Flexible-price Monetary Model Research Articles

Assessing Monetary Model of Exchange Rate Determination: Case of Indonesia

The main purpose of this paper is to assess the exchange rate determination in Indonesia after the Asian financial crisis. We use the Monetary Model to assess the prediction of the Indonesian Rupiah against the United States Dollar and other currencies of the largest trade partners of Indonesia. The models are the Flexible Price Monetary Model and the Sticky Price Monetary Model. We estimate short-run and long-run relationships using the Error Correction Model. The Monetary Model can explain partially the exchange rate variations, but the signs of money, income, and fiscal balance are not as expected. The causality may run from the exchange rate to money and price level.

Exchange rates in India: current account monetarism in a nonlinear context

Abstract The Indian exchange rate system has evolved from a pegged system to the current managed float. The study examines the presence of a long-run equilibrium in the monthly Indian exchange rate (Rs/USD) using a current account monetary model (or flexible price monetary model) while accounting for different nonlinearities over the period January 1993 to January 2014 (pre-inflation targeting period). The nonlinear adjustment to disequilibria is modelled using a nonlinear error correction model (NLECM). The nonlinear current account monetarism (CAM) model includes nonlinear transformations of long-run dynamics in the ECM to account for different nonlinearities: multiple equilibria (cubic polynomial function), nonlinear mean reversion (rational polynomial function), and smooth and gradual regime switches (exponential smooth transition autoregressive (ESTAR) function). The NLECM-ESTAR model outperforms other alternatives based on model and forecast performance measures, implying the existence of nonlinear mean reversion and smooth transition across different periods of overvaluation and undervaluation of the exchange rate. This implies the presence of asymmetric adjustment to the movements from the long-run equilibrium, but the nature of such transitions is smooth and not abrupt. The paper also establishes the uniqueness of the long-run equilibrium. A comparison to the sticky price monetary model could not be made due to stationary exchange rate disequilibrium.

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.

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.

A Study on the Impact of China’s Monetary Policy on South Korea’s Exchange Rate

Purpose - The adjustment of one country's monetary policy can cause the macroeconomic change of other countries. Due to this, this paper attempts to analyze the impact of China’s monetary policy on South Korea’s exchange rate. Research design, data, and methodology - Based on the flexible-price monetary model, sets of annual time series from 1980 to 2017 are employed to perform an empirical estimation. The vector error correction model is also used to exploit the short-run relationship between both of them. Of course, the South Korea’s real GDP, the China’s real GDP, South Korea’s interest rate, the South Korea’s interest rate and the South Korea’s monetary supply are treated as independent variables in this paper. Result - The long-run findings reveal that the China’s money supply has a negative effect on South Korea’s exchange rate. Respectively, the short-run findings depicts that the China’s money supply has negative a effect on South Korea’s exchange rate. Of course, other variables selected in this paper also have an effect on South Korea’s exchange rate whatever positive or negative. Conclusions - As the empirical evidence shows, the China’s monetary policy has a negative effect on South Korea’s exchange rate whenever in the long run or in the short run.

自适应多元货币模型与人民币汇率预测 (Adaptive Multiple Monetary Model With Application in Forecasting the RMB Exchange Rates)

Chinese Abstract: 在人民币国际化不断推进、人民币汇率双向波动加强的背景下，构建具有优良预测能力的人民币汇率预测模型愈发重要。参数模型对汇率预测的能力不仅取决于模型设定是否正确，同时还取决于能否迅速探测模型参数的结构性变化以使用最佳信息估计模型参数。本文构建了自适应多元货币模型，并对2011年1月以后的美元、欧元、英镑和日元兑人民币汇率月度数据进行样本外预测，发现在中长期(3至24个月)的人民币汇率预测中，自适应多元货币模型能显著优于随机游走模型、购买力平价模型、弹性货币模型、利率平价模型、泰勒规则模型与偏移型泰勒规则模型这六种汇率预测主流模型。该模型能准确捕捉模型参数的时变特征，探测汇率动态的结构性变化以实时检测参数同质区间，并寻找最佳参数估计以提高人民币汇率预测精度。 English Abstract: To develop an outstanding Renminbi exchange rates forecasting model based on the background of Renminbi internationalization and the increased two-way volatility becomes much more important. By developing an adaptive multivariable monetary model, we do the out-of-sample forecasting for the Renminbi exchange rates after 01/2011 and compare the forecasting accuracy with the other 6 different widely used competitive models. We find that the forecasting ability of a parameter model depends not only on whether it is correctly specified but also on the efficiency of whether it can detect the structure changes and using the effective observations to estimate the parameters. Our developed model can manage of capturing the parameters’ time-varying properties and significantly outperform the Random Walk, Purchasing Power Parity model, Flexible Price Monetary Model, Interest Rate Parity Model, Taylor Rule Model, and the Taylor Rule Differential Model in the middle and the long run (3- to 24- months ahead). In this paper, we have developed an adaptive multiple monetary regression model which can not only detect the structure changes automatically at every time point but can also detect the parameter homogenous subintervals and identify the longest homogeneous subintervals which are used as the best subinterval to estimate the parameters.

