Back Matter
Author:
Mr. Emre Alper
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Ms. Wenjie Chenhttps://isni.org/isni/0000000404811396, International Monetary Fund

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Mr. Jemma Dridi
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Mr. Herve Joly
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Mr. Fan Yang
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Publication Date:
13 Jan 2017
ISBN:
9781475560350
Language:
English
Keywords:
DPPP; DP; EAC country; country; Uganda; Kenya; Rwanda
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References

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Appendix I. A Snapshot of Financial Markets in the EAC

Based on market capitalization, turnover ratio, number of listed companies and number of cross-listed companies, the Nairobi Stock Exchange remains by far the most developed equity market in the region, despite the development of the Dar es Salaam Stock Exchange and Uganda Securities Exchange in the past few years (Table A1.1). Government domestic debt markets are also more liquid and diversified in Kenya. Kenya and Uganda show a more diversified government domestic debt holder profile, with the banking sector holding about half of the domestic debt; in Tanzania, Rwanda, and Burundi, the share of the banking sector is in excess of 70 percent of the domestic debt (Tables A1.2–3).

Table A1.1.

Stock Market in Kenya, Rwanda, Tanzania, and Uganda

(As of March 30, 2016)

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Regional cross listing on another EAC stock exchange.

Sources: Stock exchange websites.
Table A1.2.

Holders of Government Domestic Debt in the EAC

(As of end-2015)

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Sources: EAC central banks and finance ministries.
Table A1.3.

Domestic Debt in Burundi, Kenya, Rwanda, Tanzania, and Uganda

(As of end-2015)

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Sources: EAC Central banks; and finance ministries. Note: Treasury bill.

Appendix II. Detailed Information on Migration and Remittance Flow

Table A2.1.

EAC Migration Matrix, 2010 and 2013

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Sources: World Bank, Migration and Remittances Factbook, 2011 and 2014.
Table A2.2.

Remittances per Migrant, 2010 and 2013

(U.S. dollars)

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Sources: World Bank, Migration and Remittances Factbook, 2011 and 2014; and IMF staff calculations.
Table A2.3.

EAC: Remittances by Country of Origin, 2010 and 2013

(Millions of U.S. dollars)

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Sources: World Bank, Migration and Remittances Factbook, 2011 and 2014.
Table A2.4

Intra-EAC Remittances by Country of Origin, 2010 and 2013

(Millions of U.S. dollars)

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Sources: World Bank, Migration and Remittances Factbook, 2011 and 2014.
Table A2.5.

Total Population in EAC Countries, 2000–14

(Millions)

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Source: IMF, World Economic Outlook, October 2016.

Appendix III. Capital Account Restrictions: Country-Specific Details

Kenya

  • Equities: In terms of residency, EAC investors are treated as local investors. There are no restrictions on purchases; however, issuances abroad by residents require Capital Market Authority (CMA) approval. For nonresidents, there is a regulation to limit foreign investors’ share up to 60 percent of the share of a capital of a listed company. Local issuance of securities by nonresidents requires CMA approval in accordance with the Capital Markets Act.

  • Money Market Instruments: No controls apply to purchases. However, both residents and nonresidents are subject to Central Bank Kenya approval for issuance of money market instruments (abroad for the former, locally for the latter).

  • Bonds: No controls apply to purchases. The issuance of bonds abroad by residents requires CMA approval. For nonresident sales, regulations governing securities of a participating nature apply.

Tanzania

  • Equities: Purchases of shares on the DSE by a foreign investor are subject to a limit of 60 percent of total securities issued. Individual investors may not acquire more than 1 percent of an issue, and institutional investors may not acquire more than 10 percent. Investments must be made from securities accounts with local banks to be transferable. A three-month holding period also applies. Foreign companies from prescribed territories (that is, companies from the EAC—Burundi, Kenya, Rwanda, Uganda) may issue securities to the public and be cross-listed at an approved stock exchange in Tanzania, subject to approval by the Capital Markets and Securities Authority (CMSA).

