In the above main model, we have assumed that the relationship between oil and education can be explained linearly, where a %-change in X corresponds to a certain amount of change in Y.
This allowed us to measure how the size of oil activity affected education. It could be that the relationship isn’t quite as refined as this, but rather depends more broadly on the introduction of oil. To measure these effects, we use the differences-in-differences roll-out method described in Chapter 4, in Equation (2).
To define what time oil activity started to affect the level of education of the connected municipality, we look at two different introduction points: 1) the time of the first produced unit
5 This would not be the case, if the two educational lengths had coefficients with either positive or different signs;
the sum of two positive coefficients would be larger than their individual parts, and the sum of a positive and negative coefficient would be somewhere in between the two.
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of petroleum, and 2) the time of the first investment made. Every production start happens in Period 1, except for the production for Hammerfest. All years for both production and investment start can be seen in Table 3, Chapter 3.
5.3.1 Estimates
In table 10, we have summarized the results for the difference-in-difference model, when introduction is related to both production and investment. In column (2) and (5), we have confined the model to include a time span in which all of our treatment groups are active, 9 and 10 years, respectively. In column (3) and (6), we have estimated an unconfined effect, where the number of active years range from 9 to 36 years. For reference, the pre-activity average share of educational attainment is also shown.
Interpreting these results directly, the introduction of oil production has permanently reduced educational attainment in the treatment group by 0.5 pp, while the introduction of oil investment has reduced educational attainment by 0.4 pp. None of these estimates are statistically significant, but they are both close to a significance level of 10%. During the first nine years after production has started, the average permanent reduction in educational attainment is shown to be 0.23 pp, compared to the control group. Having larger effects in the long-run than in the short-run indicates that the impeding effects oil activity have on education increases as time passes. The effects for investments are more than half that of production.
Table 10. Roll-out estimates
Note. Column (1) and (4) show the average higher educational attainment one year prior to the start of production or investment, respectively. Column (2), (3), (5) and (6) contains the results from the difference-in-difference estimator from Equation (6), using production start as an indicator. The effects are an average change over the time period. Column (2) and (5) consist of a balanced panel, where there are observations for all nine years. Column (3) and (6) have a longer, but unbalanced panel, where every year for which production or investment is positive is included. P-values attained from the robust standard errors are shown in parentheses. * p < 0.10, ** p < 0.05,
*** p < 0.01
44 5.3.2 Event Study
We now try to inspect the different yearly effects of the introduction of oil activity, with an event study specification. To achieve a balanced panel along our event study, we only include years for which we have observations for every treatment group. Due to our yearly educational data starting in 1980, we are forced to omit the three treatment groups, specifically those regarding Florø, Sotra and Mongstad, due to production starting before 1980. This leaves us with a pre-treatment horizon of 6 years, due to Mongstad starting production in 1986, and a post-treatment horizon of 9 years, due to Hammerfest starting production in 2007. Translating these parameters to Equation (3) gives us T=-6 as the first event-year and q=16 as the event lasts for 16 years. The first year before the introduction (T=-1) is normalized to zero and serves as the base-year.
5.3.2.1 Production
In Figure 9 below, the pre-treatment effects display little difference from zero, while all of the post-treatment estimates are below zero, with only two years, year 7 and 9, having confidence intervals breaching zero. This indicates that the introduction of oil production to a municipality has a negative effect on tertiary educational attainment, compared to municipalities not affected yet or at all. The point estimates also indicate that the effect is increasing for the first five years, before becoming weaker and less statistically significant.
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Figure 9. Event study estimates for the start of oil production’s effect on educational attainment
Note. Event study estimates and confidence intervals for each year before and after the production of oil has started, where year 0 indicates production start. The control group is placed in the normalized year prior to production start and set to zero, to serve as the baseline for the changes in education.
5.3.2.2 Investment
The event study estimates for the introduction decided by the first investment is shown in Figure 10. We can see clear similarities between the event study for investment and production. This is to be expected, as the first investment occurs on average 4.25 years before the first instance of production (see Chapter 3). This seems to be replicated in the figures, the largest coefficient for production happening in year 5, while investment has its largest coefficient in year 9, four years later. While the trends and direction of the estimates for investment are similar to production, none of the post-treatment estimates are significant, having every confidence interval above zero.
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Figure 10. Event study estimates for the start of oil investment’s effect on educational attainment
Note. Event study estimates and confidence intervals for each year before and after the investment of oil has started, where year 0 indicates the year of investment start. The control group is placed in the normalized year prior to investment start and set to zero, to serve as the baseline for the changes in education.
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6 Robustness
Since our control group is subject to some asymmetry with our treatment group, in terms of initial educational attainment, size and population, due to our nonrandomized approach, our results could be subject to selection bias (Heckman, 1979). When we have such confounding factors, it makes it challenging to infer that differences reported in our model are due to our explanatory variable alone. To combat these issues, we attempt to create a new control group for which these factors are as close to identical as possible to our treatment group. If our results remain unaffected to the changes in these factors, it increases the robustness of our model (Brewer & Crano, 2000, p. 19) and subsequently improves the validity of our explanatory variable being responsible for the reported effects.