Monetary Model Research Articles

Animal spirits in a monetary model

We integrate Keynesian economics with general equilibrium theory in a new way. We develop a simple graphical apparatus, the IS-LM-NAC framework, that can be used by policy makers to understand how policy affects the economy. A new element, the No-Arbitrage-Condition (NAC) curve, connects the interest rate to current and expected future values of the stock market and it explains how ‘animal spirits’ influence economic activity. Our framework provides a rich new approach to policy analysis that explains the short-run and long-run effects of policy.

The Impact of Remittances on Exchange Rate and Money Supply: Does “Openness” Matter in Developing Countries?

ABSTRACT Using a perfect-foresight general equilibrium monetary model, this article explores the impact of migrants’ remittances on exchange rate and money supply in developing countries and the effect of their “openness” on the impact. The findings indicate that the inflow of remittances leads to appreciation of the nominal exchange rate and increase of money supply under the fixed exchange rate regime. Moreover, a greater degree of openness helps mitigate the appreciation. These findings suggest that remittances and the degree of openness play a significant role in complementing monetary and exchange rate policy, helping to boost economic development. Using a sample of 114 developing countries from 1970 to 2013, empirical tests with both Anderson-Hsiao with instrumental variables and system generalized method of moments’ estimations confirm the theoretical findings.

Application of new multi-objective optimization algorithm for EV scheduling in smart grid through the uncertainties

Ecological and economics issues are caused to give careful consideration to electric vehicles (EV) and sustainable power source assets. One of the proposed answers for increment the impact of these assets, is to utilize the electric vehicles potential. The capability of electric vehicles require planning for Smart Distribution Systems (SDS). Request reaction programs, as a suitable device to utilize endorsers’ potential in ideal administration of the system, gives dynamic nearness of supporters in control framework execution change and these projects, in basic conditions, can give the request prerequisites diminishment, in a brief timeframe. In this work, attempts to presents a multi-objective scheduling of EV based on the sustainable assets in smart grid, cover uncertainty caused by inexhaustible assets and EVs, by considering of the request reaction projects and EV battery stockpiling framework, limit the working expenses and the measure of intensity framework contamination, with enhancing procedures. Improved optimization algorithm is utilized for taking care of the advancing issue. Operating costs dropped much further utilizing monetary model of the demand response and vehicle charge/discharge and smart program in the hours when the load is lower. Effectiveness of proposed method is applied on 33 bus standard power system.

A monetary model of bilateral over-the-counter markets

We develop a model of monetary exchange in bilateral over-the-counter markets to study the effects of monetary policy on asset prices and financial liquidity. The theory predicts asset prices carry a speculative premium that reflects the asset's marketability and depends on monetary policy and the market microstructure where it is traded. These liquidity considerations imply a positive correlation between the real yield on such assets as stocks and housing and the nominal yield on Treasury bonds—an empirical observation long regarded anomalous. We provide novel theoretical implications and empirical evidence regarding the effect of monetary policy on the liquidity of these markets.

Markov switching in exchange rate models: will more regimes help?

This paper examines the performance of Markov switching models of the exchange rate using a data-driven approach to determine the number of regimes rather than simply assuming two states. The analysis is conducted for the British pound, Canadian dollar, and Japanese yen exchange rates against the US dollar over the last 30 years with alternative specifications including a simple segmented trends model and Markov switching autoregressive models with monetary fundamentals. A noteworthy finding is that the number of regimes that minimizes mean square forecast errors tends to correspond to the number of regimes selected by Bayesian information criteria (but not Markov-switching-specific information criteria). For the monetary models, the number of regimes that minimizes forecast errors also tends to correspond to the most parsimonious model with well-behaved residuals. Although allowing for more regimes yields forecasting improvement over single- or two-regime models, the Markov switching model is still unable to outperform a random walk. This suggests that exchange rate models need to allow for novel, as opposed to repetitive or predetermined, structural change.

Do the Markov Switching-based Hybrid Models Perform Better in Forecasting Exchange Rates?

ABSTRACT In this study, we extend the traditional monetary model and the random walk model with Markov-switching method and propose two new forecasting models called the Markov switching monetary model (MSMM) and Markov switching random walk model (MSRW). Then, we evaluate the forecasting ability of these two new mixed models, MSMM and MSRW, and compare their performance with the traditional pure monetary model and pure Random walk model based on Mean Squared Forecast Error and Mean Absolute Forecast Error. The results show that the two hybrid models significantly improve the forecasting ability compared with the two traditional models in most scenarios. Moreover, we reexamine the role of data frequency in determining the number of regimes and in affecting the accuracy of forecast evaluation with different data frequency.

