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About the book and authors Raymond J. Struyk is an international development economist Kristin Morse is an independent policy analyst with extensive on-the- ground experience in Eastern Europe

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Page 1: 1 presentation by dauren

About the book and authors

Raymond J. Struyk is an international development economist

Kristin Morse is an independent policy analyst with extensive on-the-ground experience in Eastern Europe 

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Chapter 4: Data Collection and Analysis

HIGHER SCHOOL OF ECONOMICS

N A T I O N A L R E S E A R C H U N I V E R S I T Y

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Ways of data collection:

- Informal conversations- Official government statistics and reports- Policy memoranda from institutes or universities- Information from the media- Other sources

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Reading Data for Meaning

The major problem with data presented in tables                              is that too many managers fail to even look at 

them 

For routine policymaking and monitoring, most data are presented and analyzed in a very straightforward way, requiring no special knowledge of statistics

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Data Collection

Important!Too much data can be distracting, or worse, can lead to the data

being completely ignored

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Data collection

1. Identify Existing Data Sources 2.Identify Additional Data Needs and Their Sources

     Potential sources for additional data include:- Program staff and staff of other programs, agencies, etc.- Program beneficiaries (when programs have specific beneficiaries)

- Universities or think tanks, which often produce reports or articles on current topics

- The general public (when programs do not have specific beneficiaries)

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Data collection

• 3. Determine Methods for Obtaining New Data

Quantitative Qualitative

Sampling

Administrative records

Surveys and Questionnaires

Focus Groups

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Data collection

Factors to consider in determining which

data collection methods to use

Cost Amount of training required

Completion time Expected response rate

(Perceived) objectivity

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Typical Problems with Data1. Missing of Incomplete Data2. Data Available Only in an Overly Aggregated Form3. Unknown, Different, or Changing Definition of Data

Elements4. Data That Are Linked Across Time and Clients

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- Outliers- Range Checks- Missing Data- Logic Checks- Confusion over Definitions

Data Checks for ReasonablenessSeveral simple tests can be performed to check the broad

accuracy of data

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