Developing a High Quality Baseline

Salimah Samji & Mona SurWorld Bank, New DelhiJune 21, 2006

Overview

What is a baseline? Why you should care The phases of conducting a baseline

The errors to avoid in each phase How to manage the common errors Elements of a baseline survey (TOR)

What is a baseline?

Fixing the time at the base – a benchmark from which you measure progress

Snapshot of indicators at a time Instrument used to:

Test hypotheses of project (assess results)Planning (refine targeting, indicators to

monitor)

Why you should care …

To identify whether there were any benefits for the investments made Were objectives met? What factors explain the result? How can the program be improved?

Compare alternative models to get the biggest bang for your buck

To inform next generation projects Evidence-based policy making – demonstration

effect for government

The phases of conducting a baseline

Design Implementation – actual survey Data entry and analysis Report writing

Phase 1: Design Phase

P1: Check-list

Clear objectives (what is the problem?) Clear idea of how you will achieve the

objectives (causal chain or hypotheses) Clear and measurable indicators

Clear (precise and unambiguous)Relevant (to objectives)Monitorable

Example of a causal chain

Impact

Outcomes

Outputs

Activities

Inputs Facilitators, Revolving fund (credit)

Forming, federating and organizing SHGs

Number of SHGs, decreased input prices

Increased use of credit for income generation, Loan repayment rates

Higher income levels

Example: APDPIP

P1: Check-list (cont’d)

Design survey instrument – keep it simple and related to the objectives and hypotheses you want to test

Link surveys to GIS – use consistent units Select controls/counterfactuals to attribute

change (causality) Timing of baseline

Before project (what if project never materializes)? 2 years into the project (intervention has begun)? Other factors (seasonality)

P1: Check-list (cont’d)

Sampling strategy Random allows inferences about

a population Random Stratified random (include groups

which could be excluded)

Non-random – use a group smaller than the population

Introduces selection bias. Note: every stratification introduces a level of bias.

Population Size

Sample Size

10 10

50 44

100 80

500 217

1,000 278

3,000 341

50,000 381

1,00,000 385

P1: Check-list (cont’d)

Over sample for attrition Design the database system for data entry Translate the questionnaire

Back translate to verify

Provide adequate training on The objectives and importance of the study How the sections are linked and what the questions

mean

Attend the training if possible (stay involved)

P1: Check-list (cont’d)

Test the questionnaire Ask yourself, can you answer these

questions? Are they relevant to the outcomes? Will they be understood? Field test: To test both how the surveyor

administers the instrument AND how the respondent understands the question.

P1: Why it is important to field test (i)

When asking a question about the level of awareness, the surveyor used a word that could mean awareness or knowledge – the respondent understood it to mean education. :

The question was: “Ram/ Gita knows about everything that happens (vikas) in the village. For instance, they know [the name of the sarpanch, when and where the Gram Panchayat meets, nature and

type of development work in village, etc.]”

P1: Why it is important to field test (ii)

CASE STUDY: Domestic Violence Study in India

“In studying domestic violence, a question in the survey instrument asked if female respondents had ever been beaten by their husbands in the course of their marriage. Only 22 per cent of the women responded positively to this question – a domestic violence rate much lower than studies in Britain and the US had shown. In probing the issue with in-depth interviews we discovered that the women had interpreted the word ‘beating’ to mean extremely severe beating – when they had lost consciousness or were bleeding profusely and needed to be taken to the hospital. Hair pulling, ear twisting, etc, which were thought to be more everyday occurrences, did not qualify as beating. Reponses to a broader version of the abuse question, comparable to the questions asked in the US and UK surveys, elicited a 70 per cent positive response.”

Source: Vijayendra Rao (1998) – “Wife-Abuse, Its Causes and Its Impact on Intra-Household Resource Allocation in Rural Karnataka”

Phase 2: Implementation

What would you do if you …

Were a city person who didn’t speak the local language very well

Had to travel to several villages and spend hours asking people questions that have no relevance to you.

Were paid a small sum per questionnaire Not monitored by supervisors This is not your full time job

The answer is simple

Sit at home or in a bar and fill out the questionnaires!!

