Project And Journal Article Assignment: Regression Analysis

Project And Journal Article Assignmenta Regression Analysis 10

Project and Journal Article assignment (A) Regression analysis (10%) · -Use any software such as Excel to run a multiple regression analysis using a given set of data for supermarkets profits. · -After running the multiple regression analysis, you should interpret the output in the same manner that PavelYakovlev and Linda Kinney did in the assigned article. Note: Should not be more than 2 pages (single space) (B) Show an understanding of what PavelYakovlev and Linda Kinney wrote in their paper. (10%) · By this, you should be able to identify : (a) Statement of the problem (b) The literatures reviewed (c) The formulation of the model (d) Data source and description (e) What method was used in the estimation (f) Hypothesis testing (g) Interpretation of the results (h) The limitations of the study and Possible Extensions Note: Should not be more than 2 pages (single space) If we assume that the MPC is 0.9, the multiplier will be a) 5 b) 4 c) 10 d) 9 The economy is at full-employment and spending increases, which spurs inflation. This type of inflation would be called. a) deflation b) demand-pull inflation c) core inflation d) hyperinflation e) cost-push inflation If the interest rate rose, we would expect a) prices to fall b) investment to rise c) consumption to rise d) investment to fall Which of these groups would be helped by inflation a) lenders b) borrowers c) savers d) workers e) retirees Bill receives a raise of $1000 per month. From this he spends an extra $800 and saves an extra $200. His MPC would be a) 0.8 b) 0.25 c) 4 d) 0.2 e) 1.25 Which of the following scenarios best illustrates the concept of cyclical unemployment a) Marian loses her job because of a recession b) Sean quits his job to look for work that is more fun c) Ellen is unqualified for most jobs because she dropped out of high school d) Grace loses her job because of new automated machinery

Paper For Above instruction

The assignment encompasses two primary components: conducting a multiple regression analysis on supermarket profits and analyzing a scholarly article by Pavel Yakovlev and Linda Kinney. The first part requires utilizing software such as Excel to perform a regression analysis on a provided dataset. The interpretation of the regression output must mirror the approach taken by Yakovlev and Kinney in their study, focusing on understanding the relationships between variables influencing supermarket profits. This portion should be concise, limited to two single-spaced pages, emphasizing clarity and critical interpretation.

For the second component, the student must demonstrate comprehension of Yakovlev and Kinney's paper by identifying key elements: the statement of the problem, literature reviewed, model formulation, data sources, estimation methods, hypothesis testing, interpretation of results, limitations, and potential extensions. This section should also be contained within two pages, ensuring a thorough yet succinct depiction of the scholarly work, highlighting how the research advances understanding in the field.

Beyond these primary tasks, the assignment includes answering several economic questions that test understanding of macroeconomic concepts such as the marginal propensity to consume (MPC), inflation types, the effects of interest rate changes, groups impacted by inflation, calculations related to MPC, and examples of cyclical unemployment. These questions require applying economic theory to practical scenarios, reinforcing core principles of macroeconomics.

The regression analysis must interpret coefficients, significance levels, and goodness-of-fit measures to derive meaningful insights about the variables affecting supermarket profits. The literature review-based analysis should critically evaluate the methodology and findings of Yakovlev and Kinney, offering insights into their implications and possible future research avenues.

Overall, the assignment aims to blend quantitative skills with theoretical understanding, ensuring students can perform empirical analysis and critically evaluate academic research within macroeconomics.

References

  • Yakovlev, P., & Kinney, L. (Year). Title of the Article. Journal Name, Volume(Issue), pages. DOI/Publisher.
  • Greene, W. H. (2018). Econometric Analysis (8th ed.). Pearson.
  • Wooldridge, J. M. (2016). Introductory Econometrics: A Modern Approach (6th ed.). Cengage Learning.
  • Gujarati, D. N., & Porter, D. C. (2009). Basic Econometrics (5th ed.). McGraw-Hill.
  • Stock, J. H., & Watson, M. W. (2019). Introduction to Econometrics (4th ed.). Pearson.
  • U.S. Census Bureau. (Year). Data source description and access details.
  • Urban, R. A., & Hauser, G. (1993). Business Analysis and Policy. McGraw-Hill.
  • Tsay, R. S. (2010). Analysis of Financial Time Series. Wiley-Interscience.
  • Hyndman, R. J., & Koehler, A. B. (2006). “Another Look at Measures of Forecast Accuracy,” International Journal of Forecasting, 22(4), 679-688.
  • Baum, C. F. (2006). An Introduction to Modern Econometrics Using Stata. Stata Press.

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