forecasting cpi

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Forecasting CPI. Xiang Huang , Wenjie Huang, Teng Wang , Hong Wang Benjamin Wright , Naiwen Chang, Jake Stamper. Definition. The consumer price index (CPI) measures the cost of a standard basket of goods and services commonly purchased by households. - PowerPoint PPT Presentation

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Forecasting CPI

Forecasting CPIXiang Huang , Wenjie Huang, Teng Wang , Hong Wang Benjamin Wright , Naiwen Chang, Jake StamperDefinitionThe consumer price index (CPI) measures the cost of a standard basket of goods and services commonly purchased by households.

The index is published monthly by the Bureau of Labor Statistics, and is used to calculate the rate of inflation.CPI index since 1983

Trace Histogram

Time Trend Forecast

Correlogram of CPI

Evidence of an evolutionary series.

Use first-differencing to pre-whiten and obtain a stationary series.

First-Difference of CPI

Trace Histogram

Correlogram of DCPI

AddAR(1),AR(2),and MA(12)Unit Root of DCPI

Augmented Dickey-Fuller is sufficiently negative, rejecting the presence of a unit root.ARIMA MODEL OF DCPI

Tan theta=0.36/0.28=1.2857Theta=52.125 degreeCycle=360/52.125=6.9 yearsCycle Calculation:ARIMA MODEL OF DCPIActual, Fitted and Residuals Graph

Histogram of Residuals

Correlogram of Residuals

Breusch-Godfrey Serial Correlation TestCorrelogram of Square Residuals

Add ARCH(1)

Add ARCH(1) and GARCH(1) in ARIMA model

Correlogram

Drop AR(2)

Trace of the standardized residuals

Histogram of Standardized Squared ResidualsCorrelogram of Standardized Squared ResidualsExponential Smoothing Forecast

Sample: 1 340Included observations: 340Method: Single ExponentialOriginal Series: CPIForecast Series: CPISMParameters:Alpha0.9990Sum of Squared Residuals1027.477Root Mean Squared Error1.738388End of Period Levels:Mean223.442055779 Attempt to Create Distributed Lag ModelNo Granger Causality for Relevant VariablesGDPUnemployment RateCapacity UtilizationIndustrial ProductionManufacturing ProductionCommercial and Industrial LoansConsumer LoansConsumer SentimentMoney Supply (M2)Federal Funds RateWithout Granger Causality, no distributed lag model could be cratedComparison of Different ModelsMethodForecast of CPI for April 2011Time Trend Forecast221.89ARIMA Model224.19GARCH(1,1) MODEL224.14Exponential Smoothing223.44True value CPI in April 2011: 224.43True value CPI in April 2011: 224.43Actual Value of CPI in April 2011: 224.43

Forecast for May 2011CPIMonthly Inflation Rate (Annualized)Point Forecast225.053.37%95 Percent Confidence Interval

224.22 to 225.88-1.12% to 8.03%19