MONEY GROWTH AND INFLATION IN THE UNITED STATES

2007 ◽  
Vol 11 (1) ◽  
pp. 113-127 ◽  
Author(s):  
LANCE BACHMEIER ◽  
SITTISAK LEELAHANON ◽  
QI LI
Keyword(s):  
Linear Models ◽  
Nonlinear Models ◽  
Threshold Model ◽  
Forecast Error ◽  
The United States ◽  
Nonparametric Model ◽  
Money Growth ◽  
Inflation Forecasts ◽  
Inflation Forecasting ◽  
Forecasting Inflation

Specification tests reject a linear inflation forecasting model over the period 1959–2002. Based on this finding, we evaluate the out-of-sample inflation forecasts of a fully nonparametric model for 1994–2002. Our two main results are that: (i) nonlinear models produce much better forecasts than linear models, and (ii) including money growth in the nonparametric model yields marginal improvements, but including velocity reduces the mean squared forecast error by as much as 40%. A threshold model fits the data well over the full sample, offering an interpretation of our findings. We conclude that it is important to account for both nonlinearity and the behavior of monetary aggregates when forecasting inflation.

Asymmetric Exchange Rate Effects on Cross-Border Freight Flows between the United States and Canada

2020 ◽  
Vol 2674 (4) ◽  
pp. 348-361
Author(s):  
Junwook Chi
Keyword(s):  
Exchange Rate ◽  
Linear Models ◽  
Bilateral Trade ◽  
Nonlinear Models ◽  
Exchange Rate Volatility ◽  
The United States ◽  
Trade Flows ◽  
Asymmetric Effects ◽  
Cross Border ◽  
Long Run

This paper investigates possible asymmetric influences of the exchange rate on cross-border freight flows between the U.S.A. and Canada. Linear and nonlinear autoregressive distributed lag models are used to test for the existence of long-run asymmetric effects of 1) currency appreciation and depreciation and 2) exchange rate volatility changes on trade flows by truck, rail, air, vessel, and pipeline. This paper provides evidence that both currency value and exchange rate volatility affect the U.S.–Canada freight flows in an asymmetric manner. The long-run results of the nonlinear models show that exchange rate is found to be significantly associated with the bilateral trade flows between the U.S.A. and Canada. Exchange rate volatility tends to be significantly associated with trade flows in the nonlinear models, while its effects are insignificant in most cases in the linear models. These findings suggest that the conventional linear specification may mislead the asymmetric effects of exchange rate uncertainty on cross-border freight flows. It is also found that exchange rate sensitivities of U.S.–Canada trade flows by transport mode can differ significantly from those of aggregate trade flows. The information derived from disaggregate trade data can be useful for traders and shippers to develop a long-term strategic plan for infrastructure investment and service expansion.

scholarly journals Forecasting Inflation in Latin American Countries Using a SARIMA-LSTM Combination

2021 ◽  
Author(s):  
Rodrigo Peirano ◽  
Werner Kristjanpoller ◽  
Marcel Minutolo
Keyword(s):  
Latin American ◽  
Emerging Economies ◽  
Short Term Memory ◽  
Mean Squared Error ◽  
Moving Average ◽  
Inflation Forecasts ◽  
Inflation Forecasting ◽  
Forecasting Inflation ◽  
New Research ◽  
Model Confidence Set

Abstract Inflation forecasting has been and continues to be an important issue for the world's economies. Governments, through their central banks, watch closely inflation indicators to make national decisions and policies. Controlling growth and contraction requires governments to keep a close eye on the rate of inflation. When planning strategic national investments, governments attempt to forecast inflation over longer periods of time. Getting the inflation forecast wrong, can result in significant economic hardships. However, even given its significance, there is limited new research that applies updated methodologies to forecast it, and even fewer studies in emerging economies where inflation may be drastically higher. This study proposes to forecast the inflation rate in emerging economies based on the commonly used Seasonal Autoregressive Integrated Moving Average (SARIMA) approach combined with Long Short Term Memory (LSTM). The results indicate that the proposed model based on the combination of SARIMA and LSTM, have a higher accuracy in inflation forecasts as measured by the Mean Square Error (MSE) of the proposed models over the SARIMA model and LSTM alone. The loss function used is Mean Squared Error (MSE), and the Model Confidence Set (MCS) is used to test the superiority of the models in the economies of Mexico, Colombia and Peru.

