Iraq Oil Revenue Forecasting Model — A Critical Assessment

By Ahmed Mousa Jiyad.

Any opinions expressed are those of the author, and do not necessarily reflect the views of Iraq Business News.

Iraq Revenue Forecasting Model — A Critical Assessment

INTRODUCTION

This review was prepared upon request from known international organization (XXX) regarding two documents prepared by a consultant (CCC) on Iraq Revenue Forecasting Model, and it comprises the following items: Background, which provides brief information on the deadline and the two documents; the Review Objective Criteria, which guides the assessment of the two documents by using six criterion; the Details of the Review comprises two parts corresponding to the two documents and finally the Review Assessment Matrix, which explains and calculate the final score rate for the two documents.

BACKGROUND

After a few email exchanges (XXX) posted two documents on 3 May 2021 and requested the peer review to be delivered by COB on 11 May. The first document entitled “EXPLANATORY NOTE OF IRAQ REVENUE FORECASTING MODEL” is in MS Word; hereinafter referred to as “EXPNOTE”, while the other is in MS Excel Sheet; hereinafter referred to as “EXLSHEET”.

The “EXLSHEET” comprises 22 Sheets and they differ in contents, length and size; they are referred to by their coded-names that appear in the bottom margin of the “EXLSHEET”.

(XXX) email mentions, “The model is currently being reviewed by partners before being shared with the Iraq entity (EEE) and its stakeholders in the Ministry of Oil and international oil companies.”

My assessment was delivered before the deadline and I suggested to share it with the consultant for further consideration, and requested permission to publish my assessment. (XXX) promised to share it with the consultant and asked me to wait for a couple of months before publishing it; it is today 14 December or more than seven months.

For ethical norms and considerations the names of the international organization (XXX), the consultant (CCC), the Iraq entity (EEE) and relevant entities (PPPPPPPPP) in Iraq are not disclosed.

Peer Review Objective Criteria

To conduct the peer review for the “EXPNOTE” and all 22 sheets in the “EXLSHEET” I formulated and was guided by the following criteria:

The conformity and adherence of the two documents to an acceptable standard for consultancy service regarding topics related to upstream petroleum; such standard relates to style, format, substance and research and consulting service ethics;
The qualitative aspects of the consultant methodology, strength of arguments, analysis consistency and coherence; the accuracy, validity, relevance of inputs, particularly used data; quality control of the computation, charts and contents of the “EXLSHEET”;
The “add-value/ knowledge impact” for the intended client, particularly the usefulness of the entire consulting assignment to relevant entities (PPPPPPPPP) in Iraq;
The consultant work is basically relating to 11 oil projects, hence, the work and findings of the consultant was assessed according to the contractual provisions of the related signed contracts; and also since the above mentioned Iraqi entities and IOCs are the direct parties to these contracts.
Also the consultant dwelled heavily on export price and revenues, thus the analysis and finding will be assessed comparative to SOMO’s price setting mechanisms, markets configuration and marketing modalities. Such comparative assessment complies with verification and evidence-based consulting and research methodology;
The test of reality vs. expectation. Experience with modelling and forecasting indicates that reality seldom coincides with expectation. Hence, the consultant’ “forecasting the past” will be tested against actual, historical official data regarding oil production, oil export, oil prices and oil export revenues. The outcome of reality vs. expectation test has implications for assessing the usefulness and reliability of forecasting the future by the same proposed model.

DETAILS OF THE PEER REVIEW

Part one:

EXPLANATORY NOTE OF IRAQ REVENUE FORECASTING MODEL- “EXPNOTE”

The Following remarks are made after deep and thorough examination of “EXPNOTE” text:

