Search

This paper evaluates the macroeconomic effects of monetary policy for a central bank digital currency rule with traditional monetary policy in an open environment. We build a dynamic stochastic general equilibrium small open model economy with interest-bearing central bank digital currency assets. The redistribution of asset holdings and the change in asset price are the two pathways through which a retail central bank digital currency rule under the traditional monetary policy affects the macroeconomy. Fiat's digital and traditional monetary policies complement one another in lowering macroeconomic fluctuations. As a result, the real exchange rate, current accounts, and consumption are more stable in transmitting foreign shocks. These results occur when price-based or quantitative-based fiat digital monetary policy parallels traditional price-based monetary policy.

In this paper, we develop a structural model to estimate the current level of the natural rate for a small open economy, featuring a rich set of shocks to provide economic intuition for its underlying drivers. The model follows the New Keynesian tradition with several frictions and is able to draw implications for a monetary policy stance. In contrast to other DSGE models in the literature, this framework includes two main blocks—one related to the foreign sector and one associated with the local economy, linked by the uncovered interest rate parity condition. With this structure, the natural rate is affected by local and external factors, disaggregated in permanent and transitory shocks. Using Bayesian techniques, the model estimates the natural interest rate for two example cases, Mexico and Canada, considering data from these economies and the United States. Results show that the US economy is relevant to explaining natural rates in both countries. For the Mexican case, the drivers are shocks to the US risk premium and the marginal efficiency of investment, as well as country risk premium variations. For Canada, shocks to the households’ discount factor play an important role.

In this study we evaluate a national economic model using a system dynamics approach. We use a set of macroeconomic data for a transition economy to validate the model behaviour in the past, and then simulate the alternative paths of key macroeconomic variables. Instead of studying only a fraction of the economy, or using simple and abstract models, we build a large-scale national economic model. As the study is based on system dynamics information feedback, it provides additional insights about the macroeconomic effects of the economic policy, making it a valuable tool for economic policy analysis. Such insights are instrumental for understanding the total effects of economic policies and their full economic consequences. To demonstrate this, we have simulated one actual economic policy intervention and its alternative scenario. [ABSTRACT FROM AUTHOR]

Forecasting is an attractive topic in every field of study because no one knows the exact nature of the underlying phenomena, but it can be guessed using mathematical functions. As the world progresses towards technology and betterment, algorithms are updated to understand the nature of ongoing phenomena. Machine learning (ML) algorithms are an updated phenomenon used in every task aspect. Real exchange rate data is assumed to be one of the significant components of the business market, which plays a pivotal role in learning market trends. In this work, machine learning models, i.e., the Multi-layer perceptron model (MLP), Extreme learning machine (ELM) model and classical time series models are used, Autoregressive integrated moving average (ARIMA) and Exponential Smoothing (ES) model to model and predict the real exchange rate data set (REER). The data under consideration is from January 2019 to June 2022 and comprises 864 observations. This study split the data set into training and testing and applied all stated models. This study selects a model that meets the Key Performance Indicators (KPI) criteria. This model was selected as the best candidate model to predict the behaviour of the real exchange rate data set.

The article analyzes the interaction between monetary and fiscal policy in Mexico. We calibrated a semi-structural model for a small open economy, based on Aguilar and Ramírez-Bulos (2018), for Mexico by using quarterly data from 2001Q1 to 2019Q4. The fiscal policy block models the fiscal deficit depending on output, an endogenous sovereign risk premium, a state-owned oil company, and public debt dynamics with domestic and foreign components. We assumed a fiscal rule whereby the deficit has an upper bound. The monetary policy follows a Taylor rule. We study the effects of different shocks on the economy, such as a drop in commodity prices, an expansion of public spending, an increase in the risk premium, a hike in the interest rate, and depreciation of the real exchange rate. We show that, remarkably, the risk premium channel transmits threats from the fiscal block to the monetary block, calling for the central bank to stabilize inflation. By contrast, starting at the economy’s steady state, an exogenous monetary policy shock affects the fiscal block mainly through the interest rate’s influence on the debt service, prompting a fiscal response to stabilize deficit.