The Non‐Observed Economy in Portugal: The monetary model and the MIMIC model

AbstractThis paper offers estimations for the Portuguese path of the Non‐Observed Economy (NOE), in the period 1970–2015, through two seminal approaches: monetary method and the Multiple Indicators Multiple Causes (MIMIC) model. It is observed that the tax burden and social benefits are its main causes. Then, to get a more in‐depth understanding of the phenomenon, it provides a study of the Granger causality between the NOE and the official Gross Domestic Product (GDP), emphasizing the implications of the NOE on the Portuguese economy. Evidence has been found for the existence of bidirectional causality between the NOE and the GDP, suggesting that the formal economy affects the NOE, and conversely that the NOE affects the economic growth.

New Monetarism in Continuous Time: Methods and Applications

We develop a New Monetarist model in continuous time where agents trade continuously in competitive markets and infrequently in pairwise meetings. Agents can produce and consume both in flows over time intervals and in discrete quantities at points in time. We detail the methodology to solve individual optimization problems and characterize the full set of perfect foresight equilibria. We illustrate the role of continuous time and the tractability of our approach with three applications: (i) forward guidance with policy announcements; (ii) aggregate demand management and monetary policy; (iii) open-market operations with partially liquid bonds.

Does Bitcoin Behave As a Currency?: A Standard Monetary Model Approach

We derive the Bitcoin exchange rate dynamics by solving the exchange rate equation of the standard flexible-price monetary model to investigate any characteristics of Bitcoin like a currency. The dynamics is driven by an asymmetric mean-reverting fundamental shock which can be attributed to a money demand shock. A crash occurs when the exchange rate with a weakened mean-reverting force breaches a lower boundary where a smooth-pasting condition is imposed. The empirical results show the exchange rate dynamics can be calibrated according to the model, in which the mean reversion of the dynamics is positively co-integrated with the Bitcoin transaction volume indicating demand for Bitcoin; and with the risk reversals of the commodity currencies (Australian dollar and Canadian dollar) in currency option markets. The analysis shows that the Bitcoin exchange rate shares some characteristics of commodity currencies with crash risk. This suggests that Bitcoin behaves as a currency between fiat money and a crypto-commodity used for trading and investment purposes.

Banking Panics and the Lender of Last Resort in a Monetary Economy

This paper studies the role of a lender of last resort (LLR) in a monetary model where a shortage of bank’s monetary reserves (or a banking panic) occurs endogenously. We show that while a discount window policy introduced by the LLR is welfare improving, it reduces the banks’ ex ante incentive to hold reserves, which increases the probability of a panic, and causes moral hazard in asset investments. We also examine the combined effect of other related policies such as a penalty in lending rate, liquidity requirements, and constructive ambiguity.

4-D Modeling of a Sustainable Economy: Integrating Economic, Environmental, Population, and Monetary Models

Leontief’s Input-Output Analysis equation has long been used around the world and especially in China to calculate production and consumption balances. This research shows how to connect environmental and financial balances to production balances in an economic region by generalizing the Leontief’s equations from vector form to tensor form. This is important for creating economic and environmental policies aimed at sustainable economies. It provides a general modeling approach which can quantitatively connect economic processes with biological and physical processes of the environment. If economic processes cannot be measured as to their real physical/biological impacts, one does not know whether or not such economic processes are sustainable in nature. The tensor generalization also enables the depiction of both economic processes as production and finance. The use of tensor mathematics for input-output models of both economy and its environment provides a data architecture to create simulation models of the environmental impact of an economy.

Banking Panics and the Lender of Last Resort in a Monetary Economy

This paper studies the role of a lender of last resort (LLR) in a monetary model where a shortage of bank’s monetary reserves (or a banking panic) occurs endogenously. We show that while a discount window policy introduced by the LLR is welfare improving, it reduces the banks’ ex ante incentive to hold reserves, which increases the probability of a panic, and causes moral hazard in asset investments. We also examine the combined effect of other related policies such as a penalty in lending rate, liquidity requirements, and constructive ambiguity.

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Telecom customer clustering via glowworm swarm optimisation algorithm

The glowworm swarm optimisation (GSO) algorithm is a novel algorithm with the simultaneous computation of multiple optima of multimodal functions. Data-clustering techniques are classification algorithms that have a wide range of applications. Since K-means algorithm is easy to fall into the local optimum by the selection of initial clustering centre, GSO algorithm is used for the telecom customers clustering. The customer consumption data is extracted by means of the recency frequency monetary (RFM) model and the standardised data is clustered automatically using the GSO algorithm's synchronous optimisation ability. In the clustering optimisation algorithm, adaptive step size is used instead of the original fixed step size to avoid local optimisation of the algorithm and obtain higher accuracy. Compared with K-means clustering algorithm, GSO approach can automatically generate the number of clusters and use RFM model to reduce effectively the size of the data processing. The results of the experiments demonstrate that the GSO-based clustering technique is a promising technique for the data clustering problems.

