A. Action Plan

6. The Action Plan presented below, which outlines the principal recommendations arising from the mission’s work, was discussed and cleared with the CBU management. The mission believes that the timelines and scope of the tasks to be performed are acceptable to the ESS compilers.

Priority scale: H – High, M – Medium, O – Other

Priority	Action/Milestone	Target Completion Date
Outcome: Data are compiled and disseminated using appropriate statistical techniques, including those that deal with data sources, and/or assessment and validation of intermediate data and statistical outputs
H	Correct the methodology for calculating operations involving direct investment shareholder capital for nonfinancial corporations and reflect the results obtained in the balance of payments.	February 2020
H	Correct the methodology for calculating operations involving portfolio investment shareholder capital for nonfinancial corporations and reflect the results obtained in the balance of payments.	February 2020
H	Correct the methodology for calculating operations involving reinvested income for nonfinancial corporations and reflect the results obtained in the balance of payments.	February 2020
H	Correct the methodology for calculating operations involving reinvested income for financial corporations and reflect the results obtained in the balance of payments.	Completed during the mission
H	Reflect forgiveness of nonguaranteed private debt in BOP operations.	February 2020
H	Introduce additional lines to the report forms for insurance and leasing companies and correct the methodology for calculating intercompany loans based on banking information.	February 2020
M	Reflect income on SDR allocations and holdings on a gross basis in primary income.	Completed during the mission Carried over from the previous mission’s plan
M	For banking information on nonguaranteed private sector debt, in each specific debt restructuring case contact the bank providing the given information and clarify all of the details involved in the restructuring. Make the relevant corrections on the basis of the information obtained.	Regularly
H	Remove capitalization of accrued interest and the restructuring of principal and interest into shareholder capital from other changes and reflect them in balance of payments operations.	February 2020
H	Prior to the conversion of external debt data in the settlement currency, check the compatibility of the data and in the event that inconsistencies are found, identify the reason for the discrepancies and eliminate them in accordance with the mission’s recommendations.	Regularly
H	Compare data on foreign direct investment obtained from the ITRS and from the SSC at the company level and identify reasons for discrepancies.	May 2020
H	Divide trade credits obtained through the special bank system for the recording of cross-border accounts payable/receivable into trade credits between affiliated companies and other trade credits.	December 2020
H	Adjust imports based on an analysis of import prices.	May 2020
H	Collect additional data from ministries, agencies, state-owned corporations, and commercial banks on cross-border transactions performed in 2014–2015.	December 2019
H	Revise and update BOP data for 2014–15 in BPM6 format, drawing on the Ministry of Economy’s original estimates, and on additional data sources identified.	March 2020
Outcome: Source data are adequate for the compilation of external sector statistics
H	Agree with the Ministry of Finance the format for submitting data on the principal and interest payment schedule for government and government-guaranteed debt.	February 2020
H	Include a field in the interim ITRS database for the institutional sector according to the mission’s recommendations.	February 2020
M	Analyze the data received from commercial banks and identify coding errors. Bring bank representatives together once per quarter to discuss typical errors made in ITRS coding.	Regularly, starting in February 2020
H	Make additions to the list of ITRS codes according to the mission’s recommendations and correct the text in terms of the name and application of the codes.	January 2020
H	Extend ITRS to the CBU segment.	May 2020
M	Continually update the list of nonfinancial corporations involved in foreign trade activity to include them in the survey of nonfinancial sector foreign economic activity.	Regularly Quarterly Carried over from the previous mission’s plan
M	Organize a comparison of trade credits obtained from the State Statistics Committee and from the bank system for the recording of cross-border accounts payable/receivable at the level of individual companies.	December 2020
H	Develop a file for the calculation of government Eurobonds according to the mission’s recommendations.	Completed during the mission
H	Develop a file for the calculation of operations and balances of SDR allocations and holdings (including accrued interest) in line with the mission’s recommendations.	Completed during the mission
H	Organize the compilation of external debt statistics in accordance with the standards of the External Debt Statistics Guide (2013 edition).	March 2020
H	Prepare mirror statistics to estimate unrecorded import and export transactions.	Regularly
H	Request data from commercial banks on trade credit assets in the original currency.	December 2020
M	Develop a workbook file for the calculation of gross external debt transactions and positions that would support compilation of quarterly external debt statistics tables.	July 2020
Outcome: Data dissemination policy and practice improved
H	Publish standard BOP, IIP, and GED Excel tables on the Central Bank website.	March 2020
O	When publishing quarterly data in an Excel table, provide brief press releases of one or two pages.	March 2020
Outcome: Staff capacity increased through training, especially on developing source data, compilation methods, and dissemination.
O	Send staff responsible for compilation of the balance of payments, IIP, and external debt to ESS seminars arranged by the IMF, other international organizations, and central banks of other states.	Regularly

Priority scale: H – High, M – Medium, O – Other

View Table

Priority	Action/Milestone	Target Completion Date
Outcome: Data are compiled and disseminated using appropriate statistical techniques, including those that deal with data sources, and/or assessment and validation of intermediate data and statistical outputs
H	Correct the methodology for calculating operations involving direct investment shareholder capital for nonfinancial corporations and reflect the results obtained in the balance of payments.	February 2020
H	Correct the methodology for calculating operations involving portfolio investment shareholder capital for nonfinancial corporations and reflect the results obtained in the balance of payments.	February 2020
H	Correct the methodology for calculating operations involving reinvested income for nonfinancial corporations and reflect the results obtained in the balance of payments.	February 2020
H	Correct the methodology for calculating operations involving reinvested income for financial corporations and reflect the results obtained in the balance of payments.	Completed during the mission
H	Reflect forgiveness of nonguaranteed private debt in BOP operations.	February 2020
H	Introduce additional lines to the report forms for insurance and leasing companies and correct the methodology for calculating intercompany loans based on banking information.	February 2020
M	Reflect income on SDR allocations and holdings on a gross basis in primary income.	Completed during the mission Carried over from the previous mission’s plan
M	For banking information on nonguaranteed private sector debt, in each specific debt restructuring case contact the bank providing the given information and clarify all of the details involved in the restructuring. Make the relevant corrections on the basis of the information obtained.	Regularly
H	Remove capitalization of accrued interest and the restructuring of principal and interest into shareholder capital from other changes and reflect them in balance of payments operations.	February 2020
H	Prior to the conversion of external debt data in the settlement currency, check the compatibility of the data and in the event that inconsistencies are found, identify the reason for the discrepancies and eliminate them in accordance with the mission’s recommendations.	Regularly
H	Compare data on foreign direct investment obtained from the ITRS and from the SSC at the company level and identify reasons for discrepancies.	May 2020
H	Divide trade credits obtained through the special bank system for the recording of cross-border accounts payable/receivable into trade credits between affiliated companies and other trade credits.	December 2020
H	Adjust imports based on an analysis of import prices.	May 2020
H	Collect additional data from ministries, agencies, state-owned corporations, and commercial banks on cross-border transactions performed in 2014–2015.	December 2019
H	Revise and update BOP data for 2014–15 in BPM6 format, drawing on the Ministry of Economy’s original estimates, and on additional data sources identified.	March 2020
Outcome: Source data are adequate for the compilation of external sector statistics
H	Agree with the Ministry of Finance the format for submitting data on the principal and interest payment schedule for government and government-guaranteed debt.	February 2020
H	Include a field in the interim ITRS database for the institutional sector according to the mission’s recommendations.	February 2020
M	Analyze the data received from commercial banks and identify coding errors. Bring bank representatives together once per quarter to discuss typical errors made in ITRS coding.	Regularly, starting in February 2020
H	Make additions to the list of ITRS codes according to the mission’s recommendations and correct the text in terms of the name and application of the codes.	January 2020
H	Extend ITRS to the CBU segment.	May 2020
M	Continually update the list of nonfinancial corporations involved in foreign trade activity to include them in the survey of nonfinancial sector foreign economic activity.	Regularly Quarterly Carried over from the previous mission’s plan
M	Organize a comparison of trade credits obtained from the State Statistics Committee and from the bank system for the recording of cross-border accounts payable/receivable at the level of individual companies.	December 2020
H	Develop a file for the calculation of government Eurobonds according to the mission’s recommendations.	Completed during the mission
H	Develop a file for the calculation of operations and balances of SDR allocations and holdings (including accrued interest) in line with the mission’s recommendations.	Completed during the mission
H	Organize the compilation of external debt statistics in accordance with the standards of the External Debt Statistics Guide (2013 edition).	March 2020
H	Prepare mirror statistics to estimate unrecorded import and export transactions.	Regularly
H	Request data from commercial banks on trade credit assets in the original currency.	December 2020
M	Develop a workbook file for the calculation of gross external debt transactions and positions that would support compilation of quarterly external debt statistics tables.	July 2020
Outcome: Data dissemination policy and practice improved
H	Publish standard BOP, IIP, and GED Excel tables on the Central Bank website.	March 2020
O	When publishing quarterly data in an Excel table, provide brief press releases of one or two pages.	March 2020
Outcome: Staff capacity increased through training, especially on developing source data, compilation methods, and dissemination.
O	Send staff responsible for compilation of the balance of payments, IIP, and external debt to ESS seminars arranged by the IMF, other international organizations, and central banks of other states.	Regularly

Priority scale: H – High, M – Medium, O – Other

B. Goods and Services

7. The main source of data for the goods component is information prepared on the basis of the customs declaration database (CDDB), which the CBU receives on a monthly basis from the State Customs Committee (SCC). The CDDB contains information about all goods that cross Uzbekistan’s border. Based on additional information on customs regimes, the CBU selects the relevant item – Goods. This is described in detail in the report of October 2018 mission. Further adjustments consist of the following:

• Goods procured in airports by carriers;

• Estimated data for shuttle trade;

• Conversion of CIF prices into FOB prices.

