An MCMC based Bayesian inference approach to parameter estimation of distributed lag models for forecasting used product returns for remanufacturing

As awareness of environmental issues increases, the pressures from the public and policy makers have forced original equipment manufacturers (OEMs) to consider remanufacturing as the key product design option. In order to make the remanufacturing operations more profitable, forecasting product returns is critical due to the uncertainty in quantity and timing. This paper proposes a predictive model selection algorithm to deal with the uncertainty by identifying a better predictive model. Unlike other major approaches in literature such as distributed lag models or DLMs, the predictive model selection algorithm focuses on the predictive power over new or future returns and extends the set of candidate models. The case study of reusable bottles shows that the proposed algorithm can find a better predictive model than the DLM.

Download Full-text

Using distributed lag models to predict regional budget revenues

Economic Analysis Theory and Practice ◽

10.24891/ea.19.6.1154 ◽

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.

Download Full-text

Analysis and Forecasts of the Demand for Imported Wine in China

Cornell Hospitality Quarterly ◽

10.1177/1938965520981070 ◽

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.

Download Full-text