  • Money Market Instruments: Nonresidents (outside EAC) may not hold government securities. Currently, no money market instruments are available. Purchases by residents are allowed only if funded fully by external sources. However, this requirement does not apply if the purchase is within the EAC, and it must be reported to the Bank of Tanzania for statistical purposes.

  • Bonds: Nonresidents (outside the EAC) are not permitted to hold government securities. Purchases of bonds on the DSE by a foreign investor are subject to a limit of 60 percent of total securities issued. Individual investors may not acquire more than 1 percent of an issue, and institutional investors may not acquire more than 10 percent. Investments must be made from securities accounts with local banks to be transferable. A three-month holding period also applies. Purchases and redemption of corporate debt securities must be in local currency. Bond purchases by residents are allowed only if funded fully by external sources and must be reported to the Bank of Tanzania for statistical purposes. Sales of bonds abroad by residents are subject to CMSA approval.

Uganda

  • Equities: No restrictions

  • Money Market Instruments: No restrictions.

  • Bonds: No restrictions.

South Africa

  • Equities: Approval is required for local purchases by nonresidents. Servicing must be from foreign sources if the funds are used abroad, and from domestic sources if the funds are transferred to South Africa. Effective February 27, 2014, unlisted technology, media, telecommunications, exploration, and other research and development companies may apply to the Financial Surveillance (FinSurv) department of the South African Reserve Bank for approval for primary listing abroad or to raise loans abroad and operating capital. Effective, February 27, 2014, companies listed on the Johannesburg Stock Exchange (JSE) may have a secondary listing and/or list depository receipt programs on foreign exchanges to facilitate local and FDI expansion. Approval is required for foreign entities to list shares and securities on the JSE Limited. The funds raised by the issuer are freely transferable. All inward-listed shares on the JSE Limited traded and settled in rand are classified as domestic for the purpose of trading on the exchange and are included on the JSE indices; institutional investors may invest in such shares without affecting their foreign exposure limits. Effective April 1, 2015, purchases by resident individuals are allowed within the foreign capital allowance limit of R11mil. for each individual in a calendar year (R1mil. single discretionary allowance plus R10mil. foreign capital allowance) or from the proceeds of any authorized foreign asset. Approval is required for issuances by residents abroad.

  • Money Market Instruments: There are no restrictions on local purchases by nonresidents. Approval is required for foreign entities to list money market instruments on the JSE Limited. The funds raised by the issuer are freely transferable. Money market instrument purchases abroad by residents are allowed within the foreign capital allowance limit of R5mil. for each individual in a calendar year (R1mil. single discretionary allowance plus R4mil. foreign capital allowance) or from the proceeds of any authorized foreign asset. South African institutional investors may invest in rand-denominated instruments issued abroad and in instruments issued by South African corporations in the foreign market, subject to foreign portfolio investment allowances. Approval is also required for issuances abroad by residents. Servicing must be undertaken from foreign sources if the funds are used abroad, and from domestic sources if the funds are used in South Africa.

  • Bonds: Approval is required for nonresident investors to purchase bonds locally. Approval is required for foreign entities to list bonds or other debt instruments on the JSE Limited. The funds raised by the issuer are freely transferable. Similar to money market instruments, bond purchases abroad by residents are allowed within the foreign capital allowance limit of R5mil. (R1mil. single discretionary allowance plus R4mil. foreign capital allowance) a calendar year or from the proceeds of any authorized foreign asset. Approval is also required for residents to issue bonds abroad. Servicing must be from foreign sources if the funds are used abroad, and from domestic sources if the funds are transferred to South Africa. Effective February 27, 2014, unlisted technology, media, telecommunications, exploration, and other research and development companies may apply to FinSurv for approval for primary listing abroad or to raise loans abroad and operating capital. Effective, February 27, 2014, companies listed on the JSE Limited may have a secondary listing and/or list depository receipt programs on foreign exchanges to facilitate local and foreign direct investment expansion.