8. The National Air Company (NAC) provides information about goods procured by carriers, both for export and for import. Shuttle trade is estimated on the basis of the results of a regular special survey at border-crossing posts. The methodology for converting CIF prices to FOB prices takes into account the weight of the goods and the average cost of shipping one metric ton of freight, depending on the type of transport and the region of the trading country.

9. The adjustments for goods do not include an estimate of unrecorded import/export transactions arising as a result of underreporting of prices or volumes in customs declarations. CBU has made several attempts to introduce the mirror method for comparison with the country’s main trading partners. To this end, requests were sent to the main trading partners. In some cases, however, no response was received, and in other cases data were received only on the basis of two-digit codes, which does not allow for the performance of a mirror comparison of the proper quality. As a result, the CBU has not succeeded in performing a mirror comparison with trading partners, and there is still no adjustment estimated for unrecorded import/export transactions.

10. The mission recommends that trading partners be selected for a mirror comparison on the basis of the following criteria: first, the volume of trade should be sufficiently large; second, the quality of the partner country’s trade statistics should be high, and the data should be reliable. The mission studied data from partner countries, and it recommends that mirror comparisons be performed with the following trading partners: the European Union, Turkey, Korea, Japan, China, Russia, and Kazakhstan. The data comparison should be performed at the four-digit code level and it must be in FOB prices. In order to do this, data on imports of either the partner countries or Uzbekistan must be converted from CIF prices to FOB prices at least on an approximate basis. If data from the aforementioned partners cannot be obtained, the United Nations Comtrade database can be used.

11. For each of the aforementioned countries, when comparing import/export volumes for individual commodity codes, the actual size of the discrepancies needs to be estimated. On the basis of the data obtained, the import/export correction coefficient should be calculated for each country, and then the weighted average correction coefficient should be calculated for both imports and exports. The coefficients obtained may be applied to all imports/exports, with the exception of special goods that are not subject to correction. Such goods can include electricity, natural gas and oil transported by pipeline, humanitarian goods, goods relating to state-owned enterprises, and also to companies with a production sharing agreement.

12. In its analysis of import prices, the mission found that in some declarations the price of the same goods from the same country differed several-fold from the average price for these goods. The mission recommends that an analysis be performed of the prices of major export and import goods, that those declarations with significant volumes of goods in which the unit price of the goods differs markedly from the average price of the goods from the given country be identified, and that the price be adjusted to align with the average price of the given goods from the given country.

13. Migrants’ imports and exports (personal effects) also should be removed from the goods item.¹ Migrants’ imports and exports can be estimated on the basis of the CDDB, declarations containing 10 or more entries can be selected, and they can be studied using the field that contains a written description of the goods. Such an estimate can be performed once, and the coefficient obtained can be used for the adjustment. It is also recommended that an alternative method be used to obtain an estimate of goods transported by migrants through surveys at border-crossing posts. Recommended Measures:

• Perform an analysis of prices based on individual declarations of the 20 main imported goods and 10 exported goods. In the event of a significant deviation from average prices, taking into account the goods/country, an adjustment needs to be made to the price and the difference in the value of the goods after the price adjustment should be reflected in the BOP.

• Apply the mirror comparison method to estimate unrecorded transactions involving the import/export of goods and add the data obtained to the Goods item.

• Remove from goods the estimated data for imports/exports performed by migrants.

14. The CBU has made some progress in improving the collection and compilation system for trade in services. Data from SSC survey on international trade in services were validated and revised, especially with regard to certain types of services for which the CBU developed alternative data sources and estimation methods. The CBU was able to estimate certain types of services for which there was either no estimate in the SSC data, or for which the accuracy of estimate was inadequate. For instance, passenger transport, debit was estimated at practically zero. An improvement was also made in the estimate of travel, which is a major services item. The SCC remains the main source of information, but the NAC, the Uzbek Railway (UR), the State Border Protection Committee (SBPC), the Ministry of Foreign Affairs (MFA), and other agencies are also providing information.

15. Within the context of improving the information provided for the calculation of data on trade in services, during the previous mission a form was developed for the Uzbek Railway on the use of foreign railcars by the UR and the use of Uzbek railcars by foreign railways. This form contains information on the provision of services (leasing of railcars) between Uzbekistan and the rest of the world and vice versa. It also indicates the debt of the parties at the end of the quarter and repayment of this debt after mutual offsets.

16. Data on the use of railcars are provided together with data on settlements in original currency. This information allows not only for the calculation of imports/exports of railcar leasing, but also trade credits (assets and liabilities) arising in this type of economic activity. The mission provided assistance in the processing of this information. Railcars are leased without a crew, and accordingly this service is classified as operational leasing. The mission recommends that the leasing of railcars be reflected under the technical, trade-related, and other business services item, which includes operational leasing.

17. The credit under pipeline transport is a fairly large services item, the annual volume of which remains stable within the range of US$600–700 million. The CBU receives information about this service from the SSC, and one enterprise, Uztransgaz, reports to the SSC on freight via pipeline transport. Unfortunately, during the mission it was not possible to meet with representatives of the company, and no response was received to a letter that was sent. The mission arrived at the conclusion that an analysis of Uztransgaz reporting data is needed to verify compliance with BPM6 standards. At this time the Uztransgaz report contains only the cost of transit transport through Uzbekistan and the cost of transporting exports and imports of petroleum products. In addition, the mission did not succeed in clarifying which main pipelines are located within Uzbekistan.

18. In order to improve the quality of data on financial services for which an explicit fee is charged, the mission recommends that the SSC data be replaced with data received from commercial banks. The main consumers and providers of financial services are banks, and for this reason it clearly makes more sense to obtain data from them on financial services provided and received. A letter was drafted and sent to commercial banks asking them to provide quarterly information on financial services received and provided starting with 2014. Detailed information will also be obtained from the SSC. To avoid double accounting, the CBU will ask the SSC for a separate presentation of financial services from the banking sector and from other corporations.

19. In order to improve recording of trade in services, active use should be made of ITRS data, especially for those types of services for which there are no reliable data sources. For example, due to the specific nature of Uzbekistan’s geographical location maritime transport does not appear in the country’s BOP, but there are nevertheless imports of maritime transport freight services. Goods are shipped from a number of countries via maritime transport to nearby ports and are then delivered to Uzbekistan by land. In addition to maritime transport, ITRS can be used for the following services: road transport exports; postal services and courier services; financial services of other sectors; payment for the use of intellectual property not elsewhere classified; telecommunications, computer, and information services, and other types of services for which it is difficult to collect data using regular surveys.

C. Primary and Secondary Income

20. Over the past year the CBU improved statistical data on primary income. Following the guidance of the previous mission, a number of deviations from the BPM6 standards were corrected and statistical methods for performing estimates were improved. The credit under wages and salaries in the previous version of the CBU’s balance was significantly overstated and exceeded US$3.6 billion in the first half of 2018, while in the current version of the BOP the analogous figure is around US$1.4 billion.

21. In spite of a number of improvements in the accounting of investment income, the mission identified several inaccuracies and made recommendations to correct them. The SSC used an incorrect algorithm in the calculation of reinvested income of nonfinancial corporations. The mission helped correct the algorithm for the calculation of transactions by direct investment components, including reinvested income.

22. On February 20, 2019, the Uzbekistan Ministry of Finance (MOF) issued two types of Eurobonds with maturities of 5 and 10 years. These are the country’s first debt securities. The BOPSO calculated the accrued interest on these securities and made the correct entries in the BOP. Together with BOPSO staff, the mission also developed a file for the recording of government Eurobonds at market prices, and a detailed description of this file is provided below in the section on direct and portfolio investment.

