What happened to these models?
How can the Republicans and Democrats propose policy without this data?
What is An Input-Output Model
The Input-Output model is a massively simultaneous system of equations. The equations quantify the impact of price change on each sector of the economy. Both short and long term impacts can be forecasted by quantifying the elasticity by sector over time. Time series methods corrected many of the estimation errors caused by simultaneous data streams. Leading models came out of MIT, UCLA, and Carnegie.
Google page rank (PR) uses the same massively simultaneous system of equation method for near realtime computations. My team at MIT innovated to enable these solutions with large systems.
The model tells us the direct impact, that increases in prices results in higher gasoline prices. With small changes, the demand impact is relatively inelastic. This means consumer behavior does not change much.
With the first significant oil price change in 1972, we had our first historic data point to show that the price response was not linear. Large changes have much greater impact than small changes. As forecasters, all historic models used linear estimation and were forced to fudge the data to estimate results that were different from historic patterns based on low price changes.
The model also measures indirect impacts over time. Higher gasoline prices impacted general inflation causing price increases for all goods. Over a longer period of time, commercial interests increased oil efficiency or shifted to other resources. Thus, the model quantifies the hundreds of complex economic cycles as the economy settles into a new equilibrium.
Applying the Model to the Web 2.0 Economy
As a current innovator in the Web 2.0 economy, I've hypothesized the relationship of radical oil price change to web 2.0 adoption. Specifically, an input-ouput model would show the following relationships:
- Increased Web 2.0 Use: Web 2.0 provides news, entertainment, and information over the Internet. This decreases casual driving about town. With higher gasoline prices, consumers would immediately reduce driving and consume more services at home. The relationship is non-linear with oil price change. Early data on web 2.0 trends and gasoline consumption show the inverse relationship. Is it statistically significant?
- Telecommuting and Home Work: Web 2.0 enables more telecommuting and work at home professionals to be productive without wasting (1) time commuting and (2) dollars for gas. The impact is again inversely non-linear with oil price change.
- Shift of Advertising from Paper to Web 2.0: Although this trend is true, proper analysis would show that the marginal impact from oil price increases would be insignificant. Higher transport costs increase the cost of producing, printing, and distributing paper. This includes direct mailers, newspapers, and magazines. However, the marginal impact would not reduce gasoline consumption among transporters such as the US Post Office, Fedex, UPS, and other shippers. Their costs are fixed and lower demand for shipping services won't decrease the cost to continue making the rounds for non-paper customers.
Similar hypothesis can be formed on hundreds of economic sectors. Together, the input-output model would integrate the complex relationships to produce short and long term forecasts. Like the Lionel Edie/Merrill Lynch/Bank of America group where dozens of sector economists cooperated to create one model, econometric models enable "blind men to see the elephant".
What Happened to the Input-Output Models?
The sector analysis above demonstrates the value of input-output analysis.
To verify my hypothesis, I searched for models and was shocked to see no updated studies relating to energy costs. Yet, candidates like Obama and McCain have proposed solutions without the data. How can those policy decisions make sense?
Energy Independence
The US consumes more oil than the next 20 countries combined. Our dependence on this scarce, imported resource hurts our short, near, long term future. Should we invest more to understand the problem?
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