Surveying Surveys and Questioning Questions : Learning from World Bank Experience
The World Bank has increasingly focused on firm-level surveys to build the data foundation needed for accurate policy analysis in developing and transition economies. The authors take stock of some recent Bank surveys, and discuss how to improve th...
| Main Authors: | , , |
|---|---|
| Format: | Policy Research Working Paper |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2014
|
| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2000/03/437914/surveying-surveys-questioning-questions-learning-world-bank-experience http://hdl.handle.net/10986/19848 |
| id |
okr-10986-19848 |
|---|---|
| recordtype |
oai_dc |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English en_US |
| topic |
BANK LOANS BANKING SYSTEM BANKRUPTCY BIDDING BIRTH RATE CAPITAL INVESTMENTS CAPITAL THEORY CAUSATION COLLUSION COMPETITION POLICY COMPETITIVENESS CONSOLIDATION CONSUMERS CONTRACT ENFORCEMENT CONTRACTUAL ARRANGEMENTS CORPORATE FINANCE DATA ANALYSIS DEBT DOWN PAYMENTS ECONOMIC ANALYSIS ECONOMIC CONDITIONS ECONOMIC GROWTH ECONOMISTS EMPIRICAL EVIDENCE EMPLOYMENT ENDOGENOUS VARIABLES ENGINEERS ENVIRONMENTAL REGULATIONS EXCHANGE RATES EXPENDITURES FINANCIAL SECTOR FINANCIAL STRUCTURE GOVERNMENT INTERVENTION HOUSING HUMAN CAPITAL HYPOTHESES IMPORTS INCOME INDUSTRIAL ENTERPRISES INFLATION INNOVATIONS INSTRUMENTAL VARIABLES LABOR FORCE LABOR MARKETS LAWS LEARNING LIQUIDITY MACROECONOMIC ANALYSIS MACROECONOMICS MERGERS NEW ENTRANTS OWNERSHIP STRUCTURE PATENTS PENALTIES POLICY MAKERS POLITICAL WILL PRICE INCREASES PRIVATIZATION PRODUCTION COSTS PRODUCTION FUNCTION PRODUCTION FUNCTIONS PRODUCTIVE RESOURCES PRODUCTIVITY PROFITABILITY PROPERTY RIGHTS RESEARCH AGENDA SCIENTISTS SHAREHOLDERS SUBSIDIARIES SUNK COSTS SURVEYORS TANGIBLE ASSETS TAX RATES TECHNICAL ASSISTANCE TECHNOLOGICAL CHANGE TECHNOLOGICAL PROGRESS TOTAL OUTPUT TRANSACTION COSTS TRANSITION ECONOMIES UNEMPLOYMENT VALUE ADDED WAGES |
| spellingShingle |
BANK LOANS BANKING SYSTEM BANKRUPTCY BIDDING BIRTH RATE CAPITAL INVESTMENTS CAPITAL THEORY CAUSATION COLLUSION COMPETITION POLICY COMPETITIVENESS CONSOLIDATION CONSUMERS CONTRACT ENFORCEMENT CONTRACTUAL ARRANGEMENTS CORPORATE FINANCE DATA ANALYSIS DEBT DOWN PAYMENTS ECONOMIC ANALYSIS ECONOMIC CONDITIONS ECONOMIC GROWTH ECONOMISTS EMPIRICAL EVIDENCE EMPLOYMENT ENDOGENOUS VARIABLES ENGINEERS ENVIRONMENTAL REGULATIONS EXCHANGE RATES EXPENDITURES FINANCIAL SECTOR FINANCIAL STRUCTURE GOVERNMENT INTERVENTION HOUSING HUMAN CAPITAL HYPOTHESES IMPORTS INCOME INDUSTRIAL ENTERPRISES INFLATION INNOVATIONS INSTRUMENTAL VARIABLES LABOR FORCE LABOR MARKETS LAWS LEARNING LIQUIDITY MACROECONOMIC ANALYSIS MACROECONOMICS MERGERS NEW ENTRANTS OWNERSHIP STRUCTURE PATENTS PENALTIES POLICY MAKERS POLITICAL WILL PRICE INCREASES PRIVATIZATION PRODUCTION COSTS PRODUCTION FUNCTION PRODUCTION FUNCTIONS PRODUCTIVE RESOURCES PRODUCTIVITY PROFITABILITY PROPERTY RIGHTS RESEARCH AGENDA SCIENTISTS SHAREHOLDERS SUBSIDIARIES SUNK COSTS SURVEYORS TANGIBLE ASSETS TAX RATES TECHNICAL ASSISTANCE TECHNOLOGICAL CHANGE TECHNOLOGICAL PROGRESS TOTAL OUTPUT TRANSACTION COSTS TRANSITION ECONOMIES UNEMPLOYMENT VALUE ADDED WAGES Recanatini, Francesca Wallsten, Scott J. Xu, Lixin Colin Surveying Surveys and Questioning Questions : Learning from World Bank Experience |
| relation |
Policy Research Working Paper;No. 2307 |
| description |
The World Bank has increasingly focused
on firm-level surveys to build the data foundation needed
for accurate policy analysis in developing and transition
economies. The authors take stock of some recent Bank
surveys, and discuss how to improve their results. Lessons
