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While many studies find a positive relationship between economic freedom and entrepreneurship, very few of these studies account for possible spatial autocorrelation. Moreover, the development of an overall freedom measure has allowed researchers to test the relationship between overall freedom (personal plus economic) and entrepreneurship. The literature, however, does not account for spatial dependence in entrepreneurial activity. The purpose of this paper is to test for possible spatial dependence in entrepreneurial activity.

The authors employ a spatial autoregressive model to account for possible spatial dependence in entrepreneurial activity across states. The authors have data for entrepreneurial activity and overall freedom for a cross-section of data on the 48 contiguous US states for 2009.

The authors find no evidence of spatial dependence in entrepreneurial activity.

The authors are limited to a cross-section. Combined with the spatial lag of the dependent variable, the authors might have too few observations to find statistical significance on either the spatial lag or other explanatory variables.

Future research should continue to account for possible spatial dependence.

Entrepreneurship is key to economic growth. Freedom has been shown to lead to more entrepreneurship at the state level in other research.

This brief research note is the first paper to account for spatial dependence in the relationship between overall freedom and entrepreneurial activity.

As the pressure to win and generate revenue and as the allegations of out-of-control spending continue to increase, there exists much interest in intercollegiate athletics. While researchers in the past have investigated specific issues related to athletics success, revenue generation, and graduation rates, no previous studies have attempted to evaluate these factors simultaneously. This chapter discusses the development of a data envelopment analysis (DEA) model aimed at measuring how efficient university athletic departments are in terms of the use of resources to achieve athletics success, generate revenue, and promote academic success and on-time graduation. Data from National Collegiate Athletic Association (NCAA) Division I Football Bowl Subdivision (FBS) universities are used to evaluate the relative efficiency of the institutions. The model identifies a series of “best-practice” universities which are used to calculate efficient target resource levels for inefficient institutions. The value of the proposed methodology to decision makers is discussed.

This paper aims to examine the stochastic convergence of the per capita CO₂ emissions among the top four crude oil exporter countries, namely, Canada, Iraq, Russia and Saudi Arabia, from 1960 to 2017. Assessing the stationarity and unit root properties of the environmental series in these countries is important as their large fossil fuel resources increases the potential for rising CO₂ emissions compared to other countries.

In addition to implementing the conventional unit root tests, the authors also benefit from the application of three nonlinear unit root tests, namely, wavelet unit root test, nonlinear unit root test of Güriş (2019) and the Fourier quantile unit root test. These methods are robust to the presence of possible structural breaks and other forms of nonlinearities, while the wavelet unit root test enables us to examine the stochastic behavior of the variables in both time and frequency domains. Hence, they all provide more reliable inferences on the convergences of the CO₂ emissions compared to their standard competitors.

The standard unit root test results show strong evidence in favor of non-stationarity in all countries. This conclusion supports the results of the other nonlinear unit root tests and the overall findings of the Fourier quantile unit root test. The wavelet unit root test provides a controversial finding. However, due to its limitations, its findings must be interpreted with caution. The details of the Fourier quantile unit root test indicate that per capita CO₂ emissions follow mean-reverting properties in middle quantile ranges for Canada, Russia and Iraq. This validates the asymmetric behaviors of per capita CO₂ emissions in these countries.

The novelty of the work can be stated in two ways. First, among the available studies, this is the first paper to emphasize the importance of examining the convergence of per capita CO₂ emissions among the top four oil exporters. Second, to the best of the knowledge, no study has yet been undertaken in which all these methods have been simultaneously applied. Sustainable environmental policies depend heavily on the CO₂ series’ properties. Thus, the findings can provide significant environmental and economic implications for policymakers to construct feasible and optimal policies in climate change mitigation.

We are interested in modeling the impact of spatial and interindustry dependence on firm-level innovation of Chinese firms The existence of network ties between cities imply that changes taking place in one city could influence innovation by firms in nearby cities (local spatial spillovers), or set in motion a series of spatial diffusion and feedback impacts across multiple cities (global spatial spillovers). We use the term local spatial spillovers to reflect a scenario where only immediately neighboring cities are impacted, whereas the term global spatial spillovers represent a situation where impacts fall on neighboring cities, as well as higher order neighbors (neighbors to the neighboring cities, neighbors to the neighbors of the neighbors, and so on). Global spatial spillovers also involve feedback impacts from neighboring cities, and imply the existence of a wider diffusion of impacts over space (higher order neighbors).

Similarly, the existence of national interindustry input-output ties implies that changes occurring in one industry could influence innovation by firms operating in directly related industries (local interindustry spillovers), or set in motion a series of in interindustry diffusion and feedback impacts across multiple industries (global interindustry spillovers).

Typical linear models of firm-level innovation based on knowledge production functions would rely on city- and industry-specific fixed effects to allow for differences in the level of innovation by firms located in different cities and operating in different industries. This approach however ignores the fact that, spatial dependence between cities and interindustry dependence arising from input-output relationships, may imply interaction, not simply heterogeneity across cities and industries.

We construct a Bayesian hierarchical model that allows for both city- and industry-level interaction (global spillovers) and subsumes other innovation scenarios such as: (1) heterogeneity that implies level differences (fixed effects) and (2) contextual effects that imply local spillovers as special cases.

This survey of the literature on the convergence of carbon dioxide (CO₂) emissions informs researchers on areas for future research by summarizing the countries examined, the types of convergence tested and the methodological approaches undertaken.