Appendix IV. An Analysis of Covered Interest Parity Condition for the EAC

Background

The covered interest parity (CIP) condition is one of the most relied upon indicators of financial market integration and market efficiency. Many models in international finance and open economy macroeconomics assume the CIP condition and use it as a key building block. CIP states that the actions of foreign exchange market participants, when hedged against exchange rate risk using the forward rates, should equalize interest rates on any two assets that differ only in currency of denomination.1 The CIP condition holds under the following four assumptions: (1) negligible transaction costs, (2) perfect capital mobility, (3) many participants in the spot and forward exchange markets with ample funds and no counterparty risk, and (4) underlying assets having identical political and default risk as well as liquidity, maturity, and seniority.

There has been considerable interest in investigations of whether CIP holds for a variety of currency pairs and asset types.2 Empirical tests mainly consider larger currencies and support the validity of the CIP condition with the exception of periods characterized by financial turbulence when counterparty risk is especially prevalent.

Algebraically, suppose that it,kd and it,kf and denote the interest rates on domestic currency and foreign-currency-denominated assets at time t, respectively, for an investment horizon of k. Suppose also that St denotes the spot exchange rate at time t—that is, the current price of one unit of foreign currency in domestic currency units—while Ft,k is the k-period forward exchange rate at time t—that is, the exchange rate currently agreed upon for a transaction k periods ahead. The CIP condition can be expressed as

F t , k = S t ( 1 + i t , k d ) ( 1 + i t , k f )

The actual k-period forward rate Ft,k may be different than the implied forward rate FCIP (right hand side of the equation) when any of the four CIP assumptions above is violated. This study treats violation of any of these assumptions under the general title “financial market impediments” and checks to see whether there are differences among EAC countries, where such markets exist, and compare the magnitude of such deviations to South Africa, a regional comparator. To that end the time series properties of deviations of the actual forward rate from the CIP implied forward rate, Δ, for different investment horizons (k= three, six, and 12 months) vis-à-vis the U.S. dollar are analyzed:

Δ = F t , k F C I P − 1

Data

Daily spot and nondeliverable forward (NDF) market exchange rates per U.S. dollar from 2011 to 2015 for Kenya, Tanzania, and Uganda for the EAC and the sub-Saharan Africa comparator South Africa are from Bloomberg (Figure A4.1).

Figure A4.1.
Figure A4.1.

Kenya, Tanzania, Uganda, and South Africa: Spot and NDF Exchange Rates (2011–15)

(National currency per US$)

Citation: Departmental Papers 2017, 001; 10.5089/9781475560350.087.A999

Source: Bloomberg.Note: 3m, 6m, and 12m stand for three-month, six-month and twelve-month maturities, respectively

The interest rate data used to calculate the implicit CIP in this study are three-, six-, and 12-month Treasury Bill (T-bill) auction yields for Kenya, Tanzania, and Uganda from the EAC as well as for South Africa for 2011 through 2015 and are from central bank websites and from Bloomberg. Daily T-bill data for the corresponding maturities for the United States are from Federal Reserve Economic Data. Daily secondary market T-bill rates are not available in any country in the sample. Hence, we rely on weekly auctions for Kenya, Tanzania, and South Africa, and biweekly auctions for Uganda; 364-day T-bill auctions were conducted once a month before March 2013 in Kenya, so the 12-month analysis for Kenya is restricted to the post-March 2013 period.

To derive descriptive statistics on CIP deviations, weekly averages of the daily data of the spot and NDF market exchange rates are calculated for Kenya, Tanzania, and South Africa while biweekly averages are calculated for Uganda. The corresponding maturity average U.S. T-bill yields (weekly and biweekly) are also calculated using daily data. All T-bill yields are available in annualized terms, the three-month implied forward exchange rate by first converting 91 -day annualized T-bill yields to three-month yields. Similarly, six-month yields are calculated from 182-day annualized T-bill yields. For the 364 days, annualized yields on 12-month T-bill rates are used. The implied CIP and the NDF for three-month, six-month, and 12-month horizons for Kenya, Tanzania, Uganda, and South Africa are plotted in Figures A4.2–5. Tables A4.1–3 provide summary statistics for the CIP deviations and the absolute CIP deviations, respectively.

