AI Summary
[DOCUMENT_TYPE: user_assignment]
**What This Document Is**
This document outlines the requirements for a foundational assignment in an upper-level Money and Banking course (ECON 335) at Winthrop University. It details two distinct assignment options: a term definition project and a data collection exercise. Students will select *either* to comprehensively define a key economic term *or* to compile a historical dataset relevant to monetary policy and financial markets. The assignment is designed to build both conceptual understanding and practical data handling skills.
**Why This Document Matters**
This assignment is crucial for students aiming to solidify their grasp of core concepts in money and banking. Successfully completing this work will contribute to a shared class resource – a collective glossary of terms – and provide valuable experience in sourcing, organizing, and preparing economic data for analysis. It’s particularly beneficial for students preparing for more advanced coursework or careers involving financial analysis, economic research, or policy-making. Students should review this document *before* beginning work on Assignment 1 to ensure they fully understand the expectations and scope.
**Common Limitations or Challenges**
This document specifies *what* needs to be done, but it does not provide the definitions themselves, nor does it supply the data. Students are responsible for independent research and data sourcing. It also doesn’t offer guidance on specific analytical techniques; the focus is on accurate definition and data collection, not interpretation. The document outlines formatting requirements, but doesn’t include example submissions.
**What This Document Provides**
* A clear choice between two assignment paths: term definition or data collection.
* A list of potential terms for definition, covering a range of topics within money and banking.
* A list of specific data series students can collect, focused on macroeconomic indicators and financial market variables.
* Detailed requirements regarding data frequency (quarterly), historical scope (back to 1995), and file format (Excel).
* Instructions regarding data source documentation and data type identification (growth rates, nominal values, etc.).
* Specific data collection timepoints (Jan, April, July, October).