This document is by definition an explanatory note, but where is the main report for this assignment? Usually, consulting assignment of quantitative nature comprises a main report, annexes, explanatory note and references. Hence, something was missing and neither the explanatory note nor annexes, in this case the “EXLSHEET”, replaces the main report!!. The consultant seems to apply “trust me” this is a model for forecasting Iraq’s revenue even without specifying, at the outset, what type of revenue!!
“EXPNOTE” says, “The model is built according to the FAST standard of financial modelling”. But what FAST stand for, what are its standard of financial modelling and are the standard peculiar to upstream petroleum or for general purpose!! Does FAST has mathematical, statistical specific format or it is just a computation process using Excel facilities? Is there any reference to FAST and evidence supportive to its usefulness for upstream petroleum projects? Hence, the Model is not provided and FAST modelling is unknown; this is methodological flaw.
One of the model two purposes is to “forecast the past”!!! This is both surprising and erroneous since detailed data on oil production, oil exports and oil production is available on monthly bases since mid-2007! so what is the need to forecast the past??; this not only manifests lack of information on the part of the consultant, but also seems the consultant had committed serious error of judgement, as might be interpreted to reflects arrogance, pompousness mentality thinking, “we know it better than you”!!!!!Further discussion on the validity, reliability and test of “forecast the past” is provided in Part Two below.
“EXPNOTE” states, “although SOMO publishes export sales, these figures are before the recovery of costs and payment of fees to the operating companies”. There are many flaws in such invalid statement: first; SOMO is oil marketing company while cost recovery and payment of fees to IOCs are the responsibility of other entities within the Ministry of Oil-MoO and they are paid in accordance with the related service contracts; second, SOMO export reports are monthly, while payment to IOCs are on quarterly base after auditing and verification of invoices presented in the previous quarter; third, most payment to IOCs are made in kind as per contract provision and oil lifting protocol that is elaborated in each oilfield related service contract (in Addendums two and four). It appears the consultant is not familiar with the technicalities and contractual provisions relating to SOMO’ export reporting and MoO payment to IOCs;
The consultant uses long and tedious calculations to “estimate production which is not exported.” On this I have the following remarks: first, data on oil production and allocation between export and domestic demand has been available for years and they are published on monthly bases. Therefore, there is absolutely no need to estimate what is already available. Second, the approach of “factor the field-level synthesised estimates of production against recorded exports” is conceptually and methodologically incorrect and third, as we shall see and prove that the consultant computation and estimate of production not exported was totally wrong and based on inaccurate understanding (see item 11 in Part Two below). Hence, the consultant argument for “estimate production which is not exported” is not valid and misleading and the computation model is wrong. For example the consultant model estimates 32% of production in February 2021 was for domestic consumption, while actual formal data shows only 12.21% during same month, indicating a margin of error in the consultant model of 148.32%; unusual high error margin in testing the model estimation against actual reality. Therefore, all what is written in “Estimating Production: synthesised field-level production estimates” fail the test of accuracy, validity and relevance.
In “Estimating Price”, the consultant refers to “discounts for Iraqi crudes”. Data and SOMO monthly price setting mechanism disapprove such assertion. SOMO uses different «price formulas” each has its own qualitative variables API, Sulphur content, destination and Marker crude; discounts and premiums are dependent on marketing conditions, in addition to special formula for Jordan, and almost two shipment a month, 2mb each, sold on spot platform that gives “extra price” compared to the usual “term contract” for that particular month. It appears the consultant knows very little about SOMOs oil price setting modalities. Further remarks will be provided later when comparing consultant price estimation to SOMO’s export price (See items 3, 5, 9 and 10 in Part Two below)
The model estimation reported under, “Current Results”, are all wrong because the estimated export sales for 2020 were much higher than actual official export revenues (see further details on the Dashboard Sheet in in Part Two below). Again, the model estimation fails under the test of comparison with actual data: i.e., reality.
The consultant argument regarding “Basra-Ceyhan differentials” is weak, vague. irrelevant and not convincing for the following reasons: first it is not specific whether the consultant argument is related to volume or value of export; second, due to pipeline problem Iraq export through Ceyhan have been very limited (according to final official export data for the first quarter this year 96.239% of Iraqi oil was exported from Basra, generating 96.341% of total oil export revenues); third, State Budget Law 2021 obliges KRG to deliver, at SOMO export price, 250000 per day. Hence the consultant is apparently unaware of these facts!!!
The information and argument presented by the consultant regarding the “R-factor” are also inconsistent, misleading and inaccurate; first, the consultant says “details of the terms of the R-factor are not available”: this is not true as articles addressing this issue and computation of its impact were available on the public domain since 2010!!. Second, disregarding R-factor reduces government take and thus, increases the disparity between actual government take and “net to the government” as called by the consultant; third, the reference to “Faihaa field” is misleading and disingenuous since the field was offered under BR4 (exploration blocks) and it is at very early stage of development and, thus, its contribution to total oil production is very insignificant to have an impact: in the meantime the consultant ignores other important sources of revenues (see next items 10, 11 and 12). Finally, the claim that the analysis “shows a potential margin of error of a maximum of 1.63%” is baseless and deceptive (see item 8 regarding “Analysis Sheet” in Part Two below)
The assignment did not attempt to estimate government revenues from domestically consumed oil!! No reason was provided!! Why, then, the consultant used time and efforts to “synthesized production” when related data are already available on the public domain?? Finally why and in what way domestic revenues impact “Margins of Uncertainty” in the model computation??
Both documents exclude oil production from field managed by National Effort, especially those not contracted to IOCs under the four bid rounds. Also they did not cover two oilfields offered under BR2. It is not clear why the consultant excludes these oilfields and did not say a word about them?? Ignoring oilfields managed by national efforts has significant role in underestimating government revenues and thus, such exclusion is serious flaw.
Also both documents do not include production and export revenues for LPG, NGL, Naphtha and Fuel oil. Why these are out of the consultant scope is unclear, though data on these items is available on the public domain. Again, ignoring them is additional shortcoming of the two documents.
Throughout the two documents data selection and referencing them raises further concerns. Professionally and methodologically it is vital to differentiate between convenient “selectivity” and “thoroughness“. Briefly, when data are available on the public domain but are not used or referred to by the consultant that reflects serious professional weakness, unethical, and manifest lake of thoroughness; i.e., the consultant should have searched thoroughly for the related and relevant data. When data are available on the public domain but are not used by the consultant, instead the consultant “synthesised” or “forecast the past” based on wrong premises and inaccurate understanding of the basic issues, that resembles serious infringement of methodological, professional and research ethics. When the consultant present limited selective referencing to data (mostly in the “EXLSHEET” document) that only reflect convenience for the consultant. Moreover, when that selective referencing is not related to the computed item (e.g. WQ1 “EXLSHEET”: Row 35 vs. Row 59) causes confusion for the intended client or user!!
“EXPNOTE” asserts,”The model is designed to be updated”. But all hundreds, if not thousands, cells in the “EXLSHEET” that contains computable values are codified pursuant to MS Excel program, e.g. all cells in WQ1 “EXLSHEET”: Row 66 to Row 72. To update the model these cells should be changed and, thus, the intended client and user must have good and professional experience with MS Excel; this is highly unlikely. If the clients (e.g., PPPPPPPPP) have good and professional specialists with MS Excel, they could use their model, since there is nothing intrinsic about “EXPNOTE” and “EXLSHEET”. For example the clients specialists can use the “Formulas” offered by MS Excel program and the good data they do have already; they could, then, arrive at more valuable, consistent, tested and acceptable results, much better than “EXPNOTE” and “EXLSHEET” offer!.
All above mentioned remarks, shed serious doubt on the entire work of this consultant, and, hence, limits its value or add knowledge to the intended clients. This view is further enhanced by more remarks on the “EXLSHEET” as summarised in the following part two.