Figure A4.2.
Figure A4.2.

Kenya: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

(National currency per US$)

Citation: Departmental Papers 2017, 001; 10.5089/9781475560350.087.A999

Sources: Central Bank of Kenya; Bloomberg; and IMF staff estimates.
Figure A4.3.
Figure A4.3.

Tanzania: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

(National currency per US$)

Citation: Departmental Papers 2017, 001; 10.5089/9781475560350.087.A999

Sources: Bank of Tanzania; Bloomberg; U.S. Federal Reserve; and IMF staff estimates.
Figure A4.4.
Figure A4.4.

Uganda: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

(National currency per US$)

Citation: Departmental Papers 2017, 001; 10.5089/9781475560350.087.A999

Sources: Bank of Uganda; Bloomberg; U.S. Federal Reserve; and IMF staff estimates.
Figure A4.5.
Figure A4.5.

South Africa: Actual and Implied Forward Exchange Rates (2011–15)

(National currency per US$)

Citation: Departmental Papers 2017, 001; 10.5089/9781475560350.087.A999

Sources: Reserve Bank of South Africa; Bloomberg; U.S. Federal Reserve; and staff estimates.
Table A4.1.

Summary Statistics of CIP Deviations Relative to the United States

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Sources: Bloomberg; and IMF staff calculations.

Twelve-month T-bill auctions were conducted once a month until March 2013 in Kenya. The descriptive statistics reported in the table for 12-month maturity are based on weekly auctions since March 2013. 12-month NDF rates for Tanzania are not available since September 2015.

Table A4.2.

Summary Statistics of Absolute CIP Deviations Relative to the United States

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Sources: Bloomberg and IMF staff calculations.

Twelve-month T-bill auctions were conducted once a month until March 2013 in Kenya. The descriptive statistics reported in the table for 12-month maturity are based on weekly auctions since March 2013. 12-month NDF rates for Tanzania are not available since September 2015.

Table A4.3.

Summary Statistics of Absolute CIP Deviations Relative to the EAC1

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Sources: Bloomberg; World Economic Outlok database; and IMF staff calculations.

For each country, generic EAC averages are calculated for each variable in the CIP, using purchasing power parity GDP weights of the remaining two countries.

Twelve-month T-bill auctions were conducted once a month until March 2013 in kenya. The statistics reported in the table for 12-month maturity is based on weekly auctions since March 2013. 12-month NDF rates for Tanzania is not available since September 2015.

Appendix V. Application of Convergence Concepts in the EAC

Background

The concept of financial market integration is closely related to the law of one price.1 Capital mobility, when not impeded, would ensure that financial market prices—yields—of assets identical in denomination, maturity, and risk would be the same. Thus, the presence of differences in (1) capital controls, (2) underlying risks, and (3) expectations of currency movements would cause a “wedge” among financial prices or implied returns. Such conditions in general do not hold.2 Nevertheless, it would still be informative to see the evolution of the wedge to see if such differences among countries move in the “right” direction—that is, if the dispersion of such yields is decreasing in time or the returns are converging. A reduction in dispersion, or “convergence” of yields of assets with the same maturity, would indicate increasing financial integration through reduction in capital controls and/or diminishing of differences in underlying risks, and expectations of currency depreciation/ appreciation for the duration of the holding period.

Data and Methodology

The preceding analysis introduces the concepts of β-convergence and σ-convergence in yields of selected assets and maturities within the EAC countries during 2011–15. Specifically, it considers weekly stock market returns in the EAC (with the exception of Burundi); weekly averages of overnight interbank rates; and weekly and biweekly three-, six-, and 12-month T-bill auction yields in domestic currencies.3 Data are from Bloomberg and EAC country central banks (Figure A5.1).

