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A Network Model of Multilateral Equilibrium Exchange Rates
Abstract
The objective of the paper is to propose a new network model of multilateral equilibrium exchange rates based on network theory. The model introduces a topological component into the exchange rate analysis, consistently taking into account simultaneous higher-order interactions among all currencies. The article argues that the evolution of nominal exchange rates can be modeled on a network, where the nodes represent individual currencies and the links among them represent weighted returns on a hypothetical investment in each currency. For the purposes of this article, a multilateral exchange rate network is represented by multilateral dependent changes in bilateral exchange rates. The currency demand indicator (CDI), an elementary cell of the network model, is defined as weighted log-returns on each currency. The CDI provides a useful proxy for demand for each currency from other currencies and reflects all underlying balance of payments flows. The model identifies the stationary position of the exchange rate network, i.e. the episodes of minimal temporal variety of the CDI, when weighted returns on the links are close to zero. The stationary position of the exchange rate network points to the equilibrium levels of bilateral exchange rates for each currency pair. The model applies mainly to currencies with floating exchange rate regimes, although useful information can also be obtained for currencies with pegged exchange rates. For illustration, the model is applied to bilateral daily 1995-2016 exchange rates among130 currencies sourced from the Thomson Reuters Datastream.
The Basel III regulation raised the minimum capital requirements for banks. However, its implementation may not have reduced systemic risks. Academicians investigating optimal banking regulations do not have a consensus on whether to increase or decrease capital requirements. Here, we use the agent-based approach to study capital regulation and its implications on the evolution of the banking system. We chose the Russian banking system to proxy key model parameters. We find that lower capital requirements imply higher financial stability than the Basel III regime, where the regulator requires banks to have capital over 10% of its risk-weighted assets’ amount. However, the regulatory rule to merely have a non-negative capital is the simplest solution that best fits heterogeneous economies. It produces the highest ratio of capital to assets, the least number of bank bankruptcies, and the lowest demand of banks to enter the interbank market to cover liquidity problems for all systems.
This paper proposes a method for assessing international spillovers from nominal demand shocks. It quantifies the impact of a shock in the crisis country on all other countries. The paper concludes that the network effects in shock spillovers can be substantial, comparable, and often exceed the initial shock. Individual countries may amplify, absorb, or block spillovers. Most developed countries pass-through shocks, whereas low-income countries and oil exporters tend to block shock spillovers. The method is used to study demand shocks originating from a large and medium country, China and Ukraine respectively.
We modeled the currency networks through the use of REER (real effective exchange rate) instead of a bilateral exchange rate in order to overcome the confusion in selecting base currencies. Based on the MST (minimum spanning tree) approach and the rolling-window method, we constructed time-varying and correlation-based networks with which we investigate the linkage effects among different currencies. In particular, and as the source of empirical data, we chose the monthly REER data for a set of 61 major currencies during the period from 1994 to 2014. The study demonstrated that obvious linkage effects existed among currency networks and the euro (EUR) was confirmed as the predominant world currency. Additionally, we used the rolling-window method to investigate the stability of linkage effects, doing so by calculating the mean correlations and mean distances as well as the normalized tree length and degrees of those currencies. The results showed that financial crises during the study period had a great effect on the currency network’s topology structure and led to more clustered currency networks. Our results suggested that it is more appropriate to estimate the linkage effects among currency networks through the use of REER data.
Trade flows are characterised by interdependent economic networks such as the global supply chain, international bilateral agreements, trans-national credit, and foreign direct investments, as well as non-economic components (i.e. infrastructures, cultural ties and spatial barriers). We construct an Interdependent Multi-layer Model (IMM), which is rooted in the theoretical concept of spatial interaction, in order to identify the links within these networks and trace their impacts on trade flows. In our aim to investigate horizontal and vertical interdependency among networks we calibrate the interaction model (IMM) for a set of 40 countries, and thereafter examine the influence of shocks such as economic downturns upon the interdependent networks, which in our model are represented as economic, socio-cultural and physical layers. Most importantly, the model allows us to understand the propagation of cascading effects (both positive and negative) at national and global scales.
The External Balance Assessment (EBA) methodology has been developed by the IMF’s Research Department as a successor to the CGER methodology for assessing current accounts and exchange rates in a multilaterally consistent manner. Compared to other approaches, EBA emphasizes distinguishing between the positive empirical analysis and the normative assessment of current accounts and exchange rates, and highlights the roles of policies and policy distortions. This paper provides a comprehensive description and discussion of the 2013 version (“2.0†) of the EBA methodology, including areas for its further development.
