67998 POLICY NOTE NO. 29 MARCH 2012 Africa Trade Policy Notes Olivier Cadot and Julien Gourdon Assessing the Price Raising Impact of Non-Tariff Measures in Africa Ample anecdotal evidence summarized in, inter alia, Gillson (2011) and HIGHLIGHTS Charalambides and Gillson (2011) suggests that non-tariff measures (NTMs), whether protectionist in intent or not, raise trade costs and NON-TARIFF MEASURES… inhibit regional trade in Africa.1 Beyond old-style quantitative restrictions raise trade costs and inhibit regional (QRs) and bans, even measures that could be potentially justified by trade in Africa resulting in higher market failures like Sanitary and Phytosanitary (SPS) measures or prices that hurt low-income product standards are often ill-suited to both consumer protection needs households. and State monitoring capabilities, generating unnecessary hurdles. The result is, potentially, higher prices hurting low-income households. IN AFRICA… However, beyond the anecdotal evidence, little is known about the the proportion of imported goods magnitude of the price-raising effects involved. The incidence of subject to non-tariff measures is large NTMs—how prevalent they are—is usually measured by so-called with East African countries having ―coverage ratios‖ which are in essence simple counts of how many higher coverage ratios, with the products, say at the HS6 level2, are covered by one or more NTM. The exception of Tanzania and Madagascar product lines can also be weighted by the amount of imports. However, this tends to understate the importance of restrictive NTMs since imports will be reduced where they are most restrictive. DATA RESULTS … show that Sanitary and Phytosanitary measures in Africa raise prices by anything between 12-25%, these measures raise substantially the price of cereals in Kenya, with ad-valorem equivalents of 42% for rice and 39% 1 Not all NTMs are necessarily Non-tariff barriers: some NTMs may not be unduly trade for other cereals restrictive with many of these measures being applied for genuine public policy objectives however, barriers to trade may arise through bad design and/or weak implementation. The book De-Fragmenting Africa illustrates that key barriers to trade in Africa arise from non-tariff measures. http://go.worldbank.org/MKK5U1Y2D0 The Harmonised System (HS) is a common product classification used for the coding 2 of imports and exports. The 6 digit level is the lowest level at which codes are harmonised globally and includes around 5000 separate product descriptions WORLD BANK 1 | www.worldbank.org/afr/trade Similarly, if a particular NTM becomes more authors regress prices collected by the Economist restrictive and reduces imports then the coverage Intelligence Unit at the city level (to guide indicator may actually fall - the opposite of what expatriate compensation) on suitably coded should happen. NTMs at the national level as well as control variables. Making the NTM more restrictive may then reduce the coverage ratio, which is the opposite We follow the price-based strand of the literature of what a coverage ratio is supposed to pick up. and estimate the price-raising effect of NTMs by This is a well-known problem which affects combining two databases. The first one was weighted-average tariffs as well. As for the NTMs’ compiled as part of the World Bank’s effect on trade (their severity), an important International Comparison Project (ICP) and strand of the literature has focused on the contains prices for 63 products and 42 services in variation in trade flows induced by the presence 147 countries for the year 2005. Unfortunately, of NTMs to infer their ad-valorem equivalents the results of a new wave of data collection for the (AVEs), i.e. the rate at which tariffs would have year 2011 are not yet available. Data made the same effect on trade flows (Deardorff and available to the public is very limited, so we used Stern (1998) or Kee et al. (2009)). the more complete database available only to World Bank staff. The second is an NTM As for the NTMs’ effect on trade (their severity), database compiled as part of a multi-agency an important strand of the literature has focused project to replenish the UNCTAD Trade on the variation in trade flows induced by the Analysis and Information System (TRAINS) presence of NTMs to infer their ad-valorem database. equivalents (AVEs), i.e. the rate at which tariffs would have the same effect on trade flows Data and Stylized Facts: What are NTMs? (Deardorff and Stern (1998) or Kee et al. (2009)). The term ―NTM‖ designates a vast array of Another strand, on which this paper draws, has heterogeneous regulatory instruments. The sought to estimate AVEs by comparing directly simplest way of characterizing them is through the home (NTM-ridden) product prices with the Multi-Agency Support Team (MAST) prices of similar products on markets where nomenclature, adopted by UNCTAD’s Group of those products are