Figure A5.1.
Figure A5.1.
Figure A5.1.

Various EAC Financial Returns Data Used in Convergence Analysis

Citation: Departmental Papers 2017, 001; 10.5089/9781475560350.087.A999

Two different convergence concepts are used: β-convergence and σ-convergence, because they capture different aspects of financial integration. While the former shows to what extent financial convergence has been achieved within the EAC in the observed sample, the latter shows whether markets are moving toward integration over time.

β-convergence enables the identification of the speed at which shocks are eliminated on the yields of assets with identical maturities traded in EAC countries’ financial markets. The measure involves estimating the following time series regression for each country or panel regression for the whole EAC:

Δ S p r e a d i , t = β 0 + β 1 S p r e a d i , t − 1 + Σ j = 1 N γ j Δ S p r e a d i , t − 1 + ɛ i , t

Spread variable denotes the spread of yield on an underlying asset of a specific maturity (one day or three, six, or 12 months) between country i and the synthetic EAC region, formed from the PPP-GDP weights of the remaining four EAC countries.4 The weights are Burundi, 2.3 percent; Kenya, 36.6 percent; Rwanda, 5.2 percent; Tanzania, 35.1 percent; and Uganda, 20.7 percent in 2013. Nrepresents the number of lags used in this regression to clean the residuals from autocorrelation. In our estimations we include lags up to eight weeks during 2011–15.

The β0 coefficient would provide the average “wedge” between an underlying asset for a specific maturity (one day or three, six, or 12 months) between country i and the synthetic EAC region. The β1 coefficient, if significantly negative, would suggest the existence of convergence—that is, mean reversion taking place between country i and the synthetic EAC region for an underlying asset for a specific maturity (one day or three, six, or 12 months). The magnitude of the β1 coefficient would denote the speed of convergence, with speed increasing in β1. Panel- and country-specific time series regression results are given in Table A5.1.

σ-convergence occurs when the dispersion of the levels of a yield of a specific asset between different EAC countries tends to decrease over time. The concept owes its origins to seminal work by Barro and Sala-i Martin (1992) on cross-sectional dispersion of income. The current analysis checks whether the dispersion, “σ,” tends to decrease over time for a number of selected assets in the EAC:

σ t = [ 1 n − 1 Σ i = 1 n ( R i , t − R ¯ t ) 2 ] 1 2

Rit denotes the return for an asset in country i at time t, and R¯t denotes the EAC-wide mean return at time t. Lower σ values imply higher levels of financial convergence. In theory, full integration (“law of one price”) would be implied when the standard deviation is zero. Figure A5.2 gives the evolution of σ within EAC for a number of assets.

Table A5.1.

Pooled and Individual Beta Coefficients of EAC Countries’ Selected Asset Yields (2011–15)

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Sources: Bloomberg EAC authorities; IMF staff estimates. Note: Standard errors in parentheses. *** denotes significance at 1 percent, ** at 5 percent, and * at 10 percent levels.
Figure A5.2.
Figure A5.2.
Figure A5.2.

Sigma-Convergence Analysis for the EAC Countries

Citation: Departmental Papers 2017, 001; 10.5089/9781475560350.087.A999

The analysis focuses on merchandise trade because of data quality and availability issues on services. Aggregate trade data are from the International Monetary Fund (IMF)’s Direction of Trade Statistics. Sectoral-level trade and tariff data are from World Bank’s World Integrated Trade Solution (WITS) database. Specifically, WITS provide access to sectoral level trade data from the United Nations’ Comtrade database and tariff data from the UNCTAD Trade Analysis and Information System (TRAINS) database.

1

South Sudan was admitted as a new member state in early 2016. It is not covered in this paper.

3

EAC partner states have a long history of monetary and trade arrangements. As early as 1917, Kenya and Uganda formed a customs union, which the then Tanganyika joined in 1927. After independence, in 1966, the then common currency became fully convertible legal tender in Kenya, Uganda, and Tanzania (see Drum-mond, Wajid, and Williams 2015 for more detail on the EAC background).

