Toward the Modeling of Russia's Monetary System

The paper explains the dynamics of monetary aggregates in Russia with the help of country's trade balance, the creation of deposits by commercial banks and cross-border flows of rubles and (foreign) currency. The volumes of deposits and flows, in turn, depend on changes the currency/ruble exchange rate and favorable external economic conditions. The model was estimated by the Kalman filter, the adequacy was confirmed by stimulation. Monthly money supply forecasts have an accuracy of ~ 1%. It was found that the volume of additional deposits created per month is ~ 300 billion RUB (this leads to real inflation of 9.5% per annum), money flows that are not related to payments for goods: rubles inflow from abroad ~ 100 billion RUB, currency goes abroad ~ $ 15 billion. With the growth / fall of the dollar exchange rate by 1 RUB per month, during the same month, the creation of additional ruble deposits and the arrival of rubles from outside decreases / increases by $ 0.114 billion. The increase of the Currency Reserve Assets of Russia is accompanied by going abroad ~ 5% of the increase.

Leontief Meets Markov: Sectoral Vulnerabilities Through Circular Connectivity

Economists have been aware of the mapping between an Input-Output (I-O, hereinafter) table and the adjacency matrix of a weighted digraph for several decades (Solow, Econometrica 20(1):29–46, 1952). An I-O table may be interpreted as a network in which edges measure money flows to purchase inputs that go into production, whilst vertices represent economic industries. However, only recently the language and concepts of complex networks (Newman 2010) have been more intensively applied to the study of interindustry relations (McNerney et al. Physica A Stat Mech Appl, 392(24):6427–6441, 2013). The aim of this paper is to study sectoral vulnerabilities in I-O networks, by connecting the formal structure of a closed I-O model (Leontief, Rev Econ Stat, 19(3):109–132, 1937) to the constituent elements of an ergodic, regular Markov chain (Kemeny and Snell 1976) and its chance process specification as a random walk on a graph. We provide an economic interpretation to a local, sector-specific vulnerability index based on mean first passage times, computed by means of the Moore-Penrose inverse of the asymmetric graph Laplacian (Boley et al. Linear Algebra Appl, 435(2):224–242, 2011). Traversing from the most central to the most peripheral sector of the economy in 60 countries between 2005 and 2015, we uncover cross-country salient roles for certain industries, pervasive features of structural change and (dis)similarities between national economies, in terms of their sectoral vulnerabilities.

Window dressing in the Active Share scores in publicly reported portfolios

Using a unique database that includes publicly disclosed fund holdings at the end of the quarter as well as the holdings in all non-publicly disclosed months, we found that some funds could alter their portfolios in publicly disclosed months to artificially increase their Active Share scores and consequently appear more active and take advantage of the positive relationship between Active Share and money flows. We show how, consistent with non-informed trades, these funds erode their future performance. However, these funds reach their objective of increasing future money flows. Moreover, we find that window-dresser funds can be identified by controlling the level of tracking error. The funds with high Active Share scores and low tracking errors have the highest levels of Active Share window dressing and the worst future returns. However, compared with less active funds, they are able to capture higher money flows. JEL CLASSIFICATION G23; G11

The Structure of the NHS and How Money Flows

This article sets out to explain the structure of the NHS, how this is changing and how the money flowsthrough the system.

A Blockchain based Fund Management Scheme for Financial Transactions in NGOs

: In the world of the latest technologies, the blockchain is one of the popular techniques for stopping fraudulent activities. Non-Government Organization (NGO) is increasingly being used to support all the needy people across the globe to shape the world’s responsibility towards society for sustainable development. The existing method of donating money and its monitoring is faced with a major corruption problem in several world-renowned NGOs. A blockchain can transform the way the current business of money transaction is being done in NGOs. The blockchain-based application works on the concept of a decentralized system. This article presents a blockchain-based transaction system to prevent corruption and money laundering in NGOs and government fundraising organizations. A Smart contract has been designed to stop any illegitimate block changes during a financial transaction. Since every node has a copy of the ledger, so it is very difficult to perform malicious activity. Furthermore, the donator can watch how the money flows in the different transactions, and everyone can browse the account history. An evaluative judgment, compared with various consensus algorithms, has also been presented along with their complex nature. The decentralized approach has eliminated the chance of a single point of failure, which in turn makes the system robust. The developed framework for the financial transaction using blockchain has been tested using the Rinkeby Test Network. The generators and campaign contracts have been developed and deployed in the Rinkeby testing network. The results indicate the computing to be much more secure and free from the scam in comparison to the traditional client-server financial transaction system. Finally, the proposed approach suggests scenarios such as in NGOs where the introduced security approach should prove to be adequate.

Funny Money or Legitimate Finance? Shadow Banking and Policy Impacts in China

Government officials in China have taken different views regarding shadow banking. Some have seen the industry as overly risky, potentially undermining the formal financial system, while others have asserted that it is an increasingly important part of the financial system, filling a gap in finance provision to particular sectors and smaller firms. Do their views matter? Regulators have striven to crack down on the riskiest practices in shadow banking, but are the policies effective? In this article, we analyze the impact of government attitudes and actions on the shadow banking sector. Using a unique data set based on information collected from various sources in a difference-in-difference model, we find that shadow banking regulation plays a strong role in China’s financial sector, while contradictory government views (in the form of commentary in the People’s Daily) on shadow banking do not. This reveals that shadow banking is strongly affected by political authority when it is codified into regulation. Only some aspects of shadow banking can be legitimized through regulation, while the remainder of China’s financial system remains constrained due to state dominance over the financial sector. This underscores the “funny” nature of shadow banking’s money flows. This article is one of the first to study the effects of government views and regulations on the shadow banking system.

DESIGNING A LOGISTICS NETWORK IN INTERNATIONAL TRADE

This article is devoted to the study of methods for solving the problem of increasing the economically sustainable development of international logistics networks, the study of the conditions of capital investments in logistics infrastructure with a positive accumulated cash balance as the accumulated amount of money flows with time stages of planning. The methodology of T. L. Saati will allow you to combine all the important components (indicators for evaluating the company’s performance: ROE, ROA, the ratio of own funds to attracted funds, etc.) into an analytical network.