on data issues, and hypothesis testing: 1) Use panel data,
if possible. 2) Have enough information about productivity
to estimate a production function. 3) Avoid the paradigm of
"list the severity of the obstacle/problem on a scale
of 1 to 5". Instead, ask for data on specific
dimensions of the problem that will shed light on
alternative hypothesis and policy recommendations. 4) Pick
particular disaggregated industries, and sample those
industries in each survey. 5) Identify the most important
interventions of interest, and consider how you will
empirically identify specific changes by picking instruments
useful for doing so. Lessons on questionnaire design: a)
Incorporate only one idea or dimension in each question. Do
not ask, in one question, about the "quality,
integrity, and efficiency" of services, for example. b)
Consider the costs and benefits of numeric scales compared
with adjectival scales. Scales in which each point is
labeled may be more precise than numeric scales in which
only the end points are labeled. But responses are very
sensitive to the exact adjective chosen, and it may be
impossible to translate adjectives precisely across
languages, making it impossible to compare responses across
countries. c) Recognize that the share of respondents
expressing opinions will be biased upward if the survey does
not include a middle ("indifferent" or
"don't know") category, and downward if it
does include the middle category. d) When asking
degree-of-concern and how-great-an-obstacle question,
consider first asking a filter question (such as "Do
you believe this regulation is an obstacle or not?").
If the answer is yes, then ask how severe the obstacle is.
e) Be aware of the effects of context. The act of asking
questions can affect the answers given on subsequent,
related questions. f) Think carefully about how to ask
sensitive questions. Consider using a self-administered
module for sensitive questions. alternatively, a randomized
response mechanisms may be a useful, truth-revealing mechanism. |
| format |
Publications & Research :: Policy Research Working Paper |
| author |
Recanatini, Francesca Wallsten, Scott J. Xu, Lixin Colin |
| author_facet |
Recanatini, Francesca Wallsten, Scott J. Xu, Lixin Colin |
| author_sort |
Recanatini, Francesca |
| title |
Surveying Surveys and Questioning Questions : Learning from World Bank Experience |
| title_short |
Surveying Surveys and Questioning Questions : Learning from World Bank Experience |
| title_full |
Surveying Surveys and Questioning Questions : Learning from World Bank Experience |
| title_fullStr |
Surveying Surveys and Questioning Questions : Learning from World Bank Experience |
| title_full_unstemmed |
Surveying Surveys and Questioning Questions : Learning from World Bank Experience |
| title_sort |
surveying surveys and questioning questions : learning from world bank experience |
| publisher |
World Bank, Washington, DC |
| publishDate |
2014 |
| url |
http://documents.worldbank.org/curated/en/2000/03/437914/surveying-surveys-questioning-questions-learning-world-bank-experience http://hdl.handle.net/10986/19848 |
| _version_ |
1764441670663798784 |
| spelling |