Debido a la incertidumbre al respecto, en este artículo se analiza cuál podría ser la postura de política monetaria más adecuada para México: una que mantenga el objetivo de inflación sin afectar negativamente el crecimiento del producto. Se estima el valor de la tasa de interés neutral en México para los próximos cinco años con base en la regla de Taylor y un modelo vectorial autorregresivo (VAR) cointegrado (CVAR). Los resultados sugieren que la tasa de política monetaria se encuentra por arriba de la tasa neutral de interés, lo que, combinado con el potencial recorte de tasas a escala internacional, podría conceder al banco central durante casi todo el sexenio grados de libertad para mantener su tasa por debajo del nivel actual; en el corto plazo se podría recortar la tasa de política monetaria actual en 25 puntos al menos sin arriesgar la convergencia a la meta de inflación.

This paper presents the first-ever comparison of the forecasting power of two types of narratives: articles in a major daily newspaper and regular research reports released by professional forecasters. The applied testing methodology developed in 22 and extended in this paper includes two natural language processing (NLP) techniques – the sentiment analysis and the wordscores model – that are used to convert the text corpora into the NLP indices. These indices are explanatory variables in linear regression, Granger causality test, vector autoregressive model and random forest model. The paper extends this methodology by applying Latent Dirichlet Allocation (LDA) to the newspaper corpus to filter out articles that discuss topics not relevant for economic and financial analysis. The forecasting test is conducted for two major banks in Poland – BZ WBK and mbank and for major daily newspaper Rzeczpospolita, in Polish. It is shown that mbank narratives have the best forecasting power, while BZ WBK and Rzeczpospolita trade second and third place depending on the model applied. In the vast majority of analyzed cases adding an NLP index to the model improves the forecast accuracy. The answer to the title question is – it depends. Before paying for economic research asset managers are advised to apply methods such as presented in this paper to evaluate whether sell-side research offers any forecasting value in comparison with a newspaper.

This study compares and contrasts the multiple characterizations of mean reversion in financial time series as regards the restrictions they imply. This is accomplished by translating them into statements about an alternative measure, the "Average Crossing Time" or ACT. We argue that the ACT measure, per se, provides not only a useful benchmark for the degree of mean reversion/aversion, but also an intuitive, and easily quantified sense of one time series being "more strongly mean‐reverting/averting" than another. We conclude our discussion by deriving the ACT measure for a wide class of stochastic processes and detailing its statistical characteristics. Our analysis is principally undertaken within a class of well‐understood production based asset pricing models. [ABSTRACT FROM AUTHOR]

This paper presents three measures of the output gap estimated by a dynamic stochastic general equilibrium model of the Czech economy. We argue that the most plausible description of the business cycle provides the output gap defined as a deviation from a flexible price level of output, which is generated solely by permanent growth shocks. Our model shows that 2006-2008 overheating of the economy and the following 2008-2009 slump can be largely attributed to development in a world economy and export and import sectors, while the 2012-2013 recession was caused mainly by a combination of adverse domestic demand and cost shocks.

Objective To investigate the relationship of E47, lysyl oxidase like2 protein(LOXL2) expressions with clinicopathologic parameters of esophageal squamous cell carcinoma(ESCC) patients. Methods The mRNA and protein levels of E47 and LOXL2 in ESCC and adjacent tissues were detected by qRT-PCR and immunohistochemistry method, and their correlation with the clinicopathologic parameters were analyzed. Results The expressions of E47 and LOXL2 mRNA in ESCC tissues were significantly higher than those in adjacent normal tissues (all P < 0.05). The positive expressions of E47 and LOXL2 proteins in ESCC were higher than those in adjacent tissues (all P < 0.05). The expression of E47 protein was closely correlated with invasion depth. The expression of LOXL2 protein was both significantly correlated with the level of histological differentiation and lymphatic metastasis (P < 0.05). E47 protein expression was positively correlated with LOXL2 expression (r=0.582, P < 0.05). Conclusion The mRNA and protein levels of E47 and LOXL-2 are highly expressed in ESCC tissues, and significantly correlated with clinicopathologic characteristics. High expressions of E47 and LOXL2 may promote the invasion and metastasis of ESCC, and they are expected to be the potential biomarkers for the prognosis.

