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IGNOU MECE-01
- Econometric Methods,
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(July 2023 - January 2024)

MECE-01 Assignment

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IGNOU MECE-01 July 2023 - January 2024 - Solved Assignment

Are you looking to download a PDF soft copy of the Solved Assignment MECE-01 - Econometric Methods? Then GullyBaba is the right place for you. We have the Assignment available in English and Hindi language.

This particular Assignment references the syllabus chosen for the subject of Economics, for the July 2023 - January 2024 session. The code for the assignment is MECE-01 and it is often used by students who are enrolled in the MA Degree.

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IGNOU MECE-01 (July 2023 - January 2024) Assignment Questions

Section A

Answer the following questions in about 700 words each. The word limits do not apply in case of numerical questions.

1. Consider the following data:

(a) Estimate the regression model: ЁЭСМi = ╬▒ + ╬▓Xi + ЁЭСвi, where u a stochastic error term with classical assumptions.
(b) Find out the percentage variation in Y that is explained by X.

2. Explain why an error term is added to the regression model. What assumptions are made about the error term? What are the implications of such assumptions? What will happen to the estimators of the parameters of the regression model, if these assumptions are violated?

Section B

Answer the following questions in about 400 words each.

3. What is meant by autocorrelation? Explain one of the remedial measures for the problem of heteroscedasticity.

4. What is meant by identification problem in a simultaneous equation system? How do you decide whether an equation is identified?

5. What is meant by dummy variable model? Illustrate how dummy variable is used in logit model. How do you interpret the parameters of logit model?

6. Describe how a distributed lag model is specified and estimated.

7. Write short notes on the following:

(a) Best Linear Unbiased Estimator
(b) Reduced form of a Simultaneous Equation System

IGNOU MECE-01 (July 2022 - January 2023) Assignment Questions

SECTION A

Answer the following questions in about 700 words each. The word limits do not apply in case of numerical questions.

1. What do you understand by autocorrelation? What are the consequences of autocorrelation? How do you detect autocorrelation in a data set? Explain the steps you would follow to remove the problem of autocorrelation.

2. Consider the multiple regression models in its standard matrix form. Show that OLS estimators are Best Linear Unbiased Estimators (BLUE).

SECTION B

Answer the following questions in about 400 words each. Each question carries 12 marks.

3. What is meant by heteroscedasticity? Explain one of the remedial measures for the problem of heteroscedasticity.

4. What is meant by identification problem in a simultaneous equation system? How to decide whether an equation is identified?

5. What is meant by indirect least squares (ILS) method? Explain how the following model can be estimated using this method?

where Q = quantity, P = Price, and X = income.

6. Explain the steps followed in estimation of parameters through the method of Generalised least squares (GLS).

7. Explain the concept of multicollinearity. What are its consequences on estimates? What remedial measures would you suggest for problem of multicollinearity?

IGNOU MECE-01 (July 2023 - January 2024) Assignment Questions

рднрд╛рдЧ рдХ

1. рдирд┐рдореНрдирд▓рд┐рдЦрд┐рдд рдЖрдВрдХрдбрд╝реЛрдВ рдкрд░ рд╡рд┐рдЪрд╛рд░ рдХреАрдЬрд┐рдП:

рдЕ) рдкреНрд░рддреАрдкрдЧрдорди рдкреНрд░рддрд┐рдорд╛рди Yi = ╬▒i + ╬▓Xi + ui рдХрд╛ рдЕрдиреБрдорд╛рди рд▓рдЧрд╛рдПрдВ, рдЬрд╣рд╛рдВ u рд╢рд╛рд╕реНрддреНрд░реАрдп рдорд╛рдиреНрдпрддрд╛рдУрдВ рдкрд░ рдЖрдзрд╛рд░рд┐рдд рдПрдХ рдпрд╛рджреГрдЪреНрдЫрд┐рдХ (рдкреНрд░рд╕рдВрднрд╛рд╡реНрдп) рддреНрд░реБрдЯрд┐ рдкрдж рд╣реИ ред
рдм) Y рдореЗрдВ рдкреНрд░рддрд┐рд╢рдд рдкреНрд░рд╕рд░рдг рдЬреНрдЮрд╛рдд рдХрд░реЗрдВ рдЬрд┐рд╕рдХреА рд╡реНрдпрд╛рдЦреНрдпрд╛ X рджреНрд╡рд╛рд░рд╛ рдХреА рдЧрдпреА рд╣реИред