P2: Providing incentives and motivation

Sub-contracting surveyors from the state who speak the language

Include women surveyors Include a supervisor who conducts data

scrutiny If possible pay reasonable wages Randomly verify questionnaires to reduce

the likelihood of false responses (inform them beforehand - during the training)

Phase 3: Data Entry and Analysis

P3: Check-list

Data Entry Make the data entry system as fool proof as

possible - has unique identifiers to link both household, village and GIS data

Ensure database allows for merging of data Do not change/erase data on questionnaires Raw data should always be input as is, changes

can then be made in the database software (programatically) with documentation

P3: Check-list (cont’d)

Often data entry is contracted out. Name variables corresponding to the question and section in the

questionnaire – include a dictionary Code descriptive answers (to facilitate analysis) All fields should be filled (NA or NR) Units should be uniform by district Totals calculated by formula not from summary column

Consistency checks – check for missing entries, wrong entries, sample statistics, patterns (queries should be inbuilt)

Validity checks – similar questions in different places on the questionnaire (RCH example)

P3: Check-list (cont’d)

Data analysis Common mistakes in interpreting data

No analysis! No correlations, crosstabs, statistical significance levels or

regressions

Over generalizing the results Mis-reporting statistics Using % when the numbers are small Attributing causality when it is not demonstrated

Phase 4: Report Writing

P4: What the report should be … Simple, Clear and Relevant State limitations (attribution, causality) Major findings should be upfront Focus on quality rather than quantity Technical details in an appendix Should always

include the questionnaire in the appendix ask for electronic copy of data Request copies of filled out surveys

Essential if you change consultants at midterm or want to conduct internal analysis to compare modes of delivery (data lost example).

How to manage the common errors Phase 1: Design

Clear objectives and hypotheses – know what you want to test

Identify a person in your unit who will manage this process

Write a good TOR, remember the baseline determines the quality of your panel

You can add questions as project evolves but cannot change questionnaire – threat to internal validity

Identify consultants Procurement – focus on quality not the cheapest bid “if you

throw peanuts you’ll attract monkeys” Ideally you should have a black-list of organizations

How to manage the common errors

Phase 2: ImplementationOrganize an impact evaluation workshop if

necessaryRandomly verify questionnaires to reduce the

likelihood of false responses (no filling it in a bar)

Pay reasonable wages to surveyors (if possible)

Show the client and firm that you care

How to manage the common errors

Phase 3: Data entry and analysis Double-data entry (2 separate organizations and

verify. Payment based on quality of data entry) Select 15 questionnaires at random and check data

entry – person in your unit managing Check data quality (consistency and validity checks) Hold an IE workshop to build data analysis capacity (if

necessary)

How to manage the common errors

Phase 4: Report writingAgree on an outline beforehandDedicate a chapter on indicators you are

trackingFocus on quality not quantityThink “Big Picture”

Elements of a Baseline Survey

Terms of References 1. Background: Project objectives and components2. Survey design: Consult a sampling expert!!!3. Survey instruments4. Guidance on survey implementation5. Data processing and analysis6. Staffing7. Duration and time schedule8. Submission of reports and datasets9. Support to the firm10. Budget & Payment Schedule11. Annexes: Draft questionnaires, Results Framework

Baseline Survey Design: Typical Tasks for Consultants Recommend the methodology for sampling Calculate the optimal sample size Develop the sample frame and select the sample The final sample and details of the statistical

methodology used to select the sample need to be cleared by the project

Construct the sample weights and provide documentation on the methodology used to construct the weights

Survey Instruments: Questionnaires Design or refinement and adaptation of the data

collection instruments Specify levels of data collection Length of questionnaires Prepare all support documentation including coding

guides, interviewer and supervisor manuals and the data entry manual

Translation and back-translation Skip patterns, coding open ended questions

Guidance on Survey Implementation Implementation plan Selection and training of field workers: specify

minimum duration of training Pilot testing should be explicitly specified in ToR Responsibility for all field operations, including

logistical arrangements for data collection and obtaining household consent lies with Consultants.

Ask for field-work progress reports (bi-weekly/monthly)

Staffing

Sampling expert/statistician Technical specialists as relevant Economist Sociologist. Core survey staff: the survey manager, the

field manager, the data manager Enumerators, supervisors and data entry

staff

Baseline Report & Data

Explicitly request final electronic datasets—with complete documentation.

Agree on outline of baseline report up-front.

Managing a Baseline Survey

Consult the experts—survey specialist and sampling specialist and develop the ToR in consultation.

Selection committee should include a survey expert and social scientists in addition to technical experts.

You can never over-supervise!!! Hire third-party supervision consultant if needed.

Question the data and the findings.

Lets recap what you have learned

The devil lies in the detail Be watchful No pain, No gain