In this paper the authors investigate the statistical properties of some cryptocurrencies by using three layers of analysis: alpha-stable distributions, Metcalfe’s law and the bubble behaviour through the LPPL modelling. The results show, in the medium to long-run, the validity of Metcalfe's law (the value of a network is proportional to the square of the number of connected users of the system) for the evaluation of cryptocurrencies; however, in the short-run, the validity of Metcalfe’s law for Bitcoin is questionable. According to the bidirectional causality between the price and the network size, the expected price increase is a driver for more investors to join the Bitcoin network, which may lead in the end to a super-exponential price growth, possibly due to a herding behaviour of investors. The authors then used LPPL models to capture the behaviour of cryptocurrencies exchange rates during an endogenous bubble and to predict the most probable time of the regime switching. The main conclusion of this paper is that Metcalfe’s law may be valid in the long-run, however in the short-run, on various data regimes, its validity is highly debatable.

European interest rates movements are affected by various internal and external factors. This paper studies the link between European and American short- and long-term interest rates. In particular, we consider the forward interest rates coming from euro and dollar IRS term structures. The econometric techniques employed are co-integration, Granger-causality, OLS and GMM. Our results indicate that European remote settlement forward and long-term interest rates are primarily driven by US rates and confirm that the causality acts mainly from the US to the Eurozone. This was true even during the recent periods of European Central Bank quantitative easing. These factors weaken the ECB’s ability to intervene. In fact, we found the impact of American monetary policy on long-term interest rates to be also relevant for European bonds.

Copyright of Zeitschrift für Immobilienökonomie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Forecasts are a central component of policymaking; the Federal Reserve's forecasts are published in a document called the Greenbook. Previous studies of the Greenbook's inflation forecasts have found them to be rationalizable but asymmetric if considering particular subperiods, for example, before and after the Volcker appointment. In these papers, forecasts are analyzed in isolation, assuming policymakers value them independently. We analyze the Greenbook forecasts in a framework in which the forecast errors for different variables are allowed to interact. We find that allowing the losses to interact makes the unemployment forecasts virtually symmetric, the output forecasts symmetric prior to the Volcker appointment, and the inflation forecasts symmetric after the onset of the Great Moderation. [ABSTRACT FROM AUTHOR]

Forecasting inflation is of key relevance for central banks, not least because the objective of low and stable inflation is embodied in most central banks’ mandates and the monetary policy transmission mechanism is well known to be subject to long and variable lags. To our best knowledge, central banks around the world use conditional as well as unconditional forecasts for such purposes. Turning to unconditional forecasts, these can be derived on the basis of structural and non-structural models. Among the latter, vector autoregressive (VAR)-models are among the most popular tools.

In this paper, we study the small noise asymptotic expansions for certain classes of local volatility models arising in finance. We provide explicit expressions for the involved coefficients as well as accurate estimates on the remainders. Moreover, we perform a detailed numerical analysis, with accuracy comparisons, of the obtained results by means of the standard Monte Carlo technique as well as exploiting the Polynomial Chaos Expansion approach. [ABSTRACT FROM AUTHOR]