Part Two: Reviewing “EXLSHEET”

“EXLSHEET” comprises 22 Sheets and they differ in contents, length and size; they are referred to by their coded-names that appear in the bottom margin of the “EXLSHEET” document.

By going through all of them prompted me to register large number of notes, remarks and questions; the more I read and check, the more I became concerned about the contents of the spreadsheets. Thorough and complete review and checking is daunting task and requires much longer time than (XXX) deadline permits. Hence, the following is very condensed peer review of “EXLSHEET”.

1- Excel Sheet “SynthProd” provide a chart titled “Iraq: synthesized field production profile”. The following remarks are made on this sheet: A- there is no “Missan” field; what is there (according to first bid round- BR1) three oilfields in Missan province that were contracted under one contract while they have different profiles and locations (the consultant provides no note on this and thus gives the impression as if it is one field); B- it ignores oilfields developed and managed by National Efforts”; C- it excludes two fields offered under BR2!!! D- as shall be discovered later (see item 11 in part two below) all such synthesized field production profiles were based on wrong premised computations, and this raises serious research and consulting ethical questions and standard.

2- Excel Sheet “RP- Brent”. Many observations are register on this sheet: A- chart titles are missing; B- “Y & X” axis titles and their unites of measurement are missing; C- one chart hast two trend lines and equations without specifying which is which; D- R² values for the two equations are very low, indicating weak statistical significance. E- Moreover, the table has no title, no unit of measurement and what “Y” and the other two columns represent???? F- These are simple trend-line equations that are computed instantly/automatically by Excel sheet, but the consultant provides absolutely no explanation or notes on the usefulness of these equations and used them regardless; G- the intended client and user have to wonder what these charts and table are about!! Hence, this is serious professional flaw and the sheet has zero value for the client!!

