Narrow Results

There is a fundamental conflict of interests between the ruler and most citizens in non-democracies. When the ruler maximizes his benefit from taxation, the major constraint is that citizens might make attempts to overthrow the existing regime. The continuity and stability of regime are crucially related to the degree of support to the existing political regime by the bureaucracy. In this paper, we use a simple model to argue that, when the ruler maximizes his benefit and faces exogenous restriction on wage setting, toleration of corruption is necessary to induce the required support and effort from the bureaucracy. We then relax the exogenous restriction on wages and study the case in which the ruler may eliminate corruption by setting efficiency wage. We also explore the possibility that the ruler may use an audit device to check corruption.

This paper presents a study of the bounded confidence model applied to the complex networks. Two different cases were examined: opinion formation process in the Barabási–Albert network and corruption spreading in a hierarchical network. For both cases, the value of the bounded confidence parameter ε was assumed as a constant, or its value was dependent on the degree of a node in the network. To measure the opinion formation and corruption spreading processes, we introduced the order parameter related to the number of interfaces in the system. As a results of numerical simulations, the influence of the values of ε on the final opinions in the population, as well as, the influence of an initial source of corruption in the company structure on the corruption spreading process, were obtained and discussed.

Recent studies in the innovation literature show that Foreign Direct Investment (FDI) enhances innovations in recipient countries through spill-over effects. In this paper we extend the existing literature by incorporating the corruption index in the estimation procedure. Using a cross-country analysis from the Europe and Central Asia (ECA) region, covering 57 countries over the period of 1995–2010, we find no evidence of FDI spill-over effects on innovations, when corruption is endogenously modelled in the regression. Interestingly, we find that corruption and expenditure on education sector are positively related to the number of patents applications, suggesting anti-corruption programs encourage innovations that promote economic growth. Our study shed light on the national innovations and anti-corruption programs.

In theory, trade intensity should positively affect the quality of domestic institutions and governance; the higher the economic openness, the lower the corruption. In practice, however, the growth of economic openness has not been accompanied by the expected improvements in corruption for 34 African countries between 1990 and 2009. This paper presents a plausible explanation for this conundrum. Results from panel data regression analyses indicate that a switch from trading with the Advanced Economies to trading with China increases the perceived corruption level. For instance, in a “representative” African country, a 10% point substitution from trading with the Advanced Economies to trading with China makes its ICRG corruption score decline—indicating increased corruption—by 29%.

This paper modeled the effect of corruption on growth, using Nigerian data for testing. The productivity growth channel of corruption was explored. Cointegration and error correction methods were employed in the analysis. The national system of innovations and corruption exhibited long run relations with productivity growth and were found to be credible fundamentals. The productivity growth vector was considered to be the only plausible in the long run growth analysis. The parsimonious growth equation showed productivity growth and government expenditure as significant and conformed to a priori expectations. The course of policy to sustainable growth was suggestive.

Employing annual data over the period 1996–2013 for 29 OECD countries, this paper explores the impact of corruption on domestic innovative activity, measured by the number of patent and trademark applications, via a linear panel fixed effect model and a nonlinear panel smooth transition regression with all lagged explanatory variables as instrumental variables and under the consideration of potential endogeneity biases. The results indicate several important findings. First, there exists a strong threshold effect between the control of corruption and levels of innovative activity across nations. Second, we note that corruption only has a substantial positive impact on innovation when it is over the threshold level, but not when a country has a seriously corrupt government with low bureaucratic quality, no matter for patent or trademark applications. Hence, heterogeneous beliefs about low transition speed show that OECD countries may not take actions instantly and identically to pursue better bureaucratic quality. Finally, we discover that an improvement over corruption presents greater impacts on patent applications than on trademark applications. Taken together, we confirm that corruption plays a fundamental role in determining innovation activities in OECD countries, offering meaningful policy implications for those policymakers and industries in accordance with our findings.

Using World Bank Enterprise Survey data on bribery and patent applications, we try to study the causal linkage between firm level innovation and corruption in India. Specifically, we try to understand if corruption impacts innovation at the firm level. Since we find that innovation and corruption are jointly determined, we propose instrumental variables regression approach to identify this causal effect. We instrument bribery by exogenously determined external audit parameter and then use a recursive bivariate probit model combined with industry-fixed effects to reach our results. Our findings suggest that bribery has an adverse impact on innovation. The results of our study are much in contrast to the existing literature, which largely supports a positive relationship between innovation and corruption.

