McqMate

43

29.8k

1. |
## The intercept term,β1, is absent in.................. model. |

A. | regression through the origin |

B. | lin log model |

C. | log lin model |

D. | ols model |

Answer» A. regression through the origin |

2. |
## The lin log model and log lin model are ............. in parameters. |

A. | non linear |

B. | linear |

C. | functional |

D. | dependent |

Answer» A. non linear |

3. |
## r2 in intercept less model is.... .............. negative. |

A. | always |

B. | sometimes |

C. | never |

D. | cannot say |

Answer» B. sometimes |

4. |
## The slope coefficient ,β2, of ............ model measures elasticity of Y with respect to X. |

A. | regression through the origin |

B. | log log model |

C. | log lin model |

D. | clrm |

Answer» B. log log model |

5. |
## ....................... is a growth model. |

A. | alinear trend model |

B. | lin log model |

C. | log lin model |

D. | none of the above |

Answer» A. alinear trend model |

6. |
## In regression through the origin model, ......................... is absent. |

A. | the intercept term ,β1 |

B. | the slope coefficient ,β2 |

C. | error term |

D. | explanatory variables |

Answer» A. the intercept term ,β1 |

7. |
## Econometrics is concerned with |

A. | empirical support to economic theory |

B. | quantitative analysis of economic data |

C. | use of tools of mathematics and statistical inference |

D. | all of the above |

Answer» D. all of the above |

8. |
## Which of the following is the combination of economic theory, mathematical economics and economic statistics |

A. | econometrics |

B. | statistics |

C. | mathematics |

D. | quantitative economics |

Answer» A. econometrics |

9. |
## The first step in traditional econometric methodology is |

A. | statement of theory |

B. | forecasting |

C. | obtaining data |

D. | estimation of the model |

Answer» A. statement of theory |

10. |
## Which of the following discipline express the economic theory in mathematical form |

A. | econometrics |

B. | statistics |

C. | mathematics |

D. | mathematical economics |

Answer» D. mathematical economics |

11. |
## Keynes postulated ----- relationship between income and consumption |

A. | negative |

B. | positive |

C. | non linear |

D. | infinite |

Answer» B. positive |

12. |
## In the function, Q= α+βP, the slope coefficient is |

A. | α |

B. | β |

C. | p |

D. | q |

Answer» B. β |

13. |
## In the Keynesian linear consumption function Y=β1+β2X, Y represents |

A. | income |

B. | consumption expenditure |

C. | output |

D. | price |

Answer» B. consumption expenditure |

14. |
## In the Keynesian linear consumption function Y=β1+β2X, β1 is |

A. | slope coefficient |

B. | intercept coefficient |

C. | output coefficient |

D. | none of the above |

Answer» B. intercept coefficient |

15. |
## In the Keynesian linear consumption function Y=β1+β2X, the parameters of the model are |

A. | β1and β2 |

B. | . β1and x |

C. | x and y d. y an |

D. | β2 |

Answer» A. β1and β2 |

16. |
## In the Keynesian linear consumption function Y=β1+β2X, the marginal propensity to consume is |

A. | β1 |

B. | x |

C. | y |

D. | β2 |

Answer» D. β2 |

17. |
## if the model has only one equation, the model is called |

A. | single equation model |

B. | multiple equation model |

C. | variable equation model |

D. | none of the above |

Answer» A. single equation model |

18. |
## if the model has more than one equation, the model is called |

A. | single equation model |

B. | multiple equation model |

C. | variable equation model |

D. | none of the above |

Answer» B. multiple equation model |

19. |
## In the Keynesian linear consumption function Y=β1+β2X, the dependent variable is |

A. | β1 |

B. | x |

C. | y |

D. | β2 |

Answer» C. y |

20. |
## In the Keynesian linear consumption function Y=β1+β2X, the explanatory variable is |

A. | β1 |

B. | x |

C. | y |

D. | β2 |

Answer» B. x |

21. |
## the variable appearing on the left side of the equality sign is called |