The INR/USD Exchange Rate Determination: An Empirical Investigation of the Flexible Price Monetary Model in a Vector Auto Regression Framework

The current study attempts to examine the importance of the Flexible Price Monetary (FPM) Model in explaining the INR/USD exchange rate movement with macro variables such as relative money stock, relative rates of interest and relative output for the period from April 1995 till December 2016. Prior to estimating the empirical model, an array of non-stationarity tests was employed to identify the time series characteristics of the data. Since all the data series were confirmed to be integrated of order one, the multivariate cointegration methodology was used to verify long-run validity of the model. The empirical results garner support for the FPM model in determining INR/USD exchange rate in the long run. The test on direction of causality confirmed existence of causality from FPM variables to exchange rate. The empirical model was estimated in the Vector Auto regression (VAR) framework and variance decomposition analysis was used to examine fluctuation in INR/USD exchange rate caused by the shocks in FPM model variables. It was found that, the monetary model variables explain the exchange rate patterns over a longer period of time but was found not very effective in the short run and hence cannot be considered as a useful framework in explaining the variations in INR/USD exchange rate.

An Artificial Neural Network-Based Approach to the Monetary Model of Exchange Rate

This paper aims to investigate the predictive accuracy of the flexible price monetary model of the exchange rate, estimated by an approach based on combining the vector autoregressive model and multilayer feedforward neural networks. The forecasting performance of this nonlinear, nonparametric model is analyzed comparatively with a monetary model estimated in a linear static framework; the monetary model estimated in a linear dynamic vector autoregressive framework; the monetary model estimated in a parametric nonlinear dynamic threshold vector autoregressive framework; and the naive random walk model applied to six different exchange rates over three forecasting periods. The models are compared in terms of both the magnitude of their forecast errors and the economic value of their forecasts. The proposed model yielded promising outcomes by performing better than the random walk model in 16 out of 18 instances in terms of the root mean square error and 15 out of 18 instances in terms of mean return and Sharpe ratio. The model also performed better than linear models in 17 out of 18 instances for root mean square error and 14 out of 18 instances for mean returns and Sharpe ratio. The distinguishing feature of the proposed model versus the present models in the literature is its robustness to outperform the random walk model, regardless of whether the magnitude of forecast errors or the economic value of the forecasts is chosen as a performance measure.

Demystifying the Meese–Rogoff puzzle: structural breaks or measures of forecasting accuracy?

ABSTRACTStructural breaks have been suggested by several economists as a possible explanation for the Meese–Rogoff puzzle, in the sense that an exchange rate model can outperform the random walk in terms of the out-of-sample forecasting error if the period under investigation is free of structural breaks. The results indicate that structural breaks cannot explain the inability of the flexible price monetary model to outperform the random walk. The only plausible explanation for the Meese–Rogoff puzzle is that forecasting accuracy is traditionally assessed by magnitude-only measures. When forecasting accuracy is assessed by alternative measures that do not rely exclusively on the magnitude of error, the monetary model can outperform the random walk regardless of the presence or otherwise of structural breaks.

Parallel Currency Markets and the Monetary Exchange Rate Model: A VECM Application to Turkey Over 1987–1998

This study takes a novel approach to testing the monetary model of exchange rate determination by allowing for distortions from the underground economy to be reflected via inclusion of the parallel exchange rate. Using a VECM methodology, an augmented model is tested and compared to a traditional flexible-price monetary model for Turkey over 1987–1998. While in-sample results are supportive of both models, out-of-sample analysis favors inclusion of the parallel exchange rate. Furthermore, the augmented model beats a random walk with and without drift over to mid-range forecast horizons. These results highlight the need to consider potential market distortions of exchange rate movements.