Telecom customer clustering via glowworm swarm optimisation algorithm

The glowworm swarm optimisation (GSO) algorithm is a novel algorithm with the simultaneous computation of multiple optima of multimodal functions. Data-clustering techniques are classification algorithms that have a wide range of applications. Since K-means algorithm is easy to fall into the local optimum by the selection of initial clustering centre, GSO algorithm is used for the telecom customers clustering. The customer consumption data is extracted by means of the recency frequency monetary (RFM) model and the standardised data is clustered automatically using the GSO algorithm's synchronous optimisation ability. In the clustering optimisation algorithm, adaptive step size is used instead of the original fixed step size to avoid local optimisation of the algorithm and obtain higher accuracy. Compared with K-means clustering algorithm, GSO approach can automatically generate the number of clusters and use RFM model to reduce effectively the size of the data processing. The results of the experiments demonstrate that the GSO-based clustering technique is a promising technique for the data clustering problems.

Oil Prices and the U.S. Dollar Exchange Rate: Evidence from the Monetary Model

This paper analyzes how changes in global oil prices affect the US dollar (USD) exchange rate based on the monetary model of exchange rate. We find evidence indicating a negative relationship between oil prices and the USD exchange rate against 12 currencies. Specifically, the analysis of the impulse response function shows that the depreciation rate of the USD exchange rate ranges between 0.002 and 0.018 percentage points as a result of a one-standard deviation positive shock to the real price of crude oil. In the same vein, the forecast error variance decomposition analysis reveals that variation in the USD exchange rate is largely attributable to changes in the price of oil rather than monetary fundamentals. In last, the out-of-sample forecast exercise indicates that oil prices enhance the predictability power of the monetary model of exchange rate.

On Nonlinear Effects of Inflation Across Countries

Many emerging market economies have a higher tolerance for inflation than industrialized economies. Recent empirical studies find nonlinear effects of inflation and that the threshold rate is higher for emerging countries. Motivated by the fact that emerging countries have higher business costs, this paper incorporates entrepreneurial occupational choices in a parsimonious monetary model and rationalizes the observed different thresholds rates. The reason is that business costs distort the occupational decisions and affect the inflation-output tradeoff.

Divisia monetary model of exchange rate determination: the case of Philippines

Divisia monetary model of exchange rate determination: the case of Philippines

The forward premium puzzle and Markov-switching adaptive learning,

Using Markov-switching adaptive learning, this paper builds on adaptive learning (AL) techniques pioneered in Evans and Honkapohja (2001, 2012) and presents an empirical analysis and explanation of the forward premium puzzle, first characterized in Fama (1984). Furthermore, this paper addresses the need for using mean-square stability as the criterion for stability when observing state dependent parameters rather than the traditional stability conditions presented by Blanchard and Kahn. Using these tools, I am able to parameterize a monetary exchange rate model to mimic the empirical observations which lead to the forward premium puzzle. I find that agents who possess knowledge of central bank interest rate regime changes and who use constant gain learning can replicate the negative bias present found in the forward premium regression. By using a robust parameterization aimed at weighting information in a representative agent's learning process, I am able to remove the negative bias found empirically in the forward premium regression. The central finding of this paper is that under constant gain learning, regime changes by central banks, modeled by Markov-switching liquidity preferences, explain the forward premium bias found empirically. This is different from most research, which focuses on persistent monetary model fundamentals to explain the bias. This result holds under robust parametrizations of constant gain learning, monetary fundamental persistence, and Markov-switching liquidity preferences, which govern the model. Thus, this paper offers a novel solution to the forward premium puzzle.

CURRENCY UNION WITH OR WITHOUT BANKING UNION

AbstractWe build a symmetric two‐country monetary model with credit to study the interplay between currency integration and credit markets integration. The currency arrangement affects credit availability through default incentives. We capture credit markets integration by the extra cost incurred to obtain credit for cross‐border transactions and, with the euro area context in mind, label as banking union a situation where this cost is low. For high levels of the cross‐border credit cost, currency integration may magnify default incentives, leading to more credit rationing and lower welfare. The integration of credit markets restores the optimality of the currency union.