Nathan Grawe

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Carleton College

Materials Contributed through SERC-hosted Projects

Project Leader on this Project

Carleton's Quantitative Inquiry, Reasoning, and Knowledge (QuIRK) Initiative part of QuIRK
QuIRK's goal is to better prepare students to evaluate and use quantitative evidence. The focus of the project is on how quantitative reasoning (QR) is used in the development, evaluation, and presentation of principled argument.

Activities (3)

Empirical Economics Research Proposal part of Teaching Resources:Quantitative Writing:Examples
Most of the traditional undergraduate curriculum engages students as consumers of empirical research. But in the senior year, many programs invite students to become producers of novel work. Many students find this transition difficult because the skill set required to be a critical reader are insufficient for being an effective researcher. In particular, as researchers students must learn how to generate interesting questions with clear connections to theory; where to find relevant data to answer the posed question; how to shrewdly revise the research question in light of data availability; and how to situate the original work within an existing literature. This assignment gives sophomores and juniors a chance to practice these skills in the context of a 5-page research proposal.

Data Rich Economic Policy Brief part of National Numeracy Network:Teaching Resources:Quantitative Writing:Examples
The economic models of competitive, monopolistic, monopsonistic, and oligopolistic markets are powerful tools. But they are of little use if students cannot apply them in context. This assignment asks students to do just that-apply the economic models to a policy debate, preparing a brief for a decision maker. But economic theory in the absence of contextualizing data lacks influence. How many people may be impacted by the proposed policy? Are the changes in policy large or small? Is there a pressing need addressed by the policy? How do we know? What are the opportunity costs (ie forgone policy possibilities)? This assignment exposes students to useful data sources for providing context to their arguments.

Exploring Economic Inequality with Data part of Teaching Resources:Quantitative Writing:Examples
This set of assignments exposes students to data pertaining to economic inequality in international and historical context. The first assignment asks students to use Lorenz Curves and Gini Coefficients to summarize inequality in income and taxes reported by the IRS. The second sends them to the United Nations Human Development Indicators page to find cross-country data on Gini Coefficients and some other development indicator which they hypothesize to be correlated with inequality. In the third assignment, students estimate wealth inequality from 1774 probate records and compare the result with estimates of 20th-century wealth inequality. These early assignments serve as "scaffolding" for the ultimate assignment-a thesis-driven argument supported by data drawn from one or more of the sources used here.


Measured Thinking: Reasoning with Numbers about World Events, Health, Science, and Social Issues part of QuIRK:Courses
The National Council on Education and the Disciplines (2001) warns that "The world of the twenty-first century is a world awash in numbers.... Unfortunately, despite years of study and life experience in an environment immersed in data, many educated adults remain functionally innumerate." What does it mean to be literate in a world rich with numbers? How can we learn to think with and about numbers to inform decisions? How can we marshal the power of quantitative rhetoric in argument? This course aims to condition students to approach everyday problems with Neil Lutsky's 10 Foundational Quantitative Reasoning Questions (Microsoft Word 43kB Mar26 08) in mind: What do the numbers show? How representative is that? Compared to what? Is the outcome statistically significant? What's the effect size? Are the results those of a single study or of a literature? What's the research design (correlational or experimental)? How was the variable operationalized? Who's in the measurement sample? Controlling for what?

Other Contribution

Nathan Grawe part of Starting Point: Teaching and Learning Economics:About this Project:Project Participants
Associate Professor of Economics and Director of QuIRK Initiative One North College Street Northfield, MN 55057 Phone:507-222-5239 Background Information Nathan D. Grawe is a labor economist ...

Events and Communities

Writing with Numbers Workshop Participants

NSF Projects Supporting QL Education Participants

Developing Modules for Teaching Economics Participants

Spatial Analysis and Modeling Workshop 2007 Participants

Assessing Geoscience Programs: Theory and Practice Participants