Does Existence of Long-Run Relationship Ensure Predictability of Exchange Rate? Empirical Analysis of Indian Rupee Vis-à-Vis US Dollar under Monetary Model Framework

This paper examines the empirical relevance of the flexible price monetary model in the Indian context to determine whether US dollar-Indian rupee exchange rate movements are in line with the changes in monetary fundamentals namely relative money supply, relative interest rates and relative output. A sample period of nineteen years (August 1996 to March 2015) was considered for the study and the entire period was divided into two sub periods marked by distinct patterns of exchange rate volatility and variations in the behaviour of macro-economic fundamentals. The study examined whether there exists a long-term relationship between exchange rate and variables of the monetary model besides investigating the predictive ability of the model in determining the exchange rate in the Indian context. The Johansen Juselius test of cointegration was carried out and the variables were found to be linearly cointegrated establishing the long-run relationship between exchange rate and monetary fundamentals rate thereby confirming the suitability of the flexible price monetary model in determining Indian rupee vis-a-vis US dollar. The Granger causality test [21] was conducted to determine the direction of causality between variables and to evaluate the predictive power of the monetary model and the test results exhibited some idiosyncratic patterns among the variables across the two sub periods. For the first sub period, the Granger causality test results show that there is a one-way causality from relative output and relative money supply to exchange rate, while there is no causality from relative interest rate to exchange rates. This result is quite puzzling and calls for further investigation. As the direction of causality is changing within the sample, the study suggests that the monetary model standalone cannot be effectively used for predicting exchange rate in the Indian context. A more comprehensive model with more macro-economic variables such as trade balance and capital flows may be combined with the existing variables for effective forecasting of exchange rate in India.

An Empirical Investigation of the Monetary Model Economic Fundamentals

This paper presents an empirical investigation of an important series called “economic fundamentals” derived from the flexible price monetary model of exchange rate determination. The model predicts that the nominal exchange rate is determined by the “economic fundamentals”, referred here as the series ft. As a result, the characteristics of the “economic fundamentals” process may influence the properties of the nominal exchange rate process. We will just use the term “fundamentals”. Nevertheless, many exchange rate models found in the literature assume an ad-hoc process for ft ignoring the fact that the specification of this process can be formally derived within the framework of the monetary model. Using data for several countries on GDP and money supplies, we construct the series ft according to the monetary model specification, and we examine some important characteristics of its empirical distribution such as skewness, kurtosis, stationarity, ARCH and GARCH properties. We observe that the series is not exactly normally distributed, as commonly assumed in many target zone models. This investigation essentially helps with modeling exchange rate and more importantly in the analysis of exchange rate target zones modeling by identifying potential restrictions that need to be taken into consideration when choosing a process for the modeling of the “economic fundamentals”.

Validity of the Monetary Model of the Exchange Rate: Empirical Evidence from Sri Lanka

This paper studied the behaviour of the US dollar vis-a-vis the Sri Lankan rupee exchange rate in order to check the empirical validity of the flexible price monetary model of exchange rate. Data from January 2001 to March 2011 has been studied by employing the Johansen multivariate cointegration test and the Vector Error Correction Model (VEC) as the key techniques. A long-term cointegrating relationship between the nominal exchange rate and variables of monetary model has been found. The error correction term is quite large and significant indicating that short-term deviation from long-term equilibrium is restored within a year. However, regardless of the existence of a long-term relationship found between variables of the monetary model and exchange rate, the evidence is not strong enough to support the validity of the monetary model. This is mainly because of statistically insignificant domestic money supply and incorrect sign reported for foreign money supply. Improper evidences found on key variables of the model led to serious doubt about the ability of the flexible price monetary model in explaining exchange rate movements of US dollar – Sri Lankan rupee in the free floating exchange rate regime. Staff Studies Vol.42(1&2) 2012; 47-74

Directional accuracy, forecasting error and the profitability of currency trading: model-based evidence

Three models (the flexible-price monetary model, PPP and a univariate ARIMA model) are estimated for 45 currency pairs to find out if the profitability of forecasting-based currency trading is more related to the ability of the underlying model to predict the direction of change than the magnitude of the forecasting error. Theoretical considerations show that a correct prediction of the direction of change is neither a necessary nor a sufficient condition for a profitable trade. The results of the exercise indicate that profitability is more strongly correlated with directional accuracy than with the magnitude of the error.

