A Hilbert Transform Method for Estimating Distributed Lag Models With Randomly Missed or Distorted Observations

1984 ◽  
pp. 134-157 ◽  
Author(s):  
Melvin J. Hinich ◽  
Warren E. Weber
Keyword(s):  
Hilbert Transform ◽  
Transform Method ◽  
Distributed Lag ◽  
Distributed Lag Models

Using distributed lag models to predict regional budget revenues

2020 ◽  
Vol 19 (6) ◽  
pp. 1154-1172
Author(s):  
Yu.V. Granitsa
Keyword(s):  
Unemployment Rate ◽  
Consumer Price Index ◽  
Mathematical Methods ◽  
Distributed Lag ◽  
Key Indicator ◽  
Distributed Lag Models ◽  
Regional Budget ◽  
The Impact ◽  
Financial Result

Subject. The article addresses projections of regional budget revenues, using distributed lag models. Objectives. The purpose is to review economic and statistical tools that are suitable for the analysis of relationship between the revenues of the regional budget system and regional macroeconomic predictors. Methods. The study draws on statistical, constructive, economic and mathematical methods of analysis. Results. In models with quantitative variables obtained under the Almon method, the significant predictors in the forecasting of regional budget revenues are determined mainly by the balanced financial result, the consumer price index, which characterizes inflation processes in the region, and the unemployment rate being the key indicator of the labor market. Models with quantitative variables obtained through the Koyck transformation are characterized by a wider range of predictors, the composition of which is determined by the peculiarities of economic situation in regions. The two-year forecast provides the average lag obtained during the evaluation of the models. The exception is the impact of unemployment rate, which is characterized as long-term. Conclusions. To generate forecasts of budget parameters, the results of both the Koyck method and the Almon method should be considered, though the former is more promising.

scholarly journals Analysis and Forecasts of the Demand for Imported Wine in China

2021 ◽  
pp. 193896552098107
Author(s):  
Anyu Liu ◽  
Haiyan Song
Keyword(s):  
Single Equation ◽  
Specific Model ◽  
Specific Method ◽  
Sparkling Wine ◽  
Econometric Methods ◽  
Distributed Lag ◽  
Distributed Lag Models ◽  
Wine Market ◽  
Wine Demand

The aim of this study is to investigate the long-term determinants of China’s imported wine demand and to forecast wine imports from 2019 to 2023 using econometric methods. Auto-regressive distributed lag models are developed based on neoclassical economic demand theory to investigate the long-term determinants of China’s demand for imported bottled, bulk, and sparkling wine from the top five countries of origin. The empirical results demonstrate that income is the most important determinant of China’s imported wine demand, and that price only plays a significant role in a few markets. Substitute and complement effects are identified between wines from different countries of origin and between imported wines and other liquids. China’s imported wine demand is expected to maintain its rapid growth over the forecast period. Bottled wine will continue to dominate China’s imported wine market. France will have the largest market share in the bottled wine market, Spain will be the largest provider of bulk wine, and Italy will hold the same position for sparkling wine. This is the first study to use a single equation with the general to specific method rather than a system of equations to estimate and forecast China’s demand for imported bottled, bulk, and sparkling wines from different countries of origin. The more specific model setting for each country of origin improves forecasting accuracy.

A Bayesian estimation of lag lengths in distributed lag models

2012 ◽  
Vol 84 (2) ◽  
pp. 415-427 ◽  
Author(s):  
Carlos Alberto Ribeiro Diniz ◽  
Camila Pedrozo Rodrigues ◽  
Jose Galvão Leite ◽  
Rubiane Maria Pires
Keyword(s):  
Bayesian Estimation ◽  
Distributed Lag ◽  
Distributed Lag Models

scholarly journals Critical Assessment Of The Issues In The Application Of Hilbert Transform To Compute The Logarithmic Decrement

2015 ◽  
Vol 60 (2) ◽  
pp. 1105-1108
Author(s):  
M. Majewski ◽  
L.B. Magalas
Keyword(s):  
Internal Friction ◽  
Hilbert Transform ◽  
Computing Methods ◽  
Critical Assessment ◽  
Logarithmic Decrement ◽  
High Dispersion ◽  
Mechanical Spectroscopy ◽  
Transform Method ◽  
Twin Method ◽  
Selection Of

Abstract The parametric OMI (Optimization in Multiple Intervals), the Yoshida-Magalas (YM) and a novel Hilbert-twin (H-twin) methods are advocated for computing the logarithmic decrement in the field of internal friction and mechanical spectroscopy of solids. It is shown that dispersion in experimental points results mainly from the selection of the computing methods, the number of oscillations, and noise. It is demonstrated that conventional Hilbert transform method suffers from high dispersion in internal friction values. It is unequivocally demonstrated that the Hilbert-twin method, which yields a ‘true envelope’ for exponentially damped harmonic oscillations is superior to conventional Hilbert transform method. The ‘true envelope’ of free decaying strain signals calculated from the Hilbert-twin method yields excellent estimation of the logarithmic decrement in metals, alloys, and solids.

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