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Aberystwyth University Forecasting Models for The Rate of Inflation Analysis
Experiential Learning - Forecasting models for the rate of inflation Data The variable PCEP is the price index for per ...
Aberystwyth University Forecasting Models for The Rate of Inflation Analysis
Experiential Learning - Forecasting models for the rate of inflation Data The variable PCEP is the price index for personal consumption expenditures from the U.S. National Income and Product Accounts (NIPA). In this hands-on exercise you will construct forecasting models for the rate of inflation, based on PCEP. For this analysis, use the sample period 1963:Q1–2012:Q4 (where data before 1963 may be used, as necessary, as initial values for lags in regressions). Use the QLR test with 15% trimming to test the stability of the coefficients in the AR(2) model for “the change in inflation” . Is the AR(2) model stable? Explain. Compute the (annualized) inflation rate,Plot the value of Infl from 1963:Q1 through 2012:Q4. Based on the plot, do you think that Infl has a stochastic trend? Explain. Double click in the table below to access to the excel table. Yes, It’s going upward before 1980 and going down afterwards. Its randomly determined. Compute the first four autocorrelations of Plot the value of Infl from 1963:Q1 through 2012:Q4. The plot should look “choppy” or “jagged.”Explain why this behavior is consistent with the first autocorrelation that you computed in part (i) for . Infl 0.823-0.2860.748-0.4420.7190.0920.661-0.00 Compute Run an OLS regression of on . Does knowing the change in inflation this quarter help predict the change in inflation next quarter? Explain.Estimate an AR(2) model for Infl. Is the AR(2) model better than an AR(1) model? Explain.Estimate an AR(p) model for . What lag length is chosen by BIC? What lag length is chosen by AIC?Use the AR(2) model to predict “the change in inflation from 2012:Q4 to 2013:Q1”-that is, predict the value of Use the AR(2) model to predict “the level of the inflation rate” in 2013:Q1—that is, . Use the ADF test for the regression in Equation (14.31) with two lags of to test for a stochastic trend in .Is the ADF test based on Equation (14.31) preferred to the test based on Equation (14.32) for testing for stochastic trend in ? Explain.In (i) you used two lags of . Should you use more lags? Fewer lags? Explain.Based on the test you carried out in (i), does the AR model for contain a unit root? Explain carefully. (Hint: Does the failure to reject a null hypothesis mean that the null hypothesis is true?) Using the AR(2) model for with a sample period that begins in 1963:Q1, compute pseudo out-of-sample forecasts for the change in inflation beginning in 2003:Q1 and going through 2012:Q4. That is, compute:Are the pseudo out-of-sample forecasts biased?That is, do the forecast errors have a nonzero mean?How large is the RMSFE of the pseudo out-of-sample forecasts? Is this consistent with the AR(2) model for estimated over the 1963:Q1–2002:Q4 sample period?There is a large outlier in 2008:Q4. Why did inflation fall so much in 2008:Q4? (Hint: Collect some data on oil prices. What happened to oil prices during 2008?)
Discussion Response U9R28070DO
Read instructions in the attached word document, must follow the directions given, written at the level of a P ...
Discussion Response U9R28070DO
Read instructions in the attached word document, must follow the directions given, written at the level of a PHD response. please provide the paper in the requested time frame.
Calculating power, statistics assignment help
Using the Week 1 Dataset (SPSS document) you used for the Week 1 Assignment, complete the following:Calculate the minimum ...
Calculating power, statistics assignment help
Using the Week 1 Dataset (SPSS document) you used for the Week 1 Assignment, complete the following:Calculate the minimum sample size you will need (using manual calculations) to conduct a t test to determine if the difference in age in people with and without hypertension is significant. Use the standard deviation for age calculated in week 1. Assume a 2-tailed test with alpha = .05 and Power = 80% and that the difference you expect to observe between the 2 groups is 5 years.Using two different effect sizes in addition to the one used in part 1, perform three power analyses of the sample size computed in step 1 using G*Power. (Assume a 2-tailed independent sample t test with alpha set at .05) Perform a power analysis using G*Power using the actual sample size presented in the dataset for week 1 (180) and an effect size of .30. What does this mean in terms of the study and the probability of experiencing a type 2 error?ResourcesDaniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley.Chapter 6, “Estimation” ( pp. 161 –213)Chapter 7, “Hypothesis Testing” ( pp. 214 –303)http://www.gpower.hhu.de/
Simple/Multiple Regression Questions with R code
I have couple of questions that needs to be answered. R code will be provided, but you might need to write couple more lin ...
Simple/Multiple Regression Questions with R code
I have couple of questions that needs to be answered. R code will be provided, but you might need to write couple more lines to get the needed answer. Very simple.Attached is the questions. will need in a day.
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A computer scanner can read a bar code on a package correctly 97% of the time. One company monitors the accuracy of the sc ...