23. The mission found that SDR allocations are missing from the ESS, and accordingly income on SDR allocations does not appear in other investment income. In conjunction with BOPSO staff, it was determined that the data on income on reserve assets do not contain information on accrued interest on SDR holdings, either. The mission developed and presented to the BOPSO a file for calculating accrued interest on SDR allocations and holdings. Information from this file is also suitable for the financial account and for quarterly external debt statistics tables. A detailed description of this file is provided below in the section on other investment.

D. Direct and Portfolio Investment

24. The mission analyzed the main data sources for direct investments. They are: the SSC (a survey of foreign economic activity of nonfinancial corporations – using form Invest-1); a survey of commercial banks on direct investments of financial corporations (information is collected from DTCs and from nonbank financial corporations, including microfinance institutions, insurance companies, and leasing companies); and a CBU survey of companies with a production sharing agreement (PSA) based on an updated form. The SSC also collects investments abroad (assets) but they represent a negligible amount. The format of the data collected allows for the compilation of statistics for both balances and transactions.

25. The mission performed an analysis of DI data provided by the SSC to the CBU and found that the data in the original currency are not balanced. The balances at the end of the reporting period and flows during the period do not correspond to each other. When the data are converted into U.S. dollars, this imbalance is widened by the exchange rate difference and this increases the difference between the BOP operations and changes between the balances at the beginning and end of the period.

26. The mission also found that the reason for this imbalance was an incorrect algorithm for the calculation of a net operation for both DI and PI, which was used by the SSC when generating reports for the CBU. The existing algorithm relied only on a change in a company’s total capital. If there was no change in a company’s capital, but ownership was transferred from a resident to a nonresident or vice versa, the existing algorithm did not capture these transactions and zero values were assigned to the transactions. On the other hand, these changes were correctly reflected in the positions. The existing algorithm had one more flaw, which was that it did not account for the reclassification of a direct investor into a portfolio investor and vice versa.

27. Together with BOPSO staff, the mission developed a new algorithm in which the aforementioned deficiencies were eliminated. The BOPSO prepared a cover letter and a file with a description of the new algorithm, which will be sent to the SSC for the calculation of data on DI and portfolio investment. The mission also developed a methodology for the calculation of data on the basis of which the BOPSO will process data obtained from the SSC and reflect them in the BOP and IIP under DI and PI.

28. To simplify the compilation process for data reporting by the SSC, it was decided that instead of a single table on DI, four sub-forms will be sent to the SSC with different conditions depending on the investor’s stake at the beginning and end of the reporting period. Information will be reflected in each of these sub-forms based on the following lines in form Invest-1, which the SSC uses to collect data on a company’s foreign economic activity.

• Line 201 – Authorized/shareholder capital;

• Line 202 – Additional capital;

• Line 204 – Retained earnings from previous years;

• Line 205 – Profit/loss for reporting period (actual retained earnings for the current year);

• Line 206 – Reserve capital;

• Line 207 – Other reserves;

• Line 203 – Preferred shares held by direct investors;

• Line 208 – Other financing from a nonresident direct investor (other than loans and reinvestment);

• Line 209 – Other debt securities issued by a company, held by direct investors;

• Line 210 – Dividends actually paid in the reporting period.

Of these lines, lines 204 and 205 are classified as reinvested income, lines 203 and 209 as debt instruments, and the rest are equity and investment fund shares/units.

29. In the file prepared by the SSC, flows and balances are balanced for all lines, with the exception of 204 and 205, concerning retained earnings. The net operation is recorded as both changes in indicators of the companies themselves (an increase in authorized capital, for example), and as changes related to a change in an investor’s stake.

30. For lines 204 and 205 (retained earnings), the BOP operation for each investor is calculated as the change in the company’s retained earnings multiplied by the given investor’s average stake. Under this approach, the flows for retained earnings and their balances at the beginning and end of each period will not be balanced, and the residual category will be equal to that part of retained earnings for which payment was made in cash; they should be added to equity transactions, which in turn ensures the balance of IIP data. These sub-forms and the conditions under which they are to be compiled are described below.

31. Sub-form 3. An investor’s stake at the beginning of the reporting period is equal to at least 10 percent, or it is equal to zero, and at the end of the period it is either greater than or equal to 10 percent or it is equal to zero (i.e., there is no reclassification of a direct investor into a portfolio investor). All information reflected in this sub-form will be recorded under DI.

32. Sub-form 3.1. An investor’s stake at the beginning of the reporting period is greater than or equal to 10 percent, and at the end of the period it is less than 10 percent but greater than zero (i.e., a direct investor becomes a portfolio investor). Information provided in this Sub-form will be reflected in the BOP as DI, and in the IIP it will be reflected under both DI and PI as follows.

Table 2.

Calculation of DI and PI when a Direct Investor Becomes a Portfolio Investor²

Table 2.

Calculation of DI and PI when a Direct Investor Becomes a Portfolio Investor²

Line No.	Balance at Beginning of Period	BOP Operations	Change Related to Price Changes	Other Changes	Balance at End of Period
Information received from SSC under line No.	BB	TR	V	OC	EB
The CBU prepares two entries under DI and PI based on the information received
DI	BB	TR	VC	OC-EB	0
PI	0	0	0	EB	EB

View Table

Table 2.

Calculation of DI and PI when a Direct Investor Becomes a Portfolio Investor²

Line No.	Balance at Beginning of Period	BOP Operations	Change Related to Price Changes	Other Changes	Balance at End of Period
Information received from SSC under line No.	BB	TR	V	OC	EB
The CBU prepares two entries under DI and PI based on the information received
DI	BB	TR	VC	OC-EB	0
PI	0	0	0	EB	EB

33. Sub-form 4. An investor’s stake both at the beginning and end of the reporting period is less than 10 percent. In this case, flows of balances are calculated in the same way as for sub-form 3, but they will be reflected under portfolio investments.

34. Sub-form 4.1. An investor’s stake at the beginning of the reporting period is less than 10 percent but greater than zero, and at the end of the period it is at least 10 percent (i.e., a portfolio investor acquires an additional stake and becomes a direct investor). Information provided in this table is analogous to sub-form 3.1. In the BOP it will be reflected under DI, and in the IIP it will be reflected as both DI and PI as follows:

Table 3.

Calculation of DI and PI when a Portfolio Investor Becomes a Direct Investor

Table 3.

Calculation of DI and PI when a Portfolio Investor Becomes a Direct Investor

Line No.	Balance at Beginning of Period	BOP Operations	Change Related to Price Changes	Other Changes	Balance at End of Period
Information received from SSC by line No.	BB	TR	VC	OC	EB
The CBU prepares two entries under DI and PI based on the information received
DI	0	TR	VC	OC+BB	EB
PI	BB	0	0	- BB	0

View Table

Table 3.

Calculation of DI and PI when a Portfolio Investor Becomes a Direct Investor

Line No.	Balance at Beginning of Period	BOP Operations	Change Related to Price Changes	Other Changes	Balance at End of Period
Information received from SSC by line No.	BB	TR	VC	OC	EB
The CBU prepares two entries under DI and PI based on the information received
DI	0	TR	VC	OC+BB	EB
PI	BB	0	0	- BB	0

35. The CBU did not take into account one of the direct investment components – Line 208 – other financing from a nonresident direct investor (other than loans and reinvestment). Therefore, companies include in this residual category all transactions that do not fit under the other items (for example, a donation by an investor). The mission recommends that the data under this line be included in DI and that the SSC include an additional cell in the form for a brief description of this kind of financing.

36. In addition to these sub-forms, the SSC Invest-1 survey will contain summary sub-form (Sub-form 1), which will contain information about all of the lines from its survey, but without conditions and without dividing it into direct and portfolio investors. The CBU will use summary sub-form to check data, and the sum of the data from the aforementioned four sub-forms should be equal to the data from Sub-form 1.

37. A more complicated situation was found with regard to debt instruments under DI. The SSC collects data from companies (other than those with PSAs) regarding credits and trade credits. The CBU also collects the same data through commercial banks. Banks provide data on all companies that have received credits in monetary form, and also on their own credits. The coverage of the data collected through banks is greater than that of the SSC data, and for this reason the CBU uses the bank system data. The mission studied the procedure for the collection and processing of data on credits and trade credits through the bank system and discovered a number of inconsistencies with the generally accepted standards.

38. The quality of the system for processing data on nonguaranteed loans is quite high, and the existing minor deficiencies can be easily corrected. Specifically: (i) intercompany loans of insurance and leasing companies are included in other investment, which can be corrected by expanding the coding of the institutional sectors; (ii) capitalization of interest and cancelation/forgiveness of principal and interest are included in other changes, which can be corrected by making adjustments to the formula for their calculation; (iii) there is not a balance between balances and flows in the original currency. The bank system for the collection and processing of data on loans and trade credits will be discussed in greater detail below, in the section on other investment and reserve assets.