2. рд╕рдордЭрд╛рдЗрдпреЗ рдХрд┐ рдкреНрд░рддреАрдкрдЧрдорди рдкреНрд░рддрд┐рдорд╛рди рдореЗрдВ рдПрдХ рддреНрд░реБрдЯрд┐ рдкрдж рдХреНрдпреЛрдВ рдЬреЛрдбрд╝рд╛ рдЬрд╛рддрд╛ рд╣реИ ? рддреНрд░реБрдЯрд┐ рдкрдж рдХреЗ рд▓рд┐рдП рдХреНрдпрд╛ рдорд╛рдиреНрдпрддрд╛рдПрдВ рдмрдирд╛рдИ рдЧрдИ рд╣реИрдВ? рдРрд╕реА рдорд╛рдиреНрдпрд╛рддрд╛рдУрдВ рдХреЗ рдирд┐рд╣рд┐рддрд╛рд░реНрде рд╣реИрдВ? рдпрджрд┐ рдЗрди рдорд╛рдиреНрдпрддрд╛рдУрдВ рдХрд╛ рдЙрд▓реНрд▓рдВрдШрди рдХрд┐рдпрд╛ рдЬрд╛рддрд╛ рд╣реИ, рдкреНрд░рддреАрдкрдЧрдорди рдкреНрд░рддрд┐рдорд╛рди рдХреЗ рдкреНрд░рд╛рдЪрд▓реЛрдВ рдХреЗ рдЖрдХрд▓рдХреЛрдВ рдХрд╛ рдХреНрдпрд╛ рд╣реЛрдЧрд╛?

рднрд╛рдЧ рдЦ

3. рд╕реНрд╡рд╕рд╣рд╕рдВрдмрдВрдз рдХрд╛ рдХреНрдпрд╛ рдЕрд░реНрде рд╣реИ? рд╡рд┐рд╖рдорд╡рд┐рд╕рд╛рд░рд┐рддрд╛ рдХреА рд╕рдорд╕реНрдпрд╛ рдХреЗ рдЙрдкрдЪрд╛рд░рд╛рддреНрдордХ рдЙрдкрд╛рдпреЛрдВ рдореЗрдВ рд╕реЗ рдПрдХ рдХреА рд╡реНрдпрд╛рдЦреНрдпрд╛ рдХреАрдЬрд┐рдП ред

4. рдпреБрдЧрдкрдд рд╕рдореАрдХрд░рдг рдкреНрд░рдгрд╛рд▓реА рдореЗрдВ рдЕрднрд┐рдирд┐рд░реНрдзрд╛рд░рдг рд╕рдорд╕реНрдпрд╛ рдХрд╛ рдХреНрдпрд╛ рдЕрд░реНрде рд╣реИ? рдЖрдк рдХреИрд╕реЗ рддрдп рдХрд░рддреЗ рд╣реИрдВ рдХрд┐ рд╕рдореАрдХрд░рдг рдЕрднрд┐рдирд┐рд░реНрдзрд╛рд░рд┐рдд рд╣реИ рдпрд╛ рдирд╣реАрдВ?

5. рдЖрднрд╛рд╕реА рдЪрд░ рдкреНрд░рддрд┐рдорд╛рди рдХрд╛ рдХреНрдпрд╛ рдЕрд░реНрде рд╣реИ? рд╡рд░реНрдгрди рдХреАрдЬрд┐рдП рдХрд┐ рд▓реЙрдЬрд╝рд┐рдЯ рдкреНрд░рддрд┐рдорд╛рди рдореЗрдВ рдЖрднрд╛рд╕реА рдЪрд░ рдХрд╛ рдЙрдкрдпреЛрдЧ рдХреИрд╕реЗ рдХрд┐рдпрд╛ рдЬрд╛рддрд╛ рд╣реИ? рдЖрдк рд▓реЙрдЬрд╝рд┐рдЯ рдкреНрд░рддрд┐рдорд╛рди рдХреЗ рдкреНрд░рд╛рдЪрд▓реЛрдВ рдХреА рд╡реНрдпрд╛рдЦреНрдпрд╛ рдХреИрд╕реЗ рдХрд░рддреЗ рд╣реИрдВ?

6. рд╡рд░реНрдгрди рдХреАрдЬрд┐рдП рдХрд┐ рдПрдХ рд╡рд┐рддрд░рд┐рдд рдкрд╢реНрдЪрддрд╛ рдкреНрд░рддрд┐рдорд╛рди рдХреИрд╕реЗ рдирд┐рд░реНрджрд┐рд╖реНрдЯ рдФрд░ рдЕрдиреБрдорд╛рдирд┐рдд рдХрд┐рдпрд╛ рдЬрд╛рддрд╛ рд╣реИ?