4

During 2005-11, per capita income growth reached 3.6 percent a year in the EAC, compared with 3.0 percent for sub-Saharan Africa as a whole.

5

Informal cross-border trade between EAC countries is generally thought to be significant but by nature is not well captured in trade statistics.

The analysis focuses on merchandise trade because of data quality and availability issues on services. Aggregate trade data are from the International Monetary Fund (IMF)’s Direction of Trade Statistics. Sectoral-level trade and tariff data are from World Bank’s World Integrated Trade Solution (WITS) database. Specifically, WITS provide access to sectoral level trade data from the United Nations’ Comtrade database and tariff data from the UNCTAD Trade Analysis and Information System (TRAINS) database.

1

This tariff rate is referred to as the Effectively Applied (AHS) rate in the WITS database, usually denoted as the lowest available tariff. This paper also uses “most favored nation tariffs,” which are generally applicable to countries that are part of the World Trade Organization (WTO), unless the country is part of a preferential trade agreement, in which case there is the “preferential tariff.” In the case of the EAC, because member countries adopted the tariff rates under the trade agreement of the EAC, the formal tariff rates and the effective tariff rates are the same.

2

The fact that the ratio of imports from other EAC countries to GDP is much higher in landlocked countries begs the question of the treatment of transit trade. For Burundi, Rwanda, and Uganda, the transit trade may incorrectly appear as imports from Kenya and Tanzania, the two EAC countries with ports and access to the sea, if not recorded properly.

3

More details on the gravity setup can be found in IMF 2015a, Chapter 2 on “Global Value Chains: Where Are You? The Missing Link in Sub-Saharan Africa’s Trade Integration.”

4

Table 2 shows the results for 2009–13 compared with the results for the whole period. They suggest that the EAC integration gap with Europe has decreased over recent years, but also that the EAC’s edge over the rest of Africa has disappeared. Due to lack of data for many sub-Saharan African countries, the gravity model estimations do not include a measure of industrialization.

1

These include administrators and managers (such as managing directors, executive secretaries, university vice chancellors, finance managers, planning and development managers, production and operations managers), professionals (such as civil/industrial/production/mechanical engineers, medical doctors, higher education teachers, system analysts, lawyers, performing artists, musicians), and craft and related trade workers (such as air traffic and ship controllers and technicians and metal, machinery, and related trade workers).

2

The following are partner states commitments to remove barriers by end-2015: Burundi — Professionals — by 1st July 2010; Kenya — Managers, Professionals, Technicians and Associate Professionals, and Craft and Related Trades Workers — by 1st July 2010; Rwanda — Professionals and Technicians and Associate Professionals —by 1st July 2010; Tanzania — Professionals and Technicians and Associate Professionals— ranging from by 1st July 2010 to 2015; Uganda — Managers, Professionals and Craft and Related Trades Workers—by 1st July 2010.

3

See, for example, the annual report of the African Development Bank (2014) and Basnett (2013).

4

For instance, money transferred in cash or via other means between friends, family members, or community members. According to Freund and Spatafora (2005), the proportion of informal transfers to sub-Saharan Africa could represent between 45 and 65 percent of formal flows. A World Bank (2006) study indicated that only a quarter of central banks in the sample collected data on informal transfers via the use of special inquiries, by questioning either migrants upon return to their country, or recipient households.

5

Common Market Protocol, Articles 7, 13, and 14.

6

The EAQFHE is the result of joint efforts between the Inter-University Council for East Africa, the East African Business Council, and representatives from partner states.

