USES OF BUSINESS AND CONSUMER OPINION SURVEY DATA, IMPLICATIONS FOR DATA PRODUCERS Giuseppe Parigi Bank of Italy, Economic Research Department

The art and science of short-term analysis of high frequency economic data is extremely important to economic policy decision makers, such as central bankers. “Good diagnosis helps in making predictions” Katona (1957) Nowadays there is an increasing demand of high quality survey data Among short-term indicators, survey data play a prominent role

 Information on current developments  Forward-looking information  “Animal spirits” information SURVEY DATA might be represented as containing three types of information (see Fuhrer, 1988):

Information on current developments Survey data are available soon after the end of the reference period (generally, the month) and are not revised Katona (1957): “Expectations – intentions as well as other notions about the future – are current data which help to understand what is going on at the time when expectations are held.” TIMELINESS Bridge models Early estimate of data released with delay Coincident indicators NBER and Factor models Nowcasting Help establish initial conditions

Publication of quarterly national accounts within 70 days after the end of reference period Flash estimates in 45 days National account dataHigh frequency data Survey data and other short term (composite) indicators BRIDGE MODELS Need timelier information about National accounts Bridge Models

Forecasts Private consumption Collective consumption Gross fixed capital formation Imports of goods and services GDP= CON + COC + INV + EXP - IMP + VSP GDP Changes in stocks ________________________________________________________________ (GDP+Imports) SUPPLY SIDE DEMAND SIDE Exports of goods and services Business surveys (expected demand), construction comp. Retail sales, CSI, UR Univariate model Trade variables, real exch. rates, IP, Surveys data IP, Business surveys GDP, Surveys data Bridge Models: matching variables and indicators

Coincident indicator – Eurocoin Industrial Production Prices Trade variables Money Miscellanea Survey data Labour market Total 800 variables 25% 150 series 40 series 160 series 130 series 40 series 200 series 80 series

Forward-looking and “animal spirit” information Leading Indicators Anticipate the evolution of the cycle Events which are difficult to quantify (tax changes) Expectations with self-fulfilling properties Survey data Forecasting power Theoretical and Empirical Models Interpretations of survey data: what is this thing called confidence? The problem of sometime too vague verbal questions Turning points detection Estimates of the probability of being in a recession/expansion

 SD as an alias of macroeconomic variables?  SD as a proxy of non-linearities (shocks)?  SD as a proxy of unobserved variables? … but their informative content is still a mystery Survey data and Economic analysis Although some consensus emerged in the literature that SD could play a role, this appears to be ad hoc. A convincing representation of SD is needed…

Survey data and Economic analysis Economists attempt to infer expectations by combining data on realized experience (choice data) with assumptions about the process of expectation formation. EXPECTATIONS Scepticism of economists to the use of survey data: one should believe only what people do and not what people say. Revealed preference analysis

But lack of empirical evidence on the validity of the expectations assumptions has led to a crisis of credibility. Survey data and Economic analysis “The data I have in mind are self-reports of expectations elicited in the form called for by modern economic theory; that is subjective probabilities” (Mansky, 2004) Survey data is a possible solution… The prevailing practice has been to assume that agents have expectations that are objectively correct (i.e. rational).

Survey data Probabilistic questions  Juster (1966) showed that elicited purchase probabilities are better predictors of subsequent behaviour  Vague concepts like “future economic conditions” may be avoided with questions about personal facts  Harmonization of survey across countries is more likely to be complete when based on numeric response scales  Numeric probability scales allow the comparability of responses among different people, across situations and over time

 The Health and Retirement Study in the USA (subj. prob. of living 75/85, job loss etc.)  The Bank of Italy Survey on Household Income and Wealth and The Dutch VSB-Panel Survey (subj. prob. of one year-ahead growth rates in income)  The Bank of Italy Survey on Business Investment (one of the few examples of probabilistic questions to firms)  The Michigan Survey of Consumers Probabilistic questions: Examples Survey data

Survey data: Further improvements Survey should follow the evolution of people behaviour  Developments of financial markets  Aging populations  Reforms of the welfare … Imply new forms of uncertainty

Survey data : Further improvements Survey data should be released in a more detailed way…  on a geographical, sectoral, dimensional basis (but also new classifications as technologically advanced v. traditional sectors)  by income, age, employment classes (better match with macroeconomic variables)