The resource curse is an evolving phenomenon in the context of financial development. In this paper, using the firm-level data, we assess the impact of resource curse on the banking sector of those ...countries with significant dependence on oil production. Our sample spans from 1Q2001 to 4Q2019 and includes commercial banks from twelve oil-producing countries with an oil rent (% of the GDP) being twenty percent and above. We assess the effect of resource curse on banking profit efficiency, asset quality, and solvency using interest rate spreads, credit infections, and the probability of default, respectively, during periods of varying oil prices. Our results show that during episodes of the price boom, the banking efficiency declines, credit infection worsens, and the probability of default would surge. These findings confirm the presence of resources curse and validate the reasons why countries with excess reliance on natural resources tend to have lower financial development. Considering the role of commercial banking in the financial system, these results have important implications for policymakers.
•We analyze the impact of increasing commodity prices on banking efficiency.•We employ a multifacet methodology based on panel regressions to assess the impact.•The results show that interest rate spreads contracts during the oil price boom.•Our findings depict an upsurge in credit infections due to resource trap.•The resource curse increases the probability of default of the sample banks.
Introduction Cheng, Lian
Social sciences in China,
05/2022, Volume:
43, Issue:
2
Journal Article
Peer reviewed
It's impossible to imagine a modern market economy without finance. After launching the reform and opening and opening up policy in the late 1970s, China also started to rebuilt its financial system, ...which was almost wiped out during the planned economy era. However, progress lagged behind the reform of the real economy for a considerable period of time. There are several reasons for this. First, in the "catch-up" era, the main task of the financial sector was to raise and allocate funds for economic development, while other financial functions were neglected to a large extent. In this context, a bank-dominated financial system seemed to be a right choice and structural reform was not an urgent issue. Second, the risks inherent in financial activities and their possible threats to social stability made the central government extremely cautious about local financial innovations. As a result, the successful local experimentation approach prevailing in the economic transition was not applicable to financial reform. Finally, as modern financial operations and supervision are highly technical, the lack of qualified financial experts also posed a significant obstacle to China's then financial development, especially before the 2000s.
Identifying the parameters of the chaos phenomena in the economic-financial systems is a critical issue to control and avoid the financial crises and bogging the market down. Therefore, in this ...paper, an efficient and reliable optimization algorithm is developed to identify the corresponding parameters of that chaotic dynamical behavior in the fractional-order chaotic, chaotic with noise, and hyper-chaotic financial systems. The introduced algorithm is a cooperation among the fractional calculus (FC) perspective and the basic cuckoo search algorithm to enhance the stochastic cuckoo’s walk via considering the cuckoo’s earlier behaviors from memory. The developed fractional-order cuckoo search (FO-CS) is validated with twenty-eight functions of CEC2017 with different dimensions. Several measures and non-parametric statistical tests are presented to demonstrate the superiority of the introduced algorithm while compared with the CS and the state-of-the-art techniques. The results show that merging of FC properties magnifies CS’s efficiency, convergence speed, and robustness against the complexity of the considered CEC benchmarks suite and the non-linearity of the fractional-order chaotic, chaotic with noise, and hyper-chaotic financial systems.
This study investigates the role of financial access in modulating the effect of education and lifelong learning on inequality in 48 African countries for the period 1996-2014. Lifelong learning is ...conceived and measured as the combined knowledge gained from primary through tertiary education while the three educational indicators are: primary school enrolment; secondary school enrolment and tertiary school enrolment. Financial development dynamics are measured with financial system deposits (liquid liabilities), financial system activity (credit) and financial system efficiency (deposits/credit). Three measures of inequality are employed notably: the Gini coefficient; the Atkinson index and the Palma ratio. The estimation strategy is based on the generalised method of moments. The following findings are established. First, primary school enrolment interacts with all financial channels to exert negative effects on the Gini index. Second, lifelong learning has negative net effects on the Gini index through financial deposit and efficiency channels. Third, for the most part, the other educational levels do not significantly influence inequality through financial access channels. Policy implications are discussed.
•In our novel approach, H∞ attenuates the effect of uncertainties and through H2the consumed control energy is minimized•No attempt so far has been made to design this type of controller for chaotic ...financial systems•Applying optimal mixed H2/H∞control, exploits the positive features of both controllers for financial markets•A hyperchaotic financial system with coexisting attractors is investigated•Numerical simulations clearly confirm the effectiveness of the new model
Due to the importance of consumed control energy in financial systems, employing an optimal controller for these systems could be beneficial. Also, the presence of disturbances is undeniable in most of these systems. Hence, applying optimal mixed H2/H∞ control, which posses the positive features of both H∞ and H2 control, could bring up luminous results for these systems. However, in the literature, no attempt has been made to design thistypeof controller for chaotic financial systems. This issue motivated the current study. In this study, we present a type-2 fuzzy-based optimal mixed H2/H∞ control for a hyperchaotic financial system. In this approach, H∞ attenuates the effect of uncertainties and through H2the consumed control energy is minimized. Also, since the proposed controller is equipped with a type-2 fuzzy observer, it can easily handle uncertainties and unknown functions. Via Lyapunov theorem, it is confirmed that all signals in the system are bounded. In the numerical simulation, firstly, a hyperchaotic financial system with coexisting attractors is investigated. The proposed controller is then applied to the financial system, and the proposed technique's performance is assessed. Numerical simulations clearly confirm the theoretical claims about the effectiveness of the proposed methodology.
