The Prediction for the Consumer Price Index of Residents in Perspective of Time Series Method in Case of Chongqing

The consumer price index (CPI) measures the relative number of changes in the price level of consumer goods and services over time, reflecting the trend and degree of changes in the price level of goods and services purchased by residents. This article uses the ARMA model to analyze the fluctuation trend of the CPI (taking Chongqing as an example) and make short-term predictions. To test the predictive performance of the model, the observation values from January to December 2023 were retained as the reference object for evaluating the predictive accuracy of the model. Finally, through trial predictions of the data from May to August 2023, it was found that the constructed model had good fitting performance.

Feasibility Analysis of Agricultural Product Price Index Insurance Based on Pilot Cases

Agricultural product price index insurance is a kind of index insurance. It avoids defects of traditional agricultural insurance,such as moral hazards,adverse selection,and high management cost. On the basis of studying agricultural product price index insurance of all areas of China,this paper analyzed characteristics of agricultural product price index insurance from object selection,product object,premium design,and policy support,and discussed feasibility of extending agricultural product price index insurance in an all-round way.

Forecasting Model Based on Information-Granulated GA-SVR and ARIMA for Producer Price Index

The accuracy of predicting the Producer Price Index(PPI)plays an indispensable role in government economic work.However,it is difficult to forecast the PPI.In our research,we first propose an unprecedented hybrid model based on fuzzy information granulation that integrates the GA-SVR and ARIMA(Autoregressive Integrated Moving Average Model)models.The fuzzy-information-granulation-based GA-SVR-ARIMA hybrid model is intended to deal with the problem of imprecision in PPI estimation.The proposed model adopts the fuzzy information-granulation algorithm to pre-classification-process monthly training samples of the PPI,and produced three different sequences of fuzzy information granules,whose Support Vector Regression(SVR)machine forecast models were separately established for their Genetic Algorithm(GA)optimization parameters.Finally,the residual errors of the GA-SVR model were rectified through ARIMA modeling,and the PPI estimate was reached.Research shows that the PPI value predicted by this hybrid model is more accurate than that predicted by other models,including ARIMA,GRNN,and GA-SVR,following several comparative experiments.Research also indicates the precision and validation of the PPI prediction of the hybrid model and demonstrates that the model has consistent ability to leverage the forecasting advantage of GA-SVR in non-linear space and of ARIMA in linear space.

Research on the Change of GDP Growth,Monetary Growth and Price Index based on VAR and IRF

In this paper,we use the macro data from the first quarter of 2001 to the first quarter of 2015,through vector autoregressive(VAR)model,Granger causality analysis,impulse response function(RFI)and variance decomposition analysis of quantitative analysis methods,to research on the relationship among China’s real growth variation of gross domestic product(GDP),Money supply growth rate and consumer price index.We find that the money supply growth has impact on China’s real growth variation of GDP in short-term,but there is no long-term significant effect.Economic growth is the main factor to promote the consumer price index growth,money growth is not the main factor driving the change in the price index.China’s currency growth is affected significantly by the change of the economic growth.

The Response of Consumer Food Price Index(CFPI)due to the Impact of Pandemic COVID-19 on Indian Agriculture Sector

India is an agricultural country and a core source of income for the world population.The Indian economy is greatly depending on agriculture that is decrease day by day due to pandemic COVID-19.India is a major exporter of many crop foods.India,Thailand,and Vietnam are the major exports of rice if these stopped exports it reduces the economy up to 15%.A related circumstance is built up with diverse yields too like wheat,sunflower whose fare has been stationary by Kazakhstan,Serbia individually.In India,the end of April is the main source of income to farmers because they sell their rabi crops(wheat,mustard,maize,lentil,chilies,gram,tomatoes)in the market drastically decreases of CFPI may lead to the distress of Indian agricultural economy.The change over time in the price of options on wheat futures reveals increased price volatility in response to growing uncertainty about the COVID-19 impacts.

The Virtual Repeat Sale Model for the House Price Index for New Building in China

By using the characteristics of the new building in China, this article constructs the virtual repeat sale method to produce virtual repeat data which is similar to the repeat sale model on the house price index. Case-Shiller procedure and OFHEO method are used to calculate the house price index for new building in China. A discussion is given and furthering models are needed to take advantage of the virtual repeat sale data.

The Empirical Analysis of the Relationship between our Country Steel Price Index and the International Iron ore Freight Rate

The use of econometric methods to analyze the relationship between our country steel price index and the international iron ore freight rate,time series stationarity test,cointegration test,Granger test of causality and model parameter estimation tools use,find that there is Granger causality between our country steel price index and the international iron ore freight rate,China' s steel price fluctuations to some extent affect the international iron ore freight.

Modeling Consumer Price Index in Zambia: A Comparative Study between Multicointegration and Arima Approach

Consumer Price Index (CPI) is an important indicator used to determine inflation. The main objective of this research was to compare the forecasting ability of two time-series models using Zambia Monthly Consumer Price Index. We used monthly CPI data which were collected from January 2003 to December 2017. The models that were compared are the Autoregressive Integrated Moving average (ARIMA) model and Multicointegration (ECM) model. Results show that the ECM was the best fit model of CPI in Zambia since it showed smallest errors measures. Lastly, a forecast was done using the ECM and results show an average growth rate for food CPI at 6.63% and an average growth rate for nonfood CPI at 7.41%. Forecasting CPI is an important factor for any economy because it is essential in economic planning for the future. Hence, identifying a more accurate forecasting model is a major contribution to the development of Zambia.