3- Excel Sheet “Brent vs. realised “. Questions on this sheet are: A- which “Brent” was it: dated, futures or spot ( such as the monthly EIA’ STOE or S&P Platts or Argus etc.)?; B- what is the source for the data?; C- for “SOMO weighted realized price” what is/ are the used “weights”, why and what is the source for the used “weights”?; D- how the “SOMO weighted realized price” is different from “SOMO published export prices”?; E- finally what about “Brent” was it also weighted, by what weight or no and why!!!

4- Excel Sheet “Production”. Remarks on this sheet are: A- unit of measurement is missing; B- what is the consultant explanation of an illogical contradiction that SOMO exports were higher than the “Synthesized Production” prior to 01.01.2012, as this shed serious doubt on the consultant calculation??; C- what is the consultant explanation of the odd event as per 01.01.2015 when SOMO Export up while EIA production down compared with previous year??; D- also the consultant fails to explain why the “Synthesized Production” was higher than EIA production during 2014!!

All that reflect the mechanical manner in preparing the synthesized production without considering well-known major events that impacted Iraq’ production and export!!

5- Excel Sheet “Revenues” calls for the following remarks and questions: A- chart title is ambiguous: does it refer to “total” or “oil export” or “oil sector” revenues; B- the details of IMF and EITI references are missing; C- was it IEITI or EITI ????; D- the consultant did not explain the pattern of all three data sets: why “EITI” data are higher than both IMF and SOMO during 2010-13, then it turns lower than both during 2014-16, then goes above both after 2016, when IEITI revenue data are provided by SOMO!! Can this be explained by the mixing up, by the consultant, of the usual differences between the “preliminary” and “final” SOMO’s monthly data??!!

6- Excel Sheet “Time-Esc”: this seems to be a templet Sheet for calculations. But comments and clarifications are missing, no definition of terms and acronyms are provided and some components such as discount rate, discount type, inflation rate and index are not used or referred to in other excel sheets; so what is the justification for having and computing them in abstract!! Ironically, some of these rates were computed up to 1 November 2025 (e.g., Rows: 61 and 62 on “inflation index” without specifying whether this applies to “cost recovery” or “oil price” or both; Rows: 71 and 72 on “Discounting rate” without specifying to which cash flow this applies)

The “Timing” rows (from day one of the month to last day) is repeated many times in this sheet and also in all other sheets: this format is totally unnecessary (it could be replaced easily by the name of the month) and, together with other components in this “Time-Esc” could overwhelm the user or the intended client with too many inputs, too much computations and extremely large number of codified cells.

This templet sheet manifests and could also explain the mechanical application of MS Excel by the consultant!!

7- Oilfield Excel Sheets. Most of the remarks mentioned above are generated from the Excel Sheets for the 11 covered oilfields. A comprehensive peer review of each of these sheets takes much longer time. But a quick checking reveals many flaws and shortcomings that shed serious doubt on the accuracy of the entire work.

For example Excel Sheet for Zubair’ Row 136 it was written “”Rumaila daily production”; what Rumaila has to do with Zubair oil production!!!!???? Moreover, “daily production” and “incremental production” Rows: 136, 137 and 139 were assumed to be constant for two years: from 01.01.2020 to 31.12.2022; this is totally against a declared policy by the Ministry of Oil-MoO. The inserted data in Row 148 relates to “IOC Remuneration fee”; it is totally wrong; the consultant was not informed about the changes in the Zubair consortium composition!! Moreover, why the values change when both, “daily production” and “incremental production” were assumed constant!!?? Also what is the difference between “SOC payment to Treasury” (Row 162 which has “45%” of what? but no values inserted in the row) and “SOC Transfer to Treasury” (Row 163, which shows fluctuating values during the entire period despite constant “daily production” and “incremental production”!!! Finally, the consultant provides no further notes on the fiscal system for Zubair oilfields that reflects the situation as on 2020.

