Modelling the Determinants of Job Creation: Microeconometric Models Accounting for Latent Entrepreneurial Ability

During the last decades, most developed countries have shown a remarcable increase in entrepreneurship rates. Recent research suggests that this increase is, for a considerable part, caused by an increase in the share of solo self-employed. Nowadays, for example, more than half of all Dutch business owners are solo self-employed. This raises the question which factors determine whether an entrepreneur becomes an employer or remains solo self-employed. A recent study by EIM investigates the decision of entrepreneurs whether or not to become an employer and the decision of employers to hire a certain number of employees. The first decision is examined by estimating duration models that model the duration of the time spent as solo entrepreneur before the transition to employer is made. The estimations are performed on a panel of Dutch start-ups in 1998, 1999 and 2000. We find that entrepreneurs who founded a firm to improve their work-life balance are less likely to make the transition to employership. The remaining factors that we found to influence the employer decision do this all in a positive way. These factors include whether or not the entrepreneur has the objective to maximize revenue, experience within the industry in which he operates, his entrepreneurial experience, selfefficacy, risk attitude and the time that is spent in the company. We also find that the likelihood of becoming a job creator is positively related to the business cycle. The second decision is examined by estimating count models that model the number of employees that are hired in the first year of employership. We find that higher levels of educational, entrepreneurial experience and self-efficacy of the entrepreneur lead to a greater firm size. Another factor that increases firm size is innovativeness. The moment in time at which the transition from soloentrepreneur to employer is made, also plays are role. For the first few years we find a negative relationship with firm age, indicating that the faster the switch is made, the more personnel will be employed. Also, for the employee decision we find a positive relation with the business cycle. �

Stacked Modelling Framework

The thesis develops a predictive modeling framework based on stacked Gaussian processes and applies it to two main applications in environmental and chemical en- gineering. First, a network of independently trained Gaussian processes (StackedGP) is introduced to obtain analytical predictions of quantities of interest (model out- puts) with quantified uncertainties. StackedGP framework supports component- based modeling in different fields such as environmental and chemical science, en- hances predictions of quantities of interest through a cascade of intermediate predic- tions usually addressed by cokriging, and propagates uncertainties through emulated dynamical systems driven by uncertain forcing variables. By using analytical first and second-order moments of a Gaussian process with uncertain inputs using squared ex- ponential and polynomial kernels, approximated expectations of model outputs that require an arbitrary composition of functions can be obtained. The performance of the proposed nonparametric stacked model in model composition and cascading predictions is measured in different applications and datasets. The framework has been evaluated in a wildfire and mineral resource problem using real data, and its application to time-series prediction is demonstrated in a 2D puff advection problem. In additions, the StackedGP is introduced to one of challenging environmental problems, prediction of mycotoxins. In this part of the work, we develop a stacked Gaussian process using both field and wet-lab measurements to predict fungal toxin (aflatoxin) concentrations in corn in South Carolina. While most of the aflatoxin contamination issues associated with the post-harvest period in the U.S. can be con- trolled with expensive testing, a systematic and economical approach is lacking to determine how the pre-harvest aflatoxin risk adversely affects crop producers as afla- toxin is virtually unobservable on a geographical and temporal scale. This information gap carries significant cost burdens for grain producers and is filled by the proposed stacked Gaussian process. The novelty of this part is two fold. First, the aflatoxin probabilistic maps are obtained using an analytical scheme to propagate the uncer- tainty through the stacked Gaussian process. The model predictions are validated both at the Gaussian process component level and at the system level for the entire stacked Gaussian process using historical field data. Second, a novel derivation is introduced to calculate the analytical covariance of aflatoxin production at two ge- ographical locations. Similar with kriging/Gaussian process, this is used to predict aflatoxin at unobserved locations using measurements at nearby locations but with the prior mean and covariance provided by the stacked Gaussian process. As field measurements arrive, this measurement update scheme may be used in targeted field inspections and warning farmers of emerging aflatoxin contaminations. Lastly, we apply the stackedGP framework in a chemical engineering application. Computational catalyst discovery involves identification of a meaningful model and suitable descriptors that determine the catalyst properties. First, we study the impact of combining various descriptors (e.g. reaction energies, metal descriptors, and bond counts) for modeling transition state energies (TS) based on a database of adsorption and TS energies across transition metal surfaces {Palladium (PD_111), Platinum (PT_111), Nickel (NI_111), Ruthenium (RU_0001), and Rhodium (RH_111)} for the decarboxylation and decarbonylation of propionic acid, a chemistry characteristic for biomass conversion. Results of different machine learning models for more than 1330 of these descriptor combinations suggest that there is no statistically significant difference between linear and non-linear models when using the right combination of reactant energies, metal descriptors, and bond counts. However, linear models are inferior when not including bond count and metal descriptors. Furthermore, when there are missing data for reaction steps on all metals, conventional linear scaling is inferior to linear and nonlinear models with proper choice of descriptors that are surprisingly robust. Finally, the stackedGP framework is evaluated in modeling the adsorption and transition state energies as a function of metal descriptors with data from all metal surfaces. By getting these energies, the Turn-Over-Frequency (TOF) can be estimated using micro-kinetic models