39. The mission provided BOPSO staff with methods to find the causes of discrepancies. Next it will be necessary to contact each respondent bank, identify the cause of a discrepancy, and make the relevant corrections; it is possible that data series will need to be corrected.

40. The situation involving trade credits is even more problematic. The system for recording trade credits developed by the CBU (a detailed description of this system will be provided in the section on other investment and reserve assets) at this point does not allow for the division of trade credits between affiliated companies and other trade credits. Therefore, all trade credits are reflected under other investment, which means that data on DI are underreported and other investment is overreported. SSC data make it possible to distinguish trade credits from parent companies and from independent nonresidents, but the quality of data collected at this stage needs improvement.

41. In the course of the mission’s work, a large discrepancy was found between the SSC and ITRS data for DI in the second quarter. According to the SSC, DI totaled US$923 million (this figure is reflected in the BOP, while according to the ITRS, DI was equal to around US$300 million). Such a large difference raises doubts about the reliability of both data collection systems. The CBU and SSC have not yet managed to reach an agreement on the sharing of primary data, which would significantly improve the quality of data comparisons based on these sources. At the last meeting with SSC representatives, an agreement was reached on the reconciliation of primary data (i.e., company data) on DI and trade credits. To this end, a meeting of BOPSO and SSC representatives is planned for data reconciliation.

42. In 2019, Uzbekistan issued its first series of debt securities. The government performed a large placement of Eurobonds on February 20, 2019, which were purchased for the most part by nonresidents. Detailed information about the Eurobonds, including market prices, is available in the Bloomberg system, which can be used for ESS. The BOPSO made the correct entries in the BOP, but no calculations were made based on market value. These Eurobonds were also recorded at nominal value in the IIP and GED.

43. With the mission’s assistance, an Excel file was compiled for the calculation of data on these securities both at market prices and at nominal value, in addition to income on them. The data calculated may be used in the balance of payments (securities transactions and income on securities), and also in the IIP and external debt (balances at the end of the period, transactions and other flows). The price of the securities at the time of issue was 100 percent of the nominal value, which simplified the relevant calculations. This file already contains calculations for the first three quarters of 2019; further calculations require market prices for the given securities at the end of the reporting quarter, which the BOPSO should obtain from the Foreign Exchange Reserves Management Department (FERMD). A schedule for the payment of coupons was also calculated. Table 4 shows changes in market prices, and Table 5 contains consolidated data on both Eurobonds for the third quarter of 2019.

^{Table 4.}

Net Market Price of Government Eurobonds

(%)

^{Table 4.}

Net Market Price of Government Eurobonds

(%)

	Feb. 20, 2019	March 29, 2019	June 28, 2019	Sept. 30, 2019
5-year Eurobonds	100.00	99.461	104.543	105.052
10-year Eurobonds	100.00	99.132	106.395	110.563

View Table

^{Table 4.}

Net Market Price of Government Eurobonds

(%)

	Feb. 20, 2019	March 29, 2019	June 28, 2019	Sept. 30, 2019
5-year Eurobonds	100.00	99.461	104.543	105.052
10-year Eurobonds	100.00	99.132	106.395	110.563

^{Table 5.}

Example of the Calculation of Government Securities for the Third Quarter of 2019

(Consolidated Data for Both Series)

^{Table 5.}

Example of the Calculation of Government Securities for the Third Quarter of 2019

(Consolidated Data for Both Series)

	June 30, 2019	Transaction	Rate	Price	Other	Sept 30, 2019
Principal – nominal value	1,000.0	0.0	0.0	0.0	0.0	1,000.0
Debt on coupons	18.3	-12.7	0.0	0.0	0.0	5.6
Income	X	12.7	X	X	X	X
Principal – market value	1,054.7	0.0	0.0	18.4	0.0	1,073.1
Nominal value – total	1,018.3	-12.7	0.0	0.0	0.0	1,005.6
Market value – total	1,073.0	-12.7	0.0	18.4	0.0	1,078.7

View Table

^{Table 5.}

Example of the Calculation of Government Securities for the Third Quarter of 2019

(Consolidated Data for Both Series)

	June 30, 2019	Transaction	Rate	Price	Other	Sept 30, 2019
Principal – nominal value	1,000.0	0.0	0.0	0.0	0.0	1,000.0
Debt on coupons	18.3	-12.7	0.0	0.0	0.0	5.6
Income	X	12.7	X	X	X	X
Principal – market value	1,054.7	0.0	0.0	18.4	0.0	1,073.1
Nominal value – total	1,018.3	-12.7	0.0	0.0	0.0	1,005.6
Market value – total	1,073.0	-12.7	0.0	18.4	0.0	1,078.7

E. Other Investment and Reserve Assets

44. Despite some success in the collection of data and methods for processing data under other investment items, the mission identified a number of deficiencies and deviations from generally accepted standards. Some of them were corrected during the mission, and recommendations were made to address the rest.

45. With the assistance of the previous mission, a form for the collection of information about government and government-guaranteed loans was developed and put into use. This form made it possible to divide government-guaranteed loans into three parts:

• loans of the general government sector;

• loans of other sectors guaranteed and serviced by the government;

• loans of other sectors guaranteed by the government and serviced by the borrower.

46. This form was designed to distribute guaranteed loans by the institutional sector of the borrower, but there is an insufficient breakdown of the latter by institutional sectors. All subsequent requests to the CBU to revise the procedure for the presentation of data failed to produce any results, with the MOF noting the lack of a special program for processing data on debt obligations, and existing problems with obtaining data from banks. Therefore, all loans taken out directly by the government and taken out by corporations (primarily state-owned) against a government guarantee were combined and reflected as debts of the general government sector, in connection with which the volume of government debts totaled US$12 billion, approximately half of which should be redistributed to the relevant sectors.

47. The mission visited the MOF to discuss the question of obtaining data on government and government-guaranteed loans, including historic data series, starting with 2014, which will make it possible in the future to compile ESS according to BPM6. Given that the program for processing debt obligations (the Debt Management and Financial Analysis System, or DMFAS) was established quite recently, and data have not yet been uploaded to the system, the MOF was not able to provide data starting from 2014 with the breakdown we required, but it made a commitment to promptly send updated data broken down as follows: (i) loans assumed directly by the government; (ii) loans assumed by corporations against government guarantees, and of these, the ones being serviced by state budget funds are identified separately. For a complete breakdown of guaranteed debts serviced by borrowers, it is sufficient to identify loans of the DTC sector separately as government guaranteed debt of non-financial corporations are already serviced by government and the remaining guaranteed borrowing is for financial sector only of which the bank’s data are already available to CB. The MOF also made a commitment to complete the process of uploading data to the DMFAS in the first half of 2020, after which it is prepared to discuss the matter of providing data with the required level of detail.

48. Together with BOPSO staff, the mission developed a compact reporting form to collect information on loans of the DTC sector obtained against a government guarantee. This reporting form will be sent only to those banks that borrow funds against government guarantees, mainly banks in which the government holds a controlling stake.

49. The CBU uses a special bank reporting as part of foreign exchange regulation to record nonguaranteed private debt. Banks send in fairly detailed information about external loans of Uzbekistan residents that are not guaranteed by the government. The information is provided to the CBU in the form of an Excel table and each loan is represented by a separate entry. Fairly detailed information is collected for each loan, down to the payment schedule. This information includes the name of the creditor and the code of the type of creditor is also indicated, which makes it possible to determine the relevant institutional sector. A bank report also indicates the code of the mutual relationship between the creditor and debtor. Therefore, it is possible to identify loans from a parent company or from a non-affiliated nonresident.

50. The CBU has developed a sound algorithm for the processing of assumed loans. Information is collected from all banks in a single Excel file, and then using Excel formulas and various codes applied in the file they are broken down into a number of components. When filling in the line for a given debt, a bank determines the existence of a direct investment relationship between the creditor and debtor and enters the relevant code. The bank also determines the borrower’s affiliation with an institutional sector, and the following sectors are identified: commercial banks, nonbank financial corporations, and nonfinancial corporations. In addition, there is a maturity code for each debt (long-term or short-term) and a settlement currency code. Data in the file are presented in the original currency.

51. The first level of disaggregation separates intercompany loans from the rest of the loans. Intercompany loans include only those loans of nonfinancial corporations in which the borrowers and the creditor are in a direct investment relationship, in order for the loan to be classified as an intercompany loan. Two conditions need to be met in this case:

• a) there must be a direct investment relationship between the creditor and the debtor;

• b) the company must be a nonfinancial corporation.

Under this approach all loans of nonbank financial corporations are excluded entirely from intercompany loans, while loans obtained by insurance companies or leasing companies from parent companies should be classified as intercompany loans, and not as loans under other investment.

