Summary of 岐阜聖徳学園大学 2022年度データサイエンス入門 第06回「経済学におけるDS/AI」(姜興起先生)

Main Ideas and Concepts

• Introduction to Data Science in Economics:

  The class focuses on the application of Data Science and AI in understanding economic fluctuations. Emphasis on using data to monitor economic health and trends.

• Understanding Economic Activity:

  The economy is likened to an intelligence quotient—an abstract concept that reflects the activity levels of companies and households. Economic Indicators are essential for capturing the state of economic activity.

• Two Perspectives on the Economy:
  • Objective View: Economic activity can be measured through data and indicators.
  • Subjective View: Economic perception is influenced by individual sentiments and surveys.
• Economic States:
  • Good Economic State: Characterized by increased employment, rising prices, and heightened consumer desire.
  • Bad Economic State: Marked by declining sales, reduced corporate profits, and lower individual incomes.
• Business Cycles:

  The economy experiences cyclical changes, alternating between periods of growth and recession. Understanding these cycles is critical for anticipating economic shifts.

• Gross Domestic Product (GDP):

  GDP is a key indicator of economic health, reflecting the total value of goods and services produced in a country. The importance of understanding GDP as a measure of economic activity and its limitations in real-time analysis.

• Need for Timely Economic Indicators:

  Traditional GDP calculations are often too slow for timely Economic Analysis. The necessity for alternative indicators that can provide more immediate insights into economic conditions.

• Economic Trend Indicators:
  • TI (Trend Indicator): Indicates the direction of economic fluctuations (improving or worsening).
  • CI (Composite Indicator): Measures the magnitude of change in economic conditions.
• Criteria for Selecting Economic Indicators:

  Importance of economic significance, statistical continuity, responsiveness to economic cycles, and timely publication of data.

• Methodology for Creating Economic Trend Indices:

  Detailed explanation of how to create TI and CI using various economic data. Importance of understanding the calculation processes for these indicators.

• Application of Data Science:

  The use of Data Science methodologies to enhance Economic Analysis and prediction. The proposal of a new method for analyzing economic cycles and its implications for understanding economic trends.

Methodology / Instructions

• Creating Economic Indicators:
  • Understand the economic significance of data used.
  • Ensure statistical continuity for reliable time-series data.
  • Select indicators based on their responsiveness to economic cycles.
  • Utilize data that is published early and regularly for timely analysis.
• Calculating TI and CI:
  • TI Calculation:
    • Count the number of indicators showing improvement versus those showing decline.
    • Use a simple ratio to express the proportion of indicators improving.
  • CI Calculation:
    • Involves more complex calculations, including adjustments for volume and changes over time.
    • Requires aggregation of various indicators to synthesize a comprehensive economic outlook.

Speakers / Sources Featured

• 姜興起先生 (Kang Koongi): The primary speaker and lecturer in the video, discussing the integration of Data Science and AI in Economic Analysis.

Notable Quotes

— 02:14 — « The economy is a strange disease or the situation of economic activity as perceived by households. It's the economy in the minds of those people. »

Category

Educational

Video