free of distortions, in order to Eminent Persons in July 2009. This obtain an estimated ―price gap‖. This method can nomenclature is currently under revision by the be applied by simple comparison of averages on World Trade Organization’s (WTO) legal a case-by-case basis (a prominent example of this department in order to make it suitable for the approach is the recent database of agricultural notification of measures by member states; it will distortions compiled at the World Bank—see thus change in the near future, but changes are Anderson et al. 2008; see Ferrantino 2006 for unlikely to be drastic. The logical structure of the other examples), or econometrically (see e.g. nomenclature, at its highest degree of aggregation, Andriamanjara et al. 2004). In the latter case, the is shown in Figure 1. 2 | www.worldbank.org/afr/trade Figure 1: The MAST nomenclature of NTMs TECHNICAL A SPS measures MEASURES B Technical regulations C Pre-shipment inspection D Price-control measures E Licenses, quotas, prohibitions and QRs IMPORT F Charges, taxes & para-tariff measures MEASURES G Finance measures H Anti-competitive measures NON- I TRIMs TECHNICAL J Distribution restrictions MEASURES K Restrictions on post-sales services L Subsidies (excluding export subsities M Government producrement restrictions N Intellectual property O Rules of origin P Export measures (including export subsidies) Categories A and B (Sanitary and Phytosanitary - Subsidies are often to certain companies and not SPS and Technical Barriers to Trade - TBT to other depending on their location, ownership measures) are often referred to as ―technical‖ status (ethnic minorities, special groups and so ones. Categories C to O are non-technical ones on), or type (SMEs). It is difficult to track all and cover a mixture of command-and-control subsidies granted under the myriad of schemes types of measures (price controls, quantitative typically in place to serve various societal restrictions and prohibitions) and a disparate set purposes, and even more difficult to decide when of measures. Some, like pre-shipment inspection they are sufficiently prevalent to be ascribed to a (category C), are easy to track and affect all particular product. products. Some, like taxes and para-tariff measures (category F) are much easier to track as Rules of origin are another category of non-tariff they are often administered in a transparent way, measure. They are required in preferential trade serving ostensibly to finance border-management agreements to identify which countries are administrations whose function is not always eligible for reduced or zero tariffs. However, they clear. As for measures G to O (in italics), some of can be designed in a way which makes them them are important and relatively straightforward costly to satisfy, which limits the impact of the to identify, like anti-competitive measures like trade preferences. Rules of origin are also forced channels (category H) and distribution necessary to apply contingent protection restrictions (J). Some other are very difficult to measures such as anti-dumping and safeguard code at the product level, like Trade-Related measures. Investment Measures (TRIMS) (I) or intellectual Thus, including them in the MAST property (N). Subsidies (L) are a particularly nomenclature gives an appearance of exhaustivity difficult case because of the loose definition given but are difficult to operationalize for quantitative by the MAST: work. ―Financial contribution by a government or Lastly, export measures (category P) are of government body to a production structure, being growing importance, especially for foodstuffs in a particular industry or company, such as direct times of rising food prices. Gillson (2011) argues or potential transfer of funds (e.g. grants, loans, that export restrictions in times of high prices equity infusions), payments to a funding contribute to reduce incentives to expand mechanism and income or price support‖ production, and thus make shortages worse both 3 | www.worldbank.org/afr/trade over time (because supply does not react) and monitoring and testing capabilities would be able across space (as producers in surplus regions are to handle fewer measures and therefore put fewer banned from arbitraging price differences, so on the books. This is not the case, suggesting, as price spikes in deficit regions are not dampened argued by Gillson (2011), that there is some by increased imports). Thus, export restrictions overkill even in ―modern-type‖ measures like exert negative regional externalities and increase SPS and technical regulations. consumer price volatility.3 In addition, some countries, like Kenya and Data: NTMs in Africa Burundi, are characterized by the simultaneous application of many measures (up to five) to the Data on NTMs is available through a recent data same product, as shown in Figure 3. This may collection effort undertaken jointly by the World well