52. In order to ensure the correct disaggregation by intercompany and other loans, the mission suggests that the problem be resolved as follows. A field needs to be added to the file that commercial banks provide to the CBU, which the CBU will use to divide loans into intercompany loans and other loans. The code for classification as an intercompany loan needs to be entered in this field for each debt. A loan will be considered an intercompany loan if the following two conditions are met: (a) there is a direct investment relationship between the creditor and the debtor; (b) neither the creditor nor the debtor is a financial corporation for which financial intermediation is a daily operational process (commercial banks and microfinance corporations are such institutions, as a rule).

53. Two options can be considered. Under the first option, a commercial bank itself enters an additional code and forwards the file to the CBU, and in the second case this file is added and filled in at the CBU by BOPSO staff. It would be preferable for the process of assigning this code to be defined once at the time of the first report on the given loan, and subsequently it would be automatically carried over to the following reports until the given loan is closed. A unique loan number contained in the file that commercial banks submit could be used for this purpose.

54. The second level of disaggregation breaks down loans treated as other investments by institutional sectors. The following sectors are defined: DTC, nonbank financial corporations, and nonfinancial corporations.

55. The third level of disaggregation separates loans into long-term and short-term loans, then each of these are separated by currencies, after which the data are aggregated. The following data are given for each group: disbursement and repayment of principal, accrual of interest, payment of interest, balances on principal and interest, capitalization of accrued interest, as well as data on debt forgiveness (principal and interest), and data on arrears on principal and interest. The data are submitted on a monthly basis, with part presented as a cumulative total and part in the form of net data for the reporting month.

56. Following the aggregation of data, they are converted into dollars and the exchange rate difference is calculated. The mission reviewed the data processing procedure and identified the following deviations from generally accepted standards, which are easily corrected. The following deficiencies are worth mentioning: (i) debt forgiveness operations (by mutual agreement) are recorded as other changes; (ii) capitalization of interest is recorded under the other change category; (iii) balances in the original currency at the end of reporting periods do not correspond to flows in the reporting period. This last issue means that when the conversion into U.S. dollars is performed, the imbalance between balances and flows is converted into exchange rate changes and distorts them. The mission recommends that the formulas used for the calculation be modified in such a way that debt forgiveness/cancellation is reflected in BOP operations as debt payment, and also that data on debt forgiveness be totaled separately for recording in capital transfers. Capitalization of accrued interest should be reflected as an operation involving accrual of interest and an increase in debt.

57. Together with BOPSO staff, the mission studied the reasons for the imbalance between balances and flows for the reporting period. The main reason for the imbalance turned out to be a change in the classification of loans. The same loan was classified differently in the current and previous quarter. Less frequently, the reason for the imbalance is the appearance of a new loan the use of which began in previous periods, but which was not in the file for the previous quarter. The mission recommends in both cases that contact be made with the bank providing information about the loan, in order to get an idea of the real picture and make the appropriate corrections, and if necessary, to correct the entire data series. The mission also recommends that the correspondence between balances and flows in the original currency be checked before the conversion into the settlement currency (U.S. dollars).

58. Trade credits are one of the problematic items in ESS. The CBU has two data sources for trade credits; one source is SSC data collected using the new form Invest-1 (survey of foreign economic activity of nonfinancial corporations) and the second source is the bank system for the collection of data on trade credits. Of these two sources, at this point the CBU has greater confidence in the bank system and relies entirely on it. Both of these systems have their own positive and negative aspects.

59. Trade credits between affiliated companies, which should be included in direct investment debt instruments, are presented separately in the SSC data, and other trade credits, which are included in other investment, are recorded separately. SSC data are presented in the original currency, which is convenient for performing calculations, including exchange rate changes, for the IIP and GED. But the SSC data have one significant drawback—the limited coverage of companies and accordingly the underestimated data on trade credits.

60. The bank system for the accounting of trade credits has good coverage, but it also has a number of deficiencies. This system is organized as follows: prior to the performance of an import/export transaction, every importer and exporter must upload the contract with the foreign partner to the server that is located at the Uzbek Customs Service. Commercial banks and the CBU have access to this server. A contract may be drawn up for several types of goods and for several batches of imports/exports of goods. Contracts have unique identification numbers. The recording of trade credits is performed for each contract individually.

61. When transferring or receiving funds related to imports or exports, a bank is required to record the transactions performed in the system. If a contract is not entered into the system, the bank will not perform the transaction. The flow of goods is also recorded in this system at the time the goods are processed, and it does not make any difference whether it is an import or export operation that is being performed. In any case, the volume of goods received or shipped is recorded on the server under the given contract. Finally, data on the movement of goods and funds under specific contracts are collected, and the information is entered into the system in the original currency. It is easy to determine the volume of the trade credit for each contract and its classification under assets or liabilities. At this point the CBU is not able to extract data directly from the server. At the CBU’s request, the system developer is working on resolving this issue. It is expected that the CBU will be able to obtain data directly from the server regarding trade credits under contracts in the original currency by end-2019, and that it will also be possible to group assets and liabilities separately. The CBU currently obtains data on trade credits from this system through commercial banks. At the CBU’s request, commercial banks send information on trade credit liabilities in the original currency, and data on assets that are converted into U.S. dollars.

62. The main drawback of this system is that at this stage the bank system does not distinguish trade credits between affiliated corporations and other credits, and for this reason the CBU reflects all trade credits under other investment. Furthermore, data provided by commercial banks on trade credit assets collected through this system are converted into U.S. dollars, which complicates the valuation of a transaction and exchange rate differences. There is a field for currencies in the table submitted by commercial banks, but this is a multi-currency field, which makes its automated processing difficult.

63. Data on the movement of goods are entered when customs clearance of the goods is performed, which means that goods entering customs warehouses and customs storage sites do not enter the system and do not affect the amount of trade credits. This system partially mixes the data on assets and liabilities. In other words, if a contract provides for several types of goods, trade credit assets may arise for one type of goods, while liabilities arise for the other types. In this case, the system totals them all together and assigns a single number to them. Another drawback of the system is that it retains historical trade credits that have not been closed, some of which were created before the year 2000.

64. After studying the bank system for the recording of trade credits, the mission reached the conclusion that there are prospects for further improvement and elimination of the main drawbacks. The mission recommends that a field be introduced for a code indicating a direct investment relationship between a creditor and a debtor. The nonguaranteed loan database, which contains information about companies that are in a direct investment relationship, may be used for this purpose, and in special cases requests for clarification can be sent to banks.

65. It makes sense to define a transaction as the difference between balances only when information is provided in the original currency. In cases in which data are converted into U.S. dollars, it turns out that the difference between balances, in addition to a BOP operation, also contains exchange rate differences. Furthermore, the mission recommends that trade credits that arose five years ago or more not be taken into account. The mission also recommends that after the CBU begins extracting data on trade credits directly from the server in the original currency, it will be necessary to perform regular comparisons of company-level data obtained using the bank system for the reporting of trade credits, as well as data on trade credits obtained through the SSC survey. For this purpose, BOPSO staff need to arrange a meeting with SSC representatives who have given prior consent to hold such a meeting to discuss data.

66. The mission notes that Uzbekistan’s ESS do not contain data on SDR allocations. While operations involving SDR allocations are negligible in the BOP, they are fairly significant in the IIP and GED and total around US$400 million. The mission developed a file for recording SDR allocations and for calculating accrued interest on them, and also on SDR holdings. Information for all calculations is drawn from the IMF website, namely the volume of SDR allocations, balances on SDR holdings, and the daily interest rate and exchange rates for SDRs. Accrued interest is calculated daily and totaled throughout the quarter. Mutual settlements on SDR allocations and SDR holdings are performed once per quarter in February, May, August, and November. Mutual settlements are performed based on accrued interest for the previous three months. The net amount is added to SDR holdings. A table is compiled for the recording of SDR allocations on the basis of this file. The data series begins on December 31, 2011. Table 6 presents data on SDR allocations and accrued interest for the first quarter of 2019.