The case for Majnoon oilfield is even more disturbing. In addition to all remarks I made above regarding Zubair oilfield are also valid here, the consultant seems unaware that Majnoon oilfield has been relinquished since 2018 and is now developed under the national efforts. This means no cost recovery and remuneration fee to IOC and thus all calculations are invalid and have absolutely zero value. This manifests the mechanical use of MS Excel by the consultant without full, updated and correct understanding of the fiscal system of the upstream petroleum under Iraq’ long term service contracts.

8- Excel Sheet “Analysis”. This is the core sheet for the entire calculations, and it is the largest sheet with column number reaches (FJ) and 554 rows. Thus it deserves careful attention and requires much more time to go through it thoroughly, but based on the below remarks, this sheet causes much concern and raises too many questions and remarks.

The sheet begins with confusion: in Row 1 written “RUMAILA”, but the remaining rows are not confined to Rumaila oilfield!!!.

All data for rows 10 to 20 are or could be wrong; they cannot be in “mbpd”!!!!!!????;

All oilfields offered under first bid round- BR1 were producing on 1.01.2010; therefore the data for 2010 for those oilfields are wrong because each of those fields has “baseline production”, which the consultant excluded them;

Data for rows 10 to 20 are labeled “Historical production”, while data for rows 38 to 49 are labeled “Synthesised production”, but the data are exactly the same to the last digit!! So what is the difference between the two sets of data??? As this causes confusion and also generates and replication consequences on the entire work, calculation and the chart in the consultant Excel spreadsheet;

All data in row 62 are or could be wrong; they cannot be in “mbpd”, and most likely the individual who prepared this Excel spreadsheet is not careful in selecting the “unit of measurement” or inconsistent in using defined acronyms and in using number format for Excel spreadsheet (i.e., a difference between “1066 and 1,066 since 1.066 is not permitted).

A major problem with this Excel Sheet “Analysis” is that it replicates or recycles all type of flaws that are identified in all the 22 Excel Sheets, particularly those related to specific oilfields, oil prices and oil production.

The magnitude of flaws, ambiguities, inaccuracies and absence of explanations in this core spread sheet manifest alarming poor quality control of the entire work under review!!

9- Oil price in Oilfield Excel Sheet. For example “Missan” data on oil “Price” of the related oilfield: rows 103, 104 and 105 and on “Fiscal Regime” (a misconception of revenues!!!! in row 110 (another confused data unit of measurement).

All oilfields covered by their related Excel Sheet have exactly the same oil prices; this “all fields same price” is absolutely not possible, and thus seriously wrong, since these oil fields produce crudes that are qualitatively different in terms of gravity (API), Sulphur contents and other particulars. The implications of this wrong price estimation should cause serious concerns because the contractual deemed revenues-DR depends largely on the quality of the crude and DR decides the cost recovery. Moreover, DR is, again contractually, is measured at the “delivery point” on the boarder of the oilfield not at the export terminal. Hence, the consultant approach to use unified set of oil price for all oilfields and for the covered period was not only wrong but also leads to higher amount of cost recovery; this is very serious flaw with damaging implications.

10- Another flaw is related to Basra oil price: in Excel Sheet “Mth Inputs” Row 15 the consultant uses “Basra oil price” and in Row 27 uses “Basra light”; but both price sets are identical. From oil marketing this is also wrong and not possible. In reality Iraq markets three qualitatively different crudes from the southern exports outlet: Basra Light, Basra Medium and Basra Heavy, and each have different prices whether that through the usual “Term Contract” or through the monthly limited direct/spot sales.

Finally, the differentials between “Basra light” prices and “all fields same price” was very thin and in five months it was even negative, i.e., “Basra light” prices was lower than “all fields same price”; this almost impossible oil marketing scenario adds more doubt on the professional competence and quality of the consulting work.

11- All calculations relating to the “Incremental production”, (Row 137) in the Excel Sheets for Halfaya, for Gharraf, WQ2, Badra and Majnoon (under BR2), Faihaa (BR4) and Ahdab (converted contract prior to BR1), are wrong since they contravene the related contracts, which has no incremental production. Moreover, the computation equations for the cells in the said row are wrong technically and geologically since it assumes a lasting initial production, i.e. no natural decline!!! As for Rumaila, WQ1, Zubair and the 3 Missan fields (under BR1) all are also wrong since they contravene the related contractual provisions; which has annual natural decline rate of the base-line (initial) production!!!