translate into overly complicated compliance Bank, UNCTAD and the African Development verification processes for traders. Bank. The data consists of tables with HS6 products in rows and NTMs, coded according to Patterns of coverage by type of foodstuff product the 2009 MAST nomenclature, in columns. It seem to vary more systematically by country than also contains references to the relevant legal texts by product, as shown in Figures 4 and 5. as well as indications on the issuing and/or Madagascar and Senegal have relatively few enforcing agency. The data has been collected measures on fats & oils, vegetable products and either by national governments under the prepared foods compared to other countries. coordination of regional secretariats, as in Latin The case of live animals is special given that a America, or by local consultants hired by the large part of the trade in live animal across World Bank or the African Development Bank. African borders is informal and escapes controls, In the latter case, it has been endorsed by so that measures applied to this category of governments through validation workshops held product are largely notional—although this at the end of the data collection process. remark applies to varying extents to many products and countries on the continent. By and large, the proportion of imported goods subject to NTMs is large, as shown in Figure 2 Lastly, the data suggests that old-style command- where the LHS shows the proportion of product and-control measures (quantitative restrictions lines covered by NTMs (the frequency ratio) and (QRs) and price controls) have largely receded in the RHS shows the share of imports (the the region, at least on the books, with the coverage ratio). It can be seen that East African exception of Namibia. However, this data should countries have fairly high coverage ratios, with the be interpreted cautiously as NTM inventories exception of Tanzania and Madagascar. In record only permanent measures and almost only accordance with the analysis of the previous those affecting imports, whereas Gillson (2011) section, the E.U. has very high frequency and notes numerous instances of temporary bans, coverage ratios, as public demands for traceability especially on exports. Thus, the picture should be and product safety are very high. However, one seriously nuanced in view of the data’s would expect that low-income countries with low incompleteness for a category of measures that is, judging by anecdotal evidence, on the rise. 3 However, it should be kept in mind that—at least in principle—they reduce producer-price volatility, as local prices co-variate negatively with volumes in autarky, whereas they don’t under integrated markets with a given international price. 4 | www.worldbank.org/afr/trade Figure 2: Proportion of HS6 product lines and imports covered by one or more NTM Share of Product Lines Share of Imports EU Asia MENA LAC Tanzania Senegal Madagascar South Africa Mauritius Namibia Kenya Uganda Burundi 100 80 60 40 20 0 20 40 60 80 100 Figure 3: Frequency ratios by number of NTMs applied simultaneously to the same good 100.0 90.0 80.0 70.0 60.0 5 and more 50.0 4 types of NTMs 40.0 3 types of NTMs 30.0 20.0 2 types of NTMs 10.0 1 type of NTMs 0.0 5 | www.worldbank.org/afr/trade Figure 4: Frequency ratios by type of product Figure 5: Coverage of foodstuffs by type and country, foodstuffs of measure 100 100 80 60 80 40 60 20 40 0 20 Burundi South Africa 0 Mauritius A: SPS Kenya Live Animal B: TBT Namibia Prepared Food Uganda C: Inspection Vegetables products Madagascar D: Price control Senegal Fats & Oil E: QRs Tanzania All in all, the picture that emerges is one where import and the export side, still disrupt the SPS measures and technical regulations have functioning of regional food markets. For spread while QRs and prohibitions have receded, instance, Gillson and Charalambides but this overall picture masks two important (forthcoming) note that up to one third of intra- stylized facts: (i) Many SPS measures seem to be SADC trade is potentially affected by non-tariff ill-designed given local monitoring and testing barriers notified under the SADC monitoring capabilities; (ii) many temporary QRs, on the mechanism (Table 1) Table 1: Intra-SADC trade potentially affected by notified NTBs % of intra-SADC trade Barrier Examples of products affected potentially affected Wheat, beer, poultry, flour, meat, maize, UHT milk, cement, Import bans, quotas & levies sugar, eggs, pasta, sorghum, pork, fruit & vegetables 6.1 Preferences denied Salt, fishmeal, pasta 0.4 UHT milk, bread, eggs, sugar, fruit & vegetables, livestock, Import permits & levies liquor, cooking oils, maize, oysters 5.4 Single marketing channels Wheat, meat, dairy, maize, tea & tobacco, sugar 5.3 Textiles & clothing, semi-trailers; palm oil; soap; cake Rules of origin decorations; rice; curry powder; wheat flour 3.0 Dried beans, live animals, hides, skins, sugar, tobacco, Export