scholarly journals Three Attempts at Inflation Forecasting in Pakistan

2006 ◽  
Vol 45 (3) ◽  
pp. 341-368 ◽  
Author(s):  
Madhavi Bokil ◽  
Axel Schimmelpfennig
Keyword(s):  
Phillips Curve ◽  
Var Model ◽  
Money Growth ◽  
Leading Indicators ◽  
Vector Autoregressive ◽  
Parameter Instability ◽  
Inflation Forecasting ◽  
Forecasting Inflation ◽  
Empirical Approaches ◽  
Univariate Approach

This paper presents three empirical approaches to forecasting inflation in Pakistan. The preferred approach is a leading indicators model, in which broad money growth and private sector credit growth help forecast inflation. A univariate approach also yields reasonable forecasts, but seems less suited to capturing turning-points. A vector autoregressive (VAR) model illustrates how monetary developments can be described by a Phillips-curve-type relationship. We deal with potential parameter instability on account of fundamental changes in Pakistan’s economic system by restricting our sample to more recent observations. Aspects of Gregorian and Islamic calendar seasonality are addressed by using 12-month moving averages.

Linear and non-linear models for national health expenditures in the USA

2018 ◽  
Vol 102 (554) ◽  
pp. 193-197
Author(s):  
Allan J. Kroopnick
Keyword(s):  
United States ◽  
Health Care ◽  
National Health ◽  
Linear Models ◽  
Nonlinear Models ◽  
Elementary Theory ◽  
Health Expenditures ◽  
The United States ◽  
Non Linear ◽  
The Usa

In this brief Article, using the elementary theory of differential equations as well as some basic economic theory, we will develop several estimates for national health expenditures for the United States: one using a linear model and three using non-linear models. We will derive the nonlinear models first and then compare them to the linear one in order to see if they differ significantly. While these estimates are for the United States, the methods used here, because they are robust, could be used for any country. Statistical information may be obtained from the World Bank databases which store health statistics by country [1].What we will do here is estimate the total health costs as a percentage of gross domestic product (GDP) if no further copayments are required. In other words, we are seeking to estimate the total cost of health care as a percentage of GDP when all health care costs are covered by insurance and government subsidy. Several models will be discussed here since such estimates may be made using a variety of assumptions. There is no ‘best’ model, although such a decision is possible when comparing the estimates to actual data.

scholarly journals Forecasting inflation in Romania to improve the monetary policy

2012 ◽  
Vol 64 (2) ◽  
pp. 131-143
Author(s):  
Mihaela Bratu
Keyword(s):  
Mean Squared Error ◽  
Forecast Error ◽  
Forecast Errors ◽  
Inflation Forecasts ◽  
Squared Error ◽  
Inflation Rates ◽  
State Of The Economy ◽  
National Bank ◽  
Economic State ◽  
Forecasting Inflation

Based on data of inflation forecasts provided quarterly by the National Bank of Romania, forecast intervals were built using the method of historical forecast errors. Forecast intervals were built considering that the forecast error series is normally distributed of zero mean and standard deviation equal to the RMSE (root mean squared error) corresponding to historical forecast errors. The author introduced as a measure of economic state the indicator- relative variance of the phenomenon at a specific time in relation with the variance on the entire time horizon. For Romania, when inflation rates follows an AR (1), She improved the technique of building forecast intervals taking into account the state of the economy in each period for which data were recorded. The author concludes that it is necessary to build forecasts intervals in order to have a measure of predictions uncertainty.