A. | dependent variable |

B. | independent variable |

C. | explanatory variable |

D. | none of the above |

Answer» A. dependent variable |

22. |
## In conventional model r2 is .............. negative. |

A. | always |

B. | sometimes |

C. | never |

D. | cannot say |

Answer» C. never |

23. |
## the variable appearing on the right side of the equality sign is called |

A. | independent variable |

B. | explanatory variable |

C. | all of the above |

D. | none of the above |

Answer» C. all of the above |

24. |
## independent variables are also known as |

A. | explanatory variables |

B. | dependent variable |

C. | implicit variable |

D. | static variable |

Answer» A. explanatory variables |

25. |
## which is the explanatory variable in the Keynesian consumption function |

A. | income |

B. | consumption |

C. | price |

D. | output |

Answer» A. income |

26. |
## a mathematical model assumes----- relationship between variables |

A. | inexact |

B. | exact |

C. | probable |

D. | none of the above |

Answer» B. exact |

27. |
## a function that can be represented as straight line graphically is |

A. | non linear |

B. | linear |

C. | polynomial |

D. | quadratic |

Answer» B. linear |

28. |
## in the function Y=β1+β2X+u, the term ‘u’ is called |

A. | disturbance term |

B. | intercept |

C. | slope |

D. | dependent term |

Answer» A. disturbance term |

29. |
## A model in which regressand is logarithmic is called............... |

A. | regression through the origin |

B. | lin log model |

C. | log lin model |

D. | clrm |

Answer» C. log lin model |

30. |
## the function Y=β1+β2X+u is an example of |

A. | linear regression model |

B. | econometric model |

C. | all of the above |

D. | none of the above |

Answer» C. all of the above |

31. |
## confirmation or refutation of economic theories on the basis of sample evidence is based on the branch of statistical theory called |

A. | statistical inference |

B. | standard deviation |

C. | arithmetic mean |

D. | regression analysis |

Answer» A. statistical inference |

32. |
## the term regression was first introduced by |

A. | irwing fisher |

B. | laspayer |

C. | francis galton |

D. | pearson |

Answer» C. francis galton |

33. |
## Reciprocal and log lin models are ............. in variables. |

A. | non linear |

B. | linear |

C. | functional |

D. | dependent |

Answer» B. linear |

34. |
## the function Y=β1+β2X+u is an example of |

A. | non linear regression model |

B. | linear regression model |

C. | quadratic regression model |

D. | none of the above |

Answer» B. linear regression model |

35. |
## In the Keynesian linear consumption function Y=β1+β2X, the independent variable is |

A. | β1 |

B. | . x |

C. | y |

D. | β2 |

Answer» B. . x |

36. |
## Statistical relationships assumes that variables are |

A. | random |

B. | stochastic |

C. | all of the above |

D. | none of the above |

Answer» C. all of the above |

37. |
## A statistical relationship per say cannot logically imply |

A. | regression |

B. | causation |

C. | error |

D. | random |

Answer» B. causation |

38. |
## The measure that analyses the degree of linear association between two variables is called |

A. | correlation coefficient |

B. | regression coefficient |

C. | significance level |

D. | testing of hypothesis |

Answer» A. correlation coefficient |

39. |
## In the Keynesian linear consumption function Y=β1+β2X, X represents |

A. | income |

B. | consumption expenditure |

C. | output |

D. | price |

Answer» A. income |

40. |
## Correlation analysis is concerned with |

A. | prediction of future value |

B. | prediction of average value |

C. | degree of association among variables |

D. | testing of hypothesis |

Answer» C. degree of association among variables |

41. |
## Correlation theory is based on the assumption of |

A. | randomness of variables |

B. | conditional mean |

C. | random errors |

D. | specification |

Answer» A. randomness of variables |

42. |
## The correlation coefficient between the mathematics and economics was found to be 0.64. What will be the value of correlation coefficient between economics and mathematics |

