果冻影院

Content: The objective of this module is to introduce and critically assess methods and tools used by urban economic development policy makers and practitioners to evaluate policy choices, both before and after projects and policies have been approved.

To this end, the course covers a range of common tools that draw on both quantitative and qualitative research methods. Students will build skills to understand the strengths and weaknesses of different methods, as well as to engage critically with ideas that shape the use of these tools in development literature and practice. Students will also have the opportunity to critically evaluate the quality of evaluations conducted and suggest improvements to the evaluation design, through the use of case studies.

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As such, the course includes sessions that introduce principles of quantitative data analysis 鈥� basic statistics, fundamentals of survey design, and regression analysis 鈥� needed to evaluate the quality of real-world impact evaluation case studies.

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Teaching delivery: This module is taught through 9 weekly lectures supported by readings and up to one-hour of asynchronous activities (including but not limited to short pre-recorded lectures). Indicative topics based on module content in 2023/24 (subject to possible changes) are:

Unit 1

Introduction 鈥� why evaluate, and how?

Unit 2

Introduction to qualitative data and analysis

Unit 3

Introduction to quantitative data analysis (A)

Unit 4

Introduction to quantitative data analysis (B)

Unit 5

Principles for evaluation of development projects

Unit 6

Evaluations tools to support policy choice: Cost-Benefit Analysis Cost-Benefit Analysis

Unit 7

Ex post evaluation (A)

Unit 8

Ex post evaluation (B)

Unit 9

Applying tools for the evaluation of policy

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Module objectives: students will be confident in understanding the fundamentals of ex-ante and ex-post policy evaluation tools, and the quantitative and qualitative methods that underpin both.

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More specifically, students will understand:
鈥� The rationale for policy evaluation.
鈥� Trends in policy evaluation.
鈥� Philosophical challenges of evaluation.
鈥� Pragmatic challenges of evaluation.
鈥� Available policy evaluation tools and their appropriateness in different contexts.
鈥� Principles of sound quantitative evaluation tools (Sampling, inference, hypothesis
testing and spatial analysis).

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Recommended readings: The course draws on a wide range of readings. Some examples are:

• Parkhurst, J. 2017. The Politics of Evidence. London: Routledge
• Bryman, Alan. Social Research Methods. 4th ed. Oxford: Oxford University Press, 2012. Print. Chapter 17 鈥淭he nature of qualitative research鈥�, pp. 380-414.
• Urdan, T. C. 2010. Statistics in Plain English, 3rd ed. New York-Hove, Routledge.
• E. Duflo, R. Glennerster, and M. Kremer. "Using Randomization in Development Economics Research: A Toolkit," in T. Schultz and J. Strauss (eds.), Handbook of Development Economics Vol 4. Elsevier: North Holland, 2007, pp3896-62.

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Additional costs: none.

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