1 Challenges for estimating and forecasting macroeconomic trends during financial crises: implications for counter-cyclical policies Pingfan Hong Pingfan Hong Chief for Global Economic Monitoring UN/DESA International Seminar at Ottawa, Canada May 2009 Views expressed here are solely those of the speaker and they do not necessarily represent those of the United Nations

2 Outline Introduction Introduction Forecasting performance of UN/LINK global modeling system Forecasting performance of UN/LINK global modeling system High Frequency Modeling for Rolling estimation and forecast High Frequency Modeling for Rolling estimation and forecast “turning point”: Over-year-ago (oya) Quarterly GDP growth versus Seasonally Adjusted Annual Rate (SAAR) of Quarterly GDP growth “turning point”: Over-year-ago (oya) Quarterly GDP growth versus Seasonally Adjusted Annual Rate (SAAR) of Quarterly GDP growth The importance of correctly estimating potential output The importance of correctly estimating potential output

3 Introduction Estimating versus forecasting Estimating versus forecastingEstimating:Forecasting: Importance of estimating and forecasting for counter- cyclical macroeconomic policy: timeliness, consistent, accuracy, “turning point”, and correct estimate of the potential gap Importance of estimating and forecasting for counter- cyclical macroeconomic policy: timeliness, consistent, accuracy, “turning point”, and correct estimate of the potential gap

4 Forecasting performance of UN/LINK global modeling (1)

5 Forecasting performance of UN/LINK global modeling (2)

6 Forecasting performance of UN/LINK global modeling (3)

7 Forecasting performance of UN/LINK global modeling (4) world developed economies developing countries Mean Median Standard Deviation Fraction of positive errors Serial correlation Source: DESA

8 High Frequency Modeling for rolling estimating quarterly GDP Collecting weekly data stream Collecting weekly data stream Principle Component Principle Component ARIMA ARIMA Weekly rolling estimate and forecast of quarterly GDP Weekly rolling estimate and forecast of quarterly GDP Sources for slides 8-12: L.R. Klein and W. Mak, University of Pennsylvania Current Quarter Model of the United States Economy Sources for slides 8-12: L.R. Klein and W. Mak, University of Pennsylvania Current Quarter Model of the United States Economy Y. Inada, Konan University Current Quarter Model Forecast For the Japanese Economy Y. Inada, Konan University Current Quarter Model Forecast For the Japanese Economy

9 Example: US weekly data stream Date Economic Indicator for Latest and Prior Month Apr 01 Construction Spending February -0.9% -3.5% Apr 01 Auto Sales March 9.9 Million 9.1 Million Apr 02 Manuf Ships, Inv, & Orders February -0.1%, -1.2%, 1.8% -2.6%, - 1.1%, -3.5% Apr 03 Nonfarm Payroll Employment March -663, ,000 Apr 07 Consumer Credit Outstanding February -$7.5 billion $8.1 billion Apr 09 Export/Import Price Index March -0.6%, 0.5% -0.3%, -0.1% Apr 09 Trade Balance February -$26.0 billion -$36.2 billion Apr 15 Producer Price Index, Total & Core March -1.2%, 0.0% 0.1%, 0.2% Apr 14 Retail Sales, Total & Ex-Auto March -1.1%, 0.9% 0.3%, 1.0% Apr 15 Industrial Production March -1.5% -1.5% Apr 14 Business Inventories February -1.3% -1.3% Apr 15 Consumer Price Index, Total & Core March -0.1%, 0.2% 0.4%, 0.2% Apr 16 Housing Starts February 510, ,000

10 Example: indicators used in US model for estimating quarterly GDP Industrial Production Index Manufacturers’ orders, deflated by producer price index Manufacturers’ shipments, deflated by producer price index Manufacturers’ unfilled orders, deflated by producer price index Yield spread between 6-month commercial paper and 6-month treasury bills Real interest rate (6-month commercial paper yield adjusted by consumer price index) Real M1, adjusted by consumer price index Real retail sales, adjusted by consumer price index Real personal income, adjusted by consumer price index Real 10-year treasury yield Yield spread between 10- and 1-year treasury bills Nonfarm payrolls Average weekly hours, production workers: total private Trade-weighted value of the US dollar, nominal broad dollar index

11 Example: Equations for GDP and PGDP in US model Dlog (QGDP) = 0684 – Dlog C Dlog C Dlog C6 – Dlog C AR(1) – MA(1) Dlog (QPGDP) = – Dlog C Dlog C Dlog C3 – Dlog C Dlog C5 – Dlog C MA(4)

12 Example: Japan H-F model forecast versus consensus forecast Source: Y. Inada

13 Convergence in the rolling forecast of the US H-F model M1M2M3M4 Mean error RMSE

14 Convergence in the rolling forecast of the Japan H-F model M1M2M3M4 Mean error RMSE

15 “turning point”: oya versus saar Example of China’s GDP Sources: China NBS, JPM Sources: China NBS, JPM

16 Importance of correct estimate of potential output for counter cyclical macroeconomic policy Taylor rule: Taylor rule: Hodrick-Prescott filter for estimating potential GDP growth : Hodrick-Prescott filter for estimating potential GDP growth : Production function for estimating potential GDP growth: Production function for estimating potential GDP growth:

17 Estimate of output Gap for the US economy by H-P filter

18 Estimate output Gap for the US economy by production function Source: Business Week Source: Business Week

Are these Output GAPs corrected estimated? Output gap % of GDP Record levels of spare capacity Source: World Bank.

20 Concluding remarks It’s a big challenge to make a timely and consistent estimate and forecast for economic trends during financial crisis It’s a big challenge to make a timely and consistent estimate and forecast for economic trends during financial crisis But they are crucial for macroeconomic policies But they are crucial for macroeconomic policies We can make improvement We can make improvement