## Principles of Econometrics

Principles of Econometrics

For all questions you should provide screen print outs of Excel or STATA where necessary to support your workings.

Question 1

The file Growth.xls contains the following variables:

country = country isocode name

investment = average growth rate of the investment to GDP ratio between 1970-2010

openness = average openness ratio ({exports + imports}/GDP) between 1970-2010

population = average population growth rate between 1970-2010

gdp_1970 = real GDP in 1970

growth = average growth rate of real GDP ratio between 1970-2010

All variables are in natural logs.

1. Using Excel, obtain estimates of the OLS estimators and for the regression

. (1)

2. Confirm your results from part 1 using STATA

3. The Solow model predicts that growth rates depend on the starting level of GDP, the population growth rate and the rate of investment such that

. (2)

Using STATA estimate the OLS estimators and . Comment on the sign and significance of the coefficient estimates. Outline the economic intuition underlying your results.

4. A recent academic article suggests that countries that are more open to international trade have higher growth rates. Evaluate this hypothesis using equation (3)

. (3)

5. For each of the following questions formulate a null hypothesis and test it.

i. Investment is the only determinant of growth

ii. The relationship between the population growth rate and economic growth is equal to 0.2

iii. GDP in 1970 and population growth have the same effect on economic growth

Question 2

The file Profits.xls contains data on the profits earned by a sample of 706 firms in the automobile manufacturing and semiconductor industries. The file contains the following variables:

profits = firm profits (in millions of pounds)

wage_firm = firm wages (in millions of pounds)

exporter = dummy variable equal to 1 if the firm exports; 0 otherwise

rd = R&D expenditure (in millions of pounds)

impen = import penetration in industry in % (import share of output)

industry = dummy variable equal to 1 if the firms is in the automobile manufacturing industry; 0 if it is from the semiconductor industry

Use STATA to answer the following questions.

1. Estimate the following equation

. (4)

Comment on the sign and significance of the coefficient estimates. Provide economic intuition on your findings.

2. Using your results from part 1, how much is a one standard deviation increase in R&D expenditure predicted to increase/decrease firm profits?

3. It has been hypothesised that the returns to R&D activity differ according to whether a firm exports. Outline how you would test this and provide a null hypothesis. Do the results support the hypothesis?

4. Consider the following equation.

. (5)

i. What do the results tell you about the relationship between firm profits, wages and import penetration? Why might these relationships exist?

ii. Test the hypothesis that firm profits are unaffected by wages and import penetration

5. Conditional on the explanatory variables included in equation (5), do firms in the automobile industry earn significantly different profits compared to firms in the semiconductor industry?

Question 3

In a famous article Bresnahan and Reiss (1991) conjecture that as the number of firms in a market grows, the increase in competitive pressure leads firms to reduce their price. The Excel file Competition.xls contains data covering the number of ready-mix concrete firms located in each U.S. county. The industry is geographically segmented because of high transport costs involved in transporting ready-mix concrete. Each county therefore constitutes a separate, distinct, market.

The file also contains information on population density within the county and the number of people employed in the construction sector (the primary outlet for ready-mix concrete) which might also influence demand for ready-mix concrete. The file contains the following variables:

market = the market identifier

number_firms = number of ready-mix concrete firms operating in the market

cons_emp = number of people employed in the construction industry in the market

pop_density = number of people per square kilometre living within the market

price = price in $ of a yard of ready-mix concrete in the market

(6)

1. Using the data contained within Competition.xls investigate the hypothesis that competition affects prices within a market. Comment on the results and provide intuition on the economic mechanisms underlying your findings.

2. Test to see whether heteroskedasticity is present.

3. Ready-mix concrete producers are heavily reliant upon selling their output to the construction industry within the market with 95% of firm output typically being sold to the construction sector. With this in mind, test for the presence of multicollinearity in equation (6). Using your results comment on whether multicollinearity is a problem in the model.