Appendix B: Tables for the ROW Model (MC2 Version)

This is an update of Appendix B in the
1994 book. It presents the ROW
model that is part of the MC2 model. The date of the ROW model
presented here is
December 27, 1998. This is the latest version of the ROW model
on this site.

Table B.1: The Countries and Variables in the MC Model
Table B.2: The Variables for a Given Country in Alphabetical Order
Table B.3: The Equations for a Given Country
Table B.4: Equations the Pertain to the Trade and Price Links Among
Countries
Table B.5: Links Between the US and ROW Models
Table B.6: The Procedure Used to Create Quarterly Data from Annual
Data
Table B.7: Construction of the Balance of Payments Data: Data for S
and TT 
Table B.1: The Countries
and Variables in the MC Model 
Table B.1
The Countries and Variables in the MC Model
Quarterly Countries Local Currency Trade Share Equations Only
1. US United States U.S. Dollar (mil.) 40. TU Turkey
2. CA Canada Can. Dollar (mil.) 41. PD Poland
3. JA Japan Yen (bil.) 42. RU Russia
4. AU Austria Schilling (bil.) 43. UE Ukraine
5. FR France Fr. Franc (bil.) 44. EG Egypt
6. GE Germany D. Mark (bil.) 45. IS Israel
7. IT Italy Lire (bil.) 46. KE Kenya
8. NE Netherlands Guilder (bil.) 47. BA Bangladesh
9. ST Switzerland Swiss Franc (bil.) 48. HK Hong Kong
10. UK United Kingdom Pound Sterling (mil.) 49. SI Singapore
11. FI Finland Markka (mil.) 50. VI Vietnam
12. AS Australia Aust. Dollar (mil.) 51. NI Nigeria
13. SO South Africa Rand (mil.) 52. AL Algeria
14. KO Rep. of Korea Won (bil.) 53. IA Indonesia
54. IN Iran
Annual Countries 55. IQ Iraq
56. KU Kuwait
15. BE Belgium Bel. Franc (bil.) 57. LI Libya
16. DE Denmark Den. Kroner (bil.) 58. UA United Arab Emirates
17. NO Norway Nor. Kroner (bil.) 59. AO All Other
18. SW Sweden Swe. Kroner (bil.)
19. GR Greece Drachmae (bil.)
20. IR Ireland Irish Pound (mil.)
21. PO Portugal Escudos (bil.)
22. SP Spain Pesetas (bil.)
23. NZ New Zealand N.Z. Dollar (mil.)
24. SA Saudi Arabia Riyals (bil.)
25. VE Venezuela Bolivares (bil.)
26. CO Colombia Col. Pesos (bil.)
27. JO Jordan Jor. Dinars (mil.)
28. SY Syria Syr. Pound (mil.)
29. ID India Ind. Rupee (bil.)
30. MA Malaysia Ringgit (mil.)
31. PA Pakistan Pak. Rupee (bil.)
32. PH Philippines Phil. Peso (bil.)
33. TH Thailand Baht (bil.)
34. CH China Yuan (bil.)
35. AR Argentina Arg. Peso (mil.)
36. BR Brazil Reais (mil.)
37. CE Chile Chi. Peso (bil.)
38. ME Mexico New Peso (mil.)
39. PE Peru Nuevos Soles (mil.)
Note: The countries that make up the EMU, denoted EU in the model, are
AU, FR, GE, IT, NE, FI, BE, IR, PO, SP. (Luxembourg, which is also part