On the solvability of a class of singular parabolic equations with nonlocal boundary conditions in nonclassical function spaces

The aim of this paper is to prove the existence, uniqueness, and continuous dependence upon the data of a generalized solution for certain singular parabolic equations with initial and nonlocal boundary conditions. The proof is based on an a priori estimate established in nonclassical function spaces, and on the density of the range of the operator corresponding to the abstract formulation of the considered problem

New Firm Performance: Does the Age of Founders Affect Employment Creation?

The ageing population increasingly becomes a challenge for policy makers. Given the expected changes in the age decomposition of the workforce, it becomes more pressing to understand the nature of the relationship between age and entrepreneurship. More specifically: what are the consequences of an ageing (entrepreneurial) population on entrepreneurial performance?� A recent study by EIM investigates the effect of the age of the entrepreneur at start-up on the size of newly started firms. A distinction is made between the decision of entrepreneurs whether or not to become an employer, and the decision of employers to hire a certain number of employees. To examine to which extent age has a direct and/or indirect effect on these two decision, a sample of 849 new firms has been used that survived the first three years after start-up.� A first conclusion of the empirical analysis is that it is important to make the distinction between the two decisions: the decision of entrepreneurs whether or not to become an employer depends on other factors than the decision of employers regarding the number of employees. A second conclusion is that age has a negative relationship with the outcome of both decisions, but that these relationships are completely mediated by the mediating variables included in the study. Entrepreneurs who start at older age are less likely to work fulltime in their new venture, are less willing to take risks and have a lower perception of their entrepreneurial skills. Each of these factors has, in turn, a positive impact on the probability of employing personnel. For the number of employees a negative indirect effect of age exists, through the effect of age on the perception of entrepreneurial skills. �

Corporate governance, auditor quality and the reliability of audited financial statements in Libyan banking sector

This study attempts to provide evidence on the relationship between corporate governance mechanisms, auditor quality, and reliability of audited financial information in Libya. The objectives of the study are to extend the evidence linking external corporate governance mechanisms to auditor quality, examine the relationship between internal corporate governance practices and auditor quality, investigate the relationship between auditor quality and reliability of audited financial statements, and examine the mediating effect of auditor quality on the relationship between corporate governance mechanisms and the reliability of audited financial statements in the Libyan Banking Sector. The primary data for this study is gathered by opting survey technique so the data used in this study is primary in nature. Convenient sampling is used to gather the data and the main respondent of this study are auditors and loan officers of banking sector of Libya. Then correlation and regression analysis are used to acquire empirical rsults from the data gathered, by using spss. The main findings indicate that there is a direct significant positive relationship between corporate governance mechanisms and the reliability of audited financial statements. It is also established that there is a direct positive relationship between corporate governance practices and auditor quality. The results also reveal a direct strong positive relationship between auditor quality and the reliability of audited financial statements. In terms of mediation, the findings of the study show that auditor quality partially mediates the relationship between corporate governance mechanisms and the reliability of audited financial statements. The main contribution of the study is its in-depth investigation of financial reporting and providing an understanding of the role played by external and internal corporate governance mechanisms in the external audit process in banking sector of Libya, albeit a form of investigation rarely found in prior studies, is also used to obtain the empirical results. Furthermore, the study highlights the role of audit committee in enhancing financial reporting quality. Finally, the study also improved the understanding of why and how auditor quality influences the reliability of audited financial statement

What determines the volume of informal venture finance investment and does it vary by gender?

We estimate a two-equation model to jointly determine the number of informal investors and the amount of money that they invest over the last 3 years. Our model uses data on 126,189 individuals in 21 highly developed countries in the period 2002-2006. We delve deeper into the hypothesis of Burke et al (2010) that ‘the demand for informal venture finance tends to generate its own supply’. To our knowledge, we undertake the first research to move analysis of the supply of informal venture finance investment beyond estimating the propensity for a person to become an informal investor and onto the core concern which is the total volume of venture finance. We find that a one per cent increase in entrepreneurial activity increases the number of informal investors by 1.702 per cent. However, the average invested amount declines by 0.827 per cent leading to a net positive total increase by 0.861 per cent. This result indicates that, to a considerable extent, demand for informal investment creates its own supply. This effect is stronger for males than females. We also find that the level of venture capital investment has a net positive effect on the level of informal investment and that this effect is stronger for females than males.