^{Table 6.}

Model of Data Processed for SDR Allocations

^{Table 6.}

Model of Data Processed for SDR Allocations

	Balance as of Dec. 31, 2018	Operations	Exchange Rate Differences	Other Changes	Balance as of March 31, 2019
SDR allocations – liabilities (data in SDRs)
SDR allocations principal amount	262,789,980	0	0	0	262,789,980
Accrued interest on SDRs	471,424	11,095	0	0	482,518
Total for SDR allocations	263,261,404	11,095	0	0	263,272,498
Converted into U.S. dollars
SDR allocations principal amount	365,485,676	0	-667,487	0	364,818,190
Accrued interest	655,651	15,112	-907	0	669,856
Total for SDR allocations (in U.S. dollars)	366,141,328	15,112	-668,393	0	365,488,046
Income on SDR holdings	X	1,033,234	X	X	X
Income on SDR allocations	X	1,020,343	X	X	X

View Table

^{Table 6.}

Model of Data Processed for SDR Allocations

	Balance as of Dec. 31, 2018	Operations	Exchange Rate Differences	Other Changes	Balance as of March 31, 2019
SDR allocations – liabilities (data in SDRs)
SDR allocations principal amount	262,789,980	0	0	0	262,789,980
Accrued interest on SDRs	471,424	11,095	0	0	482,518
Total for SDR allocations	263,261,404	11,095	0	0	263,272,498
Converted into U.S. dollars
SDR allocations principal amount	365,485,676	0	-667,487	0	364,818,190
Accrued interest	655,651	15,112	-907	0	669,856
Total for SDR allocations (in U.S. dollars)	366,141,328	15,112	-668,393	0	365,488,046
Income on SDR holdings	X	1,033,234	X	X	X
Income on SDR allocations	X	1,020,343	X	X	X

67. The mission recommends that the data obtained be used for the BOP, IIP, and GED with regard to liabilities on SDR allocations. The mission also determined that the information on reserve assets provided by the International Reserves Management Department (IRMD) does not contain data on accrued interest on SDR holdings, and that data on reserve assets are added to the file developed for the calculation of accrued interest as a missing component.

F. Further Improvement of the ITRS

68. At end-2018 Uzbekistan launched the trial collection of ITRS-based data, and only commercial banks were involved in the process. The original version of the ITRS had a number of drawbacks, among which were that the existing system was designed according to the requirements of the fifth edition of the BPM and did not take into consideration the changes that occurred with the transition to BPM6. The system of codes was in need of revision, the form for the collection of data did not have a field for the institutional sector code, and data were collected only from commercial banks. Over the past year, following the mission’s recommendations, the CBU has made some gains in improving the ITRS. Specifically, the system of codes was revised and expanded, and workshops were held for commercial banks. Explanations of the purpose of the ITRS were provided at these workshops, and typical errors in the coding of transactions were discussed.

69. The mission looked at the current status of the ITRS in Uzbekistan. It noted a number of improvements, and it also noted a number of deficiencies, which should be corrected in the near future. The code system has been improved and it meets the current requirements; the only thing that could be added at this stage is the codes for wages of residents employed at foreign embassies and other extraterritorial bodies within Uzbekistan.

70. The October 2018 mission recommended that a field be added to the ITRS form for institutional sectors, the absence of which limits the ability to apply the information collected, and it is simply essential for financial account data. The CBU took a different route. The ITRS form introduced by them assumed a fairly detailed classification (14 different types are identified) of (resident) participants in the transaction performed—the so-called client type. Table 7 below contains a list of client types and their codes.

^{Table 7.}

Client Type Codes and Names

^{Table 7.}

Client Type Codes and Names

Handbook Code	Client Type Code	Abbreviated Name of Client Type	Full Name of Client Type
21	0	LTK	Any client types
21	1	PMKh	Government
21	2	GSP	Government organizations and enterprises3
21	3	OBI	Private nonprofit organizations
21	4	NBF	Nonbank financial institutions
21	5	DTK	Other client types
21	6	CBU	Central Bank of the Republic of Uzbekistan
21	7	KBU	Commercial banks
21	8	ChLK	Individuals (households)
21	9	ChTK	Private businesses, farms, partnerships, and companies
21	10	SPK	Enterprises with foreign capital
21	11	ChLP	Sole proprietors
21	12	BDU	Budgetary institutions
21	13	RDF	Reconstruction and Development Fund

View Table

^{Table 7.}

Client Type Codes and Names

Handbook Code	Client Type Code	Abbreviated Name of Client Type	Full Name of Client Type
21	0	LTK	Any client types
21	1	PMKh	Government
21	2	GSP	Government organizations and enterprises3
21	3	OBI	Private nonprofit organizations
21	4	NBF	Nonbank financial institutions
21	5	DTK	Other client types
21	6	CBU	Central Bank of the Republic of Uzbekistan
21	7	KBU	Commercial banks
21	8	ChLK	Individuals (households)
21	9	ChTK	Private businesses, farms, partnerships, and companies
21	10	SPK	Enterprises with foreign capital
21	11	ChLP	Sole proprietors
21	12	BDU	Budgetary institutions
21	13	RDF	Reconstruction and Development Fund

71. Based on the given table, the institutional sector of a transaction participant can be determined by the client type. Together with staff, the mission prepared a conversion table, which can be used to determine the institutional sector of a transaction participant based on the client type. At this time the CBU is developing an interim (working) database for the ITRS. Data from all banks will be collected in this database, and it will be used to generate various output tables. A field for the institutional sector code will be added to the database, and this coding provides for the following breakdown: Central Bank, DTC, general government sector, and other sectors, divided into two subsectors – other financial corporations and nonfinancial corporations, as well as households and nonprofit institutions serving households (NPISHs).

Table 8.

Conversion Table from Client Type to Institutional Sectors

Table 8.

Conversion Table from Client Type to Institutional Sectors

Full Name of Client Type	Name of Institutional Sector	Sector Code
Any client types	Sector not defined	0
Government	General government sector	3
Government organizations and enterprises	Nonfinancial corporations, household and NPISHs	5
Private nonprofit organizations	Nonfinancial corporations, household and NPISHs	5
Nonbank financial institutions	Nonbank financial institutions	4
Other client types	Nonfinancial corporations, household and NPISHs	5
Central Bank of the Republic of Uzbekistan	Central Bank	1
Commercial banks	Deposit-taking corporations, except the central bank	2
Individuals (households)	Nonfinancial corporations, household and NPISHs	5
Private businesses, farms, partnerships, and companies	Nonfinancial corporations, household and NPISHs	5
Enterprises with foreign capital	Nonfinancial corporations, household and NPISHs	5
Sole proprietors	Nonfinancial corporations, household and NPISHs	5
Budgetary institutions	General government sector	3
Reconstruction and Development Fund	General government sector	3

View Table

Table 8.

Conversion Table from Client Type to Institutional Sectors

Full Name of Client Type	Name of Institutional Sector	Sector Code
Any client types	Sector not defined	0
Government	General government sector	3
Government organizations and enterprises	Nonfinancial corporations, household and NPISHs	5
Private nonprofit organizations	Nonfinancial corporations, household and NPISHs	5
Nonbank financial institutions	Nonbank financial institutions	4
Other client types	Nonfinancial corporations, household and NPISHs	5
Central Bank of the Republic of Uzbekistan	Central Bank	1
Commercial banks	Deposit-taking corporations, except the central bank	2
Individuals (households)	Nonfinancial corporations, household and NPISHs	5
Private businesses, farms, partnerships, and companies	Nonfinancial corporations, household and NPISHs	5
Enterprises with foreign capital	Nonfinancial corporations, household and NPISHs	5
Sole proprietors	Nonfinancial corporations, household and NPISHs	5
Budgetary institutions	General government sector	3
Reconstruction and Development Fund	General government sector	3

72. The CBU does not provide ITRS-based reporting at this time. Work is being done on technical issues, the resolution of which will enable the CBU to generate ITRS reports. The mission recommends that the technical issues be dealt with as soon as possible and that the ITRS be introduced for the CBU segment. The priority regarding the introduction of the remaining two segments—nonbank financial institutions and nonfinancial corporations with accounts abroad— needs to be determined as well.

73. The mission also recommends that the balance of neutral transactions be checked on a monthly basis, using the monthly data results. The credit and debit entries for neutral transactions should be of approximately the same value. In the event of large discrepancies, the reason for the discrepancy needs to be identified and eliminated if possible. As a rule, the main reason for discrepancies is an error in the coding of neutral transactions, when one party has coded a specific transaction as neutral and the other party has not.

G. Compilation of the Balance of Payments for 2014–2015

74. One of the tasks of this mission was to provide assistance to the CBU in the compilation of the 2014–2015 balance of payments and in the construction of dynamic series for the BOP, IIP, and GED starting with 2014, without a significant gap between the new BOP data and the historical data series. This task was complicated by a lack of reliable historical data. The level of detail in the balance produced by the Ministry of Economy (MOE) is fairly low, and many items are presented in aggregate form, which means that BOPSO staff have to seek new data sources and make estimates based on the available information.

75. The mission studied the MOE and CBU balances, it also analyzed the methods for estimating key BOP items, and it provided assistance to the CBU in the compilation of the BOP and IIP for 2014–2015. In compiling historical data in the BPM6 format, all of the available data sources were used, including data from the MOE’s BOP. The CBU sent requests to various ministries, agencies, and private corporations (the Ministry of Finance, State Customs Committee, State Statistics Committee, and commercial banks, among others), asking them to provide data for 2014–2015. Prior to the receipt of these data, the mission, together with the CBU, performed a rough estimate of the missing data. After the requested data are received, the estimated data will be replaced with the substantiated data, so the 2014–2015 BOP prepared during the mission needs to be treated as a trial version, since it could change significantly after the actual data are received from various sources. A comparative analysis of the historical balances produced by the MOE and the CBU balances for 2014–2015 is provided below.