7

Migration flows from and to the EAC as a whole remain relatively low. The number of EAC migrants (whether to another EAC country or the rest of the world) is estimated to have increased from about 1.5 million in 2000 to about 2 million in 2013. As there is a rapidly growing population, this represents a decline as a share of total population from 1.5 percent in 2000 to about 1.3 percent in 2013, well below the world average migration rate of 3.5 percent. This ratio, however, is much higher for the small landlocked countries in the EAC (Burundi and Rwanda) than the other ones. Immigrants to the EAC number about twice as many as EAC citizens living abroad. The latter are about 800,000, a number that has remained relatively stable between 2000 and 2013, while the numbers of immigrants to the EAC has increased by about 40 percent during that period.

8

The rate of skilled emigration is the ratio of tertiary-educated emigrants to the population with tertiary education. Data are available only through 2000.

9

In 2013, the average migrant from the EAC sent home about $1,312 a year. Migrants residing in the United Kingdom and the United States sent an average US$3,003 and $3,481 a year in 2013, respectively. However, migrants residing in the EAC sent home only about US$500 a year on average (with those in Burundi sending, on average, $360).

10

This reflects to some extent different geographic orientations of migration flows, with most Kenyans emigrating to advanced countries and Burundians staying in the EAC and neighboring countries. This could also reflect the fact that most Burundian regional migrants reside in temporary settlements or refugee camps, and their living conditions, combined with the absence of financial infrastructure, likely do not allow them to send money (Fransen and Mazzucato 2014).

1

EAC Secretariat. The 2014 scorecard is available at https://www.wbginvestmentclimate.org/publications/upload/East-African-Common-Market-Scorecard-20l4.pdf. The 2016 EAC Common Market Scorecard was released on October 28, 2016.

3

Tanzania liberalized its capital account partially in July 2014, allowing nonresidents to participate in the Dar es Salaam Stock Exchange securities and to some limited extent in government securities for EAC residents. These have not been reflected in the EAC Scorecard.

4

The Chinn-Ito index takes the first principal component of the AREAER summary binary codings of controls related to current account transactions, capital account transactions, multiple exchange rate, and the requirements of surrendering export proceeds.

5

The 10 categories are (i) money market instruments; (ii) bonds or other debt securities; (iii) equity, shares of other securities of a participating nature; (iv) collective investment securities; (v) financial credit and credits other than commercial credit; (vi) derivatives; (vii) commercial credits; (viii) guarantees, sureties, and financial backup facilities; (ix) real estate transactions; and (x) direct investment.

6

The Chinn-Ito index is not sufficiently nuanced to pick up the limited easing of restrictions on Tanzanian capital accounts in 2014.

7

The synthetic EAC region is formed from the purchasing power parity (PPP)-GDP weights of the five EAC countries. The weights in 2013 are Burundi, 2.3 percent; Kenya, 36.6 percent; Rwanda, 5.2 percent; Tanzania, 35.1 percent; and Uganda, 20.7 percent.

8

Kenya, Rwanda, and Uganda are also COMESA members. Other members are Burundi, Comoros, the Democratic Republic of the Congo, Eritrea, Ethiopia, Madagascar, Malawi, Mauritius, Seychelles, Swaziland, Zambia, and Zimbabwe.

9

In contrast, South Africa restricts mostly capital outflows.

10

The absence of liquid foreign exchange market among the EAC currencies and the use of NDF rates necessitate basing the analysis on bilateral exchanges with respect to the U.S. dollar. Implicit forward rates based on the CIP condition for the three EAC countries and South Africa are derived from weekly data from 2011 to 2015 on Treasury Bill (T-Bill) auction yields for three-, six-, and 12-month horizons for Kenya and South Africa, and biweekly data for Tanzania and Uganda; weekly averages of daily secondary market U.S. T-bill rates for three-month, six-month, and 12-month maturities; and weekly averages of daily bilateral daily spot exchange rates with respect to the U.S. dollar. The implicit forward rates for each country and each maturity are then compared with actual NDF rates to derive deviations from the NDF based CIP condition (Annex IV). See also Wang (2010).

12

The table shows CIP deviations with respect to the United States. Deviations for each member from a generic EAC country excluding that member were also looked at, using cross-rates. The results did not change (Table A2.3)

13

The former is a necessary but not sufficient condition for the latter. Both concepts must be tracked concurrently for evidence on convergence. See Young and others (2008).