taxes maize, meat, wood, coffee 4.8 Milk, meat, canned tuna, beer, honey, maize bran, cotton Standards/SPS/TBT cake, poultry, batteries, sugar, coffee, ostriches 2.5 Wine, electronic equipment, copper concentrate, salt, Customs-related cosmetics, medicines 5.2 Total 32.7 Source: Gillson and Charalambides (2011) 6 | www.worldbank.org/afr/trade In a recent firm-level survey carried out in five tariff on rice indicated in the TRAINS database SADC countries cited by Gillson and (and used in this paper) is 57%, whereas a United Charalambides (forthcoming), ―roughly 80 States Department of Agriculture (USDA) percent of the respondents indicated that they document (USDA 2010) mentions the faced some form of trade barrier within the imposition of a 75% common external tariff on region […]. Over half of the respondents rice in the EAC starting in 2005. If the USDA indicated that the cost of these was equivalent to 5 figure was right, our 42% AVE would pick up percent of the Cost, Insurance and Freight (CIF) 18% (75 – 57) that is actually attributable to the value of the imports/exports. A further 24 CET, which would leave a more reasonable AVE percent of respondents indicated a 5-15 percent of 24%. Clearly, something happened to the rice attribution to trade barriers; and, 23 percent market in Kenya in 2005, as shown in Figure 6. faced increased trade costs of over 15 percent‖ (p. 4). We will see later on in this paper that the Figure 6: Rice consumption per capita, Kenya econometric estimation of ad-valorem equivalents 13 (AVEs) of NTMs yields estimates in that range. 12.5 Estimation and Results 12 From our estimations we find that SPS measures 11.5 in Africa raise prices by anything between 12- 25%4. AVEs for TBT measures are not estimated 11 sufficiently precisely to reject the null hypothesis of no effect. This is in accordance with intuition, 10.5 2001 2002 2003 2004 2005 2006 2007 2008 2009 as product standards are likely to have very heterogeneous effects depending on how they are Source: USDA (2010). Note: Kilos per capita per year administered on the ground—in SSA, standard- enforcement agencies are often empty shells in However, it is difficult to ascribe this turning practice. PSI and other formalities have price- point in consumption to changes in the NTM raising effects ranging between 14% and 21%. regime, as most of the regulations affecting rice5 Price measures, surprisingly, have no significant are based on the 1923 Plant protection Act and effect, again a reflection of their heterogeneity. By do not seem to have been affected by new contrast, QRs have, where they are significant, a measures taking effect in 2005. Of course, one price-raising effect of 19%. Needless to say, these cannot rule out changes in implementation estimated effects must be interpreted very policies, but the adoption of the CET is a more cautiously in view of their weak identification. plausible candidate. We find that SPS measures raise substantially the In Uganda, rice and other cereals fetch the price of cereals in Kenya, with AVEs of 42% for highest AVE, at 30%. The remark above about rice and 39% for other cereals. Although our the rate of the EAC CET starting in 2005 applies AVEs are corrected for tariffs, it is possible that to Uganda as well, so the AVE should be also the one on rice picks up some tariff effect, as the interpreted cautiously. With a CET at 75%, it would fall to 12% instead of 30%. Domestic rice production has been encouraged by Ugandan 4 this range is a result of using different estimation methods 5 HS codes 110610-110640 7 | www.worldbank.org/afr/trade authorities since the beginning of the 2000s, with Concluding Remarks several projects financed by Japan and other donors to promote smallholder production. Our results are very preliminary and should be Consumption has also been rising substantially interpreted with many caveats, the first and (by a factor of three over a decade, according to foremost being that the degree of disaggregation informal estimates by the FAO representative in of the product nomenclature on which we base Kampala), in spite of the rising domestic price.6 our AVE calculations is much too coarse to match the degree of disaggregation of the NTM Poultry meat also has an AVE of 42% in Kenya, database. This is an area where further, whereas edible oils, another important staple, systematic data collection is urgently needed. have an AVE of 29.5%. In Uganda, the AVE on edible oils is 29.3%. The case of edible oil in There is also a need to make progress with some Uganda is one where import competition issues of the technical issues relating to the way that the are at the center of the policy debate. A web site estimates of AVEs are derived, in particular, the recently reported that way that NTMs are linked to prices. ―Edible oil producers through their umbrella Analytically, clearly more research is needed to organization, the Uganda Oil Producers and improve the identification strategy, as the choice Processors Association (UOSPA) have appealed of instrumental variables is limited given the data to government to introduce protectionist at hand and the political-economy literature gives measures against imported varieties, which they little guidance in terms of functional forms linking say come from subsidized sources that rendered NTM to prices (most of the literature links tariffs local products less competitive.