76. Goods. The MOE and CBU use a common trade system for the recording of goods, but they arrive at different results. A comparison of the MOE and CBU methods is described in the report of the previous mission in the description of the compilation of the 2016–2017 balances. The difference in goods is due to subsequent corrections. The MOE adds unrecorded import/export transactions to goods, which the MOE calls “personal goods.” In the case of exports, these goods are estimated at 20 percent of money transfers. The CBU estimates shuttle trade on the basis of a survey at border posts. The CBU also asks the NAC about goods procured in ports and airports by carriers, and adds them to goods. Data on shuttle trade and goods procured in airports by carriers for 2014–2015 were calculated on the basis of analogous data for 2016–2017, through a proportional change in exports/imports of goods not including nonmonetary gold.

77. In the case of exports, the CBU’s estimates of shuttle trade are one-fourth to one-fifth of the MOE’s upward adjustments, and in the case of imports for 2015 they are slightly above the MOE’s estimate, while for 2014 they are equal to 80 percent of the MOE figure. The mission believes that in addition to shuttle trade, exports of goods are in need of an additional upward adjustment for assumed unrecorded import/export transactions. The actual volume of unrecorded exports can be estimated on the basis of a mirror comparison. In light of the above, the mission believes that it would be advisable to take a cautious approach and estimate unrecorded export transactions at 10 percent of money transfers and deduct this amount from secondary income – personal transfers. The mission also found that goods procured in ports do not appear in the MOE’s balance, although the SSC states that these goods are recorded under services by the SSC and accordingly in the MOE’s BOP. The CBU did not estimate the cost of freight according to its own methodology, but instead used the MOE’s figures, in accordance with which the cost of freight and insurance is assumed to be equal to 10 percent of the CIF price, although this does not take into account imports of energy resources. The CBU estimates freight on the basis of the geography of shipments and the physical volume (weight) of goods, using the average cost of transporting one metric ton of cargo; imports from neighboring countries along the land border are not taken into account in the calculation. The mission recommends that the CBU introduces its own methodology for compiling 2014–2015 series and that it requests data for this purpose from the State Customs Committee for 2014–2015, with a corresponding correction in the trial balance for 2014–2015.

78. Services. The CBU estimated services based entirely on the MOE balance. Transport services were estimated as follows: consolidated data on all types of transport services from the MOE balance were distributed proportionally by types of transport and types of transport services. Cargo insurance (i.e., the entire difference between CIF and FOB prices) was also included in imports of transport services. Exports of travel services were entered without any changes from the MOE balance, while the CBU estimated imports of travel services following its own methodology. Other services were also distributed by types of services in proportion to the 2016–2017 data. Insufficient information is provided in the MOE balance for services, but maximum use should be made of this information nevertheless. Table 9 contains information that appears in the MOE balance for exports of services, using 2015 as an example, while Table 10 provides information that appears in the MOE balance for imports of services, using 2015 as an example.

^{Table 9.}

Exports of Services from the MOE Balance

^{Table 9.}

Exports of Services from the MOE Balance

			2015 Q1	2015 Q2	2015 Q3	2015 Q4
Exports of services (after correction)			713.9	750.1	797.0	800.3
Of which:
	Exports of transport services		353.3	317.8	335.8	359.6
		Rail transport	77.1	81.3	89.7	81.5
		Road transport	2.5	4.0	3.4	4.0
		Pipeline transport	146.2	109.8	121.8	148.2
		Air transport	127.5	126.8	120.9	126.1
Travel, SSC			230.2	320.3	339.1	297.9
other services			130.4	112.1	122.1	142.8

View Table

^{Table 9.}

Exports of Services from the MOE Balance

			2015 Q1	2015 Q2	2015 Q3	2015 Q4
Exports of services (after correction)			713.9	750.1	797.0	800.3
Of which:
	Exports of transport services		353.3	317.8	335.8	359.6
		Rail transport	77.1	81.3	89.7	81.5
		Road transport	2.5	4.0	3.4	4.0
		Pipeline transport	146.2	109.8	121.8	148.2
		Air transport	127.5	126.8	120.9	126.1
Travel, SSC			230.2	320.3	339.1	297.9
other services			130.4	112.1	122.1	142.8

^{Table 10.}

Imports of Services from the MOE Balance

^{Table 10.}

Imports of Services from the MOE Balance

		2015 Q1	2015 Q2	2015 Q3	2015 Q4
Imports of services in the BOP		807.7	1,001.0	958.0	721.4
	Of which:
Freight		255.0	243.0	266.4	202.0
Other transport		13.4	10.9	7.9	15.2
Passengers		92.3	175.7	141.9	82.7
Tourism		164.9	327.8	269.7	189.8
Maintenance of embassies (+)		0.9	0.8	0.4	0.4
Cargo insurance		28.3	27.0	29.6	22.4
SSC data		216.1	176.5	276.1	238.0
Other correction		36.8	39.2	-34.0	-29.1

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^{Table 10.}

Imports of Services from the MOE Balance

		2015 Q1	2015 Q2	2015 Q3	2015 Q4
Imports of services in the BOP		807.7	1,001.0	958.0	721.4
	Of which:
Freight		255.0	243.0	266.4	202.0
Other transport		13.4	10.9	7.9	15.2
Passengers		92.3	175.7	141.9	82.7
Tourism		164.9	327.8	269.7	189.8
Maintenance of embassies (+)		0.9	0.8	0.4	0.4
Cargo insurance		28.3	27.0	29.6	22.4
SSC data		216.1	176.5	276.1	238.0
Other correction		36.8	39.2	-34.0	-29.1

79. The mission recommends that when estimating exports of transport services, the breakdowns of data by types of transport provided in the MOE balance (air, rail, road, and pipeline) be used, while each of these types of transport is broken down by types of transport services in proportion to the 2016 data. Data on exports of travel services need to be drawn from the MOE balance, and the rest of the services need to be broken down in proportion to the corresponding services for 2016.

80. Estimates of imports of transport services should be performed in the same way, namely, freight should be broken down in proportion to the 2016 data. In terms of types of means of transport, the same approach should be taken for passenger travel and other transport services. The mission recommends that the institution’s own estimates be used for imports of services and travel instead of estimates from the MOE balance, which does not record expenditures of short-term employees under travel. It is also recommended that estimates of private travel be revised upward. Using data from the MOE balance, the maintenance of embassies needs to be reflected under government goods and services, not classified under other categories, and the rest of the services from the MOE balance should be broken down in proportion to the analogous data for 2016.

81. Primary and secondary income. Wages and salaries in the CBU balance were estimated in proportion to the number of citizens of Uzbekistan who crossed the state border. This same item in the MOE balance is estimated on the basis of money transfers (55 percent is used). The MOE data reflect only net transfers of funds, and not all wages and salaries, a portion of which is spent in the host country. The mission believes that the method applied by the CBU is more appropriate and is in line with the BPM6 requirements.

82. In the MOE balance the debit under wages and salaries is estimated within the range of US$30 –40 million per quarter, while the CBU survey provides significantly lower values, in the range of US$4 –US$5 million. In the mission’s opinion, the results of the CBU survey are more realistic, in view of the fact that there is a labor surplus in the country and the presence of a significant number of foreign workers is unlikely. There is a small outflow of remittances from Uzbekistan, but this is most likely not related to labor migration. The CBU believes that the debit under wages and salaries is not as significant and estimated it in line with the opposite trend.

83. In the final table in the MOE balance, “direct investment income” is represented by two lines—dividends and accrued interest. In the working files, there is another line— reinvested income. Although it does not play a direct role in the final calculations, it is more likely to be implicitly included in the line “Income on equity (reinvestments and PSA earnings),” to which the line “dividend” refers in the final version of the balance. In addition to the above, investment income includes PSA income, which is certainly income on equity, although it is shown on a separate line.

84. Under the reinvested income item, the CBU reflected reinvested income from the MOE balance, and under the “Dividends and withdrawals from the income of quasi-corporations” item it reflected data from the dividends line, although in the mission’s opinion this is equity income, and the data on PSA income were ignored. The mission agrees with the CBU with regard to the recording of reinvested income and it recommends that the data on dividends be corrected as follows: deduct employment income, all types of interest income, and reinvested income from total income as a debit. The resulting amount should be recorded as a debit under the “Dividends and withdrawals from the income of quasi-corporations” item.

85. With regard to interest income on other investments, only information about interest payments was available, and they were recorded in the trial balance. The information was drawn from the MOF and the bank system for the recording of nonguaranteed loans. As soon as the relevant information is received (from the MOF and commercial banks), interest paid needs to be replaced with accrued interest.

