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Real-Time Data at the Federal Reserve Bank of Philadelphia. 2008 World Congress on National Accounts and Economic Performance Measures for Nations Washington, DC May 13 – 17, 2008 Tom Stark Federal Reserve Bank of Philadelphia. Real Time?.

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Real time data at the federal reserve bank of philadelphia

Real-Time Data at the Federal Reserve Bank of Philadelphia

2008 World Congress on National Accounts and Economic Performance Measures for Nations

Washington, DC

May 13 – 17, 2008

Tom Stark

Federal Reserve Bank of Philadelphia


Real time
Real Time?

  • History: Observations on economic variables, measured prior to revision

    • Philadelphia Fed real-time data set

  • Forecasts: Projections based on real-time history

    • Philadelphia Fed forecast surveys


Overview of talk
Overview of Talk

  • Real-Time Data Sets at the Philadelphia FRB

    • Forecast Surveys

    • Realizations


Overview of talk1
Overview of Talk

  • Real-Time Data Sets at the Philadelphia FRB

    • Forecast Surveys

    • Realizations

  • Uses of Real-Time Data at the Philadelphia FRB

    • Analyzing revisions

    • Evaluating forecast surveys

    • Testing the forecast implications of macroeconomic theories

    • Carrying out historical policy analysis


Overview of talk2
Overview of Talk

  • Real-Time Data Sets at the Philadelphia FRB

    • Forecast Surveys

    • Realizations

  • Uses of Real-Time Data at the Philadelphia FRB

    • Analyzing revisions

    • Evaluating forecast surveys

    • Testing the forecast implications of macroeconomic theories

    • Carrying out historical policy analysis

  • Some Examples

    • Revisions to the U.S. personal saving rate

    • Forecast accuracy in the Survey of Professional Forecasters

    • Using the PIH to forecast income in real time

    • FOMC’s response to inflation expectations


Real time forecasts
Real-Time Forecasts

  • Livingston Survey

    • Semiannual: June 1946 to present

    • Focus on business indicators - Most popular: CPI

  • Survey of Professional Forecasters

    • Quarterly: 1968 Q4 to present

    • Focus on U.S. national accounts – Product side

  • Greenbook Forecasts (Federal Reserve Board)

    • Prior to each FOMC meeting, 1966 - present

    • PDF files provide wide range of variables forecast


Real time history philadelphia fed real time data set for macroeconomists
Real-Time History: Philadelphia Fed Real-Time Data Set for Macroeconomists

  • Started in early 1990s as a research project with Dean Croushore

  • Provides snapshots of the data before revision

  • Has since become an ongoing “Bank project” at the Philadelphia FRB


Real time history cont variables included at the phila frb
Real-Time History (cont.):Variables Included at the Phila. FRB

  • NIPA Income and Product Side

  • Monetary Aggregates

  • Business Indicators (IP, Capacity Utilization, Housing Starts)

  • Labor Market (Unemployment, Employment, Hours Worked)

  • Aggregate Price Indexes (GDP, CPI, PCE)


Uses of real time data at the philadelphia frb
Uses of Real-Time Data at the Philadelphia FRB

  • Analyzing Revisions

  • Evaluating Survey Forecasts

  • Testing Theories

  • Conducting Historical Policy Analysis


1 revisions u s personal saving rate
(1) Revisions:U.S. Personal Saving Rate

  • Nakamura and Stark (February 2007): Philadelphia Fed Working Paper No. 07-8

  • Key Findings on Personal Saving Rate:

    • Early estimates very unreliable

    • Large upward revisions in benchmarks


U s measured personal saving rate large upward revisions 1965 to 2005
U.S. Measured Personal Saving Rate (%)Large Upward Revisions1965 to 2005

2005 Q3 Vintage

Advance Estimates


U.S. Measured Personal Saving Rate:Distribution of RevisionsLatest Available Minus Advance Estimate1965 to 2005

Mean: 2.44

Std Dev: 1.88

MSE: 9.52


U.S. Measured Personal Saving Rate:Distribution of RevisionsLast-before-Benchmark Minus Advance Estimate1965 to 2005

Mean: 0.08

Std Dev: 1.06

MSE: 1.11


2 evaluation of survey forecasts survey of professional forecasters
(2) Evaluation of Survey Forecasts:Survey of Professional Forecasters

Two Key Issues

  • Revised or unrevised realizations

    • Does it matter?

    • If so, how much?