The aim of this paper is to explore the relationship between intelligence and economic and financial crimes. For this purpose, we use a cross-sectional sample of 182 countries for the time span of 2012–2017. Our research provides empirical evidence on the existence of a significant impact of intelligence upon economic and financial crimes. When we analyze the entire sample, we find that intelligent people are more prone to comply with the law and thus increase the efficiency of implementing government policies to reduce economic and financial crimes. However, when we conduct our analysis among the two subgroups of high- and low-income countries, different results are obtained. For high-income countries, we obtain evidence of a positive coefficient for the impact of intelligence on economic and financial crimes, meaning that increased intellectual capacities of people from these countries, including high professional knowledge and skills, are used to break the traditional technology in order to get illegal benefits. Our results conducted for the low-income countries' subsample do not support intelligence as being a determining factor for economic and financial crimes; in these countries, other determinants are more important for engaging in such activities. Our study may have important implications for the policymakers who must acknowledge that various policies in the field of economic and financial crimes need to be differentially adopted depending on the level of development of each country, which offers different ways of involvement in such crimes, related to the level of people's intelligence.

In this paper, we consider the problem of robust face recognition using color information. In this context, sparse representation-based algorithms are the state-of-the-art solutions for gray facial images. We will integrate the existing sparse representation-based algorithms with color information and this integration can improve the previous performances significantly. Furthermore, we propose a new performance metric, namely the discriminativeness (DIS) to describe the recognition effectiveness for sparse representation algorithms. We find out that the richer information in color space can be used to increase the DIS, i.e. enhancing the robustness in face recognition. Extensive experiments have been conducted under different conditions, including various feature extractors, random pixel corruptions and occlusions on AR and GT databases, to demonstrate the advantages of using color information in robust face recognition. Detailed analysis is also included for each experiment to explain why and how color improve the robustness of different sparse representation-based methods.

The importance of cooperation is self-evident to humans, yet the existence of corruption where law violators can avoid being punished by paying bribes to corrupt law enforcers may threaten the maintenance of cooperation. Although powerful monitoring has been used to resolve such matters, existing studies show that the effects of such measures are either transient or uncertain. Thus how to efficiently control the occurrence of corruption for the emergence of cooperation remains a challenge. Here, we introduce social exclusion into the public goods game, and respectively propose three measures to control corruption, namely, the exclusion of corrupt punishers, the exclusion of corrupt defectors, and the exclusion of both corrupt punishers and corrupt defectors. Our results show that the system dynamics driven by these three measures can exhibit many interesting dynamical outcomes including the dominance of defectors, rock-scissors-paper cycle, heteroclinic cycle, or interior attractor. We further demonstrate that excluding corrupt punishers can improve the situation of corruption more efficiently than excluding corrupt defectors. In addition, excluding both corrupt defectors and corrupt punishers can more effectively promote the emergence of cooperation for a broad parameter range.

Pro-social punishment is a key driver of harmonious and stable society. However, this institution is vulnerable to corruption since law-violators can avoid sanctioning by paying bribes to corrupt law-enforcers. Consequently, to understand how altruistic behavior survives in a corrupt environment is an open question. To reveal potential explanations here, we introduce corrupt enforcers and violators into the public goods game with pool punishment, and assume that punishers, as corrupt enforcers, may select defectors probabilistically to take a bribe from, and meanwhile defectors, as corrupt violators, may select punishers stochastically to be corrupted. By means of mathematical analysis, we aim to study the necessary conditions for the evolution of cooperation in such corrupt environment. We find that cooperation can be maintained in the population in two distinct ways. First, cooperators, defectors, and punishers can coexist by all keeping a steady fraction of the population. Second, these three strategies can form a cyclic dominance that resembles a rock-scissors-paper cycle or a heteroclinic cycle. We theoretically identify conditions when the competing strategies coexist in a stationary way or they dominate each other in a cyclic way. These predictions are confirmed numerically.

We review the literature on foreign direct investment (FDI) and provide an empirical analysis of factors affecting FDI. Conjectures of the disparity of FDI between the coastal and western regions of China and policy recommendations are also made.

This article analyzes different cultures of corruption with regard to their evolutionary stability, i.e. their ability to annihilate small disturbances in the equilibria between corrupt and noncorrupt agents. The article starts with the development of an evolutionary model of the interactions between corrupt and noncorrupt citizens and functionaries of the state, which is subsequently explored by formal analyses and computer simulation. It turns out that zero-corruption is always evolutionarily stable, whereas pervasive corruption displays only conditional evolutionary stability and thus is empirically rare. Between these two extremes there is organized bureaucratic corruption, which is in most cases quasi-stable with fluctuations around an equilibrium representing the coexistence of corrupt and noncorrupt agents. Empirical analyses of corruption data from 89 countries seem to corroborate these theoretical insights.