of the EMU, is not in the model.)
A Brief Listing of the Variables per Country
Variables Determined by Stochastic Equations:
1. M Merchandise Imports, 90 lc
2. C Consumption, constant lc
3. I Fixed Investment, constant lc
4. Y Real GDP, constant lc
5. PY GDP Deflator, base year = 1.0
6. M1 Money Supply, lc
7. RS Three Month Interest Rate, percentage points
8. RB Long Term Interest Rate, percentage points
9. E or H Exchange Rate, lc per $ or lc per DM
10. F Three Month Forward Rate, lc per $
11. PX Export Price Index, 1990 = 1.0
12. W Nominal Wage Rate, base year = 1.0
13. J Employment, thousands
14. L1 Labor Forcemen, thousands
15. L2 Labor Forcewomen, thousands
Variables Determined by Identities:
I1. IM Total Imports (NIPA), constant lc
I2. EX Total Exports (NIPA), constant lc
I3. X Final Sales, constant lc
I4. V1 Inventory Investment, constant lc
I5. V Inventory Stock, constant lc
I6. S Current Account Balance, lc
I7. A Net Stock of Foreign Security and Reserve Holdings, lc
I8. M90$A Merchandise Imports from the Trade Share Calculations, 90 $
I9. EE Exchange Rate, end of period, lc per $
I12. UR Unemployment Rate
I13. JMIN Minimum Required Employment, thousands
I14. JJ Employment Population Ratio
I15. JJS Peak to Peak Interpolation of JJ
I16. Z Labor Constraint Variable
I17. YS Potential Y
I18. ZZ Demand Pressure Variable
I19. PM Import Price Index, 1990 = 1.0
I20. E or H Exchange Rate, lc per $ or lc per DM
I21. NW National Wealth, constant lc
I22. PX$ Export Price Index, $/90$
Variables Determined by the Trade Share Calculations:
L1 aij Trade Share Coefficients
L2 XX90$ij Merchandise Exports from i to j, 90$
L3. X90$ Total Merchandise Exports, 90$
L4. PMP Import Price Index, 1990 = 1.0
L5. PW$ World Price Index, $/90$
Exogenous Variables:
AF Level of the Armed Forces, thousands
EXDS Export Discrepancy, 90 lc
E90 E in 1990, 90 lc per 90 $
G Government Expenditures, constant lc
IMDS Import Discrepancy, 90 lc
JJP Peak to Peak Interpolation of JJ
LAM Peak to Peak Interpolation of Y/J
MS Non Merchandise Imports, 90 lc
M90$B Merchandise Imports from Countries other than
the 58 in the Trade Share Matrix, 90 $
PM90 PM in Base Year divided by PM in 1990
POP Population, millions
POP1 Population of men, thousands
POP2 Population of women, thousands
PSI1 Ratio of (EE + EE_{1})/2 to E
PSI2 Ratio of PM to PMP
PX90 PX in Base Year divided by PX in 1990
STAT NIPA Statistical Discrepancy
T Time Trend
TT Total Net Transfers, lc
XS Non Merchandise Exports, 90 lc
Notation:
lc local currency
90 lc 1990 local currency
constant lc local currency in the NIPA base year