1

See for example, Alper and Ardic (2010).

2

See Officer and Wilier. (1970) and Taylor (1992) for comprehensive surveys of this literature.

2

In a monetary union, for example, conditions (1) and (3) would mostly be the same across member coun-tries but condition (2) may still be different.

3

As discussed earlier, there are no formal onshore forward market rates in the EAC countries to show market expectations of depreciation/appreciation during the holding period of an asset. One option would be to analyze ex post returns in U.S. dollars based on actual changes in currencies’ values during the holding period, but that would bring additional noise in the data. Thus, identical rates of expected depreciation or appreciation among EAC countries were assumed.

4

Yabara (2012) uses Kenya as the benchmark market. For each country, this paper uses as the benchmark country a synthetic EAC country (based on PPP GDP weights) after excluding the country itself. This methodology enables reporting results also for Kenya.

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Cover Departmental Papers
A Work in Progress: Integrating Markets for Goods, Labor, and Capital in the East African Community
Author:
Mr. Emre Alper
,
Ms. Wenjie Chen
,
Mr. Jemma Dridi
,
Mr. Herve Joly
, and
Mr. Fan Yang
Volume/Issue:
Volume 2017: Issue 001
Publisher:
International Monetary Fund
ISBN:
9781475560350
ISSN:
2616-5333
Pages:
76
DOI:
https://doi.org/10.5089/9781475560350.087
  • <sup><xref ref-type="fig" rid="RA01app4fig1">Figure A4.1</xref></sup>.
    View in gallery
    Figure A4.1.

    Kenya, Tanzania, Uganda, and South Africa: Spot and NDF Exchange Rates (2011–15)

    (National currency per US$)

  • <sup><xref ref-type="fig" rid="RA01app4fig2">Figure A4.2</xref></sup>.
    View in gallery
    Figure A4.2.

    Kenya: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

    (National currency per US$)

  • Figure A4.3.
    View in gallery
    Figure A4.3.

    Tanzania: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

    (National currency per US$)

  • Figure A4.4.
    View in gallery
    Figure A4.4.

    Uganda: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

    (National currency per US$)

  • <sup><xref ref-type="fig" rid="RA01app4fig5">Figure A4.5</xref></sup>.
    View in gallery
    Figure A4.5.

    South Africa: Actual and Implied Forward Exchange Rates (2011–15)

    (National currency per US$)

  • <sup><xref ref-type="fig" rid="RA01app5fig1">Figure A5.1</xref></sup>. <sup><xref ref-type="fig" rid="RA01app5fig1">Figure A5.1</xref></sup>.
    View in gallery
    Figure A5.1.

    Various EAC Financial Returns Data Used in Convergence Analysis

  • <sup><xref ref-type="fig" rid="RA01app5fig2">Figure A5.2</xref></sup>. <sup><xref ref-type="fig" rid="RA01app5fig2">Figure A5.2</xref></sup>.
    View in gallery
    Figure A5.2.

    Sigma-Convergence Analysis for the EAC Countries

Figure A4.1.

Kenya, Tanzania, Uganda, and South Africa: Spot and NDF Exchange Rates (2011–15)

(National currency per US$)
Figure A4.2.

Kenya: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

(National currency per US$)
Figure A4.3.

Tanzania: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

(National currency per US$)
Figure A4.4.

Uganda: Actual (NDF) and Implied Forward Exchange Rates (2011–15)

(National currency per US$)
Figure A4.5.

South Africa: Actual and Implied Forward Exchange Rates (2011–15)

(National currency per US$)
Figure A5.1.

Various EAC Financial Returns Data Used in Convergence Analysis
Figure A5.1.

Various EAC Financial Returns Data Used in Convergence Analysis
Figure A5.2.

Sigma-Convergence Analysis for the EAC Countries
Figure A5.2.

Sigma-Convergence Analysis for the EAC Countries