7. рдирд┐рдореНрдирд▓рд┐рдЦрд┐рдд рдкрд░ рд╕рдВрдХреНрд╖рд┐рдкреНрдд рдЯрд┐рдкреНрдкрдгрд┐рдпрд╛рдБ рд▓рд┐рдЦрд┐рдП:

i) рд╕рд░реНрд╡реЛрддреНрддрдо рд░реЗрдЦреАрдп рдЕрдирднрд┐рдирдд рдЖрдЧрдгреНрдХ
(ii) рдпреБрдЧрдкрдд рд╕рдореАрдХрд░рдг рдкреНрд░рдгрд╛рд▓реА рдХрд╛ рд▓рдШреБ рд╕реНрд╡рд░реВрдк

IGNOU MECE-01 (July 2022 - January 2023) Assignment Questions

рдЦрдВрдб-рдХ рдирд┐рдореНрдирд▓рд┐рдЦрд┐рдд рдкреНрд░рд╢реНрдиреЛрдВ рдХрд╛ рдЙрддреНрддрд░ рдкреНрд░рддреНрдпреЗрдХ рдХрд╛) рд▓рдЧрднрдЧ 700 рд╢рдмреНрджреЛрдВ рдореЗрдВ рд╣реИрдВред

1. рд╕реНрд╡рд╕рд╣рд╕рдВрдмрдВрдз рд╕реЗ рдЖрдк рдХреНрдпрд╛ рд╕рдордЭрддреЗ рд╣реИрдВ? рд╕реНрд╡рд╕рд╣рд╕рдВрдмрдВрдз рдХреЗ рдкрд░рд┐рдгрд╛рдо рдХреНрдпрд╛ рд╣реИрдВ? рдЖрдк рдПрдХ рдЖрдБрдХрдбрд╝рд╛ рд╕рдореВрд╣ рдореЗрдВ рд╕реНрд╡рд╕рд╣рд╕рдВрдмрдВрдз рдХрд╛ рдкрддрд╛ рдХреИрд╕реЗ рд▓рдЧрд╛рддреЗ рд╣реИрдВ? рд╕реНрд╡рд╕рд╣рд╕рдВрдмрдВрдз рдХреА рд╕рдорд╕реНрдпрд╛ рдХреЛ рджреВрд░ рдХрд░рдиреЗ рдХреЗ рд▓рд┐рдП рдЖрдк рдХрд┐рди рдЪрд░рдгреЛрдВ рдХрд╛ рдЕрдиреБрд╕рд░рдг рдХрд░реЗрдВрдЧреЗ? рд╕реНрдкрд╖реНрдЯ рдХреАрдЬрд┐рдПред

2. рдмрд╣реБрд╕рдорд╛рд╢реНрд░рдпрдг рдореЙрдбрд▓ рдкрд░ рдЗрд╕рдХреЗ рдорд╛рдирдХ рдЖрд╡реНрдпреВрд╣ рд╕реНрд╡рд░реВрдк рдореЗрдВ рд╡рд┐рдЪрд╛рд░ рдХреАрдЬрд┐рдПред рджрд░реНрд╢рд╛рдЗрдП рдХрд┐ рдУрдПрд▓рдПрд╕ (OLS) рдЖрдХрд▓рдХ, рд╢реНрд░реЗрд╖реНрда рд░реИрдЦрд┐рдХ рдЕрдирдорд┐рдирдд рдЖрдХрд▓рдХ (рдмреНрд▓реВ) рд╣реИред

рдЦрдВрдб-рдЦ рдордзреНрдпрдо рдЙрддреНрддрд░ рдкреНрд░рд╢реНрди (рдкреНрд░рддреНрдпреЗрдХ рдкреНрд░рд╢реНрди рдХрд╛ рдЙрддреНрддрд░ рд▓рдЧрднрдЧ 400 рд╢рдмреНрджреЛрдВ рдореЗрдВ рджреАрдЬрд┐рдП)ред

3. рд╡рд┐рд╖рдо рд╡рд┐рдЪрд╛рд▓рд┐рддрд╛ (heteroscedasticity)рд╕реЗ рдХреНрдпрд╛ рдЕрднрд┐рдкреНрд░рд╛рдп рд╣реИрдВ? рд╡рд┐рд╖рдо рд╡рд┐рдЪрд╛рд▓рд┐рддрд╛ рдХреА рд╕рдорд╕реНрдпрд╛ рдХреЗ рдХрд┐рд╕реА рдПрдХ рдирд┐рд╡рд╛рд░рдХ рдЙрдкрд╛рдп рдХреЛ рд╕реНрдкрд╖реНрдЯ рдХреАрдЬрд┐рдПред