Table B.2: The Variables
for a Given Country in Alphabetical Order 
Table B.2
The Variables for a Given Country in Alphabetical Order
Variable Eq.No. Description
aij L1 Share of i's merchandise exports to j out of total merchandise
imports of j. [See below.]
A I7 Net stock of foreign security and reserve holdings, end of
quarter, in lc. [A_{1} + S. Base value of zero used for the
quarter prior to the beginning of the data.]
AF exog Level of the armed forces in thousands. [OECD data.]
C 2 Personal consumption in constant lc. [OECD data or IFS96F/CPI.]
E 9 Exchange rate, average for the period, lc per $ . [IFSRF.]
EE I9 Exchange rate, end of period, lc per $ . [IFSAE.]
EX I2 Total exports (NIPA) in constant lc. [OECD data or (IFS90C
or IFS90N)/ PX.]
EXDS exog Discrepancy between NIPA export data and other export data
in 90 lc. [ EX  PX90(E90*X90$ + XS).]
E90 exog E in 1990, 90 lc per 90 $. [IFSRF in 1990.]
F 10 Three month forward exchnage rate, lc per $. [IFSB.]
G exog Government purchases of goods and services in constant lc.
[OECD data or (IFS91F or IFS91FF)/PY.] (Denoted GZ for
countries CO and TH.)
H 9 Exchange rate, average for the period, lc per DM. [E/E_{GE}]
I 3 Gross fixed investment in constant lc. [OECD data or IFS93/PY.]
IM I1 Total imports (NIPA) in constant lc. [OECD data or IFS98C/PM.]
IMDS exog Discrepancy between NIPA import data and other import data
in 90 lc. [IM  PM90(M + MS).]
J 13 Total employment in thousands. [OECD data or IFS67.]
JJ I14 Employment population ratio. [J/POP.]
JJP exog Peak to peak interpolation of JJ. [See Section 3.3.3.]
JJS I15 Ratio of JJ to JJP. [JJ/JJP.]
JMIN I13 Minimum amount of employment needed to produce Y in thousands.
[Y/LAM.]
LAM exog Peak to peak interpolation of Y/J . [See Section 3.3.3.]
L1 14 Labor force of men in thousands. [OECD data.]
L2 15 Labor force of women in thousands. [OECD data.]
M 1 Total merchandise imports (fob) in 90 lc. [IFS71V/PM.]
MS exog Other goods, services, and income (debit) in 90 lc, BOP data.
[(IFS77AED*E)/PM.]
M90$A I8 Merchandise imports (fob) from the trade share matrix in 90 $ .
[See below.]
M90$B exog Difference between total merchandise imports and merchandise
imports from the trade share matrix in 90 $ (i.e., imports
from countries other than the 44 in the trade share matrix).
[M/E90  M90$A.]
M1 6 Money supply in lc. [IFS34 or IFS34..B.]
NW I21 National Wealth in constant lc.
[NW_{1} + I + V1 + EX  IM. Base value of zero used
for the quarter prior to the beginning of the data.]
PM I19 Import price index, 1990 = 1.0. [IFS75/100.]
PMP L4 Import price index from DOT data, 1990 = 1.0. [See below.]
PM90 exog PM in the NIPA base year divided by PM in 1990.
POP exog Population in millions. [IFS99Z.]
POP1 exog Population of laborforceage men in thousands. [OECD data.]
POP2 exog Population of laborforceage women in thousands. [OECD data.]
PSI1 exog [(EE + EE_{1})/2]/E.]
PSI2 exog [PM/PMP.]
PW$ L5 World price index, $/90$. [See below.]
PX 11 Export price index, 1990 = 1.0. [IFS74/100. If no IFS74 data
for t, then PX_{t} = PX$_{t}*(E_{t}/E90_{t}, where