Economic integration, globalization and financial crises represent examples of processes whose understanding requires the analysis of the underlying network structure. Of particular interest is establishing whether a real economic network is in a state of (quasi)stationary equilibrium, i.e. characterized by smooth structural changes rather than abrupt transitions. While in the former case the behaviour of the system can be reasonably controlled and predicted, in the latter case this is
generally impossible. Here, we propose a method to assess whether a real economic network is in a quasi-stationary state by checking the consistency of its structural evolution with appropriate quasi-equilibrium maximum-entropy ensembles of graphs. As illustrative examples, we consider the International Trade Network (ITN) and the Dutch Interbank Network (DIN). We find that the ITN is an almost perfect example of quasi-equilibrium network, while the DIN is clearly out-of-equilibrium. In the latter, the entity of the deviation from quasi-stationarity contains precious information that allows us to identify remarkable early warning signals of the interbank crisis of 2008. These early warning signals involve certain dyadic and triadic topological properties, including dangerous ‘debt loops’ with different levels of interbank reciprocity.
We study the ever more integrated and ever more unbalanced trade relationships between European countries. To better capture the complexity of economic networks, we propose two global measures that assess the trade integration and the trade imbalances of the European countries. These measures are the network (or indirect) counterparts to traditional (or direct) measures such as the trade-to-GDP (Gross Domestic Product) and trade deficit-to-GDP ratios. Our indirect tools account for the European inter-country trade structure and follow (i) a decomposition of the global trade flow into elementary flows that highlight the long-range dependencies between exporting and importing economies and (ii) the commute-time distance for trade integration, which measures the impact of a perturbation in the economy of a country on another country, possibly through intermediate partners by domino effect. Our application addresses the impact of the launch of the Euro. We find that the indirect imbalance measures better identify the countries ultimately bearing deficits and surpluses, by neutralizing the impact of trade transit countries, such as the Netherlands. Among others, we find that ultimate surpluses of Germany are quite concentrated in only three partners. We also show that for some countries, the direct and indirect measures of trade integration diverge, thereby revealing that these countries (e.g. Greece and Portugal) trade to a smaller extent with countries considered as central in the European Union network.
Most real and engineered systems include multiple subsystems and layers of
connectivity, and it is important to take such features into account to try to
improve our understanding of these systems. It is thus necessary to generalize
"traditional" network theory by developing (and validating) a framework and
associated tools to study multilayer systems in a comprehensive fashion. The
origins of such efforts date back several decades and arose in multiple
disciplines, and now the study of multilayer networks has become one of the
most important directions in network science. In this paper, we discuss the
history of multilayer networks (and related concepts) and review the exploding
body of work on such networks. To unify the disparate terminology in the large
body of recent work, we discuss a general framework for multilayer networks,
construct a dictionary of terminology to relate the numerous existing concepts
to each other, and provide a thorough discussion that compares, contrasts, and
translates between related notions such as multilayer networks, multiplex
networks, interdependent networks, networks of networks, and many others. We
also survey and discuss existing data sets that can be represented as
multilayer networks. We review attempts to generalize single-layer-network
diagnostics to multilayer networks. We also discuss the rapidly expanding
research on multilayer-network models and notions like community detection,
connected components, tensor decompositions, and various types of dynamical
processes on multilayer networks. We conclude with a summary and an outlook.
The cross-correlations between the exchange rate fluctuations of 74
currencies over the period 1995-2012 are analyzed in this paper. The eigenvalue
distribution of the cross-correlation matrix exhibits a bulk which
approximately matches the bounds predicted from random matrices constructed
using mutually uncorrelated time-series. However, a few large eigenvalues
deviating from the bulk contain important information about the global market
mode as well as important clusters of strongly interacting currencies.We
reconstruct the network structure of the world currency market by using two
different graph representation techniques, after filtering out the effects of
global or market-wide signals on the one hand and random effects on the other.
The two networks reveal complementary insights about the major motive forces of
the global economy, including the identification of a group of potentially fast
growing economies whose development trajectory may affect the global economy in
the future as profoundly as the rise of India and China has affected it in the
past decades.
We analyze structure of the world foreign currency exchange (FX) market viewed as a network of interacting currencies. We analyze daily time series of FX data for a set of 63 currencies, including gold, silver and platinum. We group together all the exchange rates with a common base currency and study each group separately. By applying the methods of filtered correlation matrix we identify clusters of closely related currencies. The clusters are formed typically according to the economical and geographical factors. We also study topology of weighted minimal spanning trees for different network representations (i.e., for different base currencies) and find that in a majority of representations the network has a hierarchical scale-free structure. In addition, we analyze the temporal evolution of the network and detect that its structure is not stable over time. A medium-term trend can be identified which affects the USD node by decreasing its centrality. Our analysis shows also an increasing role of euro in the world's currency market.
In this paper we detect the linear and nonlinear co-movements presented on the real exchange rate in a group of 28 developed and developing countries that have suffered currency and financial crises during 15 years. We have used the matrix of Pearson correlation and Phase Synchronous (PS) coefficients and an appropriate metric distance between pairs of countries in order to construct a topology and hierarchies by using the Minimum Spanning Tree (MST). In addition, we have calculated the MST cost and global correlation coefficients to observe the co-movements dynamics along the time sample. By comparing Pearson and phase synchronous information we address a new methodology that can uncover meaningful information on the contagion economic issue and, more generally, in the debate around interdependence and/or contagion among financial time series. Our results suggest some evidence of contagion in the Asian currency crises but this crisis contagion is due to previous and stable interdependence.
