official business sector of economic activity requires good regulations, strong economic fundamentals, and a nourishing sociopolitical structure. The question to which this dissertation responds is which of these factors are quantitatively significant in describing the number of registered businesses worldwide and how these factors compare to each other when they are tested econometrically beside each other. Would the ease of doing business variables still be significant in describing the number of registered businesses when it is compared to fundamental macro policy factors such as corporate tax rate? How far does business bribery affect business growth? This dissertation presents an effort to quantitatively analyze these factors and their effects on the business growth worldwide. It also offers an estimate on the amount of annual business to government bribery around the world disaggregated to a national level. It offers an estimation of national annual bribes paid by the business sector to governments, in each country worldwide, in the currency of that country at the time, and the equivalent amount in US dollars

Efficient techniques for statistical modeling of calibration and spatio-temporal systems using Gaussian processes

Gaussian processes (GPs) are one of the most widely used tools in statistical modeling of various engineering systems. In this dissertation, we study three common types of problems in statistical modeling, i.e., prediction, calibration, and forecasting, using GPs and other related techniques.First, we study the problem of prediction using Gaussian Process Regression (GPR) in large-scale spatial systems that contain exogenous variables. We propose a Sparse Pseudo-input Local Gaussian Process (SPLGP) that addresses the inefficiencies of GPR, i.e., computational complexity and covariance heterogeneity, in dealing with spatial systems in a unifying framework. We propose new theorems that form the basis of our decomposition policy and develop an optimization procedure to find the optimal policy. We also impose continuity constraints on the boundaries of the subdomains to alleviate the problem of discontinuity of the global predictor. Next, we study the calibration problem for expensive computational models (ECM), i.e., computational models that cannot be evaluated a large number of times. We propose a Bayesian Non-isometric Matching Calibration (BNMC) approach that allows calibration of ECM. The proposed model uses GPs to embrace the restrictions of ECM and makes inferences on the calibration parameters through a Bayesian framework. We also present a geometric interpretation of calibration that enables us to take advantage of combinatorial optimization techniques to extract necessary information for constructing prior distributions of our Bayesian framework. Finally, we study the problem of forecasting in complex spatio-temporal systems with the primary focus on short-term wind speed forecasting in wind farms. We propose a similarity-based forecasting model capable of taking any type of spatial and temporal information into account to improve spatio-temporal forecasting, in particular wind speed forecasting. The proposed model is inspired by the weighted averaging technique used in a class of regression models known as non-parametric linear smoothers which includes GPR. We also equip our model with a variable selection and a parameter training procedure, so that it can be easily applied to any spatio-temporal system. We present a set of experimental results for each problem to demonstrate the efficiency of our proposed models comparing to other existing models

Trust in Leader as a Psychological Factor on Employee and Organizational Outcome

While leadership studies have tackled the concept in various ways, it can be said that often basic psychological elements are overlooked. In this sense, the notion of trust is focused in this chapter to highlight, elaborate, and provide a thorough understanding on the vitality of trust between leader and his/her followers. Whether a business achieves success or not is highly dependent on leadership of the firm. Mutual trust among staff and their managers is a crucial matter that can hinder or enhance the process of success. With the existence of trust, workplace and environment of company become soothing for individuals, leading to positive psychological outcomes, and improved wellbeing. Therefore, we argue that building, and gaining trust should be the focus of leaders regardless of their style for it will improve performance, and thus, organizational outcome while simultaneously benefiting the staff via psychological elements. This becomes more vivid in modern business world as wellbeing of individuals and their mental health are more emphasized. Both leaders and scholars can benefit from this manuscript

Regional dimensions of economic development in Iran: A new economic geography approach

This paper presents a spatial analysis on regional dimensions of poverty and economic development across provinces of Iran. It offers the first ever estimation made in developing countries using this strand of "New Economic Geography" (NEG) models and provides a comparison of the results between previously studied developed countries and Iran as a developing country. The goal of this study is to offer an analysis of the effects of agglomeration and dispersion economies on the patterns of regional economic development in Iran. It analyzes the linkages among adjacent provinces as well as effects of agglomeration and dispersion economies on the patterns of Iran's regional economic development through empirical estimation of two of the NEG models. First, it presents an estimation of a "Market Potential Function" (MPF), in which wages are associated with proximity to consumer markets. Second, the paper estimates an augmented MPF derived from the Krugman model of economic geography. The parameters in this model estimate the importance of transportation cost and economies of scale. The estimation results suggest that Iran showed generally good fit to both models and satisfied both MPF and Krugman model specifications. Compared to other similar studies in developed countries, Iran shows smaller returns to scale and consistently higher size of the effect of market potential on wages

A comparative analysis of COVID-19 and global financial crises: evidence from US economy

The COVID-19 crisis has had deep adverse effects on a global level, affecting many economies and worsening their conditions which may have led to severe recession or even depression. The numbers of positive cases have risen sharply over the last few months, and the fatalities have also reached their peak. This study aims to examine the impact of the global financial crisis, and the COVID-19 pandemic on the macroeconomic variables of the US economy. It also provides an understanding in a descriptive format, to analyze and compare the global financial crisis and COVID-19 pandemic, in a tabulated and graphical format. For analysis purposes, the tables and average method have been used. For the graphical formats, charts have been used for the later year of 2008, and the beginning of the 2009 global financial crisis. The first six months of the spread of the COVID-19 pandemic have also been taken into consideration. The results have confirmed that the current COVID-19 pandemic shows more severity in terms of economic activity, than the global financial crisis had experienced. Moreover, the impact of the crisis on the recession probabilities in the current pandemic is lower than that at the time of the global financial crisis

Regional dimensions of economic development in Iran: A new economic geography approach

This paper presents a spatial analysis of the regional dimensions of poverty and economic development across provinces of Iran. It offers one of the few estimations made in developing countries using this strand of New Economic Geography (NEG) models and provides a comparison of the results for Iran with those in previously studied developed countries. The goal of this study is to offer an analysis of the effects of agglomeration and dispersion economies on the patterns of regional economic development in Iran based on the empirical estimation of two of the NEG models. First, it presents an estimation of a Market Potential Function (MPF), in which wages are associated with proximity to consumer markets. Second, it estimates an augmented MPF derived from the Krugman model of economic geography that estimates the importance of transportation costs and economies of scale. The estimation results suggest that Iran shows a generally good fit to both models, satisfying their specifications. Compared to similar studies of developed countries, Iran shows smaller returns to scale. This might be a result of the nature of the technologies used in the non-farm private sector in Iran, which is less industrial and more traditional. Dispersion and decentralization of industries to achieve lower income inequality between provinces would create a level of loss, but less losses than they would be in Western countries. The paper also found a significantly and consistently greater effect of market potential on wages in comparison to the effect estimated in similar analyses of other countries. This might be a result of the country relying on an underdeveloped transportation system between provinces in Iran. It is also a highly mountainous and geographically diverse country. The overall result of this study corroborates the notion of centralization in the Iranian economy. The large wage variations explained by economic geography could cause significant internal migration, beyond that seen in western countries. Indeed, significant internal migration has been observed in Iran in past years