okr-10986-198482021-04-23T14:03:46Z Surveying Surveys and Questioning Questions : Learning from World Bank Experience Recanatini, Francesca Wallsten, Scott J. Xu, Lixin Colin BANK LOANS BANKING SYSTEM BANKRUPTCY BIDDING BIRTH RATE CAPITAL INVESTMENTS CAPITAL THEORY CAUSATION COLLUSION COMPETITION POLICY COMPETITIVENESS CONSOLIDATION CONSUMERS CONTRACT ENFORCEMENT CONTRACTUAL ARRANGEMENTS CORPORATE FINANCE DATA ANALYSIS DEBT DOWN PAYMENTS ECONOMIC ANALYSIS ECONOMIC CONDITIONS ECONOMIC GROWTH ECONOMISTS EMPIRICAL EVIDENCE EMPLOYMENT ENDOGENOUS VARIABLES ENGINEERS ENVIRONMENTAL REGULATIONS EXCHANGE RATES EXPENDITURES FINANCIAL SECTOR FINANCIAL STRUCTURE GOVERNMENT INTERVENTION HOUSING HUMAN CAPITAL HYPOTHESES IMPORTS INCOME INDUSTRIAL ENTERPRISES INFLATION INNOVATIONS INSTRUMENTAL VARIABLES LABOR FORCE LABOR MARKETS LAWS LEARNING LIQUIDITY MACROECONOMIC ANALYSIS MACROECONOMICS MERGERS NEW ENTRANTS OWNERSHIP STRUCTURE PATENTS PENALTIES POLICY MAKERS POLITICAL WILL PRICE INCREASES PRIVATIZATION PRODUCTION COSTS PRODUCTION FUNCTION PRODUCTION FUNCTIONS PRODUCTIVE RESOURCES PRODUCTIVITY PROFITABILITY PROPERTY RIGHTS RESEARCH AGENDA SCIENTISTS SHAREHOLDERS SUBSIDIARIES SUNK COSTS SURVEYORS TANGIBLE ASSETS TAX RATES TECHNICAL ASSISTANCE TECHNOLOGICAL CHANGE TECHNOLOGICAL PROGRESS TOTAL OUTPUT TRANSACTION COSTS TRANSITION ECONOMIES UNEMPLOYMENT VALUE ADDED WAGES The World Bank has increasingly focused on firm-level surveys to build the data foundation needed for accurate policy analysis in developing and transition economies. The authors take stock of some recent Bank surveys, and discuss how to improve their results. Lessons on data issues, and hypothesis testing: 1) Use panel data, if possible. 2) Have enough information about productivity to estimate a production function. 3) Avoid the paradigm of "list the severity of the obstacle/problem on a scale of 1 to 5". Instead, ask for data on specific dimensions of the problem that will shed light on alternative hypothesis and policy recommendations. 4) Pick particular disaggregated industries, and sample those industries in each survey. 5) Identify the most important interventions of interest, and consider how you will empirically identify specific changes by picking instruments useful for doing so. Lessons on questionnaire design: a) Incorporate only one idea or dimension in each question. Do not ask, in one question, about the "quality, integrity, and efficiency" of services, for example. b) Consider the costs and benefits of numeric scales compared with adjectival scales. Scales in which each point is labeled may be more precise than numeric scales in which only the end points are labeled. But responses are very sensitive to the exact adjective chosen, and it may be impossible to translate adjectives precisely across languages, making it impossible to compare responses across countries. c) Recognize that the share of respondents expressing opinions will be biased upward if the survey does not include a middle ("indifferent" or "don't know") category, and downward if it does include the middle category. d) When asking degree-of-concern and how-great-an-obstacle question, consider first asking a filter question (such as "Do you believe this regulation is an obstacle or not?"). If the answer is yes, then ask how severe the obstacle is. e) Be aware of the effects of context. The act of asking questions can affect the answers given on subsequent, related questions. f) Think carefully about how to ask sensitive questions. Consider using a self-administered module for sensitive questions. alternatively, a randomized response mechanisms may be a useful, truth-revealing mechanism. 2014-08-28T19:13:52Z 2014-08-28T19:13:52Z 2000-03 http://documents.worldbank.org/curated/en/2000/03/437914/surveying-surveys-questioning-questions-learning-world-bank-experience http://hdl.handle.net/10986/19848 English en_US Policy Research Working Paper;No. 2307 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank, Washington, DC Publications & Research :: Policy Research Working Paper Publications & Research |