This paper provides a survey on studies that analyze the macroeconomic effects of intellectual property rights (IPR). The first part of this paper introduces different patent policy instruments and reviews their effects on R&D and economic growth. This part also discusses the distortionary effects and distributional consequences of IPR protection as well as empirical evidence on the effects of patent rights. Then, the second part considers the international aspects of IPR protection. In summary, this paper draws the following conclusions from the literature. Firstly, different patent policy instruments have different effects on R&D and growth. Secondly, there is empirical evidence supporting a positive relationship between IPR protection and innovation, but the evidence is stronger for developed countries than for developing countries. Thirdly, the optimal level of IPR protection should tradeoff the social benefits of enhanced innovation against the social costs of multiple distortions and income inequality. Finally, in an open economy, achieving the globally optimal level of protection requires an international coordination (rather than the harmonization) of IPR protection.
The propagation of macroeconomic shocks through input-output and geographic networks can be a powerful driver of macroeconomic fluctuations. We first exposit that in the presence of Cobb-Douglas production functions and consumer preferences, there is a specific pattern of economic transmission whereby demand-side shocks propagate upstream (to input-supplying industries) and supply-side shocks propagate downstream (to customer industries) and that there is a tight relationship between the direct impact of a shock and the magnitudes of the downstream and the upstream indirect effects. We then investigate the short-run propagation of four different types of industry-level shocks: two demand-side ones (the exogenous component of the variation in industry imports from China and changes in federal spending) and two supply-side ones (TFP shocks and variation in knowledge/ideas coming from foreign patenting). In each case, we find substantial propagation of these shocks through the input-output network, with a pattern broadly consistent with theory. Quantitatively, the network-based propagation is larger than the direct effects of the shocks. We also show quantitatively large effects from the geographic network, capturing the fact that the local propagation of a shock to an industry will fall more heavily on other industries that tend to collocate with it across local markets. Our results suggest that the transmission of different types of shocks through economic networks and industry interlinkages could have first-order implications for the macroeconomy. © 2016 by the National Bureau of Economic Research. All rights reserved.
The paper models international spillovers from a hypothetical drop of China’s imports as a result of China’s rebalancing of its growth model. A network-based model used in the paper allows capturing higher round network effects of the shock, which are largely unaccounted for in the existing literature. Such effects include direct spillovers from China on its trading partners, subsequent spillins among them, and spillbacks on China itself. The paper finds that the network effects most likely will be substantial, may amplify initial shock, and change the direction of its propagation. The impact on Asia and Pacific will be the strongest followed by the Middle East and Central Asia. The impact on sub-Saharan Africa would be noticeable only for some countries. Spillovers on Europe, including the Euro area, will be moderate, and spillovers on the Western Hemisphere, including the United States, would be very marginal. Metal and non-fuel commodity exporters may experience the largest negative impact.
This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details.
The persistence of global imbalances remains a potential source of instability for the international economic system, which ought to be tackled in order to exit from the current crisis in a better position. This paper shows that the complexity of the global network of trade imbalances has increased over time in terms of the number of countries involved and of the heterogeneity of their conditions. These findings imply that orchestrating a global exchange rate adjustment plan, as done in the 1980s to tackle a similar problem, is certainly more difficult than it was 20 years ago. We also show, however, that the uncoordinated movements in bilateral exchange rates occurred since the early 2000s did not go in the direction of reducing bilateral imbalances. Rebalancing the world economy, thus, seems to require a rich set of coordinated policy actions and economic changes, involving adjustments in both exchange rates and real variables, which are heterogeneous at the country level. We argue that, provided some conditions are satisfied, the variegated effects of the ongoing financial crisis, and the policy responses this has induced, may help the global and bilateral rebalancing process.
We propose that catastrophic events are "outliers" with statistically different properties than the rest of the population and result from mechanisms involving amplifying critical cascades. We describe a unifying approach for modeling and predicting these catastrophic events or "ruptures," that is, sudden transitions from a quiescent state to a crisis. Such ruptures involve interactions between structures at many different scales. Applications and the potential for prediction are discussed in relation to the rupture of composite materials, great earthquakes, turbulence, and abrupt changes of weather regimes, financial crashes, and human parturition (birth). Future improvements will involve combining ideas and tools from statistical physics and artificial/computational intelligence, to identify and classify possible universal structures that occur at different scales, and to develop application-specific methodologies to use these structures for prediction of the "crises" known to arise in each application of interest. We live on a planet and in a society with intermittent dynamics rather than a state of equilibrium, and so there is a growing and urgent need to sensitize students and citizens to the importance and impacts of ruptures in their multiple forms.
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