•We develop a new finite-time method for controlling and synchronising fractional-order financial systems•A Deep Learning Recurrent Neural Network is integrated by terminal sliding mode control•The ...proposed technique is applied to a chaotic fractional-order financial model with market confidence under highly complex and time-varying uncertainties•It is shown comparatively that when the disturbances are high, the conventional TSMC methods fail
Disturbances are inevitably found in almost every system and, if not rejected, they could jeopardize the effectiveness of control methods. Thereby, employing state-of-the-art observers could improve the reliability and performance of controllers dramatically. Motivated by this, we develop a new finite-time method for controlling and synchronising fractional-order systems. The deep learning recurrent neural network, which is a strong tool in handling highly complex and time-varying uncertainties, is integrated by terminal sliding mode control. On the basis of Lyapunov stability theorem, the finite-time convergence and stability of the closed-loop system are proven. Then, the proposed technique is applied to a chaotic fractional-order financial model with market confidence. In simulations, it is supposed that the system is operating in the presence of complex disturbances. The results of the proposed technique are compared with terminal sliding mode control. Numerical results illustratively confirm the theoretical claims about the robust performance of the deep learning control technique. Also, it is shown that when the disturbances are high, the conventional methods fail.
The Social Life of Bitcoin Dodd, Nigel
Theory, culture & society,
05/2018, Volume:
35, Issue:
3
Journal Article
Peer reviewed
Open access
This paper challenges the notion that Bitcoin is ‘trust-free’ money by highlighting the social practices, organizational structures and utopian ambitions that sustain it. At the paper's heart is the ...paradox that if Bitcoin succeeds in its own terms as an ideology, it will fail in practical terms as a form of money. The main reason for this is that the new currency is premised on the idea of money as a ‘thing’ that must be abstracted from social life in order for it to be protected from manipulation by bank intermediaries and political authorities. The image is of a fully mechanized currency that operates over and above social life. In practice, however, the currency has generated a thriving community around its political ideals, relies on a high degree of social organization in order to be produced, has a discernible social structure, and is characterized by asymmetries of wealth and power that are not dissimilar from the mainstream financial system. Unwittingly, then, Bitcoin serves as a powerful demonstration of the relational character of money.
Bank Liquidity Risk and Performance Chen, Yi-Kai; Shen, Chung-Hua; Kao, Lanfeng ...
Review of Pacific basin financial markets and policies,
03/2018, Volume:
21, Issue:
1
Journal Article
Peer reviewed
Open access
This study employs an alternative measure of liquidity risk to investigate its determinants by using an unbalanced panel dataset of commercial banks in 12 advanced economies over the period ...1994–2006. Dependence on liquid assets for external funding, supervisory and regulatory factors, and macroeconomic factors are all determinants of liquidity risk. Because of higher funding costs for obtaining liquidity, liquidity risk is regarded as a discount for bank profitability, yet liquidity risk shows a premium on bank performance in terms of banks’ net interest margins. Liquidity risk has reverse impacts on bank performance in a market-based financial system.
Given the importance of financial intermediation and the rise of globalization, there is little prior research on how national preferences for financial intermediation (markets versus institutions) ...are determined by cultural, legal, and other national characteristics. Using panel analysis for data on a recent 8-year period for 30 countries, this paper documents that national preferences for market financing increase with political stability, societal openness, economic inequality, and equity market concentration, and decreases with regulatory quality and ambiguity aversion. We confirm with robustness tests that our result for regulatory quality is independent of differences in national wealth and that our result for political stability is independent of both wealth and political legitimacy. These results should be of much interest to managers, scholars, regulators, and policy makers.
This paper argues that the extent of financial contagion exhibits a form of phase transition: as long as the magnitude of negative shocks offecting financial institutions are sufficiently small, a ...more densely connected financial network (corresponding to a more diversified pattern of interbank liabilities) enhances financial stability. However, beyond a certain point, dense interconnections serve as a mechanism for the propagation of shocks, leading to a more fragile financial system. Our results thus highlight that the same factors that contribute to resilience under certain conditions may function as significant sources of systemic risk under others.
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