Enhancing the forecasting power of exchange rate models by introducing nonlinearity: Does it work?

It is demonstrated that the forecasting power of the flexible price monetary model of exchange rates can be enhanced by introducing dynamics through the use of a linear error correction specification. However, the introduction of nonlinearity, by using a polynomial in the error correction term, does not lead to any further improvement in forecasting accuracy and may even lead to deterioration. The results provide evidence against the proposition that the Meese–Rogoff puzzle can be explained in terms of failure to account for nonlinearity. It is also shown that the introduction of dynamics boosts the forecasting accuracy (in terms of the magnitude of the forecasting error) of the model relative to the static specification because dynamic specifications involve a random walk component. The empirical results lead to the conclusion that accounting for nonlinearity does not resolve the Meese–Rogoff puzzle.

The Augmented Monetary Model and Exchange Rate Fluctuations; Case of RUB/USD

The present study is examining the impact of macro-economic variables towards exchange rate determination in Russian Federation currency, Ruble. In order to achieve this aim, the monetary model of exchange rate determination is applied here. This study contributes to the literature by adding a new variable of Oil Price into the flexible price monetary model. This objective is examined through a regression analysis. The data is collected from 1998-2013 and natural logarithm is taken. The empirical results revealed that the augmented monetary model is not validated. But there found a significant relationship between oil price and Ruble. The industrial production function is identified not to be significant in the model.

Rupee-Dollar Exchange Rate and Macroeconomic Fundamentals: An Empirical Analysis Using Flexible-Price Monetary Model

This paper empirically investigates the link between Indian rupee-US dollar exchange rates and a set of macroeconomic fundamentals using flexible-price monetary model (FPMM) for the period 1996 M1 to 2010 M12. The Johanson-Juselius cointegration test result indicates the existence of long run relationship between exchange rate and the macroeconomic variables, implying the validity of FPMM model in Indian context even though there is no short run casual relationship exist in the VECM analysis.

THE BLACK-MARKET EXCHANGE RATE VERSUS THE OFFICIAL RATE: WHICH RATE FOSTERS THE ADJUSTMENT SPEED IN THE MONETARIST MODEL?

Many less developed countries have currency controls, which can lead to black-market trade and cause distortions in the exchange market. We test the flexible-price monetary model for 25 less developed countries, using both official and black-market exchange rates. We find that the model is supported in the long run, particularly when black-market rates are used. Measuring the speed of convergence to equilibrium, we find that it is often higher in the black-market specification, implying greater efficiency. This could offer justification for exchange-rate unification, particularly in Latin America.

Monetary Model of Exchange Rate for Thailand: Long-run Relationship and Monetary Restrictions

This paper examines the long-run relationship between exchange rate and its determinants based on the flexible-price monetary model. The multivariate cointegration approach is adopted to attain our objective of this study. The empirical results provide evidence favoring the monetary approach to exchange rate for a small and open emerging economy, namely Thailand. In addition, the validity of the underlying assumptions of the monetary approach to the determination of exchange rate is established. The findings suggest that exchange rate players may effectively monitor and forecast the exchange rate movement via the money supplies, incomes, and interest rates variables of both Thailand and Japan. Besides, one has to follow the economic development of Thailand's major trading partner, Japan, to understanding the movement of exchange rate for Thailand. Moreover, our findings add new insights to accompany previous studies that documented the important influence of the US in the emerging Asian economies.

IS MALAYSIA EXCHANGE RATE MISALIGNMENT BEFORE THE 1997 CRISIS?

This paper seeks to use the flexible-price monetary model in the cointegration and vector error correction model (VECM) contexts to determine whether there was misalignment in the Malaysian ringgit - U.S. dollar before the 1997 currency crisis. Unit roots, cointegration and weak exogeneity are tested to validate the monetary exchange rate model. Generally, it is found that all the series are I(1) process and there exists significant cointegrating vectors. Using the cointegrating vector and the final parsimonious VECM, out of sample predictions for Ringgit exchange rate are generated. The resulting residuals between the actual and the fitted values of exchange rate are the estimated misalignments. From cointegration, our results suggest that the Malaysian ringgit was overvalued from 1995Q2-1997Q2. Based on VECM, our results suggest that ringgit was overvalued from 1995Q2-1996Q2 and slightly undervalued from 1996Q3-1997Q2.