Introduction: Our model was conducted from Kuwaiti payer's perspective to provide evidence on the cost-effectiveness of Sodium zirconium cyclosilicate (SZC) versus patiromer to correct and maintain serum potassium (K+) in combination with renin-angiotensin-aldosterone system inhibitors (RAASis) with different dose titration in patients with chronic kidney disease/heart failure (CKD/HF) with/without renal replacement therapy (RRT)., Methodology: The model was developed as a patient-level, fixed-time increment stochastic simulation to simulate the complexity of disease, including multiple coexisting and competing conditional risks. This model was established to compare SZC versus patiromer as a treatment for hyperkalemia (HK) among adult populations with underlying conditions of advanced CKD stages 3a-5 or HF to correct and maintain serum K + over a lifetime horizon. The clinical outcomes of SZC and patiromer were demonstrated through arm-specific K + trajectories extracted from the HARMONIZE trial and OPAL-HK trial, respectively. The utility data was captured from different studies. Direct medical cost was captured from local data from Kuwaiti hospitals. Sensitivity analyses were conducted to assess the uncertainty in the model., Results: Within different scenarios of CKD/HF, SZC was a cost-saving option, with/without RRT, whether one-off administration or repeated administration, except for one-off treatment administration among the HF cohort, which generated an incremental cost effectiveness ratio of KWD 331/quality adjusted life year (QALY). The incremental QALY of SZC ranged from 0.007 to 0.202. In addition, the savings observed with SZC fall within a range of KWD -60 to KWD -1,235 at serum K+ ≥ 5.1 mmol/L., Conclusion: The evidence generated by our model recommends the inclusion of SZC as a treatment option to correct HK and maintain normal serum K + level for CKD/HF patients within the Kuwaiti healthcare system. The costs saved from reducing frequent HK episodes, RAASis discontinuation/down titration, major cardiovascular events, and hospitalization offset the drug acquisition cost of SZC.

China's exceptionally large share of investment in GDP has been widely noted. Rebalancing away from investment to consumption has been on China's agenda to realize more sustainable growth. As investment growth slows, the question is whether consumption could replace investment as a growth engine. This paper empirically explores the drivers of Chinese household consumption and specifically tests whether investment has affected household consumption beyond the standard income channel. Our empirical results using both national- and provincial-level data suggest that investment has had a significant impact on household consumption beyond the household income channel. The effects are particularly strong in the post-Global Financial Crisis period, suggesting that the Chinese government's stimulus measures, which aimed mostly at investment spending, have significantly affected households' decision to consume both through households' current and expected future income channel. [ABSTRACT FROM AUTHOR]

Optimal monetary policy models in the linear-quadratic framework produce high variability of interest rates, and are hence inconsistent with the data where typically interest rate smoothing is observed. In this paper we determine optimal monetary polices in a VAR model of the Polish economy with parameter uncertainty. We prove that there exists a structure of the multiplicative uncertainty in the optimal linear-quadratic model that explains the central bank’s behaviour. Thus proving that parameter uncertainty can be the rationale for “timid” movements in the short-interest rate dynamics. Finally, we show that there is trade off between parameter uncertainty and the interest rate smoothing incentive. [ABSTRACT FROM AUTHOR]

In theory, the nearest-nickel rounding scheme renders no financial gains for anyone given that each final digit has the same probability of appearing. However, in practice, rounding may yield non-zero net effects as most store prices end with nine. In this paper, price data from representative Canadian grocery stores are used to assess whether the current rounding system imposes a monetary loss on firms or consumers. Specifically, I evaluate how one- to ten-item purchases and the six different Canadian provincial sales tax rates influence penny-rounding. The results show that penny-rounding financially benefits the firms at the expense of the consumers, imposing a net transfer of approximately $3.27 million CAD from consumers to grocery vendors every year. This amount averages to $157 of additional revenue for a typical grocery store per year. [ABSTRACT FROM AUTHOR]

The natural real rate of interest has been on a declining path for the past 30 years. I present a regime-switching analysis of the natural rate, which suggests that the current low levels are likely to persist in the near future. I identify a high global demand for safe assets as the most important factor in keeping the natural rate low. I conclude that the current low levels of the policy rate are generally appropriate, with some upside risk, and that forward guidance should be characterized by a flat policy rate path. [ABSTRACT FROM AUTHOR]