86. Until the data on accrued interest are received, the mission recommends that the following method be used for estimating accrued interest on the basis of information on interest that has been paid. At the first stage, the average annual interest rate is determined, and the total interest payments for the year are divided by the average annual balance. Using government and government-guaranteed debt as an example, the mission demonstrated this method for estimating quarterly accrued interest to BOPSO staff. Updated data from the IRMD were reflected in income on reserve assets, and income on SDR holdings was added to this data. Personal transfers were defined as a residual category from money transfers and cash imports on the one hand, and net wages of short-term workers on the other hand.

87. In the MOE’s balance of payments, migrants’ remittances are reflected under capital transfers, which is not allowed under BPM6, in connection with which these transfers were removed from the experimental balance. It is possible that when debt data for 2014–2015 are received, there may also be cases of debt forgiveness, but there is no such entry yet under capital transfer items.

88. The mission made some corrections to foreign direct investment. To calculate direct investment in Uzbekistan, the MOE uses only data on shareholder equity and borrowed capital. In spite of the fact that the MOE’s working file contains data on reinvested income, these data do not appear in the calculation of direct investment. For the years 2014–2015, the CBU took the data on shareholder equity and borrowed capital from the MOE’s balance. Reinvested income was also taken from the MOE’s balance. Direct investment abroad is negligible. Data in the trial balance for 2014–2015 were taken from the MOE’s working file.

89. As already noted, portfolio investment and financial derivatives are negligible in Uzbekistan, and they were not estimated in the trial balance.

90. Other investment is not sufficiently represented in the MOE’s balance, and it is broken down into government and government-guaranteed loans and nonguaranteed loans. Together with the CBU, the mission decided to reflect updated data obtained from the MOF under government sector credits. Credits of DTCs and other sectors were taken from reporting by commercial banks. The MOE’s balance included data on credits granted by the Uzbekistan Ministry of Finance, or more precisely, on the repayment of these credits (new credits have not been granted for quite some time). The mission used these data and added data on Georgia’s repayment of its liabilities to Uzbekistan based on mirror records provided by the mission.

91. Data on assets in currency and deposits of the banking sector in the MOE balance do not coincide with the data of commercial banks. In terms of assets, fairly significant amounts are seen in the central bank sector in all of the quarters of 2014–2015. Although according to data from the IRMD, the CBU does not have external assets in non-reserve currencies. All deposits in non-reserve currencies are held at resident banks, in connection with which deposits of the DTC sector were estimated on the basis of bank reporting, and for deposits of other sectors, where households account for the bulk of the deposits, expert estimates were made on the basis of imports/exports of foreign currency into Uzbekistan. In addition, likely inflows and outflows of foreign currency among households were taken into account. In the mission’s opinion, the data obtained were overstated and are in need of further revision. The CBU sent a letter to banks asking them to provide data on liabilities in cash and deposits of the banking sector (mainly loro accounts). Until the data are received, the mission recommends that data from the MOE’s balance be used.

92. The BOPSO received data on reserve assets from the IRMD for compilation of the 2014–2015 BOP. The main operations are performed under the deposits category. No BOP transactions involving monetary gold are performed, all changes related to monetary gold are classified under other changes, and these data were reflected in the trial BOP and IIP.

93. Tables for the trial BOP, IIP, and GED for 2014–2015 are presented below in Appendices I–III. In the absence of reliable data, many of the items in these tables were estimated. The BOPSO will continue its efforts to collect additional data for 2014–2015 for the updating of BOP, IIP, and GED trial tables, as a result of which there may be significant changes.

H. Other Issues: Data Dissemination, Human Resources, and Training

94. Uzbekistan joined the e-GDDS in May 2018. The data dissemination practice in Uzbekistan today is as follows: the CBU develops quarterly BOP and IIP statistics based on BPM6 in U.S. dollars. The GED table is generated from the IIP table in accordance with the External Debt Statistics Guide. BOP and IIP data are submitted in standard form to the IMF on a quarterly basis for publication in the International Financial Statistics Yearbook and the Balance of Payments Statistics Yearbook. In spite of this, the BOP and IIP data are published on the CBU website only in a simplified format as part of a large body of analytical material. The CBU publishes some 70–80 pages of analytical materials on ESS on a quarterly basis in PDF format, and it also publishes on its website an advance release calendar for ESS indicating the publication dates. This publication contains a large amount of analytical material, diagrams, graphics, and tables, but there are no standard representations of the BOP, IIP, and GED. In terms of GED, the data that are published not only differ significantly from the standard representation, but they also do not include some components of debt liabilities.

95. The mission recommends that a wide range of data be published on the CBU website. At this stage, the quarterly BOP, IIP, and GED could be published in standard form as an Excel table. In parallel with the standard presentations on the CBU website, the publication of abbreviated presentations of BOP, IIP, and GED, which would show only the major items, could begin. The mission also recommends that quarterly publications of ESS be accompanied by short press releases of no more than 1–2 pages.

96. There are eight positions within the BOPSO responsible for the development of ESS and at this time all of these positions are filled. There is an optimal distribution of job duties among BOPSO employees and these duties are formally documented. There are many new employees in the office. As of October 2019, only three of the eight employees had completed special training courses. Another four employees have been invited to attend special courses organized by the IMF before the end of 2019, but the effort to provide training for BOPSO personnel continues to be a pressing matter. It is recommended that new employees attend courses at regional training centers, and that more experienced staff be sent to participate in in-depth courses in Washington.

I. Officials with Whom the Mission Met

Name	Organization
CENTRAL BANK OF THE REPUBLIC OF UZBEKISTAN
Bobir Abubakirov	Central Bank Deputy Chairman, Executive Board member
Doniyor Abdurahmanov	Director, Foreign Exchange Regulation and Balance of Payments Department
Rashid Mirzaahmedov	Department Deputy Director, Chief, Balance of Payments Office
Otabek Tojiddinov	Deputy Chief, Balance of Payments Office
Zilobiddin Irgashev	Chief, Current Account Division
Javokhir Aminov	Senior Economist, Financial Account and IIP Division
Jahongir Bedilov	Grade 1 Economist, Financial Account and IIP Division
Alisher Abdimajitov	Senior Economist, Current Account Division
STATE STATISTICS COMMITTEE
Javlon Saipov	Director, Office of Investment and Construction Statistics
Bahodir Jabbarov	Chief, Division for Comprehensive Statistical Observations of Investments in Nonfinancial Assets
Husan Shakirov	Chief Specialist, Division for Comprehensive Statistical Observations of Investments in Nonfinancial Assets
Hondamir Ahmedov	Deputy Chief, Division for Comprehensive Statistical Observations of Investments in Nonfinancial Assets
MINISTRY OF FINANCE
Farruh Hamdamov	Chief, Office for the Servicing and Accounting of Government and Guaranteed Debt
Zarif Olimjonov	Division Chief, Office for the Servicing and Accounting of Government and Guaranteed Debt
Bekzad Sagatov	Deputy Division Chief, Office for the Servicing and Accounting of Government and Guaranteed Debt
Mirabbas Mirpulatov	Chief Specialist, Office for the Servicing and Accounting of Government and Guaranteed Debt

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Name	Organization
CENTRAL BANK OF THE REPUBLIC OF UZBEKISTAN
Bobir Abubakirov	Central Bank Deputy Chairman, Executive Board member
Doniyor Abdurahmanov	Director, Foreign Exchange Regulation and Balance of Payments Department
Rashid Mirzaahmedov	Department Deputy Director, Chief, Balance of Payments Office
Otabek Tojiddinov	Deputy Chief, Balance of Payments Office
Zilobiddin Irgashev	Chief, Current Account Division
Javokhir Aminov	Senior Economist, Financial Account and IIP Division
Jahongir Bedilov	Grade 1 Economist, Financial Account and IIP Division
Alisher Abdimajitov	Senior Economist, Current Account Division
STATE STATISTICS COMMITTEE
Javlon Saipov	Director, Office of Investment and Construction Statistics
Bahodir Jabbarov	Chief, Division for Comprehensive Statistical Observations of Investments in Nonfinancial Assets
Husan Shakirov	Chief Specialist, Division for Comprehensive Statistical Observations of Investments in Nonfinancial Assets
Hondamir Ahmedov	Deputy Chief, Division for Comprehensive Statistical Observations of Investments in Nonfinancial Assets
MINISTRY OF FINANCE
Farruh Hamdamov	Chief, Office for the Servicing and Accounting of Government and Guaranteed Debt
Zarif Olimjonov	Division Chief, Office for the Servicing and Accounting of Government and Guaranteed Debt
Bekzad Sagatov	Deputy Division Chief, Office for the Servicing and Accounting of Government and Guaranteed Debt
Mirabbas Mirpulatov	Chief Specialist, Office for the Servicing and Accounting of Government and Guaranteed Debt