Soil radioactivity and elemental characterization of area proposed for the first nuclear power plant at Red Sea state, eastern Sudan

Abstract  This work was carried out with the aim to establish baseline data of soil radioactivity prior commissioning the first nuclear power plant for electricity production in the Sudan. A total of 105 soil samples from the proposed area were collected and analyzed using Gamma-ray spectrometer, X-ray Fluorescence and Atomic Absorption. Ambient dose rates were measured during sampling using radiation survey meters. Based on radionuclides in soil; some radiological hazard indices (such as absorbed dose rates, Radium-Equivalent Activity, External Hazard, and Gamma index) were computed. The results exhibit that226Ra, 232Th,40Kand 137Cs concentration ranged from0.55-88.9, 1.63-76.6, 24-1100 and 0.001-1.03 Bq/kg with an average value of10.43, 11.12, 361.2and 0.045Bq/kg respectively. The average value of absorbed dose rate(29.92nGy/h), Radium equivalent (70.55 Bq/Kg), external hazard (0.19), Gamma index. (0.25) and those parameters are lower than the corresponding global average. The results of the study revealed that the average values of 226Ra, 232Th, 40K and 137Cs fall within the global average value. GIS Predictive exhibited the spatial distribution of radioactivity trends with low levels at eastern part towards the Red Sea while high values observed at the desert (western part). This trend in addition to low levels has a very good impact to decision makers for consideration in site selection of NPP. Pearson correlation coefficient shows a correlation between the variables 226Ra and 232Th (0.69); Cr and Au (0.82); Br and Nb (0.84),Hf and Sb (+0.75) with no significant correlations between radioactive and radioactive elements. Keywords: Road map, GIS, Gamma-ray Spectrometer, Effective dose. 

Modeling of Aggregation and Gelation of Nanoparticles Using Quadrature Method of Moments

Applications of Nanotechnology are growing significantly in the petroleum industry such as oil recovery, and well stimulation. In aqueous media, silica nanoparticles aggregate if there is sufficient attractive energy between nanoparticles. Aggregate size distribution evolves as aggregation continues, and once it spans the space, it forms a gel. The objective of this study is to study the aggregation and gelation kinetics in the batch. Population Balance equation (PBE) is used to model the kinetics of aggregation. Quadrature method of moments (QMOM) is used to convert the PBE with continuous distribution of nanoparticle size into a set of moment equations for efficient computation. The closure problem for moment transport equation is resolved using Gaussian Quadrature that requires estimation of roots orthogonal polynomials. Wheeler algorithm is then used for calculation of the coefficients of the recursive formula of the orthogonal polynomials. This study shows that the PBE and the QMOM along with the effective medium theory can be used to model the aggregation and gelation of nanoparticles at different conditions of salinity and concentration. The modeled developed in this study is used to compare between the kinetics of aggregation and gelation of fumed silica and colloidal silica nanoparticles at the same conditions. The case studies presented show the unique behavior of fumed silica over colloidal silica nanoparticles for forming a gel network at significantly low concentration. This is basically due to the fractal structure of the fumed silica nanoparticles that has higher effective volume than the spherical particles of colloidal silica of the same size. The model also shows that there is a critical concentration of salt and nanoparticles above which the viscosity increase, and the gel network can be formed. The model developed in this study can be coupled with a transport model to simulate nanoparticles transport aggregation and in situ gelation in porous media

Optimal Charging/Discharging of PHEVs for Predictability Enhancement of Wind Power Generation

In a context of rapidly expanding renewable energy resources, the wind power is the most interest. Because of intermittent nature of wind turbines, it is difficult to predict and control the wind power generation. At high penetration level, an extra fast response reserve capacity is needed to compensate the shortage of generation when a sudden variation of wind takes place. In order to manage this uncertainty, to minimize the system losses, and to improve the voltage profiles, the injected power to the grid should be kept at its optimal level throughout the day. This paper presents an approach to keep the injected power at its optimal level by combining the wind power generation system with Plug-in Hybrid Electric Vehicles (PHEVs) and optimal utilizing of vehicle-to-grid (V2G) capacities. Optimal PHEVs charging/discharging can stabilize the injected power of the wind turbines by storing electric energy during high wind speed and deliver it during low wind speed. So, it is important to estimate enough number of participating PHEVs for the desired applications. The proposed approach is tested using a 33-bus distribution system with a variety of case studies and actual wind speed