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 modelsEarly estimate of data released with delay

Coincident indicatorsNBER and Factor models

NowcastingHelp 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 SIDEDEMAND 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 dataLabour market

Total

800 variables

25%

150 series 40 series

160 series130 series

40 series200 series

80 series

Forward-looking and “animal spirit” information

Leading IndicatorsAnticipate the evolution of the

cycle

Events which are difficultto quantify (tax changes)

Expectations with self-fulfilling properties

Survey data Forecasting power

Theoretical and Empirical ModelsInterpretations 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)