PX$_{t} is defined next.]
PX$ I22 Export price index, $/90$, 1990 = 1.0. [(E90*PX)/E. If no
IFS74 data at all, then PX$_{t} = PX_{USt} for all t.
If IFS74 data only from t through t+h, then for i>0,
PX$_{ti} = PX$_{t}*(PX_{USti}/PX_{USt}
and PX$_{t+h+i} = PX$_{t+h}*(PX_{USt+k+i}/PX_{USt}.
PX90 exog PX in the NIPA base year divided by PX in 1990.
PY 5 GDP or GNP deflator, equals 1.0 in the NIPA base year.
[OECD data or (IFS99B/IFS99B.P.]
RB 8 Long term interest rate, percentage points. [IFS61 or IFS61A.]
RS 7 Three month interest rate, percentage points. [IFS60 or
IFS60B or IFS60C or IFS60X.]
S I6 Total net goods, services, and transfers in lc. Current
account balance. [See Table B.7.] (Denoted SZ for
countries CO and TH.)
STAT exog Statistical discrepancy in constant lc. [YCIGEX+IMV1.]
T exog Time trend. [For quarterly data, 1 in 1952.1, 2 in 1952.2, etc.;
for annual data, 1 in 1952, 2 in 1953, etc.]
TT exog Total net transfers in lc. [See Table B.7.]
UR I12 Unemployment rate. [(L1 + L2  J)/(L1 + L2  AF).]
V I5 Stock of inventories, end of period, in constant lc. [V_{1} + V1.
Base value of zero was used for the period (quarter or year)
prior to the beginning of the data.]
V1 I4 Inventory investment in constant lc. [OECD data or IFS93I/PY.]
W 12 Nominal wage rate. [IFS65 or IFS65EY.]
X I3 Final sales in constant lc. [Y  V1.] (Denoted XZ for
country PE.)
XS exog Other goods, services, and income (credit) in 90 lc. BOP data.
[(IFS77ADD*E)/PX.]
X90$ L3 Merchandise exports from the trade share matrix in 90 $.
[See below.]
XX90$_{ij}L2 Merchandise exports from i to j in 90$.
[See below.]
Y 4 Real GDP or GNP in constant lc. [OECD data or IFS99A.P or
IFS99B.P or IFS99A.R or IFS99B.R.]
YS I17 Potential value of Y. [LAM*JJP*POP.]
Z I16 Labor constraint variable. [min(0, 1  JJP/JJ).]
ZZ I18 Demand pressure variable. [(YSY)/YS .]
Construction of variables related to the trade share matrix:
The raw data are:
XX$_{ij} Merchandise exports from i to j in $, i,j = 1,...,58
[DOT data. 0 value used if no data.]
X$_{i} Total merchandise exports (fob) in $. i = 1,...,39
[IFS70/E or IFS70D.]
The constructed variables are:
XX$_{i59} = X$_{i}  Sum^{58}_{j=1}XX$_{ij}, i = 1,...,39
XX90$_{ij} = XX$_{ij}/PX$_{i}, i = 1,...,39, j = 1,...,59
and i = 40,...,58, j = 1,...,58
M90$A_{i} = Sum^{58}_{j=1}XX90$_{ji}, i = 1,...,58; M90$A_{59} = Sum^{39}_{j=1}XX90$_{j59}
a_{ij} = XX90$_{ij}/M90$A_{j}, i = 1,...,39, j = 1,...,59 and i= 40,...,58,j= 1,...,58
X90$_{i} = Sum^{59}_{j=1}XX90$_{ij}, i = 1,...,39; X90$_{i} = Sum^{58}_{j=1}XX90$_{ij}, i=40,...,58
PMP_{i} = (E_{i}/E90_{i})Sum^{58}_{j=1}a_{ji}PX$_{j}, i = 1,...,39
PW$_{i} = (Sum^{58}_{j=1}PX$_{j}X90$_{j})/(Sum^{58}_{j=1}X90$_{j}), i = 1,...,39
An element in this summation is skipped if j = i. This
summation also excludes the oil exporting countries, which are
SA, VE, NI, AL, IA, IN, IQ, KU, LI, UA.
lc = local currency.
NIPA = national income and product accounts.
IFS xx = variable number xx from the IFS data.
Note: Variables available for trade share only countries are M90$A, PX$, X90$.