Abstract: Using panel data for 99 countries, we confirm that the measured elasticity of prices with respect to money is higher, and closer to unity, the higher is money growth and the longer the time horizon over which the data are averaged. We propose two explanations. In one, the true model of inflation involves a lagged response to money growth. In the other, there is negative correlation between shocks to inflation and money growth. Our empirical results can be explained if high–money‐growth countries have (i) shorter lags or (ii) less negative correlation, when compared to countries with low money growth. [ABSTRACT FROM AUTHOR]

Background: Modeling exchange rate volatility has remained crucially important because of its diverse implications. This study aimed to address the issue of error distribution assumption in modeling and forecasting exchange rate volatility between the Bangladeshi taka (BDT) and the US dollar ($). Methods: Using daily exchange rates for 7 years (January 1, 2008, to April 30, 2015), this study attempted to model dynamics following generalized autoregressive conditional heteroscedastic (GARCH), asymmetric power ARCH (APARCH), exponential generalized autoregressive conditional heteroscedstic (EGARCH), threshold generalized autoregressive conditional heteroscedstic (TGARCH), and integrated generalized autoregressive conditional heteroscedstic (IGARCH) processes under both normal and Student's t-distribution assumptions for errors. Results and Conclusions: It was found that, in contrast with the normal distribution, the application of Student's t-distribution for errors helped the models satisfy the diagnostic tests and show improved forecasting accuracy. With such error distribution for out-of-sample volatility forecasting, AR(2)-GARCH(1, 1) is considered the best. [ABSTRACT FROM AUTHOR]

We provide evidence on the sticky-information model of Mankiw and Reis () by examining how often individual professional forecasters revise their forecasts. We draw interest rate and unemployment rate forecasts from the monthly Wall Street Journal surveys. We find evidence that forecasters frequently leave forecasts unchanged but revise more often the larger the changes in the information set; additionally, the information sensitivity of revision frequencies increased after 2007. We also find that, on average, forecasters in our sample revise more frequently than found in previous research but that revised forecasts are not consistently more accurate. [ABSTRACT FROM AUTHOR]

The financial crisis and subsequent sovereign debt crisis together had a profound impact on the current economic environment. This study reexamines the established stylized facts and previous evidence regarding the predictive association between financial variables and real economic activity considering changed economic circumstances. This paper focuses on the predictive ability of the term spread, short-term interest rate and stock returns for real GDP growth in the G-7 countries. We compare the predictive content of nominal financial variables with that of real financial variables and consider the proper number of financial predictors and time variations of forecasting performance. The forecasting results unambiguously indicate that financial variables have regained their predictive power since the financial crisis. Moreover, this study shows that real financial variables are superior to nominal variables and that using several financial indicators for forecasting GDP growth is preferable. [ABSTRACT FROM AUTHOR]

In this paper, it is tried to propose a robust model for predicting inflation in Iran among alternative models. For doing this, monthly data from April 1990 to the end of September 2009 is used. Firstly, it is tried to determine whether the CPI data is chaotic or stochastic. It is shown that it is chaotic rather than stochastic. Therefore, it is predictable. Then, a stochastic differential equation model is estimated (specifically a geometric Brownian motion) for CPI in Iran. In order to compare the prediction power of the model other alternative models of prediction like ARMA, non-linear GARCH, EGARCH, TGARCH are also used to extrapolate inflation during a six month prediction period. Based on RMSE, MAE, U-Tail, it is revealed that stochastic differential equation model is much more robust than the alternative models mentioned above.

In models of monetary policy, discretionary policymaking is typically constrained in its ability to manage public beliefs. However, when a policymaker possesses private information, policy actions serve as signals to the public about unobserved economic conditions and belief management becomes an integral part of optimal discretion policies. This article derives the optimal time-consistent policy for a general linear-quadratic setting. The optimal policy is illustrated in a simple New Keynesian model, where analytical solutions can be derived as well. In this model, imperfect information about the policymaker's output target leads to lower policy losses. [ABSTRACT FROM AUTHOR]