4. рд╕рдордХрд╛рд▓рд┐рдХ рд╕рдореАрдХрд░рдг рдкреНрд░рдгрд╛рд▓реА рдореЗрдВ рдкрд╣рдЪрд╛рди (рдЕрднрд┐рдирд┐рд░реНрдзрд╛рд░рдг) рд╕рдорд╕реНрдпрд╛ рд╕реЗ рдХреНрдпрд╛ рдЕрднрд┐рдкреНрд░рд╛рдп рд╣реИ? рдпрд╣ рдХреИрд╕реЗ рддрдп рдХрд░реЗрдВрдЧреЗ рдХрд┐ рдХреЛрдИ рд╕рдореАрд░рдХрдг рдЕрднрд┐рдирд┐рд░реНрдзрд╛рд░рдг рд╣реИ рдпрд╛ рдирд╣реАрдВ?

5. рдЕрдкреНрд░рддреНрдпрдХреНрд╖ рдиреНрдпреВрдирддрдо рд╡рд░реНрдЧ (рдЖрдИ.рдПрд▓.рдПрдо.) рд╡рд┐рдзрд┐ рд╕реЗ рдХреНрдпрд╛ рдЕрднрд┐рдкреНрд░рд╛рдп рд╣реИ? рдмрддрд╛рдЗрдП рдХрд┐ рдЗрд╕ рд╡рд┐рдзрд┐ рдХреЗ рдкреНрд░рдпреЛрдЧ рд╕реЗ рдирд┐рдореНрдирд▓рд┐рдЦрд┐рдд рдореЙрдбрд▓ рдХреИрд╕реЗ рдЖрдХрд▓рд┐рдд рдХрд┐рдпрд╛ рдЬрд╛ рд╕рдХрддрд╛ рд╣реИ?

рдЬрд╣рд╛рдБ Q = рдкрд░рд┐рдорд╛рддреНрд░рд╛, P= рдХреАрдордд рдФрд░ x = рдЖрдп рд╣реЛ

6. рд╕рдорд╛рдиреНрдпреАрдХреГрдд рдиреНрдпреВрдирддрдо рд╡рд░реНрдЧ (GLS) рд╡рд┐рдзрд┐ рдХреЗ рдорд╛рдзреНрдпрдо рд╕реЗ рдкреНрд░рд╛рдЪрд▓реЛрдВ рдХреЗ рдЖрдХрд▓рди рдореЗрдВ рдЕрдиреБрд╕рд░рдгреАрдп рдЪрд░рдгреЛрдВ рдХреЛ рд╕реНрдкрд╖реНрдЯ рдХреАрдЬрд┐рдПред

7. рдмрд╣реБрд╕рдВрд░реЗрдЦрддрд╛ рдХреА рд╕рдВрдХрд▓реНрдкрдирд╛ рдХреЛ рд╕реНрдкрд╖реНрдЯ рдХреАрдЬрд┐рдПред рдЖрдХрд▓рди рдкрд░ рдЗрд╕рдХреЗ рдкрд░рд┐рдгрд╛рдо рдХреНрдпрд╛ рд╣реИрдВ? рдмрд╣реБрд╕рдВрд░реЗрдЦрддрд╛ рдХреА рд╕рдорд╕реНрдпрд╛ рдХреЛ рджреВрд░ рдХрд░рдиреЗ рдХреЗ рд▓рд┐рдП рдЖрдк рдХрд┐рди рдирд┐рд╡рд╛рд░рдХ-рдЙрдкрд╛рдпреЛрдВ рдХрд╛ рд╕реБрдЭрд╛рд╡ рджреЗрдЧреЗ?

MECE-01 Assignment Details

  • University IGNOU (Indira Gandhi National Open University)
  • Title Econometric Methods
  • Language(s) English and Hindi
  • Session July 2023 - January 2024
  • Code MECE-01
  • Subject Economics
  • Degree(s) MA
  • Course Optional Courses
  • Author Gullybaba.com Panel
  • Publisher Gullybaba Publishing House Pvt. Ltd.

Assignment Submission End Date

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  • 30th April┬а(if Enrolled in the June Exams)
  • 31st October (if Enrolled in the December Exams).

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  • July 2023 - January 2024 12 Pages (0.00 ), PDF Format SKU: IGNGB-AS-MA-MECE01-EN-415
  • July 2022 - January 2023 14 Pages (0.00 ), PDF Format SKU: IGNGB-AS-MA-MECE01-EN-344

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  • July 2023 - January 2024 16 Pages (0.00 ), PDF Format SKU: IGNGB-AS-MA-MECE01-HI-403
  • July 2022 - January 2023 18 Pages (0.00 ), PDF Format SKU: IGNGB-AS-MA-MECE01-HI-178

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