ECON 360 Lecture Notes - Lecture 5: Indian Institute Of Technology Kanpur, Structural Break, Econometrics

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lilacyak198

21 Feb 2018

School

Binghamton University

Department

Economics

Course

ECON 360

Professor

Carmen Flores

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Document Summary

A fundamental assumption in a regression modeling is that the pattern of data on dependent and independent variables remains the same throughout the period over which the data is collected. Under such an assumption, a single linear regression model is fitted over the entire data set. The regression model is estimated and used for prediction assuming that the parameters remain same over the entire time period of estimation and prediction. When it is suspected that there exist a change in the pattern of data, then the fitting of single linear regression model may not be appropriate and more than one regression models may be required to be fitted. Before taking such a decision to fit a single or more than one regression models, a question arises how to test and decide if there is a change in the structure or pattern of data.

Related Questions

Economists use economic models to guide their thinking in regards explaining and predicting that which is otherwise unknown. These models are generalizations that rest on assumptions we use in creating a simplified setting, where only that which is most-pertinent is allowed to come into play directly, and at the same time, that which is not pertinent is rendered excluded by being held constant. Simply put, if you change your founding assumptions, you change the model for you have changed the simplified setting. If you change a variable that is included directly into the model, you can then assume the variable changes marginally then trace out the effects of this marginal change on the variable being explained. Similarly, If you allow a change of a variable that has been excluded, you are relaxing an assumption so you can reason out what the effects of such a change could be.

What is important to understand here, is the description I have just relayed to you describes how economists use models. It is but one example of how models are used more-generally in ALL the other sciences and social sciences. And to go a step further, it is but a description or formalization of how we in an all-inclusive sense use assumptions when we are reasoning about that which we reason about. Our assumptions are our foundations for our thoughts about all that we consider in our efforts towards understanding the world in which we live and the people, both individually and collectively inclusive of their institutions, with whom we come into contact.

Using this knowledge, describe what you think are the dangers to our thinking and actions based on our thinking of our using simplifying assumptions that are wholly untrue or are too strong, too constricting, are way too over-generalizing. Choose whatever context you wish and provide an example. Then describe why having at the very least a small measure of skepticism may be considered healthy for one's own sake and the sake of others.

1. What does the term s*Y represent in the capital-accumulation equation of Solow growth model?

a) The labor-income share of GDP.

b) Net investment.

c) Gross investment.

d) The net change in the capital stock from one year to the other.

2. In the Solow growth model, suppose that the savings rate is 25%, the depreciation rate is 10%, the current capital stock is 10 trillion $ and current output of a country is 4 trillion $. What will the capital stock of this country be in the following period?

a) 10 trillion $.

b) 11 trillion $.

c) We cannot tell since we are not given information about technological progress.

d) We cannot tell since population growth is not known.

3. Consider a country which starts with a capital stock below its steady-state level in the Solow model (without technological change). Why is growth slowing down over time for this country?

a) Population growth is becoming stronger over time since the population is growing, which makes it harder to accumulate high levels of capital per capita.

b) A country cannot maintain the same savings rate forever, so investment must decrease at some point.

c) The more capital there is, the more of it depreciates. As the country becomes richer, it becomes ever harder to replace depreciated capital.

d) There are diminishing returns to the factor capital. Thus investment, capital and GDP per capita grow by ever smaller amounts as the country becomes richer.

4. Suppose Pakistan has a higher savings rate than Iran. Both start out with the same capital per worker. All other parameters are the same for both countries (population growth and depreciation rate). The Solow growth model (without technological change) predicts that...

blackweasel275

1. You are given only three quarterly seasonal indices and quarterly seasonally adjusted data for the entire year. What is the raw data value for Q4? Raw data is not adjusted for seasonality.

Quarter Seasonal Index Seasonally Adjusted Data

Q1 .80 295

Q2 .85 299

Q3 1.15 270

Q4 --- 271

2. One model of exponential smoothing will provide almost the same forecast as a liner trend method. What are linear trend intercept and slope counterparts for exponential smoothing?

A. Alpha and Delta

B. Delta and Gamma

C. Alpha and Gamma

D. Standard Deviation and Mean

3. When performing correlation analysis what is the null hypothesis? What measure in Minitab is used to test it and to be 95% confident in the significance of correlation coefficient.