Extracting the Influential Commodities in Stochastic Model of Simple Laspeyre Price Index Numbers with AR(2) Errors

This paper, on the first hand, deals with the problem of estimation of Laspeyre price index number when the errors are assumed to be generated from AR(2) process. The general expression of hat matrix and DFBETA measure to find the influential consumer commodities in stochastic Laspeyre price model with AR(2) errors are developed on the other. The hat values show the noteworthy findings that the corresponding weights of consumer items have large influence on the parameter estimates for simple Laspeyre price index number and are not affected by the parameter of autoregressive process of order two. While, DFBETA measures are the functions of both weights and autocorrelation parameters. Lastly, an example is presented with reference to price data of Pakistan, and shows its practical importance in financial time series.

Production Chain Length and PPI-CPI Divergence:Analysis Based on the Global Input-output Price Model

Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.

Design and implementation of China Hydrogen Price Index system

Hydrogen will be an important part of China’s energy system in the future and an important carrier for energy-using terminals to realize green and low-carbon transformation.It is important to establish a nationwide hydrogen market to promote the healthy and orderly development of the hydrogen industry chain.The core is to form a complete hydrogen price mechanism and play a decisive role in the process of resource allocation by the market.In this paper,we have developed the framework of the‘China Hydrogen Price Index’system by establishing the‘Assessment+Collection’model,which covers four types of hydrogen:hydrogen,clean hydrogen,renewable hydrogen and high-purity hydrogen.The model considers the raw materials required for hydrogen production,fixed equipment,engineering construction costs and carbon prices,and conducts sensitivity analysis on the trends and influencing factors of national and regional hydrogen prices of multiple categories since 2018.The results show that,with respect to the level of hydrogen prices,fossil-energy-rich and renewable-energy-rich areas have more advantages than other regions.The price of raw materials is the main factor of the hydrogen price change,and the utilization hours of renewable energy and hydrogen production equipment have a key influence on the price of renewable hydrogen.Next,by establishing an index update mechanism,improving the standard system and building a trading platform,we can further exert the role of price signals and continue to promote the efficient and smooth expansion of the domestic hydrogen market.

Can the Shanghai LNG Price Index indicate Chinese market?An econometric investigation using price discovery theory

China became the world's second largest liquefied natural gas(LNG)importer in 2018 but has faced extremely high import costs due to a lack of bargaining power.Assessments of the Shanghai LNG Price Index,first released in 2015,are vital for improving the understanding of these cost dynamics.This paper,using the LNG price index data from the Shanghai Petroleum and Gas Exchange(SHPGX)coupled with domestic and international LNG prices from July 1,2015 to December 31,2018,estimates several econometric models to evaluate the long-term and short-term equilibriums of the Shanghai LNG Price Index,the responses to market information shocks and the leading or lagging relationships with LNG and alternative energy prices from other agencies.The results show that the LNG price index of the SHPGX has already exhibited a long-term equilibrium and short-term adjustment mechanisms to reflect the average price level and market movements,but the market information transparency and price discovery efficiency of the index are still inadequate.China's LNG market is still relatively independent of other natural gas markets,and marketization reforms are under way in China.The influence of the SHPGX LNG price index on the trading decisions of market participants is expected to improve with further development of China's LNG reforms,the formation of a natural gas entry-exit system,and the increasing liquidity of the hub.

Is pass‑through of the exchange rate to restaurant and hotel prices asymmetric in the US?Role of monetary policy uncertainty

This study examines the exchange rate pass-through to the United States(US)restaurant and hotel prices by incorporating the effect of monetary policy uncertainty over the period 2001:M12 to 2019:M01.Using the nonlinear autoregressive distributed lag(NARDL)model,empirical evidence indicates asymmetric pass-through of exchange rate and monetary policy uncertainty.Moreover,a stronger pass-through effect is observed during depreciation and a negative shock in monetary policy uncertainty,corroborating asymmetric pass-through predictions.Our results further show that a positive shock in energy prices leads to an increase in restaurant and hotel prices.Furthermore,asymmetric causality indicates that a positive shock in the exchange rate causes a positive shock to restaurant and hotel prices.We found feedback causal effects between positive and negative shocks in monetary policy uncertainty and positive and negative shocks in the exchange rate.Additionally,we detected a one-way asymmetric causality,flowing from a positive(negative)shock to a positive(negative)shock in energy prices.Therefore,these findings provide insights for policymakers to achieve low and stable prices in the US restaurant and hotel industry through sound monetary policy formulations.Highlights.The drivers of restaurant and hotel business in tourism destinations are examined.There is asymmetric pass-through of exchange rate and monetary policy uncertainty.A stronger pass-through is observed during appreciation and a negative shock to monetary policy uncertainty.There is asymmetric causality from positive shock in exchange rate to postive shock in restaurant and hotel prices.

Uniformity Analysis for Index of Retail Price

Using the Hodges Ajne testing method, the uniformity of China retail price index was tested. The result, that population is submitting to uniform distribution, was obtained. The uniformity of CRPI indicates that the general price level is stable in the Ninth Five Year Plan. Finally, the reasons causing the uniformity was analyzed.

2024年一季度中国涂料、颜料行业经济运行简析

简析了2024年第一季度我国涂料行业生产、经营和涂料、无机颜料行业进出口简况,并对丙烯酸乳液、环氧树脂等重点成膜物质市场进行了综述和预测。对2024年一季度涂料行业双指数进行了分析,并对二季度市场进行了预测。