  • Information sets for estimating and forecasting benchmark models


Revised or Unrevised Realizations?Nowcast RMSE Q/Q Real GDP Growth (Annual Rate, PPs.)Survey of Professional Forecasters, 1985-2005


Revised or Unrevised Realizations?Four-Quarter-Ahead RMSE Q/Q Real GDP Growth (Annual Rate, PPs.)Survey of Professional Forecasters, 1985-2005


Revised or Unrevised Realizations?Nowcast RMSEQ/Q GDP Inflation (Annual Rate, PPs.)Survey of Professional Forecasters, 1985-2005


Revised or Unrevised Realizations?Four-Quarter-Ahead RMSEQ/Q GDP Inflation (Annual Rate, PPs.)Survey of Professional Forecasters, 1985-2005


Benchmark comparisons timing of information sets
Benchmark Comparisons:Timing of Information Sets

First Quarter Survey

Forecasts for Q1,…,Q4,Q1

January

February

March

NIPA Release for Q4

Questionnaire sent

R-Time Data Set for NIPA

Survey deadline

Other January data:

Retail Sales, CPI, PPI

Housing Starts

Industrial Production

January data:

Labor market

Interest rates


Benchmark comparisons ar models rmse spf ar 1985 2005 q q real gdp growth
Benchmark Comparisons: AR ModelsRMSE (SPF / AR), 1985 – 2005Q/Q Real GDP Growth


Does The Relative Value of “Nowcast Information” Decline as Data Are Revised?RMSE (SPF / AR), 1985 – 2005Q/Q Real GDP Growth


3 testing economic theories permanent income hypothesis pih
(3) Testing Economic Theories: as Data Are Revised?Permanent Income Hypothesis (PIH)

  • Nakamura and Stark (2007): Philadelphia Fed Working Paper 07-8

  • Test Ireland’s Model of Forecasting with the PIH in Real Time

  • Key Findings:

    • Model works well when estimated on revised data…

    • …Not so good in real time


The model and methodology
The Model and Methodology as Data Are Revised?

  • Estimate VAR in income growth and the saving rate

  • Impose restrictions implied by PIH

  • Run horse races between VAR-PIH and AR forecasts for income growth…

    • …Using fully revised data

    • …Using data in hand in real time


Results forecasts for income growth rmse pih ar ratio 1971 to 1981
Results: Forecasts for Income Growth as Data Are Revised?RMSE (PIH/AR) Ratio1971 to 1981


Results forecasts for income growth rmse pih ar ratio 1971 to 19811
Results: Forecasts for Income Growth as Data Are Revised?RMSE (PIH/AR) Ratio1971 to 1981


4 historical policy analysis how has the fed responded to a rise in inflation expectations
(4) Historical Policy Analysis: as Data Are Revised?How Has the Fed Responded to a Rise in Inflation Expectations?

  • Leduc, Sill, and Stark (2007): Journal of Monetary Economics

  • How has the FOMC responded to expected inflation before and after 1979?

  • Requires real-time measure of expectations for inflation: Livingston Survey

  • Findings: Strong response post-1979.


The model and methodology1
The Model and Methodology as Data Are Revised?

  • VAR in actual and expected CPI inflation, unemployment, short-term interest rate, and commodity prices

  • Real-Time Data: Expected inflation from Livingston Survey

  • Examine impulse responses to a one-time shock to expected inflation

  • Sample period cut at 1979


We examine the effect that a one percentage point shock to livingston inflation expectations
We Examine the Effect That a One Percentage Point Shock to (Livingston) Inflation Expectations….

Effect of Shock on Expectations for Inflation

Post-1979

Pre-1979


Has on inflation and the real rate
…Has on Inflation and the Real Rate (Livingston) Inflation Expectations….

Pre-1979

Post-1979

Inflation

Real Rate


Concluding remarks upcoming changes
Concluding Remarks: (Livingston) Inflation Expectations….Upcoming Changes

  • May 2, 2008: INDUSTRY dummy variable added to micro data set for SPF forecasters

    • Allows analysts to cut the data according to panelists employed in financial and nonfinancial sectors

  • Summer 2008: New data-download pages for SPF and real-time data sets

    • Easier downloads for users

  • Summer 2008: Forecast error statistics for (mostly) all variables in SPF

  • Ongoing: New variables and more frequent vintages in real-time data set [joint with Dean Croushore]

    • Monthly vintages for NIPA variables

    • Price indexes for PCE and core PCE

    • Detailed components from BEA’s personal income report


Tom stark tom stark@phil frb org

Tom Stark (Livingston) Inflation Expectations….

[email protected]


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