India, along with some of the other middle low income countries like Brazil, Russia, China and the Republic of Korea is competing with high income developed nations like USA and Japan in the knowledge sector. India has to its advantage a big pool of knowledge workers like scientists, engineers, and researchers available at low cost. The pertinent question is whether the flow of knowledge has resulted in inclusive growth. This research paper is a critical analysis of the challenges and opportunities on the pathway to India's journey towards becoming a global leader in knowledge economy with respect to the four pillars as defined by the Knowledge Assessment Model (KAM) of the World Bank, namely, economic and institutional regime, education, information and communication technology, and innovation.

This study analyzes the drivers and constraints affecting enterprise capacity utilization (CU) in the Middle East and North Africa (MENA) region. We used data from the World Bank Enterprise Survey and a fractional logit model to examine the impacts of institutional, infrastructural, and sustainability factors on firms’ CU. Our analysis highlights corruption and competition in the informal sector as significant impediments to firms’ CU, alongside complex infrastructure barriers that hinder the optimization. Conversely, environmental responsibility and innovation emerge as critical drivers for enhancing CU. Surprisingly, top managers’ experience introduces a counteractive influence that negatively affects CU. Beyond the empirical findings, this study’s implications extend to various stakeholders, notably policymakers. Emphasizing the need to address corruption, foster an enabling business environment, strategically invest in infrastructure, promote sustainability initiatives, and foster innovation to enhance CU are paramount. Additionally, providing targeted managerial training to mitigate negative managerial influences is crucial. Implementing these recommendations promises to foster an environment conducive to improved CU, driving economic growth, and sustainable development in the MENA region and benefiting stakeholders across sectors.

In his first term (2012–2017), Xi Jinping’s signature domestic policy was an anti-corruption campaign that targeted political enemies and venality in public office. The anti-corruption work has continued in his second term while being superseded in domestic political importance by a campaign to “Sweep Away Black and Eliminate Evil (2018–2020).” On the surface, the campaign to Sweep Away Black and Eliminate Evil is an anti-crime campaign that focuses on the “black and evil forces” of organized crime and their official protectors, but its scope extends well beyond the ganglands to target a wide range of social and political threats to the Chinese Communist Party (CCP). Drawing on interviews with government officials, police and citizens as well as analysis of policy documents, this paper argues that the campaign is a populist initiative designed to bolster CCP legitimacy and serve as a mechanism of social control. Like the Chongqing prototype that inspired it, however, the campaign harbors a dark side that could undermine the contemporary Chinese social contract in which people are willing to sacrifice personal freedoms in exchange for security and material benefits.

This article examines and evaluates a variety of factors that characterize the PRC at the end of 2023–including elite politics and Xi Jinping’s position; a malaise that grips society; the “securitization” of almost all dimensions of policy; economic challenges and concerns; and the state of the CCP as a ruling Leninist party.

The current evidence-base regarding the impacts of corruption on firm performance is based largely on studies of individual countries and contains mixed results. Therefore, the aim of this paper is to achieve a better insight into this relationship by reporting the results of a firm-level analysis of the impacts of corruption on firm performance using World Bank Enterprise Survey (WBES) data across 40 African countries. The clear result is that corruption significantly enhances rather than harms annual sales, employment and productivity growth rates. The outcome is to re-theorize participation in acts of corruption as beneficial for the individual firms engaged in such activity, while recognizing the wider evidence that this is not an optimal strategy at the aggregate country level. The outcome will be to advance knowledge about how corruption needs to be tackled. To eliminate corruption, it is shown here to be necessary for public authorities to recognize that corruption is an efficient strategy at the firm level and to adopt measures to alter the cost/benefit ratio confronting individual enterprises, and at the same time, to address the country-level formal institutional deficiencies that characterize many developing countries and result in the prevalence of corruption.

This paper explores how corruption indirectly affects economic growth through business regulation in Latin America and the Caribbean, a relationship that has scarcely been addressed in the literature. Although regulation of the private sector explains GDP per capita, the effect is conditioned by the level of corruption. When the control of corruption is greater, there is an increase in the extent to which bureaucracy when starting a business and trading across borders negatively affects GDP per capita in Latin America and the Caribbean. This finding corroborates the “greasing the wheels” hypothesis.

Discussions on entrepreneurial ecosystems have been a relatively recent addition to the corpus of entrepreneurship literature and have focused heavily on fostering aggressive growth, often technology-based, ventures. Here, we tune the ecosystem model to fit the non-technologically innovative entrepreneurial spaces of emerging economies. We propose a new framework for viewing the cultural effect on entrepreneurship through interactions between the individual entrepreneur’s identity, and networks within specific infrastructural and institutional regimes wrought by predominant culture. In applying the model to mid-twentieth century Bangladesh, we find a culturally predominant negative perception of entrepreneurial activity. We show this contributed to the growth of certain types of entrepreneurship in the country that were rife with (i) higher risk-tolerant behavior among entrepreneurs and (ii) the rise of entrepreneurs having strong links with specific social networks, which together led to an increase in institutional decay and the rise of corruption.