A. | 0.32 |

B. | -0.64 |

C. | 0.64 |

D. | 1.28 |

Answer» C. 0.64 |

43. |
## the law of universal regression was first introduced by |

A. | irwing fisher |

B. | laspayer |

C. | francis galton |

D. | pearson |

Answer» C. francis galton |

44. |
## In ------ analysis there is no distinction between dependent and explanatory variables |

A. | regression |

B. | correlation |

C. | hypothesis testing |

D. | estimation |

Answer» B. correlation |

45. |
## If we are studying the dependence of a variable on a single explanatory variable, the analysis is called |

A. | two variable regression analysis |

B. | multiple regression analysis |

C. | single regression analysis |

D. | none of the above |

Answer» A. two variable regression analysis |

46. |
## If we are studying the dependence of a variable on more than one explanatory variable, the analysis is called |

A. | two variable regression analysis |

B. | multiple regression analysis |

C. | single regression analysis |

D. | none of the above |

Answer» B. multiple regression analysis |

47. |
## The term “random” is synonym for the term |

A. | stochastic |

B. | variable |

C. | error |

D. | regression |

Answer» A. stochastic |

48. |
## If the data is collected at one point in time, it is called |

A. | time series data |

B. | cross section data |

C. | pooled data |

D. | none of the above |

Answer» B. cross section data |

49. |
## If the data is collected over a period of time, it is called |

A. | time series data |

B. | cross section data |

C. | pooled data |

D. | none of the above |

Answer» A. time series data |

50. |
## The combination of time series and cross sectional data is known as |

A. | pooled data |

B. | panel data |

C. | longitudinal data |

D. | none of the above |

Answer» A. pooled data |

51. |
## The set of all possible outcomes of an experiment or measurement is known as |

A. | population |

B. | census |

C. | sample |

D. | variable |

Answer» A. population |

52. |
## conditional mean of Y given X value is denoted as |

A. | con y |

B. | e(y/x) |

C. | prob (y/x) |

D. | e(x/y) |

Answer» B. e(y/x) |

53. |
## An expected value is the same as |

A. | average value |

B. | standard deviation |

C. | dispersion |

D. | none of the above |

Answer» A. average value |

54. |
## The locus of points conditional means of the dependent variable for the fixed values of the explanatory variables is |

A. | venn diagram |

B. | lorenz curve |

C. | probability curve |

D. | population regression curve |

Answer» D. population regression curve |

55. |
## The regression line or curve passes through |

A. | origin |

B. | vertical axis |

C. | horizontal axis |

D. | conditional means |

Answer» D. conditional means |

56. |
## E (Y/Xi) = f (Xi) is known as |

A. | population regression function |

B. | sample regression function |

C. | expected average |

D. | none of the above |

Answer» A. population regression function |

57. |
## In the regression function E(Y/Xi)=β1+β2Xi, regression coefficients are |