Table B.3 The Equations for a Given Country

Table B.3
The Equations for a Given Country
Stochastic Equations
LHS Var. Explanatory Variables
1. log(M/POP)
cnst, log(M/POP)_{1}, log(PY/PM), RS or RB, log(Y/POP),
[A/(PY*YS)]_{1}
2. log(C/POP)
cnst, log(C/POP)_{1}, RS or RB, log(Y/POP), [A/(PY*YS)]_{1}
3. logI
cnst, logI_{1}, logY, RS or RB
4. Y
cnst, Y_{1}, X, V_{1}
5. logPY
cnst, logPY_{1}, logW, logPM, DP, T
6. log[M1/(POP*PY)]
cnst, log[M1/(POP*PY)]_{1} or log[M1_{1}/(POP_{1}*PY)], RS, log(Y/POP)
7. RS
cnst, RS_{1}, 100[(PY/PY_{1} )^{4}  1], ZZ or JJS, [S/(PY*YS)]_{1},
RS_{GE}, RS_{US}
8. RB  RS_{2}
cnst, RB_{1}  RS_{2}, RS  RS_{2}, RS_{1}  RS_{2}
9. <>logE
cnst, logp  logE_{1}, logr, logs_{1}
9. <>logH
cnst, logp'  logH_{1}, logr', logs'_{1}
10. logF
logEE, logr
11. log[PX/(PW$*(E/E90))]
logPY  log(PW$*(E/E90))
12. logW
cnst, logW_{1}, logPY, DW, T, logPY_{1},
13. <>logJ
cnst, T, log(J/JMIN)_{1}, <>logY, <>logY_{1}
14. log(L1/POP1)
cnst, T, log(L1/POP1)_{1}, log(W/PY), Z
15. log(L2/POP2)
cnst, T, log(L2/POP2)_{1}, log(W/PY), Z
Notes:
i) The variables in equation 9 are:
p = PY/PY_{US}, p' = PY/PY_{GE},
r = [(1 + RS/100)/(1 + RS_{US}/100)]^{.25}, r' = [(1 + RS/100)/(1 + RS_{GE}/100)]^{.25},
s = [1 + S/(PY*YS)]/[1 + S_{US}/PX*YS_{US})], where PX is the US price index of firm sales
s' = [1 + S/(PY*YS)]/[1 + S_{GE}/PY_{GE}*YS_{GE})]
ii) In equation 10 r is the same variable as in equation 9.
iii) In equations 5 and 12 DP and DW are demand pressure variables.
See the discussion in Chapter 6 in Macroeconometric Modeling.
The following gives for each country the type of gap variable used
for DP and the functional form:
CA (gap2, linear), JA (gap2, nonlinear), AU (gap1, nonlinear),
FR (gap2, linear), GE (gap1, linear), IT (gap2, linear),
ST (gap2, linear), UK (UKUR, linear), FI (gap1, linear),
AS (gap2, nonlinear), BE (gap2, nonlinear), DE (gap2, nonlinear),
NO (gap2, linear), SW (gap2, nonlinear), GR (gap1, nonlinear),
IR (gap2, linear), PO (gap2, linear), SP (gap1, linear),
NE (gap1, linear), CO (gap1, linear), JO (gap2, linear),
MA (gap2, linear), Th (gap2, linear), CH (gap2, linear).
The following gives for each country the type of gap variable used
for DW and the functional form:
GE (gap1, linear), FI (gap1, nonlinear), KO (gap2, linear),
DE (gap2, nonlinear), NO (gap2, linear), SW (gap2, nonlinear),
SP (gap1, linear), NZ (gap1, nonlinear).
Identities
I1. IM = PM90(M + MS) + IMDS
I2. EX = PX90(E90*X90$ + XS) + EXDS
I3. X = C + I + G + EX  IM + STAT
I4. V1 = Y  X
I5. V = V_{1} + V1
I6. S = PX(E90*X90$ + XS)  PM(M + MS) + TT
I7. A = A_{1} + S
I8. M90$A = M/E90  M90$B
I9. EE = 2*PSI1*E  EE_{1}
I12. UR = (L1 + L2  J)/(L1 + L2  AF)
I13. JMIN = Y/LAM
I14. JJ = J/POP
I15. JJS = JJ/JJP
I16. Z = min(0, 1  JJP/JJ)
I17. YS = LAM*JJP*POP
I18. ZZ = (YS  Y)/YS
I19. PM = PSI2*PMP
I20. E = H*E_{GE} or H = E/E_{GE}
I21. NW = NW_{1} + I + V1 + EX  IM
I22. PX$ = (E90/E)*PX
Note: PX$ and M90$A are exogenous for trade share only countries
Variables Explained When the Countries are Linked Together (Table B.4)
L1. a_{ij}
L2 XX90$_{ij}
L3. X90$
L4. PMP
L5. PW$