A. Ho: r = .05 p < .5

B. Ho: r = 0 p >.05

C. Ho: r ? 0 p?.05

D. Ho: r = 0 p?.05

In decomposition what does the cycle factor (CF) of .80 represent for a monthly forecast estimate of a Y variable?

A. The estimated value is 80% of the average monthly seasonal estimate.
B. The estimate is .80 of the forecasted Y trend value.
C. The estimated value is .80 of the historical average CMA values.
D. The estimated value has 20% more variation than the average historical Y data values.

5. A Wendy's franchise owner notes that the sales per store has fallen below the stated national Wendy's outlet average of $1,368,000. He asserts a change has occurred that reduced the fast food eating habits of Americans. What is his hypothesis (H1) and what type of test for significance must be applied?

A. H1: u ? $1,368,000 A one-tailed t-test to the left.
B. H1: u = $1,368,000 A two-tailed t-test.
C. H1: u < $1,368,000 A one-tailed t-test to the left.
D. H1: p < $1,368,000 A one-tailed test to the right

6. As the sample size from a population increases, for a given level of significance what happens to the null hypothesis rejection region and size of the t-table value?

A. The rejection region and the t-table value generally gets smaller for sample size below 31.
B. The rejection region gets larger and the t-table value generally gets smaller for sample sizes below 31.
C. The rejection region remains unchanged while the t-table value gets smaller for all sample sizes.
D. The zero mean hypothesis region gets larger and the t-table value gets larger as well for sample sizes below 31.

7. You obtained autocorrelation LBQ value of 18.58 for the 12^th lag from a data sample. Are the data significantly correlated at the lag examined or not? You want to be 95% confident in your answer.

A. Yes. The data are significantly correlated through the 12th lag.
B. No. The data are not significantly correlated through the 12^th lag.

C. No. Only the 12 lag period is not correlated.

D. You cannot tell since the number of sample observations is not provided.

E. The p-value is above .05 so the data is correlated.

8. Sometimes forecasters get lazy or forgetful and do not check the significance of XY data correlations and use the X variable to forecast Y. What is the result of this?

A. Type 2 error
B. Autocorrelation error
C. Type 3 error
D. Type 1 error

9. Do error measures indicate the statistical significance of forecast model variables?

A. Yes. They move in the same direction as statistical significance.
B. Yes. As error measures decrease the variable significance increases.
C. No They indicate only the magnitude of estimate error.
D. No. They indicate only the statistical significance of a forecast or fitted values.

10. In exponential smoothing what is the weight of the alpha coefficient for a time series data observation from the 3^rd previous period if the original alpha value is set at .8?

A. The weight cannot be calculated since the data observation is not given.
B. The weight is zero since the alpha value is set relatively high.
C. .548
D. .0064

11.Given the data series below for variables Y (Monthly Inventory Balance) and X (Monthly Sales) are they significantly correlated at the 95% confidence level and how can you tell?

Ending Inv. Bal. Y		Monthly Sales X
1544		5053
1913		5052
2028		7507
1178		2887
1554		3880
1910		4454
1208		3855
2467		8824
2101		5716

A. Yes. The correlation coefficient is .873 that is greater than .05.
B. Yes. The correlation p-value is .002 which is less than .05.
C. No. The correlation coefficient is above the p-value.
D.No. The correlation p-value is greater than the 95% confidence level.

12. You have forecast the sales for your company for the last 12 months and the forecast residuals are shown below. Are these residuals to be considered random?
Residuals

-24

-348

-892

-62

-378

-489

-342

490

578

198

A. Yes, since the residuals randomly vary in magnitude.
B. Yes since the residuals are positive and negative and vary in magnitude.
C. No, since the residuals are stationary and vary in magnitude.
D. No, since the residuals indicate positive slope.

13. Given the residuals in problem 12 above what is the RMSE for the forecast?

A. -101.0
B. 411.8
C. 169603
D. 220.1

14. Which form of exponential smoothing can result in a na

ECON 360 Lecture Notes - Lecture 5: Indian Institute Of Technology Kanpur, Structural Break, Econometrics

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