‖7 to import levels). Beyond alleged subsidies in Malaysia (a major This said, given the data limitations, results are source of edible oil imports), domestic producers surprisingly precise and robust. They also complained about common issues—subsidies corroborate the factual analysis of Gillson 2011) tilted toward the dominant domestic producer, and Charalambides and Gillson (forthcoming). Mukwano, difficult access to land for expansion, Whereas SPS measures are generally those with and high electricity prices. the strongest rationale in terms of addressing potential market failures, in Sub-Saharan Africa In South Africa, NTMs on potatoes8 have a they seem to be designed and implemented in a whopping 64.35% AVE, on account of a way that makes them cumbersome and costly. restrictive (non-automatic) licensing system. Indeed, our estimation suggests that they raise the price of foodstuffs by anything between 15% and 20-25%, a range that makes these effects non- 6 http://www.africanagricultureblog.com/2008/11/uganda- increases-production-decreases.html. trivial for poor households. 7 See http://www.sunrise.ug/business/77-business/1841- This of course does not mean that SPS measures edible-oil-producers-want-protection-from-imports-.html. should be abolished, but rather that they deserve policy attention in terms of improving design and 8 Potato importers into South Africa must obtain a licence from the Director General of Agriculture, Marketing and Administration and a permit from the Directorate of Plant Egypt), accounting for 15% of imports of processed fruit, and Quality Control. They also fetch a 30% MFN tariff vegetables and agri-food other products (ITC 2010). (7.5% from the E.U. and tariff-free from SADC). Potato production is very important in South Africa, although it is also a substantial import item (from, inter alia, Argentina and 8 | www.worldbank.org/afr/trade simplifying implementation. In view of the ample Benefits of Non-Tariff Measures in Agri-Food experience on the ground, the direction of Trade‖; Iowa State University working paper improvement is clear: Systematic inspections 11001. should be replaced by risk profiling (on this, see Grigoriou forthcoming), paperwork should be Bradford, Stephen (2003), ―Paying the price: final simplified and consolidated into single forms goods protection in OECD countries‖; Review of made available online, and when testing is strictly Economic and Statistics 85, 24–37. necessary, it should as much as possible be Carrère, Céline, and J. de Melo (2011), ―Non- outsourced to competent labs. Tariff Measures : What Do We Know, What Should Be Done ?‖; Journal of Economic Integration 26, 169-196. About the Authors Deardorff, Alan, and R. Stern (1997), Olivier Cadot is professor of International ―Measurement of non-Tariff Barriers‖; Economics and the director of the Institute of Economics Department Working Paper 179, Applied Economics at the University of OECD. Lausanne. Julien Gourdon is an Economist with Disdier, Anne-Célia; L. Fontagné, and M. the Centre d'Etudes Prospectives et Mimouni (2008), ―The Impact of Regulations on d'Informations Internationales (CEPII). Paul Agricultural Trade : Evidence from the SPS and Brenton and Gözde Isik, Trade Practice Leader TBT Agreements‖; American Journal of and Economist, respectively, in the Africa Region Agricultural Economics 90, 336-350. of the World Bank, are editors of the Africa Trade Policy Notes and edited this note from a Ferrantino, Michael (2006), Quantifying the longer version by the authors. This work is Trade and Economic Effects of non-Tariff funded by the Multi-Donor Trust Fund for Measures; OECD Trade Policy Working Paper Trade and Development supported by the 28. governments of the United Kingdom, Finland, Sweden and Norway. The views expressed in this Gillson, Ian (2011), Non-Tariff Barriers to Sub- paper reflect solely those of the authors and not Saharan African Trade in Food Staples: Opening necessarily the views of the funders, the World Regional Markets to Promote Food Security and Bank Group or its Executive Directors. Price Stabilization; Washington: The World Bank, 2011. I. Gillson and N. Charalambides (forthcoming), References ―Addressing Non-Tariff Barriers on Regional Trade in Southern Africa‖; in O. Cadot and M. Andriamananjara, Soamely; J. Dean, R. Feinberg, Malouche, eds., Non-tariff measures: A fresh M. Ferrantino, R. Ludema, and M. 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