Sampling Distribution
A computer scanner can read a bar code on a package correctly 97% of the time. One company monitors the accuracy of the scanner by randomly sampling ...
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Aberystwyth University Forecasting Models for The Rate of Inflation Analysis
Experiential Learning - Forecasting models for the rate of inflation Data The variable PCEP is the price index for per ...
Aberystwyth University Forecasting Models for The Rate of Inflation Analysis
Experiential Learning - Forecasting models for the rate of inflation Data The variable PCEP is the price index for personal consumption expenditures from the U.S. National Income and Product Accounts (NIPA). In this hands-on exercise you will construct forecasting models for the rate of inflation, based on PCEP. For this analysis, use the sample period 1963:Q1–2012:Q4 (where data before 1963 may be used, as necessary, as initial values for lags in regressions). Use the QLR test with 15% trimming to test the stability of the coefficients in the AR(2) model for “the change in inflation” . Is the AR(2) model stable? Explain. Compute the (annualized) inflation rate,Plot the value of Infl from 1963:Q1 through 2012:Q4. Based on the plot, do you think that Infl has a stochastic trend? Explain. Double click in the table below to access to the excel table. Yes, It’s going upward before 1980 and going down afterwards. Its randomly determined. Compute the first four autocorrelations of Plot the value of Infl from 1963:Q1 through 2012:Q4. The plot should look “choppy” or “jagged.”Explain why this behavior is consistent with the first autocorrelation that you computed in part (i) for . Infl 0.823-0.2860.748-0.4420.7190.0920.661-0.00 Compute Run an OLS regression of on . Does knowing the change in inflation this quarter help predict the change in inflation next quarter? Explain.Estimate an AR(2) model for Infl. Is the AR(2) model better than an AR(1) model? Explain.Estimate an AR(p) model for . What lag length is chosen by BIC? What lag length is chosen by AIC?Use the AR(2) model to predict “the change in inflation from 2012:Q4 to 2013:Q1”-that is, predict the value of Use the AR(2) model to predict “the level of the inflation rate” in 2013:Q1—that is, . Use the ADF test for the regression in Equation (14.31) with two lags of to test for a stochastic trend in .Is the ADF test based on Equation (14.31) preferred to the test based on Equation (14.32) for testing for stochastic trend in ? Explain.In (i) you used two lags of . Should you use more lags? Fewer lags? Explain.Based on the test you carried out in (i), does the AR model for contain a unit root? Explain carefully. (Hint: Does the failure to reject a null hypothesis mean that the null hypothesis is true?) Using the AR(2) model for with a sample period that begins in 1963:Q1, compute pseudo out-of-sample forecasts for the change in inflation beginning in 2003:Q1 and going through 2012:Q4. That is, compute:Are the pseudo out-of-sample forecasts biased?That is, do the forecast errors have a nonzero mean?How large is the RMSFE of the pseudo out-of-sample forecasts? Is this consistent with the AR(2) model for estimated over the 1963:Q1–2002:Q4 sample period?There is a large outlier in 2008:Q4. Why did inflation fall so much in 2008:Q4? (Hint: Collect some data on oil prices. What happened to oil prices during 2008?)
Discussion Response U9R28070DO
Read instructions in the attached word document, must follow the directions given, written at the level of a P ...
Discussion Response U9R28070DO
Read instructions in the attached word document, must follow the directions given, written at the level of a PHD response. please provide the paper in the requested time frame.
Calculating power, statistics assignment help
Using the Week 1 Dataset (SPSS document) you used for the Week 1 Assignment, complete the following:Calculate the minimum ...
Calculating power, statistics assignment help
Using the Week 1 Dataset (SPSS document) you used for the Week 1 Assignment, complete the following:Calculate the minimum sample size you will need (using manual calculations) to conduct a t test to determine if the difference in age in people with and without hypertension is significant. Use the standard deviation for age calculated in week 1. Assume a 2-tailed test with alpha = .05 and Power = 80% and that the difference you expect to observe between the 2 groups is 5 years.Using two different effect sizes in addition to the one used in part 1, perform three power analyses of the sample size computed in step 1 using G*Power. (Assume a 2-tailed independent sample t test with alpha set at .05) Perform a power analysis using G*Power using the actual sample size presented in the dataset for week 1 (180) and an effect size of .30. What does this mean in terms of the study and the probability of experiencing a type 2 error?ResourcesDaniel, WW & Cross, CL. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. Hoboken, NJ: Wiley.Chapter 6, “Estimation” ( pp. 161 –213)Chapter 7, “Hypothesis Testing” ( pp. 214 –303)http://www.gpower.hhu.de/
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I have couple of questions that needs to be answered. R code will be provided, but you might need to write couple more lines to get the needed answer. Very simple.Attached is the questions. will need in a day.
4 pages
Sampling Distribution
A computer scanner can read a bar code on a package correctly 97% of the time. One company monitors the accuracy of the sc ...
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