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Use of Chilean business surveys in conjunctural assessment and short-term forecasting Michael Pedersen Central Bank of Chile Fourth joint EC-OECD workshop on business and consumer opinion surveys BANCO CENTRAL DE CHILE 13 October 2009 The presentation 1. Short presentation of the Chilean business surveys. 2. Case studies: Information in surveys about Chilean economic activity. 1. Evaluating information in aggregated indicators. 2. Using surveys for short-term forecasting. 3. Information in cross-checking answers. 3. Final remarks. 2 The Chilean business surveys are designed in line with the recommendations in the OECD handbook Some main characteristics: Frequency: monthly. Sample: fixed panel of the largest firms, random selection of smaller ones. Total sample: 607 firms (16% of GDP). 4 sectors: mining, manufacturing, retail and construction. Presentation of results: diffusion indices calculated with simple balances. 3 The series are available from November 2003 Difussion indices 90 90 80 80 70 70 60 50 60 50 40 30 40 30 20 20 2004 2005 IMCE Source: ICARE / UAI 4 2006 ICOM 2007 ICIN 2008 ICOT 2009 ICMI Three case studies are presented to illustrate the information in the surveys Because of the very small sample, the use of surveys in the conjunctural analysis has so far mainly been on an ad-hoc basis. However, now almost six years of data are available and it is possible to analyze the statistical properties of the series – on a preliminary basis. 5 1a. Relatively high coefficients of correlation for manufacturing and retail Diffusion indices and annual growth rates Retail sector (26%) Manufacturing sector (39%) 70 15 60 60 10 55 50 10 5 50 5 45 0 40 0 40 35 -5 -10 30 -5 30 -15 2004 2005 2006 ICOM (lhs) 2007 2004 2008 2005 ICIN (lhs) Re tail se ctor (rhs) Mining (17%) 15 80 10 70 5 60 50 0 -5 40 -10 30 -15 2005 2006 ICMI (lhs) 2007 2008 Mining se ctor (rhs) Sources: ICARE / UAI, Pozo and Stanger (2009) and own calculations. 6 2007 2008 Industrial prod. (rhs) Construction (18%) 90 2004 2006 15 80 20 70 15 60 10 50 5 40 0 30 -5 20 -10 2004 2005 2006 ICOT (lhs) 2007 2008 Construction (rhs) 1b. Tests suggest that surveys of manufacturing and retail Granger cause the activity indicators Cross correlation coefficients 0,80 0,80 0,60 0,60 0,40 0,40 0,20 0,20 0,00 0,00 -0,20 -0,20 -6 -4 -2 0 2 4 6 ICOM / Re tail ICIN / Ind. prod. ICMI / Mining ICOT / Construction IMCE / GDP Sources: ICARE / UAI, Pozo and Stanger (2009) and own calculations. Note: Negative numbers on the first axis indicate that the business survey leads activity. Tests for Granger causality IMCE ICOM ICIN ICMI ICOT Activity Survey survey 0.21 activity 0.10 0.95 0.00 0.62 0.00 0.87 0.76 0.26 0.43 Source: Own calculations. Note: p-values for the null hypothesis of no Granger causality tested in bivariate VAR models with the number of lags selected according to Schwarz information criteria. 7 2. Preliminary estimations indicate that the general survey contains information which is useful for short-term forecasting Out-of-sample one-step-ahead forecasting exercise a RMSE BS-model betterb D-Mc Total Retail Manufacturing sector Mining Construction 0.76 0.69 0.62 0.80 1.03 75% 67% 67% 42% 42% 0.00 0.07 0.00 0.10 0.59 Source: Own calculations. Note: aRMSE of the business survey model divided by the RMSE of the AR model. bPercentage of the twelve observations where the business survey model predicts better than the AR model. cp-value of the Diebold and Mariano (1995) test for the hypothesis that the models have equal predictive power against the alternative that the business survey model is better. 8 3a. Why did the stock accumulation fall in the last three quarters? Hypothesis 1: Because of restrictive financial conditions, firms could not borrow money to finance production. Hypothesis 2: Because of expectations of lower sale, the optimal stock level implies a reduction. Decompose the fraction of firms which replied that stocks were higher than desired: p( I tA ) p( I tA Vt A ) p(Vt A ) p( I tA Vt N ) p(Vt N ) p ( I tA Vt B ) p (Vt B ) 9 3b. Firms considered stock levels too high because of their expectation of future demand Stock flow and cross-checking business survey answers A: Stock flow / GDP (%) 3,0 B: Actual demand (%) 40 35 2,0 30 1,0 25 0,0 20 - 1,0 15 - 2,0 10 - 3,0 5 - 4,0 0 2004 - 5,0 96 40 98 00 02 04 06 08 C: Future production (3M) (%) Low 40 35 35 30 30 25 25 20 20 15 15 10 10 5 5 0 2004 0 2004 2005 2006 Dow n 2007 Unchange d 2008 2009 Up 2005 2006 2007 Normal 2008 2009 High D: Future general situation (6M) (%) 2005 Worse 2006 2007 Same 2008 2009 Be tte r Source: Echavarría et al. (2009) Note: Figure A shows the stock flows as a percentage of GDP. B-D show the proportion of the firms that considered that their stock levels were higher than desired and also considered that: (B) actual demand was low, normal and high, respectively; (C) future production will go down, not change and go up, respectively, and (D) the future general situation of the company will be worse, the same and better, respectively. 10 Final comments The preliminary results are promising with respect to the contents in Chilean business surveys about the economic activity. Several questions remain unanswered: Are surveys affected by seasonality? Do surveys lead annual growth rates, or rather monthly? Levels or changes in surveys serve as leading indicators? Ongoing research in the Central Bank of 11 Chile aims at answering some of these questions. Use of Chilean business surveys in conjunctural assessment and short-term forecasting Michael Pedersen Central Bank of Chile Fourth joint EC-OECD workshop on business and consumer opinion surveys BANCO CENTRAL DE CHILE 13 October 2009