Table B.4 Equations that Pertain to the Trade and Price
Links Among Countries

Table B.4
Equations that Pertain to the Trade and Price Links Among Countries
L1. a_{ij} = computed from trade share equations
L2. XX90$_{ij}= a_{ij}M90$A_{j}, i = 1,...,39, j = 1,...,59 and i = 40,...,58, j = 1,...,58
L3. X90$_{i} = Sum^{59}_{j=1}XX90$_{ij}, i = 1,...,39
X90$_{i} = Sum^{58}_{j=1}XX90$_{ij}, i = 40,...,58
L4. PMP_{i} = (E_{i}/E90_{i})Sum^{58}_{j=1}a_{ji}PX$_{j}, i = 1,...,39
L5. PW$_{i} = (Sum^{58}_{j=1}PX$_{j}X90$_{j})/(Sum^{58}_{j=1}X90$_{j}), i = 1,...,39
An element in this summation is skipped if j = i. This
summation also excludes the oil exporting countries, which are
SA, VE, NI, AL, IA, IN, IQ, KU, LI, UA.
Linking of the Annual and Quarterly Data
Quarterly data exist for all the trade share calculations, and all
these calculations are quarterly. Feeding into these calculations from
the annual models are predicted annual values of PX$_{i}, M90$A_{i},
and E_{i}. For each of these three variables the predicted value
for a given quarter was taken to be the predicted annual value multiplied
by the ratio of the actual quarterly value to the actual annual value.
This means in effect that the distribution of an annual value into its
quarterly values is taken to be exogenous.
Once the quarterly values have been computed from the trade share
calculations, the annual values of X90$_{i} that are needed for the
annual models are taken to be the sums of the quarterly values. Similarly,
the annual values of PMP_{i} and PW$_{i} are taken to be
the averages of the quarterly values.

Table B.5 Links Between
the US and ROW Models 
Table B.5
Links Between the US and ROW Models
The data on the variables for the United States that are needed when the
US model is imbedded in the MC model were collected as described in Table B.2.
These variables are (with the US subscript dropped): EXDS, IMDS, M, MS, M90$A,
M90$B, PM, PMP, PSI2, PW$, PX (= PX$), S, TT, XS, and X90$. The PX_{US} variable
here is not the same as the PX variable for the United States in Appendix A.
The variable here is denoted USPX in the MC2 model. The PX variable for
the United States is the price index of total sales of the firm sector.
Variable Determination
X90$_{US} Determined in Table B.4
PMP_{US} Determined in Table B.4
PW$_{US} Determined in Table B.4
PX_{US} Determined by an equation that is equivalent
to equation 11 for the other countries. See the discussion
in Section 1.4 of The MC2 Model Workbook.
PEX = DEL3*PX_{US}. In the US model by itself, PEX
is determined as PSI1*PX, which is equation 32 in Table A.2.
This equation is dropped when the US model is linked to
the ROW model. DEL3 is constructed from the data as
PEX/PX_{US} and is taken to be exogenous.
PM_{US} = PSI2_{US}*PMP_{US}. This is the same as equation I19
for the other countries.
PIM = DEL4*PM_{US}. PIM is an exogenous variable in the
US model by itself. DEL4 is constructed from the data as
PIM/PM_{US} and is taken to be exogenous.
EX = (X90$_{US} + XS_{US} + EXDS_{US})/1000.
This is the same as equation I2 for the other countries.
EX is an exogenous variable in the US model by itself. EXDS_{US}
is constructed from the data as 1000*EXX90$_{US}  XS_{US}
and is taken to be exogenous.
M_{US} = 1000*IM  MS_{US}  IMDS_{US}. This is the
same as equation I1 for the other countries. IMDS_{US} is
constructed from the data as 1000*IM  M_{US}  MS_{US}
and is taken to be exogenous.
M90$A_{US} = M_{US}  M90$B_{US}. This is the same as
equation I8 for the other countries.
S_{US} = PX_{US}(X90$_{US} + XS_{US})  PM_{US}(M_{US} + MS_{US}) + TT_{US}.
This is the same as equation I6 for the other countries.
Note:
The new exogenous variables for the US model when it is linked to the
ROW model are DEL3, DEL4, EXDS_{US}, IMDS_{US}, M90$B_{US}, MS_{US}, PSI2_{US}, TT_{US}, and XS_{US}.
EX and PIM are exogenous in the US model by itself, but endogenous when the US model
is linked to the ROW model.