A. | y and x |

B. | y and β1 |

C. | β1and β2 d β2 an |

D. | xi |

Answer» C. β1and β2 d β2 an |

58. |
## the regression function E(Y/Xi)=β1+β2Xi is a |

A. | linear regression function |

B. | sample regression function |

C. | non linear regression function |

D. | log linear regression function |

Answer» A. linear regression function |

59. |
## in the regression function E(Y/Xi)=β1+β2Xi , β1 is |

A. | intercept coefficient |

B. | slope coefficient |

C. | variable |

D. | average value |

Answer» A. intercept coefficient |

60. |
## in the regression function E(Y/Xi)=β1+β2Xi , β2 is |

A. | aintercept coefficient |

B. | slope coefficient |

C. | variable |

D. | average value |

Answer» B. slope coefficient |

61. |
## the regression function E(Y/Xi)=β1+β2Xi 2 is linear in |

A. | variables |

B. | parameters |

C. | coefficients |

D. | none of the above |

Answer» B. parameters |

62. |
## in the regression function E (Y⁄X ) = β + β X is linear in |

A. | variables |

B. | parameters |

C. | coefficients |

D. | none of the above |

Answer» A. variables |

63. |
## in the function Yi= β1+β2Xi+ui, the term ui refers to |

A. | variable |

B. | parameters |

C. | coefficient |

D. | stochastic error term |

Answer» D. stochastic error term |

64. |
## in the function Yi= β1+β2Xi+ui, the term ui is ------- in nature |

A. | random |

B. | nonsystematic |

C. | all of the above |

D. | none of the above |

Answer» C. all of the above |

65. |
## “the descriptions be kept as simple as possible until proved inadequate” corresponds to |

A. | occam’s razor |

B. | index numbers |

C. | regression |

D. | correlation |

Answer» A. occam’s razor |

66. |
## The rule or formula that tells how to estimate the population parameter from the sample information is called |

A. | estimate |

B. | estimator |

C. | population |

D. | coefficient |

Answer» B. estimator |

67. |
## The function Y = β + β X is a |

A. | sample regression function |

B. | non linear regression function |

C. | log linear regression function |

D. | population regression function |

Answer» A. sample regression function |

68. |
## the most popular method of constructing sample regression function in the regression analysis is |

A. | method of ols |

B. | generalised squares |

C. | ordinary regression method |

D. | none of the above |

Answer» A. method of ols |

69. |
## the method of ordinary least squares is attributed to |

A. | pearson |

B. | pashee |

C. | fisher |

D. | carl friedrich gauss |

Answer» D. carl friedrich gauss |

70. |
## If each estimator provides only a single value of the relevant population parameter, it is |

A. | point estimator |

B. | interval estimator |

C. | class estimator |

D. | single estimator |

Answer» A. point estimator |

71. |
## If each estimator provides a range of possible values relevant population parameter, it is |

A. | point estimator |

B. | interval estimator |

C. | class estimator |

D. | single estimator |

Answer» B. interval estimator |

72. |
## The sample regression line obtained through the OLS method passes through |

A. | sample means |

B. | sample standard deviation |

C. | origin |

D. | vertical axis |

Answer» A. sample means |

73. |
## The Gaussian standard classical linear regression model assumes------- assumptions |

A. | seven |

B. | ten |

C. | five |

D. | eight |

Answer» B. ten |

74. |
## Which is the assumption of Gaussian standard classical linear regression model |

A. | linear regression model |

B. | x values are fixed |

C. | zero mean values for disturbances |

D. | all of the above |

Answer» D. all of the above |

75. |
## The numerical value obtained by the estimator in an application is known as |

A. | estimate |

B. | estimator |

C. | population |

D. | coefficient |

Answer» A. estimate |

76. |
## Homoscedasticity means------ for disturbances |

A. | equal mean |

B. | equal variance |

C. | zero mean |

D. | none of the above |

Answer» B. equal variance |

77. |
## The literal meaning of econometrics is |

A. | estimation |

B. | economic measurement |

C. | forecasting |

D. | testing |

Answer» B. economic measurement |

78. |
## Economic theory makes statements that are mostly |

A. | quantitative |

B. | qualitative |

C. | positive |

D. | none of the above |

Answer» B. qualitative |

79. |
## In the function, Q= α+βP, the intercept coefficient is |

A. | α |

B. | β |

C. | p |

D. | q |

Answer» B. β |

80. |
## Heteroscedasticity implies |

A. | equal spread |

B. | unequal spread |

C. | equal mean |

D. | equal variance |

Answer» B. unequal spread |

81. |
## Given any two X values the classical linear regression model assumes the correlation between the disturbances as |

A. | one |

B. | infinity |

C. | negative |

D. | zero |

Answer» D. zero |

82. |
## which is the dependent variable in the Keynesian consumption function |

A. | income |

B. | consumption |

C. | price |

D. | output |

Answer» B. consumption |

83. |
## in the regression context, the OLS estimators are BLUE according to |

A. | central limit theorem |

B. | gauss markov theorem |

C. | young theorem |

D. | fisher’s theorem |

Answer» B. gauss markov theorem |

84. |
## The summary measure used to measure the goodness of fit of a regression line |