Accounting for Observed Cycle Features with a Range of Statistical Models

2016 ◽  
Author(s):  
Don Harding ◽  
Adrian Pagan
Keyword(s):  
United States ◽  
Time Series ◽  
Statistical Model ◽  
Statistical Models ◽  
Linear Models ◽  
Nonlinear Models ◽  
The United States ◽  
Multivariate Methods ◽  
Vector Autoregressions ◽  
Nonlinear Statistical Model

This chapter looks at observed features of the cycle in a variety of time series. It sets out these features for the United States and a number of other countries, and then asks whether these features can be replicated by the use of a particular statistical model—a linear autoregression. For such linear models it is possible to broadly account for the observed features using moments of the series for growth rates, and this strategy is employed in the chapter. It then uses a particular nonlinear statistical model to see if it can match all the features, and further looks at two other nonlinear models first dealt with in Chapter 4. The chapter concludes with an examination of whether the binary indicators summarizing the recurrent states can be used in the context of standard multivariate methods such as vector autoregressions. This turns out not to be straightforward owing to the nature of the binary variables.

scholarly journals Flow over Heated Terrain. Part I: Linear Theory and Idealized Numerical Simulations

2005 ◽  
Vol 133 (9) ◽  
pp. 2552-2564 ◽  
Author(s):  
N. Andrew Crook ◽  
Donna F. Tucker
Keyword(s):  
Numerical Simulations ◽  
Linear Models ◽  
Nonlinear Models ◽  
Thermal Response ◽  
Major Axis ◽  
The United States ◽  
Surface Heating ◽  
Flow Past ◽  
Orographic Forcing ◽  
The Individual

Abstract The flow past heated topography is examined with both linear and nonlinear models. It is first shown that the forcing of an obstacle with horizontally homogenous surface heating can be approximated by the forcing of an obstacle with surface heating isolated over the obstacle. The small-amplitude flow past an obstacle with isolated heating is then examined with a linear model. Under the linear approximation, the flow response to heated topography is simply the addition of the separate responses to thermal and orographic forcing. These separate responses are first considered individually and then the combined response is examined. Nondimensional parameters are developed that measure the relative importance of thermal and orographic forcing. Nonaxisymmetric forcing is then considered by examining the flow along and across a heated elliptically shaped obstacle. It is shown that the low-level lifting is maximized when the flow is along the major axis of the obstacle. The linear solutions are then tested in a nonlinear anelastic model. The response to a heat source and orography are first examined separately. Good agreement is found between nonlinear and linear models for the individual responses to thermal and orographic forcing. The case of uniformly heated flow past an obstacle is then examined. In these simulations, the thermal response is isolated by subtracting the orographic-only response from the full thermal–orographic response. The numerical simulations are able to capture the main features of the thermal response. Finally, numerical simulations of the flow along and across an elliptically shaped heated obstacle are examined, where it is verified that the lifting is maximized when the flow is along the major axis of the obstacle. These results are extended in Part II of this study to examine the moist convective response to flow over both idealized terrain and the complex terrain of the Rocky Mountains of the United States.

Turbofan Engine Robust H-∞ Dynamical Output Feedback Control Design Based on LMI Method

2005 ◽  
Author(s):  
Xi Wang ◽  
Daoliang Tan ◽  
Tiejun Zheng
Keyword(s):  
Output Feedback ◽  
Linear Models ◽  
Nonlinear Models ◽  
Design Method ◽  
State Space Model ◽  
Output Feedback Control ◽  
Linear Matrix ◽  
Turbofan Engine ◽  
Engine Simulation ◽  
Linear State