Table B.6 The Procedure Used to Create Quarterly Data
from Annual Data

Table B.6
The Procedure Used to Create Quarterly Data from Annual Data
Let y_{t} be the (observed) average value of the variable for year t,
and let y_{it} be the (unobserved) average value of the variable for
quarter i of year t (i = 1, 2, 3, 4). Then:
(i) y_{1t} + y_{2t} + y_{3t} + y_{4t} = q^{.}y_{t}
where
1 for flow variables (at quarterly rates)
q =
4 for stock variables and price variables
Assume that the annual data begin in year 1, and let q^{.}y_{1} = a_{1},
q^{.}y_{2} = a_{2}, q^{.}y_{3} = a_{3}, ... The key assumption is that the four quarterly
changes within the year are the same:
d_{2} for t = 1,2
(ii) y_{1t}  y_{4t}1 = y_{2t}  y_{1t} = y_{3t}  y_{2t} = y_{4t}  y_{3t} =
d_{t} for t = 3,...
Given i and ii for t = 1,2, one can solve for y_{40} and d_{2} in terms of a_{1} and a_{2}:
y_{40} = (13/32)a_{1}  (5/32)a_{2}
d_{2} = (a_{2}  a_{1})/16
Using y_{40} and d_{2}, one can then construct quarterly data for
years 1 and 2 using ii. Given y_{42} from these calculations and given i
and ii for t=3, one can solve for d_{3} in terms of a_{3} and y_{42}:
d_{3} = (a_{3}  4y_{42})/10
Using y_{42} and d_{3}, one can then construct quarterly data for year 3.
One can then solve for d_{4} in terms of y_{43} and a_{4}, and so on.
Note:
The annual population data that were collected for the model are mid
year estimates. In order to apply the above procedure to these data, the
assumption was made that the average value for the year equals the mid
year value.

Table B.7 Construction of the Balance of Payments Data:
Data for S and TT

Table B.7
Construction of the Balance of Payments Data: Data for S and TT
The relevant raw data variables are:
M$' Goods imports (fob) in $, BOP data. [IFS78ABD.]
M$ Goods imports (fob) in $. [IFS71V/E.]
X$' Goods exports (fob) in $, BOP data. [IFS78AAD.]
X$ Goods exports (fob) in $. [IFS70/E.]
MS$ Services and income (debit) in $, BOP data. [IFS78AED + IFS78AHD.]
XS$ Services and income (credit) in $, BOP data. [IFS78ADD + IFS78AGD.]
XT$ Current transfers, n.i.e., (credit) in $ BOP data. [IFS78AJD.]
MT$ Current transfers, n.i.e., (debit) in $ BOP data. [IFS78AKD.]
 When quarterly data on all the above variables were available,
then S$ and TT$ were constructed as:
(i) S$ = X$' + XS$  M$'  MS$ + XT$  MT$
(ii) TT$ = S$  X$  XS$ + M$ + MS$
where S$ is total net goods, services, and transfers in $ (balance of
payments on current account) and TT$ is total net transfers in $.
 When only annual data on M$' were available and quarterly
data were needed, interpolated quarterly data were constructed using
M$. Similarly for MS$.
When only annual data on X$' were available and quarterly data
were needed, interpolated quarterly data were constructed using X$.
Similarly for XS$, XT$, and MT$.
When no data on M$' were available, then M$' was taken to be
q.M$, where q is the last observed value of M$'/M$.
Similarly for MS$ (where q is the last observed annual value of MS$/M$.)
When no data on X$' were available, then X$' was taken to be q.X$,
where q is the last observed value of X$'/X$. Similarly for XS$ (where
q is the last observed annual value of XS$/X$), for XT$ (where q is the
last observed annual value of XT$/X$), and for MT$ (where q is the last
observed annual value of MT$/X$).
Equations i and ii were then used to construct quarterly data for S$ and TT$.

After data on S$ and TT$ were constructed, data on S and TT were
constructed as:
(iii) S = E*S$
(iv) TT = E*TT$

Note from MS and XS in Table B.2 and from MS$ and XS$ above that
(v) MS$ = (PM*MS)/E
(vi) XS$ = (PX*XS)/E
Note also from Table B.2 that
(vii) M$ = (PM*M)/E
(viii) X$ = (E90*PX*X90$)/E
Therefore, from equations iivii, the equation for S can be written
S = PX(E90*X90$ + XS)  PM(M + MS) + TT
which is equation I6 in Table B.3.