This survey examines peer-reviewed empirical studies of CO₂ emissions convergence with respect to country coverage and alternative approaches to test for various types of convergence.

For large multicountry studies, the support for convergence is quite limited. However, studies focused exclusively on a subset of countries defined by income classification, geographic region or institutional structure reveal the finding of convergence is more prevalent. Studies at the subnational level have primarily been in the cases of the US and China with the exception of two studies across industry sectors in Portugal and Sweden.

This study focuses exclusively on peer-reviewed published studies.

This study is relevant to the design of mitigation strategies to reduce CO₂ emissions and the assumption of convergence underlying climate change models.

As a major component of greenhouse gas emissions, CO₂ emissions is of global importance in its impact on the environment and climate change.

This study provides the most recent and comprehensive survey of the empirical literature on the convergence of CO₂ emissions.

Innovation convergence is critical to national or regional economic growth patterns. This article provides a systematic review of innovation convergence research through qualitative discussions combined with bibliometric methods. Through this article, researchers interested in the field of innovation convergence can quickly understand the development of the field, quickly identify authors and publications with significant impact, and collaborative networks in the field.

This article is based on the relevant literature included in the WOS database from 1990 to 2021, using Citespace, Gephi and other software to conduct a systematic bibliometric analysis of the research in the new convergence field.

This research shows that the second half of the twentieth century was a boom period for research on economic convergence. 2. The subject foundation of innovation convergence research mainly includes mathematics, economics, political science and computational science. 3. The journals that publish research in this field are widely distributed, including the fields of economics, natural sciences and complex sciences. 4. The research in the field of innovation convergence is inseparable from the research in the field of economic growth.

This study may help others to understand the development history and research trends of the innovation convergence field, as well as the literature and cooperative scientific research institutions that have an important influence.

The purpose of this paper is to explore how the strength of political veto players affects the long-run credibility of economic institutions and how they jointly affect entrepreneurial activity.

The authors employ an annual panel covering 30 OECD countries from 1993 to 2011.

An error correction model identifies a positive and significant short-run effect on self-employment from large government spending at low levels of veto player strength. A static model conversely indicates that smaller government spending is positively associated with entrepreneurship at lower levels of veto player strength in the long run.

The authors are the first to explore the interaction of economic and political institutions in the development of entrepreneurship.

The purpose of this study is to examine the impact of economic freedom on four key health indicators (namely, life expectancy, infant mortality rate, under-five mortality rate and neonatal mortality rate) by using a panel dataset of 34 sub-Saharan African countries from 2005 to 2016.

The study obtains data from the World Development Indicators (WDI) of the World Bank and the Fraser Institute. It uses fixed effects regression to estimate the effect of economic freedom on health outcomes and attempts to resolve the endogeneity problems by using two-stage least squares regression (2SLS).

The results indicate a favourable impact of economic freedom on health outcomes. That is, higher levels of economic freedom reduce mortality rates and increase life expectancy in sub-Saharan Africa. All areas of economic freedom, except government size, have a significant and positive effect on health outcomes.

This study analyses the effect of economic freedom on health at a broad level. Country-specific studies at a disaggregated level may provide additional information about the impact of economic freedom on health outcomes. Also, this study does not control for some important variables such as education, income inequality and foreign aid due to data constraints.

The findings suggest that sub-Saharan African countries should focus on enhancing the quality of economic institutions to improve their health outcomes. This may include policy reforms that support a robust legal system, protect property rights, promote free trade and stabilise the macroeconomic environment. In addition, policies that raise urbanisation, increase immunisation and lower the incidence of HIV are likely to produce a substantial improvement in health outcomes.

Extant economic freedom-health literature does not focus on endogeneity problems. This study uses instrumental variables regression to deal with endogeneity. Also, this is one of the first attempts to empirically investigate the relationship between economic freedom and health in the case of sub-Saharan Africa.

To produce a controlled stirring in a low conducting liquid thanks to a new kind of multiphase inductor.

An experimental pilot consisting of a cylindrical salt water pool surrounded by an innovative multiphase inductor configuration, based on the single phase asynchronous motor principle, is setup. The maximum bulk stirring velocities are measured and compared with the estimate by numerical modelling.

Shows the possibility of controlling the stirring of a low conducting liquid thanks to a multiphase inductive system. The corresponding measurement results give a significant bulk velocity of a few centimetres per second.

This new kind of multiphase inductor, working with a single phase induction generator, seems a promising way to produce a controlled stirring in low conducting media which cover a large range of induction applications.

Such an innovative inductor configuration has already been tested successfully for metal alloys stirring in the middle frequency area. In this paper, an extension of this kind of multiphase inductive system for electromagnetic stirring of low conducting liquids like electrolytes in the high frequency area is presented.

This paper formulates and analyzes Bayesian model variants for the analysis of systems of spatial panel data with binary-dependent variables. The paper focuses on cases where latent variables of cross-sectional units in an equation of the system contemporaneously depend on the values of the same and, eventually, other latent variables of other cross-sectional units. Moreover, the paper discusses cases where time-invariant effects are exogenous versus endogenous. Such models may have numerous applications in industrial economics, public economics, or international economics. The paper illustrates that the performance of Bayesian estimation methods for such models is supportive of their use with even relatively small panel data sets.