A. | coefficient of determination |

B. | coefficient of variation |

C. | standard error d standar |

D. | deviation |

Answer» A. coefficient of determination |

85. |
## The numerical value of coefficient of determination lies between |

A. | -1 and 1 |

B. | 0 and 1 |

C. | -∞ to +∞ |

D. | -∞ to 1 |

Answer» B. 0 and 1 |

86. |
## The classical theory of statistical inference consists of |

A. | estimation and hypothesis testing |

B. | regression and correlation |

C. | averages and dispersion |

D. | none of the above |

Answer» A. estimation and hypothesis testing |

87. |
## The rejecting of a true hypothesis is called |

A. | type i error |

B. | type ii error |

C. | standard error |

D. | point estimation |

Answer» A. type i error |

88. |
## Which of the following is used to measure the degree of association between two variables |

A. | coefficient of determination |

B. | coefficient of correlation |

C. | standard error d standar |

D. | deviation |

Answer» B. coefficient of correlation |

89. |
## The accepting of a false hypothesis is called |

A. | type i error |

B. | type ii error |

C. | standard error |

D. | point estimation |

Answer» B. type ii error |

90. |
## The larger the standard error, the ----- the width of the confidence interval |

A. | smaller |

B. | larger |

C. | infinity |

D. | cannot calculate |

Answer» B. larger |

91. |
## -β represents: |

A. | Diminishing returns to scale |

B. | Increasing returns to scale |

C. | Constant returns to scale |

D. | None of the above |

Answer» C. Constant returns to scale |

92. |
## _____ is the best criteria to judge the validity of a model : |

A. | Assumptions |

B. | Information it provides |

C. | Its simplicity |

D. | predictive power |

Answer» D. predictive power |

93. |
## The given function f (x) = ax + b, is an example of ____ function: |

A. | quadratic |

B. | polynomial |

C. | linear |

D. | rational |

Answer» C. linear |

94. |
## The given function f (x) = ax2 + bx + c , is an example of ____ function: |

A. | quadratic |

B. | polynomial |

C. | linear |

D. | rational |

Answer» A. quadratic |

95. |
## For a utility function u = xy + 3x + 4y, marginal utility of good x is: |

A. | xy + 3x + 4y |

B. | y + 3 |

C. | x + 4 |

D. | y + 3x |

Answer» B. y + 3 |

96. |
## Given a consumption function C = 250 + 0.75Yd, autonomous consumption is ____ |

A. | 0.75 |

B. | 0 |

C. | 250 |

D. | -0.75 |

Answer» C. 250 |

97. |
## For a total cost function TC = 1.5Q2 + 4Q + 46, MC is : |

A. | 1.5Q + 4 + |

B. | 1.5Q + 4 |

C. | 1.5Q |

D. | 4Q + 46 |

Answer» A. 1.5Q + 4 + |

98. |
## Abstraction from reality is made based on : |

A. | assumptions |

B. | prediction |

C. | theory |

D. | hypothesis |

Answer» A. assumptions |

99. |
## ____ is a simplified description of reality, designed to yield hypothesis about economic behaviour that can be tested. |

A. | theory |

B. | postulate |

C. | proposition |

D. | economic model |

Answer» B. postulate |

100. |
## ____ models are mathematical models designed to be used with data. |

A. | Empirical |

B. | Visual |

C. | Mathematical |

D. | Simulation |

Answer» A. Empirical |

Done Reading?

Tags

Question and answers in
Mathematical Economics,
Mathematical Economics
multiple choice questions and answers,
Mathematical Economics
Important MCQs,
Solved MCQs for
Mathematical Economics,
Mathematical Economics
MCQs with answers PDF download