This paper presents an approach to turbofan engine dynamical output feedback controller (DOFC) design in the framework of LMI (Linear Matrix Inequality)-based H∞ control. In combination with loop shaping and internal model principle, the linear state space model of a turbofan engine is converted into that of some augmented plant, which is used to establish the LMI formulations of the standard H∞ control problem with respect to this augmented plant. Furthermore, by solving optimal H∞ controller for the augmented plant, we indirectly obtain the H∞ DOFC of turbofan engine which successfully achieves the tracking of reference instructions and effective constraints on control inputs. This design method is applied to the H∞ DOFC design for the linear models of an advanced multivariate turbofan engine. The obtained H∞ DOFC is only in control of the steady state of this turbofan engine. Simulation results from the linear and nonlinear models of this turbofan engine show that the resulting controller has such properties as good tracking performance, strong disturbance rejection, and satisfying robustness.

scholarly journals The world market for soybeans: price transmission into Brazil and effects from the timing of crop and trade

Nova Economia ◽  
2007 ◽  
Vol 17 (2) ◽  
pp. 241-270 ◽  
Author(s):  
Mario A. Margarido ◽  
Frederico A. Turolla ◽  
Carlos R. F. Bueno
Keyword(s):  
United States ◽  
Forecast Error ◽  
The United States ◽  
World Market ◽  
Price Transmission ◽  
Long Run ◽  
Cointegration Tests ◽  
The World ◽  
The Law ◽  
The One

This paper investigates the price transmission in the world market for soybeans using time series econometrics models. The theoretical model developed by Mundlack and Larson (1992) is based on the Law of the One Price, which assumes price equalization across all local markets in the long run and allows for deviations in the short run. The international market was characterized by three relevant soybean prices: Rotterdam Port, Argentina and the United States. The paper estimates the elasticity of transmission of these prices into soybean prices in Brazil. There were carried causality and cointegration tests in order to identify whether there is significant long-term relationship among these variables. There was also calculated the impulse-response function and forecast error variance decomposition to analyze the transmission of variations in the international prices over Brazilian prices. An exogeneity test was also carried out so as to check whether the variables respond to short term deviations from equilibrium values. Results validated the Law of the One Price in the long run. In line with many studies, this paper showed that Brazil and Argentina can be seen as price takers as long as the speed of their adjustment to shocks is faster than in the United States, the latter being a price maker.

scholarly journals A global scientific literature of research on water quality indices: trends, biases and future directions

2014 ◽  
Vol 26 (3) ◽  
pp. 245-253 ◽  
Author(s):  
Maria Tereza Ribeiro Alves ◽  
Fabrício Barreto Teresa ◽  
João Carlos Nabout
Keyword(s):  
Water Quality ◽  
Linear Models ◽  
Scientific Literature ◽  
Information Criterion ◽  
The United States ◽  
Water Index ◽  
Resource Managers ◽  
Quality Of Water ◽  
Number Of Publications

AIM: Water quality has been the subject of many recent studies, moreover, the physical, chemical and biological parameters of water are used to investigate water quality and can be combined into a single index, the Water Quality Index (WQI), for use by water resource managers and the general public. The aim of this study was to use scientometrics to evaluate how water quality has been addressed in the international scientific literature. METHOD: For the quantitative analysis of the publications on WQI, we used the search database SCOPUS (http://www.scopus.com). The search was performed using the words "QUALIT* WATER* INDEX*" in papers published in all databases (through 2011). RESULTS: We found 554 articles that dealt with the use of WQI the number of publications has increased significantly over the last 20 years. India had the most studies, with 177 articles, followed by China, Brazil and the United States. These four countries together published 57% of studies on WQI. We generated 15 linear models to explain the number of publication by study sit (country). According to the Akaike Information Criterion (AIC), the best model to explain the number of publications by country was the model that combined Sanitation and Public Supply. CONCLUSION: Finally, this paper presents the state of scientific literature on WQI and demonstrates the growing interest of the scientific community in this issue, which is certainly due to the importance of the quantity and quality of water for human supply, economics, health and the conservation of water resources.

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