Predicting Future Years Description

This page will explain what was done in the two gams files:

The transformation of the 2003 SAM into the 2050 SAM was based on the projected changes of certain energy sectors and population growth. The projections are referred to as factors and were determined based on data from the DOF and UC Davis' Advanced Energy Pathways (AEP) baseline reports.

Description of the factor sources can be found here.

Calculations of the factor sources can be found here.

The file begins by defining the different sets of sectors that will be used. The factors that will be used are also defined from 2003-2050, and are based on the DOF numbers for Cal PI growth and Cal CPI. The input CPI factor is also included to convert 2003 dollars to another input year dollar.

SAM2 is then introduced by multiplying the original SAM by the 2050 income growth factor. Then, the OILGAS, OILREF, INDGAS, DISTEL, DSTGAS, WHLGAS, and RETGAS sectors are transformed individually based on the corresponding projections. The next part consists of adjustments in the investment sectors, government sectors, capital and labor, the commodity/HH and government sectors, and finally the special industries sectors.

The matrix element (‘x’,y) is read as row ‘x’ and column y. The ‘ ’ around x represents the specific sector x, whereas y represents a set of sectors. Sets are defined in the gms file and are referred to as accordingly.

The OILGAS sector is determined by taking the original SAM and multiplying the OILGAS column (inputs to all sectors, z) by the oil and gas extraction growth factor. To maintain balance in the SAM2, an adjustment to ROW imports is made to make up for the decrease in production. The following diagram shows the steps to the changes:

OIL

GAS

ROW

ICI

OIL

GAS

1.

ROW

2.

1. SAM2(ICI, ‘OILGAS’) = SAM(ICI, ‘OILGAS’) * 2050 extraction growth factor

2. SAM2(‘ROW’, ‘OILGAS’) = sum(‘OILGAS’ ‘ROW’) – sum(‘OILGAS’ column – ‘ROW’)

The same changes were made to the OILREF sector, resulting in a balanced OILREF row and column.

The INDGAS sector also begins with a change in input growth. Assuming that INDGAS is both manufacturing and distribution, it will also be scaled in its output growth. The taxes are scaled according to the output growth. ROW exports are then adjusted to maintain balance.

ICI

IND

GAS

ROW

ICI

IND

GAS

2.

1.

4.

GT

3.

ROW

1. SAM2(ICI, ‘INDGAS’) = SAM(ICI, ‘INDGAS’) * 2005 refinery growth factor

2. SAM2(‘INDGAS’, ICI) = SAM2(‘INDGAS’, ICI) * 2005 gas intensity factor

3. SAM2(GT, ‘INDGAS’) = SAM2(GT, ‘INDGAS’) * 2005 gas intensity factor

4. SAM2(‘INDGAS’, ‘ROW’) = sum(‘INDGAS’ column) – sum(‘INDGAS’ row – ‘ROW’)

The DISTEL sector begins with a change in output, which are inputs for the corresponding sectors. Due to energy/$ efficiency gains, every other sector will buy accordingly less energy. Government spending on energy will also decrease by minor amounts. Then, the taxes are scaled according to output growth. ROW exports are adjusted to maintain balance since California will sell the extra capacities to outside of the state.

ICI

GTS

DSTEL

ROW

ICI

DSTEL

1.

2.

4.

GT

3.

ROW

1. SAM2(‘DISTEL’, ICI) = SAM2(‘DISTEL’, ICI) * electricity intensity factor

2. SAM2(‘DISTEL’, GTS) ) = SAM2(‘DSTEL’, GTS) * electricity intensity factor

3. SAM2(GT, ‘DISTEL’) = SAM2(GT, ‘DISTEL’) * electricity intensity factor

4. SAM2(‘DISTEL’, ‘ROW’) = sum(‘DISTEL’ column) – sum(‘DISTEL’ row – ‘ROW’)

The next three sectors, DSTGAS, WHLGAS and RETGAS, follow the same changes as the DSTEL sector. The only difference is that for steps 1, 2, and 3, DSTGAS row is multiplied by the gas intensity factor, and the WHLGAS and RETGAS sectors are multiplied by the fuel intensity factor.

The next part deals with the investment sector of the SAM, which involves changing the CCM matrix according to adjusted inputs into capital. The CCM0304 excel file is used and recalculated to include an 11% return on total capital and a 5% depreciation rate. The resulting CCM is labeled CCCM, and the amount of investment for each industry sector is then summed to determine the investment column in the SAM. The investment sector is then balanced by its ROW imports. The formulas used are as follow:

1. CCCM(I, J) = CCM(I, J) * (0.05 * SAM2(‘CAPIT’, J) / 0.11)

2. SAM2(I, ‘INVES’) = sum(CCCM rows)

3. SAM2(‘INVES’, ‘ROW’) = sum(‘INVES’ column) – sum(‘INVES’ row – ROW)

The government sector is balanced by adjusting the columns (spending) given the row entries (taxes). First, the tax columns are balanced by distributing the difference proportional to the former value. Second, the CGENF column is balanced given the inflow from the rows. Third, all government spending to industries (columns) is balanced in accordance with the rows. Fourth, the cell (‘HOUS0’, ‘LSWEL’) is changed.

GT

CGENF

GTS_NOWEL

LSWEL

ROW

Z

I

2.

3.

1.

HOUS0

4.

The adjustments to capital and labor are made by allocating the difference in expenditures from all sectors on household income from capital proportional to old income.

CAPIT

LABOR

H

1.

2.

The commodity/household and government sectors are interrelated, and are balanced iteratively to achieve a balancing of all rows and columns. First, to balance the commodity sectors, the household columns are adjusted according to the row sums difference proportional to old numbers. Then the government sectors are balanced in the same way as previously described where the columns (spending) are adjusted given the row entries (taxes). These two steps are looped 10 times.

Step one is as follows:

C

H

Z

I

2.

1.

Step 2 follows the same diagram as described in the changes for the government sector. The four adjustments are also the same. The repetition of these two steps achieves a greater balance of the corresponding sectors.

Lastly, some final adjustments are made to the special industry sectors by compensating the decrease in demand from the special sectors with sales to the ROW.

ROW

I

1.

INVES

2.

1. SAM2(I, ‘ROW’) = columnsum(Z, I) – rowsum(I, Z – ‘ROW’)

2. SAM2(‘INVES’, ‘ROW’) = sum(‘INVES’ column) – sum(‘INVES’ row – ROW)