These wrong calculations lead, logically and practically, to underestimation of fields development efforts and their production, to wrong estimation of cost recovery and remuneration fee for all covered oilfields; what was premised on wrong understanding produces wrong results and, thus, should be disregarded.

12- The “Dashboard” Sheet contains selected charts from other sheets; thus all remarks made on these sheets are valid here. In other words, this “Dashboard” Sheet replicates all flaws, wrong calculations, misconceptions and inaccuracies (The reader is highly advised to see the comments made on Excel Sheets that are reproduced in this “Dashboard” Sheet).

In addition, the following remarks are made on this “Dashboard” Sheet: the “table” referred to in G6 was not provided!!; “Brent Futures Price Scenario” was not explained; the table (on Rows18 to 34) has no unit of measurement; the estimated export sales for 2020 is much higher than actual export oil revenues officially announced by SOMO/MoO by 22.4%. When estimation against actual (historical) data results in such margin of error, that margin of error could be even higher in forecasting the future!!!

Moreover, the cells in Rows 51 to 55 look mysterious with absolutely no explanation or clarifications:

Finally, as was the case with “Analysis” sheet, “Dashboard” sheet replicates or recycles all type of flaws that are identified on the reproduced charts.

13- Operating cost was not mentioned in the two documents “EXPNOTE” and “EXLSHEET”. Not a single row in any of the field’ related sheets mentions the operating cost for oil produced in the related field. The consultant provides no explanation for excluding this significant cost item from estimating government revenues.

Ignoring operating cost is a major and additional flaw that reduces further the soundness and usefulness of “EXPNOTE” and “EXLSHEET”.

14- All Excel sheets and their components could overwhelm (intimidate) the user or the intended client with too many inputs, too much repetition, too much computations and extremely large number of codified cells. One cannot speculate whether that was intentional or due to professional deficiency on the part of the consultant; but, it is highly likely that the current version of “EXPNOTE” and “EXLSHEET” has very limited value, if any, to the user or the intended clients in Iraq.

The Review Assessment Matrix

This final part intends to summarise the result of assessing both documents, “EXPNOTE” and “EXLSHEET” that were presented by the consultant. The following matrix was premised on the six objective criteria mentioned earlier and the evaluation score for each criterion.

The score ranges from (1), which means “bad”, through (3), which means “acceptable but not satisfactory” to (5), which means “very good”.

The six criteria have equall values, and each score was decided in the light of the above details in this peer review:

Total score under the six criteria ranges from total minimum 6 to total maximum 30 and final score rate (%) is the total gained score to maximum score:

Score rate under 50% means unfavourable assessment of the two documents, which means rejecting the consultant work and should not share it with the user or the intended clients;

Score rate at 50% means the work is acceptable but should be revised to address satisfactorily all what the peer review says before sharing it with the user or the intended clients;

Finally, score over 50% means accepting consultant work and recommends sharing it with the intended user or the intended clients.

Criteria/ Score Matrix

Peer Review Objective Criteria/ Score	1	2	3	4	5
Conformity with acceptable standard for consultancy service		2
The qualitative aspects of the consultant methodology		2
The “add-value/ knowledge impact” for the intended client		2
The contractual provisions relating to the 11 projects	1
SOMO’s price setting mechanisms and marketing modalities.	1
The test of reality vs. expectation	1
Total Score	3	6	0	0	0
Final Score Rate	((3+6)/30)=30%

The final score rate is 30%, which corresponds to 1.5 on the scale from 1 to 5.

Regretfully, this overall low score indicates that the standard, quality and usefulness of the consultant work are much less than acceptable level.

In an extensive communication with well-respected oil professional and two times oil minister, I learned that the Ministry of Oil has good Ashtar program, which seems to be by far more superior and well-functioning than this “EXLSHEET”; with the presence of Ashtar, the consultancy and its two documents, “EXPNOTE” and “EXLSHEET”, become redundant for the clients in Iraq.

Mr Jiyad is an independent development consultant, scholar and Associate with the former Centre for Global Energy Studies (CGES), London. He was formerly a senior economist with the Iraq National Oil Company and Iraq’s Ministry of Oil, Chief Expert for the Council of Ministers, Director at the Ministry of Trade, and International Specialist with UN organizations in Uganda, Sudan and Jordan. He is now based in Norway (Email: mou-jiya(at)online.no, Skype ID: Ahmed Mousa Jiyad). Read more of Mr Jiyad’s biography here.

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